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Добірка наукової літератури з теми "Electric power-plants Load Computer simulation"

Автор: Grafiati

Опубліковано: 10 грудня 2022

Оновлено: 29 січня 2023

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Статті в журналах з теми "Electric power-plants Load Computer simulation"

Alia Jasim Mohammed. "AN APPRAISAL OF THE TRANSIENT RESPONSE OF A D.C. SHUMT MOTOR USING MATLAB/SIMULINK UNDER NO LOADING AND FULL LOADING CONDITIONS." Diyala Journal of Engineering Sciences 4, no. 2 (December 1, 2011): 130–40. http://dx.doi.org/10.24237/djes.2011.04210.

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Electric machines are used to generate electrical power in power plants and provide mechanical work in industries. This paper describes the MATLAB/SIMULINK realization of the performance of a D.C. shunt motor and introduces model power components to use computer simulation as a tool for conducting transient by using Simulink and SimPower System. These simulation models were employed to calculate the speed (N), torque (T), armature current (Ia), input and output power (Pin and Pout), losses (Plosses) and efficiency (η) for the motor at no load and load conditions. The results obtained using MATLAB were compared with the practical results, the ratio of error is about (1-2) % was found. The SIMULINK was written in MATLAB languages version (6.5).

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Artsiomenka, K. I. "Structural-and-Parametric Optimization of Automatic Control System for Power Units of 300 MW in Wide Range of Load Variations." ENERGETIKA. Proceedings of CIS higher education institutions and power engineering associations 62, no. 5 (October 4, 2019): 469–81. http://dx.doi.org/10.21122/1029-7448-2019-62-5-469-481.

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The structural-parametric optimization of the automatic control system for power units (ACSPU) of 300 MW of Lukoml’skaya GRES (Lukoml Local Condensing Power Plant) in the mode of both the permanent and the variable superheated steam pressure upstream of the turbine is under consideration. During 1974–1979, eight units of the Lukoml’skaya GRES implemented the ACSPU with a leading boiler power control. At the moment, these systems no longer meet all the frequency control quality requirements. In 2016, the daily schedule of electric loads of the Belarusian power system was as follows: the basic part of the schedule of electric loads was covered by combined heat and power plants (CHP) and by mini-CHP (which are the least maneuverable of the power plants), the semi-peak part of it–by local condensing power plants (Lukoml’skaya GRES and Berezovskaya GRES), the peak part–by import electric energy from neighboring power systems. However, this year the first unit of the Belorussian NPP will be put into operation, while the second one–in 2020. After the launch of the Belorussian NPP, it will cover basic part of load curve; CPPs will cover the semi-peak part, while the peak part of load curve will be covered by local condensing power plants. Correspondingly, due to the alteration of the structure of daily schedule of electric loads of the Belarusian power system, it is necessary to improve the efficiency of power units of Lukoml’skaya GRES as well as of the entire Lukoml’skaya GRES in general. This can be achieved with the help of the method of parametric optimization of the typical ACSPU proposed in the present paper. As a result, the quality of control of power and pressure upstream of the turbine will be improved; the flow of fuel will be reduced, as well as the turbine regulation valve displacement; environmental performance of entire power plant will be improved, too. The proposed technique has been confirmed by the results of computer simulation of transient processes in the automatic control system under external and internal disturbances.

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Siraev, Fanis, and Regina Khazieva. "INVESTIGATION OF A FREQUENCY-REGULATORY ELECTRIC DRIVE WITH ASYNCHRONOUS ELECTRIC MOTOR." Electrical and data processing facilities and systems 18, no. 2 (2022): 45–51. http://dx.doi.org/10.17122/1999-5458-2022-18-2-45-51.

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Relevance AC electric drive is widely used in industry, it reduces power consumption and provides high reliability. It has received its wide distribution due to its high technological characteristics and simplicity of design, which have a positive impact on the introduction into production and modernization. Modeling of the electric drive control system is carried out in order to regulate and improve technological parameters. The assembled model in the Matlab/Simulink program using the SimPowerSystem library allows you to study the efficiency of controlling the electric drive of the pump using a visual model before switching to real objects, thanks to smooth speed control in a wide range of revolutions. Aim of research In this paper, a study is made of a frequency-controlled pump electric drive. During the hours of minimum load of enterprises where this system is used, the load on the device will decrease, since the consumption will be much less. Under loads, the power consumed by the drive can be reduced by changing the motor speed. This is achieved in many ways, but the most relevant is the use of a frequency converter. The main task is computer simulation of a frequency-controlled electric pump drive and the study of simulation results. Research methods In this study, the following methods were used: the study of scientific literature, computer modeling performed in the Matlab/Simulink software package using the SimPowerSystem library. Results The authors carry out a study of a frequency-controlled electric drive of the pump, which implements a reduction in the rotation speed to reduce the power consumed by the electric drive during the hours of minimum load of enterprises. The computer model of the object under study was developed in the Matlab/Simulink software package, the scalar control of the electric drive was evaluated. As a result of the simulation, oscillograms were obtained, where the possibility of reducing power consumption by adjusting the engine speed is clearly visible.

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Yan, Xiangwu, Ling Wang, Zhichao Chai, Shuaishuai Zhao, Zisheng Liu, and Xuewei Sun. "Electric Vehicle Battery Simulation System for Mobile Field Test of Off-Board Charger." Energies 12, no. 15 (August 6, 2019): 3025. http://dx.doi.org/10.3390/en12153025.

