Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/287241 
Year of Publication: 
2021
Citation: 
[Journal:] Journal of Global Optimization [ISSN:] 1573-2916 [Volume:] 80 [Issue:] 4 [Publisher:] Springer US [Place:] New York, NY [Year:] 2021 [Pages:] 965-989
Publisher: 
Springer US, New York, NY
Abstract: 
We develop a stochastic optimization model for scheduling a hybrid solar-battery storage system. Solar power in excess of the promise can be used to charge the battery, while power short of the promise is met by discharging the battery. We ensure reliable operations by using a joint chance constraint. Models with a few hundred scenarios are relatively tractable; for larger models, we demonstrate how a Lagrangian relaxation scheme provides improved results. To further accelerate the Lagrangian scheme, we embed the progressive hedging algorithm within the subgradient iterations of the Lagrangian relaxation. We investigate several enhancements of the progressive hedging algorithm, and find bundling of scenarios results in the best bounds. Finally, we provide a generalization for how our analysis extends to a microgrid with multiple batteries and photovoltaic generators.
Subjects: 
Chance constraints
Stochastic optimization
Lagrangian decomposition
Progressive hedging
Solar power
Photovoltaic power station
Battery storage
Virtual power plant
Out of sample validation
Microgrid
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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