Domestic Consumption Simulation and Management Using a Continuous Consumption Management and Optimization Algorithm

The recent changes concerning the consumers’ active participation in the efficient management of load devices for one’s own interest and for the interest of the network operator, namely in the context of demand response, leads to the need for improved algorithms and tools. A continuous consumption optimization algorithm has been improved in order to better manage the shifted demand. It has been done in a simulation and user-interaction tool capable of being integrated in a multi-agent smart grid simulator already developed, and also capable of integrating several optimization algorithms to manage real and simulated loads. The case study of this paper enhances the advantages of the proposed algorithm and the benefits of using the developed simulation and user interaction tool.

Energy-aware task mapping onto heterogeneous platforms using DVFS and sleep states

Heterogeneous multicore platforms are becoming an interesting alternative for embedded computing systems with limited power supply as they can execute specific tasks in an efficient manner. Nonetheless, one of the main challenges of such platforms consists of optimising the energy consumption in the presence of temporal constraints. This paper addresses the problem of task-to-core allocation onto heterogeneous multicore platforms such that the overall energy consumption of the system is minimised. To this end, we propose a two-phase approach that considers both dynamic and leakage energy consumption: (i) the first phase allocates tasks to the cores such that the dynamic energy consumption is reduced; (ii) the second phase refines the allocation performed in the first phase in order to achieve better sleep states by trading off the dynamic energy consumption with the reduction in leakage energy consumption. This hybrid approach considers core frequency set-points, tasks energy consumption and sleep states of the cores to reduce the energy consumption of the system. Major value has been placed on a realistic power model which increases the practical relevance of the proposed approach. Finally, extensive simulations have been carried out to demonstrate the effectiveness of the proposed algorithm. In the best-case, savings up to 18% of energy are reached over the first fit algorithm, which has shown, in previous works, to perform better than other bin-packing heuristics for the target heterogeneous multicore platform.

Energy-efficient MAC protocols for WBANs: Opportunities and challenges

Wireless body area networks (WBANs) are expected to play a significant role in smart healthcare systems. One of the most important attributes of WBANs is to increase network lifetime by introducing novel and low-power techniques on the energy-constrained sensor nodes. Medium access control (MAC) protocols play a significant role in determining the energy consumption in WBANs. Existing MAC protocols are unable to accommodate communication requirements in WBANs. There is a need to develop novel, scalable and reliable MAC protocols that must be able to address all these requirements in a reliable manner. In this special issue, we attracted high quality research and review papers on the recent advances in MAC protocols for WBANs.

Analysis and visualization of energy use for university campus

The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.

Assessing initial embodied energy in building structures using LCA methodology

The considerable amount of energy consumed on Earth is a major cause for not achieving sustainable development. Buildings are responsible for the highest worldwide energy consumption, nearly 40%. Strong efforts have been made in what concerns the reduction of buildings operational energy (heating, hot water, ventilation, electricity), since operational energy is so far the highest energy component in a building life cycle. However, as operational energy is being reduced the embodied energy increases. One of the building elements responsible for higher embodied energy consumption is the building structural system. Therefore, the present work is going to study part of embodied energy (initial embodied energy) in building structures using a life cycle assessment methodology, in order to contribute for a greater understanding of embodied energy in buildings structural systems. Initial embodied energy is estimated for a building structure by varying the span and the structural material type. The results are analysed and compared for different stages, and some conclusions are drawn. At the end of this work it was possible to conclude that the building span does not have considerable influence in embodied energy consumption of building structures. However, the structural material type has influence in the overall energetic performance. In fact, with this research it was possible that building structure that requires more initial embodied energy is the steel structure; then the glued laminated timber structure; and finally the concrete structure.

