State Estimation and Distributed Optimization of Multi-Energy Coupled System Based on Improved Kalman Filter Algorithm

In light of this, this paper suggests a robust optimal scheduling strategy and state estimation algorithm for multi-energy coupling systems based on an improved Kalman filter algorithm. These strategies can both preserve the system's coordinated economic operation in the face of non-collusive network attacks and effectively increase the accuracy of state estimation during complex changes in the system's state. Numerical simulations are used to validate the viability and efficacy of the distributed resilient economic scheduling method and the enhanced state estimation technique.