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Citation:Yutao Liang,Shunjiang Lin,Senior Member,et al.Coordinated Planning for Multiple Inner Networks of Offshore Wind Farms and Onshore Transmission Expansion[J].Protection and Control of Modern Power Systems,2025,V10(03):35-54[Copy]
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Coordinated Planning for Multiple Inner Networks of Offshore Wind Farms and Onshore Transmission Expansion
Yutao Liang,Shunjiang Lin, Senior Member, IEEE,,Xin Lai,Mingbo Liu, Member, IEEE,Binrui Zhang
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Abstract:
A mismatch between the rapid growth of grid-connected offshore wind farms (OWFs) and the delay of onshore transmission expansion (OTE) planning has caused significant wind curtailment in power systems. To alleviate this problem, a coordinated planning (CP) model of multiple inner networks of OWFs (INOWFs) and OTE is established in this paper. In the proposed CP model, the explicit connection topology constraints of a new double-sided ring topology for INOWFs are defined, and the connection topologies and electrical components of both INOWFs and OTE are coordinately optimized. In addition, a parallel random search method is proposed to obtain the set of feasible connection topology schemes of each INOWF, which can contract the feasible region of the CP model and reduce the difficulty in obtaining the optimal solution. Finally, a decomposition and coordination planning algorithm is developed to decompose the original complex optimization model into two tractable sub-models for INOWF and OTE planning. This approach efficiently obtains the optimal CP scheme for multiple INOWFs and OTE through alternating iterations. Case studies on the modified IEEE 39-bus system with two OWFs and an actual provincial power system with six OWFs demonstrate the correctness and efficiency of the proposed model and algorithm.
Key words:  Coordinated planning, decomposition and coordination optimization, offshore wind farm, parallel random search, transmission expansion planning.
DOI:10.23919/PCMP.2024.000078
Fund:This work is supported by the Guangdong Basic and Applied Basic Research Foundation (No. 2024B1515250007 and No. 2023A1515240075), and the Key Research and Development Project of Guangdong Province (No. 2021B0101230004).
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