Journal of Advanced Computing (2012) 1

Transcription

Journal of Advanced Computing (2012) 1
Columbia International Publishing
American Journal of Biomass and Bioenergy
(2015) Vol. 4 No. 1 pp. 28-38
doi:10.7726/ajbb.2015.1003
Research Article
A Fuzzy Analytic Hierarchy Process Model for
Selecting the Best Biogas Usage:
A Case Study of Tehran Province, Iran
Maryam Nosratinia1, Ali Asghar Tofigh2, and Mehrdad Adl3*
Received 9 February 2015; published online 25 April 2015
© The author(s) 2015. Published with open access at www.uscip.us
Abstract
Problems arising from global warming and increasing energy demand all around the world caused emerging
alternative energy resources to be inevitable. Biomass is one of renewable energies that can help in
decreasing such problems. Biogas as a popular bioenergy carrier can be used in different ways. In this paper,
a decision making model based on fuzzy analytic hierarchy process is proposed for choosing best method
based on technical, economic, social and environmental criteria in Tehran Province , Iran. The evaluated
alternatives include direct burning for heating, conversion to electricity, upgrading to vehicle fuel quality,
upgrading to bio-methane for injection into gas grid, and combined cooling, heating and power (CCHP)
generation. The evaluation process is performed on experts’ answered questionnaires basis using fuzzy
analytic hierarchy procedure. The results indicate that electricity is the best alternative among the proposed
options for biogas usage methods in Tehran Province, Iran.
Keywords: Biogas; Fuzzy analytic hierarchy process; Multi-criteria decision making
1. Introduction
Policy making during energy planning for governmental purposes is important in different aspects
and is affected by factors such as climate changing, increasing energy demand and cost of fossil
fuels. Meantime, use of renewable energies is a good solution for these challenges and can be
beneficial for environment protection and independency from fossil fuels.
Since biogas is produced by fermentation of renewable raw materials, its utilization is a promising
option to decrease such problems. In addition, due to its methane content, it has similar
______________________________________________________________________________________________________________________________
*Corresponding e-mail: madl49@yahoo.com
1 Department of Industrial Engineering, Ph.D. student of Materials and Energy Research Center,
P.O.box 31787/316, Karaj, Iran
2 Department of Industrial Engineering, Amir Kabir University of Technology, P.O.box15875-4413,
Tehran, Iran
3 Department of Energy, Materials and energy Research Center, P.O.box31787/316, Karaj, Iran
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Maryam Nosratinia, Ali AsgharTofigh, and Mehrdad Adl / American Journal of Biomass and Bioenergy
(2015) Vol. 4 No. 1 pp. 28-38
characteristics to natural gas, but in lower extent (Papong et al., 2014).
Anaerobic digestion process produces biogas through breakdown of natural organic materials with
different industrial, agricultural and rural sources. Developed countries cultivate dedicated crops
such as maize, barley, sunflower, Lucerne and sorghum for anaerobic digestion; and usually use
different mixture of waste for better methane production rate. (Bauer et al., 2010).
Biogas can be used in various ways such as generating power or heat, purifying it into bio-methane
and use it as vehicle fuel, injecting to regional gas grid, and using it in CHP systems. Each way has its
own advantages and disadvantages and choosing the best method of biogas using can be main
factor in biogas success.
In this study, we aim at comparing biogas utilization methods by defining relevant criteria and
prioritizing them by applying a fuzzy multiple criteria decision-making model to experts'
judgments. The investigation zone of this study is Tehran Province in which, the capital of Iran is
located and contains around 17% of whole country’s population. A site selection study for the most
appropriate locations for large and medium scale biogas plants was conducted using geographical
information system (GIS) through which, a final map was concluded that shows the most
appropriate zones in dark blue color (Fig. 1). The outcomes of the aforementioned study have been
disseminated elsewhere (Nosratinia et al., 2015).
Fig. 1.
Demonstration of the most suitable locations for biogas plants in Tehran Province
2. Biogas Utilization
Biogas technology can effectively decrease the harmful impacts of energy conversion and lead to
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(2015) Vol. 4 No. 1 pp. 28-38
omit the Inappropriate effects of fossil fuels in two ways; first, we can consider it as a renewable
source of energy, and second, its efficiency is high (Ou et al., 2009).
If biogas is combusted in an on-site engine or CHP system, only a primary cleaning is needed
(dehumidification and desulfurization) to remove the corrosive compounds that may damage the
engines. The excess heat of the engines can be used for maintaining the fermentation process
temperature and for the operator’s own purposes. In principle, it is also possible to feed the heat
into a local district heating network, although this is rarely done in small or medium scales.
The additional processing and upgrading of biogas into gas grid biomethane for using in allows a
decentralized energy valorization: the biomethane can be drawn and used, anywherewithin the
regional gas grid. The regulatory framework of each country usually states which purity of
biomethane can be injected and the conditions of injection. The grid operators publish their
technical specifications on bio-methane quality (Bordelanne et al., 2011).
Fig. 2.
Biogas usage methods
The order of oil consumers globally in different sectors is as follows; transportation sector (51% of
total consumption), industrial sector (34% of total consumption) and finally, residential (6% of
total consumption) sectors (International Energy Agency, 2010). It should be noted that the energy
consumption in transportation sector is increasing with a 20% growth rate since 1990 and has
been twice between 1973 and 2006 (International Energy Agency, 2010). Bordelanne et al., (2011)
predicted that it can be increased by 30% between 2010 and 2030.
CNG (Compressed Natural Gas) is an alternative fuel to the diesel oil and gasoline, allowing a
reduction of the dependency on crude oil and a diversification of the sources of fuel supply. This
diversification is important not only from an economic point of view, but also in order to secure the
energy supplies. For propose of utilizing biogas as a transportation fuel, raw biogas has to undergo
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Maryam Nosratinia, Ali AsgharTofigh, and Mehrdad Adl / American Journal of Biomass and Bioenergy
(2015) Vol. 4 No. 1 pp. 28-38
two major processes: cleaning and upgrading to achieve a quality near to natural gas. The upgraded
biogas (so called biomethane) and its compressed form (bio-CNG) are considered as green fuel with
respect to environment, climate, and human health. However, the resulting bio-CNG from the
processes still needs to be evaluated in terms of greenhouse gas emissions and energy aspects
(Bordelanne et al., 2011, Papong et al., 2014). Fig. 2 shows biogas utilization options in brief.
3. Proposed Method
3.1. Multiple Criteria Decision-Making and Analytic Hierarchy Process
The general decision making process includes four steps:




Defining decision objectives,
Determining feasible alternatives,
Evaluating the alternatives,
Select and implement the best alternative.
Multiple criteria decision making (MCDM) models have two major types; multiple-objective
decision-making (MODM) models and multiple-criteria decision making (MADM) models. The
decision problem that we consider in this paper is to determine the best alternative for biogas
utilization. We use a fuzzy analytic hierarchy process model to do this.
For selecting the best alternative we should determine criteria, each criterion has its impact and
depend on decision makers point of view. Analytic hierarchy process is a popular method for
producing subjective weights for the decision objective, criteria, sub criteria, and alternatives. In
AHP, we decompose decision problem in to hierarchy of sub problems, with the objective at top,
criteria and sub criteria at next levels, and the alternatives at the bottom (Szczypinska and
Piotrowski, 2008; Tzeng et al., 2002; Yang and Lee, 1997).
3.2. Fuzzy Analytic Hierarchy Process
Evaluation criteria in decision making process could be qualitative or quantitative. When they are
stated in linguistic terms, we should convert them to quantitative way. To do this, we can use fuzzy
sets theory and fuzzy numbers decision makers’ judgments to numbers.
In this paper, we use triangular fuzzy numbers (TFN) defined on [0, 1] range for evaluating
alternatives against criteria. We use pairwise comparisons to find the relative importance of the
criteria and sub-criteria. In this way, scales proposed by Kahraman et al. (2006) are utilized and are
given in Table 1.
We use fuzzy analytic hierarchy process (Fuzzy AHP) for determining relative importance of
criteria, sub criteria, and alternatives. In literature, there are several types of fuzzy AHP (see for
example, Laarhoven and Pedrycz, 1983; Buckley, 1985; Chang, 1996; Leung and Cao, 2000). Here,
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Maryam Nosratinia, Ali AsgharTofigh, and Mehrdad Adl / American Journal of Biomass and Bioenergy
(2015) Vol. 4 No. 1 pp. 28-38
we use Chang (1992, 1996) proposed method. Because steps of it are easier to implement in
practical cases than other proposed methods and its results are similar to crisp AHP.
Table 1 Fuzzy scales used for pairwise comparisons
Relative importance
Equal importance
Moderate importance
Strong importance
Very strong importance
Extreme importance
Fuzzy scale
(1, 1, 1)
( 1, 3/2,2)
(3/2, 2, 5/2)
(2, 5/2, 3)
(5/2, 4, 7/2)
Reciprocal scale
(1, 1, 1)
(1/2, 2/3, 1)
(2/5, 1/2, 2/3)
(1/3, 2/5, 1/2)
(2/7, 1/4, 2/5)
Here, we describe some of applications of Chang (1992, 1996) proposed method; this method was
used by Bozdag et al. (2003) in the evaluation of computer integrated manufacturing alternatives.
Kahraman et al. (2003, 2004) used the method for evaluation of the catering firms in Turkey and
selection of best facility location. Buyukozkan et al. (2004) utilized this approach for selecting the
best software development strategy. Kwong and Bai (2003) and Kahraman et al. (2006) used it to
evaluate Quality Function deployment (QFD) for customer requirements.
Here, we describe Chang (1992, 1996) method. The triangular fuzzy numbers are defined with
boundaries. Assume that we have
, and then the membership function is:
: R
We define
[0, 1] of the triangular fuzzy number defined on R is given by
on R that is given by Eq. (1):
l
 x
m  l  m  l

