BRADFORD SCHOLARS

    • Sign in
    View Item 
    •   Bradford Scholars
    • University of Bradford eTheses
    • Theses
    • View Item
    •   Bradford Scholars
    • University of Bradford eTheses
    • Theses
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of Bradford ScholarsCommunitiesAuthorsTitlesSubjectsPublication DateThis CollectionAuthorsTitlesSubjectsPublication Date

    My Account

    Sign in

    HELP

    Bradford Scholars FAQsCopyright Fact SheetPolicies Fact SheetDeposit Terms and ConditionsDigital Preservation Policy

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors

    Energy storage in the future smart grid. An investigation of pricing strategies and dynamic load levelling for efficient integration of domestic energy storage within a virtual power plant and its evaluation using a genetic algorithm optimization platform

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    View/Open
    PhD Thesis (7.782Mb)
    Download
    Publication date
    2019
    Author
    Okpako, Oghenovo
    Supervisor
    Rajamani, Haile S.
    Abd-Alhameed, Raed A.
    Keyword
    Battery storage
    Virtual power plant
    Prosumers
    Smart grid
    State of charge
    Pricing
    Stakeholders
    Genetic algorithm
    Demand side management
    Cumulative performance index
    Rights
    Creative Commons License
    The University of Bradford theses are licenced under a Creative Commons Licence.
    Institution
    University of Bradford
    Department
    School of Engineering and Informatics
    Awarded
    2019
    
    Metadata
    Show full item record
    Abstract
    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.
    URI
    http://hdl.handle.net/10454/18669
    Type
    Thesis
    Qualification name
    PhD
    Collections
    Theses

    entitlement

     
    DSpace software (copyright © 2002 - 2023)  DuraSpace
    Quick Guide | Contact Us
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.