CN105243605A - Irradiation similarity based evaluation method for light and power abandonment amount of large photovoltaic power generation cluster - Google Patents

Abstract

The invention discloses an irradiation similarity based evaluation method for a light and power abandonment amount of a large photovoltaic power generation cluster. The method comprises: by using irradiation similarity, dynamically grouping photovoltaic power stations; and calculating the light and power abandonment amount of each cluster obtained by dynamical grouping. According to the scheme, the shortcomings in the prior art of complicated calculation process, small applicable range of a calculation mode, difficulty in obtaining calculation data, low accuracy of a calculation result can be overcome, so that the advantages of simple calculation process, wide applicable range of the calculation mode, rapidness for calculation and high accuracy of the calculation result can be realized.

Description

Estimation Method of Abandoned Photovoltaic Amount of Large-scale Photovoltaic Power Generation Cluster Based on Irradiance Similarity

technical field

The present invention relates to the technical field of photovoltaic power generation abandoned light quantity evaluation technology, in particular, to a large-scale photovoltaic power generation cluster waste light quantity assessment method based on irradiation similarity.

Background technique

Photovoltaic power station abandoned photovoltaic power refers to the power that can be generated by photovoltaic power stations but cannot be generated due to factors such as grid transmission channel restrictions, grid peak regulation needs, grid safety and stability operation needs, and grid equipment maintenance and failures.

Light abandonment is a common phenomenon in the process of large-scale development of photovoltaic power generation, similar to water abandonment in the process of hydropower generation. Large-scale photovoltaic power generation bases cover a wide area and generally include multiple photovoltaic power stations or photovoltaic power station groups. Due to the transmission limit of the grid transmission channel, real-time load balancing, and photovoltaic power station equipment failures and maintenance, etc., a certain degree of light abandonment will occur, resulting in Abandoned photoelectricity. A correct and scientific understanding of the problem of solar abandonment and a reasonable calculation and analysis of the amount of solar abandonment will contribute to the healthy and stable development of large-scale photovoltaic power generation, improve the level of grid dispatching and operation, and promote the coordinated development of photovoltaic power generation planning and grid planning , Improve the utilization rate and utilization level of clean energy.

At present, since large-scale photovoltaic power generation has just emerged in my country, the domestic photovoltaic power generation industry has not yet formed a standard for the evaluation algorithm of abandoned photovoltaic power. Then it is integrated to obtain the abandoned light quantity. However, for a million-kilowatt-level photovoltaic power generation base, the simultaneous rate of actual output of each photovoltaic power station is generally low, so calculations using this method will generally result in inaccurate calculations of abandoned photovoltaic power.

Previously, in the patent document with the patent number 201310168821.1, a method for evaluating the amount of abandoned light in photovoltaic bases based on a real-time optical resource monitoring network was proposed. The main problem is that the construction of an optical resource monitoring network is a long-term process, and many photovoltaic power generation bases may not yet Construction of optical resource monitoring network, in view of the above situation, this method is invalid.

In the patent document with the patent number 201310168700.7, a large-scale photovoltaic power generation base based on benchmark photovoltaic modules is proposed. Faults and data upload interruptions or errors of benchmark photovoltaic inverters.

In the prior art, at least there are defects such as complex calculation process, narrow application range of calculation methods, difficulty in obtaining calculation data, and poor accuracy of calculation results. This method will serve as an effective supplement to the prior art.

Contents of the invention

The purpose of the present invention is to address the above problems, and propose a large-scale photovoltaic power generation cluster based on the radiation similarity evaluation method for the abandoned photovoltaic power generation, to solve the problem of using the irradiation similarity to dynamically group photovoltaic power plants and calculate the abandoned photovoltaic power of each cluster. It is easier to calculate the power of the cluster's abandoned light, improve the applicability and accuracy of the calculation, and reduce the problem of calculation errors, so as to achieve the effects of simple calculation process, wide application range of calculation methods, fast acquisition of calculation data and good accuracy of calculation results, etc. .

In order to achieve the above purpose, the technical solution adopted by the present invention is: a large-scale photovoltaic power generation cluster abandoned light quantity evaluation method based on the similarity of irradiation, including: using the similarity of irradiation to dynamically group photovoltaic power plants; calculating the dynamic grouping obtained The amount of light curtailed per cluster.

