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demand</title> <meta name="description" content="Search results for: hourly load demand"> <meta name="keywords" content="hourly load demand"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="hourly load demand"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 5776</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: hourly load demand</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5776</span> Two Day Ahead Short Term Load Forecasting Neural Network Based</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Firas%20M.%20Tuaimah">Firas M. Tuaimah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents an Artificial Neural Network based approach for short-term load forecasting and exactly for two days ahead. Two seasons have been discussed for Iraqi power system, namely summer and winter; the hourly load demand is the most important input variables for ANN based load forecasting. The recorded daily load profile with a lead time of 1-48 hours for July and December of the year 2012 was obtained from the operation and control center that belongs to the Ministry of Iraqi electricity. The results of the comparison show that the neural network gives a good prediction for the load forecasting and for two days ahead. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=short-term%20load%20forecasting" title="short-term load forecasting">short-term load forecasting</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20networks" title=" artificial neural networks"> artificial neural networks</a>, <a href="https://publications.waset.org/abstracts/search?q=back%20propagation%20learning" title=" back propagation learning"> back propagation learning</a>, <a href="https://publications.waset.org/abstracts/search?q=hourly%20load%20demand" title=" hourly load demand"> hourly load demand</a> </p> <a href="https://publications.waset.org/abstracts/7878/two-day-ahead-short-term-load-forecasting-neural-network-based" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7878.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">464</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5775</span> Enhancement of Long Term Peak Demand Forecast in Peninsular Malaysia Using Hourly Load Profile </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nazaitul%20Idya%20Hamzah">Nazaitul Idya Hamzah</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Syafiq%20Mazli"> Muhammad Syafiq Mazli</a>, <a href="https://publications.waset.org/abstracts/search?q=Maszatul%20Akmar%20Mustafa"> Maszatul Akmar Mustafa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The peak demand forecast is crucial to identify the future generation plant up needed in the long-term capacity planning analysis for Peninsular Malaysia as well as for the transmission and distribution network planning activities. Currently, peak demand forecast (in Mega Watt) is derived from the generation forecast by using load factor assumption. However, a forecast using this method has underperformed due to the structural changes in the economy, emerging trends and weather uncertainty. The dynamic changes of these drivers will result in many possible outcomes of peak demand for Peninsular Malaysia. This paper will look into the independent model of peak demand forecasting. The model begins with the selection of driver variables to capture long-term growth. This selection and construction of variables, which include econometric, emerging trend and energy variables, will have an impact on the peak forecast. The actual framework begins with the development of system energy and load shape forecast by using the system’s hourly data. The shape forecast represents the system shape assuming all embedded technology and use patterns to continue in the future. This is necessary to identify the movements in the peak hour or changes in the system load factor. The next step would be developing the peak forecast, which involves an iterative process to explore model structures and variables. The final step is combining the system energy, shape, and peak forecasts into the hourly system forecast then modifying it with the forecast adjustments. Forecast adjustments are among other sales forecasts for electric vehicles, solar and other adjustments. The framework will result in an hourly forecast that captures growth, peak usage and new technologies. The advantage of this approach as compared to the current methodology is that the peaks capture new technology impacts that change the load shape. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hourly%20load%20profile" title="hourly load profile">hourly load profile</a>, <a href="https://publications.waset.org/abstracts/search?q=load%20forecasting" title=" load forecasting"> load forecasting</a>, <a href="https://publications.waset.org/abstracts/search?q=long%20term%20peak%20demand%20forecasting" title=" long term peak demand forecasting"> long term peak demand forecasting</a>, <a href="https://publications.waset.org/abstracts/search?q=peak%20demand" title=" peak demand"> peak demand</a> </p> <a href="https://publications.waset.org/abstracts/116463/enhancement-of-long-term-peak-demand-forecast-in-peninsular-malaysia-using-hourly-load-profile" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/116463.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">172</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5774</span> Two-Level Separation of High Air Conditioner Consumers and Demand Response Potential Estimation Based on Set Point Change</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mehdi%20Naserian">Mehdi Naserian</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Jooshaki"> Mohammad Jooshaki</a>, <a href="https://publications.waset.org/abstracts/search?q=Mahmud%20Fotuhi-Firuzabad"> Mahmud Fotuhi-Firuzabad</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Hossein%20Mohammadi%20Sanjani"> Mohammad Hossein Mohammadi Sanjani</a>, <a href="https://publications.waset.org/abstracts/search?q=Ashknaz%20Oraee"> Ashknaz Oraee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In recent years, the development of communication infrastructure and smart meters have facilitated the utilization of demand-side resources which can enhance stability and economic efficiency of power systems. Direct load control programs can play an important role in the utilization of demand-side resources in the residential sector. However, investments required for installing control equipment can be a limiting factor in the development of such demand response programs. Thus, selection of consumers with higher potentials is crucial to the success of a direct load control program. Heating, ventilation, and air conditioning (HVAC) systems, which due to the heat capacity of buildings feature relatively high flexibility, make up a major part of household consumption. Considering that the consumption of HVAC systems depends highly on the ambient temperature and bearing in mind the high investments required for control systems enabling direct load control demand response programs, in this paper, a recent solution is presented to uncover consumers with high air conditioner demand among large number of consumers and to measure the demand response potential of such consumers. This can pave the way for estimating the investments needed for the implementation of direct load control programs for residential HVAC systems and for estimating the demand response potentials in a distribution system. In doing so, we first cluster consumers into several groups based on the correlation coefficients between hourly consumption data and hourly temperature data using K-means algorithm. Then, by applying a recent algorithm to the hourly consumption and temperature data, consumers with high air conditioner consumption are identified. Finally, demand response potential of such consumers is estimated based on the equivalent desired temperature setpoint changes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=communication%20infrastructure" title="communication infrastructure">communication infrastructure</a>, <a href="https://publications.waset.org/abstracts/search?q=smart%20meters" title=" smart meters"> smart meters</a>, <a href="https://publications.waset.org/abstracts/search?q=power%20systems" title=" power systems"> power systems</a>, <a href="https://publications.waset.org/abstracts/search?q=HVAC%20system" title=" HVAC system"> HVAC system</a>, <a href="https://publications.waset.org/abstracts/search?q=residential%20HVAC%20systems" title=" residential HVAC systems"> residential HVAC systems</a> </p> <a href="https://publications.waset.org/abstracts/170684/two-level-separation-of-high-air-conditioner-consumers-and-demand-response-potential-estimation-based-on-set-point-change" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/170684.