Search results for: exergy and energy models

Authors: Norshazmira Mat Azmi, Sayidal El Fatimah Masnan, Shatirah Akib

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More than 70% of the Earth is covered by oceans, which are considered to possess boundless renewable energy, such as tidal energy, tidal current energy, wave energy, thermal energy, and chemical energy. The hybrid system help in improving the economic and environmental sustainability of renewable energy systems to fulfill the energy demand. The concept of hybridizing renewable energy is to meet the desired system requirements, with the lowest value of the energy cost. This paper propose a hybrid power generation system suitable for remote area application and highlight the impact of surface waves on turbine design and performance, and the importance of understanding the site-specific wave conditions.

Keywords: marine current energy, tidal turbines, wave turbine, renewable energy, surface waves, hydraulic flume experiments, instantaneous wave phase

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Authors: E. Al Daoud

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In many cases, theoretical treatments are available for models for which there is no perfect physical realization. In this situation, the only possible test for an approximate theoretical solution is to compare with data generated from a computer simulation. In this paper, Monte Carlo tools are used to study and compare the elementary particles models. All the experiments are implemented using 10000 events, and the simulated energy is 13 TeV. The mean and the curves of several variables are calculated for each model using MadAnalysis 5. Anomalies in the results can be seen in the muons masses of the minimal supersymmetric standard model and the two Higgs doublet model.

Keywords: Feynman rules, hadrons, Lagrangian, Monte Carlo, simulation

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Authors: Izabela L. Ciesielska-Wrόbel

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This paper presents finite element models of the fingertip skin which have been created to simulate the contact of textile objects with the skin to gain a better understanding of the perception of textiles through the skin, so-called Hand of Textiles (HoT). Many objective and subjective techniques have been developed to analyze HoT, however none of them provide exact overall information concerning the sensation of textiles through the skin. As the human skin is a complex heterogeneous hyperelastic body composed of many particles, some simplifications had to be made at the stage of building the models. The same concerns models of woven structures, however their utilitarian value was maintained. The models reflect only friction between skin and woven textiles, deformation of the skin and fabrics when “touching” textiles and heat transfer from the surface of the skin into direction of textiles.

Keywords: fingertip skin models, finite element models, modelling of textiles, sensation of textiles through the skin

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Authors: Meng-Fei Cheng, Wei Fneg

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New Taiwan high school standards emphasize employing scientific models and modeling practices in physics learning. However, to our knowledge. Few studies address how scientific models and modeling are approached in current science teaching, and they do not examine the views of scientific models portrayed in the textbooks. To explore the views of scientific models and modeling in textbooks, this study investigated the atomic unit in different textbook versions as an example and provided suggestions for modeling curriculum. This study adopted a quantitative analysis of qualitative data in the atomic units of four mainstream version of Taiwan high school physics textbooks. The models were further analyzed using five dimensions of the views of scientific models (nature of models, multiple models, purpose of the models, testing models, and changing models); each dimension had three levels (low, medium, high). Descriptive statistics were employed to compare the frequency of describing the five dimensions of the views of scientific models in the atomic unit to understand the emphasis of the views and to compare the frequency of the eight scientific models’ use to investigate the atomic model that was used most often in the textbooks. Descriptive statistics were further utilized to investigate the average levels of the five dimensions of the views of scientific models to examine whether the textbooks views were close to the scientific view. The average level of the five dimensions of the eight atomic models were also compared to examine whether the views of the eight atomic models were close to the scientific views. The results revealed the following three major findings from the atomic unit. (1) Among the five dimensions of the views of scientific models, the most portrayed dimension was the 'purpose of models,' and the least portrayed dimension was 'multiple models.' The most diverse view was the 'purpose of models,' and the most sophisticated scientific view was the 'nature of models.' The least sophisticated scientific view was 'multiple models.' (2) Among the eight atomic models, the most mentioned model was the atomic nucleus model, and the least mentioned model was the three states of matter. (3) Among the correlations between the five dimensions, the dimension of 'testing models' was highly related to the dimension of 'changing models.' In short, this study examined the views of scientific models based on the atomic units of physics textbooks to identify the emphasized and disregarded views in the textbooks. The findings suggest how future textbooks and curriculum can provide a thorough view of scientific models to enhance students' model-based learning.

