Multi Objective Assessment of Rural Electrification in Remote Areas With Poverty Considerations 2009 Energy Policy

8/7/2019 Multi Objective Assessment of Rural Electrification in Remote Areas With Poverty Considerations 2009 Energy Policy

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Multi-objective assessment of rural electrification in remote areas withpoverty considerations

Diego Silva, Toshihiko Nakata

Department of Management Science and Technology, Graduate School of Engineering, Tohoku University, Aoba-yama 6-6-11-815, Sendai 980-8579, Japan

a r t i c l e i n f o

Article history:

Received 28 July 2008

Accepted 30 March 2009Available online 12 May 2009

Keywords:

Renewable energy system

Energy access

Multi-objective assessment

a b s t r a c t

Rural electrification with renewable energy technologies (RETs) offers several benefits to remote areas

where diesel generation is unsuitable due to fuel supply constraints. Such benefits include

environmental and social aspects, which are linked to energy access and poverty reduction in less-favored areas of developing countries. In this case, multi-objective methods are suitable tools for

planning in rural areas. In this study, assessment of rural electrification with renewable energy systems

is conducted by means of goal programming towards fuel substitution. The approach showed that, in

the Non-Interconnected Zones of Colombia, substitution of traditional biomass with an electrification

scheme using renewable energy sources provides significant environmental benefits, measured as land

use and avoided emissions, as well as higher employment generation rates than diesel generation

schemes. Nevertheless, fuel substitution is constrained by the elevated cost of electricity compared to

traditional biomass, which raises households energy expenditures between twofold to five times higher

values. The present approach, yet wide in scope, is still limited for quantifying the impact of energy

access improvements on poverty reduction, as well as for the assessment of energy systems technical

feasibility.

& 2009 Elsevier Ltd. All rights reserved.

1. Introduction

The Millennium Development Goals (MDGs), an initiative of

the UN looking forward the achievement of eight global targets by

nations by the year 2015, placed first on the list the reduction of

poverty by half by the year 2015 (UN, 2000). The achievement of

this goal within rural areas of developing countries is highly

correlated with energy access, a fact pointed out by the United

Nations in the UN Millennium Declaration and the International

Energy Agency in its World Energy Outlook, as well as by many

other organizations around the world (IEA, 2002). Improvement of

energy access conditions can be associated with two main

aspects: increase of electrification rates and substitution of

traditional biomass. As of year 2000, there were over 1.6 billionpeople, with no access to electricity. More than 99% of these

people come from developing countries and four out of five live in

rural areas, the majority of them living under the poverty line. In

addition, people relying on traditional biomass for space heating

and cooking reaches 2.4 billion (IEA, 2004).

Among the rural population, people living in remote areas are

especially vulnerable. Many of these areas have poor road and

public utilities infrastructures, but possess unexploited renewable

resources. Thus, decentralized electrification schemes with re-

newable energy technologies (RETs) based on local resources are a

suitable solution to satisfy energy needs. This fact contrasts with

actual unsustainable electrification schemes with diesel genera-

tion or extension of the electric grid. In spite of the relevance of

RETs for energy supply in remote rural areas, low diffusion rates of

this kind of technologies and failure of technology transfer

programs for rural electrification are common in developing

countries (Department of Economic and Social AffairsUnited

Nations, 2001; Green, 1999).

The reason why RETs have not been successful in rural areas so

far, has been attributed in part to the lack of integrated evaluation

approaches in rural electrification planning. Such approachesallow the inclusion of economic, social and environmental aspects

of technologies into the planning process, which is fundamental to

address poverty as a multi-dimensional issue. They also permit

addressing certain barriers to the diffusion of RETs in rural areas of

developing countries (Painuly, 2001). Among the integrated

evaluation approaches existent, multi-objective decision-making

(MODM) methods like goal programming (GP) are gaining

popularity in energy planning issues. MODM methods permit

the inclusion of multiple and often conflicting targets into

optimization schemes. With these methods it is also possible to

incorporate factors that cannot be expressed in comparable

units, a common limitation when addressing poverty issues in

ARTICLE IN PRESS

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0301-4215/$- see front matter& 2009 Elsevier Ltd. All rights reserved.

doi:10.1016/j.enpol.2009.03.060

Corresponding author. Tel./fax: +8122 7957004.

E-mail addresses: [email protected] (D. Silva),

[email protected] (T. Nakata).

Energy Policy 37 (2009) 30963108
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technology evaluation frameworks (Pohekar and Ramachandran,

2004). Nevertheless, research examples deploying MODM meth-

ods for energy system analysis focusing in rural planning

addressing poverty issues are scarce. Furthermore, there are few

studies dealing with modeling of optimum mix of energy

resources using a decentralized energy approach (Hiremath et

al., 2007).

The purpose of the research is to study the introduction of

renewable energy systems as a possible alternative in the futurefor rural electrification towards the substitution of traditional

biomass in developing countries by means of multi-objective

approach including multiple aspects. The integrated evaluation of

the system is used to highlight the multiple benefits offered by

RETs in remote rural areas. Goal programming is applied to assess

energy system performance with respect to electricity generation

cost, employment generation, land use, and avoided CO2 emis-

sions for the case of the Non-Interconnected Zones (NIZ) of

Colombia. The introduction of electricity for cooking may be

considered unsuitable for rural areas of developing countries, and

other alternatives such as improved cooking stoves may be more

appropriate in the short term. However, the simultaneous

inclusion of different aspects in the assessment process by means

of the application of the MODM methodology may show the

benefits from the use of electricity from renewables in the long

term overlooked by other approaches.

2. Energy access and poverty alleviation

The concept of poverty has evolved as a multi-dimensional

issue that, in addition of low income level, it is linked to several

aspects of human life, like deficient health levels and failure to

obtain access to medical assistance and safe water and food

provision. Thus, poverty alleviation can be interpreted as the

improvement of living conditions towards the achievement of

minimum basic human needs, as it has been outlined in the

targets set within the MDGs. In spite that energy is not explicitlymentioned in the MDGs and is not always considered a basic need,

energy is necessary to conduct human activities and provides

basic services for human life such as heat for cooking, space

heating and illumination. Moreover, energy provision enhances

the productivity of agricultural and industrial activities that, in

the end, may translate in higher income opportunities. Based on

the above, it has been acknowledged that access to reliable and

affordable energy plays an essential role in the achievement of the

MDGs (Modi et al., 2005). Accordingly, a minimum level of energy

consumption per capita can be associated to a condition above the

poverty line (Spreng, 2005).

