There are not smart grids and stupid grids. There are a number of things you can do with a smart grid solution and you decide, how intelligent your grid should be and how fast you move from one level to the next.
Start measuring and monitoring, then add control, and ultimately optimize the grid to make best use of all injected energy, all at your own pace.
GridEye measures the power quality of the grid according to EN50160 and IEC61000-4-30 standards at the points where a module is installed. The values are sent in 10 minutes intervals (configurable) to the server, where they are visualized and stored. They can then be used for long term analysis and asset management.
Each module sends the measured values every 10 minutes (configurable) to the server, where they are displayed in timeseries graphs and stored for future analysis. Thresholds can be defined for violation detection and notifications are sent for visualization to the dashboard from where they can be exported to a management system via an IEC-104 interface.
Based on network measurements and defined behavior, control actions can be defined and commands sent to any controllable device, injection or loads, e.g. inverters, heating/cooling systems, battery storage, etc.
Intelligent algorithms take care of finding the best operating state and the most effective control parameters to maintain a defined condition, e.g. to maintain the voltage at a pre-defined level, an optimal combination of inverter and load control will stabilize the grid. For this, several criteria and priorities can be defined.
Electricity users expect a stable power supply. According to EN50160, 10% voltage deviation is tolerated. By defining voltage and current thresholds and using advanced control algorithms, GridEye maintains the grid in a stable state by acting on energy sources and loads.
The ultimate level of grid control is the optimization of energy flows. Production and consumption are rarely aligned. Excess energy has to be redirected or stored, energy gaps have to be filled.
The knowledge of the grid, of the sources and loads, of the typical user behavior and weather forecast, and of the energy costs and injection retributions allow the calculation of an optimal operating point. The prioritization of the various criteria can align DSO requirements and customer wishes.
The evolution of the grid over time by addition of new loads, generation, cabinets, etc., requires network planning studies to ensure that the grid is technically feasible and economically viable. DSOs need to perform the grid reinforcement studies by considering different possibilities, e.g. deployment of GridEye optimal control, building new line, cable, transformer, location and size of energy storage systems, etc.
The historical data can be used to construct time series of loads and production. Then, for additional loads/generation, the risk of congestion and/or voltage deviation will be evaluated. Advanced optimization algorithms support DSOs for optimal network planning decision.
Grid management becomes more and more complex and the result is far from being guaranteed. DSOs often include regular EN50160 compliant power quality reporting in their business processes. With GridEye, you can automate this process and collect and export all required pieces of data to include in your reports.
For a better knowledge of the grid, not only in real-time, but also over a long period of time, e.g. the load distribution of a transformer or the voltage distribution and phase consistency at a given point, you can analyze the historical data as far back as you have stored them.