Dynamic evaluation method for water, wind, light and storage integrated new energy sending and accessing capacity based on long and short term nesting

Abstract

The application provides a long-short-term nested-based water-wind-sight storage integrated new energy external transmission and access capacity dynamic evaluation method, which comprises the following steps: step one, initial calculation condition preparation, including new energy resource data and runoff input data; step two, mathematical model construction, taking the maximum annual power generation of clean energy base water-wind-sight renewable energy as an objective function; step three, setting model parameters (including complementary external transmission mode, peak regulation ratio and power abandonment ratio parameters), and solving new energy access capacity results. The water-wind-sight integrated energy base comprehensive power generation benefit corresponding to the external transmission new energy access capacity under the input water-wind-sight resource level can be evaluated.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of new energy power generation technology, in particular to a water, wind, light and storage integrated new energy external transmission and access capacity dynamic evaluation method based on long-term and short-term nesting. BACKGROUND

[0002] With the consumption of fossil fuels and the increasing greenhouse effect, renewable energy is facing a huge development opportunity, and large-scale renewable energy grid connection will become the development direction of future power systems. However, the temporal and spatial distribution characteristics of renewable energy sources such as wind power and photovoltaic power have brought great challenges to the economy, safety and reliability of power grid operation. Renewable energy power system expansion planning has always been an important research topic in power systems, especially in the transformation and upgrading of future power systems. The traditional power planning time sequence simulation considering several typical operation modes (summer large, summer small, winter large, winter small, and 12 months in the dry season) cannot adapt to the strong variability of new energy output existing in hourly, daily and monthly, so there is an urgent need for annual 8760h panoramic time sequence operation simulation. The power planning time sequence simulation based on annual 8760h panoramic time sequence operation simulation has the following challenges:

[0003] 1. How to realize mathematical abstract modeling of complex operation mode?

[0004] 2. How to realize flexible inclusion of different seasonal operation modes in the planning model?

[0005] 3. How to efficiently solve the 8760h simulation caused by the million-level variable scale model?

[0006] The Chinese patent "CN117639114A A cascade hydropower cooperative configuration wind light capacity optimization method" is based on a multi-objective optimization model of cascade hydropower wind light complementary cooperative optimization configuration, establishes a capacity optimization configuration constraint condition considering the cascade hydropower constraint as the main constraint of the water coupling, and provides a cascade hydropower wind light storage complementary combined power generation system capacity optimization configuration method.

[0007] The Chinese patent "CN117526446A Cascade hydropower wind light multi-energy complementary power generation system wind light capacity double-layer optimization configuration method" establishes a double-layer optimization model, fully considers the natural complementary characteristics of wind and light resources and the peak regulation capacity of hydropower, and realizes the selection of the optimal capacity of wind and light new energy power stations.

[0008] The above existing technologies are all aimed at solving the wind light capacity optimization configuration problem in renewable energy power system expansion planning, but are all limited to traditional power planning time sequence simulation, do not involve annual 8760h panoramic time sequence operation simulation, and are difficult to effectively cope with the three challenges. SUMMARY

[0009] The technical problem solved by the present application is to provide a long-term and short-term nested water, wind, light and storage integrated new energy external sending access capacity dynamic evaluation method, which aims to evaluate the external sending new energy access capacity corresponding to the maximum comprehensive power generation benefit of the water, wind and light integrated energy base under the input water, wind and light resource level.

[0010] To solve the above technical problems, the technical solution adopted by the present application is: a long-term and short-term nested water, wind, light and storage integrated new energy external sending access capacity dynamic evaluation method, comprising the following steps:

[0011] Step one, initial calculation condition preparation, including new energy resource data and runoff input data;

[0012] Step two, mathematical model construction, taking the maximum annual power generation of clean energy base water, wind and light renewable energy as the objective function;

[0013] Step three, setting model benchmark parameters (including complementary external sending mode, peak shaving ratio, and abandoned electricity ratio parameters), and solving new energy access capacity results.

[0014] The long-term and short-term nested water, wind, light and storage integrated new energy external sending access capacity dynamic evaluation method provided by the present application has the following beneficial effects:

[0015] 1. Through target driving in the long-term scale, the long-term and short-term nested mode of realizing the maximum comprehensive benefit of water, wind and light is realized, and the constraint driving in the short-term scale meets the complementary operation regulation demand, and annual 8760h panoramic time sequence operation simulation is realized.

