Making Distribution Automation Work: The Need for Smart Data
CIM for Distribution Management System (DMS)
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- CIM for Compliance: Realizing Security and Reliability
- CIM in India: Smart and Sustainable Energy in the Developing World
- Moving Forward
- For Further Reading
- References
- Biographies
CIM for Distribution Management System (DMS)Over the last two decades, myriad vendor-dependent systems and SCADA systems have been part of utility automation, which provides support for the system operators to take prompt decisions based on the state of the grid at any given time. The interoperation between many of the proprietary systems becomes the challenging task for the power utilities. The CIM for DMS (IEC 61968) [1], has been established for developing seamless inter-application integration of a power utility, which conducts various operational and business processes for handling distribution network efficiently. Implementation of the CIM in distribution utilities is at its evolving stage. Possible implementation architecture for illustrating the integration of distribution utility application integration in CIM framework is depicted in Figure 5. The architecture is comprised of four layers, namely, databases, CIM data management, applications and data sources. There can be numerous data sources, for instance, real-time measurements received from SCADA, network model received from GIS or energy meter readings received from AMI/AMR. The data is stored in a data warehouse and accessed by multiple utility applications through the CIM data layer. The CIM data layer mainly includes adapters for converting data into CIM-compliant data definitions and for accessing data with databases. The software systems, namely Distribution Management System (DMS), Energy Management System (EMS), Outage Management System (OMS), DA, Customer Data Management (CDM) and Advanced Metering Infrastructure (AMI), communicate with the CIM message payloads over the enterprise service bus (ESB). The core DMS functions are listed in the Table 1. A few of the important applications based on the distribution network operation (NO) sub-functions are network connectivity analysis (NCA), state estimation (SE), load flow applications (LFA), Volt/VAR Control (VVC), load shed application (LSA), fault management & system restoration (FMSR), load balancing via feeder reconfiguration (LBFR) and distribution load forecasting. The OMS, an essential activity carried out in utilities, access the detailed distribution network model from the GIS and customer data from CDM. OMS deals with location of outage whenever the outage calls received from customers. In response to the outages, a process of restoration activities will be carried out. For all functions and sub functions to be carried out at the DMS, CIM can provide a common database via a CIM-oriented warehouse. The DMS interacts with smart grid data, substation level data at lower end and sends relevant data to the EMS at the higher end. Thus, the CIM helps in seamless integrations at all levels. 
Figure 5: Implementation architecture for the integration of distribution utility applications in CIM framework Table 1: DMS Functions and Sub-Functions [2]
CIM for Compliance: Realizing Security and ReliabilityThe modern grid is highly connected due to the widespread application of Internet Protocol (IP) communication and is increasingly complex as a result of deregulation. Security and reliability are important and challenging in this setting. Examples of security and reliability concerns are hard to miss. In 2013, the Industrial Control Systems Cyber Emergency Response Team (ICS-CERT), a division of the US Department of Homeland Security, responded to 145 cyber threats in the energy sector, more than the other 15 US critical infrastructure sectors combined. On the reliability front, the 2003 blackout in the US Northeast, which had impacts ranging from Michigan, Canada, and New York, and the 2012 blackout in India, which plunged over 600 million people into darkness, are stark reminders of the challenges. Due to the criticality of these issues, agencies such as North American Electric Reliability Corporation (NERC), European Network of Transmission System Operators (ENTSO), and European Network and Information Security Agency (ENISA) have developed regulatory requirements and best practice guidance. NERC Critical Infrastructure Protection (CIP) standards are an example of requirements to ensure security and NERC Protection and Control (PRC) standards are an example of requirements to ensure reliability. NERC CIP and PRC are enforceable regulatory requirements. Compliance to these standards require, for instance, connecting to protective relays at specified periodicity in order to check the system configuration (security compliance) or their protection function (reliability compliance). Erecting another silo solution for compliance activities is an ineffective approach: doing so replicates many functions that are already available in other utility systems. An efficient and effective solution, which is being espoused by many forward-looking utilities, consists of the following elements: Hardened and secure field devices that may be used in security-critical environments such as electrical substations Integration with WAMS, so that the tasks and resources are delivered to the field force device automatically GIS integration for test/compliance task visualization Test/compliance database integration, so that the test results are automatically uploaded to the database server The 61968-4 standard enables the integrations outlined. CIM-based integration is versatile and flexible: CIM even has concepts such as Document that can enable the exchange of documents such as machine-generated system security logs. The use of CIM-based integration in these new business process areas help reduce the distance to integrate (Figure 1) and, instead of creating an isolated silo, creates a foundation for an agile business landscape. CIM in India: Smart and Sustainable Energy in the Developing WorldCIM can play a pivotal role in the developing world by helping leapfrog to smart and sustainable energy by leveraging CIM-enabled smart data systems. In India, the need for developing CIM based standards has been identified by the Indian utilities and Bureau of Indian Standards (BIS) [5] (the BIS LITD-10 [5] committee is the national mirror committee of IEC TC57 in India). As an extension of CIM to suit Indian power grid requirements, BIS has published CIM standards along with its application use-cases to Indian power grid scenarios. In India, the process of implementing CIM in distribution utilities has commenced under the Restructured Accelerated Power Development and Reforms Programme (R-APDRP) [6, 7]. The program includes a standards-based development of a decision support system to aid system operators with grid disturbances, real-time