Chair of Sustainable Electric Networks and Sources of Energy TU Berlin

Chair of Sustainable Electric Networks and Sources of Energy TU Berlin
Prof. Kai Strunz Tian LAN Philip Kiese Fuel Cells in More Efficient Aircraft: Modeling Power Distribution and Heat - Biweekly Progress Review - November 8, 2012

Overall Accomplishment
06/23/2011 TUB Project Title Fuel Cells in More Efficient Aircraft: Modeling Power Distribution and Heat Principal Investigator Kai Strunz Contract PROJECT DESCRIPTION Develop multi-energy modeling and co-ordinated dynamic control to support the increasing electrification of aircraft power systems by inclusion of multiple fuel cells as additional generation sources Overall Accomplishment Physics-based modeling of PEM fuel cell for integration into power distribution Contribution to power distribution and control (PDC) model by successfully integrating fuel cell and auxiliary equipment on AC and DC bus Diverse operation strategies and configurations of the fuel cells in the PDC system have been implemented, tested and evaluated Redeveloping PDC model to secure stable running Quarterly Progress Plan Forward Defining the architecture for the development of a Combined Heat and Power (CHP) enabled fuel cell model Evaluating equations for physics-based calculation of heat exchanger pump power Develop a fuel cell model library containing diverse fuel cell systems based on the TUB fuel cell model Develop a Combined Heat and Power (CHP) architecture for the fuel cell model to include into the PDC system Integrated modeling of different time scale electrical and thermal transients Issues/Risks None.

Schedule/Progress 2012 Task Description 1
Status Q1 Q2 Q3 Q4 1 Transient modeling of combined heat-and-power distribution system for more electric aircraft (CHP-ME) 1.1 Specification of system architecture considered for the CHP-ME 1.2 Implementation of MATLAB-Simulink model of CHP for more-electric aircraft (CHP-ME) 1.3 Specification and simulation of scenarios with transients 2 Multi-time-scale modeling of combined heat-and-power distribution systems for more electric aircraft 2.1 Development of CHP-ME model with multi time scales 2.2 Specification and simulation of scenarios across flight cycle

Project Overview Project Introduction
Our project: Develop multi-energy modeling and co-ordinated dynamic control to support the increasing electrification of aircraft power systems by inclusion of fuel cells as additional generation sources The use of fuel cells in this context presents several advantages: Minimizing primary aircraft generators Managing peak loads Hydrogen can be produced locally from resources other than oil Low or zero emissions Reduction of noise and emissions Byproduct of water and waste heat could be used on board of commercial airplanes Up to now, the project has lead to several deliverables and model releases Most recent deliverable: TUB “Modeling of Heat Generation in PEM Fuel Cells”, November 21, 2011

Project Overview Physics-Based PEM Fuel Cell Model
The TUB physics-based model aims at representing the general characteristics and behavior of PEM fuel cells by considering their most relevant physical phenomena It is thus a generic fuel cell model, which can be adapted to a variety of real systems Inspired by our discussions with Boeing, we aim to develop a model library containing models of diverse fuel cell systems based on the fuel cell model developed at TU Berlin Currently, the model is validated for a Ballard Mark V and a Hydrogenics HyPM HD 12 system representing the first components of the mentioned model library Manual / Documentation: Matlab/Simulink-Based Block-Diagram Oriented Multi-Scale Fuel Cell Model for Aircraft System Integration Simulate behavior of Ballard Mark V Identified parameter set for Ballard Mark V Identified parameter set for HyPM HD12 TUB fuel cell model in Simulink Simulate behavior of HyPM HD12

Simulink Model Structure of Physics-Based PEM Fuel Cell Model
Project Overview Simulink Model Structure of Physics-Based PEM Fuel Cell Model Deliverable:TUB (28/04/2011) Electrochemistry block – Calculates stack voltage Conversion block – Transfers the amount of water from mol/s to gallon/min Conservation blocks –Calculates the partial pressures for FC reactants Simulink block diagram of fuel cell

Simulink Model Structure of Physics-Based PEM Fuel Cell Model
Project Overview Simulink Model Structure of Physics-Based PEM Fuel Cell Model Deliverable:TUB (26/03/2012) Electrochemistry block – Calculates stack voltage Conversion block – Transfers the amount of water from mol/s to gallon/min Conservation blocks –Calculates the partial pressures for FC reactants Thermodynamic block – Calculates stack temperature Simulink block diagram of fuel cell

Simulink Implementation of Power Distribution and Control (PDC) System
Project Overview Simulink Implementation of Power Distribution and Control (PDC) System GUI – Toggle between 6 operation modes of fuel cells and battery on AC and DC bus AC loads Fuel cell/battery hybrid source on DC bus GUI - reference power input for loads DC loads AC generator Fuel cell/battery hybrid source on AC bus

