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Coordinated Control of PEV and PV-based Storage System under Generation and Load Uncertainties

机译:发电和负荷不确定性下基于PEV和PV的存储系统的协调控制

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Energy storage is an attractive choice for deployment in residential and commercial applications aiming to ensure proper utilization of solar photovoltaic (PV) power generation. Energy storage can be controlled and coordinated with PV generation to satisfy electricity demand and minimize electricity purchases from the grid. However, PV generation and load profile depend on the real-time weather condition and the usage by the owners. Thus, PV generation and demand uncertainties need to be considered when designing a control scheme for the PV-based storage system. Another resource at the residential level is theplug-in electric vehicle (PEV) which has a bi-directional capability and can reduce the electric power draw from the grid during peak hours. Therefore, the charging and discharging routines of the PEV can be controlled to achieve optimal economic benefits. In this paper, a method of coordinated optimal control between PV-based storage and PEV storage is proposed considering the stochastic nature of solar PV generation and load demand. The stochastic dual dynamic programming (SDDP) algorithm is employed to optimize the charge/discharge profiles of PV-based energy storage and PEV storage to minimize the overall cost of the daily household electricity purchase from the grid. Simulation analysis is performed in order to show the advantage of coordinated control compared to the other control strategies.
机译:储能是为确保适当利用太阳能光伏(PV)发电而在住宅和商业应用中部署的诱人选择。可以控制能量存储并与PV发电协调,以满足电力需求并最大程度地减少从电网购买的电力。但是,光伏发电和负荷状况取决于实时天气状况和业主的使用情况。因此,在为基于PV的存储系统设计控制方案时,需要考虑PV的产生和需求的不确定性。住宅级别的另一资源是插电式电动汽车(PEV),它具有双向功能,可以减少高峰时段从电网获取的电力。因此,可以控制PEV的充电和放电程序,以实现最佳的经济效益。考虑到太阳能光伏发电的随机性和负荷需求,本文提出了一种基于光伏的储能与PEV储能之间的协调最优控制方法。随机双动态规划(SDDP)算法用于优化基于PV的储能和PEV储能的充电/放电曲线,以最大程度地减少每天从电网购电的总成本。为了显示协调控制相对于其他控制策略的优势,进行了仿真分析。

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