u
~
 x
M ( x)  x  

m  u m  u
0 otherwise


x  [l , m]
x  [m, u ]
(1)
where l
and m is the median and most possible value of fuzzy number is l and u is the
lower and upper limits of . The value of the fuzzy synthetic extent of the ith object is defined as:
1
~  n m ~ 
Si   M ij   M ij 
j 1
 i 1 j 1

m
m
m
m


~
M ij    lij ,  mij ,  uij 

j 1
j 1
j 1
 j 1

m m
m
m
 m

~
M ij    lij ,  mij ,  uij 

i 1 j 1
j 1
j 1
 j 1

m
(2)
(3)
(4)
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(2015) Vol. 4 No. 1 pp. 28-38


1


n m ~ 
1
1
1 

, n
, n
 M ij    n

 i 1 j 1

  uij  mij  lij 
i 1
i 1
 i 1

(5)
The triangular fuzzy number value of
(li, mi, ui) is calculated using Equations (2) to (5). After
calculating the values of Si, we can calculate degree of possibility of Sj=(lj, mj, uj) Si=(li, mi, ui) using
equation 6:


1 if m j  mi

V(S j  Si )  height ( Si  S j )   S j ( d )  
0 if li  ui

li  u j
otherwise

 ( mi  ui )  ( mi  li )
(6)
After calculating both the values of V (Sj
), we should compare Si and Sj. The
i) and V ( i
minimum degree possibility d (i) of V (Sj Si) (i, j=1, 2, …, k) can be expressed as:
V(
(7)
The normalized local weight vector is expressed as follows:
W  min V (S1  S k ),V (S 2  S k ),...., V (S 4  S k )
T
(8)
where k=1, 2,…, k and W is a crisp number.
3.3. Alternatives and Evaluation Criteria
We identified five alternative ways to us biogas for producing heats. The alternatives are given in
Table 2.
Table2 The alternatives
Alternative
1
2
3
4
5
Description
CCHP
Direct Heating
Electricity
Injection to Gas grid
Upgrading Vehicle fuel
There are variety of criteria for system evaluation and decision making in energy fields. For
instance, Jing et al., (2012), Feng and Jin (2005), and Pilavachi et al., (2006) identified four main
criteria for evaluation of a special kind of energy system that are utilized in this paper.
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(2015) Vol. 4 No. 1 pp. 28-38
Pollutant emission reduction and energy saving are the main factors evaluating the benefits of
biogas usage. For evaluation of biogas usage, technological and economic criteria should also be
taken into consideration. Conclusively, criteria selected in this paper are technology, economy,
environment and society. Based on the hierarchical structure of evaluation model, these criteria can
be divided into some sub criteria, Table 3 presents these criteria and sub criteria.
Table3 Criteria and sub criteria definition (Jing et al., 2012)
Criteria
Sub criteria
Definition
Primary energy consumption ratio (A1)
The primary energy consumption divided to the users’ demand energy.
Its goal is to reduce the amount of energy required to provide products and
services
Controllability is an important property of a control system
Is the technology well developed or not?
Is it easy for user to work with it?
The cost of the procurement and set up.
The length of time required to recover the cost of an investment
The total system cost per year
Is defined as the sum of the present values (PVs) of incoming and outgoing
cash flows over a period of time
A key ingredient in smog that can cause acid rain.
It can cause greenhouse effect and global warming.
The most important greenhouse gas.
Noise can bother people and affect their life
Is the system or technology advanced? Can be upgraded in the future?
Can the system or equipment be maintained easily?
Is the system safe for people or not?
