Scenario‐driven analysis of financial performance in a large‐scale biomass power plant using wood pellets in Java

Abstract Indonesia’s energy transition aims to decarbonize its electricity sector in alignment with Sustainable Development Goal (SDG) 7. Although the government promotes phasing out fossil‐fuel generation, renewable energy expansion remains limited, contributing only 12.06% to the national energy mix in 2023. The government’s de‐dieselization strategy identifies biomass as a technically viable substitute. This study assesses the technoeconomic feasibility of a 50.9 MW biomass power plant (BPP) using Calliandra wood pellets at three locations on Java island: Sukabumi, Purwodadi, and Saradan. Three scenarios are evaluated using RETScreen: a baseline tariff of USD 0.0929 kWh −1 , a carbon subsidy of USD 10 per tCO 2 , and a tariff‐escalation scenario with an initial rate of USD 0.111 kWh −1 and 1% annual growth. All sites face baseline viability constraints driven by high capital expenditure (CAPEX), operating expenditure (OPEX), and sensitivity to fuel‐price and tariff volatility. The carbon subsidy improves financial performance at each site. In Sukabumi, net present value (NPV) increased from USD −8.3 million to USD 14.8 million and the internal rate of return (IRR) rose from −3.7% to 4.6%. In Purwodadi, NPV increased from USD 1.6 million to USD 24.8 million and IRR from −1.2% to 7.9%. In Saradan, NPV increased from USD −5.9 million to USD 17.3 million and IRR from −10.3% to 5.4%. Tariff escalation yields stronger results, increasing NPV to USD 25.9 million in Sukabumi, USD 35.8 million in Purwodadi, and USD 28.4 million in Saradan. Equity payback periods fell to less than 2.5 years at all sites. The optimal development pathway is to prioritize BPP construction in Purwodadi, supported by carbon‐subsidy mechanisms during the early stages. Policy measures should align with investor risk profiles: risk‐tolerant investors benefit from immediate subsidy implementation, whereas risk‐averse investors may prefer tariff escalation. This study offers data‐driven guidance for strengthening BPP deployment through site‐specific feedstock localization.