LAPSE:2023.9073
Published Article
LAPSE:2023.9073
An MILP-Based Distributed Energy Management for Coordination of Networked Microgrids
Guodong Liu, Maximiliano F. Ferrari, Thomas B. Ollis, Kevin Tomsovic
February 27, 2023
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 energy resources, distributed optimization, energy management, mixed integer linear programming (MILP), networked microgrids
Suggested Citation
Liu G, Ferrari MF, Ollis TB, Tomsovic K. An MILP-Based Distributed Energy Management for Coordination of Networked Microgrids. (2023). LAPSE:2023.9073
Author Affiliations
Liu G: Grid Components & Control Group, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA [ORCID]
Ferrari MF: Grid Components & Control Group, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Ollis TB: Grid Components & Control Group, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA [ORCID]
Tomsovic K: Department of Electrical Engineering and Computer Science, The University of Tennessee, Knoxville, TN 37996, USA
Journal Name
Energies
Volume
15
Issue
19
First Page
6971
Year
2022
Publication Date
2022-09-23
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en15196971, Publication Type: Journal Article
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LAPSE:2023.9073
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https://doi.org/10.3390/en15196971
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