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A Sensitivity Matrix Approach Using Two-Stage Optimization for Voltage Regulation of LV Networks with High PV Penetration

Energies(2021)SCI 4区

Univ Peradeniya

Cited 2|Views21
Abstract
The occurrence of voltage violations is a major deterrent for absorbing more rooftop solar power into smart Low-Voltage Distribution Grids (LVDGs). Recent studies have focused on decentralized control methods to solve this problem due to the high computational time in performing load flows in centralized control techniques. To address this issue, a novel sensitivity matrix was developed to estimate the voltages of the network by replacing load flow simulations. In this paper, a Centralized Active, Reactive Power Management System (CARPMS) is proposed to optimally utilize the reactive power capability of smart Photovoltaic (PV) inverters with minimal active power curtailment to mitigate the voltage violation problem. The developed sensitivity matrix is able to reduce the time consumed by 55.1% compared to load flow simulations, enabling near-real-time control optimization. Given the large solution space of power systems, a novel two-stage optimization is proposed, where the solution space is narrowed down by a Feasible Region Search (FRS) step, followed by Particle Swarm Optimization (PSO). The failure of standalone PSO to converge to a feasible solution for 34% of the scenarios evaluated further validates the necessity of the two-stage optimization using FRS. The performance of the proposed methodology was analysed in comparison to the load flow method to demonstrate the accuracy and the capability of the optimization algorithm to mitigate voltage violations in near-real time. The deviations of the mean voltages of the proposed methodology from the load flow method were: 6.5×10−3 p.u for reactive power control using Q-injection, 1.02×10−2 p.u for reactive power control using Q-absorption, and 0 p.u for active power curtailment case.
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smart grid,renewable energy integration,rooftop solar PV,PV inverter control,voltage violation
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要点】:提出了一种基于灵敏度矩阵的两阶段优化方法,用于调节高光伏渗透率的低压网络电压,有效减少电压越限问题,并实现近实时控制优化。

方法】:通过构建灵敏度矩阵代替传统负载流模拟,结合可行区域搜索(FRS)和粒子群优化(PSO)的两阶段优化方法,实现光伏逆变器无功功率的最优管理。

实验】:使用灵敏度矩阵方法与负载流方法对比,在多个场景下验证了算法的准确性和电压调节能力,实验结果表明该方法在无功功率控制下的电压偏差分别为6.5×10^-3 p.u和1.02×10^-2 p.u,而在有功功率削减情况下电压偏差为0 p.u。数据集名称未明确提及。