Pub Date : 2010-07-25DOI: 10.1109/PES.2010.5589333
B. Ramachandran, S. Srivastava, D. Cartes, C. Edrington
This paper presents the implementation of distributed energy resource management in smart grid operation. The approach utilizes the advantages of using multi agent systems for profitable operation of a smart grid in the energy market. The trading strategy adopted for the continuous double auction is a profit-maximizing adaptive bidding strategy based on risk and competitive equilibrium price prediction. The auctioneer manages the usage of distributed energy resources by receiving bids from buyers and asks from sellers. An artificial immune system based algorithm is applied on a typical study case network to optimize the generation assuming realistic market prices for power and distributed generators bids reflecting realistic operational costs. Simulation results clearly indicate that the agent based management is effective in coordinating the various distributed energy resources economically and profitably.
{"title":"Distributed energy resource management in a smart grid by risk based auction strategy for profit maximization","authors":"B. Ramachandran, S. Srivastava, D. Cartes, C. Edrington","doi":"10.1109/PES.2010.5589333","DOIUrl":"https://doi.org/10.1109/PES.2010.5589333","url":null,"abstract":"This paper presents the implementation of distributed energy resource management in smart grid operation. The approach utilizes the advantages of using multi agent systems for profitable operation of a smart grid in the energy market. The trading strategy adopted for the continuous double auction is a profit-maximizing adaptive bidding strategy based on risk and competitive equilibrium price prediction. The auctioneer manages the usage of distributed energy resources by receiving bids from buyers and asks from sellers. An artificial immune system based algorithm is applied on a typical study case network to optimize the generation assuming realistic market prices for power and distributed generators bids reflecting realistic operational costs. Simulation results clearly indicate that the agent based management is effective in coordinating the various distributed energy resources economically and profitably.","PeriodicalId":177545,"journal":{"name":"IEEE PES General Meeting","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128867433","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 : 2010-07-25DOI: 10.1109/PES.2010.5589844
S. Jafarzadeh, S. Fadali, C. Evrenosoglu, H. Livani
This paper presents a new stochastic method for very short-term (1 hour) wind prediction in electrical power systems. The method utilizes Hidden Markov Models (HMM) and the Viterbi Algorithm (VA). Past wind farm power production data are required to develop the HMM model. The accuracy of the predictions improves drastically if hourly weather forecast data are used as pseudo-measurements. Computer simulations using Northwestern weather recordings from the Bonneville Power Administration (BPA) website show good correlation between our predictions and the actual data.
{"title":"Hour-ahead wind power prediction for power systems using Hidden Markov Models and Viterbi Algorithm","authors":"S. Jafarzadeh, S. Fadali, C. Evrenosoglu, H. Livani","doi":"10.1109/PES.2010.5589844","DOIUrl":"https://doi.org/10.1109/PES.2010.5589844","url":null,"abstract":"This paper presents a new stochastic method for very short-term (1 hour) wind prediction in electrical power systems. The method utilizes Hidden Markov Models (HMM) and the Viterbi Algorithm (VA). Past wind farm power production data are required to develop the HMM model. The accuracy of the predictions improves drastically if hourly weather forecast data are used as pseudo-measurements. Computer simulations using Northwestern weather recordings from the Bonneville Power Administration (BPA) website show good correlation between our predictions and the actual data.","PeriodicalId":177545,"journal":{"name":"IEEE PES General Meeting","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128877463","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 : 2010-07-25DOI: 10.1109/PES.2010.5590071
R. Carter, G. Ault, I. Kockar
This paper will discuss the purpose and value of energy storage as a transitional technology towards SmartGrids, as well as its utilization within the future network operational arrangements. The paper will investigate assessment techniques of energy storage at a local, system and global level, with a focus on the ways that energy storage may be valued. The paper will analyse existing techniques that are used to evaluate factors which influence decisions on the value of storage, and indicate areas which require further development in order to enable effective deployment of energy storage on current and future grids.
