A MULTI-CRITERIA

APPROACH TO LOCAL ENERGY PLANNING

The Case of Barreiro Municipality

Ana Rita Neves

, João Carlos Lourenço

and Vítor Leal

IDMEC, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, Porto, Portugal

Centre for Management Studies (CEG-IST), Instituto Superior Técnico, Technical University of Lisbon, Lisbon, Portugal

Keywords: Local energy planning, Multi-criteria evaluation, MACBETH.

Abstract: Energy planning is at the top priorities of local authorities nowadays. Problems such as the depletion of

natural resources, the wellbeing of human population and the security of energy supply have became the

main drivers to change the current fossil fuel-based energy paradigm. In order to put into practice energy

planning processes at the local level, there is a need to provide support methods and tools to local

authorities. In this paper we present a decision support methodology for sustainable local energy planning

that combines energy modelling and multi-criteria evaluation techniques. The focus of the paper is on the

building process of a multi-criteria evaluation model for the municipality of Barreiro, in Portugal. The

municipality case revealed that multi-criteria evaluation is a suitable tool for local energy planning.

1 INTRODUCTION

Today’s energy systems are largely driven by the

combustion of fossil fuels, which cause negative

impacts in the environment, in the society and in the

economy. Impacts such as the greenhouse gases

(GHG) emissions are considered to be the principal

cause of climate change (IPCC, 2007). The depletion

of natural resources affects the ecosystems and the

wellbeing of human population, and the risks on the

security of energy supply due to the dependence of a

country in imported fossil fuels affect negatively the

economy.

Energy challenges encompass an urgent change

of the current fossil fuel-based energy paradigm and

the promotion of sustainable energy systems. It is

recognized nowadays that local authorities have an

important role to play in the promotion of

sustainable energy systems. Indeed, recent policies

and initiatives, such as the Covenant of Mayors and

the C40 Cities, stress the fact that cities are

important actors for implementing sustainable

energy policies and that their actions must be

encouraged and supported. The emerging calls for

action at the local level must be accompanied by

methods and tools to assist local authorities in their

processes of energy planning. In particular, local

authorities need a decision support methodology to

help them identifying their fundamental objectives

and selecting actions to achieve these objectives.

This paper presents the application of a decision

support methodology for energy planning to the

municipality of Barreiro in Portugal. The

methodology was applied combining energy

modelling and multi-criteria evaluation techniques.

The focus of the paper is on the building process of

the multi-criteria evaluation model. Problem

structuring methods such as causal mapping (Bryson

et al., 2004) were employed in order to identify the

objectives of sustainable energy planning.

The application of the methodology to the

municipality of Barreiro encompassed the task of

energy modelling for the base year 2008 and for the

time horizon of 2020 in a business-as-usual

perspective. In this way, it was possible to see the

expected evolution in terms of energy consumption

and GHG emissions. Afterwards, the selection of a

set of actions allowed the generation of alternative

energy action plans that were evaluated with the

multi-criteria model. In this work, it was adopted a

MACBETH socio-technical approach (Bana e Costa

and Vansnick, 1999; Bana e Costa et al., 2011; see

also Bana e Costa et al., 2008, for an application in

the energy sector, and Bana e Costa and Oliveira,

313

Neves A., Lourenço J. and Leal V..

A MULTI-CRITERIA APPROACH TO LOCAL ENERGY PLANNING - The Case of Barreiro Municipality.

DOI: 10.5220/0003797603130320

In Proceedings of the 1st International Conference on Operations Research and Enterprise Systems (ICORES-2012), pages 313-320

ISBN: 978-989-8425-97-3

 2012 SCITEPRESS (Science and Technology Publications, Lda.)

2002, for an application in a municipality) involving

actors from the Barreiro City Council and the

Barreiro energy agency (S.Energia), who built a

value function for each objective and weight the

objectives in an one-day decision conference

(Phillips, 2007). At the end of the decision

conference it was possible to obtain an overall

benefit value score for each alternative energy action

plan under evaluation. The expected result of the

application of the methodology is to provide support

to decision-making in local energy planning

processes.

The next section presents the structuring of the

local energy planning problem, where the objectives

and respective attributes are identified as well as the

actions and the generation process of alternatives to

be subjected to the multi-criteria evaluation. It is

also presented how the local actors were involved in

this process Section 3 focuses in the building of the

multi-criteria evaluation model for the municipality

of Barreiro. Section 4 draws some conclusions.

2 STRUCTURING THE LOCAL

ENERGY PLANNING

PROBLEM

2.1 Identification of Objectives

and Attributes

The process of structuring the objectives aims to

provide a deeper understanding of the decision

context. The objectives were identified through a

literature review and through interviews with local

actors. Each interview made with a single actor lead

to a cognitive map, which represents “a person’s

thinking about a problem or issue” (Eden, 2004, p.

