Hilbert spectrum of c is2 (t). 

Hilbert spectrum of c is2 (t). 

Source publication
Article
Full-text available
This paper describes a platform for obtaining and analyzing real-time measurements in Microgrids. A key building block in this platform is the Empirical Mode Decomposition (EMD) used to analyze the electrical voltage and current waveforms to identify the instantaneous frequency and amplitude of the monocomponents of the original signal. The method...

Citations

... Frequency is an elemental descriptor of an oscillation, and one might expect different instability modes to show distinct frequency characteristics, yet the ordinary Fourier spectra may be not enough in this context. To be specific, frequency modulation (FM) effect has been reported in both control-involved waveform distortion [2,3] and harmonic oscillation [4], indicating that the instantaneous frequency (IF) [5,6] of VSC is constantly varying, rather than discrete frequency components, as is commonly recognized. Besides, the site signals can be rather complex that both the amplitude and the frequency are vary-ing with time. ...
Conference Paper
Full-text available
With the increasing penetration of voltage-source-converter (VSC) -interfaced distributed generations(DGs) in power systems, oscillation issues have been widelyconcerned whereas the root cause and nature of the oscilla-tion is sometimes not clear in real cases. This paper focuseson the instability mode recognition (IMR) based on a com-plete data-driven approach applied to the oscillation waveswhich can be obtained from the on-site recordings. To thisend, we explore the Hilbert-Huang Transform (HHT) fordiagnosing the root cause of instability, using only raw datasuch as the current and voltage waveforms which are acces-sible by operators. Special attention is paid to distinguishbetween the sub-synchronous oscillation (SSO) and the lossof synchronization (LOS) as they are two primary instabil-ity forms of grid-tied VSC which manifest with very similarwaveforms. The pros and cons of the considered signalanalysis tools in SSO and LOS recognition are discussed andnew lines of investigations are proposed. The analysis andresults presented in this paper could shed light on futuredata-driven analysis, e.g., serving as model-free or hybridmodel database for artificial intelligence-based stabilitydiagnosis and recognition. (PDF) Instability Mode Recognition of Grid-Tied Voltage Source Converters with Nonstationary Signal Analysis. Available from: https://www.researchgate.net/publication/360005412_Instability_Mode_Recognition_of_Grid-Tied_Voltage_Source_Converters_with_Nonstationary_Signal_Analysis [accessed Apr 18 2022].
... The notion of instantaneous frequency (IF) has not been previously explored in power systems, but with the arrival of new technologies such as distributed generation, nonlinear loads and electronic devices was necessary to include that concept [22]. For many years, different methods have been used for the analysis of signals in power systems. ...
Article
Full-text available
The use of Renewable Power Generation brings new challenges related to power quality issues. Furthermore, with the changing power system nature due to the presence of new components such as power electronics in large numbers and distributed generation systems, the tools used for more than a century to analyze signals in this type of systems are no longer providing accurate information with a good resolution in time and frequency domain. To contribute with a new view of the problem, this paper presents a hybrid technique for the analysis of oscillations in Low Voltage distribution systems considering photovoltaic generation. The aim is to characterize the behavior of the system in a time-frequency domain and get the different instantaneous frequencies that appear. The results obtained with this technique are compared with three well-known methods of analysis. The validation of the methodology is carried out in a real-time digital simulator of a distributed system with Photovoltaic generation.
... The new technologies, such as non-conventional sources of renewable energies (NCSRE), Non-linear loads and electronic devices, are producing critical variations in the behavior of the transmitted wave form, therefore it is necessary to develop new methodologies for the analysis of signals which have a wide range of characteristics [1]. The results with the traditional methods are not the best because the time-frequency resolution has some problems in the detection of low frequencies and small variations in the oscillations. ...
Chapter
Full-text available
This paper describes the development and implementation of a methodology for the signal analysis in non-conventional energy systems. The proposed methodology involves the Hilbert-Huang transform supported by Empirical Mode Decomposition (EMD) to decompose one signal in its intrinsic mode function (IMF). A computational tool designed in MATLAB is used to detect oscillations and different frequencies of a non-linear and non-stationary system
... Geir Kulia et al. [34] developed a software platform to analyze the real-time electrical voltage and current waveforms for islanded microgrids. Hilbert Huang Transformation based Empirical Mode Decomposition (HHT-EMD) was used as a key building block for the above analysis. ...
Conference Paper
Full-text available
Highly fluctuating renewable sources create enormous stability issues in microgrids. Small signal and transient stability are the major classifications in microgrid stability. For small signal studies, eigenvalue analysis based on state space modeling is the most common method. Detailed dynamic modeling of the system is required for transient analysis. Since transient stability is related to larger disturbances, it creates power imbalance problem in microgrids. Therefore, calculation of power imbalance is an essential study for an islanded microgrid. This paper gives a review of the existing microgrid stability analysis methods. It also suggests a real-time stability monitoring method for islanded microgrids. A classification method along with feature extraction is presented to identify load disturbances based on the amount of load change by using frequency oscillation data. The method is validated using MATLAB simulations applied to a simple microgrid system.
