Consensus-based distributed economic dispatch incorporating storage optimization and generator ramp-rate constraints in microgrids

Abstract

First, an extended fully distributed algorithm (FDA) is proposed, and then, on the basis of the extended FDA, a centralized-distributed algorithm (CDA) is modified to solve multi-step economic dispatch problems in microgrids. The FDA could be realized in fully distributed agents, and by contrast, CDA is presented in both locally centralized and globally distributed ways to reduce the amount of distributed agents for applying it to large-scale microgrids and eliminating the necessity for a central energy management system. Information exchange between agents, such as power mismatch and Karush-Kuhn-Tucker multiplier, is realized by consensus networks, and the optimal solutions can be found through iterative communication between each agent with its neighbours. Besides, different from the most existing single-step solver, this paper deals with multi-step decision-making problems incorporating storage optimization and generator ramp-rate constraints. Moreover, incremental costs of local generators are avoided to participate in global information exchange, and so, local privacy can be protected. Meanwhile, CDA is a robust method against communication failures. Several case studies implemented on a twelve-bus microgrid are tested, and comparison results among CDA, FDA, and the centralized quadratic programming algorithm (CA) are discussed to validate the proposed methods. Simulation results show that CDA is effective to find the global optimum reached by CA and presents a better dynamic response than FDA and can be used to solve multi-step economic dispatch problems in a globally distributed way in microgrids.