Show simple item record

dc.contributor.advisorStephenson, Janet
dc.contributor.advisorCranefield, Stephen
dc.contributor.advisorFord, Rebecca
dc.contributor.authorBakr, Salma
dc.date.available2019-03-07T20:11:46Z
dc.date.copyright2019
dc.identifier.citationBakr, S. (2019). Dynamic Demand Response in Residential Prosumer Collectives (Thesis, Doctor of Philosophy). University of Otago. Retrieved from http://hdl.handle.net/10523/9037en
dc.identifier.urihttp://hdl.handle.net/10523/9037
dc.description.abstractThis research aims at exploring how smart grid opportunities can be leveraged to ameliorate demand response practices for residential prosumer collectives, while meeting the needs of end-users and power grids. Electricity has traditionally been generated in centralized plants then transmitted and distributed to end-users, but the increasing cost-effectiveness of micro-generation (e.g. solar photovoltaics) is resulting in the growth of more decentralized generation. The term "prosumers" is commonly used to refer to energy users (usually households) who engage in small-scale energy production. Of particular interest is the relatively new phenomenon of prosumer collectives, which typically involve interactions between small-scale decentralized generators to optimize their collective energy production and use through sharing, storing and/or trading energy. Drivers of collective prosumerism include sustaining community identity, optimizing energy demand and supply across multiple households, and gaining market power from collective action. Managing power flows in grids integrating intermittent micro-generation (e.g. from solar photovoltaics and micro-wind turbines) presents a challenge for prosumer collectives as well as power grid operators. Smart grid technologies and capabilities provide opportunities for dynamic demand response, where flexible demand can be better matched with variable supply. Ideally, smart grid opportunities should incentivize prosumers to maximize their energy self-consumption from local supply while fairly sharing any income from trading surplus energy, or any loss of utility associated with altering energy demand patterns. New businesses are emerging and developing various products and services around smart grid opportunities to cater for the socio-technical needs of residential prosumer collectives, where technical energy systems overlap with social interactions. This research studies how emerging businesses are using smart grid capabilities to create dynamic demand response solutions for residential prosumer collectives, and how fairness can be adopted in solutions targeting those collectives. This research interweaves social and technical knowledge from literature to interpret the interactions and objectives of prosumer collectives in new ways, and create new socio-technical knowledge around those interpretations. Conducting this research involved using mixed research methods to draw on social science, computer science, and power systems. In the social stream of the research, semi-structured interviews were conducted with executives in businesses providing current or potential smart grid solutions enabling dynamic demand response in residential prosumer collectives. In the technical stream, optimization, computation and game theory concepts were used to develop software algorithms for integrating fairness in allocating shared benefits and loss of utility in collective settings. Interview findings show that new business models and prosumer-oriented solutions are being developed to support the growth of prosumer collectives. Solutions are becoming more software-based, and enabling more socially-conscious user choice. Challenges include dealing with power quality rather than capacity, developing scalable business models and adequate regulatory frameworks, and managing social risks. Automated flexibility management is anticipated to dominate dynamic demand response practices, while the grid is forecast to become one big prosumer community rather than pockets of closed communities. Additionally, the research has developed two software algorithms for residential collectives, to fairly distribute revenue and loss of utility among households. The algorithms used game theory, optimization and approximation algorithms to estimate fair shares with high accuracy using less computation time and memory resources than exact methods.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherUniversity of Otago
dc.rightsAll items in OUR Archive are provided for private study and research purposes and are protected by copyright with all rights reserved unless otherwise indicated.
dc.subjectProsumer
dc.subjectProsumer Collective
dc.subjectSmart Grid
dc.subjectDemand Response
dc.subjectFairness
dc.subjectFlexibility
dc.subjectMiddle Actors
dc.titleDynamic Demand Response in Residential Prosumer Collectives
dc.typeThesis
dc.date.updated2019-03-07T15:17:52Z
dc.language.rfc3066en
thesis.degree.disciplineInformation Science
thesis.degree.nameDoctor of Philosophy
thesis.degree.grantorUniversity of Otago
thesis.degree.levelDoctoral
otago.openaccessOpen
 Find in your library

Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record