Policymakers reflect on how it "coulda been." Nearly all insist "my state did it best."
California, Massachusetts, New Hampshire and Pennsylvania have deregulated their electricity...
meaningful information, which can involve several levels of analysis. The new technology designed to exploit non-operational data takes this multi-level analysis into account when serving up information.
The first level includes the analysis that addresses a specific problem or requirement. For transformers this could be diagnosing a bushing problem, or a tap problem, or an internal winding short. The next level would be an "aggregation" of results from the first level analysis. For transformers, this could be an overall predictive maintenance module or one that determined at what capacity the transformer could be safely operated. This second level is more complex and could not be done without aggregating the lower-level analysis elements.
The final level is the executive level that would be an aggregation of a selected group of mid-level modules. Such modules would address the critical business interests of the utility to include:
- Management of system stability
A near-time view of system stability, how it is changing, and actions and resources available to improve stability if needed. Executives will be aware of deteriorating system reliability and whether there are opportunities that are available to avoid an outage or catastrophic failure. Opportunities include available energy to be purchased or out-of-service transmission assets that can be restored.
- Maintenance cost optimization
A hierarchy of what equipment requires maintenance based upon the impact of its failure and cost or maintenance.
- Reliability improvement optimization
A roadmap of system improvements based upon projected reliability and congestion problems.
- System performance optimization
Executive level interface describing the operation in terms of capacity and opportunities of improving system performance.
If implemented properly, this new technology and method of processing data will provide utility executives with intelligent supportable information on which strategic operations decision can be made.
In general, electric T&D systems have been designed well and perform adequately, but significant portions of systems across the nation are growing old. As operators are forced to deal with increasingly less comfortable margins of reliability because of the growing need to run systems closer to the edge, it becomes necessary to make choices about acceptable levels of risk. Unless that risk can be identified and quantified through the use of operational and non-operational data, there is no solid basis on which to make those types of risk-management decisions.
The use of non-operational data also becomes strategically important as input to the executive decision-making processes. Since the data is already available, the cost of implementing a system to analyze and correlate the data should not be significant, and in fact can have a defined ROI just based upon addressing tactical solutions.
A solution that provides for this use of both operational and non-operational data from the grid is now available in a commercial, off-the-shelf form that has been installed and is running at a number of sites. Current market conditions make it clear that the electric industry has a mandate to apply technology such as this as quickly as possible to aid in the effort to proactively work to prevent blackouts and brownouts, and provide a more reliable, stable supply of electricity