The ever increasing integration of renewable energy sources creates a challenge
for electric network operation. Addressing the challenge called for changes in system
operation, in particular at distribution level. Demand side flexibility is one of the key
solutions proposed. Presently, customers start to actively manage their own energy
consumption. To manage the growing demand side flexibility and utilise it to benefit
grid operation, Demand Side Management (DSM) technologies are applied to manage
the consumption, assist system balancing and ensure the security of supply. Direct
Load Control (DLC) is a typical DSM technique, where demand corresponds to direct
control signals and being directly controlled by an external entity with short notice.
Under DLC, this may significantly discourage consumers to actively participate in
DLC due to distrust and perceived intrusiveness.
This thesis proposes a novel customer-centred self-scheduling concept that is
capable to overcome the distrust and perceived intrusiveness issues caused by DLC.
The self-scheduling approach encourages consumers to participate and make their own
decisions regarding when and how much they are going to consume domestic
appliances rather than remotely switched by operators /aggregators.
Consumer-centred scheduling tools (a basic and a stochastic tool) have been
developed in this research. The novelty of the developed scheduling tools is it
minimizes the expense of end-users’ energy consumption by automatically schedule
load devices, while satisfies consumer’s electricity usage preferences and their
predetermined living patterns. Moreover, the novel stochastic scheduling tool also
considered the rising uncertainty in the power system. It coordinates network/system
operators’ request and dynamic end-users energy usage behaviour, by combining long
term and short term planning into one procedure.
The developed scheduling tools are able to aid consumers to monitor the electricity
price signals intelligently, react to the network operators’ requirements, achieve
energy bill savings automatically, and satisfy consumers’ energy consumption
preferences at the same time.
Date of Award | 20 Mar 2020 |
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Original language | English |
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Awarding Institution | - University Of Strathclyde
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Sponsors | University of Strathclyde & EPSRC (Engineering and Physical Sciences Research Council) |
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Supervisor | Ivana Kockar (Supervisor) & Stephen McArthur (Supervisor) |
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