Framework for a Residential Energy Information System (REMIS) to promote energy efficient behaviour in residential energy end users

Previous studies on residential energy end use behavior reported significant reduction in energy end use of 7% to 24% when feedback is used to modify behavior in an energy efficient manner. However, most feedback systems investigated in previous studies have not benefited from advanced information systems (IS). IS can shape energy efficiency behavior by providing real-time feedback on energy consumption, cost and environmental impact. Such systems represent a new and less-researched subfield of energy informatics. This paper provides a conceptual framework for showing the potential use of IS to modify residential energy use behavior towards better energy efficiency. The framework builds on research in residential energy end use, in particular energy end use behavioral model. It provides conceptual inputs for a blue-print to develop a residential energy management information system (REMIS) and also highlights the use of new information and communications technologies (ICT) that had not been widely used, setting the grounds for further research in this area.

Simulation of a novel piezoelectric energy harvester

This paper focuses on a novel piezoelectric energy harvester for nanofiber PVDF to capture energy from vibration environment. A Resembling CMOS(R-CMOS) circuit consisting of two pMOS transistors and two nMOS transistors is presented, which can greatly increase the energy efficiency and reduce the power dissipation tremendously. Meanwhile, the novel harvester supplies smooth direct current. Simulation result of MULTISIM has shown that by using this novel piezoelectric energy harvester the input voltage (5v) can be rectified to be an output voltage (4.24v). The voltage conversion rate of the novel harvester is as high as 84.8% which is much larger than the rate of traditional rectifier circuit. Its potential application is in micro sensors, wireless transducers, and sensor networks.

Disaggregation of household energy consumption patterns in Australian

Improving energy efficiency is an important target to be achieved in residential building development and household behaviour. The aim of this research is to help building professionals and policy makers understand the current housing situations and householders’ behaviour regarding energy consumption. The results of a survey of energy consumption, including house situations and householder behaviour, of 504 households in New South Wales Australia are reported. Twelve features affecting household energy consumption are investigated. These features included cooking appliances, refrigerators, laundry appliances, televisions, computers, gaming consoles, hot water systems, space cooling and heating systems, glazing, insulation, lighting, and other major energy consumption facilities. The differences of these features across different households with different physical characteristics, social-demographic features and geographical areas are analyzed. Based on the disaggregate study, it is found that mandatory policy, geographical and socio-economic factors can significantly affect the selection of fixtures and appliances in the households. It is also found that the positive effect of the government’s mandatory policy implementation on household energy consumption behaviour is evidenced. The findings will be of use in sustainable residential building development policy-making, and tailoring the regulations and standards with consideration of the various geographical and socio-economic factors.

Integration of resident's energy costs in short stay accommodation billing system

This paper presents an energy management software package and the supporting energy information automation system to enable the short stay accommodation industry to determine actual residents' energy consumption. The proposed energy management system is used to develop a 'novel deal' method in short stay accommodation based on integration of the room level energy costs into the billing system. This system has the potential to increase energy efficiency in the short stay accommodation industry by actively engaging the residents in the energy saving process. The system is economically and environmentally sustainable and can achieve a high level of energy efficiency with low expenses. The proposed model is also effective for carbon mitigation, and offers a value proposition for all the parties in the short stay accommodation industry, including owners and residents. The paper presents a software system to capture room level energy consumption information and to present the detail of consumed energy information in the resident's accommodation bill. The presented information includes energy consumption profile, the greenhouse gas emission profile, and the cost associated to the energy related services.

Defining and developing an energy retrofitting approach

This paper identifies the dilemma faced by the stakeholders of existing buildings in regards to a decision making process for energy retrofitting. This paper also identifies the missing stage viewed as the “integrity audit “which can lead to substantial savings in the area of building operation. The methodology is centered on identifying energy waste first, reducing the overall peak electrical demand and then retrofitting for energy-efficiency. A proposed “integrity audit” leads to the classification of three main energy culprits: the identification of waste, missed opportunities, and rescheduling the operation of equipment use. A case study indicating the financial advantages of applying this methodology for a commercial building are presented. The energy retrofitting strategy is divided into two main categories, namely building control improvements and building component implementation. The payback periods are often within months if not immediate.

