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Development and evaluation of an online home energy management strategy for load coordination in smart homes with renewable energy sources

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  • Chen, Xiaoling
  • Miller, Cory
  • Goutham, Mithun
  • Hanumalagutti, Prasad Dev
  • Blaser, Rachel
  • Stockar, Stephanie

Abstract

In this paper, a real time implementable load coordination strategy is developed for the optimization of electric demands in a smart home. The strategy minimizes the electricity cost to the home owner, while limiting the disruptions associated with the deferring of flexible power loads. A multi-objective nonlinear mixed integer programming is formulated as a sequential model predictive control, which is then solved using genetic algorithm. The load shifting benefits obtained by deploying an advanced coordination strategy are compared against a baseline controller for various home characteristics, such as location, size and equipment. The simulation study shows that the deployment of the smart home energy management strategy achieves approximately 5% reduction in grid cost compared to a baseline strategy. This is achieved by deferring approximately 50% of the flexible loads, which is possible due to the use of the stationary energy storage.

Suggested Citation

  • Chen, Xiaoling & Miller, Cory & Goutham, Mithun & Hanumalagutti, Prasad Dev & Blaser, Rachel & Stockar, Stephanie, 2024. "Development and evaluation of an online home energy management strategy for load coordination in smart homes with renewable energy sources," Energy, Elsevier, vol. 290(C).
    • Handle: RePEc:eee:energy:v:290:y:2024:i:c:s0360544223035284
    DOI: 10.1016/j.energy.2023.130134
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    References listed on IDEAS

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    1. Thomas, Dimitrios & Deblecker, Olivier & Ioakimidis, Christos S., 2018. "Optimal operation of an energy management system for a grid-connected smart building considering photovoltaics’ uncertainty and stochastic electric vehicles’ driving schedule," Applied Energy, Elsevier, vol. 210(C), pages 1188-1206.
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