Monthly adjustment method for cascade hydropower annual power generation plan in electricity market environment

Abstract

The invention relates to the field of hydroelectric generation, and discloses a monthly adjustment method for a cascade hydroelectric annual power generation plan in a power market environment, which comprises the following steps of: firstly, constructing a power generation plan adjustment model, and modeling benefits and operation requirements of hydroelectric generation, inter-province power transmission and province power utilization; opportunity constraint is introduced to describe the risk of water level out-of-limit of the hydropower station caused by runoff uncertainty, two indexes of a line disturbance rate and a contract net adjustment rate are constructed to manage the influence of contract adjustment on a power transmission side and a power utilization side respectively, and the coupling relation between two types of power transmission modes of point-to-network and network-to-network and multi-province and multi-variety contracts is modeled; a # imgabs0 # solving method is constructed, the power generation plan adjustment model is converted into an SAA model, the risk level # imgabs1 # of the SAA model is iteratively adjusted, and solving verification is carried out; and finally, obtaining a contract adjustment scheme of cascade hydropower. By applying the method, the problem of contract adjustment can be effectively solved, and the provided solving method can accelerate to obtain a feasible solution with high confidence on the basis of ensuring the solving precision.

Description

Technical Field

[0001] The present invention relates to the field of hydropower generation, and in particular to a method for adjusting a cascade hydropower annual power generation plan before one month in a power market environment. Background Art

[0002] Hydropower is the clean energy with the largest installed capacity and annual power generation in China. It is safe, economical, efficient, renewable, and dispatchable. It is an important power source for China's West-to-East Power Transmission Project, and is consumed across provinces over long distances through direct current transmission channels. Traditionally, cascade hydropower is based on the unified planning and dispatching of power grid companies. This model ensures the technical feasibility and overall economic efficiency of all hydropower station power generation plans in the power grid. However, with the implementation of a new round of power system reform in China, the inter-provincial transmission of hydropower has gradually shifted from the traditional West-to-East Power Transmission Framework Agreement to inter-provincial market-based transactions, signing government-authorized priority contracts and autonomous market-based contracts. Among them, the priority electricity of the priority contract is the planned electricity that guarantees the priority consumption of clean energy. Hydropower stations usually sign contracts in the annual market according to the electricity allocated by the government; the market electricity of the market-based contract requires hydropower stations to participate in the annual market to sign contracts on their own.

[0003] In the annual market within and between provinces, cascade hydropower needs to sign the electricity contracts for each month of the following year with the hydropower station as the trading unit before the New Year, and complete the delivery on a monthly basis. For a certain delivery month, the hydropower station needs to adjust or confirm the contracted electricity for the delivery month in the previous month. Therefore, power generation companies must formulate adjustment plans for cascade hydropower priority contracts and market-based contracts before the delivery month to improve water energy utilization and reduce the performance risk caused by changes in runoff forecasts.

[0004] The contract performance of cascade hydropower involves a cascade hydropower inter-provincial transmission system consisting of cascade hydropower, transmission networks and power-consuming provinces. In this system, there are two transmission modes for cascade hydropower: network-to-network and point-to-network. Among them, network-to-network transmission means that the hydropower station is first physically connected to the power grid of the sending province, and the electricity it generates is then sent by the latter to the power grid of the landing province, which is equivalent to transactions and settlements between the two power grids. There is no direct buying and selling relationship between the hydropower station and the recipient. Point-to-network transmission is direct electricity trading and transmission between the hydropower station and the inter-provincial and inter-regional transmission enterprises and the landing provincial power grid. Therefore, the transmission mode of cascade hydropower is coupled with multi-province and multi-variety contracts. Accurate modeling when adjusting the contract is the key to ensuring reliable adjustments.

[0005] In summary, hydropower production relies heavily on random runoff with uneven temporal and spatial distribution. The uncertainty of runoff before the delivery year and the improvement of prediction accuracy before the delivery month require hydropower stations to make contract adjustments before the delivery month to correct the calculation deviation of power generation capacity caused by runoff prediction deviation, improve water energy utilization and reduce performance risk. At the same time, the multi-province and multi-variety contract coupling of cascade hydropower has brought about a variety of transmission modes, and the close hydraulic connection and various hydraulic requirements of the upstream and downstream of the cascade have further aggravated the complexity of contract adjustment. Therefore, how to formulate adjustment plans for cascade hydropower multi-variety annual contracts taking into account a variety of transmission modes is a practical problem currently faced by Chinese hydropower companies, and it is also an engineering problem that the present invention aims to solve. Summary of the invention

[0006] In view of the above problems and actual needs, the present invention provides a method for adjusting the annual power generation plan of cascade hydropower in advance under the power market environment, and constructs a power generation plan adjustment model and a supporting The solution method can jointly adjust the multi-variety annual contracts of cascade hydropower before the delivery month, give full play to the regulation ability of cascade hydropower and the mutual assistance ability of transmission lines, correct the power generation capacity deviation caused by runoff prediction deviation, and improve the total revenue of cascade hydropower; the application of the present invention can effectively solve the contract adjustment problem, and the solution method provided can accelerate the acquisition of a feasible solution with high confidence on the basis of ensuring the solution accuracy.

[0007] Technical solution of the present invention:

[0008] A method for adjusting the annual power generation plan of cascade hydropower in advance under the power market environment, the method comprising constructing a power generation plan adjustment model and a matching Solution method: First, build a power generation plan adjustment model to model the interests and operational needs of hydropower generation, inter-provincial power transmission and provincial power consumption, introduce opportunity constraints to characterize the risk of water level exceeding the limit of hydropower stations due to runoff uncertainty, build two indicators, line disturbance rate and contract net adjustment rate, to manage the impact of contract adjustment on the transmission side and the power consumption side respectively, and model the coupling relationship between the two types of transmission modes, point-to-grid and grid-to-grid, and multi-province and multi-variety contracts; then build Solution method: convert the power generation plan adjustment model into the SAA model and iteratively adjust the risk level of the SAA model , and then verify the solution; finally, the contract adjustment plan for cascade hydropower is obtained. The specific steps include:

[0009] Step 1: Construct a power generation plan adjustment model.

[0010] The constructed power generation plan adjustment model focuses on the inter-provincial transmission system of cascade hydropower. Cascade hydropower completes the power transmission of multiple provinces and multiple varieties of contracts through AC and DC lines. The contract adjustment takes into account the interests and operational needs of hydropower generation, inter-provincial transmission and provincial electricity consumption, involving complex water, electricity and market constraints. The specific steps include the following:

[0011] Step 1.1: Construct the objective function of the power generation plan adjustment model.

