Cable Connection Scheme Optimization for Offshore Wind Farm Considering Wake Effect

Abstract

In order to reduce the levelised cost of energy (LCOE) of the offshore wind farm, many optimization works should be done to reduce the investment and increase the energy production. As one of the main expenses, the electrical system can take up more than 15% of the total investment while cable costs take a large proportion. In order to make a cost-effective wind farm, the cable connection layout should be optimized. This paper proposes a novel way for offshore wind farm cable connection layout design. The LCOE, which concerns three aspects: electrical power losses, power captured by wind turbines (WT) and investment, is selected to set up the objective function. Since all the optimization variables are integers, a heuristic algorithm, integer particle swarm optimization algorithm (IPSO), is adopted to find a near optimal solution. To improve the performance of the IPSO, an adaptive method for parameter control is used to help to find a better solution. Comparisons are made with results obtained by the Norwegian center for offshore wind energy (NORCOWE) reference wind farm and the presented method. From the simulation, it can be noticed that the presented approach can help to find a cable connection scheme which can reduce the LCOE by 1.75%.

Grouping-Based Optimal Design of Collector System Topology for a Large-Scale Offshore Wind Farm by Improved Simulated Annealing

“…The optimization performance of the GA can be improved via a proper operation combined with other meta-heuristic algorithms, e.g., the combination between the cross-operators of the GA and the vaccine extraction immune algorithm (IA) [16]. As another classical meta-heuristic optimization method, different variations of PSO [17] [19] are also proposed for the optimal design of CST due to its obvious advantages of global search and parallel calculation. In [18], the case studies show that the PSO (BPSO) can acquire a lower capital cost within the shorter convergence time than the non-dominated sorting genetic algorithm-Ⅲ.…”

Optimization of the electrical connection topology of a tidal farm network

“…The energy cost of a TEC farm depends on the configuration of the power grid. In marine renewable energy applications, the electrical system cost represents between 15 and 30% of the total investment cost, of which 5% are the costs of submarine cables [2,3]. The cost of the electrical system is influenced by several factors which are intertwined [3].…”

Technical-economic analysis, modeling and optimization of floating offshore wind farms

“…The optimization of the electrical layout of FOWTs gains additional importance because the length of a power cable is increased due to the dynamic cable section, spatial requirements of the mooring system and the offset of the floating substructure. For BOWTs a common approach in literature is to simply calculate the geometric distance between wind turbines without considering the water depth [193,197,209]. The length of the power cable used for the connection of FOWTs can be obtained by…”

“…Due to the complexity, a number of studies have investigated the use of metaheuristic methods [197][198][199][200][201] or a combination [188,196,202,203]. Due to the nature of a heuristic model, the studies have therefore opted to a model that may not find a proven optimal solution but a feasible one in a reasonable time with very few constraints [188].…”

“…However, a clustering of turbines has been considered to reduce the complexity and the wake effect is not taken into account. In [197] particle swarm optimization (PSO) model has been applied as well as a single wake model considered. However, the fluctuations in wind speed and wind direction have not been considered as well as no installation cost and reliability of the system.…”