Investigation of temporal mismatch of the energy consumption and local energy generation in the domestic environment
Conventional energy sources are not only finite and depleting rapidly, but are a major source of global warming because they are key contributors of greenhouse gases to the atmosphere. Renewable energy sources are one important approach to these challenges. Distributed micro-generation energy sources are expected to increase the diversity of energy sources for the grid, but also increase the flexibility and resilience of the grid. Furthermore, it could reduce the domestic energy demand from the grid by enabling local consumption of energy generated through renewable sources. The most widely installed renewable energy generation systems in domestic environments, in UK, are based on solar power. However, there is a common recurring issue related to output intermittency of most promising renewable energy generation methods (e.g. solar and wind), resulting in a temporal energy mismatch between local energy generation and energy consumption. Current state-of-the-art technologies/solutions for tackling temporal energy mismatch rely on various types of energy storage technologies, most of which are not suitable for the domestic environments because they are designed for industrial scale application and relatively costly. As such energy storage system technologies are generally not deemed as economically viable or attractive for domestic environments. This research project seeks to tackle the temporal energy mismatch problem between local PV generated energy and domestic energy consumption without the need for dedicated energy storage systems; without affecting the householders comfort and/or imposing operational burdens on the householders. Simulation has been chosen as the major vehicle to facilitate much of the research investigation although data collated from related research projects in the UK and Jordan have been used in the research study. Solar radiation models have been established for predicting the solar radiation for days with clear-sky for any location at any time of the year. This model has achieved a correlation factor of 0.99 in relating to the experimental data-set obtained from National Energy Research Centre Amman/Jordan. Such a model is an essential component for supporting this research study, which has been employed to predict the amount of solar power that could be obtained in different locations and different day(s) of the year. A Domestic Energy Ecosystem Model (DEEM) has been established, which is comprised of two sub-models, namely “PV panels” and “domestic energy consumption” models. This model can be configured with different parameters such as power generation capacity of the photovoltaic (PV) panels and the smart domestic appliances to model different domestic environments. The DEEM model is a vital tool for supporting the test, evaluation and validation of the proposed temporal energy mismatch control strategies. A novel temporal energy mismatch control strategy has been proposed to address these issues by bringing together the concepts of load shifting and energy buffering, with the support of smart domestic appliances. The ‘What-if’ analysis approach has been adopted to facilitate the study of ‘cause-effect’ under different scenarios with the proposed temporal energy mismatch control strategy. The simulation results show that the proposed temporal energy mismatch control strategy can successfully tackle the temporal energy mismatch problem for a 3 bedroom semi-detached house with 2.5kWp PV panels installed, which can utilise local generated energy by up to 99%, and reduce the energy demand from the grid by up to 50%. Further analysis using the simulation has indicated significant socio-economic impacts to the householders and the environment could be obtained from the proposed temporal energy mismatch control strategy. It shows the proposed temporal energy mismatch control strategy could significantly reduce the annual grid energy consumption for a 3 bedrooms semi-detached house and produce significant carbon reductions.
- PhD 
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