An automated cluster-based approach for asset rescheduling in building communities

Seyyed Danial Nazemi, Mohsen A. Jafari

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The imbalance between load demand and power generation and high peak loads in the smart grid become a big concern for utility companies. Increasing the flexibility of the grid by using innovative demand response programs can improve the quality of the power grid and reduce the peak demand. In this paper, we propose a cluster-based approach for building assets rescheduling in a smart building community. This method takes advantage of interactions among the buildings and aims to minimize the total energy cost as well as the peak-to-average ratio (PAR). In the proposed model, several load actions for each household appliance are generated based on the class of the assets and consumers' preferences. A clustering approach is then presented to group similar load actions for assets via X-means clustering. In order to do a more accurate clustering, time-domain (TD) load actions are transformed to frequency-domain (FD) using the Fast Fourier Transform (FFT) method. The results of the clustering step are used as inputs of the optimization problem. Finally, a multi-objective mixed-integer linear programming (MOMILP) problem is proposed to reschedule building assets optimally. The results show that the energy cost for a small community could reduce by around 25% while the peak demand could reduce by around 7%.

Original languageEnglish (US)
Title of host publication2020 IEEE Texas Power and Energy Conference, TPEC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728144368
DOIs
StatePublished - Feb 2020
Event2020 IEEE Texas Power and Energy Conference, TPEC 2020 - College Station, United States
Duration: Feb 6 2020Feb 7 2020

Publication series

Name2020 IEEE Texas Power and Energy Conference, TPEC 2020

Conference

Conference2020 IEEE Texas Power and Energy Conference, TPEC 2020
CountryUnited States
CityCollege Station
Period2/6/202/7/20

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Safety, Risk, Reliability and Quality

Keywords

  • Asset scheduling
  • Clustering
  • Consumer preference
  • Demand response
  • Flexibility
  • Smart grid

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  • Cite this

    Nazemi, S. D., & Jafari, M. A. (2020). An automated cluster-based approach for asset rescheduling in building communities. In 2020 IEEE Texas Power and Energy Conference, TPEC 2020 [9042580] (2020 IEEE Texas Power and Energy Conference, TPEC 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TPEC48276.2020.9042580