Optimal Solar PV Capacity Planning in Bangka Power System Using Grey Wolf Optimizer
DOI:
https://doi.org/10.33019/Keywords:
Emission Mitigation, Grey Wolf Optimizer, Power System Optimization, PV Capacity Planning, Solar PhotovoltaicAbstract
This study develops a simplified optimization-based framework to determine the optimal Solar Photovoltaic (PV) capacity for the Bangka power system by combining an annual cost-minimization model with the Grey Wolf Optimizer (GWO). Annual electricity demand is supplied by PV and system-level fossil-based generation, while total annual cost comprises annualized PV investment, PV operation and maintenance (O&M), and fossil generation costs. Three scenarios are evaluated: a baseline without PV, a fixed-PV capacity of 50 MW, and a GWO-optimized PV capacity bounded between 0 and 150 MW. The calculations and GWO procedure are implemented in Python 3.10 using 30 wolves, 100 iterations, and 20 independent runs. All runs converge to the upper feasible capacity of 150 MW. At this capacity, PV generation reaches 236.52 GWh/year, representing 15.6% of annual electricity demand, compared with 78.84 GWh/year or 5.2% in the fixed-PV scenario. Fossil generation cost decreases from 181.73 to 153.35 million USD/year. After including 13.75 million USD/year in annualized PV investment and 2.25 million USD/year in PV O&M costs, the total annual system cost reaches 169.35 million USD/year, yielding net savings of approximately 12.38 million USD/year relative to the baseline. Annual CO2 emissions decrease from 1211.54 to 1022.32 ktCO2/year, corresponding to a reduction of approximately 189.22 ktCO2/year. Within the adopted annual model assumptions, the 150 MW configuration provides the lowest cost and emissions among the evaluated alternatives and represents a boundary optimum.
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