Energy Storage
Any novel energy storage concept must prove its performance across several different aspects:
- Round trip efficiency under steady-state conditions
- Transient power modulation response
- Thermal management
- Charge/discharge switching capability
- Safety and maintainability
These points apply regardless of the underlying storage principle; they are relevant for chemical
batteries, thermal storage and hydrogen systems.
We provide physical and control logic modeling to enable performance and operability assessment early in the design phase. This allows rapid and cost-effective adjustments to the concept, accelerating product development and minimizing costs to meet requirements.
Finding the right level of complexity for the model is where we excel. It involves balancing accuracy with the development and tuning effort, as well as the computational load. Our models incorporate everything relevant for the business case while excluding unnecessary elements. By achieving the right complexity balance, our models support extensive simulations covering the entire lifetime of the energy storage, establishing the complete performance envelope of the energy storage plant.
Control logic plays a crucial role in this iterative design process. We can rapidly prototype all control laws in any high- or low-level language, considering hardware aspects that constrain control possibilities, such as sensors, actuators, and other hardware and auxiliaries. Plant-level controls development is complemented by higher-level dispatching methods, which coordinate the energy storage facility with other assets of the operator.
In addition to our general expertise in energy storage, we have specific experience with:
- Thermal storage using liquid and solid mediums
- Chemical batteries such as NiMH and Li-Ion, including state-of-health (SOH) and state-ofcharge (SOC) methods
- Hydrogen-based systems, including electrolysis and fuel cells
Case studies
Goal statement:
In a thermal energy storage plant, control algorithms play a primary role in achieving:
- Best Round Trip Efficiency (RTE)
- Compliance with grid norms
- Plant operational capabilities
At the same time, such algorithms also keep plant operating parameters within the design limitations of plant components, such as turbomachinery, heat exchangers, tanks, piping, etc.
Solution provided:
A comprehensive dynamic model of the plant is built, integrating equations from different domains
(thermodynamic, electrical, etc.). The optimum trade-off in model complexity is set taking into
account PFDs and P&IDs. Such model is built to be interfaced in closed loop with the control
software. Hence a framework for developing, maintaining and versioning the model, the control
software and its tunings is put in place. Control software architecture and functionalities are then
developed with fast iterations allowed by the model-in-the-loop simulations. The simulation
iterations are made more powerful by a pre/post processing toolchain. The preprocessing allows
agile parallel execution of a high number of simulations, which combined represent the whole
spectrum of the plant operations and environmental variabilities, without relying on human input
unless strictly needed. The post-processing toolchain operates on the executed simulations to
produce automatically generated reports, optimizing the use of analysts’ time.
Control functionalities integrate the whole spectrum of traditional closed loop solutions, model
based optimum controls, estimation of non measurable variables, along with the discrete domain
solutions such as finite state machines and algebraic logics. Algorithms are tuned to comply with
requirements from all the above-mentioned sources (RTE, grid norms, operability). Compliance to
requirements is documented for all internal customers and external partners.
The control code is documented for EPC specifications where a DCS target is contemplated, while
other code fractions are used to directly generate and deploy a PLC code. Field commissioning and
performance validation follow.
Problem statement:
Wind energy is renewable and environmentally friendly. Its main weakness is that when the wind speed drops, so does the power that a wind turbine can deliver to the grid. A wind turbine manufacturer wants therefore to explore possibilities to make the power delivery of their plants immune to the natural oscillations of the wind by means of energy storage electrical devices to buffer power between the turbine and the grid. The chosen energy storage devices are supercapacitors, and Li-Ion batteries to fit into the turbine tower.
Solution provided:
We design, implement and run the dynamic models of such energy storage devices. We integrate them with the turbine model to assess the power delivery at low voltage stage. The study seeks and achieves optimum size and combination of super-capacitors and batteries to leverage their respective strengths. Upon this result, the business case is made.
Problem statement:
When estimating parameters of a mechanical system in resonance, it is typically the damping value that poses the biggest challenge, more so than the inertial and stiffness values. A wind turbine manufacturer questions its own design conditions when actual first-mode tower oscillations are suspected to be less structurally damped than was hypothesized during the development phase. The most significant source of tower oscillations damping in wind turbines are the aerodynamic
properties of the rotor themselves, meaning that the tower structural damping is even less immediately observable in the tower top acceleration data.
