Search results for: estimation of electricity
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2877

Search results for: estimation of electricity

2517 Estimation of Synchronous Machine Synchronizing and Damping Torque Coefficients

Authors: Khaled M. EL-Naggar

Abstract:

Synchronizing and damping torque coefficients of a synchronous machine can give a quite clear picture for machine behavior during transients. These coefficients are used as a power system transient stability measurement. In this paper, a crow search optimization algorithm is presented and implemented to study the power system stability during transients. The algorithm makes use of the machine responses to perform the stability study in time domain. The problem is formulated as a dynamic estimation problem. An objective function that minimizes the error square in the estimated coefficients is designed. The method is tested using practical system with different study cases. Results are reported and a thorough discussion is presented. The study illustrates that the proposed method can estimate the stability coefficients for the critical stable cases where other methods may fail. The tests proved that the proposed tool is an accurate and reliable tool for estimating the machine coefficients for assessment of power system stability.

Keywords: optimization, estimation, synchronous, machine, crow search

Procedia PDF Downloads 140
2516 Global Solar Irradiance: Data Imputation to Analyze Complementarity Studies of Energy in Colombia

Authors: Jeisson A. Estrella, Laura C. Herrera, Cristian A. Arenas

Abstract:

The Colombian electricity sector has been transforming through the insertion of new energy sources to generate electricity, one of them being solar energy, which is being promoted by companies interested in photovoltaic technology. The study of this technology is important for electricity generation in general and for the planning of the sector from the perspective of energy complementarity. Precisely in this last approach is where the project is located; we are interested in answering the concerns about the reliability of the electrical system when climatic phenomena such as El Niño occur or in defining whether it is viable to replace or expand thermoelectric plants. Reliability of the electrical system when climatic phenomena such as El Niño occur, or to define whether it is viable to replace or expand thermoelectric plants with renewable electricity generation systems. In this regard, some difficulties related to the basic information on renewable energy sources from measured data must first be solved, as these come from automatic weather stations. Basic information on renewable energy sources from measured data, since these come from automatic weather stations administered by the Institute of Hydrology, Meteorology and Environmental Studies (IDEAM) and, in the range of study (2005-2019), have significant amounts of missing data. For this reason, the overall objective of the project is to complete the global solar irradiance datasets to obtain time series to develop energy complementarity analyses in a subsequent project. Global solar irradiance data sets to obtain time series that will allow the elaboration of energy complementarity analyses in the following project. The filling of the databases will be done through numerical and statistical methods, which are basic techniques for undergraduate students in technical areas who are starting out as researchers technical areas who are starting out as researchers.

Keywords: time series, global solar irradiance, imputed data, energy complementarity

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2515 A Simulation-Based Method for Evaluation of Energy System Cooperation between Pulp and Paper Mills and a District Heating System: A Case Study

Authors: Alexander Hedlund, Anna-Karin Stengard, Olof Björkqvist

Abstract:

A step towards reducing greenhouse gases and energy consumption is to collaborate with the energy system between several industries. This work is based on a case study on integration of pulp and paper mills with a district heating system in Sundsvall, Sweden. Present research shows that it is possible to make a significant reduction in the electricity demand in the mechanical pulping process. However, the profitability of the efficiency measures could be an issue, as the excess steam recovered from the refiners decreases with the electricity consumption. A consequence will be that the fuel demand for steam production will increase. If the fuel price is similar to the electricity price it would reduce the profit of such a project. If the paper mill can be integrated with a district heating system, it is possible to upgrade excess heat from a nearby kraft pulp mill to process steam via the district heating system in order to avoid the additional fuel need. The concept is investigated by using a simulation model describing both the mass and energy balance as well as the operating margin. Three scenarios were analyzed: reference, electricity reduction and energy substitution. The simulation show that the total input to the system is lowest in the Energy substitution scenario. Additionally, in the Energy substitution scenario the steam from the incineration boiler covers not only the steam shortage but also a part of the steam produced using the biofuel boiler, the cooling tower connected to the incineration boiler is no longer needed and the excess heat can cover the whole district heating load during the whole year. The study shows a substantial economic advantage if all stakeholders act together as one system. However, costs and benefits are unequally shared between the actors. This means that there is a need for new business models in order to share the system costs and benefits.

Keywords: energy system, cooperation, simulation method, excess heat, district heating

Procedia PDF Downloads 226
2514 Sustainable Electricity Generation Mix for Kenya from 2015 to 2035

Authors: Alex Maina, Mwenda Makathimo, Adwek George, Charles Opiyo

Abstract:

This research entails the simulation of three possible power scenarios for Kenya from 2015 to 2035 using the Low Emissions Analysis Platform (LEAP). These scenarios represent the unfolding future electricity generation that will fully satisfy the demand while considering the following: energy security, power generation cost and impacts on the environment. These scenarios are Reference Scenario (RS), Nuclear Scenario (NS) and More Renewable Scenario (MRS). The findings obtained reveals that the most sustainable scenario while comparing the costs was found to be the coal scenario with a Net Present Value (NPV) of $30,052.67 million though it has the highest Green House Gases (GHGs) emissions. However, the More Renewable Scenario (MRS) had the least GHGs emissions but was found to be a most expensive scenario to implement with an NPV of $30,733.07 million.

