Artificial neural network based three phase Shunt Active Power Filter
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This work describes artificial neural network (ANN) based control algorithm for three phase three wire shunt active power filter (SAPF) to compensate harmonics and improve power quality. System consists of three phase insulated gate bipolar transistors IGBT based current controlled voltage source inverter (CC-VSI), series coupling inductor and self supported DC bus. Increasing application of non-linear loads causes power quality problem. SAPF is one of the possible configurations to improve power quality. Traditional SAPF have PLL based unit template generator for extraction of fundamental signal. Traditional PLL needs to be tuned to obtain optimal performance for frequency estimation. It requires initial assumptions for fundamental frequency and minimum frequency. With varying frequency, it can’t be dynamically tuned for optimal performance. A new ANN based fundamental extraction based on Lavenberg Marquardt back propagation algorithm is proposed. Proposed SAPF is modeled in Simulink environment. Simulated results show the capability of proposed system.
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Power quality is highlighted as an important parameter in modern power systems. Moreover, grid-connected photovoltaic power plants are increasing significantly in size and capacity. Elsewhere, due to the progressive integration of nonlinear loads in the grid, the principal role of a Solar Energy Conversion System (SECS) is not only to capture the maximum power from solar but, also to ensure some ancillary services and improve the quality of power. This paper presents a novel strategy dedicated to improve the management of active power generation, reactive power compensation and power quality of a SECS, while guaranteeing the possibility of exploiting the full capacity of the Power Conditioning System (PCS) and the PhotoVoltaic System (PVS). The proposed control algorithm is applied to a large scale PVS connected to the grid through a cascade of a DC-DC converter and a PWM inverter. This control strategy manages the SECS function’s priorities, between main active power generation, reactive power compensation and active filtering in such a way to guarantee a smooth and stable DC voltage and ensure a sinusoidal grid current. Top priority is given to the active power production over power quality improvement. Then, priority is given to reactive power compensation over mitigation of current harmonics absorbed by the non-linear load connected to the Point of Common Coupling (PCC). Moreover, the whole system upper limits of active and reactive powers have been determined in the (PQ) power plane on the basis of PVS available power, converters rated power and DC bus voltage smoothness and stability. Finally, a control procedure dedicated to the calculation of the inverter current commands is proposed in order to exploit the full capacity of the SECS and respect the determined power limits. Simulation results confirm the effectiveness and the performance of this control strategy and prove that the SECS can operate at its full power whilst the power quality can be improved by reactive power compensation and active filtering.
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In this paper, a topology using a Dual-stator Winding Induction Generator (DWIG) and a boost converter is proposed for the variable speed wind power application. At low rotor speeds, the generator saturation limits the voltage of the DWIG. Using a boost converter, higher DC voltage can be produced while the DWIG operates at Maximum Power Point Tracking (MPPT) even at low speed and low voltage conditions. Semiconductor Excitation Controller (SEC) of the DWIG utilizes Control-Winding Voltage Oriented Control (CWVOC) method to adjust the voltage, considering V/f characteristics. For the proposed topology, the SEC capacity and the excitation capacitor is optimized by analyzing the SEC reactive current considering wind turbine power-speed curve, V/f strategy, and the generator parameters. The method shows that the per-unit capacity of the SEC can be limited to the inverse of DWIG magnetizing reactance per-unit value. The topology is simulated in MATLAB/Simulink platform and experimented with a scaled 1 kW prototype. Both simulation and experimental results demonstrate wide variable speed operation range of the DWIG and verify the optimization.
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Artificial Neural Network (ANN) is becoming an attractive estimation and regression technique in many control applications due to its parallel computing nature and high learning capability. There has been a lot of effort in employing the ANN in shunt active power filter (APF) control applications. Adaptive Linear Neuron (ADALINE) and feed-forward Multilayer Neural Network (MNN) are the most commonly used ANN techniques to extract fundamental and/or harmonic components present in the non-linear currents. This paper aims to provide an in-depth understanding on realizing ADALINE and feed-forward MNN based control algorithms for shunt APF. A step-by-step procedure to implement these ANN based techniques, in Matlab/ Simulink environment, is provided. Furthermore, a detailed analysis on the performance, limitation and advantages of both methods is presented in the paper. The study is supported by conducting both simulation and experimental validations.
