Distributed Finite-Time Economic Dispatch of a Network of Energy Resources

The physical power infrastructure is moving from the centralized structure to the distributed structure for enabling integration of distributed energy resources. Due to the large number of distributed energy resources, optimal resource allocation is an important and challenging problem. To solve this problem, a distributed and fast economic dispatch algorithm is provided to share the power generation task in an optimized fashion among a set of distributed energy resources, which can address both generation-demand equality and generation capacity inequality constraints. Different from most existing economic dispatch algorithms, the finite-time convergence to the optimal value is achieved, which makes more sense in real applications. Several case studies are discussed and tested to validate the proposed methods.

I. Introduction

Economic dispatch (ED) is one of the major optimization issues in power systems. It aims at allocating the power generation among the generators while meeting the constraints of total load demand as well as respecting individual resource capacity limits. The traditional optimization methods (e.g., gradient search method [1], lambda iteration method [2]) and the intelligent computational methods (e.g., genetic algorithm [3], particle swarm optimization [4], [5]) have been extensively applied to solve the ED problem in a centralized fashion.