Optimization of a Standalone Wind–PV–Diesel Hybrid Microgrid using Finite Control Set Model Predictive Control: A Case Study of Minima-Okpukpo Island, Opobo, Rivers State
Keywords:
Energy diesel, Finite control set model predictive control (FCS-MPC), Microgrid, Solar, WindAbstract
The main goal of the study is to optimize a standalone Wind-PV-Diesel hybrid microgrid based on a Finite Control Set Model Predictive Control (FCS-MPC) approach to solve the issues of power supply shortage, heavy dependence on diesel, and poor quality of power supply for Minima-Okpukpo Island located in Opobo, Rivers State, Nigeria. This approach aims at building discrete-time models for the renewable power generation (Wind, PV), the diesel generator (DG), and the battery energy storage system (BESS) to forecast system behavior and to find an optimal set of converter switching states by minimizing a local cost function. This study demonstrates that, for a 24-h simulation considering varying operating condition scenarios, peak power generated from PV and wind, respectively, is up to 41.2 kW (when the irradiance reaches 650 W/m2) and up to 4.38 kW (when the wind speed reaches 6 m/s). The proposed method effectively reduced the DG active power output from 50 kW down to zero at peak daylight time, successfully reducing diesel consumption from 14.5 L/h to 0 L/h. As compared with other existing schemes like the droop and the PI control frameworks, the FCS-MPC strategy shows a quite smooth cost trajectory with an average normalized value of 0.1. Based on analysis of the transient responses of power quality indexes, a rapid voltage recovery time of 3 ms, a tight frequency deviation limit of within 0.04 Hz, and limited inverter current less than 185 A are achieved. The presented predictive microgrid scheme achieved great success in the enhancement of renewable power integration, resulting in a peak renewable power penetration of 51.5% and of 97.1% of the overall system efficiency for the remote island power electrification.
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