{"id":231,"date":"2025-04-16T11:00:22","date_gmt":"2025-04-16T11:00:22","guid":{"rendered":"https:\/\/sicomx.com\/?p=231"},"modified":"2025-04-16T11:00:22","modified_gmt":"2025-04-16T11:00:22","slug":"is-your-energy-storage-lying-to-you-solutions-for-inaccurate-power-readings-in-pv-systems","status":"publish","type":"post","link":"https:\/\/sicomx.com\/?p=231&lang=en-gb","title":{"rendered":"Is Your Energy Storage Lying to You? Solutions for Inaccurate Power Readings in PV Systems"},"content":{"rendered":"\n

In the era of widespread digitalization and integration of energy systems with IoT solutions, owners of photovoltaic installations with energy storage are increasingly noticing alarming discrepancies between actual electricity usage and the data presented in monitoring applications.<\/strong>
Although the issue may initially appear to be a minor technical error, its consequences can be much broader \u2013 ranging from inefficient energy management to system vulnerability to manipulation and cyber threats.<\/p>\n\n\n\n

Where do incorrect readings come from?<\/strong><\/p>\n\n\n\n

Incorrect phase sequence<\/strong>
In traditional photovoltaic installations, the phase sequence in the building was not critically important. However, in systems integrated with energy storage, this issue becomes crucial. The storage system must precisely read which phase has demand in order to deliver energy efficiently. If the phases are connected in the wrong order, the system may misinterpret which loads are active and when.
This results not only in incorrect statistics in applications but also in improper use of stored energy, lowering the system’s overall efficiency.<\/p>\n\n\n\n

In practice, this could mean that energy is not delivered where and when it is needed. This leads to two issues: rising costs for the user and improper controller decisions, which may be misinterpreted by the monitoring system as “normal.”<\/p>\n\n\n\n

Reverse connection of current transformers (CTs)<\/strong>
Current transformers are sensors used to measure current intensity. For them to work correctly, they must be installed in the proper direction. When installed backward, the system may interpret energy consumption as energy being fed into the grid \u2013 and vice versa.
Such a reversal can disrupt the logic of the storage system, leading to energy being “stored” during periods of actual demand or \u2013 worse \u2013 left unused despite the battery being fully charged.<\/p>\n\n\n\n

From the perspective of energy security, this is a serious threat. A system operating on incorrect data can generate false consumption profiles, which in extreme cases could be used to analyze household or business activity \u2013 a potential entry point for an attack.<\/p>\n\n\n\n

Data averaging by applications<\/strong>
Many monitoring apps don\u2019t show real-time readings but instead present averaged data \u2013 for example, every 5 minutes. While this may be acceptable for UI ergonomics, it carries the risk of misleading users. Sudden spikes in usage, such as when turning on an oven or EV charger, may go unnoticed in real-time.<\/p>\n\n\n\n

For autonomous systems based on local control decisions, this means delays or even inaction. Moreover, if such data is sent to the cloud or an external system, it can be misprocessed, creating the illusion of “normal” operation. This opens the door to abuse \u2013 both by unaware AI algorithms and by malicious software infiltrating the system.<\/p>\n\n\n\n

Cyber perspective \u2013 when energy data becomes the target<\/strong>
Energy management systems are becoming increasingly intelligent \u2013 but also more vulnerable to cyberattacks. Faulty sensor data \u2013 whether from installation errors or malicious actions \u2013 can be used to:<\/p>\n\n\n\n