A power system coal power unit flexibility evaluation processing method and system

Abstract

The application discloses a kind of electric power system coal power unit flexibility evaluation processing method and system, method includes according to the unit parameter data and historical operation data of renewable energy unit obtained, obtain wind light output curve and load curve;Based on time series production simulation technology determines the flexibility demand data of power supply side of electric power system;According to the coal power unit operation configuration data in electric power system, determine the flexibility supply capacity data of coal power unit;Flexibility demand data and flexibility supply capacity data are compared and analyzed, determine the flexibility evaluation result of electric power system coal power unit based on analysis result, and generate optimization processing strategy based on flexibility evaluation result.The electric power system coal power unit flexibility evaluation processing method provided by the application can realize the flexibility evaluation processing of coal power unit, help to tap the flexibility regulation potential of coal power unit, judge the flexibility adequacy of electric power system, provide theory and basis for coal power unit flexibility reconstruction decision.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power grid energy, in particular to a power system coal-fired unit flexibility evaluation processing method and system. BACKGROUND

[0002] Large-scale development and utilization of renewable energy can help reduce dependence on traditional fossil fuels such as coal, oil and natural gas. The exploitation and use of these traditional energy sources not only face the crisis of resource depletion, but also cause serious environmental pollution and greenhouse gas emissions. Therefore, the introduction of renewable energy is an important way to promote the transformation from traditional energy to clean energy.

[0003] Nowadays, in addition to traditional coal-fired energy, the power system also introduces a large number of renewable energy units such as wind power and photovoltaic power generation. However, due to the influence of meteorological conditions and geographical factors, the output of renewable energy such as wind and light has significant intermittency and randomness, so the safe and stable operation of the power system is challenged. In the prior art, only the operating conditions of renewable energy are analyzed, and the flexibility of coal-fired units is not analyzed, which cannot meet the evaluation and processing of the current new and old energy combined power grid system, and is not conducive to the optimization control of the power grid system. SUMMARY

[0004] The present application provides a power system coal-fired unit flexibility evaluation processing method and system. In the power system with renewable energy, a specific method step is designed to realize the flexibility evaluation and processing of coal-fired units, which helps to tap the flexibility regulation potential of coal-fired units, judge the flexibility adequacy of the power system, and provide theory and basis for coal-fired unit flexibility improvement decision.

[0005] To solve the above technical problems, the present application provides a power system coal-fired unit flexibility evaluation processing method, which is applied to a power system containing a high proportion of renewable energy units, the renewable energy units at least including wind units and photovoltaic units, comprising:

[0006] According to the obtained unit parameter data and historical operation data of the renewable energy units, the wind and light output curve and the load curve of the renewable energy units are obtained;

[0007] Based on the time sequence production simulation technology, at least the wind and light output curve and the load curve are processed to determine the flexibility demand data of the power supply side of the power system; and according to the coal-fired unit operation configuration data in the power system, the flexibility supply capability data of the coal-fired unit is determined;

[0008] The flexibility demand data and the flexibility supply capability data are compared and analyzed, and a flexibility evaluation result of the coal-fired generating unit of the power system is determined based on an analysis result, wherein the flexibility evaluation result at least reflects three aspects of flexibility shortage, flexibility shortage probability and peak regulation flexibility shortage expectation;

[0009] Based on the flexibility evaluation result, an optimization processing strategy matched with the power source side, the grid side and the demand side of the power system is respectively generated.

[0010] As one of the preferred solutions, the flexibility demand data includes upward flexibility demand data and downward flexibility demand data, which are represented by the following formula:

[0011]

[0012] Wherein, F t NL,upd , F t NL,dnd are the upward flexibility demand data and the downward flexibility demand data of the power system at t moment, P t de is the power source side flexibility demand data at t moment, are the minimum and maximum adjustable power source flexibility demand data at t+1 moment.

[0013] As one of the preferred solutions, the flexibility supply capability data of the coal-fired generating unit is represented by the following formula:

[0014]

[0015]

[0016]

[0017]

[0018] Wherein, are the upward / downward flexibility supply data provided by the coal-fired generating unit i at t moment, G is the number of coal-fired generating units, u i,t is the preset variable of the coal-fired generating unit i at t moment, P i max , P i min are the maximum and minimum output of the coal-fired generating unit i at t moment, P i,t is the real-time output of the coal-fired generating unit i at t moment, are the upward / downward ramp rates of the unit i, and ΔT is the time scale.

