Abstract
The traditional power collection system design separately optimizes the connection topology and the cable cross sections, which may result in the inherent shortcoming of lacking the most economical solutions. In this pursuit, the present work envisages the development of an integrated design method for general wind farm power collection systems, which integrated the coupling random fork tree coding, union-find set loop identification, current and voltage drop calculation models, and a high performance optimization algorithm. The proposed coupling random fork tree coding, for the first time, realized the coupling code of the substation location, connection topology, and cable cross sections, providing the basis for the integration design of the power collection system. The optimization results for discrete and regular wind farms indicated that the proposed integration method achieved the best match of topology, substation location, and the cable cross sections, thus presenting the most economical scheme of the power collection system. Compared to the traditional two-step methods, the integration method used more branches while acquiring them, to maintain the lower number of wind turbines in each branch. Furthermore, it also employed large cross-section cables to reduce the energy loss caused by the impedance in the topology, thereby resulting in a slight increased cable cost; however, the total cost was minimized. The proposed method is very versatile and suitable for the optimization of power collection systems containing any number of wind turbines and substations, and can be combined with any evolutionary algorithm.
Highlights
The global focus on wind farm development has shifted from land to ocean
In order to overcome the above shortcomings, initially we developed an integration optimization method to achieve the best matching of topology and cable cross sections, which involved the proposed integrated coding scheme, power parameter calculation model, and high-performance evolution algorithm
In order to solve the inherent deficiency of the lack of the economical solutions caused by the two-step method of separately optimizing the connection topology and cable planning in the traditional power collection system design, we developed a new integration design method, the proposed coupled random fork tree coding, the union-find set loop identification, and the current and the voltage drop calculation models
Summary
The global focus on wind farm development has shifted from land to ocean. Compared to land, offshore wind energy resources have many advantages, including richer reserves, higher wind energy density, smaller turbulence intensity, and more stable wind direction, which have great development potential [1]. The capitalized MST and the dynamic MST were employed separately to enhance the processing power of a large number of constraints in the optimization of the topology [9,10] Another applied graph-based model employed in the literature is the travelling salesman problem model [12,13], which obtained the optimal topology by traversing all nodes to form a collection containing multiple different shortest paths. The optimization of the current wind farm power collection system is usually a two-step method [29]: First, optimizing the connection topology under the condition of a fixed or variable substation location, and secondly, planning the cross section of each cable segment. The characteristics and performance of the method were illustrated by optimizing the power collection system of a discrete wind farm
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