Project evaluation for energy supply in rural areas of developing countries

Project evaluation for energy supply in rural areas of developing countries

230 European Journalof Operational Research49 (1990) 230-246 North-Holland Project evaluation for energy supply in rural areas of developing countri...

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230

European Journalof Operational Research49 (1990) 230-246 North-Holland

Project evaluation for energy supply in rural areas of developing countries John M. Christensen Riso National Laboratory, DK-4000 Roskilde, Denmark

Ren6 Victor Valqui Vidal The Institute of Mathematical Statistics and Operations Research, The Technical University of Denmark, DK-2800 Lyngby, Denmark

Abstract: This paper reports the methodological experiences of the project: Energy Supply Technologies in Developing Countries, carried out in collaboration with the Department of Energy, Zambia. Existing methods for project evaluation, based on cost-benefit analysis, will be briefly presented, particularly as regards their inadequacy for assessing energy projects in rural areas. An alternative practical and PC-based approach will be presented in which emphasis is placed on the problem formulation phase, including the socio-economic, cultural and political aspects of the problem. This approach has been prepared for training purposes. Finally, some methodological thoughts based on our practical experiences will be presented and our future work will be briefly discussed.

Keywords: Cost-benefit analysis, developing countries, energy management, personal computers, rural areas, socio-economic factors

1. Introduction During the seventies the approach to economic planning in many developing countries changed from mainly macro-level planning to a project-oriented approach within an overall development framework. A primary driving force in this process was the growing concern about the inefficiency of development aid programmes both within the international organisations (World Bank, UN, Regional Development Banks, etc.) and in the agencies of individual donor countries. This change in approach brought project analysis and project planning into focus. A requirement Received March 1990

evolved for better tools and methods at the various stages in the project cycle from identification to evaluation. Especially the work in the ex ante and ex post evaluation phases was given increased attention and a number of research reports [3,4,8], manuals [1,5], guidelines [2], etc. were published. The above mentioned work was mainly performed by or for the large international aid organisation and gradually modified and adopted by many of the national aid agencies. Several methods have also been transferred to sectoral and intersectoral ministries in various developing countries but often with limited practical use and success. Since 1984 the Systems Analysis Department, Riso National Laboratory and the Institute of

0377-2217/90/$03.50 © 1990 - ElsevierSciencePublishers B.V.(North-Holland)

J.M. Christensen, R. V.V. Vidal / Project evaluation for energy supply in developing countries

Mathematical Statistics and Operations Research, the Technical University of Denmark have been collaborating with the Department of Energy in Zambia. This collaboration has been centered around a PhD project concerning project analysis methods especially applicable to rural energy projects [9,21,22]. The purpose of this paper is, based on the experiences from this PhD project, to discuss especially the ex ante evaluation, which in the terms used in connection with development projects is called the appraisal phase. In this phase of the project cycle, proposals are reviewed and analyzed in order to test their technical, economical, financial and institutional viability. Various methods may be applied but as a result of the above described methodological developments, Cost-Benefit Analysis (CBA) and Social Cost-Benefit Analysis (SCBA) are now being used extensively in many international organisations. The purpose here is not to enter a theoretical discussion about specific aspects of the C B A / SCBA methods such as shadow prices which have been receiving much attention in the literature [1,10,22], but to look at the practical aspects of project analysis and assessment activities at the sector level in a specific developing country - Zambia. How is project analysis performed within the sector administrative unit both in principle and in practice? What methods are being used, and what do quantitative methods like CBA/SCBA have to offer at this level of administration? These have been some of the central questions in our work. Based on this specific experience, we have developed a practical approach to assessment designed particularly for energy projects in rural areas of developing countries. Our aim has been to interrelate social, political, energy and resource aspects with economic and financial aspects ineluding a limited SCBA part. The approach is implemented as a small computer model for a Personal Computer (PC). The objective has been to keep the model simple, 'user-friendly' and very modular, because this means that the user only has to enter those parts of the model, he/she wants to use for the analysis of the specific problem. In the next section the Zambian energy situation and project administration is very briefly

231

outlined. A more comprehensive description is given in the report "Energy Planning and Project Procedures in Zambia" by Christensen [21]. Section 3 presents a discussion of problems related to the choice of project analysis methods, e.g. the practical and political restrictions and possibilities for the selection. In Section 4 the approach that has been developed as one result of the project is described with focus on the developed PC-tool: PRAM (Project Analysis Model). Finally, in Section 5 the general experiences of our work are discussed and some of the necessary future activities are outlined. The discussion of project analysis methods and the introduction to PRAM are based on the results presented in the report "Project Planning and Analysis" by Christensen [22].

