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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 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.
Dissertation D. Dongol
The increase in households with grid connected Photovoltaic (PV) battery system poses challenge for the grid due to high PV feed-in as a result of mismatch in energy production and load demand. The purpose of this paper is to show how a Model Predictive Control (MPC) strategy could be applied to an existing grid connected household with PV battery system such that the use of battery is maximized and at the same time peaks in PV energy and load demand are reduced. The benefits of this strategy are to allow increase in PV hosting capacity and load hosting capacity of the grid without the need for external signals from the grid operator. The paper includes the optimal control problem formulation to achieve the peak shaving goals along with the experiment set up and preliminary experiment results. The goals of the experiment were to verify the hardware and software interface to implement the MPC and as well to verify the ability of the MPC to deal with the weather forecast deviation. A prediction correction has also been introduced for a short time horizon of one hour within this MPC strategy to estimate the PV output power behavior.
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 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.