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A simulation model with multi-attribute utility functions for energy consumption scheduling in a smart grid

Energy Systems volume 6, pages 533–550 (2015)Cite this article

Abstract

When consumers’ use of electricity is mainly driven by convenience, coincident demand occurs, resulting in electric load peaks. Consequently, the undesirable large gaps between peak and off-peak loads will adversely affect the system’s efficiency due to unused capacity during off-peak hours and extra ancillary generators required during peak hours. Demand response (DR) has long been proposed to reduce peak load by providing incentives to encourage consumers to shift their peak loads to off-peak periods. In most DR literature, incentive schemes are purely financial in assuming that cost is the only parameter to influence consumers’ load-shifting behavior. In this paper, we assume that in addition to cost, convenience of energy usage is also an important factor when consumers respond to DR programs. Hence, we use multi-attribute utility functions consisting of both cost and convenience factors to model consumer behavior on energy consumption for home appliances. The “convenience” herein is defined as being able to use an appliance during one’s preferred time window. A simulation model is developed to study a residential population consisting of heterogeneous households with varying preference of convenience over cost. We study the effects of time-of-use pricing structure on users’ utility-based load shifting behaviors and subsequently on system-wide performances such as peak to average ratio (PAR) and load variance (LV). We also describe a method of design of experiment (DOE) for determining an optimal time-of-use rate structure that minimizes both PAR and LV for the system.

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Acknowledgments

This work is partly supported by the Kentucky Science and Technology Inc. under the grant KSEF-2808-RDE-016. In addition, research by the last author is in part supported by the National Science Foundation under grants ECCS-1232168.

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Authors and Affiliations

  1. Industrial Engineering Department, J.B. Speed School of Engineering, University of Louisville, Louisville, KY, 40292, USA

    Prajwal Khadgi, Lihui Bai & Gerald Evans

  2. Department of Industrial Engineering and Management Systems, University of Central Florida, P.O. BOX 162993, Orlando, FL, 32816-2993, USA

    Qipeng P. Zheng

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  1. Prajwal Khadgi
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  2. Lihui Bai
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  3. Gerald Evans
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  4. Qipeng P. Zheng
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Correspondence to Lihui Bai.

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Khadgi, P., Bai, L., Evans, G. et al. A simulation model with multi-attribute utility functions for energy consumption scheduling in a smart grid. Energy Syst 6, 533–550 (2015). https://doi.org/10.1007/s12667-015-0153-9

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  • DOI: https://doi.org/10.1007/s12667-015-0153-9

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