Improvement of energy access conditions requires not only the

attainment of a reliable energy supply but also the transition to

modern energy forms like LPG and electricity. Traditional fuels,such as charcoal, straw, wood, agricultural wastes and dung,

which are termed traditional biomass, are generally not

commercially traded and are used extensively and inefficiently

by the poor, resulting in negative impacts on the people and the

environment. For example, people in rural areas of developing

countries, especially women and children, spend much of their

time for collection of firewood. Moreover, burning of biomass in

inefficient stoves is a major cause of indoor smoke pollution,

which claims each year the lives of over 1.6 million women and

children according to the World Health Organization (IEA, 2004).

Currently, in rural areas of the world more than 1.3 billion people

have no access to electricity and more than 2.1 billion people rely

on the use of traditional fuels to cover energy needs (IEA, 2004,

2006). Therefore, substitution of traditional biomass represents an

important aspect of energy access, in particular for rural areas in

developing countries.

The relationship between energy access and poverty in the

energy planning literature is scarcely addressed. Most of the

studies have approached the issue founded in the concept of

energy poverty, which describes the condition where people

cannot afford access to a sustainable energy supply. Pachauri et al.

developed the energy access-consumption matrix, a two-

dimensional indicator to measure energy poverty in the Indianhousehold sector for the period 19832000, incorporating non-

commercial energy sources and differentiating the population

according to the income level and to the type of energy source as

well as its consumed amount (Pachauri et al., 2004). Kemmler

et al. worked on the definition of indicators capable to describe

poverty and sustainable development in a multi-dimensional way

through energy consumption data, proposing the access-adjusted

useful energy as a suitable indicator (Kemmler and Spreng, 2007).

Kanagawa et al. analyzed the impacts of energy access for cooking

in rural households by designing an energy-economic model

introducing the opportunity cost associated with wood collection

and the exposure to particulate matter (Kanagawa and Nakata,

2007). The same authors extended their analysis to cover the

impact of lighting in literacy rates (Kanagawa and Nakata, 2008).

In the case of remote rural areas of developing countries,

improvement of energy access conditions by means of rural

electrification and fuel substitution is directly related to the

efficient utilization of local energy resources with RETs. Although

there are several barriers to the successful introduction of these

technologies, some of these barriers can be overcome highlighting

the benefits provided by RETs to rural communities in comparison

to conventional electrification schemes based on diesel genera-

tion. To this end, MODM methods offer a convenient approach for

assessment of technologies given that they allow the simulta-

neous inclusion of several attributes even with different units.

3. Multi-objective approach for assessment of rural

electrification

An MODM method is deployed in order to evaluate renewable

energy systems using local energy resources for rural electrifica-

tion and substitution of traditional biomass in localities of

Colombia without access to the electricity grid, referred to as

NIZ. The energy system for electrification with RETs is designed to

meet two targets. First, to satisfy electricity needs according to the

demand rates observed in the NIZ, with local renewable resources

instead of diesel generation, which is currently the main supply

alternative in the target area. The second purpose of the energy

system is to extend electricity supply in order to cover energy

demand for cooking purposes in households and to substitute

with electric stoves traditional stoves of low conversion efficiency

using firewood. This second target is referred to as fuel substitu-tion throughout the paper.

3.1. The Non-Interconnected Zones of Colombia

The NIZ of Colombia comprehends remote areas outside the

national electric grid, or National Interconnected System (NIS).

Most of the regions within the NIZ have the lowest GDP per capita

levels in the country. The NIZ, depicted in Fig. 1, extend over

756,531 km2, which is nearly 66% of countrys territory surface.

The population reaches 1,524,304, accounting for only 4% of

countrys population, and is highly dispersed as there are

approximately 2 inhabitants/km2, while countrys average is

38 inhabitants/km2. Around 88% of people in the NIZ live in

rural areas. Although average electrification rates of Colombia

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D. Silva, T. Nakata / Energy Policy 37 (2009) 30963108 3097


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were over 90% as for the year 2003 (Deparatmento Nacional de

Planeacion, 2007), almost two thirds of people in NIZ have no

access to electricity. The average electricity price is twice the price

charged in the NIS, with only half of service hours. Diesel

generation plants supplies almost all the electricity, and only a

few small hydro power plants and PV systems operate in the NIZ.

Fuels are over 60% more expensive than the capitals price due to

restrictions on their transportation and security issues. Wood and

LPG are the most important energy fuels for cooking, with a userate of 41% and 35% respectively (Unidad de Planeacion Minero

Energetica, 2000a; Zapata and Bayona, 2000). Given the

remoteness of localities and the extensive availability of

renewable resources within the NIZ, RETs are a primary

potential solution to support their development. The Unidad de

Planeacion Minero Energetica (UPME), institution in charge of

national energy planning issues in Colombia, has referred in this

regard in the national energy plan (Unidad de Planeacion Minero

Energetica, 2003). Nevertheless, inexistence of policies or

regulations encouraging the promotion of renewable energies

has raised the necessity to revise methodologies for assessment of

technologies based only on costs, so as to include environmental

and social factors (Ruiz and Rodrguez-Padilla, 2006). Table 1

summarizes the characteristics of the NIZ. Villages are categorized

into three groups of localities according to the size of population

as large, medium and small, following the typology proposed by

the UPME.