673). The individual cognitive maps were

subsequently merged into a group causal map

(Bryson et al., 2004), which was validated by the

interviewees with minor changes. The objectives

were then structured according to the procedure

described by Keeney (2007). This allowed

separating the fundamental objectives from the

means objectives. To do this, for each objective, we

asked “Why is this objective important in the

decision context?” (Keeney, 2007, p. 114) If the

response to the question identified that the objective

was important because of its implications for some

other objective, this was a means objective. If the

response was that the objective was one of the

essential reasons for interest in the situation, this was

a candidate for a fundamental objective.

Figure 1 presents the objectives hierarchy, where

the fundamental objectives (in the grey boxes) were

used to build the multi-criteria evaluation model.

Table 1 summarizes the selected objectives and

their attributes for local sustainable energy planning.

Observe that the attributes (that are also known as

descriptors of performance; see Bana e Costa et al.,

2008) are used to measure the extent to which the

objectives are achieved by alternative sets of actions

(Keeney, 2007).

Figure 1: Objectives hierarchy.

Table 1: Objectives and attributes.

Objectives Attributes

O1 Reduce GHG emissions

Tonnes of CO

equivalent reduced

Reduce air pollution from

transport

Tonnes of NO

emissions

reduced

Maximize employment

benefits

Net jobs gained

Improve long-term energy

independence

Tonnes of oil equivalent

of imported fossil fuels

reduced

Minimize the negative

impacts on human health

caused by noise from

transport

Number of people that

benefit from noise levels

reduction

Minimize the negative

impacts on human health

by improving the thermal

comfort conditions of

homes and offices

Tonnes of oil equivalent

(final energy) reduced

for space heating and

cooling

Minimize the negative

impacts on human health

caused by automobile

dependence

Number of passenger-km

shifting from passenger

cars to public transit,

walking and cycling

O8 Reduce the energy bill

Euros saved per

household per year

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2.2 Identification of Actions

and Generation of Alternatives

The identification of actions was based on an

extended literature review, having into account three

selection criteria:

 Local authority actions – the main focus of this

work was on the demand side, because it is

where the local authority can have a greater

power to act. The areas where the local

authority has no control of intervention were

excluded from this work, such as large-scale

energy supply and industry.

 Technical actions – leaving the policy actions

or promotion mechanisms outside of the scope

of this work.

 Community-scale actions – the focus of this

work is community-wide and Government

operations only.

Alternatives represent means of achieving the

objectives. They usually are a mutually exclusive set

of means among which a choice is possible. In

general, to be allowed not to choose is also

considered an alternative (Zeleny, 1982, chap. 4).

In this case, alternatives are combinations of 26

actions (10 actions in the households sector, nine

actions in the services sector, and seven actions in

the transport sector) in six different degrees of

implementation. Making all the possible

combinations between the actions and the possible

degrees of implementation would result in a very

large number of alternatives (precisely, 6

Although, it would be possible to generate them with

the help of a computer-based decision support

system it would be impractical due to the existence

of synergies between actions that needed to be

analysed. Therefore, it was decided to adopt a

pragmatic approach for the generation of alternatives

based upon a strategy-generation table procedure

(Kirkwood, 1997; Matheson and Matheson, 1998).

The actions and their degrees of implementation

were combined directly in the energy model

implemented in a Microsoft Excel spreadsheet,

allowing in this way to account for the synergetic

effects. The rows of the table represent the different

degrees of implementation for the different actions

that are presented in columns. The only exception is

the first row (named “Maintain”) that means “do not

implement the action”. The user builds an alternative

by selecting one cell from each of the 26 columns.

Figure 2 shows a screenshot of the spreadsheet

where the degrees of implementation of the 10

actions of the sector of households for alternative 1

are shown. At the end, the user can visualise if the

selected combination of actions/degrees of

implementation respect the constraint of GHG

emissions reduction (in this case a minimum level of

20% is required). If not, the user should redefine the

selection of actions/degrees of implementation in

order to accomplish the target reductions in GHG

emissions.

The adoption of the strategy-generation table

approach for the generation of alternatives provides

a structured procedure to sort out alternatives that

the user considers to make sense to analyse in more

detail. The energy model allowed the creation of five

alternatives that were subjected to a multi-criteria

evaluation process.

2.3 Involvement of the Local Actors

The involvement of local actors took place in two

stages. First, the process of identification of the

Figure 2: The strategy-generation table.

