A fuzzy control and neural network based rotor speed controller for maximum power point tracking in permanent magnet synchronous wind power generation system

When the wind speed changes significantly in a permanent magnet synchronous wind power generation system,the maximum power point cannot be easily determined in a timely manner.This study proposes a maximum power reference signal search method based on fuzzy control,which is an improvement to the climbing search method.A neural network-based parameter regulator is proposed to address external wind speed fluctuations,where the parameters of a proportional-integral controller is adjusted to accurately monitor the maximum power point under different wind speed conditions.Finally,the effectiveness of this method is verified via Simulink simulation.

Maximum Power Point Tracking in Variable Speed Wind Turbine Based on Permanent Magnet Synchronous Generator Using Maximum Torque Sliding Mode Control Strategy

The present study was carried out in order to track the maximum power point in a variable speed turbine by minimizing electromechanical torque changes using a sliding mode control strategy. In this strategy, first, the rotor speed is set at an optimal point for different wind speeds. As a result of which, the tip speed ratio reaches an optimal point, mechanical power coefficient is maximized, and wind turbine produces its maximum power and mechanical torque. Then, the maximum mechanical torque is tracked using electromechanical torque. In this technique, tracking error integral of maximum mechanical torque, the error, and the derivative of error are used as state variables. During changes in wind speed, sliding mode control is designed to absorb the maximum energy from the wind and minimize the response time of maximum power point tracking(MPPT). In this method, the actual control input signal is formed from a second order integral operation of the original sliding mode control input signal. The result of the second order integral in this model includes control signal integrity, full chattering attenuation, and prevention from large fluctuations in the power generator output. The simulation results, calculated by using MATLAB/m-file software, have shown the effectiveness of the proposed control strategy for wind energy systems based on the permanent magnet synchronous generator(PMSG).

Comprehensive review and performance evaluation of maximum power point tracking algorithms for photovoltaic system

A photovoltaic array is environmentally friendly and a source of unlimited energy generation.However,it is presently a costlier energy generation system than other non-renewable energy sources.The main reasons are seasonal variations and continuously changing weather conditions,which affect the amount of solar energy received by the solar panels.In addition,the non-linear characteristics of the voltage and current outputs along with the operating environment temperature and variation in the solar radiation decrease the energy conversion capability of the photovoltaic arrays.To address this problem,the global maxima of the PV arrays can be tracked using a maximum power point tracking algorithm(MPPT)and the operating point of the photovoltaic system can be forced to its optimum value.This technique increases the efficiency of the photovoltaic array and minimizes the cost of the system by reducing the number of solar modules required to obtain the desired power.However,the tracking algorithms are not equally effective in all areas of application.Therefore,selecting the correct MPPT is very critical.This paper presents a detailed review and comparison of the MPPT techniques for photovoltaic systems,with consideration of the following key parameters:photovoltaic array dependence,type of system(analog or digital),need for periodic tuning,convergence speed,complexity of the system,global maxima,implemented capacity,and sensed parameter(s).In addition,based on real meteorological data(irradiance and temperature at a site located in Addis Ababa,Ethiopia),a simulation is performed to evaluate the performance of tracking algorithms suitable for the application being studied.Finally,the study clearly validates the considerable energy saving achieved by using these algorithms.

Variable Parameter Nonlinear Control for Maximum Power Point Tracking Considering Mitigation of Drive-train Load

Since mechanical loads exert a significant influence on the life span of wind turbines, the reduction of transient load on drive-train shaft has received more attention when implementing a maximum power point tracking U+0028 MPPT U+0029 controller. Moreover, a trade-off between the efficiency of wind energy extraction and the load level of drive-train shaft becomes a key issue. However, for the existing control strategies based on nonlinear model of wind turbines, the MPPT efficiencies are improved at the cost of the intensive fluctuation of generator torque and significant increase of transient load on drive train shaft. Hence, in this paper, a nonlinear controller with variable parameter is proposed for improving MPPT efficiency and mitigating transient load on drive-train simultaneously. Then, simulations on FAST U+0028 Fatigue, Aerodynamics, Structures, and Turbulence U+0029 code and experiments on the wind turbine simulator U+0028 WTS U+0029 based test bench are presented to verify the efficiency improvement of the proposed control strategy with less cost of drive-train load. © 2017 Chinese Association of Automation.