Solution provided:
The tower top acceleration data is preselected according to the following validity conditions:
Blades are at feather position, right after a stop manoeuvre. This allows having the minimum aerodynamic damping factor in the fore-aft motion, while the elastic energy released in the stop manoeuvre is still relevant and exciting the fore-aft motion itself.
There is observable fore-aft tower top motion, while there is no relevant energy transfer to the sideside motion where aerodynamic damping would still intervene. Side-side motion has a neglectable amplitude. The fore-aft tower top acceleration can then be used, under the conditions above, to estimate the
inertial, elastic and damping factors associated to the first mode of vibrations of the tower, according to a classic least-square-error methodology exploring the space of parameters. The identified damping value is 25% lower than the design hypothesis. Design simulations are re-run accordingly, resulting in a non-neglectable increase in tower bottom fatigue. The early integration of knowledge from field data back into the design allows for a timely deployment of further active damping control strategies, bringing plant operations back within the fatigue design envelope, thereby ensuring the certified longevity of the turbine’s structure.
Wind turbines manufacturers
The traditional wind turbine design has focused heavily on loads and power curve aspects, while considerations for grid standards and availability management have often been postponed or outright neglected. This has led to inconsistent and unstructured design changes being made too late in the turbine development process.
There are clear market reasons behind this situation. Turbines must be certified primarily for their loads, power curve, and safety aspects to be manufactured and sold. Grid standards vary over time and region, and it can be difficult to predict where commercial success will occur. Availability is addressed in contracts, but the industry lacks systematic, quantitative measures to ensure minimum levels. This leads to frustrations and losses for both operators and manufacturers, often resulting in litigation. Missed availability targets is the single most significant impact on a turbine ROI.
It is essential for wind turbine design to transition to a comprehensive system-level approach, where all product requirements are systematically addressed throughout the development process.
We specialize in designing, implementing, and validating turbine control systems to meet the whole range of requirements, including:
- Fatigue and ultimate loads
- Power curve and Annual Energy Production (AEP)
- Grid standards
- Availability and utilization of redundancy
We provide support for turbine system-level design and component selection to ensure compliance with these requirements.
Our expertise is further enhanced by:
- Wind park level control, addressing grid compliance, electrical emergency operations, global power curve optimization, and wake management
- Model-based estimation of non-measurable variables, such as wind speed estimation for load reduction or structural damping estimation
- Certification of control and safety systems, loads and power curve, compliance with grid standards
Case studies
Goal statement:
In a thermal energy storage plant, control algorithms play a primary role in achieving:
- Best Round Trip Efficiency (RTE)
- Compliance with grid norms
- Plant operational capabilities
At the same time, such algorithms also keep plant operating parameters within the design limitations of plant components, such as turbomachinery, heat exchangers, tanks, piping, etc.
Solution provided:
A comprehensive dynamic model of the plant is built, integrating equations from different domains
(thermodynamic, electrical, etc.). The optimum trade-off in model complexity is set taking into
account PFDs and P&IDs. Such model is built to be interfaced in closed loop with the control
software. Hence a framework for developing, maintaining and versioning the model, the control
software and its tunings is put in place. Control software architecture and functionalities are then
developed with fast iterations allowed by the model-in-the-loop simulations. The simulation
iterations are made more powerful by a pre/post processing toolchain. The preprocessing allows
agile parallel execution of a high number of simulations, which combined represent the whole
spectrum of the plant operations and environmental variabilities, without relying on human input
unless strictly needed. The post-processing toolchain operates on the executed simulations to
produce automatically generated reports, optimizing the use of analysts’ time.
Control functionalities integrate the whole spectrum of traditional closed loop solutions, model
based optimum controls, estimation of non measurable variables, along with the discrete domain
solutions such as finite state machines and algebraic logics. Algorithms are tuned to comply with
requirements from all the above-mentioned sources (RTE, grid norms, operability). Compliance to
requirements is documented for all internal customers and external partners.
