Cascade hydropower station load optimization distribution strategy automatic making and pushing method

Abstract

The invention discloses a cascade hydropower station load optimization distribution strategy automatic making and pushing method, and belongs to the technical field of water conservancy and hydropower engineering information automation. Comprising the following steps: S1, establishing a comprehensive database for model calling calculation; s2, establishing an intelligent simulation model, adjusting input and constraint conditions according to data of a database number, and selecting a proper optimization target according to different scene requirements; s3, the intelligent simulation model outputs a long-term scheduling scheme, a medium-term scheduling scheme and a short-term scheduling scheme; and S4, establishing a unit combination and output distribution model, outputting an optimized unit combination and output distribution strategy after inputting a unit state constraint condition, and issuing or adjusting a corresponding plan by a power grid mechanism side person. The technical problems that a traditional cascade hydropower station load distribution strategy cannot meet the requirement of a user for automatic making and implementation of a cascade hydropower station load optimization distribution strategy, and automatic pushing cannot be achieved are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of water conservancy and hydropower project information automation, and particularly to a method for automatically formulating and pushing a load optimal distribution strategy for cascade hydropower stations. Background Art

[0002] The existing load distribution technology for cascade hydropower stations is a technology for reasonably distributing power generation in multiple hydropower stations connected in series on the same river to meet the power grid load demand. It mainly focuses on how to overcome the complex hydraulic and electrical connections between cascade hydropower stations, and how to utilize the runoff regulation ability of the hydropower station group to formulate scientific and reasonable load distribution rules on the premise of ensuring the safety of hydropower stations. Traditional theories and methods face problems of huge data and complex calculations in practical engineering applications, and are insufficient in terms of generality and scalability. They cannot meet the user's requirements for the automatic formulation and implementation of the load optimal distribution strategy for cascade hydropower stations, nor can they achieve automatic pushing. Summary of the Invention

[0003] The object of the present invention is to provide a method for automatically formulating and pushing a load optimal distribution strategy for cascade hydropower stations to solve the technical problems that the traditional load distribution strategy for cascade hydropower stations cannot meet the user's requirements for the automatic formulation and implementation of the load optimal distribution strategy for cascade hydropower stations, nor can it achieve automatic pushing.

[0004] To achieve the above object, the technical solution adopted by the present invention is: a method for automatically formulating and pushing a load optimal distribution strategy for cascade hydropower stations, including the following steps:

[0005] Step S1: Establish a comprehensive database, periodically capture data of each meteorological station, hydrological center, power plant and power grid dispatching, for model call and calculation;

[0006] Step S2: Establish an intelligent simulation model and based on the data in the database, the operator selects the dispatching object and the calculation time span according to the actual situation, adjusts the input and constraint conditions, and selects appropriate optimization objectives according to different scenario requirements;

[0007] Step S3: The intelligent simulation model adjusts the subsequent output and discharge of each period in real time according to the input information to achieve the established goal, outputs long-term dispatching plans, medium-term dispatching plans and short-term dispatching plans, and supports manual intervention;

[0008] Step S4: Establish a unit combination and output distribution model, input the long-term dispatching plan, medium-term dispatching plan and short-term dispatching plan into the unit combination and output distribution model, and output the optimized unit combination and output distribution strategy after inputting the unit status constraint conditions; upload the generated optimized unit combination and output distribution strategy to the grid agency side in a predetermined format, and the personnel on the grid agency side issue or adjust the corresponding plan.

[0009] Further, in step S4, the solution steps of the unit commitment and output allocation model are as follows:

[0010] (1) Rolling prediction of power load: First, predict the load, the power load transmitted from the west to the east, and the load transmitted overseas to obtain the load values for each day in the future months;

[0011] (2) Determine the total daily allocated power of market-oriented power plants: Predict the daily power generation of priority power plants to obtain the monthly power generation of priority power plants, which is used as the monthly power demand of priority power plants;

[0012] (3) Generate an initial solution: The daily power plan of thermal power plants is determined according to policies; the daily power plans of wind power plants, photovoltaic power plants, and hydropower plants lacking data are determined by rolling average allocation of the difference between their monthly planned power and monthly actual power generation; the daily power of hydropower plants with detailed data is initially allocated in proportion to the monthly planned power;

