Method for coordinated dispatching of market transaction decision of water-wind-sight complementary power generation system

Abstract

The application discloses a kind of water wind light complementary power generation system market transaction decision coordination scheduling operation method, it includes the following steps: S1, complementary system long-term power generation capacity evaluation and long-term market transaction;S2, day-ahead market bidding and power generation scheduling plan optimization;S3, intraday market and real-time scheduling operation;The application considers the synergistic effect between different energies and complementary characteristics, from the risk preference angle, analyzes the behavior mode of water wind light power generation enterprise electric energy transaction market, and excavates the dispatching demand closely related to its electric energy transaction, constructs the corresponding dispatching model, can effectively guide water wind light complementary power generation enterprise optimization market decision and improve water wind light resource utilization efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of water conservancy engineering, and particularly relates to a coordinated dispatching operation method for market transaction decision of a water-wind-solar complementary power generation system. BACKGROUND

[0002] Under the background of energy supply and demand contradiction, power grid peak regulation and frequency modulation difficulty, and power market demand problems such as promoting new energy consumption, the coordinated operation of water, wind, light and other energy, the use of their respective advantages and complementary potential to realize energy efficient utilization gradually becomes the main idea to solve the problem of new energy consumption. Most of the existing researches are about water power participating in the electricity market and wind light consumption, focusing on the processing of water wind light resource input uncertainty and model constraints. But with the gradual deepening of the current power market reform, the dispatching of new energy coordinated power generation system plays an increasingly important role in optimizing market decision and efficient resource allocation.

[0003] The existing technology for the research on the participation of the water-wind-solar power generation system in the electricity market transaction and the optimization of dispatching often focuses on a single electricity transaction mode, and fails to fully integrate the joint dispatching strategy of the wind and solar power generation system. The limitation of this research perspective leads to the lack of overall and continuity of the market transaction strategy. If a method that comprehensively considers the electricity transaction and dispatching demand of the water-wind-solar complementary power generation system can be proposed, the method will have more practical guiding significance and theoretical value. SUMMARY

[0004] The present application aims to overcome the above-mentioned deficiencies, and provides a coordinated dispatching operation method for market transaction decision of a water-wind-solar complementary power generation system, so as to solve the problems proposed in the background art.

[0005] To solve the above technical problems, the technical solution adopted by the present application is as follows: a coordinated dispatching operation method for market transaction decision of a water-wind-solar complementary power generation system, which comprises the following steps:

[0006] S1, long-term power generation capacity evaluation and long-term market transaction in the complementary system;

[0007] S2, day-ahead market bidding and power generation dispatching plan optimization;

[0008] S3, intra-day market and real-time dispatching operation.

[0009] Preferably, the step S1 specifically comprises the following steps:

[0010] S1-1, water, wind and light resource data processing: collect historical runoff, wind and light output data, and study the complementarity among water, wind and photovoltaic, analyze their power generation capacity changes under different seasons and weather conditions, remove abnormal data from historical output data, and process the removed water, wind and photovoltaic data into output data in units of months;

[0011] S1-2, medium and long-term power generation capacity evaluation: the water, wind and light complementary system power generation enterprise predicts and evaluates the annual power generation capacity of the water, wind and light complementary system according to the water inflow of the historical hydrology similar year, wind power and photovoltaic power generation history experience;

[0012] S1-3, long-term market contract power trading: according to the prediction result of S1-2, the annual power generation capacity is evaluated, in order to ensure that the market risk is controllable, the power generation enterprise signs a medium and long-term power contract through centralized bidding, including annual, quarterly and monthly contract power, realizing the step-by-step rolling transaction of most of the power;

[0013] S1-4, long-term market contract power decomposition: according to the medium and long-term power contract signed in S1-3, the long-term contract power is decomposed in the manner agreed in the contract, realizing the apportionment of the monthly completed power of the medium and long-term contract.