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An electric vehicle power battery simulation system simulating different power battery packs for the field test of the off-board charger is designed, which can be used to test the performance of an off-board charger. Specifically, the improved power battery model is combined with the improved lightweight charging load and the online estimation of the state of charge as well as the electromotive force of the battery model are used to adjust charging load parameters in real time to simulate the charging response. An acceleration coefficient is introduced into the traditional battery model to improve test efficiency, and the type, specification, temperature and voltage parameters of the battery can be set online according to the test requirements. An improved charging load scheme is proposed, in which a DC converter cascaded power battery pack of the mobile test vehicle is used to form a lightweight charging load with the mode of constant voltage, constant current, constant power and constant resistance and the ability to be adjusted continuously within the rated range. As a result, the size and weight of the charging load are reduced and the autonomous test of the off-board charger is realized. The performances of the proposed battery simulation system are validated through the various experimental results.

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Vasilyev, N., I. Kalinin, V. Polovinkin, A. Pustoshny, O. Savchenko, and K. Sazonov. "Load simulation of icebreaker propulsion motors at laboratory and virtual tests of electric propulsion systems." Transactions of the Krylov State Research Centre 1, no. 399 (March 15, 2022): 15–30. http://dx.doi.org/10.24937/2542-2324-2022-1-399-15-30.

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Object and purpose of research. This paper discusses ice loads on shaft-lines of icebreakers and ice-going ships as their propellers interact with ice. These loads are needed as inputs for development and fine-tuning of electric propulsion control systems, including those involving load test rigs, with the final purpose of ensuring reliable and safe operation of electric propulsion plants in ice navigation conditions. Materials and methods. This study is based on the publications about ice loads on shafting of electric propulsion plants. It analyses the terminology used in the papers on this subject. It also analyses the data on ice-induced shafting torques, as obtained from full-scale trials of Akademik Tryoshnikov ice-class research vessel. Main results. The paper describes typical cases of extreme ice loads on the propulsion system, with the input data characterizing these loads and needed, in particular, for numerical simulation of ice loads on shafting in order to fine-tune electric propulsion control system by means of computer-based simulations or laboratory tests. The paper shows the importance of considering the inertial elements of the shaft line for correct determination of limit loads. It also formulates the challenges that have to be solved in order to obtain efficient control systems for electric propulsion plants of icebreakers and ice-going ships. It determines the requirements to special full-scale trials needed to validate calculation methods for shafting loads. Conclusion. Electric propulsion systems of ice-going ships must have highly efficient control tools for the propulsion motor that would ensure its reliable and safe operation as propeller interacts with ice. Such a tool is quite hard to obtain because shafting loads are quite various and difficult to predict. One of the ways to improve an electric propulsion system is to build up a test rig with the load part simulating various scenarios of shafting loads as per the mathematical model specially developed for this purpose and validated by the accumulated database of full-scale ice loads on shaft lines. The paper also demonstrates that propulsion motor control system must properly take into account not only external loads but also inertial torques of shaft line, motor rotor and propeller with added water mass.

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Wang, Yikai, Xin Yin, Xianggen Yin, Jian Qiao, and Liming Tan. "A Petri Net-Based Power Supply Recovery Strategy for the Electric Power System of Floating Nuclear Power Plant." Applied Sciences 12, no. 18 (September 8, 2022): 9026. http://dx.doi.org/10.3390/app12189026.

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Floating nuclear power plants contain sensitive loads of nuclear reactors. After equipment faults, fast and efficient power supply recovery should be realized. To realize the unified analysis of system topology and power flow distribution, a power supply recovery strategy based on Petri nets is proposed. Considering that systems of different voltage levels cannot be connected instantaneously, a two-stage power supply recovery mode is adopted. Emergency power supply is put in first, and then the whole network is reconstructed. In the network reconstruction process, load transfer is realized through switching the transformation to redistribute the load of each switchboard and adjust the power output of each power source. Corresponding to the Petri net model, the above process is similar to the dynamic transmission process of a token in each library by firing the transition. Therefore, the topological model of system is constructed based on the Petri net, and a power flow analysis is proposed through its dynamic updating mechanism. The objective function of the network reconstruction is established by integrating load recovery amount, switch operation cost and generator operation efficiency, and the optimal switching state combination scheme that satisfies the system constraints is obtained by the multi-population genetic algorithm (MPGA). Simulation results show that the proposed method can provide complete power supply recovery.

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Kurniawan, Akhmad R., Adi Kurniawan, Sardono Sarwito, Ahlur R. N. Gumilang, and Firman Budianto. "Comparison of voltage drop in AC and DC shipboard electrical power distribution systems: A case study of 17,500 DWT tanker vessel." IOP Conference Series: Earth and Environmental Science 972, no. 1 (January 1, 2022): 012001. http://dx.doi.org/10.1088/1755-1315/972/1/012001.

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Abstract The recent emergence of power electronics equipment raises the possibility of implementation of DC shipboard electrical distribution systems. Several investigations on the effectiveness of DC shipboard electrical power distribution systems have proven that it is more profitable than AC distribution systems both in technical and economical aspect. However, known investigations are still limited to the system in ship with electric propulsion, which the consumption of electric power is enormous. The current study investigates the technical performance of both distribution systems in a non-electric propulsion ship, especially in the aspect of power losses. Both of the original AC distribution systems in a 17,500 DWT tanker ship and its equal DC distribution systems are modelled in a computer simulation program. The electric power flow simulation for both models are performed with the data of electric load during operating conditions, to compare the power losses in the distribution systems. The results show that the DC distribution systems has fewer drop voltage than its AC counterpart.

