Classifications

• • H—ELECTRICITY
  • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
  • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
  • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
  • H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
  • H02J3/241—The oscillation concerning frequency
• • H—ELECTRICITY
  • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
  • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
  • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
  • H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
• • H—ELECTRICITY
  • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
  • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
  • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
  • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]

Definitions

• the invention relates to the technical field of frequency modulation control, and in particular to a primary frequency modulation control system for small disturbance thermal power units.
• Power system frequency is a frequently changing parameter and is also the basis for stable operation of the power system. In the actual operation of the power system, when the power consumption does not match the power supply, it can cause the frequency of the power system to appear a small component with a small change and a short fluctuation period. This component is the frequency disturbance of the power system. When the power is detected When the frequency of the system is disturbed, the primary frequency regulation control strategy of thermal power units needs to be used to correct the frequency of the power system.
• CN112350344A proposes an energy storage system-thermal power unit joint frequency modulation control method that considers frequency modulation performance assessment.
• This method obtains the basic status of the joint frequency modulation unit at a certain time in the current frequency modulation cycle; based on the index calculation rules of the frequency modulation unit participating in the frequency modulation auxiliary service Divide and determine the working period of the joint frequency modulation unit; obtain the control target active power of each working period for the different working periods of the joint frequency modulation unit, and obtain the target active power of the energy storage system by cooperating with the active power of the thermal power unit; comprehensively Considering the power limit and capacity limit of the energy storage system, the target active power of the energy storage system is corrected to obtain the final active power of the energy storage system to achieve the purpose of time-division frequency modulation control.
• CN110378624B proposes a method and system for calculating primary frequency regulation indicators of thermal power units based on trend extraction. This method searches the actual power of thermal power units and historical data of grid frequency based on the characteristic quantified values of the primary frequency regulation data segments of thermal power units to obtain the primary frequency regulation of thermal power units.
• CN110912209B proposes a method, device and medium for optimizing frequency regulation under the thermal power unit machine following mode.
• This method obtains the frequency regulation of the thermal power unit in real time after the thermal power unit is running in the machine following mode and the thermal power unit performs a frequency modulation action.
• the actual value of the main steam pressure change the set value of the main steam pressure corresponding to the coordinated side main steam pressure automatic control module to the actual value of the main steam pressure until a frequency modulation action is completed, or until the thermal power plant
• the present invention provides a primary frequency modulation control method for small disturbance thermal power units.
• the purpose is to extract the signal characteristics of the power system frequency signal at different scales by using a multi-scale decomposition method, and to separate the signal from the noise through corrosion and expansion processing.
• a multi-scale frequency signal of a pure power system with better robustness is formed.
• the frequency modulation parameters of the thermal power unit with better robustness can be obtained; an adaptive small-disturbance thermal power unit primary frequency modulation parameter control can be constructed model, using the improved quantum particle swarm algorithm to optimize and solve the constructed adaptive small disturbance thermal power unit primary frequency regulation parameter control model, by inputting the robustly adjusted power system frequency signal into the optimal adaptive small disturbance thermal power unit primary
• the model outputs the current frequency modulation parameters of the thermal power unit, performs frequency modulation control on the thermal power unit based on the current frequency modulation parameters of the thermal power unit, and corrects the frequency of the power system.
• the present invention provides a primary frequency modulation control method for small disturbance thermal power units, including the following steps:
• S1 Collect power system frequency signals and preprocess the collected signals, and perform robust adjustment processing on the preprocessed power system frequency signals.
• Multi-scale signal conditioning based on morphological analysis is a robust adjustment processing method
• step S3 Collect a large number of robustly adjusted power system frequency signals with disturbances and corresponding frequency modulation parameters of thermal power units as a training set according to step S1, and use the improved quantum particle swarm algorithm to control the primary frequency modulation parameters of the adaptive small-disturbance thermal power unit.
• the model is optimized and solved to obtain the optimal adaptive small-disturbance thermal power unit primary frequency regulation parameter control model;
• step S4 Detect the frequency disturbance of the power system.
• the model outputs the current frequency modulation parameters of the thermal power unit, and performs frequency modulation control on the thermal power unit based on the current frequency modulation parameters of the thermal power unit.
