Mobility based energy efficient and multi-sink algorithms for consumer home networks

With the fast development of the Internet, wireless communications and semiconductor devices, home networking has received significant attention. Consumer products can collect and transmit various types of data in the home environment. Typical consumer sensors are often equipped with tiny, irreplaceable batteries and it therefore of the utmost importance to design energy efficient algorithms to prolong the home network lifetime and reduce devices going to landfill. Sink mobility is an important technique to improve home network performance including energy consumption, lifetime and end-to-end delay. Also, it can largely mitigate the hot spots near the sink node. The selection of optimal moving trajectory for sink node(s) is an NP-hard problem jointly optimizing routing algorithms with the mobile sink moving strategy is a significant and challenging research issue. The influence of multiple static sink nodes on energy consumption under different scale networks is first studied and an Energy-efficient Multi-sink Clustering Algorithm (EMCA) is proposed and tested. Then, the influence of mobile sink velocity, position and number on network performance is studied and a Mobile-sink based Energy-efficient Clustering Algorithm (MECA) is proposed. Simulation results validate the performance of the proposed two algorithms which can be deployed in a consumer home network environment.

Post-occupancy evaluation studies in recently refurbished office building: energy performance and employees' satisfaction

Existing buildings contribute greatly to global energy use and greenhouse gas emissions. In the UK, about 18% of carbon emissions are generated by non-domestic buildings; sustainable building refurbishment can play an important role in reducing carbon emissions. This paper looks at the performance of a recently refurbished 5-storey office building in London, in terms of energy consumption as well as occupants’ satisfaction. Pre- and post-occupancy evaluation studies were conducted using online questionnaire surveys and energy consumption evaluation. Results from pre-occupancy and post-occupancy evaluation studies showed that employees, in general, were more satisfied with their work environment at the refurbished building than with that of their previous office. Employees’ self-reported productivity improved after the move to Elms House. These surveys showed a positive relationship between employees’ satisfaction with their work environment and their self-reported productivity, well-being and enjoyment at work. The factor that contributed to increasing employee satisfaction the most was: better use of interior space. Although the refurbishment was a success in terms of reducing energy consumption per m2, the performance gap was almost 3 times greater than that estimated. Unregulated loads, problems with building control, ineffective use of space and occupants’ behaviour are argued to be reasons for this gap.

Post-occupancy studies of an office environment: Energy performance and occupants’ satisfaction

It is generally accepted that the physical workplace environment affects employees’ satisfaction and, consequently, their perceived productivity and well-being. This study investigated whether employee “satisfaction” variables can predict perceived productivity, well-being and enjoyment at work, and if so, to what extent. The study also explored whether limiting employees’ control over their environment could save energy without compromising employees’ satisfaction and perceived productivity. Preoccupancy and post-occupancy evaluation studies were conducted, in terms of both energy consumption and employee perceptions, to make comparisons between a company’s old and current headquarters buildings, both located in the same area of London. The results showed that employees were more satisfied with their work environment at their new HQ, in general, than with that of their previous office. Also, employees’ self-reported productivity, well-being and enjoyment at work improved after the move. It was revealed that the combination of employees’ level of satisfaction with “interior use of space” and “physical conditions” was the best predictor of their perceived productivity, while satisfaction with “indoor facilities” was not a good predictor. In terms of energy performance, although the new HQ’s energy consumption per m2 was significantly less than that of the previous building, there was still a gap between the refurbishment design target and the actual performance of the building. The findings suggest that this gap could be due to a number of factors, including an ineffective use of interior space, and occupants’ behaviour.

Analysis and modeling of active occupancy of the residential sector in Spain: an indicator of residential electricity consumption

The growing energy consumption in the residential sector represents about 30% of global demand. This calls for Demand Side Management solutions propelling change in behaviors of end consumers, with the aim to reduce overall consumption as well as shift it to periods in which demand is lower and where the cost of generating energy is lower. Demand Side Management solutions require detailed knowledge about the patterns of energy consumption. The profile of electricity demand in the residential sector is highly correlated with the time of active occupancy of the dwellings; therefore in this study the occupancy patterns in Spanish properties was determined using the 2009–2010 Time Use Survey (TUS), conducted by the National Statistical Institute of Spain. The survey identifies three peaks in active occupancy, which coincide with morning, noon and evening. This information has been used to input into a stochastic model which generates active occupancy profiles of dwellings, with the aim to simulate domestic electricity consumption. TUS data were also used to identify which appliance-related activities could be considered for Demand Side Management solutions during the three peaks of occupancy.