2. Background and problem formulation The Republic of Zambia lies inland between latitudes 8 to 18 south in the southern part of Africa. It gained independence in 1964 and the political system is based on a one-party participatory democracy. The official political ideology is 'humanism', which is an attempt to combine capitalistic, socialistic and nationalistic ideas. Development policy is based on a Basic Needs approach and since the launching of the First National Development Plan the main aims have been to

* diversify the economy, * minimize the inherited economic imbalance between the urban and rural sectors, * raise the general level of education, and * increase social welfare. In spite of the official political aims and efforts Zambian society is today still dominated by the fact that the economy is very 'dualistic'. On one hand the 'modern' economy dominated by the copper mines with related industries and a number of commercial farms mainly producing cashcrops for the urban markets and for export. On the other hand there is a 'traditional' economy dominated by a large number of small farms mainly on a subsistence basis.

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J.M. Christensen, R. V. V. Vidal / Project evaluation for energy supply in developing countries

Table 2 Total energy consumption in Zambia and energy use in the household sector in 1980 a

2.1. The energy situation in Z a m b i a

This duality in the structure of the society is naturally reflected in the energy supply and consumption structures. This is best illustrated by looking at the sectoral pattern of energy consumption, see Table 1. W h a t is usually referred to as commercial fuels (oil products, coal and electricity) is almost totally consumed in the ' m o d e r n ' economy, while with woodfuel the situation is almost totally reversed. As in almost all other African countries, woodfuel is the totally d o m i n a n t household fuel and its importance at the national scale can be seen in Table 2. Data about wood fuel consumption and supply is, however, very sparse and aggregated numbers are usually based either on small samples or simply 'guesstimates'. All petroleum is imported via a pipeline f r o m D a r es Salaam and refined in Zambia. Coal is almost entirely supplied from one domestic mine. Electricity is, with the exception of some small local rural diesel systems, produced at h y d r o p o w e r plants, and Z a m b i a is in a situation of excess capacity but with a national grid that only covers the major urban and industrial centres.

Energy sources

Mining Industry Transport Agriculture Others (incl. households) Total

Petroleum (%)

of total)

(TJ) b

(% of energy source)

25100 20000 11 800 2 400 11600 69 700

17.9 14.2 8.4 1.7 8.3 49.6

1290 835 11536 66 770

5.1 4.2 99.5 95.8

140600

100.0

80431

57.2

Petroleum Electricity Coal Coke Charcoal Firewood Total

(%

a Source: Chidumayo [13]. b ZJ: Tera Joule.

importance of the energy sector, the D e p a r t m e n t of Energy ( D O E ) was created in 1982 under the Ministry of Power, Transport and C o m m u n i c a tion. The D O E is responsible for energy policy and planning but due to lack of political support, staffing problems and partly overlapping responsibilities with other government bodies, the D O E is only slowly developing in the direction of overall energy strategy formulation including the performing of project analysis and elaboration of investment priorities. Since m a n y projects in Z a m b i a are partly or fully funded by external donors, coordination of the investment plans of the different sector ministries is necessary. All official c o m m u n i c a t i o n with donors goes through the coordination b o d y - - in Zambia, the N a t i o n a l Commission for Development Planning ( N C D P ) under the Ministry of Finance.

As in most other oil-importing countries, energy took on increased importance due to the rising oilprices from the early seventies to the mid-eighties. In Zambia, oil imports went from 8% to 20% of total import without increasing in volume. As one of the results of this increased

Sector

Household sector consumption

(YJ) b

2.2. Energy planning and project admin&tration

Table 1 Sectoral pattern of energy consumption in Zambia (1980/81)

Amount used

a

Coke (%)

Coal (%)

37 18 35 1

100 -

52 48 . -

9

-

-

100

100

100

Electricity (%)

Woodfuel (%)

73 17

Bagasse (%)

6 -

100

_

_

8

94

-

100

100

100

.

. 2b

a Source: Christensen [9]. b Many agrobased industries are registred as 'industry' sector e.g. sugar, coffee etc.

.

J.M. Christensen, R. V. V. Vidal / Project evaluation for energy supply in developing countries

Without going into too much detail, the planning system is based on 5-year development plans coordinated by NCDP. Project proposals must, therefore, in principle meet the overall objectives and be within the frames given by the 5-year plans. It is also the task of the N C D P to secure this accordance. All projects, that the sector ministries want to get funded by foreign donors, have to pass through N C D P for coordination and selection. Due to severe economical problems, it is, however, very difficult to make comprehensive longterm plans that can be used as a background for the project selection. In practice, therefore, the usual procedure is that the sector ministry already has established contact to an interested donor or perhaps an interested company from the possible donor country and the N C D P is then informed about this possible donor and their interest at the same time as the proposal is presented. This is only a very schematic illustration of the formal and informal project procedures. In reality this is, of course, a much more complex situation.

2.3. Project analysis From the short discussion above we can conclude that there are three levels where projects are being analyzed: * Sector level/DOE. * National Ievel/NCDP. * Donor level. At present, the selection of projects at sector level is only to a limited extend based on a detailed analysis because information and data are usually quite sparse. Moreover, there is neither staff nor financial resources to make a more detailed field study. Rural electrification projects are presently the main object of analysis, and the methods used are normally limited to calculation of Net Present Values (NPV) a n d / o r Internal Rate of Return (IRR). As previously described, projects are usually in practice approved on the basis of recommendation from the sector level. If some kind of selection is necessary, the official approach is to use one of the earlier mentioned guidelines (UNIDO's) on a limited scale, but it is doubtful whether a full analysis is ever performed.

