digilib@itb.ac.id +62 812 2508 8800

Concern for the climate change demands for a faster adoption of Variable Renewable Energy Sources (VRES). VRES (solar and wind energy) are targeted to supply 53% of the Indonesia’s 2060 total power demand, three times of that of 2020. But deploying VRES brings about reliability issue due to its intermittency, which consequently requires additional costs for the deployment of Energy Storage Systems (ESS). Since a fully reliable VRES project is expensive, it is attractive to consider decreasing portion of reliability to reduce costs for the project to be economically viable. This study investigates the deployment of multiple combinations of solar PV ground, solar PV rooftop, wind turbine, Battery ESS, Pumped Hydro ESS, Hydrogen ESS, and Ammonia ESS in 16 Virtual Power Plants (VPPs) to meet Sukabumi Municipality demand, under three scenarios: full demand (33 MW), peak demand (4 MW), and baseload demand (29 MW). Multi-objective optimization based on Strength Pareto Evolutionary Algorithm 2 (SPEA2) is conducted with objectives of minimizing both Levelized Cost of Energy (LCOE) for costs and Loss of Power Supply Probability (LPSP) for reliability. The optimization program based on SPEA2 has successfully generate Pareto Front results for 16 VPPs and three case studies, along with a support program. It has been found that every VPP with Pumped Hydro ESS in single, double, triple and quadruple ESS, ranks co-first as the best VPP. Finally, four major factors which affect techno-economic performance of VPPs have been identified: LCOEgen of VRES, VRES maximum capacity due to location specificity, matching of VRES generation profile and demand profile, and roundtrip efficiency of ESS