[0012] Under the market environment, the total revenue of cascade hydropower stations consists of contract revenue and energy storage revenue. Contract revenue refers to the power generation revenue obtained by cascade hydropower through annual contracts; energy storage revenue refers to the future power generation revenue of cascade hydropower storage at the end of the contract period. The essence of contract adjustment is to coordinate the current and future allocation of hydropower resources and weigh the decision of power generation and water storage. Therefore, starting from the interests of cascade hydropower, an objective function is constructed with the goal of maximizing the total revenue of cascade hydropower after contract adjustment, as shown in equations (1) and (2):

[0013] (1)

[0014] (2)

[0015] Where: is the total revenue of cascade hydropower; and They are Storage revenue and contract revenue from hydropower stations; , , and The contract types include preferred contracts and market-based contracts, and the delivery period is based on a monthly basis. for A collection of hydroelectric power stations and their upstream hydroelectric power stations; for The average annual water consumption rate of the hydropower station; and They are Hydropower Station Province The annual average electricity price and power delivery ratio of the contract type; and They are The final storage capacity and dead storage capacity of the hydropower station; , and They are Hydropower Station Province Contract Type The electricity price during the delivery period, the electricity before and after the contract adjustment; The number of seconds for each delivery period.

[0016] Step 1.2: Construct hydraulic constraints for the generation schedule adjustment model.

[0017] In order to meet the operational requirements of hydropower generation, the hydraulic constraints of the power generation plan adjustment model are constructed as shown in Equations (3) to (13).

[0018] Step 1.2.1: Construct the water balance equation.

[0019] The water balance equation is constructed as shown in equation (3)-(4):

[0020] (3)

[0021] (4)

[0022] Where: for Hydropower Station Storage capacity at the end of the delivery period; , , and They are Hydropower Station The interval flow, outbound flow, power generation flow and abandoned water flow during the delivery period; for The collection of hydropower stations directly upstream of the hydropower station, that is, The collection of upstream hydropower stations to which the hydropower station is directly connected; for Hydropower Station Outbound flow during the delivery period.

[0023] Step 1.2.2: Construct water level boundary constraints.

[0024] The water level and storage capacity relationship is constructed as shown in formula (5), the initial water level constraint is constructed as shown in formula (6), and the physical water level boundary constraint is constructed as shown in formula (7):

[0025] (5)

[0026] (6)

[0027] (7)

[0028] Where: for Hydropower Station The water level above the dam at the end of the delivery period (hereinafter referred to as the "water level"); for The relationship between the water level and reservoir capacity of a hydropower station is constructed using piecewise linear interpolation; and They are The initial water level of the hydropower station and its actual value; and They are Hydropower Station The upper and lower limits of the physical water level at the end of the delivery period.

[0029] In order to control the risk of water level exceeding the limit of the hydropower station due to runoff uncertainty, the water level control boundary constraint is constructed as shown in formula (8). The risk of violating the water level control boundary is modeled as a chance constraint to ensure that the water level is within the preset safety range with a certain probability level.

[0030] (8)

[0031] In the formula, and They are Hydropower Station The upper and lower limits of the control water level at the end of the delivery period; The risk level for opportunity constraints; For probability.

[0032] It should be emphasized that the random variables of the power generation plan adjustment model are , , , and , they are implicit functions of each other. To ensure the water storage safety of cascade hydropower, the final storage capacity Defined as a deterministic variable.

[0033] Step 1.2.3: Construct power generation function and output boundary constraints.

[0034] The power generation function is constructed as shown in formula (9), and the output boundary constraint is constructed as shown in formula (10):

[0035] (9)

[0036] (10)

[0037] Where: for Hydropower Station Power generation output during the delivery period; for Hydropower Station Average water consumption rate during the delivery period; and They are The upper and lower limits of a hydropower station’s output.

[0038] Step 1.2.4: Construct flow boundary constraints.

[0039] The traffic boundary constraints are constructed as shown in equations (11) to (13):

[0040] (11)

[0041] (12)

[0042] (13)

[0043] Where: and They are Hydropower Station The upper and lower limits of outbound flow during the delivery period; and They are Hydropower Station The upper and lower limits of power generation flow during the delivery period.

[0044] Step 1.3: Construct the power constraints of the generation schedule adjustment model.

[0045] Step 1.3.1: Construct node balance constraints.

[0046] Considering the power balance of each node in the transmission network, the nodes in the transmission network include hydropower stations, transmission lines and power-consuming provinces. The node balance constraints are constructed as shown in Equations (14) to (16):

[0047] (14)

[0048] (15)

[0049] (16)

[0050] Where: is the set of transmission lines, and we define For collection The index of the line in the middle includes unidirectional lines, bidirectional lines and other lines. Specifically, the DC line is defined as a unidirectional line with unidirectional power flow, the AC line is defined as a bidirectional line with bidirectional power flow, and the power plant transmission line is defined as other lines. , and They are the indexes of one-way lines, two-way lines and other lines respectively; is the set of all nodes in the transmission network, defined by equation (16), is the union symbol; is the index of the node; and Respectively The node provides input power and output power to the node set, both of which are sets A subset of When the node is a transmission line express node The transmission power during the delivery period is When the node is a hydropower station express node The power generation output during the delivery period, when The node is the power saving time express node The power consumption during the delivery period; Formula (14) expresses the energy balance relationship of each node.

[0051] Step 1.3.2: Construct transmission capacity constraints.

[0052] Based on the occupancy of transmission lines in the original cascade hydropower contracts, the transmission capacity constraints are constructed as shown in equations (17) to (20):

[0053] (17)

[0054] (18)

[0055] (19)

[0056] (20)

[0057] Where: and They are before and after the adjustment of cascade hydropower contracts. One-way lines Occupancy power during the delivery period; and They are before and after the adjustment of cascade hydropower contracts. Two-way line Forward occupied power during the delivery period; and They are before and after the adjustment of cascade hydropower contracts. Two-way line Reverse occupied power during the delivery period; Adjustment of cascade hydropower contracts Other routes Occupancy power during the delivery period; for The transmission power cap of other lines; and When the contract is adjusted One-way lines The upward adjustment capacity of all market players and non-tiered players during the delivery period, and When the contract is adjusted Two-way line The increased capacity of all market players and non-cascade players during the delivery period; Equations (17), (18) and (19) respectively express the available transmission capacity of one-way lines, two-way lines and other lines to cascade hydropower players when the contract is adjusted.

[0058] Step 1.3.3: Construct line perturbation constraints.

[0059] In order to manage the impact of cascade hydropower contract adjustments on transmission lines, the disturbance rate of one-way lines is defined as shown in formula (21), the forward disturbance rate of two-way lines is defined as shown in formula (22), the reverse disturbance rate of two-way lines is defined as shown in formula (23), and the disturbance rate constraints of one-way and two-way lines are shown in formula (24), so as to ensure that the transmission deviation before and after the contract adjustment is within the acceptable range of inter-provincial transmission. Since other lines are supporting lines for hydropower stations, no line disturbance constraints are set.

