Optimal PV Sizing and Location Based on Volt – Var Control and UPFC Using Particle Swarm Optimization for Microgrid System
Keywords:
photovoltaic, VAR and UPFC, sizing and locationAbstract
This research article details the creation and execution of a photovoltaic (PV) control system augmented with Volt-VAR (VAR) and Universal Power Flow Control (UPFC) to boost power system efficiency. The research examines the IEEE 13 bus test system, assessing four principal control strategies for effective power demand management: PV control, PV-VAR control, PV-UPFC control, and their amalgamation with Particle Swarm Optimization (PSO) for load forecasting. The PSO method is utilized to enhance load forecasting precision, facilitating accurate synchronization of PV generation with 24-hour power demand variations. The research examines the mechanisms of photovoltaic regulation, with the objective of optimizing photovoltaic resource usage and ensuring smooth integration with the electrical grid. The PV-VAR control system is examined to improve reactive power management, voltage stability, and grid resilience. The integration of photovoltaic systems with unified power flow controllers is examined to attain accurate control over power flow dynamics in the distribution network. The Open Distribution System Simulator (OpenDSS) is employed to assess electricity flow and examine grid performance under diverse load scenarios. Simulation findings illustrate the efficacy of the proposed technology, indicating a direct linkage between the photovoltaic system and the power grid optimized by particle swarm optimization. The ideal dimensions and location of the PV system were determined to be 100 kV at Bus 680, underscoring the system's capacity to conform to grid demands. This study offers essential insights into the obstacles and opportunities associated with the integration of photovoltaic systems into contemporary electricity grids. The research enhances the creation of sustainable, efficient, and resilient distribution networks in the renewable energy sector through comprehensive simulations and analysis.
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