84 resultados para power system reliability


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Microgrid (MG) power system plays an important role to fulfill reliable and secure energy supply to critical loads of communities as well as for communities in remote area. Distributed Generation (DG) sources integrated in a MG provides numerous benefits, at the same time leads to power quality issues in the MG power distribution network. Power Quality (PQ) issue arises due to the integration of an intermittent nature of Renewable Energy (RE) sources with advanced Power Electronics (PE) converter technology. Also, presence of non-linear and unbalancing loads in MG seems to affect PQ of the energy supply in power distribution network. In this paper, PQ impacts like; power variation, voltage variation, Total Harmonic Distortion (THD), and Unbalance voltage level have been analysed in Low Voltage (LV) distribution network of typical MG power system model. In this study, development of MG model and PQ impact analysis through simulation has been done in PSS-Sincal software environment. Analysis results from the study can be used as a guideline for developing a real and independent MG power system with improved PQ conditions.

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Integration of solar PV and wind in to the distribution network is one of the most promising challenges of the modern power system networks to meet the growing demand of energy. Analysis of the effects of solar and wind intermittencies in the network are vital to maintain the power quality. Keeping this in view, this research paper focuses on impact analysis study of a typical power network with hybrid generation: solar PV and wind integration to quantify the level of impacts like power variation and voltage variation in the network through load flow analysis. Initially, a typical network model is developed using PSS-SINCAL and load profile analysis has been carried out based on the typical daily load profile and wind/solar profile to verify the power and voltage variations extensively in the network considering different scenarios. Results of this research analysis can be used as guidelines for utility grid to provide regulated and improved quality of energy supply by implementing appropriate planning of generation reserve and other control measures in the network

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Microgrid (MG) integrated with Distributed Generation (DG) provides several benefits like reliable, secure, and high efficient of energy supply, while minimizing power loss, deferring expansion of power distribution infrastructures, and reduced carbon emission of energy supply etc. to the communities. Despite of the several benefits, there are several challenges existing due to the integration of different characteristics and technology of DG sources in MG network. Power Quality (PQ) issue is one of the main technical challenges in MG power system. In order to provide improved PQ of energy supply, it is necessary to analyse and quantify the PQ level in MG network. This paper investigates the detail of PQ impacts in a real MG network carried out through an experimental analysis. Voltage and frequency variations/deviations are analysed in both on-grid and off-grid mode of MG operation at varying generation and varying load conditions. Similarly un-balance voltage and current level in neutral are estimated at unbalanced PV generation and uneven load distribution in MG network. Also current and voltage THD are estimated at different PV power level. Finally the results obtained from the analysis are compared to that of Australian network standard level.

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This paper proposes a new approach to design a robust adaptive backstepping excitation controller for multimachine power systems in order to reject external disturbances. The parameters which significantly affect the stability of power systems (also called stability sensitive parameters) are considered as unknown and the external disturbances are incorporated into the power system model. The proposed excitation controller is designed in such a way that it is adaptive to the unknown parameters and robust to external disturbances. The stability sensitive parameters are estimated through the adaptation laws and the convergences of these adaptation laws are obtained through the negative semi-definiteness of control Lyapunov functions (CLFs). The proposed controller not only provides robustness property against external disturbances but also overcomes the over-parameterization problem of stability sensitive parameters which usually appears in some conventional adaptive methods. Finally, the performance of the proposed controller is tested on a two-area four machine 11-bus power system by considering external disturbances under different scenarios and is compared to that of an existing nonlinear adaptive backstepping controller. Simulation results illustrate the robustness of the proposed controller over an existing one in terms of rejecting external disturbances.

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This paper presents a new approach to design excitation controller for power systems to enhance small-signal stability. Partial feedback linearization scheme is used to design the controller for a linearized power system model which transforms a part of this model into a new system through linear coordinate transformation. In this paper, the excitation control law as a function of state variables is determined from the dynamics of the partly transformed new system provided that the controller stabilizes the remaining dynamics of the system which are not transformed through feedback linearization. The stability of the remaining dynamics is also discussed in this paper. Since the proposed control scheme uses state variables as feedback, it is analogous to a linear quadratic regulator (LQR) based excitation controller. Therefore, the performance of the proposed scheme is evaluated on a single machine infinite bus (SMIB) system and compared to that of an LQR controller.

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Wind energy system integration can lead to adverse effects on modern electric grid so it is imperative toassess their dynamic performance before actual plant startup. Transmission system operators all over theworld stress the need for a proper wind turbine generator model for dynamic performance as well asancillary service assessments. Due to the bulk power system assessment requirements, developmentof suitable generic modeling has gained high priority. Generic modeling of type 4 full converter wind turbinegenerator system for application in frequency ancillary service investigations under varying windspeed and varying reference power has been presented in this study. Prevalent generic model, manufacturerspecific proprietary generic model along with detailed wind turbine model with synchronous generatoris also provided to highlight various modelling framework difference. Descriptions of individualsub models of proposed generic model are presented in detail and performance results are comparedand validated with GE’s proprietary generic model and detailed WTG model by means of simulationsin the MATLAB Power System Block set.

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This paper presents an improved stability criterion for load frequency control (LFC) of time-delay power systems including AC/HVDC transmission links and EVs. By employing a novel refined Jensen-based inequality, an improved stability condition is derived in terms of feasible linear matrix inequalities (LMIs) which allow us to compute the maximal upper bounds of time-delay ensuring stability of the LFC scheme equipped with an embedded controller. Cases studies here are implemented for LFC scheme of a two-area power system, which is interconnected by parallel (AC/HVDC) links, with embedded proportional integral (PI) controller for discharged EVs. The relationships between the parameters of PI controller, supplementary control of HVDC links and delay margins of the LFC scheme are also discussed. As a consequence of facts, the results of delay margins can be used as a guideline to tune PI controller and set-up parameters for HVDC control.