Keywords: energy security, Kenya, low emissions analysis platform, net-present value, greenhouse gases

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2513 Empirical Model for the Estimation of Global Solar Radiation on Horizontal Surface in Algeria

Authors: Malika Fekih, Abdenour Bourabaa, Rafika Hariti, Mohamed Saighi

Abstract:

In Algeria the global solar radiation and its components is not available for all locations due to which there is a requirement of using different models for the estimation of global solar radiation that use climatological parameters of the locations. Empirical constants for these models have been estimated and the results obtained have been tested statistically. The results show encouraging agreement between estimated and measured values.

Keywords: global solar radiation, empirical model, semi arid areas, climatological parameters

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2512 Tenants Use Less Input on Rented Plots: Evidence from Northern Ethiopia

Authors: Desta Brhanu Gebrehiwot

Abstract:

The study aims to investigate the impact of land tenure arrangements on fertilizer use per hectare in Northern Ethiopia. Household and Plot level data are used for analysis. Land tenure contracts such as sharecropping and fixed rent arrangements have endogeneity. Different unobservable characteristics may affect renting-out decisions. Thus, the appropriate method of analysis was the instrumental variable estimation technic. Therefore, the family of instrumental variable estimation methods two-stage least-squares regression (2SLS, the generalized method of moments (GMM), Limited information maximum likelihood (LIML), and instrumental variable Tobit (IV-Tobit) was used. Besides, a method to handle a binary endogenous variable is applied, which uses a two-step estimation. In the first step probit model includes instruments, and in the second step, maximum likelihood estimation (MLE) (“etregress” command in Stata 14) was used. There was lower fertilizer use per hectare on sharecropped and fixed rented plots relative to owner-operated. The result supports the Marshallian inefficiency principle in sharecropping. The difference in fertilizer use per hectare could be explained by a lack of incentivized detailed contract forms, such as giving more proportion of the output to the tenant under sharecropping contracts, which motivates to use of more fertilizer in rented plots to maximize the production because most sharecropping arrangements share output equally between tenants and landlords.

Keywords: tenure-contracts, endogeneity, plot-level data, Ethiopia, fertilizer

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2511 Runoff Estimation in the Khiyav River Basin by Using the SCS_ CN Model

Authors: F. Esfandyari Darabad, Z. Samadi

Abstract:

The volume of runoff caused by rainfall in the river basin has enticed the researchers in the fields of the water management resources. In this study, first of the hydrological data such as the rainfall and discharge of the Khiyav river basin of Meshkin city in the northwest of Iran collected and then the process of analyzing and reconstructing has been completed. The soil conservation service (scs) has developed a method for calculating the runoff, in which is based on the curve number specification (CN). This research implemented the following model in the Khiyav river basin of Meshkin city by the GIS techniques and concluded the following fact in which represents the usage of weight model in calculating the curve numbers that provides the possibility for the all efficient factors which is contributing to the runoff creation such as; the geometric characteristics of the basin, the basin soil characteristics, vegetation, geology, climate and human factors to be considered, so an accurate estimation of runoff from precipitation to be achieved as the result. The findings also exposed the accident-prone areas in the output of the Khiyav river basin so it was revealed that the Khiyav river basin embodies a high potential for the flood creation.

Keywords: curve number, khiyav river basin, runoff estimation, SCS

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2510 Comparative Study on Daily Discharge Estimation of Soolegan River

Authors: Redvan Ghasemlounia, Elham Ansari, Hikmet Kerem Cigizoglu

Abstract:

Hydrological modeling in arid and semi-arid regions is very important. Iran has many regions with these climate conditions such as Chaharmahal and Bakhtiari province that needs lots of attention with an appropriate management. Forecasting of hydrological parameters and estimation of hydrological events of catchments, provide important information that used for design, management and operation of water resources such as river systems, and dams, widely. Discharge in rivers is one of these parameters. This study presents the application and comparison of some estimation methods such as Feed-Forward Back Propagation Neural Network (FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) to predict the daily flow discharge of the Soolegan River, located at Chaharmahal and Bakhtiari province, in Iran. In this study, Soolegan, station was considered. This Station is located in Soolegan River at 51° 14՜ Latitude 31° 38՜ longitude at North Karoon basin. The Soolegan station is 2086 meters higher than sea level. The data used in this study are daily discharge and daily precipitation of Soolegan station. Feed Forward Back Propagation Neural Network(FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) models were developed using the same input parameters for Soolegan's daily discharge estimation. The results of estimation models were compared with observed discharge values to evaluate performance of the developed models. Results of all methods were compared and shown in tables and charts.

