Renewable Electric Energy System Planning Considering Seasonal Electricity Imbalance Risk

The growing renewable integration significantly enhances the seasonal electricity imbalance of the electric energy system. However, traditional power system planning methods usually take into account the hourly power balance within typical days but seldom consider the seasonal imbalance risk in the long-term timescale. Therefore, this paper proposes a generation-transmission-storage co-planning model considering the seasonal imbalance risk brought by the long-term uncertainty of renewable generation in the power system. The Conditional Value at Risk (CVaR) method is introduced to quantify the seasonal imbalance risk. The power system energy balance constraints are decoupled into short-term (i.e., hourly) and long-term (i.e., monthly) energy balance so that the operation of the power system can be considered within different timescales and the seasonal imbalance risk could be calculated. The validity of the proposed model is first investigated via a modified Garver's 6-bus system case study. Furthermore, the research on the HRP-38 system (HRP represents high renewable penetration) illustrates that our proposed model could effectively control the energy imbalance risk from multiple timescales. Finally, the proposed method is applied to the whole China power system at the province level, proving that the proposed planning method could effectively enhance the reliability of China's power system, decreasing both the average annual short-term and long-term energy imbalance by 30%.