Scheduling of smart home appliances for optimal energy management in smart grid using Harris-hawks optimization algorithm

With arrival of advanced technologies, automated appliances in residential sector are still in unlimited growth. Therefore, the design of new management schemes becomes necessary to be achieved for the electricity demand in an effort to ensure safety of domestic installations. To this end, the Demand Side Management (DSM) is one of suggested solution which played a significant role in micro-grid and Smart Grid systems. DSM program allows end-users to communicate with the grid operator so they can contribute in making decisions and assist the utilities to reduce the peak power demand through peak periods. This can be done by managing loads in a smart way, while keeping up customer loyalty. Nowadays, several DSM programs are proposed in the literature, almost all of them are focused on the domestic sector energy management system. In this original work, four heuristics optimization algorithms are proposed for energy scheduling in smart home, which are: bat algorithm, grey wolf optimizer, moth flam optimization, algorithm, and Harris hawks optimization (HHO) algorithm. The proposed model used in this experiment is based on two different electricity pricing schemes: Critical-Peak-Price and Real-Time-Price. In addition, two operational time intervals (60 min and 12 min) were considered to evaluate the consumer’s demand and behavior of the suggested scheme. Simulation results show that the suggested model schedules the appliances in an optimal way, resulting in electricity-cost and peaks reductions without compromising users’ comfort. Hence, results confirm the superiority of HHO algorithm in comparison with other optimization techniques.

\(L\left( t \right)\) :

Energy-consumption of all appliances at time slot t

\(E_{a,\,\,t}^{price}\) :

Electricity-price at any time interval t

\(E_{\text{interru}}\) :

Energy consumed by interruptible appliances

\(E_{shiftable}\) :

Energy consumed by non-interruptible appliances

\(E_{fixed}\) :

Energy consumed by fixed appliances

\(\varphi_{app}\) :

Power rating of () appliance

t :

Time-slot

\(IN\) :

Group of interruptible appliances

\(X\left( t \right)\) :

Status of appliances OFF\ON

\(X_{fixed}^{\text{app}}\) :

State of fixed appliances OFF\ON

\(X_{Shiftable}^{\text{app}}\) :

State of shiftable appliances OFF\ON

\(X_{in}^{\text{app}}\) :

State of interruptible-appliances OFF\ON

\(\varphi_{in}^{t}\) :

Power-rating of interruptible-appliances

\(\varphi_{Shiftable}^{t}\) :

Power-rating of shiftable appliances

\(\varphi_{fixed}^{t}\) :

Power-rating of fixed appliances

\(L_{total}^{Sched}\) :

Total-load scheduled per 24-h

\(L_{total}^{Unsched}\) :

Total-load unscheduled during 24-h

\(C_{total}^{Sched}\) :

Total-cost scheduled per 24-h

\(C_{total}^{USched}\) :

Total-cost unscheduled during 24-h

\(t_{\alpha }\) :

Start time of appliance

\(t_{\beta }\) :

End time of appliance

PAR:

Peak average ratio

EC:

Electricity cost

LoT:

Length of operation time

RTP:

Real time pricing

CPP:

Critical peak pricing

ToU:

Time of use

SG:

Smart grid

DSM:

Demand side management

RES:

Renewable energy sources

HHO:

Harris hawks optimization

GWO:

Grey wolf optimizer

MFO:

Moth flam optimizer

BA:

Bat algorithm

PSO:

Particle-swarm-optimization

GA:

Genetic-algorithm

DE:

Differential-evolution

SSA:

Salp swarm algorithm

Many thanks to the Electrical Engineering Department, Faculty of Sciences and Applied Sciences at Bouira University for financing this work. This work was conducted fully in Department of Electrical Engineering at University of Jaen; Spain.

This work was supported in part by the Exceptional National Program of Algeria PNE and the Key Program of Fundamental Research of Electrical Engineering Department at Jaen University, Spain 2020.

Authors and Affiliations

1. Department of Electrical Engineering, University of Farhat Abbas, Sétif 1, Algeria

   Souhil Mouassa & Tarek Bouktir

2. Department of Electrical Engineering, University of Jaén, 23700 EPS Linares, Jaén, Spain

   Souhil Mouassa & Francisco Jurado

Corresponding author

Correspondence to Souhil Mouassa.

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