data acquisition at distribution level, interoperation between various enterprise applications and monitoring. A few of the important objectives of the R-APDRP are reduction of Aggregate Technical and Commercial Losses (AT&C losses), improving the reliability and quality of service in terms of reducing outages, maintaining acceptable frequency and voltage profile. The R-APDRP process is categorized into two parts: (1) Part-A will include projects for establishment of baseline data and IT applications like Meter Data Acquisition (DA), Meter Reading, Billing, Collections, Geospatial Information System (GIS), Management Information System (MIS), Energy Audit, New Connection, Disconnection, Customer Care Services, Web services, etc. to get verified baseline AT&C losses as well as SCADA/DMS Implementation. (2) Part-B will include distribution strengthening projects. Eventually, in phased manner, the CIM based DMS [2] platform will be established and will pave a way for seamless interoperation between utility enterprise applications. Moving ForwardWhile data itself does not get smarter, utilities and other stakeholders of the electric grid will be getting tremendously smarter about how data is generated, transformed, and consumed. The grid of things (GoT)1 with millions of data points will provide tremendous insight into the real-time operations of utilities. However, it will be important that as capabilities are added that they are added in a thoughtful manner. As has been noted in this article, utilities are very good at creating “successful silos”, that is, adding new systems to address problems and successfully implementing these new systems. However, the challenge is that often these new systems are not added holistically, with an eye to make sure that redundancies are not being added to the corporate IT landscape (creating rather more of a landfill than a landscape). Redundant, brittle, IT systems will create drag on organizations ability to perform at the highest levels to address new data challenges. These cautions aside, new capabilities are just now being tapped. Technologies such as wearable computers and augmented reality, not only will be consumers of this new data, but will help move workers closer to where they are needed much faster than in the past, with new insights, new ways of visualizing assets both in the field and at generation facilities. Further, the new capabilities of wearables and augmented reality will facilitate making the work in the field safer than ever before allowing workers to see energized or hot assets long before they are in proximity of danger. The new capabilities will also allow them to have “just in time” information about any asset they are working with, delivered literally, right before their eyes. The development of new use cases and maturing of existing standards will continue to be an important part of the new smarter data paradigm. While some decry the notion that “the CIM is always changing” this is in fact a reflection that new use cases continue to be identified where the CIM can be applied and extended. The first standard in the CIM “family” CIM was originally published in 2003 (IEC 61970-301). In the intervening decade plus timeframe we have seen new standards family (IEC 61968, IEC 62325) as leverage the model, each bringing additional standards documents into this body of work. The CIM has already extended far beyond its roots as a definitive standard for power assets to now being used for distribution, energy markets, dynamics, weather, and for utility application integration. These updates reflect the value that the CIM provides as a semantic standard and the value that comes not from starting from scratch each time a new use case is explored, but leveraging the good work that has gone on before. So, as data gets “smarter” so will the CIM. And rather than becoming stagnant, the CIM will only stop changing when the utility industry stops innovating.
IEC 61968-900, Getting started with IEC 61968-9 IEC 61968-4, Application integration at electric utilities – System interfaces for distribution management – Part 4: Interfaces for Records and Asset Management IntelliGrid Common Information Model Primer: Second Edition, Product ID: 3002001040, Published: 16-Oct-2013, Electric Power Research Institute, Palo Alto, CA. References[1] International Electrotechnical Commission, “IEC 61970/61968/62325 CIM standards”. [Online]. Available: http://www.iec.ch/smartgrid/standards/ [2] Y. Pradeep, P. Seshuraju, S. A. Khaparde, V. S. Warrier, and S. Cherian , "CIM and IEC 61850 integration issues: Application to power systems," Power & Energy Society General Meeting, 2009. PES '09. IEEE , pp.1-6, July 2009. [3] X. Wang, N. Schulz, and S. Neumann, “CIM extensions to electrical distribution and CIM XML for the IEEE radial test feeders,” Power Systems, IEEE Transactions on, vol. 18, no. 3, pp. 1021–1028, Aug 2003. [4] G. Ravikumar, S. A. Khaparde, and R. K. Joshi, "Towards CIM implementation challenges in control centers worldwide and Indian power grid," India Conference (INDICON), 2014 Annual IEEE , pp.1-6, Dec. 2014. [5] Bureau of Indian Standards (BIS) LITD-10 [Online]. Available: http://www.bis.org.in/index.asp [6] R-APDRP [Online]. Available: http://www.apdrp.gov.in/ [7] ISGF Advanced Distribution; Addendum to R-APDRP Study Report [Online]. Available: http://indiasmartgrid.org/en/resource-center/Reports/ISGF_White%20Paper%20on%20Post%20RAPDRP.pdf BiographiesDr. Gerald R. Gray is a Technical Executive with the Electric Power Research Institute in Knoxville, Tennessee. Dr. John Simmins is a Technical Executive with the Electric Power Research Institute in Knoxville, Tennessee Dr. Gowri Rajappan is Smart Grid Architect at Doble Engineering in Watertown, MA Gelli Ravikumar is a Ph.D. student in the Department of Electrical Engineering, I.I.T. Bombay, India Prof. S. A. Khaparde, Department of Electrical Engineering, I I T Bombay, India 1 A more useful and industry specific application of the concept of the Internet of Things Directory: Projects -> IEEEmagCIM -> Shared%20Documents -> Article%204%20-%20Making%20distribution%20automation%20work%20-%20the%20need%20for%20smart%20data -> Drafts Projects -> Terminal Decision Support Tool Systems Engineering Graduate Capstone Course Aiman Al Gingihy Danielle Murray Sara Ataya Projects -> Rajinder Sachar Committee Projects -> Cape Lookout National Seashore Historic Resource Study By Projects -> Cape Lookout National Seashore Historic Resource Study By Projects -> Revolutionizing Climate Modeling – Project Athena: a multi-Institutional, International Collaboration Projects -> What is a Hurricane? Projects -> General Information Projects -> Press Information Projects -> 1 Introduction 3 2 Designing an Embedded System 4 Drafts -> Making Distribution Automation Work: The Need for Smart Data Download 1.37 Mb. Share with your friends:
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