Abstract:

Abstract:The renewable energy sources (RESs) dominated power grid is an envisaged infrastructure of the future power system, where the commonly used grid following (GFL) control for grid-tied converters suffers from lacking grid support capability, low stability, etc. Recently, emerging grid forming (GFM) control methods have been proposed to improve the dynamic performance and stability of grid-tied converters. This paper reviews existing GFM control methods for the grid-tied converters and compares them in terms of control structure, grid support capability, fault current limiting, and stability. Considering the impact of fault current limiting strategies, a comprehensive transient stability analysis is provided. In addition, this paper explores the typical applications of GFM converters, such as AC microgrid and offshore wind farm high-voltage direct current (OWF-HVDC) integration systems. Finally, the challenges to the GFM converters in future applications are discussed.

Abstract:The two main challenges of medium voltage direct current (MVDC) distribution network are the flexible control of power flow (PF) and fault protection. In this paper, the power flow controller (PFC) is introduced to regulate the PF and inhibit the fault current during the DC fault. The coordination strategy of series-parallel PFC (SP-PFC) and hybrid DC circuit breaker (DCCB) is proposed. By regulating the polarity and magnitude of SP-PFC output voltage during the fault, the rising speed of fault current can be suppressed so as to reduce the breaking current of hybrid DCCB. The access mode of SP-PFC to the MVDC distribution network and its topology are analyzed, and the coordination strategy between SP-PFC and hybrid DCCB is investigated. Moreover, the emergency control and bypass control strategies of SP-PFC are developed. On this basis, the mathematical model of SP-PFC in different fault stages is derived. With the equivalent model of SP-PFC, the fault current of the MVDC distribution network can be calculated accurately. A simulation model of the MVDC distribution network containing SP-PFC is established in MATLAB/Simulink. The fault current calculation result is compared with the simulation result, and the effectiveness of the proposed coordination strategy is verified.

Abstract:This paper presents a controller model of asymmetric current injection for converter-interfaced generators suitable for root-mean-square (RMS) phasor-domain, fundamental-frequency, three-phase, and dynamic simulation tools. The effectiveness of the proposed controller is assessed with simulations in test systems with high percentage of converter-interfaced generation. The simulations focus on the operation of protection relays that use negative-sequence quantities in their directional elements. This paper also presents and compares two strategies to limit reactive negative-sequence currents, and active and reactive positive-sequence currents. A tutorial test system and a regional system part of the actual Brazilian Interconnected Power System are used to assess the correctness of the proposed controller in three-phase fundamental-frequency RMS dynamic simulations.

Abstract:The grid-connected converter (GCC) is widely used as the interface between various distributed generations and the utility grid. To achieve precise power control for GCC, this paper presents a model predictive direct power control (MPDPC) with consideration of the unbalanced filter inductance and grid conditions. First, the characteristics of GCC with unbalanced filter inductance are analyzed and a modified voltage control function is derived. On this basis, to compensate for the power oscillation caused by unbalanced filter inductance, a novel power compensation method is proposed for MPDPC to eliminate the DC-side current ripple while maintaining sinusoidal grid current. Besides, to improve the control robustness against mismatched filter inductance, a filter inductance identification scheme is proposed. Through this scheme, the estimated value of filter inductance is updated in each control period and applied in the proposed MPDPC. Finally, simulation results in PSCAD/EMTDC confirm the validity of the proposed MPDPC and the filter inductance identification scheme.

