The Maximum power point Tracking (MppT) controller plays a vital role in maximizing power output from the solar photovoltaic (pV) sources. The tracking efficiency of the MppT controller is affected by a rapidly varyin...
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The Maximum power point Tracking (MppT) controller plays a vital role in maximizing power output from the solar photovoltaic (pV) sources. The tracking efficiency of the MppT controller is affected by a rapidly varying environmental condition. This paper presents a novel MppT controller for standalone pV system based on a Neural Network (NN) and Gain-scheduled proportional Integral (GS-pI) controller to track the fast-changing Maximum power point (Mpp). The NN model is trained topredict the operating parameters of the pV array at which maximum power is generated. The gain scheduled pI controller parameters are optimally tuned with Real-coded Genetic algorithm (RGA) to improve the controller performance. The developed MppT controller is used to control the power converter in the solar pV system. The pV array along with the control scheme is developed using LabVIEW and Multisim environment. Further, the performance of the developed control strategy is experimentally validated with solar pV emulator and DC-DC boost converter under the varying irradiation conditions. The tracking performance of the developed MppT controller is compared with the modified perturb and observe and NN+pI controller based MppT controller. The experimental results reveal that the tracking performance of the developed MppT technique is much improved and more accurate in Mpp tracking.
Solar energy will always be available, but harnessing its power may be difficult since it is intermittent. Therefore, a technology that integrates systems is necessary to satisfy the load requirement. The integration ...
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Solar energy will always be available, but harnessing its power may be difficult since it is intermittent. Therefore, a technology that integrates systems is necessary to satisfy the load requirement. The integration of the system is referred to as a converter, and it has an algorithm that can be educated according to the requirements of the final product. The perturb and observe (p&o) technique is used in this work due to the fact that it is simple to implement and has gained widespread recognition in the industry. This study's objective is to construct a step voltage controller and a step-duty p&o maximum point tracking controller-based DC-to-DC boost converter, respectively, and then make a comparison between the two. In this study, a step voltage controller and step-duty controller-based DC-to-DC boost converter are used to develop and evaluate the performance of the various components under a variety of different climatic circumstances. In order to assess the efficiency of the system, it is also important to make a comparison between the oscillations in load power and the amount of time it takes for the circumstances to settle. MATLAB Simulink and coding are used in order to evaluate the system while taking into consideration the circumstances of India's changing temperature and the intensity of the sun's radiation.
This paper presents an improved particle swarm optimization (pSo) algorithm for determining the global maximum power point tracking (GMpp) of photovoltaic (pV) array under partially shaded conditions (pSC). Under pSC,...
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This paper presents an improved particle swarm optimization (pSo) algorithm for determining the global maximum power point tracking (GMpp) of photovoltaic (pV) array under partially shaded conditions (pSC). Under pSC, the power-voltage characteristics have a more complex shape with several local peaks and one global peak. Most of the conventional techniques that are applied in the maximum power-tracking control unit of pV stations do not provide reliable tracking of the GMpp under pSC, which leads to decrease the reliability and the performance of the pV power plant. The performances of the proposed pSoalgorithm and the conventional perturb and observe algorithms are evaluated using simulations in MATLAB/Simulink. Eight different partial shading patterns have been selected toprove the robustness of the proposed algorithm. A (step-up) DC-DC boost converter is interfaced with the proposed model. The results indicate that the modified pSoalgorithm can very fast track the GMpp within 150-280 ms for different shading conditions furthermore the quality of the tracked power is very high as compared with the previous studies in the literature. Also, the average tracking efficiency of the proposed pSoalgorithm is higher than 99.8%, which provides good prospects to apply this algorithm in the control search unit for the GMpp in pV stations.
In this paper we present the development and implementation of automatic operation and control for a pump/hydrocyclone producedwater-treatment system to maximize oil/water-separation efficiency. A so-called perturb-an...
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In this paper we present the development and implementation of automatic operation and control for a pump/hydrocyclone producedwater-treatment system to maximize oil/water-separation efficiency. A so-called perturb-and-observe (p&o) algorithm is adapted for a novel centrifugal pump to continuously optimize the point of operation. The novel pump coalesces and increases the size of oil droplets in the produced water, resulting in a unique relationship between the coalescing effect and the point of operation, and allowing for the successful implementation of the p&o algorithm. The algorithm was implemented in two different setups, one measuring the droplet-size distribution between the hydrocyclone and the pump, and the other measuring the oil concentration downstream of the hydrocyclone. The latter was considered the most robust because it required noprior knowledge of the system. Nonetheless, both setups achieved satisfying results and compared favorably with a third setup, where the optimal point of operation was predicted using measurements of the upstream produced-water characteristics.
This study discusses the widespread problem of chattering phenomena and high frequency oscillations in sliding mode controllers (SMCs) used for maximum power point (Mpp) tracking (MppT) in photovoltaic (pV) systems. M...
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This study discusses the widespread problem of chattering phenomena and high frequency oscillations in sliding mode controllers (SMCs) used for maximum power point (Mpp) tracking (MppT) in photovoltaic (pV) systems. Moreover, this study introduces an adaptive sliding mode controller (ASMC) made just for pV panels with MppT capability to address these problems. The main goal of the control method is to make pV systems more reliable and effective by precisely tracking the Mpp, even when the weather quickly changes. This strategy demonstrates superior static and dynamic responsiveness compared with traditional methods. The particle swarm optimization (pSo) algorithm is employed to determine the best gains for the SMC method, specifically for controlling the variable stepof the standard perturb and observe (p&o) algorithm. This algorithm used in the study with a Soltech 1STH-250-WH module is linked to a boost DC-DC converter. The aforementioned converter provided power to a resistive load, which was then controlled by a voltage regulator. Subsequently, the research highlights the utilization of a new voltage source inverter: a 9-level diode clamp inverter (DCI) employed to mitigate harmonics, hence enhancing power quality through the reduction of its components and generating a sinusoidal AC voltage that has multiple uses.
