A paradigm shift in distribution system design and planning is being led by the deregulation of the power industry and the increasing adoption of distributed generation (DG). Technology advances have made DG investments feasible by both local distribution companies (LDCs) and small power producers (SPPs). LDCs are interested in finding optimal long term plans that best serve their customers at the lowest cost. SPPs, as private entities, are concerned about maximizing their rates of return. Also keenly interested in distribution design and planning is the government, which, through an electricity regulator, strives to meet DG penetration and emissions reduction goals through policy implementations. This thesis first examines the distribution system planning problem from the LDC's perspective. An innovative hierarchical dynamic optimization model is proposed for the planning of distribution systems and the energy scheduling of units that is also capable of reconciling uncoordinated SPP investments in DG. The first stage of the two-stage framework consists of a siting-cum-period planning model that sets element sizing and commissioning dates. The second stage consists of a capacity-cum-production planning model that finalizes element capacities and energy import/export and production schedules. The proposed framework is demonstrated on a 32-bus radial distribution system. Four case studies encompassing different policy sets are also conducted, demonstrating that this model's usefulness also extends to predicting the impact of different energy policies on distribution system operation and economics. The analysis of different policy sets is further expanded upon through the proposal of a new mathematical model that approaches the distribution design problem from the regulator's perspective. Various case studies examining policies that may be used by the regulator to meet DG penetration and emissions goals, through DG investment, are constructed. A combination of feed-in-tariffs, CO$_2$ tax, and cap-and-trade mechanisms are among the policies studied. The results, in the context of Ontario, Canada and its Standard Offer Program, are discussed, with respect to achieving objectives in DG investment, participation by SPPs, consumer costs, and uncertainty in carbon market prices. In jurisdictions such as Ontario, the LDC cannot invest in its own DG capacity but must accommodate those of SPPs. With the successful implementation of DG investment incentives by the regulator, there is a potential for significant investments in DG by SPPs, which may exceed that of the LDCs ability to absorb. This thesis proposes a novel method that can be used by the regulator or LDC to fairly assess, coordinate, and approve multiple competing investments proposals while maintaining operational feasibility of the distribution system. This method uses a feedback between the LDC and SPPs to achieve maximum investor participation while adhering to the technical operational limits of the distribution system. The proposed scheme is successfully demonstrated on a 32-bus radial distribution system, where it is shown to increase SPP-DG investments and production, improve the system's voltage profile, and reduce losses.

A paradigm shift in distribution system design and planning is being led by the deregulation of the power industry and the increasing adoption of distributed generation (DG). Technology advances have made DG investments feasible by both local distribution companies (LDCs) and small power producers (SPPs). LDCs are interested in finding optimal long term plans that best serve their customers at the lowest cost. SPPs, as private entities, are concerned about maximizing their rates of return. Also keenly interested in distribution design and planning is the government, which, through an electricity regulator, strives to meet DG penetration and emissions reduction goals through policy implementations. This thesis first examines the distribution system planning problem from the LDC's perspective. An innovative hierarchical dynamic optimization model is proposed for the planning of distribution systems and the energy scheduling of units that is also capable of reconciling uncoordinated SPP investments in DG. The first stage of the two-stage framework consists of a siting-cum-period planning model that sets element sizing and commissioning dates. The second stage consists of a capacity-cum-production planning model that finalizes element capacities and energy import/export and production schedules. The proposed framework is demonstrated on a 32-bus radial distribution system. Four case studies encompassing different policy sets are also conducted, demonstrating that this model's usefulness also extends to predicting the impact of different energy policies on distribution system operation and economics. The analysis of different policy sets is further expanded upon through the proposal of a new mathematical model that approaches the distribution design problem from the regulator's perspective. Various case studies examining policies that may be used by the regulator to meet DG penetration and emissions goals, through DG investment, are constructed. A combination of feed-in-tariffs, CO$_2$ tax, and cap-and-trade mechanisms are among the policies studied. The results, in the context of Ontario, Canada and its Standard Offer Program, are discussed, with respect to achieving objectives in DG investment, participation by SPPs, consumer costs, and uncertainty in carbon market prices. In jurisdictions such as Ontario, the LDC cannot invest in its own DG capacity but must accommodate those of SPPs. With the successful implementation of DG investment incentives by the regulator, there is a potential for significant investments in DG by SPPs, which may exceed that of the LDCs ability to absorb. This thesis proposes a novel method that can be used by the regulator or LDC to fairly assess, coordinate, and approve multiple competing investments proposals while maintaining operational feasibility of the distribution system. This method uses a feedback between the LDC and SPPs to achieve maximum investor participation while adhering to the technical operational limits of the distribution system. The proposed scheme is successfully demonstrated on a 32-bus radial distribution system, where it is shown to increase SPP-DG investments and production, improve the system's voltage profile, and reduce losses.

