Energy Efficiency Model Research Articles

Task arrival based energy efficient optimization in smart-IoT data center.

With the growth and expansion of cloud data centers, energy consumption has become an urgent issue for smart cities system. However, most of the current resource management approaches focus on the traditional cloud computing scheduling scenarios but fail to consider the feature of workloads from the Internet of Things (IoT) devices. In this paper, we analyze the characteristic of IoT requests and propose an improved Poisson task model with a novel mechanism to predict the arrivals of IoT requests. To achieve the trade-off between energy saving and service level agreement, we introduce an adaptive energy efficiency model to adjust the priority of the optimization objectives. Finally, an energy-efficient virtual machine scheduling algorithm is proposed to maximize the energy efficiency of the data center. The experimental results show that our strategy can achieve the best performance in comparison to other popular schemes.

Energy-Efficiency Model for Residential Buildings Using Supervised Machine Learning Algorithm

Energy-Efficiency Model for Residential Buildings Using Supervised Machine Learning Algorithm

Minimal Monitoring of Improvements in Energy Performance after Envelope Renovation in Subsidized Single Family Housing in Madrid

This study quantified the improvement in energy efficiency following passive renovation of the thermal envelope in highly inefficient residential complexes on the outskirts of the city of Madrid. A case study was conducted of a single-family terrace housing, representative of the smallest size subsidized dwellings built in Spain for workers in the nineteen fifties and sixties. Two units of similar characteristics, one in its original state and the other renovated, were analyzed in detail against their urban setting with an experimental method proposed hereunder for simplified, minimal monitoring. The dwellings were compared on the grounds of indoor environment quality parameters recorded over a period covering both winter and summer months. That information was supplemented with an analysis of the energy consumption metered. The result was a low-cost, reasonably accurate measure of the improvements gained in the renovated unit. The monitoring output data were entered in a theoretical energy efficiency model for the entire neighborhood to obtain an estimate of the potential for energy savings if the entire urban complex were renovated.

Table of Contents and Foreword

This issue of the Journal of Integrated Circuits and Systems (JICS) features a very broad content, including papers on analog and digital design, presenting novel solutions for circuit synthesis, energy efficiency, memory architectures and processor modeling and also proposing new approaches for wireless communication, motion estimation and neural networks applications. Six of these papers have been selected from the presentations given at SBCCI2011 (24th Symposium on Integrated Circuits and Systems Design), which has been held in João Pessoa, Brazil in 2011. Among the contributions presented at the Symposium, only a few best rated were selected by the JICS Editorial Board and have been invited to submit an extended version to the Journal. These papers have been reviewed by external experts and have been accepted for the special section on best SBCCI2011 papers. In addition to the best papers presented at the conference, one spontaneous submission passed through the usual reviewing process and has been accepted as a regular paper. We would like to thank the authors for their effort in preparing these high quality papers, as well as the reviewers for their help on paper selection, which guarantees the scientific level of this issue.We sincerely hope that JICS readers will enjoy these contributions.Marcelo Lubaszewski - JICS Editor-in-chief Marcelo Antonio Pavanello - JICS Co-Editor

State of the Art of Techno-Economics of Nanofluid-Laden Flat-Plate Solar Collectors for Sustainable Accomplishment

Emerging nanotechnology with solar collector technology has attracted the attention of researchers to enhance the performance of solar systems in order to develop efficient solar thermal systems for future sustainability. This paper chronologically reviews the various research works carried out on the performance enhancement of nanofluid-filled flat-plate solar collectors (FPCs). Gaps in the radiation exergy models and maximum exergy of FPCs, the importance of pressure drops in collector manifolds in exergy analysis, and the economics of nanofluid-laden FPCs have been addressed. The necessity of replacing currently used chemically derived glycol products with a renewable-based glycol has not been reported in the current literature thoroughly, but it is pondered in the current paper. Moreover, the thermophysical properties of all common metal and metal oxide nanoparticles utilized in various studies are collected in this paper for the first time and can be referred to quickly as a data source for future studies. The different classical empirical correlations for the estimation of specific heat, density, conductivity, and viscosity of reported nanofluids and base liquids, i.e., water and its mixture with glycols, are also tabulated as a quick reference. Brief insights on different performance criteria and the utilized models of heat transfer, energy efficiency, exergy efficiency, and economic calculation of nanofluid-based FPCs are extracted. Most importantly, a summary of the current progress in the field of nanofluid-charged FPCs is presented appropriately within two tables. The tables contain the status of the main parameters in different research works. Finally, gaps in the literature are addressed and mitigation approaches are suggested for the future sustainability of nanofluid-laden FPCs.

