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by Meir Shargal and Doug Houseman
Capgemini
Editor’s Note: In Part One of this article series, our visiting experts from Capgemini explained why Smart Grid planning must start with understanding the communications backbone. Now they are back to provide a big picture of all the pieces that must tie together to complete the puzzle.
Figure 1 provides a conceptual view of all the components that will be needed to deliver on the Smart Grid vision. Starting from the bottom, they are:
Grid Hardware: Sensors range from meters at the home, to reclosers and sectionalizers at transformers and substations. Those sensors should be deployed in a prioritized fashion. The easiest way is to change the purchasing standards for new and replacement equipment to include the sensors. That way they are automatically deployed with each device, allowing you to fill in with additional retrofit sensors. The key is to understand which sensor readings bring operational value to your Smart Grid effort.
Figure 1: Smart Grid Conceptual Architecture
Communication Backbone: Although it is shown as the second layer in our illustration, the communications backbone is actually the first portion to plan, since it is the key to tying everything else together. (See link below to our previous article on this topic.) To support all the data sources on the grid, a high-bandwidth communication infrastructure must be in place. A wide range of wired and wireless communications technologies are available to transport data, but there is no one best choice. Any Smart Grid initiative will have to pick two or three communications methods, and mix and match as required to get to the required level of coverage. Some may be owned and operated by the utility (e.g. fiber to the substations), and some may be commercial networks (e.g. cellular phones).
Data Standards: The data sources do not always communicate via common standards. The two dominant standards are the common information model (CIM) standard and Multi Speak. Both define a standard data interface that supports batch and real-time data exchange. Multi Speak originated with the National Rural Electric Cooperative Association and CIM is an open-source standard through the IEC.
Another option is IEC 61850, a standard for data communications among intelligent electronic devices (IEDs) across a power system, it encompass the CIM model as part of IEC 61970 and IEC 61968.
Data Management: The Smart Grid will be the largest increase in data any utility has ever seen. The preliminary estimate at one utility is that the Smart Grid will generate 22 gigabytes of data each day from its 2 million customers. Just collecting the data is useless. Data management has to start at the initial reception of the data, reviewing it for events that should trigger alarms into outage management systems and other real-time systems. Then, and only then, should normal data processing start.
In addition, storing more than 11 gigabytes a day per million customers is not typically useful, so a data storage and roll off plan will be critical to managing the flood of data. Most utilities are not ready to handle this volume of data. For a utility with 5 million customers, they will have more data from their distribution grid than Wal-Mart gets from all of its stores, and Wal-Mart manages the world’s largest data warehouse.
Knowledge Continuum: Data coming from the field has different values to different parts of the company at different times. Outage data is best served to the outage management system as rapidly as possible. Load information might be best served on a 15- or 30-minute basis. Engineering analysis may need a full year of data available to analyze. This continuum can be simply characterized into three major categories:
1. Operational/Analytical Data: These are the real-time or near-real-time operational applications. They monitor and act based on notifications from grid hardware. Most are SCADA applications that sit at the operation center and are used for monitoring the grid.
2. Front Office: These functions help the business operate beyond real-time management of the grid. Examples include forecasting models that support generation planning and spot market power purchases or demand management programs. These data uses are typically same-day, same-hour applications, but there is time to scrub the data and even to try again to get information from the field.
3. Back Office: These are the non-real-time applications that provide rate analysis and/or decision support, based on the processing of data from the Smart Grid. The analytics transform data into actionable information. This is where the accountants, engineers, planners and standards engineers will find the data they need to do their jobs.
Planning and building an integrated Smart Grid is a complex collection of decisions and tasks. Laying down an overall foundation now can save money and headaches in the long run.
Adapted with permission from the authors.
Meir Shargal is a Principal with Capgemini Global Utility practice focusing on Smart Grid strategy and transformation. He is a strong, analytical leader who combines innovation with pragmatism, and vision with execution and a sense of urgency. With more than 20 years experience in strategy, transformation, and enterprise architecture, Meir is multifaceted technologist/strategist with proven experience in the alignment of technology solutions with business goals. He Holds BS in computer science and MS in Management Information Systems
Doug Houseman is CTO for Capgemini’s Global Energy, Utilities and Chemicals. He has more than 30 years of worldwide utility experience in all aspects of the utility and energy industry from engineering and design to maintenance and production. He has been selected as the lead investigator for a 20-year industry roadmap by one of the largest trade associations. Major companies in the industry and solution providers have turned to him to define innovative solutions to new complex problems. Doug has spoken at over 200 events, including international conferences. He holds a BS degree from the US Naval Academy and is a registered Professional Engineer (PE).
Email Doug Houseman and Meir Shargal
Original article: Leveraging Technology to Transform T&D Operating Models
SGN article on building a roadmap
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