New energy station operation and maintenance level rating method, device and equipment and storage medium

Abstract

The invention relates to the technical field of station management, in particular to a new energy station operation and maintenance level rating method and device, equipment and a storage medium. The method comprises the following steps: acquiring operation data of a plurality of new energy stations in a region; calculating a grading index value of each new energy station in the current period based on the operation data; calculating the production index score of each new energy station based on the current scoring index value of each new energy station, the change value of the current scoring index value relative to the historical scoring index value, and the maximum value, the minimum value and the corresponding change value of the scoring index value of each new energy station; and determining the operation and maintenance level of each new energy station according to the production index score of each new energy station. According to the method, the production index score adopted during rating is combined with the trend index, namely the change value, obtained through comparison with the historical operation state of the production index score, the maximum value, the minimum value and the like obtained through comparison with other new energy stations, and therefore the influence of inconsistent operation working conditions on evaluation of the output state of the wind turbine generator is relieved.

Description

Technical Field

[0001] The present invention relates to the field of station management technology, and in particular to a method, device, equipment and storage medium for rating the operation and maintenance level of a new energy station. Background Art

[0002] We are currently in an important stage of energy transformation and new energy development. The proportion of new energy represented by wind power is increasing year by year. In order to reduce cost expenditure and achieve more efficient operation and maintenance, new energy companies are using various high-tech technologies such as automation control technology, Internet technology, Internet of Things technology and artificial intelligence technology to gradually transform the traditional enterprise operation and maintenance model. Against this background, how to objectively and quantitatively evaluate the quality of wind power on-site operation and maintenance is particularly important.

[0003] Current evaluation methods consider the unit output status and the station's operation and maintenance capabilities within renewable energy stations, but fail to consider factors such as on-site wind resources and the unit's operating environment. Because the comparison between the unit's actual operating power curve and the guaranteed power curve varies across wind speed ranges, regional wind resources can significantly impact the unit's actual output level. For example, areas with poor wind speeds may impact the assessment of unit output levels. Evaluating a unit using the same energy efficiency or power generation metrics under inconsistent external factors cannot accurately determine its output status. Summary of the Invention

[0004] In view of this, the present invention provides a method and device for rating the operation and maintenance level of a new energy station to solve the problem of how to accurately evaluate the operation and maintenance status of a unit when the wind resources and environmental conditions are inconsistent during the operation of the unit.

[0005] In a first aspect, the present invention provides a method for rating the operation and maintenance level of new energy stations, the method comprising: obtaining operation data of multiple new energy stations in a region; calculating the current scoring index value of each new energy station based on the operation data, the scoring index value including an energy efficiency scoring index value and a reliability scoring index value; calculating the production index score of each new energy station based on the current scoring index value of each new energy station, the change value of the current scoring index value relative to the historical scoring index value, the maximum value, minimum value and corresponding change value of the scoring index value of each new energy station; determining the operation and maintenance level of each new energy station according to the production index score of each new energy station.

[0006] In the present invention, the production index score used in the rating is combined with the trend index, i.e., the change value, obtained by comparing with its own historical operating status, and the maximum and minimum values obtained by comparing with other new energy sites. Thus, the rating method reduces the impact of inconsistent operating conditions on the output status evaluation of wind turbines.

[0007] In an optional embodiment, energy efficiency scoring indicators include: energy efficiency loss rate, power prediction accuracy, utilization hour relative feasibility deviation rate, and energy utilization rate; reliability scoring indicators include: equipment availability, mean fault recovery time, mean time between failures after maintenance, average number of downtimes per unit, and average downtime per unit;

[0008] The production index scores corresponding to energy efficiency loss rate, mean fault recovery time, mean time between failures after maintenance, average number of downtimes per unit, and average downtime per unit are calculated using the following formula:

[0009]

[0010] The production indicator scores corresponding to power prediction accuracy, utilization hour relative feasibility deviation rate, energy utilization rate, and equipment availability are calculated using the following formula:

[0011]

[0012] In the formula, S represents the production index score, a represents the weight of the score index value, b represents the discrimination coefficient of the score index value, m represents the current score index value, and m max Indicates the maximum value of the scoring index of each new energy station, m min It represents the minimum value of the scoring index value of each new energy station, Δm represents the change value of the current scoring index value relative to the historical scoring index value, Δm max Indicates the change in the maximum value of the scoring index value of each new energy station, Δm min It represents the change in the minimum value of the scoring index of each new energy station, and n represents the standard score of the corresponding scoring index.

[0013] In the present invention, the above formula is used to accurately calculate the energy efficiency scoring index and the reliability scoring index.

[0014] In an optional embodiment, the reliability scoring indicators also include: platform communication interruption rate, number of defects and timeliness of problem handling. The production index score corresponding to the platform communication interruption rate is determined based on the current platform communication interruption rate and the minimum value of the platform communication interruption rate of each new energy station; the production index score corresponding to the number of defects is determined based on the statistical value of the number of defects; the production index score corresponding to the timeliness of problem handling is determined based on the maximum value of the current problem handling timeliness and the timeliness of problem handling of each new energy station.

[0015] In this invention, by adding the platform communication interruption rate, defect count, and problem handling timeliness to the reliability scoring indicators, a more reliable evaluation of new energy stations is achieved, thereby enabling a more accurate assessment of operation and maintenance levels.

[0016] In an optional embodiment, the operation and maintenance level of each new energy station is determined according to the production index score of each new energy station, including: determining the ranking, single indicator score rate and total indicator score of each new energy station according to the production index score of each new energy station; rating the new energy station whose ranking meets the first preset condition and single indicator score rate meets the second preset condition as A; rating the new energy station whose ranking meets the third preset condition and single indicator score rate meets the fourth preset condition, or the new energy station whose ranking meets the first preset condition and single indicator score rate does not meet the second preset condition as B; rating the new energy station whose ranking meets the fifth preset condition, or the new energy station whose ranking meets the third preset condition and single indicator score rate does not meet the fourth preset condition, or the new energy station that is not connected to the preset system as C; rating the new energy station whose ranking meets the sixth preset condition and the total indicator score meets the seventh preset condition, or the new energy station that has a preset fault as D.

[0017] In the present invention, new energy stations are ranked by combining factors such as ranking, individual indicator score rate, and total indicator score, so as to more objectively describe the operation and maintenance level of new energy stations.

