Wind Generation System Research Articles

Optimal dispatch of electricity storage supporting the direct supply of industrial consumers by wind generation

A rising number of industrial companies are aiming to increase the share of renewable generation in their electricity consumption, in order to decrease electricity costs or to fulfill portfolio requirements. This can be achieved by using pv or wind generation systems, which are directly connected to the industrial consumer. The volatility of the renewable generation can be balanced by employing an electricity storage system. The paper presents an MILP optimization model for the direct supply of an industrial consumer by a wind farm, coupled with a storage system. The model optimizes the dispatch of the storage system in order to minimize both the energy component as well as the capacity component of the consumers electricity cost. A case study is presented using the grid tariffs in Germany for two different legal scenarios and two load profiles. The operation of a modular compressed air energy storage system is analyzed and the optimal dimensions of the storage power and capacity are determined, for the proposed system.

Optimized Tilt Fractional Order Cooperative Controllers for Preserving Frequency Stability in Renewable Energy-Based Power Systems

The low system inertia and the high sensitivity to load and generation fluctuations represent the main challenges for future ambitious plans of modern power systems accompanied by high penetrations levels of the renewable energy sources (RESs). Therefore, this article presents a new approach for solving the load frequency control (LFC) in addition to the virtual inertia control (VIC) in interconnected RESs penetrated power systems using cooperative tilt-based controllers and a hybrid modified particle swarm optimization with genetic algorithm (MPSOGA). The VIC system is adopted using superconducting magnetic energy storage (SMES) to provide sufficient inertial energy for system stability. Two tilt-based controllers are employed in each area using the tilt-integral-derivative (TID) controller for the SMES and TID with filter (TIDF) for the LFC function. The cooperative optimum design of the TID/TIDF controllers leads to the enhancement of frequency stability in studied two-area power systems. The formulated optimization process aims to minimize the frequency nadir settling time during abrupt changes of RESs and/or load changes, considering the cooperative control of LFC and VIC. The proposed approach has been applied to a case study consisting of two-area power systems, connected via hybrid high voltage DC/AC (hybrid HVAC/HVDC) tie-line, integrated with distributed conventional generations, photovoltaic (PV), and wind generation systems. Performance analysis has been conducted to demonstrate the effectiveness of the proposed method is compared to the genetic algorithm (GA) and particle-swarm optimization (PSO) using high fluctuations of renewable generations under extreme changes in loading conditions and physical parameters variation. The obtained results show the superiority of MPSOGA approach on the other competitive optimization techniques.

ТЕХНИКА ИСКУССТВЕННОГО ИНТЕЛЛЕКТА ДЛЯ ПРОИЗВОДСТВА ЭНЕРГИИ И АВТОМАТИЗАЦИЯ УПРАВЛЕНИЯ ГИБРИДНОЙ СОЛНЕЧНО-ВЕТРО-ДИЗЕЛЬНОЙ ЭНЕРГЕТИЧЕСКОЙ СИСТЕМОЙ

The use of renewable energy sources plays an irreplaceable role in remote areas where the power grid is not available. Photovoltaic power conversion (PV) and wind power conversion are the main types of renewable energy sources used. Hybrid systems are considered the most efficient solution for remote areas that are not connected to the centralized power grid. Renewable energy is attracting the attention of researchers around the world. The main challenge is to combine the various existing sources into a single model in order to benefit from each of them, while complementing each other's disadvantages. The possibilities of managing combined hybrid systems based on renewable energy sources are currently not thoroughly studied. To increase the generation of electrical energy and reduce losses during the operation of these systems, it is necessary to conduct research aimed at improving the interactions of individual nodes of the proposed generation systems and improving the calculation methods for hybrid power plants. The integrated use of solar and wind generation systems can significantly improve energy performance and increase the generation of electrical energy. This paper proposes a method for integrating a solar photovoltaic system, a wind turbine, and a diesel generator connected to a load. An additional load is also connected to the system to absorb excess power. The hybrid system model was developed in MATLAB / Simulink. A controller based on an adaptive neuro-fuzzy inference system was developed and the system analyzed in terms of energy production and consumption. The results obtained show the degree of increase in the reliability and stability of the system.

