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More data, increased transparency

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Modern electrical grid components deliver, process, and analyze data

One consequence of digitalizing power grids is the steadily growing volume of captured data. These vast quantities of data harbor valuable information that describes the state of the grid, enables advanced computational analysis of changes, and can improve the performance and extend the service life of assets. The hardware and software from Siemens needed for this fulfills all the requirements.

Transparency in the grid

Efficient ways to increase the performance of power grids

Deep insights into what is happening in the grids enable targeted, proactive actions to ensure optimal power quality at all times. 

Thoroughly analyzed grid data enable you to make well-founded decisions. This enhances performance and extends the service life of assets, while also simplifying processes. By optimizing maintenance deployments and increasing grid availability, you can also improve the cost-effectiveness of your grid.

Find out more in detail under the following topics

Seamlessly integrate IT and OT

A large part of project costs is caused during the engineering process that can be reduced by adhering to worldwide standards.

Analyses of past projects confirm that integrating IT and OT into the engineering process can save time and money. Much of the effort involved in such system integration was attributed to converting between different protocols. High costs were also incurred when connecting differing systems in the control centers and other systems such as energy resource planning. Consequently, power providers and suppliers worldwide have developed common standards in order to reduce costs and effort. This enhances the security of investments.

 

Benefits of integrating IT and OT

  • Reduce engineering costs by avoiding data conversion between protocols and interfaces
  • Get rid of gateways to convert between different protocols
  • Secure investment using long-lasting standards and open protocols

Validation of asset connectivity

Validation of a connectivity model based on secondary data.

The volume of data collected from various locations on grids is steadily growing, particularly due to the expanding feed-in of power from renewable energy sources. As a result, for every distribution network a data model exists which lists all assets and their connections to other such assets. Based on algorithms, a rather precise tree model of the grid can be calculated without knowing what assets it contains and how these are linked to one another. 

 

This method is important if, for example, connection errors have to be detected during a generational change in the grid control system.

 

 

Benefits for grid operators

  • Prevent connection errors when migrating large amounts of data during, for example, a generational change of the control center
  • Easy localization of connection errors
  • Increased efficiency and cost savings during comprehensive changes in the grid infrastructure

Controlling and balancing distributed generation efficiently

Imbalances between generation and load caused by excess supply or lack of generated power need to be managed reliably and cost-efficiently.

Coordinated scheduling and dispatch of distributed energy resources, including energy storage, helps tackle overload situations and voltage problems, and at least balance generation and load. The most efficient manner is to gain access to the distributed energy resources to balance the infeed in combination with the load via a control system. Many industrial processes allow not only a shutdown for load reduction. They also facilitate increased consumption during a high power production period as well. These actions can avoid investments into the grid expansion.

 

Benefits of balancing generation and load

  • Avoiding shutdowns
  • Compliance with rules and regulations
  • Stable grid
  • Reduce investments into the grid expansion

Products for controlling distributed power producers

Advanced monitoring with real-time state estimation

Economic solutions for the real-time monitoring of substations without measuring equipment.

Distributing various measuring devices throughout the entire distribution grid is a question of time and money. Strategically critical and important local distribution substations are the first locations to be equipped in order to optimize such deployment from an economic standpoint. Real-time state estimation performs an important function in this process, enabling that portion of grid substations that are not equipped with measuring devices to be mapped and considered.

 

Benefits for grid operators

  • Economic real-time state estimation calculated centrally or on a distributed basis
  • Advance detection of critical grid situations
  • Load demand history and load flow diagrams
  • Voltage level monitoring 

Highlight product for real-time status estimation

Validation of asset phase assignment

Siemens offers tools for parallel data processing that facilitate the rapid localization of phase asymmetries.

Phase asymmetries in grids can be detected and located based on captured data. These asymmetries often negatively impact equipment and electrical loads (i.e. electrical consumers) such as motors. As a growing volume of sensor and meter measuring data are available, these data can be used for analysis and thereby greatly facilitate the difficult and time-intensive local search for asymmetries among loads as well as sensors that have been cross-phased connected.

 

Benefits for grid operators

  • MapReduce function for parallel data processing of large amounts of data 
  • Power snapshot analysis provides information on grid condition based on smart meter data 
  • Voltage histograms deliver information on asymmetric loads
  • Interactive visualization of defined events such as sum totals or over-/undervoltage

Taking an active role in maintenance planning

Data analytics make maintenance of assets easier and more efficient.

Distribution grid monitoring helps to prioritize maintenance deployments and to detect potential faults and failures before they occur. Failure monitoring starts with aging equipment in critical grid substations. EnergyIP Analytics – Equipment Load Management (ELM) leverages existing AMI meter data to allow a preventative maintenance approach for the installed transformers.

 

Benefits of data analytics for asset optimization

  • Improve supply quality and security level
  • Early detection of potential problems based on online insights
  • Historical database for assistance with end-of-life assessment
  • Optimization of CAPEX and OPEX by reducing costly time-based maintenance practices

Highlight product for distribution grid monitoring

References

Solutions tried and proven in reference projects

The products and solutions from Siemens help maintain the right balance of power generation and consumption load and enable cost-effective operation of microgrids. Listed below are just some of the reference projects.

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