[0018] In an optional embodiment, the current scoring index value includes a monthly scoring index value, a quarterly scoring index value, and an annual scoring index value, and the operation and maintenance level of each new energy station is determined according to the production index score of each new energy station. It also includes: determining the monthly operation and maintenance level, quarterly operation and maintenance level, and annual operation and maintenance level of each new energy station according to the production index score of each new energy station; and calculating the regional total score based on the production index score of each new energy station and the installed capacity weighted calculation of each new energy station.

[0019] In the present invention, by determining the monthly operation and maintenance level, quarterly operation and maintenance level, annual operation and maintenance level and regional total score, more data basis is provided for the operation and maintenance management of new energy stations.

[0020] In an optional embodiment, the energy efficiency loss rate is determined by the ratio of the energy efficiency loss electricity to the required power generation; the power prediction accuracy is determined by the predicted power, actual power and startup capacity; the utilization hour relative feasibility deviation rate is determined by the actual power generation, rated capacity and feasibility utilization hours; and the energy utilization rate is determined by the ratio of the actual power generation to the required power generation.

[0021] In an optional embodiment, the platform communication interruption rate is determined by the number of units connected to the platform, the communication interruption time and the calendar time; the equipment availability is determined by the total time of the unit's available state and the normal communication events; the average fault recovery time is determined by the total number of faults and the start time and recovery time of each unit's fault shutdown; the average fault-free time after maintenance is determined by the total number of maintenances and the end time of each unit's maintenance shutdown, and the start time of the first fault shutdown after maintenance; the average number of shutdowns per unit is determined by the number of units and the number of shutdowns for each unit; the average downtime per unit is determined by the number of units and the downtime for each unit; the number of defects is determined by the number of times the new energy station failure exceeds the preset time; the timeliness of problem handling is determined by the number of units that have solved the problem, the number of problem units and the number of hours used to solve the problem.

[0022] In the present invention, the calculation method of energy efficiency scoring indicators and reliability scoring indicators is defined in the above manner, providing a data basis for the calculation of subsequent production indicator scores.

[0023] In a second aspect, the present invention provides a device for rating the operation and maintenance level of a new energy station, the device comprising: a data acquisition module for acquiring the operation data of multiple new energy stations in a region; a scoring index calculation module for calculating the current scoring index value of each new energy station based on the operation data, the scoring index value including the energy efficiency scoring index value and the reliability scoring index value; a production index scoring calculation module for calculating the production index score of each new energy station based on the current scoring index value of each new energy station, the change value of the current scoring index value relative to the historical scoring index value, the maximum value, minimum value and corresponding change value of the scoring index value of each new energy station; a rating module for determining the operation and maintenance level of each new energy station according to the production index score of each new energy station.

[0024] In a third aspect, the present invention provides a computer device comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to execute the new energy station operation and maintenance level rating method of the first aspect or any corresponding embodiment thereof.

[0025] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the new energy station operation and maintenance level rating method of the above-mentioned first aspect or any corresponding embodiment thereof.

[0026] In a fifth aspect, the present invention provides a computer program product comprising computer instructions, which are used to enable a computer to execute the new energy station operation and maintenance level rating method of the above-mentioned first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0028] Figure 1 1 is a flow chart of a method for rating the operation and maintenance level of a new energy station according to an embodiment of the present invention;

[0029] Figure 2 This is a structural block diagram of a new energy station operation and maintenance level rating device according to an embodiment of the present invention;

[0030] Figure 3 Schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0031] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of the present invention.

[0032] According to an embodiment of the present invention, an embodiment of a method for rating the operation and maintenance level of a new energy station is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0033] In this embodiment, a new energy station operation and maintenance level rating method is provided, which can be used for electronic devices such as computers, mobile phones, tablet computers, etc. Figure 1 : is a flow chart of a method for rating the operation and maintenance level of a new energy station according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0034] Step S101, obtain the operating data of multiple new energy stations in the area. Specifically, the operating data may be data collected in the new energy station through the SCADA system (Supervisory Control And Data Acquisition). These data may be data generated during the operation of the new energy station, including normal operating data, abnormal and fault data, etc. The new energy station may be a wind power station, a wind-solar station or a photovoltaic station, etc. For a wind power station, if it includes an offshore wind power station and an onshore wind power station, the rating of the offshore wind power station and the onshore wind power station are carried out separately; for a wind-solar station, wind power and photovoltaic are rated separately as independent stations. When the new energy station is a wind power station, the operating data includes parameters such as wind speed, wind direction, temperature, voltage and current.

[0035] In addition, in order to make the rating of new energy stations more objective and accurate, the operating data of multiple new energy stations are obtained to facilitate the horizontal comparison of the new energy station to be evaluated with other new energy stations. In this embodiment, the operating data of multiple new energy stations in a region are obtained. The region can select a province or a city as the corresponding region according to the actual situation. In actual applications, when there are multiple new energy stations to be evaluated and they cannot be divided into one region, the operating data of multiple new energy stations in multiple regions can also be obtained according to the new energy station to be evaluated. For each new energy station, it also includes multiple units, so the obtained operating data can be stored according to the hierarchical relationship of regions, stations and units.

[0036] Step S102: Calculate the current scoring index value for each new energy station based on the operating data. The scoring index values include energy efficiency scoring index values and reliability scoring index values. Specifically, when rating new energy stations, the ratings can be conducted according to a certain period, for example, once a month, once a quarter, or once a year. Therefore, when calculating the current scoring index value, the corresponding scoring index value can be calculated based on the operating data within the corresponding period. For example, if the rating is conducted once a year, the current scoring index value is calculated based on the operating data within one year.

[0037] Among them, for scoring indicators, this embodiment determines two types of indicators: energy efficiency scoring indicators and reliability scoring indicators; among them, energy efficiency scoring indicators include indicators such as the utilization rate or efficiency of new energy stations; reliability indicators include indicators such as communication, failure and shutdown of new energy stations, which represent the reliability of new energy stations.

