A reservoir optimal operation method for scheduling plans

Abstract

The present invention provides a reservoir optimal scheduling method for scheduling plans, which relates to the technical field of reservoir multi-task coordination. The method includes randomly generating multiple groups of monthly power generation plans; calculating the available power generation water volume of the reservoir by calculating the initial reservoir storage; dynamically calculating the power generation water volume by using Newton interpolation method and improved Powell method; respectively calculating the ecological water supply volume, urban water supply volume and agricultural water supply volume; calculating the objective function for the power generation plans that meet the constraint conditions; in response to the comparison of power generation targets when the water shortage targets are equal, obtaining the global optimal and individual optimal power generation plans of each generation by comparing the objective function values; for reaching the maximum number of iterations, based on the global optimal and individual optimal power generation plans of each generation, obtaining the optimal power generation plan that meets the constraint conditions. The present invention solves the problem of mismatch between power generation plans and water supply plans in actual scheduling management.

Description

Technical Field

[0001] The present invention belongs to the technical field of reservoir multi-task coordination, and particularly relates to a reservoir optimal operation method for a scheduling plan. Background Art

[0002] With the development of the economic society and the acceleration of urbanization, the contradiction between the supply and demand of regional water resources has become increasingly prominent. How to coordinate multiple tasks of the reservoir has become a key issue in the operation of the reservoir. The scheduling plan generally includes a power generation plan and a water supply plan. In actual management, the power generation plan and the water supply plan are usually responsible for different departments. The former is usually issued by the power grid, and the latter is formulated by the water administrative department. It is difficult to comprehensively consider the competition relationship between power generation and water supply. For example, an unreasonable power generation plan may lead to the inability to meet the water supply plan, resulting in certain risks in the implementation of the scheduling plan. Therefore, it is very important to comprehensively consider the competition relationship between power generation and water supply in the total water use and process, and to formulate a reasonable reservoir scheduling plan.

[0003] To optimize the matching of the reservoir power generation plan and the water supply plan, it is necessary to fully combine the differences and commonalities of power generation and water supply. In terms of differences, the power generation scheduling has autonomous flexibility, aiming to obtain the maximum benefit under the same water inflow conditions. Therefore, it tends to operate at a high water level, so as to achieve a greater power generation benefit with less discharged water volume. Therefore, when the reservoir storage is insufficient, the power generation water volume will be reduced. The reservoir water supply scheduling has a deterministic goal, and its water supply process is determined by the water demand process of users. Water is supplied according to the storage requirements to ensure water use safety. In terms of commonalities, both need to control the reservoir storage too high or too low, causing damage or benefit loss. On the one hand, it is to consider the subsequent period effect to avoid damage caused by too little storage, and on the other hand, to avoid waste of water and loss of benefits caused by too much storage. Therefore, combining the characteristics of water inflow to reasonably allocate the water supply process, so that the reservoir storage drops reasonably during the scheduling period, and minimizing water waste and water supply damage as much as possible is the core of the scheduling plan formulation. Therefore, the difficulty in formulating the reservoir scheduling plan lies in how to comprehensively consider the differences and commonalities of the power generation and water supply processes, and coordinate the coordination relationship between the two in the total water use, water use process and storage process.

[0004] Analyze the matching of the power generation plan and the water supply plan according to the principle of "power dispatch obeys water dispatch". When the implementation of the power generation plan causes damage to the social and economic water use, it is necessary to adjust the power generation plan. The key to coordinating power generation and water supply lies in adjusting the power generation process. When the water supply plan cannot be met, the power generation plan of the current period can be adjusted, directly increasing the discharged water volume during the water shortage period, or the power generation plan of the previous period can be adjusted. On the one hand, reducing the power generation water volume in the previous period and increasing the available water volume in the subsequent period, and at the same time maintaining a certain head difference to reduce the loss of power generation benefits. Therefore, how to determine the adjustment period and adjustment amount of the power generation plan is the difficulty of this method.