• step S1 the power system frequency signal is collected and the collected signal is preprocessed, including:
• the sensors are used to collect power system frequency signals; the power system frequency signals x(t) are collected, where t ⁇ 0,1,2,...,T ⁇ , t represents Based on the timing information of the power system frequency signal x(t), perform noise reduction preprocessing on the collected power system frequency signal x(t) to obtain the preprocessed power system frequency signal x'(t).
• the process of noise processing is:
• q(x(t),a) represents the wavelet coefficient of the power system frequency signal x(t) at scale a;
• Delete the wavelet coefficients smaller than the wavelet threshold ⁇ retain the wavelet coefficients greater than or equal to the wavelet threshold ⁇ , use the wavelet inverse transform method to reconstruct the retained wavelet coefficients into noise reduction signals, and use the noise reduction signal as the preprocessed power system frequency signal x'(t), where the formula of the wavelet inverse transform method is:
• q(x(t),a') is the retained wavelet coefficient, and a' is the scale of the retained wavelet coefficient
• x'(t) is the preprocessed power system frequency signal.
• step S1 a robust adjustment process is performed on the preprocessed power system frequency signal, where multi-scale signal adjustment based on morphological analysis is a robust adjustment process, including:
• g m is a structural element, m ⁇ 0,1,2,...,M ⁇ .
• the selected structural element is a one-dimensional discrete vector, and the length dimension of the discrete vector is T+1.
• y i (t) is the power system frequency signal after robust adjustment of the i-th group of weight coding vectors
• the power system frequency signal y(t) with the smallest error value after robust adjustment is selected as the final processed signal.
• the multi-scale decomposition method is used to extract the signal characteristics of the power system frequency signal at different scales, and the corrosion expansion process is used to extract the signal characteristics of the power system frequency signal at different scales.
• the signal is separated from the noise to form a pure power system multi-scale frequency signal with better robustness.
• an adaptive small-disturbance thermal power unit primary frequency regulation parameter control model is constructed, including:
• the thermal power unit frequency regulation parameters include the rotational speed parameters of the thermal power unit, combustion Temperature parameters, by adjusting the rotation speed and heating temperature of the thermal power unit, change the thermal energy storage of the boiler of the thermal power unit, adjust the frequency of the power system, and adjust the frequency of the interfered power system to a normal value;
• the adaptive small-disturbance thermal power unit primary frequency modulation parameter control model consists of L residual units and a fully connected layer, in which the fully connected layer is a Softmax function, used to output the frequency modulation parameters of the thermal power unit, in which the jth residual unit
• r j represents the output result of the jth residual unit, j ⁇ 1,2,3,...,L ⁇ , r 0 represents the input robustly adjusted power system frequency signal, ⁇ j is the jth residual
• C 1 ( ⁇ ) means performing a convolution operation on the input value, and the convolution kernel size is 1 ⁇ 1;
• SC( ⁇ ) represents residual mapping.
• the residual unit consists of two convolution layers.
• the residual mapping operation is to perform two convolution processes on the input value.
• the convolution kernel size is 3 ⁇ 3;
• the output of the Lth residual unit is used as the input of the fully connected layer.
• step S3 a large number of robustly adjusted power system frequency signals with disturbances and corresponding fire signals are collected.
• the frequency regulation parameters of the motor unit are used as a training set, including:
• step S1 a large number of robustly adjusted power system frequency signals with disturbances and corresponding thermal power unit frequency modulation parameters are collected as training set Data.
• data k is the kth set of training data in the training set Data, and K represents the total number of sets of training data in the training set Data;
• y k (t) represents the robustly adjusted power system frequency signal with disturbance in data k ;
• par 1,k represents the thermal power unit speed parameter corresponding to y k (t)
• par 2,k represents the combustion temperature parameter of the thermal power unit corresponding to y k (t)
• by performing (par 1,k ,par 2 , k ) can make the power system frequency with small disturbance noise return to the normal frequency.
• step S3 the improved quantum particle swarm algorithm is used to optimize and solve the constructed adaptive small disturbance primary frequency regulation parameter control model of thermal power units to obtain the optimal adaptive small disturbance primary frequency regulation parameter control model of thermal power units, include:
• the improved quantum particle swarm algorithm was used to optimize and solve the adaptive small-disturbance thermal power unit primary frequency regulation parameter control model.
• the weight parameters of different residual units in the model were obtained by solving the problem.
