Heuristic Multi-Agent Control for Energy Management of Microgrids with Distributed Energy Sources

Zunaib Ali, G. Putrus, M. Marzband, M. B. Tookanlou, K. Saleem, P. K. Ray, B. Subudhi
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引用次数: 1

Abstract

The increased integration of distributed Renewable Energy Sources (RESs) and adoption of Electric Vehicles (EVs) require appropriate control and management of energy sources and EV charging. This becomes critical at the distribution system level, especially at a microgrid (MG) level. This control is required not only to mitigate the negative impacts of intermittent generation from RESs but also to make better use of available energy, reduce carbon footprint, maximize the overall profit of microgrid and increase energy autonomy by effective utilization of battery storage. This paper proposes a heuristic multi-agent based decentralized energy management approach for grid-connected MG. The MG comprises of active (controlled) and passive (uncontrolled) electrical loads, a photovoltaic (PV) system, battery energy storage system (BESS) and a charging post for electric vehicles. The proposed approach is aimed at optimizing the use of local energy generation from photovoltaic and smart energy utilization to serve electrical loads and EV as well as maximizing MG profit. The aim of the energy management is to supply local consumption at minimum cost and less dependency on the main grid supply. Utilizing energy available from RESs (PV and BESS), customers satisfaction (fulfilling local demand), considering uncertainty of renewable generation and load consumption and also taking into account technical constraint are the main strengths of the presented framework. Performance of the proposed algorithm is investigated under different operating conditions and its efficacy is verified.
分布式微电网能量管理的启发式多智能体控制
分布式可再生能源(RESs)的日益整合和电动汽车(EV)的采用要求对能源和电动汽车充电进行适当的控制和管理。这在配电系统层面变得至关重要,尤其是在微电网层面。这种控制不仅是为了减轻RESs间歇性发电的负面影响,也是为了更好地利用可用能源,减少碳足迹,最大化微电网的整体利润,并通过有效利用电池储能来提高能源自主权。提出了一种基于启发式多智能体的并网电网分散能量管理方法。MG由主动(受控)和被动(不受控)电力负载、光伏(PV)系统、电池储能系统(BESS)和电动汽车充电桩组成。所提出的方法旨在优化光伏发电和智能能源利用的本地使用,以服务于电力负荷和电动汽车,并最大化MG利润。能源管理的目的是以最低的成本提供本地消费,减少对主电网供应的依赖。利用可再生能源系统(光伏和BESS)提供的能源,客户满意度(满足当地需求),考虑可再生能源发电和负荷消耗的不确定性,并考虑到技术约束是所提出框架的主要优势。研究了算法在不同工况下的性能,验证了算法的有效性。
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