[0019] As one of the preferred solutions, the wind and light output curve of the renewable energy unit is obtained according to the obtained unit parameter data and historical operation data of the renewable energy unit, comprising:

[0020] The obtained unit parameter data and historical operation data are subjected to data cleaning and normalization processing to obtain sample data, wherein the historical operation data at least includes wind speed, wind direction, light intensity, temperature and power generation;

[0021] The prediction model based on neural network technology is trained by using the sample data;

[0022] The prediction results output by the prediction model are processed based on time series technology, and the wind and light output curve is drawn.

[0023] As one of the preferred solutions, the optimization processing strategy at least includes a coal-fired unit modification strategy, and the coal-fired unit modification strategy comprises:

[0024] Based on artificial intelligence learning algorithm and optimization technology, the operation data of the coal-fired unit are learned and predicted to adjust the peak shaving capacity and operation efficiency of the coal-fired unit.

[0025] Another embodiment of the present application provides a flexible evaluation processing system for coal-fired units of a power system, which is applied to a power system containing a high proportion of renewable energy units, wherein the renewable energy units at least include wind units and photovoltaic units, comprising:

[0026] A renewable energy module is used to obtain the wind and light output curve and load curve of the renewable energy unit according to the obtained unit parameter data and historical operation data of the renewable energy unit;

[0027] A flexibility data module is used to process at least the wind and light output curve and the load curve based on time series production simulation technology to determine the flexibility demand data of the power supply side of the power system, and to determine the flexibility supply capacity data of the coal-fired units according to the coal-fired unit operation configuration data in the power system;

[0028] An evaluation module is used to compare and analyze the flexibility demand data and the flexibility supply capacity data, and to determine the flexibility evaluation result of the coal-fired units of the power system based on the analysis result, wherein the flexibility evaluation result at least reflects three aspects of flexibility shortage, flexibility deficiency probability and peak shaving flexibility deficiency expectation;

[0029] An optimization processing module is used to generate an optimization processing strategy matched with the power supply side, the grid side and the demand side of the power system respectively based on the flexibility evaluation result.

[0030] As one of the preferred solutions, the flexibility demand data includes upward flexibility demand data and downward flexibility demand data, which are represented by the following formulas:

[0031]

[0032] wherein F t NL,upd , F t NL,dnd are upward flexibility demand data and downward flexibility demand data of the power system at time t, P t de is power supply side flexibility demand data at time t, are minimum and maximum adjustable power supply flexibility demand data at time t+1, respectively.

[0033] As one of the preferred solutions, the flexibility supply capability data of the coal-fired generating unit is represented by the following formula:

[0034]

[0035]

[0036]

[0037]

[0038] wherein, are upward / downward flexibility supply data provided by the coal-fired generating unit i at time t, G is the number of coal-fired generating units, u i,t is a preset variable of the coal-fired generating unit i at time t, P i max , P i min are maximum and minimum output of the coal-fired generating unit i at time t, P i,t is real-time output of the coal-fired generating unit i at time t, are upward / downward ramp rates of the unit i, and ΔT is a time scale.

[0039] As one of the preferred solutions, the renewable energy module includes:

[0040] a processing unit configured to perform data cleaning and normalization processing on the acquired unit parameter data and historical operation data to obtain sample data, wherein the historical operation data at least includes wind speed, wind direction, light intensity, temperature and power generation;

[0041] a training unit configured to train a prediction model constructed based on neural network technology with the sample data.

[0042] a drawing unit configured to process a prediction result output by the prediction model based on a time series technique to draw the wind-solar power output curve.

[0043] As one of the preferred solutions, the optimization processing strategy at least includes a coal-fired unit modification strategy, and the coal-fired unit modification strategy includes:

[0044] Based on an artificial intelligence learning algorithm and an optimization technique, operation data of the coal-fired unit are learned and predicted to adjust a peak regulation capacity and an operation efficiency of the coal-fired unit.

