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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.

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

This paper proposes a robust fully distributed consensus based algorithm (RFDCA) for optimal dispatch of generating units in power systems with a practical communication network, which considers noise, communication delay and a dynamically switching communication topology. The proposed approach is based on double consensus $- \lambda$ consensus achieved through first-order consensus protocol and $\Delta P$ consensus through average consensus protocol. The adverse effects of noise and communication delay can be lessened through a monotonically decreasing consensus gain function. The main advantage of this method is that the generating units need not share their cost characteristics to anyone, thereby preserving their private information. Another advantage of the proposed approach is that it can deal with networks of different sizes and topology, and by choosing the proper convergence coefficient, a faster rate of convergence can be achieved. Simulations are carried out on standard IEEE test systems to illustrate the efficacy of the RFDCA approach on both smaller and larger systems.

Double Consensus based Optimal Dispatch considering Communication Delay and Noise

An iterative distributed algorithm is proposed for existing power system optimization problems. Here the centralized optimal dispatch problem is explained in a decentralised manner. The line flow constraints along with generation limits are distributed into different nodes of the given network. In order to achieve a globally optimal solution, the incremental cost and the penalty factor for congestion are varying iteratively. The distributed algorithms provide flexibility, robustness, and scalability. The algorithm is tested for optimal power dispatch in an IEEE 39-bus system and welfare maximization problem in a 3-bus system. The results are validated with the standard centralised approach.

P. M. Naina

Papers

Double Consensus based Optimal Dispatch considering Communication Delay and Noise

An Iterative Distributed Approach for Optimal Power Dispatch in a Smart Grid Environment