[0060] (twenty one)

[0061] (twenty two)

[0062] (twenty three)

[0063] (twenty four)

[0064] Where: Adjustment of cascade hydropower contracts before and after One-way lines The disturbance rate during the delivery period; , They are respectively before and after the adjustment of cascade hydropower contracts. Two-way line Forward and reverse disturbance rates during the delivery period; Adjustment of cascade hydropower contracts before and after The upper limit of the disturbance rate during a one-way line and a single delivery period, Adjustment of cascade hydropower contracts before and after The upper limit of the disturbance rate during a single delivery period of a two-way line; for The upper limit of transmission power on a unidirectional line, for The upper limit of the transmission power for bidirectional lines.

[0065] Step 1.3.4: Construct the space constraints for absorption.

[0066] In order to ensure that the contract adjustment results of cascade hydropower meet the power consumption boundaries of power-consuming provinces, the power consumption space constraints of power-consuming provinces are constructed as shown in formula (25):

[0067] (25)

[0068] Where: express Province Electricity consumption during the delivery period, and Respectively Province The upper and lower limits of cascade hydropower consumption during the delivery period.

[0069] Step 1.4: Construct the market constraints for the generation schedule adjustment model.

[0070] Step 1.4.1: Construct the contract power matching constraint.

[0071] Considering the power matching of hydropower generation, provincial electricity consumption and market contracts, the constraints of hydropower generation and contract power matching are constructed as shown in formula (26), and the constraints of provincial electricity consumption and contract power matching are constructed as shown in formula (27):

[0072] (26)

[0073] (27)

[0074] Where: for Hydropower Station Power generation output during the delivery period; for Province The electricity consumption during the delivery period.

[0075] Step 1.4.2: Construct contract adjustment constraints.

[0076] In order to minimize the impact of cascade hydropower contract adjustments on provincial power supply, contract adjustment constraints are constructed as shown in Equations (28) to (30).

[0077] First, define the contract net adjustment rate as shown in formula (28):

[0078] (28)

[0079] Where: for Province Contract Type The net adjustment rate of the tiered contracts during the delivery period, and Right now and Represents the priority contract and market-based contract respectively. Province The net adjustment rate of tiered contracts during the delivery period.

[0080] Due to the supply guarantee function of the priority contract, the priority contract adjustment constraint is constructed as shown in formula (29): 0 to ensure strict execution of priority contracts.

[0081] (29)

[0082] Due to the flexibility of market-based contracts, the market-based contract adjustment constraints are constructed as shown in formula (30), allowing Ensure the effective implementation of market-based contracts within the acceptable range of electricity-consuming provinces.

[0083] (30)

[0084] Where: Adjustment of cascade hydropower contracts before and after The upper limit of the net adjustment rate of market-based contracts during the provincial delivery period.

[0085] Step 1.4.3: Construct transmission mode constraints.

[0086] In order to ensure the reliability and applicability of contract adjustment, the coupling relationship between the point-to-grid and grid-to-grid transmission modes and multi-province and multi-variety contracts is considered. The point-to-grid transmission mode constraint is constructed as shown in formula (31), and the grid-to-grid transmission mode constraint is constructed as shown in formula (32). The point-to-grid and grid-to-grid power components of the line make the contract adjustment results more in line with the actual project conditions.

[0087] (31)

[0088] (32)

[0089] Where: and They are line Point-to-grid and grid-to-grid power components during the delivery period; , and Respectively The collection of hydropower stations, provinces and contract types associated with the line point-to-grid components, Adjustment of cascade hydropower contracts line Occupancy power during the delivery period.

[0090] Step 2: Adoption Solution method solves the power generation plan adjustment model.

[0091] The power generation plan adjustment model constructed in step 1 is essentially a chance constraint model, and there is no general method to directly solve it. Solution Method To solve the power generation plan adjustment model, the specific steps are as follows:

[0092] Step 2.1: Transform opportunity constraints into deterministic ones.

[0093] Monte Carlo simulation is used to convert the random variables in the power generation scheduling adjustment model into discrete runoff scenarios to approximate the random variables. The probability distribution of For independent and identically distributed runoff scenarios, the chance constraint (Equation (8)) is equivalently transformed into a mixed integer linear programming model such as Equations (33) to (35) through the SAA method, which is called the SAA model. As a deterministic model, the SAA model can be directly solved by the solver.

[0094] (33)

[0095] (34)

[0096] (35)

[0097] Where: is a 0-1 variable, express Hydropower Station Delivery period Water level of the scene Satisfy the control water level constraints, express Violation of constraints; is the risk level of the SAA problem.

[0098] Step 2.2: Solve the SAA model.

[0099] exist Medium uniform dispersion Click, get of value, denoted as , . Loop to find the risk level SAA model under the current cycle number is , The initial value of is set to 1, and the maximum number of cycles is , remember The optimal solution and optimal value of the SAA model in this solution are and , and As a candidate solution for the power generation schedule adjustment model.

[0100] Step 2.3: Verify the candidate solution feasibility.

[0101] For candidate solutions ,definition To destroy the chance constraint, i.e. the true probability of controlling the water level boundary in equation (8), generate Independent and identically distributed runoff scenarios are used as verification scenarios, and the definition for Verification scenario The estimated value of It is calculated by substituting the verification scenario into the SAA model; using formula (36) to calculate of Confidence upper bound , The risk level for verification.

[0102] (36)

[0103] Where: , which is a standard normal distribution Quantile, is the cumulative distribution function of the standard normal distribution.

[0104] when hour, exist The confidence level is verified as a feasible solution to the power generation plan adjustment model; hour, Verify infeasible solutions to the generation scheduling adjustment model.

[0105] Step 2.4: Determine the level of risk Statistical bounds on the optimal value.

[0106] Step 2.4.1: Determine the lower bound.

[0107] when When As the candidate lower bound of the optimal value of the power generation plan adjustment model, it is denoted as ;when hour, Not included in the candidate lower bound; judgment Is it equal to ,if , then the risk level The maximum value of all candidate lower bounds under this risk level is the final lower bound, denoted as , and go to step 2.4.2; if , then return to step 2.2 and let Add 1 and proceed to the next loop to solve.

[0108] Step 2.4.2: Determine the upper bound.

[0109] right indivual Sort, get , then Value exist The confidence level is the upper bound of the optimal value of the power generation plan adjustment model. The maximum integer that satisfies formula (38):

[0110] (37)

[0111] (38)

[0112] Where: represents a quantity defined by the cumulative distribution function of the binomial distribution; the symbol Indicates a definition relationship, meaning is well-defined as the expression on the right-hand side; the symbol Indicates rounding down; Represents the cumulative distribution function of the binomial distribution.

