Multi Objective Slime Mould Algorithm Based Energy Management in Hybrid Micro Grid System

Jump To References Section

Authors

  • Suravi Singha
     Department of Electrical Engineering, Kalyani Government Engineering College, Kalyani-741235 ,IN
  • Parthasarathi Bera
     Department of Electrical Engineering, Kalyani Government Engineering College, Kalyani-741235 ,IN

DOI:

https://doi.org/10.24906/isc/2023/v37/i4/43717

Keywords:

Micro grid, Renewable Energy Sources, Multi-objective slime Mould Algorithm (MOSMA).

Abstract

The effective operation of Micro-grid systems involves reconciling multiple conflicting objectives, including cost minimization, renewable energy utilization maximization and emissions reduction. This study proposes the application of recently developed Multi- objective slime mould algorithm (MOSMA) to address the challenges for minimizing cost and emission of a hybrid micro-grid system connected with utility grid. Further, the results are compared with another optimization algorithm to show its efficiency, economic viability, and environmental impact for green micro-grids.

Downloads

Download data is not yet available.

Downloads

Published

2024-05-09

How to Cite

Singha, S., & Bera, P. (2024). Multi Objective Slime Mould Algorithm Based Energy Management in Hybrid Micro Grid System. Indian Science Cruiser, 37(4), 38–47. https://doi.org/10.24906/isc/2023/v37/i4/43717

Issue

Volume 37, Issue 4, July 2023

Section

Feature Article
Crossref
Scopus
Google Scholar
Europe PMC

 

References

M Alilou, B Tousi, H Shayeghi, Home energy management in a residential smart micro grid under stochastic penetration of solar panels and electric vehicles, Solar Energy, Vol 212, page 6–18, 2020. https://doi.org/10.1016/j.solener.2020.10.063

B Y Ekren, O Ekren, Simulation based size optimization of a PV/wind hybrid energy conversion system with battery storage under various load and auxiliary energy conditions, Applied Energy, Vol 86, No 9, page 1387–1394, 2009. https://doi. org/10.1016/j.apenergy.2008.12.015

M Elsied, A Oukaour, H Gualous, S Youssef, R Hassan, A A Amin, Analysis, modeling, and control of an AC microgrid system based on green energy, Renewable Energy and Power Quality Journal, Vol 10, No 12 page 896–901, 2014. https://doi. org/10.24084/repqj12.525

A Kumar, M Z U Khan, B Pandey: Wind Energy: A review paper, Gyancity Journal of Engineering and Technology, Vol 4, No 2, page 29–37, 2018. https:// doi.org/10.21058/gjet.2018.42004

Z Ullah, M Baseer, Operational planning and design of market-based virtual power plant with high penetration of renewable energy sources. International Journal of Renewable Energy Development, Vol 11, No 3, page 620–629, 2022. https://doi.org/10.14710/ijred.2022.44586

Y Zheng, B M Jenkins, K Kornbluth, A Kendall, C Traeholt, Optimization of a biomass-integrated renewable energy microgrid with demand side management under uncertainty, Applied Energy, Vol 230, page 836–844, 2018. https://doi. org/10.1016/j.apenergy.2018.09.015

T Niknam, F Golestaneh, M Shafiei, Probabilistic energy management of a renewable microgrid with hydrogen storage using self-adaptive charge search algorithm, Energy, Vol 49, page 252–267, 2013. https://doi.org/10.1016/j.energy.2012.09.055

M Elsied, A Oukaour, H Gualous, R Hassan, Energy management and optimization in microgrid system based on green energy, Energy, Vol 84, page 139–151, 2015. https://doi.org/10.1016/j. energy.2015.02.108

S Behera, N B D Choudhury, S Biswas Maiden application of the Slime mould algorithm for optimal operation of energy management on a microgrid considering demand response Program, SN Computer Science, Vol 4, No 5, 2023. https://doi. org/10.1007/s42979-023-02011-9

J L Bernal-Agustín, R Dufo-López, Simulation and optimization of stand-alone hybrid renewable energy systems, Renewable & Sustainable Energy Reviews, Vol 13, No 8, page 2111–2118, 2009. https://doi.org/10.1016/j.rser.2009.01.010

W Su, J Wang, Energy management systems in micro-grid operations. The Electricity Journal, Vol 25 No 8, page 45–60, 2012. https://doi.org/10.1016/j. tej.2012.09.010

M Motevasel, A R Seifi, T Niknam, Multi-objective energy management of CHP (combined heat and power)-based micro-grid, Energy, Vol 51, page 123–136, 2013. https://doi.org/10.1016/j. energy.2012.11.035

M H Moradi, M Hajinazari, S Jamasb, M Paripour, An energy management system (EMS) strategy for combined heat and power (CHP) systems based on a hybrid optimization method employing fuzzy programming, Energy, Vol 49, page 86–101, 2013. https://doi.org/10.1016/j.energy.2012.10.005

Y Zhang, N Gatsis, G B Giannakis, Robust energy management for microgrids with High-Penetration renewables. IEEE Transactions on Sustainable Energy, Vol 4, No 4, page 944–953, 2013. https://doi. org/10.1109/tste.2013.2255135

P Basak, S Chowdhury, S Dey, S Chowdhury, A literature review on integration of distributed energy resources in the perspective of control, protection and stability of microgrid. Renewable & Sustainable Energy Reviews, Vol 16, No 8, page 5545–5556, 2012. https://doi.org/10.1016/j. rser.2012.05.043

J J Justo, F Mwasilu, J Lee, J W Jung: AC- microgrids versus DC-microgrids with distributed energy resources: A review. Renewable & Sustainable Energy Reviews, Vol 24, page 387–405, 2013. https://doi.org/10.1016/j.rser.2013.03.067

J Shi, L Ma, C Li, N Liu & J Zhang, A comprehensive review of standards for distributed energy resource grid-integration and microgrid. Renewable & Sustainable Energy Reviews, Vol 170, No 112957, 2022. https://doi.org/10.1016/j.rser.2022.112957

P J Mago, A D Smith, Evaluation of the potential emissions reductions from the use of CHP systems in different commercial buildings. Building and Environment, Vol 53, Page 74–82, 2012. https://doi. org/10.1016/j.buildenv.2012.01.006

A D Smith, P J Mago, N Fumo, Benefits of thermal energy storage option combined with CHP system for different commercial building types. Sustainable Energy Technologies and Assessments, Vol 1, page 3–12, 2013. https://doi.org/10.1016/j. seta.2012.11.001

M Bianchi, A De Pascale, F Melino, Performance analysis of an integrated CHP system with thermal and Electric Energy Storage for residential application, Applied Energy, Vol 112, page 928–938, 2013. https://doi.org/10.1016/j. apenergy.2013.01.088

A Arsalis S K Kaer, M P Nielsen, Modeling and optimization of a heat-pump-assisted high temperature proton exchange membrane fuel cell micro-combined-heat-and-power system for residential applications, Applied Energy, Vol 147, page 569–581, 2015. https://doi.org/10.1016/j. apenergy.2015.03.031

F G Montoya, C Gil, A Alcayde, J Gómez, Optimization methods applied to renewable and sustainable energy: A review, Renewable & Sustainable Energy Reviews, Vol 15, No 4, page 1753–1766, 2011. https://doi.org/10.1016/j. rser.2010.12.008

M Fadaee, M a M Radzi, Multi-objective optimization of a stand-alone hybrid renewable energy system by using evolutionary algorithms: A review, Renewable & Sustainable Energy Reviews, Vol 16, No 5, page 3364–3369, 2012. https://doi. org/10.1016/j.rser.2012.02.071

T Niknam, R Azizipanah-Abarghooee, M R Narimani, An efficient scenario-based stochastic programming framework for multi-objective optimal micro-grid operation, Applied Energy, Vol 99, page 455–470, 2012. https://doi.org/10.1016/j. apenergy.2012.04.017

S Mohammadi, B Mozafari, S Soleymani, Optimal operation management of microgrids using the point estimate method and firefly algorithm while considering uncertainty, Turkish Journal of Electrical Engineering and Computer Sciences, Vol 22, page 735–753, 2014. https://doi.org/10.3906/elk- 1207-131

M Premkumar, P Jangir, R Sowmya, H H Alhelou, A A Heidari , H Chen, MOSMA: Multi-Objective Slime Mould algorithm based on Elitist Non-Dominated Sorting, IEEE Access, Vol 9, page 3229–3248, 2021. https://doi.org/10.1109/access.2020.3047936

S Khunkitti, A Siritaratiwat, S Premrudeepreechacharn, Multi-Objective optimal power flow problems based on Slime Mould algorithm. Sustainability, Vol 13, No 13, page 7448, 2021. https://doi.org/10.3390/su13137448

E H Houssein, M A Mahdy, D Shebl, A Manzoor, R Sarkar, W M Mohamed, An efficient slime mould algorithm for solving multi-objective optimization problems. Expert Systems With Applications, Vol 187, No 115870, 2022. https://doi.org/10.1016/j. eswa.2021.115870

M Al-Kaabi, V Dumbrava, M Eremia, A Slime Mould Algorithm Programming for Solving Single and Multi-Objective Optimal Power Flow Problems with Pareto Front Approach: A Case Study of the Iraqi Super Grid High Voltage, Energies, Vol 15, No 20, 7473, 2022. https://doi.org/10.3390/en15207473

TZhu,HWan,ZOuyang,TWu,LJi,WLi,BLi,S Han, Multi-objective slime mold Algorithm: A slime mold approach using multi-objective optimization for parallel hybrid power system, Sensors and Materials, Vol 34, No 10, page 3837, 2022. https:// doi.org/10.18494/sam4020

S Li, H Chen, M Wang, A A Heidari, S Mirjalili, Slime mould algorithm: A new method for stochastic optimization, Future Generation Computer Systems, Vol 111, Page 300–323, 2020. https://doi. org/10.1016/j.future.2020.03.055