Existing low-voltage networks may not accommodate high penetrations of low-carbon technologies. The topic of this thesis is unbalance, which if minimised can delay or avoid the constraining of these technologies or the replacing of still-useful network assets. Most of the discussion on unbalance, as seen in the standards and the literature, centres on the effects of voltage unbalance on consumer equipment. Its effects on the network are not equally reported. This thesis recognises fundamental differences between the consumer and network perspectives. It can inform distribution network operators on the interpretation of measurements taken on low-voltage networks and guide research on unbalance due to high penetrations of low-carbon technologies. Much of the work involved simulations of LV networks. Initially, existing 3 x 3 or 5 x 5 approaches to the forward-backward sweep method were thought suitable. After a review of these approaches however, there were doubts as to how accurately they accounted for the shared neutral-earth return path on which the out-of-balance current flows. This led to the derivation of a new 5 x 5 approach using only Kirchhoff s voltage (KVL) and current laws (KCL). Its results are validated thoroughly in the thesis. In addition to satisfying KVL and KCL, they match Matlab SimPowerSystems exactly and are in close agreement with measurements taken on a very unbalanced rural feeder. This thesis also investigates the mitigation of unbalance using the static balancer. This is a transformer with a single interconnected-star winding. It was used in 1930-1950s to correct unbalance. Contributions are made for its possible re-introduction as a retrofit option. They include a model for use in the forward-backward sweep method, validated by laboratory and field measurements, and the quantification of the static balancer s strengths and weaknesses as this can help identify when it should be used.

Over recent years, political, technological, environmental and economic factors have combined to increase interest in distributed energy resources (DER), and flexibility in the power system. As a resource which is both distributed and flexible, flexible demand (FD) can be considered to be particularly of interest. However, due to many facets of its nature, understanding the available flexibility, and potential value of that flexibility, is difficult. Further, understanding the effects of FD exploitation on other multi-energy system actors, given the complex nature of modern liberalised energy systems, complicates the picture further. These factors form material obstructions to the assessment of FD, for example, for the construction of business cases. To address these gaps this thesis first assesses the nature and value of various applicable current and potential markets and charging/incentive regimes, before detailing a novel multi-energy domestic demand simulation model, capable of modelling, in detail, domestic FD resources. Subsequently, a multi-commodity stochastic energy/reserve optimisation model, capable of modelling various DERs and taking into account price signals related to various energy-related commodities and services (including user utility) is specified. The separation of price components for application at different aggregation levels, which is applied in the optimisation model, also informs the described value mapping methodology, which illustrates the impacts of any, particularly demand-side, intervention on the wider multi-energy system. The power of the above detailed contributions are demonstrated through various studies, which show the physical and economic impact of various demand side interventions and of greater market participation by FD resources.

The main outcome of this research is the development of a Probabilistic Impact Assessment methodology to comprehensively understand the effects of low carbon technologies (LCTs) in low voltage (LV) distribution networks and the potential solutions available to increase their adoption. The adoption of LCTs by domestic customers is an alternative to decreasing carbon emissions. Given that these customers are connected to LV distribution networks, these assets are likely to face the first impacts of LCTs. Thus, to quantify these problems a Monte Carlo-based Probabilistic Impact Assessment methodology is proposed in this Thesis. This methodology embeds the uncertainties related to four LCTs (PV, EHPs, µCHP and EVs). Penetration levels as a percentage of houses with a particular LCT, ranging from 0 to 100% in steps of 10%, are investigated. Five minute time-series profiles and three-phase four-wire LV networks are adopted. Performance metrics related to voltage and congestion are computed for each of the 100 simulations per penetration level. Given the probabilistic nature of the approach, results can be used by decision makers to determine the occurrence of problems according to an acceptable probability of technical issues. To implement the proposed methodology, electrical models of real LV networks and high resolution profiles for loads and LCTs are also developed. Due to the historic passive nature of LV circuits, many Distribution Network Operators (DNOs) have no model for them. In most cases, the information is limited to Geographic Information Systems (GIS) typically produced for asset management purposes and sometimes with connectivity issues. Hence, this Thesis develops a methodology to transform GIS data into suitable computer-based models. In addition, thousands of residential load, PV, µCHP, EHP and EV profiles are created. These daily profiles have a resolution of five minutes. To understand the average behaviour of LCTs and their relationship with load profiles, the average peak demand is calculated for different numbers of loads with and without each LCT.The Probabilistic Impact Assessment methodology is applied over 25 UK LV networks (i.e., 128 feeders) for the four LCTs under analysis. Findings show that about half of the studied feeders are capable of having 100% of the houses with a given LCT. A regression analysis is carried out per LCT, to identify the relationships between the first occurrence of problems and key feeder parameters (length, number of customers, etc.). These results can be translated into lookup tables that can help DNOs produce preliminary and quick estimates of the LCT impacts on a particular feeder without performing detailed studies. To increase the adoption of LCTs in the feeders with problems, four solutions are investigated: feeder reinforcement, three-phase connection of LCTs, loop connection of LV feeders and implementation of OLTCs (on-load tap changers) in LV networks. All these solutions are embedded in the Probabilistic Impact Assessment. The technical and economic benefits of each of the solutions are quantified for the 25 networks implemented.