[0045] Compared with the prior art, the embodiment of the present application has at least one of the following advantages:

[0046] (1) The scheme analyzes the flexibility demand considering wind-solar and load prediction errors from the supply-demand perspective, and considers the adjustment characteristics of the coal-fired unit to obtain the corresponding flexibility supply capacity, thereby providing accurate data support for subsequent comparison analysis and improving the accuracy and comprehensiveness of system flexibility analysis;

[0047] (2) The flexibility evaluation result of the scheme reflects three aspects of flexibility shortage, flexibility deficiency probability and peak regulation flexibility deficiency expectation, thereby improving the quantitative estimation of flexibility evaluation, helping to tap the flexibility regulation potential of the coal-fired unit, judging the flexibility adequacy of the power system, and providing theory and basis for the flexibility modification decision of the coal-fired unit. BRIEF DESCRIPTION OF DRAWINGS

[0048] Figure 1 is a flowchart of a power system coal-fired unit flexibility evaluation processing method in one embodiment of the present application;

[0049] Figure 2 is a schematic diagram of a wind-solar power output curve and a load curve in one embodiment of the present application;

[0050] Figure 3 is a flexibility demand / supply schematic diagram in one embodiment of the present application;

[0051] Figure 4 is a down-regulation peak flexibility deficiency expectation schematic diagram in one embodiment of the present application;

[0052] Figure 5 is a coal-fired unit upward flexibility adjustment factor schematic diagram in one embodiment of the present application;

[0053] Figure 6 is a coal-fired unit downward flexibility adjustment factor schematic diagram in one embodiment of the present application;

[0054] Figure 7 is a structural block diagram of a power system coal power unit flexibility evaluation processing system in one of the embodiments of the present application. DETAILED DESCRIPTION

[0055] The technical solutions in the embodiments of the present application will be clearly and completely described in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments of the present application. The purpose of providing these embodiments is to make the disclosure of the present application more thorough and comprehensive. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0056] In the description of the present application, the terms "first", "second", "third" and the like are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second", "third" and the like can explicitly or implicitly include one or more features. In the description of the present application, unless otherwise specified, the meaning of "a plurality of" is two or more.

[0057] In the description of the present application, it should be noted that, unless otherwise explicitly specified and limited, the terms "mounting", "connecting", "connecting" should be understood in a broad sense, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium, or it can be the communication inside two elements. The terms "vertical", "horizontal", "left", "right", "up", "down" and similar expressions used in this paper are only for the purpose of description, and cannot be understood as indicating or implying that the devices or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present application. The term "and / or" used in this paper includes any and all combinations of one or more related listed items. For those skilled in the art, the specific meaning of the above terms in the present application can be understood in specific cases.

[0058] In the description of the present application, it should be noted that, unless otherwise defined, all technical and scientific terms used in the present application have the same meaning as understood by those skilled in the art. The terms used in the specification of the present application are only for the purpose of describing the specific embodiments, and are not intended to limit the present application. For those skilled in the art, the specific meaning of the above terms in the present application can be understood in specific cases.

[0059] It needs to be pointed out in advance that the quantitative evaluation of the flexibility of the power system under high proportion of renewable energy access plays an important role in excavating the flexibility adjustment capacity of coal-fired generating units to maintain the balance between supply and demand of system flexibility. The present application quantifies the flexibility of the renewable energy access system from the supply and demand angle based on time sequence production simulation, and calculates the flexibility evaluation index of coal-fired generating units by time sequence production simulation. Specifically, an embodiment of the present application provides a coal-fired generating unit flexibility evaluation processing method of a power system, specifically, please refer to Figure 1 , Figure 1 The flowchart shows the coal-fired generating unit flexibility evaluation processing method of the power system in one embodiment of the present application, which specifically includes steps S1-S4:

[0060] S1, according to the obtained unit parameter data and historical operation data of the renewable energy unit, the wind and light output curve and the load curve of the renewable energy unit are obtained;

[0061] S2, based on the time sequence production simulation technology, at least the wind and light output curve and the load curve are processed to determine the flexibility demand data of the power supply side of the power system; and according to the coal-fired generating unit operation configuration data in the power system, the flexibility supply capacity data of the coal-fired generating unit is determined;

[0062] S3, the flexibility demand data and the flexibility supply capacity data are compared and analyzed, and the flexibility evaluation result of the coal-fired generating unit of the power system is determined based on the analysis result, wherein the flexibility evaluation result at least reflects three aspects of flexibility shortage, flexibility deficiency probability and peak regulation flexibility deficiency expectation;

[0063] S4, based on the flexibility evaluation result, the optimization processing strategy matched with the power supply side, the grid side and the demand side of the power system is generated respectively.