[0038] Step S103, calculate the production index score of each new energy station based on the current scoring index value of each new energy station, the change value of the current scoring index value relative to the historical scoring index value, the maximum value, minimum value and corresponding change value of the scoring index value of each new energy station. Specifically, since the calculated scoring index values include multiple, it is necessary to calculate the corresponding production index score for each scoring index value. Among them, when calculating the corresponding production index score based on each scoring index value, in addition to the current scoring index value, the change value of the current scoring index value and the historical scoring index value is also calculated. The calculated change value realizes the vertical comparison between the new energy station to be evaluated and itself, so the change value can also be called the year-on-year change value. For the historical scoring index value, it can be the scoring index of the same period in history. For example, if the current scoring index value is a monthly scoring index value, the historical scoring index value can be the scoring index value of the corresponding month last year.

[0039] In addition, in order to achieve a horizontal comparison between the new energy station to be evaluated and other new energy stations, the scoring index values of other new energy stations are further considered in the production index scoring. The other new energy stations can be new energy stations located in the same area as the new energy station to be evaluated, that is, the corresponding scoring index values are also calculated for other new energy stations, and the maximum and minimum scoring index values and the corresponding change values are selected and added to the calculation of the production index score.

[0040] Step S104: Determine the operation and maintenance level of each new energy station based on its production indicator score. Specifically, each new energy station to be evaluated may have multiple production indicator scores. A final score for each new energy station can be determined by combining these multiple production indicator scores, and the operation and maintenance level of the new energy station is determined based on this final score.

[0041] The method for rating the operation and maintenance level of new energy stations provided in an embodiment of the present invention uses a production index score that combines trend indicators, i.e., change values, obtained by comparing with the station's own historical operating status, and maximum and minimum values obtained by comparing with other new energy stations. As a result, this rating method reduces the impact of inconsistent operating conditions on the output status evaluation of wind turbines.

[0042] In this embodiment, a method for rating the operation and maintenance level of a new energy station is provided, which includes the following steps:

[0043] Step S201: Obtain the operating data of multiple new energy stations in the region. Figure 1 Step S104 of the illustrated embodiment will not be described in detail here.

[0044] Step S202 calculates the current scoring index values for each new energy station based on the operating data. The scoring index values include energy efficiency and reliability. Energy efficiency scoring indicators include: energy efficiency loss rate, power prediction accuracy, utilization hour relative feasibility deviation rate, and energy utilization rate. Reliability scoring indicators include: equipment availability, mean fault recovery time, mean time between failures after maintenance, average number of downtimes per unit, and average downtime per unit.

[0045] Specifically, when calculating the scoring index value, some basic indicators are first calculated based on the operating data. These basic indicators do not participate in the final rating score, but can be used as the basis for calculating the scoring index and can also be used as some basic data for the corresponding new energy station. The basic indicators calculated in this embodiment include resource indicators, power generation indicators, power loss indicators, and maintenance indicators. When the new energy station is a wind farm, the specific basic indicators include the multiple indicators shown in Table 1 below.

[0046] Table 1

[0047]

[0048]

[0049] For the above basic indicators, the average wind speed is calculated using the following formula:

[0050]

[0051] Where, v i It represents the instantaneous wind speed at hub height or the 5-minute average wind speed, and n represents the number of all samples.

[0052] The effective wind speed hours are calculated using the following formula:

[0053]

[0054] Where, v min <v i <v max , where v min is the cut-in wind speed, v max To cut out the wind speed, Indicates the time during which the wind speed at hub height is in the power generation range during the statistical period.

[0055] The wind power density is calculated using the following formula:

[0056]

[0057] Where D WP represents the average wind power density at hub height; ρ represents the air density.

[0058] The power generation capacity is calculated using the following formula:

[0059] E0=E P +E i +E m +E h +E k +E j

[0060] Where, E p is the actual power generation; E i E is the amount of electricity to be dispatched (wind power curtailment); m The power loss due to planned downtime; E h E is the power loss due to downtime; k E is the power loss due to fault shutdown; j Power is lost for energy efficiency.

[0061] The actual power generation is calculated using the following formula:

[0062] E P =ΣE i

[0063] Where, E i is the actual power generation of the i-th unit.

[0064] The power consumption of the field is calculated using the following formula:

[0065]

[0066] Where, E C E is the electricity consumption of the field; P is the actual power generation.

[0067] The dispatch power limit is calculated using the following formula:

[0068] E i =Σ i (Po(v)-P1)

[0069] Where P1 is the active power of the unit; Po(v) is the power of the fitted power curve corresponding to the wind speed v; i is the dispatch limit load loss point.

[0070] The power loss during planned downtime is calculated using the following formula:

[0071] E m =∑ m (Po(v)-P1)

[0072] Where m is the planned outage loss point, and the outage plan is reported by the power generation enterprise on the diagnosis platform.

[0073] The power loss due to downtime is calculated using the following formula:

[0074] E h =∑ h (Po(v)-P1)

[0075] Where h is the affected shutdown loss point, and the affected shutdown status of the unit is reported by the power generation enterprise on the diagnosis platform.

[0076] The power loss due to fault shutdown is calculated using the following formula:

[0077] E k =Σ k (Po(v)-P1)

[0078] Where k is the failure downtime loss point, and unplanned downtime caused by non-involvement or scheduling power restrictions is recorded as failure downtime.

[0079] Energy efficiency loss is calculated using the following formula:

[0080] E j =∑ j (Po(v)-P1)++∑ l (Pb(v)-P1)

[0081] Where j is the load limit point; Pb(v) is the power of the guaranteed power curve corresponding to the wind speed v; l is the data point where the unit is lower than the guaranteed power.

[0082] The dispatch power restriction loss rate is calculated using the following formula:

[0083]

[0084] Where, E i is the amount of electricity lost due to power restriction; E0 is the amount of electricity that should be generated.

[0085] The loss rate due to downtime is calculated using the following formula:

[0086]

[0087] Where, E h The power loss due to downtime.

[0088] The field loss is calculated using the following formula:

[0089] E TC =E P -E out +E in -E C

[0090] Where, E P is the actual power generation; E out E is the amount of electricity used for Internet access; inE is the amount of electricity that is offline; C For the electricity consumption of the field.

[0091] The field loss rate is calculated using the following formula:

[0092]

[0093] Where, E TC is the field loss power; E P is the actual power generation.