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">67</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5773</span> Adjusting Electricity Demand Data to Account for the Impact of Loadshedding in Forecasting Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Migael%20van%20Zyl">Migael van Zyl</a>, <a href="https://publications.waset.org/abstracts/search?q=Stefanie%20Visser"> Stefanie Visser</a>, <a href="https://publications.waset.org/abstracts/search?q=Awelani%20Phaswana"> Awelani Phaswana</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The electricity landscape in South Africa is characterized by frequent occurrences of loadshedding, a measure implemented by Eskom to manage electricity generation shortages by curtailing demand. Loadshedding, classified into stages ranging from 1 to 8 based on severity, involves the systematic rotation of power cuts across municipalities according to predefined schedules. However, this practice introduces distortions in recorded electricity demand, posing challenges to accurate forecasting essential for budgeting, network planning, and generation scheduling. Addressing this challenge requires the development of a methodology to quantify the impact of loadshedding and integrate it back into metered electricity demand data. Fortunately, comprehensive records of loadshedding impacts are maintained in a database, enabling the alignment of Loadshedding effects with hourly demand data. This adjustment ensures that forecasts accurately reflect true demand patterns, independent of loadshedding's influence, thereby enhancing the reliability of electricity supply management in South Africa. This paper presents a methodology for determining the hourly impact of load scheduling and subsequently adjusting historical demand data to account for it. Furthermore, two forecasting models are developed: one utilizing the original dataset and the other using the adjusted data. A comparative analysis is conducted to evaluate forecast accuracy improvements resulting from the adjustment process. By implementing this methodology, stakeholders can make more informed decisions regarding electricity infrastructure investments, resource allocation, and operational planning, contributing to the overall stability and efficiency of South Africa's electricity supply system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electricity%20demand%20forecasting" title="electricity demand forecasting">electricity demand forecasting</a>, <a href="https://publications.waset.org/abstracts/search?q=load%20shedding" title=" load shedding"> load shedding</a>, <a href="https://publications.waset.org/abstracts/search?q=demand%20side%20management" title=" demand side management"> demand side management</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20science" title=" data science"> data science</a> </p> <a href="https://publications.waset.org/abstracts/182807/adjusting-electricity-demand-data-to-account-for-the-impact-of-loadshedding-in-forecasting-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/182807.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">61</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5772</span> Hybrid Dynamic Approach to Optimize the Impact of Shading Design and Control on Electrical Energy Demand</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=T.%20Parhizkar">T. Parhizkar</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20Jafarian"> H. Jafarian</a>, <a href="https://publications.waset.org/abstracts/search?q=F.%20Aramoun"> F. Aramoun</a>, <a href="https://publications.waset.org/abstracts/search?q=Y.%20Saboohi"> Y. Saboohi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Applying motorized shades have substantial effect on reducing energy consumption in building sector. Moreover, the combination of motorized shades with lighting systems and PV panels can lead to considerable reduction in the energy demand of buildings. In this paper, a model is developed to assess and find an optimum combination from shade designs, lighting control systems (dimming and on/off) and implementing PV panels in shades point of view. It is worth mentioning that annual saving for all designs is obtained during hourly simulation of lighting, solar heat flux and electricity generation with the use of PV panel. From 12 designs in general, three designs, two lighting control systems and PV panel option is implemented for a case study. The results illustrate that the optimum combination causes a saving potential of 792kW.hr per year. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=motorized%20shades" title="motorized shades">motorized shades</a>, <a href="https://publications.waset.org/abstracts/search?q=daylight" title=" daylight"> daylight</a>, <a href="https://publications.waset.org/abstracts/search?q=cooling%20load" title=" cooling load"> cooling load</a>, <a href="https://publications.waset.org/abstracts/search?q=shade%20control" title=" shade control"> shade control</a>, <a href="https://publications.waset.org/abstracts/search?q=hourly%20simulation" title=" hourly simulation"> hourly simulation</a> </p> <a href="https://publications.waset.org/abstracts/81507/hybrid-dynamic-approach-to-optimize-the-impact-of-shading-design-and-control-on-electrical-energy-demand" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/81507.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">171</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5771</span> Development of Prediction Models of Day-Ahead Hourly Building Electricity Consumption and Peak Power Demand Using the Machine Learning Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Dalin%20Si">Dalin Si</a>, <a href="https://publications.waset.org/abstracts/search?q=Azizan%20Aziz"> Azizan Aziz</a>, <a href="https://publications.waset.org/abstracts/search?q=Bertrand%20Lasternas"> Bertrand Lasternas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=building%20energy%20prediction" title="building energy prediction">building energy prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title=" data mining"> data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=demand%20response" title=" demand response"> demand response</a>, <a href="https://publications.waset.org/abstracts/search?q=electricity%20market" title=" electricity market"> electricity market</a> </p> <a href="https://publications.waset.org/abstracts/54774/development-of-prediction-models-of-day-ahead-hourly-building-electricity-consumption-and-peak-power-demand-using-the-machine-learning-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/54774.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">316</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5770</span> Novel Adaptive Radial Basis Function Neural Networks Based Approach for Short-Term Load Forecasting of Jordanian Power Grid </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Eyad%20Almaita">Eyad Almaita</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a novel adaptive Radial Basis Function Neural Networks (RBFNN) algorithm is used to forecast the hour by hour electrical load demand in Jordan. A small and effective RBFNN model is used to forecast the hourly total load demand based on a small number of features. These features are; the load in the previous day, the load in the same day in the previous week, the temperature in the same hour, the hour number, the day number, and the day type. The proposed adaptive RBFNN model can enhance the reliability of the conventional RBFNN after embedding the network in the system. This is achieved by introducing an adaptive algorithm that allows the change of the weights of the RBFNN after the training process is completed, which will eliminates the need to retrain the RBFNN model again. The data used in this paper is real data measured by National Electrical Power co. (Jordan). The data for the period Jan./2012-April/2013 is used train the RBFNN models and the data for the period May/2013- Sep. /2013 is used to validate the models effectiveness. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=load%20forecasting" title="load forecasting">load forecasting</a>, <a href="https://publications.waset.org/abstracts/search?q=adaptive%20neural%20network" title=" adaptive neural network"> adaptive neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=radial%20basis%20function" title=" radial basis function"> radial basis function</a>, <a href="https://publications.waset.org/abstracts/search?q=short-term" title=" short-term"> short-term</a>, <a href="https://publications.waset.org/abstracts/search?q=electricity%20consumption" title=" electricity consumption"> electricity consumption</a> </p> <a href="https://publications.waset.org/abstracts/40294/novel-adaptive-radial-basis-function-neural-networks-based-approach-for-short-term-load-forecasting-of-jordanian-power-grid" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40294.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">344</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5769</span> Demand Response from Residential Air Conditioning Load Using a Programmable Communication Thermostat</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saurabh%20Chanana">Saurabh Chanana</a>, <a href="https://publications.waset.org/abstracts/search?q=Monika%20Arora"> Monika Arora</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Demand response is getting increased attention these days due to the increase in electricity demand and introduction of renewable resources in the existing power grid. Traditionally demand response programs involve large industrial consumers but with technological advancement, demand response is being implemented for small residential and commercial consumers also. In this paper, demand response program aims to reduce the peak demand as well as overall energy consumption of the residential customers. Air conditioners are the major reason of peak load in residential sector in summer, so a dynamic model of air conditioning load with thermostat action has been considered for applying demand response programs. A programmable communicating thermostat (PCT) is a device that uses real time pricing (RTP) signals to control the thermostat setting. A new model incorporating PCT in air conditioning load has been proposed in this paper. Results show that introduction of PCT in air conditioner is useful in reducing the electricity payments of customers as well as reducing the peak demand. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=demand%20response" title="demand response">demand response</a>, <a href="https://publications.waset.org/abstracts/search?q=home%20energy%20management" title=" home energy management"> home energy management</a>, <a href="https://publications.waset.org/abstracts/search?q=programmable%20communicating%20thermostat" title=" programmable communicating thermostat"> programmable communicating thermostat</a>, <a href="https://publications.waset.org/abstracts/search?q=thermostatically%20controlled%20appliances" title=" thermostatically controlled appliances"> thermostatically controlled appliances</a> </p> <a href="https://publications.waset.org/abstracts/1662/demand-response-from-residential-air-conditioning-load-using-a-programmable-communication-thermostat" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/1662.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">607</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5768</span> The Relationship Between Hourly Compensation and Unemployment Rate Using the Panel Data Regression Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20K.%20Ashiquer%20Rahman">S. K. Ashiquer Rahman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> the paper concentrations on the importance of hourly compensation, emphasizing the significance of the unemployment rate. There are the two most important factors of a nation these are its unemployment rate and hourly compensation. These are not merely statistics but they have profound effects on individual, families, and the economy. They are inversely related to one another. When we consider the unemployment rate that will probably decline as hourly compensations in manufacturing rise. But when we reduced the unemployment rates and increased job prospects could result from higher compensation. That’s why, the increased hourly compensation in the manufacturing sector that could have a favorable effect on job changing issues. Moreover, the relationship between hourly compensation and unemployment is complex and influenced by broader economic factors. In this paper, we use panel data regression models to evaluate the expected link between hourly compensation and unemployment rate in order to determine the effect of hourly compensation on unemployment rate. We estimate the fixed effects model, evaluate the error components, and determine which model (the FEM or ECM) is better by pooling all 60 observations. We then analysis and review the data by comparing 3 several countries (United States, Canada and the United Kingdom) using panel data regression models. Finally, we provide result, analysis and a summary of the extensive research on how the hourly compensation effects on the unemployment rate. Additionally, this paper offers relevant and useful informational to help the government and academic community use an econometrics and social approach to lessen on the effect of the hourly compensation on Unemployment rate to eliminate the problem. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hourly%20compensation" title="hourly compensation">hourly compensation</a>, <a href="https://publications.waset.org/abstracts/search?q=Unemployment%20rate" title=" Unemployment rate"> Unemployment rate</a>, <a href="https://publications.waset.org/abstracts/search?q=panel%20data%20regression%20models" title=" panel data regression models"> panel data regression models</a>, <a href="https://publications.waset.org/abstracts/search?q=dummy%20variables" title=" dummy variables"> dummy variables</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20effects%20model" title=" random effects model"> random effects model</a>, <a href="https://publications.waset.org/abstracts/search?q=fixed%20effects%20model" title=" fixed effects model"> fixed effects model</a>, <a href="https://publications.waset.org/abstracts/search?q=the%20linear%20regression%20model" title=" the linear regression model"> the linear regression model</a> </p> <a href="https://publications.waset.org/abstracts/183027/the-relationship-between-hourly-compensation-and-unemployment-rate-using-the-panel-data-regression-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/183027.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">81</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5767</span> Load Management Using Multiple Sequential Load Shaping Techniques</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Amira%20M.%20Attia">Amira M. Attia</a>, <a href="https://publications.waset.org/abstracts/search?q=Karim%20H.%20Youssef"> Karim H. Youssef</a>, <a href="https://publications.waset.org/abstracts/search?q=Nabil%20H.%20Abbasi"> Nabil H. Abbasi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Demand Side Management (DSM) is an essential characteristic of current and future smart grid systems. As one of DSM functions, load management aims to control customers’ total electric consumption and utility’s load factor by using various load shaping techniques. However, applying load shaping techniques such as load shifting, peak clipping, or strategic conservation individually does not provide the desired level of improvement for load factor increment and/or customer’s bill reduction. In this paper, two load shaping techniques will be simulated as constrained optimization problems. The purpose is to reflect the application of combined load shifting and strategic conservation model together at the same time, and the application of combined load shifting and peak clipping model as well. The problem will be formulated and solved by using disciplined convex programming (CVX) based MATLAB® R2013b. Simulation results will be evaluated and compared for studying the most impactful multi-techniques model in improving load curve. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=convex%20programing" title="convex programing">convex programing</a>, <a href="https://publications.waset.org/abstracts/search?q=demand%20side%20management" title=" demand side management"> demand side management</a>, <a href="https://publications.waset.org/abstracts/search?q=load%20shaping" title=" load shaping"> load shaping</a>, <a href="https://publications.waset.org/abstracts/search?q=multiple" title=" multiple"> multiple</a>, <a href="https://publications.waset.org/abstracts/search?q=building%20energy%20optimization" title=" building energy optimization"> building energy optimization</a> </p> <a href="https://publications.waset.org/abstracts/91746/load-management-using-multiple-sequential-load-shaping-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/91746.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">313</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5766</span> Load Forecast of the Peak Demand Based on Both the Peak Demand and Its Location</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Qais%20H.%20Alsafasfeh">Qais H. Alsafasfeh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of this paper is to provide a forecast of the peak demand for the next 15 years for electrical distribution companies. The proposed methodology provides both the peak demand and its location for the next 15 years. This paper describes the Spatial Load Forecasting model used, the information provided by electrical distribution company in Jordan, the workflow followed, the parameters used and the assumptions made to run the model. The aim of this paper is to provide a forecast of the peak demand for the next 15 years for electrical distribution companies. The proposed methodology provides both the peak demand and its location for the next 15 years. This paper describes the Spatial Load Forecasting model used, the information provided by electrical distribution company in Jordan, the workflow followed, the parameters used and the assumptions made to run the model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=load%20forecast" title="load forecast">load forecast</a>, <a href="https://publications.waset.org/abstracts/search?q=peak%20demand" title=" peak demand"> peak demand</a>, <a href="https://publications.waset.org/abstracts/search?q=spatial%20load" title=" spatial load"> spatial load</a>, <a href="https://publications.waset.org/abstracts/search?q=electrical%20distribution" title=" electrical distribution"> electrical distribution</a> </p> <a href="https://publications.waset.org/abstracts/34628/load-forecast-of-the-peak-demand-based-on-both-the-peak-demand-and-its-location" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/34628.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">495</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5765</span> Hourly Solar Radiations Predictions for Anticipatory Control of Electrically Heated Floor: Use of Online Weather Conditions Forecast</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Helene%20Thieblemont">Helene Thieblemont</a>, <a href="https://publications.waset.org/abstracts/search?q=Fariborz%20Haghighat"> Fariborz Haghighat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Energy storage systems play a crucial role in decreasing building energy consumption during peak periods and expand the use of renewable energies in buildings. To provide a high building thermal performance, the energy storage system has to be properly controlled to insure a good energy performance while maintaining a satisfactory thermal comfort for building’s occupant. In the case of passive discharge storages, defining in advance the required amount of energy is required to avoid overheating in the building. Consequently, anticipatory supervisory control strategies have been developed forecasting future energy demand and production to coordinate systems. Anticipatory supervisory control strategies are based on some predictions, mainly of the weather forecast. However, if the forecasted hourly outdoor temperature may be found online with a high accuracy, solar radiations predictions are most of the time not available online. To estimate them, this paper proposes an advanced approach based on the forecast of weather conditions. Several methods to correlate hourly weather conditions forecast to real hourly solar radiations are compared. Results show that using weather conditions forecast allows estimating with an acceptable accuracy solar radiations of the next day. Moreover, this technique allows obtaining hourly data that may be used for building models. As a result, this solar radiation prediction model may help to implement model-based controller as Model Predictive Control. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=anticipatory%20control" title="anticipatory control">anticipatory control</a>, <a href="https://publications.waset.org/abstracts/search?q=model%20predictive%20control" title=" model predictive control"> model predictive control</a>, <a href="https://publications.waset.org/abstracts/search?q=solar%20radiation%20forecast" title=" solar radiation forecast"> solar radiation forecast</a>, <a href="https://publications.waset.org/abstracts/search?q=thermal%20storage" title=" thermal storage"> thermal storage</a> </p> <a href="https://publications.waset.org/abstracts/61503/hourly-solar-radiations-predictions-for-anticipatory-control-of-electrically-heated-floor-use-of-online-weather-conditions-forecast" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/61503.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">271</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5764</span> Multivariate Rainfall Disaggregation Using MuDRain Model: Malaysia Experience </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ibrahim%20Suliman%20Hanaish">Ibrahim Suliman Hanaish</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Disaggregation daily rainfall using stochastic models formulated based on multivariate approach (MuDRain) is discussed in this paper. Seven rain gauge stations are considered in this study for different distances from the referred station starting from 4 km to 160 km in Peninsular Malaysia. The hourly rainfall data used are covered the period from 1973 to 2008 and July and November months are considered as an example of dry and wet periods. The cross-correlation among the rain gauges is considered for the available hourly rainfall information at the neighboring stations or not. This paper discussed the applicability of the MuDRain model for disaggregation daily rainfall to hourly rainfall for both sources of cross-correlation. The goodness of fit of the model was based on the reproduction of fitting statistics like the means, variances, coefficients of skewness, lag zero cross-correlation of coefficients and the lag one auto correlation of coefficients. It is found the correlation coefficients based on extracted correlations that was based on daily are slightly higher than correlations based on available hourly rainfall especially for neighboring stations not more than 28 km. The results showed also the MuDRain model did not reproduce statistics very well. In addition, a bad reproduction of the actual hyetographs comparing to the synthetic hourly rainfall data. Mean while, it is showed a good fit between the distribution function of the historical and synthetic hourly rainfall. These discrepancies are unavoidable because of the lowest cross correlation of hourly rainfall. The overall performance indicated that the MuDRain model would not be appropriate choice for disaggregation daily rainfall. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=rainfall%20disaggregation" title="rainfall disaggregation">rainfall disaggregation</a>, <a href="https://publications.waset.org/abstracts/search?q=multivariate%20disaggregation%20rainfall%20model" title=" multivariate disaggregation rainfall model"> multivariate disaggregation rainfall model</a>, <a href="https://publications.waset.org/abstracts/search?q=correlation" title=" correlation"> correlation</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20model" title=" stochastic model"> stochastic model</a> </p> <a href="https://publications.waset.org/abstracts/20586/multivariate-rainfall-disaggregation-using-mudrain-model-malaysia-experience" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20586.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">515</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5763</span> Optimizing Load Shedding Schedule Problem Based on Harmony Search </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Almahd%20Alshereef">Almahd Alshereef</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20Alkilany"> Ahmed Alkilany</a>, <a href="https://publications.waset.org/abstracts/search?q=Hammad%20Said"> Hammad Said</a>, <a href="https://publications.waset.org/abstracts/search?q=Azuraliza%20Abu%20Bakar"> Azuraliza Abu Bakar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> From time to time, electrical power grid is directed by the National Electricity Operator to conduct load shedding, which involves hours' power outages on the area of this study, Southern Electrical Grid of Libya (SEGL). Load shedding is conducted in order to alleviate pressure on the National Electricity Grid at times of peak demand. This approach has chosen a set of categories to study load-shedding problem considering the effect of the demand priorities on the operation of the power system during emergencies. Classification of category region for load shedding problem is solved by a new algorithm (the harmony algorithm) based on the "random generation list of category region", which is a possible solution with a proximity degree to the optimum. The obtained results prove additional enhancements compared to other heuristic approaches. The case studies are carried out on SEGL. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=optimization" title="optimization">optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=harmony%20algorithm" title=" harmony algorithm"> harmony algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=load%20shedding" title=" load shedding"> load shedding</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a> </p> <a href="https://publications.waset.org/abstracts/15363/optimizing-load-shedding-schedule-problem-based-on-harmony-search" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15363.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">396</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5762</span> Neural Network Modelling for Turkey Railway Load Carrying Demand</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Humeyra%20Bolakar%20Tosun">Humeyra Bolakar Tosun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The transport sector has an undisputed place in human life. People need transport access to continuous increase day by day with growing population. The number of rail network, urban transport planning, infrastructure improvements, transportation management and other related areas is a key factor affecting our country made it quite necessary to improve the work of transportation. In this context, it plays an important role in domestic rail freight demand planning. Alternatives that the increase in the transportation field and has made it mandatory requirements such as the demand for improving transport quality. In this study generally is known and used in studies by the definition, rail freight transport, railway line length, population, energy consumption. In this study, Iron Road Load Net Demand was modeled by multiple regression and ANN methods. In this study, model dependent variable (Output) is Iron Road Load Net demand and 6 entries variable was determined. These outcome values extracted from the model using ANN and regression model results. In the regression model, some parameters are considered as determinative parameters, and the coefficients of the determinants give meaningful results. As a result, ANN model has been shown to be more successful than traditional regression model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=railway%20load%20carrying" title="railway load carrying">railway load carrying</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=modelling%20transport" title=" modelling transport"> modelling transport</a>, <a href="https://publications.waset.org/abstracts/search?q=transportation" title=" transportation"> transportation</a> </p> <a href="https://publications.waset.org/abstracts/92227/neural-network-modelling-for-turkey-railway-load-carrying-demand" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/92227.