Advanced Energy Technologies
Hassan Z. Al Garni; Arunachalam Sundaram; Anjali Awasthi; Rahul Chandel; Salwan Tajjour; Shyam Singh Chandel
Abstract
A major design challenge for a grid-integrated photovoltaic power plant is to generate maximum power under varying loads, irradiance, and outdoor climatic conditions using competitive algorithm-based controllers. The objective of this study is to review experimentally validated advanced maximum power ...
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A major design challenge for a grid-integrated photovoltaic power plant is to generate maximum power under varying loads, irradiance, and outdoor climatic conditions using competitive algorithm-based controllers. The objective of this study is to review experimentally validated advanced maximum power point tracking algorithms for enhancing power generation. A comprehensive analysis of 14 of the most advanced metaheuristics and 17 hybrid homogeneous and heterogeneous metaheuristic techniques is carried out, along with a comparison of algorithm complexity, maximum power point tracking capability, tracking frequency, accuracy, and maximum power extracted from PV systems. The results show that maximum power point tracking controllers mostly use conventional algorithms; however, metaheuristic algorithms and their hybrid variants are found to be superior to conventional techniques under varying environmental conditions. The Grey Wolf Optimization, in combination with Perturb & Observe, and Jaya-Differential Evolution, is found to be the most competitive technique. The study shows that standard testing and evaluation procedures can be further developed for comparing metaheuristic algorithms and their hybrid variants for developing advanced maximum power point tracking controllers. The identified algorithms are found to enhance power generation by grid-integrated commercial solar power plants. The results are of importance to the solar industry and researchers worldwide.
Renewable Energy Resources and Technologies
Nikita Gupta; Mahajan Sagar Bhaskar; Sanjay Kumar; Dhafer J. Almakhles; Tarun Panwar; Abhinav Banyal; Aanandita Sharma; Akanksha Nadda
Abstract
The sun serves as the primary energy source, providing our planet with the essential energy for sustaining life. To efficiently harness this energy, photovoltaic cells, commonly known as PV cells, are employed. These cells convert the solar energy they receive into electrical energy. The operational ...
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The sun serves as the primary energy source, providing our planet with the essential energy for sustaining life. To efficiently harness this energy, photovoltaic cells, commonly known as PV cells, are employed. These cells convert the solar energy they receive into electrical energy. The operational point of the solar cell, delivering maximum output power, is referred to as the maximum power point (MPP). However, as light availability and temperature fluctuate throughout the day, the MPP also varies accordingly. To maintain constant operation at the MPP, Maximum Power Point Tracking (MPPT) algorithms are employed to trace the MPP during module operation. These algorithms can be categorized into four groups: classical, intelligent, optimization, and hybrid, based on the tracking algorithm utilized. Each MPPT algorithm, existing in these categories, comes with its own set of advantages and limitations. This paper extensively reviews fifteen algorithms categorized under different groups. The review concludes with a comparative analysis of these algorithms, considering various parameters such as cost, complexity, tracking accuracy, and sensed parameters in a succinct manner. The paper focuses on elucidating the necessity of MPPT algorithms, their classification as per existing literature, and a comparative assessment of the studied MPPT algorithms. This comprehensive review aims to address advancements in this field, paving the way for further research.
Renewable Energy Resources and Technologies
Hossein Dastres; Ali Mohammadi; Behrooz Rezaie
Abstract
This paper deals with the problem of maximizing the extracted power from a wind turbine in the presence of model uncertainties and input saturation. An adaptive second-order integral terminal sliding mode speed control method is utilized to address this problem. The presented method benefits from the ...
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This paper deals with the problem of maximizing the extracted power from a wind turbine in the presence of model uncertainties and input saturation. An adaptive second-order integral terminal sliding mode speed control method is utilized to address this problem. The presented method benefits from the advantages of several control techniques, i.e., adaptability, robustness, finite-time convergence, and the capability of coping with the input saturation. The robust nature of the designed controller causes its high performance in facing the uncertainties in the wind turbine model. In this paper, to compensate for the effect of input saturation, an auxiliary dynamic variable is added to the tracking error and also an adaptation law is designed so that the finite-time convergence of the closed-loop system can be achieved. Moreover, to reduce the mechanical stresses which are the result of the chattering phenomenon, a second-order sliding surface is employed. The finite-time convergence of the designed controller has been proven by the Lyapunov stability theorem in which the finite-time convergence of the tracking error to zero is guaranteed. Finally, to illustrate the effectiveness and satisfactory performance of the proposed controller, two comparative simulations are carried out. The results of this comparison show that the proposed controller has less error to track the optimal speed and when the model uncertainties and input saturation occur in the wind turbine system, the proposed controller is almost 3 % more efficient than the existing controllers.
Abdolreza Esmaeli
Abstract
a new intelligent photovoltaic (PV) panel structure to extract the maximum power in mismatch irradiance is proposed. In conventional structures, difference of irradiance between series panels can cause the deviation of maximum power point. In this condition tracking MPP becomes difficult and reduces ...
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a new intelligent photovoltaic (PV) panel structure to extract the maximum power in mismatch irradiance is proposed. In conventional structures, difference of irradiance between series panels can cause the deviation of maximum power point. In this condition tracking MPP becomes difficult and reduces efficiency. Improvements in power electronics and its effects in PV industrial technology, developed many new PV structure in recent years. This paper proposes a new intelligent structure with module integrated converter for increasing energy capture in the PV series string. The advantage of new structure is that the MPP region extends from single panel MPP to a much wider range, causing the panels to operate independent of each other in mismatch condition. To study and show advantage of intelligent structure, a real simple model is selected and verified. For operating in MPP region, P&O algorithm is selected. Despite conventional structures, voltage is not appropriately varied for P&O algorithm used in intelligent structure and system experiences instability. To solve this instability problem, resistance is proposed as variable.MATLAB/Simulink is used for simulation and demonstration of expression. The results of this work have shown that using intelligent structure improves the energy harvesting up to 14 percent, and resistance is the best variable in tracking speed and accuracy.