Optimization of the Aeration of Sewage Treatment Plants with Advanced Process Control

Transcription

1 Siemens AG, Optimization of the Aeration of Sewage Treatment Plants with Advanced Process Control Dr. Andreas Pirsing

2 Sewage Treatment Plants cause High Energy Consumption An increase in energy efficiency of 5% would create a value of approx. 580 Mio. USD OPEX costs of WWTP Energy costs of approx Mrd. USD p.a. Advanced Process Control APC is state-of-the-art in several industries, esp. Chemicals, O&G à standard tools available Customer Benefits Reduced energy consumption (typically by 3- to 10%) and the utilization of raw materials Increased capacity (typically by 1 to 5%) while maintaining consistent water quality Reduced number of manual interventions required by the operator thus reducing operator workload and improving operator efficiency Better understanding of the process through modeling and prediction Source: GWI, Global Water Market, 2015 à Transfer of established approach to W&W Page 2

3 Embedded APC Functions are Part of Modern Automation Systems Advanced Process Control (APC) is a broad term for different process control methods designed to minimize the usage of resources and/or to maximize the profit of a plant Typical (embedded) APC functions: PID Tuning Override Control Smith Predictor Gain Scheduling Model Predictive Control Control Performance Monitoring Source: Siemens, SIMATIC PCS 7 catalogue Page 3

4 Model Predictive Control: Controller Reacts already before Deviations Occur Model Predictive Control is able to detect future deviations Model Internal model control i.e. controller contains complete process model Set point Internal process model identified by recording of learning data Predictive Driving process according to predictions of near future Controlled variable (CV) Manipulated variable (MV) Controller reacts already before deviation occurs! Prediction of free movement: Controller detects future deviations (e.g. exceeding of maximum permissible quality value) Control Control problem is formulated as optimization problem and solved online past (measured values) Actual time k k+n c future (predicted values) k+n p Time t Page 4

5 Model Predictive Control: Internal Process Model Identified by Using Engineering Tools Linearized Internal Process Model is automatically created based on operating data Operate plant in constant conditions and wait until steady state is reached Transfer data model to MPC function block Excitate all relevant manipulated variables separately Implement MPC controller in automation system Steady State Operation Excitation Data Logging Data Model Model Transfer Control Loop Design Verification via Simulation Create Internal Process Model with MPC Configurator Log all relevant controlled variables (CV) Page 5

6 Project Example: WWTP using Upstream Denitrification Pilot plant is located in northern part of Germany: Customer was interested in benchmarking his control concept in respect to energy efficiency and effluent quality Project Example: Large WWTP, PE Private operating company Plant with upstream denitrification High level of energy efficiency due to several EE projects in the past Simulation model available, based on Matlab/Simulink SIMATIC PCS 7 already in place Page 6

7 Project Example: WWTP using Upstream Denitrification Pilot plant is located in northern part of Germany: Customer was interested in benchmarking his control concept in respect to energy efficiency and effluent quality Previous Control Concept Independent control loops for important controlled variables: DO concentration: PI controller is used to manipulate the blower speed Nitrate concentration: Characteristic Line controller to manipulate recirculation flow Ammonium concentration only monitored, not used for feedback control Disadvantages/Limitations/Challanges Influent fluctuations can not be handled properly Complex heuristic control logic difficult to maintain and modify Further energy/cost savings expected Page 7

8 Model Predictive Control: Data Model Identified by Recording of Learning Data Comparison of real values and internally modelled values shows good fit although linearized model is based only on data, example: ammonium concentration NK_BC_NH4/mgL CV: Ammonium Zeit/Tagen NK_BC_NO3/mgL CV: Nitrate Zeit/Tagen NI_BC1_spO2/mgL MV: DO Zeit/Tagen Rezi_sp/m 3 Tag x MV: Recirculation Q_RV_RLS Zeit/Tagen 1.45 x DV: Influent flow Zeit/Tagen Page 8

