Analysis of Residential Building Energy Code Compliance for New and Existing Buildings Based on Building Energy

Currently, the International Energy Conservation Code (IECC) is the most widely-used residential building energy code in the United States. Either the IECC or IECC with amendments has been adopted by 33 states. The latest version of the IECC contains three compliance requirements, including: mandatory, prescriptive, and performance paths for compliance. The performance path includes specifications for the standard house design and the proposed design to be analyzed using whole-building energy simulations. In the performance path, the annual simulated energy cost of the proposed house must be less than the annual energy cost (or source energy usage) of the standard reference house. Unfortunately, most of the whole-building energy simulation programs are too complicated to be used by building energy code officials or homeowners without special training. To resolve this problem, simplified simulation tools have been developed that require fewer user input parameters. Such simplified software tools have had a significant impact on the increased use of the performance-based code compliance path for residential analysis. However, many of the simplified features may not represent the energy efficient features found in an existing residence. This may mis-represent the potential energy saving when/if a house owner decides to invest in a retrofit to reduce their annual energy costs. Currently, there are building energy simulation validation methods developed by ASHRAE, and RESNET including: ASHRAE Standard-140, IEA BESTEST, HVAC BESTEST, and BESTEST-EX. These tests have been developed to test the algorithms of building energy performance simulation, which require complex inputs and outputs to view the test results. Unfortunately, even though two different building simulation validation programs may produce the necessary inputs/outputs for certification, they are rarely tested side-by-side or on actual residences. Furthermore, results from a simplified analysis of a building is rarely compared against a detailed simulation of an existing building. Therefore, there is a need to compare the results of a simplified simulation versus a detailed simulation of an existing residence to better determine which parameters best represent the existing house so more accurate code-compliant simulations can be performed on existing structures. The purpose of this study is to develop an accurate, detailed simulation model of an existing single-family residence that is compared with a simplified building energy simulation of the same residence to help determine which on-site measurements can be made to help tune the simplified model so it better represents the existing residence. Such an improved building energy simulation can be used to better represent annual energy cost savings from retrofits to an existing building

Methodologies for City-scale Microgeneration Viability Assessment

Over the last decade, increasing numbers of multi-national corporations, public institutions and individual property owners have become interested in installing solar photovoltaics and small wind turbines. To best inform this broad range of actors, this research aims to assess the financial viability of such investments across broad city regions whilst maintaining accuracy at individual properties. Publicly available digital representations of urban surfaces are central to meeting this aim because they can be used to assess the area, slope and orientation of potential solar photovoltaic (PV) installation sites and to define how vertical wind profiles are altered by urban areas. A first study utilised digital surface models (DSMs) across seven UK cities to assess the roof spaces available for solar PV and also incorporated socio-economic factors to define the propensity for cities to install the technology. Despite changes to financial incentives that had recently occurred, the technologies remained viable at a very large number of locations and could theoretically meet large percentages (16% to 43%) of the cities’ electricity demands. The accuracy of slope, orientation and available area estimation in roof geometry modelling was then improved through the development of a neighbouring buildings method. In 87% of 536 validated results, the method identified the correct roof shape and roof slope was estimated to a mean absolute error of 3.76° when compared to 182 measured roofs. Work was then undertaken to improve solar insolation modelling. A radiative transfer model was created that incorporated shading based on DSM data. It estimated the power output of 17 solar PV installations across four UK cities with +2.62% mean percentage error when its 2013 insolation estimates were converted to power outputs using a 0.8 performance ratio. The validation data showed that the RTS model outperformed the market-leading esri ArcMap solar radiation software which incurred a -15.97% mean percentage error. This method was then adapted to be deployable on a city scale and predicted solar insolation with a mean percentage error of -4.39% despite the process being made far more computationally efficient. A method to estimate long-term average wind speeds for urban areas was then developed that produced results of comparable accuracy to an existing model but with considerably reduced computational demand and complexity in deployment. The mean absolute error inwind speed estimation was just 1.75% greater using the simplified methodology than the existing model. Finally, the improved modelling of roof geometries, solar insolation and long-term mean wind speed were brought together to evaluate the city-scale potential for solar PV and small to medium wind microgeneration. The research has shown that wind and solar PV microgeneration at sites that pay back within nine years could theoretically meet 88.5% of annual domestic electricity demand in the city of Leeds, or would be the equivalent of providing electricity to 300,319 homes. Current financial contexts were used to define a baseline scenario from which hypothetical changes to a variety of factors influencing microgeneration viability were investigated. When the costs and revenues were defined from a pessimistic, but still realistic, perspective the percentage of the study area’s electricity demand that could theoretically be met by wind and solar PV microgeneration fell to 0.1%. This suggests that government policy will continue to play a key role in the future growth of UK wind and solar PV deployment