Against the background of an aspired zero emission economy, residential decision making concerning low-carbon technologies (LCTs) has been researched widely to develop appropriate policy measures to foster adoption levels, however, adoption levels remain unexpectedly low. First, prevalent knowledge gaps are caused by the lacking accumulation of knowledge in the research domain, and second, the lacking common understanding of the decision process itself. Third, previous research has not sufficiently accounted for heterogeneity in the population, instead assuming similar drivers and barriers for adoption across consumer segments. Based on an extended Theory of Planned Behavior and previous research findings, a holistic decision framework for residential decision-making concerning LCTs is proposed in this doctoral thesis. A reduced framework could be confirmed for the example technology rooftop PV with a high-quality sample (n=1,800) using Partial Least Squares Structural Equation Modelling. It could be shown, that adoption intention and strength and influence of predictors vary across consumer segments, even between segments with the same broad social status and/or comparable values. Matching survey data with real-world data revealed, that stated adoption intentions of consumer segments are consistent with adoption behavior in Saxonian zip-codes only for two of five consumer segments. Moreover, it could be demonstrated that common variables used to explain adoption intentions (environmental concern and novelty seeking) are not related with adoption levels in Saxonian zip-codes. Similarly, common variables to explain adoption levels in zip-codes (city-type, share of (semi-) detached houses, population density, previous PV installations) are not related with adoption intentions among consumer segments. These results show that taking consumer heterogeneity into account is crucial to understanding drivers and barriers of residential adoption decisions, and that variables relating to intentions and actual behavior are not necessarily equivalent, providing initial insights into why political measures might not have been sufficiently successful yet.:Abstract iii Zusammenfassung v Publications ix Acknowledgments xi 1 Introductory Remarks 1 2 Residential low-carbon technology decision-making 23 3 Residential PV adoption intention 37 4 The decision towards a residential PV system 63 5 Heterogeneity in PV adoption intentions across consumer segments 83 6 Spatial and household characteristics relating to PV saturation 103 7 Spatial and household characteristics relating to PV adoption intention 121 Statement of Contribution xv Curriculum Vitae xvii Declaration of Authorship xix Bibliographic Description xxi

Assessing the impact of domestic low-carbon technologies on the electricity distribution network requires a detailed insight into the operation of networks and the power demands of consumers. When used on a wide-scale, low-carbon technologies, including domestic scale micro-generation, heat pumps, electric vehicles and flexible demand, will change the nature of domestic electricity use. In providing a basis for the quantification of the impact upon distribution networks, this thesis details the construction and use of a high-resolution integrated model that simulates both existing domestic electricity use and low voltage distribution networks. Electricity demand is modelled at the level of individual household appliances and is based upon surveyed occupant time-use data. This approach results in a simulation that exhibits realistic time-variant demand characteristics, in both individual dwellings, as well as, groups of dwellings together. Validation is performed against real domestic electricity use data, measured for this purpose, from dwellings in Loughborough in the East Midlands, UK. The low voltage distribution network is modelled using real network data, and the output of its simulation is validated against measured network voltages and power demands. The integrated model provides a highly detailed insight into the operation of networks at a one-minute resolution. This integrated model is the main output of this research, alongside published articles and a freely downloadable software implementation of the demand model.

