Method for calculating new energy light abandoning rate of regional power grid

Abstract

The invention relates to the technical field of new energy power systems, and particularly provides a regional power grid new energy light abandoning rate calculation method comprising the following steps: analyzing photovoltaic curve characteristics, and constructing a photovoltaic curve output model; obtaining the standard generating capacity of typical photovoltaic 1-12 months; calculating a power generation coefficient and a power generation duration coefficient of each month; calculating a photovoltaic output coefficient of each month, and performing normalization processing; predicting the photovoltaic installation scale of each month; the photovoltaic power generation amount of each month is predicted; calculating the output peak value of each month; the peak regulation capacity of each month is measured and calculated; comparing the peak regulation capacity of each month with the output peak value of each month, solving the ratio of the actual power generation capacity of each month to the corresponding power generation capacity by utilizing a photovoltaic curve output model, and further solving the actual power generation capacity of each month; and calculating the photovoltaic light abandoning rate of the area in one year according to the power generation amount and the actual power generation amount in one year. The method is simple in calculation, high in operability and accurate in calculation result.

Description

Technical Field

[0001] The present invention relates to the technical field of new energy power systems, and particularly relates to a method for calculating the new energy light curtailment rate of a regional power grid. Background Art

[0002] With the comprehensive development of the new power system, the installed capacity of new energy has been growing rapidly across the country. However, due to the characteristics of reverse load output and uncontrollability of new energy, the system peak shaving capacity and the power grid transmission capacity have become increasingly tense. Therefore, in the development planning research of the power system, it is necessary to calculate the new energy light curtailment rate of the power system to evaluate whether the new energy planning scheme is reasonable.

[0003] When calculating the new energy light curtailment rate of the power system, production simulation software is generally used for fitting calculation. This calculation process not only takes a long time, but also requires collecting comprehensive data on the output of various power sources and loads for one year, conducting reliability analysis and screening of the data, etc. A series of work, the calculation process is complex. In addition, due to too many dependent variables involved, the calculation is too theoretical, resulting in the calculation results often not meeting expectations.

[0004] To solve the above problems, the present invention provides a method for calculating the new energy light curtailment rate with simple calculation, strong operability, and accurate calculation results. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for calculating the new energy light curtailment rate of a regional power grid to solve the technical problems existing in the prior art. The specific technical solutions are as follows:

[0006] A method for calculating the new energy light curtailment rate of a regional power grid includes the following steps:

[0007] Analyze the curve characteristics of photovoltaic, and construct a photovoltaic curve output model;

[0008] Statistically analyze the actual power generation of multiple typical non-light-curtailed photovoltaics in the region from January to December and perform normalization processing, and combine the center clustering algorithm and the grey correlation method to obtain the standard power generation of the typical photovoltaics from January to December;

[0009] Calculate the power generation coefficient and the power generation duration coefficient for each month;

[0010] Obtain the output coefficient of the photovoltaic for each month according to the power generation coefficient and the power generation duration coefficient for each month, and perform normalization processing;

[0011] According to the new energy construction progress and grid connection plan, estimate the photovoltaic installed capacity for each month; according to the photovoltaic installed capacity for each month and the power generation coefficient for each month, predict the expected power generation of the photovoltaic for each month; according to the photovoltaic installed capacity for each month and the output coefficient for each month, obtain the output peak value for each month;

[0012] According to the maintenance and planning arrangements of the power system, estimate the fixed unit output, minimum output of adjustable units, adjustable space of adjustable units, adjustable space of power sources fed in through tie lines, adjustable space of power sources sent out through tie lines, and load magnitude for each month, and calculate the peak shaving capacity for each month;

[0013] Compare the peak shaving capacity for each month and the peak output for each month, use the photovoltaic curve output model to obtain the ratio of the actual power generation to the should-be power generation for each month, and then obtain the actual power generation for each month;

[0014] Calculate the light curtailment rate of photovoltaic power in this region within one year based on the should-be power generation and actual power generation for one year.