Bio-economic process-based modelling methodology for measuring and evaluating the ecosystem services provided by agroforestry systems

Doutoramento em Engenharia Florestal e dos Recursos Naturais / Instituto Superior de Agronomia. Universidade de LisboaAgroforestry integrates woody vegetation with crop and/or animal production. This combination can benefit from ecological and economic interactions that allow better use of natural resources and improved economic performance. But despite financial support offered through policy, the implementation of new agroforestry systems has not been widespread in the European Union. This thesis aimed to develop additional scientific knowledge on the potential of agroforestry systems in terms of productivity and environmental benefits. The method consisted in improving a bio-physical process-based model (Yield-SAFE) and an integrated bio-economic model (Farm-SAFE) and using both to model four different agroforestry systems in different edaphoclimatic conditions in Europe. Four different agroforestry tree-densities were compared to no-tree and tree-only monoculture alternatives. The results showed that: 1) in terms of productivity, the inclusion of trees in agricultural land increases the overall accumulated energy but the accumulated energy per tree decreases as the tree density of trees increases; 2) agroforestry options present a greater capacity of reducing soil erosion, nitrate leaching and increases the carbon sequestration; 3) agroforestry systems can act as more sustainable methods of food production and 4) options without trees are more interesting financially but these option are also the most polluting. And even though the consideration of a monetary valuation of the environmental services offered, agroforestry options would just become more interesting if there is a change on how public financial help is allocated to the sector. The findings of this work reflect what has been previously seen in scientific literature, particularly in terms of the capacity of agroforestry systems to be more productive than monoculture systems, whilst at the same time providing environmental benefits. However, relatively low profitability means that they still fail to attract farmers, the main agents of agroforestry uptake and currently, arable and forestry tend to receive higher subsidies making these land uses more attractive to farmers but considering environmental benefits would make agroforestry a more interesting optionN/

Analysis of Residential Building Energy Code Compliance for New and Existing Buildings based on Building Energy Simulation

Currently, the International Energy Conservation Code (IECC) is the most widely-used residential building energy code in the United States. Either the IECC or IECC with amendments has been adopted by 33 states. The latest version of the IECC contains three compliance requirements, including: mandatory, prescriptive, and performance paths for compliance. The performance path includes specifications for the standard house design and the proposed design to be analyzed using whole-building energy simulations. In the performance path, the annual simulated energy cost of the proposed house must be less than the annual energy cost (or source energy usage) of the standard reference house. Unfortunately, most of the whole-building energy simulation programs are too complicated to be used by building energy code officials or homeowners without special training. To resolve this problem, simplified simulation tools have been developed that require fewer user input parameters. Such simplified software tools have had a significant impact on the increased use of the performance-based code compliance path for residential analysis. However, many of the simplified features may not represent the energy efficient features found in an existing residence. This may mis-represent the potential energy saving when/if a house owner decides to invest in a retrofit to reduce their annual energy costs. Currently, there are building energy simulation validation methods developed by ASHRAE, and RESNET including: ASHRAE Standard-140, IEA BESTEST, HVAC BESTEST, and BESTEST-EX. These tests have been developed to test the algorithms of building energy performance simulation, which require complex inputs and outputs to view the test results. Unfortunately, even though two different building simulation validation programs may produce the necessary inputs/outputs for certification, they are rarely tested side-by-side or on actual residences. Furthermore, results from a simplified analysis of a building is rarely compared against a detailed simulation of an existing building. Therefore, there is a need to compare the results of a simplified simulation versus a detailed simulation of an existing residence to better determine which parameters best represent the existing house so more accurate code-compliant simulations can be performed on existing structures. The purpose of this study is to develop an accurate, detailed simulation model of an existing single-family residence that is compared with a simplified building energy simulation of the same residence to help determine which on-site measurements can be made to help tune the simplified model so it better represents the existing residence. Such an improved building energy simulation can be used to better represent annual energy cost savings from retrofits to an existing building

