Flywheel energy storage auxiliary thermal power generating unit AGC frequency modulation method and device and medium

Abstract

The invention discloses an AGC frequency modulation method and device for a flywheel energy storage auxiliary thermal power generating unit and a medium, and relates to the technical field of AGC frequency modulation, and the method comprises the steps: carrying out the preprocessing of original AGC instruction data, and obtaining target AGC instruction data; segmenting the target AGC instruction data to obtain a plurality of AGC instruction stages; constructing a flywheel energy storage auxiliary thermal power generating unit AGC frequency modulation strategy; the thermal power generating unit model responds to a new AGC instruction in the scene and issues the new AGC instruction in advance, and the proportional relation between the output power of the thermal power generating unit responding to the new AGC instruction and the new AGC instruction is determined; constructing an AGC frequency modulation system cost-income model; according to the method, the time for adding flywheel energy storage is accurately controlled, and the influence on the whole frequency modulation system due to the fact that the combined power of the AGC frequency modulation system and the flywheel energy storage system enters an adjustment dead zone in advance is effectively reduced.

Description

Technical Field

[0001] The present application relates to the technical field of AGC frequency modulation, and particularly to a method, device and medium for flywheel energy storage assisted AGC frequency modulation of thermal power units. Background Technique

[0002] The Automatic Generation Control (AGC) system can instantaneously detect the frequency deviation in the power grid and convert it into the corresponding active power deficit, which is reasonably allocated to the frequency modulation power sources under its regulation, thereby correspondingly adjusting their active power output. However, due to the low regulation accuracy and slow ramp rate of thermal power units, their real-time power response is weak, and their performance is poor in the process of tracking AGC commands. At the same time, frequent load changes will cause serious equipment losses of the generating units, which have a serious impact on the safety and economic benefits of thermal power units. Flywheel energy storage, as a new type of energy storage system, has the characteristics of instantaneous response and its lifespan is not affected by the state of charge, and is suitable for assisting units to participate in frequency modulation tasks.

[0003] At present, most of the secondary frequency modulation strategies for flywheel energy storage assisted thermal power units use the change of AGC power command as the sign of flywheel energy storage action, and decompose the process of thermal power units tracking the change of AGC power command into the tracking processes of thermal power units under multiple AGC power commands. According to the assessment index, the process of flywheel energy storage assisting thermal power units to track a single AGC power command is divided into a response stage, a ramp stage and a maintenance stage. In the ramp stage, due to the addition of flywheel energy storage, it assists the thermal power unit to respond to the AGC power command, so that the time for the combined power of the two to enter the regulation dead zone is advanced. Although this rapid response improves the speed of the combined response of the thermal power unit and flywheel energy storage to the AGC command, it may also lead to the early issuance of the next stage AGC command. In this case, in the face of continuously rising or falling AGC power command signals, the early issuance of a new AGC power command will cause the thermal power unit to obtain the newly issued AGC power command signal before completing the AGC power command of the previous stage, resulting in the thermal power unit being forced to undertake a larger amplitude of frequency modulation tasks. Summary of the Invention

[0004] The purpose of the present application is to provide a method, device and medium for flywheel energy storage assisted AGC frequency modulation of thermal power units, which can accurately control the time of adding flywheel energy storage and effectively reduce the impact of the combined power of the two entering the regulation dead zone in advance on the entire frequency modulation system.

[0005] To achieve the above purpose, the present application provides the following solutions.

[0006] In the first aspect, the present application provides a method for flywheel energy storage assisted AGC frequency modulation of thermal power units, including the following steps.

[0007] Obtain the original data of the thermal power plant; the original data includes the original AGC command data and the actual power generation data; preprocess the original AGC command data to obtain the target AGC command data; segment the target AGC command data to obtain several AGC command stages; each AGC command stage is data where the AGC command does not change within a continuous time period.

[0008] Construct a flywheel energy storage assisted AGC frequency modulation strategy for thermal power units.

[0009] Construct an AGC command early issuance scenario to obtain the new AGC command corresponding to each AGC command stage.

