IEC 61970 456 Edition 1 0 2013 05 INTERNATIONAL STANDARD NORME INTERNATIONALE Energy management system application program interface (EMS API) – Part 456 Solved power system state profiles Interface d[.]
General
Clause 5 presents some of the business problems that were considered in the design of this standard and discusses how the standard is expected to provide value to the industry.
EMS state estimation
EMS operations automatically run state estimators, typically triggered by specific events or set time intervals While 10-minute intervals were once standard, many installations now operate with shorter periods, approaching 5 seconds, aligning closely with SCADA systems This shift highlights the growing importance of event-based triggering for state estimators.
The state estimator is responsible for generating the most accurate representation of the system's state using the latest SCADA measurements This steady state solution of the power system serves as crucial input data for various essential functions.
A traditional Energy Management System (EMS) is typically set up by the vendor, utilizing contingency analysis based on the outcomes of the state estimator Although a standard configuration may not be required for applications from the same vendor, there is a growing interest in the industry for the capability to implement alternative algorithms for state estimation and contingency analysis.
An increasing number of analytical functions, previously not included in the Energy Management System (EMS), are now utilizing state estimator results as a foundation for real-time analysis, such as voltage stability assessments.
Market systems typically necessitate the real-time exchange of state estimation results from the Energy Management System (EMS) to the market system, which are often provided by various vendors.
Users seek the ability to integrate advanced user interface and situational awareness modules from various vendors into an Emergency Management System (EMS), with a requirement for these modules to access state estimator data.
Efficient archiving of state estimator results is essential for conducting both historical and real-time analyses Users should have the capability to import these results into network planning tool environments that are typically not provided by the EMS vendor.
All of these situations require an efficient standard method of producing state estimator results and making them available to other applications
Storing the entire set of input and output data for a large interconnection model over a 10-second period generates an immense amount of data, creating significant challenges for real-time exchange Nevertheless, certain inherent characteristics of this issue can be leveraged to alleviate the data burden.
The network model constitutes the majority of the data and remains largely stable, with infrequent changes that typically involve only a small subset of data A complete large model is only necessary during the system's initialization.
• The topology of the system changes more frequently (when switching devices change position), but still is relatively infrequent and again the changes are small compared to the complete topology
Analog measurement inputs vary with each run, yet in many cases, consumers do not require this data Additionally, if analog data is not stored, it can often be approximated from historical analog records.
• Solution state variables change at each run
To optimize business exchanges, the network model and topology should be updated only when changes occur, allowing for incremental updates instead of full model retransmissions This approach enables data consumers to initialize with a complete network model and topology at the start, receiving updates only when necessary, thereby minimizing data volume issues.
Gbytes/solution and Tbytes/day to a more manageable Mbytes/solution and Gbytes/day
5.3 ENTSO-E 3 Process: Day-ahead congestion forecast
A daily analytical operational process called day ahead congestion forecast (DACF) is currently applied in the ENTSO-E regional group continental Europe In this process,
Each Transmission System Operator (TSO) develops a power flow case that accurately reflects its territory for each hour of the upcoming day, utilizing outcomes from the day-ahead market These cases are then submitted to a central server for further processing.
• the full set of submitted cases may be checked for mutual compatibility (i.e do the boundary exchange conditions match);
After all cases are submitted, each Transmission System Operator (TSO) retrieves the cases posted by neighboring TSOs from the central server They then integrate these cases with their own models to create a comprehensive set of study models, enabling them to analyze regional congestion for the upcoming day.
• congestion result cases may be exchanged among TSOs, as the situation warrants
This work is carried out primarily with planning tools running bus-branch models (although an obvious possible variation on the process would be to generate cases with EMS tools)
The DACF process, while not real-time like state estimation, generates a series of cases at regular intervals Although solution values vary with each case, the network model remains mostly stable, with occasional changes in topology To address file size concerns, it is beneficial for the standard to permit incremental exchanges of the network model and topology.
The DACF introduces additional requirements that differ from state estimator scenarios, as it involves significant merging and extraction of solution components rather than a complete transfer of a solution As illustrated in Figure 1, TSO A conducts power flows to create a comprehensive overview.