Method and device for optimizing dispatching-control coupling operation of hydroelectric generating set

Abstract

The invention relates to the technical field of power system optimization dispatching, in particular to a hydroelectric generating set dispatching-control coupling operation optimization method and device, and the method comprises the steps: building a hydroelectric generating set dispatching-control coupling model for a water-wind-light multi-energy complementary system according to the actual parameters of the water-wind-light complementary system and a plurality of target hydroelectric generating sets, comprising a short-term scheduling sub-model and a dynamic control sub-model; taking the minimum water consumption of the hydropower station as a target, and obtaining a 15-minute scheduling result based on the established short-term scheduling model; according to a scheduling result, selecting a change signal and inputting the change signal into a dynamic control model for analogue simulation; and obtaining a second-level dynamic response result of the characteristic index according to an analogue simulation result of the dynamic control model. Therefore, the problems that feedback of a control result and simulation of upper-layer scheduling are ignored in the prior art, a control decision maker cannot understand the principle of a scheduling instruction easily, and scheduling-control coupling operation of the hydroelectric generating set is difficult to achieve are solved.

Description

Technical Field

[0001] The present application relates to the fields of energy dispatching technology and hydroelectric generator set control optimization technology, and in particular to a method and device for optimizing the dispatching-control coupling operation of a hydroelectric generator set. Background Art

[0002] With the rapid development of renewable energy, large-scale access to the power grid for wind and solar energy has become an important trend in the global energy transformation. However, the volatility, intermittency and randomness of wind and solar energy will affect the stable operation of hydropower units and put more pressure on the flexibility of unit scheduling and control. Faced with this uncertainty, existing technologies usually study the operational stability of hydropower units in the water-wind-solar complementary system from the two aspects of scheduling and control, but there are relatively few studies that combine these two aspects.

[0003] At present, the research on the coupled operation of hydropower unit dispatching and control has the following shortcomings: 1. On-site dispatching of hydropower stations: The existing technology focuses on the optimization of the dispatching model of hydropower units. It can use the improved second-order particle swarm algorithm to solve the optimal dispatching model to obtain the optimal dispatching plan for the microgrid group. In addition, the existing technology can also use the energy optimization dispatching method of wind, solar, thermal, storage and pumping based on the firefly algorithm to facilitate the dispatching model calculation, but it ignores the feedback of the control results.

[0004] 2. Control model: Most existing technologies focus on how to simulate actual operation more accurately, but ignore the simulation of upper-level scheduling, which is not conducive to control decision makers to understand the principles of scheduling instructions.

[0005] 3. Combination of scheduling and control: Very few existing technologies take control results into account when establishing scheduling models, and existing research on the combination of scheduling and control has not yet been conducted on conventional hydropower units.

[0006] In summary, the existing technology ignores the feedback of control results and the simulation of upper-level scheduling, which is not conducive to the control decision makers' understanding of the principles of scheduling instructions, and it is difficult to realize the scheduling-control coupling operation of hydropower units, which needs to be solved urgently. Summary of the invention

[0007] The present application provides a method and device for optimizing the dispatching-control coupling operation of a hydropower unit, in order to solve the problems that the prior art ignores the feedback of control results and the simulation of upper-level dispatching, which is not conducive to the control decision makers' understanding of the principles of dispatching instructions and makes it difficult to realize the dispatching-control coupling operation of the hydropower unit.

[0008] The first aspect of the present application provides a method for optimizing the scheduling-control coupling operation of a hydropower unit, comprising the following steps: obtaining actual operating parameters of a target water-wind-solar complementary system and multiple target hydropower units; determining corresponding objective functions and multiple transfer functions according to the actual operating parameters, and establishing a short-term optimization scheduling sub-model based on the objective function and multiple pre-constructed constraints, and constructing a dynamic control sub-model through the multiple transfer functions, so as to construct a hydropower unit scheduling-control coupling model corresponding to the target water-wind-solar complementary system based on the short-term optimization scheduling sub-model and the dynamic control sub-model; running the short-term optimization scheduling sub-model in the hydropower unit scheduling-control coupling model to generate a target minute-level scheduling result, and selecting a target power change signal from the target minute-level scheduling result, and inputting the target power change signal into the dynamic control sub-model to obtain a second-level dynamic response result of at least one characteristic indicator of the multiple target hydropower units, and optimizing the scheduling-control coupling operation of the multiple target hydropower units using the target minute-level scheduling result and the second-level dynamic response result.

[0009] Optionally, in one embodiment of the present application, the corresponding objective function and multiple transfer functions are determined according to the actual operating parameters, and a short-term optimization scheduling submodel is established based on the objective function and multiple pre-constructed constraints, and a dynamic control submodel is constructed through the multiple transfer functions, so as to construct a hydropower unit scheduling-control coupling model corresponding to the target water-wind-solar complementary system based on the short-term optimization scheduling submodel and the dynamic control submodel, including: obtaining the power generation flow, the number of units, the water consumption during the start-stop process and the number of scheduling time periods of the multiple target hydropower units, and determining the objective function corresponding to the short-term optimization scheduling submodel based on the power generation flow, the number of units, the water consumption during the start-stop process and the number of scheduling time periods; determining multiple constraints corresponding to the short-term optimization scheduling submodel, and constructing the short-term optimization scheduling submodel according to the objective function and the multiple constraints, wherein the multiple constraints include power balance constraints, water balance constraints, rotating reserve constraints, minimum start-stop time constraints, unit output limit constraints, reservoir capacity limit constraints and hydropower station head limit constraints.

