Method and system for configuring reserve capacity of pumped storage power station based on risk utility

Abstract

The present invention discloses a method for configuring the reserve capacity of a pumped-storage power station based on risk utility, comprising obtaining data of a target power system; obtaining forecast data of the output of new energy for the next day; obtaining actual output data of several new energy sources; calculating several output-deviation scatter plots; constructing a risk utility function; fitting the risk utility function using the least squares method; and calculating the final result of the configuration of the reserve capacity of the pumped-storage power station. The present invention also discloses a system for implementing the method for configuring the reserve capacity of a pumped-storage power station based on risk utility. The present invention uses a risk utility function to measure the attitude of a pumped-storage power station towards the uncertainty of the output of new energy, and fits the risk utility function according to the output deviation, and then configures the reserve capacity of the pumped storage; therefore, the present invention has high accuracy, good reliability, and is objective and scientific.

Description

Technical Field

[0001] The present invention belongs to the field of electrical automation, and in particular relates to a risk-utility-based pumped storage power station reserve capacity configuration method and system. Background Art

[0002] With the development of economy and technology and the improvement of people's living standards, electricity has become an indispensable secondary energy source in people's production and life, bringing endless convenience to people's production and life. Therefore, ensuring the stable and reliable supply of electricity has become one of the most important tasks of the power system.

[0003] With the large-scale integration of new energy power generation systems into the power grid, the safe and stable operation of the power system has ushered in greater challenges. Energy storage devices can greatly adjust the peak and valley differences of the power system, thereby ensuring the safe and stable operation of the power system. Therefore, energy storage devices are the best solution for the power system to cope with large-scale new energy grid integration.

[0004] Pumped storage power stations are the largest energy storage devices used in power systems; therefore, how to configure the reserve capacity of pumped storage power stations has become one of the research focuses of power systems. If the reserve capacity is too small, the pumped storage power station cannot smooth out the uncertainty of the new energy power generation system, and cannot achieve the purpose of promoting the consumption of new energy and stabilizing the operation of the power system; if the reserve capacity is too much, it will cause a waste of reserve capacity, thereby wasting resources.

[0005] At present, the reserve capacity configuration method of pumped storage power stations still adopts empirical values, that is, according to the operation of the power grid, an empirical estimate of a reserve capacity is made, and the configuration is directly carried out according to the estimated value. However, this method is highly subjective and inaccurate, and is no longer suitable for the operation of today's power system. Summary of the invention

[0006] One of the purposes of the present invention is to provide a risk-utility-based reserve capacity configuration method for a pumped-storage power station with high accuracy, good reliability and objectivity.

[0007] A second object of the present invention is to provide a system for implementing the risk-utility-based pumped-storage power station reserve capacity configuration method.

[0008] The risk-utility-based pumped storage power station reserve capacity configuration method provided by the present invention comprises the following steps:

[0009] S1. Acquire data of the target power system;

[0010] S2. According to the data obtained in step S1, the forecast data of the new energy output for the next day is obtained;

[0011] S3. Set the error distribution of the actual output of new energy, and use the sampling method to obtain some actual output data of new energy;

[0012] S4. Calculate several output-deviation scatter plots based on the actual output data of new energy obtained in step S3;

[0013] S5. Construct a risk utility function based on the risk preference of pumped storage power stations;

[0014] S6. fitting the risk-utility function using the least squares method according to the output-deviation scatter plot obtained in step S4 and the risk-utility function constructed in step S5;

[0015] S7. According to the fitting result obtained in step S6, the final backup capacity configuration result of the pumped storage power station is calculated.

[0016] The prediction data of the new energy output described in step S2 specifically includes prediction data of wind power processing and prediction data of photovoltaic output.

[0017] The error distribution of setting the actual output of new energy in step S3 and obtaining a number of actual output data of new energy by using a sampling method specifically includes the following steps:

[0018] Assume that the actual output of renewable energy follows a normal distribution with an expected value and a standard deviation of 10% of the predicted value:

[0019] P t,i ~N(μ,σ 2 )

[0020] Where P t,i is the actual output value of the i-th renewable energy source at time t; μ is the expected value, and μ=P t pre , P t pre is the predicted output value of the new energy at time t; σ is the standard deviation of the actual output of the new energy, and σ=0.1P t pre .

