Fully Distributed Adaptive Consensus Approach for Economic Dispatch Problem
This work addresses power optimization in smart grids, offering a decentralized solution for grid operators, but it is incremental as it builds on existing consensus methods with adaptive enhancements.
The research tackled the economic load dispatch problem in smart grids by developing a multi-agent distributed consensus strategy with an adaptive coupling weight mechanism, achieving optimal power allocation and maintaining system balance under dynamic loads, with validation on the IEEE 30 bus test system showing accuracy and efficiency.
This research presents a novel approach to solving the economic load dispatch (ELD) problem in smart grid systems by leveraging a multi-agent distributed consensus strategy. The core idea revolves around achieving agreement among generators on their incremental cost values, thereby enabling an optimal allocation of power generation. To enhance convergence and robustness, the study introduces an adaptive coupling weight mechanism within a fully decentralized consensus framework, carefully designed with appropriate initial settings for incremental costs. The proposed distributed control protocol is versatile it functions effectively in both constrained and unconstrained generator capacity scenarios. Importantly, the methodology ensures that total power generation continuously matches dynamic load demands throughout the dispatch process, maintaining system-wide balance. To accommodate fluctuating and time varying load profiles, a dummy node is incorporated into the network architecture, acting as a flexible proxy for real time demand changes. The resilience of the method is further evaluated under communication disruptions, specifically by analyzing generator link failures through a switching network topology. Stability of the system is rigorously established using a Lyapunov-based analysis, assuming an undirected and connected communication graph among agents. To validate the practical efficacy of the proposed technique, comprehensive simulations are conducted on the IEEE 30 bus test system within the MATLAB environment, confirming its accuracy, adaptability, and computational efficiency in realistic smart grid conditions.