Energy-Efficient Cluster based Routing Schemes for Static and Mobile Sensor Networks

The theme of the thesis is centred around one important aspect of wireless sensor networks; the energy-efficiency.The limited energy source of the sensor nodes calls for design of energy-efficient routing protocols. The schemes for protocol design should try to minimize the number of communications among the nodes to save energy. Cluster based techniques were found energy-efficient. In this method clusters are formed and data from different nodes are collected under a cluster head belonging to each clusters and then forwarded it to the base station.Appropriate cluster head selection process and generation of desirable distribution of the clusters can reduce energy consumption of the network and prolong the network lifetime. In this work two such schemes were developed for static wireless sensor networks.In the first scheme, the energy wastage due to cluster rebuilding incorporating all the nodes were addressed. A tree based scheme is presented to alleviate this problem by rebuilding only sub clusters of the network. An analytical model of energy consumption of proposed scheme is developed and the scheme is compared with existing cluster based scheme. The simulation study proved the energy savings observed.The second scheme concentrated to build load-balanced energy efficient clusters to prolong the lifetime of the network. A voting based approach to utilise the neighbor node information in the cluster head selection process is proposed. The number of nodes joining a cluster is restricted to have equal sized optimum clusters. Multi-hop communication among the cluster heads is also introduced to reduce the energy consumption. The simulation study has shown that the scheme results in balanced clusters and the network achieves reduction in energy consumption.The main conclusion from the study was the routing scheme should pay attention on successful data delivery from node to base station in addition to the energy-efficiency. The cluster based protocols are extended from static scenario to mobile scenario by various authors. None of the proposals addresses cluster head election appropriately in view of mobility. An elegant scheme for electing cluster heads is presented to meet the challenge of handling cluster durability when all the nodes in the network are moving. The scheme has been simulated and compared with a similar approach.The proliferation of sensor networks enables users with large set of sensor information to utilise them in various applications. The sensor network programming is inherently difficult due to various reasons. There must be an elegant way to collect the data gathered by sensor networks with out worrying about the underlying structure of the network. The final work presented addresses a way to collect data from a sensor network and present it to the users in a flexible way.A service oriented architecture based application is built and data collection task is presented as a web service. This will enable composition of sensor data from different sensor networks to build interesting applications. The main objective of the thesis was to design energy-efficient routing schemes for both static as well as mobile sensor networks. A progressive approach was followed to achieve this goal.

Energy Management in Wireless Sensor Networks: A Crosslayer,Channel Adaptive Approach Towards Performance Optimization

The proliferation of wireless sensor networks in a large spectrum of applications had been spurered by the rapid advances in MEMS(micro-electro mechanical systems )based sensor technology coupled with low power,Low cost digital signal processors and radio frequency circuits.A sensor network is composed of thousands of low cost and portable devices bearing large sensing computing and wireless communication capabilities. This large collection of tiny sensors can form a robust data computing and communication distributed system for automated information gathering and distributed sensing.The main attractive feature is that such a sensor network can be deployed in remote areas.Since the sensor node is battery powered,all the sensor nodes should collaborate together to form a fault tolerant network so as toprovide an efficient utilization of precious network resources like wireless channel,memory and battery capacity.The most crucial constraint is the energy consumption which has become the prime challenge for the design of long lived sensor nodes.

Assessment of Energy Conservation in Indian Cement Industry and Forecasting of Co2 Emissions

