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Capacity Share Optimization for Multiservice Energy Storage Management Under Portfolio Theory

机译:组合理论下的多业务储能管理容量分配优化

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摘要

Energy storage (ES) is playing a vital role in providing multiple services in several electricity markets. However, the benefits and risks vary across markets and time, which justifies the importance to optimize ES capacity share in different markets. In this paper, a novel portfolio theory-based approach is proposed for optimally managing ES in various markets to maximize benefits and reduce the risk for ES owners. Three markets are considered, which are energy arbitrage, ancillary services, and distributed network operator's market. They are modeled based on energy cost, frequency response cost, and system congestion cost. Portfolio theory is utilized to quantify ES capacity allocated to each market over time for various levels of risk aversions. The relation between risks and expected return of different markets is efficiently reflected by the portfolio theory, providing implications to storage operation. The extensive demonstration illustrates that the markets that storage can participate in are fundamentally different regarding to its risk aversion. In addition, the optimum portfolio of the markets for storage is on the efficient frontier, providing the maximum return at a certain risk aversion level. This study is particularly useful for guiding market participation and operation of ES to gain maximum economic return at minimum risk.
机译:储能(ES)在多个电力市场中提供多种服务中扮演着至关重要的角色。但是,收益和风险随市场和时间的不同而变化,这证明了优化不同市场中ES能力份额的重要性。在本文中,提出了一种基于投资组合理论的新颖方法,用于在各种市场中对ES进行最佳管理,以最大化ES所有者的利益并降低ES所有者的风险。考虑了三个市场,分别是能源套利,辅助服务和分布式网络运营商的市场。根据能源成本,频率响应成本和系统拥塞成本对它们进行建模。资产组合理论用于量化针对不同风险规避水平随时间分配给每个市场的ES能力。投资组合理论有效地反映了不同市场的风险与预期收益之间的关系,为仓储业务提供了启示。广泛的演示表明,存储可以参与的市场在风险规避方面根本不同。此外,存储市场的最佳组合处于有效边界上,在一定的风险规避水平下可提供最大的回报。这项研究对于指导ES的市场参与和运营以最小的风险获得最大的经济回报特别有用。

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