[0005] In the prior art, the PA-DDS algorithm is introduced into the multi-objective optimization model considering water supply and power generation, and the reservoir operation chart is optimized with the maximum water supply benefit and the maximum power generation as the objective functions. The research results are applicable to the reservoir engineering planning and the formulation stage of operation rules, but lack the research on how to coordinate the power generation plan and the water supply plan in the actual operation management. Therefore, the reservoir optimal operation needs to be based on the actual needs, aiming to reduce the impact of the operation plan, analyze the optimal operation mode, improve the matching of power generation and water supply in the total water consumption and the process, and support the formulation and actual operation of the reservoir operation plan. Its existing disadvantages are as follows:

[0006] The reservoir optimal operation mainly focuses on how to maximize the power generation benefit of the reservoir, lacks the research on how to coordinate the power generation plan and the water supply plan in the actual operation management, and does not consider the coordination of the operation plan in the actual reservoir operation management. Summary of the Invention

[0007] In view of the above deficiencies in the prior art, the present invention provides a reservoir optimal operation method for the operation plan, aiming to improve the matching of the power generation plan and the water supply plan in the total water consumption and the water consumption process on the basis of minimizing the adjustment of the original plan.

[0008] In order to achieve the above object, the technical solution adopted by the present invention is: a reservoir optimal operation method for the operation plan, comprising the following steps:

[0009] S1. Randomly generate multiple groups of monthly power generation plans;

[0010] S2. Calculate the available power generation water volume of the reservoir by calculating the initial reservoir storage;

[0011] S3. Based on the available power generation water volume of the reservoir and the power generation plan, use the Newton interpolation method and the improved Powell algorithm Powell to dynamically calculate the power generation water volume;

[0012] S4. Calculate the ecological water supply volume, the urban water supply volume and the agricultural water supply volume respectively based on the power generation water volume;

[0013] S5. Calculate the objective function of the power generation plan that meets the constraint conditions according to the calculated ecological water supply volume, urban water supply volume and agricultural water supply volume;

[0014] S6. Determine whether the maximum calculation period is reached. If so, go to step S7; otherwise, return to step S2;

[0015] S7. Based on the principle that the power dispatch obeys the water dispatch, when the water shortage targets are equal, compare the power generation targets, and obtain the global optimal and individual optimal power generation plans of each generation by comparing the objective function values in step S5;

[0016] S8. Determine whether the maximum number of iterations is reached. If so, obtain the optimal power generation plan that satisfies the constraint conditions based on the global optimal and individual optimal power generation plans of each generation. Otherwise, update the power generation plan based on the global optimal and individual optimal power generation plans of each generation, along with the evolution speed and direction, and the evolved power generation plan, and return to step S2 until the maximum number of iterations is reached.

[0017] The beneficial effect of the present invention is that by substituting the power generation plan into the reservoir water supply process to screen the optimal power generation plan that satisfies the constraint conditions, on the basis of minimizing the adjustment of the original plan, the matching degree of the power generation plan and the water supply plan in terms of the total water consumption and the water consumption process is improved.

[0018] Furthermore, the expression for the available power generation water volume of the reservoir is as follows:

[0019]

[0020]

[0021]

[0022] Wherein, represents the available power generation water volume of the reservoir in the represents initial reservoir storage volume in the represents reservoir leakage water volume in the represents the power generation water intake limit storage volume, represents final reservoir storage volume in the represents the reservoir leakage coefficient, represents the dead storage volume of the reservoir, represents inflow water volume in the

[0023] The beneficial effect of the above further solution is that the present invention calculates the available water volume for power generation to avoid the reservoir water storage volume exceeding the power generation limit storage volume after power generation.

[0024] Still further, step S3 includes the following steps:

[0025] S301. Calculate the divided differences of the Newton interpolation polynomial;

[0026] S302. Based on the divided differences of the Newton interpolation polynomial, derive the functional relationship between the water level and the reservoir storage volume;

[0027] S303. Based on the functional relationship between the water level and the reservoir storage volume, dynamically calculate the power generation water volume using the improved Powell algorithm Powell.

[0028] The beneficial effects of the above further solution are as follows: The generated water volume calculated by the present invention depends on various factors such as the power generation plan for each period, the reservoir water storage volume, the storage water level, and the storage capacity curve. Among them, the Newton interpolation method is used to solve the corresponding water level for a known storage capacity; the power generation tail water level is a function of the generated water volume. In order to solve the high-order equation, the improved Powell method is used to calculate the generated water volume.

