Optimal Scheduling of Household Appliances in Off-Grid Hybrid Energy System using PSO Algorithm for Energy Saving

Abderraouf BOUAKKAZ, Salim HADDAD, Juan Andrés Martín- García, Antonio Jose-Gil Mena, Rafael Jiménez Castañeda

Abstract


 

In a stand-alone renewables energy system (SRES), maintaining the balance of power between supply and demand with minimum cost in homes connected to these systems present one of the most important challenges to consider. In SRES, a large capacity of batteries is usually used to store the energy and reuse it when the absence or insufficient power supply to maintain energy balance. However, the batteries are costly, as well as a large amount of power lost during the charging and discharging process, represent big issues that should be avoided.  One of the most important tools to redress these issues is the scheduling strategy for household appliances. In this paper, Particle Swarm Optimization Algorithm (PSO) is proposed to schedule the household appliances in the off-grid hybrid energy system (PV, Wind turbine, batteries, and diesel generator) with the objective of saving energy and reduce the energy consumption cost (i.e. energy of diesel) by maximizing the using the power of renewable energy sources and minimizing using the power of batteries. The scheduling algorithm is based on the data forecast of one day ahead of renewable energy and the daily load power consumption profile, a case study of meteorological data in the south of Spain are  selected and tested for the simulation. Two scenarios of scheduling strategy are presented and compared with the scenario without scheduling of appliances. The simulation results show that the optimization of cost reached to 50% with 0.472 kWh of energy saved in scheduling with user preferences and can be reached up to 64% with 0.811 kWh of energy saved in case of optimal scheduling which considered the optimal for saving energy.


Keywords


Off-grid renewable energy system, household appliance, Scheduling, Particle swarm optimization, Energy cost reduction, Energy saving

Full Text:

PDF

References


International Energy Agency (IEA), WEO-2017 Special Report: Energy Access Outlook, (2017) 1–143. doi:ceo871024 .

P.Cook, "Rural Electrification and Rural Development", London: Springer-verlag, 1985, ch.2.

K. Abdulla, A.I. Mamun, Z. Uddin, L. Guha, S. Ahmed, S.G. Mostafa, "A Proposed Hybrid Renewable System To Minimize Power Crisis For Remote Area ( Kamalchor , Rangamati Hill-Tract )", pp. (2015)..

Y. Lu, S. Wang, K. Shan, Design optimization and optimal control of grid-connected and standalone nearly/net zero energy buildings, Appl. Energy. 155 (2015) 463–477. doi:10.1016/j.apenergy.2015.06.007.

S. Byhan, Y. Liu, S. Demirbas, " A Noval Energy Management Algorithm for Islanded AC M icrogrid with Limited Power Sources", Internatinal Conference on Renewable Energy Research and Applications, (ICRERA), 2017.

S. Mane, P. Kadam, G. Lahoti, F. Kazi, N.M. Singh, "Optimal Load Balancing Strategy for Hybrid Energy Management System in DC Microgrid with PV , Fuel Cell and Battery Storage", Internatinal Conference on Renewable Energy Research and Applications, (ICRERA), Vol. 5,pp. 1–6, 2016.

P. Mazidi, G. Baltas, M. Eliassi, "A Model for Flexibility Analysis of RESS with Electric Energy Storage and Reserve", Internatinal Conference on Renewable Energy Research and Applications, (ICRERA), 2017.

M. Chaindone, C. Tam, R. Campaner, G. Sulligoi," Electrical storage in distribution grids with renewable energy sources", Internatinal Conference on Renewable Energy Research and Applications, (ICRERA), 2017..

E. Hossain, R. Perez, R. Bayindir, " Implementation of Hybrid Energy Storage Systems to CompenstateMicrogrid Instability in the Presence of Constant Power Loads", Internatinal Conference on Renewable Energy Research and Applications, (ICRERA), Vol. 5,pp. 3–8, 2016.

N. Erniza, M. Rozali, S. Ra, W. Alwi, Z. Abdul, "Process integration of hybrid power systems with nergy losses considerations", Energy, pp. 1–8, 2013 .

M. Chaindone, R. Campaner, A. Massi Pavan, G. Sulligoi, P. Manià , G. Piccoli, " Impact of Distributed Generation on Power Losses on an Actual Distribution Network", Internatinal Conference on Renewable Energy Research and Applications, (ICRERA), pp. 1007–1011, 2014.