Abstract:This paper presents a novel method of power quality enrichment in a grid-connected photovoltaic (PV) system using a distribution static compensator (DSTATCOM). The paper consists of two-step control processes. In the primary step, a fuzzy logic controller (FLC) is employed in the DC-DC converter to extract the peak power point from the PV panel, where the FLC produces a switching signal for the DC-DC converter. In the secondary step, a unit vector template (UVT)/adaptive linear neuron (ADALINE)-based least mean square (LMS) controller is adopted in the DC-AC converter, i.e., voltage source converter (VSC). The input to this VSC is the boosted DC voltage, which originates from the PV panel as a result of DC-DC conversion. The VSC shunted with the power grid is known as a DSTATCOM, which can maintain the power quality in the distribution system. The UVT controller generates reference source currents from the grid voltages and DC-link voltages. The ADALINE-based LMS controller calculates the online weight according to the previous weights by the sensed load current. The UVT/ADALINE-based LMS controller of a DSTATCOM performs several tasks such as maintaining the sinusoidal source current, achieving a unity power factor, and performing reactive power compensation. The reference current extracted from the UVT/ADALINE-based LMS controller is fed to the hysteresis current controller to obtain the desired switching signal for the VSC. A 100 kW solar PV system integrated into a three-phase four-wire distribution system through a four-leg VSC is designed in MATLAB/Simulink. The performances of the FLC and UVT/ADALINE-based LMS controllers are demonstrated under various irradiances as well as constant temperature and nonlinear loading conditions.

Abstract:This paper proposes a grid-tied photovoltaic (PV) inverter capable of low-voltage ride through (LVRT), reactive power support, and islanding protection. Unlike other LVRT inverters, the proposed inverter is independent of sag severity while maintaining the maximum power-point tracking (MPPT) under normal and faulty conditions. The addition of an energy storage buffer stage mitigates the DC-link voltage surge during sags. At the same time, the inverter injects the reactive power during back-to-back sags of variable depths. The control system of the inverter generates the appropriate reference signals for normal, LVRT, and anti-islanding modes while the MPPT continues running. The salient features of the proposed inverter are: ① active power injection under normal grid conditions; ② sag-depth independent LVRT with reactive power support; ③ no DC-link fluctuations; ④ continuous MPPT mode; and ⑤ simultaneous LVRT and anti-islanding support during a grid outage. The inverter demonstrates an uninterrupted operation and seamless transition between various operating modes. Simulations and the experimental prototype have been implemented to validate the efficacy of the proposed PV inverter.

Abstract:In view of the fact that the wavelet packet transform (WPT) can only weakly detect the occurrence of fault, this paper applies a fault diagnosis algorithm including wavelet packet transform and principal component analysis (PCA) to the inverter-side fault diagnosis of multi-terminal hybrid high-voltage direct current (HVDC) network, which can significantly improve the speed and accuracy of fault diagnosis. Firstly, current amplitude and current slope are used to sample the data, and the WPT is used to extract the energy spectrum of the signal. Secondly, an energy matrix is constructed, and the PCA method is used to calculate whether the squared prediction error (SPE) statistics of various signals that can reflect the degree of deviation of the measured value from the principal component model at a certain time exceed the limit to judge the occurrence of the fault. Further, its maximum value is compared to determine the fault types. Finally, based on a large number of MATLAB/Simulink simulation results, it is shown that the PCA method using the current slope as the sampled data can detect the occurrence of a ground fault with small transition resistance within 2 ms, and identify the fault types within 10 ms, without being affected by the sampling frequency.

Abstract:With the increase of converter-based renewable energy generation connected into the power grid, the interaction between renewable energy and grid impedance has introduced lots of new issues, among which the sub- and super-synchronous oscillation phenomenon makes a big concern. The linear active disturbance rejection control (LADRC) is a potential way to improve the damping characteristics of the grid-connected system, but the key factors and influencing mechanism on system stability are unknown. This paper establishes the equivalent impedance and coupling admittance models of a typical three-phase grid-connected converter. Then, the influence of the key factors such as the bandwidth of the LADRC and grid impedance on the stability and frequency coupling effect is assessed in detail. Finally, the theoretical analysis results are verified by simulations and experiments.

Abstract:As the structures of multiple branch lines (MBLs) will be widely applied in the future flexible DC distribution network, there is a urgent need for improving system reliability by tackling the frequent non-permanent pole-to-pole (P-P) fault on distribution lines. A novel fault restoration strategy based on local information is proposed to solve this issue. The strategy firstly splits a double-ended power supply network into two single-ended power supply networks through the timing difference characteristics of a hybrid direct current circuit breaker (HDCCB) entering the recloser. Then, a method based on the characteristic of the transient energy of fault current is proposed to screen the faulty branch line in each single-ended power supply network. Also, a four-terminal flexible DC distribution network with MBLs is constructed on PSCAD to demonstrate the efficacy of the proposed strategy. Various factors such as noise, fault location, and DC arc equivalent resistance are considered in the simulation model for testing. Test results prove that the proposed strategy for fault restoration is effective, and features high performance and scalability.

