Robust Collaborative Consensus Algorithm For Economic Dispatch Under Decentralized EMS

Economic dispatch(ED)is a common nonlinear optimization in power systems,which aims to minimize the total generation cost through optimally distributing the power demand among all dispatchable generators under various constraints.Centralized ED based on centralized algorithms in the energy management system(EMS)has been proposed to handle this issue.However,the notorious 'curse of dimensionality' may emerge in centralized ED as the scale and complexity of a power system increases,which leads to a high computational burden and poor performance of these algorithms.Recently,several studies have been undertaken to investigate the feasibility of decentralized ED to handle the above obstacles,in which different consensus algorithms have been addressed.Nevertheless,the current consensus algorithms merely considered an ideal communication network,while their effectiveness remains pending if a practical communication network is taken into account.In fact,the transmission delay and noise are widely existed in a multi-agent system due to the massive data transmissions,measurement errors and external disturbances.Thus a poor convergence or even divergence of consensus algorithms may be resulted in.Additionally,the switching network may degrade the stability and convergence rate of consensus algorithms.In this paper,a robust collaborative consensus algorithm is proposed to simultaneously consider the transmission delay,noise,link failures and unexpected exit of agents for decentralized ED.The malignant effects of transmission delay and noise can be significantly reduced by using a decaying consensus gain function.Moreover,the virtual consensus variable is employed to provide great robustness in the presence of switching topology emerged in multi-agent systems,thus RCCA is adequate for the plug-and-play of generators for decentralized ED.The performance of the proposed approach has been evaluated on an IEEE 39-bus system and an IEEE 118-bus system,respectively.Simulation results verify the effectiveness and robustness of RCCA.