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Residential Prosumer Energy Management System with Renewable Integration Considering Multi-Energy Storage and Demand Response

Author

Listed:
  • Asjad Ali

    (Department of Electrical Engineering, University of Engineering and Technology, Taxila 47050, Pakistan)

  • Abdullah Aftab

    (Department of Electrical Engineering Technology, Punjab Tianjin University of Technology, Lahore 54770, Pakistan)

  • Muhammad Nadeem Akram

    (Department of Mechanical, Automotive and Materials Engineering, University of Windsor, Windsor, ON N9B 3P4, Canada)

  • Shoaib Awan

    (Department of Electrical Engineering, University of Engineering and Technology, Taxila 47050, Pakistan)

  • Hafiz Abdul Muqeet

    (Department of Electrical Engineering Technology, Punjab Tianjin University of Technology, Lahore 54770, Pakistan)

  • Zeeshan Ahmad Arfeen

    (Department of Electrical Engineering, The Islamia University of Bahawalpur (IUB), Bahawalpur 63100, Pakistan)

Abstract

Rising energy demands, economic challenges, and the urgent need to address climate change have led to the emergence of a market wherein consumers can both purchase and sell electricity to the grid. This market leverages diverse energy sources and energy storage systems to achieve significant cost savings for consumers while providing critical grid support for utilities. In this study, an energy management system has been employed to tackle the optimization problem associated with various energy sources. This approach relies on mixed-integer linear programming (MILP) to optimize energy utilization while adhering to diverse constraints, yielding a feasible energy solution. This model is applied to real-world energy system consumption data and forecasts the most cost-effective day-ahead energy plans for different types of loads engaged in demand response. Furthermore, time-based charging and discharging strategies for electric vehicles and energy storage systems are considered, conducting a comprehensive analysis of energy costs across various storage devices. Our findings demonstrate that implementing this model can lead to an 18.26% reduction in operational costs when using lithium batteries and a remarkable 14.88% reduction with lead–acid batteries, particularly when integrating solar power and an EV into the system, while GHG is reduced by 36,018 grams/day for a load of 25 kW in one particular scenario. However, the analysis reveals that integrating wind power is not economically viable due to its comparatively higher operational costs.

Suggested Citation

  • Asjad Ali & Abdullah Aftab & Muhammad Nadeem Akram & Shoaib Awan & Hafiz Abdul Muqeet & Zeeshan Ahmad Arfeen, 2024. "Residential Prosumer Energy Management System with Renewable Integration Considering Multi-Energy Storage and Demand Response," Sustainability, MDPI, vol. 16(5), pages 1-27, March.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:5:p:2156-:d:1351565
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    References listed on IDEAS

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    Cited by:

    1. Alaa Al Zetawi & Marcos Tostado-Véliz & Hany M. Hasanien & Francisco Jurado, 2024. "A Robust-Based Home Energy Management Model for Optimal Participation of Prosumers in Competitive P2P Platforms," Energies, MDPI, vol. 17(22), pages 1-22, November.
    2. Mehmet Kurucan & Panagiotis Michailidis & Iakovos Michailidis & Federico Minelli, 2025. "A Modular Hybrid SOC-Estimation Framework with a Supervisor for Battery Management Systems Supporting Renewable Energy Integration in Smart Buildings," Energies, MDPI, vol. 18(17), pages 1-30, August.
    3. Aayesha S. Ahmad & Sumit K. Chattopadhyay & B. K. Panigrahi, 2024. "A Quantitative Assessment of the Economic Viability of Photovoltaic Battery Energy Storage Systems," Energies, MDPI, vol. 17(24), pages 1-21, December.

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