Multi-Criteria Analysis for Solar Farm Location Suitability

• Main Authors: Mierzwiak Michal, Calka Beata
• Format: Article
• Language: English
• Published: Sciendo 2017-12-01
• Series: Reports on Geodesy and Geoinformatics
• Subjects: solar farms; multi-criteria decision analysis; spatial analysis
• Online Access: https://doi.org/10.1515/rgg-2017-0012

Currently the number of solar farms, as a type of renewable sources of energy, is growing rapidly. Photovoltaic power stations have many advantages, which is an incentive for their building and development. Solar energy is readily available and inexhaustible, and its production is environmentally friendly. In the present study multiple environmental and economic criteria were taken into account to select a potential photovoltaic farm location, with particular emphasis on: protected areas, land cover, solar radiation, slope angle, proximity to roads, built-up areas, and power lines. Advanced data analysis were used because of the multiplicity of criteria and their diverse influence on the choice of a potential location. They included the spatial analysis, the Weighted Linear Combination Technique (WLC), and the Analytic Hierarchy Process (AHP) as a decisionmaking method. The analysis was divided into two stages. In the first one, the areas where the location of solar farms was not possible were excluded. In the second one, the best locations meeting all environmental and economic criteria were selected. The research was conducted for the Legionowo District, using data from national surveying and mapping resources such as: BDOT10k (Database of Topographic Objects), NMT (Numerical Terrain Model), and lands and buildings register. Finally, several areas meeting the criteria were chosen. The research deals with solar farms with up to 40 kW power. The results of the study are presented as thematic maps. The advantage of the method is its versatility. It can be used not only for any area, but with little modification of the criteria, it can also be applied to choose a location for wind farms.