Among them, the dynamic grouping of photovoltaic power stations by using the similarity of irradiation includes: forming each benchmark photovoltaic power station into a subcategory or cluster; for each non-benchmark photovoltaic power The irradiation similarity of photovoltaic power plants is sorted, and a benchmark photovoltaic power station with the highest irradiation similarity with the non-benchmark photovoltaic power station is selected among all benchmark photovoltaic power stations; each non-benchmark photovoltaic power station is added to the irradiation The benchmark photovoltaic power station with the highest similarity is located in the cluster.

Wherein, calculating the abandoned light quantity of each cluster obtained by the dynamic grouping includes: setting a statistical time period m and a calculation time interval t, the statistical time period m is greater than the calculation time interval t, and m and t are both natural numbers; At the beginning of the statistical time period m, obtain the start-up capacity and theoretical output of each benchmark photovoltaic power station within the calculation time interval t; within the statistical time period m, according to the obtained start-up capacity and theoretical output, obtain the entire The abandoned photovoltaic power of the photovoltaic power generation base; at the end of the statistical period m, obtain the abandoned photovoltaic power of the entire photovoltaic cluster within the statistical period m.

Further, at the beginning of the statistical period m, obtain the start-up capacity and theoretical output of each benchmark photovoltaic power plant within the calculation time interval t, including: at the beginning of the statistical period m, upload once in each calculation time interval t through the photovoltaic power station The real-time information of photovoltaic power generation to obtain the start-up capacity of the benchmark photovoltaic power station, and calculate the average output coefficient of each benchmark photovoltaic power station within the calculation time interval t: Among them, P _i is the actual output of the i-th benchmark photovoltaic power plant, is the start-up capacity of the i-th benchmark photovoltaic power station, and samp represents the set of benchmark photovoltaic power stations.

Wherein, within the statistical time period m, according to the obtained starting capacity and theoretical output, obtaining the abandoned photovoltaic power of the entire photovoltaic power generation base within the calculation time interval t includes: within the statistical time period m, according to the obtained starting Capacity and theoretical output, calculate the real-time start-up capacity and theoretical output of each photovoltaic cluster within each calculation time interval t; according to the calculated real-time start-up capacity and theoretical output, obtain the photovoltaic power abandonment power of the entire photovoltaic power generation base.

Further, according to the obtained start-up capacity and theoretical output, calculate the real-time start-up capacity of each photovoltaic cluster within each calculation time interval t, including: calculating each cluster obtained by dynamically grouping photovoltaic power plants by using the radiation similarity, namely The real-time power-on capacity of the photovoltaic cluster within each calculation time interval t: Among them, cluster _i represents the i-th photovoltaic power station cluster, assuming that there are n such clusters in total, C _j is the start-up capacity of the j-th photovoltaic power station in the i-th photovoltaic power station cluster, when the upload of the start-up capacity of the photovoltaic power station fails or is interrupted When , the start-up capacity of the photovoltaic power plant at the previous calculation time interval t is used instead.

Further, according to the obtained start-up capacity and theoretical output, calculate the theoretical output of each photovoltaic cluster in each calculation time interval t, including: calculate the theoretical output of each photovoltaic cluster in each calculation time interval t: $T_i={\stackrel{\‾}{\mathrm{\α}}}_i\×C_{clu\mathrm{the\; s}ter,i}.$

Further, according to the calculated real-time start-up capacity and theoretical output, obtain the abandoned photovoltaic power of the entire photovoltaic power generation base, including: obtaining the average real-time output value R _i of each photovoltaic cluster within each calculation time interval t through the energy management system , when the theoretical output value T _i is greater than the average actual output value R _i , the amount of light abandoned in the entire photovoltaic power generation base in each calculation time interval t is: $Q_{i,k}=\left\{\begin{array}{cc}(T_i-R_i)t& \begin{array}{cc}if& (T_i>R_i)\end{array}\\ 0& el\mathrm{the\; s}e\end{array}\right.$

Wherein, at the end of the statistical period m, obtain the abandoned photovoltaic power of the entire photovoltaic cluster within the statistical period m, including: judging whether the end time of the statistical period m is reached; if the end time of the statistical period m is not reached, then obtain the next Calculate the start-up capacity and theoretical output of each benchmark photovoltaic power station within the time interval t; if the end time of the statistical period m has been reached, then end the acquisition of the start-up capacity and theoretical output of each benchmark photovoltaic power station within the calculation time interval t, according to Calculate the abandoned photovoltaic power of the entire photovoltaic power generation base within the time interval t, and count the abandoned photovoltaic power of the entire photovoltaic cluster within the time period m: Among them, k=1 is the start time of the statistics of abandoned photovoltaic power, k=m is the termination time of the statistics of abandoned photovoltaic power, m is a natural number, and w is the number of photovoltaic clusters; the single-field capacity of a photovoltaic power station is in MW, and The unit of quantity is MWh.

