100results about "Control algorithms type" patented technology

A fleet of vessels attached together longitudinally (rows), and transversely (columns) and operating in unison convert wave energy to electrical energy which is stored in either a chemical or electrical form. The vessels when detached from the fleet provide transportation to coastal or by navigable waterway ports of call for distribution to market centers. Both wind wave and swell wave energy conversion is performed by use of the differential motion between the vessels. Means are provided for the energy conversion systems to adapt to changes in wave direction, wave length, amplitude, and phase. Such vessels are self powered for off shore or inland waterway navigation, either singularly or in multiples, with which to deliver energy to other sea going vessels or to land based ports of call. Two or more of such vessels are capable of using the energy of waves during the delivery process. The fleet can maintain a designated geographical location by dynamic positioning. Alternatively, the fleet may maintain its designated position by moorage of a designated centrally located vessel in the fleet to a permanent anchoring system when operating at appropriate depths.

An arrangement for generating a control signal for controlling a power output of a power generation system, such as a wind turbine, is provided. The power output is supplied to a utility grid. The arrangement includes a first input terminal for receiving a first input signal indicative of an actual grid frequency of the utility grid, a control circuit for generating the control signal, and an output terminal to which the control signal is supplied. The control circuit includes a bang-bang controller for generating a first power signal being indicative of a predefined amount of power to be added to the power output of the power generation system. The bang-bang controller is adapted to be activated when the first input signal falls below a first predefined threshold. The control signal depends on the first power signal.

A fleet of vessels attached together longitudinally (rows), and transversely (columns) and operating in unison convert wave energy to electrical energy which is stored in either a chemical or electrical form. The vessels when detached from the fleet provide transportation to coastal or by navigable waterway ports of call for distribution to market centers. Both wind wave and swell wave energy conversion is performed by use of the differential motion between the vessels. Means are provided for the energy conversion systems to adapt to changes in wave direction, wave length, amplitude, and phase. Such vessels are self powered for off shore or inland waterway navigation, either singularly or in multiples, with which to deliver energy to other sea going vessels or to land based ports of call. Two or more of such vessels are capable of using the energy of waves during the delivery process. The fleet can maintain a designated geographical location by dynamic positioning. Alternatively, the fleet may maintain its designated position by moorage of a designated centrally located vessel in the fleet to a permanent anchoring system when operating at appropriate depths.

Monitoring and assessing power performance changes of one or more wind turbines of a wind farm. For each wind turbine to be monitored, a group of reference wind turbines is defined. During a training period a transfer function is generated for each monitored wind turbine. The transfer function establishes a relationship between locally measured wind speeds at each of the reference wind turbines and the power performance data for the monitored wind turbine obtained during the training period. During one or more subsequent test periods, measured power performance data for the monitored wind turbines is compared to predicted power performance data. The predicted power performance data is obtained by means of the locally measured wind speeds at the corresponding reference wind turbines during the test period(s) and the previously generated transfer function for the monitored wind turbine. This allows even small and / or gradual power performance degradation to be detected.

A system and method for supporting a wave-energy generation device that features an adaptive floating platform, which under computer control, can autonomously adjust at least one of its design elements in order to increase or decrease the responsiveness of the floating wave-energy support system to varying wave-energy conditions. By, thereby, being able to tune the wave-energy support platform for varying wave conditions, a greater amount of power can be produced from a wave energy conversion generator selected to be compatible with the adaptive floating platform.

The invention provides a multi-model prediction control method and system for a draught fan, a storage and a controller. The multi-model prediction control method for the draught fan comprises the steps that linearized models of the draught fan at all wind speed points are acquired, and dynamic differences among the linearized models of the wind speed points are acquired according to the clearance metric; wind speed ranges are divided according to the dynamic differences, and linearized model sets, formed by the linearized models of the corresponding wind speeds, of the wind speed ranges are built; optimal control input of a prediction controller, for draught fan control, of each wind speed range is acquired according to the linearized model sets of the wind speed ranges; the corresponding prediction controller is called according to switching laws of the linearized models to acquire the real-time optimal control input. Accordingly, overall working condition control over a draught fan system can be achieved, especially the complete low-redundancy linearized model sets are built according to the clearance metric, therefore, the multi-model prediction control effect of the draught fan system is improved, and the method is suitable for overall working condition control over an independent or distributed or parallel wind generation set.

