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Search results for: KEYWORDS: THERMOELECTRIC GENERATOR (TEG) MAXIMUM POWER POINT TRACKING (MPPT) SWARM INTELLIGENCE (SI) RELATIVE ERROR (RE) GENERALIZED REGRESSION NEURAL NETWORK (GRNN) GLOBAL MAXIMUM POWER POINTS (GMPP)
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Generalized regression neural network and fitness dependent optimization: Application to energy harvesting of centralized TEG systems
PublicationThe thermoelectric generator (TEG) system has attracted extensive attention because of its applications in centralized solar heat utilization and recoverable heat energy. The operating efficiency of the TEG system is highly affected by operating conditions. In a series-parallel structure, due to diverse temperature differences, the TEG modules show non-linear performance. Due to the non-uniform temperature distribution (NUTD) condition,...
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Cleaner energy for sustainable future using hybrid photovoltaics-thermoelectric generators system under non-static conditions using machine learning based control technique
PublicationIn addition to the load demand, the temperature difference between the hot and cold sides of the thermoelectric generator (TEG) module determines the output power for thermoelectric generator systems. Maximum power point tracking (MPPT) control is needed to track the optimal global power point as operating conditions change. The growing use of electricity and the decline in the use of fossil fuels have sparked interest in photovoltaic-TEG...
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Highly efficient maximum power point tracking control technique for PV system under dynamic operating conditions
PublicationThe application of small-scale electrical systems is widespread and the integration of Maximum Power Point Tracking (MPPT) control for Photovoltaic systems with battery applications further enhances the techno-economic feasibility of renewable systems. For this purpose, a novel MPPT control system using Dynamic Group based cooperation optimization (DGBCO) algorithm is utilized for PV systems. The population in the DGBCO is divided...
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Photovoltaic Maximum Power Point Technique based on Incremental Conductance (INCON) control algorithm
PublicationMaximum output power status can significantly improve the deployment rate of solar energy system. In order to get the maximum power output, issue of tracking maximum power point (MPP), reduced harmonics around MPP and improve efficiency of the solar power energy system, this paper presents the improved maximum power point tracking (MPPT) control...
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Improved maximum power point tracking algorithms by using numerical analysis techniques for photovoltaic systems
PublicationSolar photovoltaic (PV) panels generate optimal electricity when operating at the maximum power point (MPP). This study introduces a novel MPP tracking algorithm that leverages the numerical prowess of the predictor-corrector method, tailored to accommodate voltage and current fluctuations in PV panels resulting from variable environmental factors like solar irradiation and temperature. This paper delves into the intricate dynamics...
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Fuzzy Based Maximum Power Point Tracking (MPPT) Control System for Photovoltaic Power Generation System
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An Optimal Power Point Tracking Algorithm in a Solar PV Generation System
PublicationThe non-linearity in I-V characteristics of a PV panel requires to be operated at knee point to extract maximum power. In order to operate the panel at optimal point, maximum power point tracking (MPPT) algorithm is employed in the control structure. The main objective of MPP tracking is to keep the operation at knee point of I-V characteristics under varying condition of temperature and solar insolation. Under non uniform solar...
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Maximum Power Point Technique (MPPT) for PV System Based on Improved Pert and Observe (P&O) Method with PI Controller
PublicationPhotovoltaic power generation system has key rule in electricity production. Although, it is clean renewable energy with unlimited resources but it has some drawbacks in efficiency. In order to maximize the efficiency, PV array must drive at maximum power point. For the reason so, several algorithms are used in PV system to track MPP and reduce the...
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The Maximum Power Point Tracking (MPPT) of a Partially Shaded PV Array for Optimization Using the Antlion Algorithm
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Green energy extraction for sustainable development: A novel MPPT technique for hybrid PV-TEG system
PublicationThe Photovoltaic (PV) module converts only a small portion of irradiance into electrical energy. Most of the solar energy is wasted as heat, resulting in a rise in PV cell temperature and a decrease in solar cell efficiency. One way to harvest this freely available solar thermal energy and improve PV cell efficiency is by integrating PV systems with thermoelectric generators (TEG). This cogeneration approach of the hybrid PV-TEG...
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Issues of Estimating the Maximum Distributed Generation at High Wind Power Participation
PublicationThis paper presents the methods of estimating the maximum power that can be connected to the power system in distributed generation sources. Wind turbine generator systems (WTGS) were selected as the subject for analysis. Nonetheless, the considerations presented in this paper are only general and also apply to other types of power sources, including the sources that are not considered part of distributed generation.
