Search results for: energy managment

Authors: Jeongmin Kim, Eunju Lee, Kwang Ryel Ryu

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This paper addresses the problem of predictive control for energy management of large-scaled exhibition halls, where a lot of energy is consumed to maintain internal atmosphere under certain required conditions. Predictive control achieves better energy efficiency by optimizing the operation of air-conditioning facilities with not only the current but also some future status taken into account. In this paper, we propose to use predictive models learned from past sensor data of hall environment, for use in optimizing the operating plan for the air-conditioning facilities by simulating future environmental change. We have implemented an emulator of an exhibition hall by using EnergyPlus, a widely used building energy emulation tool, to collect data for learning environment-change models. Experimental results show that the learned models predict future change highly accurately on a short-term basis.

Keywords: predictive control, energy management, machine learning, optimization

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Authors: V. E. Selaule, R. M. Schoeman H. C. Z. Pienaar

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Research has shown that solar energy is a renewable energy resource with the most potential when compared to other renewable energy resources in South Africa. There are many makes of Photovoltaic (PV) panels on the market and it is difficult to assess which to use. PV panel manufacturers use Standard Test Conditions (STC) to rate their PV panels. STC conditions are different from the actual operating environmental conditions were the PV panels are used. This paper describes a practical method to determine the most cost effective available PV panel. The method shows that PV panel manufacturer STC ratings cannot be used to select a cost effective PV panel.

Keywords: PV orientation, PV panel, PV STC, Solar energy

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Authors: Seyed M. Khatami, H. Naderpour, R. Vahdani, R. C. Barros

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Many previous studies have been carried out to calculate the impact force and the dissipated energy between two neighboring buildings during seismic excitation, when they collide with each other. Numerical studies are an important part of impact, which several researchers have tried to simulate the impact by using different formulas. Estimation of the impact force and the dissipated energy depends significantly on some parameters of impact. Mass of bodies, stiffness of spring, coefficient of restitution, damping ratio of dashpot and impact velocity are some known and unknown parameters to simulate the impact and measure dissipated energy during collision. Collision is usually shown by force-displacement hysteresis curve. The enclosed area of the hysteresis loop explains the dissipated energy during impact. In this paper, the effect of using different types of impact models is investigated in order to calculate the impact force. To increase the accuracy of impact model and to optimize the results of simulations, a new damping equation is assumed and is validated to get the best results of impact force and dissipated energy, which can show the accuracy of suggested equation of motion in comparison with other formulas. This relation is called "n-m". Based on mathematical relation, an initial value is selected for the mentioned coefficients and kinetic energy loss is calculated. After each simulation, kinetic energy loss and energy dissipation are compared with each other. If they are equal, selected parameters are true and, if not, the constant of parameters are modified and a new analysis is performed. Finally, two unknown parameters are suggested to estimate the impact force and calculate the dissipated energy.

Keywords: impact force, dissipated energy, kinetic energy loss, damping relation

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Authors: Jainendra Singh, Zaheeruddin

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A typical wireless sensor networks (WSNs) consists of several tiny and low-power sensors which use radio frequency to perform distributed sensing tasks. The longevity of wireless sensor networks (WSNs) is a major issue that impacts the application of such networks. While routing protocols are striving to save energy by acting on sensor nodes, recent studies show that network lifetime can be enhanced by further involving sink mobility. A common approach for energy efficiency is partitioning the network into clusters with correlated data, where the representative nodes simply transmit or average measurements inside the cluster. In this paper, we propose an energy- efficient homogenous clustering (EHC) technique. In this technique, the decision of each sensor is based on their residual energy and an estimate of how many of its neighboring cluster heads (CHs) will benefit from it being a CH. We, also explore the routing algorithm in clustered WSNs. We show that the proposed schemes significantly outperform current approaches in terms of packet delay, hop count and energy consumption of WSNs.

Keywords: wireless sensor network, energy efficiency, clustering, routing

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Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

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‘Water-related energy’ is energy use which is directly or indirectly influenced by changes to water use. Informatics applying a range of mathematical, statistical and rule-based approaches can be used to reveal important information on demand from the available data provided at second, minute or hourly intervals. This study aims to combine these two concepts to improve the current water end use disaggregation problem through applying a wide range of most advanced pattern recognition techniques to analyse the concurrent high-resolution water-energy consumption data. The obtained results have shown that recognition accuracies of all end-uses have significantly increased, especially for mechanised categories, including clothes washer, dishwasher and evaporative air cooler where over 95% of events were correctly classified.

