An MILP-Based Distributed Energy Management for Coordination of Networked Microgrids

Guodong Liu (), Maximiliano F. Ferrari, Thomas B. Ollis and Kevin Tomsovic
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Guodong Liu: Grid Components & Control Group, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Maximiliano F. Ferrari: Grid Components & Control Group, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Thomas B. Ollis: Grid Components & Control Group, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Kevin Tomsovic: Department of Electrical Engineering and Computer Science, The University of Tennessee, Knoxville, TN 37996, USA

Energies, 2022, vol. 15, issue 19, 1-20

Abstract: An MILP-based distributed energy management for the coordination of networked microgrids is proposed in this paper. Multiple microgrids and the utility grid are coordinated through iteratively adjusted price signals. Based on the price signals received, the microgrid controllers (MCs) and distribution management system (DMS) update their schedules separately. Then, the price signals are updated according to the generation–load mismatch and distributed to MCs and DMS for the next iteration. The iteration continues until the generation–load mismatch is small enough, i.e., the generation and load are balanced under agreed price signals. Through the proposed distributed energy management, various microgrids and the utility grid with different economic, resilient, emission and socio-economic objectives are coordinated with generation–load balance guaranteed and the microgrid customers’ privacy preserved. In particular, a piecewise linearization technique is employed to approximate the augmented Lagrange term in the alternating direction method of multipliers (ADMM) algorithm. Thus, the subproblems are transformed into mixed integer linear programming (MILP) problems and efficiently solved by open-source MILP solvers, which would accelerate the adoption and deployment of microgrids and promote clean energy. The proposed MILP-based distributed energy management is demonstrated through various case studies on a networked microgrids test system with three microgrids.

Keywords: distributed optimization; energy management; networked microgrids; mixed integer linear programming (MILP); distributed energy resources (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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