CN111126847B - Cascade reservoir short-term optimization scheduling method and system coupled with riverway water power process - Google Patents
Cascade reservoir short-term optimization scheduling method and system coupled with riverway water power process Download PDFInfo
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Abstract
The invention discloses a cascade reservoir short-term optimization scheduling method and system coupled with a riverway hydrodynamic process, and belongs to the field of reservoir power generation scheduling in reservoir scheduling. The method comprises the following steps: s1, describing hydraulic connection of a cascade reservoir by using a one-dimensional hydrodynamic process calculation method, and constructing a cascade reservoir short-term optimization scheduling coupling model based on hydrodynamic warehousing flow evolution by taking the maximum generated energy of a cascade hydropower station as an objective function; aiming at the hydraulic connection, solving the coupling model by using a DPSA-POA algorithm to obtain an optimized dispatching result of the cascade reservoir; the scheduling result comprises a dam front water level process, a warehouse outlet flow process and an output process. The invention describes the hydraulic connection of the cascade reservoir by utilizing a river one-dimensional hydrodynamic process calculation method, thereby not only eliminating the aftereffect influence of water flow delay, but also more accurately calculating the warehousing flow process of the downstream reservoir, ensuring that the optimized reservoir water level result is more reasonable and improving the cascade water energy utilization efficiency.
Description
Technical Field
The invention belongs to the field of reservoir power generation scheduling in reservoir scheduling, and particularly relates to a cascade reservoir short-term optimization scheduling method and system in a coupling riverway hydrodynamic process.
Background
Compared with medium-long term scheduling of the cascade reservoir, short-term optimized scheduling needs to consider the flow propagation rule between reservoirs, and the short-term scheduling becomes a problem with aftereffect due to the existence of water flow time lag. How to accurately quantify the hydraulic connection among reservoirs so as to obtain a dispatching scheme with higher guiding value is one of the important points of short-term optimization dispatching research.
In the field of reservoir scheduling, the corresponding relationship between the upstream reservoir delivery and the downstream reservoir delivery can be called hydraulic connection. The description of hydraulic connection is independent of the selection of the short-term optimization scheduling model objective function, the consideration range of the model constraint condition and the selection of the solving algorithm. In general, descriptions of hydraulic connections in short-term optimized scheduling fall into three categories: 1. the water flow time lag is ignored or assumed to be a fixed constant, or the water flow time lag is considered to be dynamic change, and the water flow time lag is expressed as a function of the upstream ex-warehouse flow, so that the ex-warehouse flow in a single upstream time period can be distributed in the in-warehouse of a plurality of downstream time periods, and the solving difficulty of the model is increased. 2. And describing the mapping relation between the upstream reservoir delivery process and the downstream reservoir delivery process by using a Maskyoto method, and applying the relation to short-term optimization scheduling. However, in actual production, when the length of the river channel of the researched object is long, branches are numerous, the area of the drainage basin is large, and inflow of intervals is numerous, the masjing root parameter is difficult to calibrate, so that the model solution is inaccurate, and with the increase of the number of cascade reservoirs, problems of large calculated amount, difficulty in solving a short-term optimization scheduling model and the like occur. 3. By utilizing a generalization idea and a black box model, the problem of water flow propagation in the river channel is abstracted into the problem of mapping between multi-factor input such as delivery of an upstream reservoir and storage of a downstream reservoir. When the drainage basin area is large and long series of data are deficient, the result error obtained by training the black box mapping model is often large, and the actual production requirement cannot be met.
Disclosure of Invention
Aiming at the defects or improvement requirements in the prior art, the invention provides a cascade reservoir short-term optimization scheduling method and system coupled with a river hydrodynamic process, and aims to accurately calculate the warehousing flow process of a downstream reservoir, so that the water level result obtained by optimization is more reasonable, and the utilization efficiency of cascade water energy is improved.
