A fuzzy logic controlled superconducting magnetic energy storage,SMES frequency stabilizer

This paper presents application of fuzzy logic controlled superconducting magnetic energy storage device, SMES to damp the frequency oscillations of interconnected two-area power systems due to load excursions. The system frequency oscillations appear due to load disturbance. To stabilize the system frequency oscillations, the active power can be controlled via superconducting magnetic energy storage device, SMES. The error in the area control and its rate of change is used as controller input signals to the proposed fuzzy logic controller. In order to judge the effect of the proposed fuzzy logic controlled SMES, a comparative study is made between its effect and the effect of the conventional proportional plus integral (PI) controlled SMES. The studied system consists of two-area (thermal–thermal) power system each one equipped with SMES unit. The time simulation results indicate the superiority of the proposed fuzzy logic controlled SMES over the conventional PI SMES in damping the system oscillations and reach quickly to zero frequency deviation. The system is modeled and solved by using MATLAB software.     

超导磁储能系统抑制风力发电功率波动的研究

建立含超导磁储能装置(SMES)的单机无穷大系统的Phillips-Heffron模型,导出含SMES电力系统总的电磁转矩表达式,从理论上分析SMES对增强系统阻尼的作用.并设计了SMES非线性比例积分微分控制器,数字仿真结果验证了SMES阻尼系统功率振荡的特性,同时表明该控制器具有较好的鲁棒性.     

Interconnected power systems with superconducting magnetic energy storage

The objective of this work is to discuss the concept of back‐to‐back interconnection systems with energy storage, especially with a Superconducting Magnetic Energy Storage (SMES) incorporated into a back‐to‐back DC link. In this case, each converter of the back‐to‐back system is used as a power conditioning system for the SMES coils. Since the AC–DC converter can be designed independently of the frequency of the power system, a two‐way switch is connected to the AC side of each converter. This two‐way switch can select the interconnected power systems. By using the two‐way switches, this system can provide the stored energy in the SMES system to each interconnected power system through two AC–DC converters. For instance, lower‐cost power of each power network can be stored through two converters during the off‐peak hours and made available for dispatch to each power network during periods of demand peak. Then this system increases the reliability of electric power networks and enables the economical operations depending on the power demand. This paper describes the unique operations of the back‐to‐back interconnection with SMES and discuses the optimal SMES configuration for a 300‐MW‐class back‐to‐back interconnection. © 2008 Wiley Periodicals, Inc. Electr Eng Jpn, 164(2): 37–43, 2008; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20482     

A fuzzy logic supervisor for active and reactive power control of a fixed speed wind energy conversion system

In this paper, we present the design of a fuzzy logic supervisor for the control of active and reactive power which is generated by fixed speed wind energy conversion systems (WECS). First, the modelling of a three-phase induction generator driven by a horizontal axis wind turbine is described. An adjustable capacitor bank is plugged at the connection point with a Static Var Compensator (SVC), which is controlled to regulate the rms voltage. The obtained model is reduced by taking into consideration the dynamics of the system. A fuzzy logic-based supervisor is proposed in order to minimize variations of the generated active power and the stator voltage. The regulation of the rms voltage is performed while imposing a reactive power reference. The pitch angle of the turbine blades is set to obtain the maximum wind power. The obtained performances of the proposed supervisor are then presented.     

Coordinated stabilizing control for large-scale interconnected power systems,by superconducting magnetic energy storage unit and power system stabilizers

The purpose of large-scale power system interconnection is to achieve extremely economical and reliable power generation and transmission. It has established the present power systems of high quality. On the other hand, in the large power systems with complex configuration, an undamped power swing with low frequency caused by the synchronous power between interconnected systems tends to occur as well as an undamped power swing caused by the synchronous power of specific generators. Several coordinated stabilizing control schemes for the power systems by sets of power system stabilizers (PSSs) have been investigated so far. PSS is very effective for the stabilization of power swing among a few specific generators because the function of PSS is achieved by the voltage control using the generator field winding circuit. However, it seems that PSSs do not have sufficient ability to stabilize the power swings between interconnected systems. In this paper, the superconducting magnetic energy storage (SMES) which is significantly effective for the power swings between interconnected systems is introduced and a coordinated power system stabilizing control by SMES and PSSs is proposed. The advantages of the proposed control scheme are: 1) high efficiency of the controller by the distribution of functions; 2) independency of the control design for PSS and SMES; and 3) robustness of the controller, and so on.     

