Metropolitan water purification facilities towards variability mitigation of the renewable resources: Optimal bid method for small hydropower generators

As carbon neutrality in the power system arises as one of the important issues, numerous nations have been increasing penetration of the renewable resources. However, greater penetration of the renewable resources in the power systems has caused reliability issues due to the innate unpredictable output characteristics. For minimization of unpredictability and its consequential effects on the system reliability, the nations such as the Republic of Korea, Great Britain and Australia have been introduced market-based variability mitigating measures. The incentive policy driven market-based measures were designed to draw voluntary participation from the asset owners capable of providing controllability over the resources aggregated to be a single portfolio. Small hydropower generators in metropolitan water purification facilities can be actively utilized for such mitigation because of their relatively stable output characteristics. However, entities responsible for metropolitan water purification facilities with small hydropower generators have been reluctant to participate in the market with the mitigations incentive since there are no structured methods to acquire dispatch reliability of the water resources considering participation in the energy market. Thus, this paper presents a scheduling algorithm for the aggregated portfolio of renewable resources, utilizing small hydropower generators as one of the tools for variability mitigation. In the results, the portfolio-wide forecast error was reduced to below 2% in the presence of the scheduling algorithm and small hydropower generators as mitigation resources, while the water intake schedule at water purification facilities remained evenly distributed. Small hydropower generators played a key role in mitigating variability in the algorithm, and the revenue generated from the participation of these small hydropower generators contributed to approximately one third of the gross revenue from the portfolio. The algorithm was demonstrated to provide renewable resource owners with an additional revenue stream, beyond what is typically provided by government subsidies.