Authors
1
Tarbiat Modares University
2
K.N. T. University
Abstract
        Extended
abstract 1- Introduction Energy is one of the important factors in the development of human society.
On the other hand evidence, indicates the fact that the biggest cause of
environmental pollution and destruction at between man-made factors, is
production, conversion and consumption types of fossil energy. Â Renewable energy is one of strategies that proposed in
recently years to avoid such problems. Development
of renewable energy has great economic and social benefits. Such as the limited of
fossil fuels for energy supply and environmental and social costs are lower.
According to the statistics of each kilowatt hour of electricity produced from
renewable resources and wind power, respectively the release of approximately
0.7 and 1 kg CO2 compared with fossil fuel thermal power plants to
be prevented. On the other hand, the decentralized power production
capabilities of the renewable energy, provided opportunities for improvement
and development of remote and rural areas, and enhance social and economic
structure of rural areas and prevent their migration to the cities. Â Wind energy is one of these approaches that have been considered in recent
years. Therefore, the largest electricity generation capacity in renewable
energy in Europe 2008 belongs to the wind energy (43 %). Iran has very windy
areas, but the amount of electricity generation from wind power in compared to
other energy sources is very low. Therefore, the amount in 1384 was about 70
GW/h, i.e. 0.04 percent of total electricity generated in the country. In
contrast, many industrialized countries, had more attention to this sources, so
that 86% the total capacity of wind power plants located in 10 countries. Many researchers with considering only the potential of wind had many
studies on the prone areas, for construction of wind power plants. But it
should be noted that environmental issues are often complex and
multidimensional and there are many stakeholders with a lot of goals and
priorities. Therefore developing a system that can meet the needs of all groups
with regard to all criteria is essential. As regards the GIS in combination
with multi-criteria decision-making methods has many capabilities in this
field, many researchers have used to analyze the suitability of lands. The aim of
this research is assessing the land suitability for construction wind farms
with MCDM and GIS.   Material & Methods Study Area The study area of about 45481km2 is located in
the East Azerbaijan of the northwest of Iran. It lies between latitudes 36o
45' and 39o 26' N, and stretches between
longitudes 45o 5' to 48o 22' E.   Data  There are many factors and criteria for locating wind
farms. In this study, According to experts and study available resources and
local conditions the following criteria were considered including Wind Speed
(m/s), Distance to fault (m), Topography (slope & altitude), Distance to
transmission lines, Distance to rural & city, Distance to airport, Distance
to lake & rivers and Land use. All the data used maps prepared in 1: 25000
scale map and Aster satellite image for land use map were used.   Method After collecting all
data, for weighting and combining layers, the AHP and fuzzy logic methods were
used. The AHP method that presented by Saaty (1980) has been
used to obtain the optimal level. In this method for
pairwise comparison of alternatives and criteria's, the values proposed by
Saaty was used. Then to obtain the final weight, relative weights were
combined using special vector method. In this
study, the overall inconsistency index was 0.0245, indicating the appropriate
weights are assigned to the criteria and alternatives. Fuzzy sets have been use
for classifying objects and phenomena that do not have the exact boundaries. In
this method, the degree of membership in the interval [0, 1] be express. Which
0 represent non membership and 1 represent full membership of a set. In this
method for fuzzifying the wind potential, distance from cities, rural, lake,
river, fault, airport and for fuzzifying the slope and height layers, respectively
we used large and small fuzzy membership. In addition, for fuzzifying the
communication lines layer the trapezoid fuzzy membership function was used.
Then the convex combination method was used for combining the fuzzy layers.
After obtaining results of both methods, the results to the four classes
perfectly suitable (0.8-1) , relatively suitable (0.6-0.8) , relatively
unsuitable (0.4-0.6) , and perfectly unsuitable (0-0.4) was classified.    Results and Discussion  Due to the wind turbines have been a lot of noise and also negative
environmental and social impacts, locate them should be based on certain
principles and standards, to compensating these problems in addition to
increase profits and reduce capital costs. In this study for determining
suitable areas for wind power plants, 12 parameters that are the most
influential factors were used. Â Note that economical, environmental and social cultural criteria
respectively with weight 0.571, 0.286 and 0.143 influenced the output map.
According to the weights obtained from pair wise comparisons, in the economic
criteria the wind speed, altitude and in the environmental criteria distance
from lakes, land use and in the social cultural criteria distance from cities
and rurals respectively have 77 and 86 percent of the total weights that
allocated to the criteria. In the result map of fuzzy and AHP, respectively
appropriate regions located around the Sahand station, southwest of Tabriz,
Bostan Abad and Sahand station. The main reason for been suitable those stations,
having good conditions of the economic criteria and particularly wind
potential. Due to having wind speed less than threshold Marage, Miyaneh, Julfa,
Marand and Bonab stations are in constraint area and they are not suitable for
construction of wind farms. From total area, in AHP and fuzzy
model respectively, 11.26 and 1375.2 km2 are in the perfectly
suitable class. For comparison, and proper conclusion, the correlation matrix
between fuzzy and AHP methods with most layers was calculated. Results of both
methods were similar in most layers (Correlation between the two methods was
98.952%) and only difference between the wind speed and slop layers is
noticeable. In these layers, the correlation coefficient of fuzzy logic is more
than the AHP. This is because accurate modeling of uncertainties in the data
and expert knowledge (Definition of class boundaries) by fuzzy logic.    Conclusions Various factors and criteria used for wind farms
location selection. In this study, GIS based MCDM methods were used for land
suitability assessing. Energy planners may use
this analysis to determine energy production, area required and avoidance of
unsuitable sites. In this study, for the first time large and small
fuzzy membership functions was used for fuzzifying the layers in the issue. The results indicate the ability of fuzzy logic for integration
high volume data set to controllable variables. And also the results indicate
that in researched problem, the fuzzy logic has relative priority than AHP and
wind speed potential, height, lakes, land use, distance from cities and rural
are most important factors in determining suitable area for wind farms.   Â
Keywords