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A day-ahead Optimal Scheduling Operation of Battery Energy Storage with Constraints in Hybrid Power System

机译:混合动力系统约束的电池储能存储的一天前方最佳调度操作

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In present situation, the renewable energy sources (RES) are turned into significant part of power system. Such power system is generally acknowledged as the hybrid power system (HPS), which is accountable for meeting its connected load. Battery energy storage (BES) is essentially needed along with RES to deal their intermittency and to commit them as dispatchable sources at some extent. An effective optimal scheduling operation of BES in such systems is a tedious assignment, due to unpredictable nature of RES, load, and electricity tariff. In this paper, a HPS integrated with utility grid (UG) containing wind farm (WF), solar photovoltaic (SPV), BES, and connected load is taken for problem simulation. The main aim of this paper is a day-ahead optimal scheduling of BES with its operational limitations in a HPS. To improve the BES performance, BES scheduling operation is mainly constrained by quick switching cost, energy conversions loss cost along with its state of health condition and charging/ discharging rate (fast or slow) restrictions. Optimization is executed through artificial bee colony algorithm (ABC) and the results are compared or validated using the classical technique, i.e., interior point method (IPM) of MATLAB? fmincon function.
机译:在现状,可再生能源(RES)变成了电力系统的重要组成部分。这种电力系统通常被确认为混合动力系统(HPS),这对于满足其连接的负载是负责任的。电池储能(BES)基本上是必需的,以及res处理他们的间歇性,并在一定程度上将它们致力于调度源。由于RES,负载和电费的不可预测性质,这种系统中BES在这种系统中的有效优化调度操作是繁琐的作业。本文采用了包含风电场(WF),太阳能光伏(SPV),BES和连接载荷的公用电网(UG)集成的HPS用于问题模拟。本文的主要目的是前方最佳调度与HPS中的运营限制。为了提高BES性能,BES调度操作主要由快速切换成本,能量转化损失成本以及其健康状况和充电/放电率(快速或缓慢)限制的限制。通过人造蜂菌落算法(ABC)执行优化,并使用Matlab的经典技术(即内点方法(IPM)进行比较或验证结果? Fmincon功能。

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