The control code is documented for EPC specifications where a DCS target is contemplated, while
other code fractions are used to directly generate and deploy a PLC code. Field commissioning and
performance validation follow.
Problem statement:
Wind energy is renewable and environmentally friendly. Its main weakness is that when the wind speed drops, so does the power that a wind turbine can deliver to the grid. A wind turbine manufacturer wants therefore to explore possibilities to make the power delivery of their plants immune to the natural oscillations of the wind by means of energy storage electrical devices to buffer power between the turbine and the grid. The chosen energy storage devices are supercapacitors, and Li-Ion batteries to fit into the turbine tower.
Solution provided:
We design, implement and run the dynamic models of such energy storage devices. We integrate them with the turbine model to assess the power delivery at low voltage stage. The study seeks and achieves optimum size and combination of super-capacitors and batteries to leverage their respective strengths. Upon this result, the business case is made.
Problem statement:
When estimating parameters of a mechanical system in resonance, it is typically the damping value that poses the biggest challenge, more so than the inertial and stiffness values. A wind turbine manufacturer questions its own design conditions when actual first-mode tower oscillations are suspected to be less structurally damped than was hypothesized during the development phase. The most significant source of tower oscillations damping in wind turbines are the aerodynamic
properties of the rotor themselves, meaning that the tower structural damping is even less immediately observable in the tower top acceleration data.
Solution provided:
The tower top acceleration data is preselected according to the following validity conditions:
Blades are at feather position, right after a stop manoeuvre. This allows having the minimum aerodynamic damping factor in the fore-aft motion, while the elastic energy released in the stop manoeuvre is still relevant and exciting the fore-aft motion itself.
There is observable fore-aft tower top motion, while there is no relevant energy transfer to the sideside motion where aerodynamic damping would still intervene. Side-side motion has a neglectable amplitude. The fore-aft tower top acceleration can then be used, under the conditions above, to estimate the
inertial, elastic and damping factors associated to the first mode of vibrations of the tower, according to a classic least-square-error methodology exploring the space of parameters. The identified damping value is 25% lower than the design hypothesis. Design simulations are re-run accordingly, resulting in a non-neglectable increase in tower bottom fatigue. The early integration of knowledge from field data back into the design allows for a timely deployment of further active damping control strategies, bringing plant operations back within the fatigue design envelope, thereby ensuring the certified longevity of the turbine’s structure.
Problem statement:
A wind turbine manufacturer adopts an unconventional design for the pitch system, which offers clear performance and cost advantages. However, this unique design prevents the application of the most standard safety measures to prevent unwanted blade and rotor movements during operation and idle states.
Solution provided:
Roumtech leads and advises the manufacturer through an FMEA and identifies the essential electromechanical design modifications required. Protection functions are defined and integrated in accordance with ISO 13849 standards. Subsequently, full compliance with IEC 61400 standards is achieved.
Wind turbines operators
Wind turbines exhibit various forms of underperformance. This may involve the power curve falling below the manufacturer’s specification, or the availability failing to meet contractual targets. Unpredictable turbulence caused by topography, overheating generators and gearboxes, deformed stators of direct drive generators and pitch motors absorbing varying amounts of current are among the challenges encountered.
Wind turbines present unique challenges, requiring both knowledge of the specific model and broad experience to diagnose and address operational issues effectively.
We provide support by conducting root cause quantitative analysis to identify the true, deep underlying reasons for a turbine’s underperformance. This enables the implementation of corrective actions, whether through maintenance, design or retuning changes, to address the issue effectively in the long term.
Case studies
Problem statement:
When estimating parameters of a mechanical system in resonance, it is typically the damping value that poses the biggest challenge, more so than the inertial and stiffness values. A wind turbine manufacturer questions its own design conditions when actual first-mode tower oscillations are suspected to be less structurally damped than was hypothesized during the development phase. The most significant source of tower oscillations damping in wind turbines are the aerodynamic
properties of the rotor themselves, meaning that the tower structural damping is even less immediately observable in the tower top acceleration data.
