No description available.

<p>Background and Motivation</p><p>Unlike what is common in Europe and the rest of the world, Norway has traditionally met most of its stationary energy demand (including heating) with electricity, because of abundant access to hydropower. However, after the deregulation of the Norwegian electricity market in the 1990s, the increase in the electricity generation capacity has been less than the load demand increase. This is due to the relatively low electricity prices during the period, together with the fact that Norway’s energy companies no longer have any obligations to meet the load growth. The country’s generation capacity is currently not sufficient to meet demand, and accordingly, Norway is now a net importer of electricity, even in normal hydrological years. The situation has led to an increased focus on alternative energy solutions.</p><p>It has been common that different energy infrastructures – such as electricity, district heating and natural gas networks – have been planned and commissioned by independent companies. However, such an organization of the planning means that synergistic effects of a combined energy system to a large extent are neglected. During the last decades, several traditional electricity companies have started to offer alternative energy carriers to their customers. This has led to a need for a more comprehensive and sophisticated energy-planning process, where the various energy infrastructures are planned in a coordinated way. The use of multi-criteria decision analysis (MCDA) appears to be suited for coordinated planning of energy systems with multiple energy carriers. MCDA is a generic term for different methods that help people make decisions according to their preferences in situations characterized by multiple conflicting criteria.</p><p>The thesis focuses on two important stages of a multi-criteria planning task:</p><p>- The initial structuring and modelling phase</p><p>- The decision-making phase</p><p>The Initial Structuring and Modelling Phase</p><p>It is important to spend sufficient time and resources on the problem definition and structuring, so that all disagreements among the decision-maker(s) (DM(s)) and the analyst regarding the nature of the problem and the desired goals are eliminated. After the problem has been properly identified, the next step of a multi-criteria energy-planning process is the building of an energy system model (impact model). The model is used to calculate the operational attributes necessary for the multi-criteria analysis; in other words, to determine the various alternatives’ performance values for some or all of the criteria being considered. It is important that the model accounts for both the physical characteristics of the energy system components and the complex relationships between the system parameters. However, it is not propitious to choose/build an energy system model with a greater level of detail than needed to achieve the aims of the planning project.</p><p>In my PhD research, I have chosen to use the eTransport model as the energy system model. This model is especially designed for planning of local and regional energy systems, where different energy carriers and technologies are considered simultaneously. However, eTransport can currently provide information only about costs and emissions directly connected to the energy system’s operation. Details about the investment plans’ performance on the remaining criteria must be found from other information sources. Guidelines should be identified regarding the extent to which different aspects should be accounted for, and on the ways these impacts can be assessed for each investment plan under consideration. However, it is important to realize that there is not one solution for how to do this that is valid for all kind of local energy-planning problems. It is therefore necessary for the DM(s) and the analyst to discuss these issues before entering the decision-making phase.</p><p>The Decision-Making Phase</p><p>Two case studies have been undertaken to examine to what extent the use of MCDA is suitable for local energy-planning purposes. In the two case studies, two of the most well-known MCDA methods, the Multi-Attribute Utility Theory (MAUT) and the Analytical Hierarchy Process (AHP), have been tested. Other MCDA methods, such as GP or the outranking methods, could also have been applied. However, I chose to focus on value measurement methods as AHP and MAUT, and have not tested other methods. Accordingly, my research cannot determine if value measurement methods are better suited for energy-planning purposes than GP or outranking methods are.</p><p>Although all MCDA methods are constructed to help DMs explore their ‘true values’ – which theoretically should be the same regardless of the method used to elicit them – our experiments showed that different MCDA methods do not necessarily provide the same results. Some of the differences are caused by the two methods’ different ways of asking questions, as well as the DMs’ inability to express clearly their value judgements by using one or both the methods. In particular, the MAUT preference-elicitation procedure was difficult to understand and accept for DMs without previous experience with the utility concept. An additional explanation of the differences is that the external uncertainties included in the problem formulation are better accounted for in MAUT than in AHP. There are also a number of essential weaknesses in the theoretical foundation of the AHP method that may have influenced the results using that method. However, the AHP method seems to be preferred by DMs, because the method is straightforward and easier to use and understand than the relatively complex MAUT method.</p><p>It was found that the post-interview process is essential for a good decision outcome. For example, the results from the preference aggregation may indicate that according to the DM’s preferences, a modification of one of the alternatives might be propitious. In such cases, it is important to realize that MCDA is an iterative process. The post-interview process also includes presentation and discussion of results with the DMs. Our experiments showed that the DMs might discover inconsistencies in the results; that the results do not reflect the DM’s actual preferences for some reason; or that the results simply do not feel right. In these cases, it is again essential to return to an earlier phase of the MCDA process and conduct a new analysis where these problems or discrepancies are taken into account.</p><p>The results from an MAUT analysis are usually presented to the DMs in the form of expected total utilities given on a scale from zero to one. Expected utilities are convenient for ranking and evaluation of alternatives. However, they do not have any direct physical meaning, which quite obviously is a disadvantage from an application point of view. In order to improve the understanding of the differences between the alternatives, the Equivalent Attribute Technique (EAT) can be applied. EAT was tested in the first of the two case studies. In this case study, the cost criterion was considered important by the DMs, and the utility differences were therefore converted to equivalent cost differences. In the second case study, the preference elicitation interviews showed, quite surprisingly, that cost was not considered among the most important criteria by the DMs, and none of the other attributes were suitable to be used as the equivalent attribute. Therefore, in this case study, the use of EAT could not help the DMs interpreting the differences between the alternatives.</p><p>Summarizing</p><p>For MCDA to be really useful for actual local energy planning, it is necessary to find/design an MCDA method which: (1) is easy to use and has a transparent logic; (2) presents results in a way easily understandable for the DM; (3) is able to elicit and aggregate the DMs' real preferences; and (4) can handle external uncertainties in a consistent way.</p>