Since the late 1980s, the energy sector in Great Britain has undergone some core changes in its functionality; beginning with the early 1990s privatisation, followed by an increased green ambition, and commencing a transition towards a low-carbon economy. As the British energy sector prepares itself for another major overhaul, it also puts itself at risk for not being sufficiently prepared for the consequences this transition will have on the existing generating capacity, security of supply, and the national electricity market. Upon meeting existing targets, the government of the United Kingdom risks becoming complacent, putting energy regulation to the backseat and focusing on other regulatory tasks, while introducing cuts for thriving renewable and other low-carbon energy generating technologies. The government has implemented a variety of directives, initiatives, and policies that have sometimes been criticised due to their lack of clarity and potential overlap between energy and climate change directives. The government has introduced policies that aim to provide stable short-term solutions. However, a concrete way of resolving the energy trilemma and some of the long-term objectives and more importantly ways of achieving them are yet to be developed. This work builds on analysing each low-carbon technology individually by assessing its past and current state in the British energy mix. By accounting for the changes and progress the technology underwent in its journey towards becoming a part of the energy capacity in Great Britain, its impact on the future wholesale electricity prices is studied. Research covered in this thesis presents an assessment of the existing and incoming low-carbon technologies in Great Britain and their individual and combined impact on the future of British energy economics by studying their implications for the electricity market. The methodological framework presented here uses a cost-minimisation merit order model to provide useful insights for novel methods of electricity production and conventional thermal energy generation to aid with the aftermath of potential inadequate operational and fiscal flexibility. The thesis covers a variety of scenarios differing in renewable and thermal penetration and examines the impact of interconnection, energy storage, and demand side management on the British wholesale electricity prices. The implications of increasing low-carbon capacity in the British energy mix are examined and compared to similar developments across Europe. The analysis highlights that if the optimistic scenarios in terms of green energy installation are followed, there is sufficient energy supply, which results in renewable resources helping to keep the wholesale price of electricity down. However, if the desired capacity targets are not met, the lack of available supply could result in wholesale prices going up, especially in the case of a natural gas price increase. Although initially costly, the modernisation of the British grid leads to a long-term decrease in wholesale electricity prices and provides a greater degree of security of supply and flexibility for all market participants.

L’innovation dans les technologies de l’énergie bas-carbone est entravée, d’une part, par les externalités sur l’environnement et, d’autre part, par les externalités de connaissance. Ces défaillances de marché nécessitent d’être corrigées par l’intervention des pouvoirs publics. L’objectif de cette thèse est d’établir les conditions d’un soutien efficace à l’innovation dans les technologies de l’énergie bas-carbone. Le travail de recherche mène des analyses théoriques sur le traitement de ces défaillances de marché en conjonction avec des évaluations empiriques des politiques de soutien à l’innovation dans ces technologies mises en place jusqu’à présent. Cette thèse se structure en cinq chapitres. Le Chapitre 1 interroge la nécessité de mettre en place des politiques spécifiquement dédiées à l’innovation dans les technologies de l’énergie bas-carbone, en opposition à un soutien à l’innovation de la part des pouvoirs publics ne discriminant pas ces technologies des autres. La revue des instruments économiques mis en place jusqu’à présent est ensuite proposée et indique la prédominance du soutien à l’innovation dans ces technologies par la demande, plutôt que par l’offre. Le Chapitre 2 resserre l’analyse sur les instruments de soutien par la demande. Un modèle micro-fondé de diffusion est utilisé en vue de mener une analyse contrefactuelle évaluant les effets de ces instruments sur la diffusion de la technologie éolienne dans six pays européens. Le Chapitre 3 développe une méthode économétrique de mesure de la connaissance produite dans les technologies de l’énergie bas-carbone. L’utilisation d’un modèle à facteur latent commun permet d’estimer un indice de qualité des inventions brevetées entre 1980 et 2010, dans quinze types de technologies et dans six pays innovateurs. Le Chapitre 4 revisite la question du design optimal du système de brevet quand il s’adresse à une invention de procédé dont la rémunération dépend des politiques de tarification des externalités sur l’environnement. Le Chapitre 5 résume nos résultats et en déduit les principaux messages. / Innovation in low-carbon energy technologies (LCETs) is impeded by externalities on the environment on the one hand, and on knowledge on the other hand. These market failures need to be addressed through public policies. The purpose of this thesis is to investigate the conditions for effectiveness of policies aiming at supporting innovation in LCETs. It does so by having recourse to theoretical analyses in conjunction with empirical assessments. The thesis is structured into five chapters. Chapter 1 questions the need to implement innovation policies specifically dedicated to LCETs — as opposed to neutral innovation policies that do not discriminate between these technologies and other technologies. A review of the economic instruments that have been implemented is proposed and indicates the predominance of a demand-pull approach — over a supply-push approach — to support innovation in LCETs. Chapter 2 evaluates the effects of demand-pull support instruments by conducting a counterfactual analysis to determine the extent to which the diffusion of wind power in six European countries is imputable to these instruments. Chapter 3 develops an econometrical method aiming at providing a robust measure of the produced knowledge that pertains to LCETs. A common latent factor model is used to estimate the quality of inventions that have been patented by six countries between 1980 and 2010 in fifteen low-carbon energy technologies. Chapter 4 revisits the question of the optimal design of a patent system when specifically dedicated to a process invention, whose reward depends on the pricing of environmental externalities. Chapter 5 summarizes our results and articulates key issues and messages.

