Abstract
The aim of this thesis is two-fold: First, it presents the refereed work on the idea of embedding households, or more broadly economic agents, in building energy models. Second, it discusses the insights that are gained by applying this method and through its linkage with a partial equilibrium model of the greater energy system.In response to electricity price changes, households make explicit behavioural adjustments or energy efficiency purchase decisions to maximize their welfare. Those decisions entail a combination of thermostat set-point adjustments, turning off lights, re-arranging the appliance loads, and the ability to purchase from a given slate of energy efficiency measures. I have included improved air conditioner performance, upgrades to the thermal insulation of the dwelling, more-efficient lighting, and efficient window panels. Using Saudi Arabia as a case study, two key insights are derived from performing a modelling analysis for archetypical villas:
• Energy efficiency investment lowers the need for energy conservation. Raising energy efficiency subsidies causes households to reduce their energy conservation.
• As energy efficiency subsidies and electricity prices rise, the difference in household spending on other goods and services widens between the highest efficiency case and no added efficiency. This indirect rebound effect causes a situation
here firms may increase their production to meet the additional demand from households for their goods, which will require more energy.
Furthermore, the households’ electric power load profiles change during the year due to those behavioural and energy efficiency decisions. The Saudi power system experiences these two benefits in the long-run from charging real-time prices (RTP) for electricity:
• RTP reduces the variability of the marginal costs to Saudi power utilities throughout the day.
• The lowered investment in power plants brought upon by introducing RTP would more than cover the costs of residential smart meter replacements.
| Date of Award | Nov 2021 |
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| Original language | English |
| Awarding Institution |
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| Supervisor | Lester Hunt (Supervisor) |