nox reduction and boiler optimization - neuco, inc gen_conf_2015_sherco_u2_boiler...x reduction and...

Sherco Unit 2NOx Reduction and Boiler Optimization

2015 Power-Gen Conference

Jason Grimm (Xcel Energy)

Steve Piche (NeuCo)

Outline

Background

Equipment

Project Objectives

Parallel Projects

Combustion Optimization

Project Overview

Novel Neural Network Training Algorithm

Results

Conclusions

1Proprietary and Confidential

Background

EquipmentProject ObjectivesParallel Projects

2

Sherco Unit 2 Commissioned in the late 1970s

730 MWg 8 corner tangentially fired CE Boiler

Seven 1003 RP Mills, six required for full load

Wet scrubbers with electrostic precipitators

Single, shared stack with Unit 1

Wind-Following

Continuously cycle to follow demand. Turn down to about 40% of load capacity

Typically burn blend of 70% Black Thunder or Jacob’s Ranch and 30% Absaloka fuels

Proprietary and Confidential 3

Unit 2 Existing NOx Control

Mid 1990s OEM Designed LNCSFS III Low NOx system

Four levels of SOFA ports in 8 Corners

Closed Couple Over-Fired Air

Low NOx Burners

Opposed blade dampers and individual ABB damper positioners

Common stack CEMS

1 NOx and 1 CO analyzer per economizer outlet duct


Equipment Challenges

Unit 2 has older low-NOx furnace design and therefore cannot perform as well as Unit 1

Unit 1&2 common stack with common CEMS

Poor coal fineness and distribution

Limited NOx, CO, and O2 instrumentation

Unit 1 overhaul spring of 2015 Unit 2 solo operation

Project Goals

Goal: Reduce and maintain NOx emissions at least from a shared stack below 0.15 lb/MMBtu over a 30 day rolling averege starting January, 2015. At start of the project, goal was not being met.

Penalty: If the NOx is not maintained below the 0.15 lb/MMBtu average, the units must be derated to achieve the goal.

Shared Stack: Emission are measured in a shared stack from two 730 MW T-fired units with no SCRs.

CO Constraint: CO emissions must be maintained below 400 ppm.


Optimization Strategy

1. Establish optimal baseline boiler curves

2. Improve fuel fineness and fuel distribution

3. Optimize boiler performance through optimization software and operational strategies


Boiler Tuning with SmartBurn March 3 – 14, 2014

Determine baseline performance

Adjusted SOFA curves – Reduce CO and NOx,, balance O2

SOFA Yaw adjustments – Reduce CO, balance O2

Adjusted and “locked” SOFA tilts at + 20° - Max NOx Reduction

September 2 – 5, 2014

Adjusted windbox/furnace dP curve – maintain AA damper pos. ~25%

Adjusted to final SOFA damper curves

Adjusted O2 Curve and fuel-air damper curves

February 23 – 27, 2015 (Unit 2 Solo Operation)

Major Yaw Adjustments – Reduced CO from ~1000ppm ~100ppm at 2.5% O2 without Optimizer!

Full Load NOx ~0.155 lb/MMBtu with worst mill configuration!

8

Dynamic Classifier Retrofit

All 7 mills retrofitted with Loesche dynamic classifiers

Goals

>75% through 200 mesh

>99.9% through 50 mesh

Maintain current throughput

Installation Schedule

August, 2014 – March, 2015

Project included online coal flow measurement system

Courtesy of Loesche Energy

Systems


Coal Fineness Improvement

10

Combustion OptimizationProject Overview

Novel Neural Network Training Algorithm

11

Provides real-time closed-loop optimization of fuel and air

biases in the boiler as frequently as every minute.