[0029] Furthermore, the expression of the divided difference of the Newton interpolation polynomial is as follows:

[0030]

[0031] Wherein, represents the function at the point the -th divided difference, represents the storage capacity data at represents the function at the point the -th divided difference, represents the storage capacity data at represents the first storage capacity data, represents the function at the point the -th divided difference;

[0032] The functional relationship between the water level and the storage capacity is as follows:

[0033]

[0034]

[0035]

[0036]

[0037] Wherein, represents the function of the water level with respect to the storage capacity, represents the water level corresponding to the first storage capacity data, represents the reservoir storage capacity, represents the storage capacity data at , , represent the coefficients of the Newton interpolation polynomial, represents the water level corresponding to the storage capacity data at sequence 1, represents the storage capacity data at sequence 1, represents the function at the point The first-order divided difference at represents the water level corresponding to the reservoir capacity data at sequence 2, represents the reservoir capacity data at sequence 2, represents the function at the point The first-order divided difference at represents the function at the point The second-order divided difference at

[0038] The beneficial effect of the above further scheme is that: using the Newton interpolation method to solve the functional relationship between the water level and the reservoir capacity can efficiently utilize the existing data points, gradually construct a polynomial through difference calculation to achieve high-precision fitting, and at the same time facilitate the dynamic update of newly added data points to ensure the accuracy of the water level-reservoir capacity relationship.

[0039] Furthermore, based on the functional relationship between the water level and the reservoir capacity, the improved Powell algorithm Powell is used to dynamically calculate the power generation water volume, and the specific steps are as follows:

[0040] Initialization operation: Select the initial estimate Perform iteration on Set the solution accuracy ; Set the initial direction vector , where represents The power generation water volume in the time period, and

[0041] Construct the objective function: Based on the power generation water volume, use the following formula to construct the objective function. The constructed objective function is to find the that is closer to 0 :

[0042]

[0043] where represents The power generation water volume in the th iteration of the time period, represents The objective function value when dynamically solving the power generation water volume in the time period and the th iteration, represents

[0044] Linear search: Conduct a one-dimensional search along the direction to find a new point such that is close to 0;

[0045] Update direction: Determine the direction based on the linear search result Value;

[0046] Check for convergence: Judge the new function value Whether it is less than the precision , if so, stop the iteration and output based on the update result as the solution, that is, the generated water volume, otherwise, return to the linear search step.

[0047] The beneficial effect of the above further solution is: The present invention realizes the iterative evolution of the generated water volume, determines the generated water volume that meets the power generation plan, and judges whether the judgment precision for ending the iteration is reached by solving the objective function value, and can realize the solution of the required generated water volume based on the power generation plan.

[0048] Furthermore, the expression of the linear search is as follows:

[0049]

[0050]

[0051] Wherein, represents the generated water volume at the th iteration in the time period, represents the generated water volume at the th iteration in the time period, represents the search direction at the th iteration, represents the planned power generation in the time period, represents the initial reservoir capacity in the time period, represents the functional relationship between the water level and the reservoir capacity, represents the functional relationship between the tail water level of power generation and the generated water volume,

[0052] Furthermore, the expression of the update direction is as follows:

[0053]

[0054] Wherein, represents the generated water volume at the th iteration in the time period, represents the generated water volume at the Indicates the search direction for the th iteration.

[0055] Furthermore, the expression for the ecological water supply is as follows:

[0056]

[0057] Where, represents the ecological water supply volume for the time period, represents the power generation water volume for the time period, represents the initial reservoir capacity for the time period, represents the planned ecological water supply volume for the time period, represents the actual available water volume after reservoir power generation for the

[0058] The expression for the urban water supply is as follows:

[0059]

[0060] Where, represents the urban water supply volume for the time period, represents the remaining available urban water volume from the power generation tail water after ecological water supply update for the time period, represents the planned urban water supply volume for the is the remaining available urban water storage volume after the water storage volume for the

[0061] The expression for the agricultural water supply is as follows:

[0062]

[0063] Where, represents the agricultural water supply volume for the time period, represents the remaining available agricultural irrigation water volume from the power generation tail water after update for the time period, represents the planned agricultural water supply volume for the time period, represents the remaining available agricultural water storage volume after the water storage volume for the

[0064] The beneficial effects of the above further solution are as follows: This process realizes the distribution of the tail water volume of power generation according to the priorities of ecology, urban areas, and agriculture, avoiding the situation where the allocated water volume exceeds the tail water volume or the planned volume.

[0065] Furthermore, the objective function in step S5 includes:

[0066] Taking the minimum of the ecological water shortage, urban water shortage, and agricultural water shortage as the objective function:

[0067]

[0068] Wherein, represents the water shortage of the water user, represents the classification code of the water user, where the in-river ecological user is 1, the urban user is 2, and the agricultural user is 3, represents the water supply planned volume of the water user in the time period, represents the water supply volume of the water user in the time period;

[0069] Taking the minimum of the power generation plan deviation as the objective function:

[0070]

[0071] Wherein, represents the power generation plan deviation, which is expressed as the sum of the squares of the ratio of the difference between the actual power generation and the planned power generation to the planned power generation, represents the actual power generation in the time period, represents

[0072] The beneficial effects of the above further solution are as follows: The present invention determines the objective function from two directions of the water supply plan and the power generation plan, combines with the particle swarm algorithm to determine the global optimal solution and the individual optimal solution, and iteratively evolves the power generation plan.