Domestic energy models: complexities in defining specific tools

The domestic (residential) sector accounts for 30% of the world’s energy consumption hence plays a substantial role in energy management and CO2 emissions reduction efforts. Energy models have been generally developed to mitigate the impact of climate change and for the sustainable management and planning of energy resources. Although there are different models and model categories, they are generally categorised into top down and bottom up. Significantly, top down models are based on aggregated data while bottom up models are based on disaggregated data. These approaches create fundamental differences which have been the centre of debate since the 1970’s. These differences have led to noticeable discrepancies in results which have led to authors arguing that the models are of a more complementary than a substituting nature. As a result developing methods suggest that there is the need to integrate either the two models (bottom up − top down) or aspects that combine two bottom up models or an upgrade of top down models to compensate for the documented limitations. Diverse schools of thought argue in favour of these integrations – currently known as hybrid models. In this paper complexities of identifying country specific and/or generic domestic energy models and their applications in different countries have been critically reviewed. Predominantly from the review it is evident that most of these methods have been adapted and used in the ‘western world’ with practically no such applications in Africa.

The timing and societal synchronisation of energy demand

It is increasingly important to know about when energy is used in the home, at work and on the move. Issues of time and timing have not featured strongly in energy policy analysis and in modelling, much of which has focused on estimating and reducing total average annual demand per capita. If smarter ways of balancing supply and demand are to take hold, and if we are to make better use of decarbonised forms of supply, it is essential to understand and intervene in patterns of societal synchronisation. This calls for detailed knowledge of when, and on what occasions many people engage in the same activities at the same time, of how such patterns are changing, and of how might they be shaped. In addition, the impact of smart meters and controls partly depends on whether there is, in fact scope for shifting the timing of what people do, and for changing the rhythm of the day. Is the scheduling of daily life an arena that policy can influence, and if so how? The DEMAND Centre has been linking time use, energy consumption and travel diary data as a means of addressing these questions and in this working paper we present some of the issues and results arising from that exercise.

Energy-efficient hybrid system for Wireless Body Area Network Applications

Wireless Body Area Networks (WBANs) consist of a number of miniaturized wearable or implanted sensor nodes that are employed to monitor vital parameters of a patient over long duration of time. These sensors capture physiological data and wirelessly transfer the collected data to a local base station in order to be further processed. Almost all of these body sensors are expected to have low data-rate and to run on a battery. Since recharging or replacing the battery is not a simple task specifically in the case of implanted devices such as pacemakers, extending the lifetime of sensor nodes in WBANs is one of the greatest challenges. To achieve this goal, WBAN systems employ low-power communication transceivers and low duty cycle Medium Access Control (MAC) protocols. Although, currently used MAC protocols are able to reduce the energy consumption of devices for transmission and reception, yet they are still unable to offer an ultimate energy self-sustaining solution for low-power MAC protocols. This paper proposes to utilize energy harvesting technologies in low-power MAC protocols. This novel approach can further reduce energy consumption of devices in WBAN systems.

Trends in domestic electricity consumption in Botswana

Data on electricity consumption patterns relating to different end uses in domestic houses in Botswana is virtually non-existent, despite the fact that the total electricity consumption patterns are available. This can be attributed to the lack of measured and quantified data and in other instances the lack of modern technology to perform such investigations. This paper presents findings from initial studies that are envisaged to bridge the gap. Electricity consumption patterns of 275 domestic households in Gaborone (the capital city of Botswana) have been studied. This was carried out through a questionnaire survey and electricity measurements. Households were categorized based on the number of people occupying the house. From the study, it was evident that the number of people influences the amount of energy a household use although this cannot be treated as an independent factor when assessing energy use. The study also indicated that heating, cooling and domestic hot water (DHW) account for over 30% of energy used in the home. This is worth considering in energy consumption reduction measures. Due to a small sample size, it would not be wise to draw sweeping conclusions from the analysis of this paper or to make statements that would be aimed at influencing policies. However, the results presented forms a formidable base for further research, which is currently on going.