[0010] Optionally, in one embodiment of the present application, establishing the hydropower unit dispatching-control coupling model corresponding to the target water-wind-solar complementary system according to the actual operating parameters also includes: determining the governor transfer function, the water diversion system transfer function, the turbine transfer function and the generator-load transfer function corresponding to the dynamic control sub-model; and constructing the dynamic control sub-model according to the governor transfer function, the water diversion system transfer function, the turbine transfer function and the generator-load transfer function.

[0011] Optionally, in one embodiment of the present application, the short-term optimization scheduling submodel in the hydropower unit scheduling-control coupling model is operated to generate a target minute-level scheduling result, and a target power change signal is selected from the target minute-level scheduling result, and the target power change signal is input into the dynamic control submodel to obtain a second-level dynamic response result of at least one characteristic indicator of the multiple target hydropower units, including: determining the operating status of each target hydropower unit in the multiple target hydropower units at all time nodes, and based on the operating status and a preset binary artificial flock algorithm, searching for a target group combination state that satisfies the spinning reserve constraint and the minimum start-stop time constraint; according to the target group combination state and the preset dynamic λ The iterative bisection method is used to determine the target minute-level scheduling results of the multiple target hydropower units at the minimum water consumption; the target power change signal of any target hydropower unit in the target minute-level scheduling result in the target time period is obtained, and the target power change signal is converted into a corresponding per-unit value, and the per-unit value is input into the dynamic control sub-model to output the second-level dynamic response result of the at least one characteristic indicator in the target time period.

[0012] Optionally, in one embodiment of the present application, the mathematical expression of the objective function is:

[0013] in, W is the total water consumption of the multiple target hydropower units; The first of the multiple target hydropower units i Hydropower unit t The power generation flow during the time period; For a long period of time; For the i Hydropower unit t The start and stop status of the time period; They are the water consumption during the start and stop process respectively; N is the number of units of the multiple target hydropower units; T is the number of scheduling periods.

[0014] The second aspect of the present application provides a hydropower unit scheduling-control coupling operation optimization device, including: an acquisition module, used to acquire actual operating parameters of a target water-wind-solar complementary system and multiple target hydropower units; a modeling module, used to determine the corresponding objective function and multiple transfer functions according to the actual operating parameters, and establish a short-term optimization scheduling sub-model based on the objective function and multiple pre-constructed constraints, and construct a dynamic control sub-model through the multiple transfer functions, so as to construct a hydropower unit scheduling-control coupling model corresponding to the target water-wind-solar complementary system based on the short-term optimization scheduling sub-model and the dynamic control sub-model; an optimization module, used to run the short-term optimization scheduling sub-model in the hydropower unit scheduling-control coupling model to generate a target minute-level scheduling result, and select a target power change signal from the target minute-level scheduling result, and input the target power change signal into the dynamic control sub-model to obtain a second-level dynamic response result of at least one characteristic indicator of the multiple target hydropower units, and use the target minute-level scheduling result and the second-level dynamic response result to optimize the scheduling-control coupling operation of the multiple target hydropower units.

[0015] Optionally, in one embodiment of the present application, the modeling module includes: a first determination unit, used to obtain the power generation flow, the number of units, the water consumption during the start-stop process and the number of scheduling periods of the multiple target hydropower units, and determine the objective function corresponding to the short-term optimization scheduling submodel based on the power generation flow, the number of units, the water consumption during the start-stop process and the number of scheduling periods; a first construction unit, used to determine multiple constraints corresponding to the short-term optimization scheduling submodel, and construct the short-term optimization scheduling submodel according to the objective function and the multiple constraints, wherein the multiple constraints include power balance constraints, water balance constraints, rotating reserve constraints, minimum start-stop time constraints, unit output limit constraints, reservoir capacity limit constraints and hydropower station head limit constraints.

[0016] Optionally, in one embodiment of the present application, the modeling module also includes: a second determination unit, used to determine the governor transfer function, the water diversion system transfer function, the turbine transfer function and the generator-load transfer function corresponding to the dynamic control sub-model; a second construction unit, used to construct the dynamic control sub-model according to the governor transfer function, the water diversion system transfer function, the turbine transfer function and the generator-load transfer function.

[0017] Optionally, in one embodiment of the present application, the optimization module includes: a search unit, which is used to determine the operating status of each target hydropower unit in the multiple target hydropower units at all time nodes, and based on the operating status and a preset binary artificial flock algorithm, search for a target group combination state that satisfies the spinning reserve constraint and the minimum start-stop time constraint; a third determination unit, which is used to determine the target group combination state according to the target group combination state and a preset dynamic λ An iterative bisection method is used to determine the target minute-level scheduling results of the multiple target hydropower units at the minimum water consumption; a conversion unit is used to obtain the target power change signal of any target hydropower unit in the target minute-level scheduling result in the target time period, and convert the target power change signal into a corresponding per-unit value, and input the per-unit value into the dynamic control sub-model to output the second-level dynamic response result of the at least one characteristic indicator in the target time period.

[0018] Optionally, in one embodiment of the present application, the mathematical expression of the objective function is:

[0019] in, W is the total water consumption of the multiple target hydropower units; The first of the multiple target hydropower units i Hydropower unit t The power generation flow during the time period; For a long period of time; For the i Hydropower unit t The start and stop status of the time period; They are the water consumption during the start and stop process respectively; N is the number of units of the multiple target hydropower units; T is the number of scheduling periods.

[0020] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for optimizing the scheduling-control coupling operation of a hydropower unit as described in the above embodiment.

[0021] The fourth aspect of the present application provides a computer-readable storage medium, which stores a computer program, and when the program is executed by a processor, it implements the above-mentioned hydropower unit scheduling-control coupled operation optimization method.

