Against the backdrop of the world’s increasing reliance on renewable energy, the inherent intermittency and volatility of wind and solar energy pose significant challenges to the stability and economic benefits of the power system. In regions rich in renewable energy resources such as Gansu Province, due to low operational efficiency and underdeveloped market mechanisms, the potential of new energy storage systems is often not fully exploited. This paper proposes an integrated shared energy storage model designed to suppress wind power fluctuations and a two-way market trading mechanism designed to maximize social welfare to solve these problems. Firstly, a hybrid energy storage system combining electrochemical- and hydrogen-based energy storage is constructed. The modular coordination strategy is adopted to dynamically allocate power capacity, and the wind energy fluctuation suppression technology is proposed to achieve fluctuation suppression at multiple time scales. Secondly, a combined dual bidding mechanism is introduced, allowing for combined bidding across time periods and resource types, to better capture user preferences and enhance market flexibility. The model is represented as a mixed-integer nonlinear programming problem aimed at maximizing social welfare, and then transformed into a linear equivalence problem to enhance the traceability of the calculation. The branch and bound algorithm is adopted to solve this problem. Finally, the simulation results based on the bidding data of a certain area enhanced the participation of participants and improved the fairness of the market and the overall social welfare. This system effectively enhances the grid-friendliness of renewable energy grid connection and provides a scalable and replicable framework for highly renewable energy systems.
Building similarity graph...
Analyzing shared references across papers
Loading...
Yi Chai
Qinghai Hao
Ce Wang
Electronics
Northeast Electric Power University
State Grid Corporation of China (China)
Building similarity graph...
Analyzing shared references across papers
Loading...
Chai et al. (Tue,) studied this question.
www.synapsesocial.com/papers/68f10ecee6a12fd04289998c — DOI: https://doi.org/10.3390/electronics14204038