How sustainable is Australia’s pattern of energy supply and use? What are the major factors explaining Australia’s sustainable energy performance relative to other countries? This thesis explores energy supply and use in Australia during the 1990s and 2000s and examines major drivers such as policy decisions, economic structure and trade profile. Performance and drivers in Australia are compared with other OECD countries. / To address the questions posed above, it is first necessary to explore the concepts of ‘sustainable development’ and ‘sustainable energy’ and consider how best to measure sustainable energy performance. Alternative sustainability frameworks and models are examined, with the ‘strong sustainability’ model adopted for this thesis being distinguished from other models in three principal ways: i) it places biophysical constraints on economic activity; ii) it regards certain critical natural capital is being non-substitutable; and iii) it places roughly equal emphasis on intra- and intergenerational equity. The strong sustainability model is operationalised into a series of principles and objectives for energy sustainability, which in turn are used as a basis for systematically developing a suite of sustainable energy indicators. This approach is preferred over other approaches to assessing sustainable energy performance given the study’s focus on measurable objectives and outcomes. / The second part of the thesis is devoted to measuring the sustainable energy performance of Australia and other OECD countries against twelve indicators. Some of the indicators selected are ‘standard’, being quite commonly used in other contexts. A number of the indicators though, are unique or have unique features that increase their validity as measures of strong sustainability. Initial results of the performance assessment suggest that Australia is amongst the weakest performing OECD countries, ranking last of all OECD countries against two of the twelve sustainable energy indicators and in the lower quartile of OECD countries against a further six indicators. Further analysis, combining and weighting indicator scores and country rankings across the 12 indicators confirms Australia’s poor performance. Australia ranks 28th of 30 OECD countries by two different ranking methods and 15th of 16 OECD countries by another two methods. Only the USA ranks consistently lower than Australia. Denmark consistently ranks highest of all countries by all methods. / The third and final part of the thesis examines drivers of sustainable energy performance by Australia and a subset of four OECD countries: Denmark, Germany, the Netherlands and Sweden (OECD 4). The primary basis for OECD 4 selection was strong performance against the sustainable energy indicators, although other criteria including economic structure, trade and demography were also considered. A range of techniques, including factorisation, ‘what if’ analysis and linear regression are used to diagnose the underlying factors driving the performance of Australia and the OECD 4 against the sustainable energy indicators. The analysis is extended to include a qualitative assessment of policy drivers including strategic and institutional settings, energy pricing, electricity market policies, R & D and regulation. / A major conclusion of the thesis based on the analysis is that Australia’s weak sustainable energy performance since 1990, relative to other OECD countries, has been substantially shaped by domestic policy decisions, decisions that were not inevitable given Australia’s economic structure, trade profile, demography, and geography.

