Optimal operational scheduling of distribution network with microgrid via bi-level optimization model with energy bandopen access
- Authors
- Kim, Ho-Young; Kim, Mun-Kyeom; Kim, Hyung-Joon
- Issue Date
- Oct-2019
- Publisher
- MDPI AG
- Keywords
- Bi-level optimization model; Cooperation; Distributed energy resource; Distribution network; Energy band; Microgrid; Modified non-dominated sorting genetic algorithm II
- Citation
- Applied Sciences (Switzerland), v.9, no.20
- Journal Title
- Applied Sciences (Switzerland)
- Volume
- 9
- Number
- 20
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/38704
- DOI
- 10.3390/app9204219
- ISSN
- 2076-3417
2076-3417
- Abstract
- An optimal operation of new distributed energy resources can significantly advance the performance of power systems, including distribution network (DN). However, increased penetration of renewable energy may negatively affect the system performance under certain conditions. From a system operator perspective, the tie-line control strategy may aid in overcoming various problems regarding increased renewable penetration. We propose a bi-level optimization model incorporating an energy band operation scheme to ensure cooperation between DN and microgrid (MG). The bi-level formulation for the cooperation problem consists of the cost minimization of the DN and profit maximization of the MG. The goal of the upper-level is to minimize the operating costs of the DN by accounting for feedback information, including the operating costs of the MG and energy band. The lower-level aims to maximize the MG profit, simultaneously satisfying the reliability and economic targets imposed in the scheduling requirements by the DN system operator. The bi-level optimization model is solved using an advanced method based on the modified non-dominated sorting genetic algorithm II. Based on simulation results using a typical MG and an actual power system, we demonstrate the applicability, effectiveness, and validity of the proposed bi-level optimization model. © 2019 by the authors.
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Collections - College of Engineering > School of Energy System Engineering > 1. Journal Articles
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