HT-TPP: A Hybrid Twin Architecture for Thermal Power Plant Collaborative Condition Monitoring
Abstract
:1. Introduction
2. Design Methodology and Approach
2.1. Power Plant Specifications and DT Development Business Concerns
2.2. An Agent Based Modeling Framework for Digital Twins
3. HT Architecture Conceptual Design
3.1. Hybrid Twin Architecture Requirements Engineering
3.2. Hybrid Twin Architecture—Analysis
3.2.1. Organization Model
3.2.2. Goal–Role–Capability Model
3.2.3. Domain Model
4. Hybrid Twin Architecture Proof of Concept for TPP Digital Twin
4.1. TPP Digital Twin Virtual Environment (BC1)
4.1.1. Steam Turbine Modeling
- -
- A1. The steam expansion process in the turbine is supposed to be an ideal adiabatic and isentropic expansion.
- -
- A2. Water steam expanded through turbine sections is supposed to comply with ideal gas pressure and temperature law.
- -
- A3. Turbine efficiency at HP section is considered constant.
4.1.2. Generator Modeling
4.2. DT Agents’ Development and Implementation
4.2.1. Agent Class Model
4.2.2. Plan and Protocol Models for HT-OMASE Agents
- -
- Mediator Agent (RQ2.2) The observe function of the OODA loop is entrusted to mediator agents whose role consists in observing the physical environment and its digital and physical agents, collecting sightings of physical twins, analyzing them, and transmitting to upper layer decision-makers permanent conditions indicators required for assets behavioral analysis within the virtual environment. In order to achieve their assigned roles, mediator agents are provided with a set of capabilities mainly features extraction and selection, and load forecasting. Features selection and extraction are executed by mediator agents concurrently, and outputs from it are exploited for condition indicators computing and anomaly detection. Received stream data according to a defined window are transmitted to mediator agents by communication interfaces with physical twin data sources according to a Foundation for Intelligent Physical Agents (FIPA) based subscribe interaction model represented in Figure 8.
- -
- DT Instance Agent
- -
- DT Type Agents
- -
- HMI Agent
- -
- Expert Agent
- -
- Security Agent
5. Experimental Results
5.1. Testing Scenario 1: Anomaly Detection and Root Causes Analysis for Steam Turbine (ST)
5.2. Testing Scenario 2: TPP Steady State Dynamic Simulation
5.3. Testing Scenario 3: Switch from Synchronized to Islanding Mode
6. Discussion
6.1. Contributions to DT and TPP Concerns
6.2. Limitations and Challenges of the Proposed Architecture
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Acronyms
Steam Turbine | |
ṁin | flow rate at inlet (kg/s) |
ṁout | flow rate at outlet (kg/s) hin: enthalpy at inlet (kJ/kg) hout: enthalpy at outlet (kJ/kg) |
Q | heat rate (J) |
W | work of non-conservative forces (J) |
condition at outlet (KPa) | |
condition at inlet (KPa) | |
y-intercept constant | |
residuals term | |
slope coefficients for inlet conditions | |
section inlet Temperature (°C) | |
section outlet temperature (°C) | |
K | isentropic coefficient |
mass flow rate at inlet (kg/s) | |
mass flow at outlet (kg/s) | |
section volume (m3) | |
density change due to pressure changes at constant temperature (s2/m2) | |
nominal pressure of sections (KPa) | |
nominal flow rate of sections (kg/s) | |
admission stage volume (m3) | |
wheel radius inlet stage (m) | |
length inlet stage (m) | |
wheel flow rate (kg/s) | |
regulated inlet flow through the 3 control valves (kg/s) | |
length admission stage (m) | |
cross sections volume IP-BP (m3) | |
cross section radius IP-BP (m) | |
cross section length IP-BP (m) | |
ratio of nominal and actual admission pressure | |
ratio of nominal and actual wheel pressure | |
ratio of nominal and actual extraction pressure | |
power coefficient HP section | |
power coefficient IP section | |
power coefficient BP section | |
power HP section (KJ/s) | |
power IP section (KJ/s) | |
power BP section (KJ/s) | |
steam turbine total produced mechanical power | |
team turbine power losses | |
HP section flow rate (kg/s) | |
isentropic coefficient | |
wheel enthalpy (kJ/kg) | |
extraction enthalpy (kJ/kg) | |
HP section flow rate (kg/s) | |
isentropic coefficient IP | |
IP extraction enthalpy (kJ/kg) | |
