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Intelligence based coordination of large scale grid-connected photovoltaic systems

机译:基于智能的大规模并网光伏系统的协调

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This paper explores the possibility of optimizing two control strategies currently available for photovoltaic (PV) plants, namely additional reactive power and active power reduction. As the penetration of PV plants is expected to increase, controlling such plants during faults becomes increasingly important. The stability of the power system during a fault and immediately after is affected by the system capability to control the reactive and active power flows. Motivated by the fact that curtailing active and injecting reactive power during faults impacts on the system behavior, the two available controllers are tuned and optimized in such a way that the system stability during the disturbance is secured with the help of Particle Swarm Optimization (PSO) algorithm. The optimization process uses the locally measured voltage and frequency at the Point of Common Coupling (PCC) of the PV. The study takes into account various circumstances, such as levels of PV penetration and faults.
机译:本文探讨了优化当前可用于光伏(PV)电厂的两种控制策略的可能性,即额外的无功功率和有功功率降低。随着光伏电站的普及率有望提高,在故障期间控制此类电站变得越来越重要。故障期间及之后的电力系统稳定性受系统控制无功和有功潮流的系统能力的影响。由于在故障期间减少有功功率和注入无功功率会影响系统行为,因此对这两个可用的控制器进行了调整和优化,从而借助粒子群优化(PSO)确保了扰动期间的系统稳定性。算法。优化过程使用在PV的公共耦合点(PCC)上本地测量的电压和频率。该研究考虑了各种情况,例如PV渗透水平和断层。

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