Photo of Nadia Ahmed

Nadia Ahmed

Ph.D.2013 – 2017
Research Interests:
  • Consumer behavior prediction
  • Smart energy systems
  • Hidden Markov models
Education:
  • 2017
    Ph.D. in Electrical Engineering and Computer Science
    University of California, Irvine, U.S.
  • 2007
    M.S. in Electrical Engineering and Computer Science
    University of California, Irvine, U.S.
  • 2005
    B.S. in Electrical Engineering and Computer Science
    University of California, Irvine, U.S.
Website: LinkedIn

Publications

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  • Nadia Ahmed
    Marco Levorato
    Guann-Pyng Li
    N. Ahmed, M. Levorato, and G.-P. Li, Residential Consumer-Centric Demand Side Management, IEEE Transactions on Smart Grid, vol. 9, no. 5, pp. 4513 – 4524, Sep. 2017. Release

    Energy management systems (EMS) are mainly price driven with minimal consumer interaction. To improve the effectiveness of EMS in the context of demand response, an alternative EMS control framework driven by resident behavior patterns is developed. Using hidden Markov modeling techniques, the EMS detects consumer behavior from real-time aggregate consumption and a pre-built dictionary of reference models. These models capture variations in consumer habits as a function of daily living activity sequence. Following a training period, the system identifies the best fit model which is used to estimate the current state of the resident. When a request to activate a time-shiftable appliance is made, the control agent compares grid signals, user convenience constraints, and the current consumer state estimate to predict the likelihood that the future aggregate load exceeds a consumption threshold during the operating cycle of the requested device. Based on the outcome, the control agent initiates or defers the activation request. Using three consumer reference models, a case study assessing EMS performance with respect to model detection, state estimation, and control as a function of consumer comfort and grid-informed consumption constraints is presented. A tradeoff analysis between comfort, consumption threshold, and appliance activation delay is demonstrated.

    @article{ahmed-levorato-2017-tsg,
      author = {Nadia Ahmed and Marco Levorato and Guann-Pyng Li},
      title = {Residential Consumer-Centric Demand Side Management},
      journal = {IEEE Transactions on Smart Grid},
      volume = {9},
      number = {5},
      pages = {4513--4524},
      month = sep,
      year = {2017},
      doi = {10.1109/tsg.2017.2661991},
    }
  • Marco Levorato
    Nadia Ahmed
    Yang Arthur Zhang
    M. Levorato, N. Ahmed, and Y. A. Zhang, Consumer In-The-Loop: Consumers as Part of Residential Smart Energy Systems, in Proceedings of the IEEE International Conference on Smart Grid Communications (SmartGridComm), Venice, Italy, Nov. 2014. Release

    A novel framework for residential smart energy systems is proposed. The model integrates the consumer behavior in the dynamics of the technological and environmental components of the system. The objective is to classify and optimize the whole system, which includes the dynamics of the consumer. The framework is based on Markov process, model detection and Hidden Markov Model Theory. The behavior of the consumer is classified from a sequence of available observations within a set of reference classes. The detected class is used as prior information to detect the state of the system and provide feedback to the consumer to reduce the probability that undesirable states occur within a time window.

    @inproceedings{levorato-ahmed-2014-smartgridcomm,
      author = {Marco Levorato and Nadia Ahmed and Yang Arthur Zhang},
      title = {Consumer In-The-Loop: Consumers as Part of Residential Smart Energy Systems},
      booktitle = {Proceedings of the IEEE International Conference on Smart Grid Communications (SmartGridComm)},
      address = {Venice, Italy},
      month = nov,
      year = {2014},
      doi = {10.1109/smartgridcomm.2014.7007739},
    }