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Bulatov, Yu N., A. V. Kryukov, and K. V. Suslov. "The study of the isolated power supply system operation with controlled distributed generation plants, energy storage units and drive load." Power engineering: research, equipment, technology 23, no. 5 (January 9, 2022): 184–94. http://dx.doi.org/10.30724/1998-9903-2021-23-5-184-194.

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THE PURPOSE. Investigation of the operating modes of an isolated power supply system with controlled distributed generation plants, energy storage units and a drive load. Determination of the influence of the proposed prognostic controller of a distributed generation plant on the control parameters and quality indicators of the control process under various operating modes of an isolated power supply system.METHODS. The studies were carried out on a computer model of an isolated power supply system of an industrial enterprise with a turbine generator plant, a wind generator plant and a high-power electric storage unit, for which a fuzzy control system and a prognostic controller were used. The simulation was performed in MATLAB using Simulink and SimPowerSystems packages.RESULTS. The article describes a computer model of an isolated power supply system, as well as a structural diagram of the proposed autoprognostic speed controller. The simulation results showed that the combined use of an energy storage unit and an auto-prognostic generator rotor speed controller makes it possible to ensure the stability and survivability of an isolated power supply system, increasing its damping properties. The use of a fuzzy control system of a wind-generating plant made it possible to ensure its stable operation in all considered modes.CONCLUSION. The auto-prognostic speed controller, which does not require special settings, and the energy storage unit provide high quality control indicators in normal and emergency modes. It is advisable to conduct further studies to coordinate the actions of the control system of the electric energy storage unit and the auto-prognostic speed controller of the distributed generation plant.

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Veeramsetty, Venkataramana, Modem Sai Pavan Kumar, and Surender Reddy Salkuti. "Platform-Independent Web Application for Short-Term Electric Power Load Forecasting on 33/11 kV Substation Using Regression Tree." Computers 11, no. 8 (July 29, 2022): 119. http://dx.doi.org/10.3390/computers11080119.

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Short-term electric power load forecasting is a critical and essential task for utilities in the electric power industry for proper energy trading, which enables the independent system operator to operate the network without any technical and economical issues. From an electric power distribution system point of view, accurate load forecasting is essential for proper planning and operation. In order to build most robust machine learning model to forecast the load with a good accuracy irrespective of weather condition and type of day, features such as the season, temperature, humidity and day-status are incorporated into the data. In this paper, a machine learning model, namely a regression tree, is used to forecast the active power load an hour and one day ahead. Real-time active power load data to train and test the machine learning models are collected from a 33/11 kV substation located in Telangana State, India. Based on the simulation results, it is observed that the regression tree model is able to forecast the load with less error.

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Bulatov, Yuri, and Andrey Kryukov. "Study of cyber security of predictive control algorithms for distributed generation plants." Analysis and data processing systems, no. 2 (June 18, 2021): 19–34. http://dx.doi.org/10.17212/2782-2001-2021-2-19-34.

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The power industry is currently actively developing the field related to the use of distributed generation plants located near the power receiving devices of consumers. At the same time, the introduction of distributed generation plants causes a lot of engineering problems which need solutions. One of them is the optimization of the settings of automatic voltage regulators (AVR) and speed regulators (ASR) of synchronous generators in all possible operating modes. This requires the use of complex models of power supply systems, distributed generation plants and their regulators, as well as labor-intensive calculations that take into account a large number of interrelated parameters. However, there is another approach based on the use of predictive controllers. In this case only one parameter is needed for linear predictive models.The article describes a method for constructing and tuning the proposed predictive ASR synchronous generator, as well as computer models of distributed generation plants used in research. The purpose of the research was to determine cyber security of power supply systems equipped with various distributed generation plants with predictive speed controllers that can be implemented on the basis of the microprocessor technology. The studies were carried out in the MATLAB system using the Simulink and SymPowerSystems simulation packages on computer models of distributed generation plants with one turbine generator operating at a dedicated load, as well as a group of hydrogenerators connected to a high-power electric power system. The simulation results showed the effectiveness of the proposed predictive control algorithms, as well as the fact that their cyber security can be increased by introducing hardware restrictions on the range of changes in the time constant of the predictive link.

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Більше джерел

Дисертації з теми "Electric power-plants Load Computer simulation"

Moharari, Nader S. "An electric load forecasting approach using expert systems and artificial neural networks." Diss., Georgia Institute of Technology, 1993. http://hdl.handle.net/1853/13757.

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Conradie, Antonie Eduard. "Performance optimization of engineering systems with particular reference to dry-cooled power plants." Thesis, Link to the online version, 1995. http://hdl.handle.net/10019.1/1326.

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Rader, Jordan D. "Loss of normal feedwater ATWS for Vogtle Electric Generating Plant using RETRAN-02." Thesis, Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/31741.

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Thesis (M. S.)--Nuclear Engineering, Georgia Institute of Technology, 2010.
Committee Chair: Abdel-Khalik, Said I.; Committee Member: Ghiaasiaan, S. Mostafa; Committee Member: Hertel, Nolan E. Part of the SMARTech Electronic Thesis and Dissertation Collection.

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Nigrini, Lucas Bernardo. "Developing a neural network model to predict the electrical load demand in the Mangaung municipal area." Thesis, [Bloemfontein?] : Central University of Technology, Free State, 2012. http://hdl.handle.net/11462/176.