[0022] The fifth aspect of the present application provides a computer program product, including a computer program, which is executed to implement the above-mentioned hydropower unit scheduling-control coupled operation optimization method.

[0023] Therefore, the embodiments of the present application have the following beneficial effects: The embodiments of the present application can obtain the actual operating parameters of the target water-wind-solar complementary system and multiple target hydropower units; determine the corresponding objective function and multiple transfer functions according to the actual operating parameters, and establish a short-term optimization scheduling sub-model based on the objective function and multiple pre-constructed constraints, and construct a dynamic control sub-model through multiple transfer functions, so as to construct a hydropower unit scheduling-control coupling model corresponding to the target water-wind-solar complementary system based on the short-term optimization scheduling sub-model and the dynamic control sub-model; operate the short-term optimization scheduling sub-model in the hydropower unit scheduling-control coupling model to generate a target minute-level scheduling result, and select a target power change signal from the target minute-level scheduling result, and input the target power change signal into the dynamic control sub-model to obtain a second-level dynamic response result of at least one characteristic indicator of the multiple target hydropower units, and use the target minute-level scheduling result and the second-level dynamic response result to optimize the scheduling-control coupling operation of the multiple target hydropower units, thereby realizing effective coordination of unit scheduling and control, which can not only provide data support for the optimal scheduling and real-time control of the hydropower units, but also provide a scientific basis for the economic operation and management decision-making of hydropower stations in the water-wind-solar complementary system. This solves the problem that the prior art ignores the feedback of control results and the simulation of upper-level scheduling, which is not conducive to control decision makers understanding the principles of scheduling instructions and is difficult to achieve coupled operation of hydropower unit scheduling and control.

[0024] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which: Figure 1 A flowchart of a method for optimizing the scheduling-control coupling operation of a hydropower unit provided according to an embodiment of the present application; Figure 2 A dynamic control sub-model block diagram provided for one embodiment of the present application; Figure 3 A block diagram of a hydropower unit dispatch-control coupling model provided for one embodiment of the present application; Figure 4 A schematic diagram of output results of a short-term optimization scheduling sub-model provided for an embodiment of the present application; Figure 5 A schematic diagram of output results of a dynamic control sub-model provided for one embodiment of the present application; Figure 6This is an example diagram of a hydropower unit scheduling-control coupling operation optimization device according to an embodiment of the present application; Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0026] Among them, 10 is a hydropower unit dispatching-control coupling operation optimization device; 100 is an acquisition module, 200 is a modeling module, 300 is an optimization module; 701 is a memory, 702 is a processor, and 703 is a communication interface. DETAILED DESCRIPTION

[0027] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0028] The following describes the method and device for optimizing the dispatching-control coupling operation of a hydropower unit according to an embodiment of the present application with reference to the accompanying drawings. In response to the problems mentioned in the above background technology, the present application provides a method for optimizing the dispatching-control coupling operation of a hydropower unit. In this method, the actual operating parameters of a target water-wind-solar complementary system and multiple target hydropower units are obtained; the corresponding objective function and multiple transfer functions are determined according to the actual operating parameters, and a short-term optimization dispatching sub-model is established based on the objective function and multiple pre-constructed constraints, and a dynamic control sub-model is constructed through multiple transfer functions, so as to construct a hydropower unit dispatching-control coupling model corresponding to the target water-wind-solar complementary system based on the short-term optimization dispatching sub-model and the dynamic control sub-model; the hydropower unit dispatching-control coupling model is operated. The short-term optimization scheduling submodel in the model is used to generate the target minute-level scheduling result, and the target power change signal is selected from the target minute-level scheduling result, and the target power change signal is input into the dynamic control submodel to obtain the second-level dynamic response result of at least one characteristic index of multiple target hydropower units, and the target minute-level scheduling result and the second-level dynamic response result are used to optimize the scheduling-control coupling operation of multiple target hydropower units, thereby realizing the effective coordination of unit scheduling and control, which can not only provide data support for the optimal scheduling and real-time control of hydropower units, but also provide a scientific basis for the economic operation and management decision-making of hydropower stations in the water-wind-solar complementary system. Thus, the existing technology ignores the feedback of control results and the simulation of upper-level scheduling, which is not conducive to the control decision makers to understand the principle of scheduling instructions, and it is difficult to realize the scheduling-control coupling operation of hydropower units.

[0029] Specifically, Figure 1 A flow chart of a method for optimizing the dispatching-control coupling operation of a hydropower unit provided in an embodiment of the present application.

[0030] like Figure 1 As shown, the hydropower unit dispatch-control coupled operation optimization method includes the following steps: In step S101, actual operating parameters of a target water-wind-solar complementary system and a plurality of target hydropower generating units are obtained. In step S102, the corresponding objective function and multiple transfer functions are determined according to the actual operating parameters, and based on the objective function and multiple pre-constructed constraints, a short-term optimization scheduling sub-model is established, and a dynamic control sub-model is constructed through multiple transfer functions, so as to construct a hydropower unit scheduling-control coupling model corresponding to the target water-wind-solar complementary system based on the short-term optimization scheduling sub-model and the dynamic control sub-model.

[0031] The embodiments of the present application can first obtain the actual operating parameters of the target water-wind-solar complementary system and multiple target hydropower units, and establish a hydropower unit scheduling-control coupling model for the water-wind-solar multi-energy complementary system according to the corresponding actual operating parameters. The coupling model is divided into two layers. The upper layer is a short-term optimization scheduling model, which is used to determine the unit combination and load distribution results; the lower layer is a dynamic control model, which is a numerical simulation model established with the help of the MATLAB / Simulink platform to simulate the operation process of the hydropower unit.

