| Modeling of soiled PV module with neural networks and regression using particle size composition S Pulipaka, F Mani, R Kumar Journal of solar energy 123 (C), 116-126, 2016 | 63 | 2016 |
| Global maximum power point tracking using variable sampling time and pv curve region shifting technique along with incremental conductance for partially shaded photovoltaic systems R Kumar, S Khandelwal, P Upadhyay, S Pulipaka Solar Energy 189, 151-178, 2019 | 38 | 2019 |
| Characterization of power losses of a soiled PV panel in Shekhawati region of India F Mani, S Pulipaka, R Kumar Solar Energy 131, 96-106, 2016 | 31 | 2016 |
| Power prediction of soiled PV module with neural networks using hybrid data clustering and division techniques S Pulipaka, R Kumar Solar Energy 133, 485-500, 2016 | 29 | 2016 |
| Analysis of irradiance losses on a soiled photovoltaic panel using contours S Pulipaka, R Kumar Energy conversion and management 115, 327-336, 2016 | 22 | 2016 |
| Analysis of soil distortion factor for photovoltaic modules using particle size composition S Pulipaka, R Kumar Solar Energy 161, 90-99, 2018 | 20 | 2018 |
| Non‐intrusive real‐time monitoring of PV generation at inverters using Internet of photovoltaics S Pulipaka, A Ramesh, R Kumar, B Bora, S Kumar, SK Singh Electronics Letters 53 (16), 1137-1138, 2017 | 13 | 2017 |
| A proposed maximum power point operating strategy for photovoltaic applications using monthly irradiance estimates P Upadhyay, S Pulipaka, M Sharma, R Kumar Solar Energy 141, 266-277, 2017 | 13 | 2017 |
| Modeling of soiled photovoltaic modules with neural networks using particle size composition of soil F Mani, S Pulipaka, R Kumar 2015 IEEE 42nd Photovoltaic Specialist Conference (PVSC), 1-4, 2015 | 12 | 2015 |
| Comparison of SOM and conventional neural network data division for PV reliability power prediction S Pulipaka, R Kumar 2017 IEEE International Conference on Environment and Electrical Engineering …, 2017 | 10 | 2017 |
| Parameter extraction of solar photovoltaic system using Lambert-W function for different environmental condition P Upadhyay, S Pulipaka, R Kumar, M Sharma 2016 IEEE Region 10 Conference (TENCON), 1884-1888, 2016 | 5 | 2016 |
| Performance enhancement of neural network training using hybrid data division technique for photovoltaic power prediction S Pulipaka, R Kumar 2017 IEEE International Conference on Environment and Electrical Engineering …, 2017 | 2 | 2017 |
| Performance Modelling of PV Generation with Inverter Level Data Through Internet of Photovoltaics (IoPV) Using Artificial Neural Networks (ANN) S Pulinaka, P Kumar, R Kaushal, R Kumar, V Sharma, S Kumar 2018 2nd International Conference on Power, Energy and Environment: Towards …, 2018 | | 2018 |
| Performance Enhancement of Modeling Methods for Effective Solar Power Prediction and Sustainable Operation RK Subrahmanyam Pulipaka BIT's 6th New Energy Forum NEF- Qingdao 2016, At Qingdao China, 2016 | | 2016 |
| Parameter Extraction of Solar Photovoltaic System using Lambert-W Function for Different Environmental Condition RK Prashant Upadhyay, Subrahmanyam Pulipaka, Madhav Sharma IEEE TENCON 2016, 22-25 November Singapore 32, 1886-90, 2016 | | 2016 |
| Maximum power point modeling through irradiance based duty cycle calculation RK Prashant Upadhyay, Pulipaka S European PV Solar Energy Conference and Exhibition, EUPVSEC 2016, Munich …, 2016 | | 2016 |
Rajneesh kumarEEE Department, BITS, Pilani, India在 pilani.bits-pilani.ac.in 的电子邮件经过验证
