One feature that is hoped for in the smart grid is the participation of energy prosumers in
a power market through demand response program. In this work, we consider a third-party
virtual power plant (VPP) that has “real-time” control over a number of prosumers’
storage units within an envisaged free market. Typically, a VPP with domestic energy
storage will involve a bidirectional flow of energy, where energy can either flow from the
grid to the prosumers’ battery or from the prosumers’ battery to the grid. Such a system
requires prices to be set correctly in order to meet the market objectives of all the VPP
stakeholders (VPP Aggregator, prosumers, and grid).
Previous work has shown how VPPs could operate, and the benefits of using energy
storage, coupled with pricing, in terms of reducing energy cost for stakeholders and
providing the grid with its required load shape. The published work either assumes prices
or costs or then optimises for least cost within the grid parameters i.e. losses, voltage
limits, etc. However, the setting of prices in such a way that energy can be traded among
VPP stakeholders that satisfies all stakeholders’ objectives has not been fully explored in
the literature, particularly with real-time VPP aggregators.
In this thesis, we present novel strategies for evaluating and setting the prices of a
community VPP with domestic storage based on the bidirectional flow of energy through
the VPP aggregator between the grid and the prosumers that mutually meet all VPP
stakeholders’ objectives. This showed that depending on pricing and the VPP objectives,
demand-side management could be attractive. However, the effect on the grid in terms of
the load was not what was desired. A new performance index called the “Cumulative
Performance Index” CPI is proposed to measure the VPP’s performance. Using the CPI,
it was possible to compare and contrast between the VPP technical performance and its
business case for stakeholders. Optimizing with respect to the grid’s requirement for DSM
from the VPP, it was possible to achieve a CPI of 100%. This work was implemented
using a novel approach on a genetic algorithm platform. / Niger Delta Development Commission of Nigeria
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/18669 |
| Date | January 2019 |
| Creators | Okpako, Oghenovo |
| Contributors | Rajamani, Haile S., Abd-Alhameed, Raed |
| Publisher | University of Bradford, School of Engineering and Informatics |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Thesis, doctoral, PhD |
| Rights | <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/"><img alt="Creative Commons License" style="border-width:0" src="http://i.creativecommons.org/l/by-nc-nd/3.0/88x31.png" /></a><br />The University of Bradford theses are licenced under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/3.0/">Creative Commons Licence</a>. |
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