P Venkata Mahesh

Verified

P Venkata verified their affiliation via an institutional email.

Learn more

Verified

P Venkata verified their affiliation via an institutional email.

Learn more

• Doctor of Philosophy
• Professor (Assistant) at R.V.R. & J.C. College of Engineering

Adding fast charging stations (FCSs) and photovoltaic systems (PVs) to modern electrical distribution networks (EDNs) can cause problems like voltage fluctuations and more power loss. One way to solve these issues is to use a levy-flight-based improved Pufferfish optimization algorithm (IPOA), which can find better answers to the PVs and FCSs in ED...

Photovoltaic panels use the sun’s radiation on their surface to convert solar energy into electricity. This process is dependent on the temperature of the surface and the intensity of the sun's radiation. To escalate the energy transformation, the solar system must be functioned at its maximum power point (MPP). Every maximum power point tracking (...

This work presents a machine-learning (ML) algorithm for maximum power point tracking (MPPT) of an isolated photovoltaic (PV) system. Due to the dynamic nature of weather conditions, the energy generation of PV systems is non-linear. Since there is no specific method for effectively dealing with the non-linear data, the use of ML methods to operate...

Solar panels generate energy by utilizing the sun rays on their surface, which depends on the amount of surface temperature and the strength of solar radiation. To maximize the energy conversion efficiency, the solar PV panel should operate at maximum power point (MPP). Each maximum power point tracking (MPPT) method has its unique conversion effic...

Operating solar photovoltaic (PV) panels at the maximum power point (MPP) is considered to enrich energy conversion efficiency. Each MPP tracking technique (MPPT) has its conversion efficiency and methodology for tracking the MPP. This paper introduces a new method for operating the PV panel at MPP by implementing the multivariate linear regression...

It is well known that the modeling issues in Dynamical systems in chemical processes, networked control systems and automation systems are very complex and model may contain subsystems with different delays. Because of the mathematical complexity, the robust control of these types of multiple time delay system is a challenging one. The problem beco...

This paper presents a new approach for approximation of multiple time delay transfer function model to a single input/output delay transfer function. The methodology uses concept of model matching technique of comparing an approximated generalized time moments (AGTM)/ approximated generalized markov parameters (AGMP) of one system representation to...