The impact of mutual interaction between electric and water distribution systems via demand response

F. G. Bagriyanik*, M. A. Sonmez, M. Bagriyanik

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


Peak demands for electricity and water can be managed in a sustainable size and shape via residential demand response. Moreover, the mutual interaction of electric and water distribution management systems can enable to present new services and benefits. The collaborative loads that have both manageable electrical demand and water capacity can have great roles in the interaction. Peak electricity demand can be shaped by deferring their working schedule, interrupting of their run cycles, and assigning new set values that can lead to less consumption when the electricity demand and its price are high. In this paper, novel methods were introduced to uncover the impact of the residential electric demand response on household water demand. The methods were proposed for manageable capacities of electricity and water, daily normalized profile, feature extraction, and problem formulation. A feature extraction method based on Empirical Mode Decomposition was used to find convenient case profiles for incentives. Realistic electricity and water demand profiles were generated with twelve activities in 100 houses via MATLAB. Time intervals of the electricity tariff and the intervals belong to the user's daily habits were placed in the activity-based power profiles. A high correlation was obtained in the daily normalized demand for electricity and water. Collaborative appliances had a significant share (approximately 34%) in total electricity demand. Deferring collaborative loads from on-peak time caused the shaping of the water demand. The amount of the water managed in on-peak time was between 87.35 L and 120.96 L case by case in a home.

Original languageEnglish
Article number101008
JournalSustainable Energy, Grids and Networks
Publication statusPublished - Jun 2023

Bibliographical note

Publisher Copyright:
© 2023 Elsevier Ltd


  • Collaborative loads
  • Demand response
  • Energy management
  • Feature extraction
  • Mutual interaction


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