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Peter Spinney
Bob Williams, director of research for PennWell Publishing's Oil & Gas Journal Research Center Peter Spinney is Director of Market and Technology Assessment at NeuCo, Inc., the leading provider of optimization technology solutions within the electric power industry. His background combines electric power generation, economics consulting and government agency experience. Click here for a detailed bio.


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Improved Reliability and Commercial Availability Through ProcessLink®
June 5th, 2012
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As a NeuCo founder who was part of our company’s childhood as a combustion optimization provider focused largely on NOx reduction, it’s gratifying to see our technology offering expand to encompass improving the full spectrum of power generation processes affecting not only emissions, but efficiency and availability as well. And, as a former energy economist, it excites me to be able to help our customers improve their reliability and availability in particular, due to the key role they play in determining plant and corporate financial performance.

I generally try to focus my blogs on industry trends and regulatory developments, as opposed to our technology per se.  However, with the current financial challenges facing our industry, combined with the fruits of NeuCo’s intensive development effort in recent years suggest that it might be useful to summarize the many varied ways in which our technology can help improve availability.

Types of Availability Improvement
Broadly speaking, there are two fundamental ways in which ProcessLink® optimization technology contributes to improved reliability and availability. First, is through optimizing operations for coal-fired boilers. These availability improvements come in the form of reduced water wall erosion and corrosion and associated tube leaks, slagging and out-of-control process excursions through integrated optimal management of the highly interrelated processes of boiler stoichiometry, cleanliness, heat transfer and temperature control.

Second, comes from early detection of anomalous data indicating potential equipment health issues and quicker, more accurate identification of the root causes, criticality and actions needed to remedy the underlying problem.  These can be obtained from all fossil-fired generation, regardless of fuel-source or configuration.  I will address both, but let’s first focus on integrated boiler optimization for coal-fired boilers.

Availability and Boiler Optimization
NeuCo’s closed loop boiler optimization directly impacts generating unit availability.   Our closed loop optimizers reduce water wall erosion, corrosion, and thermal stress which can cause tube ruptures (which are responsible for half of the generation industry’s forced outages), lost megawatts and foregone revenue.

Erosion is the physical wear that occurs as the result of either hot gasses or boiler cleaning media: steam, compressed air or water.  Our comprehensive boiler optimization solution BoilerOpt® (combining the functions of both CombustionOpt® and SootOpt®) helps to avoid erosion through fewer cleaning actions. Water wall erosion is a major cause of tube ruptures. Where water is used as a cleaning medium, BoilerOpt helps avoid the water wall and boiler tube cracks that occur through thermal stress, which compromises the strength and integrity of the metal and contributes to tube ruptures.

Corrosion refers to a chemical process that compromises the structural integrity of steel used in the water wall and embedded tubes. It primarily occurs as a result of the reducing atmosphere from low-NOx (i.e. deeply staged) firing. In this situation, oxygen that would normally bond with iron is in such short supply (because it is used in the formation of CO) that iron monoxide (FEO) forms instead, rapidly accelerating water wall wastage and tube ruptures. This process drives the same type of unpredictable forced outages as the erosion process described earlier.

BoilerOpt helps avoid reducing atmospheres though better mixing of fuel and air and less CO formation. Its model predictive control (MPC) technology provides fundamentally better ability to maintain and achieve O2 and CO set points with controls effecting overall boiler oxygen levels, even during times of rapid load changes.  Neural network models are able to effectively resolve the cause-effect relationships between individual damper movements and a single measurement of stack CO, which is why it has been proven to not only reduce NOx and improve boiler efficiency but also avoid local pockets of substoichiometric firing conditions.  The combined effect helps avoid the oxygen-deficient conditions and reducing atmospheres that cause water wall corrosion, while simultaneously reducing NOx and improving boiler efficiency.   Optimization also helps avoid operator-induced swings (due primarily to under and over-compensation) in load, emissions, temperatures, fan and mill loading and other key operating parameters resulting in fewer outages and an increased capacity factor.

In summary, BoilerOpt consistently reduces blowing operations by 20-35% while improving boiler efficiency by 1% - 2%, reducing NOx by 5% - 20% and maintaining CO at set levels.  Comprehensive boiler optimization addresses combustion and heat transfer processes in an integrated manner by not only substantially reducing tube leaks, but also reducing de-rates and outages due to fouling, slagging, emissions excursions and overtaxing boiler equipment such fans and pulverizers.

Equipment Health and Availability
As we know, operating generating units creates complex, inter-dependent systems for moving air, grinding coal, pumping water, extracting energy from steam and converting motion into electricity. These systems are based on large-scale mostly rotating equipment with extreme duty cycles, critical needs for lubrication and cooling and multiple failure modes. Such equipment includes fans, pumps, mills (for pulverized coal), turbines and generators.

While a typical plant has thousands of real-time data points monitoring the performance and health of its equipment, noticing anomalous patterns in this sea of data is akin to finding a needle in a haystack. And while there are dedicated systems for monitoring individual signals, such as bearing vibration or metal temperatures, they focus only on the specific measured data itself, rather than the many, fast moving, relevant interactions that complex processes create, which makes it difficult to distinguish anomalies indicating actual problems from normal degradation and changes in operating conditions (load, ambient conditions, etc.).

Setting alarm thresholds based only on the measured signals themselves thus imposes a harsh tradeoff: tight thresholds result in false positive and “alarm flooding,” while relaxing them results in overlooking important but subtle changes that indicate real problems with equipment health and reliability.

Anomaly Detaction and Predictive Maintenance for Improving Availability
MaintenanceOpt® compares measured signals with model predictions in the context of system interactions to detect reliability, capacity and efficiency-related anomalies with much greater accuracy, scope and effectiveness than traditional condition monitoring systems. It also provides the information necessary to diagnose which anomalies point to real problems, to identify the causes of the problems and to prioritize the urgency of resolving them.  MaintenanceOpt is continually scanning for process and equipment health anomalies minimizing the likelihood of being blindsided by unpleasant surprises.

Working as a 24×7 ever-watchful partner, MaintenanceOpt saves time by going beyond alerts to help filter false alarms, identify root causes and corrective actions and prioritize the urgency of resolving problems. MaintenanceOpt uses neural network technology to constantly search for gaps between actual and expected behavior across a broad range of process and equipment health variables. Once these anomalies are detected, MaintenanceOpt’s heuristics knowledgebase helps to determine whether the problems are real, and if so, their most likely causes, the order in which they should be addressed based on criticality and cost impacts and the actions needed to resolve them.

MaintenanceOpt’s unique model-based predictive alerting functionality complements computerized maintenance management systems (CMMS) for planning, scheduling and tracking maintenance activities resulting from those identified anomalies. MaintenanceOpt enriches these systems by helping to more quickly and effectively identify anomalies with equipment health implications; and also help determine the cause, criticality and remediation of the underlying problems. Recently, we’ve been working more closely to integrate MaintenanceOpt with CMMS systems, a development which I’m very excited about but will have to save it for a future posting.

Let me conclude by reiterating my excitement at NeuCo having developed, proven, and commercialized a full complement of products aimed squarely at improving reliability and availability, the most fundamental determinant of plant financial performance.  The timeliness of these products with respect to current industry challenges is two-fold.  Clearly, the combination of stringent new emissions regulations and low natural gas prices means that improved availability will play a crucial role in determining the continued financial viability of coal-fired generation assets.  At the same time, MaintenanceOpt can also help with reliability issues imposed by natural gas-fired combustion turbines and combined cycle boiler plants, which by dint of emissions regulations and low gas prices are playing an increasingly important role in meeting our country’s electricity needs.

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