[0113] Step 2.5: Determine the final boundary of the generation schedule adjustment model.

[0114] judge Is it equal to ,if , then all risk levels Down The maximum value of is taken as the final lower bound of the power generation plan adjustment model, denoted as , all risk levels Down The average value of is taken as the final upper bound of the power generation plan adjustment model, denoted as , and go to step 2.6; if , then return to step 2.2 and let Add 1, Reset it to 1 and solve the SAA model at the next risk level.

[0115] Step 2.6: Determine the final contract adjustment plan.

[0116] Since the final lower bound is the best known verified feasible solution, the optimal solution of the SAA model corresponding to the final lower bound is selected. As the final contract adjustment plan.

[0117] The present invention has the following beneficial effects: the method for adjusting the annual power generation plan of cascade hydropower in advance under the power market environment provided by the present invention can jointly adjust the multi-variety annual contracts of cascade hydropower before the delivery month, give full play to the regulation ability of cascade hydropower and the mutual assistance ability of transmission lines, and ensure that the total revenue of cascade hydropower is improved on the basis of strict execution of priority contracts and effective execution of market-oriented contracts. The application of the present invention can effectively solve the problem of contract adjustment, and the proposed solution method can accelerate the acquisition of a feasible solution with high confidence on the basis of ensuring the accuracy of the solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0118] Figure 1 This is the runoff scenario generation result of Longtou Power Station, where (a) is the scenario with high runoff before the month, (b) is the scenario with moderate runoff before the month, and (c) is the scenario with low runoff before the month.

[0119] Figure 2 yes Flowchart of solution method;

[0120] Figure 3 This is the water level process of Longtou Power Station under different runoff and net adjustment rates in the previous month, among which (a) is high runoff and 0% net adjustment rate; (b) is high runoff and 5% net adjustment rate; (c) is high runoff and 10% net adjustment rate; (d) is moderate runoff and 0% net adjustment rate; (e) is moderate runoff and 5% net adjustment rate; (f) is moderate runoff and 10% net adjustment rate; (g) is low runoff and 0% net adjustment rate; (h) is low runoff and 5% net adjustment rate; (i) is low runoff and 10% net adjustment rate;

[0121] Figure 4 Figure 2 shows the adjustment of market-based contracts under different runoff and net adjustment rates before the month, where (a) is high runoff and a 5% net adjustment rate; (b) is moderate runoff and a 5% net adjustment rate; (c) is low runoff and a 5% net adjustment rate; (d) is high runoff and a 10% net adjustment rate; (e) is moderate runoff and a 10% net adjustment rate; (f) is low runoff and a 10% net adjustment rate. The gray area in each figure represents the net adjustment space of the contract.

[0122] Figure 5 It is an overall flow chart of the method of the present invention. DETAILED DESCRIPTION

[0123] The present invention is further described below in conjunction with the accompanying drawings and implementation examples.

[0124] The present invention is aimed at the cascade hydropower interprovincial transmission system composed of cascade power stations, transmission networks and power-consuming provinces, and formulates an adjustment plan for the cascade hydropower annual contract based on this. For ease of description, the present invention defines a DC line as a unidirectional line with unidirectional power flow, and an AC line as a bidirectional line with bidirectional power flow.

[0125] Project background and main parameter settings:

[0126] The following is an implementation of the present invention with the engineering background of the cascade hydropower inter-provincial transmission system consisting of five hydropower stations in the middle and lower reaches of the L River Basin in Y Province, Southwest China, multiple AC and DC lines and three sending and receiving end power grids. The L River Basin cascade power station includes five hydropower stations A, B, C, D, and E from upstream to downstream. Among them, A Hydropower Station is the leading power station, which undertakes the task of supply guarantee in Y Province. At the same time, as an important backbone power source for "West-to-East Power Transmission", it sends surplus electricity to G Province and X Province in the east for consumption through AC and DC lines. In the annual market, the contract varieties of cascade power stations are divided into priority contracts and market-oriented contracts, and the transmission methods are divided into "point-to-grid" and "grid-to-grid". The participation in the intra-provincial and inter-provincial markets is shown in Table 1. The electricity volume and electricity price of priority contracts and market-oriented contracts adopt the actual data of a certain year. Contract adjustments are arranged before January, and a 12-month adjustment plan is formulated throughout the year.

[0127] Table 1: Participation of hydropower stations in the intra-provincial and inter-provincial markets in the L basin

[0128]

[0129] The simulation generates three pre-month runoff scenarios: high, moderate, and low. The runoff scenario generation results for Longtou Power Station are shown in the figure below. Figure 1 shown.

[0130] The upper limits of the net contract adjustment rate under three pre-month runoff scenarios are set to 0%, 5% and 10%, and the transmission line adjustment capacities corresponding to the cascade hydropower are: , and , where 0% is used as the baseline model, and and Guaranteed contracts are not adjusted, including for The maximum transmission power of the line, Adjustment of the cascade hydropower contract line Occupancy power during the delivery period.

[0131] This embodiment provides a method for adjusting the annual power generation plan of cascade hydropower in advance under the power market environment. The process is as follows: Figure 5 As shown, the following steps are included:

[0132] Step 1: Construct a power generation plan adjustment model.

[0133] The constructed power generation plan adjustment model focuses on the inter-provincial transmission system of cascade hydropower. Cascade hydropower completes the power transmission of multiple provinces and multiple varieties of contracts through AC and DC lines. The contract adjustment takes into account the interests and operational needs of hydropower generation, inter-provincial transmission and provincial electricity consumption, involving complex water, electricity and market constraints. The specific steps include the following:

[0134] Step 1.1: Construct the objective function of the power generation plan adjustment model.

[0135] Under the market environment, the total revenue of cascade hydropower stations consists of contract revenue and energy storage revenue. Contract revenue refers to the power generation revenue obtained by cascade hydropower through annual contracts; energy storage revenue refers to the future power generation revenue of cascade hydropower storage at the end of the contract period. The essence of contract adjustment is to coordinate the current and future allocation of hydropower resources and weigh the decision of power generation and water storage. Therefore, starting from the interests of cascade hydropower, an objective function is constructed with the goal of maximizing the total revenue of cascade hydropower after contract adjustment, as shown in equations (1) and (2). In the equations, It is a collection of A, B, C, D, and E hydropower stations; is the collection of Province Y, Province G, and Province X; For collection ,in Indicates the preferred contract, represents a market-based contract; It is a collection of 12 months; for , for The same applies to other hydropower stations.

