Making Distribution Automation Work: The Need for Smart Data
CIM for a 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 a 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 efficiently handling a distribution network. Implementation of the CIM by distribution utilities while seeing greater adoption, continues to mature. Possible implemenStation 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, such as real-time measurements received from SCADA, a 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 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, accesses the detailed distribution network model from the GIS and customer data from CDM. The OMS performs analysis to determine the location of an outage whenever an outage call is received from a customer or an outage event received from a smart meter. In response to an outage, a utility attempts to restore service. 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 and substation-level data at the 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 interconnected 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 U.S. Department of Homeland Security, responded to 145 cyber threats in the energy sector, more than the other 15 U.S. critical infrastructure sectors combined. On the reliability front, the 2003 blackout in the U.S. 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 with 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 for network and asset management. 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 electric utilities 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 the Bureau of Indian Standards (BIS) (the BIS LITD-10 committee is the national mirror committee of IEC TC57 in India) [5]. As an extension of CIM to suit the requirements of Indian power grids, BIS has published CIM standards along with application use cases related 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, and maintaining acceptable frequency and voltage profiles. The R-APDRP process is categorized into two parts: (1) To get verified baseline AT&C losses, as well as SCADA/DMS implementation, Part A will include projects for establishment of baseline data and IT applications like meter data acquisition (DA), meter reading, billing, collections, GIS, management information system (MIS), energy audit, new connection, disconnection, customer care services, and web services. (2) Part-B will include distribution-strengthening projects. Eventually, in phased manner, the CIM-based DMS platform will be established and will pave a way for seamless interoperation between utility enterprise applications. Moving ForwardAlthough 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, 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 an organization’s ability to perform at the highest levels to address new data challenges. Irrespective of the blessings and challenges that successful silos bring, new computing capabilities continue to be tapped. Technologies such as wearable computers and augmented reality will not only be consumers of this new data but also will help move workers closer to where they are needed much faster than in the past, with new insights and 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 that 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 the greatest strength of CIM—an extensibility that is imperative as new use cases continue to be identified. The first standard in the CIM “family” was originally published in 2003 (IEC 61970-301). In the intervening dozen years, we have seen new standard families (IEC 61968, IEC 62325) 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 integration of utility applications. These updates reflect the value that the CIM provides as a semantic standard and the value that comes from not having to start from scratch each time a new use case is explored, but instead leveraging the good work that has gone on before. So, as we get smarter about the management of data, so will this be reflected in the CIM. And rather than becoming stagnant, the CIM will stop changing only when the utility industry stops innovating. For Further ReadingIEC 61968-100, Application integration at electric utilities – System interfaces for distribution management – Part 100: Implementation profiles 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
[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,”, IEEE Transactions on Power Systems, 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. Accessed 2 July 2015. http://www.bis.org.in/index.asp [6] R-APDRP. Accessed 2 July 2015. http://www.apdrp.gov.in/ [7] ISGF Advanced Distribution; Addendum to R-APDRP Study Report. Accessed 2 July 2015. http://indiasmartgrid.org/en/resource-center/Reports/ISGF_White%20Paper%20on%20Post%20RAPDRP.pdf
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, Massachusetts 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> Burma or Zimbabwe >> Rhodesia. Perhaps these authors are old-school. -->, 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 1.36 Mb. Share with your friends:
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