Power oscillation damping by superconducting magnetic energy (SMES) storage unit

With the increase in the size and capacity of electric power systems and the growth of widespread interconnections, the problem of power oscillations due to the reduced system damping has become increasingly serious. Since a Superconducting Magnetic Energy Storage (SMES) unit with a self-commutated converter is capable of controlling both the active (P) and reactive (Q) power simultaneously and quickly, increasing attention has been focused recently on power system stabilization by SMES control. This paper describes the effects of SMES control on the damping of power oscillations. By examining the case of a single generator connected to an infinite bus through both theoretical analyses and experimental tests (performed with a SMES unit with maximum stored energy of 16 kJ and an artificial model system), the difference in the effects between P and Q control of SMES is clarified as follows:

• 1 In the case of P control, as the SMES unit is placed closer to the terminal of the generator, the power oscillations will decay more rapidly.
• 2 In the case of Q control, it is most effective to install the SMES unit near the midpoint of the system.
• 3 By comparing the P control with Q control, the former is more effective than the latter based on the conditions that the SMES unit location and the control gain are the same.

     

A unified approach for the solution of power flows in electric power systems including wind farms

This paper proposes a solution approach of the power flow problem to assess the steady-state condition of power systems with wind farms in a single frame of reference, in which the state variables of the wind generators are combined with the nodal voltage magnitudes and angles of the entire network for a unified iterative solution through the Newton-Raphson method. Different wind energy conversion systems (WECS) are mathematically derived from the steady-state representation of the induction generator. Suitable strategies for initializing the state variables of the wind generators are also proposed in this paper. Lastly, three numerical examples are presented to numerically illustrate the applicability of the proposed approach.     

Sliding mode voltage control strategy for capturing maximum wind energy based on fuzzy logic control

A sliding mode voltage control strategy is proposed in this paper to capture the maximum electrical energy from wind. This control strategy mainly includes a fuzzy logic controller and a sliding mode voltage controller. The fuzzy logic controller is designed to derive the optimum DC-side voltage, while the sliding mode voltage controller is employed to track the derived optimum voltage with minimum steady-state error and hence to capture the maximum wind energy. This paper illustrates how major issues in the design and implementation of the two controllers can be handled effectively. Comparative experimental results demonstrate that significant performance improvements in maximum wind energy capture can be achieved by using the proposed control strategy.     

超导储能用电压型大功率换流器技术

在500 kVA超导储能系统研制中,为了选择合适的功率变换电路拓扑,使系统具有更高的电压等级和灵活性,比较了近年来国内外采用的几种电压型换流器。针对超导储能特点及其在电力系统中承担电能质量调节的要求,分析了传统2电平桥式换流电路、中点钳位型多电平换流电路以及级联型多电平换流电路的性能。分析结果表明,对于大功率超导储能装置,级联型多电平换流电路在电压等级、控制精度及结构灵活等方面均优于另外2种换流器拓扑,采用级联型换流器的超导储能系统实现了模块化构造,可以实现系统冗余及容错运行。仿真结果证实模块化超导储能系统能够在较低工作频率下精确控制电压质量。     

A new control strategy of WFSG-based wind turbine to enhance the LVRT capability

This paper proposes a competent and effective scheme to enhance the low voltage ride through (LVRT) capability of wound field synchronous generator (WFSG) based wind turbines (WTs) under unbalanced voltage dip conditions. A technique for grid synchronization against voltage excursions, i.e., a PLL using positive grid voltages with a high selectivity filters (HSFs) is utilized to extract a robust grid voltage synchronization signal irrespective of the mains condition to enhance the overall system performance. Besides, a new controller (adaptive fuzzy RST) for both the stator side converter (SSC) and grid side converter (GSC) current regulation are employed to further improve dynamic performance. Also, a reactive power support scheme to manage the WFSG reactive power during contingencies and fulfill the grid codes obligations is presented. Moreover, an additional device such as braking chopper (BC) circuit is used in the DC-link circuit for stable operation of the wind energy conversion system (WECS) under-line fault. Effectiveness of the proposed control strategy is verified by the numerical simulations.     

