Home energy management under correlated uncertainties
Recently, a paper entitled “Home energy management under correlated uncertainties: A statistical analysis through Copula” has been published by ESPO team in the journal of “Applied Energy” with an impact factor of 9.74. Seyyed Reza Ebrahimi, as the first author, is a PHD student of electrical engineering at the Shahrood University of Technology, Shahrood, and working on “Electrical Energy Management in Zero Energy Building” in his PHD thesis. Dr. Morteza Rahimiyan, Dr. Mohsen Assili and Dr. Amin Hajizadeh are his co-authors in this paper.
Scientific description
The correlation among the uncertain parameters may affect the home energy management decisions and the resulting costs. This paper provides a statistical simulation framework (see figure), which allows to examine the potential impact of all significant correlations among the uncertain parameters involved in the home energy management problem, for the first time. A Copula-based scenario generation technique is used to generate the correlated scenarios of uncertain parameters. To generate more accurate scenarios, the probability of presence or absence of each uncertain load in each day is also considered. The correlation among the uncertain parameters is captured through the empirical statistical analysis of real-world data of a home located in Austin, Texas. Results through different cases show that ignoring the correlation among the uncertain parameters has significant effects on the outcomes of home energy management.
Figure: Statistical framework for home energy management under correlated uncertainties
Industrial applications
The statistical analysis indicates the potential impact of uncertainty characteristics on the energy management outcomes. This input-output analysis also identifies more effective characteristics of the uncertain parameters and how they influence the energy management outcomes. In practice, the resulting analysis can be used to build a correlated uncertainty model considering the structural dependency and the probable combinations of uncertain parameters. The correlated uncertainty model can be incorporated into a stochastic model for making the day-ahead scheduling decisions of loads in homes.
Acknowledgement
Residential energy data and home information were provided in coordination with the Pecan Street Research Institute in Austin, Texas, U.S.A. The authors would like to thank the team at Pecan Street, Inc., for their collaboration and support.
Paper citation and link
Ebrahimi SR, Rahimiyan M, Assili M, Hajizadeh A. Home energy management under correlated uncertainties: A statistical analysis through Copula. Applied Energy. 2022;305:117753.
https://www.sciencedirect.com/science/article/abs/pii/S0306261921010989
