Publication
Decentralized energy management of power networks with distributed generation using periodical self-sufficient repartitioning approach
Conference Article
Conference
American Control Conference (ACC)
Edition
2019
Pages
3230-3235
Doc link
http://dx.doi.org/10.23919/ACC.2019.8814851
File
Abstract
In this paper, we propose a decentralized model predictive control (MPC) method as the energy management strategy for a large-scale electrical power network with distributed generation and storage units. The main idea of the method is to periodically repartition the electrical power network into a group of self-sufficient interconnected microgrids. In this regard, a distributed graph-based partitioning algorithm is proposed. Having a group of self-sufficient microgrids allows the decomposition of the centralized dynamic economic dispatch problem into local economic dispatch problems for the microgrids. In the overall scheme, each microgrid must cooperate with its neighbors to perform repartitioning periodically and solve a decentralized MPC-based optimization problem at each time instant. In comparison to the approaches based on distributed optimization, the proposed scheme requires less intensive communication since the microgrids do not need to communicate at each time instant, at the cost of suboptimality of the solutions. The performance of the proposed scheme is shown by means of numerical simulations with a well-known benchmark case.
Categories
automation, control theory, optimisation.
Author keywords
Economic dispatch, online periodical partitioning, decentralized MPC
Scientific reference
W. Ananduta and C. Ocampo-Martínez. Decentralized energy management of power networks with distributed generation using periodical self-sufficient repartitioning approach, 2019 American Control Conference, 2019, Philadelphia, pp. 3230-3235.
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