A communications backbone is the key to achieving that interoperability. If the backbone isn't developed early, projects may have to be retrofitted later to accommodate the eventual communications standards, adding greatly to time and expense. Moreover, each individual project will be burdened with communications planning and costs, and the business cases for each will become much harder.

To determine what the communications backbone should look like, utilities must collect the timing and data requirements. To make meaningful progress in that area, utilities should focus on five main activities:

1. Gathering data: Collect data from many sources on the grid (sensors, meters, voltage detection, etc.), in the customer premises (sensors for high-consuming appliances, etc.), and from external sources (weather, etc). How many devices, how big is the data and how often do you want to talk to the devices? Finally, what is the latency that is acceptable? Data that can be dibbled to the central location of the course of the day needs less bandwidth than the same amount of data that has time sensitivity. Remember that data travels in two directions and one of the largest transfers of data to devices is firmware updates. A simple spreadsheet can be used to collect the data. Remember to account for future growth.

2. Analyzing and forecasting needs: In the typical world not all the data that a device can send is sent, but there are times when the engineering team needs additional data for forecasting or analysis. In some cases, wave form can be captured by a sensor, but the size of the data makes it prohibitive to send for routine daily traffic. However, when there is an issue in the geographical area, that wave form data may be very useful to the analysis of the issue. In other cases, different data may be required for forecasting for engineering or other use. After large storms you may need additional data to map the causes of the outage, cascading failures, timing of events and so forth. Make sure you account for the transfer of that bulk data.

 3. Security Requirements and Security Overhead: Standards like NERC-CIP and emerging standards in Europe require a level of security that adds to the traffic on the network. Additionally, standards like ZigBee and HomePlug can have message traffic which is more than 75 percent security overhead. Adding this to the bandwidth spreadsheet is an important step.

4. Monitoring / managing / acting: Once you know what the grid is doing, you have to act on it, and the latency on those actions is impacted by the traffic level on the communications network. It is important to provide operators with data in time for them to act on it. That does not mean sub-second response for every device; in some cases (e.g. a hot transformer), data within minutes with the right alarm set points is quick enough for the data to be actionable. In other cases, seconds can matter. Careful analysis of who needs what when in order to make a good decision and act on it, is the right way to finish the bandwidth analysis. It also helps determine the right placement of sensors and controls – you could do everything, everywhere and waste a lot of money. It is better to think through the actions that you can take and define the right sensors to support those actions.

5. Rebuilding the grid to support bidirectional power flow, looping circuits and transfer of power from substation to substation: The first four steps will have little impact to the end customers if you cannot act on the information that is collected and analyzed. This will be the most expensive part of the Smart Grid deployment, and will in most cases, take 20 years or more to complete across a whole service territory.

Elements of an intelligent power grid already exist in most electric utilities, but the full transformation involves much more than communications, and much more than just hardware and software. In Part II of this article, we will provide a conceptual view of all the components needed to deliver on the Smart Grid vision.

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