Abstract:Synchrophasors are time-synchronized electrical measurements that represent both the magnitude and phase angle of the electrical sinusoids. Synchrophasors are measured by fast time-stamped devices called phasor measurement units (PMUs) to constitute the basis of realtime monitoring and control actions in the electric grid. Due to its enhanced situational awareness capabilities, many applications of PMUs are presented in the literature in the past decades. This paper presents a comprehensive summary of synchrophasor technology, its architecture, optimal placement techniques and its applications in electric power transmission and distribution systems. These applications include wide-area situational awareness and monitoring, state estimation, fault location and protective relaying, islanding detection etc. This review also covers some of the existing challenges in its implementation and its potential applications.

Abstract:With the rapid development of power electronics technology, microgrid (MG) concept has been widely accepted in the field of electrical engineering. Due to the advantages of direct current (DC) distribution systems such as reduced losses and easy integration with energy storage resources, DC MGs have drawn increasing attentions nowadays. With the increase of distributed generation, a DC MG consisting of multiple sources is a hot research topic. The challenge in such a multi-source DC MG is to provide voltage support and good power sharing performance. As the control strategy plays an important role in ensuring MG’s power quality and efficiency, a comprehensive review of the state-of-art control approaches in DC MGs is necessary. This paper provides an overview of the primary and secondary control methods under the hierarchical control architecture for DC MGs. Specifically, inner loop and droop control approaches in primary control are reviewed. Centralized, distributed, and decentralized approach based secondary control is discussed in details. Key findings and future trends are also presented at last.

Abstract:Recently, explanations of the sub-synchronous oscillation (SSO) caused by wind farms based on direct-driven wind generators (DDWGs) have been published in the literatures, in which the controller parameters of DDWGs and the system equivalent parameters play an important role. However, more than one set of parameters can cause weakly damped sub-synchronous modes. The most vulnerable and highly possible scenario is still unknown. To find scenarios that have potential oscillation risks, this paper proposes a small disturbance model of wind farms with DDWGs connected to the grid using a state-space modeling technique. Taguchi’s orthogonal array testing is introduced to generate different scenarios. Multiple scenarios with different parameter settings that may lead to SSOs are found. A probabilistic analysis method based on the Gaussian mixture model is employed to evaluate the consistency of these scenarios with the actual accidents. Electromagnetic transient simulations are performed to verify the findings.

Abstract:A small-signal model of photovoltaic (PV) generation connected to weak AC grid is established based on a detailed model of the structure and connection of a PV generation system. An eigenvalue analysis is then employed to study the stability of PV generation for different grid strengths and control parameters in a phaselocked loop (PLL) controller in the voltage source converter. The transfer function of the power control loop in the dq rotation frame is developed to reveal the influence mechanism of PLL gains on the small-signal stability of PV generation. The results can be summarized as follows: (1) oscillation phenomena at a frequency of about 5 Hz may occur when the grid strength is low; ` the tuning control parameters of the PLL have a noticeable effect on the damping characteristics of the system, and larger proportional gain can improve the system damping; (2) within a frequency range of 4-5 Hz, the PLL controller has positive feedback on the power loop of PV generation. A virtual inductance control strategy is proposed to improve the operational stability of PV generation. Finally, a simulation model of PV generation connected to weak AC grid is built in PSCAD/EMTDC and the simulation results are used to validate the analysis.

Abstract:Optimal power flow (OPF) is the fundamental mathematical model to optimize power system operations. Based on conic relaxation, Taylor series expansion and McCormick envelope, we propose three convex OPF models to improve the performance of the second-order cone alternating current OPF (SOC-ACOPF) model. The underlying idea of the proposed SOC-ACOPF models is to drop assumptions of the original SOC-ACOPF model by convex relaxation and approximation methods. A heuristic algorithm to recover feasible ACOPF solution from the relaxed solution of the proposed SOC-ACOPF models is developed. The proposed SOC-ACOPF models are examined through IEEE case studies under various load scenarios and power network congestions. The quality of solutions from the proposed SOC-ACOPF models is evaluated using MATPOWER (local optimality) and LINDOGLOBAL (global optimality). We also compare numerically the proposed SOC-ACOPF models with other two convex ACOPF models in the literature. The numerical results show robust performance of the proposed SOCACOPF models and the feasible solution recovery algorithm.