[0032] Optionally, in one embodiment of the present application, the corresponding objective function and multiple transfer functions are determined according to the actual operating parameters, and based on the objective function and multiple pre-constructed constraints, a short-term optimization scheduling submodel is established, and a dynamic control submodel is constructed through multiple transfer functions, so as to construct a hydropower unit scheduling-control coupling model corresponding to the target water-wind-solar complementary system based on the short-term optimization scheduling submodel and the dynamic control submodel, including: obtaining the power generation flow, number of units, water consumption during the start-stop process and number of scheduling time periods of multiple target hydropower units, and determining the objective function corresponding to the short-term optimization scheduling submodel based on the power generation flow, number of units, water consumption during the start-stop process and number of scheduling time periods; determining multiple constraints corresponding to the short-term optimization scheduling submodel, and constructing the short-term optimization scheduling submodel based on the objective function and multiple constraints, wherein the multiple constraints include power balance constraints, water balance constraints, rotating reserve constraints, minimum start-stop time constraints, unit output limit constraints, reservoir capacity limit constraints and hydropower station head limit constraints.

[0033] It should be noted that, in the embodiments of the present application, the objective function is constructed with the minimum total water consumption, and a corresponding short-term optimization scheduling sub-model is constructed in combination with multiple constraints.

[0034] Optionally, in one embodiment of the present application, the mathematical expression of the objective function is:

[0035] in, W is the total water consumption of multiple target hydropower units; For multiple target hydropower units i Hydropower unit t The power generation flow during the time period; For a long period of time; For the i Hydropower unit t The start and stop status of the time period; They are the water consumption during the start and stop process respectively; N The number of units of multiple target hydropower units; T is the number of scheduling periods.

[0036] It should be noted that in the short-term optimization scheduling sub-model, the embodiment of the present application takes the minimum water consumption as the optimization target, and constructs the corresponding objective function as shown in the following formula:

[0037] in, W is the total water consumption of multiple target hydropower units; For multiple target hydropower units i Hydropower unit t The power generation flow during the time period; For a long period of time; For the i Hydropower unit t The start and stop status of the time period, Express shutdown, Expression operation; They are the water consumption during the start and stop process respectively; N The number of units of multiple target hydropower units; T is the number of scheduling periods.

[0038] Therefore, the embodiment of the present application constructs the above-mentioned objective function, thereby minimizing the consumption of water resources, reducing costs and improving the economic benefits of the unit on the basis of ensuring the unit operation strategy.

[0039] After that, the embodiment of the present application also needs to set multiple constraints such as power balance constraint, water balance constraint, spinning reserve constraint, minimum start and stop time constraint, unit output limit constraint, reservoir capacity limit constraint and hydropower station head limit constraint, as described below: 1. Power balance constraints:

[0040] in, For the i Unit in t Always contribute; , They are t Wind power and photovoltaic output at all times; for t Load at all times.

[0041] 2. Water balance constraints:

[0042] in, V i and V i-1 The hydropower station i Period and i-1 The storage capacity of the time period, and The hydropower station i The inflow and outflow of a period.

[0043] 3. Spinning reserve constraints:

[0044]

[0045] in, , , , Respectively in t The unit output, wind power output, photovoltaic power output and load power at the moment; is the rotating reserve capacity.

[0046] 4. Minimum start and stop time constraints:

[0047] in, , Respectively i The startup and shutdown time of each unit.

[0048] 5. Unit output limit constraints:

[0049] in, , They are the upper and lower limits of the output of a unit respectively.

[0050] 6. Storage capacity restrictions:

[0051] in, , They are the upper and lower limits of the reservoir capacity respectively.

[0052] 7. Head limit constraints of hydropower station:

[0053]

[0054]

[0055]

[0056] in, For the hydropower station j Reservoir water level during the period, , For hydroelectric units u exist i Net head and head loss for the period, For the hydropower station i The tail water level of the period.

[0057] Therefore, the embodiment of the present application constructs a short-term optimization scheduling sub-model by determining the objective function and multiple constraints corresponding to the short-term optimization scheduling sub-model, thereby providing reliable technical and theoretical support for the construction of a hydropower unit scheduling-control coupling model.

[0058] Optionally, in one embodiment of the present application, a hydropower unit dispatching-control coupling model corresponding to the target water-wind-solar complementary system is established according to actual operating parameters, and also includes: determining the governor transfer function, water diversion system transfer function, turbine transfer function and generator-load transfer function corresponding to the dynamic control sub-model; and constructing a dynamic control sub-model according to the governor transfer function, water diversion system transfer function, turbine transfer function and generator-load transfer function.

[0059] In addition, the embodiment of the present application also needs to establish a hydropower station numerical simulation model (i.e., a dynamic control sub-model) based on the transfer function method, and its sub-links include a governor module, a water diversion system module, a turbine module, and a generator-load module, such as Figure 2 As shown, the construction of the transfer function of each sub-link is as follows: 1. Speed ​​​​regulator transfer function: The speed governor can ensure that the turbine maintains a stable speed near the operating point and respond to changes in load, thereby adjusting the output power of the unit. In the simulation model in the embodiment of the present application, the speed governor is in power regulation mode and adopts PI regulation, which can directly process the input step power change, and its transfer function is:

[0060] in, is the servomotor response time constant;s is the Laplace operator; are the turbine governor parameters, where K p is the proportional gain, K i is the integral gain.