Solution provided:
The tower top acceleration data is preselected according to the following validity conditions:
Blades are at feather position, right after a stop manoeuvre. This allows having the minimum aerodynamic damping factor in the fore-aft motion, while the elastic energy released in the stop manoeuvre is still relevant and exciting the fore-aft motion itself.
There is observable fore-aft tower top motion, while there is no relevant energy transfer to the sideside motion where aerodynamic damping would still intervene. Side-side motion has a neglectable amplitude. The fore-aft tower top acceleration can then be used, under the conditions above, to estimate the
inertial, elastic and damping factors associated to the first mode of vibrations of the tower, according to a classic least-square-error methodology exploring the space of parameters. The identified damping value is 25% lower than the design hypothesis. Design simulations are re-run accordingly, resulting in a non-neglectable increase in tower bottom fatigue. The early integration of knowledge from field data back into the design allows for a timely deployment of further active damping control strategies, bringing plant operations back within the fatigue design envelope, thereby ensuring the certified longevity of the turbine’s structure.
Automotive
We have direct experience in modeling various automotive systems, including:
- Tire, brake, suspension, and vehicle dynamics
- Hybrid powertrains, encompassing ICEs, batteries, inverters, and motors
Complementing the modeling, we have also developed the most relevant control laws applicable:
- ABS, EBD, TSC, ESC, ACC, LKA, EPB management
- HPCU, regenerative braking, EV mode, BMS
We have supported numerous customers in designing innovative, product-defining control solutions, guiding them from proof-of-concept to full maturity and certifiability.
All our services find application in the automotive sector. On the software engineering side, we offer software verification and validation toolchains, including:
- Model-in-the-Loop (MIL) unit tests and tunings
- MIL validation and performance quantification
- Software-in-the-Loop (SIL) code validation
- Hardware-in-the-Loop (HIL) and field tests
In terms of modelling, we are well-versed in various domains, such as:
- Friction and thermal phenomena for tires and brakes
- Elasticity and hydraulics for suspensions
- Three-dimensional rotational kinematics for chassis
- Thermodynamics for ICEs
- Electrochemical models for batteries
- Electrical models for DC motors and inverters
Case studies
Problem statement:
The state of charge of a battery is a non-measurable internal state. Measurable variables of a battery include voltage, current, temperature. Mathematically, the state of charge is the integral of the past current, both charging and discharging. However computationally a simple integration is not feasible because of the intrinsic instability of the integration process (even a slightest bias would result in a diverging error).
The state of charge is also correlated with the battery voltage. The strength of such correlation depends on the specific chemical makeup of the battery, but generally the voltage is much more affected by present and short-term past current than by long-term state of charge variations.
Solution provided:
Through lab-controlled tests, where the state of charge can be considered known, the battery hysteresis dynamics, i.e. the battery voltage response, is modelled as a dynamic function of current, temperature and state of charge. For the real time estimation on vehicles two models are then used. An inverted model returning state of charge as a function of current, voltage and temperature is used for short-term open-loop estimation.
A direct model returning voltage as a function of current, temperature and state of charge is used to compare the estimated voltage with the measured voltage. The voltage estimation error thus obtained is used for long-term, closed-loop, slow correction of the state of charge estimation. Combining the direct with the inverse model leads to a valid real-time state of charge estimation, allowing for optimum use of the hybrid power train. The estimation algorithm is validated in lab conditions and on vehicle.
Problem statement:
The customer’s control staff is distributed among different projects, each employing its own software development framework. This decentralized approach leads to duplicated efforts, with each project team starting from scratch for every new project, meeting and solving the same challenges each time. Valuable lessons learned are not systematically shared among teams. Furthermore, the existence of multiple library instances complicates matters, as teams struggle to identify and maintain optimal solutions.
Solution provided:
To address these challenges, we have introduced a comprehensive new development framework. It merges the expertise of Roumtech with the specific requirements, processes, and practices of each project team. Libraries are consolidated and centralized, enhancing knowledge sharing and eliminating redundancies. The resulting framework has been quickly adopted as the standard across all project teams, facilitating collaboration and reducing redundant work.
