A Co-optimization Method for AGC Response and Primary Frequency Regulation Based on Electricity Spot Market

Abstract

This invention relates to the field of frequency regulation technology for thermal power units, and discloses a method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market. The method includes: acquiring current meteorological data; predicting grid demand parameters for future periods based on the current meteorological data; establishing a control strategy set, which includes an AGC control set and a primary frequency regulation control set; optimizing the control strategy set based on the grid demand parameters to obtain an optimized control strategy for the unit; performing control simulation on the unit based on the optimized control strategy; and determining the optimal control strategy based on the simulation results. This invention effectively improves the grid frequency stability during unit frequency regulation, ensuring the safe and stable operation of the unit.

Description

Technical Field

[0001] This application relates to the field of frequency regulation technology for thermal power units, and more specifically, to a method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market. Background Technology

[0002] With the grid connection of new energy sources, load growth, and continuous expansion of the power grid, as well as the increase in installed capacity of my country's power industry and the widening of the peak-valley difference in electricity demand, all large thermal power units are required to implement AGC (Automatic Generation Control) functions in order to ensure the safe and stable operation of the power grid. Large thermal power units often operate in a wide load range, generally between 50% and 100% of the rated load, and are required to have the ability to respond quickly, accurately, and stably to load changes.

[0003] Existing AGC response and primary frequency regulation coordinated control technologies are mainly based on fixed parameter settings and local feedback control mechanisms, which can easily lead to abnormal fluctuations in grid frequency. Summary of the Invention

[0004] This invention provides a method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market, to solve the problem of abnormal fluctuations in grid frequency during coordinated control of AGC response and primary frequency regulation in existing technologies, including:

[0005] Obtain current meteorological data and predict power grid demand parameters for future periods based on the current meteorological data;

[0006] A control strategy set is established, which includes an AGC control set and a primary frequency regulation control set. The control strategy set is optimized based on the grid demand parameters to obtain the optimal control strategy for the unit.

[0007] The unit is controlled by simulation based on the optimized control strategy, and the optimal control strategy is determined based on the simulation results.

[0008] Furthermore, the prediction of future power grid demand parameters based on current meteorological data includes:

[0009] Obtain historical electricity spot market information and determine grid demand parameters for each historical period based on the historical electricity spot market information;

[0010] A training sample set is established based on the power grid demand parameters for each historical period, and a power grid demand prediction model is established based on the training sample set.

[0011] Obtain current meteorological data, input the current meteorological data into the power grid demand forecasting model, and predict the power grid demand parameters for future periods.

[0012] Furthermore, the power grid demand parameters include power demand parameters, regulation demand parameters, and economic demand parameters.

[0013] Furthermore, the method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market is characterized in that the optimization of the control strategy set according to the grid demand parameters to obtain the optimized control strategy of the unit includes:

[0014] The unit fuel cost, electricity price cost, and grid frequency deviation are determined based on grid demand parameters. An objective function is then established based on the unit fuel cost, electricity price cost, and grid frequency deviation.

[0015] Establish unit operation constraints, and perform optimization calculations on the control strategy set based on the unit operation constraints and objective function to obtain the optimal control strategy.

[0016] Furthermore, the aforementioned method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market is characterized in that the establishment of an objective function based on unit fuel cost, electricity price cost, and grid frequency deviation includes:

[0017] Obtain the initial objective function weight set, determine the preset weight values ​​of unit fuel cost, electricity price cost and grid frequency deviation based on the initial objective function weight set, and establish the objective function based on unit fuel cost, electricity price cost and grid frequency deviation and the corresponding preset weight values.

[0018] Furthermore, the aforementioned method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market is characterized in that the step of optimizing the control strategy set according to the unit operating constraints and objective function to obtain the optimized control strategy includes:

[0019] A multi-objective genetic algorithm is used to solve the objective function and obtain the optimal solution under the constraints of unit operation, which serves as the optimization control strategy.

[0020] Furthermore, the method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market is characterized in that the unit operation constraints include the upper and lower limits of unit output, ramp rate, AGC adjustment range, and primary frequency regulation dead zone.

