Water-light complementary short-term scheduling method, system, equipment and medium

Abstract

The invention relates to a water-light complementation short-term scheduling method, system and device and a medium, and the method comprises the steps: generating a typical power generation line type according to the hydroelectric load change condition in historical hydroelectric day operation data; according to the power grid load demand, the photovoltaic power prediction accuracy and the environmental condition, the minimum output of the base load area, the minimum output of the waist load area and the minimum output of the peak load area are obtained. And respectively obtaining the reservoir system constraint and the power system constraint of the hydropower station. And performing water-light complementary scheduling according to the minimum output of the base load area, the waist load area and the peak load area based on the hydropower station reservoir system constraint and the power system constraint. According to the method, drainage basin scheduling reality is fully considered, conventional hydropower historical operation data are utilized, the typical output process of hydropower scheduling is identified, the peak regulation capacity of a complementary system is exerted to the maximum extent, peak regulation benefit maximization is achieved, and the method has good operability and popularization value. The problem of low peak regulation benefit of water-light complementary short-term scheduling in the related technology is solved.

Description

Technical Field

[0001] The present application relates to the technical field of water-solar scheduling, and in particular to a method, system, device and medium for water-solar complementary short-term scheduling. Background Art

[0002] With the increasing awareness of global climate change and environmental protection, the application of clean energy is becoming more and more widespread. In particular, under the background of the "dual carbon" goal, the scale of photovoltaic installations has grown rapidly. Photovoltaic power generation, as a clean and renewable form of energy, is of great significance for reducing greenhouse gas emissions and improving environmental quality. However, due to the inherent characteristics of photovoltaic power sources - volatility, intermittency and randomness, large-scale access to the power grid will bring challenges to the stable operation of the power grid.

[0003] Hydropower units have become an ideal choice for balancing the fluctuations in photovoltaic output due to their rapid response capabilities and flexible regulation performance. By bundling hydropower and photovoltaic power, the regulation capacity of hydropower can be used to smooth the volatility of photovoltaic output and achieve complementary scheduling of hydropower and photovoltaic power. At present, the complementary scheduling of hydropower and photovoltaic power is mainly concentrated in the short term. The scheduling models used are mostly aimed at maximizing power generation and minimizing power abandonment rate, and finding the optimal or suboptimal scheduling strategy under various constraints. These strategies help scheduling decision makers better understand and predict the power generation potential of the basin, so as to make more scientific and reasonable decisions.

[0004] However, the existing optimization scheduling models still have some problems in practical applications. For example, the ideal power generation plan does not match the actual power demand and the role of hydropower in the power grid, resulting in low peak-shaving efficiency in the existing short-term scheduling of hydropower-solar complementary power generation. Summary of the invention

[0005] The embodiments of the present application provide a method, system, device and medium for short-term scheduling of water-photovoltaic complementarity, so as to at least solve the problem of low peak-shaving efficiency in short-term scheduling of water-photovoltaic complementarity in the related art.

[0006] In a first aspect, an embodiment of the present application provides a short-term scheduling method for water-solar complementarity, the method comprising:

[0007] Generate a typical power generation line type according to the hydropower load changes in the historical hydropower daily operation data, wherein the typical power generation line type is used to characterize the hydropower load distribution in different time periods, and the typical power generation line type includes a base load area, a mid-load area, and a peak load area;

[0008] According to the grid load demand, the photovoltaic power prediction accuracy and the environmental conditions, the minimum output of the base load area, the mid-load area and the peak load area are respectively obtained;

[0009] Obtain the hydropower station reservoir system constraints and power system constraints respectively;

[0010] Based on the constraints of the hydropower station reservoir system and the power system constraints, water-solar complementary scheduling is performed according to the minimum output of the base load area, the mid-load area and the peak load area.

[0011] In one embodiment, generating a typical power generation line type according to the hydropower load change in the historical hydropower daily operation data includes:

[0012] Determine a load increase segment, a load decrease segment, and a load stability segment according to the hydropower load adjustment actions in the historical hydropower daily operation data, wherein the adjustment actions include increasing the load and reducing the load;

[0013] According to the daily minimum load, daily average load and daily maximum load of hydropower, load distribution intervals in different time periods are defined, and the load distribution intervals include base load area, mid-load area and peak load area;

[0014] Based on the load increase section, the load decrease section, the load stabilization section and the load distribution interval, a typical power generation line type is determined, wherein the typical power generation line type includes a straight line type, a single peak type, a double peak type and a multi-peak type.

[0015] In one embodiment, according to the hydropower load adjustment action in the historical hydropower daily operation data, the load increase section, the load decrease section and the load stability section are determined, including:

[0016] Determine the threshold of the load increase rate and the threshold of the load reduction rate according to the load increase and load reduction actions in the historical hydropower daily operation data;

[0017] Based on the threshold of the load increase rate and the threshold of the load reduction rate, a load increase point and a load reduction point are determined according to the relative climbing rate;

[0018] Determine a load increase segment based on the load increase point, and determine a load reduction segment based on the load reduction point;

[0019] A load stabilization segment is determined according to the starting time of the load increase segment to the ending time of the load reduction segment.

[0020] In one embodiment, the obtaining of the minimum outputs of the base load area, the mid-load area, and the peak load area respectively according to the actual load demand of the power grid, the photovoltaic power prediction accuracy, and the environmental conditions includes:

[0021] Determine whether the power grid has actual load demand for the hydropower station, the actual load demand includes ecological flow and shipping load demand. If there is actual load demand, determine the minimum output of the base load area as the minimum output that meets the actual load demand; if there is no actual load demand, determine the minimum output of the base load area as 0.

[0022] Determine the minimum output of the mid-load area based on the photovoltaic power prediction accuracy 7 days before the prediction date and the weather prediction results of the prediction day;

[0023] The minimum output in the peak load area is determined according to the average load of the historical hydropower daily operation data, wherein the minimum output in the peak load area is greater than the average load.

[0024] In one embodiment, the minimum output of the mid-load area is determined according to the photovoltaic power prediction accuracy rate 7 days before the prediction date and the weather prediction result of the prediction day, including:

[0025] When the average value of the photovoltaic power prediction accuracy rate 7 days before the prediction date is greater than the preset accuracy rate, the minimum output of the mid-load area is equal to the minimum output of the hydropower in the base load area plus the photovoltaic prediction output;

[0026] When the average value of the photovoltaic power prediction accuracy rate 7 days before the prediction day is less than the preset accuracy rate, the minimum output of the mid-load area is equal to the minimum output of the base load area plus the environmental coefficient multiplied by the photovoltaic installed capacity, wherein the environmental coefficient is determined according to the weather forecast result of the prediction day, when the weather forecast result is sunny, the environmental coefficient includes 0.7-0.9, when the weather forecast result is cloudy, the environmental coefficient includes 0.4-0.6, and when the weather forecast result is rainy, the environmental coefficient includes 0.1-0.3.