[0073] Furthermore, the expressions for the evolution speed and direction in step S7 are as follows:

[0074]

[0075] The expression for the evolved power generation plan is as follows:

[0076]

[0077] Wherein, represents the th particle in the The velocity component in the represents the inertia weight, represents the -th particle in the iteration, the velocity component in the -th dimension, and both represent the learning factors, represents a random number between 0 and 1, represents the individual optimal particle, is the global optimal particle, represents the -th particle in the iteration, the position component in the -th dimension, represents the -th particle in the iteration, the position component in the -th dimension, and the particle is the power generation plan.

[0078] The beneficial effects of the above further solution are as follows: The present invention optimizes the reservoir operation for the scheduling plan, targets at minimizing the water shortage of water users and the deviation degree from the power generation plan based on algorithms (such as the particle swarm optimization algorithm), takes the monthly power generation plan as the decision variable, and determines the final power generation plan through iterative calculation, so as to improve the matching of power generation and water supply in the total water consumption and process. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 is the flowchart of the method of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0080] The following describes the specific embodiments of the present invention to facilitate those skilled in the art to understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions made using the concept of the present invention are within the scope of protection.

[0081] Embodiment

[0082] There are mainly two modes for reservoir power generation and water supply. One is the sharing of the power generation and water supply processes, where the water volumes of the two do not overlap. The other is the coupling of the power generation and water supply processes, where the tail water from power generation is used for users such as urban water supply, agricultural irrigation, and in-river ecology. Both combination methods need to consider the matching of the power generation plan and the water supply plan in terms of total volume and process. However, relatively speaking, the coupling method of power generation and water supply has a dual relationship of both water use competition and cooperation, and the influencing factors of the transfer of power generation and water supply benefits are more complex. Therefore, this invention mainly analyzes the optimal reservoir operation method for the scheduling plan based on the coupling mode of power generation and water supply processes. This invention is applicable to the coupling mode of power generation and water supply processes, where the tail water from power generation is used for users such as urban water supply, agricultural irrigation, and in-river ecology. This invention is based on actual needs, aims to reduce the impact of the scheduling plan, analyzes the optimal operation method, improves the matching of power generation and water supply in terms of total water use volume and process, and supports related work such as the formulation and actual operation of the reservoir scheduling plan. As Figure 1 shown, this invention provides an optimal reservoir operation method for the scheduling plan, and its implementation method is as follows:

[0083] S1. Randomly generate multiple groups of monthly power generation plans;

[0084] In this embodiment, randomly generate n groups of monthly power generation plans , where represents the power generation plan for the 12th month of the th particle, and represents the total power generation plan group.

[0085] S2. Calculate the available water volume for power generation in the reservoir by calculating the initial reservoir storage;

[0086] In this embodiment, calculate the initial reservoir storage, as shown in formula (1):

[0087] (1)

[0088] Calculate the reservoir leakage water volume, as shown in formula (2):

[0089] (2)

[0090] Calculate the available water volume for power generation in the reservoir, as shown in formula (3):

[0091] (3)

[0092] Among them, represents the available water volume for power generation in the reservoir during the period, represents the initial reservoir storage during the The reservoir leakage water volume during the time period represents the power generation water intake restricted storage capacity represents the end storage capacity during the time period represents the reservoir leakage coefficient represents the dead storage capacity of the reservoir represents the water inflow volume into the reservoir during the time period

[0093] S3. Based on the available power generation water volume of the reservoir and the power generation plan, use the Newton interpolation method and the improved Powell algorithm Powell to dynamically calculate the power generation water volume. The implementation method is as follows:

[0094] S301. Calculate the divided differences of the Newton interpolation polynomial

[0095] S302. Based on the divided differences of the Newton interpolation polynomial, deduce the functional relationship between the water level and the storage capacity

[0096] S303. Based on the functional relationship between the water level and the storage capacity, use the improved Powell algorithm Powell to dynamically calculate the power generation water volume. Specifically:

[0097] Initialization operation: Select the initial estimate value for to perform iteration; Set the solution accuracy ; Select the initial direction vector , where represents the power generation water volume during the time period represents the initial estimate value of the power generation water volume

[0098] Construct the objective function: Based on the power generation water volume, construct the objective function. Among them, the constructed objective function is to find the that is closer to 0 , where represents the objective function value during the time period when dynamically solving the power generation water volume for the th iteration, represents the power generation water volume during the time period

[0099] Linear search: Perform a one-dimensional search along the directionto find a new point such that is close to 0

[0100] Update the direction: Based on the linear search result, determine the value of the direction ;

[0101] Check for convergence: Judge the new function value Whether it is less than the precision , if so, stop the iteration and output as the solution, that is, the power generation water volume; otherwise, return to the linear search step.

