The global requirement for sustainable energy provision will become increasingly important over the next fifty years as the environmental effects of fossil fuel use become apparent. Therefore, the issues surrounding integration of renewable energy supplies need to be considered carefully. The focus of this work was the development of a decision support framework that will aid the design of sustainable energy systems for the supply of electricity, heat, hot water and fuel for transportation. Issues requiring consideration in high percentage renewable energy systems include the reliability of the supply when intermittent sources of electricity are being used, and the subsequent necessity for storage and back-up generation. In order to allow the modelling of realistic integrated systems that supply the total energy needs of an area, the production of fuels derived from biomass and waste and their use in a variety of different plant types (e. g. vehicles, engines, turbines, fuel cells, electrolysers, heating and hot water storage systems) is an important consideration. The temporal nature of both intermittent electricity and derived fuel supplies must be taken into account in any analysis. Existing demand and supply matching software has been enhanced to allow the full analysis described. Generic algorithms have been developed to allow the behaviour of a comprehensive list of plant types and methods for producing derived fuels to be modelled, which require only available process and manufacturers' data. The program is flexible, generic and easy to use, allowing a variety of supply strategies to be analysed. This has been shown through the study of a small Scottish island, which highlights the importance of derived fuel production and use. This work has succeeded in developing a more complete tool for analysing the feasibility of integrated renewable energy systems. This will allow informed decisions to be made about the technical feasibility of supply mix and control strategies, plant type and sizing, suitable fuel production, and fuel and energy storage sizing, for any given area and range of supply options.

The present work is a contribution towards the integration of building simulation tools in order to better represent the complexity of the real world. It attempts to overcome certain shortfalls of contemporary simulation applications with respect to indoor air flows. As a result, the evaluation of building energy consumption and indoor air quality is expected to be improved. Advanced fluid flow models (as employed within Building Thermal Simulation - BTS - and Computational Fluid Dynamics - CFD) with different degrees of detail were investigated and their modelling deficiencies identified. The CFD technique which defines the fluid flow on a micro scale was integrated into BTS in which fluid flow is described in a larger scale. The resulting combined approach strengthens the modelling potential of each methodology by overcoming their specific deficiencies. BTS's inability to predict air flow property gradients within a single space was surmounted and the difficult of estimating CFD boundary conditions are now supplied by BTS. The conflation approach is expected to be employed where gradients of indoor air flow properties can be considered crucial to the evaluation of thermal comfort and energy consumption. The BTS environment, ESP-r, was elected to perform the current work and a new CFD program, dfs, was specifically developed for the analysis of three-dimensional, turbulent, transient air flow. Finally, the two approaches were integrated. The integration work focuses on the CFD boundary conditions where the interactions of BTS and CFD take place; these occur at the inside zone surfaces and at the zone openings. Three conflation approaches were devised addressing different degrees of complexity and sophistication. The first one, involving the two types of zone boundaries, corresponds to a simple approach where the BTS and CFD systems exchange information without any direct interaction. The second approach consists of three other schemes to handle the thermal coupling at the internal zone surfaces. The third approach comprises coupling between the nodal network approach as employed by the BTS environment, and the continuity and momentum equations in the CFD technique. A validation methodology consisting of analytical validation, intermodel comparison and empirical validation is described and applied. The technique is shown to be adequate for modelling indoor air flows when compared to existing models. Three situations, covering the different types of air flows encountered within buildings are discussed to demonstrate the combined method's applicability when compared with the nodal network approach. Finally, general conclusions are presented and some possible future work is identified showing that the developed methodology is very promising.

Certain features of dynamic models of energy demand based on the economic theory of production are examined. Attention is mainly confined to first and third generation dynamic models. First generation models are partial adjustment models where energy Is treated largely in isolation from other inputs. Third generation models are based explicitly on dynamic economic optimization, incorporating the notion of costs of adjustment for quasi-fixed inputs. The analysis focusses on three main issues. The first is the characteristics of first generation models and how these models can be extended to the industrial sector. The second is the nature and empirical significance of alternative definitions of third generation models according to whether adjustment costs are treated as a function of net or gross investment. The third issue is whether first and third generation models are generically related and, if so, how. The work on first generation models is mainly confined to the Balestra-Nerlove framework. This specification generally has been applied to individual fuels in the residential/commercial sector but is also applied to aggregate residentidal energy demand and to industrial fuel demand. In terms of third generation models, recognition that adjustment costs may reflect not only net but also gross investment leads to a more complex model, with significant differences in the theoretical specification between net and gross investment formulations. These differences remain significant empirically. Application of the net and gross investment model specifications to Canadian data show that estimation of the simpler net investment version may well entail erroneous estimates of certain parameters. The energy functions of the first and third generation models are found to be generically related. The simplicity of a first generation model can under certain conditions be consistent with the richer, more complex framework of third generation models. However, empirical testing did not support the notion of treating a first generation energy function as tantamount to a reduced form specification of a third generation model.

