This thesis describes the use of a spatially explicit model to investigate the economies of scale associated with district heating technologies and consequently, their future technical potential when compared against individual building heating. Existing energy system models used for informing UK technology policy do not employ high enough spatial resolutions to map district heating potential at the individual settlement level. At the same time, the major precedent studies on UK district heating potential have not explored future scenarios out to 2050 and have a number of relevant low-carbon heat supply technologies absent from their analyses. This has resulted in cognitive dissonance in UK energy policy whereby district heating is often simultaneously acknowledged as both highly desirable in the near term but ultimately lacking any long term future. The Settlement Energy Demand System Optimiser (SEDSO) builds on key techno-economic studies from the last decade to further investigate this policy challenge. SEDSO can be distinguished from other models used for investigating UK heat decarbonisation by employing a unique combination of extensive spatial detail, technical modelling which captures key cost-related nonlinearities, and a least-cost constrained optimisation approach to technology selection. The study yields a number of original contributions to knowledge that are relevant for policymakers. Results described in the thesis suggest that the marginal economics of UK district heating schemes are significantly improved when compared against individual heat pumps rather than gas boilers. This is relevant because under current policy direction individual heat pumps are likely to be the major counterfactual option to district heating post-2030. Results also illustrate how assumptions about technology availability can drive large shifts in optima, and that utility-scale electric heat pumps could be a key enabling technology for district heating to supply a large fraction of UK heat demand in a post-gas heating future.

Policy makers in the United Kingdom (UK), as in many countries around the world, are confronted with a situation of legally binding commitments to reduce carbon emissions. In this context it remains an open question of how to find a cost-efficient approach to climate change mitigation. Marginal abatement cost (MAC) curves have already been applied to help understand the economics of many different environmental problems and can likewise assist with illustrating the economics of climate change mitigation. Current approaches to generate MAC curves rely mostly on the individual assessment of each abatement measure, which are then ranked in order of decreasing cost-efficiency. These existing ways of generating MAC curves fail to allow both the graphical representation of the technological detail and the incorporation of system-wide behavioural, technological, and intertemporal interactions. They also fail to provide a framework for uncertainty analysis. This dissertation addresses these shortcomings by proposing a new approach to deriving MAC curves through the combination of an integrated energy system model, UK MARKAL, and index decomposition analysis. The energy system model is used to capture system-wide interactions, while decomposition analysis permits the analysis of measures responsible for emissions reduction. Sensitivity analysis and stochastic modelling are also employed to represent how sensitive the measures are to variations of the underlying drivers and assumptions, as well as how they interact. With a focus on the UK and the year 2030, as an important intermediate emissions reduction target, system-wide MAC curves are presented accompanied by a detailed analysis of the power, transport, and the residential sectors. This analysis allows important insights to be made into the economics of emissions mitigation, as well as investigating the robustness of findings. The results of the dissertation project represent a suitable orientation base for decision making in long-term climate policy.

This thesis seeks to explain the economic determinants of matches between shipowners and oil traders within a spatially explicit market for shipping crude oil. Previous approaches to modeling the tanker shipping market have employed an aggregate approach in which there is a single trade route and one market clearing price. This reduced form of trade ignores the inherently spatial nature of the tanker shipping market in which the matches, market prices, and speed ships travel reflect the demand for shipping crude oil on different trade routes, the supply of ships available in each location, and agents' opportunity costs and future expectations. A matching model of the crude oil spot tanker market was developed in which the characteristics of ships and traders is reflected in the market price. The method employs a matching model to understand how supply equilibrates with demand to determine the set of shipping contracts exchanged and their prices as a function of the other agents in a competitive market. Results described in this thesis show that the contracts that form in equilibrium depend on the demand for oil cargoes in each load area market and the supply of available ships within proximity to the market. Additionally, agents' opportunity costs and future expectations has also been found to influence the matching and contract prices. When ships are differentiated by physical characteristics (including energy efficiency) and location, results show that ships which are the most favored by physical characteristics cannot compete as strongly with less preferred ships located closer to the market. These findings can be used to inform industry stakeholders about strategic operating and investment decisions. They are also useful for environmental policy makers because they explain the key drivers of ship movements given ships' reliance on carbon-intensive fuel for propulsion.

With the increasing international shift from prescriptive to performance-based regulations, a legislative call for the integration of predictive assessment tools in the design process has emerged. In relation to this, the requirements of Article 3 of the Directive on Energy Performance of Buildings (EPBD) were transposed into UK legislation with the introduction of the Building and Approved Inspectors (Amendment) Regulations 2006 (England and Wales) in April 2006. These introduced the ‘National Calculation Methodology’ (NCM), a unified compliance demonstration route for energy performance criteria specified in Approved Document Part L (Conservation of Fuel and Power), supported through the use of modelling-based building energy performance prediction (BEPP) tools accredited for the purposes of implementing associated calculations. This thesis presents an assessment of adopting the methodology, utilising a mixed-method research design to investigate key parameters identified as measures by which to quantify the success of this approach. Firstly, the adaptive capability of the UK construction industry is assessed through the analysis of primary data collected from a longitudinal survey. Secondly the applicability of the methodology is analysed through in-depth interviews examining the role of key actors and the varying dynamics of implementation and enforcement. Finally, a comparative evaluation is carried out to assess the adequacy of accredited BEPP tools. The main findings outline the shortcomings of the adaptation strategy adopted by industry and the inconsistent implementation and enforcement strategies employed. The results of the comparative tool study in particular highlight three important issues; a large degree of predictive variability between key compliance benchmarks, the lack of consistency in granting approval (a pass/fail result) between tools and limitations in the scope of their applicability. The research concludes that although a number of positive aspects can be associated with the introduction of a modelling-based approach for compliance demonstration, due to the aforementioned issues, considerable efforts are still required to extend its usefulness as a credible legislative support tool for performance-based regulations.

