Grid Signal Research Articles

Coherency and Online Signal Selection Based Wide Area Control of Wind Integrated Power Grid

This paper introduces a novel method of designing wide area control (WAC) based on a discrete linear quadratic regulator and Kalman filtering based state-estimation that can be applied for real-time damping of interarea oscillations of wind integrated power grid. The main advantages of the proposed method are that the architecture provides online coherency grouping that properly characterizes real-time changes in the power grid and online wide-area signal selection based on residue method for proper selection of the WAC signals. The proposed architecture can, thus, accurately monitors changes in the power grid and select the appropriate control signal for more effectively damping the interarea oscillation when compared to the conventional local signal based power system stabilizers or offline based WAC designs. The architecture is tested on a wind integrated two-area system and the IEEE 39 bus system in order to show the capability of the proposed method.

Hybrid Phase Locked Loop for Controlling Master-Slave Configured Centralized Inverters in Large Solar Photovoltaic Power Plants

This paper presents a hybrid phased locked loop (HPLL) algorithm for high power master-slave configured (MSC) centralized inverters for large photovoltaic power plants. Proposed PLL technique is a combination of double second order general integral (DSOGI) PLL and enhanced PLL (EPLL) with a zero crossing detector, which enables faster synchronization of slave inverters and enables early export of power into the grid. ${{3}}{\hbox{-}}\phi $ PLL structures such as synchronous reference frame (SRF), double decoupled SRF (DDSRF), EPLL, DSOGI, and DSOGI with frequency locked loop (FLL) are discussed, and a comparative analysis with the proposed PLL technique is presented. The proposed PLL technique is superior as compared with existing PLL techniques in master-slave configurations where it can provide faster synchronization, dynamic interleaving of the hardware timers generating carrier waves for master-slave converters, and low voltage ride through (LVRT) capability. The proposed PLL technique along with the existing techniques is simulated and compared in MATLAB/SIMULINK and digitally implemented in TMS320F2812 based discrete signal controller. The performance of the proposed HPLL technique is experimentally validated with unbalanced and distorted grid signals. Experimental results of proposed HPLL show faster grid synchronization in MSC-based grid-connected inverter, LVRT capability, and dynamic interleaving of MSC inverters.

Fractional Order Chaos Synchronization for Real-Time Intelligent Diagnosis of Islanding in Solar Power Grid Systems

Many different methods have been proposed for determining islanding and most of them have drawbacks. The main issue is the difficulty of detecting islanding when the current and voltage values are of the same phase or the frequency remains within the normal range of the grid when islanding occurs. In this study, a non-autonomous Chua’s circuit was used to preprocess the grid signal after which a method based on the fractional Lorenz chaotic system and extension theory was used to analyze the preprocessed voltage signal. The capability of a chaotic system to amplify an extremely small signal was effectively utilized for the diagnosis of grid islanding. Simulation results showed that the diagnostic accuracy of the proposed method could be 100% and no other diagnostic method has offered such accuracy. Furthermore, the method proposed in this study is simple, easy to implement, and could be used as a portable system for the real-time monitoring and diagnosis of islanding in a conventional home grid system.

A Power Grid Fault Diagnosis Method based on Ensemble Decision Tree

The reason for the failure of the grid is complicated. On the one hand, because the majority of the information comes from the grid signal whose description dimension is higher; on the other hand, it is a low probability that large number or types of fault problems occur in one area. To solve this problem, this paper proposed a power grid fault diagnosis method based on ensemble decision tree (PGFD-EDT). This algorithm uses attribute selection mechanism to divide a large number of power signal attributes for multiple sets of attribute subsets, each subset is trained individually for a decision tree, and multiple decision tree models vote together to determine the grid failure. Experiments show that the PGFD-EDT algorithm has higher stability and accuracy.

Utilization of optical sensors for phasor measurement units

With the help of GPS signals for synchronization, increasingly ubiquitous phasor measurement units (PMUs) provide power grid operators unprecedented system monitoring and control opportunities. However, the performance of PMUs is limited by the inherent deficiencies in traditional transformers. To address these issues, an optical sensor is used in PMU for signal acquisition to replace the traditional transformers. This is the first time the utilization of an optical sensor in PMUs has ever been reported. The accuracy of frequency, angle, and amplitude are evaluated via experiments. The optical sensor based PMU can achieve the accuracy of 9.03×10−4Hz for frequency, 6.38×10−3rad for angle and 6.73×10−2V for amplitude with real power grid signal, demonstrating the practicability of optical sensors in future PMUs.

