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Electric utility fleet optimization through process control

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Combining Data

Combining Data
Combining real-time process, business and market data allows us to drive performance excellence.
The system uses our corporate single sign-on security authentication for logon and also provides transaction logs and tracks user form submittals automatically. ProcessNet eliminates the need to maintain client software and gives commonality to all applications and reports.

Months after deployment, all 6,000 DCS plant operator graphics were replicated in ProcessNet and populated by real-time PI data. These screens look and navigate just like the plant operator screens. The user also has the ability to set the clock back in history and incrementally step through an event while watching the displays. We find this to be a very powerful and useful tool.

System Dashboards Layer

To better equip our precipitator, combustion, turbine, electrical, rotating equipment, efficiency and performance experts, specific fleet-wide real-time dashboards are being developed. Not only can subject-matter experts (SME) view these displays anywhere through a VPN connection, but the displays also will be formatted for mobile devices such as  the Blackberry. SMEs will then be able to get a real-time view of the data they identify as primary indicators of asset operation through their Blackberries.

Expert Systems Layer

A fleet-wide implementation (19 units plus ten combustion turbines generators) of SmartSignal’s EPI Center uses historic data from PI to analyze and evaluate the condition of the specific asset. SmartSignal’s EPI uses similarity-based modeling built with correlated data from the actual asset.

Mobile Data

The Technology Framework provides real-time KPIs and process data to the mobile environment.
Implementation started in January 2006 and was completed in August 2006, except for the combustion turbine generators, which were completed in July 2007. Specific assets modeled include turbines, steam generators, boiler-feed pumps, air heaters, condensers, pulverizers, induced draft fans, forced draft fans, primary air fans, precipitators, feed water heaters and combustion turbine generators.

NeuCo’s CombustionOpt, a closed-loop combustion control optimization system based on the ProcessLink neural software platform, was installed on St. Clair Unit 7 and is currently in startup. Similar projects have been proposed for our Belle River and Monroe plants. Closed-loop combustion optimization implementation is going forward under the direction of one of our nationally recognized combustion experts. In conjunction with fuel analysis and other related technologies, we expect optimization to yield huge benefits. 

We are also working with NeuCo to provide a development environment for its suite of optimization solutions. The 3,200MW Monroe Power Plant uses an elaborate fuel-blending facility that continuously blends three types of coal. The plant has an online fuel analyzer and carbon monoxide grids that map the CO profile across the boiler. We hope to use this data to implement coal pile-to-stack optimization.

Business Intelligence Layer

DTE Energy offers our units to the Midwest Independent Transmission System Operator (MISO) market, which is made up of 14 utilities in the Midwest. Accurate day-ahead real-time capacities and units costs are essential for us to be competitive in this market. 

ECG has developed a robust web-based unit-capacity famework (UCF) application that manages all unit outages and unit de-rates. The UCF tracks unit costs, de-rates and fuel blends. It also determines unit capacity and is the primary source of data that feeds MISO and our Power Plant Performance Management Generation Availability Data System. 

Performance

Dashboards are an effective way for subject matter experts to evaluate equipment performance.
DTE Energy has upgraded its enterprise business systems to SAP for financials, human resources, and supply chain; and to Maximo for work management. Our hierarchical system index (HSI) data structure provides a method to roll-up costs from individual equipment, sub-systems, systems, primary systems, units, plants,and the fleet.

Enterprise business system data is correlated through a framework with the process data to enable many views of various processes. Information resides in its primary data source but the reports extract necessary information and help the organization make informed decisions. 

What is the real cost of blending a lower BTU content coal?  How does it affect boiler slagging, precipitator and mill performance? What does an automatic generation control program cost? To answer these questions one needs to know heat-rate, fuel, milling, emissions and maintenance costs.

Performance Excellence Layer

The DTE Energy Technology Framework top layer provides process costs to the sub-system level, provides asset health based on real-time process data and enables predictive analysis for our maintenance program. It also allows optimization of closed-loop control, and it accurately and competitively offers our generating units to the marketplace.

Fleet-wide implementation of business data is coupled with process data structured in a HSI. All data is organized with our EPRI Plant Reliability Optimization business model and works within corporate operating systems that support our Lean Six Sigma environment. DTE’s integrated technology, infrastructure and business processes drive performance excellence.

John C. Kapron is process technology framework development manager and Sumanth K. Makunur is lead engineer for process control at DTE Energy.

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