A computational model of a "solar thermal utilization system" was constructed, and a case study was conducted using simulation to evaluate the system from both the energy concept and the exergy concept. As a result, the following findings were obtained. It was confirmed that the exergy concept can quantitatively evaluate the difference in resource value (quality) due to the temperature of hot water. Even when the values and ratios of exergy supply and utilization were the same, there were cases where the exergy input to the power plant differed greatly. The importance of operating with the minimum necessary flow rate (flow velocity) when utilizing natural exergy was suggested.

With increasing integration of renewable energy, especially photovoltaics (PV), maintaining supply-demand balance is a growing challenge. This study proposes a three-stage method to enable PV participation in the balancing market through day-ahead scheduling while managing imbalance risks. First, a headroom-setting algorithm is developed to absorb PV prediction errors. Second, a rare-event risk model identifies over/underestimation, supporting scenario-based bidding decisions. Third, a priority-based scheduling method is proposed for balancing market bidding.

The approach is evaluated by examining feasible annual bids, shortage count, and expected revenue. In Scenario 1, application of the Linear-SVC model resulted in 524 feasible bids, with annual shortfalls reduced to 42—close to the target of 36—and improved revenue. This framework demonstrates the potential for PV systems to provide balancing reserve power while minimizing prediction risks and enhancing market participation outcomes.