[0010] Use the thermal power unit model to respond to the new AGC command, and determine the proportional relationship between the output power of the thermal power unit responding to the new AGC command and the new AGC command.

[0011] Construct an AGC frequency modulation system cost-benefit model; the AGC frequency modulation system cost-benefit model includes an objective function and constraint conditions.

[0012] Solve the AGC frequency modulation system cost-benefit model to obtain the optimized proportional value corresponding to each AGC command stage; the optimized proportional value is the proportional value between the output power of the thermal power unit after stepping out of the response dead zone and the AGC command under each segment of AGC command.

[0013] Optionally, the preprocessing includes outlier processing and normalization processing.

[0014] Optionally, the expression of the objective function is as follows:

[0015] minC(k) = C ram (k) - B Kp (k);

[0016]

[0017] B Kp = K pd (k) × Y AGC × D;

[0018]

[0019] Wherein, C(k) is the objective function, C ram (k) is the thermal power unit cost model, B Kp (k) is the AGC frequency modulation mileage revenue model, n' is the entire AGC command time length; χ is the unit ramp loss cost, P g (t,k)) is the output power at time t with a proportional value of k, P g(t - 1, k) is the output power at time t - 1 with a proportional value of k, Δt is the time interval, and K pd is the regulation performance index for the day; Y AGC is the AGC compensation price; D is the daily regulation depth, and D i is the i-th regulation depth.

[0020] Optionally, the constraint conditions include the standby capacity constraint of the flywheel energy storage system, the SOC constraint, and the discharge power constraint of the flywheel energy storage system.

[0021] Optionally, the standby capacity constraint and the SOC constraint of the flywheel energy storage system are specifically as follows:

[0022] S min ≤S soc (t, k) ≤ S max ;

[0023] In the formula, S soc (t, k) is the SOC of the energy storage system at time t with a proportional value of k, and S max and D min are the upper and lower limits of the SOC of the energy storage system, respectively;

[0024] The discharge power constraint of the flywheel energy storage system is specifically as follows:

[0025]

[0026] In the formula, P fd is the maximum allowable discharge power of the system; P fd,e is the rated discharge power of the system installation; D low is the low value of the SOC of the energy storage system.

[0027] Optionally, solving the cost - benefit model of the AGC frequency modulation system to obtain the optimized proportional value corresponding to each AGC command stage specifically includes:

[0028] Using the particle swarm algorithm to solve the cost - benefit model of the AGC frequency modulation system to obtain the optimized proportional value corresponding to each AGC command stage.

[0029] Optionally, using the particle swarm algorithm to solve the cost - benefit model of the AGC frequency modulation system to obtain the optimized proportional value corresponding to each AGC command stage specifically includes:

[0030] Initializing the population parameters; the population parameters include the population size, the number of optimization variables, the number of optimization generations, the range of optimization variables, the forgetting factor, and the learning factor;

[0031] Calculating the fitness value of each particle in the initial population; the fitness value of the particle is calculated through the objective function;

[0032] Determine the initial individual optimal position and the global optimal position;

[0033] Update the velocities and positions of each particle;

[0034] Calculate the new fitness of each particle in the population, and determine the current individual optimal position and the current global optimal position;

[0035] Compare the values of the current individual optimal position and the current global optimal position with the initial individual optimal position and the global optimal position. If the current individual optimal position is greater than the initial individual optimal position or the current global optimal position is superior to the initial global optimal position, then replace the initial individual optimal position and the global optimal position with the current individual optimal position and the current global optimal position;

[0036] Judge whether the set iteration termination condition is reached. If it is satisfied, then jump out of the loop, and determine the optimization variable corresponding to the current iteration number as the optimization ratio value corresponding to the AGC command stage; if it is not satisfied, then return to the step of "Update the velocities and positions of each particle".

[0037] Optionally, the set iteration termination condition is that the current iteration number reaches the maximum iteration number or the fitness value of the current global optimal position reaches the preset optimization accuracy.

[0038] In a second aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the above-mentioned flywheel energy storage assisted thermal power unit AGC frequency modulation method.