[0064] The renewable energy unit in the embodiment refers to wind power unit and photovoltaic unit, with the increase of wind and light penetration rate, the flexibility supply capacity of the system itself is gradually weakened when facing the flexibility demand of the system due to the decrease of the proportion of coal-fired generating units, so it is necessary to excavate the flexibility adjustment potential of coal-fired generating units to cope with the flexibility deficiency challenge under high penetration rate. In the above embodiment, the effectiveness of the method of the present embodiment is verified and analyzed based on the improved IEEE-RTS24 node example system, the conventional units therein are replaced by coal-fired generating units in proportion to the capacity, and wind power and photovoltaic power station are added, wherein the rated capacity of the wind farm and the photovoltaic power station is 600MW and 400MW. It is assumed that each coal-fired generating unit is an adjustable unit, and the parameters of the coal-fired generating unit are as shown in the following table.

[0065] Coal-fired generating unit parameters

[0066]

[0067] Further, in the above embodiment, in order to obtain the wind and light output curve, firstly, the obtained unit parameter data and historical operation data (such as wind speed, wind direction, light intensity, temperature and power generation) need to be preprocessed, mainly data cleaning and normalization processing, and then sample data is obtained, and then based on the existing mature neural network model technology, the sample data is used to train the prediction model based on the neural network technology, and finally the obtained prediction data is used to draw the corresponding wind and light output curve. For the load curve, preferably, the output curves of the wind power plant and the photovoltaic power station can be superimposed with the load curve of the power system to obtain the equivalent load curve, and in the superposition process, the wind and light output is treated as negative load to reflect its contribution to power supply of the power system, and then the load curve is obtained.

[0068] Specifically, please refer to Figure 2 , Figure 2 The figure shows the wind and light output curve and the load curve in one embodiment of the application (a is the wind and light output curve, and b is the load curve). After obtaining the above data, analysis and processing are performed based on the time series production simulation technology. The time series production simulation is a technology for simulating the operation of a power system, which aims to simulate the operation of a power system at different time periods, including load demand, power generation output, power grid constraints, etc., to evaluate the operation of the power system and optimize the power generation plan. The purpose is to improve energy production efficiency, reduce energy production cost, and enhance the stability and reliability of the power system. Through time series production simulation, the flexibility demand data of the power source side and the flexibility supply capability data of the coal-fired unit can be obtained. Specifically, please refer to Figure 3 , Figure 3 The figure shows the flexibility demand / supply diagram in one embodiment of the application, which sets the average relative error of new energy and load to 10%, calculates the flexibility demand of the system under the current penetration rate, and obtains the flexibility supply of the system from the flexibility supply of the coal-fired unit. The flexibility demand / supply curve of the system is drawn under the hourly time scale.

[0069] Further, in the above embodiment, the flexibility demand data and the flexibility supply capability data are compared and analyzed, and the flexibility evaluation result of the coal-fired unit of the power system is determined based on the analysis result. The following will be described in detail in combination with the formula.

[0070] The flexibility demand of the power source side is represented by the following formula:

[0071]

[0072] Wherein, F t NL,upd , Ft NL,dnd These represent the upward and downward flexibility requirements of the power system at time t, respectively, P. t de The power supply flexibility requirement data at time t. These are the minimum and maximum adjustable power supply flexibility requirements at time t+1, respectively.

[0073] Within a time scale ΔT, the total flexibility requirement of the system can be categorized into three types. When P t de Less than At this point, the system generates an upward flexibility requirement; when P t de Greater than The system generates a downward flexibility requirement; P t de exist and In between, the system generates a need for two-way flexibility.

[0074] The operational flexibility of coal-fired power units is mainly reflected in their power output range and ramp rate. Faced with the upward / downward flexibility demands brought about by wind, solar, and load fluctuations, the flexibility supply of coal-fired power units within a given time scale is as follows:

[0075]

[0076]

[0077]

[0078]

[0079] in, Here, u represents the upward / downward flexibility supply data provided by coal-fired power unit i at time t, G is the number of coal-fired power units, and u represents the vertical / horizontal flexibility supply data. i,t Let P be a preset variable (0-1) for coal-fired power unit i at time t. i max P i min P represents the maximum and minimum output of coal-fired power unit i at time t. i,t For the real-time output of coal-fired power unit i at time t. ΔT represents the upward / downward ramp rate of unit i, and ΔT is the time scale.