[0013] (4) Water balance calculation: Re-calibrate the cascade calculation relationship for hydropower plants with detailed hydraulic data, and check and detect the daily initially allocated power. For power plants that fail the check, adjust their initially allocated power;

[0014] (5) Time-period power balance: After calibrating the water balance, the daily-scale power balance constraints in some time periods are violated. At this time, it is necessary to balance the power plants to adjust the power generation of different power plants in different time periods; if the load deviation is within the adjustment range of the balancing power plant, directly use the balancing power plant to adjust the deviation, and then jump to step (7); otherwise, jump to step (6);

[0015] (6) Calculate the objective function: Calculate the objective function value of power plant m in the t-th time period, and sort the objective functions from largest to smallest; if the load deviation ΔL^t > 0, indicating that the load demand is greater than the power generation, it is necessary to increase the power, then give priority to arranging the power generation of the power plants at the front (the power plan completion progress is the most unqualified); if the load deviation ΔL^t < 0, indicating that the load demand is less than the power generation, it is necessary to reduce the power, then give priority to arranging the power reduction of the power plants at the back (the power plan completion progress is the most over-standard);

[0016] (7) Re-perform water balance calculation: Go to step (4) to recalculate the water balance;

[0017] (8) Convergence condition: If the system load deviation ≤ ε, stop the calculation and go to step (9); if the load deviation ≥ ε, repeat steps (4) to (7), where ε = 0.001;

[0018] (9) Calculate the next time period.

[0019] Furthermore, the short-term scheduling scheme model can also be implemented by using the "determining electricity generation based on water volume" model of the small hydropower short-term scheduling model. The objective function of the model is:

[0020]

[0021] Where: E(T) —— the total power generation of the hydropower station within the scheduling period T (kw·h);

[0022] P i (t) —— the average output of the i-th hydropower plant at time t (kw);

[0023] ΔT h (t) —— the duration of each time period (h).

[0024] Furthermore, the constraint conditions of the "determining electricity generation based on water volume" model include the total water consumption constraint and the hydropower station characteristic constraint.

[0025] Furthermore, the total water consumption constraint function is:

[0026]

[0027] W0(T) is the total power generation water consumption of the hydropower station reservoir within the planned period.

[0028] Furthermore, the hydropower station characteristic constraint includes the head of the unit section, the expected output of the unit, the output of the unit, the unit water consumption flow characteristic constraint, and the total output limit of the hydropower station in a time period:

[0029] P min (t) ≤ P(t) ≤ P max (t)

[0030] P min (t), P max (t) are the minimum and maximum output limits of the hydropower station at time t.

[0031] Furthermore, in step S4, through the unified permission model and permission management process, the hierarchical management of user permissions for "dispatching center - middle dispatching center - cascade centralized control center / hydropower station" is realized, simplifying the user permission management work of the superior department personnel, making the handling of user and permission changes more timely, and then automatically or with one key pushing the above optimized unit combination and output distribution strategy to the power grid organization, so that the power grid organization can adopt and issue the daily and intraday power generation plans or adjustment plans in a timely and effective manner.

[0032] Furthermore, the unit status constraint conditions in step S4 include one or more of the system load constraint, the operation bandwidth of each cascade hydropower station group, the inflow process, the outflow limit, the output range, the water level range, the maintenance process, the start-up and shutdown, and the special dispatching instructions.

[0033] Due to the above technical solution, the present invention has the following beneficial effects:

[0034] 1. In terms of short-term and real-time scheduling, the present invention automatically formulates and pushes the cascade hydropower station load optimization allocation strategy, efficiently deduces the reservoir operation state, continuously proposes the optimized scheduling strategy, automatically formulates and pushes the load optimization allocation strategy, and reduces the time and intensity of inefficient operation of the reservoir and units; strengthens the joint regulation ability of upstream and downstream reservoirs, and can increase the optimized additional power generation capacity by about 1-2%; assists the water dispatcher in real-time scheduling control, greatly improves the work efficiency of the water dispatcher, and the work that originally took several hours for several personnel can now be completed by 1 person in about 10 minutes with high accuracy; realizes the process from scratch of timely pushing the cascade hydropower station load optimization allocation strategy. Solves the technical problems that the traditional cascade hydropower station load distribution strategy cannot meet the user's requirements for the automatic formulation and implementation of the cascade hydropower station load optimization allocation strategy, nor can it achieve automatic pushing. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 is the flow chart of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0036] The following further describes the specific implementation of the invention with reference to the drawings.