In photovoltaic (pV) power generating systems DC-DC converters acts as an interface between the pV source and the load. This paper deals with the use of a high voltage gain three-phase interleaved DC-DC boost converte...
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In photovoltaic (pV) power generating systems DC-DC converters acts as an interface between the pV source and the load. This paper deals with the use of a high voltage gain three-phase interleaved DC-DC boost converter (IBC) for the standalone pV system applications. Interleaving technique provides high power capability and reduces the voltage stress on the power semiconductor devices. In pV system maximum power point tracking (MppT) technique is used to track the maximum power from the pV panel. To extract the maximum power from the pV panel at different irradiation levels radial basis function network (RBFN) based MppT algorithm is developed. The output power of the high voltage gain three-phase IBC with RBFN based MppT controller is compared with traditional p&o and fuzzy logic based MppT controllers at different irradiation levels. The performance analysis of p&o, fuzzy logic and RBFN MppT algorithms with high voltage gain three-phase IBC is done by using MATLAB/ SIMULINK.
Solar energy is a renewable energy source and occupies an important position in power generation. While it is environment-friendly, silent and non-fuelled, its high investment costs and low efficiency in terms of ener...
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Solar energy is a renewable energy source and occupies an important position in power generation. While it is environment-friendly, silent and non-fuelled, its high investment costs and low efficiency in terms of energy conversion bring about various disadvantages. Therefore, studies on the improvement of systems operated via photovoltaic energy gained importance and the researches and developments within the field of current power conversion systems enabled the photovoltaic systems to gain momentum. Maximum power point tracking (MppT) must be used toobtain maximum performance from the solar energy system. In this study, perturb and observe (p&o) algorithm -the most commonly used algorithm in MppT systems- was analyzed, an approach towards eliminating oscillation problems, improving speed toobtain more power value, were maintained and reference current value was obtained from p&o algorithm under changing and constant pV panel radiation conditions. Finally, the proposed p&o algorithm was simulated and the results are discussed.
Electric vehicles (EVs) have become an attractive alternative to IC engine cars due to the increased interest in lowering the consumption of fossil fuels and pollution. This paper presents the design and simulation of...
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Electric vehicles (EVs) have become an attractive alternative to IC engine cars due to the increased interest in lowering the consumption of fossil fuels and pollution. This paper presents the design and simulation of a 4 kW solar power-based hybrid EV charging station. With the increasing demand for electric vehicles and the strain they pose on the electrical grid, particularly at fast and superfast charging stations, the development of sustainable and efficient charging infrastructure is crucial. The proposed hybrid charging station integrates solar power and battery energy storage toprovide uninterrupted power for EVs, reducing reliance on fossil fuels and minimizing grid overload. The system operates using a three-stage charging strategy, with the pV array, battery bank, and grid electricity ensuring continuous power supply for EVs. Additionally, the system can export surplus solar energy to the grid, reducing the load demand. The paper also discusses the use of MppT techniques, pV cell modeling, and charge controller algorithms tooptimize the performance of the hybrid charging station.
Recently, the energy crisis in the world has led to the rise in use of renewable energy sources. With the advancement in power electronics technology, the solar photovoltaic energy has been recognized as an important ...
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ISBN:
(纸本)9781479925834
Recently, the energy crisis in the world has led to the rise in use of renewable energy sources. With the advancement in power electronics technology, the solar photovoltaic energy has been recognized as an important renewable energy resource because it is clean, abundant and pollution free. The efficiency of the photovoltaic system may be increased by using Maximum power point Tracker (MppT). A number of algorithms are developed to track the maximum power point efficiently. Most of the existing MppT algorithms suffer from the drawback of being slow or wrong tracking. Introduction of intelligent MppTs in pV systems is very promising. The current paper proposes an intelligent control method for the maximum power point tracking (MppT) of a photovoltaic system under variable insolation conditions. Here in this paper, intelligent control method uses a Fuzzy Logic Controller applied to a DC-DC converter device. The result is compared with the results obtained by using p&o method. The effectiveness of proposed algorithm is validated by simulation using Matlab/Simulink and is compared to those obtained by the conventional methods. The result shows that the fuzzy logic controller exhibits a better performance compared to that of conventional method.
This work presents a solar photovoltaic (pV) array fed permanent magnet synchronous motor (pMSM) driven single stage solar water pumping (SWp) system. A novel vector control scheme with reduced computational burden du...
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ISBN:
(纸本)9781509066841
This work presents a solar photovoltaic (pV) array fed permanent magnet synchronous motor (pMSM) driven single stage solar water pumping (SWp) system. A novel vector control scheme with reduced computational burden due to elimination of speed controller, is proposed here for speed control of pMSM. An adaptive step size perturb and observe maximum power point tracking technique is used to accelerate the response of the system. The back-electro-motive force based technique is used for encoder-less estimation of rotor position. This improves the reliability and reduces the cost of the SWp system. A single stage topology is utilized for reducing the losses and cost associated with intermediate stage DC-DC converter. The applicability of the overall system is validated through a developed laboratory prototype using digital signal processor (DS-1202). performance of the system has been found to be quite satisfactory under both dynamic and steady state conditions.
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