[0039] In a third aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the above-mentioned flywheel energy storage assisted thermal power unit AGC frequency modulation method is implemented.

[0040] According to the specific embodiments provided by the present application, the following technical effects are disclosed in the present application:

[0041] The present application provides a flywheel energy storage assisted thermal power unit AGC frequency modulation method, device and medium. By solving the optimization ratio value corresponding to each AGC command stage through the AGC frequency modulation system cost-benefit model, the time for adding flywheel energy storage can be accurately controlled, effectively reducing the impact of the combined power of the two entering the regulation dead zone in advance on the entire frequency modulation system. Description of the Drawings

[0042] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the accompanying drawings required in the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0043] Figure 1 It is an application environment diagram of a flywheel energy storage assisted AGC frequency modulation method for a thermal power unit in an embodiment of the present application;

[0044] Figure 2 It is a schematic flowchart of a flywheel energy storage assisted AGC frequency modulation method provided by an embodiment of the present application;

[0045] Figure 3 It is a schematic diagram of the specific process of a flywheel energy storage assisted AGC frequency modulation method provided by an embodiment of the present application;

[0046] Figure 4 It is a schematic diagram of the structure of a computer device provided by an embodiment of the present application. Specific Embodiments

[0047] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0048] To make the above objects, features, and advantages of the present application more obvious and understandable, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0049] The flywheel energy storage assisted AGC frequency modulation method provided by the embodiments of the present application can be applied to, for example Figure 1In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be set separately, integrated on the server 104, placed on the cloud or other servers. The terminal 102 can send the original data to the server 104. The original data includes the original AGC instruction data and the actual power data. After receiving the original AGC instruction data, for the original AGC instruction data, the server 104 preprocesses the original AGC instruction data to obtain the target AGC instruction data, segments the target AGC instruction data to obtain several AGC instruction stages, constructs the AGC frequency modulation strategy of the flywheel energy storage assisted thermal power unit, uses the thermal power unit model to respond to the new AGC instruction issued in advance under the scenario of the AGC instruction, determines the proportional relationship between the output power of the thermal power unit responding to the new AGC instruction and the new AGC instruction, and constructs the cost-benefit model of the AGC frequency modulation system; solves the cost-benefit model of the AGC frequency modulation system to obtain the optimized proportional value corresponding to each AGC instruction stage. The server 104 can feedback the optimized proportional value corresponding to the AGC instruction stage for the thermal power plant to the terminal 102. In addition, in some embodiments, the AGC frequency modulation method of the flywheel energy storage assisted thermal power unit can also be implemented separately by the server 104 or the terminal 102. For example, the terminal 102 can directly perform AGC frequency modulation processing on the original data, or the server 104 can obtain the original data from the data storage system and perform AGC frequency modulation processing on the original data.

[0050] Among them, the terminal 102 can be, but is not limited to, various desktop computers and laptop computers. The server 104 can be implemented by an independent server or a server cluster composed of multiple servers, and can also be a cloud server.

[0051] In an exemplary embodiment, such as Figure 2 and Figure 3 shown, a method for AGC frequency modulation of a flywheel energy storage assisted thermal power unit is provided. This method is executed by a computer device, and can be specifically executed separately by a computer device such as a terminal or a server, or jointly executed by a terminal and a server. In the embodiments of the present application, taking this method applied to Figure 1 the server 104 in

[0052] Step 201: Obtain the original data of the thermal power plant; the original data includes original AGC command data and actual power generation data; preprocess the original AGC command data to obtain target AGC command data; segment the target AGC command data to obtain several AGC command stages; each AGC command stage is data where the AGC command does not change within a continuous time period.

[0053] Step 202: Construct a flywheel energy storage assisted AGC frequency modulation strategy for thermal power units.

[0054] Step 203: Construct an AGC command early issuance scenario to obtain a new AGC command corresponding to each AGC command stage.

[0055] Step 204: Use the thermal power unit model to respond to the new AGC command and determine the proportional relationship between the output power of the thermal power unit responding to the new AGC command and the new AGC command.