[0014] Preferably, the step S2 specifically comprises the following steps:

[0015] S2-1, facing day power generation capacity evaluation: according to the runoff, wind speed and light condition, a water, wind and light complementary short-term optimization scheduling model is constructed according to the reservoir scheduling regulation requirement, the facing day power generation capacity of the complementary system is predicted and evaluated through simulation scheduling;

[0016] S2-2, determination of daily load curve: the daily completed power is obtained by apportioning the monthly power generation capacity plan obtained in S1-4 according to a certain rule or agreed manner, and the daily load curve is determined according to the facing day load demand and the contract agreement manner;

[0017] S2-3, day-ahead bidding and dispatching operation: according to the daily load curve of S2-2, the predicted daily scale wind and light power generation capacity and the day-ahead electricity price are evaluated; if the power is low or the price is low, do not participate in the day-ahead bidding, directly enter the "electricity determines water" day-ahead scheduling, and establish a minimum energy consumption scheduling model; if the power is high and the price is high, participate in the day-ahead market bidding under the premise of meeting the guaranteed output, take the maximum day-ahead market benefit as the target, and construct an optimization scheduling model coupled with contract decomposition and day-ahead market bidding.

[0018] Preferably, in the step S2-1, the water, wind and light complementary short-term optimization scheduling model constructed is:

[0019] ;

[0020] wherein, is the total number of cascade hydropower stations; is the total number of time periods in the dispatch period; is the time period granularity; is the hydropower station number; is the time period total output of the hydropower station No. is the wind power output in the time period t; is the photovoltaic output in the time period t.

[0021] Preferably, in the step S2-3, the specific steps of constructing the optimization dispatching model coupling contract decomposition and day-ahead market bidding are as follows:

[0022] ;

[0023] wherein, is the total number of cascade hydropower stations; is the total number of time periods in the dispatch period; is the time period granularity; is the hydropower station number; is the time period contract electricity price of the hydropower station No., which is related to the signing mode of the long-term contract and determined by bilateral negotiation or centralized bidding; is the time period day-ahead market clearing forecast electricity price; is the time period contract electricity quantity of the hydropower station No. allocated to the hourly output, and the allocation mode of the contract electricity quantity needs to be specified in the signed long-term contract; is the time period total output of the hydropower station No. is the wind power output in the time period t; is the photovoltaic output in the time period t.

[0024] (2) Constraint conditions;

[0025] 1) Output-flow-head relationship:

[0026] ;

[0027] wherein: is k the comprehensive efficiency of the hydropower station; is t the time period k generation flow of the hydropower station, m 3 / s; is t the time period the kThe generating head of a hydroelectric power station, in meters;

[0028] 2) Contract power output constraints:

[0029] ;

[0030] 3) Water balance constraints:

[0031] ;

[0032] In the formula: for t Time period k The reservoir capacity of the hydropower station is 10. 6 m 3 ; for t Time period k The inflow of the hydropower station is m 3 / s; for t Time period k The discharge flow of each hydropower station; for t Time period k The hydropower station discharged water, m 3 / s;

[0033] 4) Downflow constraint:

[0034] ;

[0035] In the formula: , These are the minimum discharge flow rate and the maximum discharge flow rate, respectively.

[0036] 5) Power generation flow constraints:

[0037] ;

[0038] In the formula: , These represent the minimum and maximum power generation flows, respectively, m 3 / s;

[0039] 6) Reservoir capacity constraints:

[0040] ;

[0041] In the formula: , The first k Minimum and maximum restricted reservoir capacity for each hydropower station, 10 6 m 3 ;

[0042] 7) Initial and final control water level constraints:

[0043] ;

[0044] In the formula: , Reservoirs k At the beginning and end of the scheduling period, the water level is controlled in m;

[0045] 8) Reservoir capacity-water level relationship:

[0046] ;

[0047] In the formula: for t End of period k The reservoir water level of the hydropower station, in meters; For reservoir k The reservoir capacity-water level relationship function;

[0048] 9) Relationship between discharge flow rate and tailrace level:

[0049] ;

[0050] In the formula: for t Time period k The tailrace level of a hydroelectric power station, in meters; Reservoirs k The relationship function between reservoir capacity and water level, and between outflow and tailwater level;

[0051] 10) Output constraints:

[0052] ;

[0053] In the formula: , The first k Minimum and maximum output of a hydropower station, in MW;

[0054] 11) Vibration zone constraints of hydropower stations:

[0055] ;

[0056] In the formula: , The first k The first hydropower station i The upper and lower limits of each vibration zone;

[0057] 12) Equation constraints for power generation head:

[0058] ;

[0059] In the formula: is t the head loss of the m. k th

[0060] More preferably, in the step S2-3, the specific steps of establishing the minimum energy consumption scheduling model are as follows:

[0061] ;

[0062] The constraint conditions are:

[0063] ;

[0064] The constraint conditions further include the constraint conditions of 1) to 12), except for the tail water level control constraint in 2) and 7).