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environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
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Artificial neural network based three phase Shunt Active Power Filter
- 1. ELECTRICAL PROJECTS USING MATLAB/SIMULINK Gmail:asokatechnologies@gmail.com, Website: http://www.asokatechnologies.in 0-9347143789/9949240245 For Simulation Results of the project Contact Us Gmail:asokatechnologies@gmail.com, Website: http://www.asokatechnologies.in 0-9347143789/9949240245 Artificial Neural Network based Three Phase Shunt Active Power Filter ABSTRACT: This work describes artificial neural network (ANN) based control algorithm for three phase three wire shunt active power filter (SAPF) to compensate harmonics and improve power quality. System consists of three phase insulated gate bipolar transistors IGBT based current controlled voltage source inverter (CC-VSI), series coupling inductor and self supported DC bus. Increasing application of non-linear loads causes power quality problem. SAPF is one of the possible configurations to improve power quality. Traditional SAPF have PLL based unit template generator for extraction of fundamental signal. Traditional PLL needs to be tuned to obtain optimal performance for frequency estimation. It requires initial assumptions for fundamental frequency and minimum frequency. With varying frequency, it can’t be dynamically tuned for optimal performance. A new ANN based fundamental extraction based on Lavenberg Marquardt back propagation algorithm is proposed. Proposed SAPF is modeled in Simulink environment. Simulated results show the capability of proposed system. KEYWORDS: 1. Shunt Active Power Filter 2. Artificial Neural Networks 3. Indirect Current Control Technique 4. Power Quality SOFTWARE: MATLAB/SIMULINK
- 2. ELECTRICAL PROJECTS USING MATLAB/SIMULINK Gmail:asokatechnologies@gmail.com, Website: http://www.asokatechnologies.in 0-9347143789/9949240245 For Simulation Results of the project Contact Us Gmail:asokatechnologies@gmail.com, Website: http://www.asokatechnologies.in 0-9347143789/9949240245 BLOCK DIAGRAM: Fig.1. Proposed system configuration block with SAPF
- 3. ELECTRICAL PROJECTS USING MATLAB/SIMULINK Gmail:asokatechnologies@gmail.com, Website: http://www.asokatechnologies.in 0-9347143789/9949240245 For Simulation Results of the project Contact Us Gmail:asokatechnologies@gmail.com, Website: http://www.asokatechnologies.in 0-9347143789/9949240245 EXPECTED SIMULATION RESULTS: Fig.2. Source voltages Fig.3. Unbalanced load voltages Fig.4. Unbalanced load currents
- 4. ELECTRICAL PROJECTS USING MATLAB/SIMULINK Gmail:asokatechnologies@gmail.com, Website: http://www.asokatechnologies.in 0-9347143789/9949240245 For Simulation Results of the project Contact Us Gmail:asokatechnologies@gmail.com, Website: http://www.asokatechnologies.in 0-9347143789/9949240245 Fig.5. Simulation result for proposed system under non linear with unbalance load condition Fig.6. DC link voltage
- 5. ELECTRICAL PROJECTS USING MATLAB/SIMULINK Gmail:asokatechnologies@gmail.com, Website: http://www.asokatechnologies.in 0-9347143789/9949240245 For Simulation Results of the project Contact Us Gmail:asokatechnologies@gmail.com, Website: http://www.asokatechnologies.in 0-9347143789/9949240245 Fig.7. Active power Fig.8. Reactive power Fig.9. Power factor
- 6. ELECTRICAL PROJECTS USING MATLAB/SIMULINK Gmail:asokatechnologies@gmail.com, Website: http://www.asokatechnologies.in 0-9347143789/9949240245 For Simulation Results of the project Contact Us Gmail:asokatechnologies@gmail.com, Website: http://www.asokatechnologies.in 0-9347143789/9949240245 Fig.10. Harmonic spectrum of load current before compensation for three phase SAPF with non linear load
- 7. ELECTRICAL PROJECTS USING MATLAB/SIMULINK Gmail:asokatechnologies@gmail.com, Website: http://www.asokatechnologies.in 0-9347143789/9949240245 For Simulation Results of the project Contact Us Gmail:asokatechnologies@gmail.com, Website: http://www.asokatechnologies.in 0-9347143789/9949240245 Fig.11. Harmonic spectrum of source currents (phase a, phase b phase c respectively) after compensation for ANN based three phase APF with non linear load Fig.12. Harmonic spectrum of source currents (phase a) after compensation for ANN based three phase APF with non linear load with unbalance
- 8. ELECTRICAL PROJECTS USING MATLAB/SIMULINK Gmail:asokatechnologies@gmail.com, Website: http://www.asokatechnologies.in 0-9347143789/9949240245 For Simulation Results of the project Contact Us Gmail:asokatechnologies@gmail.com, Website: http://www.asokatechnologies.in 0-9347143789/9949240245 CONCLUSION: ANN based phase-locking scheme has been proposed in this paper to control three phase-three wire shunt APFs. Widrow-Hoff weights updating algorithm has been incorporated to reduce calculation time in estimation of harmonic components. To validate effectiveness of proposed approach for real-time applications, indirect current control theory based controller has been developed. Design parameters of power circuit and control circuit have been calculated and robustness of proposed system has been established with Matlab/Simulink. Simulation result and spectral response show that, obtained source current THDs is below 5% as prescribed by IEEE- 519 standard. Dynamic performance of proposed approach has been found satisfactory under sudden change in load and frequency. REFERENCES: [1] P. Kumar and D.K. Palwalia, “Decentralized autonomous hybrid renewable power generation”, Journal of Renew. Energy, pp. 1-18, 2015. [2] W. Dai, T. Huang, and N. Lin, “Design of single-phase shunt active power filter based on ANN”, IEEE Int. Symp. on Ind. Electron., pp. 770-774, 2007. [3] H. Akagi, Y. Kanazawa, and A. Nabae, “Instantaneous reactive power compensators comprising switching devices without energy storage components,” IEEE Trans. Ind. Applicat., vol. IA-20, pp. 625–630, 1984. [4] H. Akagi and A. Nabae, “The p-q theory in three-phase systems under nonsinusoidal conditions,” Eur. Trans. Elect. Power Eng., vol. 3, no. 1, pp. 27–31, 1993. [5] H. Akagi and H. Fujita, “A new power line conditioner for harmonic compensation in power systems,” IEEE Trans. Power Delivery, vol. 10, pp. 1570–1575, 1995.