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ORIGINAL RESEARCH article
Front. Energy Res.
Sec. Process and Energy Systems Engineering
Volume 12 - 2024 |
doi: 10.3389/fenrg.2024.1427582
Joint Planning of Energy Storage Site Selection and Line Capacity Expansion in Distribution Networks Considering the Volatility of New Energy
Provisionally accepted- 1 State Grid Zhejiang Electric Power Co.Ltd. Lishui Power Supply Company, Lishui, China
- 2 South China University of Technology, Guangzhou, China
- 3 Guangzhou Shuimu Qinghua Technology Co., Ltd., Guangzhou, China
Under the coordinated operation of the transmission and distribution networks, the issue of downstream grid flow returning to the upstream grid is becoming increasingly prominent. This article proposes a joint planning of energy storage site selection and line capacity expansion in distribution networks considering the volatility of new energy. This technology uses CHk-means clustering calculations based on actual large-scale operation data of new energy sources to generate typical operating curves, and finely constructs an objective function considering power transmission in the transmission-distribution network, abandonment of new energy, line limits, and energy storage construction. By introducing indicative constraints in the energy storage construction-related constraints, the optimization model achieves non-iterative direct solution. The results of the constructed new energy high-penetration distribution network example IEEE Case33 show that the output solution of this model can effectively reduce the energy sent back from the distribution network to the main grid. Compared to optimization models that do not consider the integration of new energy sources, the output solution of this model can reduce the abandonment of new energy by at least 50%. It also avoids the numerical problems that may arise from iterative algorithm and logical transformation, demonstrating engineering application value.
Keywords: reverse power flow(RPF), heuristic k-means(Hk-means), energy storage site selection, Line capacity expansion, penetration rate of renewable energy. Indices, Sets, and Parameters
Received: 04 May 2024; Accepted: 30 Oct 2024.
Copyright: © 2024 Xu, Pan, Chen, Li, Nie and Feng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Miaoyong Feng, South China University of Technology, Guangzhou, China
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