Search results for: energy forecast

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 43

Authors: Sawarni Hasibuan, Rudi Effendi Listyanto

Abstract:

The industrial sector is the largest consumer of energy consumption in Indonesia. The ceramics industry includes one of seven industries categorized as an energy-intensive industry. Energy costs on the ceramic floor production process reached 40 percent of the total production cost. The kiln is one of the machines in the ceramic industry that consumes the most gas energy reach 51 percent of gas consumption in ceramic production. The purpose of this research is to make improvement of energy consumption in kiln machine part with the innovation of burner tube to support the sustainability of Indonesian ceramics industry. The tube burner is technically designed to be able to raise the temperature and stabilize the air pressure in the burner so as to facilitate the combustion process in the kiln machine which implies the efficiency of gas consumption required. The innovation of the burner tube also has an impact on the decrease of the combustion chamber pressure in the kiln and managed to keep the pressure of the combustion chamber according to the operational standard of the kiln; consequently, the smoke fan motor power can be lowered and the kiln electric energy consumption is also more efficient. The innovation of burner tube succeeded in saving consume of gas and electricity respectively by 0.0654 GJ and 1,693 x 10-3 GJ for every ton of ceramics produced. Improvement of this energy consumption not only implies the cost savings of production but also supports the sustainability of the Indonesian ceramics industry.

Keywords: sustainable ceramic industry, burner tube, kiln, energy efficiency

Procedia PDF Downloads 306

Authors: Alia Al Nuaimi, Ayesha Al Aberi, Faiza Al Marzouqi, Shaikha Salem Ali Al Yahyaee, Ala Hussein

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In this paper, a PV micro-storage system for residential applications is proposed. The term micro refers to the size of the PV storage system, which is in the range of few kilo-watts, compared to the grid size (~GWs). Usually, in a typical load profile of a residential unit, two peak demand periods exist: one at morning and the other at evening time. The morning peak can be partly covered by the PV energy directly, while the evening peak cannot be covered by the PV alone. Therefore, an energy storage system that stores solar energy during daytime and use this stored energy when the sun is absent is a must. A complete design procedure including theoretical analysis followed by simulation verification and economic feasibility evaluation is addressed in this paper.

Keywords: battery, energy storage, photovoltaic, peak shaving, smart grid

Procedia PDF Downloads 295

Authors: Ekele T. Ochedi, Ahmad H. Taki, Birgit Painter

Abstract:

The effect of the sun and its path on thermal comfort and energy consumption in residential buildings in tropical climates constitute a serious concern for designers, building owners, and users. Passive design approaches based on the sun and its path have been identified as a means of reducing energy consumption as well as enhancing thermal comfort in buildings worldwide. Hence, a thorough understanding regarding the sun path is key to achieving this. This is necessary due to energy need, poor energy supply, and distribution, energy poverty, and over-dependence on electric generators for power supply in Nigeria. These challenges call for a change in the approach to energy-related issues, especially in terms of buildings. The aim of this study is to explore the influence of building orientation, glazing and the use of shading devices on residential buildings in Nigeria. This is intended to provide data that will guide designers in the design of energy-efficient residential buildings. The paper used EnergyPlus to analyze a typical semi-detached residential building in Lokoja, Nigeria using hourly weather data for a period of 10 years. Building performance was studied as well as possible improvement regarding different orientations, glazing types and shading devices. The simulation results show some reductions in energy consumption in response to changes in building orientation, types of glazing and the use of shading devices. The results indicate 29.45% reduction in solar gains and 1.90% in annual operative temperature using natural ventilation only. This shows a huge potential to reduce energy consumption and improve people’s well-being through the use of proper building orientation, glazing and appropriate shading devices on building envelope. The study concludes that for a significant reduction in total energy consumption by residential buildings, the design should focus on multiple design options rather than concentrating on one or few building elements. Moreover, the investigation confirms that energy performance modeling can be used by building designers to take advantage of the sun and to evaluate various design options.