[0102] In this embodiment, the power generation water volume is calculated. The reservoir power generation water volume is dynamically calculated based on the reservoir water storage and the power generation plan. The power generation output formula (4) is converted into the power generation water volume calculation formula (5).

[0103] (4)

[0104] (5)

[0105] Among them, represents the power generation output or the power generation plan; represents the power generation water volume in the time period; represents the power generation head difference, which is calculated according to the formula (6); A represents the power generation output coefficient of the power station, generally taken as 8.5, and the value can be determined based on the actual situation of the power station:

[0106] (6)

[0107] (7)

[0108] (8)

[0109] The formula (6) is the power generation head calculation formula, represents the average upstream water level of the hydropower station, represents the average downstream water level of the hydropower station, represents the head loss. The formula (7) is the water level - storage capacity curve formula, is the initial storage capacity in the time period. The formula (8) is the downstream water level - discharge curve formula, represents the reservoir water volume in the time period.

[0110] Substitute the formulas (6) - (8) into the formula (5) to obtain the power generation water consumption calculation formula (9):

[0111] (9)

[0112] Among them, represents the power generation water volume in the time period; represents the planned power generation in the time period; represents the initial storage capacity in the time period; represents the head loss.

[0113] As can be seen from formula (9), the power generation water volume depends on various factors such as the power generation plan for each period, the reservoir water storage volume, the storage water level, and the storage capacity curve. Among them, the Newton interpolation method is used to solve the average upstream water level under a known storage capacity; the power generation tail water level is a function of the power generation water volume. Therefore, there are unknowns of the power generation water volume on both sides of the equal sign in formula (9). In order to solve the high-order equation, the improved Powell algorithm Powell is used to calculate the power generation water volume.

[0114] (1) Solution process of the Newton interpolation method

[0115] The known storage capacity data of the water level-storage capacity curve are: , and the corresponding water level data are: , and the functional relationship between the water level and the storage capacity is .

[0116] 1) First, calculate the divided differences of the Newton interpolation polynomial. Define the function The first-order divided difference of the function at the point is shown in formula (10). Define the function The second-order divided difference of the function at the point is shown in formula (11). And so on, define the at the point of the -order divided difference as shown in formula (12):

[0117] (10)

[0118] (11)

[0119] (12)

[0120] 2) Deduce the functional relationship between the water level and the storage capacity. The Newton interpolation polynomial is shown in formula (13):

[0121] (13)

[0122] In the formula, from we get ; from we get ; from we get ; and so on. All the coefficients of the Newton interpolation formula can be obtained from the definition of the divided difference and mathematical induction, and substituting them into formula (13) we get the functional relationship between the water level and the storage capacity, as shown in formula (14):

[0123] (14)

[0124] Among them, represents the function The th order divided difference quotient, denotes the reservoir capacity data at denotes the function at the point the th order divided difference quotient, denotes the reservoir capacity data at denotes the first reservoir capacity data, denotes the function at the point the th order divided difference quotient, denotes the water level as a function of reservoir capacity, denotes the reservoir capacity of the reservoir, denotes the first reservoir capacity data, denotes the function at the point the th order divided difference quotient, denotes the reservoir capacity data at , , denotes the coefficients of the Newton interpolation polynomial, denotes the water level corresponding to the reservoir capacity data at sequence 1, denotes the reservoir capacity data at sequence 1, denotes the function at the point the first order divided difference quotient, denotes the water level corresponding to the reservoir capacity data at sequence 2, denotes the reservoir capacity data at sequence 2, denotes the function at the point the first order divided difference quotient, denotes the function at the point the second order divided difference quotient.

[0125] (2)Solution process of the improved Powell method

[0126] 1) Initialization: ① Select a reasonable initial estimate for iteration; ② Set the solution accuracy ; ③ Select the initial direction vector , denotes the water volume for power generation in the Represents the initial estimate of the water volume for power generation, which can be the available water volume.