[0027] In one embodiment, the obtaining of the hydropower station reservoir system constraints and the power system constraints respectively includes:

[0028] Acquisition of hydropower station reservoir system includes:

[0029] Water balance constraint: Determine the water balance constraint based on the change in storage capacity of hydropower station i at the end of the tth period and the end of the t+1th period, the inflow and outflow of the tth period, and the interval between periods;

[0030] Hydraulic connection constraints: based on the discharge flow and water lag of hydropower station i at time period t and the interval inflow of hydropower station i+1 at time period t, the hydraulic connection constraints between hydropower stations are determined;

[0031] Reservoir water level constraint, determined according to the reservoir water level of hydropower station i at time period t and the upper and lower limits of the reservoir water level;

[0032] The discharge flow constraint is determined based on the discharge flow of the hydropower station i in the tth period and the upper and lower limits of the discharge flow;

[0033] The power generation flow constraint is determined according to the power generation flow of hydropower station i in the tth period and the upper and lower limits of the power generation flow.

[0034] The reservoir water level constraint at the end of the dispatch period is determined according to the given reservoir water level at the end of the dispatch period of hydropower station i;

[0035] Obtaining power system constraints includes:

[0036] Power station output constraints: Based on the upper and lower limits of the hydropower output and photovoltaic output of hydropower station i and photovoltaic station i in time period t, the power station output constraints are determined;

[0037] Transportation channel constraints: Determine the transportation channel constraints based on the upper limit of the transportation channel of the water-photovoltaic complementary system.

[0038] In one embodiment, the water-solar complementary scheduling is performed based on the constraints of the hydropower station reservoir system and the power system, according to the minimum output of the base load area, the mid-load area and the peak load area, including:

[0039] Under the various constraints of the hydropower station reservoir system and the power system in each period, preliminary dispatch of water-solar complementary loads is carried out according to the minimum output requirements of the base load area, mid-load area and peak load area to meet the minimum output constraints of each period;

[0040] According to the daily forecast inflow of the reservoir, the initial water level and the planned final water level, the daily power generation and water consumption is determined. Based on the daily power generation and water consumption and the prediction result of photovoltaic power, the constant total water and photovoltaic output within the section is adopted;

[0041] Based on the constant total hydro-solar output within the section, the hydro-solar output is synchronously increased in multiple sections in each area according to the priority order of peak load area, mid-load area and base load area until the upper limit of the hydro-solar output is reached, forming a stable hydro-solar complementary output within the period and completing the hydro-solar complementary scheduling.

[0042] In a second aspect, an embodiment of the present application provides a short-term scheduling system for water-solar complementary power generation, the system comprising a typical power generation line module, a module for obtaining the minimum output of different load areas, a hydropower station reservoir system constraint module and a power system constraint module, and a water-solar complementary power generation scheduling module, wherein:

[0043] The typical power generation line type module is used to generate a typical power generation line type according to the change of hydropower load in the historical hydropower daily operation data. The typical power generation line type is used to characterize the distribution of hydropower load in different time periods. The typical power generation line type includes a base load area, a mid-load area and a peak load area.

[0044] The module for obtaining the minimum output of different load areas is used to obtain the minimum output of the base load area, the mid-load area and the peak load area respectively according to the grid load demand, the photovoltaic power prediction accuracy and the environmental conditions;

[0045] The hydropower station reservoir system constraint and power system constraint modules are used to obtain the hydropower station reservoir system constraint and the power system constraint respectively;

[0046] The water-solar complementary scheduling module is used to perform water-solar complementary scheduling based on the reservoir system constraints of the hydropower station and the power system constraints, according to the minimum output of the base load area, the mid-load area and the peak load area.

[0047] In a third aspect, an embodiment of the present application provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, a short-term scheduling method for water-solar complementary power generation as described in the first aspect above is implemented.

[0048] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a short-term scheduling method for water-solar complementarity as described in the first aspect above.

[0049] The embodiments of the present application provide a method, system, device and medium for short-term scheduling of water-photovoltaic complementarity, which have at least the following technical effects.

[0050] According to the changes in the hydropower load in the historical hydropower daily operation data, a typical power generation line is generated. The typical power generation line is used to characterize the distribution of hydropower load in different periods. The typical power generation line includes base load area, waist load area and peak load area. According to the load demand of the power grid, the accuracy of photovoltaic power prediction and environmental conditions, the minimum output of the base load area, waist load area and peak load area are obtained respectively. The reservoir system constraints of the hydropower station and the power system constraints are obtained respectively. Based on the reservoir system constraints of the hydropower station and the power system constraints, the water-light complementary scheduling is carried out according to the minimum output of the base load area, waist load area and peak load area. This application fully considers the actual basin scheduling, uses the historical operation data of conventional hydropower, identifies the typical output process of hydropower scheduling, and arranges the power distribution of the water-light complementary system throughout the day with the typical process as a guide, so as to maximize the peak-shaving capacity of the complementary system and maximize the peak-shaving benefit. It has good operability and promotion value. It solves the problem of low peak-shaving benefit in the short-term scheduling of water-light complementary in the related technology.

[0051] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0053] Figure 1 is a flow chart of a short-term scheduling method for water-solar complementarity according to an embodiment of the present application;

[0054] Figure 2 is a flowchart of step S101 according to an exemplary embodiment;

[0055] Figure 3 is a schematic diagram of a typical power generation line type according to an exemplary embodiment;

[0056] Figure 4 is a flowchart of step S102 according to an exemplary embodiment;

[0057] Figure 5 is a flowchart of step S104 according to an exemplary embodiment;

[0058] Figure 6 is a schematic diagram showing the topological relationship and installed capacity of a power station according to an exemplary embodiment;

[0059] Figure 7 is a schematic diagram of a typical power generation line type according to an exemplary embodiment;

[0060] Figure 8 is a schematic diagram showing a result of water-solar complementary scheduling according to an exemplary embodiment;

[0061] Fig. 9 is a block diagram of a system for short-term scheduling of water-solar complementary power according to an exemplary embodiment;

[0062] Fig.10 is a block diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is described and illustrated below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application.

[0064] Obviously, the drawings described below are only some examples or embodiments of the present application. For ordinary technicians in this field, the present application can also be applied to other similar scenarios based on these drawings without creative work. In addition, it can also be understood that although the efforts made in this development process may be complicated and lengthy, for ordinary technicians in this field related to the content disclosed in this application, some changes in design, manufacturing or production based on the technical content disclosed in this application are just conventional technical means, and should not be understood as insufficient content disclosed in this application.

[0065] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those of ordinary skill in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0066] Unless otherwise defined, the technical terms or scientific terms involved in this application should be understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the" and the like involved in this application do not indicate a quantitative limitation, and may represent the singular or plural. The terms "include", "comprise", "have" and any of their variations involved in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there may be three relationships, for example, "A and / or B" can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects before and after are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

[0067] With the increasing awareness of global climate change and environmental protection, the application of clean energy is becoming more and more widespread. In particular, under the background of the "dual carbon" goal, the scale of photovoltaic installations has grown rapidly. Photovoltaic power generation, as a clean and renewable form of energy, is of great significance for reducing greenhouse gas emissions and improving environmental quality. However, due to the inherent characteristics of photovoltaic power sources - volatility, intermittency and randomness, large-scale access to the power grid will bring challenges to the stable operation of the power grid.