Keywords: deep learning network, smart metering, water end use, water-energy data

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Authors: Ilya Kavalchuk, Hayrettin Arisoy, Alex Stojcevski, Aman Maun Than Oo

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Electric vehicles are one of the most complicated electric devices to simulate due to the significant number of different processes involved in electrical structure of it. There are concurrent processes of energy consumption and generation with different onboard systems, which make simulation tasks more complicated to perform. More accurate simulation on energy consumption can provide a better understanding of all energy management for electric transport. As a result of all those processes, electric transport can allow for a more sustainable future and become more convenient in relation to the distance range and recharging time. This paper discusses the problems of energy consumption simulations for electric vehicles using different software packages to provide ideas on how to make this process more precise, which can help engineers create better energy management strategies for electric vehicles.

Keywords: electric vehicles, EV, power consumption, power management, simulation

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Authors: Azzedine Hamza, Chouaib Chakour, Messaoud Ramdani

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Energy demand prediction plays a crucial role in achieving next-generation power systems for agricultural greenhouses. As a result, high prediction quality is required for efficient smart grid management and therefore low-cost energy consumption. The aim of this paper is to investigate the effectiveness of a hybrid data-driven model in day-ahead energy demand prediction. The proposed model consists of Discrete Wavelet Transform (DWT), and Adaptive Neuro-Fuzzy Inference System (ANFIS). The DWT is employed to decompose the original signal in a set of subseries and then an ANFIS is used to generate the forecast for each subseries. The proposed hybrid method (DWT-ANFIS) was evaluated using a greenhouse energy demand data for a week and compared with ANFIS. The performances of the different models were evaluated by comparing the corresponding values of Mean Absolute Percentage Error (MAPE). It was demonstrated that discret wavelet transform can improve agricultural greenhouse energy demand modeling.

Keywords: wavelet transform, ANFIS, energy consumption prediction, greenhouse

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Authors: Dhruv Mehta, Alexander van Zuijlen, Hester Bijl

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Large Eddy Simulation (LES) numerically resolves the large energy-containing eddies of a turbulent flow, while modelling the small dissipative eddies. On a wind farm, these large scales carry the energy wind turbines extracts and are also responsible for transporting the turbines’ wakes, which may interact with downstream turbines and certainly with the atmospheric boundary layer (ABL). In this situation, it is important to conserve the energy that these wake’s carry and which could be altered artificially through numerical dissipation brought about by the schemes used for the spatial discretisation and temporal integration. Numerical dissipation has been reported to cause the premature recovery of turbine wakes, leading to an over prediction in the power produced by wind farms.An energy-conserving scheme is free from numerical dissipation and ensures that the energy of the wakes is increased or decreased only by the action of molecular viscosity or the action of wind turbines (body forces). The aim is to create an LES package with energy-conserving schemes to simulate wind turbine wakes correctly to gain insight into power-production, wake meandering etc. Such knowledge will be useful in designing more efficient wind farms with minimal wake interaction, which if unchecked could lead to major losses in energy production per unit area of the wind farm. For their research, the authors intend to use the Energy-Conserving Navier-Stokes code developed by the Energy Research Centre of the Netherlands.

Keywords: energy-conserving schemes, modelling turbulence, Large Eddy Simulation, atmospheric boundary layer

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Authors: Nadjiba Mahfoudi, Abdelhafid Moummi , Mohammed El Ganaoui

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Thermal applications are drawing increasing attention in the solar energy research field, due to their high performance in energy storage density and energy conversion efficiency. In these applications, solar collectors and thermal energy storage systems are the two core components. This paper presents a thermal analysis of the transient behavior and storage capability of a sensible heat storage device in which sand is used as a storage media. The TES unit with embedded charging tubes is connected to a solar air collector. To investigate it storage characteristics a 3D-model using no linear coupled partial differential equations for both temperature of storage medium and heat transfer fluid (HTF), has been developed. Performances of thermal storage bed of capacity of 17 MJ (including bed temperature, charging time, energy storage rate, charging energy efficiency) have been evaluated. The effect of the number of charging tubes (3 configurations) is presented.