[0016] 2. Under the input water, wind and light resource level, the external sending new energy access capacity corresponding to the maximum comprehensive power generation benefit of the water, wind and light integrated energy base is met under the constraints of hydropower station operation, external sending channel, water, wind and light complementary bundling external sending mode (such as peak shaving ratio, peak shaving period, etc.), energy storage operation, maximum allowable abandoned electricity rate and other constraints. In the data input layer, the related parameters such as hydropower station, energy storage power station, external sending channel, resource level, operation mode and overall allowable abandoned electricity rate can be changed. In the core model calculation layer, the maximum water, wind and light resource coordinated development and utilization benefit is taken as the principle, the 8760 refined operation optimization simulation evaluation is carried out, and the optimal access scale of the newly added external sending new energy is obtained. In the data output layer, the wind power access capacity, the photovoltaic access capacity, the optimal bundling external sending mode, the total power generation of the system, the abandoned electricity quantity and the 8760h panoramic time sequence operation process of the water, wind and light storage integrated clean energy base can be obtained. BRIEF DESCRIPTION OF DRAWINGS

[0017] The present application will be further described below in combination with the drawings and embodiments:

[0018] Figure 1A flow chart of the long-short term nested based water, wind, light and storage integrated new energy external transmission and access capacity dynamic evaluation method of the present application;

[0019] Figure 2 Water, wind, light and storage bundling transmission mode (single peak, double peak, smooth) schematic diagram;

[0020] Figure 3 New energy access capacity results under different water, wind, light and storage bundling transmission modes;

[0021] Figure 4 New energy access capacity results under different energy storage configuration scenarios; DETAILED DESCRIPTION

[0022] The technical problem to be solved by the present application is to provide a long-short term nested based water, wind, light and storage integrated new energy external transmission and access capacity dynamic evaluation method, which aims to evaluate the external transmission new energy access capacity corresponding to the maximum comprehensive power generation benefit of the water, wind and light integrated energy base under the input water, wind and light resource level, the satisfaction of the water power station operation, the external transmission channel, the water, wind and light complementary bundling transmission mode (such as the peak regulation ratio, the peak regulation period, etc.), the energy storage operation, the maximum allowed abandoned power rate and many other constraints. In the data input layer, the related parameters such as the water power station, the energy storage power station, the external transmission channel, the resource level, the operation mode and the overall allowed abandoned power rate can be changed. In the core model calculation layer, the maximum wind, light and water resource coordinated development and utilization benefit is taken as the principle, the 8760 refined operation optimization simulation evaluation is carried out, and the optimal access scale of the newly added external transmission new energy is obtained. In the data output layer, the wind power access capacity, the photovoltaic access capacity, the optimal bundling transmission mode, the system total power generation, the abandoned power and the water, wind and light storage integrated clean energy base annual 8760h panoramic time sequence operation process can be obtained. The model framework is as shown in Figure 1 .

[0023] The long-short term nested based water, wind, light and storage integrated new energy external transmission and access capacity dynamic evaluation is completed according to the following steps:

[0024] Step one, initial calculation condition preparation, including one-year hourly new energy resource data (unit installed output), one-year monthly runoff input data and the water power station basic data required for calculation.

[0025] The new energy includes: wind power, photovoltaic.

[0026] Step two, mathematical model construction, taking the maximum annual power generation of the clean energy base water, wind and light renewable energy as the objective function.

[0027] Objective function:

[0028] In order to realize the maximum level of the basin renewable energy resource coordinated utilization, the maximum annual power generation of the clean energy base water, wind and light renewable energy is taken as the objective function, and the corresponding mathematical expression is as follows:

[0029]

[0030] where: h is the index of hydropower station; H is the set of hydropower station indices; m is the index of month; M is the set of month indices; d is the index of day in month; Ω m is the set of day indices in month m; t is the index of hour in day; T is the set of hour indices in day. phl h,m and phr h,m are the average output of left and right bank power plants of hydropower station h in month m; wcapl h and wcapr h are the wind power accessible capacity of left and right bank power plants of hydropower station h; scapl h and scapr h are the photovoltaic accessible capacity of left and right bank power plants of hydropower station h; UEWL h,m,d,t and UEWR h,m,d,t are the average resource level (unit installed output or called capacity factor) of wind power around left and right bank power plants of hydropower station h in month m, day d, hour t; UESL h,m,d,t and UESR h,m,d,t are the average resource level (unit installed output or called capacity factor) of photovoltaic around left and right bank power plants of hydropower station h in month m, day d, hour t.