In order to achieve the above object, according to an aspect of the present invention, there is provided a cascade reservoir short-term optimal scheduling method coupled with a river hydrodynamic process, including:
s1, describing hydraulic connection of a cascade reservoir by using a one-dimensional hydrodynamic process calculation method, and constructing a cascade reservoir short-term optimization scheduling coupling model based on hydrodynamic warehousing flow evolution by taking the maximum generated energy of a cascade hydropower station as a target function;
s2, solving the coupling model by using a DPSA-POA algorithm aiming at the hydraulic connection to obtain an optimized dispatching result of the cascade reservoir; the dispatching result comprises a dam front water level process, a warehouse outlet flow process and an output process.
Further, the objective function of the short-term optimization scheduling coupling model is as follows:
in the formula, E is the maximum value of the generating capacity of the cascade hydropower station; k and T respectively represent the total number of the cascade reservoirs and the total number of the dispatching time periods; q i，t ，H i，t Respectively the flow and the water head of the reservoir i in the time period t; n represents and Q i，t And H i，t The corresponding period of power generation.
Further, the hydraulic connection expression of the cascade reservoir is as follows:
I＝f(Q，Z)
wherein I ═ I i，1 I i，2 … I i，t ]Representing the hydrodynamic force simulation warehousing process of the downstream reservoir; q ═ Q i-1，1 Q i-1，2 … Q i-1，t ]Showing the delivery process of the upstream reservoir; z ═ Z i，1 Z i，2 … Z i，t ]Indicating the mean water level course of the reservoir downstream in the pre-dam period, Z i，t The average water level process before the dam of the reservoir i in the period t is shown, and f represents a hydrodynamic simulation function established for a specific river reach.
Further, step S2 includes:
s2.1, initializing the process of the instantaneous water level of each reservoir of the cascade power station before the initial dam;
s2.2, determining the discrete precision and the optimization range of the dam by taking the instantaneous water level in front of the dam as a state variable;
s2.3, optimizing the discrete points of the instantaneous water level in front of the dam of a single reservoir from top to bottom in sequence according to the topological structure of the cascade reservoir by taking the maximum generated energy of the cascade hydropower station as a target; when the power generation amount of a single dam front water level discrete point is calculated each time, fixing the dam front instantaneous water level process of other reservoirs, and simultaneously calling a hydrodynamic simulation method to update the warehousing process of a downstream reservoir;
s2.4, traversing all the water level discrete points before the dam to obtain one round of optimization, and judging whether the step power generation amount change of the two rounds of optimization before and after is smaller than the preset precision; if the variable quantity is smaller than the preset precision, finishing the optimization; and if the variation is larger than the preset precision, returning to execute the step S2.3.
According to another aspect of the invention, a cascade reservoir short-term optimization scheduling system coupled with a riverway hydrodynamic process is provided, which comprises:
the short-term optimization scheduling coupling model building module is used for depicting the hydraulic connection of the cascade reservoir by utilizing a one-dimensional hydrodynamic process calculation method, and building a cascade reservoir short-term optimization scheduling coupling model based on hydrodynamic warehousing flow evolution by taking the maximum generated energy of a cascade hydropower station as an objective function;
the model solving module is used for solving the coupling model by utilizing a DPSA-POA algorithm aiming at the hydraulic connection to obtain an optimized dispatching result of the cascade reservoir; the dispatching result comprises a dam front water level process, a warehouse outlet flow process and an output process.
Further, the objective function of the short-term optimization scheduling coupling model is as follows:
in the formula, E is the maximum value of the generating capacity of the cascade hydropower station; k and T respectively represent the total number of the cascade reservoirs and the total number of the dispatching time periods; q i，t ，H i，t Flow rate of reservoir i in t periodAnd a head; n represents and Q i，t And H i，t The corresponding period of power generation.
Further, the hydraulic connection expression of the cascade reservoir is as follows:
I＝f(Q，Z)
wherein I ═ I i，1 I i，2 … I i，t ]Representing the hydrodynamic force simulation warehousing process of the downstream reservoir; q ═ Q i-1，1 Q i-1，2 … Q i-1，t ]Showing the delivery process of the upstream reservoir; z ═ Z i，1 Z i，2 … Z i，t ]Indicating the mean water level course of the reservoir downstream in the pre-dam period, Z i，t The average water level process before the dam of the reservoir i in the period t is shown, and f represents a hydrodynamic simulation function established for a specific river reach.
