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Satisfaction-Based Energy Allocation with Energy Constraint Applying Cooperative Game Theory

Author

Listed:
  • Samira Ortiz

    (Department of Electrical and Computer Engineering, University of Puerto Rico-Mayagüez Campus, Mayagüez, PR 00682, USA)

  • Mandoye Ndoye

    (Department of Electrical and Computer Engineering, Tuskegee University, Tuskegee, AL 36088, USA)

  • Marcel Castro-Sitiriche

    (Department of Electrical and Computer Engineering, University of Puerto Rico-Mayagüez Campus, Mayagüez, PR 00682, USA
    Nelson Mandela African Institution of Science and Technology, Arusha, Tanzania)

Abstract

There has been an effort for a few decades to keep energy consumption at a minimum or at least within a low-level range. This effort is more meaningful and complex by including a customer’s satisfaction variable to ensure that customers can achieve the best quality of life that could be derived from how energy is used by different devices. We use the concept of Shapley Value from cooperative game theory to solve the multi-objective optimization problem (MOO) to responsibly fulfill user’s satisfaction by maximizing satisfaction while minimizing the power consumption, with energy constrains since highly limited resources scenarios are studied. The novel method uses the concept of a quantifiable user satisfaction, along the concepts of power satisfaction (PS) and energy satisfaction (ES). The model is being validated by representing a single house (with a small PV system) that is connected to the utility grid. The main objectives are to (i) present the innovative energy satisfaction model based on responsible wellbeing, (ii) demonstrate its implementation using a Shapley-value-based algorithm, and (iii) include the impact of a solar photovoltaic (PV) system in the energy satisfaction model. The proposed technique determines in which hours the energy should be allocated to maximize the ES for each scenario, and then it is compared to cases in which devices are usually operated. Through the proposed technique, the energy consumption was reduced 75% and the ES increased 40% under the energy constraints.

Suggested Citation

  • Samira Ortiz & Mandoye Ndoye & Marcel Castro-Sitiriche, 2021. "Satisfaction-Based Energy Allocation with Energy Constraint Applying Cooperative Game Theory," Energies, MDPI, vol. 14(5), pages 1-18, March.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:5:p:1485-:d:513267
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    References listed on IDEAS

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    Cited by:

    1. Mihai Daniel Roman & Diana Mihaela Stanculescu, 2021. "An Analysis of Countries’ Bargaining Power Derived from the Natural Gas Transportation System Using a Cooperative Game Theory Model," Energies, MDPI, vol. 14(12), pages 1-13, June.
    2. Andreas Reinhardt & Lucas Pereira, 2021. "Special Issue: “Energy Data Analytics for Smart Meter Data”," Energies, MDPI, vol. 14(17), pages 1-3, August.

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