[0031] Constraints:

[0032] Hydropower operation constraints:

[0033] 1) Water balance constraint

[0034] v h,m = v h,m-1 + (QN h,m + qo h-1,m - qo h,m ) Δt / 10000

[0035] where: v h,m is the reservoir capacity of hydropower station h at the end of time period m (million m 3 ); QN h,m is the natural inflow of hydropower station h in time period m (m 3 / s); qo h,m is the total outflow of hydropower station h in time period m (m 3 / s); Δt is the time period (s).

[0036] 2) Total outflow

[0037] qo h,m = qpl h,m + qpr h,m+qs h,m

[0038] where qpl h,m and qpr h,m are the power generation flow of the left and right bank power plants of the hydropower station h at the mth time period, respectively, qs h,m is the abandoned water flow of the hydropower station h at the mth time period.

[0039] 3) Upper and lower limits of reservoir capacity

[0040]

[0041] where: and are the reservoir capacity operating boundaries of the hydropower station h at the mth time period, respectively.

[0042] 4) Upper and lower limits of outflow and power generation flow

[0043]

[0044]

[0045] where: are the outflow boundaries of the hydropower station, and the power generation flow boundaries of the left and right bank power plants, respectively.

[0046] 5) Power generation function

[0047]

[0048] where phl h,m , phr h,m are the power outputs of the left and right bank power plants of the hydropower station h at the mth time period, respectively; is the average reservoir capacity of the hydropower station h at the mth time period.

[0049] 6) Upper and lower limits of power output constraint

[0050]

[0051] where: are the upper and lower limits of the power output of the left and right bank power plants of the hydropower station h at the mth time period, respectively.

[0052] 7) Residual sending power constraint:

[0053]

[0054] where: are the residual power outputs of the left and right bank power plants of the hydropower station h at the mth time period, respectively; are the sending power outputs of the left and right bank power plants of the hydropower station h at the mth time period, respectively.

[0055] 8) Residual export power allocation constraint:

[0056]

[0057] where Ω wet and Ω dry are the sets of months in wet and dry seasons, respectively. and are the residual power requirements of hydropower station h in dry and wet seasons, respectively.

[0058] Hydropower-wind-solar-storage integrated complementary operation constraint class:

[0059] 1) Wind and solar power generation constraints

[0060]

[0061] where pwl h,m,d,t , pwr h,m,d,t are the average wind power outputs of the left and right bank power plants of hydropower station h connected to the grid at t hours on day d in month m, respectively; psl h,m,d,t , psr h,m,d,t are the average solar power outputs of the left and right bank power plants of hydropower station h connected to the grid at t hours on day d in month m, respectively.

[0062] 2) Long and short-term nested power-energy coupling constraints of hydropower stations

[0063]

[0064] where are the average power outputs of the left and right bank power plants of hydropower station h at t hours on day d in month m; Δt m is the number of hours in month m.

[0065] 3) State of charge time series balance constraint of storage

[0066] se i = se i-1 + (spch i / η overall - spdis i × η overall )

[0067] where se i is the state of charge (storage capacity) of the clean energy base configured storage at i time period; i is the 8760 global hourly number in a year; spch i is the charging power of the storage at i time period; spdis i is the discharging power of the storage at i time period; η overall is the overall efficiency of the storage.

[0068] 4) Operation boundary constraints of storage

[0069] (1-γ)SE≤se i ≤SE

[0070]

[0071] SP×Tdis max =SE

[0072]

[0073] Where: SE is the energy storage rated capacity of the clean energy base, γ is the depth of discharge; SP is the rated power; Tdis max is the maximum discharge duration of energy storage; SE beg is the state of charge of energy storage at the 0th hour of the year; SE end is the state of charge of energy storage at the 8760th hour of the year.

[0074] 5) Water, wind, light, and storage bundled output

[0075]

[0076] Where: sumhwstral h,m,d,t , sumhwstrar h,m,d,t are the total water, wind, light, and storage bundled output of the left and right bank power plants of the hydropower station h at m day t; spch h,Φ(m,d,t)→i , spdisl h,Φ(m,d,t)→i , spchr h,Φ(m,d,t)→i , spdisr h,Φ(m,d,t)→i are the left and right bank charging and discharging power, respectively.

