Due to extreme summer temperatures that regularly reach 122°F (50°C), cooling energy requirements have been responsible for 70% of peak demand and 45% of total electricity consumption in Kuwait. It is estimated that 50%-60% of electric power is consumed by the residential sector, mostly in detached villas. This study analyzes the potential impact of energy efficiency measures (EEM) and renewable energy (RE) measures on the electric energy requirements of an existing villa built in 2004. Using architectural plans, interview data, and the eQUEST building energy simulation tool, a building energy model (BEM) was developed for a villa calibrated with hourly energy use data for the year 2014. Although the modeled villa consumed less energy than an average Kuwaiti villa of the same size, 26% energy reductions were still possible under compliance with 2018 building codes. Compliance with 2010 and 2014 building codes, however, would have increased energy use by 19% and 3% respectively. Furthermore, survey data of 150 villas was used to generate statistics on rooftop solar area availability. Accordingly, it was found that 78% of the survey sample’s average total rooftop area was not suitable for rooftop solar systems due to shading and other obstacles. The integration of a solar canopy circumvents this issue and also functions as a shading device for outdoor activities and as a protective cover for AC units and water tanks. Combining the highest modeled EEMs and RE measures on the villa, the energy use intensity (EUI) would be reduced to 15 kWh/m2/year from a baseline value of 127 kWh/m2/year, close to net zero. Finally, it was determined that EEMs were able to reduce the entire demand profile whereas RE measures were most effective at reducing demand around mid-day hours. In future studies, more effort should be spent on collecting hourly data from multiple villas to assist in the development of a detailed hourly bottom-up residential energy modeling methodology.

City administrators and real-estate developers have been setting up rather aggressive energy efficiency targets. This, in turn, has led the building science research groups across the globe to focus on urban scale building performance studies and level of abstraction associated with the simulations of the same. The increasing maturity of the stakeholders towards energy efficiency and creating comfortable working environment has led researchers to develop methodologies and tools for addressing the policy driven interventions whether it’s urban level energy systems, buildings’ operational optimization or retrofit guidelines. Typically, these large-scale simulations are carried out by grouping buildings based on their design similarities i.e. standardization of the buildings. Such an approach does not necessarily lead to potential working inputs which can make decision-making effective. To address this, a novel approach is proposed in the present study.

The principle objective of this study is to propose, to define and evaluate the methodology to utilize machine learning algorithms in defining representative building archetypes for the Stock-level Building Energy Modeling (SBEM) which are based on operational parameter database. The study uses “Phoenix- climate” based CBECS-2012 survey microdata for analysis and validation.

Using the database, parameter correlations are studied to understand the relation between input parameters and the energy performance. Contrary to precedence, the study establishes that the energy performance is better explained by the non-linear models.

The non-linear behavior is explained by advanced learning algorithms. Based on these algorithms, the buildings at study are grouped into meaningful clusters. The cluster “mediod” (statistically the centroid, meaning building that can be represented as the centroid of the cluster) are established statistically to identify the level of abstraction that is acceptable for the whole building energy simulations and post that the retrofit decision-making. Further, the methodology is validated by conducting Monte-Carlo simulations on 13 key input simulation parameters. The sensitivity analysis of these 13 parameters is utilized to identify the optimum retrofits.

From the sample analysis, the envelope parameters are found to be more sensitive towards the EUI of the building and thus retrofit packages should also be directed to maximize the energy usage reduction.

Schools all around the country are improving the performance of their buildings by adopting high performance design principles. Higher levels of energy efficiency can pave the way for K-12 Schools to achieve net zero energy (NZE) conditions, a state where the energy generated by on-site renewable sources are sufficient to meet the cumulative annual energy demands of the facility. A key capability for the proliferation of Net Zero Energy Buildings (NZEB) is the need for a design methodology that identifies the optimum mix of energy efficient design features to be incorporated into the building. The design methodology should take into account the interaction effects of various energy efficiency measures as well as their associated costs so that life cycle cost can be minimized for the entire life span of the building.

This research aims at developing such a methodology for generating cost effective net zero energy solutions for school buildings. The Department of Energy (DOE) prototype primary school, meant to serve as the starting baseline, was modeled in the building energy simulation software eQUEST and made compliant with the requirement of ASHRAE 90.1-2007. Commonly used efficiency measures, for which credible initial cost and maintenance data were available, were selected as the parametric design set. An initial sensitivity analysis was conducted by using the Morris Method to rank the efficiency measures in terms of their importance and interaction strengths. A sequential search technique was adopted to search the solution space and identify combinations that lie near the Pareto-optimal front; this allowed various minimum cost design solutions to be identified corresponding to different energy savings levels.

