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
Rahul Dogra; Sanjay Kumar; Nikita Gupta
Abstract
The use of these conventional resources causes continuous depletion of fossil fuels and increased greenhouse effect. Solar power is the major renewable resource used for power generation across the globe. Solar energy activities depend on the available potential of any geographical location. Therefore, ...
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The use of these conventional resources causes continuous depletion of fossil fuels and increased greenhouse effect. Solar power is the major renewable resource used for power generation across the globe. Solar energy activities depend on the available potential of any geographical location. Therefore, prior to the installation of solar technologies for these activities, estimation of solar potential is very important due to costly technologies. Data of solar potential is not present at every location in Himachal Pradesh (H. P.) due to the high cost of measurement instruments. The objective of this study includes the solar potential estimation for 12 cities of the H. P. The present study could be divided into two parts. Initially, Artificial Neural Networks (ANNs) are utilized to estimate global sun radiation utilizing meteorological and geographical data from 23 places. The ANN model with seven input parameters including latitude, longitude, altitude, air temperature, humidity, pressure, and wind speed were used to estimate the solar irradiation. Statistical indicators including Mean Absolute Percentage Error (MAPE) were used for the performance evaluation of these ANNs. The minimum MAPE value was obtained to be 2.39 % with Multi-Layer Perception (MLP) architecture 7-11-1. For the 12 districts of the H. P., the acquired network 7-11-1 was utilized to estimate Global Solar Radiation (GSR). The output of ANN model was implemented in Geographic Information System (GIS) environment to obtain the solar potential map for each month. The available map of the present study may be helpful for solar application in each district.