[0077] 6) Water, wind, light, and storage final bundled deliverable output

[0078]

[0079] Where: finalsumhwstral h,m,d,t , finalsumhwstrar h,m,d,t are the water, wind, light, and storage final bundled deliverable total output of the left and right bank power plants of the hydropower station h at m day t; CHL h,m,d,t , CHR h,m,d,t are the maximum deliverable channel capacities, respectively.

[0080] 7) Spillage constraint

[0081]

[0082] Where: curpl h,m,d,t is the spillage power of the left bank power plant of the hydropower station h at m day t caused by channel obstruction; curpr h,m,d,tThe abandoned power caused by the passage obstruction of the right bank power plant of the hydropower station h at t hours on d day in m month;

[0083] 8) Maximum allowed abandoned power rate constraint

[0084]

[0085] In the formula: λ is the maximum allowed abandoned power rate.

[0086] 9) Baling delivery mode control constraint

[0087]

[0088]

[0089] In the formula, G is the water, wind and light baling operation mode library, mainly including OnePeakMode, TwoPeakMode, SmoothMode respectively representing single peak delivery mode, double peak delivery mode, smooth delivery mode, represented by g∈G; What operation mode is taken through the Boolean variable Yl h,m,g and Yr h,m,g designate (logical variables representing true or false) Yl h,m,g =True indicates that the delivery mode of the left bank power plant of the power station h in m month is g; Yr h,m,g =True indicates that the delivery mode of the right bank power plant of the power station h in m month is g; ∨ is the "or" operator; ∨ g∈G Yl h,m,g indicates that each power plant can set one operation mode each month; TYPICAL g,t , t∈T is the typical unit curve corresponding to the operation mode g; pl h,m,d is the amplification coefficient.

[0090] Step three, set the model input parameters, solve the new energy access capacity result, the model belongs to linear programming problem, use commercial solver Gurobi to realize the solution.

[0091] Collect the runoff data of the lower reaches of Jinsha River from 1959 to 2022 for a total of 64 years, select 1987 as the normal water representative year, and the specific data is shown in Table 1. According to the left and right banks of the four power stations, the installed utilization hours of wind and light resources around each power station are shown in Table 2.

[0092] (1) New energy access capacity results under the baseline scenario

[0093] Take the normal water year (1987) as the baseline scenario, and adopt different water, wind and light baling delivery modes (including single peak delivery, double peak delivery and smooth delivery) in different months as shown in Table 3, and the schematic diagram of different delivery modes is shown in Figure 2The peak shaving ratio is set to 30% for dual-peak mode and 20% for single-peak mode. The maximum allowable curtailment rate is set to 0% (i.e., curtailment is not allowed). The peak shaving ratio is defined as the ratio of the difference between the maximum and minimum combined output of hydropower, wind power and solar power to the maximum combined output of hydropower, wind power and solar power.

[0094] Table 1. Runoff Scenario in a Normal Year (1987)

[0095]

[0096] Table 2. Utilization Hours of New Energy Installed Capacity in Pingshui Year

[0097]

[0098] Table 3 Operating Mode Settings

[0099]

[0100]

[0101] Under the parameters set above, the calculation results are shown in Table 4. The grid-connectable wind power capacity is 38,476 MW, and the grid-connectable photovoltaic capacity is 15,432 MW, corresponding to a hydropower-wind-solar capacity ratio of 46%:38%:16%. The total annual combined hydropower-wind-solar power generation is approximately 320.74 billion kWh, with hydropower generating 199.61 billion kWh (62%), wind power generating 99.98 billion kWh (31%), and photovoltaic power generating 21.15 billion kWh (7%).

[0102] Table 4. Renewable Energy Access Capacity of Each Power Station

[0103]

[0104] (2) Results of renewable energy access capacity under different bundled power transmission modes of hydropower, wind power and solar power

[0105] A comparative analysis was conducted on the scale of renewable energy access for the Jinxia cascade hydropower-wind-solar power transmission under different bundled power transmission modes, in order to determine the most suitable bundled power transmission mode for the Jinxia cascade hydropower-wind-solar power transmission. The power transmission mode settings are as follows:

[0106] External transmission mode 1 (double peak): The double peak external transmission mode is adopted throughout the year, with a peak shaving ratio of 30%, and the other parameters are the same as the baseline scenario;

[0107] External delivery mode 2 (single peak): The single peak external delivery mode is adopted throughout the year, with a peak shaving ratio of 20%, and the other parameters are the same as the baseline scenario;

[0108] Delivery Mode 3 (Smooth): The smooth delivery mode is used throughout the year, and the other parameters are the same as the baseline scenario;

[0109] Delivery mode 4: same as the reference scenario (different delivery modes are used in different months, as shown in Table 3).

