Published September 2019 | Version v1
Journal article

A Decision Support System methodology for selecting wind farm installation locations using AHP and TOPSIS: Case study in Eastern Macedonia and Thrace region, Greece

  • 1. National Agricultural Organization –"DEMETER", Forest Research Institute, Vasilika, Thessaloniki, 57006 (Greece)
  • 2. Democritus University of Thrace, Department of Forestry and Management of the Environment and Natural Resources, Pantazidou 193, Orestiada, 68200 (Greece)

Description

Highlights: • Incorporation of social factors affecting wind farm investment. • A methodology that is easily modifiable and replicable by researchers. • Ability to create and study scenarios. • Capability to modify the resolution and the accuracy of the location selection. -- Abstract: The optimization of spatial planning in order to identify the most suitable places for the installation of wind farms is one of the most difficult problems mainly due to the need of identification and calculation of a variety of qualitative and quantitative parameters as well as their effect on the final solution. Multi Criteria Decision Making Methods (MCDM) are commonly used in order to solve this problem and are combined with Geographic Information Systems (GIS) to spatially represent the results from the application of the MCDM methodology. This paper presents a methodology which is based on the combination of a MCDM methodology called Analytical Hierarch Process (AHP) and GIS in order to determine the most suitable locations for wind farms installation. The calculated locations are then ranked using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) in order to rank the locations based on installation suitability. The application of this methodology can help decision makers to easily overcome conflicting parameters and propose optimal solutions which are acceptable from citizens and stake holders while at the same time are economical and environmental friendly.

Additional details

Identifiers

DOI
10.1016/j.enpol.2019.05.020;
PII
S0301421519303167;

Publishing Information

Journal Title
Energy Policy
Journal Volume
132
Journal Page Range
p. 232-246
ISSN
0301-4215
CODEN
ENPYAC

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
55007291
Subject category
S17: WIND ENERGY;
Descriptors DEI
DECISION MAKING; INVESTMENT; OPTIMIZATION; PLANNING; WIND TURBINE ARRAYS

Optional Information

Copyright
Copyright (c) 2019 Elsevier Ltd. All rights reserved.