• the obtained weight parameters were used as model parameters to obtain the optimal
• thermo power unit speed parameter generated by the model based on y k (t) and the weight parameter ⁇ is the combustion temperature parameter of the thermal power unit generated by the model based on y k (t) and the weight parameter ⁇ ;
• U n (q) is the position representation of the n-th quantum particle in the q-th iteration.
• the position representation of each quantum particle corresponds to the weight parameter of an adaptive small-disturbance thermal power unit primary frequency modulation parameter control model.
• the position representation is The number of dimensions is L dimension, u nL represents the position coordinate of the n-th quantum particle in the L-th dimension, corresponding to the weight parameter of the L-th residual unit;
• S36 Record the historical optimal position U n (best) of any n-th quantum particle from the beginning of iteration to the current q-th iteration, and record the historical optimal position U of the quantum particle swarm from the beginning of iteration to the current q-th iteration. (best), where the historical optimal position is the position representation of the quantum particle with the smallest fitness value from the beginning of the iteration to the current q-th iteration;
• rand(0,1) is a random number between 0 and 1;
• ⁇ is the contraction and expansion factor, set to 0.2;
• detecting frequency disturbance of the power system in step S4 includes:
• Sensors in the power system collect the power system frequency signal X(t) in real time and calculate the disturbance value of the real-time power system frequency signal:
• t 0,1,2,...,T ⁇ , t represents the timing information of the power system frequency signal
• R(X(t)) represents the disturbance value of the real-time power system frequency signal
• step S4 when a frequency disturbance is detected in step S4, the current robustly adjusted power system frequency signal is collected, and the collected signal is input into the optimal adaptive small-disturbance thermal power unit primary frequency regulation parameter control model. , the model outputs the current frequency modulation parameters of the thermal power unit, and performs frequency modulation control on the thermal power unit based on the current frequency modulation parameters of the thermal power unit, including:
• the current power system frequency signal X(t) is robustly adjusted according to the method of step S1, and the robustly adjusted power system frequency signal Y(t) is input to the optimal adaptive small disturbance
• the model outputs the current thermal power unit frequency regulation parameters, and performs frequency regulation control on the thermal power unit based on the current thermal power unit frequency regulation parameters to correct the frequency fluctuation of the power system.
• the present invention also provides a primary frequency regulation control system for small disturbance thermal power units, which is characterized in that the system includes:
• the signal acquisition and processing module is used to collect power system frequency signals and preprocess the collected signals, and perform robust adjustment processing on the preprocessed power system frequency signals;
• Frequency disturbance detection module used to detect frequency disturbances in power systems
• the frequency modulation parameter acquisition device is used to construct an adaptive small-disturbance thermal power unit primary frequency modulation parameter control model.
• the improved quantum particle swarm algorithm is used to optimize and solve the constructed adaptive small-disturbance thermal power unit primary frequency modulation parameter control model.
• the robustly adjusted power system frequency signal is input into the optimal adaptive small-disturbance thermal power unit primary frequency regulation parameter control model.
• the model outputs the current thermal power unit frequency regulation parameters, and adjusts the thermal power unit based on the current thermal power unit frequency regulation parameters. Perform FM control.
• an electronic device which includes:
• a memory to store at least one instruction
• the present invention also provides a computer-readable storage medium.
• the computer-readable storage medium stores at least one instruction.
• the at least one instruction is executed by a processor in an electronic device to implement the above.
• this solution proposes a robust adjustment method for power system frequency signals.
• the flow of the robust adjustment process is: constructing a multi-scale range signal conditioning filter; performing floating-point number encoding on the weight w b of different scales b, and obtaining several sets of coding vectors, where b ⁇ 1,2,...,B ⁇ , B is the number of scale ranges,
• the preprocessed power system frequency signal x'(t) is used as the input of the multi-scale adjustment signal filter.
• the multi-scale adjustment signal filter performs continuous erosion and expansion operations on the input value to obtain filters of different scales b.
• b ⁇ 1,2,...,B ⁇ where the filtering formula of the multi-scale range adjustment signal filter is:
• w i,B is the weight of the adjustment signal filter in the multi-scale range of the filter decomposition result of scale b, w i,B Belongs to the i-th group of weight encoding vectors
• g m is the structural element, B ⁇ 0,1,2,...,B ⁇ .
• the selected structural element is a one-dimensional discrete vector, and the length dimension of the discrete vector is T+ 1.