[0037] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "center", "length", "width", "upper", "lower", "vertical", "horizontal", "top", "bottom", "inner", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention.

[0038] In the present invention, unless otherwise clearly defined and limited, the terms "installed", "connected", "connected", "fixed", etc. should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or integrated; it can be directly connected, or indirectly connected through an intermediate medium, and can be the internal communication of two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0039] In the present invention, unless otherwise clearly specified and defined, the first feature being "above" or "below" the second feature may include the direct contact between the first and second features, or may include the contact between the first and second features through other features therebetween rather than direct contact. Moreover, the first feature being "above", "over" and "on top of" the second feature includes that the first feature is directly above and obliquely above the second feature, or merely indicates that the horizontal height of the first feature is higher than that of the second feature. The first feature being "below", "beneath" and "underneath" the second feature includes that the first feature is directly below and obliquely below the second feature, or merely indicates that the horizontal height of the first feature is less than that of the second feature.

[0040] As Figure 1 shown, a method for automatically formulating and pushing a load optimal distribution strategy for cascade hydropower stations includes the following steps:

[0041] Step S1: Establish a comprehensive database, periodically capture data of each meteorological station, hydrological center, power plant and power grid dispatching, for model call and calculation; create a cross-basin, multi-temporal and spatial digital scenario. This technology is for data integration, aiming to provide data support for subsequent forecast dispatching, load optimal distribution, etc.

[0042] Step S2: Establish an intelligent simulation model and based on the data in the database, the operator selects the dispatching object and the calculation time span according to the actual situation, adjusts the input and constraint conditions, and selects appropriate optimization objectives according to different scenario requirements;

[0043] Step S3: The intelligent simulation model adjusts the subsequent period power generation and discharge in real time according to the input information to achieve the established objectives, outputs long-term dispatching plans, medium-term dispatching plans and short-term dispatching plans, and supports manual intervention; adopts a physical + digital-driven similarity forecasting method, constructs a similarity intelligent rainfall-runoff forecasting model based on multi-factor similarity indexes, overcomes the problem of insufficient accuracy, solves the problems of low reliability and poor interpretability of the data model, and significantly improves the runoff forecasting accuracy under complex conditions. This technology provides an adjustment basis for subsequent intelligent dispatching, load optimal distribution, etc.

[0044] Step S4: Establish a unit commitment and output distribution model, input the long-term dispatching plan, medium-term dispatching plan and short-term dispatching plan into the unit commitment and output distribution model, and output the optimized unit commitment and output distribution strategy after inputting the unit status constraint conditions; upload the generated optimized unit commitment and output distribution strategy to the grid agency side in a predetermined format, and the personnel on the grid agency side issue or adjust the corresponding plan.

[0045] In this embodiment, in step S4, the solution steps of the unit commitment and output distribution model are as follows:

[0046] (1) Rolling prediction of power load: First, predict the load, the power load transmitted from the west to the east, and the load transmitted overseas to obtain the load values for each day in the future months.

[0047] (2) Determine the total daily allocated power of market-oriented power plants: Predict the daily power generation of priority power plants to obtain the monthly power generation of priority power plants, which is used as the monthly power demand of priority power plants. The method for determining the total daily allocated power of market-oriented power plants is as follows: The daily decomposed total power of market-oriented power plants = the monthly total power of market-oriented power plants × (the daily power demand of the entire network - the daily power generation of priority power plants) / (the monthly power demand of the entire network - the monthly power demand of priority power plants).