[0068] Hydropower units have become an ideal choice for balancing the fluctuations in photovoltaic output due to their rapid response capabilities and flexible regulation performance. By bundling hydropower and photovoltaic power, the regulation capacity of hydropower can be used to smooth the volatility of photovoltaic output and achieve complementary scheduling of hydropower and photovoltaic power. At present, the complementary scheduling of hydropower and photovoltaic power is mainly concentrated in the short term. The scheduling models used are mostly aimed at maximizing power generation and minimizing power abandonment rate, and finding the optimal or suboptimal scheduling strategy under various constraints. These strategies help scheduling decision makers better understand and predict the power generation potential of the basin, so as to make more scientific and reasonable decisions.

[0069] However, the existing optimization scheduling models still have some problems in practical applications. For example,

[0070] Disconnection between theory and practice: Existing optimization scheduling models often pursue theoretical optimal solutions, such as maximizing power generation and minimizing power abandonment rate. However, in practical applications, these ideal power generation plans are quite different from the actual needs of the power grid and the functional positioning of the hydropower station, and are therefore difficult to be adopted by the power grid dispatching department.

[0071] Insufficient flexibility: Traditional optimization models do not fully consider the changes in grid load characteristics, nor do they adapt well to different runoff scenarios and changes in daily power generation capacity.

[0072] Inadequate consideration of constraints: The model does not fully consider the constraints of the hydropower station reservoir system, such as water balance, water level restrictions, and discharge flow, as well as the constraints of the power system, such as power station output restrictions and transmission channel restrictions.

[0073] Therefore, the existing short-term scheduling of hydro-photovoltaic complementary power generation has the problem of low peak-shaving efficiency.

[0074] In view of the above background, the present invention proposes a water-solar complementary short-term scheduling method, system, device and medium.

[0075] In a first aspect, an embodiment of the present application provides a short-term scheduling method for water-solar complementary power, which is applied to the stator winding end of a steam turbine generator. Figure 1 It is a flow chart of short-term scheduling of water-solar complementary, such as Figure 1 As shown, a short-term scheduling method for water-solar complementarity includes:

[0076] Step S101: Generate a typical power generation line type according to the hydropower load changes in the historical hydropower daily operation data. The typical power generation line type is used to characterize the hydropower load distribution in different time periods. The typical power generation line type includes a base load area, a mid-load area and a peak load area.

[0077] Step S102: According to the grid load demand, photovoltaic power prediction accuracy and environmental conditions, the minimum outputs of the base load area, the mid-load area and the peak load area are respectively obtained.

[0078] Step S103: respectively obtain the hydropower station reservoir system constraints and the power system constraints.

[0079] Step S104: Based on the constraints of the hydropower station reservoir system and the power system, water-solar complementary scheduling is performed according to the minimum output of the base load area, mid-load area and peak load area.

[0080] In summary, the embodiment of the application provides a short-term scheduling method for hydro-photovoltaic complementarity. By generating a typical power generation line type according to the changes in the hydropower load in the historical hydropower daily operation data, the typical power generation line type is used to characterize the hydropower load distribution in different time periods. The typical power generation line type includes base load area, waist load area and peak load area. According to the load demand of the power grid, the accuracy of photovoltaic power prediction and environmental conditions, the minimum output of the base load area, waist load area and peak load area are obtained respectively. The reservoir system constraints of the hydropower station and the power system constraints are obtained respectively. Based on the reservoir system constraints of the hydropower station and the power system constraints, hydro-photovoltaic complementarity scheduling is performed according to the minimum output of the base load area, waist load area and peak load area. This application fully considers the actual basin scheduling, uses conventional hydropower historical operation data, identifies the typical output process of hydropower scheduling, and arranges the power and electricity distribution of the hydro-photovoltaic complementary system throughout the day with the typical process as a guide, so as to maximize the peak-shaving capacity of the complementary system and maximize the peak-shaving benefit. It has good operability and promotion value. It solves the problem of low peak-shaving benefit in the short-term scheduling of hydro-photovoltaic complementarity in the related technology.

[0081] Figure 2 is a flowchart of step S101 according to an exemplary embodiment. Figure 2 As shown, step S101, based on the hydropower load changes in the historical hydropower daily operation data, a typical power generation line type is generated, and the typical power generation line type is used to characterize the hydropower load distribution in different time periods. The typical power generation line type includes a base load area, a mid-load area, and a peak load area. Specifically, the following steps are included:

[0082] S1011. Determine the load increase segment, load decrease segment and load stability segment according to the hydropower load adjustment actions in the historical hydropower daily operation data, wherein the adjustment actions include increasing the load and reducing the load. Specifically, it includes:

[0083] S1012. Define load distribution intervals in different time periods based on the daily minimum load, daily average load and daily maximum load of hydropower. The load distribution intervals include base load area, mid-load area and peak load area.

[0084] S1013. Determine a typical power generation line type based on the load increase segment, the load decrease segment, the load stability segment and the load distribution interval, wherein the typical power generation line type includes a straight line type, a single peak type, a double peak type and a multi-peak type.

[0085] Optionally, first, the changes in hydropower load are extracted from the historical hydropower daily operation data. These data record the load adjustment of the hydropower station in different time periods and are the basis for subsequent analysis. By identifying the load adjustment actions (increasing load and reducing load), the hydropower load changes are divided into load increase segment, load decrease segment and load stability segment. This step is to understand the trend and pattern of load changes over time. Based on the minimum load, average load and maximum load of the hydropower day, it is divided into base load area, waist load area and peak load area. Based on the comprehensive analysis of the load change segment and the load distribution interval, the typical power generation line type is determined, such as linear type (little load change), single peak type (one peak period), double peak type (two peak periods in the morning and evening) and multi-peak type (multiple peak periods). Different types of power generation line types reflect different load demand patterns and the operating characteristics of hydropower stations, which are of great significance for formulating reasonable power generation plans.

[0086] The above step S1011 specifically includes:

[0087] Determine the threshold of the load increase rate and the threshold of the load reduction rate according to the load increase and load reduction actions in the historical hydropower daily operation data;

[0088] Based on a threshold value of a load increase rate and a threshold value of a load reduction rate, a load increase point and a load reduction point are determined according to a relative climbing rate;

[0089] Determine the load increase segment based on the load increase point, and determine the load reduction segment based on the load reduction point;

[0090] The load stabilization segment is determined based on the start time of the load increase segment to the end time of the load reduction segment.

[0091] Optionally, first, extract the specific values ​​of each load increase and load reduction and their corresponding time points from the historical data. Calculate the rate of each load change, that is, the amount of change in the load per unit time. According to the statistical results, determine a threshold value for the load increase rate and a threshold value for the load reduction rate. These thresholds can be determined based on statistics such as the mean, median, and standard deviation of the historical data to ensure that they can represent the typical load change rate. Use the relative ramp rate (i.e., the comparison between the actual load change rate and the threshold) to identify the load increase point and the load reduction point. When the load change rate is greater than or equal to the threshold of the increase rate, it is considered to be a load increase point; when the load change rate is less than or equal to the threshold of the reduction rate, it is considered to be a load reduction point. These points mark the key moments when the load changes from a stable state to an increasing or decreasing state. Based on the load increase point, the subsequent time period is divided into a load increase section until the next load reduction point is encountered or a preset end condition is reached. Based on the load reduction point, the subsequent time period is divided into a load reduction section until the load change tends to stabilize or reaches another load increase point. In the time period between the load increase section and the load reduction section, if the load change rate is within the threshold range, it is considered to be a load stable section.