Saving Energy in QoS Networked Data Centers

One of the major challenges that cloud providers face is minimizing power consumption of their data centers. To this point, majority of current research focuses on energy efficient management of resources in the Infrastructure as a Service model using virtualization and through virtual machine consolidation. However, current virtualized data centers are not designed for supporting communication–computing intensive real-time applications, such as, info-mobility applications, real-time video co-decoding. In fact, imposing hard-limits on the overall per-job delay forces the overall networked computing infrastructure to adapt quickly its resource utilization to the (possibly, unpredictable and abrupt) time fluctuations of the offered workload. Jointly, a promising approach for making networked data centers more energy-efficient is the use of traffic engineering-based method to dynamically adapt the number of active servers to match the current workload. Therefore, it is desirable to develop a flexible and robust resource allocation algorithm that automatically adapts to time-varying workload and pays close attention to the consumed energy in computing and communication in virtualized networked data centers (VNetDCs). In this thesis, we propose three new dynamic and adaptive energy-aware algorithms scheduling policies that model and manage VNetDCs. Our focuses are to propose i) admission control of the offered input traffic; ii) balanced control and dispatching of the admitted workload; iii) dynamic reconfiguration and consolidation of the Dynamic Voltage and Frequency Scaling (DVFS)-enabled Virtual Machines (VMs) instantiated onto the parallel computing platform; and, iv) rate control of the traffic injected into the TCP/IP mobile connection. Necessary and sufficient conditions for the feasibility and optimality of the proposed schedulers are also provided in closed-form. Specifically, the first approach, called VNetDC, the optimal minimum-energy scheduler for the joint adaptive load balancing and provisioning of the computing-plus-communication resources. VNetDC platforms have been considered which operate under hard real-time constraints. VNetDC has capability to adapt to the time-varying statistical features of the offered workload without requiring any a priori assumption and/or knowledge about the statistics of the processed data. Green- NetDC is the second scheduling policy that is a flexible and robust resource allocation algorithm that automatically adapts to time-varying workload and pays close attention to the consumed energy in computing and communication in VNetDCs. GreenNetDC not only ensures users the Quality of Service (through Service Level Agreements) but also achieves maximum energy saving and attains green cloud computing goals in a fully distributed fashion by utilizing the DVFS-based CPU frequencies. Finally, the last algorithm tested an efficient dynamic resource provisioning scheduler which applied in Networked Data Centers (NetDCs). This method is connected to (possibly, mobile) clients through TCP/IP-based vehicular backbones The salient features of this algorithm is that: i) It is adaptive and admits distributed scalable implementation; ii) It is capable to provide hard QoS guarantees, in terms of minimum/maximum instantaneous rate of the traffic delivered to the client, instantaneous goodput and total processing delay; and, iii) It explicitly accounts for the dynamic interaction between computing and networking resources, in order to maximize the resulting energy efficiency. Actual performance of the proposed scheduler in the presence of :i) client mobility; ii)wireless fading; iii)reconfiguration and two-thresholds consolidation costs of the underlying networked computing platform; and, iv)abrupt changes of the transport quality of the available TCP/IP mobile connection, is numerically tested and compared against the corresponding ones of some state-of-the-art static schedulers, under both synthetically generated and measured real-world workload traces

Modelling and reducing gas emissions from naturally ventilated livestock buildings

Livestock buildings are identified to be a major source of ammonia emissions. About 30% of the total ammonia emission within livestock sectors is from naturally ventilated dairy cattle buildings. The main objectives of this study are to predict emissions from naturally ventilated dairy cattle buildings and to establish a systematic approach to curtail the emissions.Gas concentrations were measured inside two dairy cattle buildings in mid-Jutland, Denmark. CO2 balance method was thus applied to estimate ventilation and emission rates. Computational fluid dynamics (CFD) was used to find the optimum gas sampling positions for outlet CO2 concentration. The gas sampling positions should be located adjacent to the openings or even in the openings. The NH3 emission rates varied from 32 to77 g HPU-1 d-1 in building 1 and varied from 18 to30 g HPU-1 d-1 in building 2.Scale model experiment showed that partial pit ventilation was able to remove a large portion of polluted gases under the slatted floor. In the full scale simulations, a pit exhaust with a capacity of 37.3 m3 h-1 HPU-1 may reduce ammonia emission only by 3.16% compared with the case without pit ventilation. When the external wind was decreased to 1.4 m s-1 and the sidewall opening area were reduced to half, such a pit ventilation capacity can reduce ammonia emission by 85.2%. The utilization of pit ventilation system must be integrated with the control of the natural ventilation rates of the building