Wind farm topology-finding algorithm considering performance, costs, and environmental impacts

Optimal power in wind farms turns to be a modern problem for investors and decision makers; onshore wind farms are subject to performance and economic and environmental constraints. The aim of this work is to define the best installed capacity (best topology) with maximum performance and profits and consider environmental impacts as well. In this article, we continue the work recently done on wind farm topology-finding algorithm. The proposed resolution technique is based on finding the best topology of the system that maximizes the wind farm performance (availability) under the constraints of costs and capital investments. Global warming potential of wind farm is calculated and taken into account in the results. A case study is done using data and constraints similar to those collected from wind farm constructors, managers, and maintainers. Multi-state systems (MSS), universal generating function (UGF), wind, and load charge functions are applied. An economic study was conducted to assess the wind farm investment. Net present value (NPV) and levelized cost of energy (LCOE) were calculated for best topologies found.