3 research outputs found
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Development of a profile-based electricity demand response estimation method: an application based on UK hotel chillers
In principle, Demand Side Response (DSR) is increasingly seen as a critical component of a low-carbon electricity network with renewables as main sources of generation. In practice, DSR has been slow to emerge in most electricity markets of developed and developing countries. One of the main reasons for the slow penetration of DSR is the difficulty to assess the flexibility potential of individual sites. This paper develops a new DSR estimation method which uses detailed profiles information based on data on Heating, Ventilation and Air Conditioning (HVAC) chillers in five UK hotels between 2013 and 2017 and applies a combination of clustering analysis and subsequent stochastic sampling using cluster-weighted date-based predictors. Findings show that the profile DSR estimation method features a better balance of error compared with previous methods
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Development of a profile-based electricity demand response estimation method for reducing uncertainty, as informed through a review of aggregator assessment processes and existing estimation methods
This engineering doctorate (EngD) thesis has investigated and improved the understanding of
Demand Side Response (DSR) aggregators, DSR estimation methods, and developed a new load
profile-based estimation method. The primary motivation for this research was to develop and
improve the understanding of different DSR estimation methods and their effectiveness for
assessing new sites as suitable for DSR. DSR aggregators play a key role in facilitating DSR uptake
by providing over 80% of DSR capacity. Therefore, this research has focused on the estimation
methods that a UK-based aggregator uses to determine the suitability of new end users. As an
intermediary in the DSR assessment and programme enrolment process, aggregators need to
ensure that each end user site is suitable for DSR. Otherwise, both the aggregator and the end
user could be negatively impacted if financial returns from participation fail to cover DSR
implementation costs. Therefore, this research was undertaken with the aim of better quantifying
the uncertainty in DSR estimation methods for new sites, with a view to improving the assessment
of their suitability to participate.
The research was undertaken in conjunction with KiWi Power Limited, a UK-based DSR
aggregator, by establishing and then addressing three interlinking objectives. The first objective
mapped out the criteria used by KiWi Power to determine the suitability of an end user’s site for
DSR and found that the highest priority for KiWi Power during the assessment process is
understanding the DSR potential of a site’s assets. The second objective compared the outcome
uncertainty and information input requirements of four existing DSR estimation methods using as
the example asset HVAC Chillers and their sub-meter usage data from two UK hotel sites. The
comparison results showed a range of uncertainty levels which produced mean average
percentage error (MAPE) levels of between 39% to 159%, with the estimation methods costing
between £10 to £180 to perform on new sites. The third objective developed and evaluated a new
method that uses load profiles of assets to reduce the uncertainty of DSR potential estimation
during an aggregator’s assessment process. The new method compares favourably against the
existing DSR estimation methods, as it generated the second lowest MAPE level of 46.5% with an
estimated usage cost of £26. The new method demonstrated additional benefits of being usable
earlier in the assessment process for a new site when compared to the existing methods, and
offered the ability to use pre-calculated uncertainty levels enabling users to adjust the estimation
outputs based on an organisation’s risk appetite