Double-Consensus-Based Distributed Energy Management in a Virtual Power Plant

Abstract

The penetration of distributed generators increases the significance of virtual power plants (VPP) in the electricity market paradigm. The conventional VPP energy management system relies on a trustable centralized coordinator, which is vulnerable to single-point failure and requires a high-bandwidth communication network. This article proposes a robust, fully distributed consensus-based algorithm (RFDCA) for optimal dispatch of VPP participants in power systems with a practical communication network, which considers noise, communication delay, and a dynamically switching communication topology. The profit maximization problem is decomposed into subproblems using dual decomposition and solved using a double consensus approach, which uses a monotonically decreasing consensus gain function to suppress the adverse effects of communication delay and noise. One of the main advantages of this method is that the VPP participants need not share their private information with anyone, thereby preserving their privacy. Another advantage of the proposed approach is that it can deal with networks of different sizes and topologies. Simulations are carried out on standard 15-node VPP and IEEE 39-bus test systems to illustrate the efficacy of the RFDCA approach. The algorithm removes the need for a central controller in the VPP system, and the faster convergence of the algorithm extends its application in real-time energy management.