Keywords: design, thermal modeling, heat transfer enhancement, sand, sensible heat storage

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Authors: Balram Panjwani, Bernd Wittgens, Jan Erik Olsen, Stein Tore Johansen

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The Norwegian ferroalloy industry is a world leader in sustainable production of ferrosilicon, silicon and manganese alloys with the lowest global specific energy consumption. One of the byproducts during the metal reduction process is energy rich off-gas and usually this energy is not harnessed. A novel concept for sustainable energy recovery from ferroalloy off-gas is discussed. The concept is founded on the idea of introducing a combustion chamber in the off-gas section in which energy rich off-gas mainly consisting of CO will be combusted. This will provide an additional degree of freedom for optimizing energy recovery. A well-controlled and high off-gas temperature will assure a significant increase in energy recovery and reduction of emissions to the atmosphere. Design and operation of the combustion chamber depend on many parameters, including the total power capacity of the combustion chamber, sufficient residence time for combusting the complex Poly Aromatic Hydrocarbon (PAH), NOx, as well as converting other potential pollutants. The design criteria for the combustion chamber have been identified and discussed and sizing of the combustion chamber has been carried out considering these design criteria. Computational Fluid Dynamics (CFD) has been utilized extensively for sizing the combustion chamber. The results from our CFD simulations of the flow in the combustion chamber and exploring different off-gas fuel composition are presented. In brief, the paper covers all aspect which impacts the sizing of the combustion chamber, including insulation thickness, choice of insulating material, heat transfer through extended surfaces, multi-staging and secondary air injection.

Keywords: CFD, combustion chamber, arc furnace, energy recovery

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Authors: Ali Cheshmehzangi, Ayotunde Dawodu

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In urban planning, Floor Area Ratio (FAR) of the site plays a major role in the multiplicity of performances, from humane living environments to energy performance. When one considers the astounding volume of new housing that is going to be constructed across the globe during the next few decades due to growing urbanisation (e.g. particularly in developing world), it is imperative that we have an empirically grounded grasp of which building configurations are more energy efficient. As a common planning metric, it would be helpful to know exactly how managing FAR connects with energy efficiency. Hence, this study puts together a set of modelling of various FARs for a typical residential compound and address the considerations of energy planning integration in the practice of building configuration and urban planning. Such decision makings at the planning and design stage enable us to provide pathways of optimising urban climate at mesoscale of the built environment, i.e. the neighbourhood or community level. In this study, a comparative study is conducted using Eco-Tect Software, using a case study in the City of Ningbo, China. Findings of the study contribute to identifying scenarios of various FAR use and energy planning at mesoscale. The final results contribute to studies in urban climate, from the perspectives of urban planning, energy planning, and urban modelling.

Keywords: China, energy planning, FAR, floor-area-ratio, mesoscale, urban climate, urban modelling

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Authors: Mina Bakhshi

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Nowadays, issues such as various types of pollution, problems caused by energy consumption, population density, social activities, difficulties related to urban access and communication, transportation, etc., have challenged different communities and become the subject of their discussions. In response to this issue, theories and movements have emerged to achieve sustainable urban development, including the smart growth movement. This theory emphasizes that the physical growth and expansion of cities should serve the community and the environment, aiming to improve the quality of life and promote the use of renewable energy resources for sustainability. The smart city network system not only improves the economic situation of the society and benefits the environment but also enables the achievement of important issues such as sustainable development, continuity, and diversity of energy resources. In this article, we investigate the impact of using renewable energy sources on optimizing energy consumption and reducing pollution caused by fossil fuels with the help of smart city development. The aim of this article is to introduce renewable energy sources and their utilization as a solution to address the energy crisis and reduce environmental pollution. This research has attempted to introduce the smart city and the use of renewable energy sources as a method for solving many urban problems and achieving efficient urban control and management.