[0015] Furthermore, the photovoltaic curve output model is:

[0016]

[0017] In the above formula, j is the number of days in a year, Ws is the total power generation of photovoltaic power, Ps is the instantaneous value of photovoltaic output, A is the peak value of photovoltaic output, t is the time variable, t0 is the starting time of photovoltaic power generation, and T is the duration of photovoltaic power generation.

[0018] Furthermore, the steps to obtain the standard power generation of typical photovoltaic power from January to December include:

[0019] First, collect the outputs of multiple photovoltaic power plants in this region with installed capacities reaching the predetermined value and no light curtailment in the current year, count the photovoltaic power generation of the corresponding photovoltaic power plants from January to December, and use it as the typical photovoltaic power generation, and normalize it;

[0020] Then, use the k-means clustering algorithm to obtain the center point of the typical photovoltaic power generation for each month, and use the center point as the ideal power generation for each month;

[0021] Finally, use the grey relational analysis method to select the typical photovoltaic power generation with the highest correlation with the ideal power generation, and finally use the power generation from January to December corresponding to this typical photovoltaic power generation as the standard power generation.

[0022] Furthermore, the specific calculation of the power generation coefficient for each month is:

[0023] Take the Jth month with the most power generation among the standard power generations from January to December as the reference month, and the standard power generation of the Jth month is the reference power; divide the standard power generation of each month's photovoltaic power by the standard power generation of the Jth month to obtain the power generation coefficient for each month, that is:

[0024]

[0025] In the above formula, γ i is the power generation coefficient for the ith month, W J is the reference power, and W i is the standard power generation for the ith month.

[0026] Further, the specific calculation of the power generation duration coefficient for each month is as follows:

[0027] Statistical standard power generation corresponding to the photovoltaic power station's standard power generation duration from January to December, and take the standard power generation duration of the K months with the longest standard power generation duration as the reference power generation duration; the ratio of the standard power generation duration of each month of photovoltaic to the standard power generation duration of the K months is used to obtain the power generation duration coefficient of each month, that is:

[0028]

[0029] In the above formula, τ i is the power generation duration coefficient of the i-th month, T K is the reference power generation duration, T i is the standard power generation duration of the i-th month.

[0030] Further, the output coefficient of each month of photovoltaic is the ratio of the power generation coefficient of each month to the power generation duration coefficient of each month, that is:

[0031]

[0032] In the above formula, η i is the output coefficient of the i-th month;

[0033] Select the N months with the largest output coefficient as the reference output coefficient and normalize it, that is:

[0034]

[0035] In the above formula, is the standard output coefficient of the i-th month, η N is the reference output coefficient, that is, the N months are defined as full output months. Further, the output peak of each month is:

[0036] Ws i ≈E i ×W i Equation 7);

[0037]

[0038] In Equation 7) and Equation 8), Ws i is the photovoltaic power generation amount that should be generated in the i-th month, E i is the photovoltaic installed capacity of each month, A i is the output peak of the i-th month;

[0039] According to Equation 2), Equation 7) and Equation 8), we can get:

[0040]

[0041] In Equation 9), Psi is the instantaneous value of the equivalent power generation of PV for the i-th month.

[0042] Furthermore, the peak shaving capacity for each month is:

[0043] B i = min(GK i + LIK i , F i - L i - M i + LOK i ) Equation (10);

[0044] In Equation (10), B i is the peak shaving capacity for each month, M i is the output of fixed units for each month, L i is the minimum output of adjustable units, GK i is the adjustable space of adjustable units, LIK i is the adjustable space of power input from tie lines, LOK i is the adjustable space of power output from tie lines, F i is the load magnitude.

[0045] Furthermore, by comparing the peak shaving capacity B i of each month and the peak output A i of each month, when B i < A i , the part where Ps i > B i needs to be discarded. According to the PV curve power output model, the discarded power is the part of the PV curve power output model that is greater than B i . The actual power output model and actual power generation are obtained, that is:

[0046] if B i < A i

[0047] if B i ≥ A i Psa i = Ps i

[0048]

[0049] In Equations (11) and (12), t1 and t2 are the solutions of Ps i = B i , t1 < t2, Psa i is the instantaneous value of the actual equivalent power output for the i-th month, and Wsa i is the actual power generation for the i-th month;

[0050] Calculate the ratio φ of the actual power generation to the expected power generation for each month according to Equations (1), (2), (11), and (12), i.e.: i , namely:

[0051]

[0052] The actual power generation for each month is obtained according to Equations (9) and (13) as:

[0053]

[0054] Furthermore, the light curtailment rate of photovoltaic power in this area within one year is:

[0055]

[0056] In Equation (15), μ is the light curtailment rate of photovoltaic power in this area within one year.

