Energy Economic Dispatch for Photovoltaic–Storage via Distributed Event-Triggered Surplus Algorithm

Abstract

This paper presents a novel approach to economic dispatch in smart grids equipped with diverse energy devices. This method integrates features including photovoltaic (PV) systems, energy storage coupling, varied energy roles, and energy supply and demand dynamics. The system model is developed by considering energy devices as versatile units capable of fulfilling various functionalities and playing multiple roles simultaneously. To strike a balance between optimality and feasibility, renewable energy resources are modeled with considerations for forecasting errors, Gaussian distribution, and penalty factors. Furthermore, this study introduces a distributed event-triggered surplus algorithm designed to address the economic dispatch problem by minimizing production costs. Rooted in surplus theory and finite time projection, the algorithm effectively rectifies network imbalances caused by directed graphs and addresses local inequality constraints. The algorithm greatly reduces the communication burden through event triggering mechanism. Finally, both theoretical proofs and numerical simulations verify the convergence and event-triggered nature of the algorithm.