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Donor procedures obviously differ among the various organisations and with type, size etc. of the project. Usually, the donor will select an appraisal mission to look in more detail at the project (to some extend in the field) and present a report covering the technical, economical and institutional aspects. Usually, the analysis is centered around a CBA with limited social aspects or a more comprehensive SCBA, if it is a major project and a multilateral development organisation. The results of the donor's appraisal are presented to the sector unit for comments and approval, but major changes are seldom made. This outline of the project analysis structure shows that the sector unit in charge of energy policy and strategy formulation has only had very limited influence on project analysis and selection. This situation is clearly not satisfactory. The DOE is, therefore, interested in increasing their analysis activities. This is naturally not an easy task due to the existing political and practical constraints on the DOE. A project analysis tool designed for their specific purposes could, however, relieve some of the manpower restrictions and, a more active participation in the preparation phase by the DOE would also lead to increasing influence on the types of projects that are selected for execution.

3. Basic methodological considerations With a wish for more active participation in project analysis several basic questions arise concerning: * The type of projects/problems that are going to be analyzed. * The policy aims and administrative restriction on the analysis. * The qualifications and resources available for doing the analysis. The combined answers to these questions present the basic conditions for the selection of appropriate methods to be used in the analysis. As we are particularly interested in looking at projects for rural areas it must be emphasized that the traditional rural society is quite difficult to understand and analyze. This is mainly due to their social complexity. The various activities are

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J.M. Christensen, R. V. V. Vidal / Project evaluation for energy supply in developing countries

closely interconnected at many levels. This means that a change of one parameter can give a number of derivative effects. Technically, the structures may be quite simple. For example, typically energy consumption will consist of about 95% collected fuelwood and up to 5% purchased kerosene for lighting. Conversion technologies are also quite uniform, a fireplace and a small glass with a wick respectively. But if, through a project activity some of the existing conditions for the situation are changed, the result may be different from what you expected. One explanation can be that, in the particular situation, consumption and demand may not be equivalent. For example consumption is restricted by factors such as wood availability, collection time, necessary field work, etc., so if people get more efficient tools for the field work, one derivative effect may be more time to collect wood and an increased total consumption. This social complexity, combined with the fact that there have been very few studies of energy consumption and supply, and, therefore, little empirical data is available, makes it very difficult to 'model' the society. A quantitative or technical OR model would, therefore, have to be quite complex, if it should cover the structures of the rural society to any reasonable degree. With the generally small size of projects, it would therefore not be very appropriate with such a model. Combined with the existing lack of staff, particularly with previous model handling experience, one is led to support the use of more 'simple' and qualitative methods based in the ideas of social OR (see further [20]). There is no common denominator for these methods, but the aim is to include social, cultural, and political aspects in the analysis in order to understand the context in which the project is to be implemented. This qualitative approach is quite idealistic, and it has to be combined with existing methodological traditions, restrictions imposed by the political and administrative structures, etc. This means in the Zambian context that, due to the structural set-up between DOE, NCDP and the donor agencies, there has to be some consensus about analysis methods. The rather extensive use of quantitative methods, in particular by the multilateral donor agencies, imply that it is necessary

also to include cost-benefit or social cost-benefit methods in the analysis. Inclusion of CBA/SCBA will also increase the relevance of using the tool on other types of energy projects outside the rural context. With an appropriate combination of qualitative and quantitative methods, it should improve the possibilities of comparing rural energy projects with e.g. industrial energy projects. In order for the tool to be successful, the user must be in accordance with the basic concept, because recognizing the importance of the qualitative aspects often implies a change in traditional attitudes.

4. Outline of a practical approach Based on the present situation for the DOE but with expectations of a growing number of projects that have to be analyzed, it was decided to develop a small model that should be an operational tool in the analysis work of energy projects in general but with particular focus on rural woodfuel problems. Therefore, the model has been designed specifically with the future DOE situation in mind. Due to the modular structure and the general aspects of many of the problems, it will probably be fairly simple to adjust it to similar sector units in other developing countries. 4.1. Practical conditions and limitations

With the potential user so clearly defined, the practical conditions that should be considered in the design of the model were quite clear. The choice of hardware was given since the DOE already had two IBM Personal Computers. Because there is a general trend towards compatibility among PC's, this did not give any limitations on the possibly wider applications of the model. Spreadsheet software had just recently been introduced in the DOE. The use of wordprocessing facilities and minor spreadsheets indicated that the use of a spreadsheet program as a basis for the model would be appropriate. Although presenting some restrictions on the programming possibilities, this type of software has the ad-

