To enhance the full-timescale regulation capability of the new-type urban power grid dominated by new energy in the future, a power balance control strategy for energy storage participation in urban power grids with high-proportion green power is constructed. Taking the minimization of the daily operation total cost of the urban power grid as the optimization objective, and facing the multi-timescale power fluctuation scenarios such as step disturbances at the second level and non-step disturbances at the minute level, the complementary advantage mechanism of full-timescale regulation resources is realized through the collaborative dispatching of centralized energy storage and distributed energy storage. On this basis, a joint optimal configuration model for the day-ahead reserve capacity of multiple types of regulation resources is constructed. Aiming at the uncertainty of wind power output, a high-precision prediction method based on the Long Short-Term Memory (LSTM) network is proposed, and the probability distribution characterization of wind power fluctuations is realized by combining the indirect quantile regression technology. Based on the Conditional Value at Risk (CVaR) theory, a tail risk quantification model for wind power fluctuations is constructed. With the optimization objective of economic efficiency and risk equilibrium, an energy storage secondary frequency modulation reserve strategy that takes into account both regulation requirements and risk costs is designed. This strategy overcomes the economic losses caused by the excessive conservatism of the traditional robust optimization method, and simultaneously solves the problem of cascading failure costs that may be triggered by the inability of the chance-constrained programming to quantify extreme risks. The effectiveness of the proposed energy storage collaborative control strategy is verified through case simulation and comparative analysis of multiple schemes. The results show that under the unified control framework, the collaborative operation of centralized energy storage and distributed energy storage can ensure the safe and stable operation of the urban power grid and significantly improve the full-timescale regulation capability of the power grid.

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Power Balance Control Strategy for High-Proportion Green Power Urban Grids with Collaborative Participation of Centralized and Distributed Energy Storage in Full-Timescale

  • Mingze Zhang,
  • Lang Sun,
  • Mingke Ye,
  • Jiakai Shen,
  • Yucui Wang,
  • Shuangxi Zhou,
  • Guangxin Fan

摘要

To enhance the full-timescale regulation capability of the new-type urban power grid dominated by new energy in the future, a power balance control strategy for energy storage participation in urban power grids with high-proportion green power is constructed. Taking the minimization of the daily operation total cost of the urban power grid as the optimization objective, and facing the multi-timescale power fluctuation scenarios such as step disturbances at the second level and non-step disturbances at the minute level, the complementary advantage mechanism of full-timescale regulation resources is realized through the collaborative dispatching of centralized energy storage and distributed energy storage. On this basis, a joint optimal configuration model for the day-ahead reserve capacity of multiple types of regulation resources is constructed. Aiming at the uncertainty of wind power output, a high-precision prediction method based on the Long Short-Term Memory (LSTM) network is proposed, and the probability distribution characterization of wind power fluctuations is realized by combining the indirect quantile regression technology. Based on the Conditional Value at Risk (CVaR) theory, a tail risk quantification model for wind power fluctuations is constructed. With the optimization objective of economic efficiency and risk equilibrium, an energy storage secondary frequency modulation reserve strategy that takes into account both regulation requirements and risk costs is designed. This strategy overcomes the economic losses caused by the excessive conservatism of the traditional robust optimization method, and simultaneously solves the problem of cascading failure costs that may be triggered by the inability of the chance-constrained programming to quantify extreme risks. The effectiveness of the proposed energy storage collaborative control strategy is verified through case simulation and comparative analysis of multiple schemes. The results show that under the unified control framework, the collaborative operation of centralized energy storage and distributed energy storage can ensure the safe and stable operation of the urban power grid and significantly improve the full-timescale regulation capability of the power grid.