• the power system frequency signal y(t) after robust adjustment processing with the smallest error value is selected as the final processed signal.
• the signal characteristics of the power system frequency signal at different scales are extracted using multi-scale decomposition methods, and the signal is separated from the noise through corrosion and expansion processing to form a pure power system multi-scale frequency signal with better robustness.
• the frequency modulation parameters of the thermal power unit with better robustness can be obtained.
• this scheme constructs an adaptive small-disturbance thermal power unit primary frequency regulation parameter control model, in which the input of the model is the robustly adjusted power system frequency signal, and the model output is the thermal power unit frequency regulation parameters.
• the thermal power unit frequency regulation parameters include the thermal power unit.
• the boiler heat storage energy of the thermal power unit is changed, the frequency of the power system is adjusted, and the interfered power system frequency is adjusted to a normal value.
• this program uses the improved quantum particle swarm algorithm to optimize and solve the adaptive small-disturbance thermal power unit primary frequency regulation parameter control model, and obtain the weight parameters of different residual units in the model.
• the obtained The weight parameters are used as model parameters to obtain the optimal adaptive small-disturbance thermal power unit primary frequency regulation parameter control model, in which the optimization solution process of the model is: construct the fitness function F( ⁇ ) for model optimization solution:
• U n (q) is the position representation of the n-th quantum particle in the q-th iteration.
• the position representation of each quantum particle corresponds to the weight parameter of an adaptive small-disturbance thermal power unit primary frequency modulation parameter control model.
• the position The number of dimensions represented is L dimension, u nL represents the position coordinate of the n-th quantum particle in the L-th dimension, corresponding to the weight parameter of the L-th residual unit; for any quantum particle position, it represents any dimension of U n (q)
• the position coordinates are processed by taking absolute values, and the position coordinates in any dimension are normalized.
• max(u n ) is the maximum value among (u n1 (q), u n2 (q), u n3 (q),..., u nj (q),..., u nL (q)); any The position of n quantum particles represents U n (q) as the weight parameter of the fitness function, and the result of the fitness function is used as the fitness value F q (n) of the n-th quantum particle during the q-th round of algorithm iteration; record The historical optimal position U n (best) of any n-th quantum particle from the beginning of iteration to the current q-th iteration is recorded, and the historical optimal position U(best) of the quantum particle swarm from the beginning of iteration to the current q-th iteration is recorded.
• rand(0,1) is a random number between 0 and 1; ⁇ is the contraction and expansion factor, set it to 0.2; repeat the above steps until the maximum number of iterations is reached, and take the absolute position representation of all current quantum particles.
• values and normalization processing and calculate the fitness values of all quantum particles after position representation processing, and use the position representation of the quantum particle with the smallest fitness value as the weight parameters of different residual units in the model obtained by solving the problem.
• the update value range of particle position is restricted by the set particle speed, which easily limits the particles to a certain area, causing the algorithm to fall into a local extremum.
• the quantum particles in the improved quantum particle swarm only consider changes in position and can be based on random parameters
• the improved quantum particle swarm algorithm uses the average optimal value best of quantum particles to help any quantum particle update its position. It helps all quantum particles work together, further improves the global optimization capability of the algorithm, and can quickly solve the model parameters.
• Figure 1 is a schematic flow chart of a primary frequency modulation control method for small disturbance thermal power units provided by an embodiment of the present invention
• Figure 2 is a functional module diagram of a primary frequency regulation control system for small disturbance thermal power units provided by an embodiment of the present invention
• Figure 3 is a structural representation of an electronic device that implements a primary frequency modulation control method for a small disturbance thermal power unit provided by an embodiment of the present invention. intention.
• the embodiment of the present application provides a primary frequency modulation control method for small disturbance thermal power units.
• the execution subject of the primary frequency modulation control method for small-disturbance thermal power units includes, but is not limited to, at least one of a server, a terminal, and other electronic devices that can be configured to execute the method provided by the embodiments of the present application.
• the primary frequency regulation control method of small-disturbance thermal power units can be executed by software or hardware installed on terminal equipment or server equipment, and the software can be a blockchain platform.
• the server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.
• S1 Collect power system frequency signals and preprocess the collected signals, and perform robust adjustment processing on the preprocessed power system frequency signals.
• Multi-scale signal conditioning based on morphological analysis is a robust adjustment processing method.