Keywords: atomic models, textbooks, science education, scientific model

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Authors: Norshazmira Mat Azmi, Sayidal El Fatimah Masnan, Shatirah Akib

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Boundless renewable energy, such as tidal energy, tidal current energy, wave energy, thermal energy and chemical energy are covered and possessed by oceans. The hybrid system helps in improving the economic and environmental sustainability of renewable energy systems to fulfill the energy demand. The objective and concept of hybridizing renewable energy is to meet the desired system requirements, with the lowest value of the energy cost. This paper reviews applications of using hybrid power generation system for remote area. It also highlights the future directions to investigate the impacts of surface waves on turbine design and performance. The importance of understanding the site-specific wave conditions could also been explored.

Keywords: hybrid, marine current energy, tidal turbine, wave turbine

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Authors: Zahid Ullah, Atlas Khan

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This abstract focuses on the advancements in mathematical modeling and optimization techniques that play a crucial role in enhancing the efficiency, reliability, and performance of these systems. In this era of rapidly evolving technology, mathematical modeling and optimization offer powerful tools to tackle the complex challenges faced by control, signal processing, and energy systems. This abstract presents the latest research and developments in mathematical methodologies, encompassing areas such as control theory, system identification, signal processing algorithms, and energy optimization. The abstract highlights the interdisciplinary nature of mathematical modeling and optimization, showcasing their applications in a wide range of domains, including power systems, communication networks, industrial automation, and renewable energy. It explores key mathematical techniques, such as linear and nonlinear programming, convex optimization, stochastic modeling, and numerical algorithms, that enable the design, analysis, and optimization of complex control and signal processing systems. Furthermore, the abstract emphasizes the importance of addressing real-world challenges in control, signal processing, and energy systems through innovative mathematical approaches. It discusses the integration of mathematical models with data-driven approaches, machine learning, and artificial intelligence to enhance system performance, adaptability, and decision-making capabilities. The abstract also underscores the significance of bridging the gap between theoretical advancements and practical applications. It recognizes the need for practical implementation of mathematical models and optimization algorithms in real-world systems, considering factors such as scalability, computational efficiency, and robustness. In summary, this abstract showcases the advancements in mathematical modeling and optimization techniques for control, signal processing, and energy systems. It highlights the interdisciplinary nature of these techniques, their applications across various domains, and their potential to address real-world challenges. The abstract emphasizes the importance of practical implementation and integration with emerging technologies to drive innovation and improve the performance of control, signal processing, and energy.

Keywords: mathematical modeling, optimization, control systems, signal processing, energy systems, interdisciplinary applications, system identification, numerical algorithms

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Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

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To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: building energy prediction, data mining, demand response, electricity market

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Authors: Zakariya B. H., Idris M. I., Jungudo M. A.

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High energy consumptions of urban settlements in Nigeria are escalating due to strong population growth and migration as a result of crises. The demand for lighting, heating, ventilation and air conditioning (LHVAC) is becoming higher. Conversely, there is a poor electricity supply to both rural and urban settlement in Nigeria. Generators were mostly used in Nigeria as a source of energy for LHVAC. Energy efficiency can be defined as any measure taken to reduce the amount of energy consumed for heating ventilation and air-conditioning (HVAC), and house hold appliances like computers, stoves, refrigerators, televisions etc. The aim of the study was to minimize energy consumption in building through the integration of energy efficiency and renewable energy in building sector. Some of the energy efficient buildings within the study area were identified, the study covers there major cities of Nigeria namely, Abuja, Kaduna and Lagos city. The cost of investment on the energy efficiency and renewable energy was determined and compared with other fossil energy source for conventional building. Findings revealed that the low energy and energy efficient buildings in Nigeria are cheaper than the conventional ones. Based on the finding of the research, construction stake holders are strongly encouraged to abandon the conventional buildings and consider energy efficiency and renewable energy in buildings.

