A. Assessment of the financing trends of 50 utility-scale non-fossil energy projects in ASEAN
Financing trends were assessed through a project-level review of publicly announced utility-scale non-fossil projects across ASEAN. The project list is non-exhaustive and was compiled to identify financing patterns and illustrate how these projects were financed across the region. The assessment compiled information on project technology, installed capacity, investment value, financing structure, project sponsors, off-takers, power purchase agreement arrangements, and the participation of multilateral development banks, development finance institutions, export credit agencies, and concessional finance. Information was obtained from publicly available project announcements, company disclosures, regulatory filings, MDB and DFI databases, and government publications.
B. Assessment of solar project size, PPA rate, and interest rate on equity IRR
A Response Surface Methodology (RSM) was employed to quantify the combined effects of project scale, electricity tariff, and financing cost on the financial viability of solar PV projects. RSM was selected because it enables simultaneous evaluation of multiple interacting variables while requiring substantially fewer simulations than a full factorial experimental design. The analysis was performed using Design-Expert 360 (by State-Ease Inc., USA), applying a three-factor, three-level Box-Behnken Design to develop a second-order response surface relating project characteristics to Equity IRR.
The three independent variables were selected to represent the principal technical and financial drivers of solar project bankability:
Project capacity: 0.5–20 MWdc
Power Purchase Agreement (PPA) price: USD 0.060–0.090/kWh
Financing interest rate: 5–9%
The PPA range was established based on representative utility-scale solar tariffs observed across ASEAN markets, while the financing interest rate range reflects commercially available project finance conditions for renewable energy investments.
For each experimental run, a discounted cash flow model was used to calculate the Equity IRR assuming a representative ASEAN solar project with fixed technical parameters, including a Global Horizontal Irradiance of 5 kWh/m²/day, performance ratio of 0.8, 25-year project life, 70:30 debt-to-equity ratio, 15-year loan tenor, and 0.5% annual module degradation. Installed capital cost and annual operation and maintenance (O&M) cost were estimated using an economies-of-scale relationship,
K = Kref(S/Sref)-b
where K is the unit cost at project capacity S, Kref is the reference cost at capacity Sref, and b is the economies-of-scale exponent (b = 0.09). The reference cost at 10 MW was estimated from the representative utility-scale solar cost ranges for Other Asia reported by IRENA (2025), while the scaling relationship was subsequently used to estimate unit costs for other project capacities.
The grid projects’ equity IRR was calculated using these assumptions, a nominal cost of debt of 7% and a nominal cost of equity of 10–12%, with gearing (debt/RAB) set at 60%-70% over a 15-year debt tenor. On the operating cost side, OPEX is assumed at 2% of year 1 capex. The regulatory control period begins in 2026 and is modelled over 10 years. Annual energy transmitted is assumed in line with the transmission capacity.
C. Energy Storage Market Readiness Index (ESMRI) Calculation
To compare the maturity of enabling market conditions for energy storage deployment, this report develops the Energy Storage Market Readiness Index (ESMRI). The index evaluates four dimensions that are consistently identified in the literature as prerequisites for commercial energy storage deployment: 1) regulatory recognition, 2) revenue mechanisms, 3) procurement pathways and 4) investment certainty. Together, these dimensions capture the institutional and market conditions that enable energy storage to participate in electricity markets and attract private investment.
The assessment comprises 13 indicators derived from a review of national legislation, electricity market rules, grid codes, procurement frameworks, and government energy strategies across the five selected ASEAN countries. Each indicator is assigned one of three scores: 2 if the enabling condition is established, 1 if it is emerging or partially implemented, and 0 if it is absent.
To prevent dimensions containing more indicators from disproportionately influencing the overall assessment, each dimension is first normalised by its maximum attainable score before applying category weights. The weights reflect the relative importance of each dimension in supporting commercially viable energy storage deployment, with revenue mechanisms (35%) receiving the highest weight, followed by regulatory recognition (25%), procurement pathways (20%), and investment certainty (20%). The overall ESMRI score is then normalised to a 0–100 scale, where higher scores indicate more mature enabling market conditions. The ESMRI is calculated as:
ESMRI = ∑j=14 wj (∑i=1nj Sij / 2nj) * 100%
where Sij is the score assigned to indicator i within dimension j, nj is the number of indicators in each dimension, and wj is the corresponding category weight. The index is intended as a comparative analytical tool for assessing market readiness rather than an absolute measure of energy storage market maturity.