104 resultados para Grid connected PV system


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This paper presents a nonlinear robust adaptive excitation controller design for a simple power system model where a synchronous generator is connected to an infinite bus. The proposed controller is designed to obtain the adaption laws for estimating critical parameters of synchronous generators which are considered as unknown while providing the robustness against the bounded external disturbances. The convergence of different physical quantities of a single machine infinite bus (SMIB) system, with the proposed control scheme, is ensured through the negative definiteness of the derivative of Lyapunov functions. The effects of external disturbances are considered during formulation of Lyapunov function and thus, the proposed excitation controller can ensure the stability of the SMIB system under the variation of critical parameters as well as external disturbances including noises. Finally, the performance of the proposed scheme is investigated with the inclusion of external disturbances in the SMIB system and its superiority is demonstrated through the comparison with an existing robust adaptive excitation controller. Simulation results show that the proposed scheme provides faster responses of physical quantities than the existing controller.

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This paper presents a nonlinear controller design for vehicle-to-grid (V2G) systems with LCL output filters. The V2G systems are modeled with LCL output filters in order to eliminate harmonics for improving power qualities and the nonlinear controller is designed based on the feedback linearization. The feasibility of using the appropriate feedback linearization approaches, either partial or exact, is also investigated through the feedback linearizability of V2G systems. In this paper, partial feedback linearization is used to design the controller with a capability of sharing both active and reactive power in V2G systems. The performance of the proposed controller controller is evaluated on a single-phase full-bridge converter-based V2G system with an LCL output filter and compared to that of without any filter. Simulation results clearly demonstrate the harmonic elimination capabilities of the proposed V2G structure with the proposed control scheme.

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This paper presents a novel design of interval type-2 fuzzy logic systems (IT2FLS) by utilizing the theory of extreme learning machine (ELM) for electricity load demand forecasting. ELM has become a popular learning algorithm for single hidden layer feed-forward neural networks (SLFN). From the functional equivalence between the SLFN and fuzzy inference system, a hybrid of fuzzy-ELM has gained attention of the researchers. This paper extends the concept of fuzzy-ELM to an IT2FLS based on ELM (IT2FELM). In the proposed design the antecedent membership function parameters of the IT2FLS are generated randomly, whereas the consequent part parameters are determined analytically by the Moore-Penrose pseudo inverse. The ELM strategy ensures fast learning of the IT2FLS as well as optimality of the parameters. Effectiveness of the proposed design of IT2FLS is demonstrated with the application of forecasting nonlinear and chaotic data sets. Nonlinear data of electricity load from the Australian National Electricity Market for the Victoria region and from the Ontario Electricity Market are considered here. The proposed model is also applied to forecast Mackey-glass chaotic time series data. Comparative analysis of the proposed model is conducted with some traditional models such as neural networks (NN) and adaptive neuro fuzzy inference system (ANFIS). In order to verify the structure of the proposed design of IT2FLS an alternate design of IT2FLS based on Kalman filter (KF) is also utilized for the comparison purposes.

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Smart grid constrained optimal control is a complex issue due to the constant growth of grid complexity and the large volume of data available as input to smart device control. In this context, traditional centralized control paradigms may suffer in terms of the timeliness of optimization results due to the volume of data to be processed and the delayed asynchronous nature of the data transmission. To address these limits of centralized control, this paper presents a coordinated, distributed algorithm based on distributed, local controllers and a central coordinator for exchanging summarized global state information. The proposed model for exchanging global state information is resistant to fluctuations caused by the inherent interdependence between local controllers, and is robust to delays in information exchange. In addition, the algorithm features iterative refinement of local state estimations that is able to improve local controller ability to operate within network constraints. Application of the proposed coordinated, distributed algorithm through simulation shows its effectiveness in optimizing a global goal within a complex distribution system operating under constraints, while ensuring network operation stability under varying levels of information exchange delay, and with a range of network sizes.

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Green energy targets for coming decades advocates high penetration of wind energy in main energy matrix which also pose incendiary threat to stability and reliability of modern electric grid if their dynamic performance aspects are not assessed beforehand. Considering increasing interest in dynamic performance along with ancillary service assessment related to frequency regulation, development of suitable generic modeling has gained high priority. This paper presents modeling of type 4 full converter wind turbine generator system suitable for frequency regulation focusing on active power control. Complete model is a modification of WECC generic model with additional aerodynamic and pitch control model. Descriptions of individual sub models are presented and performance results are compared manufacturer specific GE type 4 WTG generic model by means of simulations in the MATLAB ® Power System Block set.

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This paper presents a robust model and its simulation to investigate the performance of an AC propulsion system in a rail vehicle for directly returning the regenerative braking power to the feeder substation of an AC traction network. This direct returning method can be an efficient approach for energy recovery if the regenerative braking is reliably applied. However, it is shown that this method can cause undesired voltage fluctuations if the regenerative braking regime or braking location of the rail vehicle change. The load torque on the traction motor (TM) is precisely modelled when pure electrical braking is applied. Different states of the direct torque controlled inverter are modelled when the TM regenerates. A circuit model for the utility grid, load impedances and the traction network is developed to evaluate the network receptivity against the regenerated power. The dynamics of the electromagnetic torque and the fluctuations of the DC-link voltage are investigated for two operational conditions: changes on the regenerative braking regime and changes on the rail vehicle braking location. The results justify how the DC-link voltage dramatically fluctuates with variations of the rail vehicle's operation conditions, whereas the electromagnetic torque is maintained on optimum rates.