A Comparative Performance Evaluation of Extended AANF with Different Parameter Estimation Techniques for Renewable Energy Integration

This paper presents real time performance evaluation of three phase extension of an amplitude adaptive notch filter (AANF) for online estimation of frequency, amplitude, and sequence components of the input grid voltage signal. The performance of an extended AANF is compared with conventional synchronous reference frame-phase lock loop (SRF-PLL), enhanced phase lock loop (EPLL), and existing adaptive notch filter (ANF). Comparative analysis has been carried out based on their ability in extracting frequency and amplitude of input grid voltage signal under balanced and unbalanced voltage sag/swell, frequency shift and distorted grid condition. Three phase AANF method provides high degree of accuracy than SRF-PLL, EPLL, and ANF in extracting appropriate signal information for unbalanced and harmonically distorted grid condition. The important feature of this method is its amplitude adaptability, which improves its speed of response and accuracy when grid signal is of variable amplitude. OPAL-RT’s (OP4500) real time controller with an in-built Xilinx Kintex-7 FPGA processor is used for real time implementation. Experimental results validate fast and accurate performance of an extended AANF in extracting frequency, amplitude, and sequence components of the utility grid voltage signal, which can be further used for performance improvement of grid connected renewable energy systems, custom power devices, and flexible ac transmission systems (FACTS) devices.

Occupant-behavior driven appliance scheduling for residential buildings

Building-to-grid integration is one important step in having a smart grid. This integration will support energy efficiency, load balancing, and the incorporation of renewables. This study introduces a residential building energy management solution to control connected devices based on economic signals from the grid and occupant behavior. An air-conditioning unit, a water heater, and an electric vehicle (EV) were modeled and controlled using a traditional on/off controller and model predictive controller (MPC). The MPC is designed to minimize the total building electricity costs while maintaining occupant comfort. The MPC utilizes the building thermal mass, the EV battery storage, and the water heater’s hot water tank to shift electricity use to a period when the price is lower. This controller considers occupant behavior as a constraint in controlling these devices to maintain users’ comfort. The simulation results show a 10%–30% reduction in the electricity bill by applying the MPC in a dynamic electricity price scenario, as compared to the traditional methods of control. The proposed method of control makes buildings responsive to grid signals that provide the potential of peak shaving and ancillary services.

Smart grid challenges and signal processing based solutions - A Literature survey

Smart grid challenges and signal processing based solutions - A Literature survey

Optimal Control of Energy Storage in a Microgrid by Minimizing Conditional Value-at-Risk

This paper presents two methods for online rolling horizon optimal control of an energy storage unit in a grid-connected microgrid, subject to uncertainty in demand and electricity pricing. The proposed methods are based on the concept of rolling horizon control, where battery charge/discharge activities are determined by repeatedly solving a linear optimization problem over a moving control window. The predicted values of the microgrid net electricity demand and electricity prices over the control horizon are assumed to be uncertain. The first formulation of the control is based on the scenario-based stochastic conditional value at risk (CVaR) optimization, where the cost function includes electricity usage cost, battery operation costs, and grid signal smoothing objectives. Multivariate Gaussian distribution is used to model the variations of electricity prices and net demand power around their predicted nominal values. The second formulation of the control reduces the computations by taking a worst-case CVaR stochastic optimization approach. In this case, the uncertainty in demand is still stochastic but the problem constraints are made robust with respect to price variations in a range. Simulation results under different scenarios are presented to demonstrate the effectiveness of the proposed methods.

Synchronous Control Technology of Vacuum Circuit Breaker: An Exploratory Study

Permanent magnetic actuator, for its various advantages such as high motion reliability and time accuracy, lays the foundation for the development of the synchronous control technology of circuit breaker. This paper designs a synchronous controller for the vacuum circuit breaker of 126kV. First of all, it identifies the principles and basic requirements of the synchronous control technology, based on which the grid signals are pre-processed. Secondly, white noises are removed and interfering signals are filtered by FIR digital filter so that signal zero can be accurately detected by applying the linear interpolation method. Then, the mathematical model for closing time under different voltages and temperatures are established using BP neural network technique. Later, weight and threshold are adjusted by applying L-M algorithm to conduct basic training and test for the neural network so that the opening and closing times can be compensated. Finally, FFT (fast Fourier transform) is used to calculate signal frequency and phase. Then the synchronous controller f the design undergoes the accuracy test. The result shows that the error of synchronous control is limited to less than ±1ms.

