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All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Arindam Kumar Sil
Jadavpur University
Electrical & Electronics Engineering

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Development of regional load management system based on rural, semi urban and urban loads-a critical analysis Ayandeep Ganguly; Arindam Kumar Sil
Bulletin of Electrical Engineering and Informatics Vol 11, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i1.3460

Abstract

The sharp rise in population during the last half century has created immense pressure on the resources required for generation of energy essential to lead a comfortable and healthy lifestyle. The drive towards 100% electrification in developing countries like India has also contributed to this increase in demand. Till recently, fossil fuel was use to supply the bulk of this power. Now, the world is moving more and more towards renewable energy. This paper presents a model where several regions are combined together based on the demand profile of the regions segregated as urban, semi urban and rural along with the flexibility to schedule loads on the basis of availability of renewable energy sources within the area of the regions. The main focus is on detailed neural-networking based load forecasting and developing a load management system to manage load based on availability of distributed generation capacity and available tariff system. A solution is proposed in this paper based on a new approach to answer load management on the basis of region, population demographics and per capita energy consumption. A considerable amount of improvement to manage demand is intended to be attained and has been demonstrated in this research work.
Renewable energy based dynamic tariff system for domestic load management Kuheli Goswami; Arindam Kumar Sil
Indonesian Journal of Electrical Engineering and Computer Science Vol 25, No 2: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v25.i2.pp626-638

Abstract

To deal with the present power-scenario, this paper proposes a model of an advanced energy management system, which tries to achieve peak clipping, peak to average ratio reduction and cost reduction based on effective utilization of distributed generations. This helps to manage conventional loads based on flexible tariff system. The main contribution of this work is the development of three-part dynamic tariff system on the basis of time of utilizing power, available renewable energy sources (RES) and consumers’ load profile. This incorporates consumers’ choice to suitably select for either consuming power from conventional energy sources and/or renewable energy sources during peak or off-peak hours. To validate the efficiency of the proposed model we have comparatively evaluated the model performance with existing optimization techniques using genetic algorithm and particle swarm optimization. A new optimization technique, hybrid greedy particle swarm optimization has been proposed which is based on the two aforementioned techniques. It is found that the proposed model is superior with the improved tariff scheme when subjected to load management and consumers’ financial benefit. This work leads to maintain a healthy relationship between the utility sectors and the consumers, thereby making the existing grid more reliable, robust, flexible yet cost effective.
Peak Load Chopping Applying Fuzzy Bayesian Technique For Regional Load Management-Performance Evaluation Arindam Kumar Sil; N. K. Deb; Ashok Kumar Maitra
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 8: August 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i8.pp5963-5968

Abstract

In this paper Fuzzy Bayesian Synthetic algorithm based methodology has been evaluated for its performance using real time data for chopping off peak load demand. This is achieved by judiciously scheduling load from the regional load under a new load management technique. This technique validates the timely decision making capacity of the system to reduce peak demand hence giving us a chance to reduce the peak demand and hence reduce the stress of generating excess power during the peak period. This method uses data of a previous day and then predicts for the next day. Thus by evaluating this process it was found that the new peak demand has a reduced value as compared to the actual peak demand. It is evident that this method can not only reduce peak demand by chopping of the regional loads by following the proposed algorithm but also helps in generating indirect revenue by saving energy. This method authenticates the proposed method and saves peak demand or otherwise energy by about ten to fifty megawatts on daily basis depending on the service condition of the network and solar day light hour availability over span of a day.
Co-Authors Ashok Kumar Maitra Ayandeep Ganguly Kuheli Goswami N. K. Deb