Using:

– Model Based Optimization

– Models built using data from the unit (dynamic and neural net models)

To Improve:

– NOx

– CO

– Heat rate

– Steam temps

– Opacity

CombustionOpt


System Integration


Courtesy of CombustionOpt

V3.0 User Manual

Each server reads plant data

and sends optimized

outputs to the DCS via PI

NeuCo has remote

connections via VPN to each

server

Model Based Optimization


Manipulated

Variables

(MVs)

Controlled & Disturbance

Variables

(CVs & DVs)

Optimizer Model

Model Based Optimizer

Setpoints &

Constraints

SP

DCS / Plant

Output and Gradient

Model Options:

- Dynamic models use linear dynamic models (Model Predictive Control)

- Steady State models use neural networks (Neural Network Optimization)

DCS Screen


Available Manipulated Variables

Model Predictive Control (Optimize every minute)

O2 Bias

Windbox to Furnace Differential Pressure Bias

Neural Network Optimizer (Optimized every 10 minutes)

Aux Air Damper Biases (16)

Feeder Biases (7)

Over-fired Air Biases (12)

Number of available biases is 35.


Optimizer must observe boundary and rate of

change constraints on the manipulated variables.

Next Generation Neural Network Model

Confidence can be used in both training the models (input selection) and for optimization.

Design of experiments for collecting data can be based upon model confidence.

Sherco Unit 2 Updated to V3 software in September, 2014

18Proprietary and Confidential

Neural

Network

Model

Aux Air Biases (t+1)

Feeder Biases (t+1)

SOFA Biases (t+1)

NOx(t+1) – NOx(t) and

Neural

Network

Model

+-

+

Aux Air Biases (t)

Feeder Biases (t)

SOFA Bias (t)

Next Generation: Predict a change in NOx and the confidence in that change

due to changes in manipulated variables.

Variance(NOx(t+1) – NOx(t))

Sherco 2 CombOpt V3 UpgradeSeptember, 2014

More Routine DOEs

Daily DOEs

Keep models up to date

Models now use all variables, not just furnace specific

Extended bias limits on 22 and 23 OFA dampers

Completed DOE allowing 22 OFA dampers to go 5% 100% open

Showed 22 elevation OFA dampers have a large effect in controlling CO and NOx.

Currently allow OFA 22 elevation dampers to go 5% 50% at full loads

23 elevation OFA Dampers now have a limit of +/- 20%

Optimization Results

20

45 Day Test Period Results are collected from a 45 day test period (Nov. 16, 2014 to Dec. 31,

2014).

Optimizer was on 95% of the time during the test period.


Optimizer Off Optimizer On

Note: The data shown is average boiler outlet duct analyzer values, not the

reportable CEMS data

45 Day Test Period Results


Bottom Line: 10% NOx Reduction

Note: The data shown is average boiler outlet duct analyzer values, not the

reportable CEMS data

Sherco Units 1&2 NOx Emissions

Compliance Date

Conclusion

25

Conclusion & Lesson’s Learned

Boiler Optimization is a very dynamic effort requiring many pieces of equipment to be running in optimal condition including

Pulverizers - coal fineness and distribution

Furnace equipment - burners, SOFAs, tilt systems, air dampers, etc

Boiler controls - draft control, base boiler curves established

As the optimizer “champion”, it is essential to have adequate knowledge of YOUR boiler

What makes it tick, how far can you push it…

Conclusions & Lesson’s Learned

It is imperative to keep an open line of communication with the optimizer service engineering team in order to share ideas and make progress

It is vital to have a good working and trusting relationship with I&C and operators

The work on Sherco Unit 2 shows that when the above equipment is optimized and relationships are in place, NeuCo’s 3rd generation boiler optimizer can reduce it’s NOx an additional 10%

Questions?

Detailed Results


Optimizer Off Optimizer On

- Results collected over a 45 day period from Nov 16, 2014 to Dec 31, 2014.

- Optimizer was on 95% of the time during the test period.

Gross MW 669.04

NOx Ave 0.183

NOx East 0.188

NOx West 0.178

CO Average 221

CO East 278

CO West 165

O2 Average 3.16

O2 East 3.03

O2 West 3.28

Gross MW 676.44

NOx Ave 0.166

NOx East 0.175

NOx West 0.157

CO Average 258

CO East 341

CO West 176

O2 Average 2.9

O2 East 2.79

O2 West 3.01

More Recent Analysis4/1/2015 – 7/15/2015

SOFA Layout – U2

SOFA Ports – Unit 2

Operational Guidelines


nox reduction and boiler optimization - neuco, inc gen_conf_2015_sherco_u2_boiler...x reduction and...

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