A multi-year analysis of Canadian Arctic historical weather data in support of solar and wind renewable energy deployment

This work explores the importance of renewable resource temporal distribution for solar and wind energy deployment in Arctic communities to meet building and ancillary loads. An analysis of ten years of historic weather data was performed for six locations in the Canadian Arctic to assess renewable resource variation. Simulations of similar capacity solar and wind generation systems were then coupled with the historic data to compare and contrast generation potential. This analysis highlighted the importance of considering hourly, daily, monthly, and year-to-year renewable generation when deploying solar and wind to the Arctic. As many northern communities in Canada have local electricity generation and distribution systems, and no connection to the continental grid, managing grid interactions effectively is crucial to the success of deployment, integration, and operation. The results for the solar energy analysis showed high consistency of production year-to-year. The results for the wind energy analysis showed that the annual outputs have significantly less variation than the year-to-year output of individual months for all the locations under study. For the high latitude locations studied, solar energy can still provide useful electricity generation output, but the more pronounced bias of the annual output to the summer months can leave several months with little or no output. The use of additional renewable sources is crucial in beginning to transition some electricity generating capacity within Arctic communities from being solely reliant on fossil fuels.

Bi-Furcated Stator Winding Configuration in Three-Phase Induction Generators for Wind Power Generation

The concerns over the increase in carbon footprints and global climatic changes have given momentum to find ways that reduce the use of fossil fuels to generate electricity. Offshore and onshore windmills for electricity generation are viable options for bulk power generation. A wind generation system has a variable frequency variable voltage supply at the induction generator terminals in response to the changes in the wind velocity and in turn, the speed of the wind turbine. There is a need for an additional power electronic interface to maintain the frequency and voltage at the terminals of the wind generator constant. This paper introduces a novel three-phase Bifurcated Winding Induction Generator (BWIG) comprising a bifurcated set of stator windings. A prototype model has been developed by bifurcating the stator windings of a three-phase induction machine. One part of the winding acts as the excitation winding, and the other half is used as output winding capable of producing three-phase voltages at a constant frequency at all speeds of the prime over. The machine is tested for sub and super synchronous speeds and the characteristics plotted. The flux analysis of the machine is simulated using Ansys Maxwell software. The voltage is controlled by a simple off-on control implemented using a digital controller, TMS320F28335.

Design of Cascaded PI-Fractional Order PID Controller for Improving the Frequency Response of Hybrid Microgrid System Using Gorilla Troops Optimizer

This paper proposes a cascaded Proportional Integral-Fractional Order Proportional-Integral-Derivative (PI-FOPID) controller to improve the frequency response of a hybrid microgrid system. The optimum gains of the proposed controller are fine-tuned using Gorilla Troops Optimizer (GTO) which is a recent metaheuristic optimization algorithm. The case study is a two-area microgrid system that contains diesel generators, various renewable energy sources such as photovoltaic and wind generation systems, as well as different energy storage devices. Moreover, real wind speed and solar irradiance measurements have been collected for proper system modeling. The performance of the proposed cascaded PI-FOPID controller is compared to the single structure fractional order PID (FOPID) controller based on GTO and numerous other optimization techniques presented in the previous literature such as Genetic Algorithm and Particle Swarm Optimization. The robustness of the proposed cascaded PI-FOPID controller is investigated under different scenarios such as different step load perturbations, random load disturbances, and renewable energy sources variation. The simulation results are carried out using MATLAB/Simulink. The results show that the proposed controller provides an improvement in the maximum overshoot/undershoot and settling time of 99.8% and 75.9%, respectively, compared to other competing techniques.

Inertia Response Coordination Strategy of Wind Generators and Hybrid Energy Storage and Operation Cost-Based Multi-Objective Optimizing of Frequency Control Parameters

Due to the high penetration of renewable energy resources in microgrids (MGs), the grid inertia becomes low which leads to the grid to be vulnerable to large disturbances. The energy storage devices can play an important role to enhance the inertia of MGs. However, due to the high investment cost of storages or their dp/dt limitation, the installed energy storages cannot cover the challenge of high df/dt . A prominent solution to solve the problem is to use the inertia response of the wind generators. However, relatively high second frequency nadir is the main drawback of using the inertia response of the wind generators which may impose an extensive disturbance to MGs. Accordingly, a coordinated operation strategy for MGs between wind generator and hybrid energy storage (HES) system is proposed in this paper. In addition, to improve the inertia response of the MG; providing high-quality communication infrastructures with low delay and increasing the Ultracapacitor capacity have been paid attention. In this paper, the costs of the installed Ultracapacitor and quality of communication services are defined as the operation cost. Guaranteeing enough frequency damping for the MG with low operation cost are two conflict objectives. Therefore, a multi-objective optimization method is used to set the controllers’ values and reduce the operation cost. The results confirmed that the effectiveness of the proposed strategy to control hybrid power storage in coordination with the wind generator and the frequency recovery process is improved. Also, employing the optimum values guaranteed the frequency damping effectively with low operation cost. The Integral Absolute Error (IAE) value and operation cost are reduced by 13.6% and 32%, respectively. Also, the simulation results show that the maximum MG frequency deviation and maximum df/dt is well compatible with different standards in the presence of load perturbations and different wind speeds.

Modeling and Coordinated Control Design for Brushless Doubly-Fed Induction Generator-Based Wind Turbine to Withstand Grid Voltage Unbalance

Grid codes require wind turbines to have capability to withstand a certain grid voltage unbalance without tripping. However, existing controls for brushless doubly-fed induction generator (BDFIG) based wind turbine under grid unbalance have many problems such as difficulty in realizing decoupling control, involvement with flux or current estimations, and complex control structure. Moreover, the existing studies only focused on the control of machine side converter (MSC), but the coordinated control between MSC and grid side converter (GSC) and the control objectives of overall BDFIG wind turbine system have not yet been addressed so far. To overcome these problems and improve the control capability, this paper proposes a coordinated control strategy by considering MSC and GSC together. First, the enhanced control objectives for overall BDFIG wind turbine system are determined. Second, the simple single current closed-loop controllers without involving with any flux or current estimations are designed for MSC and GSC, respectively. Meanwhile, in current loops, all the disturbances and cross-coupling terms on <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dq</i> axes are derived and used for feedforward control so as to achieve decoupling control and improve system dynamic response. Further, a fast sequence decomposition approach is employed to enhance the control characteristics of the whole system. Finally, the effectiveness of proposed control is validated through case studies for a 2 MW BDFIG based wind generation system. The results demonstrate that the proposed control can effectively achieve the control objectives of overall wind turbine system under grid voltage unbalance and provide excellent dynamic and stable performance.

Pitch Control of a Digital Hydraulics Pitch System for Wind Turbine Based on Neuro-Fuzzy Digital Pitch Controller

Digital Hydraulics has been implemented in the hydraulic pitch system of Wind Turbine (WT) which aids in uniform power generation at above-rated wind speeds. A novel Digital Hydraulic Pitch System (DHPS) model which uses a hydraulic motor as the end actuator was established and a wind generator system model was developed. Further, a Neuro-Fuzzy Digital Pitch Controller (NFDPC) with two distinct neuro-fuzzy controllers was employed in the developed models. Two comparative studies are conducted and in these studies, the proposed NFDPC was compared with Proportional Integral Derivative Cascade Controller (PIDCC) where PID is implemented in inner and outer loop. In the first comparative study (considering custom wind speed), results revealed that the proposed controller maintains rated generator speed than PIDCC. The Root Mean Square Error (RMSE) (between rated speed and generated speed) of the generator was 1.23 and 3.73 for the proposed and PIDCC, respectively. Thus, uniform power was generated. Consequently, in the second case study (real-time effective wind speed), the proposed controller maintains optimal generator speed with a minimal RMSE of 0.66 when compared to PIDCC with an RMSE of 3.55. Thus, uniform power was developed by the proposed controller. Therefore from these results, the proposed controller generates uniform power at above-rated wind speed with large wind fluctuations.

Examining the Operation Method of a Small Wind Generator System Using Storage batteries

Examining the Operation Method of a Small Wind Generator System Using Storage batteries

Dynamic Performance Improvement of Pitch Angle Control Using PID and PIDA Controllers for Wind Generation Systems

Abstract Recently, wind energy is one of energy sources most have been devoted much awareness as result of shortage of energy. This study shows loads which are formed in the rotating shaft of wind turbine (WT). These loads cause disturbances on the blades, which leads to damage the blades. these loads can be exceeded, and the amount of productive energy can be controlled by using a good control unit that adjusts the angle of the WT blade. For the previous purpose, independent electric motor is used to control blade pitch, this process called pitch control (PC) system. This paper presents a mathematical model of PC system that is controlled by using two different controllers in MATLAB/Simulink; proportional -integral-derivative controller (PID) and proportional -integral-derivative-acceleration (PIDA). In this system three different function are used as reference pitch angle; unit step function, sinewave function and step change signal which are used on control system without any controller and it is found that output system isn’t reached to a reference value for three functions. The steady state error equal to 76% when step function is used, so the controller is needed for a system. When PID and PIDA controllers are used, the time domain specification of output is improved. The steady state error in PID and PIDA controllers is 9% and 0.014% respectively. It is found that the better time domain specification is given by PIDA. PID and PIDA controllers are tested with sinewave and step change, PIDA is also produced the best response.