flow rate LP extraction (kg/s) | |
flow rate IP extraction (kg/s) | |
cross section flow rate (kg/s) | |
isentropic coefficient LP | |
enthalpy IP-LP (kJ/kg) | |
exhaust enthalpy (kJ/kg) | |
extraction 2 enthalpy (kJ/kg) | |
Generator | |
moment of inertia (kg.m2) | |
mechanical torque (N.m) | |
electrical torque (N.m) | |
rotor speed (rpm) | |
damping factor | |
reactive power (MVA) | |
active power (MW) | |
current voltage (V) | |
current intensity (A) | |
rotation angle (rad) | |
Delta power angle (rad) | |
generator reactance | |
damping ratio | |
L | cyclic inductance (H) |
Steam Condenser | |
flow rate exhaust steam (kg/s) | |
flow rate condenser (kg/s) | |
inlet temperature cooling water (°C) | |
outlet temperature cooling water (°C) | |
flow rate cooling water (kg/s) | |
cooling water mass (kg) | |
heat exchange ratio (KW) | |
thermal capacity of the cooling water (KJ/KgK) | |
condenser temperature (°C) | |
condenser volume (m3) | |
condenser specific constant KJ/(KgK) |
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Augmented OMASE Models | Conducted Work | ||||||
---|---|---|---|---|---|---|---|
DT-OMASE Views | Concerns | Stakeholder | Dynamic Diagram | Static Diagram | Views | DT | DT-OMASE |
Business View | Integration Context Awareness | Business Team Network | Goal Model for Dynamic Systems GMoDS | Domain model Scenario Descriptor | Environment View | [21,22,23,24,25] | [26,27] |
Usage View | Integration Context Awareness | Design and Development Network | State Chart Diagram Unified Modeling Language (UML) | Service model Requirements Document Use Cases Diagram for Agents | Agent Services View | [28,29,30,31,32] | [33,34,35,36,37] |
Functional View | Semantic and Syntactic Interoperability Sustainability | Design and Development Network Office Floor Shop Floor Networks | Plan Model | Activity Model | Workflow View | [38,39,40] | [41,42,43,44] |
System View | Integration | DT Architects DT Owner DT Technology Provider | NA | Architecture Diagram Role Description Agent Class Model | Architecture View | [45,46,47,48] | [49,50,51,52,53] |
Networking View | Communication Security Technical Interoperability Maintainability | DT Architects DT Owner DT Technology Provider | Protocol model | Protocol Descriptor Agent Class Model Role Descriptor Organization Model | Agent Society View | [4,54,55,56] | [57,58,59] |
Information View | Semantic and Syntatic interoperability Traceability | DT Architects DT Owner Digital User | Plan model Action model | Agent Descriptor Capability Diagram | Knowledge View | [60,61,62,63,64] | [51,65] |
BC | Derived Requirements | Type | Stakeholders |
---|---|---|---|
BC 1 | RQ 1.1 Shall simulate the three operating modes of TPP | Operational | Engineering Team |
RQ 1.2 Shall simulate a frequency disturbance from the national grid (above or below 50Hz) | Operational | Maintenance Engineer | |
RQ 1. 3 Shall simulate alternator active and reactive powers | Operational | Electrical Maintenance Engineer | |
RQ 1. 4 Shall simulate TPP with both design and dynamic data (ideal and real state of the components) | Operational | Maintenance and process engineers | |
RQ 1.5 Shall help to reproduce turbine, generator and condenser malfunctioning and failure | Operational | Maintenance engineer | |
BC 2 | RQ 2.1 Shall give predictions about medium steam consumption | Operational | Process engineers and control room collaborators |
RQ 2.2 Shall give predictions about plants units energy consumption and TTP Key Performance Indicator (KPI) | Operational | Top management | |
BC 3 | RQ 3.1 Shall give predictions of turbine and generator health and reliability performances | Operational | Process engineers and control room collaborators |
RQ 3.2 Shall detect root causes of malfunctions in the steam turbine | Operational | Maintenance engineer and control room collaborators | |
RQ 3.3 Shall enable testing and validation of new control strategies and maintenance corrective actions | Operational | Engineering team | |
BC 4 | RQ 4.1 Shall integrate the group’s current supervision interfaces | Functional | Control room collaborators |
RQ 4.2 Shall be validated by end users and control room operators before use | Functional | Engineering team | |
RQ 4.3 Shall respect security and safety standards | Functional | System architects and top management | |