J . M . Christensen, R. K K Vidal / P r o j e c t evaluation f o r e n e r g y s u p p l y in d e v e l o p i n g countries

vantage of both easy input data work and good screen and printout presentation. Other more general, but relevant aspects were that a tool should be: * 'User-friendly', not demanding previous computer experience of the user. * Easy to 'see through' without any built in hidden subjective assumptions. * Modular, in order to be usable both for small and large projects without having to go through the same total procedure. 4.2. Analysis criteria and model structure

In the specific Zambian context, we found that the process from identification to selection can be divided into two separate phases, a preparation and maturation phase, and an analysis and selection phase, as is illustrated in Figure 1, where general inputs and outputs are also shown. The analysis and criteria evaluation tasks are the ones we think should be performed by DOE. In order to relate it to the 'national' project handling, it must be emphasized that what we call selected projects, are the ones that are sent to NCDP for approval. Analysis of the technical viability will usually be taken care of by other institutions or through feasibility studies. Projects ideas and proposals may come from a number of different sources within the Zambian society and also from foreign donors and from companies working in the country. This means that a potential project can be anything from a problem that has just been identified to a fully prepared proposal. In the phase we call 'preparation and maturation', it is essential to bring the different projects to a fairly homogeneous proPreparation and maturation phase

Proposal analysis and selection phase

- political analysis

- e n e r g y criteria

- social analysis

- w o o d resource criteria

- culturalanalysis

- socio-econornic criteria

[

I I I

Policy objectives Project ideas

Project proposals - alternative - complementary

1 Projects for appraisal

Figure 1, The project selection process

235

posal level. We find this phase very important, because usually the initial selections are performed here. These selections are often unrecognized. They are mainly qualitative and frequently based on implicit political and social criteria. The first module of the model is designed to assist in this phase. Based on the general considerations about including social, cultural and political aspects in the analysis, the module offers a structure for this qualitative analysis. The structure is supported by access to various diagrams and supplementary explanations, in order to both discipline and assist the user in performing the analysis. In Table 3 the main module menu, from which the user operates, is shown. Each of the subprograms contains either tables, structured word processing sheets, explanations a n d / o r guidelines. The user chooses which parts are relevant for the specific project and can just neglect the rest. A tool like this will not prevent the user from making unsound considerations and decisions. It will, however, hopefully, stimulate the user to engage himself/herself in the analysis of the basic problems aimed at, and how the suggested activities can give the desired results. In this way it will lead to greater consciousness about the relevance and possible impact of the project. Because the present work in this phase is often very limited, the module will not relieve any activity but on the contrary, introduce more work in an often already overburdened situation. Th;.s means that the introduction of the module will have to be combined with sincere intentions of the institution to strengthen the analysis work in this phase. In addition to this rather qualitative and verbally oriented preparation phase module, the model consists of two other independent quantitatively oriented modules aiming at assisting the work in the proposal analysis and selection phase. One module is specifically designed for rural energy problems and the purpose is to analyze the consequences of a proposal on a general energy consumption criteria and a specific wood resource criteria. Based on input concerning sub-sectoral end-use consumption (in daily terms, say kg or m 3 of wood) and the actual present standing wood stock combined with an accessibility factor (wood resource is only interesting if the user is able to get to it), the task of the module is simply to aggre-

J.M. Christensen, R. K K Vidal / Project evaluation for energy supply in developing countries

236

Table 3 Project preparation module m e n u Project relevance analysis

Project description

Strategy evaluation

1: Objectives - s h o r t / l o n g term 2: Description - Strategy - Outline of activities - Components - Actions 3: Time table 4: Cost estimates

A: Problem analysis B: Target group analysis C: Development policy relevance D: Sectoral aims

Activity elaboration F: G: H: I:

Activity background Desired effects M e a n s - a i m s hierarchy Relations to other activities

F1: R E T U R N TO INTRODUCTION F2: HELP M E N U

F9:

PRINT THE WORKFRAME F10: R E T U R N TO THIS MENU

The basic menus and a few examples of both visible and 'hidden' program sheets are shown in the Appendix. In relation to the earlier described practical conditions, it can be stated that the model works in a common spreadsheet environment on an IBM-compatible personal computer. Within each of the three separate modules the structure is also very modular thus limiting the user's work to only what is absolutely necessary. Because input by the user is restricted to writing text and putting in numbers in designed forms guided by instructions and working with menus, where selection is performed by presssing a single key, the user hardly needs any previous computer experience. It will, however, be an advantage, if besides the necessary training in the model, the user also gets experience with the basic spreadsheet software. This will increase the flexibility and give access to a number of helpful facilities.

5. Conclusions and future work

gate and convert consumption to comparable energy terms and, based on the available wood yield, to estimate the standing wood stock in the selected years. For instance, if wood consumption exceeds the available yield, the stock will be reduced in accordance with the availability. The third and last module is a fairly traditional tool where the economic and financial aspects of the project can be analyzed and evaluated in the usual ways (NPV, IRR, C / B ratio etc.) We have included a very limited social cost benefit part only using shadow prices for labour on three categories. Furthermore, import consequences can be calculated and there is a possibility to build in a 'shadow' exchange rate. As we have discussed in Section 3, there are limitations to the relevance of quantitative methods especially for projects in an almost nonmonetarized rural society. This does not mean that they are to be completely avoided, but merely that one must be aware of their limitations and conscious of the basic ideological premises. The objective of this third module, as in the model as such, is to give access to a number of supplementary evaluation criteria, and to leave it up to the user to choose which ones are relevant in the specific situation.

