Our system is an independent open-innovation based system made up of hardware and software to measure, log and verify the performance of solar power installations of up to 10 kW installed power.


The hardware of the system will measure certain parameters that are important to the performance of solar modules, such as the current and voltage (in other words the power), the irradiance, the temperature, the humidity and the wind. This information is then collected and sent to our cloud service, where it is processed and analyzed together with known system parameters (in other words where all the magic happens) and then we can tell you if your system is giving you the most bang for the buck, or if you ought to be seeking retribution (or at least a warranty claim.
(Want to dig deeper into how this works? Check out The Nerdy stuff.

The information from the cloud is then presented to you in our app, where you can see both real time The system can also make predictions about future performance, and tell you if you in any not so distant future seem to be heading towards a possible warranty claim due to the system not fulfilling its lifetime requirements.

scaling up

When more and more of our systems get installed in different locations, and on different systems, even more interesting analysis and observations become possible. We can now verify the performance of individual systems by comparing the performance of systems by the same manufacturer in the same, or different geographical locations.
This enables our system to offer data on how modules made by different manufacturers are performing in real world conditions, and make this information available to both end-customers, vendors and manufacturers alike.

We can with this scaled up system also make large energy system-wise analysis of customer-based solar power, something which experts believe will be a more and more substantial part of the future energy system as we are moving away from a one-source broadcasted type energy, and towards a distributed system of many nodes that can act as both consumers and producers of energy.

Not a solar power guru? Want the basics?

The nerdy stuff.


In order to monitor and evaluate the performance and health of a solar power system, there are a number of different parameters that are important. The system is very much dependent on the IV-curves of the solar modules, which will set the limits to what performance is possible to achieve. The charge controller or inverter will then set a voltage for the solar modules in the string or strings to operate at. Sometimes this voltage is fixed as in the case of the more simple charge controllers, and sometimes the voltage can be changed as to maximize the power of the system. The most obvious parameter to measure is of course the delivered power of the string or strings.

The power is the product of the current and voltage of the system. So we need to measure the current going through the string, and the voltage over the negative and positive terminals of the string. The power is then proportional to the irradiance hitting the modules, so the irradiance should be measured. The temperature affects the performance of the modules, with a lower temperature leading to a higher possible maximum power because it raises the maximum power point to a higher voltage. But also a higher temperature might also in some systems increase the current at a given voltage and thus give a higher efficiency for a fixed-voltage system. So, in order to properly evaluate the relationship between the environment and the performance, it is best to measure both the ambient air temperature and also the temperature of the module.
Then it is also wise to also measure the ambient humidity, since it affects the heat transport of the surrounding air and might also at certain points induce a fog that shuts out the sunlight, or dew on the panels that will also degrade the performance. Another thing that affects the heat transport is the wind chill factor, why it is also wise to measure the wind.

By measuring these parameters a wide range of analysis is possible:
The most simple is to measure the power from the modules and the irradiance to make predictions about how different irradiances result in different powers. If this is information is then kept as a reference and analysed over time, we can notice if there is any rapid or slow degradation to the performance of the modules. we can then also include the measurements from the temperature sensors to see if they correlate to the changes, maybe in conjunction with the wind and the resulting wind chill, and also the humidity and information about the dew point if there might have been a fog at certain times.

If a rapid, consistent degradation is noticed, it is plausible that something has gone wrong with the system that needs correction. Maybe it is noticed that the power degrades dramatically whenever the humidity reaches a certain level. This could then be an indication to a crack in the modules that causes a partial or complete short-circuit of the module when exposed to water.

It is also possible to do even more complex analysis and troubleshooting in real-time when we have access to the manufacturer IV-curves and can interpret and program them into the system. We can then make comparisons between the expected and the actual performance of the system at different irradiances and sometimes even temperatures. If for some reason the system is not performing according to the manufacturer IV-curves then this might be reason for investigating. And maybe it turns out that the modules are faulty from the manufacturer or not performing according to their specifications as stated. When the system has been operating over a longer period of time one can make more advanced and delicate analysis using data mining methods and making statistics of the system performance over longer periods of time. Something which might reveal flaws and possible areas for improving the performance which would be hard to detect without the long-time analysis of multiple parameters.


We are developing a system using an open-innovation and open-source approach that consisting of a main logger-unit, and one sensoring unit for each string of the system. The sensoring unit is measuring the power of the strings, together with the irradiance, module temperature, ambient temperature and ambient humidity, and wind power. This information is then relayed to the main logger-unit which compiles it and sends it to the cloud for calculations. The connection to the cloud can be done both using an already existing wifi-connection, or using a 3G-connection depending on the choice of the user. If connection is lost for some reason then the logger unit contains an internal memory that is used as an emergency buffer to locally store the data until a connection can be re-established. The storage is a regular SD-card, meaning that it can also be removed physically from the unit for manual transfer of data.

The main unit is powered from the household electricity (it can be powered on both 230V, or directly from a 12/24V system depending on the need of the user and if it is a pure Island system or not) but also contains an internal battery that ensures that information is not lost in case of a power-down.

The main-unit is based upon a ARM-architecture processor, and uses readily available components. Since this processor is only used for packaging the data it ensures that we can use a minimum of energy in this hardware. All of the calculations are done in the cloud, where they are then made available for the end users either in a browser, or in an app for a smartphone or tablet.

 Our system is also developed as a modular system, in order to accomodate the needs of different users. For example, the user can use a different number of sensoring units depending on how many strings are in the system, and the user can use different methods of powering the system depending on the type of system the user has. Also, advanced user are able to make customized analysis using the cloud service, whereas a standard user will be presented with easy-to-understand information about the performance of their system.