[0092] Specifically, the load adjustment process is captured by the relative ramp rate. Let N i is the load in the i-th period, (i=1,2,…,96), kW; cap h Total installed capacity of the hydropower station, W; Δt is the time period, min; δ up ,δ down They are the thresholds of load increase and decrease rate respectively, and are determined based on the actual operation data of the hydropower station. i The definition is as follows:

[0093]

[0094] If R i ≥δ up , it is considered to be a load increase point, and continuous increase points constitute a load climbing section; if R i ≤δ down , is considered as the load reduction point, and the continuous load reduction points constitute the load reduction segment. The starting period of the load increase process is defined as t start , the end period of the load reduction process is defined as t end , from t start to end The period of time is divided into a complete stable power generation section.

[0095] The short-term complementary scheduling of hydropower and photovoltaic power generation usually takes 5 / 15 minutes as the time period and a day as the cycle. Taking the 96-point operation mode as an example, the 96 time periods are divided into n segments through the identified power generation process. Starting from time period i=1, the stable power generation segment is searched in sequence. The starting point t of the kth segment is start,k to end,k It constitutes the kth stable power generation period.

[0096] t start,k =min({iR i >δ up &i>t end,k-1})

[0097] t end,k =max({iR i <δ down &i>t start,k})

[0098] The time period between two stable power generation periods is also divided into segments, and the time period range is:

[0099] {t end,k +1, t start,k+1 -1}

[0100] Step S1011 quantifies the rate of load change by analyzing the load increase and load reduction actions in the historical hydropower daily operation data, and determines the key points of load change (i.e., load increase points and load reduction points) based on these rates, and then divides the load into the rising section, the falling section, and the stable section, providing a basis for the subsequent generation of typical power generation lines.

[0101] S1012 specifically includes: calculating the maximum load N of historical hydropower daily operation data max , minimum load N min and average load Divide the load distribution interval into base load area φ l , waist load area φ m , peak load areaφ h , the load range of each partition is as follows:

[0102]

[0103] Step S1013 specifically includes: according to the role of the hydropower station in the power grid, the typical power generation line type can be divided into straight line type, single peak type, double peak type and multi-peak type. The 96 points are completely divided into several segments, and the load mean of each segment is calculated.

[0104]

[0105] According to the mean Match the kth segment to the corresponding load partition, Figure 3 is a schematic diagram showing a typical power generation line type according to an exemplary embodiment, such as Figure 3 As shown, if all segments fall in the same load zone, the line type is straight; if there is only one segment in the peak load zone, the line type is unimodal; if there are two segments in the peak load zone, the line type is bimodal; if there are multiple segments in the peak load zone, the line type is multimodal. It is worth noting that only some common line types and zones are listed here. In practice, they can be drawn by connecting the different segments in the zones they fall in.

[0106] In order to maximize the peak-shaving capacity of the water-photovoltaic complementary system and achieve the maximum peak-shaving benefits, the photovoltaic consumption is given priority, and the planned daily hydropower generation is allocated step by step according to the order of peak load area, mid-load area, and base load area, forming a stable bundled output within the time period for external transmission. The following takes the linear type and the double peak type as examples to explain the load distribution method when the segment is in different partitions.

[0107] Linear type: During the flood season, in order to make full use of water resources, hydropower will generate electricity in the form of a large load throughout the day. When the water level is low during the dry season, it will also operate at the minimum output throughout the day. Regardless of the scenario, the linear power generation type will only fall into a single partition. It is only necessary to determine the daily power generation water consumption based on the daily forecast inflow of the reservoir, the initial water level status, and the planned final water level. According to the photovoltaic power prediction process, the total water and light output that remains constant throughout the day is used to calculate the power generation process that meets the daily water volume control demand.

[0108] Bi-peak type: In this type of power generation, the hydropower station usually has to undertake the power generation tasks during the morning and evening peaks. There are only these two sections in the peak load area; the remaining two sections are located in the mid-load area, the base load area, and the mid-load area and the base load area respectively. The multi-section load distribution needs to determine the minimum hydropower generation output of different partitions, and distribute it step by step according to the priority of different partitions.

[0109] Step S101 generates a typical power generation line type, based on the principle of not changing the role of the hydropower station in the power grid when it operates alone, using historical hydropower daily operation data, capturing the hydropower load adjustment action, and identifying the power generation process. Taking the 96-point operation mode as an example, the 96 time periods are divided into n segments through the identified power generation process, and the distribution intervals of different loads are defined, and the n segments are assigned to different load intervals, and then the load distribution priority is sorted. By generating a typical power generation line type, the changing trend of the hydropower load can be more accurately predicted and grasped, so as to formulate a more reasonable power generation plan and improve power generation efficiency. According to different types of power generation lines, the operation mode and scheduling strategy of the hydropower station can be reasonably arranged, the configuration and utilization of water resources can be optimized, and the overall economic benefits can be improved.

[0110] Figure 4 is a flowchart of step S102 according to an exemplary embodiment. Figure 4 As shown, step S102, according to the grid load demand, photovoltaic power prediction accuracy and environmental conditions, obtain the minimum output of the base load area, mid-load area and peak load area respectively. Specifically, it includes the following steps:

[0111] Step S1021, determine whether the power grid has actual load demand for the hydropower station, the actual load demand includes ecological flow and shipping load demand, and when there is actual load demand, determine the minimum output of the base load area as the minimum output that meets the actual load demand; when there is no actual load demand, determine the minimum output of the base load area as 0.

[0112] Optionally, the base load area is the area with the minimum output of the hydropower station and below, and the hydropower station operates or stops operating at the minimum output that meets the requirements of ecology, shipping, etc. The base load area is usually at night, when the photovoltaic output is 0, and there is no need to consider the complementary scheduling of water and light. If the power grid has ecological flow, shipping and other requirements for the hydropower station, the minimum output of the hydropower station that meets the conditions in this area is used as the minimum output constraint of the area. If there are no relevant requirements, the minimum output constraint is set to 0. By judging whether the power grid has actual load demand (such as ecological flow and shipping demand) for the hydropower station, the minimum output of the base load area of ​​the hydropower station is dynamically adjusted. It ensures that the hydropower station can flexibly adjust its operating status according to the actual needs of the power grid, so as to more effectively participate in the scheduling and balance of the power grid and improve the peak regulation efficiency.

[0113] Step S1022: Determine the minimum output of the mid-load area according to the photovoltaic power prediction accuracy rate 7 days before the prediction date and the weather prediction result of the prediction day. Specifically including:

[0114] When the average PV power prediction accuracy rate of the seven days before the prediction date is greater than the preset accuracy rate, the minimum output of the mid-load area is equal to the minimum hydropower output of the base load area plus the PV prediction output;

[0115] When the average value of the photovoltaic power prediction accuracy 7 days before the prediction day is less than the preset accuracy, the minimum output in the mid-load area is equal to the minimum output in the base load area plus the environmental coefficient multiplied by the photovoltaic installed capacity, where the environmental coefficient is determined based on the weather forecast result on the prediction day. When the weather forecast result is sunny, the environmental coefficient includes 0.7-0.9; when the weather forecast result is cloudy, the environmental coefficient includes 0.4-0.6; when the weather forecast result is rainy, the environmental coefficient includes 0.1-0.3.

