Open Access

ARTICLE

A Coordinated Thermal Power-Energy Storage Planning Method for Addressing Renewable Energy Uncertainty

Cheng Yang¹, Xiuyu Yang^1,*, Gangui Yan¹, Hongda Dong², Chenggang Li²
1 School of Electrical Engineering, Northeast Electric Power University, Jilin, 132012, China
2 Electric Power Research Institute, State Grid Jilin Electric Power Company Limited, Changchun, 130021, China
* Corresponding Author: Xiuyu Yang. Email:

Energy Engineering https://doi.org/10.32604/ee.2025.072773

Received 03 September 2025; Accepted 13 November 2025; Published online 22 December 2025

Abstract

The integration of renewable energy introduces significant uncertainty into daily power system operation scenarios. Traditional deterministic unit commitment methods struggle to adapt to these conditions, often resulting in poor economic performance and high curtailment rates in planning outcomes. To address these challenges, this paper proposes a coordinated thermal power-energy storage planning methodology for managing renewable energy uncertainty. First, the operational effectiveness of daily unit commitment under uncertain renewable energy scenarios is analyzed, with quantitative assessment of how different commitment strategies impact supply-demand balance and economic performance. Subsequently, by conducting flexibility evaluation under multiple renewable energy output profiles in typical days, an entropy weight-based method for determining daily unit commitment is developed. This approach evaluates the performance of commitment strategies across multiple uncertain scenarios using various flexibility metrics, enabling the identification of strategies that effectively accommodate uncertainty. Furthermore, building upon the entropy weight-based unit commitment methodology, a coordinated thermal power-energy storage planning model is formulated with the objective of minimizing expected costs across all scenarios. Finally, using actual measurement data from a Northeast China power grid, multiple typical-day uncertainty scenarios are constructed, and case study analysis validates the effectiveness of the proposed methodology.

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Keywords

RE uncertainty; joint fire-storage planning; entropy weighting method; flexibility evaluation

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