Pub Date : 2018-10-01DOI: 10.23919/ICUE-GESD.2018.8635720
Mrityunjay Kumar Mishra, S. Parida
In this paper an energy consumption scheduling for residential area considering generation, storage and the combinatorial nature of shiftable device scheduling has been proposed. The smart grid consists of the traditional users as well as users with smart meter who participate in the day ahead optimization process to reduce their energy bill by storing, generating and shifting their device to non-peak hours. These entities by participating in optimization process reduce the per unit energy cost of the grid for all users. It is assumed that all of the participating users own a storing, generating or both devices having same characteristic. A billing scheme has been adopted to encourage the user to shift their load to non-peak hour. The users will compete to shift their load as well as to charge their storage device to low load period, therefore the resulting day ahead optimization problem has been formulated as non-cooperative game between the users. The iterative distributed algorithm can be run on user’s smart meters to solve the formulated problem. The strategy set for the scheduling of time shiftable devices are discrete and combinatorial in nature, hence particle swarm algorithm for optimizing the individual users pay off function has been used. The obtained results demonstrated the effectiveness of the proposed method in terms of reduced energy price and system peak while considering the user’s privacy and comfortability.
{"title":"A Game Theoretic Approach for Demand-Side Management Considering Generation, Storage and the Combinatorial Nature of Load Scheduling","authors":"Mrityunjay Kumar Mishra, S. Parida","doi":"10.23919/ICUE-GESD.2018.8635720","DOIUrl":"https://doi.org/10.23919/ICUE-GESD.2018.8635720","url":null,"abstract":"In this paper an energy consumption scheduling for residential area considering generation, storage and the combinatorial nature of shiftable device scheduling has been proposed. The smart grid consists of the traditional users as well as users with smart meter who participate in the day ahead optimization process to reduce their energy bill by storing, generating and shifting their device to non-peak hours. These entities by participating in optimization process reduce the per unit energy cost of the grid for all users. It is assumed that all of the participating users own a storing, generating or both devices having same characteristic. A billing scheme has been adopted to encourage the user to shift their load to non-peak hour. The users will compete to shift their load as well as to charge their storage device to low load period, therefore the resulting day ahead optimization problem has been formulated as non-cooperative game between the users. The iterative distributed algorithm can be run on user’s smart meters to solve the formulated problem. The strategy set for the scheduling of time shiftable devices are discrete and combinatorial in nature, hence particle swarm algorithm for optimizing the individual users pay off function has been used. The obtained results demonstrated the effectiveness of the proposed method in terms of reduced energy price and system peak while considering the user’s privacy and comfortability.","PeriodicalId":6584,"journal":{"name":"2018 International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE)","volume":"11 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86491577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.23919/ICUE-GESD.2018.8635711
R. Prabu, S. Prabhakar Karthikeyan
In developing countries, reduction of energy consumption cost, load forecasting, scheduling and control on the utility side are the major concern towards energy management. In this paper, a solution to this problem is addressed using PERT (Program Evaluation and Review Technique) combined with CPM (Critical Path Method). It is a technique to obtain the best solutions for optimized scheduling of household appliances for Home Energy Management System (HEMS). The optimization is carried out with various constraints in the selected home environment. The state of this condition is considered as a Mixed Integer Linear Programming (MILP) problem with more complexity. To reduce the complexity of this problem, it is solved in two stages namely, a grouping of appliances and selection of optimized group. The simulation of scheduling the appliances with all necessary inter dependencies is carried out using the proposed technique which is named as Customer Choice Based Algorithm (CCBA). The input data for simulation are considered from the existing methods and its results and performance are compared with the proposed algorithm. The proposed technique has effectively managed the peak demand and reduces the cost of energy consumption.