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">143</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5761</span> Electricity Load Modeling: An Application to Italian Market</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Giovanni%20Masala">Giovanni Masala</a>, <a href="https://publications.waset.org/abstracts/search?q=Stefania%20Marica"> Stefania Marica</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Forecasting electricity load plays a crucial role regards decision making and planning for economical purposes. Besides, in the light of the recent privatization and deregulation of the power industry, the forecasting of future electricity load turned out to be a very challenging problem. Empirical data about electricity load highlights a clear seasonal behavior (higher load during the winter season), which is partly due to climatic effects. We also emphasize the presence of load periodicity at a weekly basis (electricity load is usually lower on weekends or holidays) and at daily basis (electricity load is clearly influenced by the hour). Finally, a long-term trend may depend on the general economic situation (for example, industrial production affects electricity load). All these features must be captured by the model. The purpose of this paper is then to build an hourly electricity load model. The deterministic component of the model requires non-linear regression and Fourier series while we will investigate the stochastic component through econometrical tools. The calibration of the parameters’ model will be performed by using data coming from the Italian market in a 6 year period (2007- 2012). Then, we will perform a Monte Carlo simulation in order to compare the simulated data respect to the real data (both in-sample and out-of-sample inspection). The reliability of the model will be deduced thanks to standard tests which highlight a good fitting of the simulated values. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ARMA-GARCH%20process" title="ARMA-GARCH process">ARMA-GARCH process</a>, <a href="https://publications.waset.org/abstracts/search?q=electricity%20load" title=" electricity load"> electricity load</a>, <a href="https://publications.waset.org/abstracts/search?q=fitting%20tests" title=" fitting tests"> fitting tests</a>, <a href="https://publications.waset.org/abstracts/search?q=Fourier%20series" title=" Fourier series"> Fourier series</a>, <a href="https://publications.waset.org/abstracts/search?q=Monte%20Carlo%20simulation" title=" Monte Carlo simulation"> Monte Carlo simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=non-linear%20regression" title=" non-linear regression"> non-linear regression</a> </p> <a href="https://publications.waset.org/abstracts/11709/electricity-load-modeling-an-application-to-italian-market" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/11709.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">395</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5760</span> Reliability Assessment for Tie Line Capacity Assistance of Power Systems Based on Multi-Agent System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nadheer%20A.%20Shalash">Nadheer A. Shalash</a>, <a href="https://publications.waset.org/abstracts/search?q=Abu%20Zaharin%20Bin%20Ahmad"> Abu Zaharin Bin Ahmad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Technological developments in industrial innovations have currently been related to interconnected system assistance and distribution networks. This important in order to enable an electrical load to continue receive power in the event of disconnection of load from the main power grid. This paper represents a method for reliability assessment of interconnected power systems based. The multi-agent system consists of four agents. The first agent was the generator agent to using as connected the generator to the grid depending on the state of the reserve margin and the load demand. The second was a load agent is that located at the load. Meanwhile, the third is so-called "the reverse margin agent" that to limit the reserve margin between 0-25% depend on the load and the unit size generator. In the end, calculation reliability Agent can be calculate expected energy not supplied (EENS), loss of load expectation (LOLE) and the effecting of tie line capacity to determine the risk levels Roy Billinton Test System (RBTS) can use to evaluated the reliability indices by using the developed JADE package. The results estimated of the reliability interconnection power systems presented in this paper. The overall reliability of power system can be improved. Thus, the market becomes more concentrated against demand increasing and the generation units were operating in relation to reliability indices. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=reliability%20indices" title="reliability indices">reliability indices</a>, <a href="https://publications.waset.org/abstracts/search?q=load%20expectation" title=" load expectation"> load expectation</a>, <a href="https://publications.waset.org/abstracts/search?q=reserve%20margin" title=" reserve margin"> reserve margin</a>, <a href="https://publications.waset.org/abstracts/search?q=daily%20load" title=" daily load"> daily load</a>, <a href="https://publications.waset.org/abstracts/search?q=probability" title=" probability"> probability</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-agent%20system" title=" multi-agent system"> multi-agent system</a> </p> <a href="https://publications.waset.org/abstracts/4342/reliability-assessment-for-tie-line-capacity-assistance-of-power-systems-based-on-multi-agent-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/4342.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">325</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5759</span> Do Industry Expert Audit Engagement Partners Earn Fee Premiums? Evidence from Labor Usage and the Hourly Charge Rate</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gil%20Bae">Gil Bae</a>, <a href="https://publications.waset.org/abstracts/search?q=Seung%20Uk%20Choi"> Seung Uk Choi</a>, <a href="https://publications.waset.org/abstracts/search?q=Jae%20Eun%20Lee"> Jae Eun Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Joon%20Hwa%20Rho"> Joon Hwa Rho</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Using proprietary engagement partner identity information for the Big 4 audit firms in Korea over the 2001-2011 period, we find that expert engagement partners obtain significantly higher total compensation than do non-expert partners. Importantly, we also find that expert partners increase the number of audit hours compared to their non-expert counterparts. The hourly billing rate, calculated as total fees divided by total audit hours, of expert partners is not higher than that of non-expert partners, indicating that there is no expert partner premium reflected in the hourly rate. This finding suggests that the increase in total audit fees is attributable mainly to the increase in the quantity of audit hours that expert partners work, not from the higher fee per hour. The results are not attributable to auditor selection bias. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=industry%20expert%20partners" title="industry expert partners">industry expert partners</a>, <a href="https://publications.waset.org/abstracts/search?q=expert%20premiums" title=" expert premiums"> expert premiums</a>, <a href="https://publications.waset.org/abstracts/search?q=audit%20hours" title=" audit hours"> audit hours</a>, <a href="https://publications.waset.org/abstracts/search?q=hourly%20charge%20rate" title=" hourly charge rate"> hourly charge rate</a> </p> <a href="https://publications.waset.org/abstracts/50571/do-industry-expert-audit-engagement-partners-earn-fee-premiums-evidence-from-labor-usage-and-the-hourly-charge-rate" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/50571.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">304</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5758</span> Hydrogen Production at the Forecourt from Off-Peak Electricity and Its Role in Balancing the Grid</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdulla%20Rahil">Abdulla Rahil</a>, <a href="https://publications.waset.org/abstracts/search?q=Rupert%20Gammon"> Rupert Gammon</a>, <a href="https://publications.waset.org/abstracts/search?q=Neil%20Brown"> Neil Brown</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The rapid growth of renewable energy sources and their integration into the grid have been motivated by the depletion of fossil fuels and environmental issues. Unfortunately, the grid is unable to cope with the predicted growth of renewable energy which would lead to its instability. To solve this problem, energy storage devices could be used. Electrolytic hydrogen production from an electrolyser is considered a promising option since it is a clean energy source (zero emissions). Choosing flexible operation of an electrolyser (producing hydrogen during the off-peak electricity period and stopping at other times) could bring about many benefits like reducing the cost of hydrogen and helping to balance the electric systems. This paper investigates the price of hydrogen during flexible operation compared with continuous operation, while serving the customer (hydrogen filling station) without interruption. The optimization algorithm is applied to investigate the hydrogen station in both cases (flexible and continuous operation). Three different scenarios are tested to see whether the off-peak electricity price could enhance the reduction of the hydrogen cost. These scenarios are: Standard tariff (1 tier system) during the day (assumed 12 p/kWh) while still satisfying the demand for hydrogen; using off-peak electricity at a lower price (assumed 5 p/kWh) and shutting down the electrolyser at other times; using lower price electricity at off-peak times and high price electricity at other times. This study looks at Derna city, which is located on the coast of the Mediterranean Sea (32° 46′ 0 N, 22° 38′ 0 E) with a high potential for wind resource. Hourly wind speed data which were collected over 24½ years from 1990 to 2014 were in addition to data on hourly radiation and hourly electricity demand collected over a one-year period, together with the petrol station data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hydrogen%20filling%20station%20off-peak%20electricity" title="hydrogen filling station off-peak electricity">hydrogen filling station off-peak electricity</a>, <a href="https://publications.waset.org/abstracts/search?q=renewable%20energy" title=" renewable energy"> renewable energy</a>, <a href="https://publications.waset.org/abstracts/search?q=off-peak%20electricity" title=" off-peak electricity"> off-peak electricity</a>, <a href="https://publications.waset.org/abstracts/search?q=electrolytic%20hydrogen" title=" electrolytic hydrogen"> electrolytic hydrogen</a> </p> <a href="https://publications.waset.org/abstracts/52402/hydrogen-production-at-the-forecourt-from-off-peak-electricity-and-its-role-in-balancing-the-grid" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52402.