Keywords: energy consumption, energy-efficient buildings, glazing, thermal comfort, shading devices, solar gains

Procedia PDF Downloads 183

Authors: Martin Kendra, Tomas Skrucany, Jozef Gnap, Jan Ponicky

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Paper deals with the modeling and simulation of energy consumption and GHG production of two different modes of regional passenger transport – road and railway. These two transport modes use the same type of fuel – diesel. Modeling and simulation of the energy consumption in transport is often used due to calculation satisfactory accuracy and cost efficiency. Paper deals with the calculation based on EN standards and information collected from technical information from vehicle producers and characteristics of tracks. Calculation included maximal theoretical capacity of bus and train and real passenger’s measurement from operation. Final energy consumption and GHG production is calculated by using software simulation. In evaluation of the simulation is used system ‘well to wheel’.

Keywords: bus, consumption energy, GHG, production, simulation, train

Procedia PDF Downloads 419

Authors: Eman Simbawa, Budur Alasmri, Hanan Munahir, Hanin Munahir

Abstract:

Solar energy has become currently the subject of attention around the world and is undergoing many researches and studies. Using solar energy, which is a renewable energy, is aligned with the Saudi Vision 2030. People are more aware of it and are starting to use it more for environmental and economical reasons. A questionnaire was conducted in this paper to measure the awareness of people in Saudi Arabia regarding solar energy and their attitude towards it. Then, two kinds of air conditioners (one powered by electricity only and one powered by solar panels and electricity) are compared in terms of their cost over a period of 20 years. This will help the users to decide which kind of device to use depending on its cost. The result shows that as the electricity tariffs in Saudi Arabia increases, depending on the sector, the solar air conditioner is cheaper. In fact, if the tariff in the future increases to reach 50 Halalah/kWh, the solar air conditioner is more economical. This will influence users to buy more solar powered devices, and it will decrease the consumption of electricity. Therefore, the dependence on oil will decrease.

Keywords: Airconditioner, solar energy, photovoltaic cells, present value

Procedia PDF Downloads 131

Authors: Yungtai Lo

Abstract:

The current study follows an educational intervention on bottle-weaning to simultaneously evaluate the effect of the bottle-weaning intervention on reducing bottle use, daily milk intake from bottles, and daily energy intake in toddlers aged 11 to 13 months. A shared parameter model and a random effects model are used to jointly model bottle use, daily milk intake from bottles, and daily energy intake. We show in the two joint models that the bottle-weaning intervention promotes bottleweaning, and reduces daily milk intake from bottles in toddlers not off bottles and daily energy intake. We also show that the odds of drinking from a bottle were positively associated with the amount of milk intake from bottles and increased daily milk intake from bottles was associated with increased daily energy intake. The effect of bottle use on daily energy intake is through its effect on increasing daily milk intake from bottles that in turn increases daily energy intake.

Keywords: two-part model, semi-continuous variable, joint model, gamma regression, shared parameter model, random effects model

Procedia PDF Downloads 267

Authors: Sean Kinney

Abstract:

In 1666, Newton created the Law of Universal Gravitation. And in 1915, Einstein improved it to incorporate factors such as time dilation and gravitational lensing. But currently, there is a problem with this “universal” law. The math doesn’t work outside the confines of our solar system. And something is missing; any evidence of what gravity actually is and how it manifest. This paper explores the notion that gravity must obey the law of conservation of energy as all other forces in this universe have been shown to do. Explaining exactly what gravity is and how it manifests itself. And looking at many different implications that would be created are explained. And finally, using the math of Dynamic Gravity to calculate Dark Energy and Dark Matter effects to explain all observations without the need of exotic measures.

Keywords: gravity, dynamic gravity, dark matter, dark energy

Procedia PDF Downloads 77

Authors: E. Bal Beşikçi, O. Arslan

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Fuel saving has become one of the most important issue for shipping in terms of fuel economy and environmental impact. Lowering fuel consumption is possible for both new ships and existing ships through enhanced energy efficiency measures, technical and operational respectively. The limitations of applying technical measures due to the long payback duration raise the potential of operational changes for energy efficient ship operations. This study identifies operational energy efficiency measures related voyage performance management. We use ‘noon’ data to examine the correlation between fuel consumption and operational parameters- revolutions per minute (RPM), draft, trim, (beaufort number) BN and relative wind direction, which are used as measures of ship energy efficiency. The results of this study reveal that speed optimization is the most efficient method as fuel consumption depends heavily on RPM. In conclusion, this study will provide ship operators with the strategic approach for evaluating the priority of the operational energy efficiency measures against high fuel prices and carbon emissions.