Matlab/Simulink Based Modeling and Simulation of Decoupled Power Control for DFIG Operating in Wind Generation Systems

This paper appraises the performances of two control scenarios, for doubly fed induction generator (DFIG) operating in wind generation system (WGS), which are the direct decoupled control (DDC) and indirect decoupled control (IDC). Both control scenarios studied combines vector control and Maximum Power Point Tracking (MPPT) control theory so as to maximize the captured power through wind turbine. Modeling of DFIG based WGS and details of both control scenarios have been presented, a proportional integral controller is employed in the active and reactive power control loops for both control methods. The performance of the both control scenarios in terms of power reference tracking and robustness against machine parameters inconstancy has been shown, analyzed and compared, which can afford a reference to the operators and engineers of a wind farm. All simulations have been implemented via MATLAB/Simulink.

Fractional Order Pi Controller for the Highly Efficient Power Regulation of DFIG Based Wind Power Conversion System

In an electric power grid connected wind generation system, dynamic control strategy is essential to use the wind energy efficiently as well as for an energy optimization. The present study has focused on decoupled power regulation of doubly fed induction generator, operating in wind turbine, in accordance with the vector control approach by applying fractional order proportional integral (FOPI) controller. The FOPI controller is designed based on a simple method; up such that the response of closed loop process is similar to the response of a specified fractional model whose transfer function is Bode’s ideal function. In this tuning operation, the parameters of the proposed fractional controller are established analytically using the impulse closed-loop response of the controlled process. To show the superior action of the developed FOPI controller in comparison with standard PI controller in different function conditions, the study is validated through simulation using the software MATLAB/Simulink

LOAD FREQUENCY CONTROL FOR AN ISOLATED HYBRID POWER SYSTEM WITH HYBRID CONTROL TECHNIQUE AND COMPARATIVE ANALYSIS WITH DIFFERENT CONTROL TECHNIQUES

This paper presents a hybrid isolated power system modeling and Load Frequency Controller (LFC) for different penetration levels of wind power generation. The system considered here consists of a conventional diesel generator, wind generator and energy storage system for a LFC. The purpose of the considered system is to suppress the frequency deviations (balancing the real power generation and demand). An inertia control is used to obtain the best possible gain of the wind system and Fuzzy Logic Control (FLC) is used to control the frequency of the hybrid system. The results are compared with different control techniques. The dynamic performance of the system is studied at different cases by changing the wind penetration level and also by increasing the load disturbances.

Simulation and Characteristics Analysis of Multiple Wind Generators in Large-Scale Wind Farms Based on Simplified Model

In the view of the high complexity and a large amount of data of the electromagnetic transient model for the single wind generator, it is difficult to realize the multi-unit simulation modeling of large-scale wind farms by power system simulation software. In this paper, the simplified models of single direct drive and doubly-fed wind generator system are proposed, respectively. In order to study the output characteristics of the wind generator system, the components with small inertia constant in the electromagnetic transient model are neglected, and the shafting model, the converter model, and the control loops are simplified and reduced, respectively. Based on the study of the single electromagnetic transient model of wind generators, the simplified simulation models are built by the PSCAD (Power Systems Computer Aided Design) simulation platform, which are carried out under the conditions of constant wind speed, step wind speed, and fault. The output characteristics of the simplified models under different working conditions are compared in detail models. The simulation results show that, within the allowable calculation accuracy range, the dynamic response curves of the single simplified model and the electromagnetic transient model are consistent. The simulation speed can be significantly improved, the time consumption can be reduced, and the simulation speed can be increased more obviously when the number of simulation models increases. Therefore, it can be applied to the simulation research of multi-wind generators in large-scale wind farms.

Limited-Position Set Model-Reference Adaptive Observer for Control of DFIGs without Mechanical Sensors

Operations of the doubly-fed induction generators (DFIGs) without mechanical sensors are highly desirable in order to enhance the reliability of the wind generation systems. This article proposes a limited-position set model-reference adaptive observer (LPS-MRAO) for control of DFIGs in wind turbine systems (WTSs) without mechanical sensors, i.e., without incremental encoders or speed transducers. The concept of of the developed LPS-MRAO is obtained from the finite-set model predictive control (FS-MPC). In the proposed LPS-MRAO, an algorithm is presented in order to give a constant number of angles for the rotor position of the DFIG. By using these angles, a certain number of rotor currents can be predicted. Then, a new quality function is defined to find the best angle of the rotor. In the proposed LPS-MRAO, there are not any gains to tune like the classical MRAO, where a proportional-integral is used and must be tuned. Finally, the proposed LPS-MRAO and classical one are experimentally implemented in the laboratory and compared at various operation scenarios and under mismatches in the parameters of the DFIG. The experimental results illustrated that the estimation performance and robustness of the proposed LPS-MRAO are better than those of the classical one.