[0048] (3) Generate the initial solution: The daily power plan of thermal power plants is determined according to the policy; the daily power plans of wind power, photovoltaic power, and hydropower plants lacking data are determined by rolling average distribution based on the difference between their monthly planned power and monthly actual power generation; the daily power of hydropower plants with detailed data is initially allocated in proportion to the monthly planned power; and the daily initially allocated power = the monthly power of the power plant itself / the monthly total power of the power plant × the daily decomposed total power of market-oriented power plants.

[0049] (4) Water volume balance calculation: Re-correct the cascade calculation relationship for hydropower plants with detailed hydraulic data, and use the "electricity-determining water" algorithm to calculate the water volume balance between hydropower plants and check and detect the daily initially allocated power: including network constraints, equipment maintenance plans, water level control constraints, special flow requirements, etc. For power plants that fail the check, adjust their initially allocated power: The increased power is proportionally shared by other power plants according to the size of the initially allocated power to obtain the final daily power of all market-oriented power plants for each day (the increase of the power plant with increased power shall not exceed its remaining monthly power); the power plant with increased power needs to reduce the power allocation on the next day under the premise of meeting the constraints, and the power plant with reduced power needs to increase the power allocation on the next day under the premise of meeting the constraints, that is, in principle, try to ensure the equal progress of the planned power.

[0050] (5) Time-period power balance: After correcting the water volume balance, the daily-scale power balance constraints in some time periods are violated. At this time, it is necessary to balance the power plants to adjust the power generation of different power plants in different time periods; if the load deviation is within the adjustment range of the balancing power plant, directly use the balancing power plant to adjust the deviation, and then jump to step (7); otherwise, jump to step (6);

[0051] (6) Calculate the objective function: Calculate the objective function value of power plant m at time period t, and sort the objective functions from largest to smallest; if the load deviation ΔL^t > 0, indicating that the load demand is greater than the power generation and power needs to be increased, then give priority to arranging the power generation of the power plants at the front (the power plan completion progress is the most unqualified); if the load deviation ΔL^t < 0, indicating that the load demand is less than the power generation and power needs to be reduced, then give priority to arranging the power plants at the back (the power plan completion progress is the most over-standard) to reduce power;

[0052] (7) Re - perform the water balance calculation: Go to step (4) to recalculate the water balance;

[0053] (8) Convergence condition: If the system load deviation ≤ ε, stop the calculation and go to step (9); if the load deviation ≥ ε, repeat steps (4) to (7), where ε = 0.001;

[0054] (9) Calculate the next time period.

[0055] In addition, in this embodiment, according to different known conditions, the short - term hydropower plan of the hydropower station has two corresponding modes: "determining water by electricity" and "optimal dispatching". The short - term dispatching scheme model can also be implemented by using the "determining electricity by water" model of the small - hydropower short - term dispatching model. The objective function of the model is:

[0056]

[0057] Where: E(T)——The total power generation of the hydropower station within the dispatching period T (kw·h);

[0058] P i (t)——The average output of the i - th hydropower plant at time t (kw);

[0059] ΔT h (t)——The duration of each time period (h).

[0060] Furthermore, the constraint conditions of the "determining electricity by water" model include the total water consumption constraint and the hydropower station characteristic constraint.

[0061] The total water consumption constraint function is:

[0062]

[0063] W0(T) is the total power - generation water consumption of the hydropower station reservoir during the planned period.

[0064] The hydropower station characteristic constraint includes the head of the unit section, the pre - designed output of the unit, the output of the unit, the unit water - consumption flow characteristic constraint, and the total output limit of the hydropower station in each time period:

[0065] P min (t) ≤ P(t) ≤ P max (t)

[0066] P min (t), P max (t) are the minimum and maximum output limits of the hydropower station at time t.

