Building energy simulation has become a useful tool for predicting cooling, heating and electrical loads for facilities. Simulation models have been validated throughout the years by comparing simulation results to actual measured values. The simulations have become more accurate as approaches were changed to be more comprehensive in their ability to model building features. These simulation models tend to require considerable experience in determining input parameters and large amounts of time to construct the models. As a result of the large number of man-hours required, simplified models have been sought and used. Simplified models are particularly useful for conducting preliminary assessments of energy conservation measures. These simplified models often use linear relationships in order to estimate conditions such as infiltration, energy usage, and temperature gradients. Studies have been performed in order to validate popular models such as ASHRAE's Bin or Modified Bin methods. A useful measure would be to determine the accuracy of a simplified model to establish error bounds. Having a simplified model and establishing its error bounds, technical estimations from such models could be used in selected applications with more confidence. The error bound relative to DOE-2 predictions, for a proposed simplified model denoted IEC, for estimating a commercial building's cooling load are presented along with two actual-building test cases for validation purposes. The sensitivity of the error to various building parameters such as minimum make-up air, cooling capacity oversize, and internal equipment load was investigated. The error bound was determined to be within ±15 per cent for both cases and almost all variations. / Master of Science

Yes / Detailed electricity load profile for domestic building is an important requirement for the accurate analysis of demand side management. The use of electrical appliances within domestic buildings varies significantly with respect to time, mainly in accordance with the activity and behaviour of the occupants. This paper presents results from a monitoring study of electrical energy consumption profiles for One UK household (two adults with children). Measurements for whole household electricity consumption have been obtained over a period of ten months. They were all obtained at one minute interval. Monthly energy consumptions, daily and overall profiles were derived for this household type from the monitored data. It is intended that the results presented in this paper can be used in the quest for a precise forecast method for electricity consumption for occupants living in the same type of household in the UK. This will allow greater confidence in the sizing of, e.g., adopting renewable energy sources in this type of household. Further investigation is needed for a large sample of households to improve the understanding of monitoring high resolution domestic energy consumption. / MSCRC

Yes / Energy consumers oftentimes suffer some element of discomfort associated with the implementation of demand response programs as they aim to follow a suggested energy consumption profile generated from scheduling algorithms for the purpose of optimizing grid performance. This is because people naturally do not like to be told what to do or when to use their appliances. Although advances in renewable energy have made the consumer to also become energy supplier, who can actively cash in at times of the day when energy cost is high to either sell excess energy generated or consume it internally if required, thereby nullifying the adverse effect of this discomfort. But a majority of consumers still rely wholly on the supply from the grid. This impact on users' comfort who are active participants in demand response programs was investigated and ways to minimizing load scheduling discomfort was sought in order to encourage user participation.

This thesis explored different approaches of clustering residential data. The goal was to develop a model with applications in load forecasting contexts, specifically in situations where only a limited amount of residential data is available. Four different types of approaches were explored, one of which utilised not only data pertaining to the load profile but also data related to the residency. Effects of seasonal and weekly variations were studied to identify how the load profiles were affected by these parameters. In the end the developed clusters were evaluated using silhouette scores as well as using load forecasting models developed outside of the thesis.

Yes / The introduction of smart metering has brought more detailed information on the actual load profile of a house. With the ability to measure, comes the desire to control the load profile. Furthermore, advances in renewable energy have made the consumer to become supplier, known as Prosumer, who therefore also becomes interested in the detail of his load, and also his energy production. With the lowering cost of smart plugs and other automation units, it has become possible to schedule electrical appliances. This makes it possible to adjust the load profiles of houses. However, without a market in the demand side, the use of load profile modification techniques are unlikely to be adapted by consumers on the long term. In this research, we will be presenting work on scheduling of energy appliances to modify the load profiles within a market environment. The paper will review the literature on algorithms used in scheduling of appliances in residential areas. Whilst many algorithms presented in the literature show that scheduling of appliances is feasible, many issues arise with respect to user interaction, and hence adaptation. Furthermore, the criteria used to evaluate the algorithms is often related only to reducing energy consumption, and hence CO2. Whilst this a key factor, it may not necessarily meet the demands of the consumer. In this paper we will be presenting work on a novel genetic algorithm that will optimize the load profile while taking into account user participation indices. A novel measure of the comfort of the customer, derived from the standard deviation of the load profile, is proposed in order to encourage the customer to participate more actively in demand response programs. Different scenarios will also be tested. / This work was supported by the British Council and the UK Department of Business Innovation and Skills under GII funding for the SITARA project.