[0056] Step 205: Construct an AGC frequency modulation system cost-benefit model; the AGC frequency modulation system cost-benefit model includes an objective function and constraint conditions.

[0057] Step 206: Solve the AGC frequency modulation system cost-benefit model to obtain an optimized proportional value corresponding to each AGC command stage; the optimized proportional value is the proportional value of the output power of the thermal power unit stepping out of the response dead zone to the AGC command under each segment of AGC command.

[0058] Implement the above steps 201 to 206. For the flywheel energy storage assisted AGC frequency modulation system of thermal power units in a typical scenario, with the goal of improving system benefits, combined with the power-type energy storage characteristics of the flywheel energy storage system, a control method for flywheel energy storage to participate in the AGC regulation of thermal power units in segments is proposed. Based on the assessment indicators and the real-time status of the units, the flywheel energy storage assists the units to participate in AGC frequency modulation in stages. By optimizing the proportional value of the output power of the thermal power unit stepping out of the response dead zone to the AGC command under each segment of AGC command, the time to add the flywheel energy storage is accurately controlled, effectively reducing the impact of the early issuance of the AGC command on the entire frequency modulation system caused by the combined power of the two entering the regulation dead zone in advance, and significantly improving the AGC frequency modulation system benefits of the flywheel energy storage assisted thermal power units in a typical scenario.

[0059] In another exemplary embodiment of the present application, the above step 201 may include the following steps 301 to 304:

[0060] Step 301: Data collection, collecting the original data of the thermal power plant. First, collect the original data from the distributed control system (DCS system) of the generating unit. Select four months of the whole year (one month per quarter) as the unit operation historical data to avoid errors caused by different electricity loads due to seasons or natural reasons. The data sampling time interval is 1 s, and ensure that the thermal power unit operates without shutdown and without faults within the data collection range; the collected data includes the AGC command P AGC , the actual power generation P g .

[0061] The preprocessing includes outlier processing and normalization processing to identify and correct outliers and missing values in the data. The specific processes are shown in Step 302 and Step 303 respectively.

[0062] Step 302: Outlier processing. The outlier data in the data collected in Step 301 is processed by the mean square value method. The calculation formula of the mean square value method is shown in Equation (1).

[0063]

[0064] In the formula, N is the number of samples, x i is the i-th sample value, μ is the sample mean, and δ is the sample variance. If |x i -μ|>3δ, then x i is judged as an outlier point and is replaced by the method of linear fitting.

[0065] Step 303: Normalization processing. To accelerate the training speed of the secondary frequency modulation network model, the data collected in Step 301 is normalized. The values are converted within the range of [0,1]. The normalization processing is shown in Equation (2).

[0066]

[0067] In the formula, x min is the minimum value in the processed feature data, and x max is the maximum value in the processed feature data.

[0068] After Step 302 and Step 303, the target AGC command data can be obtained.

[0069] Step 304: Segment the processed target AGC command data. Select the n-second AGC power command that continuously rises in a day, P AGC =P AGC (1),P AGC (2),…,P AGC (n) (n is the time information, indicating the total time length of the AGC command, P AGC (1)≤P AGC (2)≤…≤PAGC (n)), the P that does not change within a continuous period of time AGC is recorded as a segment of AGC instruction, that is, P AGC i = [P AGC (a i ), P AGC (a i + 1), …, P AGC (b i )] (where i is the AGC stage information. Assuming that the AGC instruction is divided into D segments in total, a i , b i are time information, which are the start and end times of the i-th segment of the AGC instruction stage respectively. P AGC (a i ) = P AGC (a i + 1) = … = P AGC (b i ), P AGC (a i ) is the AGC instruction at time a i , P AGC (a i + 1) is the AGC instruction at time a i + 1, and P AGC (b i ) is the AGC instruction at time b i ).

