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arXiv 2301.01462eess.SYcs.SY
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不确定性下社区储能系统的多目标规划

Multi-Objective Planning of Community Energy Storage Systems Under Uncertainty

K. B. J. Anuradha, Jose Iria, Chathurika P. Mediwaththe

AI总结:

本文提出多目标随机优化框架,在三类能源交易方案下规划社区储能,并通过场景生成与K-Means缩减处理负荷和光伏不确定性,证明平均电网交易价格方案最公平。

摘要:

本文评估了在不同能源交易方案(ETS)下,社区储能(CES)系统的规划如何能够公平地使低压(LV)产消者和CES提供商受益。首先,我们考虑一种ETS,其中CES提供商以平均电网能源交易价格与产消者交易能源;其次,考虑一种ETS,其中CES提供商以高于电网能源交易价格的价格交易能源;第三,考虑一种ETS,其中CES提供商以低于电网能源交易价格的价格交易能源。为此,我们提出了一个多目标随机优化框架,以最小化CES提供商的投资成本和年度运营成本以及产消者的年度运营成本,同时考虑产消者有功和无功能源消耗以及光伏(PV)发电的不确定性。这些不确定性使用正态概率密度函数建模。随后,利用轮盘赌机制(RWM)构建基于场景的随机规划。然后,使用K-Means聚类算法对从RWM获得的初始场景进行缩减,以使问题易于处理。我们的实验表明,与其他两种ETS相比,CES提供商以平均电网能源交易价格交易能源的ETS能够更公平地使产消者和CES提供商受益。

英文摘要:

This paper evaluates how the planning of a community energy storage (CES) system under different energy trading schemes (ETSs) can benefit low voltage (LV) prosumers and the CES provider equitably. First, we consider an ETS where the CES provider trades energy with prosumers at the average grid energy trading price, second, an ETS where the CES provider trades energy at a higher price than the grid energy trading price, and third, an ETS where the CES provider trades energy at a lower price than the grid energy trading price. To this end, we present a multi-objective stochastic optimization framework to minimize the investment and annual operating costs of the CES provider and annual operating costs of prosumers, taking into account the uncertainties of real and reactive energy consumption and photovoltaic (PV) generation of prosumers. The uncertainties are modeled using the normal probability density function. Then, the roulette wheel mechanism (RWM) is exploited to formulate a scenario-based stochastic program. The initial scenarios obtained from the RWM, are then reduced using the K-Means clustering algorithm, to make the problem tractable. Our experiments show that the ETS where the CES provider trades energy at the average grid energy trading price benefits prosumers and the CES provider more equitably than the other two ETSs.

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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