• step S1 the power system frequency signal is collected and the collected signal is preprocessed, including:
• the sensors are used to collect power system frequency signals; the power system frequency signals x(t) are collected, where t ⁇ 0,1,2,...,T ⁇ , t represents Based on the timing information of the power system frequency signal x(t), perform noise reduction preprocessing on the collected power system frequency signal x(t) to obtain the preprocessed power system frequency signal x'(t).
• the process of noise processing is:
• q(x(t),a) represents the wavelet coefficient of the power system frequency signal x(t) at scale a;
• Delete the wavelet coefficients smaller than the wavelet threshold ⁇ retain the wavelet coefficients greater than or equal to the wavelet threshold ⁇ , use the wavelet inverse transform method to reconstruct the retained wavelet coefficients into noise reduction signals, and use the noise reduction signal as the preprocessed power system frequency signal x'(t), where the formula of the wavelet inverse transform method is:
• q(x(t),a') is the retained wavelet coefficient, and a' is the scale of the retained wavelet coefficient
• x'(t) is the preprocessed power system frequency signal.
• step S1 the preprocessed power system frequency signal is subjected to robust adjustment processing, in which multi-scale signal adjustment based on morphological analysis is a robust adjustment processing method, including:
• g m is a structural element, m ⁇ 0,1,2,...,M ⁇ .
• the selected structural element is a one-dimensional discrete vector, and the length dimension of the discrete vector is T+1.
• y i (t) is the power system frequency signal after robust adjustment of the i-th group of weight coding vectors
• the power system frequency signal y(t) after robust adjustment processing with the smallest error value is selected as the final processed signal.
• an adaptive small-disturbance thermal power unit primary frequency regulation parameter control model is constructed, including:
• the thermal power unit frequency regulation parameters include the rotational speed parameters of the thermal power unit, combustion Temperature parameters, by adjusting the rotation speed and heating temperature of the thermal power unit, change the thermal energy storage of the boiler of the thermal power unit, adjust the frequency of the power system, and adjust the frequency of the interfered power system to a normal value;
• the adaptive small-disturbance thermal power unit primary frequency modulation parameter control model consists of L residual units and a fully connected layer, in which the fully connected layer is a Softmax function, used to output the frequency modulation parameters of the thermal power unit, in which the jth residual unit
• r j represents the output result of the jth residual unit, j ⁇ 1,2,3,...,L ⁇ , r 0 represents the input robustly adjusted power system frequency signal, ⁇ j is the jth residual
• C 1 ( ⁇ ) means performing a convolution operation on the input value, and the convolution kernel size is 1 ⁇ 1;
• SC( ⁇ ) represents residual mapping.
• the residual unit consists of two convolution layers.
• the residual mapping operation is to perform two convolution processes on the input value.
• the convolution kernel size is 3 ⁇ 3;
• the output of the Lth residual unit is used as the input of the fully connected layer.
• S3 Follow step S1 to collect a large number of robustly adjusted power system frequency signals with disturbances and corresponding thermal power plants.
• the improved quantum particle swarm algorithm was used to optimize and solve the adaptive small-disturbance thermal power unit primary frequency regulation parameter control model to obtain the optimal adaptive small-disturbance thermal power unit primary frequency regulation parameter control model.
• a large number of robustly adjusted power system frequency signals with disturbances and corresponding thermal power unit frequency modulation parameters are collected as a training set, including:
• step S1 a large number of robustly adjusted power system frequency signals with disturbances and corresponding thermal power unit frequency modulation parameters are collected as training set Data.
• the format of the training set Data is:
• data k is the kth set of training data in the training set Data, and K represents the total number of sets of training data in the training set Data;
• y k (t) represents the robustly adjusted power system frequency signal with disturbance in data k ;
• par 1,k represents the thermal power unit speed parameter corresponding to y k (t)
• par 2,k represents the combustion temperature parameter of the thermal power unit corresponding to y k (t)
• by performing (par 1,k ,par 2 , k ) can make the power system frequency with small disturbance noise return to the normal frequency.
• the improved quantum particle swarm algorithm is used to optimize and solve the constructed adaptive small-disturbance thermal power unit primary frequency regulation parameter control model, and obtain the optimal adaptive small-disturbance thermal power unit primary frequency regulation parameter control model, including:
• the improved quantum particle swarm algorithm was used to optimize and solve the adaptive small-disturbance thermal power unit primary frequency regulation parameter control model.
