Planning of Smart Microgrids with High Renewable Penetration Considering Electricity Market Conditions

2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) Pub Date : 2019-06-10 DOI:10.1109/EEEIC.2019.8783333

S. Hakimi, Hamed Bagheritabar, Arezoo Hasankhani, M. Shafie‐khah, M. Lotfi, J. Catalão

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引用次数: 8

Abstract

In this paper, a new method for optimal sizing of distributed generation (DG) is presented in order to minimize electricity costs in smart microgrids (MGs). This paper presents a study of the effect of wholesale electricity market on smart MGs. The study was performed for the Ekbatan residential complex which includes three smart MGs considering high penetration of renewable energy resources and a 63/20 kV substation in Tehran, Iran. The role of these smart MGs in the pool electricity market is a price maker, and a game-theoretical (GT) model is applied for their bidding strategies. The objective cost function considers different cost parameters in smart MGs, which are optimized using particle swarm optimization (PSO). The results show that applying this method is effective for economic sizing of DGs.

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考虑电力市场条件的可再生能源高渗透率智能微电网规划

为了使智能微电网的电力成本最小化，提出了一种新的分布式发电规模优化方法。本文研究了电力批发市场对智能电网的影响。该研究是在伊朗德黑兰的Ekbatan住宅区进行的，该住宅区包括三个考虑到可再生能源高渗透率的智能mg和一个63/20千伏变电站。智能电网在池电市场中的角色是价格制定者，并应用博弈论模型对其竞价策略进行了分析。目标代价函数考虑了智能mg的不同代价参数，并采用粒子群算法(PSO)进行优化。结果表明，应用该方法对DGs的经济施胶是有效的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)

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