Some Aspects of Investment Risks in Alternative Thermal Energy in Ukraine

The article examines investment threats in Ukraine’s alternative thermal energy sector over the period 2019 to 2025. The authors analyze financial, security, and infrastructure factors that determine project profitability during wartime. The destruction of centralized heat generation has created a capacity deficit. Investors require systematized knowledge about the nature of sectoral risks. Traditional assessment methods do not account for wartime realities. Biofuel prices fluctuate unpredictably. Tariff policy changes chaotically. Banks restrict long-term lending due to the lack of reliable threat measurement instruments. Municipalities delay payments by three to four months. Frontline territories accumulate maximum threats amid growing social demand for autonomous heat. The purpose of the study is to establish causal relationships between risk categories and investment economic efficiency. The research builds a taxonomy of threats. The authors determine the impact of each category on profitability. The paper formulates recommendations on protective mechanisms for the period up to 2030. The study classifies eight types of risks and establishes weighting coefficients. Feedstock, tariff, and security factors increase payback periods by 37 to 41 percent. Long-term contracts reduce price volatility by half. The optimal facility capacity is 3 to 7 MW to balance adaptability and unit costs. Integration of heat generation with network modernization delivers an 18 to 23 percent efficiency gain. Small facilities launch within 5 to 12 months versus 18 to 24 months for large systems. Modular commissioning adapts projects to demographic changes and demand fluctuations. Future research should develop stochastic risk assessment models with the application of machine learning. Mechanisms of public-private partnership in financing facilities in frontline territories require a separate study. International experience in insuring energy assets in conflict zones requires adaptation to Ukrainian specifics. Dynamic forecasting models must account for geopolitical development scenarios.