{"title":"Techniques for assessing the value of energy storage in the transition to and operation of SmartGrids","authors":"R. Carter, G. Ault, I. Kockar","doi":"10.1109/PES.2010.5590071","DOIUrl":"https://doi.org/10.1109/PES.2010.5590071","url":null,"abstract":"This paper will discuss the purpose and value of energy storage as a transitional technology towards SmartGrids, as well as its utilization within the future network operational arrangements. The paper will investigate assessment techniques of energy storage at a local, system and global level, with a focus on the ways that energy storage may be valued. The paper will analyse existing techniques that are used to evaluate factors which influence decisions on the value of storage, and indicate areas which require further development in order to enable effective deployment of energy storage on current and future grids.","PeriodicalId":177545,"journal":{"name":"IEEE PES General Meeting","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131913052","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 : 2010-07-25DOI: 10.1109/PES.2010.5589802
Y. Yare, G. Venayagamoorthy
An optimal preventive generator maintenance scheduling (GMS) in a smart grid environment comprising wind-hydrothermal energy resources is presented in this paper. GMS problem is solved with the aim of maximizing economic benefits subject to satisfying system constraints. This GMS formulation becomes a challenging problem because of the variability and intermittency of wind speed and the incorporation of uncertainty in wind generation. The objective is to perform preventive GMS in such a manner that the annual generation cost is minimized, the annual cost saving is increased while all operating constraints are satisfied in the presence of uncertainty in wind generation. Discrete modified particle swarm optimization (MPSO-D) algorithm is used to solve this problem. The results presented on a typical Nigerian power system show the potential and benefits obtainable from increasing wind power penetration.
{"title":"GMS considering uncertainty in wind power in a wind-hydrothermal power system","authors":"Y. Yare, G. Venayagamoorthy","doi":"10.1109/PES.2010.5589802","DOIUrl":"https://doi.org/10.1109/PES.2010.5589802","url":null,"abstract":"An optimal preventive generator maintenance scheduling (GMS) in a smart grid environment comprising wind-hydrothermal energy resources is presented in this paper. GMS problem is solved with the aim of maximizing economic benefits subject to satisfying system constraints. This GMS formulation becomes a challenging problem because of the variability and intermittency of wind speed and the incorporation of uncertainty in wind generation. The objective is to perform preventive GMS in such a manner that the annual generation cost is minimized, the annual cost saving is increased while all operating constraints are satisfied in the presence of uncertainty in wind generation. Discrete modified particle swarm optimization (MPSO-D) algorithm is used to solve this problem. The results presented on a typical Nigerian power system show the potential and benefits obtainable from increasing wind power penetration.","PeriodicalId":177545,"journal":{"name":"IEEE PES General Meeting","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115417058","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 : 2010-07-25DOI: 10.1109/PES.2010.5589535
A. Botterud, J. Wang, R. Bessa, H. Keko, Vladimiro Miranda
This paper discusses risk management, contracting, and bidding for a wind power producer. A majority of the wind power in the United States is sold on long-term power purchase agreements, which hedge the wind power producer against future price risks. However, a significant amount is sold as merchant power and therefore is exposed to fluctuations in future electricity prices (day-ahead and real-time) and potential imbalance penalties. Wind power forecasting can serve as a tool to increase the profit and reduce the risk from participating in the wholesale electricity market. We propose a methodology to derive optimal day-ahead bids for a wind power producer under uncertainty in realized wind power and market prices. We also present an initial illustrative case study from a hypothetical wind site in the United States, where we compare the results of different day-ahead bidding strategies. The results show that the optimal day-ahead bid is highly dependent on the expected day-ahead and real-time prices, and also on the risk preferences of the wind power producer. A deviation penalty between day-ahead bid and real-time delivery tends to drive the bids closer to the expected generation for the next day.