The project on which this paper is based terminated this year, but there are plans for a continued collaboration. The Project Analysis Model (PRAM) has been presented to the DOE in a draft version. If the results of this presentation is to be briefly summarized, the main points are, as could be expected: * Training in both more advanced spreadsheet use and the PRAM is absolutely essential. * The quantitative modules are, as expected, the ones met with the greatest interest, since they resemble existing works. * Modularity is extremely important in order to deal with only the necessary parts of each module. In addition to these general points, a number of minor practical adjustments and extensions were agreed upon, and a revision of the model is being prepared. Hopefully a more final version will be presented and introduced through a comprehensive training programme later. Although some parts of the PRAM are made specifically for DOE in Zambia (land use categories, electricity tariff system, consumer categories, etc.), the additional work involved in transferring to especially similar institutions in other

J.M. Christensen, R. V. ~ Vidal / Project evaluation for energy supply in developing countries

sub-Saharan African countries will not be prohibitive. It will, however, not be relevant until working experience with the model has been gained through the DOE. The problem described earlier concerning the lack of both general knowledge and energy supply and consumption data from rural areas has also become evident in relation to the use of PRAM. One of the ambitions for the continued work is, therefore, to establish a set of guidelines for surveys for estimation of such data and in particular woodfuel consumption. This activity does not aim directly at the PRAM. It is seen as a basis for general energy planning activities and support to the program established to promote activities aiming at reduction of woodfuel consumption. An improved data basis will, however, also make it easier and more meaningful to use models like PRAM in project preparation and analysis. The basic question of whether or not the PRAM will actually be used remains to be seen. Based on the preliminary presentation, it seems likely that it will happen gradually. If through increased modularity it can help perform some of the existing economical calculations in a more practical way, then it may gain acceptance as a usable tool. The other parts of the model will then be easier to get familiar with, and since the project analysis activities inevitably will be increasing in the DOE, the need for these alternative and perhaps more refined methods will grow.

References [1] Little, I.M.D., and Mirrlees, J.A. (1974), Project Appraisal and Planning for Developing Countries, London. [2] Dasgupta, S., Marglin, and Sen, A. (1972), Guidelines for Project Evaluation, UNIDO, New York. [3] Balassa, B. (1976), "The 'Effect Method' of project evaluation", World Bank Staff Working Paper No. 231, Washington.

237

[4] Weiss, D. (1978), "A critical comparison of a new World Bank Methodology with the UNIDO and the revised OECD approach", German Development Institute. [5] Little, I.M.D., and Mirrlees, J.A. (1968), "Manual of project analysis in developing countries, vol. II. Social cost-benefit analysis", OECD, Paris. [6] Elzinga, A. (1981), "Evaluating the evaluation game", SIDA, Stockholm. [7] Vidal, R.V.V, (1973), "The role of Operations Research in underdeveloped countries - An appraisal", IMSOR, DTH. [8] Stewart, F. (1978), "Social cost-benefit analysis in Practice", Worm Development 6. [9] Christensen, J. (1985), "Energy survey in Zambezi", RisoM-2553. [10] Anand, S., and Nalebuff, B. (1985), "Issues in the appraisal of energy projects for oil-importing developing countries", World Bank Staff Working Papers 738, Washington. [11] "Zambia: Issues and options in the energy sector" (1983), UNDP/World Bank, New York. [12] "Zambia - Energy assessment status report" (1985), UNDP/World Bank ESMAP no. 039, New York. [13] Chidumayo, E.N. (1985), "Population growth and energy consumption in Zambia", Natural Resources Department, Lusaka. [14] Chidumayo, E.N., and S.B.M (1984), "The status and impact of woodfuel in urban Zambia", Department of Natural Resources, Lusaka. [15] BirgegS.rd, L.E. (1975), "The project selection process in developing countries", The Economic Research Institute, Stockholm. [16] Lal, D. (1974), "Methods of project analysis - A review", World Bank Staff Occasional Papers 16, Washington. [17] "Procedures for the design and evaluation of ILO projects", ILO, Bureau of Programming and Management (1981-1982), Geneva. [18] Metodhandboken (1985), SIDA, Stockholm. [19] Project Guidelines (1985)- Appraisal- Planning, Danida, Copenhagen. [20] Ravn, H.F., and Vidal, R.V.V. (1986), "Operational Research for developing countries - A case of transfer of technology", Journal of the Operational Research Society 37/2, 205-210. [21] Christensen, J.M. (1987), "Energy planning and project procedures in Zambia", Riso-M-2676. [22] Christensen, J.M. (1988), Project planning and analysis Methods for assessment of rural energy projects in developing countries", Riso-M-2706.