[0021] Furthermore, the method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market is characterized in that determining the optimal control strategy based on simulation results includes:

[0022] Based on the simulation results, determine the power grid frequency change, plot the power grid frequency change curve, and determine the fluctuation parameters and abnormal parameters based on the power grid frequency change curve;

[0023] The initial objective function weight set is corrected based on the fluctuation parameters and abnormal parameters determined by the power grid frequency change curve. An optimized objective function is then established based on the corrected objective function weight set to obtain the optimal control strategy.

[0024] Furthermore, the aforementioned method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market is characterized in that determining the fluctuation parameters and abnormal parameters according to the power grid frequency change curve includes:

[0025] Obtain a preset sliding time window, and divide the power grid frequency change curve according to the preset sliding time window to obtain several power grid frequency change curve segments;

[0026] Calculate the average value of each power grid frequency change curve segment, and plot the average value change curve based on the average value of all power grid frequency change curve segments;

[0027] Calculate the absolute value of the slope of adjacent average values ​​in the average value change curve, and determine the fluctuation parameter based on the average of the absolute values ​​of all slopes of the average value change curve;

[0028] Obtain a preset standard frequency range, count the number of average values ​​exceeding the preset standard frequency range in the average value change curve, and determine the abnormal parameters based on the number of average values ​​exceeding the preset standard frequency range.

[0029] Furthermore, the aforementioned method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market is characterized in that the step of correcting the initial objective function weight set by determining fluctuation parameters and abnormal parameters according to the power grid frequency change curve includes:

[0030] Obtain preset standard fluctuation parameters and preset standard abnormal parameters, calculate the deviation between the fluctuation parameters and the preset standard fluctuation parameters, and determine the first correction parameter based on the deviation between the fluctuation parameters and the preset standard fluctuation parameters.

[0031] Calculate the deviation between the abnormal parameter and the preset standard abnormal parameter, and determine the second correction parameter based on the deviation between the abnormal parameter and the preset standard abnormal parameter;

[0032] The initial objective function weight set is modified according to the first and second modification parameters to obtain the modified objective function weight set.

[0033] The beneficial effects of this invention are as follows:

[0034] By applying the above technical solution, this invention can generate the lowest-cost optimized control strategy for generating units by combining electricity spot market information. At the same time, the optimized control strategy is adjusted by the abnormal parameters of grid frequency fluctuations in the optimal control strategy to obtain the optimal control strategy, which effectively improves the grid frequency stability during unit frequency regulation and ensures the safe and stable operation of the unit. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 The diagram shows a flowchart of a method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market, as proposed in an embodiment of the present invention. Detailed Implementation

[0037] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0038] This application provides a method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market, such as... Figure 1 As shown, it includes:

[0039] S101, Obtain current meteorological data and predict power grid demand parameters for future periods based on the current meteorological data;

[0040] In some embodiments of this application, the step of predicting the grid demand parameters for future periods based on current meteorological data includes: obtaining historical electricity spot market information and determining the grid demand parameters for each historical period based on the historical electricity spot market information; establishing a training sample set based on the grid demand parameters for each historical period and establishing a grid demand prediction model based on the training sample set; obtaining current meteorological data and inputting the current meteorological data into the grid demand prediction model to predict the grid demand parameters for future periods.

[0041] In some embodiments of this application, the power grid demand parameters include power demand parameters, regulation demand parameters, and economic demand parameters.

[0042] In this embodiment, a grid demand forecasting model is established based on a deep learning network model combined with grid demand parameters for each historical period from historical electricity spot market information. The grid demand forecasting model outputs grid demand parameters for future periods corresponding to the current meteorological data. The power demand parameter is the load forecast value of the generating units; the regulation demand parameter is the demand for primary frequency regulation reserve capacity and AGC regulation capacity for each future period; and the economic demand parameter is the predicted revenue information.

[0043] S102, Establish a control strategy set, which includes an AGC control set and a primary frequency regulation control set. Optimize the control strategy set according to the grid demand parameters to obtain the optimized control strategy for the unit.

[0044] In some embodiments of this application, the step of optimizing the control strategy set based on grid demand parameters to obtain the optimal control strategy for the unit includes: determining the unit's fuel cost, electricity price cost, and grid frequency deviation based on grid demand parameters; establishing an objective function based on the unit's fuel cost, electricity price cost, and grid frequency deviation; establishing unit operating constraints; and performing optimization calculations on the control strategy set based on the unit operating constraints and the objective function to obtain the optimal control strategy.

