Long-term Energy Demand in the German Residential Sector
Development of an Integrated Modelling Concept to Capture Technological Myopia
Zusammenfassung
Diese Arbeit beschäftigt sich mit dem Thema der Abnahme des technologischen Wissens über die Zeit und der damit einhergehenden Begrenzung von techno-ökonomischen Energienachfragemodellen, die zukünftige Energienachfrage im Rahmen von Langfristszenarien antizipieren. Da es sich hierbei um eine prinzipielle Limitation von Ex-ante-Analysen handelt, wird dieser Mangel seit längerem diskutiert, ohne dass bisher methodische Lösungsansätze entwickelt worden sind. In dieser Arbeit wird erstmals und in großer methodischer Breite aus unterschiedlichen Wissenschaftsdisziplinen (energiewirtschaftliche Modellierung und Innovationsökonomie) ein Konzept entwickelt, das diese Limitation adressiert. Die Anwendung des entwickelten Konzeptes auf eine praktische Fragestellung – Energieszenarien für den deutschen Haushaltssektor bis 2050 – zeigt, dass die Integration der Abnahme des technologischen Wissens zu interessanten neuen Erkenntnissen führt.
Abstract
This thesis deals with the topic of how technological knowledge declines over time and the resulting limitations of techno-economic energy demand models in anticipating future demand for energy in the long-term. Since this is a principle limitation of ex ante analyses, this deficiency has been discussed for some time, but so far no methodological solution has been developed. The study is the first to develop a concept that draws on a broad methodological basis from different scientific disciplines (energy modelling and innovation economics) to address this limitation. Applying the concept developed to a practical question – energy scenarios for the German household sector until 2050 – shows that integrating the decline in technological knowledge into answering it leads to interesting new insights.
- 1–37 Titelei/Inhaltsverzeichnis 1–37
- 39–42 1. Introduction 39–42
- 1.1 Background
- 1.2 Problem definition
- 1.3 Objective and procedure
- 43–68 2. Relevant developments in the residential sector and existing modelling approaches 43–68
- 2.1 Overview of the chapter
- 2.2 An empirical assessment of energy demand in the residential sector
- 2.2.1 Energy demand and drivers
- 2.2.2 Technological trends and relevant policies
- 2.3 Ex ante analysis of residential energy demand
- 2.4 Modelling approaches for residential energy demand
- 2.4.1 Introduction to modelling
- 2.4.2 Selection criteria for a suitable modelling approach
- 2.4.3 Characterisation of existing modelling approaches
- 2.4.4 Bottom-up modelling and selection of a suitable approach
- 2.5 Existing models focussing on very long-term energy analysis
- 2.6 Summary and research gap
- 69–78 3. Development of an integrated modelling concept for long-term energy demand analysis 69–78
- 3.1 Overview of the chapter
- 3.2 Introduction to the integrated modelling concept
- 3.3 Framework conditions and concept requirements
- 3.4 Hierarchical dimensions of the integrated modelling concept
- 3.5 Concept structure and procedure
- 79–158 4. Development of the End-Use Model 79–158
- 4.1 Overview of the chapter
- 4.2 Framework conditions and model requirements
- 4.3 Modelling structure and procedure
- 4.4 Selection of methodological approaches
- 4.4.1 Representation of innovation and diffusion
- 4.4.1.1 Introduction to innovation and diffusion modelling
- 4.4.1.2 Modelling innovation cycles
- 4.4.1.3 Modelling diffusion as an epidemic process
- 4.4.1.4 Modelling diffusion based on decision-making
- 4.4.2 Representation of the decreasing trend of investment costs
- 4.4.3 Representation of energy carrier price expectation
- 4.4.4 Representation of technology-related energy efficiency development
- 4.4.5 Representation of energy budget induced rebound effects
- 4.4.6 Representation of residual electricity demand
- 4.5 Simulation of final energy demand
- 4.5.1 Calculation of Module I
- 4.5.1.1 Calculation of ownership rates
- 4.5.1.2 Calculation of end-use stock transformation
- 4.5.1.3 Calculation of specific energy demand
- 4.5.1.4 Calculation of residual electricity demand
- 4.5.2 Calculation of Module II
- 4.5.2.1 Calculation of useful energy demand per building segment
- 4.5.2.2 Calculation of building stock transformation
- 4.5.2.3 Calculation of final energy demand and useful energy demand coverage of installed ventilation systems
- 4.5.2.4 Calculation of stock transformation of heating systems
- 4.5.2.5 Calculation of restrictions of heating system diffusion beyond the system boundaries of energy demand models
- 4.5.3 Calculation of final energy demand
- 4.5.4 Validation of the model