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Thesis (D. Tech. (Engineering: Electric)) -- Central University of technology, 2012
Because power generation relies heavily on electricity demand, consumers are required to wisely manage their loads to consolidate the power utility‟s optimal power generation efforts. Consequently, accurate and reliable electric load forecasting systems are required. Prior to the present situation, there were various forecasting models developed primarily for electric load forecasting. Modelling short term load forecasting using artificial neural networks has recently been proposed by researchers. This project developed a model for short term load forecasting using a neural network. The concept was tested by evaluating the forecasting potential of the basic feedforward and the cascade forward neural network models. The test results showed that the cascade forward model is more efficient for this forecasting investigation. The final model is intended to be a basis for a real forecasting application. The neural model was tested using actual load data of the Bloemfontein reticulation network to predict its load for half an hour in advance. The cascade forward network demonstrates a mean absolute percentage error of less than 5% when tested using four years of utility data. In addition to reporting the summary statistics of the mean absolute percentage error, an alternate method using correlation coefficients for presenting load forecasting performance results are shown. This research proposes that a 6:1:1 cascade forward neural network can be trained with data from a month of a year and forecast the load for the same month of the following year. This research presents a new time series modeling for short term load forecasting, which can model the forecast of the half-hourly loads of weekdays, as well as of weekends and public holidays. Obtained results from extensive testing on the Bloemfontein power system network confirm the validity of the developed forecasting approach. This model can be implemented for on-line testing application to adopt a final view of its usefulness.

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Popoola, Olawale Muhammed. "Adaptive neuro-fuzzy inference system (ANFIS)-based modelling of residential lighting load profile." 2015. http://encore.tut.ac.za/iii/cpro/DigitalItemViewPage.external?sp=1001770.

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D. Tech. Electrical Engineering.
Aims of this study is to develop a residential customers' lighting profile ANFIS-based model. This model is expected to address lighting load usage estimation in relation to the dynamic occupancy presence in a residential dwelling, which will take into account the climatic condition (natural lighting) of such an environment (e.g. South Africa) and its income. The objectives are as follows: 1. Develop an ANFIS-based residential lighting load profile model for middle income, low income and high-income earners. 2. Error reduction in residential lighting demand profile model. Performance evaluation and validation of the model using correlation and trend analysis, regression model, South Africa power utility application lighting program, non-weighted approach and comparison with other research studies (methodology).3. Reduction in / or elimination of repeated models for occupant presence and assumptions that residences are occupied at certain periods. 4. Derive meaning from complexities (behavioural trends) associated with lighting usage and extract patterns in such circumstances.

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Manuel, Grant. "Short term load forecasting by means of neural networks and programmable logic devices for new high electrical energy users." Thesis, 2014. http://hdl.handle.net/10210/10055.

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D.Phil. (Electrical and Electronic Engineering)
Load forecasting is a necessary and an important task for both the electrical consumer and electrical supplier. Whilst many studies emphasize the importance of determining the future demand, few papers address both the forecasting algorithm and computational resources needed to offer a turnkey solution to address the load forecasting problem. The major contribution that, this paper identified is a turnkey load forecasting algorithm. A turnkey forecasting solution is defined by a comprehensive solution that incorporates both the algorithm and processing elements needed to execute the algorithm in the most effective and efficient manner. An electrical consumer, namely the operator of a rapid railway system was faced with a problem of having to forecast the notified network demand and energy consumption. The forecast period was expected to be between a very short term window for maintenance reasons and long term for the requirements warranted by the electrical supplier. The problem was addressed by firstly reviewing the most common forms of load forecasting for which there are two types. These are statistically based methods and methods based upon artificial intelligence. The basic principle of a statistical approach is to approximate or define a curve that best defines the relationship between the load and its parameters. Regression and similar day approach methods use the defined correlation of past values in order to forecast the future behaviour. In other words the future load forecast is forecasted by observing the behaviour of the factors that influenced the load behaviour in the past. The underlying factors that influence the final load may be identified by means of a top down drill down approach. In this way both the load factors and influential variables may be identified. This paper makes use of relevance trees to create a structure of load and influential variables. For a regression forecasting model, the behaviour of the load is modelled according to weather and non-weather variables. The load may be stochastic or deterministic, linear or nonlinear. One of the biggest problems with statistical models is the lack of generality. One model may yield more acceptable results over another model simply because of the sensitivity of the model to one load element that defines the model significantly. Regression type forecast models are an example of this where the elements that define the load are broadly divided into weather and non-weather elements. It is important that the correlation curve reflects the true correlation between the load and its elements. The recursive properties of a statistical based techniques (Kalman filter) allows that the relationship be refined. For methods such as neural networks, the relationship between the load elements that define the future load behaviour is learnt by presenting a series of patterns and then a forecast model is derived. Rigorous mathematical equations are replaced with an artificial neural network where the load curve is learnt. Unlike a statistical based approach (ARMA models), the load does not first need to be defined as a stochastic or deterministic series. In terms of a stochastic approach (non stationery process), the load first would have to be brought to a stationery process. For artificial neural networks, such processes are eliminated and the future forecast is derived faster in terms of a turnkey approach (tested solution). Artificial Neural Networks (ANN) has gained momentum since the eighties. Specifically in the area of forecasting, neural networks have become a common application. In this thesis, data from a railway operator was used to train the neural network and then future data is forecasted. Two embedded processing elements were then evaluated in terms of speed, memory and ability to execute complex mathematical functions (libraries). These were namely a Complex Programmable Logic Device (CPLD) and microcontroller (MCU). The ANN forecasting algorithm was programmed on both a MCU and PLD and compared by means of timing models and hardware platform testing. The most ideal turnkey solution was found to be the ANN algorithm residing on a PLD. The accuracy and speed results surpassed that of a MCU.