[0136] Step 1.2: Construct hydraulic constraints for the generation schedule adjustment model.

[0137] In order to meet the operational requirements of hydropower generation, the hydraulic constraints of the power generation plan adjustment model are constructed as shown in Equations (3) to (13).

[0138] Step 1.2.1: Construct the water balance equation.

[0139] The water balance equation is constructed as shown in equation (3)-(4). In equation (3), is an empty set, for The same applies to other hydropower stations.

[0140] Step 1.2.2: Construct water level boundary constraints.

[0141] The water level and storage capacity relationship is constructed as shown in formula (5), the initial water level constraint is constructed as shown in formula (6), and the physical water level boundary constraint is constructed as shown in formula (7). In order to control the risk of water level exceeding the limit of the hydropower station due to runoff uncertainty, the control water level boundary constraint is constructed as shown in formula (8), and the risk of violating the control water level boundary is modeled as an opportunity constraint to ensure that the water level is within the preset safety range with a certain probability level. The risk level of the opportunity constraint in formula (8) of this embodiment is is 0.05.

[0142] Step 1.2.3: Construct power generation function and output boundary constraints.

[0143] The power generation function is constructed as shown in formula (9), and the output boundary constraint is constructed as shown in formula (10).

[0144] Step 1.2.4: Construct flow boundary constraints.

[0145] The traffic boundary constraints are constructed as shown in Equations (11) to (13).

[0146] Step 1.3: Construct the power constraints of the generation schedule adjustment model.

[0147] Step 1.3.1: Construct node balance constraints.

[0148] Considering the power balance of each node in the transmission network, the node balance constraints are constructed as shown in Equations (14) to (16).

[0149] Step 1.3.2: Construct transmission capacity constraints.

[0150] Based on the occupancy of transmission lines in the original cascade hydropower contracts, the transmission capacity constraints are constructed as shown in Equations (17) to (20).

[0151] Step 1.3.3: Construct line perturbation constraints.

[0152] In order to manage the impact of cascade hydropower contract adjustments on transmission lines, the disturbance rate of one-way lines is defined as shown in formula (21), the forward disturbance rate of two-way lines is defined as shown in formula (22), the reverse disturbance rate of two-way lines is defined as shown in formula (23), and the disturbance rate constraints of one-way and two-way lines are shown in formula (24), so as to ensure that the transmission deviation before and after the contract adjustment is within the acceptable range of inter-provincial transmission. Since other lines are supporting lines for hydropower stations, no line disturbance constraints are set. The upper limit of the disturbance rate in formula (24) of this embodiment is and Both are 0.05.

[0153] Step 1.3.4: Construct the space constraints for absorption.

[0154] In order to ensure that the contract adjustment results of cascade hydropower meet the power consumption boundaries of the power-consuming provinces, the power consumption space constraints of the power-consuming provinces are constructed as shown in formula (25).

[0155] Step 1.4: Construct the market constraints for the generation schedule adjustment model.

[0156] Step 1.4.1: Construct the contract power matching constraint.

[0157] Considering the power matching of hydropower generation, provincial electricity consumption and market contracts, the constraints for matching hydropower generation and contract power are constructed as shown in formula (26), and the constraints for matching provincial electricity consumption and contract power are constructed as shown in formula (27).

[0158] Step 1.4.2: Construct contract adjustment constraints.

[0159] In order to minimize the impact of cascade hydropower contract adjustments on provincial electricity consumption, the net contract adjustment rate is defined as shown in formula (28). Due to the supply guarantee function of the priority contract, the priority contract adjustment constraint is constructed as shown in formula (29), and the net adjustment rate =0, ensuring strict execution of the priority contract. Due to the flexibility of market-based contracts, the market-based contract adjustment constraints are constructed as shown in formula (30), allowing the net adjustment rate The effective implementation of the market-based contract is ensured within the acceptable range of the electricity-consuming provinces. is 0.05.

[0160] Step 1.4.3: Construct transmission mode constraints.

[0161] In order to ensure the reliability and applicability of contract adjustment, the coupling relationship between the point-to-grid and grid-to-grid transmission modes and multi-province and multi-variety contracts is considered. The point-to-grid transmission mode constraint is constructed as shown in formula (31), and the grid-to-grid transmission mode constraint is constructed as shown in formula (32). The point-to-grid and grid-to-grid power components of the line make the contract adjustment results more in line with the actual project conditions.

[0162] Step 2: Adoption Solution method solves the power generation plan adjustment model.

[0163] The power generation plan adjustment model constructed in step 1 is essentially a chance constraint model, and there is no general method to directly solve it. Solution method: Solve the power generation plan adjustment model. The specific solution process is as follows: Figure 2 As shown, the specific steps are as follows:

[0164] Step 2.1: Transform opportunity constraints into deterministic ones.

[0165] Monte Carlo simulation is used to convert the random variables in the power generation scheduling adjustment model into discrete runoff scenarios to approximate the random variables. The probability distribution of For independent and identically distributed runoff scenarios, the chance constraint (Equation (8)) is equivalently transformed into a mixed integer linear programming model such as Equations (33) to (35) through the SAA method, which is called the SAA model. As a deterministic model, the SAA model can be directly solved by the solver.

[0166] Step 2.2: Solve the SAA model.

[0167] The model was solved using the Gurobi 10.0.1 solver in an Intel(R) Xeon(R) Gold 5315Y CPU 3.20 GHz, 16 GB RAM, and Win10 operating system computing environment. We evenly discretize 6 points in The six values ​​of , . Loop to find the risk level SAA model under the current cycle number is , The initial value of is set to 1, and the maximum number of cycles is , remember The optimal solution and optimal value of the SAA model in this solution are and , and As a candidate solution for the power generation schedule adjustment model.

[0168] Step 2.3: Verify the candidate solution feasibility.

[0169] For candidate solutions ,definition To destroy the chance constraint, i.e. the true probability of controlling the water level boundary in equation (8), generate Independent and identically distributed runoff scenarios are used as verification scenarios, and the definition for Verification scenario The estimated value of It is calculated by substituting the verification scenario into the SAA model; using formula (36) to calculate of Confidence upper bound , verified risk level is 0.05.

[0170] when hour, The feasible solution of the power generation schedule adjustment model is verified at a 95% confidence level; hour, Verify infeasible solutions to the generation scheduling adjustment model.

[0171] Step 2.4: Determine the level of risk Statistical bounds on the optimal value.

[0172] Step 2.4.1: Determine the lower bound.

[0173] when When As the candidate lower bound of the optimal value of the power generation plan adjustment model, it is denoted as ;when hour, Not included in the candidate lower bound; judgment Is it equal to ,if , then the risk level The maximum value of all candidate lower bounds under this risk level is the final lower bound, denoted as , and go to step 2.4.2; if , then return to step 2.2 and let Add 1 and proceed to the next loop to solve.

