The management system endows every module with discrete intelligence. This has several benefits. One is that the home batteries' smart controllers enable the photovoltaic systems to operate to their full capacity. This is unusual. The law limits photovoltaic systems' infeed on very sunny days. Otherwise, the installed systems' output would overload the grid. This is why standard PV units have to be throttled just when the sun is brightest and they could generate lots of electricity. The energy management system works around this problem by rerouting the surplus electricity that grid operators do not want to buy, and storing it in the home battery for later use.

A forecasting model boosts these batteries' efficiency. The model factors the weather forecast into its predictive equation. First, it determines how much energy the photovoltaic systems are expected to produce in the hours ahead, and how much heat is likely to be consumed. Then it applies the results of these calculations to regulate storage. For example, the PV systems run at less than full capacity when the morning sky is hazy.

If the weather is expected to clear up by the afternoon so that the systems' output would have to be throttled, the energy management system will not start storing power in the morning, instead holding off until later to charge batteries. In other words, rather than following the standard practice of charging the batteries with the first kilowatt hour of electricity produced during the day, this system waits until more energy is on tap. The batteries will still be fully charged by evening, but without any solar power going to waste.