Keywords: energy, efficiency, LHVAC, sustainable development

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Authors: Hayriye Anıl, Görkem Kar

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In addition to being rich in renewable energy resources, Turkey is one of the countries that promise potential in geothermal energy production with its high installed power, cheapness, and sustainability. Increasing imbalance penalties become an economic burden for organizations since geothermal generation plants cannot maintain the balance of supply and demand due to the inadequacy of the production forecasts given in the day-ahead market. A better production forecast reduces the imbalance penalties of market participants and provides a better imbalance in the day ahead market. In this study, using machine learning, deep learning, and, time series methods, the total generation of the power plants belonging to Zorlu Natural Electricity Generation, which has a high installed capacity in terms of geothermal, was estimated for the first one and two weeks of March, then the imbalance penalties were calculated with these estimates and compared with the real values. These modeling operations were carried out on two datasets, the basic dataset and the dataset created by extracting new features from this dataset with the feature engineering method. According to the results, Support Vector Regression from traditional machine learning models outperformed other models and exhibited the best performance. In addition, the estimation results in the feature engineering dataset showed lower error rates than the basic dataset. It has been concluded that the estimated imbalance penalty calculated for the selected organization is lower than the actual imbalance penalty, optimum and profitable accounts.

Keywords: machine learning, deep learning, time series models, feature engineering, geothermal energy production forecasting

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Authors: Shafique Qadir Memon, Muhammad Safar Mirjat, Abdul Quadir Mughal, Nadeem Amjad

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The aims of this study were to determine direct input energy and indirect energy in maize production, to evaluate the inputs energy consumption and outputs energy gained for maize production in Islamabad, Pakistan for spring 2013. Results showed that grain yield was maximum under deep tillage as compared to conventional and zero tillage. Total energy input/output were maximum in deep tillage as compared to conventional tillage while lowest in zero tillage, net energy gain were found maximum under deep tillage.

Keywords: tillage, energy, grain yield, net energy gain

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Authors: Gyula I. Tóth, Shaho Abdalla

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Even though numerical simulations indeed have a significant precursory/supportive role in exploring the disordered phase displaying no long-range order in pattern formation models, studying the stability properties of this phase and determining the order of the ordered-disordered phase transition in these models necessitate an analytical description of the disordered phase. First, we will present the results of a comprehensive statistical analysis of a large number (1,000-10,000) of numerical simulations in the Swift-Hohenberg model, where the bulk disordered (or amorphous) phase is stable. We will show that the average free energy density (over configurations) converges, while the variance of the energy density vanishes with increasing system size in numerical simulations, which suggest that the disordered phase is a thermodynamic phase (i.e., its properties are independent of the configuration in the macroscopic limit). Furthermore, the structural analysis of this phase in the Fourier space suggests that the phase can be modeled by a colored isotropic Gaussian noise, where any instant of the noise describes a possible configuration. Based on these results, we developed the general mathematical framework of finding a pool of solutions to partial differential equations in the sense of continuous probability measure, which we will present briefly. Applying the general idea to the Swift-Hohenberg model we show, that the amorphous phase can be found, and its properties can be determined analytically. As the general mathematical framework is not restricted to continuum theories, we hope that the proposed methodology will open a new chapter in studying disordered phases.

Keywords: fundamental theory, mathematical physics, continuum models, analytical description

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Authors: S. Kreitlein, N. Eder, J. Franke

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The importance of energy efficiency within the production process increases steadily. Unfortunately, so far no tools for a comprehensive assessment of energy efficiency within the production process exist. Therefore the Institute for Factory Automation and Production Systems of the Friedrich-Alexander-University Erlangen-Nuremberg has developed two methods with the goal of achieving transparency and a quantitative assessment of energy efficiency: EEV (Energy Efficiency Value) and EPE (Energetic Process Efficiency). This paper describes the basics and state of the art as well as the developed approaches.

