Abstract
In the last few decades, developing countries power demand has increased which lead to several critical issues like frequent power outages and peak pricing hours. Utilization of distributed energy sources along with utility grid has helped to cope with these issues to certain level but still there are some loopholes. Novel intelligent algorithms are needed to handle such hybrid systems. In this paper, an algorithm is proposed for consistent and cost effective power supply for Grid-connected photovoltaic system which considers a set of constraints i.e. load-shedding hours, tariff hours and weather conditions. This paper proposes genetic algorithm for making optimal decision for the cost, considering all the above mentioned constraints. The research has also presented another heuristic algorithm which takes much less computation time then Genetic Algorithm and provides comparable results.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Mohsenian-Rad, H.: Communications and Control in Smart Grid, Department of Electrical & Computer Engineering, Texas Tech University (2012)
U.S. Department of Energy by Litos Strategic Communication: Exploring the Imperative of Revitalizing America’s Electric Infrastructure (2010)
Marry, G.A., Rajarajeswari, R.: Smart grid cost optimization using genetic algorithm. IJRET 3(7), 282–287 (2014)
Jeon, G., Kim, Y.B., Park, J.: Agent based smart grid modeling. In: IEEE Winter Simulation Conference (WSC), pp. 3114–3115, December 2015
Worighi, I., Maach, A., Hafid, A.: Modeling a smart grid using objects interaction. In: IEEE 2015 3rd International Renewable and Sustainable Energy Conference (IRSEC), pp. 1–6 December 2015
Meeran, S., Morshed, M.S.: A hybrid genetic tabu search algorithm for solving job shop scheduling problems: a case study, Springer Science + Business Media, LLC (2011)
Aci, M., Inan, C., Avci, M.: A hybrid classification method of k nearest neighbor, bayesian methods and genetic algorithm. Expert Syst. Appl. 37, 5061–5067 (2010)
Metaxiotis, K., Liagkouras, K.: Multiobjective evolutionary algorithms for portfolio management: a comprehensive literature review. Expert Syst. Appl. 39, 11685–11698 (2012)
Rennera, G., Ekárt, A.: Genetic algorithms in computer aided design. Comput. Aided Des. 35, 709–726 (2003)
Lin, H., Wagholikar, K., Yang, Z.: Identifying protein complexes with fuzzy machine learning model. In: IEEE International Conference on Bioinformatics and Biomedicine, October 2012
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG
About this paper
Cite this paper
Ahmad, N., Bibi, R., Khan, S.A. (2018). Cost Effective Provisioning of Electricity in Smart Nano-grid Using GA and Optimized Heuristic Algorithm. In: Carvalho, J., Martins, D., Simoni, R., Simas, H. (eds) Multibody Mechatronic Systems. MuSMe 2017. Mechanisms and Machine Science, vol 54. Springer, Cham. https://doi.org/10.1007/978-3-319-67567-1_33
Download citation
DOI: https://doi.org/10.1007/978-3-319-67567-1_33
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-67566-4
Online ISBN: 978-3-319-67567-1
eBook Packages: EngineeringEngineering (R0)