Keywords: ship, voyage related operational energy Efficiency measures, fuel consumption, pearson's correlation coefficient

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Authors: Sandeep Bandarwadkar, Tadas Zdankus

Abstract:

To maintain a comfortable indoor temperature for its residents in the colder season, heating a building is necessary. Due to the expansion in the construction sectors, the consumption of heating energy is increasing. According to Eurostat data, in the European Union, the share of energy consumption of heating energy for space and cooling in residential buildings was around 63% in 2019. These figures indicate that heating energy still accounts for a significant portion of total energy consumption in Europe. Innovation is crucial to reduce energy consumption in buildings and achieve greater energy efficiency and sustainability. It can bring about new solutions that are smarter and more natural energy generation to reduce greenhouse gas emissions. The ground can serve as an effective and sustainable heat accumulator for heating and cooling. The temperature of the ground is higher than that of the ambient air in the colder period and lower in the warmer period. The building deep in the soil could use less thermal energy compared to the above-ground buildings that provide the same amount of thermal comfort. The temperature difference between the soil and the air inside the building decreases as the temperature of the soil increases. In progress, this process generates the condition that acts against heat loss. However, heat dissipates further to the consecutive layers and reaches thermal equilibrium. The charging of the ground by heat and its dissipation through the adjacent soil layers was investigated experimentally. The results of this research showed that 9% of the energy savings in partially underground buildings and 44.4% in completely underground buildings were derived from heating the space. Heat loss to the ground is treated as a charge of the soil by thermal energy. The dependence of the intensity of the charge on time was analysed and presented.

Keywords: heat transfer, accumulation of heat, underground building, soil charge

Procedia PDF Downloads 52

Authors: A. Derrouazin, N. Mekkakia-M, R. Taleb, M. Helaimi, A. Benbouali

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Nowadays the use of different sources of renewable energy for the production of electricity is the concern of everyone, as, even impersonal domestic use of the electricity in isolated sites or in town. As the conventional sources of energy are shrinking, a need has arisen to look for alternative sources of energy with more emphasis on its optimal use. This paper presents design of a sustainable Hybrid Power System (PV-Wind-Storage) assisted by grid as supplementary sources applied to case study residential house, to meet its entire energy demand. A Fuzzy control system model has been developed to optimize and control flow of power from these sources. This energy requirement is mainly fulfilled from PV and Wind energy stored in batteries module for critical load of a residential house and supplemented by grid for base and peak load. The system has been developed for maximum daily households load energy of 3kWh and can be scaled to any higher value as per requirement of individual /community house ranging from 3kWh/day to 10kWh/day, as per the requirement. The simulation work, using intelligent energy management, has resulted in an optimal yield leading to average reduction in cost of electricity by 50% per day.

Keywords: photovoltaic (PV), wind turbine, battery, microcontroller, fuzzy control (FC), Matlab

Procedia PDF Downloads 627

Authors: Tianyu Wang, Nikita Karandikar

Abstract:

The uncertainty around cost, safety, and feasibility of the decarbonized shipping fuels has made it increasingly complex for the shipping companies to set pricing strategies and forecast their freight revenues going forward. The increase in the green fuel surcharges will ultimately influence the automobile’s consumer prices. The auto shipping demand (ton-miles) has been gradually shifting from long-haul to short-sea trade over the past years following the relocation of the original equipment manufacturer (OEM) manufacturing to regions such as South America and Southeast Asia. The objective of this paper is twofold: 1) to investigate the car-carriers freight revenue development over the years when the trade pattern is gradually shifting towards short-sea exports 2) to empirically identify the quantitative impact of such trade pattern shifting to mainly freight rate, but also vessel size, fleet size as well as Green House Gas (GHG) emission in Roll on-Roll Off (Ro-Ro) shipping. In this paper, a model of analyzing and forecasting ton-miles and freight revenues for the trade routes of AS-NA (Asia to North America), EU-NA (Europe to North America), and SA-NA (South America to North America) is established by deploying Automatic Identification System (AIS) data and the financial results of a selected car carrier company. More specifically, Wallenius Wilhelmsen Logistics (WALWIL), the Norwegian Ro-Ro carrier listed on Oslo Stock Exchange, is selected as the case study company in this paper. AIS-based ton-mile datasets of WALWIL vessels that are sailing into North America region from three different origins (Asia, Europe, and South America), together with WALWIL’s quarterly freight revenues as reported in trade segments, will be investigated and compared for the past five years (2018-2022). Furthermore, ordinary‐least‐square (OLS) regression is utilized to construct the ton-mile demand and freight revenue forecasting. The determinants of trade pattern shifting, such as import tariffs following the China-US trade war and fuel prices following the 0.1% Emission Control Areas (ECA) zone requirement after IMO2020 will be set as key variable inputs to the machine learning model. The model will be tested on another newly listed Norwegian Car Carrier, Hoegh Autoliner, to forecast its 2022 financial results and to validate the accuracy based on its actual results. GHG emissions on the three routes will be compared and discussed based on a constant emission per mile assumption and voyage distances. Our findings will provide important insights about 1) the trade-off evaluation between revenue reduction and energy saving with the new ton-mile pattern and 2) how the trade flow shifting would influence the future need for the vessel and fleet size.

Keywords: AIS, automobile exports, maritime big data, trade flows

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Authors: Eyhab El-Kharashi, Maher El-Dessouki

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The paper is dedicated to precise assessment of the induction motor output energy during the unbalanced operation. Since many years ago and until now the voltage complex unbalance factor (CVUF) is used only to assess the output energy of the induction motor while this output energy for asymmetry supply voltage does not depend on the value of unbalanced voltage only but also on the machine parameters. The paper illustrates the variation of the two unbalance factors, complex voltage unbalance factor (CVUF) and impedance unbalance factor (IUF), with positive sequence voltage component, reveals that degree and manner of unbalance in supply voltage. From this point of view the paper delineates the current unbalance factor (CUF) to exactly reflect the output energy during unbalanced operation. The paper proceeds to illustrate the importance of using this factor in the multi-machine system to precise prediction of the output energy during the unbalanced operation. The use of the proposed unbalance factor (CUF) avoids the accumulation of the error due to more than one machine in the system which is expected if only the complex voltage unbalance factor (CVUF) is used.

Keywords: induction motor, electromagnetic torque, voltage unbalance, energy conversion

Procedia PDF Downloads 537

Authors: H. M. Farghally, N. M. Ahmed, H. T. El-Madany, D. M. Atia, F. H. Fahmy

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Energy is required in almost every aspect of human activities and development of any nation in this world. Increasing fossil fuel price, energy security and climate change have important bearings on sustainable development of any nation. The renewable energy technology is considered one of the drastic approaches taken over the world to reduce the energy problem. The preservation of vegetables by freezing is one of the most important methods of retaining quality in agricultural products over long-term storage periods. Freezing factories show high demand of energy for both heat and electricity; the hybrid Photovoltaic/Thermal (PV/T) systems could be used in order to meet this requirement. This paper presents PV/T system design for freezing factory. Also, the complete mathematical modeling and Matlab Simulink of PV/T collector is introduced. The sensitivity analysis for the manufacturing parameters of PV/T collector is carried out to study their effect on the thermal and electrical efficiency.

Keywords: renewable energy, hybrid PV/T system, sensitivity analysis, ecological sciences

Procedia PDF Downloads 273

Authors: Mehrab Gholami Zangalani, Siavash Rajabpour

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In compliance with the Statistical Centre of Iran (SCI)’s results, construction and housing section in Iran is consuming 40% of energy, which is 5 times more than the world average consumption. By considering the climate in Iran, the solutions in terms of design, construction and exploitation of the buildings by utilizing the LEED rating system (LRS) is presented, regarding to the reasons for the high levels of energy consumption during construction and housing in Iran. As a solution, innovative Work Break Structure (WBS) in accordance with LRS and Iranian construction’s methods is unveiled in this research. Also, by amending laws pertaining to the construction in Iran, the huge amount of energy and cost can be saved. Furthermore, with a scale-up of these results to the scale of big cities such as Tehran (one of the largest metropolitan areas in the middle east) in which the license to build more than two hundred and fifty units each day is issued, the amount of energy and cost that can be saved is estimated.