Abstract:Because of the uncertainty and randomness of wind speed, wind power has characteristics such as nonlinearity and multiple frequencies. Accurate prediction of wind power is one effective means of improving wind power integration. Because the traditional single model cannot fully characterize the fluctuating characteristics of wind power, scholars have attempted to build other prediction models based on empirical mode decomposition (EMD) or ensemble empirical mode decomposition (EEMD) to tackle this problem. However, the prediction accuracy of these models is affected by modal aliasing and illusive components. Aimed at these defects, this paper proposes a multi-frequency combination prediction model based on variational mode decomposition (VMD). We use a back propagation neural network (BPNN), autoregressive moving average (ARMA) model, and least squares support vector machine (LS-SVM) to predict high, intermediate, and low frequency components, respectively. Based on the predicted values of each component, the BPNN is applied to combine them into a final wind power prediction value. Finally, the prediction performance of the single prediction models (ARMA, BPNN, LS-SVM) and the decomposition prediction models (EMD and EEMD) are used to compare with the proposed VMD model according to the evaluation indices such as average absolute error, mean square error, and root mean square error to validate its feasibility and accuracy. The results show that the prediction accuracy of the proposed VMD model is higher.

Abstract:Electrical power cables in tidal turbine farms contribute a significant share to capital expenditure (CAPEX). As a result, the routing of electrical power cables connecting turbines to cable collector hubs must be designed so as to obtain the least cost configuration. This is referred to as a tidal cable routing problem. This problem possesses several variants depending on the number of cable collector hubs. In this paper, these variants are modeled by employing the approach of the single depot multiple traveling salesman problem (mTSP) and the multiple depot mTSP of operational research for the single and multiple cable collector variants, respectively. The developed optimization models are computationally implemented using MATLAB. In the triple cable collector cable hub variant, an optimal solution is obtained, while good-quality suboptimal solutions are obtained in the double and single cable collector hub variants. In practice, multiple cable collector hubs are expected to be employed as the multiple hub configurations tend to be more economic than the single hub configurations. This has been confirmed by this paper for an optimal tidal turbine layout obtained with OpenTidalFarm. Suggestions are presented for future research studies comprising a number of heuristics.

Abstract:With the rapid load increase in some countries such as China, power grids are becoming more strongly interconnected, and the differences between peak and valley loads are also increasing. As a result, some bulk power systems are facing high voltage limit violations during light-load periods. This paper proposes to utilize transmission switching (TS) to eliminate voltage violations. The TS problem is formed as a mixed-integer non-linear program (MINLP) with AC power flow constraints and binary variables. The proposed MINLP problem is non-deterministic polynomial hard. To efficiently solve the problem, a decomposition approach is developed. This approach decomposes the original problem into a mixed integer linear programming master problem and an AC optimal power flow slave problem that is used to check the AC feasibility. Prevention of islanding is also taken into consideration to ensure the feasibility of the TS results. The modified IEEE 39-bus and IEEE 57-bus test systems are used to demonstrate the applicability and effectiveness of the proposed method.

Abstract:Nanogrids are expected to play a significant role in managing the ever-increasing distributed renewable energy sources. If an off-grid nanogrid can supply fully-charged batteries to a battery swapping station (BSS) serving regional electric vehicles (EVs), it will help establish a structure for implementing renewable-energy-to-vehicle systems. A capacity planning problem is formulated to determine the optimal sizing of photovoltaic (PV) generation and battery-based energy storage system (BESS) in such a nanogrid. The problem is formulated based on the mixed-integer linear programming (MILP) and then solved by a robust optimization approach. Flexible uncertainty sets are employed to adjust the conservativeness of the robust optimization, and Monte Carlo simulations are carried out to compare the performance of the solutions. Case studies demonstrate the merits of the proposed applications and verify our approach.

Abstract:In recent years, urban rail systems have developed drastically. In these systems, when induction electrical machine suddenly brakes, a great package of energy is produced. This package of energy can be stored in energy storage devices such as battery, ultra-capacitor and flywheel. In this paper, an electrical topology is proposed to absorb regenerative braking energy and to store it in ultracapacitor and battery. Ultra-capacitor can to deliver the stored energy to DC grid and to charge the battery for auxiliary applications such as lighting and cooling systems. The proposed system is modeled based on large signal averaged modeling, which leads to the simplicity of calculations. The control system is based on Lyapunov stability theorem which guarantees system stability. Also, an energy management algorithm is proposed to control energy under braking and steady-state conditions. Finally, the simulation results validate the effectiveness of the proposed control and energy management system.