Simulation Example for Strategy of Peak Power Supply
Project Overview Simulation Example for Strategy of Peak Power Supply a) Motor power references b) Motor speeds AC generator operates constantly at 120 kVA c) Power demand of loads d) Power share of different generation sources

1. Task 2: Multi-time-scale modeling of combined heat-and-power distribution systems for more electric aircraft – Work Content Task 2 divided into three subtasks: Development of CHP-ME model with multi time scales Integrate CHP-ME model into PDC system Possible solutions for Multi-time-scale modeling Specification and simulation of scenarios across flight cycle Specifying usage of fuel cell Creat simulation scenarios with transients

Outline Overall progress Ideas for Multi-time-scale modeling
Next Steps

1. Overall progress Task 1 : Modeling of CHP distribution system for more electric aircraft (CHP-ME) Specification of system architecture considered for CHP Implementation of MATLAB-Simulink model of CHP Specification and simulation of scenarios Task 2 : Multi-time-scale modeling Development of CHP-ME model with multi time scales as well as PDC system Long term simulation

2. Ideas for multi-time-scale modeling
Questions to be answered: Why do we need the multi-time-scale modeling? Short term simulation: Transients analysis Long term simulation: Efficiency analysis of Fuel Cell Long term production and viability for Fuel Cell Fuel Cell effect on system reliability

Questions to be answered: Does the PDC system need to be simplified? Implementing PDC system with MATLAB Simulink: Variable time step size Easy to be implemented PDC system needs to be simplified, Simulink will adjust time scale automatically Implementing PDC system with MATLAB Code: PDC system may not be changed Time step size could be flexible and controllable A completely new task, which would consume a lot of time √ preferable

Current situation: It is very time consuming to run the simulation. For example, a 5-second simulation (Maximum Power Supply) takes s on 3.20-GHz CPU with 4GB of RAM Short term goal: Reduce the computational time to a usable span for running second simulations Long term goal: Simulation may cover the whole flight cycle

– Solution Approach 1 Detailed Model: Contains most detailed models for each system component Requires smallest time step size Averaged Model: Simplification by averaging state variables Approximating controlled state variables with constants Larger time step size Feedforward Model: Low resolution Usage of low resolution models Removing all state variables except for storage devices Increase of time step size

– Solution Approach 1 Three modeling methods : Detailed Modeling Averaged Modeling Removing Partial Pressure Feedforward Modeling Removing Double Layer Charging Effect

– Solution Approach 1 Load Current with transients: TUB

– Solution Approach 1

– Solution Approach 1 Detailed documents of PDC System are necessary The whole system should be very well understood. State variables check

– Solution Approach 2 Test and optimize the PDC-System function blocks separately First subsystem: Fuel Cell, and Local Control on HVDC Bus Optimization for 10s time span These weeks focus is control block of Fuel Cell

– Solution Approach 2 Replacement of Simulink origin control blocks 10s simulation time with Simulink blocks: s 10s simulation time with new blocks: s

– Solution Approach Conclusion and Findings: PDC System Simplification is necessary Simulation method Averaged modeling and Feedforward modeling can be used Short term goal Make the system model more practicable

3. Next Steps Next two weeks: Focus on PDC- System

Outline Recent Significant Accomplishments Project Summary
Introduction and Project Partners Power Distribution and Control (PDC) System Overall Accomplishments Physics-Based PEM Fuel Cell Model Fuel Cell Integration in PDC Simulation Example Comparative Analysis of Fuel Cell Controls for Diverse Configurations Summary Appendix – Technical Details

2.1. Introduction Our project: Develop modeling and co-ordinated dynamic control for integration of fuel cell and storage devices to support increasing electrification of aircraft power systems Application: primary and secondary power generating systems The use of fuel cells in this context presents several advantages: Minimizing primary aircraft generators Managing peak loads Hydrogen can be produced locally from resources other than oil Low or zero emissions Reduction of noise and emissions Byproduct of water and wasted heat could be use on board of commercial airplanes

2.1. Project Partners and Work Share
For optimized operation of the power management and distribution (PDC) system including fuel cells as power sources, a hierarchy of power management is required: A global energy management optimizer generates optimal set points for each load and source based on associated cost penalties Local dynamic controllers for each load and source optimally meet the set points generated by the global optimizer For the PDC system under consideration, the Adaptive Power Management (APM) designed at UW is the global optimizer, and the Power Distribution and Control (PDC) designed at TU Berlin is the dynamic local control for the fuel cell/battery hybrid source Power Distribution and Control (PDC) - SENSE Laboratory - TU Berlin Adaptive Power Management (APM) - DSSL - University of Washington Professor Kai Strunz Professor Mehran Mesbahi Johannes Schiffer Ran Dai