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">231</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5757</span> Assessment of Solar Hydrogen Production in Energetic Hybrid PV-PEMFC System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=H.%20Rezzouk">H. Rezzouk</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Hatti"> M. Hatti</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20Rahmani"> H. Rahmani</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Atoui"> S. Atoui</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper discusses the design and analysis of a hybrid PV-Fuel cell energy system destined to power a DC load. The system is composed of a photovoltaic array, a fuel cell, an electrolyzer and a hydrogen tank. HOMER software is used in this study to calculate the optimum capacities of the power system components that their combination allows an efficient use of solar resource to cover the hourly load needs. The optimal system sizing allows establishing the right balance between the daily electrical energy produced by the power system and the daily electrical energy consumed by the DC load using a 28 KW PV array, a 7.5 KW fuel cell, a 40KW electrolyzer and a 270 Kg hydrogen tank. The variation of powers involved into the DC bus of the hybrid PV-fuel cell system has been computed and analyzed for each hour over one year: the output powers of the PV array and the fuel cell, the input power of the elctrolyzer system and the DC primary load. Equally, the annual variation of stored hydrogen produced by the electrolyzer has been assessed. The PV array contributes in the power system with 82% whereas the fuel cell produces 18%. 38% of the total energy consumption belongs to the DC primary load while the rest goes to the electrolyzer. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electrolyzer" title="electrolyzer">electrolyzer</a>, <a href="https://publications.waset.org/abstracts/search?q=hydrogen" title=" hydrogen"> hydrogen</a>, <a href="https://publications.waset.org/abstracts/search?q=hydrogen%20fueled%20cell" title=" hydrogen fueled cell"> hydrogen fueled cell</a>, <a href="https://publications.waset.org/abstracts/search?q=photovoltaic" title=" photovoltaic"> photovoltaic</a> </p> <a href="https://publications.waset.org/abstracts/12766/assessment-of-solar-hydrogen-production-in-energetic-hybrid-pv-pemfc-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/12766.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">492</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5756</span> Energy Analysis of Seasonal Air Conditioning Demand of All Income Classes Using Bottom up Model in Pakistan</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saba%20Arif">Saba Arif</a>, <a href="https://publications.waset.org/abstracts/search?q=Anam%20Nadeem"> Anam Nadeem</a>, <a href="https://publications.waset.org/abstracts/search?q=Roman%20Kalvin"> Roman Kalvin</a>, <a href="https://publications.waset.org/abstracts/search?q=Tanzeel%20Rashid"> Tanzeel Rashid</a>, <a href="https://publications.waset.org/abstracts/search?q=Burhan%20Ali"> Burhan Ali</a>, <a href="https://publications.waset.org/abstracts/search?q=Juntakan%20Taweekun"> Juntakan Taweekun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Currently, the energy crisis is taking serious attention. Globally, industries and building are major share takers of energy. 72% of total global energy is consumed by residential houses, markets, and commercial building. Additionally, in appliances air conditioners are major consumer of electricity; about 60% energy is used for cooling purpose in houses due to HVAC units. Energy demand will aid in determining what changes will be needed whether it is the estimation of the required energy for households or instituting conservation measures. Bottom-up model is one of the most famous methods for forecasting. In current research bottom-up model of air conditioners' energy consumption in all income classes in comparison with seasonal variation and hourly consumption is calculated. By comparison of energy consumption of all income classes by usage of air conditioners, total consumption of actual demand and current availability can be seen. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=air%20conditioning" title="air conditioning">air conditioning</a>, <a href="https://publications.waset.org/abstracts/search?q=bottom%20up%20model" title=" bottom up model"> bottom up model</a>, <a href="https://publications.waset.org/abstracts/search?q=income%20classes" title=" income classes"> income classes</a>, <a href="https://publications.waset.org/abstracts/search?q=energy%20demand" title=" energy demand"> energy demand</a> </p> <a href="https://publications.waset.org/abstracts/83887/energy-analysis-of-seasonal-air-conditioning-demand-of-all-income-classes-using-bottom-up-model-in-pakistan" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/83887.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">248</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5755</span> Correlation Analysis of Energy Use, Architectural Design and Residential Lifestyle in Japan Smart Community</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tran%20Le%20Na">Tran Le Na</a>, <a href="https://publications.waset.org/abstracts/search?q=Didit%20Novianto"> Didit Novianto</a>, <a href="https://publications.waset.org/abstracts/search?q=Yoshiaki%20Ushifusa"> Yoshiaki Ushifusa</a>, <a href="https://publications.waset.org/abstracts/search?q=Weijun%20Gao"> Weijun Gao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper introduces the characteristics of Japanese residential lifestyle and Japanese Architectural housing design, meanwhile, summarizes the results from an analysis of energy use of 12 households in electric-only multi dwellings in Higashida Smart Community, Kitakyushu, Japan. Using hourly load and daily load data collected from smart meter, we explore correlations of energy use in households according to the incentive of different levels of architectural characteristics and lifestyle, following three factors: Space (Living room, Kitchen, Bedroom, Bathroom), Time (daytime and night time, weekdays and weekend) and User (Elderly, Parents, Kids). The energy consumption reports demonstrated that the essential demand of household’s response to variable factors. From that exploratory analysis, we can define the role of housing equipment layout and spatial layout in residential housing design. Likewise, determining preferred spaces and time use can help to optimize energy consumption in households. This paper contributes to the application of Smart Home Energy Management System in Smart Community in Japan and provides a good experience to other countries. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=smart%20community" title="smart community">smart community</a>, <a href="https://publications.waset.org/abstracts/search?q=energy%20efficiency" title=" energy efficiency"> energy efficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=architectural%20housing%20design" title=" architectural housing design"> architectural housing design</a>, <a href="https://publications.waset.org/abstracts/search?q=residential%20lifestyle" title=" residential lifestyle"> residential lifestyle</a> </p> <a href="https://publications.waset.org/abstracts/96377/correlation-analysis-of-energy-use-architectural-design-and-residential-lifestyle-in-japan-smart-community" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/96377.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">204</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5754</span> Multiobjective Economic Dispatch Using Optimal Weighting Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mandeep%20Kaur">Mandeep Kaur</a>, <a href="https://publications.waset.org/abstracts/search?q=Fatehgarh%20Sahib"> Fatehgarh Sahib</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purpose of economic load dispatch is to allocate the required load demand between the available generation units such that the cost of operation is minimized. It is an optimization problem to find the most economical schedule of the generating units while satisfying load demand and operational constraints. The multiobjective optimization problem in which the engineer’s goal is to maximize or minimize not a single objective function but several objective functions simultaneously. The purpose of multiobjective problems in the mathematical programming framework is to optimize the different objective functions. Many approaches and methods have been proposed in recent years to solve multiobjective optimization problems. Weighting method has been applied to convert multiobjective optimization problems into scalar optimization. MATLAB 7.10 has been used to write the code for the complete algorithm with the help of genetic algorithm (GA). The validity of the proposed method has been demonstrated on a three-unit power system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=economic%20load%20dispatch" title="economic load dispatch">economic load dispatch</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=generating%20units" title=" generating units"> generating units</a>, <a href="https://publications.waset.org/abstracts/search?q=multiobjective%20optimization" title=" multiobjective optimization"> multiobjective optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=weighting%20method" title=" weighting method"> weighting method</a> </p> <a href="https://publications.waset.org/abstracts/117420/multiobjective-economic-dispatch-using-optimal-weighting-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/117420.