{"title":"Risk management and optimal bidding for a wind power producer","authors":"A. Botterud, J. Wang, R. Bessa, H. Keko, Vladimiro Miranda","doi":"10.1109/PES.2010.5589535","DOIUrl":"https://doi.org/10.1109/PES.2010.5589535","url":null,"abstract":"This paper discusses risk management, contracting, and bidding for a wind power producer. A majority of the wind power in the United States is sold on long-term power purchase agreements, which hedge the wind power producer against future price risks. However, a significant amount is sold as merchant power and therefore is exposed to fluctuations in future electricity prices (day-ahead and real-time) and potential imbalance penalties. Wind power forecasting can serve as a tool to increase the profit and reduce the risk from participating in the wholesale electricity market. We propose a methodology to derive optimal day-ahead bids for a wind power producer under uncertainty in realized wind power and market prices. We also present an initial illustrative case study from a hypothetical wind site in the United States, where we compare the results of different day-ahead bidding strategies. The results show that the optimal day-ahead bid is highly dependent on the expected day-ahead and real-time prices, and also on the risk preferences of the wind power producer. A deviation penalty between day-ahead bid and real-time delivery tends to drive the bids closer to the expected generation for the next day.","PeriodicalId":177545,"journal":{"name":"IEEE PES General Meeting","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115691212","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 : 2010-07-25DOI: 10.1109/PES.2010.5589776
M. Ilić
The combined industry changes, technological and organizational, have brought about new complexity from the highest level system to the smallest level component. The consequent burden on new technical leaders is enormous. Most of all, they must be capable of rethinking how to plan, rebuild and operate an infrastructure which has been turned upside-down from what it used to be. In order to prepare for such major challenge, leaders must understand 3-φ physics (the basic foundations); modeling of complex systems (architecture-dependent models, components and their interactions, performance objectives); dependence of models on sensors and actuators; design for desired system performance (defined by economic policy and engineering specifications); numerical methods and algorithms, and IT, in its broadest sense.
{"title":"Teaching smart grids: Yet another challenge and opportunity for transforming power systems curriculum","authors":"M. Ilić","doi":"10.1109/PES.2010.5589776","DOIUrl":"https://doi.org/10.1109/PES.2010.5589776","url":null,"abstract":"The combined industry changes, technological and organizational, have brought about new complexity from the highest level system to the smallest level component. The consequent burden on new technical leaders is enormous. Most of all, they must be capable of rethinking how to plan, rebuild and operate an infrastructure which has been turned upside-down from what it used to be. In order to prepare for such major challenge, leaders must understand 3-φ physics (the basic foundations); modeling of complex systems (architecture-dependent models, components and their interactions, performance objectives); dependence of models on sensors and actuators; design for desired system performance (defined by economic policy and engineering specifications); numerical methods and algorithms, and IT, in its broadest sense.","PeriodicalId":177545,"journal":{"name":"IEEE PES General Meeting","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115887794","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 : 2010-07-25DOI: 10.1109/PES.2010.5589605
C. Binding, D. Gantenbein, Bernhard Jansen, O. Sundstrom, Peter Bach Andersen, F. Marra, B. Poulsen, C. Traeholt
The Danish EDISON project has been launched to investigate how a large fleet of electric vehicles (EVs) can be integrated in a way that supports the electric grid while benefitting both the individual car owners and society as a whole through reductions in CO2 emissions. The consortium partners include energy companies, technology suppliers and research laboratories and institutes. The aim is to perform a thorough investigation of the challenges and opportunities of EVs and then to deliver a technical platform that can be demonstrated on the Danish island of Bornholm. To reach this goal, a vast amount of research is done in various areas of EV technology by the partners. This paper will focus on the ICT-based distributed software integration, which plays a major role for the success of EDISON. Key solution technologies and standards that will accommodate communication and optimize the coordination of EVs will be described as well as the simulation work that will help to reach the goals of the project.
{"title":"Electric vehicle fleet integration in the danish EDISON project - A virtual power plant on the island of Bornholm","authors":"C. Binding, D. Gantenbein, Bernhard Jansen, O. Sundstrom, Peter Bach Andersen, F. Marra, B. Poulsen, C. Traeholt","doi":"10.1109/PES.2010.5589605","DOIUrl":"https://doi.org/10.1109/PES.2010.5589605","url":null,"abstract":"The Danish EDISON project has been launched to investigate how a large fleet of electric vehicles (EVs) can be integrated in a way that supports the electric grid while benefitting both the individual car owners and society as a whole through reductions in CO2 emissions. The consortium partners include energy companies, technology suppliers and research laboratories and institutes. The aim is to perform a thorough investigation of the challenges and opportunities of EVs and then to deliver a technical platform that can be demonstrated on the Danish island of Bornholm. To reach this goal, a vast amount of research is done in various areas of EV technology by the partners. This paper will focus on the ICT-based distributed software integration, which plays a major role for the success of EDISON. Key solution technologies and standards that will accommodate communication and optimize the coordination of EVs will be described as well as the simulation work that will help to reach the goals of the project.","PeriodicalId":177545,"journal":{"name":"IEEE PES General Meeting","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124152019","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 : 2010-07-25DOI: 10.1109/PES.2010.5590012
Xinru Dong, M. Ni
The Chinese Nanyang-Jingmen 1000 kV UHV AC demonstration project began commercial operations in early 2009. Multiple 1000kV AC and 800kV HVDC transmission lines are part of the transmission expansion plan up to the year 2020. The transmission expansion plan is the result of a comprehensive analysis of China's economic development, generation expansion forecasts, and power flow import and export requirements. This paper describes the current and future development of the UHV power grid in China. Further research and development efforts are being pursued.
