Sanjeevikumar Padmanaban

Bio: Sanjeevikumar Padmanaban is an academic researcher from Aarhus University. The author has contributed to research in topics: Photovoltaic system & Boost converter. The author has an hindex of 34, co-authored 367 publications receiving 5244 citations. Previous affiliations of Sanjeevikumar Padmanaban include Sathyabama University & National Institute of Technology, Puducherry.

Identification of Sludge in Water Pumping System Using Support Vector Machine

Abstract: Pumps playa pivotal role in both energy and water conservation. They account for the 20% of the world's total energy consumption and thus monitoring it becomes more relevant to decrease an energy wastage. The performance of the pump deteriorates for various reasons, such as cavitation, sedimentation of silt and water hammering, electrical and mechanical faults. Performance of the pump under silt-laden and identification of silt is seldom studied. It causes severe damage in the pumping system. Identification of sludge particles can productively result in energy savings, water conservation, and energy efficiency. With the advent of machine learning and artificial intelligence, pumps can incorporate these methods to become self-reliant in the identification of type and concentration of silt while pumping the fluid. Machine learning is a modern advanced technology, which leads to predict the anomalies of the machine in ground level. This paper presents the how to identify and predict sludge problem in water pumping system using machine learning algorithm.

Boundary Detection and Enhancement of Islanding Operation Investigation Under Fault Condition

Abstract: Distribution systems can form islands when faults occur. Each island represents a subsection with variable boundaries subject to the location of a fault(s) in the system. A subsection with variable boundaries is referred to as island in this paper. For operation in autonomous mode, it is imperative to detect the island configurations and stabilize these subsections. This paper presents a novel scheme for the detection of islanding boundaries and stabilizing the system during autonomous operation. In the first stage, a boundary detection method is proposed to detect the configuration of the island. In the second stage a dynamic voltage sensitivity factor (DVSF) is proposed to assess the dynamic performance of the system. In the third stage, a wide area load shedding program is adopted based on DVSF to shed the load in weak busbars and stabilize the system. The proposed scheme is validated and tested on a generic 18-bus system using a combination of EMTDC/PSCAD and MATLAB softwares.

Using an Intelligent Control Method for Electric Vehicle Charging in Microgrids

Abstract: Recently, electric vehicles (EVs) that use energy storage have attracted much attention due to their many advantages, such as environmental compatibility and lower operating costs compared to conventional vehicles (which use fossil fuels). In a microgrid, an EV that works through the energy stored in its battery can be used as a load or energy source; therefore, the optimal utilization of EV clusters in power systems has been intensively studied. This paper aims to present an application of an intelligent control method to a bidirectional DC fast charging station with a new control structure to solve the problems of voltage drops and rises. In this switching strategy, the power converter is modeled as a DC fast charging station, which controls the fast charging of vehicles with a new constant current or reduced constant current method and considers the microgrid voltage stability. The proposed method is not complicated because simple direct voltage control realizes the reactive power compensation, which can provide sufficient injected reactive power to the network. As a result, the test is presented on a fast charging system of electrical outlets with a proposed two-way reactive power compensation control strategy, in which AC/DC converters are used to exchange two-way reactive power to maintain the DC link voltage as well as the network bus voltage in the range of the basis. This charging strategy is carried out through the simulation of fast charge control, DC link voltage control, and reactive power compensation control to adjust the voltage and modify the power factor in the MATLAB software environment and is then verified. Finally, the results indicate that the proposed method can charge with high safety without increasing the battery’s maximum voltage. It can also significantly reduce the charging time compared to the common CV mode.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Exoelectrogenic bacteria that power microbial fuel cells

Abstract: The use of microbial fuel cells to generate electrical current is increasingly being seen as a viable source of renewable energy production In this Progress article, Bruce Logan highlights recent advances in our understanding of the mechanisms used by exoelectrogenic bacteria to generate electrical current and the important factors to consider in microbial fuel cell design There has been an increase in recent years in the number of reports of microorganisms that can generate electrical current in microbial fuel cells Although many new strains have been identified, few strains individually produce power densities as high as strains from mixed communities Enriched anodic biofilms have generated power densities as high as 69 W per m2 (projected anode area), and therefore are approaching theoretical limits To understand bacterial versatility in mechanisms used for current generation, this Progress article explores the underlying reasons for exocellular electron transfer, including cellular respiration and possible cell–cell communication