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">150</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5753</span> Optimal Load Control Strategy in the Presence of Stochastically Dependent Renewable Energy Sources</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mahmoud%20M.%20Othman">Mahmoud M. Othman</a>, <a href="https://publications.waset.org/abstracts/search?q=Almoataz%20Y.%20Abdelaziz"> Almoataz Y. Abdelaziz</a>, <a href="https://publications.waset.org/abstracts/search?q=Yasser%20G.%20Hegazy"> Yasser G. Hegazy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a load control strategy based on modification of the Big Bang Big Crunch optimization method. The proposed strategy aims to determine the optimal load to be controlled and the corresponding time of control in order to minimize the energy purchased from substation. The presented strategy helps the distribution network operator to rely on the renewable energy sources in supplying the system demand. The renewable energy sources used in the presented study are modeled using the diagonal band Copula method and sequential Monte Carlo method in order to accurately consider the multivariate stochastic dependence between wind power, photovoltaic power and the system demand. The proposed algorithms are implemented in MATLAB environment and tested on the IEEE 37-node feeder. Several case studies are done and the subsequent discussions show the effectiveness of the proposed algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=big%20bang%20big%20crunch" title="big bang big crunch">big bang big crunch</a>, <a href="https://publications.waset.org/abstracts/search?q=distributed%20generation" title=" distributed generation"> distributed generation</a>, <a href="https://publications.waset.org/abstracts/search?q=load%20control" title=" load control"> load control</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=planning" title=" planning"> planning</a> </p> <a href="https://publications.waset.org/abstracts/44666/optimal-load-control-strategy-in-the-presence-of-stochastically-dependent-renewable-energy-sources" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/44666.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">344</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5752</span> Overview of Different Approaches Used in Optimal Operation Control of Hybrid Renewable Energy Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=K.%20Kusakana">K. Kusakana </a> </p> <p class="card-text"><strong>Abstract:</strong></p> A hybrid energy system is a combination of renewable energy sources with back up, as well as a storage system used to respond to given load energy requirements. Given that the electrical output of each renewable source is fluctuating with changes in weather conditions, and since the load demand also varies with time; one of the main attributes of hybrid systems is to be able to respond to the load demand at any time by optimally controlling each energy source, storage and back-up system. The induced optimization problem is to compute the optimal operation control of the system with the aim of minimizing operation costs while efficiently and reliably responding to the load energy requirement. Current optimization research and development on hybrid systems are mainly focusing on the sizing aspect. Thus, the aim of this paper is to report on the state-of-the-art of optimal operation control of hybrid renewable energy systems. This paper also discusses different challenges encountered, as well as future developments that can help in improving the optimal operation control of hybrid renewable energy systems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=renewable%20energies" title="renewable energies">renewable energies</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20systems" title=" hybrid systems"> hybrid systems</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=operation%20control" title=" operation control"> operation control</a> </p> <a href="https://publications.waset.org/abstracts/48787/overview-of-different-approaches-used-in-optimal-operation-control-of-hybrid-renewable-energy-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/48787.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">379</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5751</span> Modeling of Virtual Power Plant</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Fanseem%20E.%20M.">Muhammad Fanseem E. M.</a>, <a href="https://publications.waset.org/abstracts/search?q=Rama%20Satya%20Satish%20Kumar"> Rama Satya Satish Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=Indrajeet%20Bhausaheb%20Bhavar"> Indrajeet Bhausaheb Bhavar</a>, <a href="https://publications.waset.org/abstracts/search?q=Deepak%20M."> Deepak M.</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Keeping the right balance of electricity between the supply and demand sides of the grid is one of the most important objectives of electrical grid operation. Power generation and demand forecasting are the core of power management and generation scheduling. Large, centralized producing units were used in the construction of conventional power systems in the past. A certain level of balance was possible since the generation kept up with the power demand. However, integrating renewable energy sources into power networks has proven to be a difficult challenge due to its intermittent nature. The power imbalance caused by rising demands and peak loads is negatively affecting power quality and dependability. Demand side management and demand response were one of the solutions, keeping generation the same but altering or rescheduling or shedding completely the load or demand. However, shedding the load or rescheduling is not an efficient way. There comes the significance of virtual power plants. The virtual power plant integrates distributed generation, dispatchable load, and distributed energy storage organically by using complementing control approaches and communication technologies. This would eventually increase the utilization rate and financial advantages of distributed energy resources. Most of the writing on virtual power plant models ignored technical limitations, and modeling was done in favor of a financial or commercial viewpoint. Therefore, this paper aims to address the modeling intricacies of VPPs and their technical limitations, shedding light on a holistic understanding of this innovative power management approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cost%20optimization" title="cost optimization">cost optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=distributed%20energy%20resources" title=" distributed energy resources"> distributed energy resources</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20modeling" title=" dynamic modeling"> dynamic modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=model%20quality%20tests" title=" model quality tests"> model quality tests</a>, <a href="https://publications.waset.org/abstracts/search?q=power%20system%20modeling" title=" power system modeling"> power system modeling</a> </p> <a href="https://publications.waset.org/abstracts/184043/modeling-of-virtual-power-plant" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/184043.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">62</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5750</span> Iterative Replanning of Diesel Generator and Energy Storage System for Stable Operation of an Isolated Microgrid</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jiin%20Jeong">Jiin Jeong</a>, <a href="https://publications.waset.org/abstracts/search?q=Taekwang%20Kim"> Taekwang Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Kwang%20Ryel%20Ryu"> Kwang Ryel Ryu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The target microgrid in this paper is isolated from the large central power system and is assumed to consist of wind generators, photovoltaic power generators, an energy storage system (ESS), a diesel power generator, the community load, and a dump load. The operation of such a microgrid can be hazardous because of the uncertain prediction of power supply and demand and especially due to the high fluctuation of the output from the wind generators. In this paper, we propose an iterative replanning method for determining the appropriate level of diesel generation and the charging/discharging cycles of the ESS for the upcoming one-hour horizon. To cope with the uncertainty of the estimation of supply and demand, the one-hour plan is built repeatedly in the regular interval of one minute by rolling the one-hour horizon. Since the plan should be built with a sufficiently large safe margin to avoid any possible black-out, some energy waste through the dump load is inevitable. In our approach, the level of safe margin is optimized through learning from the past experience. The simulation experiments show that our method combined with the margin optimization can reduce the dump load compared to the method without such optimization. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=microgrid" title="microgrid">microgrid</a>, <a href="https://publications.waset.org/abstracts/search?q=operation%20planning" title=" operation planning"> operation planning</a>, <a href="https://publications.waset.org/abstracts/search?q=power%20efficiency%20optimization" title=" power efficiency optimization"> power efficiency optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=supply%20and%20demand%20prediction" title=" supply and demand prediction"> supply and demand prediction</a> </p> <a href="https://publications.waset.org/abstracts/23002/iterative-replanning-of-diesel-generator-and-energy-storage-system-for-stable-operation-of-an-isolated-microgrid" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/23002.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">432</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5749</span> Application of ANN for Estimation of Power Demand of Villages in Sulaymaniyah Governorate</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Majeed">A. Majeed</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20Ali"> P. Ali</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Before designing an electrical system, the estimation of load is necessary for unit sizing and demand-generation balancing. The system could be a stand-alone system for a village or grid connected or integrated renewable energy to grid connection, especially as there are non–electrified villages in developing countries. In the classical model, the energy demand was found by estimating the household appliances multiplied with the amount of their rating and the duration of their operation, but in this paper, information exists for electrified villages could be used to predict the demand, as villages almost have the same life style. This paper describes a method used to predict the average energy consumed in each two months for every consumer living in a village by Artificial Neural Network (ANN). The input data are collected using a regional survey for samples of consumers representing typical types of different living, household appliances and energy consumption by a list of information, and the output data are collected from administration office of Piramagrun for each corresponding consumer. The result of this study shows that the average demand for different consumers from four villages in different months throughout the year is approximately 12 kWh/day, this model estimates the average demand/day for every consumer with a mean absolute percent error of 11.8%, and MathWorks software package MATLAB version 7.6.0 that contains and facilitate Neural Network Toolbox was used. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20network" title="artificial neural network">artificial neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=load%20estimation" title=" load estimation"> load estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=regional%20survey" title=" regional survey"> regional survey</a>, <a href="https://publications.waset.org/abstracts/search?q=rural%20electrification" title=" rural electrification"> rural electrification</a> </p> <a href="https://publications.waset.org/abstracts/87380/application-of-ann-for-estimation-of-power-demand-of-villages-in-sulaymaniyah-governorate" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/87380.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">123</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5748</span> Quantifying the Methods of Monitoring Timers in Electric Water Heater for Grid Balancing on Demand-Side Management: A Systematic Mapping Review</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yamamah%20Abdulrazaq">Yamamah Abdulrazaq</a>, <a href="https://publications.waset.org/abstracts/search?q=Lahieb%20A.%20Abrahim"> Lahieb A. Abrahim</a>, <a href="https://publications.waset.org/abstracts/search?q=Samuel%20E.%20Davies"> Samuel E. Davies</a>, <a href="https://publications.waset.org/abstracts/search?q=Iain%20Shewring"> Iain Shewring</a> </p> <p class="card-text"><strong>Abstract:</strong></p> An electric water heater (EWH) is a powerful appliance that uses electricity in residential, commercial, and industrial settings, and the ability to control them properly will result in cost savings and the prevention of blackouts on the national grid. This article discusses the usage of timers in EWH control strategies for demand-side management (DSM). Up to the authors' knowledge, there is no systematic mapping review focusing on the utilisation of EWH control strategies in DSM has yet been conducted. Consequently, the purpose of this research is to identify and examine main papers exploring EWH procedures in DSM by quantifying and categorising information with regard to publication year and source, kind of methods, and source of data for monitoring control techniques. In order to answer the research questions, a total of 31 publications published between 1999 and 2023 were selected depending on specific inclusion and exclusion criteria. The data indicate that direct load control (DLC) has been somewhat more prevalent than indirect load control (ILC). Additionally, the mixing method is much lower than the other techniques, and the proportion of Real-time data (RTD) to non-real-time data (NRTD) is about equal. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=demand%20side%20management" title="demand side management">demand side management</a>, <a href="https://publications.waset.org/abstracts/search?q=direct%20load%20control" title=" direct load control"> direct load control</a>, <a href="https://publications.waset.org/abstracts/search?q=electric%20water%20heater" title=" electric water heater"> electric water heater</a>, <a href="https://publications.waset.org/abstracts/search?q=indirect%20load%20control" title=" indirect load control"> indirect load control</a>, <a href="https://publications.waset.org/abstracts/search?q=non%20real-time%20data" title=" non real-time data"> non real-time data</a>, <a href="https://publications.waset.org/abstracts/search?q=real-time%20data" title=" real-time data"> real-time data</a> </p> <a href="https://publications.waset.org/abstracts/166279/quantifying-the-methods-of-monitoring-timers-in-electric-water-heater-for-grid-balancing-on-demand-side-management-a-systematic-mapping-review" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/166279.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">82</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5747</span> Disaggregation the Daily Rainfall Dataset into Sub-Daily Resolution in the Temperate Oceanic Climate Region</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammad%20Bakhshi">Mohammad Bakhshi</a>, <a href="https://publications.waset.org/abstracts/search?q=Firas%20Al%20Janabi"> Firas Al Janabi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> High resolution rain data are very important to fulfill the input of hydrological models. Among models of high-resolution rainfall data generation, the temporal disaggregation was chosen for this study. The paper attempts to generate three different rainfall resolutions (4-hourly, hourly and 10-minutes) from daily for around 20-year record period. The process was done by DiMoN tool which is based on random cascade model and method of fragment. Differences between observed and simulated rain dataset are evaluated with variety of statistical and empirical methods: Kolmogorov-Smirnov test (K-S), usual statistics, and Exceedance probability. The tool worked well at preserving the daily rainfall values in wet days, however, the generated data are cumulated in a shorter time period and made stronger storms. It is demonstrated that the difference between generated and observed cumulative distribution function curve of 4-hourly datasets is passed the K-S test criteria while in hourly and 10-minutes datasets the P-value should be employed to prove that their differences were reasonable. The results are encouraging considering the overestimation of generated high-resolution rainfall data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=DiMoN%20Tool" title="DiMoN Tool">DiMoN Tool</a>, <a href="https://publications.waset.org/abstracts/search?q=disaggregation" title=" disaggregation"> disaggregation</a>, <a href="https://publications.waset.org/abstracts/search?q=exceedance%20probability" title=" exceedance probability"> exceedance probability</a>, <a href="https://publications.waset.org/abstracts/search?q=Kolmogorov-Smirnov%20test" title=" Kolmogorov-Smirnov test"> Kolmogorov-Smirnov test</a>, <a href="https://publications.waset.org/abstracts/search?q=rainfall" title=" rainfall"> rainfall</a> </p> <a href="https://publications.waset.org/abstracts/99470/disaggregation-the-daily-rainfall-dataset-into-sub-daily-resolution-in-the-temperate-oceanic-climate-region" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/99470.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">201</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=hourly%20load%20demand&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=hourly%20load%20demand&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=hourly%20load%20demand&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=hourly%20load%20demand&page=5">5</a></li> <li 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