Die vorliegende Arbeit untersucht wie rationale Entscheidungsfindungen in Transformationsländern katalysiert werden können, indem durch den Fokus auf die internationale Wertschöpfungskette Synergieeffekte zwischen den Unternehmen genutzt und in deren Folge die Transaktionskosten, für Investitionsentscheidungen in energieeffiziente Technologien und Prozesse zur Erfüllung der Emissionsreduktionen, gesenkt werden können. Es wird das Wirken der Marktmechanismen analysiert und der Fokus auf die Transformationstheorie sowie die Ingenieurwissenschaften gelegt. Das Supply Chain Management, als anwendungsorientierte Realwissenschaft mit expliziter Ausrichtung auf Wertschöpfungsprozesse, wird in Bezug auf strategische Investitionsentscheidungen im Allgemeinen und Investitionen in Energieeffizienzmaßnahmen im Speziellen, weiterentwickelt. Mit Hilfe einer empirisch basierten Fallstudie werden die abgeleiteten Erkenntnisse einer kritischen Prüfung unterzogen und beispielhaft dargestellt, wie das entwickelte Entscheidungsmodell eingesetzt werden kann.:Inhaltsverzeichnis Geleitwort ................................................................................................................ III Danksagung ............................................................................................................ IV Inhaltsverzeichnis ...................................................................................................... V Formelverzeichnis .................................................................................................... XI Abkürzungsverzeichnis............................................................................................. XII Teil A Konzeption der Arbeit...................................................................................... 16 1 Einführung – Integrierte Klima- und Energiepolitik und Entscheidungstheorie .. 16 2 Problemstellung...................................................................................... 25 3 Zielsetzung der Arbeit.............................................................................. 27 4 Wissenschaftstheoretische Fundierung und Methodischer Aufbau der Arbeit .. 30 4.1 Zur wissenschaftlichen Fundierung der Arbeit ................................................... 30 4.2 Aufbau der Arbeit und Beitrag zum wissenschaftlichen Erkenntnisfortschritt .......... 34 Teil B Theoretischer Bezugsrahmen........................................................................... 40 5 Basale Begriffe und Definitionen ............................................................... 40 5.1 Kohlenstoffdioxid und andere Treibhausgase .................................................... 40 5.2 Der Effizienzbegriff ........................................................................................ 44 5.3 Energie-Effizienz-Indikatoren .......................................................................... 47 5.4 Unternehmensrelevante Normen..................................................................... 52 5.5 Theoretischer Ansatz des Supply Chain Managements ...................................... 55 5.6 Transformationsländer und Systemtransformation ............................................. 62 5.6.1 Zum Begriff des Transformationslandes ..................................................... 62 5.6.2 Ökonomische Systemtransformation in Transformationsländern.................... 66 5.6.3 Bedeutung der Energieeffizienz in der polnischen Industrie im Rahmen des Transformationsprozesses ....................................................................... 71 5.6.4 Die Industrie Rumäniens unter energetischem Gesichtspunkt ....................... 74 5.7 Transaktionskostentheorie.............................................................................. 78 5.7.1 Die Transaktionskostentheorie im Rahmen der Neuen Institutionentheorie ..... 78 5.7.2 Transaktionskosten im Rahmen des Emissionshandels................................ 83 5.8 System -und Entscheidungstheorie.................................................................. 85 5.8.1 Grundlagen der System– und Entscheidungstheorie.................................... 85 5.8.2 Betriebswirtschaftliche Entscheidungstheorie.............................................. 90 5.8.2.1 Zum Problembegriff....................................................................................90 5.8.2.2 Alternativenkonfiguration............................................................................92 5.8.2.3 Präferenzmodellierung ...............................................................................94 5.8.3 Unternehmenspolitische Entscheidungsansätze.......................................... 96 5.8.3.1 Argumentenbilanz ......................................................................................96 5.8.3.2 Nutzwertanalyse.........................................................................................97 5.8.3.3 Portfolioanalyse..........................................................................................99 VI 5.8.4 Die Entscheidungsorientierte Betriebswirtschaftslehre................................ 102 5.8.5 Modellklassen ...................................................................................... 109 5.8.6 Entscheidungsregeln............................................................................. 