RQ 4.4 Shall integrate interfaces to communicate securely with plants PLC, archiving systems and others TPP plants within the industrial complex | Functional | System architects | |
RQ 4.5 Shall integrate secure remote access | Operational | Engineering team |
Pressure Models | Temperature Models | Flow Rate Models | |
---|---|---|---|
Admission Model | |||
HP Section | |||
IP Section | |||
IP-BP Section | |||
BP1 | |||
BP2 |
Symbol | Description | Unit |
---|---|---|
Inputs | ||
Fad | Admission Flow | t/h |
Tad | Admission Temperature | °C |
Pad | Admission Pression | bar |
Outputs | ||
Proue | Admission wheel pressure | bar |
Pex | First steam extraction pressure | bar |
Fex | First steam extraction flow | t/h |
Pa1 | Steam extraction 1 pression | bar |
Fa1 | Steam extraction 1 flow | t/h |
Pa2 | Steam extraction 2 pressure | bar |
Fa2 | Steam extraction 2 flow | t/h |
Pech | Exhaust steam pressure | bar |
Tech | Exhaust steam temperature | °C |
VHP-x | HP shaft vibration X | µm |
VHP-y | High pressure (HP) shaft vibration Y | µm |
VLP-x | Low pressure (LP) shaft vibration X | µm |
VLP-y | LP shaft vibration Y | µm |
Tspeed | Steam turbine speed | rpm |
PTurbine | Steam turbine generated power | MW |
Pa | Generator active power | MW |
F | Generator frequency | Hz |
Pr | Generator reactive power | MW |
Papp | Generator apparent power | MW |
MAE | RMSE | R2_Score | Execution Time (s) | |
---|---|---|---|---|
MPCA-BI Bidirectional-LSTM-Attention | 0.136 | 0.024 | 0.960 | 110 |
MPCA-LSTM-Attention | 0.131 | 0.023 | 0.964 | 103 |
MPCA-LSTM | 0.117 | 0.019 | 0.975 | 104 |
XGBoost-BILSTM | 0.143 | 0.027 | 0.948 | 110 |
BILSTM | 0.145 | 0.028 | 0.945 | 111 |
XGBoost-GRU | 0.151 | 0.031 | 0.936 | 800 |
Variational Auto Encoder (VAE)-BILSTM | 0.144 | 0.026 | 0.954 | 157 |
AE-LSTM | 0.140 | 0.026 | 0.955 | 500 |
Parameters | MAD | MSE | RMSE | MAPE |
---|---|---|---|---|
Condenser Temperature | 1.65 × 10−9 | 7.12 × 10−13 | 2.32 × 10−6 | 9.36 × 10−5 |
Condenser Pressure | 5.30 × 10−6 | 6.79 × 10−6 | 0.004 | 2.86 × 10−5 |
Parameters | MAD | MSE | RMSE | MAPE |
---|---|---|---|---|
Active Power | 0.00014 | 0.0001 | 0.0132 | 0.0032 |
Reactive Power | 4.8412 × 10−5 | 2.9477 × 10−5 | 0.0111 | 0.0002 |
Apparent Power | 4.8412 × 10−5 | 2.9477 × 10−5 | 0.0111 | 0.0002 |
Current L1 | 0.0144 | 4.2884 | 2.0497 | 0.0011 |
Current L2 | 0.0142 | 4.0556 | 2.0596 | 0.0011 |
Current L3 | 0.0144 | 4.2884 | 2.0497 | 0.0011 |
Voltage L1–L2 | 2.4039 × 10−5 | 1.1400 × 10−5 | 0.0033 | 0.0002 |
Voltage L2–L3 | 2.4386 × 10−5 | 1.1655 × 10−5 | 0.0034 | 0.0028 |
Parameters | MAD | MSE | RMSE | MAPE |
---|---|---|---|---|
Admission pressure | 8.1217 × 10−7 | 2.1625 × 10−8 | 0.00014 | 3.264 × 10−6 |
HP pressure | 1.1584 × 10−7 | 3.4997 × 10−10 | 1.3502 × 10−5 | 2.7478 × 10−6 |
HP temperature | 0.0001 | 0.0006 | 0.0258 | 6.4394 × 10−5 |
HP flow rate | 0.0765 | 190.1617 | 13.793 | 0.5297 |
HP enthalpy | 2.2562 × 10−6 | 1.4752 × 10−5 | 0.0003 | 7.6123 × 10−8 |
IP pressure | 1.1584 × 10−7 | 3.4997 × 10−10 | 1.3502 × 10−5 | 2.7478 × 10−6 |
LP pressure | 5.673 × 10−6 | 1.0437 × 10−6 | 0.0010 | 9.46689 × 10−5 |
Exhaust pressure | 1.6522 × 10−9 | 7.129 × 10−13 | 2.3234 × 10−6 | 9.36019 × 10−5 |
Exhaust temperature | 5.3081 × 10−6 | 6.7922 × 10−6 | 0.0045 | 2.8694 × 10−5 |
Exhaust enthalpy | 4.981 × 10−5 | 7.6735 × 10−5 | 0.0084 | 0.0002 |
Turbine speed | 0.0408 | 54.1245 | 7.3480 | 0.0006 |
Turbine power | 0.0001 | 0.0007 | 0.0294 | 0.0008 |
Ref. | Proposed Architecture | Models and Tools | Provided Services | |||
---|---|---|---|---|---|---|
Domain | Links | Concerns | ||||
Grey Box | [72] | Functional view Information view Usage view Communication view | DT-PT DT-User PT-DT DT-DT DT- Third party | Interoperability Security Awareness Communication Ergonomics Robustness | Net logo multi-agent systems K means clustering for agents’ collaboration Empirical physical model of degradation | Anomaly detection Collaborative maintenance -Usage and maintenance phase |
[73] | Functional view Information view Usage view System view | DT-PT DT-User PT-DT DT-DT DT- Third party | Interoperability Security Awareness Ergonomics Robustness | Logical, kinematic and geometric models TCP/IP real time data communication Processing cycle and data integration | Assembly and virtual design and engineering of generators and turbines rotors -Manufacturing phase (rotor) | |
