Hybrid meta-heuristic optimization based home energy management system in smart grid

Abstract

The emergence of the smart grid has empowered the consumers to manage the home energy in an efficient and effective manner. In this regard, home energy management (HEM) is a challenging task that requires efficient scheduling of smart appliances to optimize energy consumption. In this paper, we proposed a meta-heuristic based HEM system (HEMS) by incorporating the enhanced differential evolution (EDE) and harmony search algorithm (HSA). Moreover, to optimize the energy consumption, a hybridization based on HSA and EDE operators is performed. Further, multiple knapsacks are used to ensure that the load demand for electricity consumers does not exceed a threshold during peak hours. To achieve multiple objectives at the same time, hybridization proved to be effective in terms of electricity cost and peak to average ratio (PAR) reduction. The performance of the proposed technique; harmony EDE (HEDE) is evaluated via extensive simulations in MATLAB. The simulations are performed for a residential complex of multiple homes with a variety of smart appliances. The simulation results show that EDE performs better in terms of cost reduction as compared to HSA. Whereas, in terms of PAR, HSA is proved to be more efficient as compared to EDE. However, the proposed scheme outperforms the existing meta-heuristic techniques (HSA and EDE) in terms of cost and PAR.

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Abbreviations

\(\rho\) :

Power rating

\(\varsigma _{a,t}\) :

Electricity price at time interval t

\(E_{in}\) :

Power consumption of interruptible appliances

\(\rho _{in}\) :

Power rating of interruptible appliances

t :

Time slot

IN :

Set of interruptible appliances

\(sv_{in}\) :

ON/OFF status of interruptible appliances

NI :

Set of non-interruptible appliances

\(E_{ni}\) :

Power consumption of non-interruptible appliances

\(\rho _{ni}\) :

Power rating of non-interruptible appliances

\(sv_{ni}\) :

ON/OFF status of non-interruptible appliances

B :

Set of base appliances

\(E_{b}\) :

Power consumption of base appliances

\(\rho _{b}\) :

Power rating of base appliances

\(sv_{b}\) :

ON/OFF status of base appliances

L(t):

Power consumption of all appliances at time interval t

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

Per day total scheduled load

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

Per day total unscheduled load

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

Per day total scheduled cost

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

Per day total unscheduled cost

\(t_{\alpha }\) :

Start time of an appliance

\(t_{\beta }\) :

End time of an appliance

F:

Scaling factor

NP:

Population size

SG:

Smart grid

SM:

Smart meter

DSM:

Demand side management

DR:

Demand response

RES:

Renewable energy sources

PAR:

Peak to average ratio

TOU:

Time of use

IBR:

Inclined block rate

CPP:

Critical peak pricing

DAP:

Day ahead pricing

RTP:

Real time pricing

HSA:

Harmony search algorithm

DE:

Differential evolution

EDE:

Enhanced differential evolution

GA:

Genetic algorithm

CR:

Cross over rate

HEM:

Home energy management

EMC:

Energy management controller

HAN:

Home area network

HMCR:

Harmony memory consideration rate

bw:

Bandwidth

PSO:

Particle swarm optimization

MILP:

Mixed integer linear programming

PA:

Pitch adjustment rate

MKP:

Multiple knapsack problem

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Funding

This project was full financially supported by the King Saud University, through the Vice Deanship of Research Chairs.

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Correspondence to Zahoor Ali Khan.

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Khan, Z.A., Zafar, A., Javaid, S. et al. Hybrid meta-heuristic optimization based home energy management system in smart grid. J Ambient Intell Human Comput 10, 4837–4853 (2019). https://doi.org/10.1007/s12652-018-01169-y

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Keywords

  • Smart grid
  • Demand side management
  • Heuristic techniques