{"title":"Ultra high voltage power grid development in China","authors":"Xinru Dong, M. Ni","doi":"10.1109/PES.2010.5590012","DOIUrl":"https://doi.org/10.1109/PES.2010.5590012","url":null,"abstract":"The Chinese Nanyang-Jingmen 1000 kV UHV AC demonstration project began commercial operations in early 2009. Multiple 1000kV AC and 800kV HVDC transmission lines are part of the transmission expansion plan up to the year 2020. The transmission expansion plan is the result of a comprehensive analysis of China's economic development, generation expansion forecasts, and power flow import and export requirements. This paper describes the current and future development of the UHV power grid in China. Further research and development efforts are being pursued.","PeriodicalId":177545,"journal":{"name":"IEEE PES General Meeting","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124449718","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 : 2010-07-25DOI: 10.1109/PES.2010.5589593
P. Sauer
Advances in technology and major programs to enhance the electric power system throughout the world have led to the concept of the “Smart Grid”. This concept has been formally defined in various places and is driving many of the current changes in educational curricula at all levels. This paper provides a brief summary of the known definitions and the resulting educational needs for the technical workforce of the future.
{"title":"Educational needs for the “Smart Grid” workforce","authors":"P. Sauer","doi":"10.1109/PES.2010.5589593","DOIUrl":"https://doi.org/10.1109/PES.2010.5589593","url":null,"abstract":"Advances in technology and major programs to enhance the electric power system throughout the world have led to the concept of the “Smart Grid”. This concept has been formally defined in various places and is driving many of the current changes in educational curricula at all levels. This paper provides a brief summary of the known definitions and the resulting educational needs for the technical workforce of the future.","PeriodicalId":177545,"journal":{"name":"IEEE PES General Meeting","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124534693","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 : 2010-07-25DOI: 10.1109/PES.2010.5589389
A. Hawkes
Microgrids are defined as an area of network that is capable of operating autonomously from the rest of the electricity system. They achieve this by containing enough energy resources to meet all incorporated electrical (and thermal) loads, and by coordinating control in order to meet the participants' aims, and afford adequate quality/reliability of power and heat supply. From an economic point-of-view, the key determinant is the fact that sufficient resources must exist within the microgrid to meet the demands of participants with a degree of reliability that is commensurate with the value of the load being served. Framed by these issues, this paper presents a method for cost-optimal microgrid design (i.e. choice of generation components) under uncertainty of energy price and technology performance. Results serve to aid debate regarding the tractability of problems of this type, and demonstrate that currently-dominant deterministic approaches can lead to poor choice of components.
{"title":"Optimal selection of generators for a microgrid under uncertainty","authors":"A. Hawkes","doi":"10.1109/PES.2010.5589389","DOIUrl":"https://doi.org/10.1109/PES.2010.5589389","url":null,"abstract":"Microgrids are defined as an area of network that is capable of operating autonomously from the rest of the electricity system. They achieve this by containing enough energy resources to meet all incorporated electrical (and thermal) loads, and by coordinating control in order to meet the participants' aims, and afford adequate quality/reliability of power and heat supply. From an economic point-of-view, the key determinant is the fact that sufficient resources must exist within the microgrid to meet the demands of participants with a degree of reliability that is commensurate with the value of the load being served. Framed by these issues, this paper presents a method for cost-optimal microgrid design (i.e. choice of generation components) under uncertainty of energy price and technology performance. Results serve to aid debate regarding the tractability of problems of this type, and demonstrate that currently-dominant deterministic approaches can lead to poor choice of components.","PeriodicalId":177545,"journal":{"name":"IEEE PES General Meeting","volume":"107 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114430094","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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