[0021] Step S4, according to the actual output data of the new energy obtained in step S3, calculates a number of output-deviation scatter plots, which specifically includes the following steps:

[0022] According to the actual output data of the new energy obtained in step S3, the output deviation ΔP of the new energy at time t is calculated. t,i ΔP t,i =|P t,i -P t pre |;P t,i is the actual output value of the i-th renewable energy source at time t; Pt pre is the predicted output value of the new energy at time t;

[0023] With the output deviation as the ordinate and the actual output as the abscissa, several output-deviation scatter plots are obtained.

[0024] The step S5 described in constructing a risk utility function according to the risk preference of the pumped storage power station specifically includes the following steps:

[0025] If the willingness of pumped storage power stations to provide backup capacity decreases as the uncertainty of renewable energy processing increases, then the function U(x t )=c1+a1log(c3x t +c2) as the risk utility function of pumped storage power station;

[0026] If the willingness of pumped storage power stations to provide backup capacity increases nonlinearly with the increase of uncertainty in renewable energy processing, then the function As a risk utility function for pumped storage power plants;

[0027] If the willingness of pumped storage power stations to provide backup capacity increases linearly with the increase of uncertainty in the handling of renewable energy, then the function U(x t )=c1+a1·x t As a risk utility function for pumped storage power plants;

[0028] Among them, x t The independent variable is the predicted output value P of the new energy at time t. t pre ; U(x t ) is the utility value of the reserve capacity provided by the pumped storage power station; a1, a2, c1, c2 and c3 are all function parameters.

[0029] Step S7, according to the fitting result obtained in step S6, calculates and obtains the final standby capacity configuration result of the pumped storage power station, which specifically includes the following steps:

[0030] The final reserve capacity of the pumped storage power station is calculated using the following formula:

[0031]

[0032] Where rc t is the reserve capacity of each pumped storage unit; λ is the set capacity factor; U(x t ) is the risk utility function of the pumped storage power station; N H is the number of pumped storage units.

[0033] The present invention also provides a system for implementing the risk-utility-based pumped-storage power station reserve capacity configuration method, including a data acquisition module, an output prediction calculation module, an actual output calculation module, a scatter plot calculation module, a risk utility function calculation module, a fitting module and a reserve capacity calculation module; the data acquisition module, the output prediction calculation module, the actual output calculation module and the scatter plot calculation module are connected in series in sequence; the fitting module and the reserve capacity calculation module are connected in series in sequence; the output ends of the scatter plot calculation module and the risk utility function calculation module are simultaneously connected to the fitting module; the data acquisition module is used to acquire data of the target power system and upload the data to the output prediction calculation module; the output prediction calculation module is used to calculate the forecast data of the next day's new energy output based on the received data, and upload the data to the output prediction calculation module. Upload the actual output calculation module; the actual output calculation module is used to set the error distribution of the actual output of new energy according to the received data, and use the sampling method to obtain a number of actual output data of new energy, and upload the data to the scatter plot calculation module; the scatter plot calculation module is used to calculate a number of output-deviation scatter plots according to the received data, and upload the data to the fitting module; the risk utility function calculation module is used to construct a risk utility function according to the risk preference of the pumped storage power station, and upload the data to the fitting module; the fitting module is used to fit the risk utility function according to the received data using the least squares method, and upload the data to the spare capacity calculation module; the spare capacity calculation module is used to calculate the final spare capacity configuration result of the pumped storage power station according to the received data.

[0034] The risk-utility-based pumped-storage power station reserve capacity configuration method and system disclosed in the present invention adopt a risk-utility function to measure the attitude of the pumped-storage power station to the uncertainty of the output of renewable energy, and fit the risk-utility function according to the output deviation, and then configure the pumped-storage reserve capacity; therefore, the present invention has high accuracy, good reliability, and is objective and scientific. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a schematic diagram of the method flow of the present invention.

[0036] Figure 2 Schematic diagram of output-deviation scatter points of an embodiment of the method of the present invention.

[0037] Figure 3 Schematic diagram of the risk-utility function fitting results of the method embodiment of the present invention.

[0038] Figure 4 This is a schematic diagram of the pumped storage reserve capacity utility results of an embodiment of the method of the present invention.

