Filtering by
- All Subjects: Buildings
- Creators: Reddy, T. Agami
For lighting control, the dissertation describes how the problem is non-deterministic polynomial-time hard(NP-Hard) but can be resolved by heuristics. The resulting system controls blinds to ensure uniform lighting and also adds artificial illumination to ensure light coverage remains adequate at all times of the day, while adjusting for weather and seasons. In the absence of daylight, the system resorts to artificial lighting.
For temperature control, the dissertation describes how the temperature control problem is modeled using convex quadratic programming. The impact of every air conditioner on each sensor at a particular time is learnt using a linear regression model. The resulting system controls air-conditioning equipments to ensure the maintenance of user comfort and low cost of energy consumptions. The system can be deployed in large scale environments. It can accept multiple target setpoints at a time, which improves the flexibility and efficiency of cooling systems requiring temperature control.
The methods proposed work as generic control algorithms and are not preprogrammed for a particular place or building. The feasibility, adaptivity and scalability features of the system have been validated through various actual and simulated experiments.
In LAC, residential electricity demand could increase as much as 55-68% between 2020 and 2060, and building technology lock-in has constricted the options for mitigating energy demand, as major changes to the building stock itself are not possible, as only a small portion of the stock is turned over every year. Aggressive and timely efficiency upgrades to residential appliances and building thermal shells can significantly offset the projected increases, potentially avoiding installation of new generation capacity, but regulations on new construction will likely be ineffectual due to the long residence time of the stock (60+ years and increasing). These findings can be extrapolated to other U.S. cities where the majority of urban expansion has already occurred, such as the older cities on the eastern coast. U.S. population is projected to increase 40% by 2060, with growth occurring in the warmer southern and western regions. In these growing cities, improving new construction buildings can help offset electricity demand increases before the city reaches the lock-in phase.
The leading source of weather-related deaths in the United States is heat, and future projections show that the frequency, duration, and intensity of heat events will increase in the Southwest. Presently, there is a dearth of knowledge about how infrastructure may perform during heat waves or could contribute to social vulnerability. To understand how buildings perform in heat and potentially stress people, indoor air temperature changes when air conditioning is inaccessible are modeled for building archetypes in Los Angeles, California, and Phoenix, Arizona, when air conditioning is inaccessible is estimated.
An energy simulation model is used to estimate how quickly indoor air temperature changes when building archetypes are exposed to extreme heat. Building age and geometry (which together determine the building envelope material composition) are found to be the strongest indicators of thermal envelope performance. Older neighborhoods in Los Angeles and Phoenix (often more centrally located in the metropolitan areas) are found to contain the buildings whose interiors warm the fastest, raising particular concern because these regions are also forecast to experience temperature increases. To combat infrastructure vulnerability and provide heat refuge for residents, incentives should be adopted to strategically retrofit buildings where both socially vulnerable populations reside and increasing temperatures are forecast.