Multiple-criteria decision analysis

Normalization (sociology)

Engineering

Environmental economics

Weighting

Selection (genetic algorithm)

Economics

Data mining

Computer science

Anthropology

Management science

Radiology

Biochemical engineering

Operations research

Analytic hierarchy process

Renewable energy

Political science

Sociology

Site selection

Environmental science

Artificial intelligence

Medicine

Machine learning

Electrical engineering

Renewable Energy

Multi-criteria decision making (MCDM) methods have become increasingly popular in site selection decision-making of renewable energy power plants because they consider multiple conflicting goals and decision-maker preferences. In this paper, a systematic literature review of MCDM applications for renewable energy site selection is performed, covering a total of 85 papers published from 2001 to 2018 in high-level journals (chosen from the ScienceDirect database). This paper has summarized the exclusion criteria and evaluation criteria of site selection for five energy sources. The five site selection stages, criteria selection, data normalization, criteria weighting, alternative evaluation and result validation, are revealed by content analysis. All papers are further classified by the date, energy source, journal of publication, country of author affiliation, and study area. It is found that different energy sources emphasize different criteria; however, some similarities exist. Literature surveys and expert opinions are most common criteria selection method. Reclassification is most frequently used data normalization method. The analytic hierarchy process is popular for weighting. In alternative evaluation, geographic information systems and weighted linear combination are the most popular tools. Varying the criteria weights is most commonly used result validation method.

A review of multi-criteria decision making applications for renewable energy site selection