Abstract:To better utilize the diversity of renewable energies in the U.S., this paper proposes a cross-seam hybrid multi-terminal high-voltage direct current (MTDC) system for the integration of different types of renewable energies in the U.S. Based on a developed station-hybrid converter design, the proposed hybrid MTDC system further investigates the connection methods of renewable energies and develops novel flexible power flow control strategies for realizing uninterrupted integration of renewable energies. In addition, the frequency response control of the hybrid MTDC system is proposed by utilizing the coordination between the converters in the hybrid MTDC system. The feasibility of the hybrid MTDC system and the performance of its corresponding control strategies are conducted in the PSCAD/EMTDC simulation. The simulation results indicate that the proposed hybrid MTDC system could realize the uninterrupted integration of renewable energies and flexible power transmission to both coasts of U.S.

Abstract:This paper puts forward a new practical voltage source converter (VSC) based AC-DC converter model suitable for conducting power flow assessment of multi-terminal VSC-based high-voltage direct current (VSC-MTDC) systems. The model uses an advanced method to handle the operational limits and control modes of VSCs into the power flow formulation. The new model is incorporated into a unified framework encompassing AC and DC power grids and is solved by using the Newton-Raphson method to enable quadratically convergent iterative solutions. The use of complementarity constraints, together with the Fischer-Burmeister function, is proposed to enable the seamless incorporation of operational control modes of VSC and automatic enforcement of any converter’s operational limits that become violated during the iterative solution process. Thus, a dedicated process for checking limits is no longer required. Furthermore, all existing relationships between the VSC control laws and their operational limits are considered directly during the solution of the power flow problem. The applicability of the new model is demonstrated with numerical examples using various multi-terminal AC-DC transmission networks, one of which is a utility-sized power system.

Abstract:In order to overcome the problems of power flow control and fault current limiting in multi-terminal high voltage direct current (MTDC) grids, this paper proposes a modular multi-terminal DC power flow controller (MM-DCPFC) with fault current limiting function. The topology structure, operation principle, and equivalent circuit of MM-DCPFC are introduced, and such a structure has the advantages of modularity and scalability. The power balance mechanism is studied and a hierarchical power balance control strategy is proposed. The results show that MM-DCPFC can achieve internal power exchange, which avoids the use of external power supply. The fault characteristics of MM-DCPFC are analyzed, fault current limiting and self-protection methods are proposed, and the factors affecting the current limiting capability are studied. The simulation models are established in PLECS, and the simulation results verify the effectiveness of MM-DCPFC in power flow control, fault current limiting, and scalability. In addition, a prototype is developed to validate the function and control method of MM-DCPFC.

Abstract:Highly reliable and flexible control is required for distributed generation (DG) to efficiently connect to the grid. Smart inverters play a key role in the control and integration of DG into the power grid and provide advanced functionalities. In this paper, an energy-based single-phase voltage-source smart inverter (SPV-SSI) of 5 kVA is designed and analyzed in detail. SPV-SSI is capable of supplying the power to local load and the utility load up to the rated capacity of the inverter, injecting the power into the grid, storing the energy in lead-acid battery bank, controlling the voltage at the point of common coupling (PCC) during voltage sags or faults, and making decisions on real-time pricing information obtained from the utility grid through advanced metering. The complete design of smart inverter in dq frame, bi-directional DC-DC buck-boost converter, IEEE standard 1547 based islanding and recloser, and static synchronous compensator (STATCOM) functionalities is presented in this paper. Moreover, adaptive controllers, i.e., fuzzy proportional-integral (F-PI) controller and fuzzy-sliding mode controller (F-SMC) are designed. The performances of F-PI controller and F-SMC are superior, stable, and robust compared with those of conventionally tuned PI controllers for voltage control loop (islanded mode) and current control loop (grid-connected mode).