Background and Motivation Unlike what is common in Europe and the rest of the world, Norway has traditionally met most of its stationary energy demand (including heating) with electricity, because of abundant access to hydropower. However, after the deregulation of the Norwegian electricity market in the 1990s, the increase in the electricity generation capacity has been less than the load demand increase. This is due to the relatively low electricity prices during the period, together with the fact that Norway’s energy companies no longer have any obligations to meet the load growth. The country’s generation capacity is currently not sufficient to meet demand, and accordingly, Norway is now a net importer of electricity, even in normal hydrological years. The situation has led to an increased focus on alternative energy solutions. It has been common that different energy infrastructures – such as electricity, district heating and natural gas networks – have been planned and commissioned by independent companies. However, such an organization of the planning means that synergistic effects of a combined energy system to a large extent are neglected. During the last decades, several traditional electricity companies have started to offer alternative energy carriers to their customers. This has led to a need for a more comprehensive and sophisticated energy-planning process, where the various energy infrastructures are planned in a coordinated way. The use of multi-criteria decision analysis (MCDA) appears to be suited for coordinated planning of energy systems with multiple energy carriers. MCDA is a generic term for different methods that help people make decisions according to their preferences in situations characterized by multiple conflicting criteria. The thesis focuses on two important stages of a multi-criteria planning task: - The initial structuring and modelling phase - The decision-making phase The Initial Structuring and Modelling Phase It is important to spend sufficient time and resources on the problem definition and structuring, so that all disagreements among the decision-maker(s) (DM(s)) and the analyst regarding the nature of the problem and the desired goals are eliminated. After the problem has been properly identified, the next step of a multi-criteria energy-planning process is the building of an energy system model (impact model). The model is used to calculate the operational attributes necessary for the multi-criteria analysis; in other words, to determine the various alternatives’ performance values for some or all of the criteria being considered. It is important that the model accounts for both the physical characteristics of the energy system components and the complex relationships between the system parameters. However, it is not propitious to choose/build an energy system model with a greater level of detail than needed to achieve the aims of the planning project. In my PhD research, I have chosen to use the eTransport model as the energy system model. This model is especially designed for planning of local and regional energy systems, where different energy carriers and technologies are considered simultaneously. However, eTransport can currently provide information only about costs and emissions directly connected to the energy system’s operation. Details about the investment plans’ performance on the remaining criteria must be found from other information sources. Guidelines should be identified regarding the extent to which different aspects should be accounted for, and on the ways these impacts can be assessed for each investment plan under consideration. However, it is important to realize that there is not one solution for how to do this that is valid for all kind of local energy-planning problems. It is therefore necessary for the DM(s) and the analyst to discuss these issues before entering the decision-making phase. The Decision-Making Phase Two case studies have been undertaken to examine to what extent the use of MCDA is suitable for local energy-planning purposes. In the two case studies, two of the most well-known MCDA methods, the Multi-Attribute Utility Theory (MAUT) and the Analytical Hierarchy Process (AHP), have been tested. Other MCDA methods, such as GP or the outranking methods, could also have been applied. However, I chose to focus on value measurement methods as AHP and MAUT, and have not tested other methods. Accordingly, my research cannot determine if value measurement methods are better suited for energy-planning purposes than GP or outranking methods are. Although all MCDA methods are constructed to help DMs explore their ‘true values’ – which theoretically should be the same regardless of the method used to elicit them – our experiments showed that different MCDA methods do not necessarily provide the same results. Some of the differences are caused by the two methods’ different ways of asking questions, as well as the DMs’ inability to express clearly their value judgements by using one or both the methods. In particular, the MAUT preference-elicitation procedure was difficult to understand and accept for DMs without previous experience with the utility concept. An additional explanation of the differences is that the external uncertainties included in the problem formulation are better accounted for in MAUT than in AHP. There are also a number of essential weaknesses in the theoretical foundation of the AHP method that may have influenced the results using that method. However, the AHP method seems to be preferred by DMs, because the method is straightforward and easier to use and understand than the relatively complex MAUT method. It was found that the post-interview process is essential for a good decision outcome. For example, the results from the preference aggregation may indicate that according to the DM’s preferences, a modification of one of the alternatives might be propitious. In such cases, it is important to realize that MCDA is an iterative process. The post-interview process also includes presentation and discussion of results with the DMs. Our experiments showed that the DMs might discover inconsistencies in the results; that the results do not reflect the DM’s actual preferences for some reason; or that the results simply do not feel right. In these cases, it is again essential to return to an earlier phase of the MCDA process and conduct a new analysis where these problems or discrepancies are taken into account. The results from an MAUT analysis are usually presented to the DMs in the form of expected total utilities given on a scale from zero to one. Expected utilities are convenient for ranking and evaluation of alternatives. However, they do not have any direct physical meaning, which quite obviously is a disadvantage from an application point of view. In order to improve the understanding of the differences between the alternatives, the Equivalent Attribute Technique (EAT) can be applied. EAT was tested in the first of the two case studies. In this case study, the cost criterion was considered important by the DMs, and the utility differences were therefore converted to equivalent cost differences. In the second case study, the preference elicitation interviews showed, quite surprisingly, that cost was not considered among the most important criteria by the DMs, and none of the other attributes were suitable to be used as the equivalent attribute. Therefore, in this case study, the use of EAT could not help the DMs interpreting the differences between the alternatives. Summarizing For MCDA to be really useful for actual local energy planning, it is necessary to find/design an MCDA method which: (1) is easy to use and has a transparent logic; (2) presents results in a way easily understandable for the DM; (3) is able to elicit and aggregate the DMs' real preferences; and (4) can handle external uncertainties in a consistent way.