Keywords: smart city, renewable energy sources, sustainable development, sustainable city

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Authors: Abdelazziz Aouiche, El Moundher Aouiche, Mouhamed Salah Soudani

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Renewable energy sources now significantly contribute to the replacement of traditional fossil fuel energy sources. One of the most potent types of renewable energy that has developed quickly in recent years is photovoltaic energy. We all know that solar energy, which is sustainable and non-depleting, is the best knowledge form of energy that we have at our disposal. Due to changing weather conditions, the primary drawback of conventional solar PV cells is their inability to track their maximum power point. In this study, we apply artificial neural networks (ANN) to automatically track and measure the maximum power point (MPP) of solar panels. In MATLAB, the complete system is simulated, and the results are adjusted for the external environment. The results are better performance than traditional MPPT methods and the results demonstrate the advantages of using neural networks in solar PV systems.

Keywords: modeling, photovoltaic panel, artificial neural networks, maximum power point tracking

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Authors: M. Benbouzid, Q. Bresson, A. Duclos, K. Longo, Q. Morel

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Currently, electricity suppliers must predict the consumption of their customers in order to deduce the power they need to produce. It is, then, important in a first step to optimize household consumption to obtain more constant curves by limiting peaks in energy consumption. Here centralized real time scheduling is proposed to manage the equipment's starting in parallel. The aim is not to exceed a certain limit while optimizing the power consumption across a habitat. The Raspberry Pi is used as a box; this scheduler interacts with the various sensors in 6LoWPAN. At the scale of a single dwelling, household consumption decreases, particularly at times corresponding to the peaks. However, it would be wiser to consider the use of a residential complex so that the result would be more significant. So, the ceiling would no longer be fixed. The scheduling would be done on two scales, firstly, per dwelling, and secondly, at the level of a residential complex.

Keywords: smart grid, energy box, scheduling, Gang Model, energy consumption, energy management system, wireless sensor network

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Authors: Nayden Takev, Remy van Leeuwen, Shiva Chotoe, Hani Alers, Xiao Peng

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Citizens, businesses, and public authorities all around the world are becoming aware of the impact that they have on the environment. Currently, climate change is an apparent cause to urge everyone to act and move to sustainable energy solutions. After the Paris Climate Agreement, every country has thought of a way to cut down carbon emissions. The Netherlands formulated the National Climate Agreement. “The government’s central goal with the National Climate Agreement is to reduce greenhouse gas emissions in the Netherlands by 49% compared to 1990 levels. At a European level, the government is advocating a 55% reduction of greenhouse gas emissions by 2030.” [5]. From a survey of the CBS, it is apparent that citizens are not putting in as much effort into the transition to sustainable energy as the government would like them to. After analysing the data, it became clear that the citizens miss the motivation to switch to sustainable energy because they do not believe it is urgent at this point and it is too expensive for them [2]. This needs to be changed. The citizens need to be aware of their impact on the climate and the advantages that this process will bring them. For example, the implementation of smart home displays 4 for real time energy measuring will give the citizens an overview of their energy usage so they are aware of the impact they have. Researchers have also found that the citizens must be included in the decision-making aimed at changing their behaviour [4, 3, 1]. In the future, the government will need to include the citizens when they create campaigns, strategies or introduce new policies [7, 6]. By including and informing the citizens about the policies it will be more attractive for them to choose sustainable energy. However, is all of this enough to motivate the citizens towards energy transition? Or are there other and better ways to do it?

Keywords: Awereness, Energy Transition, Netherlands, citizens

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Authors: Aldona Kluczek

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Energy efficient process have become a pressing research field in manufacturing. The arguments for having an effective industrial energy efficiency processes are interacted with factors: economic and environmental impact, and energy security. Improvements in energy efficiency are most often achieved by implementation of more efficient technology or manufacturing process. Current processes of electricity production represents the biggest consumption of energy and the greatest amount of emissions to the environment. The goal of this study is to improve the potential energy-savings and reduce greenhouse emissions related to improvement scenarios for the treatment of hardwood lumber produced by an industrial plant operating in the U.S. through the application of green balancing procedure, in order to find the preferable efficient technology. The green procedure for energy is based on analysis of energy efficiency data. Three alternative scenarios of the cogeneration systems plant (CHP) construction are considered: generation of fresh steam, the purchase of a new boiler with the operating pressure 300 pounds per square inch gauge (PSIG), an installation of a new boiler with a 600 PSIG pressure. In this paper, the application of a bottom-down modelling for energy flow to devise a streamlined Energy and Emission Flow Analyze method for the technology of producing electricity is illustrated. It will identify efficiency or technology of a given process to be reached, through the effective use of energy, or energy management. Results have shown that the third scenario seem to be the efficient alternative scenario considered from the environmental and economic concerns for treating hardwood lumber. The energy conservation evaluation options could save an estimated 6,215.78 MMBtu/yr in each year, which represents 9.5% of the total annual energy usage. The total annual potential cost savings from all recommendations is $143,523/yr, which represents 30.1% of the total annual energy costs. Estimation have presented that energy cost savings are possible up to 43% (US$ 143,337.85), representing 18.6% of the total annual energy costs.

