Energy System Modeling For The Least Developed Countries

Energy is a vital commodity and is closely intertwined with climate change anddevelopment. While energy is needed for basic human needs, such as cooking, heating,lighting, boiling water and for other household based activities, it is also required tosustain and expand economic processes like agriculture, electricity production,industries, services and transport. Energy contributes to a virtuous cycle of human,economic and social improvements that are essential to sustainable development indeveloping countries. Sufficient supplies of clean energy are the basis for raisingstandards of living, improving the quality and quantity of human capital, enhancing thebusiness and natural environment, and increasing the efficiency of government policies.In this context energy consumption should be at an affordable cost on a long termbasis without disturbing the ecological balance. This means that energy production andend-use technologies should be environment-friendly and cost-effective. Although thereseem to be no physical limits to the world’s energy supply for at least the next50years,today’s energy system is unsustainable because of equity issues as well asenvironmental, economical and geopolitical concerns that have implications far into thefuture.Global energy use has grown by a factor of more than20over the past200years.This increase constitutes the first major energy transition, a transition from penury toabundance. However, this transition is far from complete, and is characterized bypersistent spatial and temporal heterogeneity. This transition in energy quantities is alsoclosely linked to corresponding energy transitions in terms of energy structure as well asin terms of energy quality.A second important transition is the structural change of energy use in terms ofwhere energy is used, and in what form. This transition entails a move away fromtraditional energy forms, collected locally and used largely in rural areas, to processedmodern energy forms, imported to and used predominantly in urban settings.The other major energy transition is the improvement of energy intensity (orenergy productivity), measured at the aggregate macroeconomic level in terms ofenergy use per unit of GDP. Aggregate energy intensities, including noncommercialenergy use, generally improve over time across all countries. However, the process isnot always smooth, as periods of rapid improvements are interlaced with periods ofstagnation or short-term trend reversals. The patterns of energy intensity improvements in various countries reflect theirdifferent situations and development histories. Economic development is a cumulativeprocess that, in various countries, incorporates different consumption lifestyles,different income levels, different settlement patterns, different transport requirements,different industrial structures, and different take-off dates toward industrialization.Energy transitions and/or consumption can be analyzed, planned and managed bythe use of energy modeling tools to explore the future of the global, regional andnational settings and the effects of energy use on the human and natural environment.There is a great variety of energy models and energy modeling approaches forvarious purposes. However, most of these energy models were built and used byindustrialized countries, so that assumptions about energy systems of developing andleast developed countries were mainly based on the experience from energy systems ofindustrialized countries. It was therefore assumed that the energy systems of developingand least developed countries would behave like those of industrialized countries. It wasfurther assumed, that present day development trajectories for developing and leastdeveloped countries would be similar to the historic development trajectories inindustrialized countries which in reality is not the case. Evidence from rapidlydeveloping countries has shown that this perception of development may be defied.There is, therefore, a need to adapt energy models to properly describe the energy futurefor developing, in particular least developed, countries.Due to varied energy collection and consumption patterns, the energy planningprocess should be different in developed and least developed countries. In LDCs,energy planning should focus on the decentralized management of resources, whicheventually should involve demand and supply management tools such as energy pricingand the marketing of improved technologies.Malawi’s energy, as is the case in many LDCs, is derived from several sources.These include electricity, fuel-wood, petroleum, coal, solar and wind with fuel-woodbeing the most used energy by the majority of the Malawian population both in the ruraland urban areas.The demand for energy consumption for both domestic and industrial consumptionin Malawi has increased over the past decade. During the last decade Malawi has facedproblems of power failure evidenced by frequent blackouts and acute shortage of fuel.The economic implications of this unreliable energy services are daunting. A number ofLDCs, including Malawi, suffer from inadequate generation capacity, limitedelectrification, inefficient systems, and high costs. Countries affected by chronic energy issues take a heavy toll with regard to the loss of economic growth and productivity. Itis therefore of crucial importance to find ways of optimizing the allocation of Malawi’senergy resources to meet the demand and reduce the negative impact that other forms ofenergy have on the economy and environment.In view of the foregoing, this thesis first sets out to find the best option: whether todevelop Malawi’s own national energy system model or to adopt some of the availablemodeling tools. Being in line with the current worldwide trend in energy systemmodeling, it has been suggested that the best approach is to go for both optionssimultaneously. Consequently, the main aim of the thesis is to propose an integratedenergy system model for LDCs. Hence, the modeling tools that have been adopted andintegrated are MAED, AHP and multi-objective programming. Specifically, the thesisaims at (a) developing an energy database and demand projections from2008to2030using MAED;(b) integrating