[0094] The average planned maintenance time is calculated using the following formula:

[0095]

[0096] Where, T jsi is the start time of planned maintenance shutdown of unit i; T jdi is the end time of the planned maintenance shutdown of the i-th unit; q is the total number of planned maintenance shutdowns of the units during the statistical period.

[0097] Based on the above basic indicators combined with operating data, scoring indicators can be further calculated. When the new energy site is a wind power site, the scoring indicators, their units, statistical periods and other parameters are shown in Table 2 below.

[0098] Table 2

[0099]

[0100]

[0101] For the above scoring indicators, the energy efficiency loss rate is determined by the ratio of energy efficiency loss power to the required power generation; the energy efficiency loss rate is calculated using the following formula:

[0102]

[0103] Where, E j is the energy efficiency loss; E0 is the amount of electricity that should be generated.

[0104] The power prediction accuracy is determined by the predicted power, actual power and startup capacity. For the power prediction accuracy, the short-term power prediction accuracy C can be calculated separately according to the different predicted powers. RS and the ultra-short-term power prediction accuracy C RSS The power prediction accuracy is calculated using the following formula:

[0105]

[0106] Where n is the number of all samples; P Pi is the actual power at time i; P Pmis the predicted power at time i; C i is the startup capacity at time i. Pm When the short-term predicted power at time i is the power prediction accuracy, the calculated power prediction accuracy is the short-term power prediction accuracy C RS , when P Pm When the ultra-short-term predicted power at time i is the power prediction accuracy, the calculated power prediction accuracy is the ultra-short-term power prediction accuracy C RSS .

[0107] The utilization hour relative feasibility study deviation rate is determined by the actual power generation, rated capacity and feasibility study utilization hours; the utilization hour relative feasibility study deviation rate is calculated using the following formula:

[0108]

[0109] Where, E p is the actual power generation; C n is the rated capacity of the new energy station; h n The number of hours used for feasibility study.

[0110] The energy utilization rate is determined by the ratio of actual power generation to expected power generation. The energy utilization rate is calculated using the following formula:

[0111]

[0112] Where, E P is the actual power generation; E0 is the expected power generation.

[0113] The platform communication interruption rate is determined by the number of units connected to the platform, the communication interruption time, and the calendar time; the platform communication interruption rate is calculated using the following formula:

[0114]

[0115] Where n is the number of units connected to the platform; T intj is the communication interruption time of the jth unit; T total The platform is the information platform that the unit accesses during normal operation and is used for operation and maintenance management of the unit.

[0116] The equipment availability is determined by the total time of the unit's available state and the number of normal communication events; the equipment availability is calculated using the following formula:

[0117]

[0118] Where, T kj is the total available time of the jth unit in the statistical period (the total available time = normal communication time - planned downtime - fault downtime); T0 is the normal communication time of the unit in the calculation period.

[0119] The average fault recovery time is determined by the total number of faults and the start and recovery time of each unit fault shutdown; the average fault recovery time is calculated using the following formula:

[0120]

[0121] Where, T gsi is the start time of the shutdown of the i-th unit due to failure; T gdi is the recovery time of the i-th unit failure shutdown; q is the total number of unit failures during the statistical period.

[0122] The average time between failures after maintenance is determined by the total number of maintenance units, the end time of each unit maintenance shutdown, and the start time of the first failure shutdown after maintenance; the average time between failures after maintenance is calculated using the following formula:

[0123]

[0124] Where, T jdi is the end time of the maintenance shutdown of the i-th unit; T jgi is the starting time of the first fault shutdown after the i-th unit is overhauled; q is the total number of unit overhauls during the statistical period.

[0125] The average number of outages per unit is determined by the number of units and the number of outages per unit; the average number of outages per unit is calculated using the following formula:

[0126]

[0127] Where, f ti is the number of shutdowns of the i-th unit in the statistical time period; n is the number of units.

[0128] The average downtime per unit is determined by the number of units and the downtime of each unit; the average downtime per unit is calculated using the following formula:

[0129]

[0130] Where, t ti is the downtime of the i-th unit in the statistical time period; n is the number of units.

[0131] The number of defects is determined by the number of times the fault of the new energy station exceeds the preset time; specifically, for wind farms, the following defects can be counted: the wind turbine is continuously shut down for more than 240 hours; any single-loop collection line in the wind farm stops operating for more than 24 hours; large components such as gearboxes and generators are damaged.

[0132] The timeliness of problem handling is calculated by the number of units with resolved problems, the number of units with problems, and the number of hours spent on resolving the problems. The timeliness of problem handling is calculated using the following formula:

[0133]

[0134] Where, q is the number of units with solved problems; Q total The number of problem units; D i Timeliness of problem handling for unit i.

[0135]

[0136] Among them, H orij The number of hours it takes to solve the problem for the i-th fan.

[0137] Based on the calculation formula of the above scoring indicators, according to whether the calculated current scoring indicator value is a monthly scoring indicator value, a quarterly scoring indicator value or an annual scoring indicator value, the corresponding operating data is substituted to obtain the current scoring indicator value.

[0138] Step S203, calculating the production index score of each new energy station based on the current score index value of each new energy station, the change value of the current score index value relative to the historical score index value, the maximum value, minimum value and corresponding change value of the score index value of each new energy station.

[0139] The production index scores corresponding to energy efficiency loss rate, mean fault recovery time, mean time between failures after maintenance, average number of downtimes per unit, and average downtime per unit are calculated using the following formula:

[0140]

[0141] The production indicator scores corresponding to power prediction accuracy, utilization hour relative feasibility deviation rate, energy utilization rate, and equipment availability are calculated using the following formula:

[0142]

[0143] In the formula, S represents the production index score, a represents the weight of the score index value, b represents the discrimination coefficient of the score index value, m represents the current score index value, and m max Indicates the maximum value of the scoring index of each new energy station, m min It represents the minimum value of the scoring index value of each new energy station, Δm represents the change value of the current scoring index value relative to the historical scoring index value, Δm max Indicates the change in the maximum value of the scoring index value of each new energy station, Δm min It represents the change in the minimum value of the scoring index of each new energy station, and n represents the standard score of the corresponding scoring index.

[0144] Among them, for the scoring indicators of energy efficiency loss rate, average fault recovery time, average trouble-free time after maintenance, average number of shutdowns per unit, and average downtime per unit, the smaller the scoring indicator value, the better; while for the scoring indicators of power prediction accuracy, utilization hour relative feasibility deviation rate, energy utilization rate, and equipment availability, the larger the scoring indicator value, the better. Therefore, when calculating the corresponding production indicator scores, the two scoring methods of the above formula are used.

