Reliability Assessment Of Power Systems With High Renewable Energy Penetration Using Shadow Price And Impact Increment Methods

With the ever-increasing penetration of renewable resources, more complexities and uncertainties are introduced in power system reliability assessment. This entails an enormous number of contingency states to represent the characteristics of renewable energy. As a result, the unbearable computation burden is the main challenge toward the efficiency of the state enumeration (SE) method. To address that, this paper proposes an improved reliability evaluation approach that can not only increase the accuracy but also accelerate the analysis. In detail, the impact increment method is first employed to decrease the proportion of higher-order contingency states, leading to accuracy improvement. Then, the shadow price is used to solve the optimal power flow (OPF) problem in a faster manner. This shadow price (SP) method allows us to obtain the optimal load curtailment directly from linear functions rather than the time-consuming OPF algorithms. In addition, one hundred percent criterion is used to match shadow-price-based linear functions with system states. Case studies are performed on the RTS-79 system and IEEE 118-bus system, in which test scenarios include loads, photovoltaics (PV), and wind turbines (WT). Results indicate that the proposed method can significantly ease the computation burden and outperform traditional reliability assessment methods in terms of both computing time and accuracy.