[0039] Figure 5 It is a schematic diagram of the system function modules of the present invention. DETAILED DESCRIPTION

[0040] like Figure 1 The method flow chart of the present invention is shown as follows: The risk-utility-based pumped storage power station reserve capacity configuration method provided by the present invention comprises the following steps:

[0041] S1. Acquire data of the target power system;

[0042] S2. According to the data obtained in step S1, the forecast data of the new energy output for the next day is obtained; the forecast data of the new energy output specifically includes the forecast data of wind power processing and the forecast data of photovoltaic output;

[0043] S3. Setting the error distribution of the actual output of new energy and obtaining some actual output data of new energy by sampling method; specifically including the following steps:

[0044] Assume that the actual output of renewable energy follows a normal distribution with an expected value and a standard deviation of 10% of the predicted value:

[0045] P t,i ~N(μ,σ 2 )

[0046] Where P t,i is the actual output value of the i-th renewable energy source at time t; μ is the expected value, and μ=P t pre , P t pre is the predicted output value of the new energy at time t; σ is the standard deviation of the actual output of the new energy, and σ=0.1P t pre ;

[0047] S4. According to the actual output data of the new energy obtained in step S3, several output-deviation scatter plots are calculated; specifically, the steps include:

[0048] According to the actual output data of the new energy obtained in step S3, the output deviation ΔP of the new energy at time t is calculated. t,i ΔP t,i =|P t,i -P t pre |;P t,i is the actual output value of the i-th renewable energy source at time t; P t pre is the predicted output value of the new energy at time t;

[0049] With the output deviation as the ordinate and the actual output as the abscissa, several output-deviation scatter plots are obtained;

[0050] S5. Construct a risk utility function based on the risk preference of the pumped storage power station; specifically, the steps include:

[0051] If the willingness of pumped storage power stations to provide backup capacity decreases as the uncertainty of renewable energy processing increases, then the function U(x t )=c1+a1log(c3x t +c2) as the risk utility function of pumped storage power station;

[0052] If the willingness of pumped storage power stations to provide backup capacity increases nonlinearly with the increase of uncertainty in renewable energy processing, then the function As a risk utility function for pumped storage power plants;

[0053] If the willingness of pumped storage power stations to provide backup capacity increases linearly with the increase of uncertainty in the handling of renewable energy, then the function U(x t )=c1+a1·x t As a risk utility function for pumped storage power plants;

[0054] Among them, x t The independent variable is the predicted output value P of the new energy at time t. t pre ; U(x t ) is the utility value of the reserve capacity provided by the pumped storage power station; a1, a2, c1, c2 and c3 are all function parameters;

[0055] S6. According to the output-deviation scatter plot obtained in step S4 and the risk utility function constructed in step S5, the risk utility function is fitted by using the least square method; in specific implementation, the curve_fit function can be called on the Python platform, and the risk utility function is fitted by using the least square method to obtain function parameters;

[0056] S7. According to the fitting result obtained in step S6, the final backup capacity configuration result of the pumped storage power station is calculated; specifically comprising the following steps:

[0057] The final reserve capacity of the pumped storage power station is calculated using the following formula:

[0058]

[0059] Where rc t is the reserve capacity of each pumped storage unit; λ is the set capacity factor; U(x t ) is the risk utility function of the pumped storage power station; N H is the number of pumped storage units.

[0060] The method of the present invention is further described below in conjunction with an embodiment:

[0061] The forecast data of the next day's renewable energy 24-hour output are selected, as shown in Table 1;

[0062] Table 1 Typical daily renewable energy output forecast data

[0063]

[0064] Assuming that the error of the actual output of new energy follows a normal distribution with a standard deviation of 10% of the predicted value, a large amount of actual output data is generated through the Monte Carlo sampling method; the output deviation between the actual value and the predicted value is calculated, and the actual output is used as the horizontal axis and the output deviation is used as the vertical axis to generate a certain scale of "output-deviation" scatter plot, such as Figure 2 shown.

