Comparison of Simulated Annealing and Greedy Optimizations for Controllable Loads
Haslak T (2021)
Publication Language: English
Publication Type: Conference contribution
Publication year: 2021
Publisher: Institute of Electrical and Electronics Engineers Inc.
Conference Proceedings Title: 2021 IEEE Green Energy and Smart Systems Conference (IGESSC)
Event location: Long Beach, CA
ISBN: 978-1-6654-3457-7
DOI: 10.1109/IGESSC53124.2021.9618696
Abstract
I pick random renewable power supply functions with a resolution of 1 s and optimize the behavior of a population of controllable loads. I implement a Greedy heuristic that requires only knowledge of the currently available power supply. Next I derive a fitness function that augments beneficial behavior. With the forecast I implement a Greedy strategy that utilizes forecast histograms as a heuristic and improves upon the results of the no-forecast Greedy. Lastly I show that Simulated Annealing can deliver significant improvements - however they are tied to extended computation times.
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How to cite
APA:
Haslak, T. (2021). Comparison of Simulated Annealing and Greedy Optimizations for Controllable Loads. In 2021 IEEE Green Energy and Smart Systems Conference (IGESSC). Long Beach, CA, US: Institute of Electrical and Electronics Engineers Inc..
MLA:
Haslak, Tuncer. "Comparison of Simulated Annealing and Greedy Optimizations for Controllable Loads." Proceedings of the 2021 IEEE Green Energy and Smart Systems Conference, IGESSC 2021, Long Beach, CA Institute of Electrical and Electronics Engineers Inc., 2021.
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