Multi-timescale Virtual Power Plant Optimization Strategy Considering Flexible Resource Real-time Schedulable Domain Characterization

With the diversification of the subjects of Virtual Power Plant (VPP) aggregation topics, the requirements for exploring the flexible potential of distributed resources have increased. This paper proposes a multi-timescale VPP optimization strategy based on accurately characterizing a flexible resou...

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Published in2024 IEEE 25th China Conference on System Simulation Technology and its Application (CCSSTA) pp. 869 - 874
Main Authors Ren, Yuan, Kong, Xiangyu, Zhang, Peirong, Zhang, Xiyuan, Zhu, Jingkai, Zheng, Qingrong
Format Conference Proceeding
LanguageEnglish
Published IEEE 21.07.2024
Subjects
conditional value at risk
Decision making
Electric potential
Electricity
Heuristic algorithms
mixed integer linear programming
Optimization
optimization strategy
Real-time systems
Self-organizing feature maps
Turbines
Uncertainty
Virtual power plants
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Summary:With the diversification of the subjects of Virtual Power Plant (VPP) aggregation topics, the requirements for exploring the flexible potential of distributed resources have increased. This paper proposes a multi-timescale VPP optimization strategy based on accurately characterizing a flexible resource schedulable domain. Firstly, a dispatch ability evaluation model for Electric Vehicles (EVs) is formulated based on the Minkowski summation, which accurately portrays the flexible adjustment range of distributed resources. The Self-Organizing Map (SOM) algorithm is used to reduce the set of scenes, so that the interests of virtual power plants and electric vehicles are balanced. Secondly, the KKT(Karush-Kuhn-Tucker) algorithm is introduced to construct the two-layer co-scheduling model for VPP and EVs, which transforms the two-layer problem into a solvable Mixed Integer Linear Programming (MILP) problem. Finally, the model integrates Conditional Value at Risk (CVaR) to evaluate the interplay between potential bid revenues and associated uncertainty risks. The actual Virtual Power Plant demonstration project of Tianjin was used to verify the accuracy and economics of the method in improving the overall profitability of the VPP.
DOI:10.1109/CCSSTA62096.2024.10691705