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Книги з теми "Electric power-plants Load Computer simulation"

Knowles, J. B. Simulation and control of electrical power stations. Taunton, Somerset, England: Research Studies Press, 1990.

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Szymański, Grzegorz. Symulacja cyfrowa niebezpiecznych oddziaływań stacji i linii wysokich napięć. Poznań: Wydawn. Politechniki Poznańskiej, 1998.

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International Joint Power Generation Conference (1998 Baltimore, Md.). Proceedings of the 1998 International Joint Power Generation Conference: Presented at the 1998 International Joint Power Generation Conference, August 23-26, 1998, Baltimore, Maryland. New York: American Society of Mechanical Engineers, 1998.

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European, Simulation Multiconference (1990 Nuremberg Germany). Simulation in energy systems: One track from the European Simulation Multiconference, June 10-13, 1990, the Atrium Hotel, Nuremberg, Germany. San Diego, Calif: Society for Computer Simulation International, 1990.

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Piazza, Maria Carmela Di. Photovoltaic Sources: Modeling and Emulation. London: Springer London, 2013.

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Damian, Flynn, and Institution of Electrical Engineers, eds. Thermal power plant simulation and control. London: Institution of Electrical Engineers, 2003.

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Sungiae, Cho, Lee Sang-hoon, U.S. Nuclear Regulatory Commission. Office of Nuclear Regulatory Research., Han ơguk Cho llyo k Kongsa., and Han ơguk Wo njaryo k Anjo n Kisurwo n., eds. Assessment of RELAP5/MOD2 computer code against the net load trip test data from Yong-Gwang, unit 2. Washington, DC: Office of Nuclear Regulatory Research, U.S. Nuclear Regulatory Commission, 1993.

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Assessment of RELAP5/MOD2 against a load rejection from 100% to 50% power in the Vandellos II nuclear power plant. Washington, DC: Office of Nuclear Regulatory Research, U.S. Nuclear Regulatory Commission, 1993.

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P, Deschutter, U.S. Nuclear Regulatory Commission. Office of Nuclear Regulatory Research, and TRACTEBEL (Firm), eds. Assessment study of RELAP5/MOD2 cycle 36.04 based on the DOEL-4 manual loss of load test of November 23, 1985. Washington, DC: Office of Nuclear Regulatory Research, U.S. Nuclear Regulatory Commission, 1992.

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L, Dolce James, and United States. National Aeronautics and Space Administration., eds. An expert system for simulating electric loads aboard Space Station Freedom. [Washington, D.C.]: NASA, 1990.

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Частини книг з теми "Electric power-plants Load Computer simulation"

Recioui, Abdelmadjid, and Fatma Zohra Dekhandji. "Implementation of Load Control for Smart Metering in Smart Grids." In Advances in Computer and Electrical Engineering, 119–55. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-4027-5.ch006.

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The conventional energy meters are not suitable for long operating purposes as they spend much human and material resources. Smart meters, on the other hand, are devices that perform advanced functions including electrical energy consumption recording of residential/industrial users, billing, real-time monitoring, and load balancing. In this chapter, a smart home prototype is designed and implemented. Appliances are powered by the grid during daytime, and a photovoltaic panel stored power during the night or in case of an electricity outage. Second, consumed power from both sources is sensed and further processed for cumulative energy, cost calculations and bill establishment for different proposed scenarios using LABVIEW software. Data are communicated using a USB data acquisition card (DAQ-USB 6008). Finally, a simulation framework using LABVIEW software models four houses each equipped with various appliances. The simulator predicts different power consumption profiles to seek of peak-demand reduction through a load control process.

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Anwar, Adnan, Md Apel Mahmud, Md Jahangir Hossain, and Himanshu Roy Pota. "Distributed Generation Capacity Planning for Distribution Networks to Minimize Energy Loss." In Advances in Computer and Electrical Engineering, 76–95. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9911-3.ch005.

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This chapter presents an unbalanced multi-phase optimal power flow (UMOPF) based planning approach to determine the optimum capacities of multiple distributed generation units in a distribution network. An adaptive weight particle swarm optimization algorithm is used to find the global optimum solution. To increase the efficiency of the proposed scheme, a co-simulation platform is developed. Since the proposed method is mainly based on the cost optimization, variations in loads and uncertainties within DG units are also taken into account to perform the analysis. An IEEE 123 node distribution system is used as a test distribution network which is unbalanced and multi-phase in nature, for the validation of the proposed scheme. The superiority of the proposed method is investigated through the comparisons of the results obtained that of a Genetic Algorithm based OPF method. This analysis also shows that the DG capacity planning considering annual load and generation uncertainties outperform the traditional well practised peak-load planning.

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Khan, Baseem, Samuel Degarege, Fsaha Mebrahtu, and Hassan Alhelou. "Energy Storage System and Its Power Electronic Interface." In Research Anthology on Smart Grid and Microgrid Development, 183–95. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-3666-0.ch009.

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This chapter examines the modeling and simulation of energy storage (battery, flywheel, etc.) systems interfaced to the power grid by using power electronic device, like chopper module, Rectifier module, and filter circuits, which are essential to the load balance between supply and demand, and to eliminate harmonics and to ensure efficient, cost effective, and reliable operations. Energy storage system in power grid is the same as memory in computer system. Energy efficiency is a key performance indicator for energy storage system. The energy storage system is the most promising component to enhance the system reliability and flexibility.

