A Partnership of Virtual Power Plant in Day-Ahead Energy and Reserve Markets Based on Linearized AC Network-Constrained Unit Commitment Model

This paper presents coordinated energy management as a virtual power plant (VPP) framework with a wind farm, a storage system, and a demand response program in the transmission network according to the cooperation of VPPs in day-ahead energy and reserve markets. This strategy is based on a bilevel m...

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Veröffentlicht in:International transactions on electrical energy systems Jg. 2022; S. 1 - 16
Hauptverfasser: Haghighi, Yadollah, Bahmani-Firouzi, Bahman, Nafar, Mehdi
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Hoboken Hindawi 06.09.2022
John Wiley & Sons, Inc
Schlagworte:
Algorithms
Benders decomposition
Computing time
Constraints
Decomposition
Energy industry
Energy management
Integer programming
Linear programming
Linearization
Literature reviews
Mixed integer
Monte Carlo simulation
Operating costs
Optimization
Power plants
Profits
Reserve requirements
Stochastic programming
Taxonomy
Unit commitment
Virtual power plants
Wind farms
Wind power
ISSN:2050-7038, 2050-7038
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Zusammenfassung:This paper presents coordinated energy management as a virtual power plant (VPP) framework with a wind farm, a storage system, and a demand response program in the transmission network according to the cooperation of VPPs in day-ahead energy and reserve markets. This strategy is based on a bilevel method, where it maximizes the expected VPP revenue in the proposed markets subject to constraints of renewable and flexible sources and the VPP reserve model in the upper-level problem. Also, a market-clearing model based on network-constrained unit commitment (NCUC) is explained in the lower-level problem so that it minimizes the expected operating cost of generation units constrained to a linearized AC-NCUC model. The scenario-based stochastic programming (SBSP) models the uncertainties of loads and WF power generation. Then, the master/slave decomposition method solves the bilevel problem to achieve an optimal solution at a low computational time. Also, since the lower-level problem is mixed-integer linear programming, the Benders decomposition algorithm is adopted to solve this problem. Finally, the suggested approach is implemented on IEEE test networks in GAMS software, and numerical results confirm the efficiency of the coordinated VPP management in DA energy and reserve markets and its capabilities in improving network operation.
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ISSN:2050-7038
2050-7038
DOI:10.1155/2022/5650527