[0057] Applying the technical solution of the present invention has the following beneficial effects:

[0058] A method for calculating the light curtailment rate of new energy in a regional power grid provided by the present invention, compared with the method for calculating the light curtailment rate of the traditional simulation model (using simulation software to perform power balance calculations for 8760 hours in a year, and then accumulating the surplus power to calculate the light curtailment rate of photovoltaic power), the advantages of the method of the present invention are that the model is simple and easy to understand, the calculation amount is small, the calculation efficiency is high, the operability is strong, and the calculation result is more in line with the actual situation and the calculation accuracy is high.

[0059] In addition to the purposes, features, and advantages described above, the present invention has other purposes, features, and advantages. The following will refer to the drawings to further elaborate on the present invention in detail. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] The drawings constituting a part of the present invention are used to provide a further understanding of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0061] Figure 1 is a flowchart of the method for calculating the light curtailment rate of new energy in the regional power grid of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0062] The following will elaborate on the embodiments of the present invention in detail with reference to the drawings, but the present invention can be implemented in various different ways defined and covered.

[0063] In the description of the present invention, it should be noted that the orientation or positional relationship indicated by the terms "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", "front", "rear", "lateral", "longitudinal", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention.

[0064] In addition, the terms "first", "second", etc. are only used for descriptive purposes and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first", "second", etc. may explicitly or implicitly include one or more of such features. In the description of the present invention, unless otherwise specified, the meaning of "a plurality" is two or more.

[0065] Embodiment:

[0066] The present invention provides a method for calculating the curtailment rate of new energy in a regional power grid. The method is as Figure 1 shown, and its content includes the following steps:

[0067] (1) Analyze the curve characteristics of photovoltaic power generation and construct a photovoltaic curve output model;

[0068] Photovoltaic power generation only occurs during the day, and the daily output curve of photovoltaic power generation is approximately a sine function. Therefore, a daily output model of the photovoltaic curve is constructed based on the sine function, that is:

[0069]

[0070] In the above formula, j is the number of days in a year, Ws is the total power generation of photovoltaic power generation, Ps is the instantaneous value of photovoltaic power output, A is the peak value of photovoltaic power output, t is the time variable, t0 is the starting time of photovoltaic power generation, and T is the photovoltaic power generation duration.

[0071] (2) Statistically analyze the actual power generation of multiple typical non-curtailed photovoltaic power generations in the region from January to December and perform normalization processing. Combine the center clustering algorithm and the grey correlation method to obtain the standard power generation of typical photovoltaic power generations from January to December. Specifically:

[0072] First, collect the power output (accurate to every hour) of multiple photovoltaic power stations in the region with an installed capacity of 10,000 kW or more (the lower limit of the selected installed capacity can be appropriately adjusted according to the total installed capacity of regional photovoltaic power generation) and without curtailment in the current year. Statistically analyze the photovoltaic power generation of the corresponding photovoltaic power stations from January to December and use it as the typical photovoltaic power generation, and perform normalization processing on it;

[0073] Then, the center of the typical photovoltaic power generation for each month is obtained by using the center clustering algorithm, and the center is used as the ideal power generation for each month;

[0074] Finally, the typical photovoltaic power generation with the highest correlation with the ideal power generation is selected by using the grey correlation method, and the power generation from January to December corresponding to this typical photovoltaic power generation is finally used as the standard power generation.

[0075] (3) Calculate the power generation coefficient and power generation duration coefficient for each month. Specifically:

[0076] Calculating the power generation coefficient for each month is specifically:

[0077] Take the Jth month with the most power generation from the standard power generation from January to December as the reference month, and the standard power generation in the Jth month is the reference power; the standard power generation of each month's photovoltaic divided by the standard power generation in the Jth month gives the power generation coefficient for each month, that is:

[0078]

[0079] In the above formula, γ i is the power generation coefficient for the ith month, W J is the reference power, and W i is the standard power generation for the ith month.

