| 1. |
- Balouji, Ebrahim, 1985, et al.
(författare)
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Deep Reinforcement Learning Based Grid-Forming Inverter
- 2023
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Ingår i: 2023 IEEE Industry Applications Society Annual Meeting, IAS 2023.
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Konferensbidrag (refereegranskat)abstract
- This research work introduces Deep Deterministic Policy Gradient (DDPG), a type of Reinforcement Learning (RL), for grid modeling, estimating voltage and phase angle, and control method for grid-forming inverters. The aim is to develop a grid-forming inverter that sets the voltage level and frequency of the grid and mitigates voltage dips originating from faults and frequency deviation fluctuations. Unlike conventional methods for estimating setpoints for the controller loops, we do not need several chains of estimation tools such as Fast Fourier Transform (FFT), Synchronous Reference Frame (SRF), or lowpass filters. With the DDPG, we also optimize the phase lock-loop (PLL) and accurately deliver the angle for the actuation part of the inverter to generate the given reference signal. The developed method does not need exhaustive tuning of parameters such as coefficients of PID controllers and lowpass filters. We observe that the proposed method has a faster response time than the PID-based control unit (15ms compared to 50ms) for the grid-forming inverter in the case of compensating voltage dips. We also observed that the DDPG-based grid-forming inverter is more efficient in compensating continuous voltage variations and frequency deviations than a trivial PID-based version.
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| 2. |
- Holmberg, Carl, 1992, et al.
(författare)
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Accurate and Efficient Crosstalk Analysis by Full-wave Computations and System Identification
- 2020
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Ingår i: Proceedings of the 2020 International Symposium on Electromagnetic Compatibility - EMC EUROPE, EMC EUROPE 2020.
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Konferensbidrag (refereegranskat)abstract
- We present a system-identification procedure applied to a crosstalk problem, which can be accurately analyzed by an in-house full-wave solver based on the method of moments (MoM). Given a relatively few frequency-samples of the crosstalk current, we demonstrate that it is feasible to estimate a reduced-order model of the continuous frequency dependence, where the frequency band of interest corresponds to an electrical size of the system that ranges roughly from 0.005 to 2.7 wavelengths. The estimated low-order model of the frequency response takes the form of a Padé approximant and it yields an accurate representation when compared to the reference frequency-response, as it is computed directly by the MoM solver. In addition, the low-order model can be evaluated at an extremely low computational cost and it provides useful information such as resonance frequencies and their quality factors. For the system analysis of a real-world device, the low-order model can serve as a computationally powerful and accurate representation of the electromagnetic response for a subsystem that features full-wave phenomena that otherwise could be too challenging to describe at a system level.
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| 3. |
- Klintberg, Jacob, 1994, et al.
(författare)
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Mitigation of Ground Clutter in Airborne Bistatic Radar Systems
- 2020
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Ingår i: Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop. - 2151-870X. ; 2020-June
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Konferensbidrag (refereegranskat)abstract
- Space-Time Adaptive Processing is a commonly used technique to mitigate ground clutter reflections from an airborne radar system. It estimates a covariance matrix based on spatial and temporal information, and the estimate is thereafter used to suppress the ground clutter. In a side-looking monostatic radar system, the estimate is rather straight forward based on radar observations. However, in this paper, we consider bistatic systems where the power of adaptivity is limited due to nonstationarity of the ground clutter reflections over the range dimension. To overcome this, scenario dependent transformations are commonly used when forming the sample covariance matrix. In this contribution we instead investigate a detector where the clutter covariance matrix is determined from the geometry of the bistatic scenario. Using a Monte-Carlo simulation, we investigate how sensitive the detector is to errors in the assumed geometry, and compare this with state-of-the-art adaptive methods. The results indicates that a good clutter rejection is obtained for errors of order 103 m for assumed transmitter position and 100km/h for assumed transmitter velocity.
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| 4. |
- Klintberg, Jacob, 1994, et al.
(författare)
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Scenario Tracking for Airborne Bistatic Radar Systems
- 2024
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Ingår i: IEEE Transactions on Aerospace and Electronic Systems. - 1557-9603 .- 0018-9251. ; In Press
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Tidskriftsartikel (refereegranskat)abstract
- An effective space-time adaptive processing implementation provides an accurate estimate of the corresponding space-time covariance matrix of the distribution of the interference and the noise. Such an estimate is commonly calculated from secondary observations associated with the most recent coherent processing interval. In this paper, we derive the covariance matrix using a parametric model which depends on a few parameters describing the state of the radar scenario. With this formulation, it is sufficient to estimate the scenario parameters to obtain the covariance matrix estimate. The scenario parameters represents the position and velocities of the platforms comprising the airborne bistatic configuration. Moreover, the framework of radar scenarios enables information from previously considered coherent processing intervals to contribute to the covariance matrix estimate. Consequently, as the scenario parameters denotes motion characteristics of a platform, the scenario parameters can be tracked over time by assuming a motion model. Thus, the estimator of this paper uses a combination of the likelihood density of the most recent set of radar observations, together with a dynamical model which enables the propagation of the scenario parameters dynamics through time. Hence, the density of the likelihood and the prior density from the propagation of previous scenario parameter estimates through time is combined to calculate a maximum a posteriori estimate of the scenario parameters. In numerical simulations, the maximum a posteriori estimate is compared with the corresponding scenario parameter estimate considering only a maximum likelihood estimate. The numerical simulations indicates that the maximum a posteriori estimate obtains a scenario parameter estimate which is closer to the true scenario parameters. Moreover, the maximum a posteriori estimate is more robust towards a low number of secondary data comprising the likelihood density compared to the maximum likelihood estimate.
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| 5. |
- Mazidi, Mohammadreza, 1987, et al.
(författare)
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A Pure Data-Driven Method for Online Inertia Estimation in Power Systems Using Local Rational Model Approach
- 2022
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Ingår i: 2022 IEEE International Conference on Environment and Electrical Engineering and 2022 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2022. - 1939-9367 .- 0093-9994.
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Konferensbidrag (refereegranskat)abstract
- This paper proposes a novel data-driven method for estimating inertia constants of synchronous generators (SGs) connected to the power system. The proposed method only requires ambient data which can be continuously measured by PMUs in the normal operation of the system. A non-parametric technique based on the local rational model (LRM) is used to identify frequency response functions (FRFs) of SGs from the measured ambient data. Then, the inertia constants of SGs are estimated from FRFs. Numerical studies on the WSCC 9-bus system demonstrate that the proposed method can accurately estimate the inertia constants of SGs in short time windows, which enables tracking total system inertia. Likewise, the robustness of the proposed method against measurement noises is confirmed.
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| 6. |
- Razi, Maryam, 1978, et al.
(författare)
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Design and comparative analyses of optimal feedback controllers for hybrid electric vehicles
- 2021
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Ingår i: IEEE Transactions on Vehicular Technology. - 0018-9545 .- 1939-9359. ; 70:4, s. 2979-2993
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents an adaptive equivalent consumption minimization strategy (ECMS) and a linear quadratic tracking (LQT) method for optimal power-split control of a combustion engine and an electric machine in a hybrid electric vehicle (HEV). The objective is to deliver demanded torque and minimize fuel consumption and usage of service brakes, subject to constraints on actuator limits and battery state of charge (SOC). First, we derive a function for calculating maximum deliverable torque that is as close as possible to demanded torque and then reduce the number of control inputs to one while minimizing the usage of service brakes in the case of negative demanded torque. Next, we propose modeling SOC constraints by tangent or logarithm functions that provide an interior point to both the ECMS and the LQT. Then, we show that the resulting objective functions are convex, and we propose sub-optimal analytic solutions for the optimization problem by applying their second order approximation about a given reference. We also consider robustness of the controllers to measurement noise using a simple model of noise. Simulation results of the two controllers are compared, and their effectiveness is discussed.
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| 7. |
- WINGES, JOHAN, 1987, et al.