[0061] 2. Mathematical model of water diversion system (i.e. transfer function of water diversion system module): The simulation adopts the elastic water hammer model. The simplified transfer function can be derived from the dynamic equation and continuity equation in the hydraulic principle as follows:

[0062] in, is the water flow inertia time constant; is the elastic time constant of water flow; a For T e The relevant coefficients can be obtained by fitting the amplitude-frequency characteristic curve of the transfer function.

[0063] 3. Turbine mathematical model (i.e. turbine model transfer function): The turbine is a complex nonlinear system. Flow and torque are two important parameters of the turbine. Generally, the torque and flow are expressed as functions of the guide vane opening, speed, and water head. The equation can be preliminarily expressed as:

[0064] in, y Indicates the guide vane opening; n Indicates the rotation speed; H For the water head.

[0065] It should be noted that, by adopting the method of local linearization at the steady-state operating point, the turbine characteristic equation in the embodiment of the present application can be expressed by the transfer coefficient linear equation and the flow equation as follows:

[0066] in, x Indicates the rotation speed; h Indicates water head; is the transfer coefficient of turbine torque to speed; is the transfer coefficient of turbine torque to guide vane opening; is the transfer coefficient of turbine torque to water head; is the transfer coefficient of turbine flow to speed; is the transfer coefficient of turbine flow to guide vane opening; is the transfer coefficient of turbine flow to head.

[0067] 4. Generator-load mathematical model (i.e. generator-load module transfer function): When the power station is operating in an isolated grid, the generator and load can adopt a first-order simplified model, and the transfer function can be written as

[0068] in, is the unit inertia time constant; It is called the generator self-regulation coefficient.

[0069] Therefore, the numerical simulation model of the hydropower station in the power regulation mode of the embodiment of the present application is a key tool for simulating the precise control of power output by the hydropower unit. Through detailed simulation of the hydropower unit and its control system, the model can provide a theoretical basis for the regulation strategy in actual operation.

[0070] In step S103, the short-term optimization scheduling submodel in the hydropower unit scheduling-control coupling model is run to generate a target minute-level scheduling result, and a target power change signal is selected from the target minute-level scheduling result, and the target power change signal is input into the dynamic control submodel to obtain a second-level dynamic response result of at least one characteristic indicator of multiple target hydropower units, and the target minute-level scheduling result and the second-level dynamic response result are used to optimize the scheduling-control coupling operation of multiple target hydropower units.

[0071] Furthermore, the embodiment of the present application aims to minimize the water consumption of the hydropower station, and obtains a 15-minute scheduling result (i.e., the target minute-level scheduling result) based on the established short-term scheduling sub-model; secondly, the change signal is selected according to the scheduling result and input into the dynamic control sub-model for simulation; then, according to the simulation results of the dynamic control model, the characteristic indicator second-level dynamic response result is obtained.

[0072] Therefore, the embodiments of the present application, by combining the two-step process from short-term scheduling within the hydropower station to real-time control of the hydropower units in the water-wind-solar complementary system, can reflect the power response results of the hydropower units at two time scales of 15 minutes and seconds, and achieve effective coordination of unit scheduling and control, thereby not only providing data support for the optimal scheduling and real-time control of the hydropower units, but also providing a scientific basis for the economic operation and management decisions of the hydropower stations in the water-wind-solar complementary system.

[0073] Optionally, in one embodiment of the present application, a short-term optimization scheduling submodel in a hydropower unit scheduling-control coupling model is operated to generate a target minute-level scheduling result, and a target power change signal is selected from the target minute-level scheduling result, and the target power change signal is input into a dynamic control submodel to obtain a second-level dynamic response result of at least one characteristic indicator of multiple target hydropower units, including: determining the operating status of each target hydropower unit in the multiple target hydropower units at all time nodes, and based on the operating status and a preset binary artificial flock algorithm, searching for a target group combination state that satisfies the spinning reserve constraint and the minimum start-stop time constraint; according to the target group combination state and the preset dynamic λ The iterative bisection method is used to determine the target minute-level scheduling results of multiple target hydropower units at the minimum water consumption; the target power change signal of any target hydropower unit in the target minute-level scheduling result in the target time period is obtained, and the target power change signal is converted into a corresponding per-unit value, and the per-unit value is input into the dynamic control sub-model to output the second-level dynamic response result of at least one characteristic indicator in the target time period.

[0074] It should be noted that the embodiment of the present application runs the above short-term optimization scheduling sub-model to obtain a 15-minute scheduling result, and selects a change signal from the scheduling result and inputs it into the dynamic control model, such as Figure 3 As shown, the dynamic control sub-model is run for simulation to obtain the characteristic index second-level dynamic response results.

[0075] Specifically, the process of running and solving the short-term optimization scheduling sub-model is as follows: (1) Before running the short-term optimization scheduling sub-model, the operating status of each unit at all time nodes is set. The initial parameters that need to be set are based on the actual situation of the hydropower, wind and solar multi-energy complementary base, including the number of hydropower station units, installed capacity, rated power, load curve of wind and solar access, reservoir water level and flow, and wind and solar load data. These data are then input into the short-term optimization scheduling sub-model to run the short-term optimization scheduling sub-model; (2) Based on the constraints of spinning reserve capacity and unit start and stop time, the binary artificial flock algorithm is used to search for the optimal unit combination state so that the state of each unit at all time nodes meets the requirements of spinning reserve capacity and meets the constraints of minimum downtime and maximum operating time; (3) Use dynamic λ The iterative bisection method is used to determine the load distribution result under the condition of minimum water consumption, so as to output the start-stop state combination of the unit and the output value of each time period that meets the objective function and various constraints. The start-stop state and output change of the unit every 15 minutes within 24 hours (i.e., the start-stop combination of the unit and the output result of the unit) can be obtained.