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This paper presents a H∞ dynamic output feedback control scheme for load frequency control (LFC) of interconnected power systems with multiple input timedelays. In this study, electric vehicles (EVs) are participated in the LFC to support reheated thermal power units to rapidly suppress load and frequency fluctuations. A mathematical model of an interconnected power system is first introduced. This model takes into consideration of the different time delays in control inputs; specifically the communication/information delays between the control center and the fleet of EVs. We then derive stabilization conditions in terms of feasible linear matrix inequalities (LMIs) for the proposed system and develop an effective algorithm to parameterize H∞ controllers ensuring stability of the closed-loop system with H∞ performance. Extensive simulations are given to show the effectiveness of the proposed control method.

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For the operator of a power system, having an accurate forecast of the day-ahead load is imperative in order to guaranty the reliability of supply and also to minimize generation costs and pollution. Furthermore, in a restructured power system, other parties, like utility companies, large consumers and in some cases even ordinary consumers, can benefit from a higher quality demand forecast. In this paper, the application of smart meter data for producing more accurate load forecasts has been discussed. First an ordinary neural network model is used to generate a forecast for the total load of a number of consumers. The results of this step are used as a benchmark for comparison with the forecast results of a more sophisticated method. In this new method, using wavelet decomposition and a clustering technique called interactive k-means, the consumers are divided into a number of clusters. Then for each cluster an individual neural network is trained. Consequently, by adding the outputs of all of the neural networks, a forecast for the total load is generated. A comparison between the forecast using a single model and the forecast generated by the proposed method, proves that smart meter data can be used to significantly improve the quality of load forecast.

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This paper presents a new robust nonlinear excitationcontroller design for synchronous generators in multimachine powersystems to enhance the transient stability. The mismatches betweenthe original power system model and formulated mathematical modelare considered as uncertainties which are modeled through thesatisfaction of matching conditions. The exogenous noises appearingfrom measurements are incorporated with the power system modelincluding the two-axis model of synchronous generators. The partialfeedback linearization technique is used to design the controller whichtransforms the original nonlinear multimachine power system modelinto several reduced-order linear and autonomous subsystems. Thedesired control law is obtained for each subsystem and implemented ina decentralized manner provided that the dynamics of the autonomoussubsystems have no effects on the overall stability of the system. Theanalysis related to the dynamics of noisy autonomous subsystems isalso included and the proposed controller has the excellent capabilityto decouple these noises. Finally, the performance of the proposedcontrol scheme is evaluated on an IEEE 39-bus benchmark powersystem following different types of large disturbances. The performanceof the proposed controller is compared to that of a partialfeedback linearizing controller, which is designed without robustnessproperties, to verify the effectiveness of the proposed control scheme.

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This paper presents an approach to design a nonlinear observer-based excitation controller for multimachine power systems to enhance the transient stability. The controller is designed based on the partial feedback linearization of a nonlinear power system model which transforms the model into a reducedorder linear one with an autonomous dynamical part. Then a linear state feedback stabilizing controller is designed for the reduced-order linear power system model using optimal control theory which enhances the stability of the entire system. The states of the feedback stabilizing controller are obtained from the nonlinear observer and the performance of this observer-based controller is independent of the operating points of power systems. The performance of the proposed observer-based controller is compared to that of an exact feedback linearizing observer-based controller and a partial feedback linearizing controller without observer under different operating conditions.

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In this paper, for the first time, electric vehicles are used for both the primary and secondary frequency controls to support power plants to rapidly suppress fluctuations in the system frequency due to load disturbances. Via networked control and wide-area communication infrastructures, multiple interval time-varying delays exist in the communication channels between the control center, power plant, and an aggregation of electric vehicles. By coordinating batteries’ state of charge control, the behaviors of the vehicle owners and the uncertainties imposed by the changes of the batteries’ state of charge are taken intoconsideration. A power system model incorporating multiple time-varying delays and uncertainties is first proposed. Then, a robust static output feedback frequency controller is designed to guarantee the resulting closed-loop system stable with an H∞ attenuation level. By utilizing a novel integral inequality, namely refined-Jensen inequality, and an improved reciprocally convex combination, the design conditions are formulated in terms of tractable linear matrix inequalities which can be efficiently solved by various computational tools. The effectiveness of the proposed control scheme is verified by extensive simulations.

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In this paper, electromagnetic emission at the frequency range of 30MHz to 300MHz is used to detect physical defects on the 22kV outdoor zinc-oxide (ZnO) surge arresters. Different weather conditions combining with artificially created pollution were produced in a laboratory environment and measurements were recorded over a fixed period of time. Pollution due to fine dust particles has been created according to IEC standard under both wet and dry conditions. The aim is to detect the defects (bushing damage) when the surge arrester is subjected to various weather and surface condition. The collected electromagnetic signals were sampled and analyzed using analysis tools such as the autocorrelation coefficient and Wigner-Ville distribution. The results from the present paper indicate that electromagnetic radiation from the defects on surge arrester combining with the adequate analysis tools can be used as a valuable diagnostic tool for power system operator.


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This paper reports on determination of structurally constrained controllers for linear uncertain time-invariant systems from state controllers. It is shown that practical structures such as output and decentralized controllers may be derived from state feedback controllers. A previously studied load frequency control of a two-area interconnected power system is considered to illustrate the proposed approach.