[0065] Preferably, the step S3 specifically includes the following steps:

[0066] S3-1, facing period power generation capacity evaluation: according to the daily runoff, wind speed, illumination, and the transaction results of the scheduling plan executed by S2 as the boundary, the daily real-time optimization distribution of the water-wind-solar complementary power generation system is predicted and evaluated to evaluate the complementary system facing period power generation capacity;

[0067] S3-2, real-time market participation evaluation: according to the optimization distribution results of S3-1 and the scheduling plan before the day, the power surplus of the water-wind-solar complementary system is evaluated to determine whether it has the condition to participate in the real-time market; if there is power surplus and the market price is at a high level, the system will start the continuous bidding process to participate in the daily market transaction at the optimal price; at the same time, the rolling adjustment of the scheduling plan is carried out to respond to the changes of the real-time market and ensure the maximization of the value of the complementary system power.

[0068] The present application has the beneficial effects: the present application considers the synergistic effect and complementary characteristics between different energies, analyzes the power transaction market behavior mode of the water-wind-solar power generation enterprise from the risk preference angle, and excavates the scheduling demand closely related to the power transaction, constructs the corresponding scheduling model, and can effectively guide the water-wind-solar complementary power generation enterprise to optimize the market decision and improve the water-wind-solar resource utilization efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0069] Figure 1 is an implementation flowchart of a coordinated scheduling operation method of a water-wind-solar complementary power generation system market transaction decision;

[0070] Figure 2 is a complementary power generation system medium and long term power generation capacity evaluation and market transaction strategy implementation flowchart;

[0071] Figure 3The flowchart for the implementation of market bidding and power generation dispatch plan optimization is as follows;

[0072] Figure 4 Flowchart of intraday market and real-time dispatch operation;

[0073] Figure 5 Flowchart for short-term scheduling of hydro-wind-solar hybrid power systems;

[0074] Figure 6 A diagram showing the relationship between risk and contracted electricity volume;

[0075] Figure 7 This is a schematic diagram of the algorithm results. Detailed Implementation

[0076] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0077] Example 1: As Figure 1 As shown, a coordinated scheduling operation method for market transaction decision-making of a hydro-wind-solar hybrid power generation system includes the following steps:

[0078] S1. Assessment of medium- and long-term power generation capacity and forward market transactions in complementary systems:

[0079] S1-1, Data processing of hydropower, wind power and solar power output: Using the Laida criterion, abnormal data is removed from the raw real-time power output data of hydropower, wind power and solar power fields, and the removed hydropower, wind power and solar power data are processed into power output data on a monthly basis.

[0080] S1-2, Medium and Long-Term Power Generation Capacity Assessment: Based on the water inflow conditions of similar historical hydrological years and historical experience of wind and solar power generation, power generation companies of hydro-wind-solar hybrid systems predict and assess the annual power generation capacity of the hydro-wind-solar hybrid system.

[0081] S1-3, Forward Market Contract Electricity Trading: Based on the forecast results of S1-2, the annual power generation capacity is assessed. To ensure that market risks are controllable, power generation companies sign medium- and long-term electricity contracts through centralized bidding, including annual, quarterly, and monthly contract electricity volumes, to achieve tiered rolling trading of most electricity volumes.

[0082] S1-4. Decomposition of forward market contract volume: Based on the medium- and long-term volume contracts (annual, quarterly, and monthly) signed in S1-3, the forward contract volume is decomposed in accordance with the contractual agreement to achieve the allocation of medium- and long-term contract volume to the monthly completed volume.

[0083] S2. Optimization of day-ahead market bidding and power generation dispatch plan:

[0084] S2-1, facing the day generation capacity evaluation: according to the runoff, wind speed, light condition, according to the reservoir operation regulation requirement, the water wind light complementary short-term optimization scheduling model (scheduling model technical process as shown in Figure 5 ) is constructed, the facing day generation capacity of the complementary system is predicted and evaluated through the simulation scheduling mode;

[0085] The constructed water wind light complementary short-term optimization scheduling model is:

[0086] ;

[0087] In the formula, The total number of cascade hydropower stations is; The total time period number of scheduling period is; The time period granularity is; The water power station number is; The total output of time period The number of hydropower station is; The time period The wind power output of time period t is; The photovoltaic output of time period t is.

[0088] S2-2, day load curve determination: according to the monthly power generation plan obtained in S1-4, the daily completed power is obtained by apportioning according to certain rules or agreed mode, and the day load curve is determined according to the facing day load demand and contract agreement mode;

[0089] S2-3, day-ahead bidding and dispatching operation: according to the day load curve of S2-2, the predicted day-scale wind light generation capacity and day-ahead electricity price are evaluated. If the power is high and the price is high, under the premise of meeting the guaranteed output, the day-ahead market bidding is participated, the optimization scheduling model coupled with contract decomposition and day-ahead market bidding is constructed, and the day-ahead market benefit maximization is taken as the target; if the power is low or the price is low, the day-ahead bidding is not participated, and the minimum energy consumption scheduling model is established directly.

[0090] If the power is high and the price is high, under the premise of meeting the guaranteed output, the day-ahead market bidding is participated, the optimization scheduling model coupled with contract decomposition and day-ahead market bidding is constructed, and the day-ahead market benefit maximization is taken as the target.

[0091] The specific steps of constructing the optimization scheduling model coupled with contract decomposition and day-ahead market bidding are as follows:

[0092] ;

[0093] In the formula, The total number of cascade hydropower stations is; The total time period number of scheduling period is; The time period granularity is; The water power station number is; For Period The contract price of the No. t power station is related to the way of signing the forward contract, which is determined by bilateral negotiation or centralized bidding, etc. For Period For Period The contract power of the No. t power station is allocated to the hourly output, and the allocation method of the contract power needs to be explained in the signed forward contract. For Period The total output of the No. t power station, The wind power output of the t period; The photovoltaic output of the t period;

[0094] (2) Constraints;

[0095] 1) Output-flow-head relationship:

[0096] ;

[0097] In the formula: For k The comprehensive efficiency of the hydropower station; For t Period k The generating flow of the hydropower station, m 3 / s; For t Period k The generating head of the No. t hydropower station, m;

[0098] 2) Contract power decomposition output constraint:

[0099] ;

[0100] 3) Water balance constraint:

[0101] ;

[0102] In the formula: For t Period k The reservoir capacity of the No. t hydropower station, 10 6 m 3 ; For t Period k The inflow of the No. t hydropower station, m 3 / s; For t Period k The discharge of the No. t hydropower station; Fort Time period k The hydropower station discharged water, m 3 / s;

[0103] 4) Downflow constraint:

[0104] ;

[0105] In the formula: , These are the minimum discharge flow rate and the maximum discharge flow rate, respectively.

[0106] 5) Power generation flow constraints:

[0107] ;

[0108] In the formula: , These represent the minimum and maximum power generation flows, respectively, m 3 / s;

[0109] 6) Reservoir capacity constraints:

[0110] ;

[0111] In the formula: , The first k Minimum and maximum restricted reservoir capacity for each hydropower station, 10 6 m 3 ;

[0112] 7) Initial and final control water level constraints:

[0113] ;

[0114] In the formula: , Reservoirs k At the beginning and end of the scheduling period, the water level is controlled in m;

[0115] 8) Reservoir capacity-water level relationship:

[0116] ;

[0117] In the formula: for t End of period k The reservoir water level of the hydropower station, in meters; For reservoir k The reservoir capacity-water level relationship function;

[0118] 9) Relationship between discharge flow and tailrace level:

[0119] ;

[0120] wherein: t is the tail water level of the i-th hydropower station, m; k are the reservoir storage-water level and discharge-tail water level functions of the reservoir, respectively; k are the reservoir storage-water level and discharge-tail water level functions of the reservoir, respectively;

[0121] 10) Power constraint:

[0122] ;

[0123] wherein: , are the minimum and maximum power of the i-th hydropower station, MW, respectively; k 11) Hydropower station vibration zone constraint:

[0124]

[0125] ;

[0126] wherein: , are the upper and lower limits of the j-th vibration zone of the i-th hydropower station, respectively; k i 12) Power generation water head equality constraint:

[0127]

[0128] ;

[0129] wherein: is the head loss of the i-th hydropower station in the time period, m. t k The specific steps of establishing the minimum energy consumption scheduling model are as follows:

[0130] ;

[0131] Constraints:

[0132] ;

[0133] ;

[0134] The constraint conditions further include the constraint conditions of 1) to 12), except for the tail water level control constraint in 2) and 7).