[0070] The specific steps for constructing the AGC frequency modulation strategy of the flywheel energy storage assisted thermal power unit in step 202 above are as follows:

[0071] Within the i-th segment of the AGC instruction stage:

[0072] (1) When P g (t) ≤ P AGC (i - 1) + P x :

[0073] P f_ref (t) = P AGC (i - 1) + P x - P g (t) (3);

[0074] In the formula, P f_ref (t) is the set power of the flywheel output; P AGC (i - 1) is the AGC instruction of the (i - 1)-th stage; P x is the response dead zone, which is 1% of the rated power of the thermal power unit; t is the time information, a i ≤ t ≤ a i + t i , in seconds.

[0075] (2) When P g (t) > P AGC (i - 1) + P x :

[0076]

[0077] In the formula, P t is the regulation dead zone, which is 0.5% of the rated power of the thermal power unit; t f,i is the moment when the flywheel energy storage is added in stage i, t f,i ≥ t, and P g (t f,i ) = k × P AGCi , P g (t f,i ) is the output power at time t f,i , and k is the ratio of the output power of the thermal power unit to the AGC command after stepping out of the response dead zone under the AGC command.

[0078] In step 203 above, during the ramp-up stage, due to the addition of the flywheel energy storage, the time for the combined power of it and the thermal power unit to enter the regulation dead zone is advanced, which may lead to the early issuance of the AGC command in the next stage. In the i-th stage of the AGC command, according to step 202, the flywheel energy storage is added and starts to output power at time t f,i . Based on its characteristics of fast response speed and accurate following of load changes, this application assumes that the flywheel energy storage reaches its power setting value 1 second after starting to respond. That is, in the i-th stage of the AGC command, the system output power reaches the current stage AGC regulation dead zone at time (t f,i + 1), and a new stage of AGC command is issued at time (t f,i + 2). At this time, P AGCi = [P AGC (a i ), P AGC (a i + 1), …, P AGC (t f,i + 1)], t f,i + 1 ≤ b i , a i+1 = t f,i + 2.

[0079] In step 204, use the established thermal power unit model to respond to the new AGC command. Denote the output power of the thermal power unit responding to the new AGC command as P' g . From step 202, it can be seen that P' g = f(k).

[0080] The modeling process of the thermal power unit model is as follows: Based on the rotational speed of the feed water pump, the feed water pressure, feed water flow rate, and separator pressure parameters are simplified and calculated; the drum / separator water level is simplified to the integral of the difference between the incoming and outgoing working fluid flow rates; the mass conservation and energy conservation methods are adopted, and the steam flow rate is determined by calculating the dryness of the working fluid; the integral function of the PID module is used to calculate the temperature from the pressure and enthalpy values, and then the main steam temperature is simulated and calculated using the principles of mass and energy conservation; the flue gas volume and the suction volume of the induced draft fan are simulated and calculated, and the difference between the two is integrated, and then the integral inlet deviation is changed to simplify the simulation of the furnace negative pressure; the secondary air pressure and primary air pressure are simulated and calculated using a method similar to the simulation of the flue gas volume and the suction volume of the induced draft fan; the boiler fuel quantity is simulated and calculated according to the rotational speed of the coal feeder; the unit load is simulated and calculated according to the fuel quantity or the main steam flow rate; a simulation method for establishing a simplified model of the controlled object is adopted within the DCS system using the DCS configuration tool, thereby realizing the control closed-loop, that is, after establishing a simulation model within the distributed control system (DCS) of the thermal power unit, the control closed-loop is achieved.

[0081] The following is to construct a cost-benefit model for the flywheel energy storage assisted AGC frequency modulation system of the thermal power unit and optimize the cost-benefit model of the AGC frequency modulation system. The specific process is as follows.

[0082] (1) Construct a cost model for the thermal power unit.

[0083]

[0084] In the formula: C ram (k) is the cost model of the thermal power unit, n' is the entire AGC command time length; χ is the unit ramp loss cost, P g (t,k) is the output power at time t with a ratio value of k, P g (t - 1,k) is the output power at time t - 1 with a ratio value of k, and Δt is the time interval.

[0085] (2) Construct an AGC frequency modulation mileage revenue model. For the economic losses caused by the thermal power plant participating in AGC, the market will give a certain AGC economic compensation to the AGC unit. The calculation formula for the daily compensation cost of the AGC service contribution, that is, the AGC frequency modulation mileage revenue model, is shown in Equation (6).

