The Experts below are selected from a list of 213732 Experts worldwide ranked by ideXlab platform
Jianfei Pan - One of the best experts on this subject based on the ideXlab platform.
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distributed robust Energy management of a multimicrogrid system in the real time Energy Market
IEEE Transactions on Sustainable Energy, 2019Co-Authors: Yun Liu, H B Gooi, Ye Jian, Huanhai Xin, Xichen Jiang, Jianfei PanAbstract:In this paper, a distributed robust Energy management scheme for multiple interconnected microgrids (MGs) is developed. It aims to optimize the total operational cost of the MGs through Energy trading with neighboring MGs and the main grid in the real-time Energy Market. Various uncertainties including renewable generation, load consumption, and buying/selling prices of the main grid are handled using an adjustable robust optimization technique. To keep consistent with the distributed nature of the multiple MGs, we propose a distributed adjustable robust optimal scheduling algorithm. Within the framework, each MG Energy management system determines its own selling price and operation schedule via distributed communication of noncritical information with its neighboring MGs. Robust optimal scheduling and fair Energy trading can be collectively achieved. A case study of a 4-MG system is conducted to validate the effectiveness of the proposed approach.
Xiaojun Lin - One of the best experts on this subject based on the ideXlab platform.
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storage or no storage duopoly competition between renewable Energy suppliers in a local Energy Market
IEEE Journal on Selected Areas in Communications, 2019Co-Authors: Dongwei Zhao, Hao Wang, Jianwei Huang, Xiaojun LinAbstract:Renewable Energy generations and Energy storage are playing increasingly important roles in serving consumers in power systems. This paper studies the Market competition between renewable Energy suppliers with or without Energy storage in a local Energy Market. The storage investment brings the benefits of stabilizing renewable Energy suppliers’ outputs, but it also leads to substantial investment costs as well as some surprising changes in the Market outcome. To study the equilibrium decisions of storage investment in the renewable Energy suppliers’ competition, we model the interactions between suppliers and consumers using a three-stage game-theoretic model. In Stage 1, at the beginning of the investment horizon (containing many days), suppliers decide whether to invest in storage. Once such decisions have been made (once), in the day-ahead Market of each day, suppliers decide on their bidding prices and quantities in Stage 2, based on which consumers decide the electricity quantity purchased from each supplier in Stage 3. In the real-time Market, a supplier is penalized if his actual generation falls short of his commitment. We characterize a price-quantity competition equilibrium of Stage 2 in the local Energy Market, and we further characterize a storage-investment equilibrium in Stage 1 incorporating electricity-selling revenue and storage cost. Counter-intuitively, we show that the uncertainty of renewable Energy without storage investment can lead to higher supplier profits compared with the stable generations with storage investment due to the reduced Market competition under random Energy generation. Simulations further illustrate results due to the Market competition. For example, a higher penalty for not meeting the commitment, a higher storage cost, or a lower consumer demand can sometimes increase a supplier’s profit. We also show that although storage investment can increase a supplier ’s profit, the first-mover supplier who invests in storage may benefit less than the free-rider competitor who chooses not to invest in storage.
Yun Liu - One of the best experts on this subject based on the ideXlab platform.
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distributed robust Energy management of a multimicrogrid system in the real time Energy Market
IEEE Transactions on Sustainable Energy, 2019Co-Authors: Yun Liu, H B Gooi, Ye Jian, Huanhai Xin, Xichen Jiang, Jianfei PanAbstract:In this paper, a distributed robust Energy management scheme for multiple interconnected microgrids (MGs) is developed. It aims to optimize the total operational cost of the MGs through Energy trading with neighboring MGs and the main grid in the real-time Energy Market. Various uncertainties including renewable generation, load consumption, and buying/selling prices of the main grid are handled using an adjustable robust optimization technique. To keep consistent with the distributed nature of the multiple MGs, we propose a distributed adjustable robust optimal scheduling algorithm. Within the framework, each MG Energy management system determines its own selling price and operation schedule via distributed communication of noncritical information with its neighboring MGs. Robust optimal scheduling and fair Energy trading can be collectively achieved. A case study of a 4-MG system is conducted to validate the effectiveness of the proposed approach.
Andrew L. Ott - One of the best experts on this subject based on the ideXlab platform.
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The PJM RTO Energy Market
2002Co-Authors: Andrew L. OttAbstract:lOverview - This section will outline the basic functions of the Pennsylvania Jersey Maryland (PJM) Interconnection Regional Transmission Organization (RTO) * PJM Energy Market - This section will describe the PJM Energy Market design. The discussion will describe the various wholesale Energy Market products and hedging options. * Expansion of PJM Market, PJM West - This section will describe the implementation process to expand the PJM Market to include the PJM West control area which is scheduled for implementation on January 1,2002. * PJM Energy Market Operations - This section will provide summary statistics on the PJM Energy Market and will include lessons learned from the past four years of Energy Market operations.
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The PJM RTO Energy Market [electricity supply industry]
2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309), 1Co-Authors: Andrew L. OttAbstract:Summary form only given, as follows. This paper outlines the basic functions of the Pennsylvania Jersey Maryland (PJM) Interconnection Regional Transmission Organization (RTO) in the USA. Subjects covered include: the PJM Energy Market design; the various wholesale Energy Market products and hedging options; the implementation process to expand the PJM Market to include the PJM West control area which is scheduled for implementation on January 1, 2002; and summary statistics on the PJM Energy Market, including lessons learned from the past four years of Energy Market operations.
Kazem Zare - One of the best experts on this subject based on the ideXlab platform.
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stochastic optimization of Energy hub operation with consideration of thermal Energy Market and demand response
Energy Conversion and Management, 2017Co-Authors: M J Vahidpakdel, Sayyad Nojavan, Behnam Mohammadiivatloo, Kazem ZareAbstract:Abstract Multi carrier Energy systems or Energy hubs has provided more flexibility for Energy management systems. On the other hand, due to mutual impact of different Energy carriers in Energy hubs, Energy management studies become more challengeable. The initial patterns of Energy demands from grids point of view can be modified by optimal scheduling of Energy hubs. In this work, optimal operation of multi carrier Energy system has been studied in the presence of wind farm, electrical and thermal storage systems, electrical and thermal demand response programs, electricity Market and thermal Energy Market. Stochastic programming is implemented for modeling the system uncertainties such as demands, Market prices and wind speed. It is shown that adding new source of heat Energy for providing demand of consumers with Market mechanism changes the optimal operation point of multi carrier Energy system. Presented mixed integer linear formulation for the problem has been solved by executing CPLEX solver of GAMS optimization software. Simulation results shows that hub’s operation cost reduces up to 4.8% by enabling the option of using thermal Energy Market for meeting heat demand.