A fuzzy logic supervisor for active and reactive power control of a variable speed wind energy conversion system associated to a flywheel storage system

In this paper, we propose a Wind Energy Conversion System (WECS) at variable speed using a Doubly Fed Induction Generator (DFIG) controlled on the rotor side through converters. A Flywheel Energy Storage System (FESS) is connected to the studied wind generator at the DC bus in order to evaluate its capacity to participate to the ancillary services. We study the improvement of the active and reactive power quality produced by the wind generator and its effect on the load voltage regulation connected to the wind generator. For that, a fuzzy logic supervisor is established to control the FESS operation and the DC bus voltage in order to smooth the active power fluctuations due to the random wind speed variations. A control law is also described to smooth the reactive power at the connection node to the grid.     

Maximum power tracking control for a wind energy conversion system based on a quasi‐ARX neural network model

By itself, a wind turbine is already a fairly complex system with highly nonlinear dynamics. Changes in wind speed can affect the dynamic parameters of wind turbines, thus rendering the parameters uncertain. However, we can identify the dynamics of the wind energy conversion system (WECS) online by a quasi‐ARX neural network (QARXNN) model. A QARXNN presents a problem in searching for the coefficients of the regression vector (input vector). A multilayer perceptron neural network (MLPNN) is an embedded system that provides the unknown parameters used to parameterize the input vector. Fascinatingly, the coefficients of the input vector from prediction model can be set as controller parameters directly. The stability of the closed‐loop controller is guaranteed by the switching of the linear and nonlinear parts of the parameters. The dynamic of WECS is derived with given parameters, and then a wind speed signal created by a random model is fed to the system causing uncertainty parameters and reducing the power that can be absorbed from wind. By using a minimum variance controller, the maximum power is tracked from WECS. From the simulation results, it is observed that the proposed controller is effective in tracking the maximum power of WECS. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Optimized coordinated control of LFC andSMES to enhance frequency stability of areal multi-source power system consideringhigh renewable energy penetration

With rapidly growing of Renewable Energy Sources (RESs) in renewable power systems, several disturbances influence on the power systems such as; lack of system inertia that results from replacing the synchronous generators with RESs and frequency/voltage fluctuations that resulting from the intermittent nature of the RESs. Hence, the modern power systems become more susceptible to the system instability than conventional power systems. Therefore, in this study, a new application of Superconducting Magnetic Energy Storage (SMES) (i.e., auxiliary Load Frequency Control (LFC)) has been integrated with the secondary frequency control (i.e., LFC) for frequency stability enhancement of the Egyptian Power System (EPS) due to high RESs penetration. Where, the coordinated control strategy is based on the PI controller that is optimally designed by the Particle Swarm Optimization (PSO) algorithm to minimize the frequency deviations of the EPS. The EPS includes both conventional generation units (i.e., non-reheat, reheat and hydraulic power plants) with inherent nonlinearities, and RESs (i.e., wind and solar energy). System modelling and simulation results are carried out using Matlab/ Simulink® software. The simulation results reveal the robustness of the proposed coordinated control strategy to preserve the system stability of the EPS with high penetration of RESs for different contingencies.     

超导储能改善并网风电场稳定性的研究

建立了风电机组和超导储能(SMES)装置的数学模型以研究SMES对并网风电场运行稳定性的改善.针对风电系统中经常出现的联络线短路故障和风电场的风速扰动,提出利用SMES安装点的电压偏差作为SMES有功控制器的控制信号的策略.对实例系统进行的仿真计算结果表明,SMES采用该控制策略,不仅可以在网络故障后有效地提高风电场的稳定性,而且能够在快速的风速扰动下平滑风电场的功率输出,降低风电场对电网的冲击.     

Battery energy storage-based system damping controller for alleviating sub-synchronous oscillations in a DFIG-based wind power plant

This paper presents the issue of the Sub-synchronous resonance (SSR) phenomenon in a series compensated DFIGbased wind power plant and its alleviation using a Battery Energy Storage-based Damping Controller (BESSDCL). A supplementary damping signal is developed considering the angular speed deviation and is incorporated into the BESS control system. Wide-area Measurement System data is used to determine the angular speed deviation. A linearized system model is developed to perform eigenvalue analysis, and to detect and examine unstable SSR modes. The variation of wind speed and three-phase fault are also taken into consideration to validate the robustness of the controller. To further verify the efcacy of the proposed damping controller, time-domain simulations are performed using MATLAB/Simulink. The application of the proposed BESSDCL stabilizes all the unstable system modes efectively at wind speeds of 7 m/s, 9 m/s, and 11 m/s, and at 40%, 50%, and 60% series compensation levels, as well three-phase fault conditions.     