[0045] In this embodiment, the unit fuel cost is determined by calculating the fuel cost generated by the AGC command and the expected primary frequency regulation action; the electricity price cost is determined by the settlement deviation cost or benefit caused by the deviation of the unit's power generation plan from the original market plan due to the AGC command and the primary frequency regulation; and the grid frequency deviation is determined by the grid frequency deviation generated by the AGC command and the expected primary frequency regulation action.

[0046] In some embodiments of this application, the step of establishing an objective function based on unit fuel cost, electricity price cost, and grid frequency deviation includes: obtaining an initial objective function weight set; determining preset weight values ​​for unit fuel cost, electricity price cost, and grid frequency deviation based on the initial objective function weight set; and establishing an objective function based on unit fuel cost, electricity price cost, grid frequency deviation, and the corresponding preset weight values.

[0047] In this embodiment, an initial objective function weight set is set based on historical unit operating experience, thereby establishing an objective function through the initial objective function weight set and the corresponding unit fuel cost, electricity price cost, and grid frequency deviation.

[0048] In some embodiments of this application, the step of optimizing the control strategy set based on unit operation constraints and objective function to obtain an optimized control strategy includes: using a multi-objective genetic algorithm to solve the objective function and obtain the optimal solution under unit operation constraints as the optimized control strategy.

[0049] In some embodiments of this application, the unit operating constraints include the upper and lower limits of unit output, ramp rate, AGC adjustment range, and primary frequency regulation dead zone.

[0050] S103, perform control simulation on the unit according to the optimized control strategy, and determine the optimal control strategy based on the simulation results.

[0051] In some embodiments of this application, determining the optimal control strategy based on simulation results includes: determining the power grid frequency variation based on simulation results; plotting the power grid frequency variation curve based on the power grid frequency variation; determining fluctuation parameters and abnormal parameters based on the power grid frequency variation curve; correcting the initial objective function weight set based on the fluctuation parameters and abnormal parameters determined by the power grid frequency variation curve; establishing an optimized objective function based on the corrected objective function weight set; and obtaining the optimal control strategy.

[0052] In some embodiments of this application, the method of determining fluctuation parameters and abnormal parameters based on the power grid frequency variation curve includes: obtaining a preset sliding time window; dividing the power grid frequency variation curve into several power grid frequency variation curve segments according to the preset sliding time window; calculating the average value of each power grid frequency variation curve segment; drawing an average value variation curve based on the average value of all power grid frequency variation curve segments; calculating the absolute value of the slope of adjacent average values ​​in the average value variation curve; determining the fluctuation parameters based on the average value of all absolute values ​​of the slope of the average value variation curve; obtaining a preset standard frequency range; counting the number of average values ​​in the average value variation curve that exceed the preset standard frequency range; and determining the abnormal parameters based on the number of average values ​​that exceed the preset standard frequency range.

[0053] In some embodiments of this application, the step of determining fluctuation parameters and abnormal parameters based on the power grid frequency variation curve to correct the initial objective function weight set includes: obtaining preset standard fluctuation parameters and preset standard abnormal parameters; calculating the deviation value between the fluctuation parameters and the preset standard fluctuation parameters; determining a first correction parameter based on the deviation value between the fluctuation parameters and the preset standard fluctuation parameters; calculating the deviation value between the abnormal parameters and the preset standard abnormal parameters; determining a second correction parameter based on the deviation value between the abnormal parameters and the preset standard abnormal parameters; and correcting the initial objective function weight set based on the first correction parameter and the second correction parameter to obtain the corrected objective function weight set.

[0054] In this embodiment, the weights in the objective function weight set are corrected by calculating the deviation, thereby increasing the weight of grid frequency deviation and reducing the weights of unit fuel cost and electricity price cost. The larger the deviation, the higher the degree of correction, so as to achieve optimal control of the unit.

[0055] By applying the above technical solutions, this invention acquires current meteorological data and predicts future grid demand parameters based on this data; establishes a control strategy set, including an AGC control set and a primary frequency regulation control set; optimizes the control strategy set based on grid demand parameters to obtain an optimized control strategy for the generating unit; performs control simulation on the generating unit based on the optimized control strategy; and determines the optimal control strategy based on the simulation results. This invention effectively improves the grid frequency stability during unit frequency regulation, ensuring the safe and stable operation of the generating unit.