This thesis examines energy planning to reduce GHG emissions from cities. Examining federal government policy to reduce GHG emissions suggests that municipalities and provinces may be the better government levels for action. A review of types of municipal energy planning, and energy-GHG reduction plans from three cities shows different strategies and policies in implementation, and differing levels of success. Interviewing planners from these case-study cities provides critical insight into the challenges of implementing energy-GHG planning. The lessons learned show the best course of action for other jurisdictions, including the importance of an appropriate policy framework to support municipalities. Such a framework is suggested by this thesis. This research is meant to inform planners of best practices, challenges, opportunities, and courses of action for municipalities in formulating GHG reduction strategies.

This thesis examines energy planning to reduce GHG emissions from cities. Examining federal government policy to reduce GHG emissions suggests that municipalities and provinces may be the better government levels for action. A review of types of municipal energy planning, and energy-GHG reduction plans from three cities shows different strategies and policies in implementation, and differing levels of success. Interviewing planners from these case-study cities provides critical insight into the challenges of implementing energy-GHG planning. The lessons learned show the best course of action for other jurisdictions, including the importance of an appropriate policy framework to support municipalities. Such a framework is suggested by this thesis. This research is meant to inform planners of best practices, challenges, opportunities, and courses of action for municipalities in formulating GHG reduction strategies.

No description available.

As energy security and climate issues are emerging as global concerns, it is commonly agreed that a transition from a conventional centralized energy system, which is largely based on combustion of fossil fuel, to a more sustainable decentralized energy system that includes mainly renewable energy sources is necessary and urgent. Due to the highly variable geographical qualities of renewable energy sources, spatial energy planning is becoming essential. This study aims to address the challenges in linking spatial modelling with assessment of regional energy consumption and renewable energy supply potential. A novel approach for exploring the feasibility of achieving energy self-sufficiency through matching energy deficit areas with energy surplus areas is proposed. A method for energy deficit and surplus area matching is developed and implemented in a VBA- based tool that serves as a decision-support tool by exploring possible future deployment of renewable energy in decentralized ways. Achieving Ontario residential electricity self-sufficiency through solar PV energy on an annual basis is explored as a case study. The results show that it is technically feasible for Ontario to be residential electricity self-sufficient through the development of solar PV energy with energy deficit areas within the region getting energy supply from nearby energy surplus areas. The case study implies that regional residential electricity self- sufficiency is achievable and it is useful for planners and policy makers to bear the regional energy deficit-surplus matching idea in mind when making urban and energy plans.

