ANFIS Based Approach for Stochastic Modeling of Smart Home

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Abstract

Designing a proper energy management system for
a smart home is crucial to monitor, control and optimize the
flow and use of energy. The energy management system is highly dependent on a well-developed and accurate model of the smart home components. In this paper, the stochastic characteristics and uncertainties of the smart home components including photovoltaic, plug-in electric vehicle and heat pump are taken into account to develop a stochastic model. Hence, forecasting models are developed for photovoltaic power generation and load demand by the adaptive neuro-fuzzy inference system. Moreover, a Markov chain is proposed to model the trip time of the plugin electric vehicle model and a conditional probability model is also employed for calculation of battery energy at the plug-in time. Finally, the performance of the proposed stochastic model is compared with a neural
Original languageEnglish
Title of host publicationIEEE proceeding : 2nd European Conference on Electrical Engineering & Computer Science
Publication date22 Dec 2018
DOIs
Publication statusPublished - 22 Dec 2018

Fingerprint

Energy management systems
Stochastic models
Fuzzy inference
Electric vehicles
Markov processes
Power generation
Pumps
Uncertainty
Hot Temperature
Plug-in electric vehicles

Keywords

  • smart home
  • Plug-in electric vehicle
  • Adaptive Neuro-Fuzzy inference system
  • Stochastic Modeling, Photovoltaic Array
  • Heat Pump

Cite this

Yousefi, M., Kianpoor, N., Hajizadeh, A., & N. Soltani, M. (2018). ANFIS Based Approach for Stochastic Modeling of Smart Home. In IEEE proceeding: 2nd European Conference on Electrical Engineering & Computer Science https://doi.org/10.1109/EECS.2018.00091
Yousefi, Mojtaba ; Kianpoor, Nasrin ; Hajizadeh, Amin ; N. Soltani, Mohsen. / ANFIS Based Approach for Stochastic Modeling of Smart Home. IEEE proceeding: 2nd European Conference on Electrical Engineering & Computer Science. 2018.
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abstract = "Designing a proper energy management system fora smart home is crucial to monitor, control and optimize theflow and use of energy. The energy management system is highly dependent on a well-developed and accurate model of the smart home components. In this paper, the stochastic characteristics and uncertainties of the smart home components including photovoltaic, plug-in electric vehicle and heat pump are taken into account to develop a stochastic model. Hence, forecasting models are developed for photovoltaic power generation and load demand by the adaptive neuro-fuzzy inference system. Moreover, a Markov chain is proposed to model the trip time of the plugin electric vehicle model and a conditional probability model is also employed for calculation of battery energy at the plug-in time. Finally, the performance of the proposed stochastic model is compared with a neural",
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Yousefi, M, Kianpoor, N, Hajizadeh, A & N. Soltani, M 2018, ANFIS Based Approach for Stochastic Modeling of Smart Home. in IEEE proceeding: 2nd European Conference on Electrical Engineering & Computer Science. https://doi.org/10.1109/EECS.2018.00091

ANFIS Based Approach for Stochastic Modeling of Smart Home. / Yousefi, Mojtaba; Kianpoor, Nasrin; Hajizadeh, Amin; N. Soltani, Mohsen.

IEEE proceeding: 2nd European Conference on Electrical Engineering & Computer Science. 2018.

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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Yousefi M, Kianpoor N, Hajizadeh A, N. Soltani M. ANFIS Based Approach for Stochastic Modeling of Smart Home. In IEEE proceeding: 2nd European Conference on Electrical Engineering & Computer Science. 2018 https://doi.org/10.1109/EECS.2018.00091