[0135] S3, Intraday market and real-time scheduling operation:

[0136] ​​​​​​S3-1, facing period power generation capacity evaluation: according to the daily runoff, wind speed, light condition, the transaction result of the scheduling plan executed by S2 is as the boundary, the daily real-time optimization distribution of the water, wind and light complementary power generation system is carried out, the complementary system facing period power generation capacity is predicted and evaluated;

[0137] S3-2, real-time market participation evaluation: according to the optimization distribution result of S3-1 and the scheduling plan before the day, the power surplus of the water, wind and light complementary system is evaluated, whether it has the condition of participating in the real-time market is judged. If there is power surplus and the market price is at a high level, the system will start the process of continuous bidding to participate in the daily market transaction at the optimal price. At the same time, the rolling adjustment of the scheduling plan is carried out when necessary to respond to the changes of the real-time market and ensure the maximization of the value of the complementary system power.

[0138] As shown in the risk contract power relationship diagram of Figure 6 , according to the runoff, wind and light output of different years, the annual power probability distribution curve of the water, wind and light multi-energy complementary system is counted. According to the risk preference of the decision maker, the annual contract power is signed. The example in the figure shows that the contract power of the decision maker when the risk preference P 风险 is E 合同， The decision maker can provide decision support for participating in the forward market;

[0139] As shown in the algorithm result schematic diagram of Figure 7 , the scheme obtained by the model method is that the output of each period in the day-ahead market is greater than the contract power decomposition output, which meets the contract power segmentation requirement. In comparison, although the power generation benefit maximum model can obtain the maximum power in the day-ahead market, the benefit is less than the scheme obtained by the model, and it cannot meet the contract power segmentation requirement; although the power generation maximum model can obtain the maximum power generation benefit in the day-ahead market, it cannot meet the contract power segmentation requirement. Therefore, the superiority of the model method is embodied.

[0140] The above embodiments are only preferred technical solutions of the present application, and should not be regarded as limiting the present application, and the protection scope of the present application should be the technical solutions recited in the claims, including the equivalent replacement solutions of the technical features recited in the claims. That is, the equivalent replacement improvement within this range is also within the protection scope of the present application.

Claims

1. A method for coordinated dispatching of market transactions of a hydro-photovoltaic complementary power generation system, characterized in that: It comprises the following steps: S1, long-term power generation capacity evaluation in complementary system and long-term market transaction; S2, day-ahead market bidding and generation dispatching plan optimization; S3, intra-day market and real-time dispatching operation; The step S1 specifically comprises the following steps: S1-1, water, wind and light resource data processing: collecting historical runoff, wind and light output data, and studying the complementarity among water, wind and light, analyzing the power generation capacity changes of them under different seasons and weather conditions, eliminating abnormal data from the historical output data, and processing the water, wind and light data after elimination into output data in units of month; S1-2, medium and long-term power generation capacity evaluation: the water, wind and light complementary system power generation enterprise predicts and evaluates the annual power generation capacity of the water, wind and light complementary system according to the water inflow of historical hydrology similar years, wind power and light power generation history experience; S1-3, long-term market contract power transaction: according to the prediction result of S1-2, the annual power generation capacity is evaluated, in order to ensure that the market risk is controllable, the power generation enterprise signs a medium and long-term power contract through centralized bidding, including annual, quarterly and monthly contract power, and realizes the step-by-step rolling transaction of most of the power; S1-4, long-term market contract power decomposition: according to the medium and long-term power contract signed in S1-3, the long-term contract power is decomposed in the way agreed in the contract, and the monthly completed power of the medium and long-term contract is allocated; The step S2 specifically comprises the following steps: S2-1, facing day power generation capacity evaluation: according to the runoff, wind speed and light condition, a short-term optimization dispatching model of water, wind and light complementarity is constructed according to the requirements of reservoir dispatching rules, the facing day power generation capacity of the complementary system is predicted and evaluated through simulation dispatching; S2-2, determination of daily load curve: the daily completed power is obtained by allocating the monthly power generation capacity obtained in S1-4 according to certain rules or agreed way, and the daily load curve is determined according to the facing day load demand and contract agreement way; S2-3, day-ahead bidding and dispatching operation: according to the daily load curve of S2-2, the predicted daily scale wind and light power generation capacity and the day-ahead power price are evaluated; if the power is low or the price is low, it does not participate in the day-ahead bidding, and directly enters the "water for electricity" day-ahead dispatching, and a minimum energy consumption dispatching model is established; if the power is high and the price is high, under the premise of meeting the guaranteed power, it participates in the day-ahead market bidding, and an optimization dispatching model coupled with contract decomposition and day-ahead market bidding is constructed to maximize the day-ahead market benefit; The step S3 specifically comprises the following steps: S3-1, facing time period power generation capacity evaluation: according to the intra-day runoff, wind speed and light condition, the transaction results of the dispatching plan execution of S2 are taken as the boundary, the intra-day real-time optimization distribution of the water, wind and light complementary power generation system is predicted and evaluated, and the facing time period power generation capacity of the complementary system is predicted and evaluated. S3-2, real-time market participation evaluation: according to the optimal allocation result of S3-1 and the day-ahead scheduling plan, the power surplus of the water-wind-solar complementary system is evaluated to determine whether it has the condition to participate in the real-time market; if there is power surplus and the market price is at a high level, the system will start the process of continuous bidding to participate in the intraday market transaction at the optimal price; at the same time, the rolling adjustment of the scheduling plan is carried out to respond to the changes of the real-time market and ensure the maximization of the value of the complementary system power.

