In this study, a new distributed technique is introduced to address the economic dispatch problem. Unlike traditional methods, our approach operates in a decentralized way, eliminating the need for a central control unit. We leverage symmetric communication networks to facilitate information exchange among participating entities. Our analysis demonstrates that the estimated solutions produced by the proposed dynamics display exponential convergence towards the optimal value of the dispatch problem for connected networks. Furthermore, we undertake assessments utilizing an IEEE benchmark to evaluate the effectiveness of the approach we put forward.

In this paper, we introduce an online estimation algorithm to monitor the electromechanical oscillations in the interconnected power system operation. The proposed continuous-time adaptive algorithm, provides online estimations of the frequency and damping factor of exponentially damped sinusoidal signals. We discuss the convergence of the estimated parameters to their nominal values under several scenarios. In contrast to most of the existing adaptive techniques, the proposed algorithm does not require an a-priori knowledge about the parameters of oscillations. Furthermore, tuning of the parameters of the proposed structure is straightforward. Simulation studies are also provided to corroborate our claims.

This paper investigates the distributed economic dispatch problem in electric power systems. We propose a distributed algorithm to solve the economic dispatch problem over potentially asymmetric communication networks, without using any central control unit. In particular, the proposed algorithm is shown to converge to the optimal dispatch if the generation costs are convex and the underlying communication network is strongly connected. Simulations on the benchmark IEEE 14–bus system are used to validate the theoretical claims, and to illustrate the performance of the proposed algorithm.