Technical Project Summary for a new E-Monitoring Center
The TAQA Group is a world leader in energy production. As the top private electricity producer in Morocco, TAQA Morocco provides nearly 50% of Morocco’s electricity, serving ~18 million people through the 6 unit 2056 MW Jorf Plant and the 300MW 2×1 Takoradi Combined Cycle Plant.
To bolster their high availability and modernize their maintenance practices, TAQA sought to digitize and implement a central TAQA NA E-Monitoring Center. In addition to their desire to historize their asset data and visualize their
practices in real-time, TAQA wanted a predictive analytics solution that would find anomalous events within asset data and flag potential developing issues. The ECG Predict-It and PlantView solution provided TAQA with the ability to apply data processing through state-of-the-art tools using advanced software for early failures detection, close performance evaluation and support decision making regarding maintenance cycles optimization.
Selection & Implementation
ECG’s Predict-It software was chosen as TAQA’s predictive analytics solution in their centralized monitoring center to monitor their asset health in real-time. In order to implement the solution, ECG worked with TAQA to install the software using the OSIsoft PI System Asset Framework established by PIMSOFT. The Predict-It APR and Diagnostic Software Scope included:
252 total APR asset models were built for the 6 unit Jorf plant with assets including:
- Air Heaters • FD, ID, PA Fans • Pulverizers • Boiler Feed Pumps
- Generators • Condensers • Steam Turbines
53 total APR asset models were built for the Takoradi Plant with assets including:
- Sea Water Pumps • HRSGs • Gas Turbines • Steam Turbine
- Condensate Pumps • Generators • Boiler Feed Pumps
ECG configured the Predict-It Diagnostic Reasoner with asset specific casual asset networks (CANs) for the listed assets. 134 causal asset networks were deployed across the two plants. To do this the association of common faults and observed symptoms are arranged in a Bayesian framework for deductive reasoning that is backed by expert knowledge of each critical assets. With a total of 305 total APR and Diagnostic Reasoner models, ECG exceeded the original 225 model scope, to ensure the best monitoring capabilities for TAQA NA’s facilities.
ECG also deployed PowerVision’s PlantView PdM asset management module for the two sites. This integrated module within Predict-It allows TAQA NA to input advanced findings as well as other reliability-centered maintenance program reports, such as oil analysis, thermography, etc., to gauge overall equipment health.
Thermal Heat Rate Project Scope
In collaboration with TAQA, ECG was able to reduce the cost of opening a Monitoring & Diagnostic Center by leveraging their new investment in the OSIsoft PI system framework to calculate, track, and visualize equipment thermal performance and unit heat rate. Using OSIsoft PI Asset Framework and extracting features already existing in Predict-It, ECG was able to develop a performance monitoring system that calculated the following:
- Net Unit Heat Rate • Turbine Cycle Heat Rate • Mass Balances
- Regenerative Air Heater • Steam Turbine HP/IP Efficiency
- HP & IP Feedwater Heaters • Boiler Efficiency • Heat Loss Method
Using a Predict-It feature to write the predicted value to a PI Tag permitted ECG to apply “Intelligent Substitution” within the asset framework based Thermal Performance calculations. For each input to the performance calculations, an intelligent substitution was applied to maintain calculation integrity and fidelity with minimal loss to asset performance visibility. Most importantly, ECG was able to completely templatize the entire system saving time and adding value by enabling the application of this system to multiple generation assets.
ECG provided TAQA NA’s team with comprehensive and thorough training on all aspects of model development, maintenance, and live monitoring for Predict-It and heat rate calculations. ECG continues to support TAQA Morocco in their ongoing implementation of their monitoring efforts through supervision of model development completed by the TAQA NA staff.