Based on the results of this study, it was found that the cost optimal combination of measures over the 30 year analysis span resulted in an annual energy cost reduction of 47%, while net zero site energy conditions were achieved by the addition of a 435 kW photovoltaic generation system that covered 73% of the roof area. The simple payback period for the additional technology required to achieve NZE conditions was calculated to be 26.3 years and carried a 37.4% premium over the initial building construction cost. The study identifies future work in how to automate this computationally conservative search technique so that it can provide practical feedback to the building designer during all stages of the design process.

Improving the conditions of schools in many parts of the world is gradually acquiring importance. The Green School movement is an integral part of this effort since it aims at improving indoor environmental conditions. This would in turn, enhance student- learning while minimizing adverse environmental impact through energy efficiency of comfort-related HVAC and lighting systems. This research, which is a part of a larger research project, aims at evaluating different school building designs in Albania in terms of energy use and indoor thermal comfort, and identify energy efficient options of existing schools. We start by identifying three different climate zones in Albania; Coastal (Durres), Hill/Pre-mountainous (Tirana), mountainous (Korca). Next, two prototypical school building designs are identified from the existing stock. Numerous scenarios are then identified for analysis which consists of combinations of climate zone, building type, building orientation, building upgrade levels, presence of renewable energy systems (solar photovoltaic and solar water heater). The existing building layouts, initially outlined in CAD software and then imported into a detailed building energy software program (eQuest) to perform annual simulations for all scenarios. The research also predicted indoor thermal comfort conditions of the various scenarios on the premise that windows could be opened to provide natural ventilation cooling when appropriate. This study also estimated the energy generated from solar photovoltaic systems and solar water heater systems when placed on the available roof area to determine the extent to which they are able to meet the required electric loads (plug and lights) and building heating loads respectively.

The results showed that there is adequate indoor comfort without the need for mechanical cooling for the three climate zones, and that only heating is needed during the winter months.

The objective of this thesis is to investigate the various types of energy end-uses to be expected in future high efficiency single family residences. For this purpose, this study has analyzed monitored data from 14 houses in the 2013 Solar Decathlon competition, and segregates the energy consumption patterns in various residential end-uses (such as lights, refrigerators, washing machines, ...). The analysis was not straight-forward since these homes were operated according to schedules previously determined by the contest rules. The analysis approach allowed the isolation of the comfort energy use by the Heating, Venting and Cooling (HVAC) systems. HVAC are the biggest contributors to energy consumption during operation of a building, and therefore are a prime concern for energy performance during the building design and the operation. Both steady state and dynamic models of comfort energy use which take into account variations in indoor and outdoor temperatures, solar radiation and thermal mass of the building were explicitly considered. Steady State Inverse Models are frequently used for thermal analysis to evaluate HVAC energy performance. These are fast, accurate, offer great flexibility for mathematical modifications and can be applied to a variety of buildings. The results are presented as a horizontal study that compares energy consumption across homes to arrive at a generic rather than unique model - to be used in future discussions in the context of ultra efficient homes. It is suggested that similar analyses of the energy-use data that compare the performance of variety of ultra efficient technologies be conducted to provide more accurate indications of the consumption by end use for future single family residences. These can be used alongside the Residential Energy Consumption Survey (RECS) and the Leading Indicator for Remodeling Activity (LIRA) indices to assist in planning and policy making related to residential energy sector.

The building sector is responsible for consuming the largest proportional share of global material and energy resources. Some observers assert that buildings are the problem and the solution to climate change. It appears that in the United States a coherent national energy policy to encourage rapid building performance improvements is not imminent. In this environment, where many climate and ecological scientists believe we are running out of time to reverse the effects of anthropogenic climate change, a local grass-roots effort to create demonstration net zero-energy buildings (ZEB) appears necessary. This paper documents the process of designing a ZEB in a community with no existing documented ZEB precedent. The project will establish a framework for collecting design, performance, and financial data for use by architects, building scientists, and the community at large. This type of information may prove critical in order to foster a near-term local demand for net zero-energy buildings.

Through manipulation of adaptable opportunities available within a given environment, individuals become active participants in managing personal comfort requirements, by exercising control over their comfort without the assistance of mechanical heating and cooling systems. Similarly, continuous manipulation of a building skin's form, insulation, porosity, and transmissivity qualities exerts control over the energy exchanged between indoor and outdoor environments. This research uses four adaptive response variables in a modified software algorithm to explore an adaptive building skin's potential in reacting to environmental stimuli with the purpose of minimizing energy use without sacrificing occupant comfort. Results illustrate that significant energy savings can be realized with adaptive envelopes over static building envelopes even under extreme summer and winter climate conditions; that the magnitude of these savings are dependent on climate and orientation; and that occupant thermal comfort can be improved consistently over comfort levels achieved by optimized static building envelopes. The resulting adaptive envelope's unique climate-specific behavior could inform designers in creating an intelligent kinetic aesthetic that helps facilitate adaptability and resiliency in architecture.