Abstract:Nowadays, the most notable uncertainty for an electricity utility lies in the electrical demand of end-users. Demand response (DR) has acquired considerable attention due to uncertain generation outputs from intermittent renewable energy sources and advancements of smart grid technologies. The percentage of the air-conditioner (AC) load over the total load demand in a building is usually very high. Therefore, controlling the power demand of ACs is one of significant measures for implementing DR. In this paper, the increasing development of ACs, and their impacts on power demand are firstly introduced, with an overview of possible DR programs. Then, a comprehensive review and discussion on control techniques and DR programs for ACs to manage electricity utilization in residential and commercial energy sectors are carried out. Next, comparative analysis among various programs and projects utilized in different countries for optimizing electricity consumption by ACs is presented. Finally, the conclusions along with future recommendations and challenges for optimal employment of ACs are presented in the perspective of power systems.

Abstract:We propose a dual decomposition based algorithm that solves the AC optimal power flow (ACOPF) problem in the radial distribution systems and microgrids in a collaborative and distributed manner. The proposed algorithm adopts the second-order cone program (SOCP) relaxed branch flow ACOPF model. In the proposed algorithm, bus-level agents collaboratively solve the global ACOPF problem by iteratively sharing partial variables with its 1-hop neighbors as well as carrying out local scalar computations that are derived using augmented Lagrangian and primal-dual subgradient methods. We also propose two distributed computing platforms, i.e., high-performance computing (HPC) based platform and hardware-in-the-loop (HIL) testbed, to validate and evaluate the proposed algorithm. The computation and communication performances of the proposed algorithm are quantified and analyzed on typical IEEE test systems. Experimental results indicate that the proposed algorithm can be executed on a fully distributed computing structure and yields accurate ACOPF solution. Besides, the proposed algorithm has a low communication overhead.

Abstract:This study focuses on a virtual synchronous machine (VSM) based on voltage source converters to mimic the behavior of synchronous machines (SMs) and improve the damping ratio of the power system. The VSM model is simplified according to some assumptions (neglecting the speed variation and the stator transients) to allow for the possibility of dealing with low-frequency oscillation in large-scale systems with many VSMs. Furthermore, a virtual power system stabilizer (VPSS) structure is proposed and tuned using a method based on a linearized power system dynamic model. The linear and nonlinear analyses examine the stability of two modified versions of a 16-machine power system in which, in the first case, partial classical machines are replaced by VSMs, and in the second case, all SMs are replaced by VSMs. The simulation results of the case studies validate the efficiency of the proposed control strategy.

Abstract:With the rapid development of power-electronics-enabled power systems, the new converter-based generators are deteriorating the small-signal stability of the power system. Although the numerical differentiation method has been widely used for approximately calculating the eigenvalue sensitivities, its accuracy has not been carefully investigated. Besides, the element-based formulation for computing closed-form eigenvalue sensitivities has not been used in any commercial software due to the average efficiency, complicated formulation, and error-prone characteristics. Based on the matrix calculus, this paper proposes an easily manipulated formulation of the closed-form eigenvalue sensitivities with respect to the power generation. The distinguishing feature of the formulation is that all the formulas consist of vector and matrix operations, which can be performed by developed numerical algorithms to take full advantages of architectural features of the modern computer. The tests on WSCC 3-machine 9-bus system, New England 10-machine 39-bus system, and IEEE 54-machine 118-bus system show that the accuracy of the proposed formulation is superior to the numerical differentiation method and the efficiency is also greatly improved compared to the element-based closed-form formulation. The proposed formulation will be helpful to perform a more accurate and faster stability analysis of a power grid with converter-based devices.