The importance and application of MODM methods to aid in

rural energy planning issues in Colombia have been referenced in

previous researches (Henao Piza, 2004). The UPME developed an

information and analysis tool to support the decision makers in

energy planning in the NIZ considering an integral analysis, using

indicators to estimate the performance of alternatives in several

aspects such as costs, level of adoption of technologies andenvironmental factors (Unidad de Planeacion Minero Energetica,

2000b; Zapata and Bayona, 2000). The result of this study foresees

that diesel generation is the most suitable technology for

supplying electricity in the majority of NIZ localities, and that

RETs are suitable only for localities with less than 200 inhabitants

(Zapata and Bayona, 2000). In addition, the evaluation of

appropriate rural electrification alternatives towards improve-

ment of communitys livelihoods within the NIZ has been

analyzed using a multi-criteria approach (Cherni et al., 2007).

The authors suggest that a micro-hydro power plant and a hybrid

system combining this alternative with a diesel generator are the

most appropriate energy generation options for a remote rural

area of 400 inhabitants. An initial insight of the use of a multiple

objective approach in the analysis of renewable energy systems

has been given for rural electrification in the NIZ (Silva and

Nakata, 2008).

3.2. Renewable energy system for the NIZ

The proposed energy system is designed considering the three

locality types outlined above, in accordance with the character-

ization made by the UPME. The energy system, presented in Fig. 2,

is a representation of the elements involved in the supply and

consumption of energy in a single locality. This system is

composed by three main groups of elements, namely the energy

resources representing the sources of primary energy; the energy

conversion technologies symbolizing the power plants for the

supply of electricity; and energy demand sectors making use ofthe electricity supplied in different devices in order to satisfy

certain needs.

Renewable energy resources which can be harnessed locally in

NIZ are considered in contrast to diesel fuel. Distribution of fuels

within the NIZ is highly constrained. This results in high fuel

prices which rises the costs of electricity supply, since in these

areas the service is almost totally supplied by diesel generators

(Unidad de Planeacion Minero Energetica, 2000a). Therefore

utilization of local resources is fundamental to boost sustain-

ability of electricity supply. Energy resources geographical

distribution is not included in the analysis, and average avail-

ARTICLE IN PRESS

Fig. 1. The Non-Interconnected Zones of Colombia.

Table 1

Characterization of the NIZ by localities.

Large Medium Small

Population range 4500 200500 o200

Population per locality (assumed) 1000 500 200

Total population 344,526 145,066 38,128

Electricity demand per house (kWh/month/household) 68 25 23

Total electricity demand (GWh/yr) 83.7 11.4 2.8

Firewood demand for cooking (kWh/month/household) 1932 2286 1189

Total cooking energy demand (GWh/yr)a 239 104 14

Total final energy demand (GWh/yr)b 323 115 17

Share of energy for cooking in total energy demand (%) 74 90 84

Calculated based on data from Unidad de Planeacion Minero Energetica (2000a).a Conversion efficiency of 10% assumed, LHV for firewood 16.7MJ/kg.b

Sum of electricity demand and cooking energy demand.

D. Silva, T. Nakata / Energy Policy 37 (2009) 309631083098


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ability values corresponding to the NIZ are used (Silva and Nakata,2008).

Electricity conversion technologies under consideration corre-

spond to different small-scale power plants, namely a steam

turbine coupled with direct combustion of firewood (Dir.Comb.-

Firewood), a steam turbine coupled with direct combustion of

organic wastes (Dir.Comb.Waste), a gas engine using biogas

produced by anaerobic digestion of organic wastes (Dig.Biogas-

Comb.), solar photovoltaic (PV) panels, windmills (Wind), and

small hydro power plants (Hydro). These technologies are

combined to form a single energy supply unit for a single locality.

They, together with the energy resources employed by them, are

designated as the renewable energy system. A diesel generation

scheme, composed by a diesel generator using diesel fuel, is used

to establish the baseline of comparison for evaluation of the

renewable energy systems performance with respect to multiple

attributes. The main features of the technologies are summarized

in Table 2.

Energy demand includes the energy for cooking and for electric

appliances in the residential sector, and energy for electric

appliances in other sectors, namely industrial, commercial and

institutional sectors. Energy demand for cooking is approximated

to the final energy quantities resulting from the combustion of

firewood in traditional stoves with 10% energy conversionefficiency, taking into account current consumption levels of this

fuel in the NIZ. Energy for other purposes corresponds to average

electricity consumption levels observed in all sectors of the NIZ.

For purposes of the analysis each locality type is considered

homogeneous, neglecting any differences by income or energy

consumption levels among the population. The population under

study corresponds to human groups living together in small towns

or villages excluding peasants living in farms.

3.3. Case setting

The study considers the baseline and the two cases explained

below:

(a) Baseline for comparison: energy for cooking purposes is

supplied by traditional biomass and electricity demand in all

sectors, equivalent to actual consumption rates in the NIZ, is

supplied by a diesel generation scheme.

(b) No fuel substitution (NFS): energy for cooking purposes is

supplied by traditional biomass and electricity demand is

supplied by the renewable energy system.

(c) Total fuel substitution (TFS): traditional stoves are replaced by

electric stoves and electricity is supplied by the renewable

energy system, including demand for cooking.

3.4. Integrated assessment of the renewable energy system

Performance of the rural energy system is evaluated with

respect to economic, social and environmental aspects, by means

of four attributes.

(a) Electricity generation cost: given that low income of population

may prevent the introduction of the energy system, cost of

electricity supplied can be used as a parameter for the need of

subsidies or other mechanisms to adjust electricity prices.

(b) Employment generation: jobs needed for operation of the

renewable energy system are an income opportunity to some

of the inhabitants of the NIZ; thus, employment generation is

used to relate system introduction with poverty alleviation.

(c) Land use: construction of power plants may represent a

negative impact on the local environment of remote ruralareas in developing countries, since it may interfere with

other important uses for land like agriculture and habitat

conservation.

(d) Avoided emissions: the amount of emissions of CO2 avoided by

the displacement of diesel generation electrification schemes

serves to highlight one characteristic advantage of introducing

renewable energy systems; avoided emissions can be used as

a factor to promote environmental acceptability of renewable

energy systems based on local resources.

