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Title: The development, implementation, and application of Demand Side Management and control (DSM+c) algorithm for integrating micro-generation system within built environment
Author: Hong, Jun
ISNI:       0000 0004 2678 3103
Awarding Body: University of Strathclyde
Current Institution: University of Strathclyde
Date of Award: 2009
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Recent legislation and building regulations aim to reduce the energy demands of buildings and include renewable and low carbon based micro-generation technologies. Due to the intermittent nature of renewable energy systems and fluctuating demand profiles at the domestic level, matching the demand with a volatile supply of low operating efficiency, as is the case with some low carbon energy systems, at the local level, becomes a big challenge for the widespread implementation of zero/low carbon energy systems. The research undertaken centres on the potential exploitation of demand side resources to provide the solutions to the issues addressed above. This thesis focuses on the development, implementation, and application of a bottom-up Demand Side Management and control (DSM+c) algorithm to create greater flexibility in demand and better facilitate the integration of renewable and low carbon energy technologies within the built environment, without significantly compromising user satisfaction. This DSM+c algorithm can be applied to both strategic and operational levels. The strategic level DSM+c algorithm is suitable for the development and analysis of DSM approaches. The measures of load shifting and demand side control are available to specify the DSM options upon loads. The results, in terms of demand/supply match, energy export/import, and environmental impact etc., before and after having applied DSM+c algorithm upon loads, are quantified when linked with Renewable (RE) & Low Carbon (LC) energy supply systems. The DSM+c algorithm at strategic level has been embedded within a decision support platform, MERIT. MERIT is a demand-supply matching tool for assessing the feasibility of renewable energy systems. This allows engineers to develop appropriate demand supply control strategies. The operational level DSM+c algorithm is capable of controlling loads based on the available supply at a certain time, through the assistance of information gathered from simulation or via real-time measurement. The control impact of the operational level DSM+c algorithm upon internal environmental parameters can be quantified. A virtual platform for implementing the DSM+c algorithm is established, within which the information of demand, supply, and internal environmental parameters, are obtained through simulation and input to carry out the process of the DSM+c algorithm. Furthermore, an Internet-enabled Energy System (IE-ES) platform for implementing these control actions upon individual loads in a practical environment has been developed. Finally two types of case studies are presented respectively, showing how the DSM+c algorithm plays a key role within the whole decision-making procedure in a project and how it is applied to an individual appliance at operational level. The thesis concludes with recommendations of potential applications for this work and prospective further development.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral