Interfacing PowerFactory: Co-simulation, Real-Time Simulation and Controller Hardware-in-the-Loop Applications

Stifter, Matthias; Andrén, Filip; Schwalbe, Roman; Tremmel, Werner

doi:10.1007/978-3-319-12958-7_15

Cited by 11 publications

(8 citation statements)

References 12 publications

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“…Besides the python interface, there are several other ways to solve this task. Other possibilities such as OPC UA are discussed in detail in [54]. The solution was chosen because the whole functionality of PowerFactory's internal scripting language (DPL) can also be addressed using the Python interface.…”

Section: Analysis Of the Cycle Time For The Examined Setupsmentioning

confidence: 99%

Comparison of Power Hardware-in-the-Loop Approaches for the Testing of Smart Grid Controls

et al. 2018

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The fundamental changes in the energy sector, due to the rise of renewable energy resources and the possibilities of the digitalisation process, result in the demand for new methodologies for testing Smart Grid concepts and control strategies. Using the Power Hardware-in-the-Loop (PHIL) methodology is one of the key elements for such evaluations. PHIL and other in-the-loop concepts cannot be considered as plug’n’play and, for a wider adoption, the obstacles have to be reduced. This paper presents the comparison of two different setups for the evaluation of components and systems focused on undisturbed operational conditions. The first setup is a conventional PHIL setup and the second is a simplified setup based on a quasi-dynamic PHIL (QDPHIL) approach which involves fast and continuously steady state load flow calculations. A case study which analyses a simple superimposed voltage control algorithm gives an example for the actual usage of the quasi-dynamic setup. Furthermore, this article also provides a comparison and discussion of the achieved results with the two setups and it concludes with an outlook about further research.

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Section: Analysis Of the Cycle Time For The Examined Setupsmentioning

confidence: 99%

Comparison of Power Hardware-in-the-Loop Approaches for the Testing of Smart Grid Controls

et al. 2018

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“…The Matlab control functions are WS estimation using CEEMDAN-ELM, and HMPPT using a fuzzy controller. The PowerFactory control functions are modelling and control of complete WF and power system grid [38][39][40]. The complexity of the integrated intelligent model impacts a significant challenge to the balance among the model accuracy and the system complexity when Matlab is integrated with PowerFactory [21,41].…”

Section: Full Wf System Descriptionsmentioning

confidence: 99%

Integrated optimal active and reactive power control scheme for grid connected permanent magnet synchronous generator wind turbines

Mahmoud

Zhang²,

2018

IET Electric Power Applications

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This research presents a novel approach for optimal active and reactive power control using permanent magnet synchronous generator with fully rated converter (PMSG-FRC). The power output variations and wind energy intermittent performance create significant challenges for power system integration, operation, and control. A fast and reliable sensorless optimal wind speed (WS) control system-based extreme learning machines and complete ensemble empirical mode decomposition with adaptive noise is developed. Also, an approximate entropy-based complexity measure is used for online WS estimation. The fuzzy controller system is used for calculating the optimal wind turbine (WT) speed, power, and torque, and then adjusts WT by the optimal speed value. Moreover, the wind farm (WF) active and reactive power controller is utilised for obtaining the active and reactive power reference values for every region/feeder. The system is applied and integrated to power system grid by using IEEE standard models, and the speed of WT is adjusted by the required active power level and the estimated WS value to increase the maximum power capture from WF. The simulations results using different cases studies and power system voltage levels have confirmed the validity and accuracy of the proposed control algorithms for practical applications and demonstrated excellent performance for power system integration.

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“…Due to the fact that this API is not usable for more than two subscriber or multiple threads at the same time, the simulation and the PowerFactory Client are combined into one multithreaded LabLink client which uses the PowerFactory API in a single threaded manner. • PowerFactory Client: PowerFactory supports several interfaces [20]. The Python API is an ideal fit for the LabLink environment Python bindings.…”

Section: B Prototypical Realizationmentioning

confidence: 99%

Hardware-in-the-Loop Co-Simulation Based Validation of Power System Control Applications

Otte¹,

Leimgruber²,

Bründlinger³

et al. 2018

2018 IEEE 27th International Symposium on Industrial Electronics (ISIE)

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Renewables are key enablers for the realization of a sustainable energy supply but grid operators and energy utilities have to mange their intermittent behavior and limited storage capabilities by ensuring the security of supply and power quality. Advanced control approaches, automation concepts, and communication technologies have the potential to address these challenges by providing new intelligent solutions and products. However, the validation of certain aspects of such smart grid systems, especially advanced control and automation concepts is still a challenge. The main aim of this work therefore is to introduce a hardware-in-the-loop co-simulation-based validation framework which allows the simulation of large-scale power networks and control solutions together with real-world components. The application of this concept to a selected voltage control example shows its applicability.

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Interfacing PowerFactory: Co-simulation, Real-Time Simulation and Controller Hardware-in-the-Loop Applications

Cited by 11 publications

References 12 publications

Comparison of Power Hardware-in-the-Loop Approaches for the Testing of Smart Grid Controls

Comparison of Power Hardware-in-the-Loop Approaches for the Testing of Smart Grid Controls

Integrated optimal active and reactive power control scheme for grid connected permanent magnet synchronous generator wind turbines

Hardware-in-the-Loop Co-Simulation Based Validation of Power System Control Applications

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