Keywords: energy efficiency, energy efficiency value, energetic process efficiency, production

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Authors: Nachtane Mourad, Tarfaoui Mostapha, Saifaoui Dennoun, El Moumen Ahmed

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The current energy policy recommends the subject of energy efficiency and to phase out fossil energy as a master question for the prospective years. The kingdom requires restructuring its power equipment by improving the percentage of renewable energy supply and optimizing power systems and storage. Developing energy efficiency, therefore, obliges as a consubstantial objection to reducing energy consumption. The objective of this work is to show the energy transition in Morocco towards renewable energies, in particular, to show the great potential of renewable marine energies in Morocco, This goes back to the advantages of cost and non-pollution in addition to that of the independence of fossil energies. Bearing in mind the necessity of the balance of the Moroccan energy mix, hydraulic and thermal power plants have also been installed which will be added to the power stations already established as a prospect for a balanced network that is flexible to fluctuate demand.

Keywords: renewable marine energy, energy transition, efficiency energy, renewable energy

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Authors: Evelyn Nwamaka Ogbeide-Osaretin, Bright Orhewere

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This study examined the role of the population in the linkage between energy consumption and economic development in Nigeria. Time series data on energy consumption, population, and economic development were used for the period 1995 to 2020. The Autoregressive Distributed Lag -Error Correction Model (ARDL-ECM) was engaged. Economic development had a negative substantial impact on energy consumption in the long run. Population growth had a positive significant effect on energy consumption. Government expenditure was also found to impact the level of energy consumption, while energy consumption is not a function of oil price in Nigeria.

Keywords: dynamic analysis, energy consumption, population, economic development, Nigeria

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Authors: S. Balubaid, M. Z. Abd Majid, R. Zakaria

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Energy efficiency is one of the most important issues for green buildings and their sustainability. This is not only due to the environmental impacts, but also because of significantly high energy cost. The aim of this study is to identify the potential actions required for toll plaza that lead to energy reduction. The data were obtained through set of questionnaire and interviewing targeted respondents, including the employees at toll plaza, and architects and engineers who are directly involved in design of highway projects. The data was analyzed using descriptive statistics analysis method. The findings of this study are the critical elements that influence the energy usage and factors that lead to energy wastage. Finally, potential actions are recommended to reduce energy consumption in toll plazas.

Keywords: energy efficiency, toll plaza, energy consumption

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Authors: Jackson Niyongabo

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This study addresses a notable gap in the existing literature on the relationship between energy consumption, economic growth, and CO₂ emissions, particularly within the African context. While numerous studies have explored these dynamics globally and regionally across various development levels, few have delved into the nuances of regions and income levels specific to African countries. Furthermore, the evaluation of the interplay between green growth policies, green energy technologies, and their impact on environmental quality has been underexplored. This research aims to fill these gaps by conducting a comprehensive analysis of the transition from conventional economic growth and energy consumption to a paradigm of green growth coupled with green energy utilization across the African continent from 1980 to 2018. The study is structured into three main parts: an empirical examination of the long-term effects of energy intensity, renewable energy consumption, and economic growth on CO₂ emissions across diverse African regions and income levels; an estimation of the long-term impact of green growth and green energy use on CO₂ emissions for countries implementing green policies within Africa, as well as at regional and global levels; and a comparative analysis of the impact of green growth policies on environmental degradation before and after implementation. Employing advanced econometric methods and panel estimators, the study utilizes a testing framework, panel unit tests, and various estimators to derive meaningful insights. The anticipated results and conclusions will be elucidated through causality tests, impulse response, and variance decomposition analyses, contributing valuable knowledge to the discourse on sustainable development in the African context.