112 5.8.6.1 Entscheidungsregeln bei Unsicherheit .....................................................116 5.8.6.1.1 Minimax-Entscheidungsregel.............................................................116 5.8.6.1.2 Maximax- Entscheidungsregel...........................................................116 5.8.6.1.3 Hurwicz-Entscheidungsregel (Pessimissmus-Optimismus-Regel) .....117 5.8.6.1.4 Savage-Niehans-Entscheidungsregel................................................118 5.8.6.1.5 Laplace-Entscheidungsregel .............................................................119 5.8.6.2 Entscheidungsregeln bei Risiko ...............................................................121 5.8.6.2.1 Erwartungswert-Regel .......................................................................121 5.8.6.2.2 μ -σ -Regel.......................................................................................121 5.8.6.2.3 Bernoulli-Regel..................................................................................122 5.8.6.2.4 Entscheidungsbaum..........................................................................123 5.8.7 Anforderungen an ein Entscheidungsmodell ............................................. 125 Teil C Energieeffizienzstrategien: Europäische Union versus Transformationsländer ...... 128 6 Integrierte Ansätze zur Energieeffizienzsteigerung in Transformationsländern128 6.1 Emissionshandel als marktorientierter Mechanismus zur Effizienzerhöhung ........ 128 6.2 Ordnungspolitik versus Marktmechanismen – Kohlenstoffdioxidsteuer und Handel mit Emissionsrechten............................................................................................... 131 6.3 Die flexiblen Mechanismen des Kyoto -Protokolls ............................................ 136 6.3.1 Clean development mechanism.............................................................. 141 6.3.2 Joint Implementation ............................................................................. 143 6.4 Unternehmensstrategien unter cap – and trade Regulierung ............................. 152 Teil D Energieeffizienzinvestitionen entlang der Wertschöpfungskette........................... 156 7 Herausarbeitung des Handlungsbedarfes für Investitionen in Energieeffizienztechnologien – das ENEFFTECH-Entscheidungsmodell ....................... 156 7.1 Anforderungen an das ENEFFTECH-Entscheidungsmodell............................... 156 7.2 Das ENEFFTECH-Strukturmodell .................................................................. 157 7.3 Datenmodellierung im ENEFFTECH-Strukturmodell......................................... 158 7.3.1 Grundsätze der Datenmodellierung im ENEFFTECH-Strukturmodell............ 158 7.3.2 Informationsarchitektur und Prozessgestaltung für Strategisches Supply Chain Management ........................................................................................ 160 7.3.3 Datenmodell – Informationsebene ........................................................... 166 7.3.4 Datenmodell - Datenerfassungebene....................................................... 169 7.3.5 Datenmodell - Entscheidungsebene ........................................................ 171 7.3.5.1 Vorgaben zur Berechnung........................................................................171 7.3.5.2 Investitionsalternativen.............................................................................172 7.3.5.3 Umweltzustände.......................................................................................173 7.4 Abgrenzung von Bilanzräumen...................................................................... 174 7.5 Formulierung des Entscheidungsproblems...................................................... 178 7.6 Identifizierung von Handlungsalternativen auf Unternehmensebene ................... 183 7.7 Ableitung von Aussagen auf Branchenebene .................................................. 190 VII 7.7.1 Mikro-Makro-Link (MML) ........................................................................ 190 7.7.2 Erfassung relevanter Daten zur Ableitung von Branchenaussagen............... 194 7.7.3 Erweiterung des Ansatzes auf Emissionsreduzierende Energieeffizienzsteigerung ..................................................................... 199 7.7.4 Bewertung des ENEFFTECH-Entscheidungsmodell und Vergleich mit anderen Entscheidungsmethoden........................................................................ 203 8 Modelltest: Fallstudie zum ENEFFTECH-Entscheidungsmodell ................... 205 8.1 Energieeffizienzinvestionen entlang der Supply Chain am Beispiel eines mittelständischen Energieversorgers..................................................................... 205 8.1.1 Allgemeine Informationen und Rahmenbedingungen ................................. 205 8.1.2 Auswahl des Kooperationspartners der Stadtwerke ENEFFTECH-Stadt GmbH... .......................................................................................................... 206 8.1.3 Rahmenbedingungen hinsichtlich des Emissionshandels............................ 208 8.1.4 Auswahl der Wertschöpfungspartner ....................................................... 211 8.2 Lösungsansätze unter Nutzung des Supply Chain Managements ...................... 212 8.2.1 Systematisierung der Investitionsalternativen............................................ 212 8.2.2 Ableitung der Investitionsentscheidung .................................................... 217 Teil E Zusammenfassung und Schlussbetrachtungen ................................................. 220 9 Zusammenfassung und Fazit der Arbeit ................................................... 220 9.1 Zusammenfassende Einschätzung ................................................................ 220 9.2 Quo Vadis? - Ableitung des weiteren Forschungsbedarfes................................ 225 Symbole, Einheiten und Umrechnungen ................................................................... 227 Glossar ................................................................................................................ 229 Literatur- und Quellenverzeichnis............................................................................. 244 Anhang ................................................................................................................ 276