Keywords: alternative scenario improvements, cogeneration system, energy and emission flow analyze, energy balancing, green procedure, hardwood lumber manufacturing process

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Authors: Ali Jamshidi, Kiyofumi Kurumisawa, Toyoharu Nawa

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Transportation infrastructure assets can be considered as backbone of transportation system. They are routinely developed and or maintained which can be used effectively for movement of passengers, commodities and providing vital services. However, the infrastructure assets construction, maintenance and rehabilitation significantly depend on non-renewable natural resources, such as carbon-based energy carriers and aggregate materials. In this study, effects of thermal properties of aggregate materials were characterized for production of hot-mix asphalt in Japan, as a case study. The results indicated that incorporation of the aggregate with lower required heat energy significantly reduces fuel consumption greenhouse gas emission, irrespective of physical property of aggregate. The results also clearly showed that as 75% high-energy limestone is replaced with low-energy limestone in producing an asphalt mixture at 180 °C, 97,879 Japanese households would be energized per annum using the saved energy without any modification in the current asphalt mixing plants.

Keywords: zero energy infrastructure, sustainable development, greenhouse gas emission, asphalt pavement

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Authors: Chia-Chi Chang, Chuan-Bi Lin, Chia-Min Chan

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Most ZigBee sensor networks to date make use of nodes with limited processing, communication, and energy capabilities. Energy consumption is of great importance in wireless sensor applications as their nodes are commonly battery-driven. Once ZigBee nodes are deployed outdoors, limited power may make a sensor network useless before its purpose is complete. At present, there are two strategies for long node and network lifetime. The first strategy is saving energy as much as possible. The energy consumption will be minimized through switching the node from active mode to sleep mode and routing protocol with ultra-low energy consumption. The second strategy is to evaluate the energy consumption of sensor applications as accurately as possible. Erroneous energy model may render a ZigBee sensor network useless before changing batteries. In this paper, we present a ZigBee wireless sensor node with four key modules: a processing and radio unit, an energy harvesting unit, an energy storage unit, and a sensor unit. The processing unit uses CC2530 for controlling the sensor, carrying out routing protocol, and performing wireless communication with other nodes. The harvesting unit uses a 2W solar panel to provide lasting energy for the node. The storage unit consists of a rechargeable 1200 mAh Li-ion battery and a battery charger using a constant-current/constant-voltage algorithm. Our solution to extend node lifetime is implemented. Finally, a long-term sensor network test is used to exhibit the functionality of the solar powered system.

Keywords: ZigBee, Li-ion battery, solar panel, CC2530

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Authors: Li Hung-Hui, Chen Chi-Chieh, Yang Zon-Yee

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This study aims to explore the impact energy absorption in the fragmented processes of rock samples during the split-Hopkinson-pressure-bar tests. Three kinds of rock samples including granite, marble and sandstone were tested. The impact energy absorptions were calculated according to the incident, reflected and transmitted strain wave histories measured by a oscilloscope. The degree of fragment rocks after tests was quantified by the box dimension of the fractal theory. The box dimension of rock fragments was obtained from the particle size distribution curve by the sieve analysis. The results can be concluded that: (1) the degree of rock fragments after tests can be well described by the value of box dimension; (2) with the impact energy absorption increasing, the degrees of rock fragments are varied from the very large fragments to very small fragments, and the corresponding box dimension varies from 2.9 to 1.2.