Keywords: economic growth, green growth, energy consumption, CO₂ emissions, econometric models, green energy

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Authors: Dimitrios I. Tselentis, Simon P. Washington

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Considerable literature has been focused over the last few decades on forecasting the consumer demand of Energy Efficient Vehicles (EEVs). These methodological issues range from how to capture recent purchase decisions in revealed choice studies and how to set up experiments in stated preference (SP) studies, and choice of analysis method for analyzing such data. This paper reviews the plethora of published studies on the field of forecasting demand of EEVs since 1980, and provides a review and annotated bibliography of that literature as it pertains to this particular demand forecasting problem. This detailed review addresses the literature not only to Transportation studies, but specifically to the problem and methodologies around forecasting to the time horizons of planning studies which may represent 10 to 20 year forecasts. The objectives of the paper are to identify where existing gaps in literature exist and to articulate where promising methodologies might guide longer term forecasting. One of the key findings of this review is that there are many common techniques used both in the field of new product demand forecasting and the field of predicting future demand for EEV. Apart from SP and RP methods, some of these new techniques that have emerged in the literature in the last few decades are survey related approaches, product diffusion models, time-series modelling, computational intelligence models and other holistic approaches.

Keywords: demand forecasting, Energy Efficient Vehicles (EEVs), forecasting methodologies review, methodological approaches

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Authors: Young Min Kim, Dong Gil Shin, Assmelash Assefa Negash

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This study describes the application of a single loop organic Rankine cycle (ORC) for recovering waste heat from an excavator. In the case of waste heat recovery of the excavator, the heat of hydraulic oil can be used in the ORC system together with the other waste heat sources including the exhaust gas and engine coolant. The performances of four different cases of single loop ORC systems were studied at the main operating condition, and critical design factors are studied to get the maximum power output from the given waste heat sources. The energy and exergy analysis of the cycles are performed concerning the available heat source to determine the best fluid and system configuration. The analysis demonstrates that the ORC in the excavator increases 14% of the net power output at the main operating condition with a simpler system configuration at a lower expander inlet temperature than in a conventional vehicle engine without the heat of the hydraulic oil.

Keywords: engine, excavator, hydraulic oil, organic Rankine cycle (ORC), waste heat recovery

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Authors: Okorowo Cyril Agochi

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More than ever human activity relating to uncontrolled greenhouse gas (GHG) and its effects on the earth is gaining greater attention in the global academic and policy discussions. Activities of man has greatly influenced climate change over the years as a result of consistent increase in the use of fossil fuel energy. Scientists and researchers globally are making significant and devoted efforts towards the development and implementation of renewable energy technologies that are harmless to the environment. One of such energy is solar energy with its source from the sun. There are currently two primary ways of harvesting this energy from the sun: through photovoltaic (PV) panels and through thermal collectors. This work discuses solar energy the abundant renewable energy in the tropical Nigeria, processes of harvesting and recommends same as an alternative means of electric power generation in a time the demand for power supersedes supply.

Keywords: electric, power, renewable energy, solar energy, sun, tropical

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Authors: Samuel Fekadu A., Esayas Alemayehu B., Bultum Oljira D., Seid Tiku D., Dessalegn Dadi D., Bart Van Der Bruggen A.

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The peroxi-photoelectrocoagulation process was evaluated for the removal of chemical oxygen demand (COD) and color from healthcare wastewater. A 2-level full factorial design with center points was created to investigate the effect of the process parameters, i.e., initial COD, H₂O₂, pH, reaction time and current density. Furthermore, the total energy consumption and average current efficiency in the system were evaluated. Predictive models for % COD, % color removal and energy consumption were obtained. The initial COD and pH were found to be the most significant variables in the reduction of COD and color in peroxi-photoelectrocoagulation process. Hydrogen peroxide only has a significant effect on the treated wastewater when combined with other input variables in the process like pH, reaction time and current density. In the peroxi-photoelectrocoagulation process, current density appears not as a single effect but rather as an interaction effect with H₂O₂ in reducing COD and color. Lower energy expenditure was observed at higher initial COD, shorter reaction time and lower current density. The average current efficiency was found as low as 13 % and as high as 777 %. Overall, the study showed that hybrid electrochemical oxidation can be applied effectively and efficiently for the removal of pollutants from healthcare wastewater.