J.M. Christensen, R. V. V. Vidal / Project evaluation for energy supply in developing countries

238 Appendix

PRAM." E x a m p l e s o f p r o g r a m sheets

Table A1 Project preparation module menu Apps [MENU]

Disk

Create

Edit

Locate

Frames

Words

Numbers

Graph

Print

A

B

C

D

E

F

G

H

I

1 2

Project Preparation Module Menu

3 4 5

Project relevance analysis

Project description

Strategy evaluation

6 7 8 9

A: B: C: D:

1 : Objectives - s h o r t / l o n g term 2: Description - Strategy - Outline of activities - Components - Actions 3: Time table 4: Cost estimates

Problem analysis Target group analysis Development policy relevance Sectoral aims

10

Activity elaboration

11 12 13 14 15 16 17

F: G: H: I:

Activity background Desired effects M e a n s - a i m s hierarchy Relations to other activities

FI: R E T U R N TO I N T R O D U C T I O N F2: R E T U R N TO P R A M M E N U

PRESS F5 TO S T A R T

F9: P R I N T T H E W O R K F R A M E F10: R E T U R N T O THIS M E N U

MENU

Doe: 1 / 1

Table A2 Resource module menu Input

Output

Household

Tertiary

Energy consumption status

A: B: C: D: E:

K: L: M: N: O:

Q: Sectors and Total (GJ) 1988 R: Sectors and Total (GJ) 1993 S: Sectors and Total (GJ) 1998

High Middle Low Subsist Alt.

Service Administration Schools Water works Health centers

Agriculture

Other input

F: Large G: Medium H: Small

P: Conversion factors W: Wood resource data 1988

Industry I: J:

Formal Informal

FI: R E T U R N T O PRAM MENU

Wood source 1: 2: 3: 4: 5:

Wood Wood Wood Wood Wood

resource status 1993 resource status 1998 c o n s / s u p status 1988 c o n s / s u p status 1993 c o n s / s u p status 1998

F8: R E T U R N T O I N T R O D U C T I O N F9: P R I N T T H E W O R K F R A M E F10: R E T U R N T O THIS M E N U

8.17 am

J.M. Christensen, R. V. V. Vidal / Project evaluation for energy supply in developing countries

Table A3 Socio-economic module menu Input forms

Output forms

Project definition

Financial results

A: B: C: D: E: F: G: H: I:

Financial cash flow 5: Period 1988-1992 7: Period 1993-1997 6: Period 1998-2002 8: Period 2003-2007

Project base data Economic base assumptions Electricity system definition Fuel and source prices Employment quotas - men Employment quotas - women Energy transformation values Net present value - C / B ratio Internal rate of return

Economic cash flow 1: 2: 3: 4:

Period Period Period Period

FI: F8: F9: F10:

1988-1992 1993-1997 1998-2002 2003-2007

RETURNS TO I N T R O D U C T I O N RETURN TO PRAM M E N U PRINT THE W O R K F R A M E RETURN TO THIS M E N U

Economic results J: K: L: M: N: O: P:

Net present value - C / B ratio Internal rate of return Cost-benefit efficiency Social cost-benefit Import value 1988-1997 Import value 1998-2007 Employment valuation

239

Rural electrification (example)

Aimed results

Cheaper production

Larger capacity and new users, Better utilization of production

Minimize drop-out and no need for local backup

Secure that one energy source is always available

Possible actions

Substitute with: - efficient diesel - local hydro - grid connection

Increase capacity or utilization of existing system

Establish priority connection to h.c. New better supply, Improve system or provide emergency backup

See above actions. Increase charcoal supply

Project name

Identified problems

High production costs of electricity

Insufficient production capacity prevents connection of additional customers

Frequent drop-out necessitate backup capacity at the health center

High costs and drop-out lead to increase in charcoal use

Table A4 Target group analysis

-t-

+

?

M

F -t-

Industry

+

Service

Other groups

Cheaper supply is not expected to lead to connection of other income categories

Elaboration of impacts

If rising charcoal use leads to higher prices, it could be negative for low and middle income families ?

F

Subsistence

The low n u m b e r of electricity users with cookers will not affect local woodfuel market

?

+

M

Low

It is not possible to identify any specific target group

?

+

M

Female

Male

F

Middle

High

Assessment of target impact

Only very small emergency d e m a n d battery system may be relevant to investigate, if new system impossible

Existing system old and upgrading would be very difficult

Distance to both grid and hydro potential too large - no need for study

Comments

2'

2

J.M. Christensen, R. V. 11". Vidal / Project evaluation for energr' supply in developing countries Table A5 Means-aims hierarchy. Project name: Improvement of charcoal production and utilization Activity Organise local group of metal workers e.g. in a cooperative Survey possible scrap metal sources and design routine for collection Adjust new stove and kiln designs to local traditions and habits Supply tools for 10 metalworkers and maybe a new building

Result

Local basis for production and collection of metal established

Direct aim

Sector aim

Development goal

Production of e.g. 500 stoves early and kilns according to user demand

Ensure that energy resource allocation yields greater social end economic benefit

