A Transactive Energy Framework for Coordinated Energy Management of Networked Microgrids With Distributionally Robust Optimization

• Published in: IEEE transactions on power systems Vol. 35; no. 1; pp. 395 - 404
• Main Authors: Liu, Zhaoxi, Wang, Lingfeng, Ma, Li
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-01-2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Case studies; Coordination; Decisions; Distribution management; Distributionally robust optimization (DRO); Electric power grids; Energy management; Microgrids; networked microgrids; Operating costs; Optimization; Power markets; Reactive power; Robustness (mathematics); Scheduling; transactive control; Transactive energy
• ISSN: 0885-8950; 1558-0679
• DOI: 10.1109/TPWRS.2019.2933180

Networked microgrids (MGs) are considered as an emerging grid design for the future distribution system (DS). The coordination of the networked MGs is critical in order to further enhance the operation efficiency and reliability of the system. In this paper, a transactive energy (TE) framework is proposed for the coordinated energy management of networked MGs in DS. Instead of direct coordination signals and fixed pricing schemes, the distribution network operator (DNO) organizes a transactive market with the MGs to coordinate the energy management in the operation. Further, a distributionally robust optimization (DRO)-based algorithm is developed to provide a robust solution of the detailed scheduling decisions in the proposed TE framework under uncertainty without being too conservative. Case studies with the proposed framework were conducted with the IEEE 33-bus system with three MGs and the IEEE 123-bus system with nine MGs. The results of the case studies show that the proposed TE-based framework can effectively coordinate the energy scheduling of the MGs. The operational cost of the DS is reduced significantly. Meanwhile, the proposed DRO-based algorithm provides a robust but not over-conservative solution for the operation decisions of the DNO and MGs in the proposed framework.