[0110] The results are shown in Figure 3 , Figure 3 The left graph in the figure is the installed capacity of new energy, and the right graph is the annual power generation of water, wind and light. It can be seen that the proposed method can effectively solve the new energy access capacity under different delivery modes, and it is found that the double-peak mode has the worst power generation benefit. Compared with the smooth mode, the power output decreases by 24.2 billion kWh, with a decrease of 7.1%. The water, wind and light bundled delivery mode will significantly affect the access capacity of new energy and the delivery power. It is recommended to preferentially choose the smooth mode for delivery to obtain better power generation benefits.

[0111] (3) New energy access capacity results under different energy storage configuration scenarios

[0112] Scenario 1: 1200MW / 4800MWh energy storage is configured, i.e. the rated power lasts for 4h, representing electrochemical energy storage and conventional pumped storage.

[0113] Scenario 2: 1200MW / 86400MWh energy storage is configured, i.e. the rated power lasts for 72h, representing long-time energy storage technology.

[0114] Scenario 3: 1200MW / 432000MWh energy storage is configured, i.e. the rated power lasts for 360h (15 days), representing seasonal energy storage technology, hydrogen energy storage or seasonal pumped storage power station. Other settings are the same as the reference scenario.

[0115] The calculation results are shown in Figure 4 , Figure 4 The left graph in the figure is the installed capacity of new energy, and the right graph is the annual power generation of water, wind and light. The proposed method can effectively obtain the new energy access capacity of each hydropower station under different energy storage configuration scenarios. The results of scenarios 1-3 have almost no obvious difference, which shows that compared with short-time energy storage technology, configuring long-time or seasonal energy storage technology is difficult to further improve the new energy access capacity and delivery power generation benefit. The results show that configuring general short-time energy storage technology is the best energy storage configuration scheme.

[0116] The application results under the above different scenarios fully show that the proposed method can realize the dynamic evaluation of water, wind and light storage integrated new energy delivery and access capacity. The method has high flexibility and reliability.

Claims

1. A dynamic evaluation method for the transmission and access capacity of integrated hydro-wind-solar-storage renewable energy based on a nested long- and short-term approach, characterized in that, Includes the following steps: Step 1: Preparation of initial calculation conditions, including new energy resource data and runoff input data, specifically including hourly new energy resource data for one year, monthly runoff input data for one year, and basic data of hydropower stations required for calculation; Step 2: Mathematical Model Construction: The objective function is to maximize the annual power generation of renewable energy sources, including water, wind, and solar power, within the clean energy base. The expression for the objective function is as follows: ； In the formula: For power station indexing; A set of power station indexes; Indexed by month; A set of month indexes; For the daily index of each month; for The set of day indices for the month; For daily hourly indexes, A daily hourly index set; and Hydropower stations Left bank power plant and right bank power plant Average monthly output; and Hydropower stations Wind power grid connection capabilities of left bank and right bank power plants; and Hydropower stations The grid connection capability of photovoltaic power plants on the left and right banks; and Hydropower stations Wind power around the left bank power plant and the right bank power plant moon day Average resource level at that time; and Hydropower stations Photovoltaics around the left bank power plant and the right bank power plant moon day Average resource level at that time; The constraints of the mathematical model include hydropower operation constraints and integrated hydropower-wind-solar-storage complementary operation constraints; Step 3: Set model parameters and calculate the new energy access capacity results. The model parameters include complementary transmission mode, peak shaving ratio, and curtailment ratio. The complementary transmission mode includes three transmission modes: single-peak transmission, double-peak transmission, and smooth transmission. The peak shaving ratio is the ratio of the difference between the maximum and minimum bundled output of hydropower, wind power, and solar power to the maximum bundled output of hydropower, wind power, and solar power. The curtailment ratio parameter is the maximum allowable curtailment rate.

2. The dynamic evaluation method for the transmission capacity of integrated hydro-wind-solar-storage renewable energy based on a nested long- and short-term approach, as described in claim 1, is characterized in that... In step one, new energy sources include wind power and photovoltaic power.