[0076] After obtaining the dispatch result of the unit at the 15-minute level, the embodiment of the present application selects the output data of a unit in the dispatch result (such as taking the #1 turbine as the analysis object) in a specific time period (such as 2:00-2:15), such as Figure 4 As shown, from the dispatching results, it can be known that the unit output has changed from 339.66MW to 331.01MW. This power change command is converted into a per-unit value as a step change signal, and is input into the dynamic control sub-model for simulation, so that the power control result at the second level can be obtained.

[0077] Afterwards, since the input of the dynamic control sub-model is a step signal, its output can be set as the response of one or more characteristic indicators (such as water level, flow rate, unit output and other parameters involved in the operation of the hydropower unit) to the input command within a time period of 900 seconds (i.e. 15 minutes).

[0078] In the specific implementation process, the embodiment of the present application obtains the output change and fluctuation of the unit within 900 seconds (i.e. 15 minutes) through simulation. Figure 5 As shown in the figure, in terms of power, the unit output fluctuated within 900 seconds, first rising to the peak point and then falling to the target value, and it has achieved stable operation near the target value within 100 seconds. In addition, the simulation model (i.e., the dynamic control sub-model) can also output the change process of the unit's flow, head, and guide vane opening; for the unit's flow and guide vane opening, the changes are both smooth and reach the target value, and the overshoot is 0; and the turbine head still returns to the original value after the fluctuation. This is because if the unit output decreases, the unit flow and guide vane opening will decrease accordingly; and the dynamic control sub-model does not take into account the changes in upstream and downstream water levels, so the unit head will still return to the original value.

[0079] Therefore, the embodiment of the present application selects the change signal in the 15-minute scheduling result and inputs it into the dynamic control model, thereby combining the 15-minute short-term optimization scheduling model with the second-level dynamic control model to achieve the coupled operation of the two models; in addition, the dynamic control sub-model in the embodiment of the present application can reflect the operating status of the unit by dynamically analyzing the characteristic indicators of the hydropower unit during operation at a time scale of seconds, which is helpful to understand the operating characteristics of the unit under different load conditions.

[0080] According to the method for optimizing the dispatching-control coupling operation of a hydropower unit proposed in an embodiment of the present application, actual operating parameters of a target water-wind-solar complementary system and multiple target hydropower units are obtained; the corresponding objective function and multiple transfer functions are determined according to the actual operating parameters, and a short-term optimization dispatching sub-model is established based on the objective function and multiple pre-constructed constraints, and a dynamic control sub-model is constructed through multiple transfer functions, so as to construct a hydropower unit dispatching-control coupling model corresponding to the target water-wind-solar complementary system based on the short-term optimization dispatching sub-model and the dynamic control sub-model; the short-term optimization dispatching sub-model in the dispatching-control coupling model of the hydropower unit is operated to generate a target minute-level dispatching result, and a target power change signal is selected from the target minute-level dispatching result, and the target power change signal is input into the dynamic control sub-model to obtain a second-level dynamic response result of at least one characteristic indicator of multiple target hydropower units, and the dispatching-control coupling operation of multiple target hydropower units is optimized by using the target minute-level dispatching result and the second-level dynamic response result, thereby realizing effective coordination of unit dispatching and control, which not only provides data support for the optimal dispatching and real-time control of hydropower units, but also provides a scientific basis for the economic operation and management decision-making of hydropower stations in the water-wind-solar complementary system.

[0081] Secondly, the hydropower unit scheduling-control coupling operation optimization device proposed according to the embodiment of the present application is described with reference to the accompanying drawings.

[0082] Figure 6 It is a block diagram of a hydropower unit scheduling-control coupled operation optimization device according to an embodiment of the present application.

[0083] like Figure 6 As shown, the hydropower unit scheduling-control coupled operation optimization device 10 includes: an acquisition module 100, a modeling module 200 and an optimization module 300.

[0084] Among them, the acquisition module 100 is used to obtain the actual operating parameters of the target water-wind-solar complementary system and multiple target hydropower units.

[0085] Modeling module 200 is used to determine the corresponding objective function and multiple transfer functions according to actual operating parameters, and to establish a short-term optimization scheduling sub-model based on the objective function and multiple pre-constructed constraints, and to construct a dynamic control sub-model through multiple transfer functions, so as to construct a hydropower unit scheduling-control coupling model corresponding to the target water-wind-solar complementary system based on the short-term optimization scheduling sub-model and the dynamic control sub-model.

[0086] The optimization module 300 is used to run the short-term optimization scheduling submodel in the hydropower unit scheduling-control coupling model to generate a target minute-level scheduling result, and select a target power change signal from the target minute-level scheduling result, and input the target power change signal into the dynamic control submodel to obtain a second-level dynamic response result of at least one characteristic indicator of multiple target hydropower units, and use the target minute-level scheduling result and the second-level dynamic response result to optimize the scheduling-control coupling operation of multiple target hydropower units.

[0087] Optionally, in one embodiment of the present application, the modeling module 200 includes: a first determining unit and a first constructing unit.

[0088] Among them, the first determination unit is used to obtain the power generation flow, number of units, water consumption during the start and stop process and number of scheduling periods of multiple target hydropower units, and determine the objective function corresponding to the short-term optimization scheduling sub-model based on the power generation flow, number of units, water consumption during the start and stop process and number of scheduling periods.

[0089] The first construction unit is used to determine multiple constraints corresponding to the short-term optimization scheduling submodel, and construct the short-term optimization scheduling submodel according to the objective function and the multiple constraints, wherein the multiple constraints include power balance constraints, water balance constraints, spinning reserve constraints, minimum start and stop time constraints, unit output limit constraints, reservoir capacity limit constraints and hydropower station head limit constraints.