[0080] In the embodiments of the present application, the flexible supply of coal-fired units minus the flexible demand generated by wind power, photovoltaic and load fluctuation is the available flexible adjustment capacity of the current system. When the upward / downward flexible supply of coal-fired units is less than the upward / downward flexible demand of the system, i.e., the flexible supply of coal-fired units is insufficient, it will lead to load shedding and wind and light curtailment. To measure the supply and demand of flexibility in the system, from the perspective of system operation, the embodiments of the present application propose the following flexibility indicators (i.e., flexibility evaluation results): flexibility shortage, flexibility adjustment factor, peak regulation flexibility shortage expectation, and flexibility shortage probability.

[0081] (1) Flexibility shortage: reflects the insufficient supply and demand of flexibility of coal-fired units.

[0082] F t ins,up = F t NL,upd F t g,ups

[0083] F t ins,dn = F t NL,dnd F t g,dns

[0084] In the formula, F t ins,up , F t ins,dn are the upward and downward flexibility shortage of the system at time t; F t NL,upd , F t NL,dnd are the upward and downward flexibility demand of the system at time t; F t g,ups , F t g,dns are the upward / downward flexibility that can be provided by the coal-fired unit group to the system at time t. The total flexibility shortage of the system can be obtained by summing up the flexibility shortage in the total time period. When the flexibility shortage at time t is less than 0, it means that the upward and downward flexibility at time t+1 is very sufficient, otherwise it means that there is a flexibility shortage in the system.

[0085] (2) Flexibility shortage probability: the flexibility shortage probability is defined as the ratio of the peak regulation flexibility shortage period to the total scheduling period, and the flexibility shortage probability P LOF can be calculated by the following formula.

[0086]

[0087] In the formula, T M is the set of peak regulation flexibility shortage periods; Mt the number of insufficient peak regulation flexibility periods; T is the entire scheduling period.

[0088] (3) Expected insufficient peak regulation flexibility: The difference between the flexibility supply and the flexibility demand in the unit time scale reflects the flexibility adequacy and the regulation speed of the system. The expected insufficient peak regulation flexibility power shortage of the system can be calculated by counting the insufficient peak regulation flexibility section in a period, which is obtained by the following formula.

[0089]

[0090]

[0091] In the formula, ΔP t up , ΔP t down are the insufficient upward / downward peak regulation flexibility amounts in the unit time; H t , J t are the numbers of upward / downward peak regulation flexibility insufficient power time periods; T H , T J are the upward / downward ramping flexibility insufficient power time period sets.

[0092] ΔP t up greater than 0 indicates that at this time, the coal-fired unit cannot cope with the flexibility demand brought by the new energy and load fluctuation even at the maximum output that can be reached, and load reduction will occur. ΔP t dn greater than 0 indicates that at this time, even if the coal-fired unit is at the minimum output that can be reached, it still cannot accommodate part of the new energy in the face of flexibility demand.

[0093] (4) Flexibility regulation factor: In order to measure the proportion of the flexibility supply of each coal-fired unit in the entire system, the flexibility regulation factor is defined as follows:

[0094]

[0095]

[0096] In the formula, P are the upward / downward flexibility supplies of the flexible regulation power source i; are the proportions of the flexible regulation power source i at time t to meet the upward / downward flexibility demand of the system, which reflects the contribution ability of each coal-fired unit to the flexibility balance of the power system.

[0097] When the sum of the flexible adjustment factors of the coal-fired unit group is greater than 1, it indicates that the flexibility supply of the coal-fired unit group can completely meet the flexibility demand of the system at this time, and the system belongs to a flexible system with sufficient flexibility; when the sum of the flexible adjustment factors is equal to 1, it indicates that the coal-fired unit group just meets the flexibility demand of the system, and the system flexibility is neither sufficient nor redundant; if the flexible adjustment factor is less than 1, it indicates that the system has insufficient flexibility at this time.