Abstract:Since the variation pattern of load during holidays is different than that of non-holidays, forecasting holiday load is a challenging task. With a focus on this problem, we propose a learning framework based on weighted knowledge transfer for daily peak load forecasting during holidays. First, we select source cities which can provide extra hidden knowledge to improve the forecast accuracy of the load of the target city. Then, all the instances which are from source cities and the target city will be weighted and trained by the improved weighted transfer learning algorithm which is based on the TrAdaBoost algorithm and can decrease negative transfer. We evaluate our method with the classical support vector machine method and a method based on knowledge transfer on a real data set, which includes eleven cities from Guangdong province to illustrate the performance of the method. To solve the problem of limited historical holiday load data, we transfer the data from nearby cities based on the fact that nearby cities in Guangdong province have a similar economic development level and similar load variation pattern. The results of comparative experiments show that the forecasting framework proposed by this paper outperforms these methods in terms of mean absolute percent error and mean absolute scaled error.

Abstract:Partial shading is a common problem that affects bus regulation in DC microgrids with several photovoltaic (PV) modules as energy sources, as a result of reduced solar irradiance reaching the modules. The problem can be mitigated by incorporating batteries, but if they are not included, appropriate control strategies must be used. This paper presents a new approach in a PV-based DC microgrid, which provides a high quality bus voltage regulation in islanding mode, without being affected by partial shading or problems associated with PV module connection and disconnection. The solution proposed herein ensures a proper voltage regulation without being affected by problems such as failures in PV modules or mismatch between them. Besides, it can help to prevent PV partial shade stress by disconnecting the modules affected. A further advantage of the approach is the flexibility to connect more PV modules. The advantages of this approach were verified in a 200 W prototype.

Abstract:In order to accurately identify a bearing fault on a wind turbine, a novel fault diagnosis method based on stochastic subspace identification (SSI) and multi-kernel support vector machine (MSVM) is proposed. First, the collected vibration signal of the wind turbine bearing is processed by the SSI method to extract fault feature vec_x0002_tors. Then, the MSVM is constructed based on Gauss kernel support vector machine (SVM) and polynomial kernel SVM. Finally, fault feature vectors which indicate the condition of the wind turbine bearing are inputted to the MSVM for fault pattern recognition. The results indicate that the SSI-MSVM method is effective in fault diagnosis for a wind turbine bearing and can successfully identify fault types of bearing and achieve higher diagnostic accuracy than that of K-means clustering, fuzzy means clustering and traditional SVM.

Abstract:This paper proposes a novel high-efficiency generation technique for photovoltaic (PV) system, named maximum power point capturing (MPPC) technique. This is an aperiodic perturbation MPPC technique compared to the conventional periodic perturbation maximum power point tracking technique. Firstly, under a closed-loop circuit and an open-loop circuit, the complete I–V curves and P–V curves are defined. Secondly, the proposed MPPC technique is based on the complete I–V curves and a practical model of solar PV systems. The proposed method realizes that maximum power point (MPP) is captured online, and its control strategy is designed to set a steady operating area around MPP. The duty cycle keeps constant when the operating point is within the steady operating area, i.e., aperiodic perturbation, and when the operating point is outside the steady operating area, MPPC is triggered to capture a new MPP with an updated steady operating area. Simulation results demonstrate that no oscillations exist in steady-state; dynamic performances are improved; and only two perturbations are required to capture the new MPP. Using the proposed MPPC method, low voltage ride through and high voltage ride through can be prevented.

Abstract:The doubly fed induction generator (DFIG) is major type of wind turbine generator used in grid-connected wind farms. Practical models of DFIG have been built to study the influence of wind power generation on power system dynamics. However, most existing practical models of the DFIG are based on rectangular coordinates, in which frequency variation is neglected. In this paper, a phase–amplitude (P–A) model is proposed for a DFIG based on phase and amplitude of the internal voltage. The model structure is much like that of the synchronous generator, and the rotor voltage can manipulate both the amplitude and the phase of the internal voltage. Comparisons have been made between the new P–A model of the DFIG and the synchronous generator model, as well as the asynchronous motor model. The contributions of the new P–A model of the DFIG are discussed and it is demonstrated that the proposed model has better ability in describing power system dynamic phenomena such as voltage dynamics and structural dynamics in general. Simulation results and a field test validate these contributions.