[0127] 2) Construct the objective function: Define the objective function as shown in Equation (15). The constructed objective function is to find the one that makes closer to 0:

[0128] (15)

[0129] Where, Represents the objective function when dynamically solving the water volume for power generation, Represents The planned power generation volume in the Represents the head loss, Represents the power generation output coefficient of the power station, Represents the functional relationship between water level and reservoir capacity, Represents the average water level upstream of the hydropower station, Represents the functional relationship between the tail water level for power generation and the water volume for power generation.

[0130] 5) Line search: Conduct a one-dimensional search along the direction to find a new point such that is closer to 0:

[0131] (16)

[0132] (17)

[0133] Where, Represents The water volume for power generation at the th iteration in the Represents The water volume for power generation at the th iteration in the Represents the search step size, Represents the search direction at the th iteration, Represents The planned power generation volume in the Represents The initial reservoir capacity in the Represents the functional relationship between water level and reservoir capacity, Represents the functional relationship between the tail water level for power generation and the water volume for power generation, Represents the head loss.

[0134] 6) Update the direction: Calculate the new function value , and the direction update formula is shown in Equation (18):

[0135] (18)

[0136] Among them, represents the generated water volume at the -th iteration of the time period, represents the generated water volume at the -th iteration of the time period, represents the search direction at the -th iteration.

[0137] 7) Check for convergence: If , then stop the iteration and output as the solution.

[0138] S4. Based on the generated water volume, calculate the ecological water supply, urban water supply, and agricultural water supply respectively;

[0139] (1) Ecological water supply

[0140] The tail water of power generation gives priority to ensuring the ecological flow downstream. However, when the reservoir water storage reaches the power generation water intake limit storage capacity, the water storage exceeding the dead storage capacity can continue to supply the ecology, as shown in formula (19):

[0141] (19)

[0142] Among them, represents the ecological water supply volume in the time period, represents the generated water volume in the time period, represents the initial storage capacity in the time period, represents the power generation water intake limit storage capacity, represents the ecological water supply planned volume in the time period, represents the actual available water volume after reservoir power generation in the time period.

[0143] (2) Urban water supply

[0144] Considering the importance of off - river users, calculate the water supply volume in the order of giving priority to urban water supply and then agricultural irrigation. The calculation of urban water supply is shown in formula (20):

[0145] (20)

[0146] Among them, represents the urban water supply volume in the time period, represents the remaining available water volume for urban use from the tail water of power generation after the update of ecological water supply in the -th time period, denote The planned urban water supply volume for a time period is The urban water storage volume that can still be supplied after the water storage volume in a time period reaches the power generation water intake limit reservoir capacity

[0147] (3)Agricultural water supply

[0148] After the urban water supply is completed, update the remaining water volume of the power generation tail water. The agricultural water supply is calculated as shown in formula (21):

[0149] (21)

[0150] Wherein denote The agricultural water supply volume for a time period denote after update The remaining agricultural irrigation water volume that can be supplied by the power generation tail water in a time period denote The planned agricultural water supply volume for a time period denote The agricultural water storage volume that can still be supplied after the water storage volume in a time period reaches the power generation water intake limit reservoir capacity

[0151] S5. According to the calculated ecological water supply, urban water supply and agricultural water supply, calculate the objective function for the power generation plan that meets the constraint conditions

[0152] In this embodiment, (1) The minimum water shortage

[0153] Take the minimum ecological, urban and agricultural water shortages as the objective function

[0154] (22)

[0155] Wherein denote the water shortage of the water user denote the classification code of the water user, where the in-river ecological user is 1, the urban user is 2, and the agricultural user is 3 denote the water user in the planned water supply volume of the water user in a time period denote the water user in the water supply volume of the water user in a time period

[0156] (2)The minimum deviation of the power generation plan

[0157] To ensure the stability of the power grid, it is necessary to minimize the adjustment range of the power generation plan. Therefore, take the minimum deviation of the power generation plan as the objective function

[0158] (23)

[0159] Among them, represents the deviation degree of the power generation plan, which is expressed by the sum of squares of the ratio of the difference between the actual power generation and the planned power generation to the planned power generation. represents the actual power generation in the represents the planned power generation in the

[0160] S6. Determine whether the maximum calculation period is reached. If so, go to step S7; otherwise, return to step S2.

[0161] S7. Based on the principle that the electric power dispatching obeys the water resources dispatching, when the water shortage targets are equal, compare the power generation targets, and obtain the global optimal and individual optimal power generation plans for each generation by comparing the objective function values in step S5.