[0090] Optionally, in one embodiment of the present application, the modeling module 200 further includes: a second determining unit and a second constructing unit.

[0091] The second determination unit is used to determine the governor transfer function, the water diversion system transfer function, the turbine transfer function and the generator-load transfer function corresponding to the dynamic control sub-model.

[0092] The second construction unit is used to construct a dynamic control sub-model according to the governor transfer function, the water diversion system transfer function, the turbine transfer function and the generator-load transfer function.

[0093] Optionally, in one embodiment of the present application, the optimization module 300 includes: a search unit, a third determination unit and a conversion unit.

[0094] Among them, the search unit is used to determine the operating status of each target hydropower unit among multiple target hydropower units at all time nodes, and based on the operating status and the preset binary artificial flock algorithm, search for the target group combination state that meets the spinning reserve constraint and the minimum start-stop time constraint.

[0095] The third determination unit is used to determine the target group combination state and the preset dynamic λThe iterative bisection method is used to determine the target minute-level scheduling results of multiple target hydropower units at minimum water consumption.

[0096] A conversion unit is used to obtain the target power change signal of any target hydropower unit in the target minute-level scheduling result in the target time period, and convert the target power change signal into a corresponding per-unit value, and input the per-unit value into the dynamic control sub-model to output the second-level dynamic response result of at least one characteristic indicator in the target time period.

[0097] Optionally, in one embodiment of the present application, the mathematical expression of the objective function is:

[0098] in, W is the total water consumption of multiple target hydropower units; For multiple target hydropower units i Hydropower unit t The power generation flow during the time period; For a long period of time; For the i Hydropower unit t The start and stop status of the time period; They are the water consumption during the start and stop process respectively; N The number of units of multiple target hydropower units; T is the number of scheduling periods.

[0099] It should be noted that the aforementioned explanation of the embodiment of the hydropower unit scheduling-control coupling operation optimization method is also applicable to the hydropower unit scheduling-control coupling operation optimization device of this embodiment, and will not be repeated here.

[0100] The hydropower unit scheduling-control coupling operation optimization device proposed in the embodiment of the present application includes an acquisition module 100, which is used to obtain the actual operating parameters of the target water-wind-solar complementary system and multiple target hydropower units; a modeling module 200, which is used to determine the corresponding objective function and multiple transfer functions according to the actual operating parameters, and establish a short-term optimization scheduling sub-model based on the objective function and multiple pre-constructed constraints, and construct a dynamic control sub-model through multiple transfer functions, so as to construct a hydropower unit scheduling-control coupling model corresponding to the target water-wind-solar complementary system based on the short-term optimization scheduling sub-model and the dynamic control sub-model; an optimization module 300, which is used to operate the hydropower unit scheduling -A short-term optimization scheduling submodel in the control coupling model is used to generate a target minute-level scheduling result, and a target power change signal is selected from the target minute-level scheduling result, and the target power change signal is input into the dynamic control submodel to obtain a second-level dynamic response result of at least one characteristic indicator of multiple target hydropower units, and the target minute-level scheduling result and the second-level dynamic response result are used to optimize the scheduling-control coupling operation of multiple target hydropower units, thereby realizing the effective coordination of unit scheduling and control, which not only provides data support for the optimal scheduling and real-time control of hydropower units, but also provides a scientific basis for the economic operation and management decision-making of hydropower stations in the water-wind-solar complementary system.

[0101] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include: A memory 701 , a processor 702 , and a computer program stored in the memory 701 and executable on the processor 702 .

[0102] When the processor 702 executes the program, the hydropower unit scheduling-control coupled operation optimization method provided in the above embodiment is implemented.

[0103] Furthermore, the electronic device further comprises: The communication interface 703 is used for communication between the memory 701 and the processor 702 .

[0104] The memory 701 is used to store computer programs that can be executed on the processor 702 .

[0105] The memory 701 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0106] If the memory 701, the processor 702 and the communication interface 703 are implemented independently, the communication interface 703, the memory 701 and the processor 702 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 7 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0107] Optionally, in a specific implementation, if the memory 701, the processor 702 and the communication interface 703 are integrated on a chip, the memory 701, the processor 702 and the communication interface 703 can communicate with each other through an internal interface.

[0108] The processor 702 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0109] An embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the above-mentioned method for optimizing the scheduling-control coupling operation of a hydropower unit is implemented.

[0110] The embodiment of the present application also provides a computer program product, including a computer program, which, when executed, is used to implement the above-mentioned hydropower unit scheduling-control coupled operation optimization method.

[0111] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0112] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0113] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0114] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection with one or N wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary and then storing it in a computer memory.

[0115] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0116] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0117] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0118] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for optimizing the dispatching-control coupling operation of a hydropower unit, characterized in that: The following steps are involved: Obtain the actual operating parameters of the target hydro-wind-solar complementary system and multiple target hydropower units; Determine the corresponding objective function and multiple transfer functions according to the actual operating parameters, and establish a short-term optimization scheduling sub-model based on the objective function and multiple pre-constructed constraints, and construct a dynamic control sub-model through the multiple transfer functions, so as to construct a hydropower unit scheduling-control coupling model corresponding to the target water-wind-solar complementary system based on the short-term optimization scheduling sub-model and the dynamic control sub-model; Run the short-term optimization scheduling submodel in the hydropower unit scheduling-control coupling model to generate a target minute-level scheduling result, select a target power change signal from the target minute-level scheduling result, and input the target power change signal into the dynamic control submodel to obtain a second-level dynamic response result of at least one characteristic indicator of the multiple target hydropower units, and use the target minute-level scheduling result and the second-level dynamic response result to optimize the scheduling-control coupling operation of the multiple target hydropower units.