[0080] Calculating the power generation duration coefficient for each month is specifically:

[0081] Statistical the standard power generation duration of the photovoltaic power station corresponding to the standard power generation from January to December, and take the standard power generation duration of the Kth month with the longest power generation duration as the reference power generation duration; the standard power generation duration of each month's photovoltaic divided by the standard power generation duration of the Kth month gives the power generation duration coefficient for each month, that is:

[0082]

[0083] In the above formula, τ i is the power generation duration coefficient for the ith month, T K is the reference power generation duration, and T i is the standard power generation duration for the ith month.

[0084] (4) Obtain the output coefficient of the photovoltaic for each month according to the power generation coefficient and power generation duration coefficient for each month, and perform normalization processing. Specifically:

[0085] The output coefficient of the photovoltaic for each month is the power generation coefficient for each month divided by the power generation duration coefficient for each month, that is:

[0086]

[0087] In the above formula, η i is the output coefficient for the ith month.

[0088] J is not necessarily equal to K, and the maximum value of the output coefficient is not necessarily equal to 1. Therefore, the Nth month with the largest output coefficient is selected as the reference output coefficient and normalized, that is:

[0089]

[0090] In the above formula, is the standard output coefficient of the ith month, and η N is the reference output coefficient, that is, the Nth month is defined as the full output month.

[0091] (5) According to the new energy construction progress and grid connection plan, estimate the monthly photovoltaic installed capacity; according to the monthly photovoltaic installed capacity and monthly power generation coefficient, predict the monthly generated electricity of photovoltaic; according to the monthly photovoltaic installed capacity and monthly output coefficient, obtain the monthly output peak. Specifically:

[0092] The monthly output peak is:

[0093] Ws i ≈E i ×W i Formula 7);

[0094]

[0095] In Formula 7) and Formula 8), Ws i is the monthly generated electricity of photovoltaic, E i is the monthly photovoltaic installed capacity, A i is the output peak of the ith month;

[0096] According to Formula 2), Formula 7) and Formula 8), we can get:

[0097]

[0098] In Formula 9), Ps i is the instantaneous value of the equivalent output of the generated electricity of photovoltaic in the ith month.

[0099] (6) According to the maintenance and planning arrangements of the power system, estimate the fixed unit output, minimum output of adjustable units, adjustable space of adjustable units, adjustable space of power sources fed into the grid connection line, adjustable space of power sources sent out of the grid connection line and load size in each month, and measure the peak shaving capacity in each month. Specifically:

[0100] The peak shaving capacity in each month is:

[0101] B i =min(GK i +LIK i ,F i -L i -M i +LOKi ) Equation (10);

[0102] In Equation (10), B i is the peak shaving capacity for each month, M i is the output of fixed units for each month, L i is the minimum output of adjustable units, GK i is the adjustable space of adjustable units, LIK i is the adjustable space of the power supply fed in through the tie line, LOK i is the adjustable space of the power supply sent out through the tie line, F i is the load magnitude.

[0103] (7) Compare the peak shaving capacity for each month and the peak output for each month, and use the photovoltaic curve output model to find the ratio of the actual power generation to the expected power generation for each month, and then obtain the actual power generation for each month. Specifically:

[0104] Compare the peak shaving capacity B i and the peak output A i for each month. When B i < A i , the part where Ps i > B i needs to be discarded. According to the photovoltaic curve output model, the discarded power is the part greater than B i in the photovoltaic curve output model, and the actual output model and actual power generation are obtained, that is:

[0105] if B i < A i

[0106] if B i ≥ A i Psa i = Ps i

[0107]

[0108] In Equations (11) and (12), t1 and t2 are the solutions of Ps i = B i , t1 < t2, Psa i is the instantaneous value of the actual equivalent output for the i-th month, and Wsa i is the actual power generation for the i-th month;

[0109] Calculate the ratio φ i of the actual power generation to the expected power generation for each month according to Equations (1), (2), (11), and (12), that is:

[0110]

[0111] According to Equation (9) and Equation (13), the actual power generation per month is as follows:

[0112]

[0113] (8) Calculate the light curtailment rate μ of photovoltaic power in this area within one year based on the expected power generation and actual power generation in one year:

[0114]

[0115] In Equation (15), μ is the light curtailment rate of photovoltaic power in this area within one year.