Keywords: costs reduction, energy statistics, leed rating system (LRS), work brake structure (WBS)

Procedia PDF Downloads 505

Authors: Mejri Achref

Abstract:

This paper proposes an energy management strategy for an electrical hybrid vehicle which is composed of a Proton Exchange Membrane (PEM) fuel cell and a supercapacitor storage device. In this paper, the mathematical model for the proposed power train, comprising the PEM Fuel Cell, supercapacitor, boost converter, inverter, and vehicular structure, was modeled in MATLAB/Simulink. The proposed algorithm is evaluated for the Highway Fuel Economy Test (HWFET) driving cycle. The obtained results demonstrate the effectiveness of the proposed energy management strategy in reduction of hydrogen consumption.

Keywords: proton exchange membrane fuel cell, hybrid vehicle, hydrogen consumption, energy management strategy

Procedia PDF Downloads 161

Authors: Dewi Liesnoor Setyowati, Puji Hardati, Tri Marhaeni Puji Astuti, Muhammad Amin

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Universitas Negeri Semarang (UNNES) is a university with a vision of conservation. The impact of the UNNES conservation is the existence of a positive response from the community for the effort of greening the campus and the planting of conservation value in the academic community. But in reality,  energy consumption in UNNES campus tends to increase. The objectives of the study were to analyze the energy consumption in the campus area, to analyze the absorption of emissions by trees and the awareness of UNNES citizens in reducing emissions. Research focuses on energy consumption, carbon emissions, and awareness of citizens in reducing emissions. Research subjects in this study are UNNES citizens (lecturers, students and employees). The research area covers 6 faculties and one administrative center building. Data collection is done by observation, interview and documentation. The research used a quantitative descriptive method to analyze the data. The number of trees in UNNES is 10,264. Total emission on campus UNNES is 7.862.281.56 kg/year, the tree absorption is 6,289,250.38 kg/year. In UNNES campus area there are still 1,575,031.18 kg/year of emissions, not yet absorbed by trees. There are only two areas of the faculty whose trees are capable of absorbing emissions. The awareness of UNNES citizens in reducing energy consumption is seen in change the habit of: using energy-saving equipment (65%); reduce energy consumption per unit (68%); do energy literacy for UNNES citizens (74%). UNNES leaders always provide motivation to the citizens of UNNES, to reduce and change patterns of energy consumption.

Keywords: energy consumption, carbon emission absorption, emission reduction, energy literation

Procedia PDF Downloads 225

Authors: Jiří Hirš, Jitka Mohelnikova

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A photovoltaic system integrated into a high-rise building façade was studied. The high-rise building is located in the Central Europe region with temperate climate and dominant partly cloudy and overcast sky conditions. The PV façade has been monitored since 2013. The three-year monitoring of the façade energy generation shows that the façade has an important impact on the building energy efficiency and sustainable operation.

Keywords: buildings, energy, PV façade, solar radiation

Procedia PDF Downloads 281

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 96

Authors: Diyono Harun

Abstract:

Indonesia aims to reduce carbon emissions from energy generation by reaching 23% and 31% of the national energy supply from renewable energy sources (RES) in 2025 and 2030. The potential for RES in Indonesia is enormous, but not all province has the same potential for RES. Yogyakarta, one of the most travel-destinated provinces in Indonesia, has less potential than its neighbour, Central Java. Consequently, Yogyakarta must meet its electricity demand by importing electricity from Central Java if this province only wants to use electricity from RES. Thus, achieving the objective is balancing the electricity supply between an importer (Yogyakarta) and an exporter province (Central Java). This research aims to explore the RES potential and the current capacity of RES for electricity generation in both provinces. The results show that the present capacity of RES meets the annual domestic electricity demand in both provinces only with an extension of the RES potential. The renewable energy mixes in this research also can lower CO2 emissions compared to gas-fired power plants. This research eventually provides insights into exploring and using the domestic RES potentials between two areas with different RES capacities.

