Research on Robust State Estimation Method for Electrical Interconnection of Integrated Energy System Based on EVO

Due to the inconsistent sampling time units of the measuring devices, the measurement data of gas electricity interconnection in integrated energy systems (GEIES) has significant errors. To improve the accuracy of GEIES state estimation applying the discrete energy valley optimization (EVO) algorithm to the state estimation of integrated energy systems, a new GEIES state estimation method is proposed. Establish a Bayesian measurement model to obtain measurement data for gas and power grid state estimation, increase the completeness of the measurement dataset, and set Gaussian noise variance to ensure that GEIES state estimation results are not affected by noise factors. Substitute the measurement results into GEIES state estimation, establish separate power grid state estimation models and gas grid state estimation models, and combine the two to establish a comprehensive energy system electrical interconnection robust state estimation model. Use the discrete EVO algorithm to solve the model and obtain the optimal state estimation solution. The calculation results show that regardless of whether there is no noise environment or a noisy environment, the state estimation accuracy of the proposed method is high, and it can play a role in identifying bad data, indicating that its state estimation effect is good.