Further, based on the hydraulic connection of the cascade reservoir, solving the coupling model by using a DPSA-POA algorithm specifically comprises the following steps:
01. initializing the process of the instantaneous water level of each reservoir of the cascade power station before the initial dam;
02. determining the discrete precision and the optimizing range of the dam by taking the instantaneous water level in front of the dam as a state variable;
03. optimizing the discrete points of the instantaneous water level in front of the dam of a single reservoir from top to bottom in sequence according to the topological structure of the cascade reservoir by taking the maximum generated energy of the cascade hydropower station as a target; fixing the dam-front instantaneous water level process of other reservoirs and simultaneously calling a hydrodynamic simulation method to update the warehousing process of the downstream reservoir when performing power generation amount calculation of a single dam-front instantaneous water level discrete point each time;
04. traversing all the instantaneous water level discrete points before the dam to obtain one round of optimization, and judging whether the step power generation amount change of the two rounds of optimization before and after is smaller than the preset precision; if the variable quantity is smaller than the preset precision, finishing the optimization; and if the variable quantity is larger than the preset precision, returning to execute the step 04.
In general, compared with the prior art, the above technical solution contemplated by the present invention can achieve the following beneficial effects:
(1) the invention provides a short-term optimization scheduling method of a cascade reservoir coupled with a river hydrodynamic process, which is characterized in that a river one-dimensional hydrodynamic process calculation method is used for describing hydraulic connection of the cascade reservoir, when the delivery process of an upper section is known, the storage process of a lower section at the same time can be obtained by simulation, not only can the aftereffect influence of water flow delay be eliminated, but also the storage flow process of a downstream water level can be more accurately calculated, so that the optimized reservoir water level result is more reasonable, and the utilization efficiency of cascade water energy is improved.
(2) The coupling method of the short-term optimization scheduling and the riverway hydrodynamic process considers the influence of the water blocking effect of the downstream reservoir on the warehousing flow of the downstream reservoir, and the warehousing flow is calculated more accurately. Due to the adoption of the DPSA-POA solving algorithm, the solving of the coupling model is easy to realize, and the calculation efficiency is high.
Drawings
FIG. 1 is a flow chart of a cascade reservoir short-term optimization scheduling method coupled with a riverway hydrodynamic process;
FIG. 2 is a schematic diagram of a short-term model optimization process;
FIG. 3 is a diagram showing a comparison between three gorges warehousing procedures in different evolutionary modes;
FIG. 4(a) is a graph comparing the fixed lag time evolution and the hydrodynamic force evolution towards the water level of the dam;
FIG. 4(b) is a comparison graph of the three gorges water level process when the fixed lag time evolves and the hydrodynamic force evolves;
FIG. 4(c) is a graph comparing the process of applying force to the home dam during the evolution of the fixed lag time and the evolution of the hydrodynamic force;
fig. 4(d) is a graph comparing the fixed lag time evolution and hydrodynamic evolution of the three isthmus output process.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the respective embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
As shown in fig. 1, the method for short-term optimal scheduling of a cascade reservoir coupled with a hydrodynamic process of a river includes:
(1) the method comprises the steps of describing the hydraulic connection of a cascade reservoir by utilizing a one-dimensional hydrodynamic process calculation method, and constructing a cascade reservoir short-term optimization scheduling coupling model based on hydrodynamic warehousing flow evolution by taking the maximum generated energy of a cascade hydropower station as an objective function;
specifically, the process of short-term optimized scheduling can be essentially regarded as a process of gradually adjusting the water level in front of the cascade power station or the single-station dam by using an optimization algorithm, and as long as the water level process of the whole scheduling period of each reservoir is determined, the hydraulic connection among the reservoirs and the operation process of each reservoir are also determined. Compared with medium-long term scheduling, one important point of the short-term optimized scheduling of the cascade reservoir is to deal with the influence of water flow delay (because a certain time is needed before the outlet flow of an upstream reservoir reaches a dam of a downstream reservoir, the delay is called in the field of reservoir scheduling) on the reservoir scheduling process. The existence of the time lag enables the step reservoir solving to become a multi-stage decision problem with aftereffect, so that a Dynamic Programming algorithm (Dynamic Programming) based on the non-aftereffect type is not suitable for solving the problem any more. How to accurately describe the hydraulic connection of the cascade reservoir and reasonably process the influence of time delay is always a difficult point for optimizing and scheduling the watershed in a short term.
