Making Distribution Automation Work: The Need for Smart Data

Making Distribution Automation Work: The Need for Smart Data

Introduction

Grid modernization is a transformative phenomenon that is expanding (1) the number and variety of active participants and devices, (2) the types of energy sources, and (3) the kinds of active business processes. The result is a significant increase in operational complexity at many utilities that are not supported by current corporate governance policies and business practices. The reality is that all of this is only practical with extensive computer-based automation dependent on multiple systems at multiple locations owned and operated by multiple parties cooperating within defined business scenarios. This requires information transfers between systems that were designed and operate independently. The challenge is to ensure that the hundreds of transfers involved in these complex processes are all informationally compatible with one another in order to achieve the desired end result. This is complicated in that each time a new system is acquired, without using standards, it will generate data in a form unique to that system. This data will often need to be transformed either before or after it is sent to other systems for consumption. When this data has different and possibly conflicting properties as described by its meta-data, this introduces complexity into the data transfer and the “care and feeding” of the systems at both ends of the integration. For instance, consider the different possible data definitions of “customer” that may be used by many different transacting systems.

The solution to this complexity needs to start with an awareness at the corporate level that data governance policies are needed to ensure data compatibility and consistency across all computer systems. Further, projects undertaken to procure distribution systems should also be compliant with the data governance policy, starting with the requirements phase. There needs to be a commitment to take the time to identify all the key computer system interactions within a utility redefine supporting business processes. While the governance review and the process of data transformation costs more up front, it pays significant dividend is system agility as opposed to the brittle interfaces that typically reflect organizations that lack data governance maturity.

A key foundational element to satisfy these policies and requirements as well as to also minimize the impact of adding/replacing major systems is a common language for data – a common semantic model. Various power system standards have been evolved which represent power systems using common information model at different levels in the power system sub-domains. Some of the information standards are IEC 61970/61968/62325 [1] - CIM, IEC 61850 - supervisory control and data acquisition (SCADA), and IEEE C37.118 phasor measurement unit (PMU). The Common Information Model (CIM) standard defines ontology semantics that represents the power system information in a unified way, which reduces the difficulty of interoperation between distinct proprietary power system applications. The CIM is an international standard incorporated in many of the largest utilities all over the world as a basis for scalable, maintainable model-driven system integration solutions. It involves all types of information exchanges for power system management, operations, and planning. Furthermore, the CIM is updated continually as new use cases are identified. For example, the CIM extensions to electrical distribution and CIM Extensible Markup Language (XML) were created to facilitate information exchange related to IEEE radial test feeders across power distribution applications [3].

The CIM approach to solving the problems described in this article is for most, if not all system interactions involving information exchange or database access to be based on the CIM semantic model and supporting standards. The scope of this article includes systems for advanced distribution management, geographic information, meter data management, outage management, work management, asset management, facilities management, customer information, and many others. The overall scope of the CIM, however, includes models for generation, transmission, and markets which are described in the other articles in this special publication on the CIM.