Parasitic Effects on the Performance of DC-DC SEPIC in Photovoltaic Maximum Power Point Tracking Applications

This paper presents an analysis of the effect of parasitic resistances on the performance of DC-DC Single Ended Pri- mary Inductor Converter (SEPIC) in photovoltaic maximum power point tracking (MPPT) applications. The energy storage elements incorporated in the SEPIC converter possess parasitic resistances. Although ideal components significantly simplifies model development, but neglecting the parasitic effects in models may sometimes lead to failure in predicting first scale stability and actual performance. Therefore, the effects of parasitics have been taken into consideration for improving the model accuracy, stability, robustness and dynamic performance analysis of the converter. Detail mathematical model of SEPIC converter including inductive parasitic has been developed. The performance of the converter in tracking MPP at different irradiance levels has been analyzed for variation in parasitic resistance. The converter efficiency has been found above 83% for insolation level of 600 W/m2 when the parasitic resistance in the energy storage element has been ignored. However, as the parasitic resistance of both of the inductor has increased to 1 ohm, a fraction of the power managed by the converter has dissipated;as a result the efficiency of the converter has reduced to 78% for the same insolation profile. Although the increasing value of the parasitic has assisted the converter to converge quickly to reach the maximum power point. Furthermore it has also been observed that the peak to peak load current ripple is reduced. The obtained simulation results have validated the competent of the MPPT converter model.

Improved MPPT Control Based on the Reduction of Tracking Range

考虑到基于转矩调整的改进方法存在难以获取最优调整状态的问题，该文针对传统功率曲线法提出收缩风机转速的跟踪区间、减小跟踪路程的改进思路，以优化风机最大功率点跟踪的性能。在此基础上，设计出根据平均风速，周期性的调整起始发电转速的改进功率曲线法。其设计机理在于风速平均值恰好反映了风速及风能量集中分布的区间。因此，最优转速跟踪区间与平均风速存在数量上的直接关系而变得容易预估，且无需迭代搜索。与目前基于调整转矩的改进方法相比，该文所提方法不仅提高了风能捕获效率，且简单易行。最后，通过对模拟风速序列的仿真计算与比较分析，验证了该方法的有效性和先进性。

Maximum production point tracking method for a solar-boosted biogas energy generation system

Low biogas yield in cold climates has brought great challenges in terms of the flexibility and resilience of biogas energy systems. This paper proposes a maximum production point tracking method for a solar-boosted biogas generation system to enhance the biogas production rate in extreme climates. In the proposed method, a multi-dimensional R–C thermal circuit model is formulated to analyze the digesting thermodynamic effect of the anaerobic digester with solar energy injection, while a hydrodynamic model is formulated to express the fluid dynamic interaction between the hot-water circulation flow and solar energy injection. This comprehensive dynamic model can provide an essential basis for controlling the solar energy for digester heating to optimize anaerobic fermentation and biogas production efficiency in extreme climates. A model predictive control method is developed to accurately track the maximum biogas production rate in varying ambient climate conditions. Comparative results demonstrate that the proposed methodology can effectively control the fermentation temperature and biogas yield in extreme climates, and confirm its capability to enhance the flexibility and resilience of the solar-boosted biogas generation system.

Stochastic maximum power point tracking of photovoltaic energy system under partial shading conditions

A large portion of the available power generation of a photovoltaic (PV) array could be wasted due to partial shading, temperature and irradiance effects, which create current/voltage imbalance between the PV modules. Partial shading is a phenomenon which occurs when some modules in a PV array receive non-uniform irradiation due to dust, cloudy weather or shadows of nearby objects such as buildings, trees, mountains, birds etc. Maximum power point tracking (MPPT) techniques are designed in order to deal with this problem. In this research, a Markov Decision Process (MDP) based MPPT technique is proposed. MDP consists of a set of states, a set of actions in each state, state transition probabilities, reward function, and the discount factor. The PV system in terms of the MDP framework is modelled first and once the states, actions, transition probabilities, and reward function, and the discount factor are defined, the resulting MDP is solved for the optimal policy using stochastic dynamic programming. The behavior of the resulting optimal policy is analyzed and characterized, and the results are compared to existing MPPT control methods.

Novel power capture optimization based sensorless maximum power point tracking strategy and internal model controller for wind turbines systems driven SCIG

Under the trends to using renewable energy sources as alternatives to the traditional ones,it is important to contribute to the fast growing development of these sources by using powerful soft computing methods.In this context,this paper introduces a novel structure to optimize and control the energy produced from a variable speed wind turbine which is based on a squirrel cage induction generator(SCIG)and connected to the grid.The optimization strategy of the harvested power from the wind is realized by a maximum power point tracking(MPPT)algorithm based on fuzzy logic,and the control strategy of the generator is implemented by means of an internal model(IM)controller.Three IM controllers are incorporated in the vector control technique,as an alternative to the proportional integral(PI)controller,to implement the proposed optimization strategy.The MPPT in conjunction with the IM controller is proposed as an alternative to the traditional tip speed ratio(TSR)technique,to avoid any disturbance such as wind speed measurement and wind turbine(WT)characteristic uncertainties.Based on the simulation results of a six KW-WECS model in Matlab/Simulink,the presented control system topology is reliable and keeps the system operation around the desired response.