Promotion of labour intensive production increasing employment

Small scale rural industrialization

Suitable designs of both stoves and kilns developed

10 trained metal workers and the facilities for production provided

Basis for a selfsustained continued production of the products established

Demonstrations of new stoves on market places and in some low-cost housing area

Market response to the new ideas and introduction of the basic saving concept

Sale of the annual production through traditional market structures

Organise network for dissemination of the new type of stoves

The basic sales structure for later dissemination established

Training course in production of new stove and kiln design

Involve charcoal burners in design and test of kilns and find appropriate type of financing for the investments

Participation of the existing users in development process

Reduction of the annual consumption of charcoal by 10% growing by 5% next 4 years

Improve energy supply for rural and urban households

Expansion of the training facilities

Minimize the costs of energy

General rural development

Conserve energy

Improvement of the charcoal production efficiency by 5% growing to 25% in 5 years

Minimize possible environmental consequences of the energy supply and consumption

2

4

Time schedule (year) 0

1

Table A6 Datasheet for low-income households (input) District: Zambezi Total number of households Average household size Average consumption of: - Electricity (kwh) - Charcoal (kg) - Firewood (kg) Kerosene (1) Bottle gas (m3) Wooduse other purposes (kg) -

-

1988

1993

1998

500

550

600

7.30 0 635 2000 40 0 400

7.20 0 1000 1000 0 0 400

7.00 0 1400 700 0 0 400

241

242

J.M. Christensen, R. K V. Vidal / Project evaluation for energy supply in developing countries

Table A7 Wood resource database District: Zambezi Year: 1988 Land use/vegetation Town/village Cultivated land Grasslands Miombo woodland Kalahari woodland Mopane woodland Munga woodland Bush Evergreen forest Deciduous forest Plantations Swamps Open Water Totals/Averages

Import Export

Land area 1 10 794 22 748 0 0 3 220 23 2 1 0 1824

Stock

Availability

Yield factor

Yield

1 3 1 25 18 0 0 0 33 40 50 0 0

100 100 15 3 2 0 0 0 3 3 0 0 0

3 5 6 7 6 0 0 0 10 10 17 0 0

30 1500 7146 1155 16157 0 0 0 21780 2760 0 0 0

12.67

3.22

6.78

Charcoal

Wood

0 0

0 0

Land area in 1000 ha Standing stock in tonnes per ha Availability as the percentage that can be reached Yield factor as the increment percentage available each year Accessible wood yield in tonnes

50 528

J.M. Christensen, R. V. V. Vidal / Project evaluation for energy supply in developing countries

Table A8 Status sheet for the wood use and supply situation Supply (year: 1988) Accessible annual yield Imports-exports (wood) Imports-exports (charcoal)

50528 tonnes 0 tonnes 0 tonnes

(dry wood) (dry wood) (dry wood)

50 528 tonnes

(dry wood)

19681 tonnes 12916 tonnes 2811 tonnes

(dry wood) (dry wood) (dry wood)

0 tonnes 1 tonnes 0 tonnes

(dry wood) (dry wood) (dry wood)

Agriculture Energy purposes Building material Fencing etc

154 tonnes 0 tonnes 30 tonnes

(dry wood) (dry wood) (dry wood)

Tertiary sector Energy purposes Building material Other

76 tonnes 4 tonnes 0 tonnes

(dry wood) (dry wood) (dry wood)

35 671 tonnes

(dry wood)

Available wood supply (without stock cutting) Consumption (Year: 1988) Household consumption of: Firewood Charcoal Poles etc Industrial wood use Energy purposes Raw material Building materials etc.

Total annual wood consumption

Total annual surplus/deficit( - ) 14 857 Tonnes (dry wood) (year 1988)

243

244

J.M. Christensen, R. V.V. Vidal / Project evaluation for energy supply in developing countries

Table A9 S u m m a r y sheet f o r sectoral e n e r g y c o n s u m p t i o n ( G J) in 1988. D i s t r i c t : Z a m b e z i H o u s e sector ( G J) Subsector/ source

Electricity

Charcoal

Fire wood

Kerosene

Gasoline

Total

Per capita

High income M i d d l e inc. Low income Subsistence Other

4455 2580 0 0 0

5208 26 660 39 370 128 960 0

358 7091 15 500 282100 0

0 0 702 5704 0

0 0 0 0 0

10021 36 331 55 572 4 1 6 764 0

27 18 15 11 0

Total

7035

200198

305 0 4 9

6106

0

518 688

11

A g r i c u l t u r a l s e c t o r ( G J ) (1988) Subsector/ source Large farms - domestic productive Medium farm domestic productive Small farms domestic - productive -