Interpolated-DFT-Based Fast and Accurate Amplitude and Phase Estimation for the Control of Power

AbstractQuality of energy produced in renewable energy systems has to be at the high level specified by respective standards and directives. One of the most important factors affecting quality is the estimation accuracy of grid signal parameters. This paper presents a method of a very fast and accurate amplitude and phase grid signal estimation using the Fast Fourier Transform procedure and maximum decay side-lobes windows. The most important features of the method are elimination of the impact associated with the conjugate’s component on the results and its straightforward implementation. Moreover, the measurement time is very short ‒ even far less than one period of the grid signal. The influence of harmonics on the results is reduced by using a bandpass pre-filter. Even using a 40 dB FIR pre-filter for the grid signal with THD ≈ 38%, SNR ≈ 53 dB and a 20‒30% slow decay exponential drift the maximum estimation errors in a real-time DSP system for 512 samples are approximately 1% for the amplitude and approximately 8.5・10‒2rad for the phase, respectively. The errors are smaller by several orders of magnitude with using more accurate pre-filters.

A Fast Orthogonal Signal-Generation Algorithm Characterized by Noise Immunity and High Accuracy for Single-Phase Grid

Conventional orthogonal signal-generation methods for single-phase grid suffer from long response time, approximation errors, and/or noise amplification. To remedy this problem, a novel orthogonal signal-generation algorithm, which is characterized by remarkable response speed, high accuracy, noise immunity, and easy implementation, is developed in this paper. The developed algorithm can precisely calculate the orthogonal signal within about 2.5 ms when the amplitude/phase of the grid signal changes suddenly, under the premise of not significantly increasing the computational burden compared with the conventional methods. Far more important is that the high accuracy of the proposed method is independent of the system sampling frequency; hence, effectively avoiding the approximation errors in a wide range of sampling frequencies. In addition, it is shown how the noise amplification issue caused by the developed algorithm, which is nearly equal to that of the first-order differentiating method, can be effectively solved by proper time-span scaling and restricted into an acceptable range. Finally, the validity and advancement of the developed algorithm are verified by experimental results.

Polarisation properties of [SQUID]2horizontal components at the LSBB (Laboratoire Souterrain à Bas Bruit)

Polarisation properties of the geomagnetic signal are computed using the coherence matrix of horizontal components (EW and NS) of the [SQUID]2 datasets, in a relatively small bandwidth. Wavefront ellipticity, signal-to-noise ratio (snr ) and wavefront arrival angle of the magnetic quasi-monochromatic waves are determined. From the variation of ellipticity extremum position in the vicinity of 8 Hz, the temporal variation of the peak frequency is traced for the LSBB and two Northern American stations distant from the LSBB by ∼8,000 km. The spectra of the peak frequency variation display the daily, half daily and third-daily harmonics at all stations, which are characteristic of the first Schumann resonance. Ellipticity spectrograms also unveil a type of chirping local nighttime resonances, known as ionospheric Alfven resonances (IAR), observed at all stations. Thanks to the snr spectrograms, components of the signal which are local to the LSBB station are cancelled from the output, particularly the 50-Hz power grid signal which is minimised in the snr spectra.

Passive Transport Disrupts Grid Signals in the Parahippocampal Cortex

Navigation is usually thought of relative to landmarks, but neural signals representing space also use information generated by an animal's movements. These signals include grid cells, which fire at multiple locations, forming a repeating grid pattern. Grid cell generation depends upon theta rhythm, a 6-10 Hz electroencephalogram (EEG) oscillation that is modulated by the animals' movement velocity. We passively moved rats in a clear cart to eliminate motor related self-movement cues that drive moment-to-moment changes in theta rhythmicity. We found that passive movement maintained theta power and frequency at levels equivalent to low active movement velocity, spared overall head-direction (HD) cell characteristics, but abolished both velocity modulation of theta rhythmicity and grid cell firing patterns. These results indicate that self-movement motor cues are necessary for generating grid-specific firing patterns, possibly by driving velocity modulation of theta rhythmicity, which may be used as a speed signal to generate the repeating pattern of grid cells.

Dynamic Single-Phase Synchronized Phase and Frequency Estimation at the Distribution Level

This paper proposes a method for estimating synchronized phase and frequency at the distribution level under both steady-state and dynamic conditions. The discrete Fourier transform-based method is widely used for phasor and frequency estimation, thanks to its low computational burden. However, errors arise when the power system is operating at off-nominal frequency, especially under dynamic conditions such as phase modulation. Additionally, the power grid signal at the distribution level contains more noise and harmonics, which cause phase and frequency estimation errors. In this paper, a synchronized phase and frequency estimation algorithm suitable for measurement at the distribution level is proposed and tested under noise and harmonic conditions, as well as various conditions in the phasor measurement unit Standard (C37.118.1-2011 and C37.118.1a-2014), to verify its measurement accuracy at the distribution level.

