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.

Realization of 5-bus system using soft computing technique for flexible alternating current transmission system (FACTS) devices

Abstract: Total transfer capability analysis of power system is currently a critical issue in both planning & operating of systems. These issues mainly occur due to increase in area and interchanges among utilities. To reduce the flows in heavily loaded lines, Flexible Alternating Current Transmission System (FACTS) devices is used, this results in increased transfer capability, improve stability of the network, low system losses, and fulfill contractual required by controlling the power flows in the network. To achieve parameters FACTS devices are placed optimally and is done with the help of reduction of total system reactive power loss sensitivity indices analysis method and real power flow performance index sensitivity indices analysis method. Thyristor-Control-Series-Capacitor (TCSC) is used as a FACTS device in the proposed sensitivity analysis method. To decide priority of line for placing TCSC, soft computing technique "Fuzzy logic method" is employed. The performance evaluation of proposed sensitivity analysis methods is done using electrical IEEE-5 bus system. The sensitivity indices are programmed using Matrix Laboratory.

An adaptive-neuro fuzzy inference system based-hybrid technique for performing load disaggregation for residential customers

Abstract: Effective and efficient use of energy is key to sustainable industrial and economic growth in modern times. Demand-side management (DSM) is a relatively new concept for ensuring efficient energy use at the consumer level. It involves the active participation of consumers in load management through different incentives. To enable the consumers for efficient energy management, it is important to provide them information about the energy consumption patterns of their appliances. Appliance load monitoring (ALM) is a feedback system used for providing feedback to customers about their power consumption of individual appliances. For accessing appliance power consumption, the determination of the operating status of various appliances through feedback systems is necessary. Two major approaches used for ALM are intrusive load monitoring (ILM) and non-intrusive load monitoring (NILM). In this paper, a hybrid adaptive-neuro fuzzy inference system (ANFIS) is used as an application for NILM. ANFIS model being sophisticated was difficult to work with, but ANFIS model helps to achieve better results than other competent approaches. An ANFIS system is developed for extracting appliance features and then a fine tree classifier is used for classifying appliances having more than 1 kW power rating based on the extracted feature. Several case studies have been performed using ANFIS on a publicly available United Kingdom Domestic Appliance Level Electricity (UK-Dale dataset). The simulation results obtained from the ANFIS for NILM are compared with relevant literature to show the performance of the proposed technique. The results prove that the novel application of ANFIS gives better performance for solving the NILM problem as compared to the other existing techniques.

Mitigation of Complex Non-Linear Dynamic Effects in Multiple Output Cascaded DC-DC Converters

Abstract: In the modern world of technology, the cascaded DC-DC converters with multiple output configurations are contributing a dominant part in the DC distribution systems and DC micro-grids. An individual DC-DC converter of any configuration exhibits complex non-linear dynamic behavior resulting in instability. This paper presents a cascaded system with one source boost converter and three load converters including buck, Cuk, and Single-Ended Primary Inductance Converter (SEPIC) that are analyzed for the complex non-linear bifurcation phenomena. An outer voltage feedback loop along with an inner current feedback loop control strategy is used for all the sub-converters in the cascaded system. To explain the complex non-linear dynamic behavior, a discrete mapping model is developed for the proposed cascaded system and the Jacobian matrix’s eigenvalues are evaluated. For the simplification of the analysis, every load converter is regarded as a fixed power load (FPL) under reasonable assumptions such as fixed frequency and input voltage. The eigenvalues of period-1 and period-2 reveal that the source boost converter undergoes period-2 orbit and chaos whereas all the load converters operate in a stable period-1 orbit. The proposed configuration eliminates the period-2 and chaotic behavior from all the load converters and is also validated using simulation in MATLAB/Simulink and experimental results.

Exact path delay grading with fundamental BDD operations

Abstract: Formulates the fault grading problem as a combinatorial problem that amounts to storing and manipulating sets on a special type of binary decision diagrams (BDDs), called zero-suppressed BDDs (ZBDDs), that represent sets in a unique and compact manner. A simple modification of the basic scheme allows us to overcome memory problems that may arise by complex set representation. Experimental results on the ISCAS'85 benchmarks show considerable improvement over all existing techniques for exact PDF grading. The main advantages of the proposed methodology are the simplicity of the approach, in terms of it being expressed by a polynomial number of increasingly efficient BDD-based operations, its organization, and its ability to handle very large test sets.

A New Multilevel Member of Modified CUK Converter Family for Renewable Energy Applications

Abstract: A new multilevel family member of Modified CUK Converter (MCC) by topping up with Voltage Multiplier (VM) to term as MCC VM is developed in this article. Suitable goal to generate high-voltage output and fits the renewable energy applications. By integrating the specific arrangement of diodes and capacitors in MCC, the voltage gain is boosted in the proposed MCC VM converter. An effective solution for renewable energy applications such as PV, fuel cell, etc. Features of the proposed converter are (a) single switch topology which required simple digital control scheme, (b) low-voltage stress on switch as compare to the output voltage, (c) continuous input current, (d) inverted output with respective to the input voltage. The operating principle, the mathematical derivation of proposed MCC VM converter are discussed in the paper. The functionality and performance of the proposed high-voltage converter are verified by means of MatLab (R2016a) numerical simulation. Followed by the experimental verifications through hardware prototype model and which always show a good agreement with the numerical simulation and theoretical analysis.

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