{"title":"Scheduling and Energy Management of Smart Homes Using Customer Choice Based Algorithm","authors":"R. Prabu, S. Prabhakar Karthikeyan","doi":"10.23919/ICUE-GESD.2018.8635711","DOIUrl":"https://doi.org/10.23919/ICUE-GESD.2018.8635711","url":null,"abstract":"In developing countries, reduction of energy consumption cost, load forecasting, scheduling and control on the utility side are the major concern towards energy management. In this paper, a solution to this problem is addressed using PERT (Program Evaluation and Review Technique) combined with CPM (Critical Path Method). It is a technique to obtain the best solutions for optimized scheduling of household appliances for Home Energy Management System (HEMS). The optimization is carried out with various constraints in the selected home environment. The state of this condition is considered as a Mixed Integer Linear Programming (MILP) problem with more complexity. To reduce the complexity of this problem, it is solved in two stages namely, a grouping of appliances and selection of optimized group. The simulation of scheduling the appliances with all necessary inter dependencies is carried out using the proposed technique which is named as Customer Choice Based Algorithm (CCBA). The input data for simulation are considered from the existing methods and its results and performance are compared with the proposed algorithm. The proposed technique has effectively managed the peak demand and reduces the cost of energy consumption.","PeriodicalId":6584,"journal":{"name":"2018 International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE)","volume":"190 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85544213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.23919/ICUE-GESD.2018.8635693
Nanami Gana Lantewa, N. Magaji
This paper presents artificial intelligent controller based on Artificial Neural Network (ANN) for Doubly Fed Induction Generator (DFIG) wind turbine system. For the purpose of maintaining constant active power based on PI controller concepts. The ANN controller is based on rotor loop design for a variable speed wind turbine. An active power and reactive control law are created for controlling the rotor voltages of DFIG, and error signals for both the two powers act as the input to ANN Controller; this approach eliminates the use of current inner-loops and estimation of any flux components. For the purpose of comparison PI-based vector controller is developed. The simulation results based on dynamic performance indicate the superiority of ANN based rotor loop controller over the conventional PI controller.
{"title":"Control of Doubly Fed Induction Generator of Variable Speed Wind Turbine System using Neural Network","authors":"Nanami Gana Lantewa, N. Magaji","doi":"10.23919/ICUE-GESD.2018.8635693","DOIUrl":"https://doi.org/10.23919/ICUE-GESD.2018.8635693","url":null,"abstract":"This paper presents artificial intelligent controller based on Artificial Neural Network (ANN) for Doubly Fed Induction Generator (DFIG) wind turbine system. For the purpose of maintaining constant active power based on PI controller concepts. The ANN controller is based on rotor loop design for a variable speed wind turbine. An active power and reactive control law are created for controlling the rotor voltages of DFIG, and error signals for both the two powers act as the input to ANN Controller; this approach eliminates the use of current inner-loops and estimation of any flux components. For the purpose of comparison PI-based vector controller is developed. The simulation results based on dynamic performance indicate the superiority of ANN based rotor loop controller over the conventional PI controller.","PeriodicalId":6584,"journal":{"name":"2018 International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE)","volume":"76 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90440141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.23919/ICUE-GESD.2018.8635709
Tanawat Chaonafai, Natthakorn Ruengkitrattanakul, Saranya Penpho, R. Nitisoravut, Pornthip Wimonsong
Hemp stem was used as a raw material to make available activated carbon as it contains high carbon and adsorption capacity. It was synthesized by a chemical activation using H3PO4. The effect of activation temperature within a range of 350-500°C was explored. The obtained hemp stem activated carbons (H-ACs) were used for biohydrogen enhancement. Treated activated carbon (TAC) from the National Nanotechnology Center, Thailand was used for a comparative study. The results showed that H-AC with activation temperature of 500°C obtained the maximum hydrogen yield of 2.64 ± 1.16 mol of H2/mol of sucrose. Determination of specific surface area based on the Brunauer-Emmet-Teller (BET) theory, showed that H-AC (500°C) possessed the highest mesopore volume of 0.3650 cm3/g with specific surface area of 1,219.24 m2/g. A greater porosity of H-AC (500°C) as compared to TAC and other H-ACs led to a greater adsorption ability, particularly for volatile fatty acids, thus enhanced fermentative hydrogen production.