The hydraulic connection upstream and downstream of the cascade reservoir can be expressed as:
in the formula I i，t The warehousing flow rate of the downstream reservoir i in the time period t, Q i，t The discharge flow of the upstream reservoir i in the time period t,
is an interval inflow;
according to the formula, the warehousing flow of the lower reservoir is the ex-warehouse flow sequence Q of the upstream reservoir i-1，0 ，Q i-1，1 ，…Q i-1，t And t time period as a function of flow rate between the upstream and downstream reservoir zones. Scheduling model solving for short-term optimization in generalSolving difficulty, adopting fixed time-lag method to process the evolution relation of the above formula, i.e.
Wherein τ is the lag time between reservoirs i and i-1; although the hydraulic connection of the cascade reservoir is greatly simplified by the fixed time lag method, the cascade reservoir is not suitable for cascade reservoir objects with long space distance, large basin confluence area and numerous branches, so that the precision of a short-term optimization scheduling scheme is urgently required to be improved by a new hydraulic connection description method. The evolution of the one-dimensional hydrodynamic model is based on a continuity equation of section integral and a time-averaged Navier-Stokes equation of section average, a connection relation between a main stream river section and a branch river channel is established by adopting a non-structural grid coding method aiming at researching a basin dendritic river network, a one-dimensional calculation grid is subdivided, on the basis, a theta semi-hidden method is adopted to disperse a control equation on the calculation grid, an Euler-Lagrangian method is used for solving a convection term of a momentum equation, a finite volume method is used for dispersing the continuity equation, a dendritic river network sparse linear system is decomposed into a plurality of three diagonal subsystems by combining a prediction correction method, a pursuit method is used for carrying out model solution, and then processes of water surface lines of each river channel along the journey and water level flow of each section are obtained. The hydraulic connection of the cascade reservoir is described by using a river channel one-dimensional hydrodynamic process calculation method, and when the delivery process of the upper section is known, the lower section storage process at the same time period can be simulated, so that the one-dimensional hydrodynamic process calculation not only can improve the calculation accuracy of the storage flow, but also can eliminate the influence of water flow delay aftereffect.
A one-dimensional hydrodynamic evolution method is embedded in a short-term optimization scheduling model, and the key point is to analyze the correlation of the two methods and extract a key coupling factor. The evolution water flow of the one-dimensional hydrodynamic model firstly needs to determine the boundary of the model, wherein the starting point of the evolution is an upper boundary, the end point of the evolution is a lower boundary, and both the flow process and the water level process can be used as boundary parameter simulation calculation. Considering that the natural propagation rule of the flow in a river channel is destroyed by establishing a large reservoir, the difference between the front water level and the tail water level of the reservoir dam is large, so that the water level jumps on the section surface of the dam site, the upper boundary of hydrodynamic simulation is selected as the outlet process of an upstream reservoir, the lower boundary is the front water level process of a lower reservoir, and the hydraulic connection of the cascade reservoir is established. Therefore, the key coupling factor of the short-term optimal scheduling and the hydrodynamic flow evolution is the outlet process of the upstream reservoir and the dam front water level process of the downstream reservoir. And replacing the fixed time-lag flow calculation method with the hydrodynamic process simulation method to establish a short-term optimization scheduling coupling model considering the hydrodynamic process of the riverway.
Generally, the short term optimization of cascade reservoir groups can be divided into "water-based power" and "water-based power" models. The invention focuses on 'fixing power by water', namely, on the basis of determining available water quantity in a scheduling period of a cascade reservoir group, determining the length of a short-term scheduling period (1 day, 3 days or 7 days) of a hydropower station by taking the maximum generated energy as a target and combining a flow propagation rule among reservoirs, optimally distributing input provided by medium-term and long-term optimal scheduling by utilizing the optimal power characteristics of the hydropower station or the real-time water consumption rate of the hydropower station, and realizing optimal power generation planning of shorter scheduling periods (1 day, 2 hours and 15min), including the determination of parameters such as reservoir water level, output hydropower station and the like, so as to realize safe and economic operation of the hydropower station.