... Due to the penetration of the new technologies, such as non-conventional sources of renewable energies (NCSRE) in distribution networks, the harmonic distortion of current and voltage waveform is becoming an important issue [4]. Therefore, it is necessary to develop new methodologies for the analysis of signals that have a wide content of harmonics and noise from NCSRE signals [5]. ...
... The instantaneous frequency is defined by (5). ...
... In this paper we have discussed different methods of signal analysis, in order to find the most efficient strategy in terms of frequency separation for signals with high noise content, characteristic of signals with high penetration of Non-Conventional Sources of Renewable Energies [5]. In Fig. 4, it is possible to see the IMFs obtained with EMD Masking, which do not adequately break down the signal, this is caused by the high noise of the signal; this being evident in Fig. 5. ...
Conference Paper
Full-text available
This paper aims to develop a combination method for the evaluation of power quality disturbances. First, we apply the Fast Fourier Transform, Wavelet Transform and Hilbert Huang Transform on a synthetic signal that represents typical behavior in a power system with high penetration of Renewable Energies. Then, we combine the methods to extract the best of each of these and achieve a better signal decomposition. The paper seeks to generate decision criteria on the method of analysis of signals to be used according to the application.
... Geir Kulia et al. [34] developed a software platform to analyze the real-time electrical voltage and current waveforms for islanded microgrids. Hilbert Huang Transformation based Empirical Mode Decomposition (HHT-EMD) was used as a key building block for the above analysis. ...
... The arrival of new technologies such as distributed generation, nonlinear loads and power electronic devices has increased the network complexity and caused new problems in power quality. This has called for new methodologies for analyzing signals which have different characteristics to previously studied ones [1]. One of the most common techniques used in power systems for signal analysis is the Fast Fourier Transform (FFT) with its intrinsic limitation of frequency resolution. ...
Conference Paper
Full-text available
Nonlinear and/or nonstationary properties have been observed in measurements coming from microgrids in modern power systems and biological systems. Generally, signals from these two domains are analyzed separately although they may share many features and can bene�t from the use of the same methodology. This paper explores the use of Hilbert-Huang transform (HHT) and Wavelet transform (WT) for instantaneous frequency detection in these two di�erent domains, in the search for a new adaptive algorithm that can be used to analyze signals from these domains without the need to make many a-priory adjustments. Two signals are selected for the investigation: a synthetic signal containing a time varying component and a real EEG signal obtained from The Ecole Polytechnique Federale de Lausanne. The two signals are analyzed with HHT and a discrete WT (DWT). When interpreting the results obtained with the synthetic signal, it is clear that the HHT reproduces the true components, while the DWT does not, making a meaningful interpretation of the modes more challenging. The results obtained when applying HHT to the EEG signal shows 5 modes of oscillations that appear to be well behaved Intrinsic Mode Functions (IMFs), while the results with DWT are harder to interpret in terms of modes. The DWT requires a higher level of decomposition to get closer to the results of the HHT, however multi-frequency bands may be useful depending on the application. The reconstruction of the signal from the approximation and detail coe�cients shows a good behavior and this is one application for DWT especially for removing the unwanted noise of a signal.
... This technique has proven to be effective when the signal to which the filter is applied does not contain time varying frequencies, as also reported by Tarasiuk in [4]. In the presence of time varying frequency as the ones reported in [7], [4], the classical determination of oscillating and average power components needs to be revised. The instantaneous power theory (p-q Theory, [2]) provides a foundation that is widely implemented in industry for various applications, ranging from active filters, grid tied inverter control, and any other application that requires a separation of oscillating and average power components from the total instantaneous power calculated from voltage and current measurements. ...
Conference Paper
Full-text available
The paper addresses the impact that time varying angular frequencies observed in electrical signals can have on the calculation and separation of components from the instantaneous electric power signal. Instantaneous power theories provide various methods for calculating the instantaneous power components in an electrical network. These methods are based on the basic assumption of constant fundamental frequency and harmonics that are multiple of the fundamental frequency. Recent field measurements in isolated electrical systems have however reported the existence of time varying angular frequencies or instantaneous frequencies. This new observation will affect the very foundation of the established methods for instantaneous power calculation and components separation. This paper analyses the separation of instantaneous average and oscillatory components of powers by using linear and non-linear filtering approaches in systems that exhibit time varying angular frequencies. The results of this comparison reveals the limitations of the assumption of fundamental and harmonic frequency when using linear filtering techniques in the presence of time varying angular frequencies. Non-linear filtering may offer a more robust and accurate estimation of the instantaneous values of powers and a power quality assessment that better reflects the actual system conditions.
... For many years, Fourier-based analyses were enough to study signals in power systems. The arrival of new technologies such as distributed generation, nonlinear loads and electronic devices causes problems in power quality, and this has generated the necessity to develop new methodologies for analyzing signals which have different characteristics to previously studied (Geir et al., 2016). One the most common strategies used in power systems for signal analysis has been fast Fourier transform (FFT), but a big limitation is frequency resolution; therefore, new methods for accurate and fast disturbance detection are necessary. ...
Article
Full-text available
Purpose Nowadays, an extra consumption of electric energy in the Colombian houses is generated due to electric or electronic elements plugged into the electric network. This fact produces a cost overrun in the user’s electricity bills. To reduce this extra cost, and also with a plus of reducing greenhouse gas emission, a monitoring system for the consumption of electric energy in a household will be designed and implemented to make electricity users realize how much money and energy is being wasted due to the unnecessary electric elements plugged into the network. This paper aims to show a monitoring system that allows the client to supervise the consumption of some appliances inside his/her home, remotely. It is also considered the HMI to be able to log in, choose the intervals of data and generate reports and graphics. The monitoring system is based on the integration of several technologies that are already used and implemented in houses and buildings, such as: measuring and treatment of data electronically using microcontrollers, Wi-Fi technology and dynamic graphic interface (website). Design/methodology/approach The methodology consists of several tasks, starting from documentation of the variables, instrumentation and methods for getting to the solution; the first part of the methodology focuses on selecting the electric and/or electronic elements to be monitored, so the instrumentation is able to monitor. Then, the power stage was implemented in this stage to measure signals from the sensors while sensing the electric nodes are adjusted, so does the transmission and reception. In the third stage, the design information system was implemented; this is where the received data from the sensors are stored and managed for further organization and visualization. Activities included the following: Analysis of the model of use cases: Identification of actors and actions that are involved in the system. Server selection: Study of the different server to manage the database. Design of the database: The variables, tables, fields, profiles are determined for managing the information. Connection between sensors and database: Correct data transmission and managing to the database from the sensors. Finally, the system is validated in a rural house for a month. Findings The monitoring system satisfies the main objective of making a tracing of the behavior of some appliances inside a house, showing graphically the instant current generated while connected, the cumulated energy consumed and the cost in Colombian pesos of the energy consumed so far, in real time. Research limitations/implications The monitoring system requires the correct functioning of the sensors connected to each household appliance in the home. Practical implications The main approach in the monitoring platform is the real-time measurement of energy consumption by nodes (in each appliance) that allows the user to control the money. The innovative impact of the project will be based on the use of hardware and information systems in the measurement of electrical consumption. Social implications This research has a direct impact on the economic aspects of the low-income population by allowing them to manage their energy consumption through the proposed system. Originality/value The main approach in the monitoring platform is the real-time measurement of energy consumption by nodes (in each appliance) that allows the user to control the money.
... After an extensive study of IEC Standard 61000-4-7 measuring methods, [4] states that these methods do not produce accurate results in environments with time-varying angular frequency. Keeping the aforementioned problems of nonlinearities and time-varying quantities in mind, measurements and estimation in isolated microgrids should rather be based on instantaneous amplitude and frequency rather than the usage of average values [1,5]. With improved data acquisition-and measurement tools, the supervisory control systems in isolated microgrids may perform better actions, and earlier hidden distortions may be revealed. ...
... The notions of instantaneous amplitude and frequency for general signals are not welldefined [5,37]. For a perfect sinusoid, the instantaneous frequency will be f = 1 T . ...
... The HHT, in fact a NASA designated name, combines EMD and the aforementioned HT, and is well suited for analysis of non-stationary signals. The use of HHT has proven useful for obtaining instantaneous amplitude, frequency and power in power systems and isolated microgrids [1,5,38,39]. As will be outlined in the next subsection, the EMD decomposes signals into monocomponents/IMFs. ...
Thesis
Full-text available
Several cases with time varying frequencies have been reported in isolated electrical systems such as stand-alone microgrids and marine vessel power systems. This thesis studies the use of several types of Kalman filters (KF), Hilbert-Huang Transform (HHT) and the proposed method of merging empirical mode decomposition (EMD) and KF for the purpose of tracking instantaneous values of voltage- and current waveforms in isolated microgrids with the aforementioned challenges. Both synthetic signals and real measurements from a marine vessel power system were used to validate the methods. The algorithms and methods were implemented in Matlab and Simulink. In varying degrees, the methods did all prove to be viable options for tracking of the fundamental frequency on the marine vessel. The proposed method turned out to be particularly powerful to decompose multicomponent signals consisting of several time-varying monocomponents, and track their instantaneous amplitude and frequency.