The system needs the land area or space
Energy efficiency(A2)
Technology
(A)
Controllability(A3)
Maturity (A4)
Regulation property(A5)
Investment cost(B1)
Investment recovery period(B2)
Total annual cost(B3)
Economy (B)
Net present value(NPV) (B4)
NOX emission (C1)
CO emission(C2)
CO2 emission (C3)
Noise (C4)
Advanced performance(D1)
Maintenance convenience(D2)
Safeguards (D3)
Footmark (D4)
Environment
(C)
Society (D)
3.4. Results
Table 4 Pairwise comparisons of criteria.
A
B
C
D
A
(1,1,1)
(2/5,1/2,2/3)
(2/5,1/2,2/3)
(2/5,1/2,2/3)
B
(3/2,2,5/2)
(1,1,1)
(2/5,1/2,2/3)
(2/5,1/2,2/3)
C
(3/2,2,5/2)
(3/2,2,5/2)
(1,1,1)
(2/3,1,2)
D
(3/2,2,5/2)
(3/2,2,5/2)
(2/3,1,3/2)
(1,1,1)
Table 5 Pairwise comparisons of technology sub criteria
A1
A2
A3
A4
A5
A1
(1,1,1)
(3/2,2,5/2)
(1,3/2,2)
(2/3,1,2)
(1,3/2,2)
A2
(2/5,1/2,2/3)
(1,1,1)
(2/5,1/2,2/3)
(1/3,2/5,1/2)
(2/5,1/2,2/3)
A3
(1/2,2/3,1)
(3/2,2,5/2)
(1,1,1)
(1/2,2/3,1)
(1/2,2/3,1)
A4
(1/2,1,3/2)
(2,5/2,3)
(1,3/2,2)
(1,1,1)
(1,3/2,2)
A5
(1/2,2/3,1)
(3/2,2,5/2)
(1,3/2,2)
(1/2,2/3,1)
(1,1,1)
We used judgments of 10 Iranian biogas experts in order to form pairwise comparisons and extract
the weights based on fuzzy AHP method. It should be noticed that the results in decision making
strongly depend on decision makers, if the governments wants make decision, in most cases the
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(2015) Vol. 4 No. 1 pp. 28-38
policy makers give more weight to social and environmental criteria by considering their people
benefits in long term, but in private sector they usually emphasize on technical and economic
aspects. Our decision is based on private sector and we chose our experts from faculty member and
industry and pairwise comparisons for criteria and sub criteria according to their opinion are given
in table 4 and Tables 5-8 respectively. Table 9 demonstrates the weights of hierarchy elements.
Table 6 Pairwise comparisons of economy sub criteria
B1
(1,1,1)
(2/3,1,3/2)
(2/3,1,3/2)
(3/2,2,5/2)
B1
B2
B3
B4
B2
(2/3,1,3/2)
(1,1,1)
(2/3,1,3/2)
(3/2,2,5/2)
B3
(2/3,1,3/2)
(2/3,1,3/2)
(1,1,1)
(3/2,2,5/2)
B4
(2/5,1/2,2/3)
(2/5,1/2,2/3)
(2/5,1/2,2/3)
(1,1,1)
Table 7 Pairwise comparisons of environment sub criteria
C1
(1,1,1)
(2/3,1,3/2)
(3/2,2,5/2)
(3/2,2,5/2)
C1
C2
C3
C4
C2
(2/3,1,3/2)
(1,1,1)
(1,1,1)
(2/3,1,3/2)
C3
(2/5,1/2,2/3)
(1,1,1)
(1,1,1)
(2/5,1/2,2/3)
C4
(2/5,3,7/2)
(2/3,1,3/2)
(3/2,2,5/2)
(1,1,1)
D3
(5/2,3,7/2)
(2/5,1/2,2/3)
(1,1,1)
(2/5,1/2,2/3)
D4
(3/2,2,5/2)
(2/3,1,3/2)
(3/2,2,5/2)
(1,1,1)
Table 8 Pairwise comparisons of society sub criteria
D1
D2
D3
D4
D1
(1,1,1)
(3/2,2,5/2)
(2/7,1/3,2/5)
(3/2,2,5/2)
D2
(2/5,1/2,2/3)
(1,1,1)
(3/2,2,5/2)
(2/3,1,3/2)
Table 9 calculated weights for criteria and sub criteria
Factors
Weight
A
0.535
B
0.385
C
0.040
D
0.040
Sub factors
A1
A2
A3
A4
A5
B1
B2
B3
B4
C1
C2
C3
C4
D1
D2
D3
D4
Normalized Weight
0.062
00.44
0.239
0.084
0.175
0.164
0.164
0.164
0.507
0.072
0.216
0.430
0.281
0.420
0.56
0.314
0.032
Total Weight
0.03317
0.2354
0.127865
0.04494
0.093625
0.06314
0.06314
0.06314
0.195195
0.00288
0.00864
0.0172
0.01124
0.0168
0.0224
0.01256
0.00128
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(2015) Vol. 4 No. 1 pp. 28-38
Based on Fuzzy Analytic Hierarchy Process in section 3.2, we calculated criteria's weight and the
results show technology criterion has the highest weight than other criteria, then, environment and