Keywords: electrochemical oxidation, UV, healthcare pollutants removals, factorial design

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Authors: Abdelghafour Galadi

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In this paper, accurate power MOSFET models including quasi-saturation effect are presented. These models have no internal node voltages determined by the circuit simulator and use one JFET or one depletion mode MOSFET transistors controlled by an “effective” gate voltage taking into account the quasi-saturation effect. The proposed models achieve accurate simulation results with an average error percentage less than 9%, which is an improvement of 21 percentage points compared to the commonly used standard power MOSFET model. In addition, the models can be integrated in any available commercial circuit simulators by using their analytical equations. A description of the models will be provided along with the parameter extraction procedure.

Keywords: power MOSFET, drift layer, quasi-saturation effect, SPICE model

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Authors: G. Gurguze, I. Turkoglu

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Today, the developing features of technological tools with limited energy resources have made it necessary to use energy efficiently. Energy management techniques have emerged for this purpose. As with every field, energy management is vital for robots that are being used in many areas from industry to daily life and that are thought to take up more spaces in the future. Particularly, effective power management in autonomous and multi robots, which are getting more complicated and increasing day by day, will improve the performance and success. In this study, robot management algorithms, usage of renewable and hybrid energy sources, robot motion patterns, robot designs, sharing strategies of workloads in multiple robots, road and mission planning algorithms are discussed for efficient use of energy resources by mobile robots. These techniques have been evaluated in terms of efficient use of existing energy resources and energy management in robots.

Keywords: energy management, mobile robot, robot administration, robot management, robot planning

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Authors: W. Schellong

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Industry accounts for one-third of global final energy demand. Crossover technologies (e.g. motors, pumps, process heat, and air conditioning) play an important role in improving energy efficiency. These technologies are used in many applications independent of the production branch. Especially electrical power is used by drives, pumps, compressors, and lightning. The paper demonstrates the algorithm of the energy analysis by some selected case studies for typical industrial processes. The energy analysis represents an essential part of energy management systems (EMS). Generally, process control system (PCS) can support EMS. They provide information about the production process, and they organize the maintenance actions. Combining these tools into an integrated process allows the development of an energy critical equipment strategy. Thus, asset and energy management can use the same common data to improve the energy efficiency.

Keywords: crossover technologies, data management, energy analysis, energy efficiency, process control

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Authors: Ayman Aboelkassem, Mohamoud Ali, Rezq Diab

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This project aims to document and preserve boat models which were discovered in the Saqqara by Czech Institute of Egyptology archeological mission at Saqqara (GEM numbers, 46007, 46008, 46009). These boat models dates back to Egyptian Old Kingdom and have been transferred to the Conservation Center of the Grand Egyptian Museum, to be displayed at the new museum.The project objectives making such boat models more visible to visitors through the use of 3D reconstructed models and high resolution photos which describe the history of using the boats during the Ancient Egyptian history. Especially, The Grand Egyptian Museum is going to exhibit the second boat of King Khufu from Old kingdom. The project goals are to document the boat models and arrange an exhibition, where such Models going to be displayed next to the Khufu Second Boat. The project shows the importance of using boats in Ancient Egypt, and connecting their usage through Ancient Egyptian periods till now. The boat models had a unique Symbolized in ancient Egypt and connect the public with their kings. The Egyptian kings allowed high ranked employees to put boat models in their tombs which has a great meaning that they hope to fellow their kings in the journey of the afterlife.

Keywords: archaeology, boat models, 3D digital tools for heritage management, museums

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Authors: Suparman

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Piecewise linear regression models are very flexible models for modeling the data. If the piecewise linear regression models are matched against the data, then the parameters are generally not known. This paper studies the problem of parameter estimation of piecewise linear regression models. The method used to estimate the parameters of picewise linear regression models is Bayesian method. But the Bayes estimator can not be found analytically. To overcome these problems, the reversible jump MCMC algorithm is proposed. Reversible jump MCMC algorithm generates the Markov chain converges to the limit distribution of the posterior distribution of the parameters of picewise linear regression models. The resulting Markov chain is used to calculate the Bayes estimator for the parameters of picewise linear regression models.