A Review of Energy Management Assessment Models for Industrial Energy Efficiency

The necessity to ensure energy efficiency in the industries is of significant importance to attain reduction of energy consumption and greenhouse gases emissions. Energy management is one of the effective features that ensure energy efficiency in the industries. Energy management models are the infancy in the industrial energy domain with practical guidelines towards implementation in the organizations. Despite the increased interest in energy efficiency, a gap exists concerning energy management literature and present application practices. This paper aims to methodologically review the energy management assessment models that facilitate the assessment of industrial energy management. In this context, the minimum requirements model, maturity model, energy management matrix model, and energy efficiency measures characterization framework are discussed with implications. The study concludes with interesting propositions for academia and industrial think tanks delineating few further research opportunities.

Investment risk management and energy efficiency, considering capital and operating expenditure in industrial development

The article clarified the impact of investment risk management on energy efficiency as a significant factor affecting the cost of an industrial development project. The effective implementation of any new construction or reconstruction project is inextricably linked with financial risk management, that allows take into account all possible expenditures that are not only once spent on its implementation (capital expenditures), but also operational expenditures that will be incurred when it is transferred into operation. A very important problem is the assessment of the real cost of the project, taking into account the operational expenditures during the life cycle of the building, as well as the optimization of both the capital expenditures (CAPEX) of the development company and the operational expenditures (OPEX). The implementation of development projects can be divided into three main stages: pre-investment, investment and operational. The sources of possible successes or failures in the implementation of entrepreneurial development projects are questions that are usually laid down in the early stages of organizing the construction of real estate objects. Therefore, the most important feature in the construction projects management in the field of industrial development is taking into account the dominant influence exerted on the efficiency of the first, pre-investment, phase. As a result, it allows to obtain significant cost-savings in the total cost of the project. All this requires to analyze various design solutions due to the Investor's desire to optimize capital expenditures, which will significantly reduce the costs of some project design solutions. Considering the above, a calculation algorithm is proposed to determine the total cost of the building's life cycle. During the research, an economically and energy-efficient model of using the enclosing structure for an industrial building was determined, which allows obtaining significant costs-savings, taking into account the operational expenditures during the life cycle of the building.

The role of forging a model of energy efficient production

The main principle of industrial cooperation - is, first of all, the construction of effective interaction between the costs of production of products and the potential profit from its sale. If the sale of products is unstable or cannot always be allowed to enter the market, there is often a decrease in the activity of the enterprise. At the same time, the production that organizes their activities on the principles of reducing costs and increasing output per unit of costs gets the competitive advantages of the enterprise. This generates a search that is determined by the relevance of scientific research. The novelty of the work is determined by the fact that the article presents aspects of the formation of effective and efficient industrial cooperation based on the integration of production into the global economic environment, focused on increasing competitiveness across the entire world space. With equal energy prices, improving energy efficiency creates an economically competitive product. In scientific work, the author forms a model of energy efficiency and exposes aspects of its use in industry. The practical significance of scientific research is determined by the fact that it allows to form a model of the transition to innovative forms of production based on energy conservation.

Energy efficient clustering and routing optimization model for maximizing lifetime of wireless sensor network

Recently, the wide adoption of WSNs (Wireless-Sensor-Networks) is been seen for provision non-real time and real-time application services such as intelligent transportation and health care monitoring, intelligent transportation etc. Provisioning these services requires energy-efficient WSN. The clustering technique is an efficient mechanism that plays a main role in reducing the energy consumption of WSN. However, the existing model is designed considering reducing energy- consumption of the sensor-device for the homogenous network. However, it incurs energy-overhead (EO) between cluster-head (CH). Further, maximizing coverage time is not considered by the existing clustering approach considering heterogeneous networks affecting lifetime performance. In order to overcome these research challenges, this work presents an energy efficient clustering and routing optimization (EECRO) model adopting cross-layer design for heterogeneous networks. The EECRO uses channel gain information from the physical layer and TDMA based communication is adopted for communication among both intra-cluster and inter-cluster communication. Further, clustering and routing optimization are presented to bring a good trade-off among minimizing the energy of CH, enhancing coverage time and maximizing the lifetime of sensor-network (SN). The experiments are conducted to estimate the performance of EECRO over the existing model. The significant-performance is attained by EECRO over the existing model in terms of minimizing routing and communication overhead and maximizing the lifetime of WSNs.