[0116] Optionally, the mid-load area is usually located in the stage when the demand for electricity is not prominent during the day. The minimum output constraint in this period considers the complementary scheduling of water and photovoltaic. In order to maximize the proportion of photovoltaic consumption and deliver high-quality total output of water and photovoltaic, the forecast uncertainty of photovoltaic is fully considered, and the minimum output N of water and photovoltaic is determined in combination with the photovoltaic power forecast level in the previous 7 days. minWhen the average value of the PV power daily forecast accuracy for the current seven days is greater than 85%:

[0117] N min = Minimum hydropower output in base load area + predicted photovoltaic output

[0118] When less than 85%:

[0119] N min = minimum output in base load area + ε* photovoltaic installed capacity

[0120] Among them, when the weather forecast for the next day is sunny, cloudy and rainy, the environmental coefficient ε takes values ​​of 0.8, 0.5 and 0.3 respectively.

[0121]

[0122] Among them, P Mi , P Pi are the actual power and predicted power at time i respectively; Cap s is the rated capacity of the photovoltaic power station, and n=96 is the number of samples.

[0123] Step S1022 can evaluate the credibility of the photovoltaic power forecast by calculating the average value of the photovoltaic power forecast accuracy of the previous 7 days. When the forecast accuracy is high, it means that the forecast result is more reliable, and the forecast value can be relied on more to determine the minimum output of the waist-load area. The weather conditions on the forecast day have a direct impact on the photovoltaic output. The photovoltaic output is higher on sunny days and lower on cloudy and rainy days. Therefore, adjusting the environmental coefficient in the minimum output of the waist-load area according to the weather forecast results can more accurately reflect the actual situation of the photovoltaic output. The waist-load area is usually located in a stage where the electricity demand is not prominent during the day. At this time, considering the complementary scheduling of water and light can make full use of the complementarity of hydropower and photovoltaics and improve energy utilization efficiency. By reasonably determining the minimum output of the waist-load area, it can be ensured that when the photovoltaic output is insufficient, the hydropower station can replenish electricity in time to meet the needs of the power grid.

[0124] Step S1023: Determine the minimum output in the peak load area according to the average load of the historical hydropower daily operation data, wherein the minimum output in the peak load area is greater than the average load.

[0125] Optionally, the peak load area is the peak period of power consumption of the power grid, when the power grid has the greatest demand for power. As one of the important sources of power, hydropower stations need to provide sufficient power support at this stage. Therefore, the minimum output of the peak load area needs to be higher than the average load to ensure that the load demand of the power grid can be met during the peak period.

[0126] Step S1023: By ensuring that the minimum output in the peak load area is higher than the average load, the hydropower station can provide stable power support to the power grid during peak power consumption periods. This helps reduce power grid fluctuations and improve the stability and reliability of the power grid.

[0127] In one embodiment, step S103, respectively obtain the hydropower station reservoir system constraints and the power system constraints.

[0128] Specifically include:

[0129] Acquisition of hydropower station reservoir system includes:

[0130] The water balance constraint is determined based on the change in storage capacity of hydropower station i at the end of the tth period and the end of the t+1th period, the inflow and outflow in the tth period, and the time interval.

[0131] Optionally, the water balance constraint is obtained by the following formula:

[0132] V i,t+1 =V i,t +(I i,t -Q i,t )*Δt

[0133] Where: V i,t+1 ,V i,t are the storage capacities of hydropower station i at the end of time periods t+1 and t respectively; Q i,t I is the discharge flow of hydropower station i in period t; i,t is the inflow flow of hydropower station i in period t; Δt is the period interval.

[0134] The hydraulic connection constraints are determined based on the discharge flow and water lag of hydropower station i in the tth period and the interval inflow of hydropower station i+1 in the tth period to determine the hydraulic connection constraints between the hydropower stations.

[0135] Optionally, the hydraulic connection constraint is obtained by the following formula:

[0136] I i+1,t =Q i,t-τ +B i+1,t

[0137] Where: I i+1,t The inflow of hydropower station i+1 in period t; Q i,t-τ is the discharge flow of hydropower station i in the t-τ period; τ is the water flow stagnation time; B i+1,t The inflow of the hydropower station i+1 in the tth period.

[0138] Reservoir water level constraints are determined based on the reservoir water level of hydropower station i in period t and the upper and lower limits of the reservoir water level.

[0139] Optionally, the reservoir water level constraint is obtained by the following formula:

[0140]

[0141] Where: Z i,t is the reservoir water level of hydropower station i at period t; are the upper and lower limits of the reservoir water level of hydropower station i in period t respectively.

[0142] The downstream flow constraint is determined based on the downstream flow of hydropower station i in the tth period and the upper and lower limits of the downstream flow.

[0143] Optionally, the downstream flow constraint is obtained by the following formula:

[0144]

[0145] Where: are the upper and lower limits of the discharge flow of hydropower station i in period t respectively.

[0146] The power generation flow constraint is determined according to the power generation flow and the upper and lower limits of the power generation flow of hydropower station i in the tth period.

[0147] Optionally, the power generation flow constraint is obtained by the following formula:

[0148]

[0149] Where: is the power generation flow of hydropower station i in period t; are the upper and lower limits of the power generation flow of hydropower station i respectively.

[0150] The reservoir water level constraint at the end of the dispatching period is determined according to the reservoir water level at the end of the dispatching period of the given hydropower station i.

[0151] Optionally, the reservoir water level constraint at the end of the dispatch period is obtained by the following formula:

[0152]

[0153] Where: is the reservoir water level at the end of the dispatch period of a given hydropower station i.

[0154] Obtaining power system constraints includes:

[0155] Power station output constraints: Based on the upper and lower limits of the hydropower output and photovoltaic output of hydropower station i and photovoltaic station i in time period t, the power station output constraints are determined.

[0156] Optionally, the power station output constraint is obtained by the following formula:

[0157]

[0158] Where: They are the upper and lower limits of hydropower output of hydropower station i in period t respectively; They are the upper and lower limits of photovoltaic output in period t of photovoltaic power station i respectively.

[0159] Transportation channel constraints: Determine the transportation channel constraints based on the upper limit of the transportation channel of the water-photovoltaic complementary system.

[0160] Optionally, the transport channel constraint is obtained by the following formula:

[0161]

[0162] Where: N max It is the upper limit of the transmission channel of the water-photovoltaic complementary system.

[0163] Through the hydropower station reservoir system constraints and power system constraints in step S103, the power generation plan of the hydropower station can be reasonably arranged to improve power generation efficiency and economy.

[0164] Figure 5 is a flowchart of step S104 according to an exemplary embodiment. Figure 5 As shown, step S104, based on the constraints of the hydropower station reservoir system and the power system constraints, according to the minimum output of the base load area, the mid-load area and the peak load area, performs water-solar complementary scheduling. Specifically, it includes the following steps:

[0165] Step S1041: Under the various constraints of the hydropower station reservoir system and the power system in each time period, preliminary scheduling of the water-solar complementary load is carried out according to the minimum output requirements of the base load area, mid-load area and peak load area to meet the minimum output constraints of each time period.

[0166] Optionally, first ensure that the combined output of the hydropower station and the photovoltaic power station can meet the minimum output requirements of the base load area, mid-load area and peak load area in any period of time. This is the basis for ensuring the stable operation of the power grid. Through this step, the basic power supply capacity of the power grid under different load demands can be ensured to prevent power outages or voltage fluctuations caused by insufficient output.

[0167] Step S1042: determine the daily power generation and water consumption according to the daily forecast inflow of the reservoir, the initial water level and the planned final water level; based on the daily power generation and water consumption and the forecast result of photovoltaic power, adopt the form of constant total water and photovoltaic output within the section.

[0168] Optionally, the daily water consumption for power generation can be scientifically and reasonably determined based on the daily forecast inflow, initial water level and planned final water level of the reservoir. This is an important prerequisite for realizing the complementary scheduling of water and photovoltaic power generation. By accurately calculating the daily water consumption for power generation, the effective use of reservoir water resources can be ensured, while avoiding ecological problems caused by excessive water release or the impact of low reservoir water level on subsequent power generation.

[0169] Step S1043: Based on the constant total hydro-solar output within the segment, the hydro-solar output is synchronously increased in multiple stages in each area according to the priority order of the peak load area, the mid-load area, and the base load area, until the upper limit of the hydro-solar output is reached, so as to form a stable hydro-solar complementary output within the period and complete the hydro-solar complementary scheduling.

[0170] Optionally, based on the determined daily water consumption for power generation, combined with the prediction results of photovoltaic power, a constant total output of water and light within the segment is adopted. This output form is conducive to the dispatch and stability of the power grid. The constant output form within the segment simplifies the dispatch process, reduces the impact of output fluctuations on the power grid, and improves the stability and reliability of the power grid. The lifting strategy fully considers the load characteristics and peak-shaving needs of the power grid. When the power generation capacity is small, the needs of the peak load area are met first; when the power generation capacity is large, the needs of the waist load area and the base load area are gradually met. This flexible dispatching method can maximize the advantages of water and light complementarity, improve energy utilization efficiency, and meet the diversified needs of the power grid.

[0171] Step S104, the multi-segment priority allocation principle combines the load characteristics of the power grid and covers all different runoff scenarios and daily power generation capacities. When the daily power generation capacity of hydropower is small, the power generation process of the peak load area segment is raised; when the power generation capacity of hydropower is large, the peak load area segment is raised to the maximum output, and then the mid-load area and base load area segments are raised to the maximum output in turn, until the linear power generation process of the hydropower generation capacity is reached. This method does not solidify the segmentation form within the day, and can learn in real time based on the latest historical samples to form a typical power generation line that best suits the current power consumption situation to meet the peak regulation needs under different circumstances. It provides a strong guarantee for the safe, stable and efficient operation of the power grid.

[0172] Examples of practical applications:

[0173] This paper takes the cascade hydropower stations in the Beipanjiang River Basin in the southwest as the research object to discuss the implementation process of this application. Figure 6 is a schematic diagram showing the topological relationship and installed capacity of a power station according to an exemplary embodiment. Figure 6 As shown in Figure 2, due to the ecological flow requirement, the minimum discharge flow of hydropower station B is 31m 3 / s, the minimum discharge flow of hydropower station C is 50m 3 / s.

[0174] The actual operation process of historical hydropower is used to generate typical power generation lines. Figure 7 is a schematic diagram showing a typical power generation line type according to an exemplary embodiment, such as Figure 7As shown in the figure below, hydropower stations A and B are unimodal, and hydropower station C is bimodal. Among them, power stations B and C are restricted by ecological flow, and their minimum power generation outputs are 18 and 80MW respectively. According to the segmentation method proposed in this paper, the 96 time periods of the three power stations are divided into multiple processes and summarized into corresponding load partitions. The results are shown in Table 1.

[0175] Table 1: Load partition table

[0176]

[0177] Given the predicted runoff of cascade hydropower stations, predicted output of photovoltaic power stations, and sunrise and end-of-day control boundaries on the scheduling plan making date, intraday load allocation is carried out according to the multi-segment priority allocation principle proposed in this paper. Figure 8 is a schematic diagram showing the result of water-solar complementary scheduling according to an exemplary embodiment. The scheduling result is as follows Figure 8 shown.

[0178] The selected measurement date is in the dry season, the runoff is lower than the average level, and the available water cannot guarantee the operation at a large load throughout the day. In this case, the minimum output limit of each period should be met first. Secondly, the remaining estimated power generation on that day should be raised to the upper limit of water-solar output in multiple stages in the order of peak load area, mid-load area and base load area. Figure 8 It can be seen that the three groups of hydropower and photovoltaic complementary power stations have maintained the original peak-shaving role of hydropower while fully cooperating with photovoltaic power transmission. The total output of hydropower and photovoltaic power is stable, and the requirements of ecological flow are also met.

[0179] This allocation mode can be applied to different water inflow scenarios and different operating locations. With the increase of inflow or photovoltaic output, the hydro-photovoltaic complementary power station can increase the power generation output in the peak load area, mid-load area, and base load area in turn until the maximum power generation capacity of the hydro-photovoltaic complementary power station is reached throughout the entire period. This scheduling method is easy to operate, has clear principles, and has a comprehensive scope of application, which is conducive to the guidance and application of short-term hydro-photovoltaic complementary scheduling.

[0180] Principles of this application: Taking into full consideration the actual dispatching of the basin, using the historical operation samples of conventional hydropower, identifying the typical output process of hydropower dispatching, and taking the typical process as a guide, according to the multi-segment priority allocation principle proposed in this paper, arrange the distribution of power and electricity of the hydropower complementary system throughout the day, maximize the peak-shaving capacity of the complementary system, and maximize the peak-shaving benefits. The model starts from the existing hydropower dispatching situation in the basin and the demand for hydropower complementary dispatching. The goal setting is scientific and reasonable, with good operability and promotion value, smoothing the natural randomness, volatility and intermittency of optical power, and improving the overall power supply quality of hydropower.

[0181] In summary, the embodiment of the application provides a short-term scheduling method for hydro-photovoltaic complementarity. By generating a typical power generation line type according to the changes in the hydropower load in the historical hydropower daily operation data, the typical power generation line type is used to characterize the hydropower load distribution in different time periods. The typical power generation line type includes base load area, waist load area and peak load area. According to the load demand of the power grid, the accuracy of photovoltaic power prediction and environmental conditions, the minimum output of the base load area, waist load area and peak load area are obtained respectively. The reservoir system constraints of the hydropower station and the power system constraints are obtained respectively. Based on the reservoir system constraints of the hydropower station and the power system constraints, hydro-photovoltaic complementarity scheduling is performed according to the minimum output of the base load area, waist load area and peak load area. This application fully considers the actual basin scheduling, uses conventional hydropower historical operation data, identifies the typical output process of hydropower scheduling, and arranges the power and electricity distribution of the hydro-photovoltaic complementary system throughout the day with the typical process as a guide, so as to maximize the peak-shaving capacity of the complementary system and maximize the peak-shaving benefit. It has good operability and promotion value. It solves the problem of low peak-shaving benefit in the short-term scheduling of hydro-photovoltaic complementarity in the related technology.