Keywords: energy mix, renewable energy sources, domestic electricity, electricity generation

Procedia PDF Downloads 68

Authors: Corrado Grassi, Achim Schröter, Yves Gloy, Thomas Gries

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Air jet weaving is the most productive, but also the most energy consuming weaving method. Increasing energy costs and environmental impact are constantly a challenge for the manufacturers of weaving machines. Current technological developments concern with low energy costs, low environmental impact, high productivity, and constant product quality. The high degree of energy consumption of the method can be ascribed to the high need of compressed air. An energy efficiency method is applied to the air jet weaving technology. Such method identifies and classifies the main relevant energy consumers and processes from the exergy point of view and it leads to the identification of energy efficiency potentials during the weft insertion process. Starting from the design phase, energy efficiency is considered as the central requirement to be satisfied. The initial phase of the method consists of an analysis of the state of the art of the main weft insertion components in order to point out a prioritization of the high demanding energy components and processes. The identified major components are investigated to reduce the high demand of energy of the weft insertion process. During the interaction of the flow field coming from the relay nozzles within the profiled reed, only a minor part of the stream is really accelerating the weft yarn, hence resulting in large energy inefficiency. Different tools such as FEM analysis, CFD simulation models and experimental analysis are used in order to design a more energy efficient design of the involved components in the filling insertion. A different concept for the metal strip of the profiled reed is developed. The developed metal strip allows a reduction of the machine energy consumption. Based on a parametric and aerodynamic study, the designed reed transmits higher values of the flow power to the filling yarn. The innovative reed fulfills both the requirement of raising energy efficiency and the compliance with the weaving constraints.

Keywords: air jet weaving, aerodynamic simulation, energy efficiency, experimental validation, weft insertion

Procedia PDF Downloads 176

Authors: Bawadi M. A., Abbad J. A., Baras E. A.

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This study was conducted to assess wind energy resources in the area of Al-Adwas Ras-Huwirah Hadhramout Governorate, Yemen, through using statistical calculations, the Weibull model and SPSS program were used in the monthly and the annual to analyze the wind energy resource; the convergence of wind energy; turbine efficiency in the selected area. Wind speed data was obtained from NASA over a period of ten years (2010-2019) and at heights of 50 m above ground level. Probability distributions derived from wind data and their distribution parameters are determined. The density probability function is fitted to the measured probability distributions on an annual basis. This study also involves locating preliminary sites for wind farms using Geographic Information System (GIS) technology. This further leads to maximizing the output energy from the most suitable wind turbines in the proposed site.

Keywords: wind speed analysis, Yemen wind energy, wind power density, Weibull distribution model

Procedia PDF Downloads 61

Authors: Nikhil V. Nayak, P. P. Revankar, M. B. Gorawar

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Wind energy has been shown to be one of the most viable sources of renewable energy. With current technology, the low cost of wind energy is competitive with more conventional sources of energy such as coal. Most airfoil blades available for commercial grade wind turbines incorporate a straight span-wise profile and airfoil shaped cross sections. This paper is aimed at studying and designing a wind-solar hybrid system for light load application. The tools like qblade and solidworks are used to model and analyze the wind turbine system, the material used for the blade and hub is balsa wood and the tower a lattice type. The expected power output is 100 W for an average wind speed of 4.5 m/s.

Keywords: renewable energy, hybrid, airfoil blades, wind speeds, make-in-india, camber, QBlade, solidworks, balsa wood

Procedia PDF Downloads 287

Authors: Juan José Mesas, Luis Sainz

Abstract:

The motivation for the development of this paper lies in the need for energy networks to reduce losses, improve performance, optimize their operation and try to benefit from the interconnection capacity with other networks enabled for other energy carriers. These interconnections generate interdependencies between some energy networks and others, which requires suitable models and methods for their analysis. Traditionally, the modeling and study of energy networks have been carried out independently for each energy carrier. Thus, there are well-established models and methods for the steady-state analysis of electrical networks, gas networks, and thermal networks separately. What is intended is to extend and combine them adequately to be able to face in an integrated way the steady-state analysis of networks with multiple energy carriers. Firstly, the added value of multi-energy networks, their operation, and the basic principles that characterize them are explained. In addition, two current aspects of great relevance are exposed: the storage technologies and the coupling elements used to interconnect one energy network with another. Secondly, the characteristic equations of the different energy networks necessary to carry out the steady-state analysis are detailed. The electrical network, the natural gas network, and the thermal network of heat and cold are considered in this paper. After the presentation of the equations, a particular case of the steady-state analysis of a specific multi-energy network is studied. This network is represented graphically, the interconnections between the different energy carriers are described, their technical data are exposed and the equations that have previously been presented theoretically are formulated and developed. Finally, the two iterative numerical resolution methods considered in this paper are presented, as well as the resolution procedure and the results obtained. The pros and cons of the application of both methods are explained. It is verified that the results obtained for the electrical network (voltages in modulus and angle), the natural gas network (pressures), and the thermal network (mass flows and temperatures) are correct since they comply with the distribution, operation, consumption and technical characteristics of the multi-energy network under study.

Keywords: coupling elements, energy carriers, multi-energy networks, steady-state analysis

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Authors: Uche A. Nnawulezi

Abstract:

Over the past decades, the acquisition and utilization of nuclear energy have remained a standout amongst the most intractable issues which past world leaders have unsuccessfully endeavored to grapple with. This study analyzes the present advancement and enactment on the acquisition and utilization of nuclear energy in contemporary international law. It seeks to address international co-operations in the field of nuclear energy by looking at what nuclear energy is all about and how it came into being. It also seeks to address concerns expressed by a few researchers on the position of nuclear law in the most extensive domain of the law by looking at the authoritative procedure for nuclear law, system of arrangements and traditions. This study also agrees in favour of treaty on non-proliferation of nuclear weapons based on human right and humanitarian principles that are not duly moral, but also legal ones. Specifically, the past development activities on nuclear weapon and the practical system of the nuclear energy institute will be inspected. The study noted among others, former president Obama's remark on nuclear energy and Pakistan nuclear policies and its attendant outcomes. Essentially, we depended on documentary evidence and henceforth scooped a great part of the data from secondary sources. The study emphatically advocates for the adoption of absolute liability principles and setting up of a viability trust fund, all of which will help in sustaining global peace where global best practices in acquisition and use of nuclear energy will be widely accepted in the contemporary international law. Essentially, the fundamental proposals made in this paper if completely adopted, might go far in fortifying the present advancement and enactment on the application and utilization of nuclear energy and accordingly, addressing a portion of the intractable issues under international law.

Keywords: nuclear energy, international law, acquisition, development

Procedia PDF Downloads 159

Authors: Chin-Yuan Hsu, Yu-Lung Chuang

Abstract:

The expression, concentration, and activity of mitochondrial energy-utilized molecules and cellular energy-regulated molecules decreased with age in the trophocytes and oenocytes of honeybees (Apis mellifera), but those of cellular energy-metabolized molecules is unknown. In this study, the expression, concentration, and activity of cellular energy-metabolized molecules were assayed in the trophocytes and fat cells of young and old worker bees by using the techniques of cell and biochemistry. The results showed that (i) the •-hydroxylacyl-coenzyme A dehydrogenase (HOAD) activity/citrate synthase (CS) activity ratio, non-esterified fatty acids concentrations, the expression of eukaryotic initiation factor 4E, and the expression of phosphorylated eIF4E binding protein 1 decreased with age; (ii) fat and glycogen accumulation increased with age; and (iii) the pyruvate dehydrogenase (PDH) activity/citrate synthase (CS) activity ratio was not correlated with age. These finding indicated that •-oxidation (HOAD/CS) and protein synthsis decreased with age. Glycolysis (PDH/CS) was unchanged with age. The most likely reason is that sugars are the vital food of worker bees. Taken together these data reveal that young workers have higher cellular energy metabolism than old workers and that aging results in a decline in the cellular energy metabolism in worker honeybees.