A wind turbine is disclosed which comprises a control system configured to execute at least one ice removal routine which comprises a heating stage of at least one of the blades (3), and a mechanical removal ice stage. A wind turbine removing ice method is also disclosed which comprises a stage wherein the presence of ice is detected on at least one of the blades and, once said presence of ice is detected, comprises a stage wherein at least one ice removal routine is activated which comprises, in turn, a heating stage of at least one of the blades and a mechanical removing ice stage on at least said blade.

The invention discloses a blade-root bolt fracture fault detection method which comprises the steps of S01, selecting multiple characteristics for preprocessing, standardizing three variables describing the running status of a blade by adopting mean value-variance, then summing, and outputting; S02, using data without bolt fracture fault for training an LSTM normal model; using data before bolt fracture fault occurrence for training an LSTM fault model; putting the data of S01 into the LSTM normal model and the LSTM fault model, and extracting an error vector characteristic; S03, substitutingthe error vector characteristic into a random forest algorithm for training a random forest model; and substituting fan operation data into the random forest algorithm model for carrying out fault diagnosis. The invention further discloses a computer readable storage medium stored with a computer program, and the program implements the method when being executed by a processor. The detection method and the medium provided by the invention have the advantages of high automation degree, high detection accuracy, cost reduction and the like.

A wind turbine generator derives the gradient of a change in output power of a generator that generates power by rotation of a wind turbine rotor, and determines an increase / decrease in the output power of the generator on the basis of the derived gradient of the change in output power. Then, when the frequency of a utility grid has dropped, power control is performed on the basis of the determination results. Therefore, a decrease in the amount of power supplied to the utility grid can be more effectively compensated for by accurately detecting output power fluctuations of the generator, using a simple configuration.

The invention discloses a method for detecting the clearance value of blades of a wind driven generator set based on a 77 GHz millimeter wave radar, and relates to the technical field of new energy. According to the method, the wind driven generator set is digitized, a special coordinate system is established, the 77GHz millimeter wave radar is adopted as a core sensor, the radar with a special wave beam is installed at the bottom of the tail of a wind driven generator cabin, the FOV direction of the radar points to a fixed airspace, when the blades rotate to the area, reflected waves are subjected to data acquisition, a reflection point is formed through a radar signal processing correlation algorithm, and the blade attitude is fitted by using algorithms such as extended Kalman, curve fitting, data fusion in combination with information such as rotating speed and pitch angle; and the real-time clearance value is calculated by combining the simulation information of the set, the risk level of 'tower colliding 'of the blades is evaluated, and a final result is transmitted to a main control system in real time through a controller to finish the control of the wind driven generator.

The invention discloses an ELM based maximum wind energy capturing method which comprises the following steps: obtaining effective wind speed information of a unit within certain time segment and theunit output data related to the effective wind speed within a corresponding time segment, removing the correlation of the obtained unit output data, carrying out normalization operation, constructinga training set of ELM, adopting the training set to determine an ELM model to obtain a wind speed estimation model, giving an effective wind speed value on time by the model to further calculate the revolving speed tracking error, and giving a continuous and maximum wind energy capturing controller. According to the ELM based maximum wind energy capturing method, the obtained maximum wind energy capturing controller can eliminate the buffeting phenomenon, so that the load of a drive system is reduced, the service life of the unit is prolonged, the defect that the traditional optimal torque algorithm is lower in convergence rate is overcome, the wind energy capturing efficiency is improved, the method is simple and easy to do, the implementation cost is low, and the parameters to be debugged are fewer; and compared with the traditional optimal torque control algorithm, the unit productivity can be improved to improve the economic benefit of a wind farm.

The invention discloses a self-adaptive internal mold vibration control method of an intelligent fan blade based on grey information optimization. The self-adaptive internal mold vibration control method based on grey information theory optimization is adopted for uncertain factors existing in an intelligent fan blade vibration system in a complex operating environment, that is, the blade vibration system under the influence of uncertain factors is accurately identified by using a grey incidence optimization differential evolution identifying way, so that the internal mold vibration process is identified more ideally and accurately; and the parameters of a self-adaptive internal mold vibration controller for a blade is self-adaptively optimized and adjusted by using a grey planning theory, so that the dynamic characteristics and the robustness of a control system are beneficial for being improved, and a high-performance intelligent fan blade self-adaptive vibration control effect can be obtained when a closed-loop system overcomes the influence of uncertain factors. The self-adaptive internal mold vibration control method based on grey information optimization, provided by the invention, can overcome the influence of uncertain factors of the intelligent fan blade in the complex operating environment.