[0145] Specifically, for the energy efficiency loss rate, the corresponding production index score is calculated using the following formula:

[0146]

[0147] Where a1 is the weight of the current energy efficiency loss rate score (i.e., the scoring index value); b1 is the discrimination coefficient of the energy efficiency loss rate score; η emax is the maximum energy efficiency loss rate of each station; η emin is the minimum energy efficiency loss rate of each station; Δη e =η e -η′ e , Δη e is the year-on-year change in the current energy efficiency loss rate compared with the same period last year, η' e is the energy efficiency loss rate of the same period last year; Δη emax is the maximum year-on-year change in energy efficiency loss rate of each station; Δη emin It is the minimum year-on-year change in the energy efficiency loss rate of each station.

[0148] For the power prediction accuracy, the corresponding production index score is calculated using the following formula:

[0149]

[0150] Where a2 is the weight of the current power prediction accuracy score; b2 is the discrimination coefficient of the power prediction accuracy score; C RSmax 、C RSSmax is the maximum accuracy of short-term and ultra-short-term power prediction for each station; C RSmin 、C RSSmin is the minimum accuracy of short-term and ultra-short-term power prediction for each station; ΔC RS =C RS -C′ RS , ΔC RSS =C RSS -C′ RSS , ΔC RS , ΔC RSS is the year-on-year change in the accuracy of current short-term and ultra-short-term power forecasts compared with the same period last year, C' RS , C'RSS is the short-term and ultra-short-term power forecast accuracy rate for the same period last year; ΔC RSmax , ΔC RSSmax is the maximum year-on-year change in the short-term and ultra-short-term power prediction accuracy of each station; ΔC RSmin , ΔC RSSmin It is the minimum year-on-year change in the short-term and ultra-short-term power forecast accuracy of each station.

[0151] For the utilization hour relative feasibility deviation rate, the corresponding production indicator score is calculated using the following formula:

[0152]

[0153] Where a3 is the weight of the current period's utilization hours relative to the feasibility study deviation rate score; b3 is the discrimination coefficient of the utilization hours relative to the feasibility study deviation rate score; η hmax is the maximum relative feasibility study deviation rate of each station’s utilization hours; η hmin is the minimum relative feasibility study deviation rate of each station’s utilization hours; Δη h =η h -η′ h , Δη h is the year-on-year change in the relative feasibility deviation rate of the current period's utilization hours compared with the same period last year, η' h Δη is the relative feasibility deviation rate of utilization hours in the same period last year; hmax is the maximum year-on-year change in the relative feasibility study deviation rate of each station’s utilization hours; Δη hmin It is the minimum year-on-year change in the relative feasibility study deviation rate of utilization hours of each station.

[0154] For energy utilization, the corresponding production index score is calculated using the following formula:

[0155]

[0156] Where a4 is the weight of the current energy utilization rate score; b4 is the discrimination coefficient of the energy utilization rate score; η Emax is the maximum energy utilization rate of each station; η Emin is the minimum energy utilization rate of each station; Δη E =η E -η′ E , Δη E is the year-on-year change in energy utilization rate for the current period compared with the same period last year, η' E is the energy utilization rate of the same period last year; Δη Emax is the maximum year-on-year change in energy utilization rate of each station; Δη Emin It is the minimum year-on-year change in energy utilization rate of each station.

[0157] For equipment availability, the corresponding production indicator score is calculated using the following formula:

[0158]

[0159] In the formula, a6 is the weight of the current equipment availability score; b6 is the discrimination coefficient of the equipment availability score; R max is the maximum utilization rate of equipment at each station; R min is the minimum value of the equipment availability of each station; ΔR=RR′, ΔR is the year-on-year change of the equipment availability of the current period compared with the same period last year, and R′ is the equipment availability of the same period last year; ΔR max is the maximum year-on-year change in the equipment availability of each station; ΔR min It is the minimum year-on-year change in equipment availability at each station.

[0160] For the average fault recovery time, before calculating its production index score, the formula is first used to calculate the average time T of each unit fault recovery time exceeding 24 hours during the statistical period. h24 Make a rating.

[0161]

[0162] Where, T gsi24 T is the start time of the shutdown of the i-th unit whose fault recovery time exceeds 24 hours; gdi24 The recovery time of the i-th unit whose fault recovery time exceeds 24 hours; q 24 It is the total number of units whose fault recovery time exceeds 24 hours during the statistical period.

[0163] Based on the scoring results, the production index score is further calculated using the following formula:

[0164]

[0165] Where a7 is the weight of the current average fault recovery time score; b7 is the discrimination coefficient of the average fault recovery time score; T h24max T is the maximum average fault recovery time of each station; h24min is the minimum average fault recovery time of each station; ΔT h24 =T h24 -T′ h24 , ΔT h24 T' is the year-on-year change in the average fault recovery time for the current period compared with the same period last year. h24 ΔT is the average fault recovery time of the same period last year; h24max is the maximum year-on-year change in the average fault recovery time of each station; ΔT h24min It is the minimum year-on-year change in the average fault recovery time of each station.

[0166] For the mean time between failures after repair, the corresponding production index score is calculated using the following formula:

[0167]

[0168] Where a8 is the weight of the average time between failures after maintenance in the current period; b8 is the discrimination coefficient of the average time between failures after maintenance; T wmax T is the maximum value of the average trouble-free time after maintenance of each station; wmin is the minimum value of the average trouble-free time after maintenance of each station; ΔT w =T w -T′ w , ΔT w T' is the year-on-year change in the average trouble-free time after maintenance in the current period compared with the same period last year. w ΔT is the average trouble-free time after maintenance in the same period last year; wmax is the maximum year-on-year change in the average trouble-free time after maintenance at each station; ΔT wmin It is the minimum year-on-year change in the average trouble-free time after maintenance of each station.

