CVaR-based Reserve Optimization for Isolated Multi-energy Complementary Generation Systems in Mixed Time Scale

With the rapid growth of photovoltaic integration, the volatility and uncertainty of intermittent photovoltaic injection will dramatically reduce system operation reliability from the generation side. The system operator may face certain financial risks brought by unexpected power failure under low operation reliability. Therefore, maintaining sufficient power reserve to meet system operation reliability and reduce risk, especially in an isolated system, is essential. However, the traditional reserve preparation strategy fails to consider the uncertainties of the power generation under the high penetration levels of emerging renewable energy resources. A novel reserve preparation strategy for an isolated system is developed in this paper using a two-stage model. In the first stage, the optimal hourly scheduling of an isolated system is determined. In the second stage, a minute level conditional value-at-risk (CVaR) based model is established where the uncertainty of the reserve requirement is introduced with the chance constraint. The proposed discretized step transformation (DST) and subtraction type convolution (STC) methods are utilized to convert the model into mixed-integer linear programming, and finally solved by applying the CPLEX solver. The IEEE 39-bus system is used as the test case to validate the feasibility and effectiveness of the proposed two-stage model.