Keywords: aging, energy, honeybee, metabolism

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Authors: Vaishakh Medikeri

Abstract:

Energy in this Universe is the most basic characteristic of every particle. Since the birth of life on this planet, there has been a quest undertaken by the living beings to analyze, understand and harness the precious natural facts of the nature. In this quest, one of the greatest undertaken is the process of harnessing the naturally available energy. Scientists around the globe have discovered many ways to harness the freely available energy. But even today we speak of “Power Crisis”. Nikola Tesla once said “Nature has stored up in this universe infinite energy”. Energy is everywhere around us in unlimited quantities; all of it waiting to be harnessed by us. Here in this paper a method has been proposed to harness earth's electric field and transmit the stored electric energy using strong magnetic fields and electric fields. In this paper a new technique has been proposed to harness earth's electric field which is everywhere around the world in infinite quantities. Near the surface of the earth there is an electric field of about 120V/m. This electric field is used to charge a capacitor with high capacitance. Later the energy stored is allowed to pass through a device which converts the DC stored into AC. The AC so produced is then passed through a step down transformer to magnify the incoming current. Later the current passes through the RLC circuit. Later the current can be transmitted wirelessly using the principle of resonant inductive coupling. The proposed apparatus can be placed in most of the required places and any circuit tuned to the frequency of the transmitted current can receive the energy. The new source of renewable energy is of great importance if implemented since the apparatus is not costly and can be situated in most of the required places. And also the receiver which receives the transmitted energy is just an RLC circuit tuned to the resonant frequency of the transmitted energy. By using the proposed apparatus the energy losses can be reduced to a very large extent.

Keywords: capacitor, inductive resonant coupling, RLC circuit, transmission of electricity

Procedia PDF Downloads 355

Authors: M. Ranjeeth, S. Anuradha

Abstract:

Spectrum sensing is the main feature of cognitive radio technology. Spectrum sensing gives an idea of detecting the presence of the primary users in a licensed spectrum. In this paper we compare the theoretical results of detection probability of different fading environments like Rayleigh, Rician, Nakagami-m fading channels with the simulation results using energy detection based spectrum sensing. The numerical results are plotted as P_f Vs P_d for different SNR values, fading parameters. It is observed that Nakagami fading channel performance is better than other fading channels by using energy detection in spectrum sensing. A MATLAB simulation test bench has been implemented to know the performance of energy detection in different fading channel environment.

Keywords: spectrum sensing, energy detection, fading channels, probability of detection, probability of false alarm

Procedia PDF Downloads 513

Authors: S. Yessengabulov, A. Uyzbayeva

Abstract:

Residential buildings fund of Kazakhstan was built in the Soviet time about 35-60 years ago without considering energy efficiency measures. Currently, most of these buildings are in a rundown condition and fail to meet the minimum of hygienic, sanitary and comfortable living requirements. The paper aims to examine the reports of recent building energy survey activities in the country and provide a possible solution for retrofitting existing housing stock built before 1989 which could be applicable for building envelope in cold climate. Methodology also includes two-dimensional modeling of possible practical solutions and further recommendations.

Keywords: energy audit, energy efficient buildings in Kazakhstan, retrofit, two-dimensional conduction heat transfer analysis

Procedia PDF Downloads 222

Authors: Sandija Zeverte-Rivza, Irina Pilvere, Baiba Rivza

Abstract:

The use of renewable energy sources incl. biogas has become topical in accordance with the increasing demand for energy, decrease of fossil energy resources and the efforts to reduce greenhouse gas emissions as well as to increase energy independence from the territories where fossil energy resources are available. As the technologies of biogas production from agricultural biomass develop, risk assessment and risk management become necessary for farms producing such a renewable energy. The need for risk assessments has become particularly topical when discussions on changing the biogas policy in the EU take place, which may influence the development of the sector in the future, as well as the operation of existing biogas facilities and their income level. The current article describes results of the risk assessment for farms producing biomass from agriculture biomass in Latvia, the risk assessment system included 24 risks, that affect the whole biogas production process and the obtained results showed the high significance of political and production risks.

Keywords: biogas production, risks, risk assessment, biosystems engineering

Procedia PDF Downloads 382