[0169] For the average number of downtimes per unit, the corresponding production index score is calculated using the following formula:

[0170]

[0171] Where a9 is the weight of the average number of downtimes per station in the current period; b9 is the discrimination coefficient of the average number of downtimes per station; F tmax is the maximum number of downtimes at each station; F tmin is the minimum number of downtimes at each station; ΔF t =F t -F′ t , ΔF t F' is the year-on-year change in the average number of outages per station during the current period compared with the same period last year. t is the average number of outages per station in the same period last year; ΔF tmax is the maximum year-on-year change in the average number of downtimes at each station; ΔF tmin It is the minimum value of the year-on-year change in the average number of shutdowns at each station.

[0172] For the average downtime per unit, the corresponding production index score is calculated using the following formula:

[0173]

[0174] Where a 10 is the weight of the average downtime performance of the current period; b 10 is the discrimination coefficient of the average downtime performance; T tmaxis the maximum downtime of each platform; T tmin is the minimum downtime of each platform; ΔT t =T t -T′ t , ΔT t T' is the year-on-year change in the average downtime per station in the current period compared with the same period last year. t ΔT is the average downtime of each unit in the same period last year; tmax is the maximum year-on-year change in the average downtime of each platform; ΔT tmin It is the minimum year-on-year change in the average downtime of each platform.

[0175] It should be noted that the above weights can be determined based on actual conditions, for example, 70%. In other embodiments, other values can also be selected. The discrimination coefficient is used to adjust the benchmark score, that is, to ensure that the calculated benchmark score is above a certain score, such as 50 points. In this embodiment, the discrimination coefficient is 3.

[0176] In addition to the above indicators, reliability scoring indicators also include: platform communication interruption rate, number of defects, and timeliness of problem handling. The production indicator score corresponding to the platform communication interruption rate is determined based on the current platform communication interruption rate and the minimum value of the platform communication interruption rate of each new energy station. Therefore, the platform communication interruption rate is calculated using the following formula:

[0177]

[0178] Where C 1min It is the minimum value of the communication interruption rate of each station platform.

[0179] The production index score corresponding to the number of defects is determined based on the statistical value of the number of defects. Different formulas are used for different statistical periods:

[0180] S 111 =max(50-10N,0)

[0181] S 112 =max(50-5N,0)

[0182] S 113 =max(50-5N,0)

[0183] S 114 =max(50-N,0)

[0184] Where S 111 Indicates the station quarterly score, S 112 Indicates the annual score of the station, S 113 Indicates the regional monthly score, S 114represents the annual score of the region, and N represents the number of defects in the corresponding period.

[0185] The production index score corresponding to the timeliness of problem handling is determined based on the maximum value of the timeliness of problem handling in the current period and the timeliness of problem handling at each new energy station. Therefore, the timeliness of problem handling is calculated using the following formula:

[0186]

[0187] Where C 2max To maximize the timeliness of problem handling at each station.

[0188] Step S204: determining the operation and maintenance level of each new energy station according to the production indicator score of each new energy station.

[0189] Specifically, the above step S204 includes:

[0190] Step S2041: Determine the ranking, individual indicator score rate, and total indicator score of each new energy station based on the production indicator score of each new energy station. For each new energy station, it includes multiple production indicator scores, and all production indicator scores can be added together to obtain the total indicator score of the new energy station. Then, all new energy stations in the region are ranked based on the total indicator score of each new energy station. The higher the score, the higher the ranking. For the individual indicator score rate, if the full score is 100, directly divide the individual indicator score by 100 to obtain the corresponding score rate. If the full score is not 100, first convert it to 100 and then divide it by 100. For example, if the full score is 150, multiply the score by 2 / 3 and then divide it by 100 to obtain the score rate.

[0191] Step S2042: The new energy stations whose rankings meet the first preset condition and whose single indicator score rate meets the second preset condition are rated as A.

[0192] Step S2043: Rating the new energy stations whose rankings meet the third preset condition and whose single indicator score rate meets the fourth preset condition, or the new energy stations whose rankings meet the first preset condition and whose single indicator score rate does not meet the second preset condition, as B-level.

[0193] Step S2044: Rating the new energy stations whose rankings meet the fifth preset condition, or the new energy stations whose rankings meet the third preset condition and whose single indicator score rate does not meet the fourth preset condition, or the new energy stations that are not connected to the preset system as C-level.

[0194] Step S2045: The new energy stations whose rankings meet the sixth preset condition and whose total index scores meet the seventh preset condition, or the new energy stations that have a preset fault, are rated as D.

[0195] In actual applications, the first through seventh preset conditions can be determined based on actual circumstances. In this embodiment, the first through seventh preset conditions are determined as follows: New energy stations ranked in the top 10% and with a single indicator score of at least 85% are rated A. Stations ranked between the top 10% and 50% with a single indicator score of at least 75%, or those ranked in the top 10% but not meeting the A-level criteria, are rated B. Stations ranked between the top 50% and 90%, or those ranked in the top 50% but not meeting the B-level criteria, or those not connected to the benchmarking system, are rated C. Stations ranked in the bottom 10% with a score below 800, or if, during the evaluation quarter or year, a wind turbine runaway, tower collapse, blade breakage, fire, main transformer damage, or other equipment incidents occur, grid accidents caused by inadequate wind and solar station operation and maintenance, major or higher-level hidden dangers are not eliminated on schedule, or if data reporting involves fraudulent practices, are rated D.

[0196] In an optional embodiment, the above step S204 also includes: determining the monthly operation and maintenance level, quarterly operation and maintenance level, and annual operation and maintenance level of each new energy station based on the production index score of each new energy station; and calculating the regional total score based on the production index score of each new energy station and the installed capacity of each new energy station.

[0197] Specifically, the current scoring index values include monthly scoring index values, quarterly scoring index values and annual scoring index values. Based on this, the monthly operation and maintenance level, quarterly operation and maintenance level and annual operation and maintenance level of each new energy station can be calculated respectively in combination with the above steps S2041 to S2045; in addition, for the regional total score, it is calculated based on the weighted total score of the individual station indicators using the station installed capacity.