(1.1) objective function:
the objective function of the cascade short-term scheduling model is that the generating capacity of the cascade hydropower station is maximum, namely
In the formula, E is the maximum value of the generating capacity of the cascade hydropower station; k and T respectively represent the total number of the cascade reservoirs and the total number of the dispatching time periods; q i，t ，H i，t Respectively the flow and the water head of the reservoir i in the time period t; n represents and Q i，t And H i，t The corresponding period of power generation.
(1.2) constraint conditions
(1.2.1) Water balance formula
V i，t+1 ＝V i，t +(I i，t -Q i，t )*ΔT
In the formula V i，t The capacity of the power station i at the beginning of the time period t,I i，t representing the warehousing of the power station i in a time period T, and delta T represents the time period length;
(1.2.2) selecting an upstream ex-warehouse flow process and a downstream dam front water level process as coupling factors of a short-term optimization scheduling and hydrodynamic flow evolution coupling method. Therefore, the downstream reservoir warehousing process, i.e., the cascade reservoir hydraulic connection, can be described as:
I＝f(Q，Z)
wherein I ═ I i，1 I i，2 … I i，t ]Representing the hydrodynamic force simulation warehousing process of the downstream reservoir; q ═ Q i-1，1 Q i-1，2 … Q i-1，t ]Showing the delivery process of the upstream reservoir; z ═ Z i，1 Z i，2 … Z i，t ]Indicating the mean water level course of the reservoir downstream in the pre-dam period, Z i，t Representing the average water level process before the dam of the reservoir i in the period t; and (4) simulating the warehousing process of the downstream reservoir according to the warehousing-out process of the upstream reservoir by using the formula, wherein f represents a hydrodynamic simulation function established for a specific river reach.
(1.2.3) Hydraulic restraint
In the formula Z i，t Is the water level in front of the dam of the power station,
then the relation curve of the water level of the ex-warehouse and the tail without jacking is shown,
showing the relation curve of the water level of the ex-warehouse and the tail with the jacking. Typically, the plant tailwater level is a concave function of its letdown flow. However, when the dam site of the upstream power station is located in the backwater area of the downstream power station and the cascade hydropower station has a water head overlapping condition (namely 'jacking'), the tail water level of the power station is also related to the front water level of the dam of the downstream power station.
(1.2.4) reservoir level restriction
|Z i，t -Z i，t+1 |≤ΔZ i
In the formula
And
for minimum and maximum water level limits, Δ Z, of station i during time t i Representing the maximum allowable water level variation over the time period. In the dry period of the water, the water is in the dry period,
generally, the water level is normal water level,
the lowest water level in the falling period is obtained; in the flood season,
is the flood limiting water level,
is the dead water level.
(1.2.5) force constraints
In the formula
The maximum output of the power station i in the time period t is determined comprehensively by the power characteristics of the power station unit, the limitation of the power transmitted by the power station, the expected output of the unit and the like. Wherein the content of the first and second substances,
the constraint (ensuring output constraint) is flexible constraint and falls to the minimum in runoff ultra-dry hydropower stationsWhen the water level can not meet the requirement of ensuring the output force, the value of ensuring the output force can be properly reduced or the constraint of ensuring the output force is not considered.
(1.2.6) flow restriction
In the formula
The maximum let-down flow of the power station i in the time period t is obtained;
is the minimum bleed down flow. The maximum and minimum discharge flow is generally determined by the discharge capacity of a dam, the flood demand of river navigation and the comprehensive water demand of river ecology, water supply and the like in different periods.
(1.2.7) boundary constraint
In the formula
The water level is adjusted for the start of the power station,
the water level is controlled for the end of the scheduling period.
(1.2.8) outgoing section quota constraints
In the formula (I), the compound is shown in the specification,
the maximum output of the station i during the time period t,
the outgoing section quota for station i at time t.
(1.2.9) Water head calculation formula
In the formula
Indicating head loss.
