Subhadeep Bhattacharjee

Bio: Subhadeep Bhattacharjee is an academic researcher from National Institute of Technology Agartala. The author has contributed to research in topics: Renewable energy & Photovoltaic system. The author has an hindex of 12, co-authored 43 publications receiving 620 citations.

Grey wolf optimisation for optimal sizing of battery energy storage device to minimise operation cost of microgrid

Abstract: Nowadays, optimal operational planning of micro-grid (MG) with regard to energy costs minimisation of MG and better utilisation of renewable energy sources (RES) such as solar and wind energy systems, has become the head of concern of modern power grids and energy management systems. Due to large integration of RES into the MG, the necessity of battery energy storage (BES) has increased rapidly. Size of BES plays an important role in the operation cost minimisation of MG. A cost-based formulation has been performed in this study to determine the optimal size of BES in the operation cost minimisation problem of MG under various constraints, such as power capacity of distributed generators (DGs), power and energy capacity of BES, charge/discharge efficiency of BES, operating reserve and load demand satisfaction. A recently developed optimisation technique known as grey wolf optimisation (GWO) has been applied here to solve the problem. The proposed algorithm is tested on a typical MG. Simulation results establish that the proposed approach outperforms several existing optimisation techniques such as genetic algorithm, particle swarm optimisation, tabu search, differential evolution, biogeography-based optimisation, teaching–learning-based optimisation, bat algorithm (BA) and improved BA in terms of quality of solution obtained and computational efficiency.

Calculation of monthly average insolation on tilted surfaces

Abstract: Several simplified design procedures for solar energy systems require monthly average meteorological data. Monthly average daily totals of the solar radiation incident on a horizontal surface are available. However, radiation data on tilted surfaces, required by the design procedures, are generally not available. A simple method of estimating the average daily radiation for each calendar month on surfaces facing directly towards the equator has been presented by Liu and Jordan [1]. This method is verified with experimental measurements and extended to allow calculation of monthly average radiation on surfaces of a wide range of orientations.

Grey wolf optimizer: a review of recent variants and applications

Abstract: Grey wolf optimizer (GWO) is one of recent metaheuristics swarm intelligence methods. It has been widely tailored for a wide variety of optimization problems due to its impressive characteristics over other swarm intelligence methods: it has very few parameters, and no derivation information is required in the initial search. Also it is simple, easy to use, flexible, scalable, and has a special capability to strike the right balance between the exploration and exploitation during the search which leads to favourable convergence. Therefore, the GWO has recently gained a very big research interest with tremendous audiences from several domains in a very short time. Thus, in this review paper, several research publications using GWO have been overviewed and summarized. Initially, an introductory information about GWO is provided which illustrates the natural foundation context and its related optimization conceptual framework. The main operations of GWO are procedurally discussed, and the theoretical foundation is described. Furthermore, the recent versions of GWO are discussed in detail which are categorized into modified, hybridized and paralleled versions. The main applications of GWO are also thoroughly described. The applications belong to the domains of global optimization, power engineering, bioinformatics, environmental applications, machine learning, networking and image processing, etc. The open source software of GWO is also provided. The review paper is ended by providing a summary conclusion of the main foundation of GWO and suggests several possible future directions that can be further investigated.

Optimal planning of hybrid renewable energy systems using HOMER: A review

Abstract: World energy consumption is rising due to population growth and increasing industrialization. Traditional energy resources cannot meet these requirements with notice to their challenges, e.g., greenhouse gas emission and high lifecycle costs. Renewable energy resources are the appropriate alternatives for traditional resources to meet the increasing energy consumption, especially in electricity sector. Integration of renewable energy resources with traditional fossil-based resources besides storages creates Hybrid Renewable Energy Systems (HRESs). To access minimum investment and operation costs and also meet the technical and emission constraints, optimal size of HRES׳s equipment should be determined. One of the most powerful tools for this purpose is Hybrid Optimization Model for Electric Renewables (HOMER) software that was developed by National Renewable Energy Laboratory (NREL), United States. This software has widely been used by many researchers around the world. In this paper a review of the state-of-the-art of researches, which use HOMER for optimal planning of HRES, is presented.