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When Will Smart Grid Be Available?
The concept of an intelligent electric utility infrastructure or "Smart Grid" is attracting wide interest among utilities, consultants, regulators, and other utility stakeholders. This interest, however, is accompanied by widely differing expectations about when Smart Grid will emerge. Some confidently proclaim that the Smart Grid is here or "just around the corner." But utility management and staff responsible for operating real electric systems are understandably cautious. They realize that Smart Grid will not suddenly become available in a suite of closely bundled technologies and applications. And they are pragmatic about the technology needed today to improve distribution operations for the next few years.
What Grid Is Already Here?
The concept of intelligent infrastructure will continue to evolve, but utilities have tangible choices now, and they do not have to wait passively to provide practical solutions as Smart Grid develops. Utilities can begin using existing and emerging technologies and applications to create something we might call an "Agile Grid", on the way to creating a Smart Grid. Many utilities already have deployed, or are planning, key elements or components of an Agile Grid. While there are numerous examples of these technologies and applications, in this article we discuss just one: integration of advanced metering infrastructure (AMI) with engineering analysis (EA) tools. An EA application may be operated as a stand-alone tool, with no consideration of a Smart Grid, and it will produce ample value. But some utilities are using available data interfaces and protocols to link EA to other applications to create even greater value, and this increases the utilities' agility in operating the grid: It takes them a step closer to Smart Grid.
One view of this Agile Grid concept is illustrated
in the diagram below. Many of the technologies and applications shown support data interfaces and protocols to exchange data and report actionable information that utilities can use now to improve reliability and plant utilization, and to better leverage their capital and operating expenditures. The exchange between EA and AMI is shown by the dark arrow.
EA Is a Great Tool
Available EA applications are robust tools capable of performing very sophisticated analyses on personal computers. EA applications vary by vendor, but they all perform a variety of distribution simulations based on an underlying model of the utility's distribution system configuration, equipment, and loads. A utility may have several different models saved to reflect the existing system, future capital budgeting construction plans, and current and future loads for winter and summer, etc.
Distribution system models can be built and maintained in several ways. One method in widespread use is to export a detailed representation of the distribution system from the utility's GIS, and add load data to it from other sources. The data quality and detail available in these GIS exports has improved dramatically over the past few years. Many utilities, including small municipal and cooperative systems, have very detailed and accurate distribution system models. A typical distribution system model will be geographically correct and include accurate circuit configuration, equipment and device data, and detailed connectivity information by phase at the meter level. These distribution system models are also used by some OMS applications for outage analysis.
To prepare an EA study of a particular area of interest on the distribution system, utility engineers need a distribution model that represents the actual distribution configuration and system loads for the particular time period of interest. Circumstances change frequently, and utility engineers may need to update their EA distribution models by importing updates from their GIS. This is readily done.
Updating load information isn't quite so easy. The process typically goes like this: Load data for the date and time of interest, collected from feeder or substation metering points and/or SCADA, is entered by engineers, often manually, into the EA software application. Engineers next use a routine within the EA software to allocate this load to feeders, and to individual line sections that make up each feeder. The load allocation is essential to produce a practical result, and its accuracy is crucial in determining the accuracy of all subsequent voltage, current, thermal loading, and loss calculations.
This load allocation usually depends, to some extent, on the available data and utility engineers' judgment and preferences. Load allocations along a feeder can be made proportional to the installed distribution transformer capacity, or based on customers' energy consumption and spot loads in individual line sections. If customers' monthly energy consumption and spot load information is used, this introduces another step in the process since all this information has to be imported from billing system databases. All in all, this process to import and allocate new load data within a new EA distribution model can be tedious. And its accuracy is generally limited by the fact that most of the customer load data are monthly.
Utility engineers have traditionally mitigated this tedious process by developing and saving a variety of winter and summer models of their distribution systems. When doing a new study, the utility engineer can choose a saved model for the analysis that is most appropriate for the planning horizon and load level.
AMI Improves Agility of EA
Traditional utility planning is becoming more volatile because of changing priorities and needs. Examples typically include changing financing priorities, interest rates, reliability needs, new technology, customer preferences, load changes, and political considerations, among others. The advantage that EA applications provide utility engineers -- to create different models such as winter and summer capital budgeting models previously discussed -- is also a disadvantage in a changing planning environment. None of the saved planning models may adequately represent the distribution system and loads today. But with AMI data, the planning engineer can model the actual system, as it is operating right now.
The effectiveness of EA applications is constrained by the timeliness and accuracy of the load data. The value and functionality of EA is dramatically improved by importing meter loads -- actual measured loads, not allocated loads -- recorded by AMI. Demand data for each active meter for a specific date and time can be exported by the AMI system directly into a detailed EA distribution model with little or no load allocation process required. AMI demand data, depending on the frequency of reads and billing constraints, can conceivably be imported on the same day it is collected, along with current GIS data, into a new EA distribution model.
An EA distribution model frequently updated with circuit and load data from the GIS and AMI systems allows utility engineers to use EA as a planning and operational tool. This allows the utility engineer to perform sophisticated, near real-time distribution simulations and analyses. Three examples of how utility engineers can use these EA capabilities include the following:
- Investigate proposed short-term solutions to immediate distribution problems and refine those solutions as necessary to make sure they're consistent with long-term capital budgeting plans. Alternate short-term solutions are sometimes required if the availability of approved budget funds is postponed.
- Identify and schedule upgrades/replacements of overloaded distribution line equipment such as transformers, regulators, reclosers, fuses, and line switches before they fail in service.
- Prepare contingency switching analyses to assist outage restoration, planned maintenance, and/or switching of loads to alleviate thermal loading and improve voltage levels.
Agile Grid Today -- Smart Grid Tomorrow
Widespread automation throughout a typical distribution system may someday be available and affordable. One of the many deliverables envisioned to be provided by Smart Grid applications is information about critical distribution functions. AMI can provide near real-time demand data on all active meters, which can be exported to detailed EA distribution models that enable utility engineers to perform near real-time distribution simulations and analyses. This may not be considered Smart Grid by some, but it is part of an Agile Grid that's readily available to utilities today, and is a capability that didn't exist just a few years ago.
In the next article in this series, we'll address how AMI can help improve work order management and operations activities.