The integrated evaluation of the renewable energy system

considers the benefits granted in these four attributes by systems

introduction. Benefits are estimated as the percentage deviation

with respect to a goal value set to each attribute, by means of the

ARTICLE IN PRESS

Outcomes of the analysis

Energy access in remote rural areas

Feasibility of fuel substitution

with local energy resources

(No fuel substitution)(Total fuel substitution)

ElectrificationElectrification &

fuel substitution

Target area

Non Interconnected Zones of Colombia

Type 1

(> 500 people)

Type 2

(200-500 people)

Type 3

(< 200 people)

Technology alternatives

Diesel generation

(used as basis

for comparison)

Renewable energy system

(energy supply with

local resources)

Alternative for rural electrification

Methodology

Goal programming

(four goals, four priority structures)

Benefits

(deviation from goal's values)

System's configuration

System's performance

Fig. 2. Energy system for rural areas of Colombia.



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following equation:

bj gj Aj

gj

! 100; j felectricity cost; land useg (1)

bj Aj gj

gj

! 100; j femployment generation; av: emissionsg

(2)

where j is the goal, bj is the benefit with respect to attribute j, Aj is

the performance of renewable energy system with respect to

attribute j and gj is the goal with respect to attribute to attribute j.Goals values and their meaning are explained in the following

subsection. The integrated assessment of the system includes the

design of the energy system. For this purpose a specific MODM

method called goal programming is utilized. Different to other

MODM methods used in energy planning which can only consider

a limited number of combinations of technologies defined by the

decision maker with anticipation, such as the analytical hierarchy

process and many other multi-criteria methods, GP allows for the

estimation of an optimal mix of technologies, indicated by the

system configuration, in a continuous range of alternatives. A

graphic representation of the multi-objective approach proposed

in the study is presented in Fig. 3.

3.5. Goal programming formulation

GP is an MODM method very close to optimization methods,

and is considered an extension of linear programming (LP).1 In

addition to an objective function and a set of inequalities

representing the constraints of the problem, in GP formulations

functions for multiple objectives with respect to different

attributes are introduced and formulated as goal constraints.

The right-hand side values in these inequalities correspond to

constant target values or goals. Each goal constraint equation

involves a pair of deviation variables which indicate the deviation

of the goal constraints with respect to their respective goals. The

objective function in GP is to minimize these deviations

(Schneiderjans, 1995). The objective function can be expressed

as a weighted sum or as an order of preferences. The latter case,

known as a preemptive GP, refers to a GP formulation where the

optimization procedure is performed minimizing deviation vari-

ables with respect to each attribute in the sequence specified by

the order of preferences in a priority structure. In the study

preemptive GP is applied in order to obtain the optimal

configuration of the system, using the electricity to be supplied

by each technology as the decision variables. The order of

preferences considered is presented in a further subsection.

Equations of the GP formulation deployed in the study are

presented in the Appendix A.

GP has been used in rural energy planning studies looking at

energy resource allocation at local and regional level (Rama-

nathan and Ganesh, 1995; Kanniappan and Ramachandran, 2000)

and at country level (Mezher et al., 1998). Calculations were

performed with LINDOs software. This is a computer tool

commonly used for solving linear programming models. Its

application has been referenced for the optimum utilization of

renewable energy sources in a remote area (Akella et al., 2007).

3.6. Goal constraints and goals

In the study goals represent evaluation guidelines for theperformance of renewable energy systems. Performance values of

the baseline energy system are used as goals for the formulation.

Models goal constraints and goal values used for this study are

explained below.

(a) Electricity generation cost (US$/kWh): this goal constraint looks

for an electricity generation cost value lower or at most equal

to that of diesel generation, which translates in the mini-

mization of the overachievement of the electricity costs goal

value (US$0.136/kWh for large localities, US$0.209/kWh for

medium localities and US$0.216/kWh for small localities).

Economic performance of the system is calculated based on

operation and maintenance costs, capital cost, and resource

cost, considering a life time of 20 years for technologies and a

ARTICLE IN PRESS

Table 2

Main features of energy conversion technologies.

Technology Diesel Dir.comb. firewood Dir.comb. waste Dig.biogas comb. PV Wind Hydro

Scale (kW)b 30/75/150a 32/79/182 1/3/7 1/2/4 22/54/124 2/6/13 11/26/61

Efficiency (%) 30a 28c 28c 35d 11.3c 45d 80d

Capital cost (US$/kWp)a 300 3000 3000 500 8000 3200 4500

O&M cost (USb/kWh) 1.9/5.8/6.1n 4.74c 4.74c 5.5d 0.15c 1.0c 1.5c

Employees (jobs/GW)f 0.83/0.27/0.25o 1 1 6 2.7 2 1.4

Land use (m2

/kW) 182h

45.1c,i

45.1c,i

144j

48.5c,k

267.7e,l

50m

Emissions (kg-CO2/kWh)g 0.262 0.273 0.273 0.305 0 0 0

a Unidad de Planeacion Minero Energetica (2000a).b Plant size calculated according to resource availability and electricity demand.c EPRI and US Department of Energy (1997).d IEA (1997).e Micro-grid verification test facilities, Tokyo Gas.f For operation and maintenance, Moreno and Lopez (2008).g For plant operation, Mezher et al. (1998).h Calculated based on land required for fuel storage (Unidad de Planeacion Minero Energetica, 2000a).i A scaling factor of 5 is assumed.j Iwate biogas plant, Iwate prefecture, Japan.k Device area is 20 m2.l Spacing between windmills equal to rotor diameter (5.5 m).m Assumed value.n Equivalent to 10% of capital cost.o

Calculated based on value from Mezher et al. (1998).

1 Linear programming (LP): planning of activities to obtain an optimal result,

its application generally involves the problem of allocating limited resources to

competing activities in a best (i.e. optimal) way (Hillier and Lieberman, 2001).

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10% discount rate. The cost of electric stoves is omitted, and it

is assumed that households will purchase these devices

independently. Same costs for transmission and distribution

of electricity are considered for all technologies and, thus, also

disregarded in the analysis.

(b) Employment generation (jobs/kWh): seek an employment level

at least equal to or higher than that of diesel generation,

equivalent to 5.130 107 jobs/kWh according to Mezher et al.

