Sustainable wind plant location optimization using fuzzy cross-efficiency data envelopment analysis

Abstract

Due to sustainability of wind energy, demands for this source of energy have increased rapidly. Strategic decisions such as determining the suitable location for wind plants can improve the feasibility of wind energy system projects. In this paper, a novel approach entailing data envelopment analysis (DEA) cross-efficiency and fuzzy-cross-efficiency models is proposed to find most suitable locations for wind plants establishment. Sustainability criteria are used as inputs and outputs of the presented approach. The developed method considers uncertainties associated with candidate locations efficiency value. The efficiency is defined as the ratio of weighted sum of outputs to that of inputs. A simulated annealing (SA) algorithm is applied to achieve a new ranking that has the lowest distance from the mean of all the available rankings obtained by the models. To evaluate the performance of the approach, a real case study in Iran is investigated. The numerical results show that the average values of efficiency obtained from the proposed aggressive and benevolent models are equal to 0.481 and 0.665, respectively. While, the obtained values for the deterministic aggressive and benevolent models are 0.491 and 0.609, respectively. Hence, fuzzy-cross-efficiency models provide lower and upper bounds for corresponding cross-efficiency models.