[0067] As an important core module for the daily power generation dispatching operation of the power grid, the short-term power generation plan compilation will provide the daily 24-point power generation plan for the unified dispatching power station group with a step size of 1 hour. Based on runoff prediction and load prediction, considering the power grid peak regulation, sectional control of different regions, maintenance and other safety and stability control and power supply requirements, combined with the water inflow and water level control of the unified dispatching reservoir group of the power grid, various power generation dispatching instructions and plan arrangements that meet different types of power stations and different operation requirements are given in advance, and multiple optional optimal dispatching objectives are provided to achieve the efficient compilation of the short-term power generation dispatching plan. At the same time, visualization display and simulation interaction functions are provided. It is necessary to give full play to the regulating capacity of the reservoir and the peak regulation and frequency modulation functions of the hydropower units, optimize the utilization of water energy resources, and meet the needs of system safety, stability and power supply.

[0068] In the short-term hydropower plan compilation module, the dispatching objects and the calculation time span can be flexibly selected; the system has a short-term power generation conventional model for the cascade hydropower station group in the basin and an optimal dispatching model for short-term power generation of the hydropower stations in the basin. The boundary conditions consider the guiding role of the medium- and long-term dispatching results (such as: final water level, daily average water consumption, or daily average power generation control), solve the model, and seek a short-term optimal dispatching plan. Different optimal dispatching models can be flexibly selected according to actual needs and different dispatching tasks; the cross-basin cascade hydropower station group power generation dispatching for short-term dispatching will be provided. Based on the optimal dispatching of the cascade hydropower station group in the basin, according to the operation bandwidth of each hydropower station or the cascade hydropower station group, considering the water inflow of each basin and the load of the whole network, the cross-basin compensation regulation analysis and calculation within the regional power grid are carried out to minimize the water abandonment and give full play to the regulating performance of the hydropower stations. Users will be able to easily adjust the input and constraint conditions, including: system load constraint, operation bandwidth of each cascade hydropower station group, water inflow process, water discharge limit, output range, water level range, maintenance process, start-up and shutdown, special dispatching instructions, etc., and automatically set various constraint conditions under default conditions.

[0069] The real-time dispatching power generation plan adjustment model includes an automatic adjustment model and an artificial intervention model. Specifically:

[0070] Automatic adjustment model: The automatic adjustment target of the ultra-short-term power generation plan of the cascade hydropower station group is to minimize the maximum deviation between the calculated water level at the end of the dispatching period and the ideal water level. To avoid large differences in the objective function value caused by different water level magnitudes of different power stations, the maximum relative deviation between the calculated water level at the end of the dispatching period and the ideal water level is minimized.

[0071] Artificial Intervention Model: Based on the actual power grid load demand, the characteristics of the whole network's hydropower, the characteristics of cascade basins, the dispatching objectives of individual stations, etc., and combined with the experience of dispatching personnel, on the basis of the automatic adjustment of the aforementioned ultra-short-term generation dispatching plan, it is necessary to manually intervene in the generation plan, provide generation suggestions, provide a basis for the ultra-short-term dispatching decision-making of hydropower, and guide the hydropower dispatching and operation command. Classify power stations according to their characteristics (balancing power stations, non-balancing power stations), and put forward two dispatching instructions, namely, controlling the power generation amount and controlling the water level at the end of the day, in combination with the operation conditions of the power stations, to minimize the dispatching deviation. At the same time, it can deeply integrate the rich dispatching experience of dispatchers to achieve reliable, economical and rapid adjustment of the ultra-short-term generation plan and guide the operation of hydropower.

[0072] Real-time generation dispatching can monitor the incoming water, outgoing water and the execution of daily plans of unified dispatching power stations in real time and in a rolling manner. According to the short-term and real-time forecast of the change in incoming water, predict the operation trend of the reservoir, judge the water level over-limit situation, calculate the possible water abandonment situation, automatically give early warnings for possible abnormalities in advance, output various dispatching process values and characteristic statistical values related to the dispatching results in the form of rich charts, and give real-time prompts to dispatchers.

[0073] Considering special dispatching requirements such as the output control, water level control, outgoing flow control, and section control of important power stations, an automatic adjustment strategy for the generation plan and an artificial intervention dispatching strategy are provided. By adjusting the dispatching plans of a small number of power stations, the ultra-short-term dispatching requirements can be met.