{"title":"Hemp Stem Activated Carbon for Fermentative Hydrogen Enhancement","authors":"Tanawat Chaonafai, Natthakorn Ruengkitrattanakul, Saranya Penpho, R. Nitisoravut, Pornthip Wimonsong","doi":"10.23919/ICUE-GESD.2018.8635709","DOIUrl":"https://doi.org/10.23919/ICUE-GESD.2018.8635709","url":null,"abstract":"Hemp stem was used as a raw material to make available activated carbon as it contains high carbon and adsorption capacity. It was synthesized by a chemical activation using H3PO4. The effect of activation temperature within a range of 350-500°C was explored. The obtained hemp stem activated carbons (H-ACs) were used for biohydrogen enhancement. Treated activated carbon (TAC) from the National Nanotechnology Center, Thailand was used for a comparative study. The results showed that H-AC with activation temperature of 500°C obtained the maximum hydrogen yield of 2.64 ± 1.16 mol of H2/mol of sucrose. Determination of specific surface area based on the Brunauer-Emmet-Teller (BET) theory, showed that H-AC (500°C) possessed the highest mesopore volume of 0.3650 cm3/g with specific surface area of 1,219.24 m2/g. A greater porosity of H-AC (500°C) as compared to TAC and other H-ACs led to a greater adsorption ability, particularly for volatile fatty acids, thus enhanced fermentative hydrogen production.","PeriodicalId":6584,"journal":{"name":"2018 International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE)","volume":"61 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89355783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.23919/ICUE-GESD.2018.8635670
S. Selvakkumaran, E. Ahlgren, P. Winyuchakrit, B. Limmeechokchai
The adoption of electric vehicles (EV) is effectively a problem of socio-technical transitions and comes with its complexities. The Thai Energy Efficiency Development Plan includes the adoption of EV as a voluntary measure to increase the energy effectiveness of its transport sector and to mitigate GHG emissions. But, there are other important social, technological, economic and policy factors which need to be thoroughly investigated before the EV transition is attempted in Thailand, since the environmental cost may outweigh the benefits of the EV transition. The methodology used is based on systems thinking and called Causal Loop Diagrams (CLD). In CLD, the factors underpinning the benefits accruing from the EV transition in Thailand are characterized as causal relationships and feedback loops. Preliminary CLD investigation into the factors for EVs show the technological factor EV efficiency levels and their cost (economic factor) are important in determining the GHG reduction benefit, along with the grid emission factor.
{"title":"Electric Vehicle (EV) Transition in Thailand: Is it Beneficial?","authors":"S. Selvakkumaran, E. Ahlgren, P. Winyuchakrit, B. Limmeechokchai","doi":"10.23919/ICUE-GESD.2018.8635670","DOIUrl":"https://doi.org/10.23919/ICUE-GESD.2018.8635670","url":null,"abstract":"The adoption of electric vehicles (EV) is effectively a problem of socio-technical transitions and comes with its complexities. The Thai Energy Efficiency Development Plan includes the adoption of EV as a voluntary measure to increase the energy effectiveness of its transport sector and to mitigate GHG emissions. But, there are other important social, technological, economic and policy factors which need to be thoroughly investigated before the EV transition is attempted in Thailand, since the environmental cost may outweigh the benefits of the EV transition. The methodology used is based on systems thinking and called Causal Loop Diagrams (CLD). In CLD, the factors underpinning the benefits accruing from the EV transition in Thailand are characterized as causal relationships and feedback loops. Preliminary CLD investigation into the factors for EVs show the technological factor EV efficiency levels and their cost (economic factor) are important in determining the GHG reduction benefit, along with the grid emission factor.","PeriodicalId":6584,"journal":{"name":"2018 International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE)","volume":"50 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78268204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.23919/ICUE-GESD.2018.8635758
Van Ky Huynh, Van Duong Ngo, D. Le
Probabilistic power flow has been widely used to manage uncertainties of demand, renewable energy sources and so on in power systems. Among many methods developed for probabilistic power flow, Monte Carlo simulation can give highly accurate results; however, it is usually computationally very intensive, and this makes it impractical for calculation and analysis of large power systems in practice. In this paper, we make use of data clustering techniques to group the input data to reduce the computation time, while maintaining an appropriate level of accuracy. The proposed approach is carried out on the modified IEEE-118 bus test system to demonstrate the performance of the proposed method in comparison with the result obtained by the traditional Monte Carlo simulation.