Keywords: SHPB test, energy absorption, rock fragments, impact loading, box dimension

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Authors: D. Deepak, N. Yagnesh Sharma

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Abrasive Water Jet (AWJ) machining is a relatively new nontraditional machine tool used in machining of fiber reinforced composite. The quality of machined surface depends on jet exit kinetic energy which depends on various operating and material parameters. In the present work the effect abrasive parameters such as its size, concentration and type on jet kinetic energy is investigated using computational fluid dynamics (CFD). In addition, the effect of these parameters on wall shear stress developed inside the nozzle is also investigated. It is found that for the same operating parameters, increase in the abrasive volume fraction (concentration) results in significant decrease in the wall shear stress as well as the jet exit kinetic energy. Increase in the abrasive particle size results in marginal decrease in the jet exit kinetic energy. Numerical simulation also indicates that garnet abrasives produce better jet exit kinetic energy than aluminium oxide and silicon carbide.

Keywords: abrasive water jet machining, jet kinetic energy, operating pressure, wall shear stress, Garnet abrasive

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Authors: Wided Abidi, Tahar Ezzedine

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Low-Energy Adaptive Clustering Hierarchy (LEACH) has been considered as one of the effective hierarchical routing algorithms that optimize energy and prolong the lifetime of network. Since the selection of Cluster Head (CH) in LEACH is carried out randomly, in this paper, we propose an approach of electing CH based on LEACH protocol. In other words, we present a formula for calculating the threshold responsible for CH election. In fact, we adopt three principle criteria: the remaining energy of node, the number of neighbors within cluster range and the distance between node and CH. Simulation results show that our proposed approach beats LEACH protocol in regards of prolonging the lifetime of network and saving residual energy.

Keywords: wireless sensors networks, LEACH protocol, cluster head election, energy efficiency

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Authors: Jaroslav Frantík, Jan Najser

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This article deals with increasing the energy efficiency of a plant in terms of optimizing the process. The European Union is striving to achieve the climate-energy package in the area increasing of energy efficiency. The goal of energy efficiency is to reduce primary energy consumption by 20% within the EU until 2020. The objective of saving energy consumption in the Czech Republic was set at 47.84 PJ (13.29 TWh). For reducing electricity consumption, it is possible to choose: a) mandatory increasing of energy efficiency, b) alternative scheme, c) combination of both actions. The Czech Republic has chosen for reducing electricity consumption using-alternative scheme. The presentation is focused on the proposal of a technological unit dealing with the gasification process of processing of biomass with an increase of power in the output. The synthesis gas after gasification of biomass is used as fuel in a cogeneration process of reciprocating internal combustion engine with the classic production of heat and electricity. Subsequently, there is an explanation of the ORC system dealing with the conversion of waste heat to electricity with the using closed cycle of the steam process with organic medium. The arising electricity is distributed to the power grid as a further energy source, or it is used for needs of the partial coverage of the technological unit. Furthermore, there is a presented schematic description of the technology with the identification of energy flows starting from the biomass treatment by drying, through its conversion to gaseous fuel, producing of electricity and utilize of thermal energy with minimizing losses. It has been found that using of ORC system increased the efficiency of the produced electricity by 7.5%.

Keywords: biomass, efficiency, gasification, ORC system

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Authors: Enas R. Shouman

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Economic development with population growth is leading to a continuous increase in energy demand. At the same time, growing global concern for the environment is driving to decrease the use of conventional energy sources and to increase the use of renewable energy sources. The objective of this study is to present the market trends of solar energy photovoltaic technology over the world and to represent economics methods for PV financial analyzes on the basis of expectations for the expansion of PV in many applications. In the course of this study, detailed information about the current PV market was gathered and analyzed to find factors influencing the penetration of PV energy. The paper methodology depended on five relevant economic financial analysis methods that are often used for investment decisions maker. These methods are payback analysis, net benefit analysis, saving-to-investment ratio, adjusted internal rate of return, and life-cycle cost. The results of this study may be considered as a marketing guide that helps diffusion of using PV Energy. The study showed that PV cost is economically reliable. The consumers will pay higher purchase prices for PV system installation but will get lower electricity bill.