[0174] Step 2.4.2: Determine the upper bound.

[0175] right indivual Sort, get , then Value exist The confidence level is the upper bound of the optimal value of the power generation plan adjustment model. is the largest integer that satisfies equation (38).

[0176] Step 2.5: Determine the final boundary of the generation schedule adjustment model.

[0177] judge Is it equal to 6? , then all risk levels Down The maximum value of is taken as the final lower bound of the power generation plan adjustment model, denoted as , all risk levels Down The average value of is taken as the final upper bound of the power generation plan adjustment model, denoted as , and go to step 2.6; if , then return to step 2.2 and let Add 1, Reset it to 1 and solve the SAA model at the next risk level.

[0178] Step 2.6: Determine the final contract adjustment plan

[0179] Since the final lower bound is the best known verified feasible solution, the optimal solution of the SAA model corresponding to the final lower bound is selected. As the final contract adjustment plan.

[0180] Implementation results analysis:

[0181] 1) Effect analysis

[0182] Table 2 Figure 3 and Figure 4 They are the cascade hydropower revenues, the water level process of the leading power station and the market-based contract adjustments for different runoffs and net adjustment rates in different months. The results are all the final lower bounds, that is, the effects of the final contract adjustment plan.

[0183] Table 2: Cascade power station revenue under different runoff and net adjustment rates

[0184]

[0185] When the runoff is high before the month, Figure 3 It can be seen from (a)-(c) that under the three net adjustment rates, the final water level of the leading power station reaches the upper limit of the control water level, and the contract adjustment has little effect on the improvement of cascade energy storage. Figure 4 (a) and (d) show that under the two net adjustment rates, the market-based contracts in Provinces Y and G are both adjusted up to the maximum, reaching the upper limit of the contract revenue (in the original contract, the market-based contract for cascade hydropower in Province G only exists during the flood season, i.e., June-November).

[0186] When the runoff before the month is moderate, Figure 3 (d)-(f) show that, compared with 0% net adjustment rate, the final water level of Longtou Power Station increased by 21.16m to the upper limit of the control water level at 5% and 10%, and the increase of cascade energy storage benefits reached 7.66% and 7.49%; Figure 4 (b) and (e) show that under the two net adjustment rates, the market-based contracts in Province Y are adjusted to the maximum in the dry season and to the minimum in the flood season, while the market-based contracts in Province G are adjusted to the maximum in most months. This is because Province Y is a major hydropower province with low electricity prices during the flood season. When runoff is moderate, the market-based contracts in Province Y are lowered during the flood season and converted to cascade energy storage or market-based contracts in Province G.

[0187] When the runoff is low before the month, Figure 3 (g)-(i) show that, compared with 0% net adjustment rate, the final water level of Longtou Power Station increased by 31.40m and 33.45m respectively, and the cascade energy storage benefits increased by 10.44% and 11.18%; Figure 4(c) and (f) show that under the two net adjustment rates, the market-based contracts in Provinces Y and G are basically adjusted to the minimum, close to the lower limit of contract revenue. This is because when runoff is insufficient, the value of water used to replenish the leading power station to increase cascade energy storage is greater than the value of water used for power generation.

[0188] Therefore, under different pre-month runoff conditions, on the basis of ensuring the strict implementation of the priority contract, the water storage of the leading power station takes precedence over the market-based power transmission in Province G, and the market-based power transmission in Province G takes precedence over the market-based power transmission in Province Y. At the same time, it can be seen from Table 2 that with the decrease of pre-month runoff, the difference in the improvement rate of the total revenue of the cascade power stations under the 5% and 10% net adjustment rates gradually decreases, which also confirms that the water storage of the leading power station takes precedence over the market-based power transmission in various provinces.

[0189] In summary, the power generation plan adjustment model constructed by the present invention balances the interests and operational needs of hydropower generation, inter-provincial power transmission and provincial electricity consumption, effectively solves the problem of contract adjustment, and can give full play to the regulation capabilities of upstream and downstream cascade hydropower and the mutual assistance capabilities of its transmission channels. Under different runoff conditions, it can effectively improve the total revenue of cascade power stations on the basis of ensuring the strict execution of priority contracts and the effective execution of market-oriented contracts.

[0190] 2) Efficiency analysis

[0191] To verify the present invention The effectiveness and superiority of the solution method, taking the high pre-month runoff and the upper limit of the contract net adjustment rate of 5% as an example, the solution accuracy and speed of the model under different underlying parameters (including the number of iterations, the number of runoff scenarios and the risk level) are analyzed.

[0192] right The algorithm sets 3 iterations , 10 and 15, the number of three runoff scenarios , 150 and 250, and step 1 and step 2 are implemented for 9 combinations in turn. Table 3 shows the solution results of the model under different underlying parameters, which contains the upper and lower bounds of the optimal value of the power generation plan adjustment model and their gaps. The results show that the power generation plan adjustment model under different underlying parameters can obtain a smaller gap value, and the solution accuracy can be maintained within 1%, and with the number of runoff scenarios, the gap value is smaller than that of the original model. As the gap value increases, it gradually decreases, especially when , When , the gap value reaches 0.09%. Therefore, The solution method has high solution accuracy and can converge effectively.

[0193] Table 3: Solution results of the power generation plan adjustment model under different underlying parameters

[0194]

[0195] right Solution method settings , , implement steps 1 and 2. Table 4 shows the solution results of the power generation plan adjustment model under different SAA risk levels, where the feasible rate is the ratio of the optimal solution of the SAA model to the feasible solution of the power generation plan adjustment model, the feasible target value is the average value of the target value of the verified feasible solution, the single time consumption is the average time to solve a SAA model, and the single solution time consumption is the average time to obtain a verified feasible solution. The results show that the feasible target values ​​of the models under different SAA risk levels are not much different, but the single solution time consumption varies greatly. Most people choose , the feasibility rate of the SAA solution method is only 0.4%, and the single solution takes 4.86 hours; The feasibility rate of the SAA solution method is 3.2%, and the single solution takes only 0.53 hours. 11% of the solution time. Therefore, When using the solution method, you can first Accelerate the acquisition of high-confidence feasible solutions and then iterate step by step Get a better solution.

[0196] Table 4: Solution results of the power generation plan adjustment model under different SAA risk levels

[0197]

[0198] In summary, the calculation results show that the The solution method has higher solution accuracy under different underlying parameters. As a constant, it can speed up the acquisition of a feasible solution with high confidence while ensuring accuracy.