2. The method of claim 1, wherein the method further comprises: determining a market price of electricity; and determining a market price of hydrogen. In the step S2-1, the constructed water-wind-solar complementary short-term optimal scheduling model is: ； In the formula, is the total number of cascade hydropower stations; is the total number of time periods in the dispatch period; is the time period granularity; is the hydropower station number; is the total output of is the time period is the total output of the hydropower station; is the wind power output in time period t; is the photovoltaic power output in time period t.

3. The method of claim 1, wherein the method further comprises: determining a market price of electricity; and determining a market price of hydrogen. In the step S2-3, the specific steps of constructing the optimal scheduling model coupled with contract decomposition and day-ahead market bidding are as follows: ； In the formula, is the total number of cascade hydropower stations; is the total number of time periods in the dispatch period; is the time period granularity; is the hydropower station number; is the time period is the contract price of the No. hydropower station, which is related to the signing mode of the long-term contract and is determined by bilateral negotiation or centralized bidding; is the time period day-ahead market clearing forecast price; is the time period is the contract capacity of the No. hydropower station allocated to the hourly output, and the allocation method of the contract capacity needs to be specified in the signed long-term contract; is the time period is the total output of the No. hydropower station, is the wind power output in the t time period; is the photovoltaic output in the t time period; (2) constraint conditions; 1) output-flow-head relationship: ； In the formula: is k the overall efficiency of the hydropower station; is t the time period k the power generation flow of the hydropower station, m 3 / s; is t the power generation head of the first k hydropower station, m; 2) contract power decomposition output constraint: ； 3) water balance constraint: ； In the formula: is t the period of the first k reservoir capacity of the hydropower station, 10 6 m 3 ; is t the period of the first k inflow of the hydropower station, m 3 / s; is t the period of the first k outflow of the hydropower station; is t the period of the first k water abandonment of the hydropower station, m 3 / s; 4) discharge flow constraint: ； wherein: , Qmin and Qmax are the minimum and maximum flow rates, respectively. 5) power generation flow constraint: ； wherein: , Qmin and Qmax are minimum and maximum power generation flow rates, m 3 / s; 6) reservoir storage constraint: ； In the formula: , are the minimum and maximum limit storage of the first k th hydropower station, respectively, 10 6 m 3 ; 7) initial and final control water level constraint: ； In the formula: , Reservoir k At the beginning and end of the dispatching period, m; 8) reservoir storage-water level relationship: ； In the formula: is t the reservoir water level of the last k water power station, m; is the reservoir k storage-capacity-water level function; 9) discharge flow-tail water level relationship: ； In the formula: is t the tailwater level of the nth hydropower station, m; k are the reservoir storage-water level and discharge-tailwater level functions, respectively; and k is the tailwater level of the nth hydropower station, m.​ 10) output constraint: ； In the formula: , The first k Minimum and maximum output of a hydropower station, in MW; 11) power station vibration area constraint: ； In the formula: , are the upper and lower limits of the first k vibration zone of the first i hydropower station, respectively. 12) power generation head equation constraint: ； In the formula: for t Time period k The head loss of a hydroelectric power station is measured in meters (m).

4. The method of claim 3, wherein the method further comprises: determining a market price of electricity; and determining a market price of hydrogen. In the step S2-3, the specific steps of establishing the minimum energy consumption scheduling model are as follows: ； Constraint conditions: ； The constraint conditions also include the constraint conditions of 1) to 12), except for the final water level control constraint in 2) and 7).

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