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Decisions on Energy Demand Response Option Contracts in Smart Grids Based on Activity-Based Costing and Stochastic Programming

Author

Listed:
  • Seog-Chan Oh

    (General Motors, 30500 Mound Road, Warren, MI 48090, USA)

  • Alfred J. Hildreth

    (General Motors, 30009 Van Dyke, Warren, MI 48090, USA)

Abstract

Smart grids enable a two-way energy demand response capability through which a utility company offers its industrial customers various call options for energy load curtailment. If a customer has the capability to accurately determine whether to accept an offer or not, then in the case of accepting an offer, the customer can earn both an option premium to participate, and a strike price for load curtailments if requested. However, today most manufacturing companies lack the capability to make the correct contract decisions for given offers. This paper proposes a novel decision model based on activity-based costing (ABC) and stochastic programming, developed to accurately evaluate the impact of load curtailments and determine as to whether or not to accept an energy load curtailment offer. The proposed model specifically targets state-transition flexible and Quality-of-Service (QoS) flexible energy use activities to reduce the peak energy demand rate. An illustrative example with the proposed decision model under a call-option based energy demand response scenario is presented. As shown from the example results, the proposed decision model can be used with emerging smart grid opportunities to provide a competitive advantage to the manufacturing industry.

Suggested Citation

  • Seog-Chan Oh & Alfred J. Hildreth, 2013. "Decisions on Energy Demand Response Option Contracts in Smart Grids Based on Activity-Based Costing and Stochastic Programming," Energies, MDPI, vol. 6(1), pages 1-19, January.
    • Handle: RePEc:gam:jeners:v:6:y:2013:i:1:p:425-443:d:22919
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    References listed on IDEAS

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    1. João Soares & Bruno Canizes & Cristina Lobo & Zita Vale & Hugo Morais, 2012. "Electric Vehicle Scenario Simulator Tool for Smart Grid Operators," Energies, MDPI, vol. 5(6), pages 1-19, June.
    2. Jaeyeong Yoo & Byungsung Park & Kyungsung An & Essam A. Al-Ammar & Yasin Khan & Kyeon Hur & Jong Hyun Kim, 2012. "Look-Ahead Energy Management of a Grid-Connected Residential PV System with Energy Storage under Time-Based Rate Programs," Energies, MDPI, vol. 5(4), pages 1-19, April.
    3. Suvrajeet Sen & Julia L. Higle, 1999. "An Introductory Tutorial on Stochastic Linear Programming Models," Interfaces, INFORMS, vol. 29(2), pages 33-61, April.
    4. A. Charnes & W. W. Cooper, 1963. "Deterministic Equivalents for Optimizing and Satisficing under Chance Constraints," Operations Research, INFORMS, vol. 11(1), pages 18-39, February.
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    Cited by:

    1. Richard P. van Leeuwen & Annelies E. Boerman & Edmund W. Schaefer & Gerwin Hoogsteen & Yashar S. Hajimolana, 2022. "Model Supported Business Case Scenario Analysis for Decentral Hydrogen Conversion, Storage and Consumption within Energy Hubs," Energies, MDPI, vol. 15(6), pages 1-22, March.
    2. Wen-Hsien Tsai, 2018. "A Green Quality Management Decision Model with Carbon Tax and Capacity Expansion under Activity-Based Costing (ABC)—A Case Study in the Tire Manufacturing Industry," Energies, MDPI, vol. 11(7), pages 1-30, July.
    3. Ying Yu & Tongdan Jin & Chunjie Zhong, 2015. "Designing an Incentive Contract Menu for Sustaining the Electricity Market," Energies, MDPI, vol. 8(12), pages 1-22, December.
    4. Seog-Chan Oh & Alfred J. Hildreth, 2014. "Estimating the Technical Improvement of Energy Efficiency in the Automotive Industry—Stochastic and Deterministic Frontier Benchmarking Approaches," Energies, MDPI, vol. 7(9), pages 1-27, September.
    5. Luis Hernández-Callejo, 2019. "A Comprehensive Review of Operation and Control, Maintenance and Lifespan Management, Grid Planning and Design, and Metering in Smart Grids," Energies, MDPI, vol. 12(9), pages 1-50, April.

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