[0074] For some power stations, especially the leading power stations and those far from the upstream, their incoming flow is less affected by the outgoing flow of the upstream, and the incoming flow can be regarded as the sectional flow. The prediction of the sectional flow is actually the prediction of the incoming flow. Generally speaking, the incoming flow of the leading power station will not change suddenly within a short period of time (2 - 5 hours), and the incoming flow process is very smooth. The incoming flow in the subsequent periods can be predicted by using statistical methods based on the actual incoming water situation before the current moment.

[0075] Determine the real-time power generation scheduling plan adjustment model: The automatic adjustment goal of the ultra-short-term power generation plan for cascade hydropower stations is to minimize the maximum deviation between the calculated water level at the end of the scheduling period and the ideal water level. To avoid large differences in the objective function value caused by different water level magnitudes of different power stations, the minimum value of the maximum relative deviation between the calculated water level at the end of the scheduling period and the ideal water level is adopted; according to the actual power grid load demand, the characteristics of the whole network's hydropower, the characteristics of the cascade basin, the scheduling objectives of individual stations, etc., combined with the experience of dispatchers, on the basis of the above-mentioned automatic adjustment of the ultra-short-term power generation scheduling plan, it is necessary to manually intervene in the power generation plan, provide power generation suggestions, provide a basis for the ultra-short-term scheduling decision-making of hydropower, and guide the hydropower scheduling and command operation. Classify power stations according to their characteristics (balanced power stations, unbalanced power stations), and put forward two scheduling instructions of controlled power and controlled water level at the end of the day in combination with the operation of the power stations to minimize the scheduling deviation. At the same time, the rich scheduling experience of dispatchers can be deeply integrated to realize the reliable, economical and rapid adjustment of the ultra-short-term power generation plan and guide the hydropower operation.

[0076] In this embodiment, in step S4, through the unified authority model and authority management process, the hierarchical management of user authorities for "dispatcher - middle dispatcher - cascade centralized control center / hydropower station" is realized, which simplifies the user authority management work of personnel in superior departments, enables the processing of user and authority changes to be more timely, and then automatically or with one key pushes the above-mentioned optimized unit combination and output distribution strategy to the power grid organization, so that the power grid organization can adopt and issue the daily and intraday power generation plans or adjustment plans in a timely and effective manner.

[0077] The above description is a detailed description of a preferred and feasible embodiment of the present invention, but the embodiment is not intended to limit the scope of the patent application of the present invention. Any equivalent changes or modified changes completed under the technical spirit disclosed by the present invention shall fall within the scope of the patent covered by the present invention.

Claims

1. An automatic formulation and push method for the load optimal distribution strategy of cascade hydropower stations, characterized in that: It includes the following steps: Step S1: Establish a comprehensive database, and periodically capture the data of each meteorological station, hydrological center, power plant, and power grid dispatching for model call and calculation; Step S2: Establish an intelligent simulation model and based on the data in the database, the operator selects the dispatching object and the calculation time span according to the actual situation, adjusts the input and constraint conditions, and selects appropriate optimization objectives according to different scenario requirements; Step S3: The intelligent simulation model adjusts the output and discharge of each subsequent period in real time according to the input information to achieve the established goal, outputs long-term dispatching plans, medium-term dispatching plans, and short-term dispatching plans, and supports manual intervention; Step S4: Establish a unit commitment and output allocation model, input the long-term dispatching plan, medium-term dispatching plan, and short-term dispatching plan into the unit commitment and output allocation model, and output the optimized unit commitment and output allocation strategy after inputting the unit status constraint conditions; upload the generated optimized unit commitment and output allocation strategy to the grid agency side in the established format, and the personnel on the grid agency side issue or adjust the corresponding plan.

