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Optimal Day-ahead Energy Scheduling of Battery in Distribution Systems Considering Uncertainty

机译:考虑不确定性的分配系统中电池的最佳节能调度

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One of the features in the modern smart grid is accommodation of different distributed generation resources and battery energy storage system (BESS). Because the renewable power generation is intermittent and uncertain, the BESS can help regulation of power generation, voltage and even system frequency. This paper explores a short term (24h) energy scheduling of batteries in a power system considering uncertain photovoltaic (PV) power generations and loads. The cost of losses is minimized while both equality and inequality constraints are satisfied. The equality constraints consist of the power flow equations and the energy balance equations for batteries. The inequality constraints comprise the limits of power and energy of batteries. The states (charging and discharging) of batteries are set according to the tariffs of electricity. Due to the uncertainty of PV powers and loads, the problem is solved by two loops: the outer loop is implemented by point-estimation method while the inner loop deals with the 24 h optimal power flow considering deterministic PV generations and loads using the interior-point method. A 33-bus distribution system of 3.454 MW (peak load) was used to show the simulation results. One PV farm (1MW) and six BESS at different buses were considered. The deterministic and stochastic results obtained by the proposed method were discussed and compared.
机译:现代智能电网中的一个功能是不同的分布式发电资源和电池储能系统(BESS)的住宿。因为可再生发电是间歇性的并且不确定,因此BESS可以帮助调节发电,电压甚至系统频率。本文探讨了考虑不确定的光伏(PV)电力代和负载的电力系统中电池中电池的短期(24h)能量调度。损失成本最小化,同时满足平等和不等式约束。平等约束包括电流方程和电池的能量平衡方程。不等式约束包括电池的功率和能量的限制。电池的状态(充电和放电)根据电力关税设置。由于PV功率和负载的不确定性,两个环路解决了问题:外环通过点估计方法实现,而内环考虑使用内部的确定性PV世代和负载的24 H最优功率流程。点方法。 33柱式分配系统3.454 MW(峰值负荷)显示仿真结果。考虑了一个PV Farm(1MW)和不同公共汽车的六个贝斯。通过该方法获得的确定性和随机结果进行了讨论并进行比较。

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