Sakshi Sharma
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Sakshi Sharma has a total of 9 co-authors. Here are the top co-authors by number of shared publications:
- Piyush Kuchhal
University of Petroleum and Energy Studies Dehradun
2 shared publications - Ahmed Farag Ali
Department of Electrical and Electronic Engineering Technology, University of Johannesburg, Johannesburg 2006, South Africa
1 shared publication - Akanksha Singh S. Vardhan
National Institute of Technology Jamshedpur
1 shared publication - Baseem Khan
Department of Electrical and Computer Engineering, Hawassa University, Hawassa, Ethiopia
1 shared publication - Brian Azzopardi
MCAST Energy Research Group, Institute of Engineering and Transport, Malta College of Arts, Science and Technology (MCAST), Main Campus, Corradino Hill, PLA 9032 Paola, Malta
1 shared publication - Keshav Kumar
Pranveer Singh Institute of Technology
1 shared publication
Latest Publications
- 26 December 2023
- Published by Springer Nature in Electrical Engineering
- Vol. 106 (2) , 1225-1239
Numerical simulations, design and modeling of methylammonium tin iodide halide-based single-junction perovskite solar cell
- 26 December 2023
- Published by Springer Nature in Electrical Engineering
- Vol. 106 (2) , 1225-1239
Numerical simulations, design and modeling of methylammonium tin iodide halide-based single-junction perovskite solar cell
- Open Access
A Comprehensive Review of Flexible Power-Point-Tracking Algorithms for Grid-Connected Photovoltaic Systems
The rapid increase in the penetration of photovoltaic (PV) power plants results in an increased risk of grid failure, primarily due to the intermittent nature of the plant. To overcome this problem, the flexible power point tracking (FPPT) algorithm has been proposed in the literature over the maximum power point tracking (MPPT) algorithm. These algorithms regulate the PV power to a certain value instead of continuously monitoring the maximum power point (MPP). The proposed work carries out a detailed comparative study of various constant power generation (CPG) control strategies. The control strategies are categorized in terms of current-, voltage-, and power-based tracking capabilities. The comparative analysis of various reported CPG/FPPT techniques was carried out. This analysis was based on some key performance indices, such as the type of control strategy, irradiance pattern, variation in G, region of operation, speed of tracking, steady-state power oscillations, drift severity scenario, partial shading scenario, implementation complexity, stability, fast dynamic response, robustness, reactive power, cost, and tracking efficiency. Among existing FPPT algorithms, model-based control has a superior performance in terms of tracking speed and low steady-state power oscillations, with a maximum tracking efficiency of 98.57%.
Open AccessA Comprehensive Review of Flexible Power-Point-Tracking Algorithms for Grid-Connected Photovoltaic Systems
The rapid increase in the penetration of photovoltaic (PV) power plants results in an increased risk of grid failure, primarily due to the intermittent nature of the plant. To overcome this problem, the flexible power point tracking (FPPT) algorithm has been proposed in the literature over the maximum power point tracking (MPPT) algorithm. These algorithms regulate the PV power to a certain value instead of continuously monitoring the maximum power point (MPP). The proposed work carries out a detailed comparative study of various constant power generation (CPG) control strategies. The control strategies are categorized in terms of current-, voltage-, and power-based tracking capabilities. The comparative analysis of various reported CPG/FPPT techniques was carried out. This analysis was based on some key performance indices, such as the type of control strategy, irradiance pattern, variation in G, region of operation, speed of tracking, steady-state power oscillations, drift severity scenario, partial shading scenario, implementation complexity, stability, fast dynamic response, robustness, reactive power, cost, and tracking efficiency. Among existing FPPT algorithms, model-based control has a superior performance in terms of tracking speed and low steady-state power oscillations, with a maximum tracking efficiency of 98.57%.