Competitive peak regulation optimization and tracing-based cost allocation model for high-proportion renewable energy power systems

With the continuous expansion of intermittent renewable energy integration into the grid, power systems' peak regulation demand and peak regulation cost steadily increase. Simultaneously, the phenomenon of renewable power curtailment is becoming frequent, driven by increasingly complex factors, such as transmission network constraints and insufficient peak regulation support. The high costs of peak regulation and frequent renewable power curtailment present a serious challenge to the economic operation of power systems. To fully incentivize peak regulation resources (PRRs) and ensure appropriate allocation of responsibility and costs for peak regulation and renewable power curtailment. This paper proposes a competitive peak regulation optimization model for power systems that incorporates PRRs' preferences and the pricing effects of market share. In this model, the independent system operator (ISO) first identifies the peak regulation demand in power systems (including peak regulation periods and required power) and then organizes an iterative bidding process for PRRs, thereby enhancing PRRs’ incentives while simulating a real competitive process. Additionally, an allocation method for peak regulation cost is proposed based on incremental power. For renewable power curtailment cost, two factors, i.e., insufficient PRRs and transmission network constraints, are included in the cost allocation, enabling the attribution and traceability of renewable power curtailment issues. Finally, case studies are conducted based on an improved IEEE 30-bus test system and an improved IEEE 118-bus test system to validate the effectiveness of the proposed peak regulation optimization and cost allocation model.