Cement industry ranks 2nd in energy consumption among the industries in India. It is one of the major emitter of CO2, due to combustion of fossil fuel and calcination process. As the huge amount of CO2 emissions cause severe environment problems, the efficient and effective utilization of energy is a major concern in Indian cement industry. The main objective of the research work is to assess the energy cosumption and energy conservation of the Indian cement industry and to predict future trends in cement production and reduction of CO2 emissions. In order to achieve this objective, a detailed energy and exergy analysis of a typical cement plant in Kerala was carried out. The data on fuel usage, electricity consumption, amount of clinker and cement production were also collected from a few selected cement industries in India for the period 2001 - 2010 and the CO2 emissions were estimated. A complete decomposition method was used for the analysis of change in CO2 emissions during the period 2001 - 2010 by categorising the cement industries according to the specific thermal energy consumption. A basic forecasting model for the cement production trend was developed by using the system dynamic approach and the model was validated with the data collected from the selected cement industries. The cement production and CO2 emissions from the industries were also predicted with the base year as 2010. The sensitivity analysis of the forecasting model was conducted and found satisfactory. The model was then modified for the total cement production in India to predict the cement production and CO2 emissions for the next 21 years under three different scenarios. The parmeters that influence CO2 emissions like population and GDP growth rate, demand of cement and its production, clinker consumption and energy utilization are incorporated in these scenarios. The existing growth rate of the population and cement production in the year 2010 were used in the baseline scenario. In the scenario-1 (S1) the growth rate of population was assumed to be gradually decreasing and finally reach zero by the year 2030, while in scenario-2 (S2) a faster decline in the growth rate was assumed such that zero growth rate is achieved in the year 2020. The mitigation strategiesfor the reduction of CO2 emissions from the cement production were identified and analyzed in the energy management scenarioThe energy and exergy analysis of the raw mill of the cement plant revealed that the exergy utilization was worse than energy utilization. The energy analysis of the kiln system showed that around 38% of heat energy is wasted through exhaust gases of the preheater and cooler of the kiln sysetm. This could be recovered by the waste heat recovery system. A secondary insulation shell was also recommended for the kiln in the plant in order to prevent heat loss and enhance the efficiency of the plant. The decomposition analysis of the change in CO2 emissions during 2001- 2010 showed that the activity effect was the main factor for CO2 emissions for the cement industries since it is directly dependent on economic growth of the country. The forecasting model showed that 15.22% and 29.44% of CO2 emissions reduction can be achieved by the year 2030 in scenario- (S1) and scenario-2 (S2) respectively. In analysing the energy management scenario, it was assumed that 25% of electrical energy supply to the cement plants is replaced by renewable energy. The analysis revealed that the recovery of waste heat and the use of renewable energy could lead to decline in CO2 emissions 7.1% for baseline scenario, 10.9 % in scenario-1 (S1) and 11.16% in scenario-2 (S2) in 2030. The combined scenario considering population stabilization by the year 2020, 25% of contribution from renewable energy sources of the cement industry and 38% thermal energy from the waste heat streams shows that CO2 emissions from Indian cement industry could be reduced by nearly 37% in the year 2030. This would reduce a substantial level of greenhouse gas load to the environment. The cement industry will remain one of the critical sectors for India to meet its CO2 emissions reduction target. India’s cement production will continue to grow in the near future due to its GDP growth. The control of population, improvement in plant efficiency and use of renewable energy are the important options for the mitigation of CO2 emissions from Indian cement industries

RF Energy Harvesting in WSNs

As a vital factor affecting system cost and lifetime, energy consumption in wireless sensor networks (WSNs) has been paid much attention to. This article reviews existing energy harvesting technology applied in WSNs, and analyzes advantages of harvesting radio frequency (RF) energy in WSNs.

Energy substitutability in transition agriculture: estimates and implications for Hungary

Subsidised energy prices in pre-transition Hungary had led to excessive energy intensity in the agricultural sector. Transition has resulted in steep input price increases. In this study, Allen and Morishima elasticities of substitution are estimated to study the effects of these price changes on energy use, chemical input use, capital formation and employment. Panel data methods, Generalised Method of Moments (GMM) and instrument exogeneity tests are used to specify and estimate technology and substitution elasticities. Results indicate that indirect price policy may be effective in controlling energy consumption. The sustained increases in energy and chemical input prices have worked together to restrict energy and chemical input use, and the substitutability between energy, capital and labour has prevented the capital shrinkage and agricultural unemployment situations from being worse. The Hungarian push towards lower energy intensity may be best pursued through sustained energy price increases rather than capital subsidies. (C) 2003 Elsevier B.V. All rights reserved.