[0098] Based on the flexibility supply and demand of each period, the flexibility shortage probability and the total flexibility shortage index of the system can be calculated by the above formula. Through calculation, the total flexibility shortage of the system is 2551.7317 MW, and the flexibility shortage probability is 0.3958. It can be seen that the flexibility adjustment capacity of the coal-fired unit is insufficient.

[0099] Through calculation, the expected up-regulation peak flexibility shortage of the system is 106.3222 MW. For details, please refer to Figure 4 , Figure 4 The figure shows the down-regulation peak flexibility shortage expectation diagram in one of the embodiments of the present application. When the wind and light output is large, in order to absorb wind and light as much as possible, the coal-fired unit is operated at a low output level, and the up-regulation flexibility supply of the coal-fired unit at this time is sufficient to meet the up-regulation flexibility demand generated by the system, and there is no up-regulation peak flexibility shortage, but when the down-regulation flexibility demand is generated, the coal-fired unit is limited by the minimum unit output, and serious down-regulation peak flexibility shortage will occur.

[0100] For details, please refer to Figure 5 , Figure 5 The figure shows the up-regulation flexibility adjustment factor diagram of the coal-fired unit in one of the embodiments of the present application, wherein the red dotted line represents that the coal-fired unit can completely meet the flexibility demand of the system. It can be seen that in all time periods, the flexibility adjustment factor is greater than 1, which indicates that the up-regulation flexibility supply capacity of the coal-fired unit at this time can completely meet the flexibility demand of the system.

[0101] For details, please refer to Figure 6 , Figure 6 The figure shows the down-regulation flexibility adjustment factor diagram of the coal-fired unit in one of the embodiments of the present application. The down-regulation flexibility supply capacity of the system in the whole time period is mainly provided by the G8 unit with the largest capacity, and the down-regulation flexibility supply capacity of the coal-fired unit is seriously insufficient in most of the time. The main reason is that when the new energy output value is high, most of the coal-fired units are operated at the minimum output, and have basically no down-regulation flexibility supply capacity.

[0102] Further, in the above embodiment, after the evaluation, an optimization processing strategy matching the power system power supply side, grid side and demand side is also generated, which takes into account that the insufficient energy unit flexibility supply capacity is a complex problem that needs to be optimized and controlled from multiple aspects. For example, for the power supply side, a coal-fired unit modification strategy can be generated to accelerate the flexible modification progress of thermal power and improve the peak shaving capacity and operation efficiency of coal-fired units, wherein advanced artificial intelligence algorithms and optimization techniques can be introduced to learn and predict the operation data of coal-fired units, which will not be described here. For the grid side, the grid structure can be optimized to improve the flexibility and reliability of the grid. For the demand side, a demand response mechanism can be established and improved to guide users to adjust their power consumption behavior according to the power system demand.

[0103] Specifically, please refer to Figure 7 , Figure 7 shows the structure block diagram of the coal-fired unit flexibility evaluation processing system in one embodiment of the present application, which is used in a power system containing a high proportion of renewable energy units, including wind units and photovoltaic units, comprising:

[0104] a renewable energy module 11 for obtaining the wind and light output curves and load curves of the renewable energy units according to the obtained unit parameter data and historical operation data of the renewable energy units;

[0105] a flexibility data module 12 for processing at least the wind and light output curves and the load curves based on time series production simulation technology to determine the flexibility demand data of the power supply side of the power system, and determining the flexibility supply capacity data of the coal-fired units according to the coal-fired unit operation configuration data in the power system;

[0106] an evaluation module 13 for comparing and analyzing the flexibility demand data and the flexibility supply capacity data, and determining the flexibility evaluation result of the coal-fired units in the power system based on the analysis result, wherein the flexibility evaluation result at least reflects three aspects of flexibility shortage, flexibility deficiency probability and peak shaving flexibility deficiency expectation;

[0107] an optimization processing module 14 for generating an optimization processing strategy matching the power supply side, grid side and demand side of the power system based on the flexibility evaluation result.

[0108] Further, in the above embodiment, the flexibility demand data includes upward flexibility demand data and downward flexibility demand data, which is represented by the following formula:

[0109]

[0110] wherein, Ft NL,upd , F t NL,dnd respectively represent upward and downward flexibility demand data of the power system at time t, P t de represents power supply side flexibility demand data at time t, respectively represent minimum and maximum adjustable power supply flexibility demand data at time t+1.

