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A hybrid algorithm for parameter estimation (HAPE) for dynamic constant power loads

Published in:
IEEE Trans. Ind. Electron., Vol. 68, No. 11, November 2021, pp. 10326-35.
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Summary

Low-inertia microgrids may easily have a single load which can make up most of the total load, thereby greatly affecting stability and power quality. Instead of a static load model, a dynamic constant power load (DCPL) model is considered here. Next, a hybrid algorithm for parameter estimation (HAPE) is introduced. In order to verify the load model and the HAPE, two experiments are conducted with different DCPLs using a Power-Hardwarein-the-Loop (PHiL) testbed. The PHiL testbed consists of a real-time computer working with a programmable power amplifier in order to perturb the input voltage's amplitude and frequency. Each connected DCPL in two separate experiments serves as the device under test (DUT). Using the captured experimental data as a reference, the HAPE is then invoked. The resulting parameter estimates are used to define simulation models. Both resulting DCPL models are simulated to produce waveforms that closely resemble experimental waveforms. Finally, the HAPE's resulting parameter estimates are presented, and the performance of the HAPE is discussed.
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Summary

Low-inertia microgrids may easily have a single load which can make up most of the total load, thereby greatly affecting stability and power quality. Instead of a static load model, a dynamic constant power load (DCPL) model is considered here. Next, a hybrid algorithm for parameter estimation (HAPE) is introduced...

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Toward distributed control for reconfigurable robust microgrids

Published in:
2020 IEEE Energy Conversion Congress and Exposition, ECCE, 11-15 October 2020.
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Summary

Microgrids have been seen as a good solution to providing power to forward-deployed military forces. However, compatibility, robustness and stability of current solutions are often questionable. To overcome some of these problems, we first propose a theoretically-sound modeling method which defines common microgrid component interfaces using power and rate of change of power. Using this modeling approach, we propose a multi-layered distributed control: the higher control layer participates in dynamic power management that ensures acceptable voltage, while the lower layer stabilizes frequency by regulating the dynamics to the power determined by the higher layer. Numerical and hardware tests are conducted to evaluate the effectiveness of the proposed control.
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Summary

Microgrids have been seen as a good solution to providing power to forward-deployed military forces. However, compatibility, robustness and stability of current solutions are often questionable. To overcome some of these problems, we first propose a theoretically-sound modeling method which defines common microgrid component interfaces using power and rate of...

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A workflow for non-linear load parameter estimation using a power-hardware-in-the-loop experimental testbed

Published in:
2020 IEEE Applied Power Electronics Conf. and Expo., APEC, 15-19 March 2020.

Summary

Low-inertia microgrids may easily have a single load which can make up most of the total load, thereby greatly affecting stability and power quality. Instead of static load models, dynamic load models are presented here for constant current loads (CILs) and constant power loads (CPLs). Next, a flexible Power-Hardware-in-the-Loop (PHiL) testbed is employed for the experiments in this work. The PHiL testbed consists of a real-time computer working with a power amplifier in order to perturb its voltage and frequency. A connected load serves as the device under test (DUT). Using the captured experimental data as a reference, a parameter estimation algorithm is then implemented. The resulting parameter estimates are used to define simulation models. Both the CIL and CPL dynamic models are simulated to produce waveforms that closely resemble experimental waveforms. The algorithm, referred to as an enhanced monte carlo algorithm (EMCA), is explained in this work. Finally, the EMCA's resulting parameter estimates are presented.
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Summary

Low-inertia microgrids may easily have a single load which can make up most of the total load, thereby greatly affecting stability and power quality. Instead of static load models, dynamic load models are presented here for constant current loads (CILs) and constant power loads (CPLs). Next, a flexible Power-Hardware-in-the-Loop (PHiL)...

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High performance computing techniques with power systems simulations

Published in:
IEEE High Performance Extreme Computing Conf., HPEC, 25-27 September 2018.
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Summary

Small electrical networks (i.e., microgrids) and machine models (synchronous generators, induction motors) can be simulated fairly easily, on sequential processes. However, running a large simulation on a single process becomes infeasible because of complexity and timing issues. Scalability becomes an increasingly important issue for larger simulations, and the platform for running such large simulations, like the MIT Supercloud, becomes more important. The distributed computing network used to simulate an electrical network as the physical system presents new challenges, however. Different simulation models, different time steps, and different computation times for each process in the distributed computing network introduce new challenges not present with typical problems that are addressed with high performance computing techniques. A distributed computing network is established for some example electrical networks, and then adjustments are made in the parallel simulation set-up to alleviate the new kinds of challenges that come with modeling and simulating a physical system as diverse as an electrical network. Also, methods are shown to simulate the same electrical network in hundreds of milliseconds, as opposed to several seconds--a dramatic speedup once the simulation is parallelized.
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Summary

Small electrical networks (i.e., microgrids) and machine models (synchronous generators, induction motors) can be simulated fairly easily, on sequential processes. However, running a large simulation on a single process becomes infeasible because of complexity and timing issues. Scalability becomes an increasingly important issue for larger simulations, and the platform for...

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