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Khan, Baseem, Samuel Degarege, Fsaha Mebrahtu, and Hassan Alhelou. "Energy Storage System and Its Power Electronic Interface." In Handbook of Research on New Solutions and Technologies in Electrical Distribution Networks, 309–21. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1230-2.ch016.

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Alhelou, Hassan Haes. "Fault Detection and Isolation in Power Systems Using Unknown Input Observer." In Advances in Computer and Electrical Engineering, 38–58. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-6989-3.ch002.

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Unknown input observers (UIO) find application in many cases for successful fault detection and isolation (FDI). In this chapter, a scenario where the unknown input observer is applied to load frequency control loops in interconnected power systems is analyzed. A UIO was chosen because load demand is not always constant and it can be considered to introduce an unknown disturbance to the system. Mathematical formulations on how to detect and isolate sensor faults are presented which are then implemented in MATLAB Simulink for simulations. Based on this historical survey on the application of UIO, a thesis on UIO application in FDI in distributed generation is done.

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Jabari, Farkhondeh, Heresh Seyedia, Sajad Najafi Ravadanegh, and Behnam Mohammadi Ivatloo. "Stochastic Contingency Analysis Based on Voltage Stability Assessment in Islanded Power System Considering Load Uncertainty Using MCS and k-PEM." In Advances in Computer and Electrical Engineering, 12–36. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-9911-3.ch002.

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Increased electricity demands and economic operation of large power systems in a deregulated environment with a limited investment in transmission expansion planning causes interconnected power grids to be operated closer to their stability limits. Meanwhile, the loads uncertainty will affect the static and dynamic stabilities. Therefore, if there is no emergency corrective control in time, occurrence of wide area contingency may lead to the catastrophic cascading outages. Studies show that many wide area blackouts which led to massive economic losses may have been prevented by a fast feasible controlled islanding decision making. This chapter introduces a novel computationally efficient approach for separating of bulk power system into several stable sections following a severe disturbance. The splitting strategy reduces the large initial search space to an interface boundary network considering coherency of synchronous generators and network graph simplification. Then, a novel islanding scenario generator algorithm denoted as BEM (Backward Elimination Method) based on PMEAs (Primary Maximum Expansion Areas) has been applied to generate all proper islanding solutions in the simplified network graph. The PPF (Probabilistic Power Flow) based on Newton-Raphson method and Q-V modal analysis has been used to evaluate the steady-state stability of created islands in each generated scenario. BICA (Binary Imperialistic Competitive Algorithm) has then been applied to minimize total load-generation mismatch considering integrity, voltage permitted range and steady-state voltage stability constraints. The best solution has then been applied to split the entire power network. A novel stochastic contingency analysis of islands based on PSVI (Probability of Static Voltage Instability) using MCS (Monte Carlo Simulation) and k-PEM (k-Point Estimate Method) have been proposed to identify the critical PQ buses and severe contingencies. In these approaches, the ITM (Inverse Transform Method) has been used to model uncertain loads with normal probability distribution function in optimal islanded power system. The robustness, effectiveness and capability of the proposed approaches have been validated on the New England 39-bus standard power system.

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Kaliannan, Jagatheesan, Anand Baskaran, and Nilanjan Dey. "Automatic Generation Control of Thermal-Thermal-Hydro Power Systems with PID Controller Using Ant Colony Optimization." In Renewable and Alternative Energy, 761–78. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-1671-2.ch023.

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In this work, Artificial Intelligence (AI) based Ant Colony Optimization (ACO) algorithm is proposed for Load Frequency Control (LFC) of interconnected multi–area hydrothermal power systems. Area 1&2 are thermal power systems and area 3 is a hydro power system, all the areas are interconnected through the appropriate tie-line. Thermal and hydro power plants are applied with reheat turbine and electric governor respectively. Investigated power system initially applied with conventional Proportional-Integral (PI) controller and controller parameters are optimized by using trial and error method considering Integral Time Absolute Error (ITAE) objective function. After that, the system is equipped with Proportional – Integral – Derivative (PID) controller and controller parameters are optimized by using ACO algorithm with ITAE objective function. The superiority of the proposed algorithm has been demonstrated by comparing conventional controller. Finally, The Simulation results of multi-area power system prove the effectiveness of the proposed optimization technique in LFC scheme and show its superiority over conventional PI controller.

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Тези доповідей конференцій з теми "Electric power-plants Load Computer simulation"

Hu, Yelin, Chun Yin, Haigang Zang, Panpan Li, and Zhaoquan Chen. "Simulation on the Application of Electric Spring for Reactive Power Compensation at Load Side." In 2016 International Conference on Intelligent Control and Computer Application (ICCA 2016). Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/icca-16.2016.6.

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Yu, Jian G. "TAROS Computer Simulation Software for DC and AC Traction Power Systems: Methods and Applications." In 2015 Joint Rail Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/jrc2015-5635.

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This paper describes the computer simulation methods for dc traction power systems and ac power traction power systems that have been used to develop the computer simulator TAROS® at Gannett Fleming. The simulator has been designed and developed to support both load flow analysis and fault analysis. The paper also presents some examples of practical applications of the simulator in engineering and design under various operational conditions that may be encountered in transit and rail systems, such as normal, abnormal and fault conditions. Examples include: electric load cycles in various system components for their rating and size selection or verification; distribution of traction return currents in return conductors and ground for electromagnetic interference assessment; touch and step voltage analysis for the design of the traction return system grounding and bonding to meet safety requirements; and fault calculations for relay protection coordination.