Keywords: ANN, multi linear regression, Bayesian network, forecasting, discharge, gene expression programming

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2509 Evolution of Germany’s Feed-in Tariff Policy

Authors: Gaafar Muhammed, N. T. Ersoy

Abstract:

The role of electricity in the economic development of any country is undeniable. The main goal of utilizing renewable sources in electricity generation, especially in the emerging countries, is to improve electricity access, economic development and energy sustainability. Germany’s recent transition from conventional to renewable energy technologies is overwhelming, this might not be associated with its abundant natural resources but owing to the policies in place. In line with the fast economic and technological developments recorded in recent years, Germany currently produces approximately 1059 GW of its energy from renewable sources. Hence, at the end of 2016, Germany is among the world leaders in terms of installed renewable energy capacity. As one of the most important factors that lead to renewable energy utilization in any nation is an effective policy, this study aims at examining the effect of policies on renewable energy (RE) development in Germany. Also, the study will focus on the evolution of the adopted feed-in tariff policies, as this evolution has affected the renewable energy capacity in Germany over a period of 15 years (2000 to 2015). The main contribution of the study is to establish a link between the feed-in tariff and the increase of RE in Germany’s energy mix. This is done by analyzing the characteristics of various feed-in tariff mechanisms adopted through the years. These characteristics include the feed-in-tariff rate, degression, special conditions, supported technology, etc. Then, the renewable energy development in Germany has been analyzed through the years along with the targets and the progress in reaching these targets. The study reveals that Germany’s renewable energy support policies (especially feed-in tariff) lead to several benefits and contribute towards the targets existing for renewable energy.

Keywords: feed-in tariff, Germany, policy, penewable energy

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2508 Tourism Area Development Optimation Based on Solar-Generated Renewable Energy Technology at Karimunjawa, Central Java Province, Indonesia

Authors: Yanuar Tri Wahyu Saputra, Ramadhani Pamapta Putra

Abstract:

Karimunjawa is one among Indonesian islands which is lacking of electricity supply. Despite condition above, Karimunjawa is an important tourism object in Indonesia's Central Java Province. Solar Power Plant is a potential technology to be applied in Karimunjawa, in order to fulfill the island's electrical supply need and to increase daily life and tourism quality among tourists and local population. This optimation modeling of Karimunjawa uses HOMER software program. The data we uses include wind speed data in Karimunjawa from BMKG (Indonesian Agency for Meteorology, Climatology and Geophysics), annual weather data in Karimunjawa from NASA, electricity requirements assumption data based on number of houses and business infrastructures in Karimunjawa. This modeling aims to choose which three system categories offer the highest financial profit with the lowest total Net Present Cost (NPC). The first category uses only PV with 8000 kW of electrical power and NPC value of $6.830.701. The second category uses hybrid system which involves both 1000 kW PV and 100 kW generator which results in total NPC of $6.865.590. The last category uses only generator with 750 kW of electrical power that results in total NPC of $ 16.368.197, the highest total NPC among the three categories. Based on the analysis above, we can conclude that the most optimal way to fulfill the electricity needs in Karimunjawa is to use 8000 kW PV with lower maintenance cost.

Keywords: Karimunjawa, renewable energy, solar power plant, HOMER

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2507 Parameter Estimation in Dynamical Systems Based on Latent Variables

Authors: Arcady Ponosov

Abstract:

A novel mathematical approach is suggested, which facilitates a compressed representation and efficient validation of parameter-rich ordinary differential equation models describing the dynamics of complex, especially biology-related, systems and which is based on identification of the system's latent variables. In particular, an efficient parameter estimation method for the compressed non-linear dynamical systems is developed. The method is applied to the so-called 'power-law systems' being non-linear differential equations typically used in Biochemical System Theory.

Keywords: generalized law of mass action, metamodels, principal components, synergetic systems

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2506 Foil Bearing Stiffness Estimation with Pseudospectral Scheme

Authors: Balaji Sankar, Sadanand Kulkarni

Abstract:

Compliant foil gas lubricated bearings are used for the support of light loads in the order of few kilograms at high speeds, in the order of 50,000 RPM. The stiffness of the foil bearings depends both on the stiffness of the compliant foil and on the lubricating gas film. The stiffness of the bearings plays a crucial role in the stable operation of the supported rotor over a range of speeds. This paper describes a numerical approach to estimate the stiffness of the bearings using pseudo spectral scheme. Methodology to obtain the stiffness of the foil bearing as a function of weight of the shaft is given and the results are presented.

Keywords: foil bearing, simulation, numerical, stiffness estimation

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2505 Mobile Smart Application Proposal for Predicting Calories in Food

Authors: Marcos Valdez Alexander Junior, Igor Aguilar-Alonso

Abstract:

Malnutrition is the root of different diseases that universally affect everyone, diseases such as obesity and malnutrition. The objective of this research is to predict the calories of the food to be eaten, developing a smart mobile application to show the user if a meal is balanced. Due to the large percentage of obesity and malnutrition in Peru, the present work is carried out. The development of the intelligent application is proposed with a three-layer architecture, and for the prediction of the nutritional value of the food, the use of pre-trained models based on convolutional neural networks is proposed.

