Visvesvaraya National Institute of Technology

About: Visvesvaraya National Institute of Technology is a education organization based out in Nagpur, India. It is known for research contribution in the topics: Inverter & Computer science. The organization has 2347 authors who have published 4266 publications receiving 43648 citations.

A review of multi criteria decision making (MCDM) towards sustainable renewable energy development

Abstract: In the current era of sustainable development, energy planning has become complex due to the involvement of multiple benchmarks like technical, social, economic and environmental. This in turn puts major constraints for decision makers to optimize energy alternatives independently and discretely especially in case of rural communities. In addition, topographical limitations concerning renewable energy systems which are mostly distributed in nature, the energy planning becomes more complicated. In such cases, decision analysis plays a vital role for designing such systems by considering various criteria and objectives even at disintegrated levels of electrification. Multiple criteria decision making (MCDM) is a branch of operational research dealing with finding optimal results in complex scenarios including various indicators, conflicting objectives and criteria. This tool is becoming popular in the field of energy planning due to the flexibility it provides to the decision makers to take decisions while considering all the criteria and objectives simultaneously. This article develops an insight into various MCDM techniques, progress made by considering renewable energy applications over MCDM methods and future prospects in this area. An extensive review in the sphere of sustainable energy has been performed by utilizing MCDM technique.

A Simplified Nearest Level Control (NLC) Voltage Balancing Method for Modular Multilevel Converter (MMC)

Abstract: In this paper, a simplified nearest level control balancing method for modular multilevel converter is presented. The proposed method neither requires individual sorting of the submodule voltages nor the redundancy of the switching states. Once the sorting of the submodules is done on the basis of the number of the submodules to be switched on, the identifications of the submodules can be carried out throughout the stages of the implementation of the this method. The proposed method also does not require the individual submodule status in the gate pulse generation stage. The gate logic in the presented method can be implemented with the help of the switching states of the voltage levels. Those simplifications and removing of the some of the stages by the proposed balancing method may ease and lead to the less processor time at the implementation level. The pictorial presentation further helps in consolidating the understanding of the different stages of the method. Rigorous simulations are carried out for open and one of the prominent closed-loop applications, i.e., modular multilevel converter-based high-voltage direct current to demonstrate the validity and effectiveness of the proposed simplified balancing method under normal and emergency conditions.

A Systematic Review of Compressive Sensing: Concepts, Implementations and Applications

Abstract: Compressive Sensing (CS) is a new sensing modality, which compresses the signal being acquired at the time of sensing. Signals can have sparse or compressible representation either in original domain or in some transform domain. Relying on the sparsity of the signals, CS allows us to sample the signal at a rate much below the Nyquist sampling rate. Also, the varied reconstruction algorithms of CS can faithfully reconstruct the original signal back from fewer compressive measurements. This fact has stimulated research interest toward the use of CS in several fields, such as magnetic resonance imaging, high-speed video acquisition, and ultrawideband communication. This paper reviews the basic theoretical concepts underlying CS. To bridge the gap between theory and practicality of CS, different CS acquisition strategies and reconstruction approaches are elaborated systematically in this paper. The major application areas where CS is currently being used are reviewed here. This paper also highlights some of the challenges and research directions in this field.