Whether it is based on current emissions data or future projections of further growth, the building sector currently represent the largest and singular most important contributor to greenhouse gas (GHG) emissions globally. This notion is also supported by the Intergovernmental Panel on Climate Change based on projection scenarios for 2030 that emissions from buildings will be responsible for about one-third of total global emissions. As such, improving the energy efficiency of buildings has become a top priority worldwide. A significant majority of buildings that exist now will still exist in 2030 and beyond; therefore the greatest energy savings and carbon footprint reductions can be made through retrofit of existing buildings. A wide range of retrofit options are readily available, but methods to identify optimal solutions for a particular abatement project still constitute a major technical challenge. Investments in building energy retrofit technologies usually involve decision-making processes targeted at reducing operational energy consumption and maintenance bills. For this reason, retrofit decisions by building stakeholders are typically driven by financial considerations. However, recent trends towards environmentally conscious and resource-efficient design and retrofit have focused on the environmental merits of these options, emphasising a lifecycle approach to emissions reduction. Retrofit options available for energy savings have different performance characteristics and building stakeholders are required to establish an optimal solution, where competing objectives such as financial costs, energy consumption and environmental performance are taken into account. These key performance parameters cannot be easily quantified and compared by building stakeholders since they lack the resources to perform an effective decision analysis. In part, this is due to the inadequacy of existing methods to assess and compare performance indicators. Current methods to quantify these parameters are considered in isolation when making decisions about energy conservation in buildings. To effectively manage the reduction of lifecycle environmental impacts, it is necessary to link financial cost with both operational and embodied emissions. This thesis presents a novel deterministic decision support system (DSS) for the evaluation of economically and environmentally optimal retrofit of non-domestic buildings. The DSS integrates the key variables of economic and net environmental benefits to produce optimal decisions. These variables are used within an optimisation scheme that consists of integrated modules for data input, sensitivity analysis and takes into account the use of a set of retrofit options that satisfies a range of criteria (environmental, demand, cost and resource constraints); hierarchical course of action; and the evaluations of ‘best’ case scenario based on marginal abatement cost methods and Pareto optimisation. The steps involved in the system development are presented and its usefulness is evaluated using case study applications. The results of the applications are analysed and presented, verifying the feasibility of the DSS, whilst encouraging further improvements and extensions. The usefulness of the DSS as a tool for policy formulation and developments that can trigger innovations in retrofit product development processes and sustainable business models are also discussed. The methodology developed provides stakeholders with an efficient and reliable decision process that is informed by both environmental and financial considerations. Overall, the development of the DSS which takes a whole-life CO2 emission accounting framework and an economic assessment view-point, successfully demonstrates how value is delivered across different parts of the techno-economic system, especially as it pertains to financial gains, embodied and operational emissions reduction potential.