On-Shore Wind Farm Cable Network Optimisation Utilising a Multiobjective Genetic Algorithm

Abstract

A wind farm is a collection of large scale (usually > 1MW) wind turbines generally located across wide and uneven terrain in order to capture sufficient wind resources to generate a source of electrical energy. The electric power networks of such farms serve to electrically connect all the turbines in the farm back to a central substation, which is in turn connected to a load, often via an existing electricity distribution or transmission network. While optimisation methods currently exist for the design of cable networks in off-shore wind farms, which primarily aim to reduce installation cost and energy loss, the design for onshore farms is usually achieved manually and iteratively, and can often result in a suboptimal design. This paper offers a Genetic Algorithm based optimisation method for onshore applications, and demonstrates how an optimal wind farm cable network design solution can be reached in terms of minimum cost, minimum power losses and maximum reliability. The algorithm developed performs the required calculations and demonstrates that an optimised solution has been reached. It is demonstrated that this method provides faster calculations than the manual method and can be used for any standard on-shore wind farm layout design, utilising components as desired by the user such as underground or overhead cables and single or triple-core cables. Index Terms — Energy networks, genetic algorithms, multi-objective optimization, wind energy.

General mathematical model for the calculation of economic cross sections of cables for wind farms collector systems

“…The authors use few different algorithms: minimum spanning tree (MST), dynamic MST, and the algorithm based on the concept of MST and further improved by the adaptive particle swarm optimisation algorithm. In [13,14], optimisation of the wind farm cabling is done by taking into account the investment costs and energy losses. In [13], it is demonstrated how a wind farm cable network design solution for onshore applications optimal in terms of the minimum cost, minimum power losses and maximum reliability can be reached by using genetic algorithm-based optimisation method.…”

“…In [13,14], optimisation of the wind farm cabling is done by taking into account the investment costs and energy losses. In [13], it is demonstrated how a wind farm cable network design solution for onshore applications optimal in terms of the minimum cost, minimum power losses and maximum reliability can be reached by using genetic algorithm-based optimisation method. While [14] presents an approach, based on MILP method, for solving the problem of optimal design of internal cable network by taking into consideration the investment and operation costs.…”