From Static Risk Registers to Phase-Adaptive Risk Analytics: A Market-to-Credit Monitoring Framework for Renewable Energy Projects in Bulgaria

Static risk registers compiled at financial close do not follow the market conditions that determine the cash flows of merchant-exposed renewable projects. This study asks how far public day-ahead market data can support a phase-adaptive decision-support and monitoring framework for market-to-credit risk in solar-dominated renewable projects in Bulgaria. It uses 1096 daily observations (13 July 2023–12 July 2026) of day-ahead prices, renewable generation, and interpolated installed capacity. Across thirteen price specifications, the capacity coefficient is a conditional association that cannot be separated from time trends and has the sign opposite to the merit-order hypothesis, and same-day generation shows no stable negative association with the daily average price. In 730 rolling-origin forecasts, the capacity-and-trend model improves on a naive forecast by 5.9%, but not on an AR(1) benchmark, whereas calendar terms reduce the root-mean-squared error by about 25%. Days with a negative minimum price rise from 15 to 44 per sample year. Candidate monitoring indicators do not outperform a seasonal benchmark in the test sample and are not validated early-warning signals. A rolling debt service coverage ratio (DSCR) analysis of a stylized 1 MW PV asset rests on assumed capture rates, generation profiles, and financing terms, not on observed project data; under the base structure, no 12-month window breaches a 1.20× reference value at a capture rate of 0.70, and breaches appear only at lower capture rates or under tighter structures. These scenario results do not generalize, and the framework requires project-level validation.