考虑功率最大输出与储能协调的光储VSG控制策略

在传统虚拟同步发电机(virtual synchronous generator, VSG)控制的光储系统中,电池通过频繁充放电处理波动的光伏功率,易出现早衰问题。为优化电池运行,提出一种考虑功率最大输出与储能协调的光储VSG控制策略。首先,建立输出频率与直流侧电容电压偏差的比例关系,实现光伏功率的最大输出与VSG的惯性支撑。其次,利用下垂特性控制电池功率输出,在实现系统一次调频功能的基础上提升电池能量管理的灵活度。然后,设计一种稳定直流侧电压的分段控制方案,确保系统正常工作时直流侧电压在合理范围之内。最后,通过仿真实验验证所提方法不仅保留了VSG的惯性支撑和一次调频功能,还实现了光伏功率的最大输出,减少了对电池的依赖。     

一种新型的基于风速预测的风力发电系统

为了使风力发电系统的有功出力波动维持在规定的范围内,同时保证系统的蓄电池储能水平基本保持不变,使系统能有效地应对输入功率突然增加及输出功率急剧下降的紧急情况,在风速预测的基础上提出一种新型的风力发电系统蓄电池充放电控制策略。当预测的风力发电系统输入功率的波动超过规定的功率变化范围时,通过对蓄电池的充放电控制以减弱网侧功率的波动,并且使蓄电池的充放电能量在一个周期内基本平衡,从而保证系统预留一定容量的储能装置以接收大功率输入或补充严重不足的并网功率,有效地减少了风能损失、提高了系统的效率。仿真结果验证了所提控制策略的有效性和可靠性。     

混合储能系统平滑风电出力的变分模态分解-模糊控制策略

在风电机组并网处安装储能装置可以有效平滑功率波动,提出了变分模态分解-模糊控制策略平抑风电功率波动。首先通过滑动平均滤波获得储能系统参考功率,采用变分模态分解(Variational Mode Decomposition, VMD)将储能系统参考功率分解后,分别将高频信号和低频信号分配给超级电容器和锂电池。结合超级电容器和锂电池当前荷电状态与其参考值偏差,经模糊控制规则修正储能系统设备的充放电功率。最后利用Matlab/Simulink仿真,结果表明该控制策略不仅能够满足风电场最大输出功率变化率限制要求,还可以保持荷电状态(SOC)维持在合理范围,避免过充和过放的发生。     

A control scheme for improving the efficiency of DFIG at low wind speeds with fractional rated converters

This study proposes a scheme for extending the low speed range of operation of a Doubly Fed Induction Generator (DFIG) without down grading the efficiency. Also, only fractional rated converters are employed. The technique involves two operational modes for the generator. When the rotor speed is between 70% and 130% of the synchronous speed, the machine is operated in the normal Doubly Fed Induction Generator (DFIG) mode and when the rotor speed falls below 70%, it is operated in Stator Short Circuited (SSC) mode. The switch-over from the DFIG mode to the SSC mode is carried out at a threshold speed to maintain the efficiency of generator with the same fractional rated converters. The computer simulations on a typical DFIG (250 kW) in Matlab/Simulink environment illustrate that the range of efficiency improvement is from zero to 15%. Further, the experimental results on a 2.3 kW DFIG set up are also illustrated to demonstrate the efficacy of the scheme.     

Statistical distribution for wind power forecast error and its application to determine optimal size of energy storage system

Accurate wind power forecast is an important tool for wind farm to participate in day-ahead or hours-ahead energy markets. However, forecast errors with any methodology are so large that they cannot be neglected. The forecast error needs to be analyzed individually for single wind farm to estimate the impact of this error on trading wind energy in electricity market. Although forecast error is always assumed as normal distribution, it can be demonstrated that it is not proper with a simple statistical analysis. In this paper, a mixed distribution is proposed based on laplace and normal distribution to model forecast errors associated with persistence forecast for single wind farm over multiple timescales. Then the proposed distribution is used to estimate the penalties for prediction errors in the electricity market. Energy storage system (ESS) can smooth the wind power output and make wind power more “dispatchable”. A probabilistic method is proposed to determine optimal size of ESS for wind farm in electricity markets. The results indicate that the proposed distribution and probabilistic method is efficient to find optimal size of ESS.