Keywords: volume estimation, calorie estimation, artificial vision, food nutrition

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2504 Optimization and Operation of Charging and Discharging Stations for Hybrid Cars and their Effects on the Electricity Distribution Network

Authors: Ali Heydarimoghim

Abstract:

In this paper, the optimal placement of charging and discharging stations is done to determine the location and capacity of the stations, reducing the cost of electric vehicle owners' losses, reducing the cost of distribution system losses, and reducing the costs associated with the stations. Also, observing the permissible limits of the bus voltage and the capacity of the stations and their distance are considered as constraints of the problem. Given the traffic situation in different areas of a city, we estimate the amount of energy required to charge and the amount of energy provided to discharge electric vehicles in each area. We then introduce the electricity distribution system of the city in question. Following are the scenarios for introducing the problem and introducing the objective and constraint functions. Finally, the simulation results for different scenarios are compared.

Keywords: charging & discharging stations, hybrid vehicles, optimization, replacement

Procedia PDF Downloads 138
2503 An Assessment of Wind Energy in Sanar Village in North of Iran Using Weibull Function

Authors: Ehsanolah Assareh, Mojtaba Biglari, Mojtaba Nedaei

Abstract:

Sanar village in north of Iran is a remote region with difficult access to electricity, grid and water supply. Thus the aim of this research is to evaluate the potential of wind as a power source either for electricity generation or for water pumping. In this study the statistical analysis has been performed by Weibull distribution function. The results show that the Weibull distribution has fitted the wind data very well. Also it has been demonstrated that wind speed at 40 m height is ranged from 1.75 m/s in Dec to 3.28 m/s in Aug with average value of 2.69 m/s. In this research, different wind speed characteristics such as turbulence intensity, wind direction, monthly air temperature, humidity wind power density and other related parameters have been investigated. Finally it was concluded that the wind energy in the Sanar village may be explored by employing modern wind turbines that require very lower start-up speeds.

Keywords: wind energy, wind turbine, weibull, Sanar village, Iran

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2502 Evaluation of Dual Polarization Rainfall Estimation Algorithm Applicability in Korea: A Case Study on Biseulsan Radar

Authors: Chulsang Yoo, Gildo Kim

Abstract:

Dual polarization radar provides comprehensive information about rainfall by measuring multiple parameters. In Korea, for the rainfall estimation, JPOLE and CSU-HIDRO algorithms are generally used. This study evaluated the local applicability of JPOLE and CSU-HIDRO algorithms in Korea by using the observed rainfall data collected on August, 2014 by the Biseulsan dual polarization radar data and KMA AWS. A total of 11,372 pairs of radar-ground rain rate data were classified according to thresholds of synthetic algorithms into suitable and unsuitable data. Then, evaluation criteria were derived by comparing radar rain rate and ground rain rate, respectively, for entire, suitable, unsuitable data. The results are as follows: (1) The radar rain rate equation including KDP, was found better in the rainfall estimation than the other equations for both JPOLE and CSU-HIDRO algorithms. The thresholds were found to be adequately applied for both algorithms including specific differential phase. (2) The radar rain rate equation including horizontal reflectivity and differential reflectivity were found poor compared to the others. The result was not improved even when only the suitable data were applied. Acknowledgments: This work was supported by the Basic Science Research Program through the National Research Foundation of Korea, funded by the Ministry of Education (NRF-2013R1A1A2011012).

Keywords: CSU-HIDRO algorithm, dual polarization radar, JPOLE algorithm, radar rainfall estimation algorithm

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2501 Improved Distance Estimation in Dynamic Environments through Multi-Sensor Fusion with Extended Kalman Filter

Authors: Iffat Ara Ebu, Fahmida Islam, Mohammad Abdus Shahid Rafi, Mahfuzur Rahman, Umar Iqbal, John Ball

Abstract:

The application of multi-sensor fusion for enhanced distance estimation accuracy in dynamic environments is crucial for advanced driver assistance systems (ADAS) and autonomous vehicles. Limitations of single sensors such as cameras or radar in adverse conditions motivate the use of combined camera and radar data to improve reliability, adaptability, and object recognition. A multi-sensor fusion approach using an extended Kalman filter (EKF) is proposed to combine sensor measurements with a dynamic system model, achieving robust and accurate distance estimation. The research utilizes the Mississippi State University Autonomous Vehicular Simulator (MAVS) to create a controlled environment for data collection. Data analysis is performed using MATLAB. Qualitative (visualization of fused data vs ground truth) and quantitative metrics (RMSE, MAE) are employed for performance assessment. Initial results with simulated data demonstrate accurate distance estimation compared to individual sensors. The optimal sensor measurement noise variance and plant noise variance parameters within the EKF are identified, and the algorithm is validated with real-world data from a Chevrolet Blazer. In summary, this research demonstrates that multi-sensor fusion with an EKF significantly improves distance estimation accuracy in dynamic environments. This is supported by comprehensive evaluation metrics, with validation transitioning from simulated to real-world data, paving the way for safer and more reliable autonomous vehicle control.