2. The automatic formulation and push method for the load optimal distribution strategy of a cascade hydropower station according to claim 1, wherein: In Step S4, the solution steps of the unit commitment and output allocation model are as follows: (1) Rolling prediction of power load: First, predict the load, the power load transmitted from the west to the east, and the load transmitted overseas to obtain the load values of each day in the future month; (2) Determine the total daily allocated power of market-oriented power plants: Predict the daily power generation of priority power plants to obtain the monthly power generation of priority power plants, which is used as the monthly power demand of priority power plants; (3) Generate an initial solution: The daily power plan of thermal power plants is determined according to policies; the daily power plans of wind power, photovoltaic, and hydropower plants lacking data are determined by rolling average distribution of the difference between their monthly planned power and monthly actual power generation; the daily power of hydropower plants with detailed data is initially allocated in proportion to the monthly planned power; (4) Water balance calculation: Re-calibrate the cascade calculation relationship of hydropower plants with detailed hydraulic data, check and detect the initially allocated daily power, and adjust the initially allocated power of power plants that fail the check; (5) Periodic power balance: After correcting the water balance, the daily-scale power balance constraints in some periods are violated. At this time, it is necessary to balance the power plants to adjust the power generation of different power plants in different periods; if the load deviation is within the adjustment range of the balancing power plant, directly use the balancing power plant to adjust the deviation, and then jump to step (7); otherwise, jump to step (6); (6) Calculate the objective function: Calculate the objective function value of power plant m in the t-th period, and sort the objective functions from largest to smallest; if the load deviation ΔL^t>0, it means that the load demand is greater than the power generation, and the power needs to be increased, then give priority to arranging the power generation of the power plants at the front (the power plan completion progress is the least up to standard); if the load deviation ΔL^t<0, it means that the load demand is less than the power generation, and the power needs to be reduced, then give priority to arranging the power plants at the back (the power plan completion progress is the most over-standard) to reduce the power; (7) Re-calculate the water balance: Go back to step (4) to re-calculate the water balance; (8) Convergence condition: If the system load deviation ≤ ε, stop the calculation and go to step (9); if the load deviation ≥ ε, repeat steps (4) to (7), where ε = 0.001; (9) Calculate the next time period.

3. The automatic formulation and pushing method for the load optimal distribution strategy of a cascade hydropower station according to claim 1, characterized in that: The short-term scheduling scheme model can also be implemented by the "electricity determined by water" model of the small hydropower short-term scheduling model. The objective function of the model is: Where: E(T) —— The total power generation of the hydropower station within the scheduling period T (kw·h); P i (t) —— The average output (kW) of the i-th hydropower plant at time t; ΔT h (t) - The duration (h) of each time period.

4. A method for automatically formulating and pushing a load optimal distribution strategy for a cascade hydropower station according to claim 3, characterized in that: The constraint conditions of the "electricity determined by water" model include the total water consumption constraint and the hydropower station characteristic constraint.

5. The automatic formulation and push method for the load optimal distribution strategy of a cascade hydropower station according to claim 4, characterized in that: The total water consumption constraint function is: W0(T) is the total power generation water consumption of the hydropower station reservoir within the planning period.

6. A method for automatically formulating and pushing a load optimal distribution strategy for a cascade hydropower station according to claim 4, characterized in that: The hydropower station characteristic constraint includes the head of the unit section, the pre-outlet power of the unit, the output of the unit, the unit flow consumption characteristic constraint, and the total output limit of the hydropower station in a time period: P min P(t) ≤ P(t) ≤ P max (t) P min (t), P max (t) is the minimum and maximum output limits of the hydropower station during the t period.

7. A method for automatically formulating and pushing a load optimization distribution strategy for a cascade hydropower station according to claim 1, characterized in that: In step S4, through the unified authority model and the authority management process, the hierarchical management of user authorities for "dispatching center - middle dispatching center - cascade centralized control center / hydropower station" is realized, simplifying the user authority management work of the personnel in the superior department, making the handling of user and authority changes more timely, and then automatically or with one key pushing the above optimized unit combination and output distribution strategy to the power grid organization, so that the power grid organization can adopt and issue the daily and intraday power generation plans or adjustment plans in a timely and effective manner.

8. The automatic formulation and push method for the load optimal distribution strategy of a cascade hydropower station according to claim 1, wherein: The unit state constraint conditions in step S4 include one or more of the system load constraint, the operation bandwidth of each cascade hydropower station group, the inflow process, the outflow limit, the output range, the water level range, the maintenance process, the start-up and shutdown, and the special dispatching instruction.

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