The operation of energy storage systems (ESSs) in power systems where variable renewable energy sources (VRESs) and ESSs must contribute to securing the supply, can be considered as an arbitrage against scarcity. The value of using stored energy instantly must be balanced against its potential future value and future risk of scarcity. This paper proposes a multi-stage stochastic programming model for the operation of microgrids with VRESs, ESSs and thermal generators that is divided into a short- and a long-term model. The short-term model utilizes information from forecasts updated every six hours, while the long-term model considers the value of stored energy beyond the forecast horizon. The model is solved using stochastic dual dynamic programming and Markov chains, and the results show that the significance of accounting for short- and long-term uncertainty increases for systems with a high degree of variable renewable generation and ESSs and limited dispatchable generation capacity.

中文翻译：

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可再生能源发电和储能微电网运行的随机优化


在可变可再生能源 (VRES) 和 ESS 必须有助于确保供应的电力系统中，储能系统 (ESS) 的运行可以被视为针对稀缺性的套利。立即使用储存能源的价值必须与其潜在的未来价值和未来稀缺风险相平衡。本文提出了一种用于具有 VRES、ESS 和火力发电机的微电网运行的多阶段随机规划模型，该模型分为短期模型和长期模型。短期模型利用每六小时更新一次的预测信息，而长期模型则考虑预测范围之外的储存能量的价值。该模型使用随机对偶动态规划和马尔可夫链进行求解，结果表明，对于可再生发电和储能系统高度可变且可调度发电容量有限的系统，考虑短期和长期不确定性的重要性增加。