Fully Distributed DC Optimal Power Flow Based on Distributed Economic Dispatch and Distributed State Estimation

TL;DR

This paper presents a fully distributed DC optimal power flow method that integrates distributed economic dispatch and state estimation, enabling scalable and constraint-compliant operation of future power systems with distributed generators.

Contribution

It introduces a novel fully distributed DC OPF approach that eliminates centralized control, combining economic dispatch, state estimation, load prediction, and constraint correction.

Findings

Achieves optimal power dispatch with lowest cost

Prevents system overflow through load prediction and correction

Operates without any centralized control facility

Abstract

Optimal power flow (OPF) is an important technique for power systems to achieve optimal operation while satisfying multiple constraints. The traditional OPF are mostly centralized methods which are executed in the centralized control center. This paper introduces a totally Distributed DC Optimal Power Flow (DDCOPF) method for future power systems which have more and more distributed generators. The proposed method is based on the Distributed Economic Dispatch (DED) method and the Distributed State Estimation (DSE) method. In this proposed scheme, the DED method is used to achieve the optimal power dispatch with the lowest cost, and the DSE method provides power flow information of the power system to the proposed DDCOPF algorithm. In the proposed method, the Auto-Regressive (AR) model is used to predict the load variation so that the proposed algorithm can prevent overflow. In addition, a method called constraint algorithm is developed to correct the results of DED with the proposed correction algorithm and penalty term so that the constraints for the power system will not be violated. Different from existing research, the proposed method is completely distributed without need for any centralized facility.