2.1. Project Partners and Work Share
TU Berlin: Dynamic power distribution and control (PDC) Load & Source Management Optimizer System Supervisor (Logic) UW: Adaptive power management (APM)

Introduction and Project Partners Power Distribution and Control (PDC) System Overall Accomplishments Physics-Based PEM Fuel Cell Model Fuel Cell Integration in PDC Simulation Example Summary Appendix – Technical Details

2.2. a) Power Distribution and Control (PDC) System: Overall Accomplishments
Physics-based fuel cell model Contribution to power distribution and control (PDC) system Fast-reaction fuel cell/storage combination Integration on AC and DC bus Dynamic control Deriving, implementing and testing of operation strategies for fuel cells

2.2. a) Power Distribution and Control (PDC) System: Simulink Implementation
GUI – Toggle between 6 operation modes of fuel cells and battery on AC and DC bus AC loads Fuel cell/battery hybrid source on DC bus GUI - reference power input for loads DC loads AC generator Fuel cell/battery hybrid source on AC bus

2.2. b) Physics-Based PEM Fuel Cell Model: Overview
Physics-based modeling of a PEM fuel cell Electrochemical, thermal and conservation phenomena considered in model Multi-scale modeling provides different scales of accuracy addressing different application and simulation purposes Validation with experimental data Manual / Documentation: Matlab/Simulink-Based Block-Diagram Oriented Multi-Scale Fuel Cell Model for Aircraft System Integration

2.2. b) Physics-Based PEM Fuel Cell Model: Model Structure
Electrochemistry model – Calculates stack voltage Thermal model – Calculates stack temperature Conservation model –Calculates the partial pressures for FC reactants The conservation model has a fast time constant and is the focus of model-order reduction Conservation Thermal Electrochemistry Simulink block diagram of fuel cell

2.2. b) Physics-Based Fuel Cell Model: Model Validation
The models are validated with experimental data of a Ballard Mark V with 35 cells and 232 cm2 membrane obtained from related literature [6],[7] In steady state both detailed and averaged model give same results Fast transient response reveals differences in accuracy and reaction time of detailed and averaged model due to model reduction

2.2. b) Physics-Based PEM Fuel Cell Model: Simulation Results
Test with a Ballard Mark V model consisting of 35 cells with an active area for each cell of 232 cm² and a maximum power of 5 kW The oxygen and hydrogen inputs remain constant Load current step from 50 A to 150 A after 2 seconds Partial pressure hydrogen Fuel cell current Partial pressure oxygen Fuel cell voltage

2.2. c) Fuel Cell Integration in PDC: Overview
Contribution to power distribution and control (PDC) system Integration of fuel cell and auxiliary equipment (compressor, tanks) in PDC as AC and DC source For faster and more efficient operation, fuel cell is combined with a Li-Ion battery Control and power management algorithms for a flexible and fast power supply share

2.2. c) Fuel Cell Integration in PDC: Implementation of Different System Configurations
Consideration of four different configurations of the PDC is proposed: PDC without fuel cell PDC with fuel cell on DC bus PDC with fuel cell on AC bus PDC with fuel cell on AC and DC bus Each of these configurations incl. the required power electronics and local controllers is modeled The additional integration of batteries is optional and may be included as necessary for purposes of dynamic control All configurations are included in one Matlab/Simulink model Operation modes allow to switch interactively between different configurations

2.2. c) Fuel Cell Integration in PDC: Realized Configurations
a) PDC without fuel cell b) PDC with fuel cell on DC side c) PDC with fuel cell on AC side d) PDC with fuel cell on DC and AC side

2.2 c) Fuel Cell Integration in PDC – Operation Strategies
Operation strategy Main strategy characteristics Maximum Power Supply (PFC,max) Operate fuel cell(s) always at maximum power output Peak Power Supply (PPeakSupply) Perform peak power shaving of generator with fuel cell(s) Percentaged Power Supply (P%) Provide always certain percentage of load by fuel cell(s) to support generator

2.2. c) Fuel Cell Integration in PDC: Control Hierarchy

2.3. Simulation Example: Matlab/Simulink Model - HVDC Loads
100 kW motor 50 kW motor Current supply from fuel cell on DC bus

2.3. Simulation Example: Matlab/Simulink Model - Fuel Cell and Battery
Fuel cell and battery on AC bus

Local controllers for fuel cell and battery MIMO system (4 PI-controllers) Fuel cell, battery and local control Fuel cell and battery on AC bus