(1.2.10) Water level amplitude variation restraint
ΔZ≤ΔZ max
Wherein, Delta Z is the water level variation during the dispatching time interval of the hydropower station, and is max And scheduling the maximum water level variation in the time interval for the hydropower station.
(1.2.11) daytime output amplitude constraint
ΔN≤ΔN max
Wherein, Delta N is the output amplitude of the power station in time interval, Delta N max The maximum output amplitude of the power station in a time interval.
(2) The model solution process is shown in fig. 2 and includes:
(2.1) initializing instantaneous water level process Z before initial dam of each reservoir of cascade power station i，t ＝(Z i，0 Z i，1 ，Z i，2 ，...，Z i，t ) The average water level before the dam of each time period can be obtained by averaging the instantaneous water levels at the beginning and the end of each time period, and the average water level process before the dam of the downstream reservoir is a necessary boundary condition for hydrodynamic calculation of the riverway.
And (2.2) taking the instantaneous water level before the dam as a state variable, and determining the discrete precision and the optimizing range of the instantaneous water level before the dam. The water level restriction ranges to the home dam and the three gorges are divided into [370m, 380m ] and [145m, 175m ], the daily amplitude restriction of the water level is 1m/d and 0.6m/d respectively, the intersection of the water level restriction and the daily amplitude restriction of the water level is taken by taking the initial water level of a time interval as a starting point, the optimization range of the water level before the dam can be obtained, meanwhile, the dispersion precision to the home dam and the three gorges is set to be 0.1m, and the water level restriction ranges can be set according to actual requirements in specific application (the initial water level and the final water level of a reservoir are constant values and do not participate in dispersion and optimization).
(2.3) sequentially optimizing the discrete points of the instantaneous water level in front of the dam of a single reservoir from top to bottom in time intervals according to the topological structure of the cascade reservoir by taking the maximum power generation capacity of the cascade hydropower station as a target; and when the power generation amount of the single pre-dam instantaneous water level discrete point is calculated each time, fixing the pre-dam instantaneous water level process of other reservoirs, simultaneously calling a hydrodynamic simulation method to update the warehousing process of the downstream reservoir, and selecting the optimal discrete point of the current time of the current optimizing reservoir according to the maximum standard of the power generation amount of the cascade reservoir in the whole period.
According to the topological structure of the cascade reservoir, when the instantaneous water level before the dam of a single reservoir is sequentially optimized from top to bottom, the instantaneous water level process before the dam of other reservoirs, namely a DPSA (successive Approximation algorithm) algorithm, is fixed, when the instantaneous water level before the dam of the single reservoir is optimized, only the water level value at the single moment of optimizing is dispersed, and the water level at other moments, namely a POA (Progressive optimization algorithm) algorithm is fixed, wherein the DPSA-POA algorithm is formed by combining the two algorithms. And the judgment standard of the optimal discrete point is that the total step power generation amount is maximum.
(2.4) traversing all the instantaneous water level discrete points before the dam to obtain one round of optimization, and judging whether the step power generation amount change of the two rounds of optimization before and after is smaller than the preset precision; if the variable quantity is smaller than the preset precision, finishing the optimization; and if the variation is larger than the preset precision, returning to execute the step (2.3). In the embodiment of the invention, the preset precision is set to be that the total power generation variation of the two adjacent optimizing step reservoirs is less than 1 ten thousand kilowatt-hours.
In order to verify the effectiveness of the method, the embodiment of the invention optimizes the short-term scheduling of the family dam and the three gorges reservoir. Because the watershed area between the domestic dam and the three gorges reservoir is wide, and a large amount of rainfall observation data is needed for obtaining more accurate water coming from the region, and the existing data are difficult to support, the method selects the dry season with less water coming from the non-flood period region to perform scheduling analysis, and the specific scheduling time is from 0 point of 2/10 th in 2019 to 0 point of 2/17 th in 2019. Under the condition of only considering inflow sinks of Minjiang, Tuojiang, Jialing and Wujiang branches, the actual warehouse-out process of the Jia dam and the actual dam front water level process of the three gorges are taken as the upper and lower boundaries, and the precision of the three gorges warehouse-in obtained by adopting a fixed time lag and hydrodynamic evolution method is compared, and the result is shown in figure 3, so that the three gorges warehouse-in is always lower than the actual process when the fixed time lag evolves, and the hydrodynamic evolution is closer to the actual warehouse-in process.