[0162] In this embodiment, in accordance with the principle of "the electric power dispatching obeys the water resources dispatching", during the optimization process, the water shortage targets are compared preferentially. When the water shortage targets are equal, the power generation targets are compared, and the global optimal and individual optimal power generation plans for each generation are selected according to the comparison of the objective function.

[0163] S8. Determine whether the maximum number of iterations is reached. If so, based on the global optimal and individual optimal power generation plans for each generation, obtain the optimal power generation plan that meets the constraint conditions; otherwise, update the power generation plan based on the global optimal and individual optimal power generation plans for each generation, with the evolution speed and direction, and the evolved power generation plan, and return to step S2 until the maximum number of iterations is reached.

[0164] In this embodiment, determine whether the maximum number of iterations is reached. If not, update the evolution speed and direction of the power generation plan and the evolved power generation plan based on the particle swarm optimization algorithm. The velocity and position update formulas are shown in formulas (24) and (25). Start cycling from step S2 until the maximum number of iterations of the particle swarm optimization algorithm is reached. At this time, terminate the operation and output the optimal power generation plan that meets the constraint conditions:

[0165] (24)

[0166] (25)

[0167] Among them, represents the velocity component of the th particle in the th iteration in the th dimension, represents the inertia weight, represents the velocity component of the th particle in the th iteration in the th dimension, and both represent the learning factors. Represents a random number between 0 and 1, Represents the individual optimal particle, Is the global optimal particle, Represents the th particle at the th iteration, the dimensional position component, Represents the th particle at the th iteration, the dimensional position component, and the particle is a power generation plan.

[0168] In this embodiment, other optimization methods can be used, such as genetic algorithms, simulated annealing algorithms, etc.

Claims

1. A reservoir optimal operation method for scheduling plans, characterized in that It includes the following steps: S1. Randomly generate multiple groups of monthly power generation plans; S2. Calculate the available power generation water volume of the reservoir by calculating the initial reservoir storage; S3. Based on the available power generation water volume of the reservoir and the power generation plan, use Newton interpolation method and the improved Powell algorithm (Powell) to dynamically calculate the power generation water volume; S4. Based on the power generation water volume, calculate the ecological water supply volume, urban water supply volume and agricultural water supply volume respectively; S5. According to the calculated ecological water supply volume, urban water supply volume and agricultural water supply volume, calculate the objective function for the power generation plan that meets the constraint conditions; The objective function includes: Taking the minimum of ecological water shortage, urban water shortage and agricultural water shortage as the objective function: Among them, represents the water shortage of water users, represents the classification code of water users, where the in-river ecological users are 1, urban users are 2, and agricultural users are 3, represents the water supply planned volume of water users during the period, represents the water supply volume of water users during the period; Taking the minimum deviation of the power generation plan as the objective function: Among them, represents the deviation degree of the power generation plan, which is expressed as the sum of squares of the ratio of the difference between the actual power generation and the planned power generation to the planned power generation. represents the actual power generation in the represents planned power generation in the S6. Judge whether the maximum calculation period is reached. If so, enter step S7; otherwise, return to step S2; S7. Based on the principle that power dispatch obeys water dispatch, when the water shortage objectives are equal, compare the power generation objectives, and obtain the global optimal and individual optimal power generation plans for each generation by comparing the objective function values in step S5; S8. Judge whether the maximum number of iterations is reached. If so, based on the global optimal and individual optimal power generation plans for each generation, obtain the optimal power generation plan that meets the constraint conditions; otherwise, update the power generation plan based on the global optimal and individual optimal power generation plans for each generation, with the evolution speed and direction, and the evolved power generation plan, and return to step S2 until the maximum number of iterations is reached.

2. The reservoir optimal operation method for scheduling plan according to claim 1, wherein The expression of the available power generation water volume of the reservoir is as follows: Among them, represents the available power generation water volume of the reservoir in the period, represents the initial reservoir capacity in the period, represents the reservoir leakage water volume in the period, represents the power generation water intake limit reservoir capacity, represents the end reservoir capacity in the period, represents the reservoir leakage coefficient, represents the dead reservoir capacity of the reservoir, represents the inflow water volume in the period.

3. The reservoir optimal operation method for scheduling plans according to claim 1, characterized in that The step S3 includes the following steps: S301. Calculate the divided differences of the Newton interpolation polynomial; S302. Based on the divided differences of the Newton interpolation polynomial, deduce the functional relationship between water level and reservoir storage; S303. Based on the functional relationship between water level and reservoir storage, use the improved Powell algorithm (Powell) to dynamically calculate the power generation water volume.