(1998). Employment generation levels correspond to values

estimated by Moreno and Lopez (2008) for operation and

maintenance of electricity generation plants and are utilized

irrespective of plant scale, disregarding possible numericaldifferences for low-scale plants. These values are only mean-

ingful as relative quantities to differentiate employment

generation levels among the technologies being considered.

(c) Land use (m2/kWh/yr): achieve a plant area no greater than the

required for the storage of the amount of diesel needed for the

supply of electricity (0.0415 m2/kWh/yr). This attribute mea-

sures the efficient use of land and it is calculated based on

land requirements for plant installation.

(d) Avoided CO2 emissions (kg-CO2/kWh): avoid a quantity of CO2emissions equivalent to the emissions produced by a diesel

generation scheme (0.36kg-CO2/kWh). Emissions are calcu-

lated with respect to CO2 emissions generated by a diesel

generation plant. In addition to emissions contributed by

system operation those stemming from the deforestation

associated with land use requirements are also accounted,

measured based on the average rate of CO2 sequestration per

square meter in tropical zones. Equivalent CO2 emissions due

to methane production from the decay of organic wastes are

taken into account for direct combustion of waste and biogas

technologies.

3.7. Constraints

The models constraints are the total electricity demand andthe maximum resource availability in each NIZ locality type. Data

regarding the electricity demand and the availability of energy

resources are listed in Table 3.

3.8. Order of preferences

The configuration and outcomes respect to the attributes of the

energy systems obtained are analyzed according to four priority

structures, listed in Table 4, each one describing a different order

of preferences set for the objective functions. They represent the

possible views of the decision maker towards the assessment of

rural electrification projects. The first two priority structures serve

to assess whether there is a conflict between economic

performance and employment generation. The latter two

ARTICLE IN PRESS

Electricity

distribution

Small -Hydro

Dir.Comb .Firewood

Windmill

Dir.Comb .

Waste

PV

Organic

Resid . Waste

Wind

resource

Solar

resource

Hydro

resource

Firewood

resource

Dig.Biogas

Comb .

Org.Resid .Waste : organic residential waste

Dir .Comb . : direct combustion

Dig .BiogasComb .: anaerobic digestion and combustion of biogas

Cooking

Electricity

demand

Residential

Electric

appliances

Electric

stove

Traditional

stove

Energy

resourcesEnergy demand

Energy using

devices

Energy

conversion

technologies

Electricity

demand

Electric

appliances

Other sectors

Diesel

generationDiesel fuel

RENEWABLE ENERGY SYSTEM

DIESEL GENERATION SCHEME

Fig. 3. Multi-objective approach for energy access issues in rural areas.



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US$0.158/kWh. This occurs as a consequence of the introduction

of lower-performance technologies in the system configuration at

the expense of the depletion of Wind and Hydro resources. Fuel

substitution requires the introduction of direct combustion of

firewood (Dir.Comb.Firewood) but still with small shares, below

30% of the total electricity supply.

In localities with population between 200 and 500 people

(Medium) benefits were obtained in avoided emissions and

employment generation in the case of no fuel substitution as

can be seen from Fig. 5b. Transition to electricity put into evidence

a clear trade-off between employment generation and electricitycosts. For total fuel substitution employment benefits rise sharply

from over 50% to more than 100% of the baseline value. In

contrast, system performance in the other three attributes decline

to negative values, in particular the electricity cost, which

increases from around b12 to b23 per kWh. This cost increase

is a result of the large electricity output required for fuel

substitution, which must be covered by expensive technologies

such as PV or direct combustion of firewood as long as resources

for cheaper technologies are depleted. This electricity supply

increase is more than ten times bigger than electricity demand

without fuel substitution, different to other locality types where

total substitution of traditional biomass represents only four to six

times the original electricity demand values. For the Cost and Job

priority structures benefits for avoided emissions were 6%. Thisnegative value, although indicates underachievement of goals

value, represents no lower performance than that of diesel

generation as the absolute value of the avoided emissions was

0.34kg-CO2/kWh.

For the smallest localities (Small) electrification without fuel

substitution brought along considerable increases in employment

generation and avoided emissions, as illustrated in Fig. 5c. Energy

system configuration for this type of localities included Wind,

Hydro and biogas (Dig.BiogasComb.) technologies, similar to

configurations for no fuel substitution in Large and Medium

localities. Substitution of traditional biomass resulted in similar

employment generation levels, while benefits in other attributes

decreased, in particular avoided emissions benefits considerably

reduced from 0.93 kg-CO2/kWh to less than 0.60 kg-CO2/kWh.

Nevertheless, share of technologies in electricity supply remained

almost unchanged.

The results for all the three locality types showed no variability

with respect to the priority structure chosen when no fuel

substitution is considered. Slight variations were present in

priority structures emphasizing environmental aspects (Land

priority and Emissions priority) for total substitution of traditional

biomass, resulting in inferior cost benefits and increased benefits

in other attributes. However, attainment of positive or negative

benefits was more correlated to whether fuel substitution

occurred or not, rather than being linked to the priority structurechosen.

4.2. Sensitivity analysis

In all types of localities renewable energy systems perfor-

mance declined in some aspects with total substitution of

traditional biomass, in particular the electricity cost. Therefore,

sensitivity analysis was conducted in order to inspect system

performance through benefits at rates of substitution between 0%

and 100%. A sample set of graphs showing trends in benefits by

attribute for Large localities are presented in Fig. 6. Table 6

summarizes the maximum levels of fuel substitution for which

positive benefits may be achieved in each attribute.Sensitivity analysis showed that in Large localities there is a

marked trade-off between benefits in electricity cost and employ-

ment generation. When higher priority is given to costs negative

benefits in electricity cost are obtained only for total (100%) fuel

substitution rates. On the other hand, employment generation

benefits fall under negative values from a 30% fuel substitution

rate onwards. For other priority structures this relation maintains,

but in an opposite way, showing negative values for benefits in

electricity costs from a 30% rate and positive employment benefits

for the whole range of fuel substitution rate. Land use and avoided

emissions benefits remained positive for all fuel substitution

rates, achieving maximum values at 80% for the former, and at 10%

and 20% for the later. Therefore, it can be said that if surpassing

electricity cost levels of diesel generation are to be avoided up to a

ARTICLE IN PRESS

Table 5

Performance outcomes for renewable energy system.