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Photovoltaic maximum power point varying with illumination and temperature
PublicationW pracy przedstawiono wyniki badań eksperymentalnych zmian położenia punktu maksymalnej mocy na charakterystyce prądowo-napięciowej modułu ogniw fotowoltaicznych, związanych ze zmieniającą się temperaturą i natężeniem padającego promieniowania. Badano czas narastania napięcia pracy i temperatury ogniw w początkowej fazie ekspozycji na promieniowanie słoneczne. Przedstawiono niektóre praktyczne aspekty zastosowania układu automatycznego...
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Estimation of the Maximum Permissible PV Power to be Connected to the MV Grid
PublicationIn recent decades, a significant increase in the share of renewable energy sources in power grids at various voltage levels has been observed. A number of articles have been published highlighting emerging problems in low-voltage grids with a large share of prosumers and in medium- and high-voltage grids to which photovoltaic (PV) plants are connected. The article analyzes the medium-voltage grid in terms of the possibility of...
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Global Surrogate Modeling by Neural Network-Based Model Uncertainty
PublicationThis work proposes a novel adaptive global surrogate modeling algorithm which uses two neural networks, one for prediction and the other for the model uncertainty. Specifically, the algorithm proceeds in cycles and adaptively enhances the neural network-based surrogate model by selecting the next sampling points guided by an auxiliary neural network approximation of the spatial error. The proposed algorithm is tested numerically...
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Interior Point Method Evaluation for Reactive Power Flow Optimization in the Power System
PublicationThe paper verifies the performance of an interior point method in reactive power flow optimization in the power system. The study was conducted on a 28 node CIGRE system, using the interior point method optimization procedures implemented in Power Factory software.
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Monitoring Regenerative Heat Exchanger in Steam Power Plant by Making Use of the Recurrent Neural Network
PublicationArtificial Intelligence algorithms are being increasingly used in industrial applications. Their important function is to support operation of diagnostic systems. This paper pesents a new approach to the monitoring of a regenerative heat exchanger in a steam power plant, which is based on a specific use of the Recurrent Neural Network (RNN). The proposed approach was tested using real data. This approach can be easily adapted to...
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A Salp-Swarm Optimization based MPPT technique for harvesting maximum energy from PV systems under partial shading conditions
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Advanced Control Structures of Turbo Generator System of Nuclear Power Plant
PublicationIn the paper a synthesis of advanced control structures of turbine and synchronous generator for nuclear power plant working under changing operating conditions (supplied power level) is presented. It is based on the nonlinear models of the steam turbine and synchronous generator cooperating with the power system. Considered control structure consists of multi-regional fuzzy control systems with local linear controllers, including...
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Advanced Control Structures of Turbo Generator System of Nuclear Power Plant
PublicationIn the paper a synthesis of advanced control structures of turbine and synchronous generator for nuclear power plant working under changing operating conditions (supplied power level) is presented. It is based on the nonlinear models of the steam turbine and synchronous generator cooperating with the power system. Considered control structure consists of multi-regional fuzzy control systems with local linear controllers, including...
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Control of a wind power generator in case of voltage sags in power network
PublicationW artykule poruszono problem związany ze sposobem sterowania generatorem elektrowni wiatrowej w przypadku wystąpienia po stronie sieci zapadów napięcia.Jako generator wykorzystano maszynę dwustronnie zasilaną której stojan podłączono bezpośrednio do sieci natomiast wirnik zasilano poprzez kaskadę przekształtników. Wystąpienie spadku lub zapadu napięcia sieci w przypadku pracy tego typu generatora może doprowadzić do uszkodzenia...
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Application of Maximum Lenght Sequence in Silent Sonar
PublicationSilent sonars are designed to reduce the distance over which their sounding pulses can be detected by intercept sonars. In order to meet this objective, we can use periodical sounding signals that have low power, a very long duration and wide spectrum. If used in the silent sonar's receiver, matched filtration ensures very good detection of motionless or slow moving targets. However, it is more difficult to detect echo signals...
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Michał Michna dr hab. inż.
PeopleMichal Michna received the M.Sc. and Ph.D. degrees in electrical engineering from the Gdansk University of Technology (GUT), Gdansk, Poland, in 1998 and 2005, respectively. Since 2004, he was employed at the Department of Power Electronics and Electrical Machines of the Gdańsk University of Technology (assistant, assistant professor, senior lecturer). In 2010-2015 he was a deputy of head of the Department of Power Electronics and...
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Modeling and Simulation for Exploring Power/Time Trade-off of Parallel Deep Neural Network Training
PublicationIn the paper we tackle bi-objective execution time and power consumption optimization problem concerning execution of parallel applications. We propose using a discrete-event simulation environment for exploring this power/time trade-off in the form of a Pareto front. The solution is verified by a case study based on a real deep neural network training application for automatic speech recognition. A simulation lasting over 2 hours...