{"title":"A Probabilistic Analysis Approach for Large Power Systems with Renewable Resources","authors":"Van Ky Huynh, Van Duong Ngo, D. Le","doi":"10.23919/ICUE-GESD.2018.8635758","DOIUrl":"https://doi.org/10.23919/ICUE-GESD.2018.8635758","url":null,"abstract":"Probabilistic power flow has been widely used to manage uncertainties of demand, renewable energy sources and so on in power systems. Among many methods developed for probabilistic power flow, Monte Carlo simulation can give highly accurate results; however, it is usually computationally very intensive, and this makes it impractical for calculation and analysis of large power systems in practice. In this paper, we make use of data clustering techniques to group the input data to reduce the computation time, while maintaining an appropriate level of accuracy. The proposed approach is carried out on the modified IEEE-118 bus test system to demonstrate the performance of the proposed method in comparison with the result obtained by the traditional Monte Carlo simulation.","PeriodicalId":6584,"journal":{"name":"2018 International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE)","volume":"12 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72766100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.23919/ICUE-GESD.2018.8635756
Tanawat Laopaiboon, W. Ongsakul, Pradya Panyainkaew, Nikhil Sasidharan
Solar photovoltaic power generation highly relies on solar irradiance, cloud cover variability, temperature, atmospheric aerosol levels, and other atmosphere parameters. Accurate forecasting of solar power is crucial to very short-term generation scheduling and on-line secure economic operation. In this paper, hour-ahead forecasting using BP-ANN is proposed. The inputs of BP-ANN include previous intervals of solar irradiation, moving average temperature, moving average relative humidity, time of the day and day of the year index. The supervised learning ANN render a higher accuracy with the good convergence mapping between input to target output data. The simulation of hour-ahead solar irradiation forecasting results from ANN render a better performance compared with autoregressive moving average model in terms of mean absolute Error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), mean bias error (MBE) and correlation coefficient (Corr).
{"title":"Hour-Ahead Solar Forecasting Program Using Back Propagation Artificial Neural Network","authors":"Tanawat Laopaiboon, W. Ongsakul, Pradya Panyainkaew, Nikhil Sasidharan","doi":"10.23919/ICUE-GESD.2018.8635756","DOIUrl":"https://doi.org/10.23919/ICUE-GESD.2018.8635756","url":null,"abstract":"Solar photovoltaic power generation highly relies on solar irradiance, cloud cover variability, temperature, atmospheric aerosol levels, and other atmosphere parameters. Accurate forecasting of solar power is crucial to very short-term generation scheduling and on-line secure economic operation. In this paper, hour-ahead forecasting using BP-ANN is proposed. The inputs of BP-ANN include previous intervals of solar irradiation, moving average temperature, moving average relative humidity, time of the day and day of the year index. The supervised learning ANN render a higher accuracy with the good convergence mapping between input to target output data. The simulation of hour-ahead solar irradiation forecasting results from ANN render a better performance compared with autoregressive moving average model in terms of mean absolute Error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), mean bias error (MBE) and correlation coefficient (Corr).","PeriodicalId":6584,"journal":{"name":"2018 International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE)","volume":"221 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73245819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.23919/ICUE-GESD.2018.8635667
S. Shahabuddin, A. K. Pandey, Jesbains Kaur, R. Saidur, N. A. Mazlan, S. Baharin
The present study illustrates an approach for the synthesis of nanoparticle doped polyaniline (PANI) nanocomposites by in-situ oxidative polymerization technique in devising electrode material for high performance supercapacitors for energy storage. A simple, facile technique to designed low cost materials based on conducting polymers for an efficient hybrid supercapacitor was discussed briefly in this article. The nanocomposites fabrication into electrodes was then discussed for the analysis of the electrochemical efficiencies employing cyclic voltammetry (CV), galvanostatic charge-discharge (GCD) and electrochemical impedance spectroscopy (EIS). The electrochemical investigations as reported by previous researchers revealed an excellence electrochemical performance of the conducting polymer-based nanocomposites leading to enhanced capacitive nature. The conducting polymer-based nanocomposite also presented an improved life cycle capacitance retention. Thus, conducting polymer-based nanocomposites demonstrates excellent efficiency and can be explored as economic alternatives to tackle the issue of energy storage.