[0086] B Kp (k) = K pd (k) × Y AGC × D (6).

[0087] Among them, B Kp (k) is the AGC frequency modulation mileage revenue model, K pd is the regulation performance index of the day; Y AGCThe price for AGC compensation; D is the daily regulation depth, i.e., the total sum of daily regulation amounts, and the expression is as shown in Equation (7).

[0088]

[0089] In the formula, D i is the regulation depth at the i-th time. If the system output reaches the command value when receiving the next AGC command, D i = |P AGCi - P si |; if the system output does not reach the command value when receiving the next AGC command, D i = |P Ei - P Si |; P Si is the output of the system at the start of the i-th AGC regulation; P Ei is the output of the system at the end of the i-th AGC regulation.

[0090] (3) Optimize the cost-benefit model of the flywheel energy storage assisted thermal power unit AGC frequency modulation system.

[0091] Define the expression of the objective function as shown in the following Equation (8).

[0092] minC(k) = C ram (k) - B Kp (k) (8).

[0093] Among them, C(k) is the objective function.

[0094] The constraint conditions include the reserve capacity constraint and SOC constraint of the flywheel energy storage system and the discharge power constraint of the flywheel energy storage system.

[0095] Among them, the reserve capacity constraint and SOC constraint of the flywheel energy storage system are specifically as shown in the following Equation (9).

[0096] S min ≤ S soc (t, k) ≤ S max (9).

[0097] In the formula, S soc (t, k) is the SOC of the energy storage system at time t with a proportion value of k; S max and S min are respectively the upper and lower limits of the SOC of the energy storage system, which can be taken as 0.8 and 0.2 respectively.

[0098] The discharge power constraint of the flywheel energy storage system is specifically as shown in the following Equation (10).

[0099]

[0100] In the formula, Pfd is the maximum discharge power allowed by the system; P fd,e is the rated discharge power of the system installed capacity; S low is the low value of the SOC of the energy storage system, and 0.4 can be taken.

[0101] In another exemplary embodiment of the present application, the above step 206 specifically includes: using the particle swarm algorithm to solve the cost-benefit model of the AGC frequency modulation system, and obtaining the optimized proportional value corresponding to each AGC instruction stage. It may specifically include the following steps 401 to step 407.

[0102] Step 401: Initialize the population parameters; the population parameters include the population size m, the number of optimization variables N, the number of optimization generations t, the range of the optimization variable X, the forgetting factor ω, the learning factor, etc. The optimization variable is the proportional value k.

[0103] Step 402: Calculate the fitness value of each particle in the initial population; the fitness value of the particle is calculated through the objective function. The fitness Q of the initial population is expressed in the form shown in Equation (11).

[0104] Q = C ram (k) - B Kp (k) (11).

[0105] Step 403: Determine the initial individual optimal position k bestin,i and the global optimal position k bestgn,i .

[0106] Step 404: Update the velocity v in and the position k i of each particle; the update formulas for the velocity and the position are shown in Formulas (12) and (13) respectively.

[0107] v in = ωv (i-1)n + c1r1[k bestin,i-1 - k i-1 + c2r2[k bestgn,i-1 - k i-1 (12).

[0108] k i = k i-1 + v in (13).

[0109] In the formula, c1 and c2 are learning factors, and the values can be 2; r1 and r2 are random numbers between (0, 1); v (i-1)n is the velocity of the particle in the (i - 1)th update, k bestin,i-1 is the individual optimal position corresponding to the (i - 1)th iteration, k bestgn,i-1is the global optimal position corresponding to the (i - 1)-th iteration; k i-1 is the particle position corresponding to the (i - 1)-th iteration.

[0110] Step 405: Calculate the new fitness of each particle in the population, and determine the current individual optimal position and the current global optimal position.