Multi-objective Pareto based Optimal Placement and Sizing of Solar PV and Wind Generation System

Appropriate placement and sizing of distributed generation is required for reducing power loss and improvement in voltage profile of power system. Solar photovoltaic (PV) and wind energy are two prominent sources of distributed generation. In this paper, the authors propose a novel method to analyze the optimal placement and sizing of the solar PV and wind generation system in a radial distribution system. A multi objective function is selected for optimal siting and sizing. A 33-bus distribution system has been considered for testing the developed algorithm. Optimal location is obtained by placing DG source at each bus and satisfying objective function. Jaya algorithm is implemented for optimal sizing of PV and wind system. Also the system has been analyzed by placing the solar PV and Wind generation system independently and then simultaneously.

Sensorless fractional order composite sliding mode control design for wind generation system

A high-performance control system is essential to transfer maximum power from wind power generation system (WPGS) to the utility grid. In this paper, a fuzzy fractional-order terminal sliding mode control (Fuzzy-FOSMC) is presented based on the boundary layer approach. This boundary layer approach leads to the trade-off between chattering elimination and control performances. Initially a fractional order terminal sliding mode control (FOTSMC) is designed in this paper. Then, the reaching control part of the FOTSMC is replaced by a fuzzy system that eliminates the chattering even in the presence of lumped parametric uncertainties. The fuzzy control part is designed such that:(a) it maintains the stability of the system by introducing a non-linear slope inside the thin boundary layer near the sliding surface, and (b) it eliminates the chattering by acting like a saturation function. A novel wind speed estimation technique is also proposed in this paper based on Gaussian process regression (GPR). The inputs to the GPR framework are selected as the wind turbine power and its rotational speed. The superior performance of the proposed wind speed estimation technique is verified using error comparison with pre-existing techniques. The stability of the proposed GPR-based Fuzzy-FOSMC control paradigm is ensured by using the Lyapunov stability theorem. The proposed paradigm is compared with benchmark sliding mode control (SMC) and FOTSMC strategies. The proposed Fuzzy-FOSMC performance in terms of chattering elimination and stability is validated under normal conditions and lumped parametric uncertainties using extensive simulations in Matlab/SIMULINK and processor in the loop based experimental workbench.

Wind turbine multiphase operational trajectory in an all‐DC wind generation system

Wind turbine multiphase operational trajectory in an all‐DC wind generation system

Model Reference Adaptive System with Finite-Set for Encoderless Control of PMSGs in Micro-Grid Systems

In micro-grid systems, wind turbines are essential power generation sources. The direct-driven surface-mounted permanent-magnet synchronous generators (SMPMSGs) in variable-speed wind generation systems (VS-WGSs) are promising due to their high efficiency/power density and the avoidance of using a gearbox, i.e., regular maintenance and noise are averted. Usually, the main goal of the control system for SMPMSGs is to extract the maximum available power from the wind turbine. To do so, the rotor position/speed of the SMPMSG must be known. Those signals are obtained by the help of an incremental encoder or speed transducer. However, the system reliability is remarkably reduced due to the high failure rate of these mechanical sensors. To avoid this problem, this paper presents a model reference adaptive system with finite-set (MRAS-FS) observer for encoderless control of SMPMSGs in VS-WGSs. The motif of the presented MRAS-FS observer is taken from the direct-model predictive control (DMPC) principle, where a certain number of rotor position angles are utilized to estimate the stator flux of the SMPMSG. Subsequently, a new optimization criterion (also called quality or cost function) is formulated to select the best rotor position angle based on minimizing the error between the estimated and reference value of the stator flux. Accordingly, the traditional fixed-gain proportional-integral regulator generally employed in the classical MRAS observers is not needed. The proposed MRAS-FS observer is validated experimentally, and its estimation response has been compared with the conventional MRAS observer under different conditions. In addition to that, the robustness of the MRAS-FS observer is tested at mismatches in the parameters of the SMPMSG.