An investigation of the existing situation and trends in building energy efficiency management in China

According to the Chinese State Council's "Building Energy Efficiency Management Ordinance", a large-scale investigation of energy efficiency (EE) in buildings in contemporary China has been carried out in 22 provincial capitals and major cities in China. The aim of this project is to provide reliable information for drawing up the "Decision on reinforcing building energy efficiency" by the Ministry of Construction of China. The surveyed organizations include government departments, research institutions, property developers, design institutions, construction companies, construction consultancy services companies, facility management departments, financial institutions and those which relate to the business of building energy efficiency. In addition, representatives of the media and residents were also involved. A detailed analysis of the results of the investigation concerning aspects of the cur-rent situation and trends in building energy consumption, energy efficiency strategy and the implementation of energy efficiency measures has been conducted. The investigation supplies essential information to formulate the market entrance policy for new buildings and the refurbishment policy for existing buildings to encourage the development of energy efficient technology.

Qualitative modelling of sustainable energy scenarios: An application and extension of the Bon Qualitative Input-Output model

Climate change is one of the major challenges facing economic systems at the start of the 21st century. Reducing greenhouse gas emissions will require both restructuring the energy supply system (production) and addressing the efficiency and sufficiency of the social uses of energy (consumption). The energy production system is a complicated supply network of interlinked sectors with 'knock-on' effects throughout the economy. End use energy consumption is governed by complex sets of interdependent cultural, social, psychological and economic variables driven by shifts in consumer preference and technological development trajectories. To date, few models have been developed for exploring alternative joint energy production-consumption systems. The aim of this work is to propose one such model. This is achieved in a methodologically coherent manner through integration of qualitative input-output models of production, with Bayesian belief network models of consumption, at point of final demand. The resulting integrated framework can be applied either (relatively) quickly and qualitatively to explore alternative energy scenarios, or as a fully developed quantitative model to derive or assess specific energy policy options. The qualitative applications are explored here.

A conceptual design of a wireless sensor actuator system for optimising energy and well-being in a building

This article presents a prototype model based on a wireless sensor actuator network (WSAN) aimed at optimizing both energy consumption of environmental systems and well-being of occupants in buildings. The model is a system consisting of the following components: a wireless sensor network, `sense diaries', environmental systems such as heating, ventilation and air-conditioning systems, and a central computer. A multi-agent system (MAS) is used to derive and act on the preferences of the occupants. Each occupant is represented by a personal agent in the MAS. The sense diary is a new device designed to elicit feedback from occupants about their satisfaction with the environment. The roles of the components are: the WSAN collects data about physical parameters such as temperature and humidity from an indoor environment; the central computer processes the collected data; the sense diaries leverage trade-offs between energy consumption and well-being, in conjunction with the agent system; and the environmental systems control the indoor environment.

Radio frequency energy harvesting in wireless sensor networks

As a vital factor affecting system cost and lifetime, energy consumption in wireless sensor networks (WSNs) has been paid much attention to. This article presents a new approach to making use of electromagnetic energy from useless radio frequency (RF) signals transmitted in WSNs, with a quantitative analysis showing its feasibility. A mechanism to harvest the energy either passively or actively is proposed.

A model of intelligent building energy management for the indoor environment

People's interaction with the indoor environment plays a significant role in energy consumption in buildings. Mismatching and delaying occupants' feedback on the indoor environment to the building energy management system is the major barrier to the efficient energy management of buildings. There is an increasing trend towards the application of digital technology to support control systems in order to achieve energy efficiency in buildings. This article introduces a holistic, integrated, building energy management model called `smart sensor, optimum decision and intelligent control' (SMODIC). The model takes into account occupants' responses to the indoor environments in the control system. The model of optimal decision-making based on multiple criteria of indoor environments has been integrated into the whole system. The SMODIC model combines information technology and people centric concepts to achieve energy savings in buildings.