-

-

-

Total

Electricity

Charcoal

Firewood

Kerosene

Diesel

Total

0 0

2170 -

217 -

25 -

95

2412 95

0 0

0 -

0 -

0 -

0

0 0

0 0

0 -

0 -

0 -

0

0 0

0

2170

217

25

95

2506

I n d u s t r i a l s e c t o r ( G J ) (1988) Subsector/ source

Electricity

Charcoal

Firewood

Kerosene

Diesel

Gasoline

Sum

Formal Informal

0 155

0 0

0 0

0 0

0 0

0 0

0 155

Total

155

0

0

0

0

0

155

Kerosene

Diesel

Gasoline

Total

0 0 -

344 271 356 0 0 1687 209 1720 0

0

4587

T e r t i a r y sector ( G J ) (1988) Subsector/ source

Electricity

Adm.-Office Transport Hospitals Clinics Schools Service - I n t - Transport Water works Wells

339 . 344 0 516 1720 0

Total

2919

-

Charcoal

Firewood

0

0

5

12 0 930 -

0 0 0 233

-

0 0 0 9 0 -

271 0 0 0 209 0 0

942

233

14

480

.

.

.

245

J.M. Christensen, R. V, V. Vidal / Project evaluation for energy supply in developing countries Table A9 (continued) Total for all sectors (GJ) (1988) Subsector/ source

Electricity

Households Agriculture Industry Tertiary Total

Charcoal

Firewood

Kerosene

Diesel

Gasoline

Total

7035 0 155 2919

200198 2170 0 942

305 049 217 0 233

6406 25 0 14

95 0 480

0 0 0

518 688 2506 155 4587

10108

203 310

305 499

6444

575

0

525 936

Table A12 Net present value (NPV) calculation (kwacha)

Table A10 Basic economic assumptions Project: Scenario: Parameters

New diesel engines testcase Values (1988)

Inflation rate (%) Interest rate (market) (%) Interest rate (state) (%) V.A.T. (%) Privat taxation (%) Currency ( n a m e / n a m e ) Exchange rate (1 US $ = ) State subsidy (%) Loans: - Amort. period (years) - Type Annuity (percentage) - Serial (percentage) Index (percentage) -

-

6 10 10 0 0 kwacha/ngwee 5 0 20 100 0 0

Interest (%) 3 0 0

Project: New diesel engines

Scenario: testcase

Calculations of the economic net present values Investments - 5 454 545 Operational costs - 526 377 Fuel costs - 15 474 809 Fuel savings 29 759 249 Revenues 0

Economic cost-benefit ratio NPV - benefits CBR = N P V - costs

Total NPV

8 303 517

NPV of imports Local (%)

Foreign (%)

20 0 0

80 0 0

- 10329054

Actual CBR CBR =1.39 Foreign loan: 4 800000

Table A l l Economic results (kwacha) (Period 1988-1992) Project: Activities

New diesel engines 1988

Scenario: testcase 1990

1989

1991

1992

Investments

6 000 000

0

0

0

0

- materials import quota (%) labour local part (%)

5000000 100 1 000000 75

0 0 0 0

0 0 0 0

0 0 0 0

0 0 0 0

501300 0 100 50000 100

130 000 30000 100 100000 100

150 000 50000 100 100000 100

200 000 100000 100 100000 100

200 000 100 000 100 100000 100

2080000 4 000 000 0 -4130000 - 4130 000

2184000 4 200 000 0 1886000 - 2 244 000

2 293 200 4 410 000 0 1966800 - 277 200

2407 860 4 630 500 0 2022640 1 745 440

2 528 253 4 862 025 0 2133772 3 879 212

-

-

-

Operational costs - materials import quota (%) - labour local part (%) -

-

Fuel costs Fuel savings Revenues

Cashflow A ccum. cash flow

246

J.M. Christensen, R. V. V. Vidal / Project evaluation for energy supply in developing countries

Table A13 Example of calculation program behind one of the cells WOODRES2: F5 to recalc + display

@eraseprompt,

@ Y I E L D R E S U L T (yield,stock,deforest)

A programme to calculate the resulting yield after a reduction of the stock Using the existing numbers for yield and stock in the wood-resl file and the resulting number for the difference between the available annual yield and the total annual consumption (deforest) from the wood-sup file

@eraseprompt, @local (deforest,accum, i, j, k,reldef), definition of the local variables deforest := [woodsupl].E41, reldef := ( - 1) * deforest/[woodresl].e22, accum := reldef * 5, @if (deforest >/0, @list(@while(i ~ # null!, J := @get([woodresl].eS:[woodresl].e20), @put([woodres2].E8 :[woodres2].E20, j ), i:= @next([woodresl ].e8 :[woodresl].e20), @next([woodres2].E8:[woodres2].E20), @prompt("no reduction in wood stock, same yield available ",10))), @list(@while(i ~ # null!, J := @get([woodresl].e8:[woodresl].e20), k := @get([woodresl].gS:[woodresll.g20), @put([woodres2].ES:[woodres2].E20, j - ( j * accum * k /lO0)), i := @next([woodresl].e8:[woodresl].e20), @next([woodresl].g8:[woodresl].g20), @next([woodres2].ES:[woodres2].E20), @prompt("stock and yield reduced ",20))))