Priority Based Critical Load Selection Algorithm for Grid Integrated PV Powered EV Charging System with Optimal DC Link Control

M. Aijaz, Ikhlaq Hussain, S. A. Lone
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Abstract

This article presents a single phase double stage photovoltaic (PV) array powered grid connected residential premise integrated with electric vehicle (EV) charging functionality. Taking criticality of the loads into consideration, a unique multi-modal control is developed which ensures incessant power supply to the loads via EVs in case of common occurrences of power interruption thereby enhancing the power security of the system. Favourable regulation of DC link voltage is achieved via proportional integral (PI) controller (DCVPI). Comparison between genetic algorithm (GA) and modified particle swarm optimisation (PSO) based tuning proves modified PSO tuned DCVPI achieves faster convergence and better fitness function evaluation. The system is subjected to various dynamic conditions during which modified PSO tuned DCVPI stabilises to the reference voltage faster and results in 1.38% reduction in overshoots opposed to the manual tuning. The proposed system is designed to work both in grid connected mode as well as islanded mode of operation. Moreover, a resynchronisation control is developed to achieve a seamless transition from islanded mode to grid connected mode post the mitigation of power failure. The proposed system achieves unity power factor and complies with the IEEE -519 power quality standard
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基于优先级的直流链路最优控制并网光伏充电系统临界负荷选择算法
本文介绍了一种单相双级光伏(PV)阵列并网住宅住宅,并集成了电动汽车(EV)充电功能。考虑到负荷的临界性,提出了一种独特的多模态控制方法,在常见的停电情况下,保证电动汽车不间断地向负荷供电,从而提高了系统的电力安全性。通过比例积分(PI)控制器(DCVPI)实现了直流链路电压的良好调节。通过遗传算法(GA)和改进粒子群算法(PSO)的调优比较,证明改进粒子群算法(PSO)调优后的DCVPI收敛速度更快,适应度函数评价效果更好。系统经受各种动态条件,在此期间,改进的PSO调谐DCVPI稳定到参考电压更快,与手动调谐相比,超调量减少1.38%。该系统既能在并网模式下工作,也能在孤岛模式下工作。此外,开发了一种再同步控制,以实现从孤岛模式到电网连接模式的无缝过渡,缓解了电力故障。该系统实现了统一的功率因数,符合IEEE -519电能质量标准
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