The method for evaluating the amount of abandoned light in large-scale photovoltaic power generation clusters based on irradiation similarity in each embodiment of the present invention includes: using the irradiation similarity to dynamically group photovoltaic power plants; calculating the abandoned light of each cluster obtained by the dynamic grouping Therefore, it can overcome the defects of complex calculation process, small application range of calculation methods, high difficulty in obtaining calculation data and poor accuracy of calculation results in the prior art, so as to realize simple calculation process, large application range of calculation methods, and fast acquisition of calculation data and calculation The advantage of good accuracy of the results.

Additional features and advantages of the invention will be set forth in the description which follows, and in part will be apparent from the description, or may be learned by practice of the invention.

The technical solutions of the present invention will be described in further detail below with reference to the accompanying drawings and embodiments.

Description of drawings

The accompanying drawings are used to provide a further understanding of the present invention, and constitute a part of the description, and are used together with the embodiments of the present invention to explain the present invention, and do not constitute a limitation to the present invention. In the attached picture:

Fig. 1 is a flow chart of the calculation and analysis of the abandoned light quantity in the present invention.

detailed description

The preferred embodiments of the present invention will be described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described here are only used to illustrate and explain the present invention, and are not intended to limit the present invention.

In general, the real-time power generation per unit capacity of photovoltaic power plants with similar real-time irradiance should also be similar. Photovoltaic evaluation.

In view of the defects existing in the existing technology, according to the embodiment of the present invention, as shown in Figure 1, a method for evaluating the curtailed power of large-scale photovoltaic power generation clusters based on irradiation similarity is provided to realize the advantages of accurate and reliable calculation and analysis of curtailed power. The method includes:

The following table shows some photovoltaic power stations in the Jinchang-Wuwei area of Gansu Province. The following 20 photovoltaic power stations are taken as examples to illustrate the method.

Step 1: Each benchmark photovoltaic power station constitutes a subcategory, so five benchmark photovoltaic power stations constitute five clusters. For each non-benchmark photovoltaic power station (except for benchmark photovoltaic power stations), according to the radiation Sort according to the similarity, select a benchmark photovoltaic power station with the highest similarity, and add it to the cluster of the benchmark photovoltaic power station.

Step 2: Calculate the start-up capacity and theoretical output of each benchmark photovoltaic power station. From the initial stage, the start-up capacity of the benchmark photovoltaic power station is obtained through the real-time information of photovoltaic power generation uploaded by the photovoltaic power station every 5 minutes. Calculate the average output coefficient of each benchmark photovoltaic power plant within 5 minutes:

${\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}{{\stackrel{<span\; class="notranslate">\; ~</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; a</span>}\mathrm{<span\; class="notranslate">\; m</span>}\mathrm{<span\; class="notranslate">\; p</span>}<span\; class="notranslate">\; ;</span>$

Among them, P _i is the actual output of the i-th benchmark photovoltaic power plant, is the start-up capacity of the i-th benchmark photovoltaic power station, and samp represents the set of benchmark photovoltaic power stations.

According to the above formula, the average output coefficient of the benchmark photovoltaic power station within 5 minutes is:

Step 3: Calculate the real-time start-up capacity of each photovoltaic cluster every 5 minutes obtained in step 1:

${\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; u</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; t</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; \&Element;</span>{\mathrm{<span\; class="notranslate">\; cluster</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}{<span\; class="notranslate">\; \&Sigma;</span>}{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; ;</span>$

Among them, cluster _i represents the i-th photovoltaic power station cluster, assuming that there are n such clusters in total, C _j is the start-up capacity of the j-th photovoltaic power station in the i-th photovoltaic power station cluster, when the upload of the start-up capacity of the photovoltaic power station fails or is interrupted When , the start-up capacity of the photovoltaic power station at the previous moment is used instead.

cluster Installed capacity (MW) Power capacity (MW) Cluster 1 500 400 Cluster 2 20 20 Cluster 3 20 20 Cluster 4 200 180 Cluster 5 480 460