[0116] In this embodiment, a certain regional power grid in the northwest region of China is selected for verification calculation. The standard power generation, power generation coefficient, power generation duration coefficient, and standard output coefficient of standard photovoltaic power from January to December in this area are shown in Table 1 below.

[0117] Table 1 Standard photovoltaic power generation and various coefficients of typical photovoltaic power from January to December

[0118]

[0119]

[0120] As of the end of 2024, the thermal power installed capacity in this area reached 3 million kilowatts, the hydropower was about 0.23 million kilowatts, and the maximum installed capacity of photovoltaic power was 1.77 million kilowatts. After measurement, in 2024, the maximum peak shaving capacity was 1.84 million kilowatts, the expected photovoltaic power generation was 2.655 billion kWh, the actual power generation was 2.599 billion kWh, and the light curtailment rate was 2.11%. The comparison with the actual statistical data is shown in Table 2.

[0121] Table 2 Comparison of the total light curtailment rate in 2024

[0122]

[0123] As can be seen from Table 2, the light curtailment rate calculated by this method is 2.11%, and the actually statistically light curtailment rate is 2.06%, with a difference of only 0.05%. Compared with the allowable error threshold (0.75% - 2%) of traditional electricity meter (current sensor) measurement, the calculation accuracy of the light curtailment rate by this method is relatively high.

[0124] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for calculating the abandonment rate of renewable energy in a regional power grid, characterized in that: The following steps are involved: Analyze the curve characteristics of photovoltaics and build a photovoltaic curve output model; The actual power generation of several typical non-abandoned photovoltaic power plants in the region from January to December was counted and normalized, and the standard power generation of typical photovoltaic power plants from January to December was obtained by combining the center clustering algorithm and the grey correlation method; Calculate the power generation coefficient and power generation duration coefficient for each month; The photovoltaic output coefficient for each month is obtained based on the power generation coefficient and power generation duration coefficient for each month, and normalized; According to the progress of new energy construction and grid connection plan, the photovoltaic installed capacity of each month is estimated; according to the photovoltaic installed capacity of each month and the power generation coefficient of each month, the photovoltaic power generation of each month is predicted; according to the photovoltaic installed capacity of each month and the output coefficient of each month, the output peak of each month is obtained; According to the maintenance and planning arrangements of the power system, the output of fixed units, the minimum output of adjustable units, the adjustable space of adjustable units, the adjustable space of the interconnection line input power, the adjustable space of the interconnection line output power and the load size are estimated in each month, and the peak load regulation capacity of each month is calculated; Compare the peak load regulation capacity and output peak of each month, and use the photovoltaic curve output model to calculate the ratio of actual power generation to expected power generation in each month, and then calculate the actual power generation of each month; The photovoltaic abandonment rate in the area within a year is calculated based on the expected power generation and actual power generation in a year.

2. The method for calculating the abandonment rate of renewable energy in a regional power grid according to claim 1 is characterized in that: The photovoltaic curve output model is: In the above formula, j is the number of days in a year, Ws is the total photovoltaic power generation, Ps is the instantaneous value of photovoltaic output, A is the peak photovoltaic output, t is the time variable, t0 is the start time of photovoltaic power generation, and T is the duration of photovoltaic power generation.

3. The method for calculating the abandonment rate of renewable energy in a regional power grid according to claim 1 is characterized in that: The steps to derive the standard power generation of a typical photovoltaic system from January to December include: First, the output of multiple photovoltaic power stations in the region whose installed capacity reached the predetermined value and had not abandoned power in the year was collected, and the photovoltaic power generation of the corresponding photovoltaic power stations from January to December was counted and taken as the typical photovoltaic power generation, and then normalized; Then, the center point of typical photovoltaic power generation in each month is obtained by using the center clustering algorithm, and the center point is taken as the ideal power generation in each month; Finally, the grey correlation method is used to select the typical photovoltaic power generation with the highest correlation with the ideal power generation, and finally the power generation from January to December corresponding to the typical photovoltaic power generation is used as the standard power generation.