[0065] The risk preference of pumped storage is divided into risk aversion, risk preference and risk neutrality, and the corresponding concave, convex and linear risk utility functions are constructed respectively; based on the generated scatter plot, the risk utility function is fitted by the least squares method, and the results are as follows: Figure 3 As shown;

[0066] The utility function is:

[0067] Concave utility function: U(x t )=-3610.26+78821.44×log(9.46×10 -7 x t +1.047);

[0068] Convex utility function:

[0069] Linear utility function: U(x t )=10.43+0.071x t ;

[0070] from Figure 3 It can be seen that the concave risk utility function graph (curve 1) and the linear risk utility function graph (straight line 3) are basically the same, and the convex risk utility function graph (curve 2) is quite different from the former two. In addition, the three curves intersect at around 1200 and 2300 respectively.

[0071] According to the obtained risk utility analytical formula, the predicted value of the next day's renewable energy output is substituted into the analytical formula to obtain the utility value of the backup provided by pumped storage. The result is as follows: Figure 4 shown.

[0072] from Figure 4 It can be seen that before 14:00, the utility value of the reserve capacity configured by the convex function is generally higher than the utility values ​​of the other two functions. This is because the predicted output values ​​of new energy sources are all less than 1200MW before 14:00. Figure 3The graph of the convex function is above the graphs of the other two functions. At other times, the utility value of the reserve capacity configured by the convex function is generally lower than the utility values ​​of the other two functions. This is because the predicted output values ​​of new energy at other times are all in the range of 1200-2300MW. Figure 3 The graph of the convexity function is below the graphs of the other two functions. Figure 4 Results and Figure 3 It can be inferred that if the predicted value of renewable energy output is higher than 2300MW, the utility value of the reserve capacity configured by the convex function will be higher than the utility values ​​of the other two functions.

[0073] Finally, based on the overall situation of the output deviation of new energy and the rated operating capacity of the pumped-storage unit, the capacity coefficient is set and the number of pumped-storage units is determined, and then the backup capacity provided by the pumped-storage unit can be calculated.

[0074] like Figure 5 The system functional module schematic diagram of the present invention is shown as follows: the system disclosed in the present invention for realizing the risk-utility-based pumped-storage power station spare capacity configuration method comprises a data acquisition module, an output prediction calculation module, an actual output calculation module, a scatter plot calculation module, a risk utility function calculation module, a fitting module and a spare capacity calculation module; the data acquisition module, the output prediction calculation module, the actual output calculation module and the scatter plot calculation module are connected in series in sequence; the fitting module and the spare capacity calculation module are connected in series in sequence; the output ends of the scatter plot calculation module and the risk utility function calculation module are simultaneously connected to the fitting module; the data acquisition module is used to acquire the data of the target power system and upload the data to the output prediction calculation module; the output prediction calculation module is used to calculate the forecast of the next day's new energy output according to the received data. The measured data is uploaded to the actual output calculation module; the actual output calculation module is used to set the error distribution of the actual output of the new energy according to the received data, and adopts the sampling method to obtain a number of actual output data of the new energy, and uploads the data to the scatter plot calculation module; the scatter plot calculation module is used to calculate a number of output-deviation scatter plots according to the received data, and upload the data to the fitting module; the risk utility function calculation module is used to construct a risk utility function according to the risk preference of the pumped storage power station, and upload the data to the fitting module; the fitting module is used to fit the risk utility function according to the received data by the least squares method, and upload the data to the spare capacity calculation module; the spare capacity calculation module is used to calculate the final spare capacity configuration result of the pumped storage power station according to the received data.

Claims

1. A method for configuring reserve capacity of a pumped storage power station based on risk utility, comprising the following steps: S1. Acquire data of the target power system; S2. According to the data obtained in step S1, the forecast data of the new energy output for the next day is obtained; S3. Set the error distribution of the actual output of new energy, and use the sampling method to obtain some actual output data of new energy; S4. Calculate several output-deviation scatter plots based on the actual output data of new energy obtained in step S3; S5. Construct a risk utility function based on the risk preference of pumped storage power stations; S6. fitting the risk-utility function using the least squares method according to the output-deviation scatter plot obtained in step S4 and the risk-utility function constructed in step S5; S7. According to the fitting result obtained in step S6, the final backup capacity configuration result of the pumped storage power station is calculated.

2. The risk-utility-based pumped storage power station reserve capacity configuration method according to claim 1 is characterized in that The prediction data of the new energy output described in step S2 specifically includes prediction data of wind power processing and prediction data of photovoltaic output.