Abstract:This study aims to determine the improvement effect on the delay margin if fractional-order proportional integral (PI) controller is used in the control of a singlearea delayed load frequency control (LFC) system. The delay margin of the system with fractional-order PI control has been obtained for various fractional integral orders and the effect of them has been shown on the delay margin as a third controller parameter. Furthermore, the stability of the system that is either under or over the delay margin is examined by generalized modified Mikhailov criterion. The stability results obtained have been confirmed numerically in time domain. It is demonstrated that the proposed controller for delayed LFC system provides more flexibility on delay margin according to integer-order PI controller.

Abstract:We present a sensorless efficiency test system with energy recovery for a high-speed permanent magnet synchronous motor (PMSM). In the system, two identical high-speed PMSMs are used as the motor under test (MUT) and the load machine (LM), respectively. A new sensorless vector control (VC) method based on a hypothetical reference frame is presented to control both the MUT and the LM. Also, a regenerating unit is used to implement energy circulation to save energy. Experiments were carried out on a prototype, with a digital controller based on the TMS320F28335, to verify the adequacy of the sensorless VC method. As a result, the efficiency test system achieves the load test at the speed of 21000 r/min without any reduction equipment. During the test, the energy regenerated by the LM could be fed back to the MUT by the regenerating unit, and 81.31% electrical power was saved. In addition, with the proposed sensorless VC method, both the MUT and the LM can work at id = 0 without a position sensor.

Abstract:Due to interconnection of various renewable energies and adaptive technologies, voltage quality and frequency stability of modern power systems are becoming erratic. Superconducting magnetic energy storage (SMES), for its dynamic characteristic, is very efficient for rapid exchange of electrical power with grid during small and large disturbances to address those instabilities. In addition, SMES plays an important role in integrating renewable sources such as wind generators to power grid by controlling output power of wind plant and improving the stability of power system. Efficient application of SMES in various power system operations depends on the proper location in the power system, exact energy and power ratings and appropriate controllers. In this paper, an effort is given to explain SMES device and its controllability to mitigate the stability of power grid integrated with wind power generation systems.

Abstract:A common method to examine the current-limiting performance of saturated iron-core fault current limiter (SI-FCL) in high-voltage direct-current transmission based on voltage source converter (VSC-HVDC) systems is to solve differential equations based on the system fault transient characteristics and the equivalent inductance calculation equation. This method analyzes the fault current of the VSC-HVDC system in the time domain. However, it is computationally complex and cannot directly reflect the relationship between parameters and the currentlimiting effect of the SI-FCL. In this paper, the relationship between the magnetic flux density and magnetic field energy of the SI-FCL is analyzed. The energy exchange between the DC capacitor and the SI-FCL in the DC short circuit fault process is analyzed. From the perspective of electromagnetic energy conversion, the criterion for determining the current-limiting ability of the SI-FCL in the transient process is given based on the parameters of the SI-FCL and VSC-HVDC system. On this basis, the characteristics of the DC side fault current and the capacitor voltage when the SI-FCL has current-limiting ability are examined. Based on the parameters of the SI-FCL and VSC-HVDC system, a method for calculating the fault current peak value and capacitor voltage drop time is given. Finally, the accuracy of the analysis of the SI-FCL in the VSC-HVDC system based on the electromagnetic energy conversion mechanism is demonstrated through a case study and simulation results of the VSC-HVDC system with different SI-FCLs.

Abstract:In order to improve maximum power point tracking (MPPT) performance, a variable and adaptive perturb and observe (P&O) method with current predictive control is proposed. This is applied in three-phase threelevel neutral-point clamped (NPC) photovoltaic (PV) generation systems. To control the active power and the reactive power independently, the decoupled power control combined with a space vector modulation block is adopted for three-phase NPC inverters in PV generation systems. To balance the neutral-point voltage of the three-phase NPC grid-connected inverter, a proportional and integral control by adjusting the dwell time of small voltage vectors is used. A three-phase NPC inverter rated at 12 kVA was established. The performance of the proposed method was tested and compared with the fixed perturbation MPPT algorithm under different conditions. Experimental results confirm the feasibility and advantages of the proposed method.