[0111] Further, in the above embodiment, the flexibility supply capability data of the coal-fired generating unit is represented by the following formula:

[0112]

[0113]

[0114]

[0115]

[0116] wherein, respectively represent upward and downward flexibility supply data provided by the coal-fired generating unit i at time t, G represents the number of coal-fired generating units, u i,t represents a preset variable of the coal-fired generating unit i at time t, P i max , P i min respectively represent maximum and minimum output of the coal-fired generating unit i at time t, P i,t represents real-time output of the coal-fired generating unit i at time t, respectively represent upward and downward ramping rates of the generating unit i, and ΔT represents a time scale.

[0117] Further, in the above embodiment, the renewable energy module comprises:

[0118] a processing unit configured to perform data cleaning and normalization processing on the obtained unit parameter data and historical operation data to obtain sample data, wherein the historical operation data at least includes wind speed, wind direction, light intensity, temperature and power generation;

[0119] a training unit configured to train a prediction model constructed based on neural network technology by using the sample data;

[0120] a drawing unit configured to process a prediction result output by the prediction model based on time series technology to draw the wind-solar power output curve.

[0121] Further, in the above-mentioned embodiments, the optimization processing strategy at least includes a coal power unit modification strategy, and the coal power unit modification strategy includes:

[0122] Based on the artificial intelligence learning algorithm and optimization technology, the operation data of the coal power unit are learned and predicted to adjust the peak shaving capability and operation efficiency of the coal power unit.

[0123] The power system coal power unit flexibility evaluation processing method and system provided by the embodiments of the present application have at least one of the following beneficial effects:

[0124] (1) The scheme analyzes the flexibility demand considering wind, light and load prediction errors from the supply and demand angle, and considers the adjustment characteristics of the coal power unit to obtain the corresponding flexibility supply capability, thereby providing accurate data support for subsequent comparison analysis and improving the accuracy and comprehensiveness of the system flexibility analysis;

[0125] (2) The flexibility evaluation result of the scheme reflects three aspects of flexibility shortage, flexibility deficiency probability and peak shaving flexibility deficiency expectation, thereby improving the quantitative estimation of flexibility evaluation, helping to tap the flexibility regulation potential of the coal power unit, judging the flexibility adequacy of the power system, and providing theory and basis for the flexibility modification decision of the coal power unit.

[0126] The above-mentioned embodiments only express several embodiments of the present application, and the description is more specific and detailed, but it cannot be understood as a limitation on the scope of the patent of the present application. It should be pointed out that for ordinary skilled persons in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A method for assessing the flexibility of coal-fired power units in a power system, applied to a power system containing a high proportion of renewable energy units, wherein the renewable energy units include at least wind turbines and solar power units, characterized in that, include: Based on the obtained unit parameter data and historical operating data of the renewable energy unit, the wind and solar power output curves and load curves of the renewable energy unit are obtained; Based on time-series production simulation technology, at least the wind and solar power output curves and the load curves are processed to determine the flexibility demand data of the power system's power supply side. And, based on the operating configuration data of the coal-fired power units in the power system, determine the flexible supply capacity data of the coal-fired power units; The flexibility demand data and the flexibility supply capacity data are compared and analyzed. Based on the analysis results, the flexibility assessment results of the coal-fired power units in the power system are determined. The flexibility assessment results reflect at least three aspects: flexibility deficit, probability of insufficient flexibility, and expectation of insufficient peak-shaving flexibility. Based on the flexibility assessment results, optimized processing strategies matching the power supply side, grid side, and demand side of the power system are generated respectively.

2. The power system coal-fired power unit flexibility assessment method as described in claim 1, characterized in that, The flexibility requirement data includes upward flexibility requirement data and downward flexibility requirement data, which are expressed by the following formula: Among them, F t NL,upd F t NL,dnd These represent the upward and downward flexibility requirements of the power system at time t, respectively, P. t de The power supply flexibility requirement data at time t. These are the minimum and maximum adjustable power supply flexibility requirements at time t+1, respectively.