Keywords: sensor fusion, EKF, MATLAB, MAVS, autonomous vehicle, ADAS

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2500 Biomass Carbon Credit Estimation for Sustainable Urban Planning and Micro-climate Assessment

Authors: R. Niranchana, K. Meena Alias Jeyanthi

Abstract:

As a result of the present climate change dilemma, the energy balancing strategy is to construct a sustainable environment has become a top concern for researchers worldwide. The environment itself has always been a solution from the earliest days of human evolution. Carbon capture begins with its accurate estimation and monitoring credit inventories, and its efficient use. Sustainable urban planning with deliverables of re-use energy models might benefit from assessment methods like biomass carbon credit ranking. The term "biomass energy" refers to the various ways in which living organisms can potentially be converted into a source of energy. The approaches that can be applied to biomass and an algorithm for evaluating carbon credits are presented in this paper. The micro-climate evaluation using Computational Fluid dynamics was carried out across the location (1 km x1 km) at Dindigul, India (10°24'58.68" North, 77°54.1.80 East). Sustainable Urban design must be carried out considering environmental and physiological convection, conduction, radiation and evaporative heat exchange due to proceeding solar access and wind intensities.

Keywords: biomass, climate assessment, urban planning, multi-regression, carbon estimation algorithm

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2499 Material Choice Driving Sustainability of 3D Printing

Authors: Jeremy Faludi, Zhongyin Hu, Shahd Alrashed, Christopher Braunholz, Suneesh Kaul, Leulekal Kassaye

Abstract:

Environmental impacts of six 3D printers using various materials were compared to determine if material choice drove sustainability, or if other factors such as machine type, machine size, or machine utilization dominate. Cradle-to-grave life-cycle assessments were performed, comparing a commercial-scale FDM machine printing in ABS plastic, a desktop FDM machine printing in ABS, a desktop FDM machine printing in PET and PLA plastics, a polyjet machine printing in its proprietary polymer, an SLA machine printing in its polymer, and an inkjet machine hacked to print in salt and dextrose. All scenarios were scored using ReCiPe Endpoint H methodology to combine multiple impact categories, comparing environmental impacts per part made for several scenarios per machine. Results showed that most printers’ ecological impacts were dominated by electricity use, not materials, and the changes in electricity use due to different plastics was not significant compared to variation from one machine to another. Variation in machine idle time determined impacts per part most strongly. However, material impacts were quite important for the inkjet printer hacked to print in salt: In its optimal scenario, it had up to 1/38th the impacts coreper part as the worst-performing machine in the same scenario. If salt parts were infused with epoxy to make them more physically robust, then much of this advantage disappeared, and material impacts actually dominated or equaled electricity use. Future studies should also measure DMLS and SLS processes / materials.

Keywords: 3D printing, additive manufacturing, sustainability, life-cycle assessment, design for environment

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2498 Switched System Diagnosis Based on Intelligent State Filtering with Unknown Models

Authors: Nada Slimane, Foued Theljani, Faouzi Bouani

Abstract:

The paper addresses the problem of fault diagnosis for systems operating in several modes (normal or faulty) based on states assessment. We use, for this purpose, a methodology consisting of three main processes: 1) sequential data clustering, 2) linear model regression and 3) state filtering. Typically, Kalman Filter (KF) is an algorithm that provides estimation of unknown states using a sequence of I/O measurements. Inevitably, although it is an efficient technique for state estimation, it presents two main weaknesses. First, it merely predicts states without being able to isolate/classify them according to their different operating modes, whether normal or faulty modes. To deal with this dilemma, the KF is endowed with an extra clustering step based fully on sequential version of the k-means algorithm. Second, to provide state estimation, KF requires state space models, which can be unknown. A linear regularized regression is used to identify the required models. To prove its effectiveness, the proposed approach is assessed on a simulated benchmark.

Keywords: clustering, diagnosis, Kalman Filtering, k-means, regularized regression

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2497 Fuel Cells Not Only for Cars: Technological Development in Railways

Authors: Marita Pigłowska, Beata Kurc, Paweł Daszkiewicz

Abstract:

Railway vehicles are divided into two groups: traction (powered) vehicles and wagons. The traction vehicles include locomotives (line and shunting), railcars (sometimes referred to as railbuses), and multiple units (electric and diesel), consisting of several or a dozen carriages. In vehicles with diesel traction, fuel energy (petrol, diesel, or compressed gas) is converted into mechanical energy directly in the internal combustion engine or via electricity. In the latter case, the combustion engine generator produces electricity that is then used to drive the vehicle (diesel-electric drive or electric transmission). In Poland, such a solution dominates both in heavy linear and shunting locomotives. The classic diesel drive is available for the lightest shunting locomotives, railcars, and passenger diesel multiple units. Vehicles with electric traction do not have their own source of energy -they use pantographs to obtain electricity from the traction network. To determine the competitiveness of the hydrogen propulsion system, it is essential to understand how it works. The basic elements of the construction of a railway vehicle drive system that uses hydrogen as a source of traction force are fuel cells, batteries, fuel tanks, traction motors as well as main and auxiliary converters. The compressed hydrogen is stored in tanks usually located on the roof of the vehicle. This resource is supplemented with the use of specialized infrastructure while the vehicle is stationary. Hydrogen is supplied to the fuel cell, where it oxidizes. The effect of this chemical reaction is electricity and water (in two forms -liquid and water vapor). Electricity is stored in batteries (so far, lithium-ion batteries are used). Electricity stored in this way is used to drive traction motors and supply onboard equipment. The current generated by the fuel cell passes through the main converter, whose task is to adjust it to the values required by the consumers, i.e., batteries and the traction motor. The work will attempt to construct a fuel cell with unique electrodes. This research is a trend that connects industry with science. The first goal will be to obtain hydrogen on a large scale in tube furnaces, to thoroughly analyze the obtained structures (IR), and to apply the method in fuel cells. The second goal is to create low-energy energy storage and distribution station for hydrogen and electric vehicles. The scope of the research includes obtaining a carbon variety and obtaining oxide systems on a large scale using a tubular furnace and then supplying vehicles. Acknowledgments: This work is supported by the Polish Ministry of Science and Education, project "The best of the best! 4.0", number 0911/MNSW/4968 – M.P. and grant 0911/SBAD/2102—B.K.

Keywords: railway, hydrogen, fuel cells, hybrid vehicles

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2496 Microbial Fuel Cells and Their Applications in Electricity Generating and Wastewater Treatment

Authors: Shima Fasahat

Abstract:

This research is an experimental research which was done about microbial fuel cells in order to study them for electricity generating and wastewater treatment. These days, it is very important to find new, clean and sustainable ways for energy supplying. Because of this reason there are many researchers around the world who are studying about new and sustainable energies. There are different ways to produce these kind of energies like: solar cells, wind turbines, geothermal energy, fuel cells and many other ways. Fuel cells have different types one of these types is microbial fuel cell. In this research, an MFC was built in order to study how it can be used for electricity generating and wastewater treatment. The microbial fuel cell which was used in this research is a reactor that has two tanks with a catalyst solution. The chemical reaction in microbial fuel cells is a redox reaction. The microbial fuel cell in this research is a two chamber MFC. Anode chamber is an anaerobic one (ABR reactor) and the other chamber is a cathode chamber. Anode chamber consists of stabilized sludge which is the source of microorganisms that do redox reaction. The main microorganisms here are: Propionibacterium and Clostridium. The electrodes of anode chamber are graphite pages. Cathode chamber consists of graphite page electrodes and catalysts like: O2, KMnO4 and C6N6FeK4. The membrane which separates the chambers is Nafion117. The reason of choosing this membrane is explained in the complete paper. The main goal of this research is to generate electricity and treating wastewater. It was found that when you use electron receptor compounds like: O2, MnO4, C6N6FeK4 the velocity of electron receiving speeds up and in a less time more current will be achieved. It was found that the best compounds for this purpose are compounds which have iron in their chemical formula. It is also important to pay attention to the amount of nutrients which enters to bacteria chamber. By adding extra nutrients in some cases the result will be reverse.  By using ABR the amount of chemical oxidation demand reduces per day till it arrives to a stable amount.

Keywords: anaerobic baffled reactor, bioenergy, electrode, energy efficient, microbial fuel cell, renewable chemicals, sustainable

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2495 Fuel Economy of Electrical Energy in the City Bus during Japanese Test Procedure

Authors: Piotr Kacejko, Lukasz Grabowski, Zdzislaw Kaminski

Abstract:

This paper discusses a model of fuel consumption and on-board electricity generation. Rapid changes in speed result in a constantly changing kinetic energy accumulated in a bus mass and an increased fuel consumption due to hardly recuperated kinetic energy. The model is based on the results achieved from chassis dynamometer, airport and city street researches. The verified model was applied to simulate the on-board electricity generation during the Japanese JE05 Emission Test Cycle. The simulations were performed for several values of vehicle mass and electrical load applied to on-board devices. The research results show that driving dynamics has an impact on a consumption of fuel to drive alternators.

Keywords: city bus, heavy duty vehicle, Japanese JE05 test cycle, power generation

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2494 Assessment of On-Site Solar and Wind Energy at a Manufacturing Facility in Ireland

Authors: A. Sgobba, C. Meskell

Abstract:

The feasibility of on-site electricity production from solar and wind and the resulting load management for a specific manufacturing plant in Ireland are assessed. The industry sector accounts directly and indirectly for a high percentage of electricity consumption and global greenhouse gas emissions; therefore, it will play a key role in emission reduction and control. Manufacturing plants, in particular, are often located in non-residential areas since they require open spaces for production machinery, parking facilities for the employees, appropriate routes for supply and delivery, special connections to the national grid and other environmental impacts. Since they have larger spaces compared to commercial sites in urban areas, they represent an appropriate case study for evaluating the technical and economic viability of energy system integration with low power density technologies, such as solar and wind, for on-site electricity generation. The available open space surrounding the analysed manufacturing plant can be efficiently used to produce a discrete quantity of energy, instantaneously and locally consumed. Therefore, transmission and distribution losses can be reduced. The usage of storage is not required due to the high and almost constant electricity consumption profile. The energy load of the plant is identified through the analysis of gas and electricity consumption, both internally monitored and reported on the bills. These data are not often recorded and available to third parties since manufacturing companies usually keep track only of the overall energy expenditures. The solar potential is modelled for a period of 21 years based on global horizontal irradiation data; the hourly direct and diffuse radiation and the energy produced by the system at the optimum pitch angle are calculated. The model is validated using PVWatts and SAM tools. Wind speed data are available for the same period within one-hour step at a height of 10m. Since the hub of a typical wind turbine reaches a higher altitude, complementary data for a different location at 50m have been compared, and a model for the estimate of wind speed at the required height in the right location is defined. Weibull Statistical Distribution is used to evaluate the wind energy potential of the site. The results show that solar and wind energy are, as expected, generally decoupled. Based on the real case study, the percentage of load covered every hour by on-site generation (Level of Autonomy LA) and the resulting electricity bought from the grid (Expected Energy Not Supplied EENS) are calculated. The economic viability of the project is assessed through Net Present Value, and the influence the main technical and economic parameters have on NPV is presented. Since the results show that the analysed renewable sources can not provide enough electricity, the integration with a cogeneration technology is studied. Finally, the benefit to energy system integration of wind, solar and a cogeneration technology is evaluated and discussed.

Keywords: demand, energy system integration, load, manufacturing, national grid, renewable energy sources

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2493 The Generalized Pareto Distribution as a Model for Sequential Order Statistics

Authors: Mahdy ‎Esmailian, Mahdi ‎Doostparast, Ahmad ‎Parsian

Abstract:

‎In this article‎, ‎sequential order statistics (SOS) censoring type II samples coming from the generalized Pareto distribution are considered‎. ‎Maximum likelihood (ML) estimators of the unknown parameters are derived on the basis of the available multiple SOS data‎. ‎Necessary conditions for existence and uniqueness of the derived ML estimates are given‎. Due to complexity in the proposed likelihood function‎, ‎a useful re-parametrization is suggested‎. ‎For illustrative purposes‎, ‎a Monte Carlo simulation study is conducted and an illustrative example is analysed‎.

Keywords: bayesian estimation‎, generalized pareto distribution‎, ‎maximum likelihood estimation‎, sequential order statistics

Procedia PDF Downloads 509
2492 Comparison of Fuel Cell Installation Methods at Large Commercial and Industrial Sites

Authors: Masood Sattari

Abstract:

Using fuel cell technology to generate electricity for large commercial and industrial sites is a growing segment in the fuel cell industry. The installation of these systems involves design, permitting, procurement of long-lead electrical equipment, and construction involving multiple utilities. The installation of each fuel cell system requires the same amount of coordination as the construction of a new structure requiring a foundation, gas, water, and electricity. Each of these components provide variables that can delay and possibly eliminate a new project. As the manufacturing process and efficiency of fuel cell systems improves, so must the installation methods to prevent a ‘bottle-neck’ in the installation phase of the deployment. Installation methodologies to install the systems vary among companies and this paper will examine the methodologies, describe the benefits and drawbacks for each, and provide guideline for the industry to improve overall installation efficiency.

Keywords: construction, installation, methodology, procurement

Procedia PDF Downloads 196
2491 A Feasibility Study of Replacing High Pressure Mercury Vapor and Sodium Vapor Lamp Street Lighting Bulbs with LEDs in Turkish Republic of Northern Cyprus

Authors: Olusola Olorunfemi Bamisile, Mustafa Dagbasi, Serkan Abbasoglu

Abstract:

Feasibility of an Energy Audit program is the main aim of this paper. LEDs are used to replace Sodium Vapor lamps and High Pressured Mercury Vapor lamps that are currently used for the street lighting system in Turkish Republic of Northern Cyprus. 44% of the fossil fuels imported into Turkish Republic of Northern Cyprus are used for electricity generation which makes the reduction in the consumption of electricity very important. This project will save as much as 40,206,210 kWh on site annually and 121,837,000 kWh can be saved from source. The economic environmental and fossil fuels saving of this project is also evaluated.

Keywords: energy conservation management, LEDs, sodium vapor, high pressure mercury vapor, life cycle costing

Procedia PDF Downloads 466
2490 Ranking of Optimal Materials for Building Walls from the Perspective of Cost and Waste of Electricity and Gas Energy Using AHP-TOPSIS 1 Technique: Study Example: Sari City

Authors: Seyedomid Fatemi

Abstract:

The walls of the building, as the main intermediary between the outside and the inside of the building, play an important role in controlling the environmental conditions and ensuring the comfort of the residents, thus reducing the heating and cooling loads. Therefore, the use of suitable materials is considered one of the simplest and most effective ways to reduce the heating and cooling loads of the building, which will also save energy. Therefore, in order to achieve the goal of the research "Ranking of optimal materials for building walls," optimal materials for building walls in a temperate and humid climate (case example: Sari city) from the perspective of embodied energy, waste of electricity and gas energy, cost and reuse been investigated to achieve sustainable architecture. In this regard, using information obtained from Sari Municipality, design components have been presented by experts using the Delphi method. Considering the criteria of experts' opinions (cost and reuse), the amount of embodied energy of the materials, as well as the amount of waste of electricity and gas of different materials of the walls, with the help of the AHP weighting technique and finally with the TOPSIS technique, the best type of materials in the order of 1- 3-D Panel 2-ICF-, 3-Cement block with pumice, 4-Wallcrete block, 5-Clay block, 6-Autoclaved Aerated Concrete (AAC), 7-Foam cement block, 8-Aquapanel and 9-Reinforced concrete wall for use in The walls of the buildings were proposed in Sari city.