Claims

1. A method for adjusting the annual power generation plan of cascade hydropower in advance under the power market environment, characterized in that: The pre-month adjustment method includes: firstly, constructing a power generation plan adjustment model, modeling the interests and operation needs of hydropower generation, inter-provincial power transmission and provincial power consumption, introducing opportunity constraints to characterize the risk of water level exceeding the limit of hydropower stations due to runoff uncertainty, constructing two indicators, line disturbance rate and contract net adjustment rate, to manage the impact of contract adjustment on the transmission side and the power consumption side respectively, modeling the coupling relationship between the two types of transmission modes, point-to-grid and grid-to-grid, and multi-province and multi-variety contracts; then constructing Solution method: convert the power generation plan adjustment model into the SAA model and iteratively adjust the risk level of the SAA model , and verify the solution; finally, the contract adjustment plan for cascade hydropower is obtained.

2. The method for adjusting the annual power generation plan of cascade hydropower in the power market environment according to claim 1 is characterized in that: The pre-month adjustment method specifically includes the following steps: Step 1: Construct a power generation plan adjustment model; Step 1.1: Construct the objective function of the power generation plan adjustment model; Based on the interests of cascade hydropower, an objective function is constructed with the goal of maximizing the total revenue of cascade hydropower after contract adjustment: （1） （2） Where: is the total revenue of cascade hydropower; and They are Storage revenue and contract revenue from hydropower stations; , , and The contract types include preferred contracts and market-based contracts, and the delivery period is based on a monthly basis. for A collection of hydroelectric power stations and their upstream hydroelectric power stations; for The average annual water consumption rate of the hydropower station; and They are Hydropower Station Province The annual average electricity price and power delivery ratio of the contract type; and They are The final storage capacity and dead storage capacity of the hydropower station; , and They are Hydropower Station Province Contract Type The electricity price during the delivery period, the electricity before and after the contract adjustment; The number of seconds for each delivery period; Step 1.2: Construct hydraulic constraints for the power generation schedule adjustment model; Step 1.2.1: Construct the water balance equation; Construct the water balance equation: （3） （4） Where: for Hydropower Station Storage capacity at the end of the delivery period; , , and They are Hydropower Station The interval flow, outbound flow, power generation flow and abandoned water flow during the delivery period; for A collection of hydroelectric power stations directly upstream of the hydroelectric power station; for Hydropower Station Outbound flows during the delivery period; Step 1.2.2: Construct water level boundary constraints; The water level and storage capacity relationship is constructed as shown in formula (5), the initial water level constraint is constructed as shown in formula (6), and the physical water level boundary constraint is constructed as shown in formula (7): （5） （6） （7） Where: for Hydropower Station The water level above the dam at the end of the Delivery Period, hereinafter referred to as "Water Level"; for The relationship between the water level and reservoir capacity of a hydropower station is constructed using piecewise linear interpolation; and They are The initial water level of the hydropower station and its actual value; and They are Hydropower Station The upper and lower limits of the physical water level at the end of the delivery period; In order to control the risk of water level exceeding the limit of the hydropower station due to runoff uncertainty, the control water level boundary constraint is constructed as shown in formula (8). The risk of violating the control water level boundary is modeled as a chance constraint to ensure that the water level is within the preset safety range with a certain probability level; （8） In the formula, and They are Hydropower Station The upper and lower limits of the control water level at the end of the delivery period; The risk level for opportunity constraints; is probability; The random variables of the power generation plan adjustment model are , , , and , they are implicit functions of each other. To ensure the water storage safety of cascade hydropower, the final storage capacity Defined as a deterministic variable; Step 1.2.3: Construct power generation function and output boundary constraints; The power generation function is constructed as shown in formula (9), and the output boundary constraint is constructed as shown in formula (10): （9） （10） Where: for Hydropower Station Power generation output during the delivery period; for Hydropower Station Average water consumption rate during the delivery period; and They are The upper and lower limits of the hydropower station’s output; Step 1.2.4: Construct flow boundary constraints; Construct traffic boundary constraints: （11） （12） （13） Where: and They are Hydropower Station The upper and lower limits of outbound flow during the delivery period; and They are Hydropower Station The upper and lower limits of power generation flow during the delivery period; Step 1.3: Construct the power constraints of the power generation plan adjustment model; Step 1.3.1: Construct node balance constraints; Considering the power balance of each node in the transmission network, the nodes in the transmission network include hydropower stations, transmission lines and power-consuming provinces, and constructing node balance constraints: （14） （15） （16） Where: is the set of transmission lines, and we define For collection The index of the line in the middle includes unidirectional lines, bidirectional lines and other lines. Specifically, the DC line is defined as a unidirectional line with unidirectional power flow, the AC line is defined as a bidirectional line with bidirectional power flow, and the power plant transmission line is defined as other lines. , and They are the indexes of one-way lines, two-way lines and other lines respectively; is the set of all nodes in the transmission network, defined by equation (16), is the union symbol; is the index of the node; and Respectively The node provides input power and output power to the node set, both of which are sets A subset of When the node is a transmission line express node The transmission power during the delivery period is When the node is a hydropower station express node The power generation output during the delivery period, when The node is the power saving time express node The power consumption during the delivery period; Formula (14) expresses the energy balance relationship of each node; Step 1.3.2: Construct transmission capacity constraints; Based on the occupancy of transmission lines in the original cascade hydropower contracts, the transmission capacity constraints are constructed: （17） （18） （19） （20） Where: and They are before and after the adjustment of cascade hydropower contracts. One-way lines Occupancy power during the delivery period; and They are before and after the adjustment of cascade hydropower contracts. Two-way line Forward occupied power during the delivery period; and They are before and after the adjustment of cascade hydropower contracts. Two-way line Reverse occupied power during the delivery period; Adjustment of cascade hydropower contracts Other routes Occupancy power during the delivery period; for Transmission power caps for other lines; and When the contract is adjusted One-way lines The upward adjustment capacity of all market players and non-tiered players during the delivery period, and When the contract is adjusted Two-way line The upward adjustment capacity of all market players and non-cascade players during the delivery period; Formulas (17), (18) and (19) respectively express the available transmission capacity of one-way lines, two-way lines and other lines to cascade hydropower players when the contract is adjusted; Step 1.3.3: Construct line disturbance constraints; In order to manage the impact of cascade hydropower contract adjustment on transmission lines, the disturbance rate of unidirectional lines is defined as shown in formula (21), the forward disturbance rate of bidirectional lines is defined as shown in formula (22), the reverse disturbance rate of bidirectional lines is defined as shown in formula (23), and the disturbance rate constraints of unidirectional and bidirectional lines are shown in formula (24), so as to ensure