3. The risk-utility-based pumped storage power station reserve capacity configuration method according to claim 2 is characterized in that The error distribution of setting the actual output of new energy in step S3 and obtaining a number of actual output data of new energy by using a sampling method specifically includes the following steps: Assume that the actual output of renewable energy follows a normal distribution with an expected value and a standard deviation of 10% of the predicted value: P t,i ~N(μ,σ 2 ) Where P t,i is the actual output value of the i-th renewable energy source at time t; μ is the expected value, and μ=P t pre , P t pre is the predicted output value of the new energy at time t; σ is the standard deviation of the actual output of the new energy, and σ=0.1P t pre .

4. The risk-utility-based pumped storage power station reserve capacity configuration method according to claim 3 is characterized in that Step S4, according to the actual output data of the new energy obtained in step S3, calculates a number of output-deviation scatter plots, which specifically includes the following steps: According to the actual output data of the new energy obtained in step S3, the output deviation ΔP of the new energy at time t is calculated. t,i ΔP t,i =|P t,i -P t pre |;P t,i is the actual output value of the i-th renewable energy source at time t; P t pre is the predicted output value of the new energy at time t; With the output deviation as the ordinate and the actual output as the abscissa, several output-deviation scatter plots are obtained.

5. The risk-utility-based pumped storage power station reserve capacity configuration method according to claim 4 is characterized in that The step S5 described in constructing a risk utility function according to the risk preference of the pumped storage power station specifically includes the following steps: If the willingness of pumped storage power stations to provide backup capacity decreases as the uncertainty of renewable energy processing increases, then the function U(x t )=c1+a1log(c3x t +c2) as the risk utility function of pumped storage power station; If the willingness of pumped storage power stations to provide backup capacity increases nonlinearly with the increase of uncertainty in renewable energy processing, then the function As a risk-utility function for pumped storage power plants; If the willingness of pumped storage power stations to provide backup capacity increases linearly with the increase of uncertainty in the handling of renewable energy, then the function U(x t )=c1+a1·x t As a risk-utility function for pumped storage power plants; Among them, x t The independent variable is the predicted output value P of the new energy at time t. t pre ; U(x t ) is the utility value of the reserve capacity provided by the pumped storage power station; a1, a2, c1, c2 and c3 are all function parameters.

6. The risk-utility-based pumped storage power station reserve capacity configuration method according to claim 5 is characterized in that Step S7, according to the fitting result obtained in step S6, calculates and obtains the final standby capacity configuration result of the pumped storage power station, which specifically includes the following steps: The final reserve capacity of the pumped storage power station is calculated using the following formula: Where rc t is the reserve capacity of each pumped storage unit; λ is the set capacity factor; U(x t ) is the risk utility function of the pumped storage power station; N H is the number of pumped storage units.

7. A system for implementing the risk-utility-based pumped storage power station reserve capacity configuration method according to any one of claims 1 to 6, characterized in that It includes a data acquisition module, an output prediction calculation module, an actual output calculation module, a scatter plot calculation module, a risk utility function calculation module, a fitting module and a spare capacity calculation module; the data acquisition module, the output prediction calculation module, the actual output calculation module and the scatter plot calculation module are connected in series in sequence; the fitting module and the spare capacity calculation module are connected in series in sequence; The output ends of the scatter plot calculation module and the risk utility function calculation module are simultaneously connected to the fitting module; the data acquisition module is used to obtain the data of the target power system and upload the data to the output prediction calculation module; the output prediction calculation module is used to calculate the prediction data of the new energy output of the next day based on the received data, and upload the data to the actual output calculation module; The actual output calculation module is used to set the error distribution of the actual output of the new energy according to the received data, and obtain a number of actual output data of the new energy by using the sampling method, and upload the data to the scatter plot calculation module; The scatter plot calculation module is used to calculate a number of output-deviation scatter plots based on the received data, and upload the data to the fitting module; The risk utility function calculation module is used to construct a risk utility function according to the risk preference of the pumped storage power station and upload the data to the fitting module; The fitting module is used to fit the risk utility function using the least squares method based on the received data, and upload the data to the spare capacity calculation module; the spare capacity calculation module is used to calculate the final spare capacity configuration result of the pumped storage power station based on the received data.

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