Description
Optimal Energy Storage System Operation under Uncertainty, Sarah Wimmeder OR 2022, KIT - 29 WE-09 OR2022 Karlsruhe Due to the increasing share of renewable energies the demand for power storage has been growing significantly in recent years. This development opens a wide variety of possible battery applications at generation as well as consumption level. The focus of this paper is on optimally operating an energy storage system by dynamically adjusting electricity storage decisions in response to randomly evolving state variables, such as electricity demand, photovoltaic generation and electricity prices. To quantify the value of integrating a battery storage into the system, a multistage stochastic programming model is formulated with the objective to minimize the expected total electricity costs over a finite planning horizon. It provides optimal charging and discharging decisions under uncertainty at each stage of the decision horizon. As a consequence of the so called curse of dimensionality, stochastic dynamic decision problems are really challenging as it implies that the complexity of the problem increases exponentially in the number of states, and that in general no solution algorithm which converges towards an exact solution in polynomial time exists. To guarantee computational tractability, the problem is solved by a combination of stochastic dual dynamic programming and a quantization method which approximates the input data by a discrete scenario lattice. This method is referred to as approximate dual dynamic programming (ADDP). To assess the added value of the stochastic solution, the results obtained by the ADDP method are compared to results assessed by a deterministic approach. We find that the stochastic optimization approach is quiet promising. Compared to conventional optimization, stochastic optimization enables more advantageous decision making.Period | 6 Sept 2022 → 9 Sept 2022 |
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Event title | OR 2022 |
Event type | Other |
Degree of Recognition | International |
Research Field
- Former Research Field - Integrated Energy Systems
Keywords
- stochastic optimization
- energy storage
- ADDP