<p>Planning is what sustains an energy system. It is a process of analysis and ongoing decision making about what resources and energy technologies to use when supplying energy to society. This research focuses on integrated energy systems, i.e. systems that are comprised of several energy carriers – electricity, gas, hot water - and energy distribution networks. The planning of these kinds of systems is a complex process, influenced by many factors, among which the most important are the availability of energy resources and the competition between different energy carriers in satisfying energy demand. During the last 10-20 years significant changes have taken place on the world energy scene, which have important implications for energy planning. Two main factors have triggered these changes. The first factor is the immediate need to address environmental changes or more generally, to take measures that are sustainable in the long run. Sustainability can be defined in many ways and in relation to different issues such as economic and ecologic development, reduction of greenhouse gases, responsible use of natural resources, social equity, etc. In recent years, an increased awareness of these issues has been observed at all levels of the society. The second factor is the deregulation of national energy sectors in more than 50 countries. This process brought changes in the ownership of different parts of the formerly integrated energy systems. New business opportunities were created in power generation, wholesale power/gas trading and energy retailing, while the energy infrastructures remained state owned or/and under regulatory control. The newly created energy markets (many of them international) have attracted both new players (power, oil and gas companies and financial institutions) together with the old ones (integrated utilities). In parallel with this vertical separation of national energy sectors, recent studies have shown a tendency for horizontal integration at the regional/company level. For instance, in order to reduce their overall business risk, companies prefer to participate in several segments of the energy value chain (in both regulated and non-regulated activities), and often across more than one fuel commodity, such as gas and electricity or district heating. In this context, the competition between different energy carriers in satisfying the end-use energy demand became obvious in economic as well as in technological and environmental terms. Traditionally, in integrated planning, this competition did not play a big role, since the same state entity made decisions at both national and regional levels. However, in the post-deregulation era it is no longer obvious who the planner is. In many cases, planning decision at local levels involve at least three main interest groups: energy companies (and/or other investors), the state and the local community. This thesis is motivated by the need to help planners to cope with the changes in concepts and values concerning the planning of local energy supply systems. This thesis has two aims. The first aim is to improve the understanding of what planning of local systems implies and how such a process can be structured. The second aim is to contribute to the development of decision support methodologies and tools that can cope with the needs in planning. For this purpose, the use of energy modelling and Multi- Criteria Decision Analysis has been studied.</p>

Planning is what sustains an energy system. It is a process of analysis and ongoing decision making about what resources and energy technologies to use when supplying energy to society. This research focuses on integrated energy systems, i.e. systems that are comprised of several energy carriers – electricity, gas, hot water - and energy distribution networks. The planning of these kinds of systems is a complex process, influenced by many factors, among which the most important are the availability of energy resources and the competition between different energy carriers in satisfying energy demand. During the last 10-20 years significant changes have taken place on the world energy scene, which have important implications for energy planning. Two main factors have triggered these changes. The first factor is the immediate need to address environmental changes or more generally, to take measures that are sustainable in the long run. Sustainability can be defined in many ways and in relation to different issues such as economic and ecologic development, reduction of greenhouse gases, responsible use of natural resources, social equity, etc. In recent years, an increased awareness of these issues has been observed at all levels of the society. The second factor is the deregulation of national energy sectors in more than 50 countries. This process brought changes in the ownership of different parts of the formerly integrated energy systems. New business opportunities were created in power generation, wholesale power/gas trading and energy retailing, while the energy infrastructures remained state owned or/and under regulatory control. The newly created energy markets (many of them international) have attracted both new players (power, oil and gas companies and financial institutions) together with the old ones (integrated utilities). In parallel with this vertical separation of national energy sectors, recent studies have shown a tendency for horizontal integration at the regional/company level. For instance, in order to reduce their overall business risk, companies prefer to participate in several segments of the energy value chain (in both regulated and non-regulated activities), and often across more than one fuel commodity, such as gas and electricity or district heating. In this context, the competition between different energy carriers in satisfying the end-use energy demand became obvious in economic as well as in technological and environmental terms. Traditionally, in integrated planning, this competition did not play a big role, since the same state entity made decisions at both national and regional levels. However, in the post-deregulation era it is no longer obvious who the planner is. In many cases, planning decision at local levels involve at least three main interest groups: energy companies (and/or other investors), the state and the local community. This thesis is motivated by the need to help planners to cope with the changes in concepts and values concerning the planning of local energy supply systems. This thesis has two aims. The first aim is to improve the understanding of what planning of local systems implies and how such a process can be structured. The second aim is to contribute to the development of decision support methodologies and tools that can cope with the needs in planning. For this purpose, the use of energy modelling and Multi- Criteria Decision Analysis has been studied.