Keywords: photovoltaic, financial methods, solar energy, economics, PV panel

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Authors: Safieh Javadinejad

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In order to make well-informed decisions respecting long-term system planning, resource managers and policy creators necessitate to comprehend the interconnections among energy and water utilization and manufacture—and also the energy-water nexus. Planning and assessment issues contain the enhancement of strategies for declining the water and energy system’s vulnerabilities to climate alteration with also emissions of decreasing greenhouse gas. In order to deliver beneficial decision support for climate adjustment policy and planning, understanding the regionally-specific features of the energy-water nexus, and the history-future of the water and energy source systems serving is essential. It will be helpful for decision makers understand the nature of current water-energy system conditions and capacity for adaptation plans for future. This research shows an integrated hydrology/energy modeling platform which is able to extend water-energy examines based on a detailed illustration of local circumstances. The modeling links the Water Evaluation and Planning (WEAP) and the Long Range Energy Alternatives Planning (LEAP) system to create full picture of water-energy processes. This will allow water managers and policy-decision makers to simply understand links between energy system improvements and hydrological processing and realize how future climate change will effect on water-energy systems. The Zayandeh Rud river basin in Iran is selected as a case study to show the results and application of the analysis. This region is known as an area with large integration of both the electric power and water sectors. The linkages between water, energy and climate change and possible adaptation strategies are described along with early insights from applications of the integration modeling system.

Keywords: climate impacts, hydrology, water systems, adaptation planning, electricity, integrated modeling

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Authors: Zihua Wu, Yueming He, Xiaoxiao Yu, Yuanyuan Wang, Huaqing Xie

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The match of Solar thermoelectric generator (STEG) and phase change materials (PCM) can enhance the solar energy storage and reduce environmental impact from the day-and-night transformation and weather changes. This work utilizes D-mannitol (DM) matrix as the suitable PCM for coupling with thermoelectric generator to achieve the middle-temperature solar energy storage performance at 165℃-167℃. DM/MWCNT composite phase change materials prepared by ball milling not only can keep a high phase change enthalpy of DM material but also have great photo-thermal conversion efficiency of 82%. Based on the self-made storage device container, the effect of PCM thickness on the solar energy storage performance is further discussed and analyzed. The experimental results prove that PCM-STEG coupling system can output more electric energy than pure STEG system because PCM can decline the heat transfer and storage thermal energy to further generate the electric energy through thermal-to-electric conversion when the light is removed. The increase of PCM thickness can reduce the heat transfer and enhance thermal storage, and then the power generation performance of PCM-STEG coupling system can be improved. As the increase of light intensity, the output electric energy of the coupling system rises accordingly, and the maximum amount of electrical energy can reach by 113.85 J at 1.6 W/cm2. The study of the PCM-STEG coupling system has certain reference for the development of solar energy storage and application.

Keywords: solar energy, solar thermoelectric generator, phase change materials, solar-to-electric energy, DM/MWCNT

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Authors: Amirmozafar Benshams, Khatere Kashmari, Farzad Hatami, Mesbah Saybani

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Shape memory alloys with high capability of energy dissipation and large deformation bearing with return ability to their original shape without too much hysteresis strain have opened their place among the other damping systems as smart materials. Ninitol which is the most well-known and most used alloy material from the shape memory alloys family, has high resistance and fatigue and is coverage for large deformations. Shape memory effect and super-elasticity by shape alloys like Nitinol, are the reasons of the high power of these materials in energy depreciation. Thus, these materials are suitable for use in reciprocating dynamic loading conditions. The experiments results showed that Nitinol wires with small diameter have greater energy dissipation capability and by increase of diameter and thickness the damping capability and energy dissipation increase.

Keywords: shape memory alloys, shape memory effect, super elastic effect, nitinol, energy dissipation

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Authors: V. Rao, A. Bedford

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As the efficient performance of national grid becomes increasingly important to maintain the electrical network stability, the balance between the generation and the demand must be effectively maintained. To do this, any losses that occur in the power network must be reduced by compensating for it. In this paper, one of the main cause for the losses in the network is identified as the variance, which hinders the grid’s power carrying capacity. The reason for the variance in the grid is investigated and identified as the rise in the integration of renewable energy sources (RES) such as wind and solar power. The intermittent nature of these RES along with fluctuating demands gives rise to variance in the electrical network. The losses that occur during this process is estimated by analyzing the network’s power profiles. Whilst researchers have identified different ways to tackle this problem, little consideration is given to energy storage. This paper seeks to redress this by considering the role of energy storage systems as potential solutions to reduce variance in the network. The implementation of suitable energy storage systems based on different applications is presented in this paper as part of variance reduction method and thus contribute towards maintaining a stable and efficient grid operation.

