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A model predictive control based peak shaving application of battery for a household with photovoltaic system in a rural distribution grid.

  • In rural low voltage grid networks, the use of battery in the households with a grid connected Photovoltaic (PV) system is a popular solution to shave the peak PV feed-in to the grid. For a single electricity price scenario, the existing forecast based control approaches together with a decision based control layer uses weather and load forecast data for the on–off schedule of the batteryIn rural low voltage grid networks, the use of battery in the households with a grid connected Photovoltaic (PV) system is a popular solution to shave the peak PV feed-in to the grid. For a single electricity price scenario, the existing forecast based control approaches together with a decision based control layer uses weather and load forecast data for the on–off schedule of the battery operation. These approaches do bring cost benefit from the battery usage. In this paper, the focus is to develop a Model Predictive Control (MPC) to maximize the use of the battery and shave the peaks in the PV feed-in and the load demand. The solution of the MPC allows to keep the PV feed-in and the grid consumption profile as low and as smooth as possible. 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.show moreshow less

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Metadaten
Document Type:Article (reviewed)
Zitierlink: https://opus.hs-offenburg.de/3311
Bibliografische Angaben
Title (English):A model predictive control based peak shaving application of battery for a household with photovoltaic system in a rural distribution grid.
Author:Deepranjan DongolStaff Member, Thomas FeldmannStaff Member, Elmar BollinStaff MemberGND, Michael SchmidtStaff MemberORCiDGND
Year of Publication:2018
Publisher:Elsevier
First Page:1
Last Page:13
Parent Title (English):Sustainable Energy, Grids and Networks
Volume:16
ISSN:2352-4677
DOI:https://doi.org/10.1016/j.segan.2018.05.001
Language:English
Inhaltliche Informationen
Institutes:Forschung / CRT - Campus Research & Transfer
Institutes:Bibliografie
DDC classes:600 Technik, Medizin, angewandte Wissenschaften
Tag:MPC; Photovoltaic; rural distribution grid
Formale Angaben
Open Access: Closed Access 
Licence (German):License LogoUrheberrechtlich geschützt