Smart Grid, Part 4: The Intersection of the Power and ICT Fields

This is the last of the series of blogs on the intersection of the power and ICT fields. I started at home and moved toward the utility’s back office. Because of smart grid, a lot of data of many types will pour in to the back office, including data about power usage, monitoring of transmission and distribution lines, generator health and status, and weather. Someone said that data would be useless unless they could be queried and analyzed.

Those data must be aggregated, processed, analyzed, stored, and queried. Some data may be shared by multiple applications. Some applications interact with other applications via data and/or control. Even before discussing specific applications, we know the following:

  • Multiple applications must be loosely integrated to exchange data and control, and that requires an enterprise bus.
  • Each application and each platform for applications must be expandable and scalable. We cannot foresee all the future applications that might require specific interfaces and high scalability. It is very hard to predict what they will be, but we can make the architecture as flexible as possible.

Data can be roughly classified into two types: real time and non–real time. Monitoring of transmission and distribution lines happens in real time, and the collected data should be processed in real time so that any necessary measures can be taken. In severe weather conditions, outages could occur at any second, so the data associated with such weather also falls into this category. However, other weather-related data, such as tomorrow’s temperature, may not be processed in real time, although prompt processing may be necessary.

Another type of real-time information concerns generator status. Several different types of generators are in service at a given time. The attributes of each generator are in the utility’s database. Such attributes include total generation capacity, operation requirements (the number of hours the generator is permitted to run before it hits the limit on GHG emissions), current health, and any contractual agreements of its owners (if the generator belongs to someone else). In high demand time, the utility needs to assess what to do. It may calculate the number of kilowatts to curb by issuing D/R signals and seeing if that would satisfy the current demand. If not, it may have to start its own or someone else’s generators to satisfy the demand.

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Data Replication: Making Sense of the Options
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The total power consumption data also must be processed in real time to balance the fragile demand/supply balance. But the same data are also processed in non–real time for consumers to obtain. One of the biggest advantages of smart grid is that it informs consumers of their hourly (or less) power usage. Each household’s power consumption data are collected along with millions of other households’ and sent over to the utility’s back office to be processed and stored. Each consumer has access to the stored data. Currently, in the PG&E territory, access to the data is at least 24 hours late, and power usage information is only hourly. Some people claim that more frequent usage data is desirable. However, I am not sure what to do with data collected more frequently than hourly.

Several applications and keywords stand out in smart grid reports, articles, and books: SCADA, DMS, EMS, OMS, MDM, DA, grid optimization, AMI, CIM, D/R, and so on. I am not going to touch on each one here. But all these applications still deal with fairly low layers of smart grid and are directly related to the health of the infrastructure and the data collected by the meters. As smart grid progresses, more applications not directly related to usage data or infrastructure health will be developed. Everyone wants to know what the killer applications are going to be. At this time, D/R is considered a killer application. D/R is like magic. It produces extra power without your having to turn on extra power plants or generators. Yet it fixes the fragile balance of demand and supply without spending a lot of money, and does so almost instantly.

If you can name the next killer applications, you could build a Google of smart grid and become very successful.

Zen Kishimoto

About Zen Kishimoto

Seasoned research and technology executive with various functional expertise, including roles in analyst, writer, CTO, VP Engineering, general management, sales, and marketing in diverse high-tech and cleantech industry segments, including software, mobile embedded systems, Web technologies, and networking. Current focus and expertise are in the area of the IT application to energy, such as smart grid, green IT, building/data center energy efficiency, and cloud computing.

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