H2 tank Fuel cell Compressor for O2 supply Battery Fuel cell, battery and auxiliary equipment Local controllers for fuel cell and battery MIMO system (4 PI-controllers) Fuel cell, battery and local control Fuel cell and battery on AC bus

2.3. Simulation Example: Matlab/Simulink Model - Simulation Start-Up
Selection of operation mode Definition of motor power reference values

2.3. Simulation Example – Test Setup for Evaluation of Operation Strategies
Sizing of fuel cell may be to supply the loads during boarding without any other source Based on one string from [1]: Suggested total fuel cell nominal power 80 kW Load demand AC: 25 kW + 25 kW = 50 kW Load demand DC: 100 kW + 50 KW =150 kW Loads Power Demand Count Galley 15 kVA 3 45 kVA Air condition 1 Illumination 12 kVA Total power demand 72 kVA [1] Meckler, Fecht, Kurrat, Wilkening, Lindmayer, “Schalten in Bordnetzen mit variabler Frequenz bis 800Hz“

2.3. Simulation Example – Strategy 2: Peak Power Supply (Overview)
This strategy is designed for peak power shaving of the AC generator by the fuel cells Thus, the available fuel cells shall only support the AC generator in periods of high load demand These periods are specified by a certain threshold to be determined for every specific case This strategy could be used to operate the AC generator constantly at its optimal operation point and use the fuel cells to balance out fluctuations in the demand In the present example, the threshold for peak-shaving is set to 120 kVA Consequently, the control of the reference signal generation for the alternative sources is designed such, that these 120 kVA are covered by the AC generator and every demand exceeding this threshold is covered by the fuel cells

2.3. Simulation Example – Strategy 2: Peak Power Supply (Simulation)
a) Motor power references b) Motor speeds AC generator operates constantly at 120 kVA c) Power demand of loads d) Power share of different generation sources

2.3. Simulation Example – Strategy 2: Peak Power Supply (Simulation cont´d)
Battery provides fast power supply Battery is charged during fast load decrease Battery provides fast power supply a) Fuel Cell and Battery on DC Bus b) Fuel Cell and Battery on AC Bus

Introduction and Project Partners Power Distribution and Control (PDC) System Overall Accomplishments Physics-Based PEM Fuel Cell Model Fuel Cell Integration in PDC Simulation Example Comparative Analysis of Fuel Cell Controls for Diverse Configurations Summary Appendix – Technical Details

2.4. Comparative Analysis of Fuel Cell Controls for Diverse Configurations
– Introduction In Task 1 a general simulation platform suitable for the dynamic analysis of fuel cell integration into aircraft power systems has been developed In Task 2 diverse operation strategies for hybridization studies with fuel cells have been implemented for 4 selected configurations of the PDC system Now, Task 3 discusses and evaluates the different configurations and strategies with respect to their potential benefits for supporting the increasing electrification of aircraft power systems. The focus of the evaluation is on the impact of alternative generation sources regarding minimization of primary aircraft generators Analysis of diverse operation strategies revealed significant changes in power factor of AC generator Reasons therefor are investigated by means of analysis of generated and consumed power in PDC system for diverse fuel cell locations

– Reactive Power Consumption in PDC System
2.4. Comparative Analysis of Fuel Cell Controls for Diverse Configurations – Reactive Power Consumption in PDC System AC loads do hardly require any reactive power due to internal power factor correction AC/DC conversion for supplying the DC loads with AC generation accounts for the remaining % of reactive power consumption Main feeder of PDC system exhibits inductive behavior and consumes about % of all reactive power in system

– Evaluation of Mode 3: Allocation of Fuel Cell on DC Bus
2.4. Comparative Analysis of Fuel Cell Controls for Diverse Configurations – Evaluation of Mode 3: Allocation of Fuel Cell on DC Bus Allocation of fuel cell on DC bus allows significant reduction of reactive power in system due to Reduced power transmission over main feeder Reduced AC/DC power conversion This results in an increased power factor of the AC generator, here: 0.99 compared to in basic case However, fuel cell power supply limited to DC loads

– Evaluation of Mode 5: Allocation of Fuel Cell on AC Bus
2.4. Comparative Analysis of Fuel Cell Controls for Diverse Configurations – Evaluation of Mode 5: Allocation of Fuel Cell on AC Bus For the allocation of the fuel cell on the AC bus, no reduction in reactive power can be observed due to No reduction in power transmission over main feeder No reduction in AC/DC power conversion But: As consequence of active power supply of fuel cell on AC bus, a reduced active power generation of AC generator can be observed However, the required reactive power is not reduced AC generator in mode 5 compared to basic case: reduced active power generation, equal reactive power generation Consequence: decreased power factor of AC generator (0.92 compared to 0.97)