The invention discloses pneumatic imbalance correction method, device and equipment for blades of a wind generating set. The method comprises the steps of acquiring waving direction bending moment values of root parts of the three blades of the wind generating set acquired through a load sensor; calculating a deviation value between each waving direction bending moment value and a datum load; according to the deviation values, calculating a correction pitch angle corresponding to each blade; and adding each correction pitch angle and a target control pitch angle of each corresponding blade, and carrying out pitch control on the wind generating set. According to the pneumatic imbalance correction method, the device and the equipment for the blades of the wind generating set provided by the invention, by utilizing blade root load measurement, the pitch angles of the blades are online corrected, and the pneumatic imbalance of the blades is reduced, so that the pneumatic imbalance of the blades and the influences brought to unit operation safety and generating efficiency due to the conditions such as blade processing accuracy, installation accuracy and blade surface contamination are reduced, and the wind generating set can stably and high-efficiently run.

A wind turbine generator derives the gradient of a change in output power of a generator that generates power by rotation of a wind turbine rotor, and determines an increase / decrease in the output power of the generator on the basis of the derived gradient of the change in output power. Then, when the frequency of a utility grid has dropped, power control is performed on the basis of the determination results. Therefore, a decrease in the amount of power supplied to the utility grid can be more effectively compensated for by accurately detecting output power fluctuations of the generator, using a simple configuration.

The invention provides a universal windmill with adjustable propeller length, and relates to the field of wind application equipment. The universal windmill comprises a support, propellers, propeller heads, a rotating shaft and propeller length control systems; two to four propellers are uniformly distributed around the rotating shaft; the cross sections of the propellers are provided with wing profiles in form of wings with camber; the propellers are obliquely arranged on the support by the propeller heads, so that a V-shaped structure can be formed; the gradient, eccentricity and mounting attack angle of each propeller can be adjusted by each propeller head, therefore, the propellers of the windmill can be kept in the best operating state; the propellers of the windmill are divided into two to three sections which are integrally nested and can be stretched and contracted just like a telescopic antenna of a radio receiver, therefore, the propellers can be contracted during high wind and stretched during low wind, and as a result, the output power or the rotating speed can be stabilized, the utilization scope of the wind energy is expanded, and the safety of the windmill in operation can be ensured. The application of the universal windmill is as follows: 1, the universal windmill can be used as a vertical axis wind turbine to be applied to a wind power plant; 2, the universal windmill also can be used as a water turbine to be applied to a dam-free power station or used for tidal power generation; and 3, the universal windmill also can be used as a toy for a child.

The invention relates to a MPPT method of a SMESC wind power system based on IIWO optimization. The method comprises the following steps of: initializing an intrusion weed algorithm parameter; substituting the randomly generated initial solutions Kp and rho s into a constructed Simulink model to calculate fitness values corresponding to each weed, outputting a fan control amount, and feed backingthe optimal speed in the current generation for the maximum power tracking of the fan by the SMESC; sorting the fitness values, and selecting the number of seeds allowed by the maximum number of populations for breeding and regeneration to produce offspring seeds; calculating the number of seeds produced by each weed according to the fitness values; substituting the position information of the offspring weed seeds into the SMESC parameter optimization model, outputting and generating a new control amount and fitness values of the offspring seed; judging whether a termination condition is satisfied; and outputting the optimal Kp and rho s if the termination condition is satisfied, wherein the corresponding power is the maximum power output by the fan.

The invention discloses a power control method of a wave power generation device based on Fourier analysis and an improved grey wolf algorithm. On the basis of reserving the most essential characteristic of a grey wolf optimization algorithm, a brand new elite wolf searching policy and a wolf pack integral unfolding policy are added, and an encirclement ring formingpolicy, a wolf pack prey searching mode and a wolf pack structure are optimized, so that the improved grey wolf algorithm can be prevented from falling into local optimum as a result of hydrodynamic force nonlinearity of a floater.A Fourier analysis method is introduced to decompose ocean incident waves and respond to moving parts of a motor, the corresponding optimum motor control parameters are solved for wave components within a floater capturing frequency range by means of the improved grey wolf algorithm, and the carried power is captured to the maximum extent, so that maximum power point tracing is achieved.