[68] | Functional view Information view Communication view | DT-PT DT-User PT-DT DT-DT | Security Awareness Connectivity Ergonomics Robustness | Neural network Physics and electrical diagram system and controller | Supporting the physical twin throughout its life cycle -All life cycle phases included | |
[71] | Functional view Information view Usage view System view Communication View | DT-PT DT-User PT-DT DT-DT DT- Third party | Interoperability Security Awareness Ergonomics Robustness | ANN Mechanical models based on the first principle of mechanics and differential equation | System dynamics and integration of operational data for the approximation of complex parameters -Design and engineering phase | |
[7] | Functional view Information view Communication view | DT-PT DT-User PT-DT DT- Third party | Interoperability Security Awareness Connectivity Robustness | Thermodynamic model Approximation and linear regression | Representation of steam turbine control system modeling -Operation and maintenance | |
Hybrid agent based | [51] | Functional view Information view Usage view System view Communication View | DT-PT DT-User PT-DT DT-DT | Awareness Connectivity Interoperability Security and operational safety Robustness | Cosimulation alternatives through OPCUA and OSGi for selecting synchronization technology MATLAB is used for simulations of models; MAS module is developed with JAVA | Modeling and simulation of plant assets smart services for operation optimization -Operation and maintenance phase |
[33] | Functional view Information view Usage view System view | DT-PT DT-User PT-DT DT-DT | Awareness Connectivity Interoperability Security and operational safety Robustness | JACAMO framework is proposed for MAS development and REST API based on a service-oriented architecture SOA (Service-Oriented Architecture) for DT | Smart quality control and operation optimization -Operation and maintenance phase | |
Ours | Functional view Information view Usage view Communication view Environment View System view | DT-PT DT-User PT-DT DT-Third Party DT-DT | Interoperability Security Awareness Connectivity Ergonomics Robustness Resiliency Traceability | OMASE for Architecture modeling MATLAB/SIMULINK for virtual environment modeling Python for agents’ services development A MAS establishment | Power plant simulation and assets mirroring Collaborative prognostics and smart condition monitoring -All life cycle phases included | |
[72] | Functional view Information view System view Communication View Security view | DT-PT DT-User PT-DT DT-DT DT-Third party software | Awareness Connectivity Interoperability Security and operational safety Robustness Traceability | Simulations are performed with Siemens Tacnomatix Process Simulated and OPC protocol for communication online and offline learning modules are developed on the top of the real system supervisory control system | Smart control and collaborative maintenance of plants assets Integration of DT into control architecture -Operation and maintenance | |
[73] | Functional view Information view Usage view System view | DT-User PT-DT DT-DT DT-Third party software | Awareness Communication Interoperability Ergonomics Robustness | Simulation of DT and agent’s operation testing is performed on MATLAB through its set of Toolbox and Simulink for DES (discrete event simulation) | Mining trucks and shovels maintenance operations monitoring -Operation and maintenance phase |
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Ghita, M.; Siham, B.; Hicham, M.; Amine, M. HT-TPP: A Hybrid Twin Architecture for Thermal Power Plant Collaborative Condition Monitoring. Energies 2022, 15, 5383. https://doi.org/10.3390/en15155383
Ghita M, Siham B, Hicham M, Amine M. HT-TPP: A Hybrid Twin Architecture for Thermal Power Plant Collaborative Condition Monitoring. Energies. 2022; 15(15):5383. https://doi.org/10.3390/en15155383
Chicago/Turabian StyleGhita, Mezzour, Benhadou Siham, Medromi Hicham, and Mounaam Amine. 2022. "HT-TPP: A Hybrid Twin Architecture for Thermal Power Plant Collaborative Condition Monitoring" Energies 15, no. 15: 5383. https://doi.org/10.3390/en15155383