A. Ganguly, S. Ghosh, T. Mukhopadhyay, "A Review on Performance , Emission and Combustion Characteristics of Biodiesel Blends in a Diesel Engine with Varying Injection Pressures", nt. J. Renew. ENERGY Res, Vol. 7, N. 4, 2017.

L. Yao, S. Member, W. Chang, R. Yen, "An Iterative Deepening Genetic Algorithm for Scheduling of Direct Load Control", IEEE Transactıons on power systems,Vol. 20, pp. 1414–1421, , AUGUST 2005.

P. Du, N. Lu, "Appliance commitment for household load scheduling", IEEE Trans. Smart Grid, doi:10.1109/TSG.2011.2140344, Vol. 2, pp. 411–419, June2011.

B. Zhou, W. Li, K.W. Chan, Y. Cao, Y. Kuang, X. Liu, X. Wang, "Smart home energy management systems: Concept, configurations, and scheduling strategies", Renew. Sustain. Energy Rev, doi:10.1016/j.rser.2016.03.047, Vol. 61, pp. 30–40, 2016.

M.S. Ahmed, A. Mohamed, T. Khatib, H. Shareef, R.Z. Homod, J.A. Ali, "Real time optimal schedule controller for home energy management system using new binary backtracking search algorithm", Energy Build, doi:10.1016/j.enbuild.2016.12.052, Vol. 138, pp. 215–227, 2017.

D. Setlhaolo, X. Xia, J. Zhang, "Optimal scheduling of household appliances for demand response", Electr. Power Syst. Res, doi:10.1016/j.epsr.2014.04.012, Vol. 116, pp. 24–28, 2014.

S. Lin, C. Chen, "Optimal energy consumption scheduling in home energy management system",International Conference on Machine Learning and Cybernetics, Jeju, South Korea, pp. 10-13 July, 2016.

D. Zhang, N. Shah, L.G. Papageorgiou, "Efficient energy consumption and operation management in a smart building with microgrid", Energy Convers. Manag, doi:10.1016/j.enconman.2013.04.038, Vol. 74, pp. 209–222, 2013.

K. Ma, S. Hu, J. Yang, X. Xu, X. Guan, "Appliances scheduling via cooperative multi-swarm PSO under day-ahead prices and photovoltaic generation", Appl. Soft Comput. J, doi:10.1016/j.asoc.2017.09.021, Vol. 62, pp. 504–513, 2018.

A.H. Habib, V.R. Disfani, J. Kleissl, R.A. De Callafon, "Optimal switchable load sizing and scheduling for standalone renewable energy systems", Sol. Energy, doi:10.1016/j.solener.2017.01.065, Vol. 144, pp. 707–720, 2017.

Y. Riffonneau, S. Bacha, F. Barruel, S. Ploix, "Optimal Power Flow Management for Grid Connected PV Systems With Batteries", IEEE Trans. Sustain. Energy, doi:10.1109/TSTE.2011.2114901, Vol. 2, pp. 309–320, 2011.

C.M.T. Huang, Y.C. Huang, K.Y. Huang, "A hybrid method for one-day ahead hourly forecasting of PV power output", 9th IEEE Conf. Ind. Electron. Appl. ICIEA, Vol. 5, pp. 526–531, 2014..

L. Wang, C. Singh, "PSO-Based Multi-Criteria Optimum Design of A Grid-Connected Hybrid Power System With Multiple Renewable Sources of Energy", In: Swarm intelligence symposium. SIS, IEEE, pp. 250–257, 2007.

J.F. Manwell, J.G.McGowan, “Extension of the Kinetic Battery Model for Wind/Hybrid Power Systemsâ€. Proceedings of EWEC, pp. 284–289, 1994.

Skarstein O, Uhlen K,“Design considerations with respect to long-term diesel saving in wind/diesel plantsâ€. Wind Eng, Vol.13(2), pp. 72–87, 1989.

J. Kennedy, R. Eberhart, "Particle Swarm Optimization", International Conference on Neural Networks, pp. 1942–1948, 1995.




DOI (PDF): https://doi.org/10.20508/ijrer.v9i1.8860.g7599

Refbacks



Online ISSN: 1309-0127

Publisher: Gazi University

IJRER is cited in SCOPUS, EBSCO, WEB of SCIENCE (Clarivate Analytics);

IJRER has been cited in Emerging Sources Citation Index from 2016 in web of science.

WEB of SCIENCE between 2020-2022; 

h=30,

Average citation per item=5.73

Impact Factor=(1638+1731+1808)/(189+170+221)=9.24

Category Quartile:Q4