An Inertia Reserve Capacity Planning Method for Power Systems Considering Risk Preference

The traditional reserve planning method implicitly includes inertia in the frequency response reserve without realizing separate and accurate planning for inertia reserve, and cannot consider the risk preference of the decision maker, which leads to the homogenization of small probability extreme events. This paper refines the reserve classification system, adds inertia reserve for the first time, and proposes an inertia reserve capacity planning method considering the risk preference of decision makers. Based on the Sequential Monte Carlo method, component state models for conventional units, wind turbines, and photovoltaic units are established, and system load shedding sets are obtained through probabilistic production simulation. Based on the inertia response characteristics, the system frequency response model with multiple types of source-storage-load regulation resources is established to track the system frequency trajectory after disturbance. The minimum inertia demand is determined based on Rate of Change of Frequency (RoCoF) constraints, and then an inertia mismatch penalty model is constructed to measure the loss caused by RoCoF exceeding limits. The total cost-benefit model of inertia reserve considering risk preferences is then established, and the feasibility of the planning scheme is verified. Based on the improved IEEE RTS79 case studies, it is demonstrated that the proposed inertia reserve capacity planning method can flexibly formulate the optimal planning scheme under different risk ranges according to the decision maker’s risk preferences and the grid’s risk tolerance capability, avoiding the extreme events to be submerged in the massive and frequent occurrence of ordinary events, and effectively improving the risk response capability of the power system to extreme events, thus providing a more targeted decision basis for system planning, scheduling, and operation control.