Evaluating demand response opportunities for power systems resilience using MILP and MINLP Formulations |
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Authors: | Michael Bynum Anya Castillo Jean-Paul Watson Carl D. Laird |
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Affiliation: | 1. Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN 47907;2. Sandia National Laboratories, Albuquerque, NM 87185 |
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Abstract: | While peak shaving is commonly used to reduce power costs, chemical process facilities that can reduce power consumption on demand during emergencies (e.g., extreme weather events) bring additional value through improved resilience. For process facilities to effectively negotiate demand response (DR) contracts and make investment decisions regarding flexibility, they need to quantify their additional value to the grid. We present a grid-centric mixed-integer stochastic programming framework to determine the value of DR for improving grid resilience in place of capital investments that can be cost prohibitive for system operators. We formulate problems using both a linear approximation and a nonlinear alternating current power flow model. Our numerical results with both models demonstrate that DR can be used to reduce the capital investment necessary for resilience, increasing the value that chemical process facilities bring through DR. However, the linearized model often underestimates the amount of DR needed in our case studies. Published 2018. This article is a U.S. Government work and is in the public domain in the USA. AIChE J, 65: e16508, 2019 |
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