arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1610.09413math.OC
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能源和储备市场中的可扩展储能规划

Scalable Planning for Energy Storage in Energy and Reserve Markets

Bolun Xu, Yishen Wang, Yury Dvorkin, Ricardo Fernandez-Blanco, Cesar A. Silva-Monroy, Jean-Paul Watson, Daniel S. Kirschen

摘要:

储能可通过提供套利和辅助服务,促进可再生能源的整合。在集中式电力市场中联合优化能源和辅助服务可以降低系统的运营成本,提高储能系统的盈利能力。但是,要实现这些目标,需要正确定位存储并确定存储大小。我们使用一个双层公式来优化储能系统的位置和大小,这些储能系统执行能源套利并提供监管服务。我们的模型还通过实施回报率约束来确保储能投资的盈利能力。计算的易处理性是通过实施的原始分解和基于子梯度的割平面法。我们测试所提出的方法在240总线模型的西部电力协调委员会(WECC)系统和分析不同的存储技术,回报率的要求,和监管市场政策ES参与的最佳存储投资决策的影响。我们还表明,所提出的方法优于精确的方法在解决方案的质量和计算性能。

英文摘要:

Energy storage can facilitate the integration of renewable energy resources by providing arbitrage and ancillary services. Jointly optimizing energy and ancillary services in a centralized electricity market reduces the system's operating cost and enhances the profitability of energy storage systems. However, achieving these objectives requires that storage be located and sized properly. We use a bi-level formulation to optimize the location and size of energy storage systems which perform energy arbitrage and provide regulation services. Our model also ensures the profitability of investments in energy storage by enforcing a rate of return constraint. Computational tractability is achieved through the implementation of a primal decomposition and a subgradient-based cutting-plane method. We test the proposed approach on a 240-bus model of the Western Electricity Coordinating Council (WECC) system and analyze the effects of different storage technologies, rate of return requirements, and regulation market policies on ES participation on the optimal storage investment decisions. We also demonstrate that the proposed approach outperforms exact methods in terms of solution quality and computational performance.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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