LAI Xin, LIN Shunjiang, LIANG Yutao, et al. Coordinated Planning Approach for Offshore Wind Farm Turbines and Collection Networks[J]. 2025, 51(6): 2819-2829.
DOI:
LAI Xin, LIN Shunjiang, LIANG Yutao, et al. Coordinated Planning Approach for Offshore Wind Farm Turbines and Collection Networks[J]. 2025, 51(6): 2819-2829. DOI: 10.13336/j.1003-6520.hve.20241763.
Coordinated Planning Approach for Offshore Wind Farm Turbines and Collection Networks
In order to rationally plan offshore wind farm(OWF) and improve the economics of OWF investment and operation
it is necessary to study the planning of offshore wind farm turbines and collection networks. For the OWF collection system using AC grid-connected mode
a coordinated optimization planning model of wind turbines(WTs) and collection network is established with the goal of maximizing the annual expected profit of the OWF collection system. Meanwhile
the decision variables are the WTs' locations and capacities
the voltage level and topological connection of the collection network
the collection cable capacities
the locations of the offshore platforms and the transformer capacities. In the model
the wake effect model considering regional wind directions is used to accurately reflect the wake effect between different WTs. In order to solve the coordinated planning model
by using the Benders decomposition method
the original mixed integer nonlinear programming model is decomposed into the master problem of mixed integer linear programming model and the sub-problem of quadratic programming model; moreover
the optimal coordinated planning scheme is efficiently obtained through alternative iteration solution
and a method of using polyline to handle cross submarine cables is proposed to improve the efficiency of model solution. Finally
two practical OWFs with installed capacity of 200 MW and 1 000 MW are analyzed. The results show that
compared with the centralized solution and other methods
the proposed method has higher solution efficiency
and the obtained OWF planning scheme has higher economy and reliability.