– Evaluation of Mode 6: Allocation of Fuel Cell on AC and DC Bus
2.4. Comparative Analysis of Fuel Cell Controls for Diverse Configurations – Evaluation of Mode 6: Allocation of Fuel Cell on AC and DC Bus For the allocation of the fuel cell on the AC and DC bus, a reduction in reactive power can be observed due to Reduction in power transmission over main feeder Reduction in AC/DC power conversion This reduction is lower than for mode 3, due to the splitting of the total fuel cell power rate into fuel cells on AC and DC bus The power generated by the fuel cell on the AC bus still needs to be transmitted over the main feeder, which causes reactive power consumption Due to the fuel cell allocation on the AC bus, a reduction of active power generation of the AC generator can be achieved As a result the power factor of the AC generator is slightly lower compared to the basic case ( to )

2.4. Comparative Analysis of Fuel Cell Controls for Diverse Configurations
– Average Peak Power Generation of AC Generator for Operation Modes 3, 5 and 6 Generator Active Power P [kW] Generator Reactive Power Q [kVar] Generator Apparent Power S [kVA] Power Factor (P/S) Only AC Generator 201.6 50.6 207.9 0.970 Mode 3 (Fuel Cell DC) 117.2 16.9 118.3 0.991 Mode 5 (Fuel Cell AC) 121.3 50.4 131.4 0.923 Mode 6 (Fuel Cell AC and DC) 118.7 30.9 122.0 0.973 Operation mode 3 achieves highest AC generator relief with respect to minimizing its peak power and best power factor

2.4. Summary The project provided the following new knowledge up to now: Multi-scale model of a PEM fuel cell Electrochemical, thermal and conservation phenomena considered in model Multi-scale modeling provides different scales of accuracy Validation with experimental data Contribution to power management and distribution (PDC) system Fuel cell integration on AC and DC bus Combination of fuel cell with fast reacting battery storage Different configurations are included in one Matlab/Simulink model Development and testing of of several operation strategies incl. dynamic control for PDC system Comparative Analysis of Fuel Cell Controls for Diverse Configurations Decision of allocation and operation for alternative energy systems is depended on desired system performance and system configuration A combination of DC and AC integrated fuel cell system could be a good tradeoff and provide high system flexibility

Appendix – Technical Details Physics-Based Modeling of PEM Fuel Cell Extending PDC Suitable for Hybridization Studies With Fuel Cells Fuel Cell Integration in PDC Power Distribution and Control

App. a) Physics-Based Modeling of PEM Fuel Cell - Overview
Modular block-oriented concept: Main block remains equal for each scale Inputs and outputs remain equal for each scale Same subsystems for each scale: Electrochemistry model Thermal model Conservation model

App. a) Physics-Based Modeling of PEM Fuel Cell - Temperature Model
Heat produced in the electrochemical reaction based on the voltage drop associated with losses in the fuel cell: Heat loss due to natural air convection: Temperature of the fuel cell is calculated as:

App. a) Physics-Based Modeling of PEM Fuel Cell – Electrochemistry Model
Nernst voltage is the ideal fuel cell voltage level without losses: For a PEM fuel cell the activation voltage drop is calculated as: Double layer charging effect is calculated as: For a PEM fuel cell the ohmic losses are calculated as: The final fuel cell output voltage equation integrates the double layer charging effect into the calculation with the following result:

App. a) Physics-Based Modeling of PEM Fuel Cell – Conservation Model Anode
The partial pressure of the hydrogen evaluated in the conservation model is calculated according to: The stack output molar flow rate, no is calculated from: The molar fractions of the hydrogen is calculated as:

App. a) Physics-Based Modeling of PEM Fuel Cell – Conservation Model Cathode
According to the anode model the partial pressure of the oxygen and water is calculated as: As well as the molar fractions of the oxygen and water:

App. b) Extending PDC Model Suitable for Hybridization Studies With Fuel Cells: Flexible Load Integration – Standardized DC Load For flexible load representation, we have designed a standard DC load model The model inputs are: Specified power demand in kW Voltage level in V The model output is: Related DC current in A A low pass filter is used for softening the transients to avoid iteration problems in Matlab/Simulink The current is calculated by the power divided by the voltage

App. b) Extending PDC Model Suitable for Hybridization Studies With Fuel Cells: Flexible Load Integration – Standardized AC Load (1) For flexible load representation, we have designed a standard AC load model in DQ-frame The model inputs are: Specified apparent power in kVA Specified power factor Operating voltage in DQ-frame in V The model output is: Related current in DQ-frame in A A low pass filter is used for softening the transients to avoid iteration problems in Matlab/Simulink

