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Hardware Implementation of a Home Energy Management System Using Remodeled Sperm Swarm Optimization (RMSSO) Algorithm

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  • Senthil Prabu Ramalingam

    (School of Electrical Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India)

  • Prabhakar Karthikeyan Shanmugam

    (School of Electrical Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India)

Abstract

A remodeled sperm swarm optimization (RMSSO) algorithm for a home energy management (HEM) system is proposed, and its real-time efficacy was evaluated using a hardware experimental model. This home environment comprised sixteen residential loads, a smart meter and a Raspberry Pi controller to optimize the energy consumption cost (ECC) in response to the Indian day-ahead pricing (DAP) scheme. A wired/wireless communication network was considered to communicate with the smart meter and controller. To address this optimization problem, the sperm swarm optimization (SSO) algorithm’s constriction coefficient was remodeled to improve its global searching capability and proposed as RMSSO. For the first time, salp swarm optimization (SSA), SSO, and RMSSO algorithms were employed to schedule home appliances in the Indian scenario. To validate the proposed technique’s outcome, the results were compared to those of the conventional SSO and SSA algorithms. This problem was solved using the Python/GUROBI optimizer tool. As a consequence, consumers can use this control strategy in real-time to reduce energy consumption costs.

Suggested Citation

  • Senthil Prabu Ramalingam & Prabhakar Karthikeyan Shanmugam, 2022. "Hardware Implementation of a Home Energy Management System Using Remodeled Sperm Swarm Optimization (RMSSO) Algorithm," Energies, MDPI, vol. 15(14), pages 1-24, July.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:14:p:5008-:d:858821
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    References listed on IDEAS

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    1. Bilal Naji Alhasnawi & Basil H. Jasim & Pierluigi Siano & Josep M. Guerrero, 2021. "A Novel Real-Time Electricity Scheduling for Home Energy Management System Using the Internet of Energy," Energies, MDPI, vol. 14(11), pages 1-29, May.
    2. Zafar Iqbal & Nadeem Javaid & Saleem Iqbal & Sheraz Aslam & Zahoor Ali Khan & Wadood Abdul & Ahmad Almogren & Atif Alamri, 2018. "A Domestic Microgrid with Optimized Home Energy Management System," Energies, MDPI, vol. 11(4), pages 1-39, April.
    3. Happy Aprillia & Hong-Tzer Yang & Chao-Ming Huang, 2020. "Short-Term Photovoltaic Power Forecasting Using a Convolutional Neural Network–Salp Swarm Algorithm," Energies, MDPI, vol. 13(8), pages 1-20, April.
    4. Antimo Barbato & Antonio Capone, 2014. "Optimization Models and Methods for Demand-Side Management of Residential Users: A Survey," Energies, MDPI, vol. 7(9), pages 1-38, September.
    5. Arshad Mohammad & Mohd Zuhaib & Imtiaz Ashraf & Marwan Alsultan & Shafiq Ahmad & Adil Sarwar & Mali Abdollahian, 2021. "Integration of Electric Vehicles and Energy Storage System in Home Energy Management System with Home to Grid Capability," Energies, MDPI, vol. 14(24), pages 1-27, December.
    6. Muqaddas Naz & Zafar Iqbal & Nadeem Javaid & Zahoor Ali Khan & Wadood Abdul & Ahmad Almogren & Atif Alamri, 2018. "Efficient Power Scheduling in Smart Homes Using Hybrid Grey Wolf Differential Evolution Optimization Technique with Real Time and Critical Peak Pricing Schemes," Energies, MDPI, vol. 11(2), pages 1-25, February.
    7. Filipe Quintal & Daniel Garigali & Dino Vasconcelos & Jonathan Cavaleiro & Wilson Santos & Lucas Pereira, 2021. "Energy Monitoring in the Wild: Platform Development and Lessons Learned from a Real-World Demonstrator," Energies, MDPI, vol. 14(18), pages 1-15, September.
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