dc.contributor.advisor | Harrison, Gareth | |
dc.contributor.advisor | Kiprakis, Aristides | |
dc.contributor.advisor | Van Der Weijde, Harry | |
dc.contributor.author | Oluwole, Oluwadamilola | |
dc.date.accessioned | 2018-09-18T13:12:04Z | |
dc.date.available | 2018-09-18T13:12:04Z | |
dc.date.issued | 2018-11-29 | |
dc.identifier.uri | http://hdl.handle.net/1842/33043 | |
dc.description.abstract | The historical underinvestment in power infrastructure and the poor performance of
power delivery has resulted in extensive and regular power shortages in Nigeria. As
Nigeria aims to bridge its power supply gap, the recent deregulation of its electricity
market has seen the privatisation of its generation and distribution companies.
Ambitious plans have also been put in place to expand the transmission network and
the total power generation capacity. However, these plans have been developed with
essentially arbitrary estimates for prevailing demand levels as the network and
generation limits mean actual demand cannot be measured directly due to a programme
of almost constant load shedding; the managed and intermittent distribution of
inadequate energy allocation from the system operator.
Network expansion planning and system reliability analysis require time series
demand data to assess generation adequacy and to evaluate the impact of daily and
seasonal influences on the energy supply-demand balance. To facilitate such analysis
this thesis describes efforts to develop a credible time series electricity demand model
for Nigeria.
The focus of the approach has been to develop a fundamental bottom-up model of
individual households accounting for a range of dwelling characteristics,
socioeconomic factors, appliance use and household activities. A householder survey
was conducted to provide essential inputs to allow a portfolio of household demand
models which can account for weather-dependence and other factors. A range of
national and regional socioeconomic and weather datasets have been employed to
create a regionally disaggregated time series demand model. The generated demand
estimates are validated against metered data obtained from Nigeria.
The value of the approach is highlighted by using the model to investigate the potential
for future load growth as well as analyse the impact of renewable energy generation
on the Nigerian grid. | en |
dc.contributor.sponsor | other | en |
dc.language.iso | en | en |
dc.publisher | The University of Edinburgh | en |
dc.relation.hasversion | Oluwole, O., Harrison, G. & Van Der Weijde, A., 2017. Modelling electricity and cooling load profiles for domestic customers in Nigeria. Bari, Italy, 4th International Conference on Energy Meteorology. | en |
dc.subject | power infrastructure | en |
dc.subject | Nigeria | en |
dc.subject | weather datasets | en |
dc.subject | time series demand model | en |
dc.title | Weather-sensitive, spatially-disaggregated electricity demand model for Nigeria | en |
dc.type | Thesis or Dissertation | en |
dc.type.qualificationlevel | Doctoral | en |
dc.type.qualificationname | PhD Doctor of Philosophy | en |