Conceptual Model of Energy Efficiency for Environmentally Safe Utilization of Liquid Pig Manure

Introduction. The growth of production capacity of livestock enterprises results in increased environmental pressures on bio- and agrocenoses, created by potential energy carriers, one of which is liquid pig manure. Representative parameters, which characterize the energy value, are the total content of nitrogen and its various forms N2 = 3...8 kg/m3; phosphorus oxide P2O5 = 3...6 kg/m3; potassium oxide K2O = 2...4 kg/m3; chemical oxygen consumption to the mass of organic matter 1.2, biochemical 0.42. In parallel, the groups of Escherichia coli, staphylococci, enterococci, aerobic spore-forming microorganisms, various forms of eggs, protozoan cysts and Eimeria oocysts are also the environmental burden. In addition, the physical and rheological properties of liquid manure can have a significant impact on energy efficiency and the way of its further utilization. In terms of agricultural chemistry, the most rational option for its utilization is fractional use in the form of organic fertilizer that is possible only under the conditions of sanitary and epidemiological safety, which is an energy-intensive process depending on various factors. The purpose of this study is to develop a conceptual model of the energy efficiency of operational impacts in obtaining an environmentally safe cycle of utilizing liquid pig manure. Materials and Methods. The object of the study is the operational impacts in obtaining an environmentally safe cycle of utilizing liquid pig manure; the subject is the function of maximizing the energy efficiency of this object under the conditions of sanitary-epidemiological and agrochemical restrictions. There is conducted the analysis of factors and their categorization depending on the type of functional impact. Results. A conceptual model of operational impacts in producing environmentally safe liquid pig manure has been developed, which determines the components of specific energy consumption, the factors affecting them, and the restrictions imposed on them. This model is the source data for the factor analysis and statistical models. Discussion and Conclusion. The practical significance of the work is the identification and categorization of factors depending on the type of functional impact on the operations of the preparatory cycle of ecologically safe utilization of pig manure that can provide initial data for developing specific research methods and statistical models.

Energy efficient clustering with disease diagnosis model for IoT based sustainable healthcare systems

Sustainable energy efficient networking models are needed to satisfy the increasing demands of the information and communication technologies (ICT) applications like healthcare, smart cities, education, and so on. The futuristic sustainable computing solutions in e-healthcare applications are based on the Internet of Things (IoT) and cloud computing platform, has offered numerous features and real time services. Several studies revealed that the amount of energy spent on transmitting data from IoT devices to a cloud server is considerably high and resulted in rapid energy depletion. In this view, this paper presents an Energy Efficient Particle Swarm Optimization (PSO) based Clustering (EEPSOC) technique for the effective selection of cluster heads (CHs) among diverse IoT devices. The IoT devices used for sensing healthcare data are grouped into a form of clusters and a CH will be elected by the use of EEPSOC. The elected CH will forward the data to the cloud server. Then, the CH is responsible for transmitting data of the IoT devices to the cloud server through fog devices. Next to that, an artificial neural network (ANN) based classification model is applied to diagnose the healthcare data in the cloud server to identify the severity of the diseases. For experimentation, a systematic student perspective healthcare data is produced utilizing UCI dataset and medicinal gadgets to foresee the diverse student levels of disease severity. A detailed comparative analysis is carried out and the simulation outcome ensured the goodness of the EEPSOC-ANN model over the compared methods under various aspects.

Modeling and Evaluation of Energy Efficiency of New Hybrid Turning-Burnishing Process in Terms of Surface Properties

The combination of the turning and burnishing process is an efficient approach to improve machined quality and productivity. This paper aims to optimize energy efficiency (EF), improved hardness ratio (IHR), and decreased roughness ratio (DRR) of a new hybrid turning-burnishing process. The machining parameters are the feed rate (f), turning speed (v), depth of cut (a), burnishing pressure (p), and the diameter of the compressing ball (d). A new turning-burnishing tool using compressed air has been designed and fabricated. A set of experiments for Aluminum Alloy 5083 were performed using the Taguchi method. The weightage principal component analysis (WPCA) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) were applied to obtain the weight values and optimal outcomes. The results indicated that optimum values of the depth of cut, pressure, diameter, feed rate, and speed are 1.00 mm, 0.4 MPa, 16.00 mm, 0.084 mm/rev, and 120 m/min, respectively. The improvements in the EF and IHR are by 20.75% and 8.23% respectively, while the DDR is decreased by 19.05%, as compared to common values.