An investigation for improved home energy management

 Increasing household energy consumption and increasing primary energy cost urged to improve home energy efficiency. Improved energy management can suggest the ways to improve home energy efficiency. Various home appliances are the prime cause to the increased power demand. Appliance's energy rating information helps to develop awareness and reduce energy consumption. Load shifting can help to reduce overall cost of used energy bill by shifting peak time load to off-peak time. However most of the present appliances remains in standby mode (active or passive) for a significant part of the day, and load shifting cannot reduce the total energy consumption. Therefore investigation is required to identify any possible scopes to improve energy management at home. This paper investigated several home appliances and monitored daily time of use power consumption. It was found that by controlling standby power from a daily home load of 4.482 kWh, power demand can be reduced 12.56% moreover energy related greenhouse gas (GHG) emission can be reduced 133.08kg/year.

Energy efficient information discovery approach for range queries in multi-dimensional WSNs

Multidimensional WSNs are deployed in complex environments to sense and collect data relating to multiple attributes (multi-dimensional data). Such networks present unique challenges to data dissemination, data storage and in-network query processing (information discovery). Recent algorithms proposed for such WSNs are aimed at achieving better energy efficiency and minimizing latency. This creates a partitioned network area due to the overuse of certain nodes in areas which are on the shortest or closest or path to the base station or data aggregation points which results in hotspots nodes. In this paper, we propose a time-based multi-dimensional, multi-resolution storage approach for range queries that balances the energy consumption by balancing the traffic load as uniformly as possible. Thus ensuring a maximum network lifetime. We present simulation results to show that the proposed approach to information discovery offers significant improvements on information discovery latency compared with current approaches. In addition, the results prove that the Quality of Service (QoS) improvements reduces hotspots thus resulting in significant network-wide energy saving and an increased network lifetime.

Identifying the determinants of renewable energy consumption in leading renewable energy investor emerging countries

This article analyses the determinants of renewable energy consumption in six major emerging economies who are proactively accelerating the adoption of renewable energy. The long-run elasticities from both panel methods (fully modified ordinary least square and dynamic least square) and the time series method (autoregressive distributed lag) seem to be pretty consistent. For Brazil, China, India and Indonesia, in the long-run, renewable energy consumption is significantly determined by income and pollutant emission. However, for Philippines and Turkey, income seems to be the main driver for renewable energy consumption. In the short-run, for Brazil and China bi-directional causalities between renewable energy and income; and between renewable energy and pollutant emission are found. This research justifies the efforts undertaken by emerging countries to reduce the carbon intensity by increasing the energy efficiency and substantially increasing the share of renewable in the overall energy mix

Energy minimization in multi-task software-defined sensor networks

Abstract—
After a decade of extensive research on application-specific wireless sensor networks (WSNs), the recent development of information and communication technologies makes it practical to realize the software-defined sensor networks (SDSNs), which are able to adapt to various application requirements and to fully explore the resources of WSNs. A sensor node in SDSN is able to conduct multiple tasks with different sensing targets simultaneously. A given sensing task usually involves multiple sensors to achieve a certain quality-of-sensing, e.g., coverage ratio. It is significant to design an energy-efficient sensor scheduling and management strategy with guaranteed quality-of-sensing for all tasks. To this end, three issues are investigated in this paper: 1) the subset of sensor nodes that shall be activated, i.e., sensor activation, 2) the task that each sensor node shall be assigned, i.e., task mapping, and 3) the sampling rate on a sensor for a target, i.e., sensing scheduling. They are jointly considered and formulated as a mixed-integer with quadratic constraints programming (MIQP) problem, which is then reformulated into a mixed-integer linear programming (MILP) formulation with low computation complexity via linearization. To deal with dynamic events such as sensor node participation and departure, during SDSN operations, an efficient online algorithm using local optimization is developed. Simulation results show that our proposed online algorithm approaches the globally optimized network energy efficiency with much lower rescheduling time and control overhead.