Power Loss-Aware Transactive Microgrid Coalitions under Uncertainty
Power Loss-Aware Transactive Microgrid Coalitions under Uncertainty
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DOI：
10.3390/en13215782
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发表时间：
2020-11
期刊：
影响因子：
3.2
通讯作者：
M. Sadeghi;Shahram Mollahasani;M. Erol-Kantarci
中科院分区：
文献类型：
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作者：
M. Sadeghi;Shahram Mollahasani;M. Erol-Kantarci
微电网(MG)社区内的点对点能源交易成为未来交易型配电系统和交易型电力市场的关键推动因素。MG内部的能量交易是指一个MG的剩余能量可以用来满足另一个MG或组成MG社区的一组MG的需求。这些社区可以根据互联MG的需求和供应的变化，随着时间的推移而动态建立。在许多现代MG中，电动汽车(EV)因其易用性(即插即用)和日益增长的司机采用率而被认为是一种可行的存储选择。另一方面，电动汽车的动态特性加剧了互动式分销系统的不确定性。本文研究了在存在不确定性的情况下，以功率损耗最小为目标的发电机组与电动汽车之间的能量交易问题。我们提出了一种新的基于贝叶斯联盟博弈(BCG)的算法，通过允许MG和EV智能地组成联盟来降低整体功率损失。与传统的基于联盟博弈论的方法和基于Q学习的方法进行了比较。我们的结果表明，与其他比较的技术相比，我们的技术有了显著的改进。
Peer-to-peer energy trading within microgrid (MG) communities emerges as a key enabler of the future transactive distribution system and the transactive electricity market. Energy trading within MGs refers to the idea that the surplus energy of one MG can be used to satisfy the demand of another MG or a group of MGs that form an MG community. These communities can be dynamically established through time, based on the variations of demand and supply of the interconnected MGs. In many modern MGs, Electric Vehicles (EVs) have been considered as a viable storage option due to their ease of use (plug-and-play) and their growing adoption rates by drivers. On the other hand, the dynamic nature of EVs escalates the uncertainty in the transactive distribution system. In this paper, we study the problem of energy trading among MGs and EVs with the aim of power loss minimization where there is uncertainty. We propose a novel Bayesian Coalition Game (BCG) based algorithm, which allows the MGs and EVs to reduce the overall power loss by allowing them to form coalitions intelligently. The proposed scheme is compared with a conventional coalitional game theory-based approach and a Q-learning based approach. Our results show significant improvement over other compared techniques.