Handling heterogeneity in frontier modeling of city-level energy efficiency: The case of China

Cities have been playing significant role in promoting energy efficiency and driving sustainable development. Energy consumption in different cities usually exhibit different characteristics. It is therefore important to evaluate and compare city-level energy efficiency performance by considering the impact of heterogeneity. This study employed stochastic frontier analysis to assess the spatial and temporal disparity of energy efficiency in Chinese cities in 2005–2015. The energy efficiency disparity across different cities was found to be significant, with energy efficient cities mainly located in more developed regions. We introduced a Mean-Variance Classification approach to address the effects of city heterogeneities and improve assessment reliability. This classification showed better discriminating power through narrowing the gap within groups and widening the gap across different groups. The empirical results reveal that mature cities with steady and high energy efficiency may influence and guide energy efficiency improvement of surrounding areas. To achieve energy efficiency improvement quickly, more attention should be paid to the promising cities with significant energy efficiency fluctuations.

Modelling energy performance using a new hybrid DE/MARS-based approach for fossil-fuel thermal power stations.

Despite their environmental impact, fossil-fuel power plants are still commonly used due to their high capacity and relatively low cost compared to renewable energy sources. The aim of this paper is to assess the performance of such energy systems as a key element within a fossil-fuel energy supply network. The methodology relies on fossil-fuel power plant modelling to define an optimal energy management level. However, it can be difficult to model the energy management of thermal power stations (TPS). Therefore, this paper shows an energy efficiency model found on a new hybrid algorithm that is a combination of multivariate adaptive regression splines (MARS) and differential evolution (DE) to estimate net annual electricity generation (NAEG) and carbon dioxide (CO2) emissions (CDE) from economic and performance variables in thermal power plants. This technique requires the DE optimisation of the MARS hyperparameters during the development of the training process. In addition to successfully forecast net annual electricity generation (NAEG) and carbon dioxide (CO2) emissions (CDE) (coefficients of determination with a value of 0.9803 and 0.9895, respectively), the mathematical model used in this work can determine the importance of each economic and energy parameter to characterize the behaviour of thermal power stations.

Energy Efficiency Augmentation in Massive MIMO Systems through Linear Precoding Schemes and Power Consumption Modeling

Massive multiple-input multiple-output or massive MIMO system has great potential for 5th generation (5G) wireless communication systems as it is capable of providing game-changing enhancements in area throughput and energy efficiency (EE). This work proposes a realistic and practically implementable EE model for massive MIMO systems while a general and canonical system model is used for single-cell scenario. Linear processing schemes are used for detection and precoding, i.e., minimum mean squared error (MMSE), zero-forcing (ZF), and maximum ratio transmission (MRT/MRC). Moreover, a power dissipation model is proposed that considers overall power consumption in uplink and downlink communications. The proposed model includes the total power consumed by power amplifier and circuit components at the base station (BS) and single antenna user equipment (UE). An optimal number of BS antennas to serve total UEs and the overall transmitted power are also computed. The simulation results confirm considerable improvements in the gain of area throughput and EE, and it also shows that the optimum area throughput and EE can be realized wherein a larger number of antenna arrays at BS are installed for serving a greater number of UEs.

FIS-RGSO: Dynamic Fuzzy Inference System Based Reverse Glowworm Swarm Optimization of energy and coverage in green mobile wireless sensor networks