Thermal energy harvesting circuit with maximum power point tracking control for self-powered sensor node applications

We present a simple implementation of a thermal energy harvesting circuit with the maximum power point tracking（MPPT） control for self-powered miniature-sized sensor nodes. Complex start-up circuitry and direct current to direct current（DC-DC） boost converters are not required, because the output voltage of targeted thermoelectric generator（TEG） devices is high enough to drive the load applications directly. The circuit operates in the active/asleep mode to overcome the power mismatch between TEG devices and load applications. The proposed circuit was implemented using a 0.35-μm complementary metal-oxide semiconductor（CMOS） process. Experimental results confirmed correct circuit operation and demonstrated the performance of the MPPT scheme. The circuit achieved a peak power efficiency of 95.5% and an MPPT accuracy of higher than 99%.

Direct driven wind energy conversion system based on hybrid excitation synchronous machine

A novel direct-drive type wind power generation system based on hybrid excitation synchronous machine（HESM）is introduced in this paper.The generator is connected to an uncontrollable rectifier,and a fully controlled voltage-sourceinverter is used to connect the system to utility grid.An intermediate DC bus exists between the rectifier and inverter.A new control strategy is proposed which achieves the maximum power point tracking（MPPT） with the control of excitation current of HESM and stabilizes the DC link voltage with the control of inverter output current simultaneously.Specially-designed buck circuit is used to control the excitation current of HESM,and grid voltage-oriented vector control strategy is employed to realize the decoupling of the inverter output power.Simulation results and experiment in 3 kW lab prototype show an excellent static and dynamic performance of the proposed system.

OUTPUT MAXIMIZATION CONTROL FOR VSCF WIND ENERGY CONVERSION SYSTEM USING EXTREMUM CONTROL STRATEGY

The energy conversion optimization control strategy is presented for a family of horizontal-axis variablespeed fixed-pitch wind energy conversion systems,working in the partial load region.The system uses a variablespeed wind turbine(VSWT)driving a squirrel-cage induction generator(SCIG)connected to a grid.A new maximum power point tracking(MPPT)approach is proposed based on the extremum seeking control principles under the assumption that the wind turbine model and its parameters are poorly known.The aim is to drive the average position of the operation point close to optimality.Here the wind turbulence is used as search disturbance instead of inducing new sinusoidal search signals.The discrete Fourier transform(DFT)process of some available measures estimates the distance of operation point to optimality.The effectiveness of the proposed MPPT approach is validated under different operation conditions by numerical simulations in MATLAB/SIMULINK.The simulation results prove that the new approach can effectively suppress the vibration of system and enhance the dynamic performance of system.

Enhanced Perturb and Observe Control Algorithm for a Standalone Domestic Renewable Energy System

The generation of electricity,considering environmental and eco-nomic factors is one of the most important challenges of recent years.In this article,a thermoelectric generator(TEG)is proposed to use the thermal energy of an electric water heater(EWH)to generate electricity independently.To improve the energy conversion efficiency of the TEG,a fuzzy logic con-troller(FLC)-based perturb&observe(P&O)type maximum power point tracking(MPPT)control algorithm is used in this study.An EWH is one of the major electricity consuming household appliances which causes a higher electricity price for consumers.Also,a significant amount of thermal energy generated by EWH is wasted every day,especially during the winter season.In recent years,TEGs have been widely developed to convert surplus or unused thermal energy into usable electricity.In this context,the proposed model is designed to use the thermal energy stored in the EWH to generate electricity.In addition,the generated electricity can be easily stored in a battery storage system to supply electricity to various household appliances with low-power-consumption.The proposed MPPT control algorithm helps the system to quickly reach the optimal point corresponding to the maximum power output and maintains the system operating point at the maximum power output level.To validate the usefulness of the proposed scheme,a study model was developed in the MATLAB Simulink environment and its performance was investigated by simulation under steady state and transient conditions.The results of the study confirmed that the system is capable of generating adequate power from the available thermal energy of EWH.It was also found that the output power and efficiency of the system can be improved by maintaining a higher temperature difference at the input terminals of the TEG.Moreover,the real-time temperature data of Abha city in Saudi Arabia is considered to analyze the feasibility of the proposed system for practical implementation.