[0198] In the present invention, a comprehensive scoring model with a two-layer architecture of basic indicators and scoring indicators is proposed. First, the basic indicators of the operation of the new energy station are calculated to determine the objective operation status. Then, based on the basic indicators, the energy efficiency and reliability of the equipment are calculated to generate a series of scoring indicators to support the calculation of the final score. The production indicator scores corresponding to the scoring indicators are obtained by weighted calculation of two parts, including the trend indicator obtained by comparing with its own historical operation status and the ranking indicator obtained by comparing with the output status of other units. The final score is obtained by averaging the two parts according to their own weights, which reduces the impact of inconsistent operating conditions on the output status evaluation of wind turbines. Each production indicator score is finally summarized according to its own weight. The weight can be adjusted according to the needs of the management subject to complete the personalization of the new energy operation and maintenance benchmarking management, and comprehensively improve the benchmarking level of new energy operation and maintenance management.

[0199] As a specific application example of the embodiment of the present invention, taking a new energy site as a wind farm site as an example, the following process is described for the rating method of the operation and maintenance level of the new energy site:

[0200] S1, obtain the SCADA data of the wind farm station that needs to be benchmarked, form the full data of the wind power equipment, and store the data according to the hierarchical relationship of region (province), station, and unit.

[0201] S2, first calculate the basic indicators, confirm the resource indicators, power generation indicators, power loss indicators, and maintenance time indicators of the new energy unit to be evaluated, clarify the definitions and units of relevant indicators, and determine the statistical period. The basic indicators are only used as basic data and do not participate in the scoring.

[0202] S3, basic indicators of computing resources. For the specific calculation formula, please refer to the above formula.

[0203] S4, calculates basic indicators of power consumption. For specific calculation formulas, please refer to the above formula.

[0204] S5, calculate the basic indicators of power loss. For the specific calculation formula, please refer to the above formula.

[0205] S6, calculate the basic indicators of maintenance time. For the specific calculation formula, please refer to the above formula.

[0206] S7. Determine the scoring indicators. Scoring indicators are the core indicators used to calculate the final score, including equipment energy efficiency indicators and equipment reliability indicators for operation and maintenance management. The definitions and units of relevant indicators must be clarified, and the statistical period must be determined. Calculations must be based on basic indicators.

[0207] S8, calculates the energy efficiency scoring indicators of the equipment. For the specific calculation formula, please refer to the above formula.

[0208] S9, calculate the equipment reliability scoring index. For the specific calculation formula, please refer to the above formula.

[0209] S10: Calculate the wind power equipment energy efficiency production index score. For the specific calculation formula, please refer to the above formula.

[0210] S11. Calculate the reliability production index score of wind power equipment. For the specific calculation formula, see the above formula.

[0211] S12: Calculate the production index scores using a weighted average or direct summation method to obtain a final score, namely the total index score. This total index score determines the final rating of the station and comprehensively considers the current index completion level, ranking among the benchmarked equipment, and year-on-year changes. Among them, for a single station, its total score is set to 1000 points, and it is evaluated and scored based on the completion of monthly and annual wind power production indicators; the total score of a single region is set to 100 points, and the regional total score is calculated based on the individual station evaluation score and the weighted installed capacity of the station.

[0212] S13, site rating. Wind and solar power stations will be evaluated and rated on a quarterly and annual basis, and the results will be reported. The ratings are divided into four levels, from high to low: A (excellent), B (good), C (average), and D (poor). Levels A, B, and C must meet the corresponding prerequisites. Given the unique nature of the offshore wind power operation and maintenance window, the offshore wind farm index evaluation and rating work is conducted separately from onshore wind farms. For wind and solar power plants operating on the same site, wind power and photovoltaic power will be evaluated and rated as independent sites.

[0213] S14: Wind farms that rank in the top 10% in terms of production index evaluation scores and whose individual index scores are no less than 85% will be rated A.

[0214] S15: Wind farms that rank in the top 10%-50% of production index evaluation scores and have a single index score rate of no less than 75%, or those that rank in the top 10% and do not meet the A-level conditions, will be rated as B.

[0215] S16: Wind farms that rank in the top 50%-90% of the production index evaluation scores, or rank in the top 50% and do not meet the B-level conditions, or are not connected to the benchmarking system, will be rated as C-level.

[0216] S17. Wind farms that rank in the bottom 10% of production index evaluation scores and have a score below 800 points, or that experience equipment accidents such as wind turbine runaway, tower collapse, blade breakage, fire, or main transformer damage during the evaluation quarter or year, or that experience power grid accidents due to inadequate wind farm operation and maintenance, or that fail to eliminate major or above hidden dangers on schedule, or that engage in fraudulent data reporting, will be assessed as D.

[0217] S18: Monthly scoring: Before the 10th of each month, the wind power production indicators of each directly affiliated unit in the previous month will be statistically evaluated. Quarterly and annual scoring: Before the 15th of the first month, the wind power production indicators of each wind farm station in the previous quarter and year will be evaluated and rated.

[0218] S19. Based on the evaluation results, for areas with poor indicator scores or wind farms rated as D, management will be strengthened through notifications, interviews, special supervision and other measures. Relevant units will be required to formulate rectification plans, clarify rectification measures, strengthen implementation efforts, and improve the level of wind power production management.

[0219] In this embodiment, a new energy station operation and maintenance level rating device is also provided. The device is used to implement the above-mentioned embodiments and preferred embodiments. The details that have been described will not be repeated here. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and conceivable.

[0220] This embodiment provides a new energy station operation and maintenance level rating device, such as Figure 2 As shown, including:

[0221] The data acquisition module 21 is used to obtain the operating data of multiple new energy stations in the area.

[0222] The scoring index calculation module 22 is used to calculate the current scoring index value of each new energy station based on the operating data. The scoring index value includes the energy efficiency scoring index value and the reliability scoring index value;

[0223] The production index score calculation module 23 is used to calculate the production index score of each new energy station based on the current score index value of each new energy station, the change value of the current score index value relative to the historical score index value, the maximum value, minimum value and corresponding change value of the score index value of each new energy station;

[0224] The rating module 24 is used to determine the operation and maintenance level of each new energy station based on the production indicator score of each new energy station.

[0225] The further functional description of each of the above modules is the same as that of the above corresponding embodiments and will not be repeated here.

[0226] The embodiment of the present invention also provides a computer device having the above Figure 2 The new energy station operation and maintenance level rating device shown.

[0227] See also Figure 3 , Figure 3 is a structural diagram of a computer device provided by an optional embodiment of the present invention, such as Figure 3As shown, the computer device includes: one or more processors 10, memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components utilize different buses to communicate with each other and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in the memory or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Equally, multiple computer devices can be connected, and each device provides part of the necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 3 A processor 10 is taken as an example.