In mobile wireless sensor networks, energy consumption and area coverage are two well-known optimization problems. An efficient and restricted sensor movement is essential so that redundant area coverage, as well as consumed energy, can be reduced to mitigate these two issues in mobile wireless sensor networks. To make equilibrium between energy consumption and the total area coverage by the sensor nodes is a difficult task. In this context, optimized path planning for sensor movement is crucial to reach the target. The article presents a Dynamic Fuzzy Inference System Based Reverse Glowworm Swarm Optimization (FIS-RGSO) of energy and coverage in smart green mobile wireless sensor networks. The objective of this article is to achieve minimum energy consumption by the sensors through their optimum movements so that sensors can cover maximum area and increase their lifetime. The proposed approach improves the sustainability and performance of green sensor networks in terms of a lifetime and energy-efficiency by implementing restricted and organized sensor movements based on the decision taken by the Fuzzy Inference System, which leads to minimum energy consumption and less distance traversing. The simulation results reveal that our proposed model reduces the consumed energy in a range of 5%–45% as compared with the existing method in reverse glowworm swarm optimization (RGSO) algorithm. The total distance covered by the sensors is also minimized by almost 7%–62% as compared with the existing one. The proposed method has experimented extensively and the result shows it performs better than the existing one in terms of the total number of live sensors that exist after execution. Therefore, the proposed methodology is realized as an energy-efficient model in wireless sensor networks that proliferate network lifetime.

School Building Occupancy and Energy Efficiency Modelling: Two Case Studies

Comparing the results of energy simulations with real energy consumption of the buildings, often shows discrepancies between the two. This research aims in, exploring the gap between simulated models and actual energy consumption of buildings, by analyzing the impacts of, number of occupants and their presence time in the building. Two Italian school buildings (Aldo Moro and Andersen schools in Seregno) are chosen as cases. The buildings’ simulations, once using standard profiles (ASHRAE), and once using the actual occupancy profiles (from real schedules) are compared with the real gas consumption of the buildings in three years (2014-2016). In Andersen school, the results show 47% of a discrepancy between the ASHRAE and actual occupancy simulations, with the average of the gas bills of 3 years. In Aldo Moro, there is a variation of 65% (ASHRAE) and 55% (actual occupancy) from the average value of the bills. It shows that by implementing the real occupancy of the building in Aldo Moro, the results got closer to the real energy bills. This could be due to the reason that Aldo Moro has a higher number of students and considering the more precise schedule of occupants, had a greater impact on annual energy consumption, as compared to the Andersen school, which is smaller and has a smaller number of students.

Calculating ships' real emissions of pollutants and greenhouse gases: Towards zero uncertainties

The energy output and emissions from maritime transport have increased considerably over the last two decades. Countries in Europe, North America and Asia use different methodologies to calculate these important variables; two of the main methods used are known as the Ship Traffic Emission Assessment Model (STEAM) and the Ship Traffic, Energy and Environmental Model (STEEM). Furthermore, the International Maritime Organization has recently required additional parameters to be included in the calculation, but the procedure for calculating these is not defined. In this paper, a model named SENEM (Ship's ENergy Efficiency Model) is proposed to calculate the power delivered in real time by the main engine taking into account all the equations required for defining and calculating all these parameters together with the efficiency of both the shaft and propulsion system. This model has been tested and validated on board four Ro-Pax ships operating across the Strait of Gibraltar - three vessels powered by waterjet and the fourth by propeller. The results show differences of up to 40% compared with other models.

Modeling and analysis of energy efficiency of methods for maintaining temperature conditions in microbioreactors

A mathematical model of maintaining the thermal conditions of microreactors used in biological, medical and other experiments that require stabilization or temperature control software is considered. Several heating modes are considered: using a liquid heating jacket, heating from below through the bottom, heating from the side using a flexible silicone heater. Simulated heat loss and dynamic modes of temperature control.

Simulation and analysis on the ship energy efficiency operational indicator for bulk carriers by Monte Carlo simulation method

The ship energy efficiency management is an important topic in the field of the energy management onboard and the exhaust gases emission nowadays. The advanced model plays a vital role to improve the ship energy efficiency management when considering the variable factors. The establishment of the ship energy efficiency model through energy efficiency operational indicator (EEOI) index has been conducted through Monte Carlo simulation method along with using the operation data of a bulk carrier. A bulk carrier is chosen, namely, M/V NSU JUSTICE 250,000 DWT of VINIC Shipping Transportation Company in Vietnam. This research uses the real operational data to perform a statistical methodology which calculates the various factors used to calculate EEOI. This method is supported by Matlab program through the curve fitting tool. The normal distribution estimation and the kernel density estimation method are used for the parametric curve fitting and non-parametric curve fitting, respectively. The average weather condition (wind speed and wave height) and the fouling condition of hull have been investigated and compared with the research results. The validation of the proposed methods has been conducted through the study of the external factors influencing the research results. The research result shows the optimal operational data for the fuel consumption at each certain voyage. This paper is useful for the ship-owners and the ship-operators in the field of the ship energy efficiency management.