Optimal Placement of Wind Turbines Using Multi-population Genetic Algorithm and Assessment of Hong Kong offshore Power Potential

Flexible wind turbine (WT) layout location is benefit for the wind farm (WF) performance. This paper proposes a multi-population genetic algorithm (MPGA) program for WT layout optimization which aims at extracting the maximum power in a minimum investment cost. For validation, the MPGA program is applied to a 2km×2km WF considering three different wind scenarios, i.e. (a): constant wind speed of 12m/s with fixed wind direction; (b): constant wind speed of 12m/s with variable wind direction and (c): variable wind speed of 8m/s, 12m/s 17m/s, respectively with variable wind directions. Compared with previous studies, the results of power generation cost of energy and wind farm efficiency are improved. Additionally, the wind turbine layout optimization in a hypothetical offshore wind farm located in Hong Kong southeastern water is attempted using the 20 years’ wind data with an assessment of the offshore wind power potential in Hong Kong. It is indicated that, by optimization, 42.33×10⁸ kWh/year electricity can be converted, which occupies 9.83% of the 2012 electricity consumption in Hong Kong. Results show MPGA program can be applied in real-world wind farms for wind turbine layout optimization when the wind farm boundary is determined as well as the local wind is obtained.