Journal
AIMS MATHEMATICS
Volume 6, Issue 11, Pages 11815-11836Publisher
AMER INST MATHEMATICAL SCIENCES-AIMS
DOI: 10.3934/math.2021686
Keywords
optimization modeling; linear programming; nonlinear programming; energy distribution system modeling; sliding window algorithm
Categories
Funding
- French Environment and Energy Management Agency (ADEME) , as part of the Future Investment Program of the French government
Ask authors/readers for more resources
This study focuses on optimization problems in energy distribution systems with storage, considering a simplified network topology around four nodes: the load aggregator, the external grid, the consumption, and the storage. By solving two optimization problems, mathematical models are established and a new method based on a sliding window algorithm is proposed to reduce computational time and enable real-time simulations.
This work is devoted to study optimization problems arising in energy distribution systems with storage. We consider a simplified network topology organized around four nodes: the load aggregator, the external grid, the consumption and the storage. The imported power from the external grid should balance the consumption and the storage variation. The merit function to minimize is the total price the load aggregator has to pay in a given time interval to enforce this balance. Two optimization problems are considered. The first one is linear and standard. It can be solved through classical optimization methods. The second problem is obtained from the previous one by taking into account a power subscription, which makes it piecewise linear. We establish mathematical properties on both these models. Finally, a new method based on a sliding window algorithm is derived. It allows to reduce drastically the computational time and makes feasible real time simulations. Numerical results are performed on real data to highlight both models and to illustrate the performance of the sliding window algorithm.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available