95. Strategic Demand-Side Management: A Probability Maximization-Based Optimization Approach
Invited abstract in session TE-3: Stochastic optimization and applications II, stream Stochastic optimization and applications.
Thursday, 16:45 - 18:15Room: C 104
Authors (first author is the speaker)
| 1. | Rajmund Drenyovszki
|
| Dept. of Informatics, John von Neumann University | |
| 2. | Edit Csizmás
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| Dept. of Informatics, John von Neumann University | |
| 3. | Tamas Szantai
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| Institute of Mathematics, Budapest University of Technology and Economics | |
| 4. | Csaba Fabian
|
| Dept. of Informatics, John von Neumann University |
Abstract
The variability introduced by wind and solar energy, along with the increasing number of storage elements, introduces new challenges into the electricity grid. Factors such as weather conditions and individual usage patterns further contribute to uncertainty in energy consumption predictions. Our presentation focuses on a demand-side management model and probability maximization-based optimization approach that schedules controllable devices over various time frames while considering unpredictable energy use. Our solver is designed for straightforward implementation and demonstrates resilience to noise in gradient calculations, offering a practical solution to managing demand amidst the growing adoption of EVs and the fluctuating nature of renewable energy inputs.
Keywords
- Optimization under uncertainty and applications
- Optimal control and applications
Status: accepted
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