- 4.6 Methodological conclusions
- 4.6.1 Added value of the model
- 4.6.2 Opportunities for further research
- 159–204 5. Development of the Transition Model 159–204
- 5.1 Overview of the chapter
- 5.2 Framework conditions and model requirements
- 5.3 Measures to quantify innovation activity
- 5.3.1 Comparison and selection of innovation measures
- 5.3.2 Critical discussion of patent applications as a measure of innovation
- 5.4 Modelling structure and procedure
- 5.5 Selection of methodological approaches
- 5.5.1 Development of a procedure for a patent-based concordance
- 5.5.2 Quantification of the pace of technological progress
- 5.5.2.1 Classification of indicators based on patents
- 5.5.2.2 Selection of an indicator based on patents
- 5.5.2.3 Discussion of studies applying the technology-cycle-time indicator
- 5.6 Calculation of the end-use-specific depreciation of technological knowledge
- 5.6.1 Development of a concordance between the International Patent Classification scheme and end-uses
- 5.6.1.1 Concept development
- 5.6.1.2 Quantitative assessment
- 5.6.2 Calculation of the technology-cycle-time
- 5.6.2.1 Concept development
- 5.6.2.2 Quantitative assessment
- 5.6.3 Calculating the depreciation of technological knowledge
- 5.6.3.1 Concept development
- 5.6.3.2 Quantitative assessment
- 5.6.4 Validation of the model
- 5.7 Methodological conclusions
- 5.7.1 Added value of the model
- 5.7.2 Opportunities for further research
- 205–240 6. Development of the Energy Service Model 205–240
- 6.1 Overview of the chapter
- 6.2 Framework conditions and model requirements
- 6.3 Modelling structure and procedure
- 6.4 Selection of methodological approaches
- 6.4.1 Representation of decomposed energy demand by effects
- 6.4.2 Representation of long-term energy demand trends
- 6.5 Simulation of final energy demand
- 6.5.1 Decomposition analysis of empirical energy demand
- 6.5.2 Determination of explanatory variables
- 6.5.3 Discussion of alternative linear regression models and statistical testing methods
- 6.5.4 Extension of regression models to capture long-term elasticities
- 6.5.5 Calculation of Module I
- 6.5.5.1 Assignment of explanatory variables to decomposition effects
- 6.5.5.2 Selection of regression models
- 6.5.6 Calculation of Module II
- 6.5.6.1 Assignment of explanatory variables to decomposition effects
- 6.5.6.2 Selection of regression models
- 6.5.7 Calculation of final energy demand
- 6.5.8 Validation of the model
- 6.6 Methodological conclusions
- 6.6.1 Added value of the model
- 6.6.2 Opportunities for further research
- 241–254 7. Development of the Integrated Demand Model 241–254
- 7.1 Overview of the chapter
- 7.2 Integration of models
- 7.2.1 Framework conditions and requirements of model coupling
- 7.2.2 Structure and procedure of the model integration
- 7.2.3 Modelling the transition from a technology-based to an energy service-based representation of energy demand
- 7.2.4 Modelling the impact of the technology-cycle-time on energy efficiency development
- 7.2.5 Calculation of final energy demand
- 7.2.6 Plausibility check of model coupling
- 7.3 Methodological conclusions
- 7.3.1 Added value of the integrated model
- 7.3.2 Opportunities for further research
- 255–280 8. Analysis of long-term energy demand using the Integrated Demand Model 255–280
- 8.1 Overview of the chapter
- 8.2 Scenario analysis
- 8.2.1 Definition and parameters
- 8.2.1.1 Scenario definition
- 8.2.1.2 Socio-economic, price and climate parameters
- 8.2.1.3 Techno-economic parameters
- 8.2.1.4 Energy service-related parameters
- 8.2.1.5 Technology-cycle-time
- 8.2.2 Results
- 8.2.2.1 Analysing energy demand based on the End-Use Model
- 8.2.2.2 Comparison of energy demand based on the End-Use Model and the Energy Service Model
- 8.2.2.3 Analysing energy demand based on the Integrated Demand Model
- 8.3 Sensitivity analysis
- 8.3.1 Definition
- 8.3.2 Results
- 8.3.2.1 Analysing the impact on energy demand of drivers essentially influencing technological knowledge
- 8.3.2.2 Analysing the impact on the technological knowledge stock of drivers essentially influencing technological knowledge
- 281–292 9. Conclusions and outlook 281–292
- 9.1 Contributions to the scientific discussion
- 9.1.1 Recommendations to extend bottom-up models for the assessment of long-term scenarios by explicitly taking technological myopia into account
- 9.1.2 Implications of the newly developed concept for ex ante residential energy demand analysis
- 9.1.3 General limitations on the meaningfulness of bottom-up results due to technological myopia
- 9.2 Critical reflections
- 9.3 Outlook
- 293–298 10. Summary 293–298
- 299–338 References 299–338