3. The method for dynamic evaluation of the integrated hydro-wind-solar-storage renewable energy transmission capacity based on a nested long- and short-term approach, as described in claim 1, is characterized in that... The hydropower operation constraints include the following: 1) Water balance constraint ； In the formula: For hydroelectric power station reservoir Storage capacity at the end of the time period; For hydroelectric power station exist Natural inflow runoff during a given period; For hydroelectric power station reservoir Total outbound flow during the time period; For time periods; 2) Total outbound flow ； In the formula: and These are hydroelectric power stations The left and right bank power plants Power generation flow during the period For hydroelectric power station exist The amount of water discharged during a given time period; 3) Upper and lower limits of storage capacity ； In the formula: and Hydropower stations exist The operational boundary of the reservoir capacity during a given time period; 4) Upper and lower limits of outflow and power generation flow ； ； In the formula: This represents the boundary of the power plant's outflow. This represents the boundary between the power generation flow rates of the left and right bank power plants. 5) Generation function ； In the formula: , They are the left and right bank hydroelectric power stations respectively. Left and right bank power plants Efforts during a specific time period; For hydroelectric power station exist Average storage capacity over a given period; 6) Output upper and lower limit constraints ； In the formula: Hydropower stations The left and right bank power plants Upper and lower limits of output during different time periods; 7) Remaining power transmission capacity constraint ； In the formula: Hydropower stations The left and right bank power plants The remaining output during the period; Hydropower stations The left and right bank power plants Delivery capacity during specific time periods; 8) Constraints on the allocation of remaining external power transmission capacity ； In the formula: and These are sets of months representing the wet season and the dry season, respectively. and Hydropower stations The requirement for remaining electricity during the dry and wet seasons.

4. The dynamic evaluation method for the integrated hydro-wind-solar-storage renewable energy transmission capacity based on a nested long- and short-term approach, as described in claim 1, is characterized in that... The operational constraints of the integrated hydro-wind-solar-storage complementary system include the following: 1) Constraints on wind and solar power generation ； In the formula: Hydropower stations Wind power connected to power plants on the left and right banks moon day Average output at time; Hydropower stations Photovoltaics connected to power plants on both the left and right banks moon day Average output at time; 2) Short-term and long-term nested power-energy coupling constraints of hydropower stations ； In the formula: Hydropower stations Left and right bank power plants moon day Average output at time; for Hours per month; 3) Energy storage state of charge timing balance constraints ； In the formula: Configuring energy storage for clean energy bases State of charge over a period of time; The 8760 global numbers are assigned hourly throughout the year; For energy storage Charging power during a given period; For energy storage Discharge power over a given period of time; For overall energy storage efficiency; 4) Energy storage operation boundary constraints ； ； ； ； In the formula: Rated energy storage capacity for clean energy bases Depth of discharge; Rated power; Maximum discharge duration of energy storage This represents the energy storage state of charge at time 0 of the year. This marks the 8760th hour of the year's energy storage state of charge. 5) Water, wind, solar, and energy storage bundled together ； In the formula: Hydropower stations Left and right bank power plants moon day Time, water, scenery, and storage are all combined to generate total output. These represent the charging and discharging power of the left and right banks, respectively. 6) Hydropower, wind power, solar power, and energy storage can be bundled together and transmitted externally. ； In the formula: Hydropower stations Left and right bank power plants moon day The total output of the bundled storage of water, wind, and solar energy for final external transmission; These refer to the maximum external delivery channel capacity; 7) Curtailment of power consumption ； In the formula: For hydroelectric power station Left Bank Power Plant moon day The power wasted due to channel obstruction; For hydroelectric power station Right Bank Power Plant moon day The power wasted due to channel obstruction; 8) Maximum allowable curtailment rate constraint ； In the formula: The maximum allowable curtailment rate; 9) Bundled delivery mode control constraints ； ； In the formula, The library of bundled operation modes for water, wind, and solar power mainly includes These represent single-peak delivery mode, double-peak delivery mode, and smooth delivery mode, respectively. Characterization; the operating mode adopted is indicated by Boolean variables. and Specify, and Logical variables representing true or false, i.e. Indicates power station Left Bank Power Plant The monthly delivery mode is ; Indicates power station Right Bank Power Plant The monthly delivery mode is ; For the "or" operator; This means that each power plant can set one operating mode per month; For operating mode The corresponding typical per-unit curve; This is the magnification factor.

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