the output from the MAED databases with multi-objectiveprogramming and AHP for policy analysis;(c) implementing this system for the studyarea, in this case Malawi and study the applicability of the model; and (d)recommending possible policy options for the study area.The modeling methodology involved data collection, screening, and analysis. Datawere collected through residential and commercial building energy consumptionsurveys. These surveys were conducted using stratified sampling technique in thehousehold and commercial sectors. In addition to these surveys, data also includedstatistical information, official energy data, and utility data, among others.In order to develop present and future energy demand for the residential andcommercial sectors, an energy balance for the base year (2008) was constructed. Dataon energy consumption from the main economic sectors were collected. For the futureprojection of energy demand, three scenarios have been developed based onassumptions made on important parameters. These assumptions include Gross DomesticProduct (GDP) growth rate, GDP structure, demographic changes, industrialdevelopment, life-style changes, macro-economic data, technology choice andmanagement and Government policies contained in such documents as Malawi Growthand Development Strategy (MGDS), Vision2020, and National Energy Policy (NEP).The three scenarios that have been developed are the reference growth, the acceleratedgrowth and moderate growth scenarios.The projections show that total energy demand will grow from about48,000GWhto60,000GWh,69,000GWh, and54,000GWh under the reference, accelerated andmoderate growth scenarios, respectively, by2030. Final energy demand by sector shows a general increase in energy and electricity demand in all sectors with hugeincreases in industry and transport sectors. Energy demand in industry and transport willboth increase by3times by2030. However, household will still dominate the energydemand. Total energy demand per capita decreases from3,700kWh to about3,000kWh,3,500kWh and2,700kWh under the reference, accelerated, and moderate growthscenarios, respectively, by2030.Electricity demand per capita increases from100kWh to about1,000kWh,1,400kWh and800kWh under the reference, accelerated, and moderate growthscenarios, respectively, by2030. Peak electricity demand has been projected to reach4,274MW,5,352MW and3,622MW in2030under the reference, accelerated, andmoderate growth scenarios, respectively, by2030.The seasonal variation in electricity consumption for commercial and householdsectors shows no significant differences in these two sectors, except during weekends.On a weakly basis the load pattern is almost the same indicating that the demand levelsare not significantly different. However, Sundays have got the lowest demand levelsfollowed by Saturdays and picks up during working days. This is due to the workingpattern observed in the service and industry sectors.Normalized daily load curves show a similar pattern of electricity use inhouseholds for all the seasons. However, there is a significant drop and delay onSaturday and Sunday mornings as compared to working days. The shapes depictdomestic lifestyles and behavior in Malawi. Two peaks are observed one in the morningfrom07:00hours to12:00hours, and the other in the evening, from17:00hours to21:00hours; with the latter being more pronounced and sharp. For the service sector,there are no significant differences in profile shapes. However, the service sectorprofiles show a significant consumption during the day time from0600hours to1800hours. The load factor is also significantly high.Multi-objective analysis has been performed with an aim of maximising the socialwelfare of the people by considering issues of economic efficiency, equity andenvironmental quality. Seven objectives have been considered and the results ofindividual optimizations allocate53,000TJ to firewood and2,500TJ to solar per year.However, being determinant in the multi-objective optimization solution, some theobjectives can have more weight than others which can be based on emphasis of choiceaccording to different technical, economic, environmental or personal preferences. Suchbeing the case, four different scenarios have been assumed in order of privilege. Theseare (1) actions dealing with the best economical benefits,(2) actions devoted to energy saving and rationalization of global energy system,(3) actions generating lowestenvironmental impact, and (4) actions preferring the personal aspects and workingconvenienceThe results with weight allocation to objective functions show that firewood isfavored highly in all the four cases. However, the use of solar PV should also bepromoted except in the economic-oriented scenario, where it loses to charcoal. Thisimplies that its costs must be reduced for it to become favorable. Charcoal finds somefavor in energy saving and global rationalization scenario. When energy saving andglobal rationalization become more important than others, grid electricity is favoredhighly. This is the case because it is suitable for almost all of the end-uses. It isobserved that kerosene has not been allocated at all. This, therefore, means thatkerosene is not suitable for home use.Sensitivity analysis of the objectives has shown that fuel-wood is not a scarceresource in Malawi and that there would be no change in the optimal value in the use offuel-wood products with small changes in any of the constraints. It is further observed(a) that the objective functions representing energy cost, use of petroleum products, anduse of renewable energy resources are sensitive to the estimation of cooking energydemand, hydropower potential and kerosene supply, and (b) that the objectives forsafety, convenience and comfort are sensitive to the estimation of hydropower potentialand kerosene supply.Based on the projections and analysis made in this thesis several recommendationshave been put forward. These include, among others, promotion of solar water heatingand energy efficient housing; installation of energy saver equipments; introduction ofsubsidies and direct financing in the energy sector; forest protection; and exploitation ofthe available hydro resources for electricity generation.