[0111] Step 406: Compare the values of k bestin and k bestgn If it is superior, it will be replaced. Specifically: Compare the current individual optimal position and the current global optimal position with the initial individual optimal position and the global optimal position values. If the current individual optimal position is greater than the initial individual optimal position or the current global optimal position is superior to the initial global optimal position, then replace the initial individual optimal position and the global optimal position with the current individual optimal position and the current global optimal position.

[0112] Step 407: Determine whether the set iteration termination condition is reached. If it is satisfied, break out of the loop and determine the optimization variable corresponding to the current iteration number as the optimization ratio value corresponding to the AGC instruction stage; if it is not satisfied, return to Step 404. The set iteration termination condition is that the current iteration number reaches the maximum iteration number or the fitness value of the current global optimal position reaches the preset optimization accuracy.

[0113] After iteration, the optimized variable k is obtained, such that the objective function C(k)=C ram (k)-B Kp (k) is minimized, thus achieving the optimal solution.

[0114] The present application also provides an application scenario, which applies the above-mentioned flywheel energy storage assisted thermal power unit AGC frequency modulation method. Specifically: The flywheel energy storage assisted thermal power unit AGC frequency modulation method provided in this embodiment can be applied in the AGC frequency modulation scenario. The AGC frequency modulation scenario includes a data acquisition link and an AGC frequency modulation link; the original AGC command data enters the AGC frequency modulation link from the data acquisition link to obtain the optimized ratio value corresponding to the corresponding AGC command stage. The flywheel energy storage assisted thermal power unit AGC frequency modulation method provided in this embodiment belongs to the AGC frequency modulation link. Specifically, in the process of the AGC frequency modulation link for the original AGC command data, the original AGC command data can be preprocessed to obtain the target AGC command data, the target AGC command data can be segmented to obtain several AGC command stages, a flywheel energy storage assisted thermal power unit AGC frequency modulation strategy can be constructed, and the new AGC command in the scenario where the thermal power unit model responds to the AGC command in advance is used to determine the proportional relationship between the output power of the thermal power unit responding to the new AGC command and the new AGC command, and an AGC frequency modulation system cost-benefit model is constructed; the AGC frequency modulation system cost-benefit model is solved to obtain the optimized ratio value corresponding to each AGC command stage.

[0115] In an exemplary embodiment, a computer device is provided. The computer device can be a server or a terminal, and its internal structure diagram can be as Figure 4 shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store AGC frequency modulation data. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements a flywheel energy storage assisted thermal power unit AGC frequency modulation method.

[0116] Those skilled in the art can understand that Figure 4 the structure shown in

[0117] In an exemplary embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the steps in the above method embodiments are implemented.

[0118] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0119] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0120] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium, and when the computer program is executed, it can include the processes of the above method embodiments. Among them, any reference to a memory, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0121] In each of the embodiments provided in the present application, the database involved may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on a blockchain, etc., and is not limited thereto. In each of the embodiments provided in the present application, the processor involved may be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., and is not limited thereto.

[0122] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered to be within the scope described in this specification.

[0123] Specific examples are used in this article to elaborate on the principles and implementation manners of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. A flywheel energy storage assisted AGC frequency modulation method for thermal power generating units, characterized in that, The method for AGC frequency modulation of a flywheel energy storage assisted thermal power unit includes: Obtaining the original data of the thermal power plant; the original data includes original AGC command data and actual power generation data; preprocessing the original AGC command data to obtain target AGC command data; segmenting the target AGC command data to obtain several AGC command stages; each AGC command stage is data where the AGC command does not change within a continuous time period. Constructing a flywheel energy storage assisted thermal power unit AGC frequency modulation strategy. Constructing an AGC command early issuance scenario to obtain a new AGC command corresponding to each AGC command stage. Using the thermal power unit model to respond to the new AGC command and determining the proportional relationship between the output power of the thermal power unit responding to the new AGC command and the new AGC command. Constructing an AGC frequency modulation system cost-benefit model; the AGC frequency modulation system cost-benefit model includes an objective function and constraint conditions. Solving the AGC frequency modulation system cost-benefit model to obtain an optimized proportional value corresponding to each AGC command stage; the optimized proportional value is the proportional value between the output power of the thermal power unit after stepping out of the response dead zone and the AGC command under each segment of AGC command.