Differences in traffic evolution may lead to differences in short-term optimized scheduling schemes. And calculating a short-term optimization scheduling scheme under a fixed time lag and hydrodynamic evolution mode. The important boundary and initial value conditions of the model are shown in table 1:
TABLE 1
The initial water level process is set as a linear interpolation process of the initial water level and the final water level of the reservoir, and the results obtained by the DPSA-POA algorithm are shown in fig. 4(a) -4 (d), so that when the flow is evolved by adopting a fixed time lag method, the process of the whole water level of the home dam is low, and the flow out of the reservoir is large. From the water level process of the whole scheduling period, the water level process of the fixed time-lag method for 3 days before the three gorges is lower, and the water level process for 4 days later is higher. Under the condition that the same interval incoming water, the same reservoir initial and final water level and the same branch inflow sink are not considered, when the time delay evolution flow is fixed, because the influence of the front water level of the three gorges dam on the warehousing flow is not considered, and the propagation time from each entry point to the three gorges reservoir area is fixed, the dynamic corresponding relation between the upstream ex-warehousing flow and the downstream warehousing flow cannot be truly and dynamically reflected, and the warehousing flow calculation deviation is large. When the hydrodynamic flow evolution is adopted, the warehouse-out process of the home dam corresponds to the warehouse-in process of the three gorges one by one, and the water harmony effect of the water level in front of the three gorges dam on the warehouse-in flow of the three gorges is taken into account, so that the warehouse-in flow of the three gorges is calculated more accurately.
By adopting a hydrodynamic force and fixed time lag evolution method, the total cascade generating capacity is 22.79 hundred million kilowatt hours and 21.06 million kilowatt hours, and the cascade increment is 1.73 million kilowatt hours. The hydrodynamic flow rate evolution is more accurate in warehousing flow rate calculation, the water level result obtained by optimization is more reasonable, the generated energy is larger, and the cascade hydroenergy utilization efficiency is higher.
The embodiment of the invention also provides a cascade reservoir short-term optimization scheduling system coupled with the hydrodynamic process of the riverway, each module of the system and the implementation process thereof correspond to the method, and the invention is not repeated herein.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (6)
1. A cascade reservoir short-term optimization scheduling method coupled with a river channel hydrodynamic process is characterized by comprising the following steps:
s1, describing hydraulic connection of a cascade reservoir by using a one-dimensional hydrodynamic process calculation method, and constructing a cascade reservoir short-term optimization scheduling coupling model based on hydrodynamic warehousing flow evolution by taking the maximum generated energy of a cascade hydropower station as an objective function;
s2, solving the coupling model by using a DPSA-POA algorithm aiming at the hydraulic connection to obtain an optimized dispatching result of the cascade reservoir; the scheduling result comprises a dam front water level process, a warehouse outlet flow process and an output process; step S2 includes:
s2.1, initializing the process of the instantaneous water level of each reservoir of the cascade power station before the initial dam;
s2.2, determining the discrete precision and the optimization range of the dam by taking the instantaneous water level in front of the dam as a state variable;
s2.3, with the maximum target of the generating capacity of the cascade hydropower station, sequentially optimizing the discrete points of the instantaneous water level in front of the dam of a single reservoir from top to bottom in time intervals according to the topological structure of the cascade reservoir; fixing the dam-front instantaneous water level process of other reservoirs and simultaneously calling a hydrodynamic simulation method to update the warehousing process of the downstream reservoir when performing power generation amount calculation of a single dam-front instantaneous water level discrete point each time;
s2.4, traversing all the instantaneous water level discrete points in front of the dam to obtain one round of optimization, and judging whether the step power generation amount change of the two rounds of optimization in front and back is smaller than preset accuracy; if the variable quantity is smaller than the preset precision, finishing the optimization; and if the variation is larger than the preset precision, returning to execute the step S2.3.
