A. Hajizadeh,
Volume 9, Issue 1 (3-2013)
Abstract
This paper presents modeling and control of a hybrid distributed energy sources including photovoltaic (PV), fuel cell (FC) and battery energy storage (BES) in a microgrid which provides both real and reactive power to support an unbalanced utility grid. The overall configuration of the microgrid including dynamic models for the PV, FC, BES and its power electronic interfacing are briefly described. Then controller design methodologies for the power conditioning units to control the power flow from the hybrid power plant to the unbalanced utility grid are presented. In order to distribute the power between power sources, the neuro-fuzzy power controller has been developed. Simulation results are presented to demonstrate the effectiveness and capability of proposed control strategy.
R. Ghazi, A. Khajeh,
Volume 9, Issue 3 (9-2013)
Abstract
Nowadays, the doubly-fed induction generators (DFIGs) based wind turbines (WTs) are the dominant type of WTs connected to grid. Traditionally the back-to-back converters are used to control the DFIGs. In this paper, an Indirect Matrix Converter (IMC) is proposed to control the generator. Compared with back-to-back converters, IMCs have numerous advantages such as: higher level of robustness, reliability, reduced size and weight due to the absence of bulky electrolytic capacitor. According to the recent grid codes it is required that wind turbines remain connected to the grid during grid faults and following voltage dips. This feature is called low voltage ride-through (LVRT) capability. In this paper the linear quadratic regulator (LQR) controller is used for optimal control of the DFIG. The weighting matrices of the LQR are obtained using the genetic algorithm (GA) technique. With the LQR controller the intention is to improve the LVRT capability of the DFIG wind turbines to satisfy the new LVRT requirements. Compared to the PI controller, the superiority of the LQR controller in improving the transient stability and LVRT performance of the DFIG wind turbines is evident. Simulation results confirm the efficiency of the proposed controller.
A. Gharaveisi, G. A. Heydari, Z. Yousofi,
Volume 10, Issue 3 (9-2014)
Abstract
In this paper, the Vector Based Swarm Optimization method is used for designing an optimal controller for the maximum power point tracker of a stand-alone PV System. The proposed algorithm is executed on vectors in a multi-dimension vector space. These vectors by appropriated orientation converge to a global optimum while the algorithm runs. The Remarkable point of the VBSO algorithm is how using completely random coefficients have good influence on algorithm performance. The generated energy is delivered to a boost converter including a resistive load. The duty cycle of the converter’s switch is determined in order to minimize generated power deviation, relative to PV voltage.
M. Hosseinabadi, H. Rastegar,
Volume 10, Issue 4 (12-2014)
Abstract
This paper is concerned with behavior analysis and improvement of wind turbines with Doubly Fed Induction Generator (DFIG) when using a new fractional-order control strategy during wind variations. A doubly fed induction generator, two types of variable frequency power electronic converters and two input wind waveforms are considered. A fractional-order control strategy is proposed for the wind turbine control unit. Output parameters of the wind turbine are drawn by simulations using MATLAB/Simulink for both fractional-order and integer-order (classic) control systems and a complete comparison between these two strategies has been presented. Results show a better operation when using fractional-order control system.
M. Alizadeh Moghadam, R. Noroozian, S. Jalilzadeh,
Volume 11, Issue 3 (9-2015)
Abstract
This paper presents modeling, simulation and control of matrix converter (MC) for variable speed wind turbine (VSWT) system including permanent magnet synchronous generator (PMSG). At a given wind velocity, the power available from a wind turbine is a function of its shaft speed. In order to track maximum power, the MC adjusts the PMSG shaft speed.The proposed control system allowing independent control maximum power point tracking (MPPT) of generator side and regulate reactive power of grid side for the operation of the VSWT system. The MPPT is implemented by a new control system. This control system is based on control of zero d-axis current (ZDC). The ZDC control can be realized by transfer the three-phase stator current in the stationary reference frame into d-and q-axis components in the synchronous reference frame. Also this paper is presented, a novel control strategy to regulate the reactive power supplied by a variable speed wind energy conversion system. This control strategy is based on voltage oriented control (VOC). The simulation results based on Simulink/Matlab software show that the controllers can extract maximum power and regulate reactive power under varying wind velocities.
H. Rajabi Mashhadi, M. A. Armin,
Volume 11, Issue 3 (9-2015)
Abstract
Utilization of wind turbines as economic and green production units, poses new challenges to the power system planners, mainly due to the stochastic nature of the wind, adding a new source of uncertainty to the power system. Different types of distribution and correlation between this random variable and the system load makes conventional method inappropriate for modeling such a correlation. In this paper, the correlation between the wind speed and system load is modeled using Copula, a mathematical tool recently used in the field of the applied science. As the effect of the correlation coefficient is the main concern, the copula modeling technique allows simulating various scenarios with different correlations. The conducted simulations in this paper reveals that the wind speed correlation with the load has significant effect on the system reliability indices, such as expected energy not served (EENS) and loss of load probability (LOLP). Moreover, in this paper the effect of the correlation coefficient on the effective load carrying capability (ELCC) of the wind turbines is analyzed, too. To perform the aforementioned simulations and analyses, the modified RBTS with an additional wind farm is used.
M.a Armin, H Rajabi Mashhadi,
Volume 11, Issue 4 (12-2015)
Abstract
Wind energy penetration in power system has been increased very fast and large amount of capitals invested for wind farms all around the world. Meanwhile, in power systems with wind turbine generators (WTGs), the value of Available transfer capability (ATC) is influenced by the probabilistic nature of the wind power. The Mont Carlo Simulation (MCS) is the most common method to model the uncertainty of WTG. However, the MCS method suffers from low convergence rate. To overcome this shortcoming, the proposed technique in this paper uses a new formulation for solving ATC problem analytically. This lowers the computational burden of the ATC computation and hence results in increased convergence rate of the MCS. Using this fast technique to evaluate the ATC, wind generation and load correlation is required to get into modeling. A numerical method is presented to consider load and wind correlation. The proposed method is tested on the modified IEEE 118 bus to analyze the impacts of the WTGs on the ATC. The obtained results show that wind generation capacity and its correlation with system load has significant impacts on the network transfer capability. In other words, ATC probability distribution is sensitive to the wind generation capacity.
H. Afkar, M. A. Shamsi Nejad, M. Ebadian,
Volume 12, Issue 2 (6-2016)
Abstract
Load balancing is an important issue in distributed systems. In addition, using distributed generation sources such as photovoltaic is increasing. Power electronic converters are main interfaces between the sources and the grid. In this paper, a method has been proposed to reduce the load imbalancing in distribution networks using PV Grid Interface Converter. Two DC/DC and DC/AC converters have been utilized for connecting PV to the grid. A control strategy is presented which enables the converter to compensate the load imbalancing by injecting power of solar cells to the load and grid. Simulation results by MATLAB/SIMULINK software indicate the ability of the proposed control method to reduce the load imbalancing.
E. Alizadeh, A. M. Birjandi, M. Hamzeh,
Volume 12, Issue 4 (12-2016)
Abstract
This paper proposes an autonomous and economic droop control scheme for DC microgrid application. In this method, a cost-effective power sharing technique among various types of DG units is properly adopted. The droop settings are determined based on an algorithm to individually manage the power management without any complicated optimization methods commonly applied in the centralized control method. In the proposed scheme, the system retains all the advantages of the traditional droop method while minimizes the generation costs of the DC microgrid. In the proposed method, all DGs are classified in a sorting rule based on their total generation cost and the reference voltage of their droop equations is then determined. The proposed scheme is applied to a typical DC microgrid consisting of four different types of DGs and a controllable load. The simulation results are presented to verify the effectiveness of the proposed method using MATLAB/SIMULINK software.
H. Shayeghi, A. Ghasemi,
Volume 12, Issue 4 (12-2016)
Abstract
Microgrids is an new opportunity to reduce the total costs of power generation and supply the energy demands through small-scale power plants such as wind sources, photo voltaic panels, battery banks, fuel cells, etc. Like any power system in micro grid (MG), an unexpected faults or load shifting leads to frequency oscillations. Hence, this paper employs an adaptive fuzzy P-PID controller for frequency control of microgrid and a modified multi objective Chaotic Gravitational Search Algorithm (CGSA) in order to find out the optimal setting parameters of the proposed controller. To provide a robust controller design, two non-commensurable objective functions are formulated based on eigenvalues-domain and time-domain and multi objective CGSA algorithm is used to solve them. Moreover, a fuzzy decision method is applied to extract the best and optimal Pareto fronts. The proposed controller is carried out on a MG system under different loading conditions with wind turbine generators, photovoltaic system, flywheel energy, battery storages, diesel generator and electrolyzer. The simulation results revealed that the proposed controller is more stable in comparison with the classical and other types of fuzzy controller.
S. Heshmatian, D. Arab Khaburi, M. Khosravi, A. Kazemi,
Volume 14, Issue 1 (3-2018)
Abstract
Wind energy is one of the most promising renewable energy resources. Due to instantaneous variations of the wind speed, an appropriate Maximum Power Point Tracking (MPPT) method is necessary for maximizing the captured energy from the wind at different speeds. The most commonly used MPPT algorithms are Tip Speed Ratio (TSR), Power Signal Feedback (PSF), Optimal Torque Control (OTC) and Hill Climbing Search (HCS). Each of these algorithms has some advantages and also some major drawbacks. In this paper, a novel hybrid MPPT algorithm is proposed which modifies the conventional methods in a way that eliminates their drawbacks and yields an improved performance. This proposed algorithm is faster in tracking the maximum power point and provides a more accurate response with lower steady state error. Moreover, it presents a great performance under conditions with intensive wind speed variations. The studied Wind Energy Conversion System (WECS) consists of a Permanent Magnet Synchronous Generator (PMSG) connected to the dc link through a Pulse-Width Modulated (PWM) rectifier. The proposed algorithm and the conventional methods are applied to this WECS and their performances are compared using the simulation results. These results approve the satisfactory performance of the proposed algorithm and its notable advantages over the conventional methods.
H. Ahmadi, A. Rajaei, M. Nayeripour, M. Ghani,
Volume 14, Issue 4 (12-2018)
Abstract
Considering the increasing usage of the clean and renewable energies, wind energy has been saliently improved throughout the world as one of the most desired energies. Besides, most power houses and wind turbines work based on the doubly-fed induction generator (DFIG). Based on the structure and the how-ness of DFIG connection to the grid, two cases may decrease the performance of the DFIG. These two cases are known as a fault and a low-voltage in the grid. In the present paper, a hybrid method is proposed based on the multi-objective algorithm of krill and the fuzzy controller to improve the low-voltage ride through (LVRT) and the fault ride through (FRT). In this method, first by using the optimal quantities algorithm, the PI controllers’ coefficients and two variables which are equal to the demagnetize current have been calculated for different conditions of fault and low voltage. Then, these coefficients were given to the fuzzy controller. This controller diagnosed the grid condition based on the stator voltage and then it applied the proper coefficients to the control system regarding the diagnosed condition. To test the proposed method, a DFIG is implemented by taking the best advantages of the proposed method; additionally, the system performance has been tested in fault and low voltage conditions.
A. Dameshghi, M. H. Refan,
Volume 14, Issue 4 (12-2018)
Abstract
Wind turbines are very important and strategic instruments in energy markets. Wind power production is unreliable. Wind power is weather dependent and the extreme wind speed changes make difficult to control of grid voltage and reactive power. Based on these reasons, Wind Power Prediction (WPP) is important for real applications. In this paper, a new short-term WPP method based on Support Vector Machine (SVM) is proposed. In contrast to physical approaches based on very complex differential equations, the proposed method is based on data history. Firstly, data preprocessing and normalization is done. Secondly, formulate the prediction as a regression problem. Thirdly, the prediction model is constructed using the Particle Swarm Optimization (PSO) and Least Square Support Vector Machine (LSSVM). In this paper, instead of using the conventional kernels, such as linear kernel, Polynomial and Radial basis function (RBF), the Wavelet (W) transform is used. The PSO-LS-WSVM accuracy has been tested with industrial wind energy data. This method has been compared with other methods and the experimental results based on practical data illustrate that PSO-LS-WSVM proposed method has better responses than other methods. Statistical results indicate that the predicting error of PSO-LS-WSVM is 2.98% for one look-ahead hour.
A. Azghandi, S. M. Barakati, B. Wu,
Volume 14, Issue 4 (12-2018)
Abstract
A voltage source inverter (VSI) is widely used as an interface for distributed generation (DG) systems. However, high-power applications with increasing voltage levels require an extra power converter to reduce costs and complications. Thus, a current source inverter (CSI) is used. This study presents a precise phasor modeling and control details for a VSI-based system for DG and compares it with a CSI-based system. First, the dynamic characteristics of the system based on amplitude-phase transformation are investigated via small signal analysis in the synchronous reference frame. Moreover, the performance of the grid-connected system is determined by adopting the closed-loop control method based on the obtained dynamic model. The control strategies employ an outer active-power loop cascaded with an inner reactive-power loop, which the inner loop is a single-input single-output system without coupling terms. The sensitivity analysis of the linearized model indicates the dynamic features of the system. The simulation results for the different conditions confirm proposed model and design of the controller.