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Application capabilities of the maximum distributed generation estimate methodology
PublicationThe paper presents application capabilities of the maximum distributed generation estimate methodology. This subject is an example of solutions to the problem that today face the transmission system operator and distribution system operators, which is related to the high saturation with wind power generation predicted for the near future.
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Methods for evaluating rated power of diesel-powered generator set
PublicationBasic concepts for evaluating rated power of generator sets powered by combustion engines are presented in this article. A relation between parameters of the engine and the generator are shown. Recommendations contained in the standards and technical literature are systematized. The scheme and methodology for evaluating rated power of the generator set, based on laboratory research, are suggested. Also, the main problems which...
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Zbigniew Lubośny prof. dr hab. inż.
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Induction Generator with Direct Control and a Limited Number of Measurements on the Side of the Converter Connected to the Power Grid
PublicationThe article presents an induction generator connected to the power grid using the AC/DC/AC converter and LCL coupling filter. Three-level inverters were used in the converter, both from the generator side and the power grid side. The algorithm realizing Pulse Width Modulation (PWM) in inverters has been simplified to the maximum. Control of the induction generator was based on the Direct Field-Oriented Control (DFOC) method. At...
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Performance and Energy Aware Training of a Deep Neural Network in a Multi-GPU Environment with Power Capping
PublicationIn this paper we demonstrate that it is possible to obtain considerable improvement of performance and energy aware metrics for training of deep neural networks using a modern parallel multi-GPU system, by enforcing selected, non-default power caps on the GPUs. We measure the power and energy consumption of the whole node using a professional, certified hardware power meter. For a high performance workstation with 8 GPUs, we were...
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JOURNAL OF POWER SOURCES
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Models of Brushless Synchronous Generator for Studying Autonomous Electrical Power System
PublicationThis is a PhD dissertation. The work presented in this monograph was carried out at the Department of Power Electronics and Electrical Machines, Faculty of Electrical and Control Engineering at the Gdansk University of Technology. Developed during the research models of brushless synchronous generator ware verified using FEM based simulations and measurements conducted on the prototype generator. The main focus of the research...
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Numbers, Please: Power- and Voltage-Related Indices in Control of a Turbine-Generator Set
PublicationThis paper discusses the proper selection and interpretation of aggregated control performance indices values mirroring the quality of electrical energy generation by a turbine-generator set cooperating with a power system. Typically, a set of basic/classical and individual indices is used in energy engineering to ensure the mirroring feature and is related to voltage, frequency and active or reactive power deviations from their...
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Artificial Neural Network in Forecasting the Churn Phenomena Among Costumers of IT and Power Supply Services
PublicationThis paper presents an attempt to use an artificial neural network to investigate the churn phenomenon among the customers of a telecommunications operator. An attempt was made to create a data model based on the customer lifetime value (CLV) rather than on activity alone. A multilayered artificial neural network was used for the experiments. The results yielded a 99% successful identification rate for customers in no danger of...
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Nuclear Power
e-Learning CoursesNuclear Power is a course for student II degree in full-time studies at Chemistry Faculty, majoring in Green Technology and Monitoring.
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Power System Stabilizer as a Part of a Generator MPC Adaptive Predictive Control System
PublicationIn this paper, a model predictive controller based on a generator model for prediction purposes is proposed to replace a standard generator controller with a stabilizer of a power system. Such a local controller utilizes an input-output model of the system taking into consideration not only a generator voltage Ug but also an additional, auxiliary signal (e.g., α, Pg, or ωg). This additional piece of information allows for taking...
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Modern power-electronics installations in the Polish electrical power network
PublicationThe paper discusses the most important areas of application of power electronics arrangements in the Polish electrical power system; especially in the distribution system. The examples presented demonstrate both the need for and the purpose of further research and its applications in these fields, as well as indicating the direction of future research, with special consideration given to the research required in Poland. The proposed...
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Application of Generalized Regression Neural Network and Gaussian Process Regression for Modelling Hybrid Micro-Electric Discharge Machining: A Comparative Study
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Resource constrained neural network training
PublicationModern applications of neural-network-based AI solutions tend to move from datacenter backends to low-power edge devices. Environmental, computational, and power constraints are inevitable consequences of such a shift. Limiting the bit count of neural network parameters proved to be a valid technique for speeding up and increasing efficiency of the inference process. Hence, it is understandable that a similar approach is gaining...
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Nonlinear model of a synchronous generator for analysis of more electric aircraft power systems
PublicationA nonlinear model for studying a variable-speed synchronous generator (SG) in more electric aircraft (MEA) power system has been developed. The saturation effects of the SG magnetic circuit have been considered. The model has been implemented in the Synopys/Saber simulation environment. The modelling language MAST has been used to elaborate the SG model. The model exhibit a network with the same number of external terminals/ports...