The invention discloses an online optimization method and system for the optimal gain parameter of a wind generating set. The online optimization method comprises the steps that the optimization rangeand the optimization step length for the optimal gain parameter are determined; the performance indexes of all parameters within the optimization range for the optimal gain parameter are calculated through an exhaustion method, and an optimal gain parameter value corresponding to the maximum performance index is found out by comparing the values of the performance indexes and is used as the optimal gain parameter value of the current cycle; a list circulation counting value and an optimizing threshold are determined, and an optimizing list is circulated to obtain the optimal gain parameters of multiple cycles; and whether or not an optimization ending condition is met is judged, the steps are repeated if not, and the final gain parameter of the wind generating set is obtained if yes. By adoption of the online optimization method and system for the optimal gain parameter of the wind generating set, the accuracy of the optimal gain parameter of the wind generating unit is improved whilethe hardware cost is not increased, the rotating speed and torque curve of the wind generating unit is optimized, and the generating capacity of the wind generating set is improved.

The invention provides a control method based on slip form extreme searching. The control method is applied to control over a wind power generation system to achieve maximum power tracking. The control method comprises the steps that in the current state detection step, the current power and the current rotation speed of a draught fan are detected; in the parameter matching step, a gain parameter value is matched from a pre-constructed parameter table according to the current power and the current rotation speed; in the maximum power tracking step, the gain parameter value is input into a controller, the gain parameter is optimized by adopting the pre-constructed optimization function according to the pre-determined slip form extreme searching range and the pre-constructed target function, accordingly, the optimal gain parameter value is obtained, and the wind power generation system tracks the maximum power. According to the provided control method, the gain parameter value is matched from the pre-constructed parameter table and then is optimized through the optimization function, the wind power generation system tracks the maximum power, the wind power generation system can be controlled in real time, and the response speed is high.

The invention relates to a blade leading edge corrosion monitoring method and system. The blade leading edge corrosion monitoring method comprises the following steps that a wind sweeping signal of a blade is collected through a sound sensor; through a condition filtering module, sound data, meeting conditions, in the operation process of a draught fan are obtained at fixed intervals; quality detection is conducted on the sound data through a data quality processing module, and the sound data with poor data quality are screened out; and whether blade leading edge corrosion exists or not is identified, the severity degree of the corrosion is evaluated, and early warning information is given out when the corrosion degree exceeds a set threshold value. By means of the blade leading edge corrosion monitoring method and system, the blade leading edge corrosion based on the machine position level can be recognized in time, alarm information is provided before the blade leading edge corrosion damages a structural layer, and targeted and timely maintenance is supported.

The invention discloses a self-adaptive dynamic surface control method for a variable pitch system of a wind driven generator, and relates to the field of variable pitch control of wind turbines. Firstly, due to the fact that a wind turbine system has factors such as time varying and nonlinearity, an accurate high-order system model is difficult to establish, linear order increasing is conducted on an original wind turbine system model, and a high-order feedback variable is obtained; then, an extended observer is adopted to observe system parameters after order increasing, so that the change of the high-order system parameters can be observed more accurately; meanwhile, due to the influence of external factors, part of uncertain parameters, unknown interference and the like exist in a high-order system, an adaptive algorithm is proposed to be adopted for approximation, and therefore real-time compensation of the system model is achieved; and finally, a system control law is derived through a dynamic surface algorithm, so that the whole system meets the requirements.

The invention discloses a vertical axis wind turbine with a protective sleeve. The vertical axis wind turbine with the protective sleeve comprises a power generation device and a protective device. According to the power generation device, a generator, a rotary speed sensor and a PLC are arranged in a barrel. The rotary speed sensor detects the rotary speed of a wind turbine body and outputs pulse signals to the PLC. According to the protective device, an installing hole is formed in the outer side surface of the protective sleeve, installing plates are arranged on the parts, on two sides of the installing hole, of the protective sleeve, and gears connected rotationally are arranged in the installing plates on two sides. Driving motors on the outer sides of the installing plates drive the gears to rotate. Racks engaged with the gears are arranged on the outer side surface of a protective pillar and the portion, extending to the barrel, of the protective pillar. The PLC controls the driving motors to operate through driving interfaces. According to the vertical axis wind turbine with the protective sleeve, the whole power generator unit system is controlled by the PLC, the PLC reads the rotary speed of blades in real time and controls the driving motors so that the protective sleeve can move upwards or downwards, the rotary speed is kept in a stable state, and therefore the purposes of controllable rotary speed, safety, reliability and durability are realized.