Control and monitoring networks often operate on AC/DC power systems. DC batteries and chargers are commonly used on industrial plants as auxiliary DC power systems for these control and monitoring networks. The energy demand and load profiles for these control networks differ from application to application. Proper design, sizing, and maintenance of the components that forms part of the DC control power system are therefore required. Throughout the load profile of a control and monitoring system there are various peak currents. The peak currents are classified as inrush and momentary loads. These inrush and momentary loads play a large role when calculating the required battery size for an application. This study investigates the feasibility of using supercapacitors in conjunction with batteries, in order to reduce the size of the required battery capacity. A reduction in the size of the required battery capacity not only influences the cost of the battery itself, but also influences the hydrogen emissions, the physical space requirements, and the required rectifiers and chargers. When calculating the required size batteries for an auxiliary power system, a defined load profile is required. Control and monitoring systems are used to control dynamic processes, which entails a continuous starting and stopping of equipment as the process demands. This starting and stopping of devices will cause fluctuations in the load profile. Ideally, data should be obtained from a live plant for the purpose of defining load profiles. Unfortunately, due to the economic risks involved, installing data logging equipment on a live industrial plant for the purpose of research, is not allowed. There are also no historical data available from which load profiles could be generated. In order to evaluate the influence of supercapacitors, complex load profiles are required. In this study, an alternative method of defining the load profile for a dynamic process is investigated. Load profiles for various applications are approximated using a probabilistic approach. The approximation methodology make use of plant operating philosophies as input to the Markov Chain Monte Carlo simulation theory. The required battery sizes for the approximated profiles are calculated using the IEEE recommended practice for sizing batteries. The approximated load profile, as well the calculated battery size are used for simulating the auxiliary power system. A supercapacitor is introduced into the circuit and the simulations are repeated. The introduction of the supercapacitor relieves the battery of the inrush and momentary loads of the load profile. The battery sizing calculations are repeated so as to test the influence of the supercapacitor on the required battery capacity. In order to investigate the full influence of adding a supercapacitor to the design, the impact on various factors are considered. In this study, these factors include the battery size, charger size, H2 extraction system, as well as maintenance requirements and the life of the battery. No major cost savings where evident from the results obtained. Primary reasons for this low cost saving are the fixed ranges in which battery sizes are available, as well as conservative battery data obtained from battery suppliers. It is believed that applications other than control and monitoring systems will show larger savings. / MIng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2015

Control and monitoring networks often operate on AC/DC power systems. DC batteries and chargers are commonly used on industrial plants as auxiliary DC power systems for these control and monitoring networks. The energy demand and load profiles for these control networks differ from application to application. Proper design, sizing, and maintenance of the components that forms part of the DC control power system are therefore required. Throughout the load profile of a control and monitoring system there are various peak currents. The peak currents are classified as inrush and momentary loads. These inrush and momentary loads play a large role when calculating the required battery size for an application. This study investigates the feasibility of using supercapacitors in conjunction with batteries, in order to reduce the size of the required battery capacity. A reduction in the size of the required battery capacity not only influences the cost of the battery itself, but also influences the hydrogen emissions, the physical space requirements, and the required rectifiers and chargers. When calculating the required size batteries for an auxiliary power system, a defined load profile is required. Control and monitoring systems are used to control dynamic processes, which entails a continuous starting and stopping of equipment as the process demands. This starting and stopping of devices will cause fluctuations in the load profile. Ideally, data should be obtained from a live plant for the purpose of defining load profiles. Unfortunately, due to the economic risks involved, installing data logging equipment on a live industrial plant for the purpose of research, is not allowed. There are also no historical data available from which load profiles could be generated. In order to evaluate the influence of supercapacitors, complex load profiles are required. In this study, an alternative method of defining the load profile for a dynamic process is investigated. Load profiles for various applications are approximated using a probabilistic approach. The approximation methodology make use of plant operating philosophies as input to the Markov Chain Monte Carlo simulation theory. The required battery sizes for the approximated profiles are calculated using the IEEE recommended practice for sizing batteries. The approximated load profile, as well the calculated battery size are used for simulating the auxiliary power system. A supercapacitor is introduced into the circuit and the simulations are repeated. The introduction of the supercapacitor relieves the battery of the inrush and momentary loads of the load profile. The battery sizing calculations are repeated so as to test the influence of the supercapacitor on the required battery capacity. In order to investigate the full influence of adding a supercapacitor to the design, the impact on various factors are considered. In this study, these factors include the battery size, charger size, H2 extraction system, as well as maintenance requirements and the life of the battery. No major cost savings where evident from the results obtained. Primary reasons for this low cost saving are the fixed ranges in which battery sizes are available, as well as conservative battery data obtained from battery suppliers. It is believed that applications other than control and monitoring systems will show larger savings. / MIng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2015