A MULTI-CRITERIA APPROACH TO LOCAL ENERGY PLANNING - The Case of Barreiro Municipality

315

Figure 3: Reference levels “Good” and “Neutral” defined on each attribute.

objectives had the participation of the City

Councilman for Environment of Barreiro City

Council and the director of the energy agency

(S.Energia). This process also involved the

participation of local actors from other

municipalities in Portugal. Second, a decision

conference was held with the participation of two

technicians from the Environmental Sustainability

Division of Barreiro City Council and two

technicians and the director of the energy agency.

The actors involved represented the points of view

of those two organizations concerning the

implementation of the sustainable energy action

plan.

During the decision conference, a facilitator

guided the decision process helped by an analyst.

The facilitator started by remembering the model

structure created until then, namely by presenting

the objectives and their attributes. The facilitator

also had the task of stimulating the group discussion

concerning the development of the multi-criteria

value model without contributing to the content of

discussion (Phillips, 2007). The analyst used the

decision support system M-MACBETH (www.m-

macbeth.com) to display on-the-spot the model

being developed.

3 BUILDING THE

MULTI-CRITERIA

EVALUATION MODEL FOR

THE MUNICIPALITY OF

BARREIRO

3.1 Building a Value Function for Each

Objective

The objectives and attributes presented in table 1

were used in the model of the municipality of

Barreiro after having the agreement from the local

actors involved. The exception was in the objective

“Reduce noise impacts from transport”, which was

dropped from the model due to lack of data.

For each attribute the group was asked to define

a “neutral” reference level; this means to define a

performance that would be neither positive nor

negative in the linked objective. The group was also

asked to define a “good” reference level for each

attribute, i.e. a performance level considered

significantly attractive in the light of the objective.

Figure 3 shows the performance reference levels

defined upon each attribute.

For each attribute the group was asked to define

a “neutral” reference level; this means to define a

performance that would be neither positive nor

negative in the linked objective. The group was also

asked to define a “good” reference level for each

attribute, i.e. a performance level considered

significantly attractive in the light of the objective.

Tonnesof

CO2eq.

emissions

reduced

Tonnesof

Nox

emissions

reduced

Netjobs

gained

Toeof

imported

fossilfuels

reduced

Toeoffinalenergy

reducedforspace

heatingandcooling

ofhomesand

offices

NumberofPkm

shiftingfrom

passengercarsto

publictransit,

walkingandcycling

Euros

savedper

household

peryear

20%

tCO

2

eq.

tNO

Numbe r toe

toe millionpkm €/household/year

30%

200 150

27000

3000 600 500

QualityofLifeEnvironment EconomicDevelopment

Good

Neutral

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Figure 3 shows the performance reference levels

defined upon each attribute.

Afterwards, more levels were added to the

attributes such that each attribute had four

performance levels equally spaced in the attribute

scale.. The group was then asked to judge the

differences in attractiveness between each two levels

of performance, choosing one of the MACBETH

semantic categories: very weak, weak, moderate,

strong, or extreme. For each objective, the process

was initiated by asking the difference of

attractiveness of changing from the “neutral”

performance level to the “good” performance level

and followed by asking the difference between each

two of the other levels.

Figure 4: MACBETH judgements matrix for the objective

“Maximize employment benefits”.

Figure 5: Value functions for the objectives.

Figure 4 presents the group judgments matrix for the

objective “Maximize employment benefits”.The M-

MACBETH decision support system proposes a

numerical value scale based on the set of qualitative

judgments inputted in the matrix of judgments

(figure 4) using linear programming (see details in

Bana e Costa et al., 2011). The numerical scale is

anchored on the two predefined reference levels

(neutral and good) to which were assigned the scores

0 and 100. The proposed MACBETH scale is then

subjected to group analysis and discussion in terms

of proportions of the resulting scale intervals. In the

case of Barreiro, the group decided to make minor

scale adjustments on the value scales of some

objectives. Figure 5 represents the value functions

obtained for the objectives after the group

discussion.

3.2 Weighting the Objectives

The relative weights for the seven objectives were

defined using the MACBETH weighting procedure.

The group was first asked to rank the “neutral-good”

swings by their overall attractiveness. The facilitator

started by asking the question: “From the seven

objectives, if you could choose just one objective to

change from a neutral performance to a good

performance which objective would you choose?”

The questioning procedure continued till the final

ranking of “neutral-good” swings was achieved.

During the MACBETH questioning procedure to fill

in the weighting judgements matrix, the group

engaged in a deeper thinking and discussion about the

relative importance of the “neutral-good” swings and

decided to change the ranking of the second, third and

fourth most attractive swings. The final ranking of the

“neutral-good” swings is presented in figure 6.

Figure 6: Final ranking of the swings.

