Optimal planning of hybrid energy conversion systems for annual energy cost minimization in Indian residential buildings

Abstract

The increasing interest in renewables has encouraged power system planners to include the concept of hybrid energy systems in modern power industry. Besides, the modern power consumers are becoming more concerned about their energy bills which has led to the concept of hybrid energy management systems (HEMSs) for buildings to monitor, control and optimally manage energy consumptions without any waste. In this study, an optimal planning framework is proposed to determine optimal capacities and sharing of hybrid energy conversion systems (HECS) such as wind turbine, solar photovoltaic, battery energy storage and the utility grid. The objective is to maximize the net present value of the project/system which includes the cost of annual investment, operation and maintenance costs of HEMS expected to have incurred in the planning period. All the costs and parameters are considered in the Indian context, and Genetic Algorithm (GA) is adopted to solve this proposed planning framework. The simulation results obtained are compared with same obtained for conventional houses in India. The comparison shows that the proposed framework effectively reduces the electricity bills while improving its reliability.

Publication DOI: https://doi.org/10.1016/j.egypro.2019.01.965
Divisions: College of Engineering & Physical Sciences
Additional Information: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Uncontrolled Keywords: Genetic algorithm,Hybrid energy conversion systems,Renewables,Smart homes,General Energy
Publication ISSN: 1876-6102
Last Modified: 09 Dec 2024 08:34
Date Deposited: 19 Jul 2019 12:46
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://www.sci ... 0173?via%3Dihub (Publisher URL)
PURE Output Type: Conference article
Published Date: 2019-02-01
Accepted Date: 2019-01-01
Authors: Meena, Nand K. (ORCID Profile 0000-0002-4092-3921)
Kumar, Abhishek
Singh, Arvind R.
Swarnkar, Anil
Gupta, Nikhil
Niazi, K. R.
Kumar, Praveen
Bansal, R. C.

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