Interpolated-DFT-Based Fast and Accurate Frequency Estimation for the Control of Power

The energy produced by renewable energy systems must fulfill quality requirements as defined in the respective standards and directives. Improvement of the quality could be achieved through a more accurate estimation of the frequency of the grid's signal that is used to control an inverter. This paper presents an overview of a method for spectrum interpolation and frequency estimation, and a generalized method for very accurate frequency grid estimation using the fast Fourier transform procedure coupled with maximum decay sidelobe windows. An important feature of this algorithm is the elimination of the impact associated with the conjugate's component on the estimation's outcome (i.e, the possibility of designating the frequency even if the signal's measurement time is on the order of 2.5 periods), and the implementation of the algorithm is straightforward. The results of the simulation show that the algorithm could be successfully used for a fast and accurate estimation of the grid signal frequency. The systematic frequency estimation error is approximately 5·10 -11 Hz for a 5-ms measurement window. The algorithm could be used not only for a single sinusoidal signal, but also for a multifrequency signal. This is assuming that the appropriate spectrum leakage reduction (by a time window) will be performed.

Single-Phase Grid Voltage Attributes Tracking for the Control of Grid Power Converters

Grid interfacing power converters are indispensable for renewable energy conversion schemes. Fast and precise detection of grid signal parameters is essential for effective operation and control of these converters. For such applications, synchronous reference frame phase-locked loop (SRF PLL) involving two orthogonal signals (OS) is widely deployed. For the single-phase system, this requires another signal orthogonal to the input. In this paper, single-phase SRF PLL with fixed sampling period sliding discrete Fourier transform (SDFT) filter as OS generator is proposed. Additionally, this filter is capable of rejecting dc offset and harmonics present in the grid voltage. With this arrangement, the loop filter of PLL need not be equipped with filtering capability. Therefore, PLL could be designed with larger bandwidth, which will result in better transient performance. However, SDFT output will be erroneous with asynchronous sampling, under grid frequency drift. With suitable study, relation between those errors and deviation of frequency from nominal value is established. Using this relation, error compensation at any grid frequency can be achieved. To validate the proposed method, various grid abnormalities are emulated with the aid of programmable power source and dSPACE real-time controller board. The effectiveness of the proposed scheme is demonstrated through experimental investigations.

Influence of A/D Quantization in an Interpolated DFT Based System of Power Control with A Small Delay

Abstract Fast and accurate grid signal frequency estimation is a very important issue in the control of renewable energy systems. Important factors that influence the estimation accuracy include the A/D converter parameters in the inverter control system. This paper presents the influence of the number of A/D converter bits b, the phase shift of the grid signal relative to the time window, the width of the time window relative to the grid signal period (expressed as a cycle in range (CiR) parameter) and the number of N samples obtained in this window with the A/D converter on the developed estimation method results. An increase in the number b by 8 decreases the estimation error by approximately 256 times. The largest estimation error occurs when the signal module maximum is in the time window center (for small values of CiR) or when the signal value is zero in the time window center (for large values of CiR). In practical applications, the dominant component of the frequency estimation error is the error caused by the quantization noise, and its range is from approximately 8×10-10 to 6×10-4.

The Study of Access Frequency Extraction Technology of Intelligent Substation Based on SVD

The frequency is the important operating parameters of the power system, it is also the important indicator of power quality. A large number of frequency measurement device is installed in modern power system, which can record the frequency of occurrence in the system dynamic process. Besides, in order to obtain useful signals and to improve the precision of frequency measurement of Automation System Access Frequency Information, many methods had been taken to process the signal. However, many of them may be much better, so the proposed methods called SVD (Singular Value Decomposition) is proposed in this paper. This paper focuses on discussing the basic principle, SVD theoretical study, and how to process the Automation System Access Frequency signal based on the SVD. Finally, the frequency measurement and numerical example is done to show that the proposed method can improve the grid signal accurately and prevent the impact of voltage instability.

The Design and Implementation of PV Inverter for Grid-Connected System Base on SVPWM

A PV inverter Grid-Connected system based on SVPWM is designed here, which is consisted of DC/DC circuit, TMS320F2812 , optical isolating circuit and driver circuit, three-phase inverter bridge, Grid signal acquisition circuit. Besides,program of the system is built with CCS3.3. SVPWM, MPPT, Grid-Connected, control comes true with the help of C language. Improved variable step size perturbation and observation method is applied in MPPT, which saves time of searching maximum power point and avoids oscillation generated. The experimental results show that the system can not only meet the design requirements, the Grid-Connect effect is also ideal.