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The measurement of input power of power supply in network disturbed by low frequency distortions
PublicationIn the paper authors present results of observation of input power changes versus harmonics amplitude in supply voltage of low-power power supply device. In the study, the electrical measurements supported with thermal imaging were used. The input circuit elements of studied device responsible for input power increase are pointed
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A Bayesian regularization-backpropagation neural network model for peeling computations
PublicationA Bayesian regularization-backpropagation neural network (BRBPNN) model is employed to predict some aspects of the gecko spatula peeling, viz. the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle. K-fold cross validation is used to improve the effectiveness of the model. The input data is taken from finite element (FE) peeling results. The neural network...
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Regression points in non-intrusive polynomial chaos expansion method and D-optimal design
PublicationThe paper addresses selected issues of uncertainty quantification in the modelling of a system containing surgical mesh used in ventral hernia repair. Uncertainties in the models occur e.g. due to variability of abdominal wall properties among others. In order to include them, a non-intrusive regression-based polynomial chaos expansion method is employed. Its accuracy depends on the choice of regression points. In the study a relation...
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Neural network training with limited precision and asymmetric exponent
PublicationAlong with an extremely increasing number of mobile devices, sensors and other smart utilities, an unprecedented growth of data can be observed in today’s world. In order to address multiple challenges facing the big data domain, machine learning techniques are often leveraged for data analysis, filtering and classification. Wide usage of artificial intelligence with large amounts of data creates growing demand not only for storage...
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Simplified, multiregional fuzzy model of a nuclear power plant steam turbine
PublicationPower systems, including steam turbines and synchronous generators, are complex nonlinear systems with parameters varying over time. The paper presents the developed simplified, multiregional fuzzy model of the steam turbine of a nuclear power plant turbine generator set and compares the results with a full nonlinear model and commonly used linear input-output model of a steam turbine. The proposed model consist of series of linear...
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Modified Inductive Multi-Coil Wireless Power Transfer Approach Based On Z-Source Network
PublicationThis article presents a non-conventional approach to a multi-coil wireless power transfer system based on a Z-source network. The novelty of the approach lies in the use of a Z-source as a voltage source for energy transmission through the wireless power transfer coils. The main advantage is in a reduced number of semiconductors. This paper provides the design approach, simulation and experimental study. Feasibility and possible...
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The distributed model predictive controller for the nuclear power plant turbo-generator set
PublicationTypically there are two main control loops with PI controllers operating at each turbo-generator set. In this paper a distributed model predictive controller DMPC, with local QDMC controllers for the turbine generator, is proposed instead of a typical PI controllers. The local QDMC controllers utilize step-response models for the controlled system components. These models parameters are determined based on the proposed black-box...
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Iterative Global Sensitivity Analysis Algorithm with Neural Network Surrogate Modeling
PublicationGlobal sensitivity analysis (GSA) is a method to quantify the effect of the input parameters on outputs of physics-based systems. Performing GSA can be challenging due to the combined effect of the high computational cost of each individual physics-based model, a large number of input parameters, and the need to perform repetitive model evaluations. To reduce this cost, neural networks (NNs) are used to replace the expensive physics-based...
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The Influence of Cooperation on the Operation of an MPC Controller Pair in a Nuclear Power Plant Turbine Generator Set
PublicationThe paper discusses the problem of cooperation between multiple model predictive control (MPC) systems. This approach aims at improving the control quality in electrical energy generation and forms the next step in a series of publications by the authors focusing on the optimization and control of electric power systems. Cooperation and cooperative object concepts in relation to a multi MPC system are defined and a cooperative control...
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A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks
PublicationThis article proposes the use of a feedforward neural network (FNN) to select the starting point for the first iteration in well-known iterative location estimation algorithms, with the research objective of finding the minimum size of a neural network that allows iterative position estimation algorithms to converge in an example positioning network. The selected algorithms for iterative position estimation, the structure of the...
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Impact of power electronic Var compensators installed in certain grid points on the voltage failure
PublicationThe article presents the test results of the various types of static compensators FACTS models in the power system. The basic case, which was analyzed, it was behavior of compensators which are installed in select points of the system during voltage failure. The article presents selected results of studies conducted as part of a work [2].
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Intelligent turbogenerator controller based on artifical neural network
PublicationThe paper presents a desing of an intelligent controller based on neural network (ICNN). The ICNN ensures at the same time two fundamental functions : the maintaining of generator voltage at the desired value and the damping of the electromechanical oscillations. Its performance is evaluted on a single machine infinite bus power system through computer simulations. The dynamic and transient operation of the proposed controller...