The algorithm of this optimization feature increases the self-consumption of the electrical energy produced by the photovoltaic system by shifting the battery charging (power storage system). It also covers the use case where the DC power produced by the photovoltaic system is higher than the maximum amount of AC (feed-in) power (e.g. due to a lower peak power of the inverter or due to regulatory restrictions).
Without optimization
In the scenario shown in graph 1, the sunny weather conditions mean that priority is given to charging the battery, which is fully charged before noon. The photovoltaic system can produce even more energy and the system could now start feeding into the public grid. However, it is only able to do it to a limited extent, for example, due to regulatory restrictions and due to limited AC inverter power. The area marked in gray displays the amount of energy that the system could be produced but was not feasible due to the limitation. This amount of energy can be considered as lost potential.
With optimization
The algorithm of the optimization feature “Forecast based battery charging” ensures that the battery is charged and discharged in a way that maximizes the amount of the PV energy produced and at the same time the earnings from the feed-in. In the scenario in graph 2, the algorithm has predicted that the peak load will occur around noon and is above the grid feed-in limitation. Therefore, the battery charging is stopped at 10:00 a.m. and storage capacity is reserved for the midday period. Once the feed-in power reaches the limit, the battery charging is continued, allowing for the maximum possible PV earning to be achieved.