The electricity industry faces the challenge of adapting to new circumstances where environmental concerns and the optimal use of resources are crucial. In this scenario, Distributed Energy Resources (DER) are recognised as one of the possible solutions for sustainable economic development. The optimal integration of DER in the distribution networks is essential to maximise DER benefits and minimise the cost of DER integration. An adequate DER planning method is required to obtain valuable information for the best deployment of these resources. The integration of DER has several drivers, such as the minimisation of cost, the reduction of carbon emission and the reduction of energy losses, among others. At the same time, several stakeholders are involved in DER research, development and management. Consequently, a flexible and multi-objective planning method that considers technical, environmental and economic impacts of DER integration can provide a deep insight into the advantages and drawbacks of DER, and can reflect the different perspectives on the problem. Most renewable DER have a variable output. Hence, the planning of DER integration must consider the stochastic nature of DER Likewise, the active management of DER and the network has been recognised recently as one of the new paradigms for the integration of larger penetrations of DER As a result, an appropriate planning technique for DER integration must consider the simultaneous interaction of controllable and stochastic DER to provide an adequate evaluation of DER impacts and benefits. Novel multi-objective optimisation techniques, known as Multi-objective Evolutionary Algorithms (MOEA), have been developed recently. MOEA are able to analyse complex objective functions and offer a "true" multi-objective approach. Consequently, MOEA are able to handle complex multi-objective problems such as DER planning effectively. This thesis proposes to use multi-objective planning to analyse the optima This thesis proposes to use multi-objective planning to analyse the optimal integration of stochastic and controllable DER It presents the design, development and demonstration of a planning framework based on a state-of-the-art MOEA. Results from two relevant case studies show that the multi-objective planning method proposed is a novel and valuable tool for the analysis of DER integration. The framework proposed is generic and can be applied to other energy planning problems.

The regulatory and economic pressures from climate change are driving adoption at the domestic scale of low and zero carbon microgenerators such as thermal and photovoltaic solar panels and combined heat and power units. For efficiency household energy use should be co-ordinated with the operation of these devices, but many consumers have difficulty controlling current heating systems so are unlikely to be able to provide the management interventions needed. A control system is required that can collectively optimise a diverse range of energy sources and sinks on behalf of the consumer while providing them with useful information. This system should also respond to the dynamics of grid electricity, for example the variability of output from large scale wind generation, so that embedded microgenerators contribute to the matching of electricity supply and demand. Its realization is the focus of this work. A hypothesis is proposed that ecosystems, which seek and conserve exergy through complexity and diversity of species, offer a model for this control system and the complex range of devices it must manage. To test it, the performance in actual domestic use of several microgenerators is investigated and opportunities for collective optimisation are identified. Minimisation of exergy loss is shown by analysis and computer modelling to be preferable as an objective function when compared to minimisation of carbon emissions or cost, and capable of effective use as a signal for management of electricity demand and despatch of micro generators. To facilitate complexity and diversity, techniques are devised to automatically identify and characterise microgenerators, other appliances, the thermal properties of a home, and consumer energy needs. A prototype control system providing many of these functions is designed, implemented, and tested. It is shown to be capable of improving the energy efficiency of many households, and increased comfort for certain disadvantaged consumers. A conclusion is offered that exergy loss is preferable to market price as a system management metric for all aspects of renewable energy capture, distribution, and use.

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This thesis explores the dynamics of industrial consolidation in the EU27 electricity and gas industry. The research aim is to characterise the consolidation dynamics, its underlying key drivers and implications related to the EU27 electricity and gas industry's consolidation. This research follows a systematic evaluation and comparative analysis of the concentration and internationalisation dynamics since the United Kingdom's privatisation start in the year 1986. This thesis contributes to the discussions about concentration, cooperation and internationalisation strategies in special consideration of competition and competitive advantage in both sectors. This thesis offers a retro perspective, independent, neutral and objective research under special consideration of the interdisciplinary from the perspectives of (energy) economists, institutions, and .management on this transformation • process. The research findings base on the empiric-quantitative analysis of 5,309 realised and closed Mergers & Acquisitions and Joint Venture transactions with a total deal volume of EUR1,184bn covering the period between 01/01/1986 and 31/12/2008 targeting the EU27 electricity and gas industry. In addition, the data set contains all worldwide transactions realised by the companies based in the EU27 member states. Research conveyed a semi-structured survey about the consolidation key determinants issued to the industry's Chief Executive Officers in spring 2010. The survey asked for the economic crisis impact on the industry, and asked for assessment of the prospective consolidation development ~ after the crisis. The research findings demonstrate that economic and regulatory pressures are the main forces influencing the concentration process. Thereby, the incumbent companies mainly drove the consolidation process in Europe. The main reasons for the EU27 electricity and gas industry's internationalisation are an eased market access, advanced by privatisations and market liberalisation, growth orientation, as well as cartel restrictions due to high concentration. The corporate key strategies remain to achieve economies of scale and synergies, meanwhile, focussing on core competencies and the strategic fit. The companies had to struggle during the economic crisis due to decreasing demand, but developed unexpected opportunities from divestures and/or by regulatory restrictions.