4. The method for calculating the abandonment rate of renewable energy in a regional power grid according to claim 3 is characterized in that: The specific calculation of the power generation coefficient for each month is: From the standard power generation from January to December, the month with the largest power generation is taken as the base month, and the standard power generation of month J is taken as the base power; the power generation coefficient of each month is obtained by dividing the standard power generation of photovoltaic power generation in each month by the standard power generation of the previous month J, that is: In the above formula, γ i is the power generation coefficient of the ith month, W J is the reference power, W i is the standard power generation in month i.

5. The method for calculating the abandonment rate of renewable energy in a regional power grid according to claim 4 is characterized in that: The specific calculation of the power generation duration coefficient for each month is: The standard power generation time of the photovoltaic power station from January to December corresponding to the standard power generation is counted, and the standard power generation time of month K with the longest standard power generation time is taken as the benchmark power generation time; the standard power generation time of photovoltaic power generation in each month is compared with the standard power generation time of the previous month K, and the power generation time coefficient of each month is obtained, that is: In the above formula, τ i is the power generation duration coefficient of the i-th month, T K is the benchmark power generation duration, T i is the standard power generation duration in month i.

6. The method for calculating the abandonment rate of renewable energy in a regional power grid according to claim 5 is characterized in that: The monthly output coefficient of photovoltaic power generation is the monthly power generation coefficient divided by the monthly power generation duration coefficient, that is: In the above formula, η i is the output coefficient of the i-th month; Select the Nth month with the largest output coefficient as the benchmark output coefficient and normalize it, that is: In the above formula, is the standard output coefficient of the ith month, η N is the base output coefficient, that is, month N is defined as the full output month.

7. The method for calculating the abandonment rate of renewable energy in a regional power grid according to claim 6, characterized in that: The peak output of each month is: Ws i ≈E i ×W i Equation 7); In formula 7) and formula 8), Ws i is the photovoltaic power generation in the ith month, E i is the photovoltaic installed capacity of each month, A i is the peak output of the ith month; According to formula 2), formula 7) and formula 8), we get: In formula 9), Ps i is the instantaneous value of the photovoltaic equivalent output in the i-th month.

8. The method for calculating the abandonment rate of renewable energy in a regional power grid according to claim 7, characterized in that: The peak load regulation capacity of each month is: B i = min(GK i + LIK i , F i - L i - M i + LOK i ) Equation (10); In formula 10), B i is the peak load regulation capacity of each month, M i The fixed unit output for each month, L i is the minimum output of the adjustable unit, GK i Adjustable space for adjustable units, LIK i Adjustable space and LOK for power supply to the contact line i Adjustable space for sending power to the interconnection line, F i For the load size.

9. The method for calculating the abandonment rate of renewable energy in a regional power grid according to claim 8, characterized in that: Compare the peak load capacity of each month B i And the peak output A of each month i , when B i <A i When Ps i >B i The part needs to be discarded. According to the photovoltaic curve output model, the discarded power is the power greater than B in the photovoltaic curve output model. i The actual output model and actual power generation are obtained from the part, namely: ifB i ≥A i Psa i =Ps i W i =∫Psa i dt (formula 12); In formula 11) and formula 12), t1 and t2 are Ps i =B i Solution, t1<t2, Psa i is the instantaneous value of the actual equivalent output in the ith month, Wsa i is the actual power generation in month i; The ratio of actual power generation to required power generation is calculated based on equations 1), 2), 11) and 12). Right now: According to equation 9) and equation 13), the actual power generation per month is:

10. The method for calculating the abandonment rate of renewable energy in a regional power grid according to claim 9, characterized in that: The photovoltaic abandonment rate in this area within one year is: In formula (15), μ is the photovoltaic abandonment rate in the region within one year.

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