Abstract:In this paper, we propose an AC power flow based cascading failure model that explicitly considers external weather conditions, extreme temperatures in particular, and evaluates the impact of extreme temperature on the initiation and propagation of cascading blackouts. Based on this model, resilience analysis of the power system is performed with extreme temperatures. Specifically, the changes of load and dynamic line rating are modeled due to temperature disturbance. The probabilities for transmission line and generator outages are evaluated, and the timing for each type of events is calculated to decide the actual event sequence. It should be emphasized that the correlated events, in the advent of external temperature changes, could contribute to voltage instability. Besides, we model undervoltage load shedding and operator re-dispatch as control strategies for preventing the propagation of cascading failures. The effectiveness of the proposed model is verified by simulation results on the RTS-96 3-area system. It is found that temperature disturbances can lead to correlated load change and line/generator tripping, which will greatly increase the risk of cascading and voltage instability. Critical temperature change, critical area with temperature disturbance, the identification of most vulnerable buses, and the comparison of different control strategies are also investigated.

Abstract:Contingency analysis is an important building block in the stability and reliability analysis of power grid operations. However, due to the large number of transmission lines, in practice only a limited number of contingencies could be evaluated. This paper proposes a graph theory based N-1 contingency selection method to effectively identify the most critical contingencies, which can be used in security-constrained unit commitment (SCUC) problems to derive secure and economic operation decisions of the power grid. Specifically, the power flow transferring path identification algorithm and the vulnerability index are put forward to rank individual contingencies according to potential transmission line overloads. Effectiveness of the proposed N-1 contingency selection method is quantified by applying the corresponding SCUC solution to the full N-1 security evaluation, i.e., quantifying total post-contingency generation-load imbalance in all N-1 contingencies. Numerical results on several benchmark IEEE systems, including 5-bus, 24-bus, and 118-bus systems, show effectiveness of the proposed method. Compared with existing contingency selection methods which usually resort to full power flow calculations, the proposed method relies on power gird topology to effectively identify critical contingencies for facilitating the optimal scheduling of SCUC problems.

Abstract:This paper proposes a delay discretization based H∞ load frequency control strategy for interconnected power systems. The effect of time delay is considered in the system for the design of stabilizing controller. To improve the tolerable delay margin of the system, a two-term state feedback controller structure is used. The controller requires delayed state information as control input. In the proposed approach, the amount of delay introduced in the state of the system, i.e., artificial delay, for taking control action is assumed to be constant. The approach is based on the discretization of this delay interval. In order to define a simple Lyapunov-Krasovskii (LK) function for each of the discretized interval, a stabilization criterion is developed in such a way that a single one satisfies the requirement of all the intervals. The developed criterion is computationally simple and efficient.

Abstract:This paper proposes a fast and decentralized solution methodology for the robust operation of multi-area integrated electricity-gas systems (M-IEGSs). A deterministic reformulation is obtained for the two-stage robust model by applying the linear decision rule based electrical reserve utilization scheme as well as regulating the distributed gas storages. Two linear approximations are developed for the nonconvex Weymouth equation in the gas network to determine the gas flow directions. The penalty convex-concave procedure (P-CCP) is then adopted to refine a feasible local optimum for the nonconvex model with an acceleration strategy. The decentralized decision-making is enabled by the alternating direction multipliers method (ADMM). The convergence as well as computation performance of the overall solution procedure can be guaranteed as only convex optimizations are solved. Simulation results validate the effectiveness of the proposed methods as well as the benefits of the proposed convex programing based solution procedure.

Abstract:To improve energy efficiency and protect the environment, the integrated energy system (IES) becomes a significant direction of energy structure adjustment. This paper innovatively proposes a wavelet neural network (WNN) model optimized by the improved particle swarm optimization (IPSO) and chaos optimization algorithm (COA) for short-term load prediction of IES. The proposed model overcomes the disadvantages of the slow convergence and the tendency to fall into the local optimum in traditional WNN models. First, the Pearson correlation coefficient is employed to select the key influencing factors of load prediction. Then, the traditional particle swarm optimization (PSO) is improved by the dynamic particle inertia weight. To jump out of the local optimum, the COA is employed to search for individual optimal particles in IPSO. In the iteration, the parameters of WNN are continually optimized by IPSO-COA. Meanwhile, the feedback link is added to the proposed model, where the output error is adopted to modify the prediction results. Finally, the proposed model is employed for load prediction. The experimental simulation verifies that the proposed model significantly improves the prediction accuracy and operation efficiency compared with the artificial neural network (ANN), WNN, and PSO-WNN.

