Journal Article10.1109/TSG.2018.2833108
Distributed Consensus Based Algorithm for Economic Dispatch in a Microgrid
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TL;DR: Using multi-parameter perturbation theory and graph theory, the convergence of the algorithm is proved and it is obtained that the algorithm converges to the optimal solution at a rate governed by the second largest eigenvalue of the system matrix.
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Abstract: Economic dispatch problem (EDP) is a fundamental optimization problem of power systems. With the penetration of renewable energy sources in microgrids, this paper proposes a distributed algorithm based on consensus theory to solve the EDP with a quadratic cost function. The method takes advantage of the fact that incremental costs need to be equal for all buses at optimal output power values. Thus, the incremental cost of each bus is selected as a consensus variable and the local mismatch between total demand and generation is assigned as a feedback variable to meet demand constraints. Unlike the existing related works, the feedback gains for the feedback variables are different and time-varying. Using multi-parameter perturbation theory and graph theory, the convergence of the algorithm is proved. Furthermore, the upper bounds of the feedback gains are given theoretically, and we obtain that the algorithm converges to the optimal solution at a rate governed by the second largest eigenvalue of the system matrix. Meanwhile, the algorithm is a fully distributed algorithm without a leader or a virtual command node. The simulation results illustrate the effectiveness of the algorithm even though there is a demand change and generator damage. Some simulation results intuitively illustrate how the convergence speed changes with the feedback gains.
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Citations
A novel hybrid soft computing optimization framework for dynamic economic dispatch problem of complex non-convex contiguous constrained machines
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A consensus approach for economic dispatch problem in a microgrid with random delay effects
TL;DR: A consensus approach to solve the economic dispatch problem (EDP) with the effect of random delay is proposed and one allowable delay bound is calculated based on the Lyapunov stability condition.
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Virtual-Action-Based Coordinated Reinforcement Learning for Distributed Economic Dispatch
TL;DR: A unified distributed reinforcement learning (RL) solution is offered for both static and dynamic economic dispatch problems (EDPs) and a distributed form of Hysteretic Q-learning achieves coordination among agents.
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Privacy-Preserving Distributed Economic Dispatch of Microgrids: A Dynamic Quantization-Based Consensus Scheme With Homomorphic Encryption
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TL;DR: In this paper , a homomorphically encrypted consensus algorithm is developed in the absence of a third party to achieve optimal power distribution with the least cost while preventing sensitive information leakage during the entire communication process.
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