SMUD upgrades its distribution system

In 2009 the Sacramento Municipal Utility District (SMUD), the nation’s sixth largest community-owned electric utility, started introducing smart-grid technology from transmission lines to customer meter as part of a $ 350 million upgrade of its power distribution system.

 


f7b9be29873ad525695063e6e748eae3

f7b9be29873ad525695063e6e748eae3

In 2009 the Sacramento Municipal Utility District (SMUD), the nation’s sixth largest community-owned electric utility, started introducing smart-grid technology from transmission lines to customer meter as part of a $ 350 million upgrade of its power distribution system.

A new Distribution Control Center got a wireless mesh network to support automated metering and more than 600,000 smart meters were installed. An advanced operating system was implemented to support new supervisory control and data acquisition (SCADA) equipment in substations and lines. The improved efficiency and reliability of the system is expected to save from $8 million to $15 million annually in power-supply costs and produce a return on investment in about seven years.

However, a way to analyse the data was needed by 2011. To monitor variables from transformers to customer meters, the company installed Situational Intelligence Server (SI Server). The new control centre correlates data from disparate sources that included technical operational systems, business systems and outside sources such as weather information. It uses geospatial and visual analytics software to produce charts, graphs and reports.

The smart grid upgrade was expected to save the utility — and its customers — from 1 to 3 %. The savings also come from avoided expenses. SMUD will reduce peak summer loads by 10.4 MW and reduce annual energy use by 36,520 MW-hours.

It took about six months for the new system to become fully functional. The operators were the first users of the system who are most interested in current conditions rather than trends, but other departments began finding ways to use stored data and analytics to help with planning.

For example, city designers can see what loads on specific transformers are over time to help with future planning and locating new feeder lines.

Source: GCN