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Miyano, Hiroshi, Naoto Sekimura, Masayuki Takizawa, and Masaaki Matsumoto. "Review of Pipe Wall Thinning Mechanism Study and its National Project in Japan." In ASME 2011 Pressure Vessels and Piping Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/pvp2011-58023.

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For nuclear power plants, the four major requirements are 1) high safety, 2) high reliability, 3) economical competitiveness, and 4) minimum environmental impact. However, it is still difficult to completely avoid problems concerning structural materials caused by stress corrosion cracking (SCC) and for piping systems caused by flow accelerated corrosion (FAC) and liquid drop impingement (LDI). Since especially FAC and LDI are uncertain phenomena as pipe wall thinning, there are the piping rupture accident risks on all piping systems under the specific conditions. In Japan, after August 2004, the accident of the secondary pipe rupture in Mihama Power Plant Unit 3, The Kansai Electric Power Co., Inc. (KEPCO), R&D projects on pipe wall thinning phenomena and mechanism have been employed by many organizations. On the other hand, evaluation of the safety and reliability of piping systems of long term operating plants and with the special attention to seismic condition have been requested. It was requested to enable evaluation of pipe wall thinning and its reliability with more accuracy. This project was programmed under the government budget from 2006 to 2010 fiscal year according to the Strategy Load-Map for Ageing Management generated by the society of industry, government and academia [1]. As the milestone for the first half decade of the load-map, the project had these achievements: 1) Establish computer program for FAC simulation, 2) Clarify droplet behavior for LDI prediction, 3) Simplified calculation model of pipe wall thinning for seismic evaluation, 4) Evaluate safety margin of thinned piping by FAC or LDI.

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Ravelli, S., and A. Perdichizzi. "Performance Assessment of an Integrated Gasification Combined Cycle Under Flexible Operation." In ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/gt2018-75198.

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In this paper a simulation tool (Thermoflex®) has been setup to model an entire Integrated Gasification Combined Cycle (IGCC) on the basis of the report entitled “Cost and Performance of PC and IGCC Plants for a Range of Carbon dioxide Capture” by DOE/NETL [1]. The investigated layout has no water-gas-shift (WGS) reactor and does not allow for any CO2 capture. Two gasification islands are included, each of which consists of Air Separation Unit (ASU), GEE radiant-only gasifier, quench and syngas scrubber as well as syngas cleanup. Two advanced GE’s F-class gas turbines (2 × 232 MW), coupled with two heat recovery steam generators and one steam turbine (276 MW) constitute the power block. In the IGCC simulation, the base model of the GE 7F.05 gas turbine has been adapted to burn syngas. Mass and energy balances were carefully computed on design condition to validate the proposed modelling procedure against the IGCC performance data contained in the above mentioned report: the net power output of 622 MW was underestimated by about 5% whereas the net electric efficiency was slightly overpredicted. The off-design behavior of the syngas turbine was then simulated as dependent on ambient temperature and partial load, in preparation for modelling flexible operation of the whole power plant. The variation in IGCC net efficiency and power output was assessed in a load following operational strategy, thus reducing the load factor and varying the number and slope of ramps in a typical day. The IGCC net efficiency goes down from 42.5% to 32.8% when the load is reduced from 100% to 40% of the design rate.

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Wang, Li, Yang Liu, Yun Tai, Yawei Zhang, and Zhenpeng Tang. "Extension of Load Follow Operation of PWRs Without Boron Adjustment." In 2013 21st International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/icone21-15479.

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Due to development of electric power system, the proportion of nuclear power and its needs for Load follow operation have become large. Then there would be higher requirements to the power control ability of the nuclear power system. The project with China’s own brands and using the advanced pressurized water reactor (APWR) nuclear power technology, CPR1000, adopts a control method called Mode G, using G banks, N banks, R bank and soluble boron to perform the load follow control. The common Point Model, widely used in conventional core modeling, cannot successfully research the axial power distribution. But in this paper, a two-node dynamic function model was built, taking CPR1000 as an example, considering the coupling coefficient and mutual influence. The transient parameter values were obtained by the steady-state calculation of single channel with its original structure parameter and operation parameter. Then the core system simulation of CPR1000 was modeled. In order to carry out the load follow operation without the boron adjustment, known as BTP mode, the control banks were regrouped to control the average temperature by M banks and axial offset by AO bank. The last, the optimal control implementation was connected to the core simulation platform to operate with the variable daily load. The feasibility and effectiveness of the control policy and the simulation system are validated by the calculation results via one-dimensional in axial computer code APOC. Results of computations performed for a reference reactor were present, giving the possibility that the optimal control policy could stretches the capability of the reactor to follow an average daily load curve. The paper demonstrated in principle that the BTP mode was feasible for CPR1000.

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Sadineni, Suresh B., Fady Atallah, and Robert F. Boehm. "Measurements and Simulations of Electrical Demand From Residential Buildings for Peak Load Reduction." In ASME 2011 5th International Conference on Energy Sustainability. ASMEDC, 2011. http://dx.doi.org/10.1115/es2011-54291.