Yes / In the last 10 years the University of Bradford Library Acquisitions Department has shrunk from 13 members of staff to 5. This has led to us embracing new technology to help streamline workflows within the department. As well as utilising EDI functionality, changing processing workflows and using shelf-ready books, we have devised innovative ways of dealing with everyday tasks. Topics included cover: PDA deduplication; spine labelling on a large scale; the weeding of discarded books; using saved global updates on incoming MARC records and using load profiles innovatively.

Research in solar heating has traditionally focused solely on increasing the system efficiency by improving the technical components. In this thesis the technical methodology and system boundaries are widened to connect the technical aspects with market actors that are highly influential on the implementation of solar technology. The research was focused on how social aspects can be brought into technical studies to improve the understanding of solar heating, and how solar thermal technology can be optimized in a larger energy system. Both heat storage and different system solutions have been investigated. The thesis is built on a number of sub-projects exploring different aspects of solar heating. Improved components and system configurations may result in higher fractional energy savings and thereby make solar energy go from a marginal contribution to be the main energy supplier. Both components and systems are considered in this thesis. The solar heating technology has been shown to work well, also in unique system solutions. Technical possibilities with medium-sized stores for single-family houses and seasonal stores for residential areas are presented. Methods to bring studies of technology and actor studies together are also proposed; domestic hot water use has been modelled based on time-use data, while a multifaceted market situation, in which new system solutions must find their way, has been described by the solar and pellet industries. The complexity of assessing installation and use of a particular heating system in relation to the overall energy system is also discussed. Overall, this thesis shows that successful use of solar heating does not only come down to proper technical solutions, but also depends on the interaction between technology and market actors. A widened perspective, including the social context in which the heating system appears, is then essential. This thesis constitutes a step in that direction.

Les territoires ruraux disposent du principal gisement d’énergie renouvelable en France. Les réseaux énergétiques y sont moins denses que dans les zones urbaines et certains vecteurs, tels que le gaz, en sont souvent absents. Or, alors que les systèmes énergétiques urbains ont été abondamment étudiés, les spécificités de la demande énergétique rurale restent méconnues, notamment dans le secteur résidentiel. Des travaux récents mettent en avant les enjeux liés à la décentralisation du système énergétique français et le besoin d’une connaissance fine de l’offre et de la demande, tant sur le plan spatial que temporel. Ce travail de thèse poursuit deux objectifs. Tout d’abord il s’attache à identifier les spécificités de la consommation énergétique des logements ruraux par rapport aux logements urbains. Ensuite, il vise à analyser la réponse que peut apporter le gisement local d’énergie renouvelable à la demande résidentielle sur un territoire mixte urbain-rural, dans une optique de territoire à énergie positive – équilibre annuel entre l’offre et la demande énergétique du territoire. / Rural areas have the main resources of renewable energy in France. Energy networks are less dense there than in urban areas and some energy vectors, like gas, are often missing. However, as urban energy systems have been widely studied, the specificities of rural energy demand remain little-known, especially for the residential sector. Recent works highlight new challenges related to decentralization of the French energy system and the need for fine knowledge of demand and supply, on both spatial and time scales. This research work pursues two objectives. First, it commits to identify the specificities of rural housing energy consumption. Then, it aims at analyzing the potential response of local renewable energy sources to the residential demand in a mixed urban-rural territory, in a 100 % RES process – equilibrium between annual energy demand and supply on the territory.