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Title: Appliance-level demand side management for power network stress mitigation
Author: Kang, Ren
ISNI:       0000 0004 6497 0807
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2016
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Power networks are under increasing pressure to maintain operation within permissible voltage and current limits with higher penetrations of renewable energy. This thesis aims to develop and evaluate a practical and economical way to control key domestic appliances to alleviate stress caused by high level of renewable energy penetration. The first objective in this thesis is to develop a network stress identification technique that does not rely on communication infrastructure. Traditionally, there is an emphasis on using centralized control strategies for demand side management (DSM) involving a central brain which collects information from each individual device and sends out commands to them which schedules their operation. This approach relies heavily on communication infrastructure and introduces security challenges, which are not problems for distributed or decentralised control. Whilst the latter two approaches have the virtue of scalability and flexibility, they require a good network model or good estimation of network condition without real time communication for effective control. A tap change detection approach via local voltage measurement has been developed and validated to enable the domestic smart appliance to perceive the network stress in three different levels across the power network without any real-time communication. The second objective is to explore the economic benefits associated with the usage of electric hot water tanks (EHWTs) as an alternative to home batteries or electric vehicles for demand response. To do this, an optimization approach for sizing of the EHWT is proposed. Real-world hot water usage data is analysed and applied, revealing four typical hot water usage patterns and 100-litre as the most common optimal tank size for UK consumer. Finally, since increasing PV generation has risen voltage concerns in various locations across the UK, such as in Cornwall, this thesis investigated to what extend intelligent EHWTs can be used to alleviate the LV network stress caused by the high level of PV penetration. A Monte-Carlo simulation is carried out on real UK LV networks, showing that the presence of intelligent EHWTs could improve both the voltage and current performance of the LV network and allow 50% more PV installations beyond the network's original capacity.
Supervisor: McCulloch, Malcolm Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available