A Robust State Estimation Method Based on SOCP for Integrated Electricity-Heat System

With the application and development of combined heat and power (CHP) techniques, the coupling of electrical and heat energy is gradually increasing. State estimation (SE) is essential to achieve the comprehensive and accurate operating status in an integrated electricity-heat system (IEHS). This article proposes a robust SE method based on second-order conic programming (SOCP) for IEHS. Firstly, auxiliary state variables and measurements are introduced to obtain the exact linear measurement equations for IEHS. Then, a robust SE model based on weighted least absolute values (WLAV) for IEHS is proposed. To further improve the estimation performance, the constraint conditions satisfied by auxiliary state variables are relaxed into second-order cone constraints and added to the proposed WLAV model, leading a SOCP-based robust SE method. Simulations demonstrate that the proposed method ensures a global optimal solution and has good robustness and high estimation accuracy.