Step 4: Calculate the theoretical output of the photovoltaic cluster every t minutes:

${\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>{\stackrel{<span\; class="notranslate">\; \&OverBar;</span>}{\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; u</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; t</span>}\mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; r</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ;</span>$

cluster Installed capacity (MW) Theoretical output (MW) Cluster 1 500 360.5 Cluster 2 20 20 Cluster 3 20 20 Cluster 4 200 170.2 Cluster 5 480 402

Step 5: Obtain the average actual output value Ri of each photovoltaic cluster every 5 minutes through EMS (Energy Management System). When the theoretical output value T _i is greater than the average actual output value R _i , it is considered that there is light abandonment. The abandoned photovoltaic power of the power generation base can be expressed as:

${\mathrm{<span\; class="notranslate">\; Q</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; =</span>\left\{\begin{array}{cc}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; t</span>}& \begin{array}{cc}\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; f</span>}& <span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ></span>{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>\end{array}\\ \mathrm{<span\; class="notranslate">\; 0</span>}& \mathrm{<span\; class="notranslate">\; e</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; e</span>}\end{array}\right.<span\; class="notranslate">\; ;</span>$

The energy management system can adopt the power grid operation management system used for dispatching in the power system.

Step 6: Judging whether the statistical end time has been reached, if the statistical end time has not been reached, then return to step 1, and if the statistical end time is reached, then proceed to step 7.

Step 7: Therefore, the amount of abandoned photovoltaic power of the entire photovoltaic cluster within a certain period of time is expressed as:

$\mathrm{<span\; class="notranslate">\; Q</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; w</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; Q</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; ;</span>$

Among them, j=1 is the start time of the statistics of abandoned photovoltaic power, j=1440 is the termination time of the statistics of abandoned photovoltaic power, w=5 is the number of photovoltaic clusters; the single field capacity of photovoltaic power station is in MW, and the The unit is MWh.

According to calculations, the 1-day abandoned photovoltaic power of the five photovoltaic power station clusters is 655.89MWh.

In one embodiment, when the output of the photovoltaic cluster is limited, the benchmark power station does not participate in the load-limited adjustment, and always maintains a normal power generation state; The abandoned photovoltaic power of other benchmark photovoltaic power plants is used to calculate the abandoned photovoltaic power of the entire cluster.

After a large number of experimental verifications, the scheme of the present invention evaluates the theoretical power of the entire photovoltaic cluster through the power generation of each benchmark photovoltaic power station, and obtains the corresponding abandoned wind power of the photovoltaic cluster through comparison with the actual power, which achieves the accurate calculation of the abandoned light power. Purpose.

The patent (201310168821.1) proposes a method for evaluating the amount of abandoned light in photovoltaic bases based on a real-time optical resource monitoring network. The main problem is that the construction of an optical resource monitoring network is a long-term process. Many photovoltaic power generation bases may not have built an optical resource monitoring network. In view of the above situation , the method fails.

In the patent document with the patent (application) No. 201310168700.7, a method for evaluating the amount of abandoned light in large-scale photovoltaic power generation bases based on benchmark photovoltaic modules is proposed. The main disadvantage is that some power stations do not have fixed benchmark photovoltaic modules, or benchmark photovoltaic module operation management It is not standardized enough, there are problems such as failures and interruption or error in uploading data of benchmark photovoltaic inverters. The solution of the present invention will serve as an effective supplement to the statistical method of abandoned photovoltaic power based on benchmark photovoltaic modules.

Finally, it should be noted that: the above is only a preferred embodiment of the present invention, and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, for those skilled in the art, it still The technical solutions recorded in the foregoing embodiments may be modified, or some technical features thereof may be equivalently replaced. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims (9)