Geographic information systems (GIS) are increasingly being used in energy planning and by private sector practitioners. Through qualitative interviews with 49 leading practitioners in the public and private sector, this thesis establishes the data of most importance, current open access data sources for energy access along with the information currently lacking from open data sources. The interviews revealed grid infrastructure, population density, renewable power potential and energy expenditure to be the most sought after data for both practitioners’ groups. However, it was evident that the private sector had a stronger focus on land, water resource and climate data determining the renewable power potential for a specific area of interest, while the public sector focused on socioeconomic indicators and energy expenditure. A following data aggregation and analysis of the most desired datasets showed that a majority of the needed datasets were available with the exception of energy expenditure. A least-cost option electrification model developed by KTH-dESA has proven to be a powerful tool in assessing the cost of nationwide electrification. This thesis compares the average least-cost option electrification cost for each region in Tanzania with a projected average income. The comparison showed that the average household cost for least-cost option electrification as a share of projected household income varies between regions. The average share per household in the western regions of Tanzania were significantly higher compared to households in the central and eastern regions. The comparison was combined with the geographical location of donor-supported energy development projects showing that majority of the projects were located in the central parts of Tanzania and not targeting the most vulnerable households in regions furthest away from the national grid. In order to successfully introduce electricity nationwide in Tanzania, more support needs to be provided to the poorest regions.  Open data aggregation and coordination are the key to expand the support from GIS for energy access. Even though multiple data sources have been identified, they are scattered and leads to data being collected again. Coordinated efforts aimed to provide means to share aggregated updated and freely accessible data can help reduce high transaction costs, helping to alleviate energy poverty. / Geografiska informationssystem (GIS) används i allt större utsträckning inom energiplanering och av privata aktörer. Genom kvalitativa intervjuer med 49 ledande aktörer i offentlig och privat sektor redogör denna rapport för de viktigaste dataseten för aktörer, befintliga källor för öppen data och vilka informationsluckor som finns i dessa källor. Intervjuerna visade att dataseten gällande energiinfrastruktur, befolkningstäthet, potential för förnybar energi och energiutgifter var viktigast för både offentlig och privat sektor. Privat sektor hade ett större fokus på land, vatten och klimatdata, som alla är viktiga för att avgöra ett områdes potential för förnybar energi. Offentlig sektor hade ett större intresse av socioekonomiska faktorer och energiutgifter. En dataaggregation och analys visade att de mest eftertraktade dataseten fanns öppet tillgängliga med undantag för energiutgifter. En modell för energialternativ till lägsta kostnad utvecklad av KTH-dESA har visat sig vara ett kraftfullt verktyg för att kostnadsbedöma en landsomfattande elektrifiering. I en fallstudie för Tanzania jämför denna rapport den genomsnittliga kostnaden för hushåll för en implementering av en sådan elektrifiering med en beräknad genomsnittlig hushållsinkomst. Jämförelsen visade att kostnaden för hushållen som andel av total hushållsinkomst varierar kraftigt mellan regioner. Den genomsnittliga andelen av hushållsinkomsten som skulle läggas på elektricitet i de västra regionerna av Tanzania var betydligt högre jämfört med de centrala och östra regionerna. Jämförelsen kombinerade även detta resultat med den geografiska positionen hos biståndsstödda energiprojekt. vilken visade att majoriteten av dessa projekt fanns i de centrala delarna av landet och inte i de mest utsatta regionerna som präglas av låg genomsnittlig inkomst och långa avstånd till det nationella kraftnätet. För att framgångsrikt kunna genomföra en landsomfattande elektrifiering behöver mer stöd ges till dessa regioner. Aggregation av öppen data och koordinering är nyckeln till att framgångsrikt utveckla GIS som stöd vid framtida energiprojekt som syftar till att ge fler tillgång till elektricitet. Trots att flertalet datakällor kunde identifieras är dessa spridda vilket leder till att data behöver samlas in gång på gång. Koordinerade insatser för att öka möjligheten till att dela redan insamlad öppen och uppdaterad data kan bidra till att minska transaktionskostnader och därmed minska energifattigdomen