society have equal importance, and finally, economy has the lowest weight than other criteria.
In sub criteria level, energy efficiency, net present value, and controllability play the most
important roles in the selection of best biogas usage. On other hand, footmark, CO emission, and
NOX emission play the least important roles in the selection of best biogas usage. Considering
technology criterion, energy efficiency is the most important sub criteria and Primary energy
consumption ratio is the least important sub criteria. Considering economy criterion, net present
value is the most important sub criterion and investment cost, investment recovery period, and
total annual cost are the least important sub criterion. Considering environment criterion, CO2
emission is the most important sub criterion and NOX emission is the least important sub criterion.
Considering society criterion, Maintenance convenience is the most important sub criterion and
footmark is the least important sub criterion.
In last part we used calculated weights and experts' knowledge for ranking alternative and table 10
presents this ranking. As seen in the table, electricity is the most preferable alternative and vehicle
fuel is the least preferable one. This ranking is reasonable according to technology level in Iran and
required costs. Although cruel oil can increase environmental problems of Iran, it has not reached
to required technology for vehicle fuel.
Table 10 Ranking Results for the alternatives
Alternative
1
2
Description
CCHP
Direct heating
Rank
3
2
3
Electricity
generation
1
4
Upgrading/Injection
to gas grid
4
5
Upgrading to
vehicle fuel
5
4. Conclusion and Future Research Directions
In this paper, we aimed at selecting the best usage of biogas using a fuzzy analytic hierarchy process
model. Despite the importance of decision making in renewable energy using methods , this field
have been neglected and this study can be a guideline for decision makers in biogas field so a
decision making model based on fuzzy analytic hierarchy process is proposed for choosing the best
method of biogas usage in Tehran Province , Iran. This model can be adopted in other countries too.
In this paper we defined criteria and sub criteria, and then identified five alternatives. Our decision
problem consisted of four levels; decision objective, criteria, sub criteria, and alternatives. Criteria
included technology, economy, environment and society and alternative included CCHP, heating,
electricity, gas grid, and vehicle fuel. In order to select the best alternative, we asked 10 Iranian
biogas experts to do pairwise comparisons. We found that electricity generation is the best usage of
biogas among other alternatives.
This study can be further developed by adding more details related to Iran’s regulations and
conditions to it. We also should be noted that current results should have expire date and need to
be updated time by time. That’s because by expanding knowledge and passing the time, the
importance of criteria can changed, for example for Iran, US sanctions to energy filed may causes to
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(2015) Vol. 4 No. 1 pp. 28-38
change the importance of environment criteria. Updating the decision making process from time to
time can help governments in making right policy, especially for Iran that suffers from wrong
decision making in renewable energy field.
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