{"title":"The Metal Oxide Nanoparticles doped Polyaniline based Nanocomposite as Stable Electrode Material for Supercapacitors","authors":"S. Shahabuddin, A. K. Pandey, Jesbains Kaur, R. Saidur, N. A. Mazlan, S. Baharin","doi":"10.23919/ICUE-GESD.2018.8635667","DOIUrl":"https://doi.org/10.23919/ICUE-GESD.2018.8635667","url":null,"abstract":"The present study illustrates an approach for the synthesis of nanoparticle doped polyaniline (PANI) nanocomposites by in-situ oxidative polymerization technique in devising electrode material for high performance supercapacitors for energy storage. A simple, facile technique to designed low cost materials based on conducting polymers for an efficient hybrid supercapacitor was discussed briefly in this article. The nanocomposites fabrication into electrodes was then discussed for the analysis of the electrochemical efficiencies employing cyclic voltammetry (CV), galvanostatic charge-discharge (GCD) and electrochemical impedance spectroscopy (EIS). The electrochemical investigations as reported by previous researchers revealed an excellence electrochemical performance of the conducting polymer-based nanocomposites leading to enhanced capacitive nature. The conducting polymer-based nanocomposite also presented an improved life cycle capacitance retention. Thus, conducting polymer-based nanocomposites demonstrates excellent efficiency and can be explored as economic alternatives to tackle the issue of energy storage.","PeriodicalId":6584,"journal":{"name":"2018 International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE)","volume":"46 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91387175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.23919/ICUE-GESD.2018.8635783
M. S. Muhit, A. Karim
A Solar-grid hybrid system design has been proposed in this paper. The design is expected to provide an economical and sustainable power supply to the AC loads. A Differential amplifier and series P channel MOSFET linear regulator technology based charge controller has been used to attain faster charging. An automatic relay based Switching between solar & grid has also been developed utilizing essential power being generated from solar; an automatic switching to solar & reducing power consumption from grid. Vice versa, if renewable output being moderately less then power demand, then it will switch to both solar and grid. Finally, when grid supplies main power when renewable output turns out to be insufficient. A real time online Wi-Fi module based monitoring circuit has been incorporated and adapted to monitor the whole system for efficient operation of the system.
{"title":"Solar – Grid Hybrid System – A Cost Effective and Improved Renewable Energy Utilization Approach","authors":"M. S. Muhit, A. Karim","doi":"10.23919/ICUE-GESD.2018.8635783","DOIUrl":"https://doi.org/10.23919/ICUE-GESD.2018.8635783","url":null,"abstract":"A Solar-grid hybrid system design has been proposed in this paper. The design is expected to provide an economical and sustainable power supply to the AC loads. A Differential amplifier and series P channel MOSFET linear regulator technology based charge controller has been used to attain faster charging. An automatic relay based Switching between solar & grid has also been developed utilizing essential power being generated from solar; an automatic switching to solar & reducing power consumption from grid. Vice versa, if renewable output being moderately less then power demand, then it will switch to both solar and grid. Finally, when grid supplies main power when renewable output turns out to be insufficient. A real time online Wi-Fi module based monitoring circuit has been incorporated and adapted to monitor the whole system for efficient operation of the system.","PeriodicalId":6584,"journal":{"name":"2018 International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE)","volume":"25 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80721141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.23919/ICUE-GESD.2018.8635716
Juan C. Oviedo, J. Solano, C. Duarte, D. St-Pierre, L. Boulon
This paper considers the problem of day ahead pricing in an islanded microgrid. In order to find cost reflective tariffs, an optimization problem is formulated to estimate the hourly day ahead prices. The optimization problem maximizes the profit of the owner of the microgrid in one hand and reduces the payment of the customers for their needed energy on the other hand. The proposed load forecasting method is achieved using a generative hierarchical model. The estimation of the marginal costs of the generated electrical energy has been established using the levelized cost of energy theory as a basis. The forecasted energy generation and consumption and the marginal costs of producing the energy are the inputs of the optimization problem. The optimization problem is used to simulate the behavior of the customers in a microgrid with 25 residential homes. The obtained results reflect the effectiveness of the proposed model reducing the electrical consume during peak hours.
{"title":"Day Ahead Tariff Setting for Islanded Microgrids Considering Customers Response","authors":"Juan C. Oviedo, J. Solano, C. Duarte, D. St-Pierre, L. Boulon","doi":"10.23919/ICUE-GESD.2018.8635716","DOIUrl":"https://doi.org/10.23919/ICUE-GESD.2018.8635716","url":null,"abstract":"This paper considers the problem of day ahead pricing in an islanded microgrid. In order to find cost reflective tariffs, an optimization problem is formulated to estimate the hourly day ahead prices. The optimization problem maximizes the profit of the owner of the microgrid in one hand and reduces the payment of the customers for their needed energy on the other hand. The proposed load forecasting method is achieved using a generative hierarchical model. The estimation of the marginal costs of the generated electrical energy has been established using the levelized cost of energy theory as a basis. The forecasted energy generation and consumption and the marginal costs of producing the energy are the inputs of the optimization problem. The optimization problem is used to simulate the behavior of the customers in a microgrid with 25 residential homes. The obtained results reflect the effectiveness of the proposed model reducing the electrical consume during peak hours.","PeriodicalId":6584,"journal":{"name":"2018 International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE)","volume":"56 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77864215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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