2. The AGC frequency modulation method for a flywheel energy storage assisted thermal power unit according to claim 1, wherein The preprocessing includes outlier processing and normalization processing.

3. The AGC frequency modulation method for a flywheel energy storage assisted thermal power unit according to claim 1, wherein The expression of the objective function is as follows: minC(k) = C ram (k) - B Kp (k); B Kp (k) = K pd (k) × Y AGC × D; Among them, C(k) is the objective function, C ram (k) is the cost model of thermal power units, B Kp (k) is the AGC frequency modulation mileage revenue model, n' is the entire AGC command time length; χ is the unit ramp loss cost, P g (t,k) is the output power at time t with a ratio value of k, P g (t - 1,k) is the output power at time t - 1 with a ratio value of k, Δt is the time interval, K pd is the regulation performance index for the day; Y AGC is the AGC compensation price; D is the daily regulation depth, D i is the regulation depth for the i-th time.

4. The AGC frequency modulation method for a flywheel energy storage assisted thermal power unit according to claim 1, wherein The constraint conditions include the standby capacity constraint and SOC constraint of the flywheel energy storage system and the discharge power constraint of the flywheel energy storage system.

5. The flywheel energy storage assisted AGC frequency modulation method for thermal power generation units according to claim 4, wherein The standby capacity constraint and SOC constraint of the flywheel energy storage system are specifically as follows: S min ≤S soc (t,k)≤S max ; Where S soc (t, k) is the SOC of the energy storage system when the proportional value is k at time t, S max and S min are the upper and lower limits of the SOC of the energy storage system, respectively; The discharge power constraint of the flywheel energy storage system is specifically as follows: Where P fd is the maximum discharge power allowed by the system; P fd,e is the rated discharge power of the installed system; S low is the low value of the SOC of the energy storage system.

6. The AGC frequency modulation method for a flywheel energy storage assisted thermal power unit according to claim 1, wherein, Solving the AGC frequency modulation system cost-benefit model to obtain an optimized proportional value corresponding to each AGC command stage specifically includes: Using the particle swarm algorithm to solve the AGC frequency modulation system cost-benefit model to obtain an optimized proportional value corresponding to each AGC command stage.

7. The AGC frequency modulation method for a flywheel energy storage assisted thermal power unit according to claim 6, wherein Using the particle swarm algorithm to solve the AGC frequency modulation system cost-benefit model to obtain an optimized proportional value corresponding to each AGC command stage specifically includes: Initializing the population parameters; the population parameters include population size, number of optimization variables, number of optimization generations, range of optimization variables, forgetting factor, and learning factor. Calculating the fitness value of each particle in the initial population; the fitness value of the particle is calculated through the objective function. Determining the initial individual optimal position and global optimal position. Updating the velocity and position of each particle. Calculating the new fitness of each particle in the population and determining the current individual optimal position and current global optimal position. Comparing the numerical values of the current individual optimal position and current global optimal position with the initial individual optimal position and global optimal position. If the current individual optimal position is greater than the initial individual optimal position or the current global optimal position is superior to the initial global optimal position, then replace the initial individual optimal position and global optimal position with the current individual optimal position and current global optimal position. Determine whether the set iteration termination condition is reached. If it is satisfied, break out of the loop and determine the optimization variable corresponding to the current iteration number as the optimization ratio value corresponding to the AGC instruction stage; if it is not satisfied, return to the step of "updating the velocity and position of each particle".

8. The AGC frequency modulation method for a flywheel energy storage assisted thermal power unit according to claim 7, wherein, The set iteration termination condition is that the current iteration number reaches the maximum iteration number or the fitness value of the current global optimal position reaches the preset optimization accuracy.

9. A computer device, comprising: A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the flywheel energy storage assisted thermal power unit AGC frequency modulation method according to any one of claims 1-8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the flywheel energy storage assisted thermal power unit AGC frequency modulation method according to any one of claims 1-8.

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