(författare)
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System Identification and Tuning of Wireless Power Transfer Systems with Multiple Magnetically Coupled Resonators
- 2018
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Ingår i: Transactions on Environment and Electrical Engineering. - : EEEIC International Publishing. - 2450-5730. ; 2:2, s. 86-92
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Tidskriftsartikel (refereegranskat)abstract
- We present a procedure for system identification and tuning of a wireless power transfer (WPT) system with four magnetically coupled resonators, where each resonator consists of a coil and a capacitor bank. The system-identification procedure involves three main steps: 1) individual measurement of the capacitor banks in the system; 2) measurement of the frequency-dependent two-port impedance matrix of the magnetically coupled resonators; and 3) determining the inductance of all coils and their corresponding coupling coefficients using a Bayesian approach. The Bayesian approach involves solving an optimization problem where we minimize the mismatch between the measured and simulated impedance matrix together with a penalization term that incorporates information from a direct measurement procedure of the inductance and losses of the coils. This identification procedure yields an accurate system model which we use to tune the four capacitance values to recover high system-performance and account for, e.g., manufacturing tolerances and coil displacement. For a prototype WPT system, we achieve 3.3 kW power transfer with 91 % system efficiency over an air-gap distance of approximately 20 cm.
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| 8. |
- McKelvey, Tomas, 1966
(författare)
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Auto-calibration of Uniform Linear Array Antennas
- 2019
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Ingår i: European Signal Processing Conference. - 2219-5491. ; 2019-September
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Konferensbidrag (refereegranskat)abstract
- Calibration is instrumental to realize the full performance of a measurement system. In this contribution we consider the calibration of a uniformly linear array antenna where we assume each antenna element has an unknown complex gain. We present an algorithm which can be used to calibrate the array without full knowledge of the environment. Particularly, if the number of signal sources are known we show that we can determine the individual unknown antenna gains up to an ambiguity parametrized by a single complex scalar. If the ratio of the complex gains between two consecutive elements is also known, this ambiguity is resolved. The method is based on determining the antenna calibration parameters such that the Hankel matrix of the array snapshots has a given rank. A numerical example illustrates the performance of the method. The numerical results suggest that the method is consistent in SNR.
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| 9. |
- Kylin, Carl, 1996, et al.
(författare)
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Over-The-Air Identification of Coupled Nonlinear Distortion in a MIMO Radar
- 2022
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Ingår i: Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop. - 2151-870X. ; 2022-June, s. 121-125
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Konferensbidrag (refereegranskat)abstract
- Compensation for nonlinear distortion caused by power amplifiers being driven into compression is a field that has been extensively explored by a number of authors. More complex models describing the coupled nonlinear distortion that can occur in an active antenna array also exist. To identify these models most authors assume that the output of each power amplifier can be measured directly. For a system with many antennas over-the-air identification might be favorable. The problem of identifying a system describing the joint effects of coupled nonlinear distortion over-the-air has been solved by other authors assuming model or setup simplifications. To tackle the problem with a more accurate model, an algorithm for identifying parameters of a Volterra series model describing coupled non-linear distortion in a digital radar is explored and illustrated with simulated data.
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| 10. |
- Mazidi, Mohammadreza, 1987, et al.
(författare)
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A Pure Data-Driven Method for Online Inertia Estimation in Power Systems Using Local Rational Model Approach
- 2023
-
Ingår i: IEEE Transactions on Industry Applications. - 0093-9994 .- 1939-9367. ; 59:5, s. 5506-5516
-
Tidskriftsartikel (refereegranskat)abstract
- This paper presents an online data-driven method to estimate the inertia constant of synchronous generators (SGs) and the virtual inertia of converter-based resources (CBRs), which enables time-dependent inertia tracking in the normal operation of a power system. The proposed method is based on continuous monitoring of frequency response functions (FRFs) of SGs and CBRs, which are identified by ambient wide-area measurements of phasor measurement units (PMUs). To identify FRFs, a novel non-parametric approach, namely the local rational model (LRM), is used which does not require correct model order selection. LRM approach has a low computational burden and requires a short window of data, both of which are essential for estimating time-dependent inertia using ambient data. The applicability of the proposed method is evaluated in the IEEE 39-bus system and an actual system. The results demonstrate the accuracy, robustness to noise, and effectiveness of the proposed method in estimating the time-dependent inertia of power systems.
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