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• Authors propose MILP approach for optimal cable routing in an onshore wind farm. • The novelty in the proposed algorithm is reliability assessment of the proposed network. Based on the suggested outline of the network, the failure rate as well as the cost of lost energy production for every wind turbine within the farm is updated. • The algorithm supports the optimal selection among different cable options, with different features, prices and capacities. The algorithm also takes into account the calculation of steady-state voltage at the point of connection (POC) and thus, accounts effect of power quality in the network. • The proposed algorithm is tested on an actual distribution model including a wind farm. The algorithm gives optimal solution for all 12 case scenarios that have been tested. Designing an onshore wind farm is a complex planning process that requires various stages to be completed. The prime focus of this work is to assist planners and experts in finding the optimal cable layout of the onshore wind farm. The optimization algorithm is designed using mixed integer linear programming (MILP). The MILP algorithm takes into account system reliability, power transfer capacities and power quality issue. The novelty in this optimization algorithm is to simultaneously minimize cable installation cost and the cost of lost energy production and therefore maximize the reliability of the system. Additionally, the algorithm supports the optimal selection among different cable options, with different features, prices and capacities. By calculating voltage increase at the point of connection (POC), power quality issue is considered as well. The designed algorithm provides optimal results for four different wind farm layouts. Every layout is tested for three different case scenarios, where different number and type of cables are considered. The results show that more cable options contribute in lowering the total costs. Moreover, cables with higher capacity can help in improving the power quality issue. [ABSTRACT FROM AUTHOR]

In traditional wind farm planning, the design of wind turbine locations and cable layouts is usually undertaken sequentially. However, this approach may potentially result in suboptimal solutions. While the increased spacing between wind turbines enhances power output by reducing wake losses, it also imposes a negative impact by raising cable costs. Addressing this challenge, we propose a novel multi-objective optimization model that simultaneously considers the micrositing of wind turbines and cable routing. A joint framework of the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and the Mixed-Integer Linear Programming (MILP) is established to optimize the layout of wind turbine locations, points of connection, and cable paths. The results indicate that, compared to the traditional sequential optimization, our integrated optimization exhibits significant economic advantages since improved the balance between micro siting and cable routing. By strategically sacrificing a portion of power generation to reduce cable costs, the overall investment profitability can be remarkably improved, with a maximum gain equivalent to 10.02 % of the cable costs. • Proposing a layout optimization model considering micro-siting and cable routing. • An integrated framework of the NSGA-II and the MILP is established. • The comparison between sequential and integrated designs for windfarm is studied. • Wake effects and cable crossing constraints are considered in the proposed model. [ABSTRACT FROM AUTHOR]