Building Envelope includes walls, roofs and openings, which react to the outdoor environmental condition. Today, with the increasing use of glass in building envelope, the energy usage of the buildings is increasing, especially in the offices and commercial buildings. Use of right glass type and control triggers helps to optimize the energy use, by tradeoff between optical and thermal properties. The part of the research looks at the different control triggers and its range that governs the use of electrochromic glass to regulate the energy usage in building. All different control trigger that can be possibly used for regulating the clear and tint state of glass were analyzed with most appropriate range. Its range was triggered such that 80% time of the glass is trigger between the ranges. The other building parameters like window wall ratio and orientations were also investigated. The other half of the research study looks into the feasibility of using the Electrochromic windows, as it is ought to be the main factor governing the market usage of Electrochromic windows and to investigate the possible ways to make it feasible. Different LCC parameters were studied to make it market feasible product. This study shows that installing this technology with most appropriate trigger range can reduce annual building energy consumption from 6-8% but still cost of the technology is 3 times the ASHRAE glass, which results in 70-90 years of payback. This study concludes that south orientation saves up to 3-5% of energy and 4-6% of cooling tons while north orientation gives negligible saving using EC glass. LCC parameters show that there is relative change in increasing the net saving for different parameters but none except 50% of the present glass cost is the possible option where significant change is observed.

A major problem faced by electric utilities is the need to meet electric loads during certain times of peak demand. One of the widely adopted and promising programs is demand response (DR) where building owners are encouraged, by way of financial incentives, to reduce their electric loads during a few hours of the day when the electric utility is likely to encounter peak loads. In this thesis, we investigate the effect of various DR measures and their resulting indoor occupant comfort implications, on two prototype commercial buildings in the hot and dry climate of Phoenix, AZ. The focus of this study is commercial buildings during peak hours and peak days. Two types of office buildings are modeled using a detailed building energy simulation program (EnergyPlus V6.0.0): medium size office building (53,600 sq. ft.) and large size office building (498,600 sq. ft.). The two prototype buildings selected are those advocated by the Department of Energy and adopted by ASHRAE in the framework of ongoing work on ASHRAE standard 90.1 which reflect 80% of the commercial buildings in the US. After due diligence, the peak time window is selected to be 12:00-18:00 PM (6 hour window). The days when utility companies require demand reduction mostly fall during hot summer days. Therefore, two days, the summer high-peak (15th July) and the mid-peak (29th June) days are selected to perform our investigations. The impact of building thermal mass as well as several other measures such as reducing lighting levels, increasing thermostat set points, adjusting supply air temperature, resetting chilled water temperature are studied using the EnergyPlus building energy simulation program. Subsequently the simulation results are summarized in tabular form so as to provide practical guidance and recommendations of which DR measures are appropriate for different levels of DR reductions and the associated percentage values of people dissatisfied (PPD). This type of tabular recommendations is of direct usefulness to the building owners and operators contemplating DR response. The methodology can be extended to other building types and climates as needed.

The Urban Heat Island (UHI) has been known to have been around from as long as people have been urbanizing. The growth and conglomeration of cities in the past century has caused an increase in the intensity and impact of Urban Heat Island, causing significant changes to the micro-climate and causing imbalances in the temperature patterns of cities. The urban heat island (UHI) is a well established phenomenon and it has been attributed to the reduced heating loads and increased cooling loads, impacting the total energy consumption of affected buildings in all climatic regions. This thesis endeavors to understand the impact of the urban heat island on the typical buildings in the Phoenix Metropolitan region through an annual energy simulation process spanning through the years 1950 to 2005. Phoenix, as a representative city for the hot-arid cooling-dominated region, would be an interesting example to see how the reduction in heating energy consumption offsets the increased demand for cooling energy in the building. The commercial reference building models from the Department of Energy have been used to simulate commercial building stock, while for the residential stock a representative residential model prescribing to IECC 2006 standards will be used. The multiyear simulation process will bring forth the energy consumptions of various building typologies, thus highlighting differing impacts on the various building typologies. A vigorous analysis is performed to see the impact on the cooling loads annually, specifically during summer and summer nights, when the impact of the 'atmospheric canopy layer' - urban heat island (UHI) causes an increase in the summer night time minimum and night time average temperatures. This study also shows the disparity in results of annual simulations run utilizing a typical meteorological year (TMY) weather file, to that of the current recorded weather data. The under prediction due to the use of TMY would translate to higher or lower predicted energy savings in the future years, for changes made to the efficiencies of the cooling or heating systems and thermal performance of the built-forms. The change in energy usage patterns caused by higher cooling energy and lesser heating energy consumptions could influence future policies and energy conservation standards. This study could also be utilized to understand the impacts of the equipment sizing protocols currently adopted, equipment use and longevity and fuel swapping as heating cooling ratios change.