[0182] In a second aspect, an embodiment of the present application provides a system for short-term scheduling of water-solar complementarity. Fig. 9 FIG. 1 is a block diagram of a system for short-term scheduling of water-solar complementary power according to an exemplary embodiment. Fig. 9 As shown, the system includes a typical power generation line module 910, a module for obtaining the minimum output of different load areas 920, a hydropower station reservoir system constraint and power system constraint module 930, and a water-solar complementary scheduling module 940, wherein:

[0183] Typical power generation line type module 910, used to generate a typical power generation line type according to the hydropower load change in the historical hydropower daily operation data. The typical power generation line type is used to characterize the hydropower load distribution in different time periods. The typical power generation line type includes a base load area, a mid-load area and a peak load area;

[0184] The module 920 for obtaining the minimum output of different load areas is used to obtain the minimum output of the base load area, the mid-load area and the peak load area according to the grid load demand, the photovoltaic power prediction accuracy and the environmental conditions;

[0185] A hydropower station reservoir system constraint and a power system constraint module 930, for obtaining a hydropower station reservoir system constraint and a power system constraint respectively;

[0186] The hydro-solar complementary scheduling module 940 is used to perform hydro-solar complementary scheduling based on the constraints of the hydropower station reservoir system and the power system, according to the minimum output of the base load area, the mid-load area and the peak load area.

[0187] In summary, the embodiment of the present application provides a water-photovoltaic complementary short-term scheduling system, which solves the problem of low peak-shaving efficiency in the short-term scheduling of water-photovoltaic complementary in the related art through a typical power generation line type module 910, a module 920 for obtaining the minimum output of different load areas, a hydropower station reservoir system constraint and a power system constraint module 930, and a water-photovoltaic complementary scheduling module 940. Specifically, a typical power generation line type is generated according to the changes in the hydropower load in the historical hydropower daily operation data. The typical power generation line type is used to characterize the distribution of hydropower loads in different time periods. The typical power generation line type includes a base load area, a waist load area, and a peak load area. According to the load demand of the power grid, the accuracy of photovoltaic power prediction, and environmental conditions, the minimum output of the base load area, the waist load area, and the peak load area are obtained respectively. The hydropower station reservoir system constraints and the power system constraints are obtained respectively. Based on the hydropower station reservoir system constraints and the power system constraints, water-photovoltaic complementary scheduling is performed according to the minimum output of the base load area, the waist load area, and the peak load area. This application fully considers the actual basin dispatching, uses the historical operation data of conventional hydropower, identifies the typical output process of hydropower dispatching, and arranges the power distribution of the hydropower complementary system throughout the day based on the typical process, maximizes the peak-shaving capacity of the complementary system, and maximizes the peak-shaving benefit. It has good operability and promotion value. It solves the problem of low peak-shaving benefit in the short-term dispatching of hydropower complementary in related technologies.

[0188] It should be noted that the water-photovoltaic complementary short-term scheduling system provided in this embodiment is used to implement the above-mentioned implementation mode, and the descriptions that have been made will not be repeated. As used above, the terms "module", "unit", "subunit", etc. can implement a combination of software and / or hardware for a predetermined function. Although the device described in the above embodiment is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0189] In a third aspect, an embodiment of the present application provides an electronic device, Fig.10 FIG. 1 is a block diagram of an electronic device according to an exemplary embodiment. Fig.10 As shown, the electronic device may include a processor 1001 and a memory 1002 storing computer program instructions.

[0190] Specifically, the processor 1001 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0191] Among them, the memory 1002 may include a large capacity memory for data or instructions. For example, but not limitation, the memory 1002 may include a hard disk drive (HDD), a floppy disk drive, a solid state drive (SSD), a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 1002 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 1002 may be inside or outside the data processing device. In a specific embodiment, the memory 1002 is a non-volatile memory. In a specific embodiment, the memory 1002 includes a read-only memory (ROM) and a random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (Programmable Read-Only Memory, PROM for short), an erasable PROM (ErasableProgrammable Read-Only Memory, EPROM for short), an electrically erasable PROM (Electrically ErasableProgrammable Read-Only Memory, EEPROM for short), an electrically alterable ROM (ElectricallyAlterable Read-Only Memory, EAROM for short) or a flash memory (FLASH) or a combination of two or more of these. Under appropriate circumstances, the RAM can be a static random access memory (SRAM) or a dynamic random access memory (DRAM), wherein the DRAM can be a fast page mode dynamic random access memory (FPMDRAM), an extended data output dynamic random access memory (EDODRAM), a synchronous dynamic random access memory (SDRAM), etc.

[0192] The memory 1002 may be used to store or cache various data files that need to be processed and / or used for communication, as well as possible computer program instructions executed by the processor 1001 .

[0193] The processor 1001 reads and executes computer program instructions stored in the memory 1002 to implement any one of the water-solar complementary short-term scheduling methods in the above embodiments.

[0194] In one embodiment, a device for short-term scheduling of water-solar complementary power may further include a communication interface 1003 and a bus 1000. Fig.10 As shown, the processor 1001, the memory 1002, and the communication interface 1003 are connected via a bus 1000 and communicate with each other.

[0195] The communication interface 1003 is used to implement communication between the modules, devices, units and / or equipment in the embodiment of the present application. The communication port 1003 can also implement data communication with other components such as: external devices, image / data acquisition equipment, databases, external storage, and image / data processing workstations.

[0196] The bus 1000 includes hardware, software or both, and couples the components of a water-photovoltaic complementary short-term scheduling device to each other. The bus 1000 includes but is not limited to at least one of the following: a data bus, an address bus, a control bus, an expansion bus, and a local bus. By way of example and not limitation, bus 1000 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses or a combination of two or more of these. Where appropriate, bus 1000 may include one or more buses. Although embodiments of the present application describe and illustrate a particular bus, the present application contemplates any suitable bus or interconnect.

[0197] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a program stored thereon. When the program is executed by a processor, a short-term scheduling method for water-solar complementarity provided in the first aspect is implemented.

[0198] The readable storage medium may include but is not limited to: a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device or any suitable combination of the above.

[0199] In a possible implementation, the present invention can also be implemented in the form of a program product, which includes program code. When the program product runs on a terminal device, the program code is used to enable the terminal device to execute the steps of a water-photovoltaic complementary short-term scheduling method provided in the first aspect.

[0200] Among them, the program code for executing the present invention can be written in any combination of one or more programming languages, and the program code can be executed completely on the user device, partially on the user device, as an independent software package, partially on the user device and partially on a remote device, or completely on the remote device.

