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Essays on Mathematical Optimization for Residential Demand Response in the Energy Sector

Palaparambil Dinesh, Lakshmi
http://orcid.org/0000-0002-4811-7481
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1511860511116905

Abstract Details

2017, PhD, University of Cincinnati, Business: Business Administration.
In the electric utility industry, it could be challenging to adjust supply to match demand due to large generator ramp up times, high generation costs and insufficient in-house generation capacity. Demand response (DR) is a technique for adjusting the demand for electric power instead of the supply. Direct Load Control (DLC) is one of the ways to implement DR. DLC program participants sign up for power interruption contracts and are given financial incentives for curtailing electricity usage during peak demand time periods. This dissertation studies a DLC program for residential air conditioners using mathematical optimization models. First, we develop a model that determines what contract parameters to use in designing contracts between the provider and residential customers, when to turn which power unit on or off and how much power to cut during peak demand hours. The model uses information on customer preferences for choice of contract parameters such as DLC financial incentives and energy usage curtailment. In numerical experiments, the proposed model leads to projected cost savings of the order of 20%, compared to a current benchmark model used in practice. We also quantify the impact of factors leading to cost savings and study characteristics of customers picked by different contracts. Second, we study a DLC program in a macro economic environment using a Computable General Equilibrium (CGE) model. A CGE model is used to study the impact of external factors such as policy and technology changes on different economic sectors. Here we differentiate customers based on their preference for DLC programs by using different values for price elasticity of demand for electricity commodity. Consequently, DLC program customers could substitute demand for electricity commodity with other commodities such as transportation sector. Price elasticity of demand is calculated using a novel methodology that incorporates customer preferences for DLC contracts from the first model. The calculation of elasticity based on our methodology is useful since the prices of commodities are not only determined by aggregate demand and supply but also by customers’ relative preferences for commodities. In addition to this we quantify the indirect substitution and rebound effects on sectoral activity levels, incomes and prices based on customer differences, when DLC is implemented.
Uday Rao, Ph.D. (Committee Chair)
Debashis Pal, Ph.D. (Committee Member)
R. Kenneth Skinner, Ph.D. (Committee Member)
Yan Yu, Ph.D. (Committee Member)
Jeffrey Camm, Ph.D. (Committee Member)
69 p.
Operations Research
Demand Response; Computable General Equilibrium Models; Mixed Integer Linear Programming

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Citations

  • Palaparambil Dinesh, L. (2017). Essays on Mathematical Optimization for Residential Demand Response in the Energy Sector [Doctoral dissertation, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1511860511116905

    APA Style (7th edition)

  • Palaparambil Dinesh, Lakshmi. Essays on Mathematical Optimization for Residential Demand Response in the Energy Sector. 2017. University of Cincinnati, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1511860511116905.

    MLA Style (8th edition)

  • Palaparambil Dinesh, Lakshmi. "Essays on Mathematical Optimization for Residential Demand Response in the Energy Sector." Doctoral dissertation, University of Cincinnati, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1511860511116905

    Chicago Manual of Style (17th edition)

ucin1511860511116905
526
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This open access ETD is published by University of Cincinnati and OhioLINK.