App. b) Extending PDC Model Suitable for Hybridization Studies With Fuel Cells: Motor Power Limitations - Motor Power References GUI Interface Interface between PDC (developed at TUB) and Load Manager (developed at UW) has been implemented PDC can receive external speed commands via a GUI, which can be a generic load power (kW) commands Implementation based on look-up tables for each motor ( kW  rpm ) The model input is: Specified active power in kW for motors (can be sequence) The model output is: Motor speeds in rpm

App. b) Extending PDC Model Suitable for Hybridization Studies With Fuel Cells: Consideration of Constraints – Fuel Cell Weight and Volume Real integration of fuel cell system is subject to constraints It is proposed to consider most relevant constraints in fuel cell dimensioning of PDC Relevant constraints include: Volume of fuel cell system Dynamic and static power limitations on output side Weight of fuel cell system The next table gives an overview of suitable fuel cell types by different manufacturers Manufacturer Hydrogenics Ballard Nuvera Model HyPM HD16 Velo City - 9SSL FC Velocity - HD6 HDL - 82 Power Module Volume [m3] 0,133 0,014 0,558 0,15 Weight [kg] 92 17 < 350 230 Power [kW] 16,50 19,3 75 82 Table: Overview of hydrogen fueled fuel cells

App. b) Extending PDC Model Suitable for Hybridization Studies With Fuel Cells: Consideration of Constraints – Types of H2-Tanks An other important aspect of constraints is the type of tank There are two common solutions to store hydrogen for fuel cells: Metal hydride tanks High pressure tanks Each storage type has advantages and disadvantages Metal hydride tanks compared to high pressure tanks: Metal hydride tanks High pressure tanks - Energy density by weight + Energy density by weight - Slow flow rate + Fast flow rate - Slow charging and discharging + Fast charging and discharging - Higher temperature needed - Higher pressure needed + Reduced risk caused by high pressure - Increased risk caused by high pressure + Less space - More space + advantage / - disadvantage compared to other solution respectively

Fuel Cell and Local Control
App. c) Fuel Cell Integration in PDC: Integration of Multiple Fuel Cells – Fuel Cell, Battery and Local Control on AC Bus (Schematic Representation) AC integration of the fuel cell using a voltage source inverter (VSI) Fuel cell/battery is mere DC source Fuel cell reference power determined by instantaneous power flow through the main feeder A VSI is used to transform active power (DC) of fuel cell to apparent power for AC bus Therefore, specific control for VSI is implemented VSI Control vDC iDC vdq,in Main Feeder vdq,out idq,out vdq,Gen idq,Gen vq,VSI vd,VSI iDC* iFC,gen Fuel Cell and Local Control Fuel Reference Power Calculation PFC,ref Inductor DC Link vDC,ref Qref

App. c) Fuel Cell Integration in PDC: Integration of Multiple Fuel Cells – VSI Controller
The VSI control is implemented according to [1]: VSI control determines DC current iDC* drawn by VSI from DC link capacitor The DC link capacitor voltage vDC is used to control the reference active power Pref by PIPAC The instantaneous active power is used to control the voltage vq,VSI in q-frame by PIvq The instantaneous reactive power is used to control the voltage vd,VSI in d-frame by the PIvd PIPAC, PIvq, PIvd are PI controllers PIPAC PIvq vDC,ref vDC - + Pref P vq,VSI Q PIvd vd,VSI Qref Instantaneous Power Calculation iDC* vdq,out idq,out ÷ [1] “Integration of Alternative Sources of Energy”, Felix A. Farret & M. Godoy Simoes

App. d) Power Distribution and Control – Schematic Representation of Local Control
Local controllers of fuel cell and battery are PI controllers

App. d) Power Distribution and Control – Fuel Cell Environment
H2 tank Humidifier Fuel cell Additional control variables: O2 excess ratio H2 utilization NEW: Compressor with buck converter Li-Ion battery

App. d) Power Distribution and Control – Mode 1: Schematic Overview
What would have happened if we would not have done the project? Total current demand of AC and DC loads is only covered by the AC source. The DC sources (fuel cell and battery) do not provide any current.

What benefits does the combination of the fuel cell with a battery provide on DC bus? Total current supply of AC and DC loads is shared by the AC source, a fuel cell and a battery. The combination of fuel cell and battery improves the reaction time of the alternative source.

What benefits does the combination of the fuel cell with a battery provide on AC bus? Total current supply of AC and DC loads is shared by the AC source, a fuel cell and a battery. The combination of fuel cell and battery improves the reaction time of the alternative source.