Attribute Locality Goal value No fuel

substitutionaTotal fuel substitution

Priorities (a),

(b), (c), (d)

(a) Cost

priority

(b) Job

priority

(c) Land

priority

(d) Emissions

priority

Electricity cost (US$/kWh) Large 0.136 0.136 0.146 0.158 0.158 0.158

Medium 0.209 0.21 0.326 0.326 0.443 0.443Small 0.216 0.212 0.226 0.226 0.238 0.238

Total 0.147 0.147 0.190 0.199 0.226 0.226

Employment (107 jobs/kWh) Large 5.13 5.15 4.55 5.14 5.14 5.14

Medium 5.13 7.65 11.20 11.20 15.37 15.37

Small 5.13 8.21 8.33 8.33 8.67 8.67

Total 5.13 5.53 6.21 6.64 7.61 7.61

Land use (m2/kWh/yr) Large 0.041 0.034 0.024 0.023 0.023 0.023

Medium 0.041 0.042 0.053 0.053 0.046 0.046

Small 0.041 0.041 0.043 0.043 0.041 0.041

Total 0.041 0.035 0.031 0.031 0.029 0.029

Avoided emissions (kg-CO2/kWh) Large 0.36 0.46 0.38 0.41 0.41 0.41

Medium 0.36 0.47 0.34 0.34 0.46 0.46

Small 0.36 0.93 0.56 0.56 0.57 0.57

Total 0.36 0.47 0.38 0.40 0.43 0.43

a Results in this case were the same for the four priority structures considered.



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90% fuel substitution rate can be pursued. If costs are disregarded

then total fuel substitution is feasible. But, if benefits in both cost

and employment generation are desired only a 20% of fuel

substitution is possible.

The contrasting results in costs and employment benefits were

present again in Medium localities. Fuel substitution rates lower

or equal to 50% allowed positive electricity cost benefits. However,employment benefits over this fuel substitution rate grew

considerably from 50% to more than 100%, at the expense of

increasing electricity costs which surpassed goals value up to

60%. Regarding land use, maximum fuel substitution rates of 70%

for Cost and Job priorities, and 80% for other priority structures,

allowed positive benefits. Emissions benefits turned negative only

at total fuel substitution rates for priority structures centered on

non-environmental attributes. Nevertheless, these negative values

still represent gains for the system performance since the zero

benefit value represents a positive emission reduction amount

equivalent to the goals value (0.360 kg-CO2/kWh).

For Small localities, focusing on electricity cost benefits

permits a maximum 80% of fuel substitution for Cost and Job

priorities, and a maximum of 40% for other priority structures.

Targeting the reduction of land use rates enables up to 50% of fuel

substitution for Cost and Job priorities, and up to 100% of fuel

substitution for Land and Emissions priorities. Employment

generation and emissions benefits kept positive values over the

entire range of fuel substitution.

5. Discussion

Among the four attributes considered, the electricity cost

presented the major limitation for the achievement of a favorable

performance of renewable energy systems in the NIZ of Colombia.

Different to other attributes, negative values for benefits were

more likely in electricity cost, and only partial substitution of

traditional biomass was possible without rising electricity costs

over diesel generation electricity cost. Nevertheless, fuel substitu-

tion can still be afforded at high rates for Large and Small localities

depending on the priority structure. In general, viability of fuel

substitution is more likely for smaller localities as a result of lower

energy consumption rates compared to availability of energy

resources. If the cost of electricity is taken as an indicator of

ARTICLE IN PRESS

-100

0

100

0

100

-100 0 1000100

Electricity cost

benefits

Employment

generation

benefits

Land use

benefits

Avoided

emissions

benefits

-100

0

100

0

100

-100 0 1000100

Electricity cost

benefits

Employment

generation

benefits

Land use

benefits

Avoided

emissions

benefits

-100

0

100

0

100

-100 0 100 2000100200

Electricity cost

benefits

Employment

generation

benefits

Land use

benefits

Avoided

emissions

benefits

No fuel substitution Total fuel substitution

Fig. 5. Benefits as goal deviation rates: (a) Large localities; (b) Medium localities; (c) Small localities.



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energy expenditure, it is clear that household expenditure rises as

a greater amount of fuel is replaced by electricity, given the low

price of traditional biomass, or more specifically, of firewood. The

electricity cost, which ranged between US$0.136/kWh to

US$0.216/kWh, is considerably higher than firewood price, which

is US$0.062/kWh (considering a conversion efficiency of 10% for

traditional firewood stoves). Furthermore, these costs are higher

than the average price of electricity being supplied in the NIZ,

corresponding to US$0.168/kWh (Unidad de Planeacion Minero

Energetica, 2000a). In terms of household energy expenditures,

fuel substitution imply an increase in electricity cost proportional

to the firewood consumption rates observed in each locality, as

can be seen in Table 7. For example, for Large localities energy

expenditure almost doubles, while for Medium localities

expenditures increase three-fold to five-fold. Initially, this

economic drawback resulting from fuel transition may be seen

as a hardship in the short term. The payback from reducing both

indoor air pollution and firewood collection time, translated into

lesser health risks and more free time for other activities, may not

be economically evident but in the mid or long term. However,

ARTICLE IN PRESS

-20

-10

0

10

20

0 20 40 60 80 100

Electric

itycostbenefit(%)

Fuel substitution rate (%)

Cost priority Job priority Land priority Emissions priority

0

20

40

60

80

100

0 20 40 60 80 100

Landusebenefit(%)


-20

-10

0

10

20

0 20 40 60 80 100

Employmentgenerationbenefit(%)


0

20

40

60

80

100

0 20 40 60 80 100

Avoidedemiss

ionsbenefit(%)


Fig. 6. Sensitivity analysis results for Large localities benefits: (a) electricity cost benefits; (b) employment generation benefits; (c) land use benefits; (d) avoided emissions

benefits.

Table 6Maximum rates of fuel substitution obtained from the sensitivity analysis.

Locality Attribute Maximum rate of fuel substitution (%)

(a) Cost priority (b) Job priority (c) Land priority (d) Emissions priority

Large Electricity cost 90 20 20 20

Employment 20 100 100 100

Land use 100 100 100 100

Avoided emissions 100 100 100 100

Medium Electricity cost 50 50 50 50

Employment 100 100 100 100

Land use 70 70 80 80


Small Electricity cost 80 80 40 40

Employment 100 100 100 100Land use 50 50 100 100




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this is not to mean that fuel transition is completely unacceptable

for people dwelling in remote areas. Rural people are likely to

allocate savings for higher energy expenditures and accept the

financial risk involved if technology adoption is considered in the

planning of rural electrification, namely by the inclusion of

households into the decision-making process.

Regulatory policies based on financial mechanisms, such as

subsidies in the electricity tariff or in the initial costs of

technologies through international aid among others, may be

needed to improve sustainability of electrification with renew-

ables. Another approach could be the transaction of other benefits

directly as cost reductions in the electrification project. This

alternative may prove helpful for avoided emissions and land use

benefits, which could be internalized by means of a Clean

Development Mechanism (CDM) as part of carbon mitigation

and carbon sequestration initiatives. Regarding actual implemen-

tation of the CDM in the NIZ of Colombia, it has been reported that

actual transaction costs of carbon emissions limits feasibility of

projects working under the CDM only to large electricity outputs,like in highly populated areas or a group of localities served by a

common plant. Thus, other instruments derived from climate

change international agreements, such as special climate change

fund (SCCF), have to be considered in order to promote

electrification in the NIZ at a larger extent based on carbon

reduction initiatives (Oficina Colombiana para la Mitigacion del

Cambio Climatico (OCMCC), 2003). In addition, other alternatives

for fuel substitution need to be considered. For example,

introduction of improved cooking stoves using firewood instead

of electric stoves is a promising alternative in many countries, as

these devices can be manufactured by people living in rural areas,

increasing income generation opportunities. However, it has to be

remarked that the total substitution of traditional biomass for

electricity is rather a process than a one-single-step transition. Ithas been found that several poor families in developing countries

that gain access to electricity use the service selectively,

principally for lighting and communication devices. In this regard

three main determinants in the transition to modern forms of

energy have been identified: the fuel availability, affordability and

cultural preferences (IEA, 2002). Accordingly, the shift from

traditional biomass to electricity is expected to be encouraged

by the continuous rise of income rates among rural people.

Employment generation was used in the multi-objective model

in order to introduce a factor directly related to the impact that

energy access may have on poverty reduction. However, the

quantification of this attribute was surrounded by several

uncertainties. As a consequence, the model deployed in the study

is too limited for the assessment of impacts of energy access on

income poverty. Instead, the model is more suitable to address the

impact on other poverty aspects, such as energy supply infra-

structure development and substitution of traditional biomass.

The most significant benefit from fuel substitution with

renewables was the reduction of greenhouse gases, estimated by

means of the avoided emissions. Table 7 summarizes these

benefits in absolute values and taking into account emissions

from combustion of firewood in traditional stoves. CO2 emissions

reduction accounted for over 190,000 t-CO2/yr in Large localities,

68,00077,000 t-CO2/yr in Medium localities, and 14,000 t-CO2/yr

in Small localities. Total emissions reductions, which summed

between 268,000 and 287,000 t-CO2/yr, are larger than actual CO2emissions reported in the NIZ due to the consumption of fuels,

equivalent to 116,983t-CO2/yr (Oficina Colombiana para la

Mitigacion del Cambio Climatico (OCMCC), 2003). Nevertheless,

these figures are relatively small compared to the entire emissions

in the Colombian energy sector, which summed more than 55

million t-CO2 by the year 1994 (Instituto de Hidrologa and

Meteoreloga y Estudios Ambientales (IDEAM), 2001).Recognizing economic and social benefits regarding the

creation of jobs, the reduction of energy expenditures and a

better utilization of energy sources provided by the substitution of

traditional biomass, may allow the inclusion of RETs implementa-

tion in local development programs. In that sense, the success of

RETs penetration in rural areas of Colombia and, in general, of

developing countries, requires the commitment of the national

government and the international community: the former,

through the creation and enforcement of regulatory policies

promoting the growth of RETs market; and the later by means of

cooperation programs facilitating technology transfer towards the

use renewable energy resources.

The application of GP under an energy systems analysis context

provides a more straightforward method to integrate and assessquantitatively different aspects of energy technologies in rural

communities. For example, compared to the sustainable livelihoods

approach used by Cherni et al. (2007), the application of GP has a

stronger quantitative foundation, since the set of indices deployed in

that study are constructed based on the views of rural people rather

than on exact measurements, for example, of the energy resources

and the energy demand rates. Thus, the process governing the

selection of technologies in that study involves a considerable level

of uncertainty. In addition, the methodology proposed by Cherni et

al. (2007) is able to evaluate only a set of eight alternatives

previously defined, reducing the possibility to evaluate several

combinations of technologies as energy supply alternatives. Never-

theless, such an approach is more complete in the estimation of the

impacts on rural communities given that it includes a broader range

ARTICLE IN PRESS

Table 7

Energy expenditure and emissions reduction for diesel and renewable energy schemes.

Feature Locality Diesel generation Renewable energy system

No fuel

substitution

Total fuel

substitution

No fuel substitutiona Total fuel substitution

Priorities (a), (b), (c),

(d)

(a) Cost

priority

(b) Job

priority

(c) Land

priority

(d) Emissions

priority

Energy expenditure (US$/yr/household)

Large 255 427 255 457 496 496 496Medium 232 634 232 988 988 1341 1341

Small 148 366 147 383 383 404 404

Emissions reduction (103 t-CO2/

yr)bLarge 0 65.3 38.8 187 196 196 196

Medium 0 28.4 5.3 67.6 67.6 77.3 77.3

Small 0 3.9 2.6 13.5 13.5 13.6 13.6

Emission factor for traditional biomass equivalent to 0.273kg-CO2/kWh was used.a Results in this case were the same for the four priority structures considered.b Emission reductions calculated as [(avoided emissions)(electricity supply)+(emissions traditional biomass)(substituted traditional biomass as final energy)].



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International Energy Agency (IEA), 2002. Energy and poverty. In: World EnergyOutlook 2002. International Energy Agency, Paris. Available: /http://www.iea.org//textbase/nppdf/free/2000/weo2002.pdfS.

International Energy Agency (IEA), 2004. Energy and development. In: WorldEnergy Outlook 2004. International Energy Agency, Paris. Available: /http://www.iea.org//textbase/nppdf/free/2004/weo2004.pdfS.

International Energy Agency (IEA), 2006. Energy for cooking in developingcountries. In: World Energy Outlook 2006. International Energy Agency, Paris.Available: /http://www.iea.org/textbase/nppdf/free/2006/weo2006.pdfS.

Kanagawa, M., Nakata, T., 2007. Analysis of the energy access improvement and itssocio-economic impacts in rural areas of developing countries. Ecological

Economics 62 (2), 319329.Kanagawa, M., Nakata, T., 2008. Assessment of access to electricity and the socio-

economic impacts in rural areas of developing countries. Energy Policy 36 (6),20162029.

Kanniappan, P., Ramachandran, T., 2000. Goal programming model for sustainableelectricity production from biomass. International Journal of Energy Research24, 118.

Kemmler, A., Spreng, D., 2007. Energy indicators for tracking sustainability indeveloping countries. Energy Policy 35 (4), 24662486.

Mezher, T., Chedid, R., Zahabi, W., 1998. E nergy resource allocation using multi-objective goal programming: the case of Lebanon. Applied Energy61 (4),175192.

Modi, V., McDade, S., Lallement, D., Saghir, J., 2005. Energy services for theMillennium Development Goals. World Bank, UNDP, New York.

Moreno, B., Lopez, A.J., 2008. The effect of renewable energy on employment. Thecase of Asturias (Spain). Renewable and Sustainable Energy Reviews 12 (3),732751.

Oficina Colombiana para la Mitigacion del Cambio Climatico (OCMCC)Ministeriode Ambiente, Vivienda y Desarrollo Territorial, Instituto de Planificacion y

Promocion de Soluciones Energeticas (IPSE), 2003, Estrategia para laimplementacion del mecanismo de desarrollo limpio en zonas no interconec-tadas (in Spanish). Bogota, Colombia.

Pachauri, S., Mueller, A., Kemmler, A., Spreng, D., 2004. On measuring energypoverty in Indian households. World Development 32 (12), 20832104.

Painuly, J.P., 2001. Barriers to renewable energy penetration: a framework foranalysis. Renewable Energy 24, 7389.

Pohekar, S.D., Ramachandran, M., 2004. Application of multi-criteria decisionmaking to sustainable energy planninga review. Renewable and SustainableEnergy Reviews 8, 365381.

Ramanathan, R., Ganesh, L.S., 1995. Energy resource allocation incorporatingqualitative and quantitative criteria: an integrated model using goal program-ming and AHP. Socio-Economic Planning Sciences 29 (3), 197218.

Ruiz, B.J., Rodrguez-Padilla, V., 2006. Renewable energy sources in the Colombianenergy policy, analysis and perspectives. Energy Policy 34 (18), 36843690.

Schneiderjans, MarcJ., 1995. Goal Programming: Methodology and Applications.

Kluwer Academic Publishers, Massachusetts.Silva, D., Nakata, T., 2008. Renewable technologies for rural electrification in

Colombiaa multiple objective approach. International Journal of EnergySector Management 2 (1), 139154.

Spreng, D., 2005. Distribution of energy consumption and the 2000 W/capitatarget. Energy Policy 33 (15), 19051911.

Unidad de Planeacion Minero Energetica, 2000a. Establecimiento de un planestructural, institucional y financiero, que permita el abastecimiento energe-tico de las Zonas No Interconectadas con participacion de las comunidades y elsector privado. Centros poblados, caracterizacion energetica y agrupacion (inSpanish). UPME, Bogota, Colombia.

Unidad de Planeacion Minero Energetica, 2000b. Linea base geo-referenciada parala formulacion del plan de suministro energetico en las Zonas No Inter-conectadas de Colombia (in Spanish). UPME, Bogota, Colombia.

Unidad de Planeacion Minero Energetica, 2003. Plan energetico nacional,Estrategia energetica integral, Vision 20032020 (in Spanish). UPME, Bogota,Colombia.

United Nations, 2000. United Nations Millennium Declaration. Resolution. UN,

New York.Zapata, J., Bayona, L., 2000. Nuevo esquema de organizacion para el suministroenergetico en las Zonas No Interconectadas de Colombia (in Spanish).Escenarios y EstrategiasUPME. UPME, Bogota, Colombia.

ARTICLE IN PRESS

http://www.iea.org//textbase/nppdf/free/2000/weo2002.pdfhttp://www.iea.org//textbase/nppdf/free/2000/weo2002.pdfhttp://www.iea.org//textbase/nppdf/free/2004/weo2004.pdfhttp://www.iea.org//textbase/nppdf/free/2004/weo2004.pdfhttp://www.iea.org/textbase/nppdf/free/2006/weo2006.pdfhttp://www.iea.org/textbase/nppdf/free/2006/weo2006.pdfhttp://www.iea.org//textbase/nppdf/free/2004/weo2004.pdfhttp://www.iea.org//textbase/nppdf/free/2004/weo2004.pdfhttp://www.iea.org//textbase/nppdf/free/2000/weo2002.pdfhttp://www.iea.org//textbase/nppdf/free/2000/weo2002.pdf

Multi Objective Assessment of Rural Electrification in Remote Areas With Poverty Considerations 2009 Energy Policy

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