The invention discloses an adaptive internal model vibration control method based on gray information optimization for intelligent fan blades. The method aims at various uncertain factors existing in the vibration system of intelligent fan blades in a complex operating environment, and adopts a method based on gray information theory optimization. The self-adaptive internal model vibration control method uses the differential evolution identification method of gray relational optimization to accurately identify the blade vibration system under the influence of uncertainty, making the identification of the internal model vibration process more ideal and accurate; The parameters of the modal vibration controller are adaptively optimized and adjusted, which is conducive to improving the dynamic characteristics and robustness of the control system, so that the closed-loop system can achieve high-performance adaptive vibration control of intelligent fan blades while overcoming the influence of uncertain factors. Through the present invention, the gray optimization self-adaptive internal model vibration control method provided can overcome the influence of multiple uncertain factors of intelligent fan blades in a complex working environment.

A method for controlling an electrical drive of an electrically driven air compressor of a motor vehicle and a corresponding control circuit. A prevailing load torque of the air compressor that is applied at a drive shaft of the compressed air compressor is estimated as a function of at least one operating parameter and is fed forward as an estimated disturbance variable to the control circuit of the electrical drive to reduce a control error produced as a result of the prevailing load torque.

The invention discloses a fan damping adaptive control method based on PSO optimization and a controller thereof. The method comprises the following steps of 1, designing a damping controller mathematical model, and initializing the frequency and the damping ratio; 2, modifying damping controller parameters to obtain drive chain damping; 3, acquiring particle speed; 4, obtaining a particle historical optimal position; 5, acquiring a particle position; and 6, judging whether the optimal value of the allowable range is judged according to the damping ratio error; and obtaining the optimal valueof the damping controller parameters through the PSO algorithm, finding the optimal value of the damping controller parameter through the PSO algorithm, and finally achieving the required transmissionchain damping value after the set damping controller adds the torque ring. The fan damping adaptive control method is simple in algorithm, easy to implement, good in running speed and low in calculation amount, and the model performance and stability can be guaranteed.

The invention provides a method and device for adjusting the position of a minimum pitch angle of blades of a wind turbine generator. The method comprises the following steps of obtaining the output power when the wind turbine generator runs at the minimum pitch angle at a predetermined wind speed, wherein the predetermined wind speed is lower than a rated wind speed enabling the wind turbine generator to normally run; and when the output power is smaller than the optimal output power that the wind turbine generator runs at the minimum pitch angle at the predetermined wind speed, and adjustingthe position of the minimum pitch angle in a preset range, so as to enable the output power to approach or be equal to the optimal output power. Through the adoption of the method and the device disclosed by the invention, the error of the position of the minimum pitch angle caused by the processing, mounting and debugging of the wind turbine generators can be effectively eliminated, and the method is convenient for subsequent blade changing operation of the wind turbine generator to provide an accurate blade changing standard.

The present disclosure provides a method and system for calculating aerodynamic force of a wind turbine airfoil under different turbulence intensities. The method of the present disclosure includes: calculating a lift coefficient and a drag coefficient according to measured wind pressure, performing function fitting to obtain a fitted lift coefficient model and a fitted drag coefficient model at the different turbulence intensities, and selecting a corresponding fitted lift coefficient model and drag coefficient model according to a turbulence intensity on a wind turbine to be measured, to directly calculate a lift coefficient and a drag coefficient for the aerodynamic force of the airfoil.

The invention discloses a vertical axis wind power generation testing device based on distributed detection and data judgment and measurement. The device is mainly composed of a field measuring and processing device and an upper computer intelligent display device. The field measuring and processing device comprises an aerodynamic measurement module, a generated power measurement module, a vertical axis polarization measurement module, an electromagnetism and noise measurement module and a data monitoring and processing module. The interior of a microprocessor of the data monitoring and processing module has a data exception judgment and measurement algorithm so that whether measured data are abnormal or not can be judged. Zigbee wireless communication is adopted in the field measuring and processing device, and power is supplied in a wind-solar storage manner. The field measuring and processing device and the upper computer intelligent display device conduct WiFi wireless communication with each other. The vertical axis wind power generation testing device based on distributed detection and data judgment and measurement has the characteristics of being convenient to mount, reliable in testing, modular in function, flexible in networking, friendly in interface, easy to maintain and the like through the technologies such as multi-sensor detection, wireless network communication and multi-microprocessor operation.