Since the end of the Second World war, United Kingdom energy policy has been highly influenced by beliefs about the adequacy of indigeneous resources, security of supply and macro-economic objectives. Over the same period we observe a growing sophistication in the official projections of energy requirements both in terms of content and technique. An analysis of the methods and models used in the calculation of recent official projections of UK energy demand identifies a number of problems. These mainly concern the size of the price elasticity of energy demand employed in the sectoral models and the modelling of interfuel substitution particularly in the Domestic Sector market for space and water heating. A review of econometric studies of UK demand indicates that the price elasticities of energy demand employed in the Department of Energy models of sectoral energy demand are generally lower than the estimates reported elsewhere. In contrast, official estimates of the own price and cross price elasticities for individual fuels in the Other Industry Sector are broadly consistent with other econometric studies. However the body of work carried out in this area is found to have a number of shortcomings: (i) in general, the problem of autocorrelation has been dealt with inadequately and inappropriately, (ii) it has not been possible to distinguish long run and short run effects satisfactorily, (iii) it has not been possible to distinguish the independent influences of income and price satisfactorily, (iv) models of interfuel substitution have generally performed poorly in the Domestic Sector and (v) the impact of biased disembodied technical change has not been considered in most studies of interfuel substitution. A new study of energy demand in the Industrial and Domestic Sectors of the UK economy attempts to address these problems. The results are mixed. Well established techniques are used to detect and adjust the results for first order autocorrelation. Biases of technical change are estimated and in particular the Domestic Sector interfuel substitution model performs well. However the problem of modelling the dynamic structure of energy demand remains unresolved. In the Industrial Sector, cross section and time series data is pooled in order to distinguish the independent influences of output and price. While the resulting price and output elasticities conform to the values that we would expect a priori, the explanatory power of the model is low. In the Domestic Sector it is possible to develop a model of energy demand with a good predictive performance, however simulation experiments with the model show that the high frequency variation of the dependent variable is mostly explained by the exogeneous temperature variable which itself is difficult to predict. In contrast it is found that relatively simple relationships between overall primary energy demand and key economic and demographic variables can have surprisingly good forecasting properties. This probably arises because of the inertia of systems at this level of aggregation. A severe test is constructed for a number of single equation forecasting models. The parameters of the models are estimated on UK time series data from 1954 to 1973 then the results are used to generate forecasts of the dependent variables over the highly unstable period between 1974 and 1980. Several of the models provide very accurate predictions. The main purpose of the thesis is to assess recent official forecasts of UK energy demand. The single equation model which performs best in the forecasting test is used as a basis for generating projections to the year 2000. The results are compared with the latest official projections. It is found that the official forecasts imply a lower price elasticity than used in the single equation model, a similar relationship between the structural composition of GDP and aggregate energy demand while the implicit income elasticity is higher than our estimate under high fossil fuel price assumptions but lower when fossil fuel prices are assumed to be lower. The simple model yields very similar forecasts to the official projections for 2000 with the exception of one case. With regard to projections of final energy consumption in the year 2000, there are some areas of contention between the bulk of econometric evidence and the implications of the official forecasts but they are small. Most aspects of the fuel mix forecasts are broadly supported by the econometric evidence given the relative fuel price assumptions. It is concluded that the latest official projections represent a fairly realistic appraisal of the likely outcome of an interplay of market forces in the energy market.

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An evaluation is made of the potential fuel and financial savings possible when a small, autonomous diesel system sized to meet the demands of an individual, domestic consumer is adapted to include: (1) combined heat and power (CUP) generation. (2) wind turbine generation. (3) direct load control. The potential of these three areas is investigated by means of time-step simulation modelling on a microcomputer. Models are used to evaluate performance and a Net Present Value analysis used to assess costs. A cost/benefit analysis then enables those areas, or combination of areas, that facilitate the greatest savings to be identified. The modelling work is supported by experience gained from the following: (1) field study of the Lundy Island wind/diesel system. (2) laboratory testing of a small diesel generator set. (3) study of a diesel based CUP unit. (4) study of a diesel based direct load control system. (5) statistical analysis of data obtained from the long-term monitoring of a large number of individual household's electricity consumption. Rather than consider the consumer's electrical demand in isolation, a more flexible approach is adopted, with consumer demand being regarded as the sum of primarily two components: a small, electricity demand for essential services and a large, reschedulable demand for heating/cooling. The results of the study indicate that: (1) operating a diesel set in a CUP mode is the best strategy for both financial and fuel savings. A simple retrofit enables overall conversion efficiencies to be increased from 25% to 60%, or greater, at little cost. (2) wind turbine generation in association with direct load control is a most effective combination. (3) A combination of both the above areas enables greatest overall financial savings, in favourable winds resulting in unit energy costs around 20% of those of diesel only operation.

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