2. The method for cascade reservoir short-term optimal scheduling coupled with river hydrodynamic process according to claim 1, wherein the objective function of the short-term optimal scheduling coupled model is as follows:
in the formula, E is the maximum value of the generating capacity of the cascade hydropower station; k and T respectively represent the total number of the cascade reservoirs and the total number of the dispatching time periods; q i,t ，H i,t Respectively the flow and the water head of the reservoir i in the time period t; n represents and Q i,t And H i,t The corresponding period of power generation.
3. The method for the short-term optimized dispatching of the cascade reservoir coupled with the hydrodynamic process of the riverway as claimed in claim 1 or 2, wherein the hydraulic connection expression of the cascade reservoir is as follows:
I＝f(Q,Z)
wherein I ═ I i,1 I i,2 …I i,t ]Representing the hydrodynamic force simulation warehousing process of the downstream reservoir; q ═ Q i-1,1 Q i-1,2 …Q i-1,t ]Showing the delivery process of the upstream reservoir; z ═ Z i,1 Z i,2 …Z i,t ]Indicating the mean water level course of the reservoir downstream in the pre-dam period, Z i,t The average water level process before the dam of the reservoir i in the period t is shown, and f represents a hydrodynamic simulation function established for a specific river reach.
4. A cascade reservoir short-term optimization scheduling system coupled with a riverway hydrodynamic process is characterized by comprising:
the short-term optimization scheduling coupling model building module is used for depicting the hydraulic connection of the cascade reservoir by utilizing a one-dimensional hydrodynamic process calculation method, and building a cascade reservoir short-term optimization scheduling coupling model based on hydrodynamic warehousing flow evolution by taking the maximum generated energy of a cascade hydropower station as an objective function;
the model solving module is used for solving the coupling model by utilizing a DPSA-POA algorithm aiming at the hydraulic connection to obtain an optimized dispatching result of the cascade reservoir; the scheduling result comprises a dam front water level process, a warehouse outlet flow process and an output process; the step reservoir hydraulic connection based method for solving the coupling model by using the DPSA-POA algorithm specifically comprises the following steps:
01. initializing an initial dam front water level instantaneous process of each reservoir of the cascade power station;
02. determining the discrete precision and the optimizing range of the dam by taking the instantaneous water level in front of the dam as a state variable;
03. optimizing the discrete points of the instantaneous water level in front of the dam of a single reservoir from top to bottom in sequence by time intervals according to the topological structure of the cascade reservoir with the maximum target of the generating capacity of the cascade hydropower station; when the power generation amount of a single dam front water level discrete point is calculated each time, fixing the dam front instantaneous water level process of other reservoirs, and simultaneously calling a hydrodynamic simulation method to update the warehousing process of a downstream reservoir;
04. traversing all the instantaneous water level discrete points before the dam to obtain one round of optimization, and judging whether the step power generation amount change of the two rounds of optimization before and after is smaller than the preset precision; if the variable quantity is smaller than the preset precision, finishing the optimization; and if the variation is larger than the preset precision, returning to execute the step 03.
5. The cascade reservoir short-term optimization scheduling system coupled with the hydrodynamic process of the riverway as claimed in claim 4, wherein the objective function of the short-term optimization scheduling coupling model is as follows:
in the formula, E is the maximum value of the generating capacity of the cascade hydropower station; k and T respectively represent the total number of the cascade reservoirs and the total number of the dispatching time periods; q i,t ，H i,t Respectively the flow and the water head of the reservoir i in the time period t; n representsAnd Q i,t And H i,t The corresponding period of power generation.
6. The system for the short-term optimized dispatching of the cascade reservoir coupled with the hydrodynamic process of the riverway is characterized in that the hydraulic connection expression of the cascade reservoir is as follows:
I＝f(Q,Z)
wherein I ═ I i,1 I i,2 …I i,t ]Representing the hydrodynamic force simulation warehousing process of the downstream reservoir; q ═ Q i-1,1 Q i-1,2 …Q i-1,t ]Showing the delivery process of the upstream reservoir; z ═ Z i,1 Z i,2 …Z i,t ]Indicating the mean water level course of the reservoir downstream in the pre-dam period, Z i,t The average water level process before the dam of the reservoir i in the period t is shown, and f represents a hydrodynamic simulation function established for a specific river reach.
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