4. The reservoir optimal operation method for a scheduling plan according to claim 3, wherein The expression of the divided differences of the Newton interpolation polynomial is as follows: Among them, represents the function at the point of the order divided difference quotient, represents the reservoir capacity data at represents the function at the point of the order divided difference quotient, represents the reservoir capacity data at represents the first reservoir capacity data, represents the function at the point of the order divided difference quotient; The functional relationship between water level and reservoir storage is as follows: Among them, represents the function of water level with respect to reservoir capacity, represents the water level corresponding to the first reservoir capacity data, represents the reservoir capacity of the reservoir, represents the reservoir capacity data at 、 、 represent the coefficients of the Newton interpolation polynomial, represents the water level corresponding to the reservoir capacity data at sequence 1, represents the reservoir capacity data at sequence 1, represents the function at the point the first-order divided difference, represents the water level corresponding to the reservoir capacity data at sequence 2, represents the reservoir capacity data at sequence 2, represents the function at the point the first-order divided difference, represents the function at the point the second-order divided difference.

5. The reservoir optimal operation method for scheduling plan according to claim 3, characterized in that Based on the functional relationship between water level and reservoir storage, using the improved Powell algorithm (Powell) to dynamically calculate the power generation water volume, specifically: Initialization operation: Select an initial estimate value For Perform iteration; Set the solution accuracy ; Set the initial direction vector , where represents the water volume for power generation in a time period, represents the initial estimate value of the water volume for power generation; Construct the objective function: Based on the water volume for power generation, construct the objective function using the following formula, where the constructed objective function is to find the closer to 0 : Among them, represents the generated water volume at the th iteration in the time period, represents the objective function value when dynamically solving the generated water volume at the th iteration in the time period, represents the generated water volume at the th iteration in the time period; Linear search: perform a one-dimensional search along the direction to find a new point such that is close to 0; Update direction: Determine the direction based on the linear search result Value; Check for convergence: Determine the new function value whether it is less than the precision , if so, stop the iteration and output based on the updated result as the solution, i.e., the generated water volume; otherwise, return to the line search step.

6. The reservoir optimal operation method for scheduling plan according to claim 5, characterized in that The expression of the line search is as follows: Among them, represents the generated water volume at the th iteration in the time period, represents the generated water volume at the th iteration in the time period, represents the search step size, represents the th iteration's search direction, represents the planned power generation volume in the time period, represents the initial reservoir capacity in the time period, represents the functional relationship between water level and reservoir capacity, represents the functional relationship between the power generation tail water level and the generated water volume, represents the head loss.

7. The reservoir optimal operation method for a scheduling plan according to claim 5, characterized in that The expression of the update direction is as follows: Among them, represents the generated water volume at the th iteration in the time period, represents the generated water volume at the th iteration in the time period, represents the search direction at the th iteration.

8. The reservoir optimal operation method for scheduling plan according to claim 1, characterized in that The expression of the ecological water supply volume is as follows: Among them, represents the ecological water supply volume in a time period, represents the power generation water volume in a time period, represents the initial reservoir storage volume in a time period, represents the power generation water intake limit reservoir storage volume, represents the planned ecological water supply volume in a time period, represents the actual available water volume after reservoir power generation in a time period; The expression of the urban water supply volume is as follows: Among them, represents the urban water supply volume during a time period, represents the remaining available urban water volume from the power generation tail water after the ecological water supply is updated during a time period, represents the urban water supply planned volume during a time period, is the remaining available urban water storage volume after the water storage volume during a time period reaches the power generation water intake restricted reservoir capacity; The expression of the agricultural water supply volume is as follows: Among them, represents agricultural water supply volume during a time period, represents remaining available agricultural irrigation water volume in the tail water of power generation after update during a time period, represents agricultural water supply planned volume during a time period, represents remaining available agricultural water storage volume after the water storage volume during a time period reaches the power generation water intake limit reservoir capacity.

9. The reservoir optimal operation method for scheduling plans according to claim 1, characterized in that The expressions of the evolution speed and direction in step S8 are as follows: The expression of the evolved power generation plan is as follows: Among them, represents the velocity component of the th particle in the th dimension at the th iteration, represents the inertia weight, and and both represent the learning factors, represents a random number between 0 and 1, represents the individual best particle, is the global best particle, represents the th particle in the th iteration in the th dimension of the position component, represents the th particle in the th iteration in the th dimension of the position component, and the particle is the power generation plan.

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