that the transmission deviation before and after the contract adjustment is within the acceptable range of inter-provincial transmission; （21） （22） （23） （24） Where: Adjustment of cascade hydropower contracts before and after One-way lines The disturbance rate during the delivery period; , They are respectively before and after the adjustment of cascade hydropower contracts. Two-way line Forward and reverse disturbance rates during the delivery period; Adjustment of cascade hydropower contracts before and after The upper limit of the disturbance rate during a one-way line and a single delivery period, Adjustment of cascade hydropower contracts before and after The upper limit of the disturbance rate during a single delivery period of a two-way line; for The upper limit of transmission power on a unidirectional line, for The upper limit of transmission power for bidirectional lines; Step 1.3.4: Construct the space constraints for absorption; In order to ensure that the contract adjustment results of cascade hydropower meet the power consumption boundaries of power-consuming provinces, the power consumption space constraints of power-consuming provinces are constructed: （25） Where: express Province Electricity consumption during the delivery period, and Respectively Province The upper and lower limits of cascade hydropower consumption during the delivery period; Step 1.4: Construct the market constraints of the generation schedule adjustment model; Step 1.4.1: Construct the contract power matching constraint; Considering the power matching of hydropower generation, provincial electricity consumption and market contracts, the constraints of hydropower generation and contract power matching are constructed as shown in formula (26), and the constraints of provincial electricity consumption and contract power matching are constructed as shown in formula (27): （26） （27） Where: for Hydropower Station Power generation output during the delivery period; for Province The power consumption during the delivery period; Step 1.4.2: Construct contract adjustment constraints; In order to minimize the impact of cascade hydropower contract adjustment on provincial power supply, the contract adjustment constraints are constructed as shown in Equations (28) to (30); First, define the contract net adjustment rate as shown in formula (28); （28） Where: for Province Contract Type The net adjustment rate of the tiered contracts during the delivery period, and Right now and Represents the priority contract and market-based contract respectively. Province The net adjustment rate of the tiered contracts during the delivery period; Due to the supply guarantee function of the priority contract, the priority contract adjustment constraint is constructed as shown in formula (29): 0, ensuring strict execution of the priority contract; （29） Due to the flexibility of market-based contracts, the market-based contract adjustment constraints are constructed as shown in formula (30), allowing Ensure the effective implementation of market-based contracts within the acceptable range of electricity-consuming provinces; （30） Where: Adjustment of cascade hydropower contracts before and after The upper limit of the net adjustment rate of market-based contracts during the provincial delivery period; Step 1.4.3: Construct transmission mode constraints; In order to ensure the reliability and applicability of contract adjustment, the coupling relationship between the point-to-grid and grid-to-grid transmission modes and multi-province and multi-variety contracts is considered. The point-to-grid transmission mode constraint is constructed as shown in formula (31), and the grid-to-grid transmission mode constraint is constructed as shown in formula (32). The point-to-grid and grid-to-grid power components of the line make the contract adjustment results more consistent with the actual project situation; （31） （32） Where: and They are line Point-to-grid and grid-to-grid power components during the delivery period; , and Respectively The collection of hydropower stations, provinces and contract types associated with the line point-to-grid components, Adjustment of cascade hydropower contracts line Occupancy power during the delivery period; Step 2: Adoption Solution method solves the generation plan adjustment model; The power generation plan adjustment model constructed in step 1 is essentially a chance constraint model, and there is no general method to directly solve it. Solution Method To solve the power generation plan adjustment model, the specific steps are as follows: Step 2.1: Transform opportunity constraints into deterministic ones; Monte Carlo simulation is used to convert the random variables in the power generation scheduling adjustment model into discrete runoff scenarios to approximate the random variables. The probability distribution of For independent and identically distributed runoff scenarios, the chance constraint (Equation (8)) is equivalently transformed into a mixed integer linear programming model such as Equations (33)-(35) through the SAA method, which is called the SAA model. As a deterministic model, the SAA model can be directly solved by the solver; （33） （34） （35） Where: is a 0-1 variable, express Hydropower Station Delivery period Water level of the scene Satisfy the control water level constraints, express Violation of constraints; The risk level of the SAA problem; Step 2.2: Solve the SAA model; exist Medium uniform dispersion Click, get of value, denoted as , ; Loop to solve the risk level SAA model under the current cycle number is , The initial value of is set to 1, and the maximum number of cycles is , remember The optimal solution and optimal value of the SAA model in this solution are and , and As a candidate solution for the generation schedule adjustment model; Step 2.3: Verify the candidate solution feasibility; For candidate solutions ,definition To break the chance constraint, i.e. the true probability of controlling the water level boundary in equation (8), we calculate of Confidence upper bound , The risk level for verification; when hour, exist The confidence level is verified as a feasible solution to the power generation plan adjustment model; hour, Verify infeasible solutions to the model for adjusting generation schedules; Step 2.4: Determine the level of risk Statistical bounds on the lower optimum; Step 2.4.1: Determine the lower bound; when When As the candidate lower bound of the optimal value of the power generation plan adjustment model, it is denoted as ;when hour, Not included in the candidate lower bound; judgment Is it equal to ,if , then the risk level The maximum value of all candidate lower bounds under this risk level is the final lower bound, denoted as , and go to step 2.4.2; if , then return to step 2.2 and let Add 1 and proceed to the next loop to solve; Step 2.4.2: Determine the upper bound; right indivual Sort, get , then Value exist The confidence level is the upper bound of the optimal value of the power generation plan adjustment model. is the largest integer satisfying formula (38); （37） （38） Where: represents a quantity defined by the cumulative distribution function of the binomial distribution; the symbol Indicates a definition relationship, meaning is well-defined as the expression on the right-hand side; the symbol Indicates rounding down; represents the cumulative distribution function of the binomial distribution; Step 2.5: Determine the final boundary of the generation schedule adjustment model; judge Is it equal to ,if , then all risk levels Down The maximum value of is taken as the final lower bound of the power generation plan adjustment model, denoted as , all risk levels Down The average value of is taken as the final upper bound of the power generation plan adjustment model, denoted as , and go to step 2.6; if , then return to step 2.2 and let Add 1, Reset it to 1 and solve the SAA model at the next risk level; Step 2.6: Determine the final contract adjustment plan; Since the final lower bound is the best known verified feasible solution, the optimal solution of the SAA model corresponding to the final lower bound is selected. As the final contract adjustment plan.

3. The method for adjusting the annual power generation plan of cascade hydropower in the power market environment according to claim 2 is characterized in that: In step 2.3, calculate The specific process is: generate Independent and identically distributed runoff scenarios are used as verification scenarios, and the definition for Verification scenario The estimated value of It is obtained by substituting the verification scenario into the SAA model; it is calculated using formula (36) of Confidence upper bound ; （36） Where: , which is a standard normal distribution Quantile, is the cumulative distribution function of the standard normal distribution.

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