[0056] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market, characterized in that, include: Obtain current meteorological data and predict power grid demand parameters for future periods based on the current meteorological data; A control strategy set is established, which includes an AGC control set and a primary frequency regulation control set. The control strategy set is optimized based on the grid demand parameters to obtain the optimal control strategy for the unit. The unit is controlled by simulation based on the optimized control strategy, and the optimal control strategy is determined based on the simulation results.

2. The method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market according to claim 1, characterized in that, The parameters for predicting future power grid demand based on current meteorological data include: Obtain historical electricity spot market information and determine grid demand parameters for each historical period based on the historical electricity spot market information; A training sample set is established based on the power grid demand parameters for each historical period, and a power grid demand prediction model is established based on the training sample set. Obtain current meteorological data, input the current meteorological data into the power grid demand forecasting model, and predict the power grid demand parameters for future periods.

3. The method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market according to claim 2, characterized in that, The power grid demand parameters include power demand parameters, regulation demand parameters, and economic demand parameters.

4. The method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market according to claim 1, characterized in that, The optimization of the control strategy set based on grid demand parameters to obtain the optimized control strategy for the unit includes: The unit fuel cost, electricity price cost, and grid frequency deviation are determined based on grid demand parameters. An objective function is then established based on the unit fuel cost, electricity price cost, and grid frequency deviation. Establish unit operation constraints, and perform optimization calculations on the control strategy set based on the unit operation constraints and objective function to obtain the optimal control strategy.

5. The method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market according to claim 4, characterized in that, The objective function established based on unit fuel cost, electricity price cost, and grid frequency deviation includes: Obtain the initial objective function weight set, determine the preset weight values ​​of unit fuel cost, electricity price cost and grid frequency deviation based on the initial objective function weight set, and establish the objective function based on unit fuel cost, electricity price cost and grid frequency deviation and the corresponding preset weight values.

6. The method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market according to claim 4, characterized in that, The process of optimizing the control strategy set based on unit operating constraints and objective function to obtain an optimized control strategy includes: A multi-objective genetic algorithm is used to solve the objective function and obtain the optimal solution under the constraints of unit operation, which serves as the optimization control strategy.

7. The method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market according to claim 4, characterized in that, The unit's operating constraints include the unit's upper and lower output limits, ramp rate, AGC adjustment range, and primary frequency regulation dead zone.

8. The method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market according to claim 5, characterized in that, The process of determining the optimal control strategy based on simulation results includes: Based on the simulation results, determine the power grid frequency change, plot the power grid frequency change curve, and determine the fluctuation parameters and abnormal parameters based on the power grid frequency change curve; The initial objective function weight set is corrected based on the fluctuation parameters and abnormal parameters determined by the power grid frequency change curve. An optimized objective function is then established based on the corrected objective function weight set to obtain the optimal control strategy.

9. The method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market according to claim 8, characterized in that, The process of determining fluctuation parameters and abnormal parameters based on the power grid frequency variation curve includes: Obtain a preset sliding time window, and divide the power grid frequency change curve according to the preset sliding time window to obtain several power grid frequency change curve segments; Calculate the average value of each power grid frequency change curve segment, and plot the average value change curve based on the average value of all power grid frequency change curve segments; Calculate the absolute value of the slope of adjacent average values ​​in the average value change curve, and determine the fluctuation parameter based on the average of the absolute values ​​of all slopes of the average value change curve; Obtain a preset standard frequency range, count the number of average values ​​exceeding the preset standard frequency range in the average value change curve, and determine the abnormal parameters based on the number of average values ​​exceeding the preset standard frequency range.

10. The method for coordinated optimization of AGC response and primary frequency regulation based on the electricity spot market according to claim 8, characterized in that, The step of correcting the initial objective function weight set based on the fluctuation parameters and anomaly parameters determined according to the power grid frequency variation curve includes: Obtain preset standard fluctuation parameters and preset standard abnormal parameters, calculate the deviation between the fluctuation parameters and the preset standard fluctuation parameters, and determine the first correction parameter based on the deviation between the fluctuation parameters and the preset standard fluctuation parameters. Calculate the deviation between the abnormal parameter and the preset standard abnormal parameter, and determine the second correction parameter based on the deviation between the abnormal parameter and the preset standard abnormal parameter; The initial objective function weight set is modified according to the first and second modification parameters to obtain the modified objective function weight set.

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