Keywords: energy storage, electrical losses, national grid, renewable energy, variance

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Authors: Christian Böning, Henrik Prinzhorn, Eric C. Hund, Malte Stonis

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In this article, the flexible job-shop scheduling problem is extended by consideration of energy costs which arise owing to the power peak, and further decision variables such as work in process and throughput time are incorporated into the objective function. This enables a production plan to be simultaneously optimized in respect of the real arising energy and logistics costs. The energy-costs-aware flexible job-shop scheduling problem (EFJSP) which arises is described mathematically, and a memetic algorithm (MA) is presented as a solution. In the MA, the evolutionary process is supplemented with a local search. Furthermore, repair procedures are used in order to rectify any infeasible solutions that have arisen in the evolutionary process. The potential for lowering the real arising costs of a production plan through consideration of energy consumption levels is highlighted.

Keywords: energy costs, flexible job-shop scheduling, memetic algorithm, power peak

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Authors: Sherif Keddis, Mohamed Azzam, Norbert Schwesinger

Abstract:

Harvesting mechanical energy from footsteps or other impacts is a possibility to enable wireless autonomous sensor nodes. These can be used for a highly efficient control of connected devices such as lights, security systems, air conditioning systems or other smart home applications. They can also be used for accurate location or occupancy monitoring. Converting the mechanical energy into useful electrical energy can be achieved using the piezoelectric effect offering simple harvesting setups and low deflections. The challenge facing piezoelectric transducers is the achievable amount of energy per impact in the lower mJ range and the management of such low energies. Simple setups for energy extraction such as a full wave bridge connected directly to a capacitor are problematic due to the mismatch between high impedance sources and low impedance storage elements. Efficient energy circuits for piezoelectric harvesters are commonly designed for vibration harvesters and require periodic input energies with predictable frequencies. Due to the sporadic nature of impact harvesters, such circuits are not well suited. This paper presents a self-powered circuit that avoids the impedance mismatch during energy extraction by disconnecting the load until the source reaches its charge peak. The switch is implemented with passive components and works independent from the input frequency. Therefore, this circuit is suited for impact harvesting and sporadic inputs. For the same input energy, this circuit stores 150% of the energy in comparison to a directly connected capacitor to a bridge rectifier. The total efficiency, defined as the ratio of stored energy on a capacitor to available energy measured across a matched resistive load, is 63%. Although the resulting energy is already sufficient to power certain autonomous applications, further optimization of the circuit are still under investigation in order to improve the overall efficiency.

Keywords: autonomous sensors, circuit design, energy harvesting, energy management, impact harvester, piezoelectricity

Procedia PDF Downloads 154

Authors: Gaurav Kumar Sinha

Abstract:

In an era marked by increasing concerns about energy sustainability, this research endeavors to address the pressing challenge of energy consumption in buildings and industries. This study delves into the transformative potential of AWS services in optimizing energy efficiency. The research is founded on the recognition that effective management of energy consumption is imperative for both environmental conservation and economic viability. Buildings and industries account for a substantial portion of global energy use, making it crucial to develop advanced techniques for analysis and reduction. This study sets out to explore the integration of AWS services with big data analytics to provide innovative solutions for energy consumption analysis. Leveraging AWS's cloud computing capabilities, scalable infrastructure, and data analytics tools, the research aims to develop efficient methods for collecting, processing, and analyzing energy data from diverse sources. The core focus is on creating predictive models and real-time monitoring systems that enable proactive energy management. By harnessing AWS's machine learning and data analytics capabilities, the research seeks to identify patterns, anomalies, and optimization opportunities within energy consumption data. Furthermore, this study aims to propose actionable recommendations for reducing energy consumption in buildings and industries. By combining AWS services with metrics-driven insights, the research strives to facilitate the implementation of energy-efficient practices, ultimately leading to reduced carbon emissions and cost savings. The integration of AWS services not only enhances the analytical capabilities but also offers scalable solutions that can be customized for different building and industrial contexts. The research also recognizes the potential for AWS-powered solutions to promote sustainable practices and support environmental stewardship.

Keywords: energy consumption analysis, big data analytics, AWS services, energy efficiency

Procedia PDF Downloads 64