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Today’s power system network is more complex with enhanced responsibility to maintain reliable, stable and quality supply of power at transmission and distribution level. Maintaining grid balance is a bigger issue, in case of any unexpected generation shortage or grid disturbance or any participation of an intermittent nature of renewable energy sources like wind and solar power in the energy mix. In order to compensate such imbalance and improve reliability, and stability of power system, an energy storage system (ESS) can be considered as a vital solution. Also ESS can be used to mitigate associated issues of renewable energy sources while integration into the power system network. Thus ESS supports to get a reduction in greenhouse gas (GHG) emissions by means of integrating more renewable energy sources to the grid effectively. There are various types of Energy Storage (ES) technologies which are being used in power systems network for large scale (MW) to small scale (KW) level. Based on the type and characteristics, each storage technology is suitable for a particular role of applications. This paper presents an extensive review study on various types of ES technologies in characteristics and applications point of view. It also demonstrates various applications of ESS in detail. Finally, with the aid of ES-selectTM tool software, a feasibility analysis has been carried out to identify a suitable ES technology for appropriate applications at different grid locations and also helps to develop a smart hybrid storage system for grid applications in future.

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Energy crisis is one of the major problems facing the progress of human society. There are several energy-efficient technologies that can be applied to save energy and make a sustainable environment. Passive air cooling of earth pipe cooling technology is one of them to reduce the energy consumption for hot and humid subtropical climates. The technology works with a long buried pipe with one end for intake air and the other end for providing air cooled by soil to the desired space such as residential, agricultural, or industrial buildings. It can be an attractive economical alternative to conventional cooling since there are no compressors or any customary mechanical unit. This chapter reports the performance of a vertical earth pipe cooling system for a hot and humid subtropical climatic zone in Queensland, Australia. A series of buried pipes were installed in vertical arrangement in order to increase earth pipe cooling performance. To measure the performance of the system, a numerical model was developed and simulated using the CFD software Fluent in ANSYS 15.0. Data were collected from two modeled rooms built from two shipping containers and installed at the Sustainable Precinct at Central Queensland University, Rockhampton, Australia. The impact of air temperature and velocity on room cooling performance has also been assessed. A temperature reduction of 1.82 °C was observed in the room connected to the vertical earth pipe cooling system, which will save the energy cost for thermal cooling in buildings.

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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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The chapter presents a dynamical model and power conversion technology of electric vehicles (EVs) used in smart grids. The efficient power conversion of EVs in smart grids depends on the operation of bi-directional converters as these EVs need to be either charged or discharged. In this chapter, the mathematical model of a bi-directional converter used in EVs is developed and a nonlinear controller is designed to facilitate the power conversion in the smart grid environments. Since the power conversion of EVs in smart grids requires the communication, a nonlinear partial feedback linearising distributed controller based on the communication with different EVs is proposed to ensure high power quality and system stability.

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© 2015 IEEE.This paper presents an H« controller synthesised based on linear matrix inequalities (LMI) for a current source converter based superconducting magnetic energy systems (SMESs) connected to a node of power systems where the regulation of grid current has considered as a control objective. To facilitate the control design, the system is represented in terms of state space realization with uncertainties. The control design involves selecting proper weighting functions and performing LMI-synthesis. The controller order is reduced by Henkel-norm method. Simulations are carried out to evaluate the characteristics of the controller under parametric uncertainties. It is found out that the proposed controller is inherently stable, possesses significantly small tracking error, and preserves robust performance for the SMES.

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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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In this paper, a nonlinear adaptive backstepping controlleris designed to control the bidirectional power flow (charging/discharging) of battery energy storage systems (BESSs) in a DCmicrogrid under different operating conditions. The controller isdesigned in such a manner that the BESSs can store the excess energyfrom the renewable energy sources (RESs) in a DC microgrid aftersatisfying the load demand and also feeding back the stored energyto the load when RESs are not sufficient. The proposed controller isalso designed to maintain a constant voltage at the DC bus, whereall components of DC microgrids are connected, while controllingthe power flow of BESSs. This paper considers solar photovoltaic(PV) systems as the RES whereas a diesel generator equipped witha rectifier is used as a backup supply to maintain the continuity ofpower supply in the case of emergency situations. The controller isdesigned recursively based on the Lyapunov control theory whereall parameters within the model of BESSs are assumed to beunknown. These unknown parameters are then estimated throughthe adaptation laws and whose stability is ensured by formulatingsuitable control Lyapunov functions (CLFs) at different stages ofthe design process. Moreover, a scheme is also presented to monitorthe state of charge (SOC) of the BESS. Finally, the performanceof the proposed controller is verified on a test DC microgrid undervarious operating conditions. The proposed controller ensures the DCbus voltage regulation within the acceptable limits under differentoperating conditions.

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This work develops a transactive energy management system in order to automate the operation and efficiently utilize the energy generated from the solar PV unit and BESS in a single house as well as in the microgrid and provides cost-benefit analysis.