[0228] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic, or any combination thereof.

[0229] The memory 20 stores instructions that can be executed by at least one processor 10, so as to enable at least one processor 10 to execute the method shown in the above embodiment.

[0230] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created based on the use of a computer device for displaying a small program landing page, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0231] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0232] The computer device further includes a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0233] The embodiment of the present invention also provides a computer-readable storage medium. The above-mentioned method according to the embodiment of the present invention can be implemented in hardware, firmware, or implemented as a computer code that can be recorded in a storage medium, or implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memory. It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.

[0234] A portion of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the form in which the computer program instruction exists in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc. Accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium that can be accessed by the computer.

[0235] Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention. Such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for rating the operation and maintenance level of new energy stations, characterized in that: The method comprises: Obtain operating data of multiple new energy stations in the region; Calculate the current scoring index value of each new energy station based on the operating data, wherein the scoring index value includes an energy efficiency scoring index value and a reliability scoring index value; The production index score of each new energy station is calculated based on the current score index value of each new energy station, the change value of the current score index value relative to the historical score index value, the maximum value, minimum value and corresponding change value of the score index value of each new energy station; The operation and maintenance level of each new energy station is determined based on the production indicator score of each new energy station.

2. The method according to claim 1, characterized in that Energy efficiency scoring indicators include: energy efficiency loss rate, power prediction accuracy, utilization hour relative feasibility deviation rate, and energy utilization rate; reliability scoring indicators include: equipment availability, mean fault recovery time, mean time between failures after maintenance, average number of downtimes per unit, and average downtime per unit; The production index scores corresponding to energy efficiency loss rate, mean fault recovery time, mean time between failures after maintenance, average number of downtimes per unit, and average downtime per unit are calculated using the following formula: The production indicator scores corresponding to power prediction accuracy, utilization hour relative feasibility deviation rate, energy utilization rate, and equipment availability are calculated using the following formula: In the formula, S represents the production index score, a represents the weight of the score index value, b represents the discrimination coefficient of the score index value, m represents the current score index value, and m max Indicates the maximum value of the scoring index of each new energy station, m min It represents the minimum value of the scoring index value of each new energy station, Δm represents the change value of the current scoring index value relative to the historical scoring index value, Δm max Indicates the change in the maximum value of the scoring index value of each new energy station, Δm min It represents the change in the minimum value of the scoring index of each new energy station, and n represents the standard score of the corresponding scoring index.

3. The method according to claim 1, characterized in that Reliability scoring indicators also include: platform communication interruption rate, number of defects and timeliness of problem handling. The production index score corresponding to the platform communication interruption rate is determined based on the current platform communication interruption rate and the minimum value of the platform communication interruption rate of each new energy station; the production index score corresponding to the number of defects is determined based on the statistical value of the number of defects; the production index score corresponding to the timeliness of problem handling is determined based on the maximum value of the current problem handling timeliness and the timeliness of problem handling of each new energy station.

4. The method according to claim 1, wherein The operation and maintenance level of each new energy station is determined based on the production indicator score of each new energy station, including: The ranking, individual indicator score rate and total indicator score of each new energy station are determined based on the production indicator score of each new energy station; New energy stations whose rankings meet the first preset condition and whose individual indicator scores meet the second preset condition will be rated as A-level; New energy stations whose rankings meet the third preset condition and whose individual indicator scores meet the fourth preset condition, or new energy stations whose rankings meet the first preset condition and whose individual indicator scores do not meet the second preset condition, will be rated as Class B; New energy stations that meet the fifth preset condition, or meet the third preset condition but whose individual indicator scores do not meet the fourth preset condition, or new energy stations that are not connected to the preset system will be rated as C. New energy stations whose rankings meet the sixth preset condition and whose total index scores meet the seventh preset condition, or new energy stations that have preset failures, will be rated D.

5. The method according to claim 1, wherein The current scoring index values include monthly, quarterly and annual scoring index values. The operation and maintenance level of each new energy station is determined based on the production index score of each new energy station, and also includes: Determine the monthly, quarterly and annual operation and maintenance levels of each new energy station based on the production indicator scores of each new energy station; The total regional score is calculated based on the production index score of each new energy station and the weighted installed capacity of each new energy station.

6. The method according to claim 2, characterized in that The energy efficiency loss rate is determined by the ratio of energy efficiency loss electricity to the required power generation; the power prediction accuracy is determined by the predicted power, actual power and startup capacity; the utilization hour relative feasibility deviation rate is determined by the actual power generation, rated capacity and feasibility utilization hours; and the energy utilization rate is determined by the ratio of actual power generation to required power generation.

7. The method according to claim 2, characterized in that The platform communication interruption rate is determined by the number of units connected to the platform, the communication interruption time and the calendar time; the equipment availability is determined by the total time of the unit's available status and the normal communication events; the average fault recovery time is determined by the total number of faults and the start and recovery times of each unit's fault shutdown; the average fault-free time after maintenance is determined by the total number of maintenances, the end time of each unit's maintenance shutdown, and the start time of the first fault shutdown after maintenance; the average number of shutdowns per unit is determined by the number of units and the number of shutdowns for each unit; the average downtime per unit is determined by the number of units and the downtime for each unit; the number of defects is determined by the number of times the new energy station failure exceeds the preset time; the timeliness of problem handling is determined by the number of units that have solved the problem, the number of units with problems and the hours used to solve the problem.

8. A new energy station operation and maintenance level rating device, characterized in that: The device comprises: Data acquisition module, used to obtain operating data of multiple new energy stations in the region; A scoring index calculation module, configured to calculate a current scoring index value for each new energy station based on the operating data, wherein the scoring index value includes an energy efficiency scoring index value and a reliability scoring index value; A production index scoring calculation module is used to calculate the production index score of each new energy station based on the current scoring index value of each new energy station, the change value of the current scoring index value relative to the historical scoring index value, the maximum value, minimum value and corresponding change value of the scoring index value of each new energy station; The rating module is used to determine the operation and maintenance level of each new energy station based on the production indicator score of each new energy station.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the new energy station operation and maintenance level rating method according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the new energy station operation and maintenance level rating method according to any one of claims 1 to 7.

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