Identifying behavioural predictors of small power electricity consumption in office buildings

It is widely accepted that there is a gap between design energy and real world operational energy consumption. The behaviour of occupants is often cited as an important factor influencing building energy performance. However, its consideration, both during design and operation, is overly simplistic, often assuming a direct link between attitudes and behaviour. Alternative models of decision making from psychology highlight a range of additional influential factors and emphasise that occupants do not always act in a rational manner. Developing a better understanding of occupant decision making could help inform office energy conservation campaigns as well as models of behaviour employed during the design process. This paper assesses the contribution of various behavioural constructs on small power consumption in offices. The method is based upon the Theory of Planned Behaviour (TPB) which assumes that intention is driven by three factors: attitude, subjective norms, and perceived behavioural control, but we also consider a fourth construct: habit measured through the Self- Report Habit Index (SRHI). A questionnaire was issued to 81 participants in two UK offices. Questionnaire results for each behavioural construct were correlated against each participant’s individual workstation electricity consumption. The intentional processes proposed by TPB could not account for the observed differences in occupants’ interactions with small power appliances. Instead, occupants were interacting with small power “automatically”, with habit accounting for 11% of the variation in workstation energy consumption. The implications for occupant behaviour models and employee engagement campaigns are discussed.

Decoupling of building energy use and climate

Energy use intensity (EUI) and climate have a well documented correlation, which is generally applied in building energy management. Green buildings have sought to greatly reduce energy consumption and a number of examples are documented in the literature. A sample of high performance buildings constructed in a variety of global locations is analyzed here, and provides evidence that measures to reduce energy consumption have reduced EUI to the point where its correlation with heating degree days is no longer apparent. This result suggests that end-user behaviour is the next major hurdle in lowering the energy consumption of greener buildings.

Energy savings in buildings or UHI mitigation? Comparison between green roofs and cool roofs

The intensification of the Urban Heat Island effect (UHI) is a problem that involves several fields, and new adequate solutions are required to mitigate its amplitude. The construction sector is strictly related with this phenomenon; in particular, roofs are the envelope components subject to the highest solar irradiance, hence any mitigation strategy should start from them and involve their appropriate design process. For this purpose, cool materials, i.e. materials which are able to reflect a large amount of solar radiation and avoid overheating of building surfaces have been deeply analyzed in the last years both at building and urban scales, showing their benefits especially in hot climates. However, green roofs also represent a possible way to cope with UHI, even if their design is not straightforward and requires taking into account many variables, strictly related with the local climatic conditions. In this context, the present paper proposes a comparison between cool roofs and green roofs for several Italian cities that are representative of different climatic conditions. In search of the most effective solution, the answers may be different depending on the perspective that leads the comparison, i.e. the need to reduce the energy consumption in buildings or the desire to minimize the contribution of the UHI effect.

Wireless energy behaviour monitoring (Wi-be) for office buildings

This paper presents a study on reduction of energy consumption in buildings through behaviour change informed by wireless monitoring systems for energy, environmental conditions and people positions. A key part to the Wi-Be system is the ability to accurately attribute energy usage behaviour to individuals, so they can be targeted with specific feedback tailored to their preferences. The use of wireless technologies for indoor positioning was investigated to ascertain the difficulties in deployment and potential benefits. The research to date has demonstrated the effectiveness of highly disaggregated personal-level data for developing insights into people’s energy behaviour and identifying significant energy saving opportunities (up to 77% in specific areas). Behavioural research addressed social issues such as privacy, which could affect the deployment of the system. Radio-frequency research into less intrusive technologies indicates that received-signal-strength-indicator-based systems should be able to detect the presence of a human body, though further work would be needed in both social and engineering areas.