• the weight parameters of different residual units in the model were obtained by solving the problem.
• the obtained weight parameters were used as model parameters to obtain the optimal
• the thermal power unit speed parameter generated by the weight parameter ⁇ is the combustion temperature parameter of the thermal power unit generated by the model based on y k (t) and the weight parameter ⁇ ;
• U n (q) is the position representation of the n-th quantum particle in the q-th iteration.
• the position representation of each quantum particle corresponds to the weight parameter of an adaptive small-disturbance thermal power unit primary frequency modulation parameter control model.
• the position representation is The number of dimensions is L dimension, u nL represents the position coordinate of the n-th quantum particle in the L-th dimension, corresponding to the weight parameter of the L-th residual unit;
• S36 Record the historical optimal position U n (best) of any n-th quantum particle from the beginning of iteration to the current q-th iteration, and record the historical optimal position U of the quantum particle swarm from the beginning of iteration to the current q-th iteration. (best), where the historical optimal position is the position representation of the quantum particle with the smallest fitness value from the beginning of the iteration to the current q-th iteration;
• rand(0,1) is a random number between 0 and 1;
• ⁇ is the contraction and expansion factor, set to 0.2;
• step S4 Detect the frequency disturbance of the power system.
• the model outputs the current frequency modulation parameters of the thermal power unit, and performs frequency modulation control on the thermal power unit based on the current frequency modulation parameters of the thermal power unit.
• step S4 The frequency disturbance of the power system is detected in step S4, including:
• Sensors in the power system collect the power system frequency signal X(t) in real time and calculate the disturbance value of the real-time power system frequency signal:
• t 0,1,2,...,T ⁇ , t represents the timing information of the power system frequency signal
• R(X(t)) represents the disturbance value of the real-time power system frequency signal
• step S4 When a frequency disturbance is detected in step S4, the current robustly adjusted power system frequency signal is collected, and the collected signal is input into the optimal adaptive small disturbance thermal power unit primary frequency regulation parameter control model, and the model outputs the current Frequency modulation parameters of thermal power units, frequency modulation control of thermal power units based on the current frequency modulation parameters of thermal power units, including:
• the current power system frequency signal X(t) is robustly adjusted according to the method of step S1, and the robustly adjusted power system frequency signal Y(t) is input to the optimal adaptive small disturbance
• the model outputs the current thermal power unit frequency regulation parameters, and performs frequency regulation control on the thermal power unit based on the current thermal power unit frequency regulation parameters to correct the frequency fluctuation of the power system.
• FIG. 2 it is a functional module diagram of a primary frequency modulation control system for small disturbance thermal power units provided by an embodiment of the present invention, which can implement the frequency modulation control method in Embodiment 1.
• the primary frequency modulation control system 100 for small disturbance thermal power units of the present invention can be installed in electronic equipment.
• the primary frequency modulation control system for small disturbance thermal power units may include a signal acquisition and processing module 101, a frequency disturbance detection module 102 and a frequency modulation parameter acquisition device 103.
• the module of the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of the electronic device and can complete fixed functions, and are stored in the memory of the electronic device.
• the signal acquisition and processing module 101 is used to collect power system frequency signals and preprocess the collected signals, and perform robust adjustment processing on the preprocessed power system frequency signals;
• Frequency disturbance detection module 102 is used to detect frequency disturbances in the power system
• the frequency modulation parameter acquisition device 103 is used to construct an adaptive small-disturbance thermal power unit primary frequency modulation parameter control model.
• the improved quantum particle swarm algorithm is used to optimize and solve the constructed adaptive small-disturbance thermal power unit primary frequency modulation parameter control model.
• the robustly adjusted power system frequency signal is input into the optimal adaptive small-disturbance thermal power unit primary frequency regulation parameter control model.
• the model outputs the current thermal power unit frequency modulation parameters, and the thermal power unit is frequency modulated according to the current thermal power unit frequency modulation parameters. control.
• each module in the small-disturbance thermal power unit primary frequency regulation control system 100 described in the embodiment of the present invention adopts the same technical means as the above-mentioned small-disturbance thermal power unit primary frequency regulation control method described in Figure 1 when used. , and can produce the same technical effect, so we will not go into details here.
• FIG. 3 it is a schematic structural diagram of an electronic device that implements a primary frequency modulation control method for a small-disturb thermal power unit provided by an embodiment of the present invention.
