Monitoring and control of installations with solar production

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The integration of renewable energy sources and storage in buildings generates additional needs for control and monitoring, not only to ensure optimal operation but also to obtain a return of investment as quickly as possible.

IEC 60364-8-82:2022 Clause 82.7 Control and Monitoring requires an electrical energy management system (EEMS) defined as: "a system monitoring, operating, controlling and managing energy resources and loads of the installation."

The EEMS can be a dedicated system or part of an integrated system, such as a home and building electronic system (HBES) or building management system (BMS or BACS) or other similar management system. See also Smart Panels

Monitor to understand your energy production and usage, to detect problems early, and take the appropriate actions

To understand how electrical energy is being used and how it can be optimized, owners should:

  • Track how the local energy produced (PV ...) is being consumed by the loads, stored, or injected to the grid
  • Follow and analyze the trends of the local production alongside the loads’ consumption
  • Calculate economic benefits related to the reduced consumption of energy from the grid

Asset management features should also be provided by a monitoring system. This should include assessment of local production systems performance, detection of drifts or malfunctions, and immediate notification about faults.

Also, because local sources inverters can affect the power quality of the electrical installation, it is recommended that power quality disturbances be measured and followed, especially harmonics and unbalance.

Control local sources and loads depending on constraints and goals

When integrating local sources such as a PV system into a building electrical installation, control functions are often required. These functions will depend mainly on the available local sources, on the contract with the local energy supplier, and on the type of installation: grid-connected, islandable, or off grid.

For example, for an installation with grid-connected PV production, the required control functions could include:

If we take the example of an islandable installation, additional control functions are required because the control system should ensure the transition from grid-connected mode to island mode and vice versa, as well as the balance between electrical consumption and local electrical energy production in island mode.

Use advanced analytics to optimize usage of local sources

Advanced cloud-based analytics enable further optimization of the usage of local electricity production, which generates additional economic savings. By considering complementary criteria such as changing electricity tariffs, weather forecasts, and expected consumption, advanced analytics provide the optimal system configuration. A set point for each local source is transmitted to the local control system to continuously implement this optimal configuration.

A digital architecture fulfills monitoring, control, and optimization functions

Now, let’s review the digital architecture that can meet these requirements.

Fig. K77 – Example of digital architecture for installation with local production (photovoltaic, for example)

First, you need to collect input data, such as:

  • Local production and inverter status, from the local sources inverters
  • Power measurements, energy usage, and power quality data, from the power meters
  • Information on weather conditions, such as temperature and irradiance, provided by sensors

This data is collected using communication networks. High-end power measurement devices and local source inverters are usually connected directly through Ethernet. For sensors and other devices, gateways may be needed.

For monitoring purposes only, the data acquisition frequency can be every 10 minutes on average. But when local control functions are required, the data should be collected more frequently.

The collected data is used by an on-premises control system to operate the electrical installation equipment effectively and efficiently. Algorithms and analytics can provide optimal set points for the local energy sources and controllable loads.

The collected data is also used by on-premises or cloud-based software for visualization, analysis, and reporting.