Optimal power management strategy for energy storage with stochastic loads

In this paper, a power management strategy (PMS) has been developed for the control of energy storage in a system subjected to loads of random duration. The PMS minimises the costs associated with the energy consumption of specific systems powered by a primary energy source and equipped with energy storage, under the assumption that the statistical distribution of load durations is known. By including the variability of the load in the cost function, it was possible to define the optimality criteria for the power flow of the storage. Numerical calculations have been performed obtaining the control strategies associated with the global minimum in energy costs, for a wide range of initial conditions of the system. The results of the calculations have been tested on a MATLAB/Simulink model of a rubber tyre gantry (RTG) crane equipped with a flywheel energy storage system (FESS) and subjected to a test cycle, which corresponds to the real operation of a crane in the Port of Felixstowe. The results of the model show increased energy savings and reduced peak power demand with respect to existing control strategies, indicating considerable potential savings for port operators in terms of energy and maintenance costs.

Cross layer based protocols for energy aware and critical data delivery related applications using wireless sensor networks

Wireless Sensor Networks (WSNs) have been an exciting topic in recent years. The services offered by a WSN can be classified into three major categories: monitoring, alerting, and information on demand. WSNs have been used for a variety of applications related to the environment (agriculture, water and forest fire detection), the military, buildings, health (elderly people and home monitoring), disaster relief, and area or industrial monitoring. In most WSNs tasks like processing the sensed data, making decisions and generating emergency messages are carried out by a remote server, hence the need for efficient means of transferring data across the network. Because of the range of applications and types of WSN there is a need for different kinds of MAC and routing protocols in order to guarantee delivery of data from the source nodes to the server (or sink). In order to minimize energy consumption and increase performance in areas such as reliability of data delivery, extensive research has been conducted and documented in the literature on designing energy efficient protocols for each individual layer. The most common way to conserve energy in WSNs involves using the MAC layer to put the transceiver and the processor of the sensor node into a low power, sleep state when they are not being used. Hence the energy wasted due to collisions, overhearing and idle listening is reduced. As a result of this strategy for saving energy, the routing protocols need new solutions that take into account the sleep state of some nodes, and which also enable the lifetime of the entire network to be increased by distributing energy usage between nodes over time. This could mean that a combined MAC and routing protocol could significantly improve WSNs because the interaction between the MAC and network layers lets nodes be active at the same time in order to deal with data transmission. In the research presented in this thesis, a cross-layer protocol based on MAC and routing protocols was designed in order to improve the capability of WSNs for a range of different applications. Simulation results, based on a range of realistic scenarios, show that these new protocols improve WSNs by reducing their energy consumption as well as enabling them to support mobile nodes, where necessary. A number of conference and journal papers have been published to disseminate these results for a range of applications.

Composition and cure temperature: The influence on properties of final flexible PU cold cure foam parts

Foams are cellular structures, produced by gas bubbles formed during the polyurethane polymerization mixture. Flexible PU foams meet the following two criteria: have a limited resistance to an applied load, being both permeable to air and reversibly deformable. There are two main types of flexible foams, hot and cold cure foams differing in composition and processing temperatures. The hot cure foams are widely applied and represent the main composition of actual foams, while cold cure foams present several processing and property advantages, e.g, faster demoulding time, better humid aging properties and more versatility, as hardness variation with index changes are greater than with hot cure foams. The processing of cold cure foams also is attractive due to the low energy consumption (mould temperature from 30 degrees to 65 degrees C) comparatively to hot cure foams (mould temperature from 30 degrees to 250 degrees C). Another advantage is the high variety of soft materials for low temperature processing moulds. Cold cure foams are diphenylmethane diisocyanate (MDI) based while hot cure foams are toluene diisocyanate (TDI) based. This study is concerned with Viscoelastic flexible foams MDI based for medical applications. Differential Scanning Calorimetry (DSC) was used to characterize the cure kinetics and Dynamical Mechanical Analisys to collect mechanical data. The data obtained from these two experimental procedures were analyzed and associated to establish processing/properties/operation conditions relationships. These maps for the selection of optimized processing/properties/operation conditions are important to achieve better final part properties at lower costs and lead times.