3. The power system coal-fired power unit flexibility assessment method as described in claim 1, characterized in that, The flexible supply capacity data of the coal-fired power units is expressed by the following formula: in, Here, u represents the upward / downward flexibility supply data provided by coal-fired power unit i at time t, G is the number of coal-fired power units, and u represents the vertical / horizontal flexibility supply data. i,t Let P be the preset variable of coal-fired power unit i at time t. i max P i min P represents the maximum and minimum output of coal-fired power unit i at time t. i,t For the real-time output of coal-fired power unit i at time t. ΔT represents the upward / downward ramp rate of unit i, and ΔT is the time scale.

4. The power system coal-fired power unit flexibility assessment method as described in claim 1, characterized in that, The step of obtaining the wind and solar power output curves of the renewable energy units based on the acquired unit parameter data and historical operating data includes: The acquired unit parameter data and historical operating data are cleaned and normalized to obtain sample data, wherein the historical operating data includes at least wind speed, wind direction, solar intensity, temperature and power generation. The sample data is used to train a prediction model built on neural network technology; The prediction results output by the prediction model are processed using time series technology to obtain the wind and solar power output curve.

5. The power system coal-fired power unit flexibility assessment method as described in claim 1, characterized in that, The optimization strategy includes at least a coal-fired power unit retrofit strategy, which includes: Based on artificial intelligence learning algorithms and optimization techniques, the operating data of the coal-fired power units are learned and predicted in order to adjust the peak-shaving capacity and operating efficiency of the coal-fired power units.

6. A power system coal-fired power unit flexibility assessment and processing system, applied to a power system containing a high proportion of renewable energy units, wherein the renewable energy units include at least wind turbines and photovoltaic units, characterized in that, include: The renewable energy module is used to obtain the wind and solar power output curves and load curves of the renewable energy unit based on the acquired unit parameter data and historical operating data. The flexibility data module is used to process at least the wind and solar power output curves and the load curves based on time-series production simulation technology to determine the flexibility demand data of the power system's power source side. And, based on the operating configuration data of the coal-fired power units in the power system, determine the flexible supply capacity data of the coal-fired power units; The assessment module is used to compare and analyze the flexibility demand data and the flexibility supply capacity data, and determine the flexibility assessment result of the coal-fired power units in the power system based on the analysis results. The flexibility assessment result reflects at least three aspects: flexibility deficit, probability of insufficient flexibility, and expectation of insufficient peak-shaving flexibility. An optimization processing module is used to generate optimization processing strategies that match the power supply side, grid side, and demand side of the power system, respectively, based on the flexibility assessment results.

7. The power system coal-fired power unit flexibility assessment and processing system as described in claim 6, characterized in that, The flexibility requirement data includes upward flexibility requirement data and downward flexibility requirement data, which are expressed by the following formula: Among them, F t NL,upd F t NL,dnd These represent the upward and downward flexibility requirements of the power system at time t, respectively, P. t de The power supply flexibility requirement data at time t. These are the minimum and maximum adjustable power supply flexibility requirements at time t+1, respectively.

8. The power system coal-fired power unit flexibility assessment and processing system as described in claim 6, characterized in that, The flexible supply capacity data of the coal-fired power units is expressed by the following formula: in, Here, u represents the upward / downward flexibility supply data provided by coal-fired power unit i at time t, G is the number of coal-fired power units, and u represents the vertical / horizontal flexibility supply data. i,t Let P be the preset variable of coal-fired power unit i at time t. i max P i min P represents the maximum and minimum output of coal-fired power unit i at time t. i,t For the real-time output of coal-fired power unit i at time t. ΔT represents the upward / downward ramp rate of unit i, and ΔT is the time scale.

9. The power system coal-fired power unit flexibility assessment and processing system as described in claim 6, characterized in that, The renewable energy module includes: The processing unit is used to perform data cleaning and normalization on the acquired unit parameter data and the historical operating data to obtain sample data, wherein the historical operating data includes at least wind speed, wind direction, light intensity, temperature and power generation. A training unit is used to train a prediction model built on neural network technology using the sample data. The plotting unit is used to process the prediction results output by the prediction model based on time series technology and plot the wind and solar power output curve.

10. The power system coal-fired power unit flexibility assessment and processing system as described in claim 6, characterized in that, The optimization strategy includes at least a coal-fired power unit retrofit strategy, which includes: Based on artificial intelligence learning algorithms and optimization techniques, the operating data of the coal-fired power units are learned and predicted in order to adjust the peak-shaving capacity and operating efficiency of the coal-fired power units.

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