Agent-Based Distributed Security Constrained Optimal Power Flow

The need for the coordination of distributed energy resources in the future electric power system provides motivation to move from the current highly centralized control of resources toward a more distributed control structure. This paper presents an agent-based fully distributed dc security constrained optimal power flow (DC-SCOPF) approach. The algorithm is based on a multi-agent system, in which geographically distributed network entities are designated as agents with local sensing, communication, and computation abilities as envisioned for a smart grid. This distributed approach is based on solving the first order optimality conditions associated with DC-SCOPF formulation through an iterative process. At each iteration, each agent updates a few local variables through simple computations, and exchanges information with its neighboring agents. In particular, the updates for each agent incorporate local information such as the Lagrange multipliers, as well as enforcing the supply/demand balance through a local innovation term. Also, the performance is evaluated using the IEEE test systems with 14 and 57 buses and a 944-bus system consisting of eight IEEE 118-bus systems. Finally, analytical arguments concerning the convergence of the proposed method to the optimal solution of the DC-SCOPF are provided.