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Due to extreme summers in the Desert Southwest region of the U.S., there are substantial peaks in electricity demand. Through a grant from the U.S. Department of Energy, a consortium has been formed between the University of Nevada Las Vegas, Pulte Homes, and NV Energy (formerly known as Nevada Power) to address this issue. The team has been developing a series of approximately 200 homes in Las Vegas to study substation level peak electric load reduction strategies. The targeted goal of the project is a peak reduction of more than 65%, between 1:00 PM and 7:00 PM, compared to code standard housing developments. Energy performances of the homes have been monitored and the results were stored for further analysis. A computer model has been developed for one of the homes in the new development using building energy simulation code, ENERGY 10. Influence of different peak reduction strategies on the electricity demand from the home has been analyzed using the developed model. The simulations predict that the annual electrical energy demand from the energy efficient home compared to a code standard home of the same size decreases by 38%. The simulations have also shown that the energy efficient measures reduce the electricity demand from the home during the peak periods. Simulations on the photovoltaic (PV) orientation show that a south oriented PV system is best suited for a home enrolled to flat electricity pricing schedule and a 220°(40° west of due south) orientation is economically optimal for homes enrolled in the time-of-use pricing. The energy efficiency methods in the building coupled with a 220° oriented PV and two degrees thermostat setback for three hours (from 3:00–6:00 PM) can reduce the peak demand by 62% compared to a code standard building of the same size.

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Venkataraman, Shankar, Reghu Ramawarrier, Vivek Kozhikkoottungal Satheesh, Nikhil Mathew Mundupalam, and Siddaling Bhure. "Computer Simulation of Diesel Fueled Engine Processes Using MATLAB and Experimental Investigations on Research Engine." In ASME 2017 Power Conference Joint With ICOPE-17 collocated with the ASME 2017 11th International Conference on Energy Sustainability, the ASME 2017 15th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2017 Nuclear Forum. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/power-icope2017-3498.

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The depletion of conventional fuel source at a fast rate and increasing environmental pollution have motivated extensive research in combustion modeling and energy efficient engine design. In the present work, a computer simulation incorporating progressive combustion model using thermodynamic equations has been carried out using MATLAB to evaluate the performance of a diesel engine. Simulations at constant speed and variable load have been carried out for the experimental engine available in the laboratory. For simulation, speed and Air/Fuel ratios, which are measured during the experiment, have been used as input apart from other geometrical details. A state-of-the-art experimental facility has been developed in-house. The facility comprises of a hundred horsepower water cooled eddy current dynamometer with appropriate electronic controllers. A normal load test has been carried out and the required parameters were measured. A six gas analyzer was used for the measurement of NOx, HC, CO2, O2, CO and SOx. and a smoke meter was used for smoke opacity. The predicted Pressure-Volume (PV) diagram was compared with measurements and found to match closely. It is concluded that the developed simulation software could be used to get quick results for parametric studies.

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Arsie, I., V. Marano, and G. Rizzo. "A Model for Thermo-Economic Analysis and Optimization of Steam Power Plants for Power and Cogeneration." In ASME 2004 Power Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/power2004-52132.

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The paper presents a model for thermoeconomic analysis and optimal design of steam power plants, for power generation and cogeneration use. The model, including both thermodynamic and economic description of a general steam power plant with regeneration, reheating and cogeneration, can be used for simulations, parametric analysis and optimization, with mathematical programming techniques. The variability of components performance and efficiency versus costs can be also analyzed, and optimal trade-off between costs and performace obtained by optimization analysis. Significant applications to cogeneration are presented in the paper, discussing the effects of electrical and thermal loads, fuel price and changes in technology. The computer code, built in Matlab®, allows to perform complex optimization analyses with very limited computational time.

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Xu, Xiaoqiang, Yongjia Wu, Lei Zuo, and Shikui Chen. "Multimaterial Topology Optimization of Thermoelectric Generators." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-97934.

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Abstract Over 50% of the energy from power plants, vehicles, oil refining, and steel or glass making process is released to the atmosphere as waste heat. As an attempt to deal with the growing energy crisis, the solid-state thermoelectric generator (TEG), which converts the waste heat into electricity using Seebeck phenomenon, has gained increasing popularity. Since the figures of merit of the thermoelectric materials are temperature dependent, it is not feasible to achieve high efficiency of the thermoelectric conversion using only one single thermoelectric material in a wide temperature range. To address this challenge, this paper proposes a method based on topology optimization to optimize the layouts of functional graded TEGs consisting of multiple materials. The objective of the optimization problem is to maximize the output power and conversion efficiency as well. The proposed method is implemented using the Solid Isotropic Material with Penalization (SIMP) method. The proposed method can make the most of the potential of different thermoelectric materials by distributing each material into its optimal working temperature interval. Instead of dummy materials, both the P and N-type electric conductors are optimally distributed with two different practical thermoelectric materials, namely Bi2Te3 & PbTe for P-type, and Bi2Te3 & CoSb3 for N-type respectively, with the yielding conversion efficiency around 12.5% in the temperature range Tc = 25°C and Th = 400°C. In the 2.5D computational simulation, however, the conversion efficiency shows a significant drop. This could be attributed to the mismatch of the external load and internal TEG resistance as well as the grey region from the topology optimization results as discussed in this paper.

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Garcia, Ivan F. Galindo, Saul Rodriguez Lozano, and Oscar P. Hernandez De La O. "Development of a Real Time Simulator to Test Load and Speed Control Systems of Hydroelectric Power Plants." In 2009 International Conference on Electrical, Communications, and Computers (CONIELECOMP). IEEE, 2009. http://dx.doi.org/10.1109/conielecomp.2009.44.

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