The next step consisted in asking the group to judge

the overall attractiveness of each “neutral-good”

swing, which allowed filling in the last

Tonnes CO

eq. reduced (%) Tonnes of NO

reduced Net jobs gained

Toe of imported fossil

fuels reduced

Toe of final energy reduced

for space heating and cooling

of homes and offices

Number of Pkm shifting

from passenger cars to

public transit, walking

and cycling

Euros saved per

household per year

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Figure 7: The MACBETH weighting matrix.

Figure 9: Overall benefit scores of the alternatives.

column of the MACBETH matrix in figure 7.

Subsequently, the group was asked to pairwise

compare the most attractive swing to the second

most attractive. The pairwise comparison continued

between the most attractive swing and each of the

other swings till filling in the first row of the

MACBETH matrix (figure 7). Afterwards,

judgments concerning the comparison of each two

consecutive swings were also made and the

questioning procedure stopped. It was not necessary

to ask more judgments, once MACBETH is able to

create the weighting scale with the information

already present in the matrix of judgments (see

figure 7).

Figure 8: Weighting scale obtained for the objectives

presented in table 1.

Figure 8 presents the weighting scale proposed

by M-MACBETH. The facilitator asked the group to

check the resulting weights in order to validate them.

For example, the facilitator asked if the “neutral-

good” swing on objective “GHG emissions

reduction potential” is worth four times the “neutral-

good” swing on objective “Maximize employment

benefits” (note that the weights of these objectives

are 16% and 4%, respectively), and also if the

“neutral-good” swing on objective “Improve long-

term energy independence” is worth 1.9 times the

neutral-good swing on objective “Minimize the

negative impacts on human health by improving the

thermal comfort conditions of homes and offices”,

which the group agreed.

3.3 Aggregation and Robustness

Analysis

The performances of the six alternatives upon each

of the objectives were determined in the energy

model developed in the spreadsheet and were then

inputted in M-MACBETH. The decision support

system transformed these performances into benefit

scores, using the value functions previously built,

and determined an overall benefit score for each

alternative by weighted summation of its value

scores. At the end of the decision conference, it was

possible to visualize the overall benefit scores for

the six alternative sustainable energy action plans

created (see column “Overall” in figure 9).

The alternative A4 ranked first with 143.83

benefit units and alternative A3 ranked second with

128.25 benefit units. Both A4 and A3 obtained

overall scores higher than that of a hypothetical

alternative “Good all over”, which shows that they

are very attractive alternatives. The remaining

O4 O8 O2 O1 O7 O6 O3

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Figure 10: Robustness analysis.

alternatives also had positive overall scores, i.e.

higher scores than that of a hypothetical alternative

“Neutral all over”, which means that all of them are

globally attractive.

Given the hesitations the group had during the

weighting process it is wise to analyze if A4 would

continue to rank first when the weights are modified.

A robustness analysis made with M-MACBETH

considering variations of ±3% on the weights of all

objectives revealed that A4 continues to be the most

attractive alternative from the set of six alternatives

evaluated (figure 10). Observe that a green cross in a

cell of figure 10 means that the alternative in row

additively dominates the alternative in column (in

this case the dominance relationship depends on the

constraints defined upon the parameters of the

additive model), and a red triangle indicates

dominance in the classic sense (the alternative in

row is always preferred to the alternative in column

irrespectively of the constraints defined upon the

parameters of the model).

4 CONCLUSIONS

This paper had a particular focus on the multi-

criteria evaluation process and its application to the

municipality of Barreiro in the context of energy

planning. The multi-criteria evaluation model

presented is part of a comprehensive decision

support methodology which includes also an

extensive work on energy modelling of the local

energy system. The energy modelling was developed

in Microsoft Excel and has several features

necessary to the multi-criteria evaluation, namely the

process of generating alternatives and the

quantification of the performances of the alternatives

in each objective (which are required inputs to the

additive model developed with M-MACBETH). We

underline that the developed model not only allowed

to identify which alternative performed best out of

six alternatives, but also allowed to verify that it is a

very attractive alternative by comparing its overall

benefit score with those of the two reference profiles

– “good all over” and “neutral all over”. Indeed, in

this context, selecting the best alternative of a set of

unattractive alternatives would not be a wise

decision to make.

With respect to the multi-criteria evaluation

process, it is possible to conclude that this is a

suitable tool and with great potentiality to be applied

to local energy planning processes. In particular, it

promotes the participation of several local actors and

stimulates thinking and discussion about the key

issues for energy planning in their contexts. The

decision conference process and the M-MACBETH

software used were of valuable help to implement

the multi-criteria evaluation.

The development of the methodology had in

mind its replication for any local context, as so it is

expected that more municipalities will adopt this

common methodological framework in the

elaboration of their sustainable energy action plans.

Future research will still cover the assessment of

investment costs for each alternative to be traded-off

with the overall benefits of the alternatives.

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