Keywords: optimum materials, building walls, moderate and humid climate, sustainable architecture, AHP-TOPSIS technique

Procedia PDF Downloads 77
2489 Techno-Economic Assessment of Distributed Heat Pumps Integration within a Swedish Neighborhood: A Cosimulation Approach

Authors: Monica Arnaudo, Monika Topel, Bjorn Laumert

Abstract:

Within the Swedish context, the current trend of relatively low electricity prices promotes the electrification of the energy infrastructure. The residential heating sector takes part in this transition by proposing a switch from a centralized district heating system towards a distributed heat pumps-based setting. When it comes to urban environments, two issues arise. The first, seen from an electricity-sector perspective, is related to the fact that existing networks are limited with regards to their installed capacities. Additional electric loads, such as heat pumps, can cause severe overloads on crucial network elements. The second, seen from a heating-sector perspective, has to do with the fact that the indoor comfort conditions can become difficult to handle when the operation of the heat pumps is limited by a risk of overloading on the distribution grid. Furthermore, the uncertainty of the electricity market prices in the future introduces an additional variable. This study aims at assessing the extent to which distributed heat pumps can penetrate an existing heat energy network while respecting the technical limitations of the electricity grid and the thermal comfort levels in the buildings. In order to account for the multi-disciplinary nature of this research question, a cosimulation modeling approach was adopted. In this way, each energy technology is modeled in its customized simulation environment. As part of the cosimulation methodology: a steady-state power flow analysis in pandapower was used for modeling the electrical distribution grid, a thermal balance model of a reference building was implemented in EnergyPlus to account for space heating and a fluid-cycle model of a heat pump was implemented in JModelica to account for the actual heating technology. With the models set in place, different scenarios based on forecasted electricity market prices were developed both for present and future conditions of Hammarby Sjöstad, a neighborhood located in the south-east of Stockholm (Sweden). For each scenario, the technical and the comfort conditions were assessed. Additionally, the average cost of heat generation was estimated in terms of levelized cost of heat. This indicator enables a techno-economic comparison study among the different scenarios. In order to evaluate the levelized cost of heat, a yearly performance simulation of the energy infrastructure was implemented. The scenarios related to the current electricity prices show that distributed heat pumps can replace the district heating system by covering up to 30% of the heating demand. By lowering of 2°C, the minimum accepted indoor temperature of the apartments, this level of penetration can increase up to 40%. Within the future scenarios, if the electricity prices will increase, as most likely expected within the next decade, the penetration of distributed heat pumps can be limited to 15%. In terms of levelized cost of heat, a residential heat pump technology becomes competitive only within a scenario of decreasing electricity prices. In this case, a district heating system is characterized by an average cost of heat generation 7% higher compared to a distributed heat pumps option.

Keywords: cosimulation, distributed heat pumps, district heating, electrical distribution grid, integrated energy systems

Procedia PDF Downloads 150
2488 Construction Unit Rate Factor Modelling Using Neural Networks

Authors: Balimu Mwiya, Mundia Muya, Chabota Kaliba, Peter Mukalula

Abstract:

Factors affecting construction unit cost vary depending on a country’s political, economic, social and technological inclinations. Factors affecting construction costs have been studied from various perspectives. Analysis of cost factors requires an appreciation of a country’s practices. Identified cost factors provide an indication of a country’s construction economic strata. The purpose of this paper is to identify the essential factors that affect unit cost estimation and their breakdown using artificial neural networks. Twenty-five (25) identified cost factors in road construction were subjected to a questionnaire survey and employing SPSS factor analysis the factors were reduced to eight. The 8 factors were analysed using the neural network (NN) to determine the proportionate breakdown of the cost factors in a given construction unit rate. NN predicted that political environment accounted 44% of the unit rate followed by contractor capacity at 22% and financial delays, project feasibility, overhead and profit each at 11%. Project location, material availability and corruption perception index had minimal impact on the unit cost from the training data provided. Quantified cost factors can be incorporated in unit cost estimation models (UCEM) to produce more accurate estimates. This can create improvements in the cost estimation of infrastructure projects and establish a benchmark standard to assist the process of alignment of work practises and training of new staff, permitting the on-going development of best practises in cost estimation to become more effective.

Keywords: construction cost factors, neural networks, roadworks, Zambian construction industry

Procedia PDF Downloads 364