离网型风光储微电网控制策略研究

为了解决偏远地区电力供应不足的问题,笔者提出一种含风力发电、光伏发电及蓄电池储能的离网型风光储微电网系统。风力发电最大功率点跟踪(maximum power point tracking,MPPT)采用叶尖速比法的控制策略,光伏发电MPPT采用变步长扰动观察法的控制策略,蓄电池储能系统采用基于双闭环控制的充放电控制策略。结合广西地区实际风速及光照强度变化情况,利用MATLAB/Simulink平台对所提出的风光储微电网系统进行了建模及仿真,验证了所提系统的可靠性和控制策略的有效性。

永磁直驱风力发电机非奇异终端滑模控制

为提高永磁直驱风力发电系统的抗扰能力和控制精度,提出了一种扰动观测器与非奇异快速终端滑模控制相结合的最大功率跟踪控制策略。利用扰动观测器得到风力发电机的转矩变化,对控制器进行前馈补偿;采用非奇异快速终端滑模面提高控制器的动态性能,实现系统快速收敛,减少因扰动引起的抖振。仿真结果表明,所提策略在随机风速的情况下可以准确估计转矩变化,提高最大功率跟踪过程中的转速跟踪精度和风能利用率。

基于自适应粒子群优化算法的串联复合涡轮储能优化策略

针对发动机串联复合涡轮发电系统储能困难等问题,提出了一种基于自适应粒子群优化(SAPSO)算法的最大功率点追踪(MPPT)方法,增强发电系统功率的捕获能力。此外,采用混合储能系统(HESS)替代单一蓄电池储能,实现电能的高效、稳定存储。通过Matlab/Simulink软件,建立了基于发动机串联复合涡轮发电的储能优化控制仿真模型,对比分析了不同控制方法在设定工况下的功率追踪性能以及混合储能系统的储能特性。仿真结果表明,相较于传统扰动观测法(P&O)控制方法,在所提的SAPSO-MPPT方法下,发电功率提高了190 W,响应时间缩短了0.15 s。同时,HESS能够有效追踪母线上的需求功率,电能回收效率高达95.3%。最后,基于Y24型改装发动机台架搭建了串联复合涡轮发电系统实验平台,对所提储能优化控制策略的节油潜力进行了实验验证。结果表明,SAPSO-MPPT+HESS储能优化策略能够有效提高排气能量回收效率,优化后系统总热效率比原发动机提高了提高0.53个百分点。

开绕组无刷双馈风力发电机直接功率控制容错策略

针对无刷双馈发电机提出了一种控制绕组采用开绕组拓扑(OW-BDFG)的馈电方案,将三相控制绕组两端打开分别连接变流器构成双两电平变流器(D-TLCs)馈电拓扑,对机侧变流器功率器件IGBT因故障切除后的容错控制策略进行深入分析,提出了功率偏差比较直接功率控制(PEC-DPC)的D-TLCs电压空间矢量优化方案。对比分析了8/4极25kW样机的仿真及实验结果,表明:当机侧变流器1个或2个IGBT被切除后,所提OW-BDFG的PEC-DPC仍可实现变速恒频、最大功率点跟踪及单位功率因数控制,进一步提高了该发电机系统的可靠性和鲁棒性。

计及风电场的飞轮储能一次调频控制策略

随着新能源渗透率的提高,电力系统频率稳定性问题愈加严重。本文提出一种改进飞轮储能辅助风电场一次调频的控制策略,分析风储系统的频率特性和容量配置,风电场采用虚拟惯性控制参与一次调频。由于风电场的输出功率根据自然风速随机变化,可能会导致飞轮长期运行至较高或较低转速的状态,在风速骤变时甚至会引起飞轮转速越限。采用虚拟下垂控制结合模糊规则防止飞轮转速越限,从而弥补风电场在一次调频中的功率缺额。通过仿真分析及实验验证阶跃扰动和连续扰动的工况下的频率特性,得出改进控制策略在阶跃扰动和连续负荷扰动2种工况下最大频率偏差更小、响应速度更快的结论.

面向光伏能量收集应用的实时MPPT预估算法研究

对于环境中存在的各种类型能量源,其往往具有不同的阻抗特性以及输出功率范围。为了提高能量收集系统的能量萃取能力,合理的接口电路设计是关键。基于此,通过对环境中光伏(Photovoltaic,PV)能量源微弱直流特性以及高效率收集和转化的研究,在传统开路电压法(Open-Circuit Voltage,OCV)的基础上,结合输入电压纹波控制,提出了一种可实时最大功率点追踪(Maximum Power Point Tracking,MPPT)的预估算法。该预估算法根据能量源的输出特性,采用了分数开路电压法(Fractional Open-Circuit Voltage,FOCV),并根据纹波大小动态调节变换器的工作模式,实现阻抗匹配。为了尽可能减小因采样带来的能量损失,采用可片上全集成的较小的采样电容,并逐周期的进行开路电压采样和计算,实现了对源功率变化的高精度追踪。仿真结果表明,所提出的追踪算法能够实时监测能量源的状态,具有高的追踪速度和追踪精度,且采样时间仅需100 ns。能量源功率在1μW~10 mW范围内变化时,最短的追踪时间仅需4.37μs,追踪精度可达99.7%。