Keywords: regression, piecewise, Bayesian, reversible Jump MCMC

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Authors: Pattra Pukdeekiat, Siriluk Ruangrungrote

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This work was originated to precisely determine direct solar radiation by using atmospheric physics models since the accurate prediction of solar radiation is necessary and useful for solar energy applications including atmospheric research. The possible models and techniques for a calculation of regional direct solar radiation were challenging and compulsory for the case of unavailable instrumental measurement. The investigation was mathematically governed by six astronomical parameters i.e. declination (δ), hour angle (ω), solar time, solar zenith angle (θz), extraterrestrial radiation (Iso) and eccentricity (E0) along with two atmospheric parameters i.e. air mass (mr) and dew point temperature at Bangna meteorological station (13.67° N, 100.61° E) in Bangkok, Thailand. Analyses of five models of solar radiation determination with the assumption of clear sky were applied accompanied by three statistical tests: Mean Bias Difference (MBD), Root Mean Square Difference (RMSD) and Coefficient of determination (R2) in order to validate the accuracy of obtainable results. The calculated direct solar radiation was in a range of 491-505 Watt/m2 with relative percentage error 8.41% for winter and 532-540 Watt/m2 with relative percentage error 4.89% for summer 2014. Additionally, dataset of seven continuous days, representing both seasons were considered with the MBD, RMSD and R2 of -0.08, 0.25, 0.86 and -0.14, 0.35, 3.29, respectively, which belong to Kumar model for winter and CSR model for summer. In summary, the determination of direct solar radiation based on atmospheric models and empirical equations could advantageously provide immediate and reliable values of the solar components for any site in the region without a constraint of actual measurement.

Keywords: atmospheric physics models, astronomical parameters, atmospheric parameters, clear sky condition

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Authors: Mehdi Rostamzadeh

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Genetic Algorithms (GAs) are an adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. In this study, we apply GAs for fundamental and technical models of exchange rate determination in exchange rate market. In this framework, we estimated absolute and relative purchasing power parity, Mundell-Fleming, sticky and flexible prices (monetary models), equilibrium exchange rate and portfolio balance model as fundamental models and Auto Regressive (AR), Moving Average (MA), Auto-Regressive with Moving Average (ARMA) and Mean Reversion (MR) as technical models for Iranian Rial against European Union’s Euro using monthly data from January 1992 to December 2014. Then, we put these models into the genetic algorithm system for measuring their optimal weight for each model. These optimal weights have been measured according to four criteria i.e. R-Squared (R2), mean square error (MSE), mean absolute percentage error (MAPE) and root mean square error (RMSE).Based on obtained Results, it seems that for explaining of Iranian Rial against EU Euro exchange rate behavior, fundamental models are better than technical models.

Keywords: exchange rate, genetic algorithm, fundamental models, technical models

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Authors: Kwame B. O. Amoah

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This paper focuses on retrofitting an old existing office building to a net-zero energy building (NZEB). An existing small office building in Melbourne, Florida, was chosen as a case study to integrate state-of-the-art design strategies and energy-efficient building systems to improve building performance and reduce energy consumption. The study aimed to explore possible ways to maximize energy savings and renewable energy generation sources to cover the building's remaining energy needs necessary to achieve net-zero energy goals. A series of retrofit options were reviewed and adopted with some significant additional decision considerations. Detailed processes and considerations leading to zero energy are well documented in this study, with lessons learned adequately outlined. Based on building energy simulations, multiple design considerations were investigated, such as emerging state-of-the-art technologies, material selection, improvements to the building envelope, optimization of the HVAC, lighting systems, and occupancy loads analysis, as well as the application of renewable energy sources. The comparative analysis of simulation results was used to determine how specific techniques led to energy saving and cost reductions. The research results indicate this small office building can meet net-zero energy use after appropriate design manipulations and renewable energy sources.

