A MPC Based Peak Shaving Application for a Household with Photovoltaic Battery System
- This paper presents the use of model predictive control (MPC) based approach for peak shaving application of a battery in a Photovoltaic (PV) battery system connected to a rural low voltage gird. The goals of the MPC are to shave the peaks in the PV feed-in and the grid power consumption and at the same time maximize the use of the battery. The benefit to the prosumer is from the maximum use ofThis paper presents the use of model predictive control (MPC) based approach for peak shaving application of a battery in a Photovoltaic (PV) battery system connected to a rural low voltage gird. The goals of the MPC are to shave the peaks in the PV feed-in and the grid power consumption and at the same time maximize the use of the battery. The benefit to the prosumer is from the maximum use of the self-produced electricity. The benefit to the grid is from the reduced peaks in the PV feed-in and the grid power consumption. This would allow an increase in the PV hosting and the load hosting capacity of the grid.
The paper presents the mathematical formulation of the optimal control problem
along with the cost benefit analysis. The MPC implementation scheme in the
laboratory and experiment results have also been presented. The results show
that the MPC is able to track the deviation in the weather forecast and operate
the battery by solving the optimal control problem to handle this deviation.…
| Document Type: | Conference Proceeding |
|---|---|
| Conference Type: | Konferenzartikel |
| Zitierlink: | https://opus.hs-offenburg.de/3886 | Bibliografische Angaben |
| Title (English): | A MPC Based Peak Shaving Application for a Household with Photovoltaic Battery System |
| Conference: | 7th International Conference on Smart Cities and Green ICT Systems, March 16-18, 2018, Funchal, Madeira, Portugal |
| Author: | Deepranjan DongolStaff Member, Thomas Feldmann , Elmar BollinStaff MemberGND, Michael SchmidtStaff MemberORCiDGND |
| Edition: | 1. |
| Year of Publication: | 2019 |
| Date of first Publication: | 2019/09/02 |
| Place of publication: | Cham, Switzerland |
| Publisher: | Springer |
| First Page: | 44 |
| Last Page: | 66 |
| Parent Title (English): | Smart Cities, Green Technologies and Intelligent Transport Systems : 7th International Conference, SMARTGREENS, and 4th International Conference, VEHITS 2018, Funchal-Madeira, Portugal, March 16-18, 2018, Revised Selected Papers |
| ISBN: | 978-3-030-26632-5 (Softcover) |
| ISBN: | 978-3-030-26633-2 (eBook) |
| DOI: | https://doi.org/10.1007/978-3-030-26633-2_3 |
| Language: | English | Inhaltliche Informationen |
| Institutes: | Fakultät Elektrotechnik, Medizintechnik und Informatik (EMI) (ab 04/2019) |
| Collections of the Offenburg University: | Bibliografie |
| Research: | INES - Institut für nachhaltige Energiesysteme |
| DDC classes: | 600 Technik, Medizin, angewandte Wissenschaften |
| GND Keyword: | Energiemanagement |
| Tag: | Battery storage; Model Predictive Control; Peak shaving | Formale Angaben |
| Open Access: | Closed Access |
| Licence (German): |  Urheberrechtlich geschützt |