Main strategy characteristics
App. d) Power Distribution and Control – Selected Operation Strategies and Fuel Cell Sizes for Diverse PDC Configurations Operation strategy Main strategy characteristics FC and Battery on DC Bus on AC Bus on AC and DC Bus Maximum Power Supply (PFC,max) Operate fuel cell(s) always at maximum power output 80 kW 40 kW each FC Peak Power Supply (PPeakSupply) Perform peak power shaving of generator with fuel cell(s) Percentaged Power Supply (P%) Provide always certain percentage of load by fuel cell(s) to support generator

App. d) Power Distribution and Control – Strategy 1: Maximum Power Supply (Overview)
The main objective of this strategy is to operate the available fuel cells constantly at their maximum power rate The power output will only be reduced if the total load demand of the system is below the maximum power rate of the fuel cells For the fuel cell system on the DC bus we have to consider, that the power supply cannot be higher than the demand of the two DC motors due to the unidirectional converter which connects the DC bus to the AC main feeder

App. d) Power Distribution and Control – Strategy 1: Maximum Power Supply (Simulation)
a) Motor power references b) Motor speeds Both fuel cells provide constantly 40 kW c) Power demand of loads d) Power share of different generation sources

App. d) Power Distribution and Control – Strategy 1: Maximum Power Supply
(Simulation cont´d) Fuel cell follows power demand with slower dynamics and operates then at maximum power output Battery provides fast power supply a) Fuel Cell and Battery on DC Bus b) Fuel Cell and Battery on AC Bus

𝑃 %,DC = 𝑃 F C DC ,nom 𝑃 Load,DC = 40 kW 150 kW =26.7 %
App. d) Power Distribution and Control – Strategy 3: Percentaged Power Supply (Overview) The objective of this strategy is to provide a certain percentage of the load demand by the fuel cells Thus, the AC generator is supported by the available fuel cells at each moment The DC integrated fuel cell can only supply the DC loads whereas the AC integrated fuel cell can supply all loads in the PDC system The respective percentage value for the different configurations is calculated depending on the nominal power rate PFC,nom of the alternative energy sources and the load demand PLoad In the present example, the following values are chosen for the fuel cell on DC and AC bus: 𝑃 %,DC = 𝑃 F C DC ,nom 𝑃 Load,DC = 40 kW 150 kW =26.7 % 𝑃 %,AC = 𝑃 F C AC ,nom 𝑃 Load − 𝑃 F C DC ,nom = 40 kW 160 kW =25 %

App. d) Power Distribution and Control – Strategy 3: Percentaged Power Supply (Simulation)
a) Motor power references b) Motor speeds Both fuel cells contribute continuously to power supply c) Power demand of loads d) Power share of different generation sources

App. d) Power Distribution and Control – Strategy 3: Percentaged Power Supply (Simulation cont´d)
Fuel cell continuously follows changes in power demand a) Fuel Cell and Battery on DC Bus b) Fuel Cell and Battery on AC Bus

1. a) Power Analysis of PDC for Diverse Configurations - Introduction
Analysis of diverse operation strategies revealed significant changes in power factor of AC generator This fact seems to be mainly dependent on fuel cell allocation in system Reasons therefor are now investigated by means of analysis of generated and consumder power in PDC system for diverse fuel cell locations All simulations are performed for the same test setup based on operation strategy „PFC,max“ The analyzed configurations are Basic case (only AC generator) Mode 3 (AC generator and fuel cell DC) Mode 5 (AC generator and fuel cell AC) Mode 6 (AC generator, fuel cell AC, and fuel cell DC)

1. a) Power Analysis of PDC for Diverse Configurations – Peak Load Analysis Basic Case (Only AC Generator) P (kW) 201.62 Q (kVar) 50.56 S (kVA) 207.86 P (kW) 45.48 Q (kVar) 0.32 S (kVA) P (kW) 3.49 Q (kVar) -0.72 S (kVA) 3.56 P (kW) 44.99 P (kW) 48.97 Q (kVar) -0.39 S (kVA) P (kW) 139.94 P (kW) 200.62 Q (kVar) 50.56 S (kVA) 206.9 P (kW) 192.06 Q (kVar) 15.11 S (kVA) 192.66 P (kW) 143.09 Q (kVar) 15.51 S (kVA) 143.93

1. a) Power Analysis of PDC for Diverse Configurations – Peak Load Analysis Mode 3 for Strategy PFC,max (AC Generator and Fuel Cell on DC Bus) P (kW) 113.20 Q (kVar) 15.29 S (kVA) 114.23 P (kW) 60.47 Q (kVar) 4.24 S (kVA) 60.61 P (kW) 48.97 Q (kVar) -0.39 S (kVA) P (kW) 139.92 P (kW) 80.68 P (kW) 112.27 Q (kVar) 15.29 S (kVA) 113.31 P (kW) 109.44 Q (kVar) 3.84 S (kVA) 109.51 P (kW) 80.68 P (kW)