Abstract:As an important part of demand side, residential users have the characteristics of imperfect rationality and strong randomness, which are rarely considered in the existing study. Moreover, to effectively improve the energy efficiency, integrated demand response (IDR) is proposed as an effective measure to reduce the local energy supply pressure. This paper focuses on a scenario for IDR programs, in which the intelligent building aggregator (IBA) wants to encourage residential users to participate in IDR according to a proper contract price policy. To analyze how the participation degree tendency evolves over time, an evolutionary game approach is proposed considering residential users’ bounded-rationality. A symmetric evolutionary game model and an asymmetric evolutionary game model are established, and the stability of equilibrium points in the above models is proven. Simulation results show that different contract price policies will obviously influence residential users’ strategy, and affect the stable equilibrium points of the evolutionary game. The simulation results provide an effective reference for IBA to set proper and effective price incentives.

Abstract:Although wind power ramp events (WPREs) are relatively scarce, they can inevitably deteriorate the stability of power system operation and bring risks to the trading of electricity market. In this paper, an imprecise conditional probability estimation method for WPREs is proposed based on the Bayesian network (BN) theory. The method uses the maximum weight spanning tree (MWST) and greedy search (GS) to build a BN that has the highest fitting degree with the observed data. Meanwhile, an extended imprecise Dirichlet model (IDM) is developed to estimate the parameters of the BN, which quantificationally reflect the ambiguous dependencies among the random ramp event and various meteorological variables. The BN is then applied to predict the interval probability of each possible ramp state under the given meteorological conditions, which is expected to cover the target probability at a specified confidence level. The proposed method can quantify the uncertainty of the probabilistic ramp event estimation. Meanwhile, by using the extracted dependencies and Bayesian rules, the method can simplify the conditional probability estimation and perform reliable prediction even with scarce samples. Test results on a real wind farm with three-year operation data illustrate the effectiveness of the proposed method.

Abstract:Accurate wind power prediction can scientifically arrange wind power output and timely adjust power system dispatching plans. Wind power is associated with its uncertainty, multi-frequency and nonlinearity for it is susceptible to climatic factors such as temperature, air pressure and wind speed. Therefore, this paper proposes a wind power prediction model combining multi-frequency combination and feature selection. Firstly, the variational mode decomposition (VMD) is used to decompose the wind power data, and the sub-components with different fluctuation characteristics are obtained and divided into high-, intermediate-, and low-frequency components according to their fluctuation characteristics. Then, a feature set including historical data of wind power and meteorological factors is established, which chooses the feature sets of each component by using the max-relevance and min-redundancy (mRMR) feature selection method based on mutual information selected from the above set. Each component and its corresponding feature set are used as an input set for prediction afterwards. Thereafter, the high-frequency input set is predicted using back propagation neural network (BPNN), and the intermediate- and low-frequency input sets are predicted using least squares support vector machine (LS-SVM). After obtaining the prediction results of each component, BPNN is used for integration to obtain the final predicted value of wind power, and the ramping rate is verified. Finally, through the comparison, it is found that the proposed model has higher prediction accuracy.

Abstract:A partial shading condition can adversely affect the energy conversion efficiency of domestic photovoltaic (PV) systems. Connecting each PV module to a microinverter and performing module-level maximum power point tracking (MPPT) are proposed as promising solutions. In this paper, a feedback linearization-based control strategy is designed for the nonlinear system by a novel straightforward approach. The obtained nonlinear control law can independently govern each microinverter, providing module-level MPPT for PV modules without DC optimizer. Moreover, PV modules can be easily connected or disconnected due to the lug-and-play ability of the proposed controller. As a result, the proposed PV system can be easily maintained and extended even by non-expert users. Moreover, any module failure in the proposed PV system can be tolerated without impacts on the normal operation of other PV modules. The advantages of the proposed control strategy are verified by the simulation of a test PV system in MATLAB/Simulink under various partial shading conditions as well as adding or removing PV modules.