• the electronic device 1 may include a processor 10, a memory 11 and a bus, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a small disturbance thermal power unit primary frequency modulation control program 12 .
• the memory 11 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (such as SD or DX memory, etc.), magnetic memory, magnetic disk, CD etc.
• the memory 11 may be an internal storage unit of the electronic device 1 , such as a mobile hard disk of the electronic device 1 .
• the memory 11 may also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), or a secure digital device equipped on the electronic device 1. , SD) card, flash card (Flash Card), etc. Further, the memory 11 may also include both an internal storage unit of the electronic device 1 and an external storage device.
• the memory 11 can not only be used to store application software and various types of data installed in the electronic device 1, such as the code of the primary frequency modulation control program 12 of the small disturbance thermal power unit, etc., but can also be used to temporarily store data that has been output or will be output. .
• the processor 10 may be composed of an integrated circuit, for example, it may be composed of a single packaged integrated circuit, or it may be composed of multiple integrated circuits packaged with the same function or different functions, including one or more Central processing unit (Central Processing unit, CPU), microprocessor, digital processing chip, graphics processor and various control chip combinations, etc.
• the processor 10 is the control core (Control Unit) of the electronic device, using various interfaces and lines to connect various components of the entire electronic device, and by running or executing programs or modules (small perturbation) stored in the memory 11 Thermal power unit primary frequency modulation control program, etc.), and call the data stored in the memory 11 to execute various functions of the electronic device 1 and process data.
• Control Unit Control Unit
• the bus may be a peripheral component interconnect standard (PCI for short) bus or an extended industry standard architecture (EISA for short) bus, etc.
• PCI peripheral component interconnect standard
• EISA extended industry standard architecture
• the bus can be divided into address bus, data bus, control bus, etc.
• the bus is configured to enable connection communication between the memory 11 and at least one processor 10 and the like.
• FIG. 3 only shows an electronic device with components. Persons skilled in the art can understand that the structure shown in FIG. 3 does not limit the electronic device 1 and may include fewer or more components than shown in the figure. components, or combinations of certain components, or different arrangements of components.
• the electronic device 1 may also include a power supply (such as a battery) that supplies power to various components.
• the power supply may be logically connected to the at least one processor 10 through a power management device, so that through the power management device
• the device implements functions such as charging management, discharge management, and power consumption management.
• the power supply may also include one or more DC or AC power supplies, recharging devices, power failure detection circuits, power converters or inverters, power status indicators and other arbitrary components.
• the electronic device 1 may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here. narrate.
• the electronic device 1 may also include a network interface.
• the network interface may include a wired interface and/or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which are usually used in the electronic device. 1. Establish communication connections with other electronic devices.
• the electronic device 1 may also include a user interface, which may be a display (Display) or an input unit (such as a keyboard).
• the user interface may also be a standard wired interface or a wireless interface.
• the display may be an LED display, a liquid crystal display, a touch-controlled liquid crystal display, an OLED (Organic Light-Emitting Diode, organic light-emitting diode) touch device, etc.
• the display may also be appropriately referred to as a display screen or a display unit, and is used for displaying information processed in the electronic device 1 and for displaying a visualized user interface. It should be understood that the above embodiments are for illustration only, and the scope of the patent application is not limited by this structure.
• the small-disturbance thermal power unit primary frequency modulation control program 12 stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When run in the processor 10, it can realize:
• an adaptive small-disturbance thermal power unit primary frequency regulation parameter control model is constructed
• the robustly adjusted power system frequency signal is collected and processed, and the robustly adjusted power system frequency signal is input to the optimal adaptive small disturbance thermal power unit.
• the model outputs the current frequency modulation parameters of the thermal power unit, and performs frequency modulation control on the thermal power unit based on the current frequency modulation parameters of the thermal power unit.
• the methods of the above embodiments can be implemented by means of software plus the necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is better. implementation.
• the technical solution of the present invention can be embodied in the form of a software product that is essentially or contributes to the existing technology.
• the computer software product is stored in a storage medium (such as ROM/RAM) as mentioned above. , magnetic disk, optical disk), including several instructions to cause a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the method described in various embodiments of the present invention.

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• 2022
  • 2022-06-13 CN CN202210662211.6A patent/CN114899844B/zh active Active
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