2. The method for optimizing the dispatching-control coupling operation of a hydropower unit according to claim 1, characterized in that: Determining the corresponding objective function and multiple transfer functions according to the actual operating parameters, and establishing a short-term optimization scheduling sub-model based on the objective function and multiple pre-built constraints, includes: Obtaining the power generation flow, the number of units, the water consumption during the start-stop process, and the number of scheduling periods of the multiple target hydropower units, and determining the objective function corresponding to the short-term optimization scheduling submodel based on the power generation flow, the number of units, the water consumption during the start-stop process, and the number of scheduling periods; Determine multiple constraints corresponding to the short-term optimization scheduling submodel, and construct the short-term optimization scheduling submodel according to the objective function and the multiple constraints, wherein the multiple constraints include power balance constraints, water balance constraints, spinning reserve constraints, minimum start and stop time constraints, unit output limitation constraints, reservoir capacity limitation constraints and hydropower station head limitation constraints.

3. The method for optimizing the dispatching-control coupling operation of a hydropower unit according to claim 2, characterized in that: The dynamic control sub-model is constructed by the multiple transfer functions to construct a hydropower unit dispatching-control coupling model corresponding to the target water-wind-solar complementary system based on the short-term optimization dispatching sub-model and the dynamic control sub-model, including: Determine a governor transfer function, a water diversion system transfer function, a turbine transfer function, and a generator-load transfer function corresponding to the dynamic control submodel; The dynamic control sub-model is constructed according to the governor transfer function, the water diversion system transfer function, the turbine transfer function and the generator-load transfer function.

4. The method for optimizing the dispatching-control coupling operation of a hydropower unit according to claim 3 is characterized in that: The short-term optimization scheduling submodel in the scheduling-control coupling model of the hydropower unit is operated to generate a target minute-level scheduling result, and a target power change signal is selected from the target minute-level scheduling result, and the target power change signal is input into the dynamic control submodel to obtain a second-level dynamic response result of at least one characteristic indicator of the multiple target hydropower units, including: Determine the operating status of each target hydropower unit among the multiple target hydropower units at all time nodes, and search for a target unit combination state that satisfies the spinning reserve constraint and the minimum start-stop time constraint based on the operating status and a preset binary artificial flock algorithm; Dynamics based on the target group combination state and preset λ Iterative dichotomy method is used to determine the target minute-level scheduling results of the multiple target hydropower units at the minimum water consumption; Obtain the target power change signal of any target hydropower unit in the target minute-level scheduling result in the target time period, convert the target power change signal into a corresponding per-unit value, and input the per-unit value into the dynamic control sub-model to output the second-level dynamic response result of the at least one characteristic indicator in the target time period.

5. The method for optimizing the dispatching-control coupling operation of a hydropower unit according to claim 2, characterized in that: The mathematical expression of the objective function is: in, W is the total water consumption of the multiple target hydropower units; The first of the multiple target hydropower units i Hydropower unit t The power generation flow during the time period; For a long period of time; For the i Hydropower unit t The start and stop status of the time period; They are the water consumption during the start and stop process respectively; N is the number of units of the multiple target hydropower units; T is the number of scheduling periods.

6. A hydropower unit dispatching-control coupling operation optimization device, characterized in that: include: An acquisition module is used to acquire actual operating parameters of a target water-wind-solar complementary system and multiple target hydropower units; A modeling module, used to determine the corresponding objective function and multiple transfer functions according to the actual operating parameters, and to establish a short-term optimization scheduling sub-model based on the objective function and multiple pre-constructed constraints, and to construct a dynamic control sub-model through the multiple transfer functions, so as to construct a hydropower unit scheduling-control coupling model corresponding to the target water-wind-solar complementary system based on the short-term optimization scheduling sub-model and the dynamic control sub-model; An optimization module is used to run the short-term optimization scheduling submodel in the scheduling-control coupling model of the hydropower unit to generate a target minute-level scheduling result, and select a target power change signal from the target minute-level scheduling result, and input the target power change signal into the dynamic control submodel to obtain a second-level dynamic response result of at least one characteristic indicator of the multiple target hydropower units, and use the target minute-level scheduling result and the second-level dynamic response result to optimize the scheduling-control coupling operation of the multiple target hydropower units.

7. The hydropower unit dispatching-control coupling operation optimization device according to claim 6 is characterized in that: The modeling module includes: A first determination unit is used to obtain the power generation flow, the number of units, the water consumption during the start-stop process, and the number of scheduling periods of the multiple target hydropower units, and determine the objective function corresponding to the short-term optimization scheduling submodel based on the power generation flow, the number of units, the water consumption during the start-stop process, and the number of scheduling periods; The first construction unit is used to determine multiple constraints corresponding to the short-term optimization scheduling submodel, and construct the short-term optimization scheduling submodel according to the objective function and the multiple constraints, wherein the multiple constraints include power balance constraints, water balance constraints, spinning reserve constraints, minimum start and stop time constraints, unit output limitation constraints, reservoir capacity limitation constraints and hydropower station head limitation constraints.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for optimizing the coupled operation of the hydropower unit scheduling-control as described in any one of claims 1 to 5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the hydropower unit scheduling-control coupled operation optimization method as described in any one of claims 1 to 5.

10. A computer program product, comprising a computer program, characterized in that The computer program is executed to implement the method for optimizing the dispatching-control coupling operation of a hydropower unit as described in any one of claims 1 to 5.

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