1. a) Power Analysis of PDC for Diverse Configurations – Peak Load Analysis Mode 5 for Strategy PFC,max (AC Generator and Fuel Cell on AC Bus) P (kW) 121.53 Q (kVar) 50.53 S (kVA) 131.62 P (kW) 48.97 Q (kVar) -0.39 S (kVA) P (kW) 139.94 P (kW) 79.99 P (kW) 143.08 Q (kVar) 15.51 S (kVA) 143.92 P (kW) 200.61 Q (kVar) 50.53 S (kVA) 206.88 P (kW) 79.99 Q (kVar) S (kVA) P (kW) P (kW) 192.06 Q (kVar) 15.10 S (kVA) 192.65

1. a) Power Analysis of PDC for Diverse Configurations – Peak Load Analysis Mode 6 for Strategy PFC,max (AC Generator and Fuel Cells on AC and DC Bus) P (kW) 48.97 Q (kVar) -0.39 S (kVA) P (kW) 101.43 Q (kVar) 9.23 S (kVA) 101.85 P (kW) 116.55 Q (kVar) 30.50 S (kVA) 120.47 P (kW) 139.94 P (kW) 40 P (kW) 40.58 P (kW) 155.67 Q (kVar) 30.50 S (kVA) 158.63 P (kW) 40 Q (kVar) S (kVA) P (kW) 150.40 Q (kVar) 8.836 S (kVA) 150.66 P (kW) P (kW) 40.58 P (kW)

1. a) Power Analysis of PDC for Diverse Configurations - Evaluation
Main feeder of PDC system exhibits inductive behavior Main feeder consumes about % of all reactive power in system The AC/DC conversion for supplying the DC loads with AC generation accounts for the remaining % of reactive power consumption AC loads do not require any reactive power due to internal power factor correction Mode 3: Allocation of fuel cell on DC bus Allocation of fuel cell on DC bus allows significant reduction of reactive power in system due to Reduced power transmission over main feeder Reduced AC/DC power conversion This results in an increased power factor of the AC generator, here: 0.99 compared to in basic case

Mode 5: Allocation of fuel cell on AC bus For the allocation of the fuel cell on the AC bus, no reduction in reactive power can be observed due to No reduction in power transmission over main feeder No reduction in AC/DC power conversion But: As consequence of active power supply of fuel cell on AC bus, a reduced active power generation of AC generator can be observed However, the required reactive power is not reduced AC generator in mode 5 compared to basic case: reduced active power generation, equal reactive power generation Consequence: decreased power factor of AC generator (0.92 compared to 0.97)

Mode 6: Allocation of fuel cells on AC and DC bus For the allocation of the fuel cell on the AC and DC bus, a reduction in reactive power can be observed due to Reduction in power transmission over main feeder Reduction in AC/DC power conversion This reduction is lower than for mode 3, due to the splitting of the total fuel cell power rate into fuel cells on AC and DC bus The power generated by the fuel cell on the AC bus still needs to be transmitted over the main feeder, which causes reactive power consumption Due to the fuel cell allocation on the AC bus, a reduction of active power generation of the AC generator can be achieved As a result the power factor of the AC generator is slightly lower compared to the basic case ( to )

References [1] Felix A. Farret & M. Godoy Simoes, Integration of Alternative Sources of Energy, Wiley & Sons, 1st edition, 2006. [2] Jay T. Pukrushpan, Ana G. Stefanopoulou, Huei Peng, Control of Fuel Cell Power Systems, Springer, 1st edition, 2004. [3] J. Larminie and A. Dicks, Fuel Cell Systems Explained, Wiley & Sons , 1st edition, 2000. [4] A. Vahidi, A. Stefanopoulou, H. Peng, Current Management in a Hybrid Fuel Cell Power System: A Model-Predictive Control Approach, IEEE Transactions on Control Systems Technology, vol. 14, no. 6, pp [5] A. Vahidi, A. Stefanopoulou, H. Peng, Model predictive control for starvation prevention in a hybrid fuel cell system, in Proc. Amer. Contr. Conf., 2004, pp. 834–839. [6 ] R. F. Mann; J. C. Amphlett et al. Development and application of a generalized steady-state electrochemical model for a PEM fuel cell, Journal of Power Sources, vol. 86, pp , Mar [7] J. M. Correa; F. A. Farret; L. N. Canha; M. G. Simoes, An Electrochemical-Based Fuel-Cell Model Suitable for Electrical Engineering Automation Approach, IEEE Transactions on Industrial Electronics, vol. 51, no. 5, pp Oct

Chair of Sustainable Electric Networks and Sources of Energy TU Berlin

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