[0201] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0202] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A short-term scheduling method for water-solar complementarity, characterized in that: The method comprises: Generate a typical power generation line type according to the hydropower load changes in the historical hydropower daily operation data, wherein the typical power generation line type is used to characterize the hydropower load distribution in different time periods, and the typical power generation line type includes a base load area, a mid-load area, and a peak load area; According to the grid load demand, the photovoltaic power prediction accuracy and the environmental conditions, the minimum output of the base load area, the mid-load area and the peak load area are respectively obtained; Obtain the hydropower station reservoir system constraints and power system constraints respectively; Based on the constraints of the hydropower station reservoir system and the power system constraints, water-solar complementary scheduling is performed according to the minimum output of the base load area, the mid-load area and the peak load area.

2. The method according to claim 1, characterized in that The generation of typical power generation lines based on the hydropower load changes in the historical hydropower daily operation data includes: Determine a load increase segment, a load decrease segment, and a load stability segment according to the hydropower load adjustment actions in the historical hydropower daily operation data, wherein the adjustment actions include increasing the load and reducing the load; According to the daily minimum load, daily average load and daily maximum load of hydropower, load distribution intervals in different time periods are defined, and the load distribution intervals include base load area, mid-load area and peak load area; Based on the load increase section, the load decrease section, the load stabilization section and the load distribution interval, a typical power generation line type is determined, wherein the typical power generation line type includes a straight line type, a single peak type, a double peak type and a multi-peak type.

3. The method according to claim 2, characterized in that According to the hydropower load adjustment actions in the historical hydropower daily operation data, the load increase section, load decrease section and load stability section are determined, including: Determine the threshold of the load increase rate and the threshold of the load reduction rate according to the load increase and load reduction actions in the historical hydropower daily operation data; Based on the threshold of the load increase rate and the threshold of the load reduction rate, a load increase point and a load reduction point are determined according to the relative climbing rate; Determine a load increase segment based on the load increase point, and determine a load reduction segment based on the load reduction point; A load stabilization segment is determined according to the starting time of the load increase segment to the ending time of the load reduction segment.

4. The method according to claim 1, characterized in that: The obtaining of the minimum output of the base load area, the mid-load area and the peak load area respectively according to the actual load demand of the power grid, the photovoltaic power prediction accuracy and the environmental conditions includes: Determine whether the power grid has actual load demand for the hydropower station, the actual load demand includes ecological flow and shipping load demand, and if there is actual load demand, determine the minimum output of the base load area as the minimum output that meets the actual load demand; if there is no actual load demand, determine the minimum output of the base load area as 0; Determine the minimum output of the mid-load area based on the photovoltaic power prediction accuracy 7 days before the prediction date and the weather prediction results of the prediction day; The minimum output in the peak load area is determined according to the average load of the historical hydropower daily operation data, wherein the minimum output in the peak load area is greater than the average load.

5. The method according to claim 4, characterized in that Based on the photovoltaic power prediction accuracy of 7 days before the prediction day and the weather prediction results of the prediction day, the minimum output of the mid-load area is determined, including: When the average value of the photovoltaic power prediction accuracy rate 7 days before the prediction date is greater than the preset accuracy rate, the minimum output of the mid-load area is equal to the minimum output of the hydropower in the base load area plus the photovoltaic prediction output; When the average value of the photovoltaic power prediction accuracy rate 7 days before the prediction day is less than the preset accuracy rate, the minimum output of the mid-load area is equal to the minimum output of the base load area plus the environmental coefficient multiplied by the photovoltaic installed capacity, wherein the environmental coefficient is determined according to the weather forecast result of the prediction day, when the weather forecast result is sunny, the environmental coefficient includes 0.7-0.9, when the weather forecast result is cloudy, the environmental coefficient includes 0.4-0.6, and when the weather forecast result is rainy, the environmental coefficient includes 0.1-0.

3.

6. The method according to claim 1, characterized in that The obtaining of the hydropower station reservoir system constraints and the power system constraints respectively includes: Acquisition of hydropower station reservoir system includes: Water balance constraint: Determine the water balance constraint based on the change in storage capacity of hydropower station i at the end of the tth period and the end of the t+1th period, the inflow and outflow of the tth period, and the interval between periods; Hydraulic connection constraints: Based on the discharge flow and water lag of hydropower station i at time period t and the interval inflow of hydropower station i+1 at time period t, the hydraulic connection constraints between hydropower stations are determined; Reservoir water level constraint, determined according to the reservoir water level of hydropower station i at time period t and the upper and lower limits of the reservoir water level; The discharge flow constraint is determined based on the discharge flow of the hydropower station i in the tth period and the upper and lower limits of the discharge flow; Power generation flow constraint, determining the power generation flow constraint according to the power generation flow of the hydropower station i in the tth period and the upper and lower limits of the power generation flow; The reservoir water level constraint at the end of the dispatch period is determined according to the given reservoir water level at the end of the dispatch period of hydropower station i; Obtaining power system constraints includes: Power station output constraints: Based on the upper and lower limits of the hydropower output and photovoltaic output of hydropower station i and photovoltaic station i in time period t, the power station output constraints are determined; Transportation channel constraints: Determine the transportation channel constraints based on the upper limit of the transportation channel of the water-photovoltaic complementary system.

7. The method according to claim 1, characterized in that The water-solar complementary scheduling is performed based on the constraints of the hydropower station reservoir system and the power system, according to the minimum output of the base load area, the mid-load area and the peak load area, including: Under the various constraints of the hydropower station reservoir system and the power system in each period, preliminary dispatch of water-solar complementary loads is carried out according to the minimum output requirements of the base load area, mid-load area and peak load area to meet the minimum output constraints of each period; According to the daily forecast inflow of the reservoir, the initial water level and the planned final water level, the daily power generation and water consumption is determined. Based on the daily power generation and water consumption and the prediction result of photovoltaic power, the constant total water and photovoltaic output within the section is adopted; Based on the constant total hydro-solar output within the section, the hydro-solar output is synchronously increased in multiple sections in each area according to the priority order of peak load area, mid-load area and base load area until the upper limit of the hydro-solar output is reached, forming a stable hydro-solar complementary output within the period and completing the hydro-solar complementary scheduling.

8. A water-solar complementary short-term scheduling system, characterized in that: The system includes a typical power generation line module, a module for obtaining the minimum output of different load areas, a hydropower station reservoir system constraint module and a power system constraint module, and a water-solar complementary scheduling module, wherein: The typical power generation line type module is used to generate a typical power generation line type according to the change of hydropower load in the historical hydropower daily operation data. The typical power generation line type is used to characterize the distribution of hydropower load in different time periods. The typical power generation line type includes a base load area, a mid-load area and a peak load area. The module for obtaining the minimum output of different load areas is used to obtain the minimum output of the base load area, the mid-load area and the peak load area respectively according to the grid load demand, the photovoltaic power prediction accuracy and the environmental conditions; The hydropower station reservoir system constraint and power system constraint modules are used to obtain the hydropower station reservoir system constraint and the power system constraint respectively; The water-solar complementary scheduling module is used to perform water-solar complementary scheduling based on the reservoir system constraints of the hydropower station and the power system constraints, according to the minimum output of the base load area, the mid-load area and the peak load area.

9. An electronic device, characterized in that: The invention comprises a memory and a processor, a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, a water-photovoltaic complementary short-term scheduling method as claimed in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, a short-term scheduling method for water-photovoltaic complementarity is implemented as described in any one of claims 1 to 7.

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