Abstract:The interactions between randomly fluctuating power outputs from photovoltaic (PV) at the DC side and background voltage distortions at the AC side could generate interharmonics in the PV grid-connected system (PVGS). There is no universal method that can reveal the transmission mechanism of interharmonics and realize accurate calculation in different scenarios where interharmonics exist in the PVGS. Therefore, extended dynamic phasors (EDPs) and EDP sequence components (EDPSCs) are employed in the interharmonic analysis of the PVGS. First, the dynamic phasors (DPs) and dynamic phasor sequence components (DPSCs) are extended into EDPs and EDPSCs by selecting a suitable fundamental frequency other than the power frequency. Second, an interharmonic analysis model of the PVGS is formulated as a set of state space equations. Third, with the decoupling characteristics of EDPSCs, generation principles and interactions among the interharmonics in the PVGS are presented by the sequence components, and its correctness is verified by simulation and experiment. The presented model can be used to accurately calculate the interharmonics generated in the PVGS both at the AC and DC sides. Because of the decoupling among the EDPSCs, the set of state space equations can effectively describe the principle.

Abstract:The power quality is becoming an extensively addressing aspect of the power system because of the sensitive operation of the smart grid, awareness of power quality, and the equipment of modern power systems. In this paper, we have conceived a new hybrid Quantum inspired particle swarm optimization and least square (QPSO-LS) framework for real-time estimation of harmonics presented in time-varying noisy power signals. The technique has strong, robust, and reliable search capability with powerful convergence properties. The proposed approach is applied to various test systems at different signal to noise ratio (SNR) levels in the presence of uniform and Gaussian noise. The results are presented in terms of precision, computation time, and convergence characteristics. The computation time decreases by 3-5 times as compared to the existing algorithms. The technique is further authenticated by estimating harmonics of real-time current or voltage waveforms, obtained from light emitting diode (LED) lamp and axial flux permanent magnet synchronous generator (AFPMSG). The results demonstrate the superiority of QPSO-LS over other methods such as LS-based genetic algorithm (GA), particle swarm optimization (PSO), bacterial foraging optimization (BFO), artificial bee colony (ABC), and biogeography based optimization with recursive LS (BBO-RLS) algorithms, in terms of providing satisfactory solutions with a significant amount of robustness and computation efficiency.

Abstract:We propose a nonlinear coordinated control of the generator excitation and the static var compensator (SVC) in order to enhance the transient stability and voltage regulation of power system by the passivation approach. SVC is installed in the middle of the transmission line of power system and consists of a single machine infinite bus (SMIB) system. The design of the proposed controller consists of two parts. On one hand, the generator excitation controller is designed based on a back-stepping controller. On the other hand, the conception of SVC control input is based on the coordinated passivation approach, which can guarantee the asymptotic stability of the closed-loop system. The simulation results show the effectiveness of the proposed controller compared with other methods, which ensures better performance than the uncoordinated control when the system is subjected to a disturbance.

Abstract:The membrane water content of the proton exchange membrane fuel cell (PEMFC) is the most important feature required for water management of the PEMFC system. Any improper management of water in the fuel cell may lead to system faults. Among various faults, flooding and drying faults are the most frequent in the PEMFC systems. This paper presents a new dynamic semi-empirical model which requires only the load current and temperature of the PEMFC system as the input while providing output voltage and membrane water content as its major outputs. Unlike other PEMFC systems, the proposed dynamic model calculates the internal partial pressure of oxygen and hydrogen rather than using special internal sensors. Moreover, the membrane water content and internal resistances of PEMFC are modelled by incorporating the load current condition and temperature of the PEMFC system. The model parameters have been extracted by using a quantum lightening search algorithm as an optimization technique, and the performance is validated with experimental data obtained from the NEXA 1.2 kW PEMFC system. To further demonstrate the capability of the model in fault detection, the variation in membrane water content has been studied via the simulation. The proposed model could be efficiently used in prognostic and diagnosis systems of PEMFC fault.