Keywords: energy consumption, building energy analysis, energy retrofits, energy-efficiency

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Authors: Fatih Tarlak

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Predictive microbiology can be considered as an important field in food microbiology in which it uses predictive models to describe the microbial growth in different food products. Predictive models estimate the growth of microorganisms quickly, efficiently, and in a cost-effective way as compared to traditional methods of enumeration, which are long-lasting, expensive, and time-consuming. The mathematical models used in predictive microbiology are mainly categorised as primary and secondary models. The primary models are the mathematical equations that define the growth data as a function of time under a constant environmental condition. The secondary models describe the effects of environmental factors, such as temperature, pH, and water activity (aw) on the parameters of the primary models, including the maximum specific growth rate and lag phase duration, which are the most critical growth kinetic parameters. The combination of primary and secondary models provides valuable information to set limits for the quantitative detection of the microbial spoilage and assess product shelf-life.

Keywords: shelf-life, growth model, predictive microbiology, simulation

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Authors: Eduardo Rodrigues, Gisela Mendes, José M. Torres, José E. Sousa

Abstract:

In the sequence of the liberalisation of the electricity sector a progressive engagement of consumers has been considered and targeted by sector regulatory policies. With the objective of promoting market competition while protecting consumers interests, by transferring some of the upstream benefits to the end users while reaching a fair distribution of system costs, different market models to value consumers’ demand flexibility at the energy community level are envisioned. Local Energy and Flexibility Markets (LEFM) involve stakeholders interested in providing or procure local flexibility for community, services and markets’ value. Under the scope of DOMINOES, a European research project supported by Horizon 2020, the local market concept developed is expected to: • Enable consumers/prosumers empowerment, by allowing them to value their demand flexibility and Distributed Energy Resources (DER); • Value local liquid flexibility to support innovative distribution grid management, e.g., local balancing and congestion management, voltage control and grid restoration; • Ease the wholesale market uptake of DER, namely small-scale flexible loads aggregation as Virtual Power Plants (VPPs), facilitating Demand Response (DR) service provision; • Optimise the management and local sharing of Renewable Energy Sources (RES) in Medium Voltage (MV) and Low Voltage (LV) grids, trough energy transactions within an energy community; • Enhance the development of energy markets through innovative business models, compatible with ongoing policy developments, that promote the easy access of retailers and other service providers to the local markets, allowing them to take advantage of communities’ flexibility to optimise their portfolio and subsequently their participation in external markets. The general concept proposed foresees a flow of market actions, technical validations, subsequent deliveries of energy and/or flexibility and balance settlements. Since the market operation should be dynamic and capable of addressing different requests, either prioritising balancing and prosumer services or system’s operation, direct procurement of flexibility within the local market must also be considered. This paper aims to highlight the research on the definition of suitable DR models to be used by the Distribution System Operator (DSO), in case of technical needs, and by the retailer, mainly for portfolio optimisation and solve unbalances. The models to be proposed and implemented within relevant smart distribution grid and microgrid validation environments, are focused on day-ahead and intraday operation scenarios, for predictive management and near-real-time control respectively under the DSO’s perspective. At local level, the DSO will be able to procure flexibility in advance to tackle different grid constrains (e.g., demand peaks, forecasted voltage and current problems and maintenance works), or during the operating day-to-day, to answer unpredictable constraints (e.g., outages, frequency deviations and voltage problems). Due to the inherent risks of their active market participation retailers may resort to DR models to manage their portfolio, by optimising their market actions and solve unbalances. The interaction among the market actors involved in the DR activation and in flexibility exchange is explained by a set of sequence diagrams for the DR modes of use from the DSO and the energy provider perspectives. • DR for DSO’s predictive management – before the operating day; • DR for DSO’s real-time control – during the operating day; • DR for retailer’s day-ahead operation; • DR for retailer’s intraday operation.

Keywords: demand response, energy communities, flexible demand, local energy and flexibility markets

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