9 Project Example: WWTP using Upstream Denitrification Pilot plant is located in northern part of Germany: Customer was interested in benchmarking his control concept in respect to energy efficiency and effluent quality Previous Control Concept Independent control loops for important controlled variables: DO concentration: PI controller is used to manipulate the blower speed Nitrate concentration: Characteristic Line controller to manipulate recirculation flow Ammonium concentration only monitored, not used for feedback control Disadvantages/Limitations Influent fluctuations can not be handled properly Complex heuristic control logic difficult to maintain and modify New Control Concept, based on MPC Implementation of 2x2x1 MPC controller New controlled variables (CV): - Ammonia - Nitrate Manipulated variables (MV): - DO concentration - recirculation flow Disturbance variable: Influent flow Previous DO controller and recirculation controller used as slave controllers for cascade structure, can be used as back up as well Advantages Easy implementation of Model Predictive Control, based on standard function blocks Early consideration of influent fluctuations, due to dynamic disturbance compensation Page 9

10 Results of Model Predictive Control Quality Limits are Fulfilled or Increased Effluent Quality Performance of the plant in respect to effluent quality is increased à quality limits are fulfilled NH4/mgL Red: Previous control concept klassische Regelung MPC Blue: MPC control concept Influent Zulauf/m 3 Tag -1 Temp./ C 4 x Zeit/Tage Zeit/Tage NO3/mgL Zeit/Tage Zeit/Tage Page 10

11 Results of Model Predictive Control while Energy Consumption is Reduced by 5% Previous control concept and new MPC concept show different behavior, especially for recirculation Effluent Quality quality standards are fulfilled Main Results Transparent controller structure with direct access to setpoints for ammonium and nitrate à reduced maintenance efforts for automation updates Energy savings of approx. 5% More smooth operation of devices Rezi./m 3 Tag -1 O2/mgL Zeit/Tage 10 x Zeit/Tage 5 Red: Previous control concept Blue: MPC control concept Page 11

12 Project Example: WWTP using Intermittent Denitrification Pilot plant is located in North Rhine-Westphalia, Germany: Customer was interested in evaluating innovative control concepts because there is an update planned for the main WWTP, PE Project Example: Small WWTP, PE Aeration tank with aerated and unaerated phases, typical for small plants WWTP has been extended, incl. new automation system SIMATIC PCS 7 MPC is part of the new control concept, implementation foreseen in 2016 Page 12

13 Results of Model Predictive Control while Energy Consumption is Reduced by >30% Previous control concept and new MPC concept show different behavior, especially for the blowers Effluent Quality quality standards are fullfilled Main Results Energy savings of approx. 33%, to be confirmed under real conditions Reduced DO concentration due to optimized blower speed More smooth operation of blowers MPC is able to handle fluctuations in influent Red: Previous concept Blue: MPC control Page 13

14 Advanced Process Control Advantages of Integrated Approach Model Predictive Control (MPC) is part of SIMATIC PCS 7: There will be further functional enhancements, coming with new versions APC Engineering Tool è Modeling & Test Engineering Station ES Advantages of integrated APC: OS Clients Fully integrated into OS-LAN SIMATIC PCS 7 Ethernet OS-Server (redundant) (same look & feel in engineering & operation) Set of APC functions implemented in PCS 7 (free of charge, no additional license costs) Automation System High availability for APC as well (using redundant controller) Industrial Ethernet / Fast Ethernet APC OS Faceplates è Operation & Control APC Runtime function blocks è Runtime calculation Page 14

15 Advanced Process Control Summary of Pilot Installations Pilot installations show that MPC helps to increase the plant performance while energy consumption can be reduced Plant 1 Plant with upstream denitrification, approx PE Private operating company High level of energy efficiency due to several EE projects in the past SIMATIC PCS 7 already in place Plant 2 Plant with intermittent denitrification, approx PE Plant modernization ongoing, incl. new automation system SIMATIC PCS 7 Customer Benefits Increased plant performance, esp. effluent peaks can be avoided Energy savings of - approx. 33% - approx. 5% More smooth operation of devices, esp. blowers Transparent controller structure à reduced maintenance efforts for automation updates Easy implementation of MPC due to Integrated Approach with SIMATIC PCS 7 Page 15

16 Results of Pilot Plants are Documented in a White Paper and an Engineering Template Engineering Template enables quick and easy use of results of pilot installations White Paper Optimization of Sewage Treatment Plants by Advanced Process Control, 04/2015 Distribution via Internet Engineering Template PCS 7 Unit Template - Biological Stage Control of a Wastewater Treatment Plant with Primary Denitrification, 08/2015 Distribution via Internet Siemens Industry Online Support, Entry ID: Page 16

17 Siemens AG, Thank you very much for your attention Dr. Andreas Pirsing Contact: