The welfare economics of measuring sustainability: a new approach based on social choice theory and systems analysis

This paper presents a new measure of sustainability within a welfare economics framework. Gross domestic product (GDP) can be used as an indicator of sustainability if the GDP estimates are undertaken within a cost-benefit analysis framework based on social choice perspectives. Sustainability is dependent on a healthy and functioning socio-economic and environmental (SEE) system. Economic development can damage the SEE system through resource degradation, over-harvesting and pollution. This paper addresses the tensions between economic development and sustainability by undertaking a number of SEE-based adjustments to GDP based on social choice perspectives in order to measure sustainability. These adjustments include the environmental and social costs caused by economic development such as water pollution, the depletion of non-renewable resources, and deforestation. Thailand is used as a case study for a 25 year period (1975-1999). The results show a divergence in terms of GDP per capita and the SEE-adjusted GDP per capita figure. The paper concludes that, with increasing environmental and social costs of economic development, pursuing such extreme high growth objectives without due environmental and social considerations can threaten present social welfare and future sustainability. Copyright © 2005 John Wiley & Sons, Ltd and ERP Environment.

A systems analysis method for online teaching and learning systems

A Method for Educational Analysis and Design (MEAD) was developed to analyse and design online teaching and learning systems. The method is based upon a participational design approach focused on the requirements of the users (students)

The relationship between repeated sprint ability and the aerobic and anaerobic energy systems

A large number of team games require participants to repeatedly produce maximal or near maximal sprints of short duration with brief recovery periods. The purpose of the present study was to determine the relationship between a repeated sprint ability (RSA) test that is specific to the energy demands of Australian Rules football (ARF), and the aerobic and anaerobic energy systems. 

The contribution of residential solar energy systems to the reduction of greenhouse gas emissions in the borough of Queenscliffe

The Borough of Queenscliffe has identified the importance of reducing its greenhouse gas emissions and aims to become a carbon zero municipality by 2020. For a house, suburb or town to become carbon neutral ideally it produces an equivalent amount of energy from renewable resources to that which it consumes. By increasing the number of solar systems, both photovoltaic (PV) and hot water, in the residential sector, greenhouse gas emissions will be reduced. The number of solar systems located in the Borough of Queenscliffe has been estimated and a database of these systems has been created, including the size and panel orientation. The energy generated by each solar system, in addition to the reductions in greenhouse gas emissions, has been calculated for an average year.

Development of distributed energy systems for Middle East Countries

Although Renewable energy applications in Middle East countries were started in the middle of the seventies, they have only gained momentum in the last ten years. Considering the past gained experience, a proposed national Renewable Energy (RE) plan aims toward bringing RE into the main stream of the national energy supply system with a target contribution of 10% of the electricity demand by the year 2020. The proposed plan calls for a wide spectrum of renewable energy applications. This paper will highlight renewable energy applications in Middle East countries, the gained experience, the RE resources, and the future prospects for the utilization of RE recourses.

Empowering the smart grid : can redox batteries be matched to renewable energy systems for energy storage?

The charging of an undivided cerium–zinc redox battery by various current waveforms some of which mimic the output of renewable energy (solar, wind, tidal, biofuel burning) to electricity transducers is considered in this work, where the battery operates through diffusion-only conditions, and is discharged galvanostatically. Under reasonable assumption, the mathematical model developed enables the observation that the performance characteristic of the cells charged with a constant power input differentiates between the various current–charge waveforms, with cell geometry and electrode kinetics playing subtle, but significant, roles; in particular, high efficiency is observed for sunlight-charged batteries which are thin and suffer no corrosion of the sacrificial electrode, and which have already experienced a charge–discharge cycle. The performance characteristics of the systems are interpreted in the light of consequences for smart grid realisation, and indicate that, for a constant power input, the most matched renewable is biofuel burning with a current output that linearly increases with time.

Energy-efficiency analysis of cluster-based routing protocols in wireless sensor network

This paper extends the conditions of the cluster-based routing protocols in terms of general algorithm complexity of data fusion, general compressing ratio of data fusion, and network area with long distance. Corresponding three general evaluation methods to evaluate the energy efficiency of the cluster-based routing protocols such as LEACH, PEGASIS, and BCDCP are provided. Moreover, three facts are found in them: (1) High-level software energy macro model is used to compute the energy dissipation of general data fusion software and make the constant value of energy dissipation of 1-bit data fusion an especial instance. (2) Multi-hop energy efficiency is related to the radio hardware parameters and the dynamic topology of network and the above protocols do not exploit the best use of the energy efficiency of multi-hop scheme. (3) High-energy dissipation non-cluster-head nodes, whose number changes with the density of the sensor nodes in clusters, worsen the death of nodes. The numerical results of experiments reprove these discoveries. Furthermore, they provide helpful guide for improving the above routing protocols to extent their application ranges.

Characteristics evaluation of an LMI-synthesis H∞ controller for a superconducting magnetic energy systems applied in power systems

© 2015 IEEE.This paper presents an H« controller synthesised based on linear matrix inequalities (LMI) for a current source converter based superconducting magnetic energy systems (SMESs) connected to a node of power systems where the regulation of grid current has considered as a control objective. To facilitate the control design, the system is represented in terms of state space realization with uncertainties. The control design involves selecting proper weighting functions and performing LMI-synthesis. The controller order is reduced by Henkel-norm method. Simulations are carried out to evaluate the characteristics of the controller under parametric uncertainties. It is found out that the proposed controller is inherently stable, possesses significantly small tracking error, and preserves robust performance for the SMES.

Automating performance and energy consumption analysis for cloud applications

In cloud environments, IT solutions are delivered to users via shared infrastructure, enabling cloud service providers to deploy applications as services according to user QoS (Quality of Service) requirements. One consequence of this cloud model is the huge amount of energy consumption and significant carbon footprints caused by large cloud infrastructures. A key and common objective of cloud service providers is thus to develop cloud application deployment and management solutions with minimum energy consumption while guaranteeing performance and other QoS specified in Service Level Agreements (SLAs). However, finding the best deployment configuration that maximises energy efficiency while guaranteeing system performance is an extremely challenging task, which requires the evaluation of system performance and energy consumption under various workloads and deployment configurations. In order to simplify this process we have developed Stress Cloud, an automatic performance and energy consumption analysis tool for cloud applications in real-world cloud environments. Stress Cloud supports the modelling of realistic cloud application workloads, the automatic generation of load tests, and the profiling of system performance and energy consumption. We demonstrate the utility of Stress Cloud by analysing the performance and energy consumption of a cloud application under a broad range of different deployment configurations.

Multi-agent approach for enhancing security of protection schemes in cyber-physical energy systems

This paper presents a distributed multi-agent scheme to detect and identify cyber threats on the protection systems of power grids. The integration of information and communication technologies (ICTs) into existing power grids builds critical cyberphysical energy systems CPESs) in which digital relays are networked cyber-physical components subject to various cyber threats. Cyber attacks on protection systems may mimic real faults, cause component failure, and disable the communication links. Agents utilize both cyber and physical properties to reinforce the detection technique and further distinguish cyber attacks from physical faults. This paper also introduces the problem of secure communicationprotocols and highlights the comparative studies for enhancing thesecurity of the protection systems. The proposed scheme is validatedusing a benchmark power system under various fault and cyber attack scenarios.

Life-cycle energy analysis of building integrated photovoltaic systems (BiPVs) with heat recovery unit

Building integrated photovoltaic (BiPV) systems generate electricity, but also heat, which is typically wasted and also reduces the efficiency of generation. A heat recovery unit can be combined with a BiPV system to take advantage of this waste heat, thus providing cogeneration. Two different photovoltaic (PV) cell types were combined with a heat recovery unit and analysed in terms of their life-cycle energy consumption to determine the energy payback period. A net energy analysis of these PV systems has previously been performed, but recent improvements in the data used for this study allow for a more comprehensive assessment of the combined energy used throughout the entire life-cycle of these systems to be performed. Energy payback periods between 4 and 16.5 years were found, depending on the BiPV system. The energy embodied in PV systems is significant, emphasised here due to the innovative use of national average input–output (I–O) data to fill gaps in traditional life-cycle inventories, i.e. hybrid analysis. These findings provide an insight into the net energy savings that are possible with a well-designed and managed BiPV system.

Automated analysis of performance and energy consumption for cloud applications

In cloud environments, IT solutions are delivered to users via shared infrastructure. One consequence of this model is that large cloud data centres consume large amounts of energy and produce significant carbon footprints. A key objective of cloud providers is thus to develop resource provisioning and management solutions at minimum energy consumption while still guaranteeing Service Level Agreements (SLAs). However, a thorough understanding of both system performance and energy consumption patterns in complex cloud systems is imperative to achieve a balance of energy efficiency and acceptable performance. In this paper, we present StressCloud, a performance and energy consumption analysis tool for cloud systems. StressCloud can automatically generate load tests and profile system performance and energy consumption data. Using StressCloud, we have conducted extensive experiments to profile and analyse system performance and energy consumption with different types and mixes of runtime tasks. We collected finegrained energy consumption and performance data with different resource allocation strategies, system configurations and workloads. The experimental results show the correlation coefficients of energy consumption, system resource allocation strategies and workload, as well as the performance of the cloud applications. Our results can be used to guide the design and deployment of cloud applications to balance energy and performance requirements.

Analysis of different scenarios for residential energy management under existing retail market structure

This paper presents an analysis of a residential energy management scheme under existing retail market structure with the integration of solar photovoltaic (PV) and battery energy storage systems. In this paper, different scenarios are analyzed with an aim of achieving the most cost-effective solutions for the integration of solar PV and battery energy storage systems. The main idea behind these analyses is to obtain a grid independent residential energy management system through the reduction of purchasing energy from the existing power grid. The results from the analysis of different scenarios for a typical Australian house demonstrate that the shortage of energy during the high loads and excess of energy during the higher output of solar PV system can be reduced with the design of a proper energy management scheme employing a transactive energy management framework.