1. A method for evaluating the amount of abandoned light in large-scale photovoltaic power generation clusters based on irradiation similarity, which is characterized in that it includes: Dynamic grouping of photovoltaic power plants by using irradiation similarity; Calculating the abandoned light quantity of each cluster obtained by the dynamic clustering. 2. The method according to claim 1, wherein the dynamic grouping of photovoltaic power plants using the similarity of radiation comprises: Constitute each benchmark photovoltaic power plant into a subcategory or cluster; For each non-benchmark photovoltaic power station, that is, photovoltaic power stations other than the benchmark photovoltaic power station, sort according to the irradiance similarity of all benchmark photovoltaic power stations, and select the one with the highest irradiance similarity with the non-benchmark photovoltaic power station among all benchmark photovoltaic power stations Benchmark photovoltaic power station; add each non-benchmark photovoltaic power station to the cluster of the benchmark photovoltaic power station with the highest irradiance similarity to the non-benchmark photovoltaic power station. 3. The method according to claim 1 or 2, characterized in that, calculating the abandoned light quantity of each cluster obtained by the dynamic grouping includes: Set the statistical time period j and the calculation time interval t. The statistical time period j is greater than the calculation time interval t, and both j and t are real numbers; when the statistical time period j starts, obtain the Starting capacity and theoretical output; In the statistical time period j, according to the obtained start-up capacity and theoretical output, obtain the abandoned light quantity of the entire photovoltaic power generation base in the calculation time interval t; At the end of the statistical time period j, the abandoned photovoltaic power of the entire photovoltaic cluster in the statistical time period j is obtained. 4. The method according to claim 3, characterized in that, at the beginning of the statistical period j, obtaining the start-up capacity and theoretical output of each benchmark photovoltaic power station within the calculation time interval t includes: At the beginning of the statistical period j, the start-up capacity of the benchmark photovoltaic power station is obtained through the real-time information of photovoltaic power generation uploaded once in each calculation time interval t of the photovoltaic power station, and the average output coefficient of each benchmark photovoltaic power station in the calculation time interval t is calculated: Among them, P _i is the actual output of the i-th benchmark photovoltaic power plant, is the start-up capacity of the i-th benchmark photovoltaic power station, and samp represents the set of benchmark photovoltaic power stations. 5. The method according to claim 3, characterized in that, within the statistical time period m, according to the obtained starting capacity and theoretical output, obtaining the amount of abandoned light of the entire photovoltaic power generation base in the calculation time interval t includes: In the statistical time period m, according to the obtained starting capacity and theoretical output, calculate the real-time starting capacity and theoretical output of each photovoltaic cluster in each calculation time interval t; According to the calculated real-time start-up capacity and theoretical output, the abandoned photovoltaic power of the entire photovoltaic power generation base is obtained. 6. The method according to claim 5, characterized in that, according to the obtained starting capacity and theoretical output, calculating the real-time starting capacity of each photovoltaic cluster within each calculation time interval t, including: Calculate the real-time start-up capacity of each cluster obtained by dynamically grouping photovoltaic power plants by using the radiation similarity, that is, the photovoltaic cluster within each calculation time interval t: Among them, cluster _i represents the i-th photovoltaic power station cluster, assuming that there are n such clusters in total, C _j is the start-up capacity of the j-th photovoltaic power station in the i-th photovoltaic power station cluster, when the upload of the start-up capacity of the photovoltaic power station fails or is interrupted When , the start-up capacity of the photovoltaic power plant at the previous calculation time interval t is used instead. 7. The method according to claim 5, wherein, according to the obtained starting capacity and theoretical output, calculating the theoretical output of each photovoltaic cluster within each calculation time interval t includes: Calculate the theoretical output of each photovoltaic cluster in each calculation time interval t: 8. The method according to claim 5, characterized in that, according to the calculated real-time start-up capacity and theoretical output, the amount of light abandoned for each photovoltaic power generation cluster is obtained, including: The average actual output value R _i of each photovoltaic cluster in each calculation time interval t is obtained through the energy management system. When the theoretical output value T _i is greater than the average actual output value R _i , the entire photovoltaic power generation base in each calculation time interval t The abandoned light quantity is: 9. The method according to any one of claims 3-8, characterized in that, at the end of the statistical time period m, obtaining the abandoned light quantity of the entire photovoltaic cluster within the statistical time period m includes: Determine whether the end time of the statistical period m is reached: If the end time of the statistical time period m is not reached, then obtain the starting capacity and theoretical output of each benchmark photovoltaic power plant in the next calculation time interval t; If the end time of the statistical time period m has been reached, the acquisition of the start-up capacity and theoretical output of each benchmark photovoltaic power station within the calculation time interval t will end. The abandoned photovoltaic power of the entire photovoltaic cluster within m: Among them, k=1 is the start time of the statistics of abandoned photovoltaic power, k=m is the termination time of the statistics of abandoned photovoltaic power, m is a natural number, and w is the number of photovoltaic clusters; the single-field capacity of a photovoltaic power station is in MW, and The unit of quantity is MWh.