Multi-Criteria Decision-Making Approach for Selecting Wind Energy Power Plant Locations

Abstract

In pursuit of green technology innovations, the energy industry is showing an interest in sustainable sources such as wind energy generation. The Saudi Arabian energy industry has a 2030 target to generate and transmit electricity to major customers nationwide and other neighboring Gulf countries. However, the selection of wind energy power plant locations is a concern because the decision process involves social, technological, economical, and environmental factors. The originality of this study lies in (1) proposing an integrated quantitative and qualitative multi-criteria decision making framework for selecting wind-energy power plant locations; (2) applying the proposed framework in the context of the energy industry in a gulf region country and investigating expert-based and entropy-based criterion weight assignments; (3) choosing five possible alternative wind energy power plant locations with 17 response criteria for each alternative to help decision makers identify the best possible alternative; and (4) establishing the superiority of one alternative over another (if it exists). The presented approach extends considerable support to the comparing and ranking of alternatives along with its validation and sensitivity analysis. Based on the proposed multi-criteria decision-making approach, an appropriate wind energy power plant location has been successfully selected among the five alternatives.

Study of Social and Environmental Needs for the Selection of Sustainable Criteria in the Procurement of Public Works

“…For each indicator, a preference function must be computed to translate the difference between the evaluations obtained by two countries into a preference degree ranging from zero to one [96]. The preference function is the V-shaped function with the strict preference threshold (p); this is the maximum value of each indicator, if the indicators need to be maximized, while, in the case of indicators to be minimized, the value of this threshold will be the maximum as well, but with a negative sign [97]. In addition, this method requires the definition of weights and the selection of preference functions that convert the difference between alternatives into a ranging [22].…”

Are MCDA Methods Benchmarkable? A Comparative Study of TOPSIS, VIKOR, COPRAS, and PROMETHEE II Methods

“…The choice of this set was dictated by the properties and popularity of these methods. These methods and their modifications found an application in many different domains such as sustainability assessment [34][35][36], logistics [37][38][39], supplier selection [7,40,41], manufacturing [42][43][44], environment management [45][46][47], waste management [48,49], energy management [50][51][52][53][54][55], chemical engineering [56][57][58], and many more [59,60]. The choice of a group of TOPSIS, VIKOR, and COPRAS methods is justified, as they form a coherent group of methods of the American MCDA school and are based on the same principles, using the concepts of the so-called reference points.…”

A Hybrid Multi-Criteria Methodology for Solving the Sustainable Dispatch Problem

“…To use the function (6) to determine the wind speed distribution, a transformation of this distribution is required to make the WECS compatible, i.e., the function is transformed to no longer depend on the incidence of wind speed-it considers only its expression in relation to the power of wind generators. The Weibull probability distribution function for the WECS is hence transformed in order to be represented as ( 10):…”

“…This can apply to a range of strategic and operational decision problems arising throughout the lifecycle of a wind farm. Recent works in this regard include that of Rehman et al [6], who consider the location of onshore wind farms from a discrete set of alternatives. Seventeen underlying criteria across economic, environmental, social, and technical sustainability dimensions are considered, and the authors apply the Promethee MCDM methodology to investigate multiple criteria trade-offs and, hence, suggest optimal locations.…”