Optimal Switching in a Dynamic, Stochastic, Operating Environment

• Published in: 2020 Winter Simulation Conference (WSC) pp. 2083 - 2092
• Main Authors: Choi, Byunghee, Weaver, Robert D.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 14-12-2020
• Subjects: Computational complexity; Hydroelectric power generation; Irrigation; Optimal control; Stochastic processes; Switches; Uncertainty
• ISSN: 1558-4305
• DOI: 10.1109/WSC48552.2020.9383854

The value of flexibility in operations for hydroelectric power plants is apparent from their investment in multiple generators to allow variable intensity of operation. This flexibility supports rapid response to outside factors that impact their performance. It follows that hydroelectricity generation often competes for water flow with downstream water demands including irrigation, urban water use, or ecosystem services. Each of these follows stochastic process that implies asynchronous demand for water flow. The associated management problem is of interest encompassing multiple switching and motivating other extensions. This paper considers the dynamic stochastic problem of water allocation for hydroelectric generation and downstream use. Our main contribution is to present a novel numerical solution to this problem. Moreover, the method allows generalization not previously possible including: (i) multiple dynamic stochastic processes with jump diffusions, (ii) the number of contingent decisions with reversibility, and (iii) characterization of risk and uncertainty including dynamic constraints.