A condensate system and control method based on a condensate system

Abstract

The application provides a condensate water system and a control method based on the condensate water system. The condensate water system comprises a condenser, a condensate water pump, a No. 7 low-pressure heater, a No. 6 low-pressure heater, a No. 5 low-pressure heater, a deaerator, a first regulating valve and a second regulating valve. The first end of the condenser is connected with the first end of the condensate water pump. The second end of the condensate water pump is connected with the first end of the No. 7 low-pressure heater, and the third end of the condensate water pump is connected with the first end of the deaerator through a large bypass. The first regulating valve is arranged on the large bypass. The second end of the No. 7 low-pressure heater is connected with the first end of the No. 6 low-pressure heater. The second end of the No. 6 low-pressure heater is connected with the first end of the No. 5 low-pressure heater, and the third end of the No. 6 low-pressure heater is connected with the second end of the deaerator through a small bypass. The second regulating valve is arranged on the small bypass. The second end of the No. 5 low-pressure heater is connected with the third end of the deaerator.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power generation equipment, and in particular to a condensate water system and a control method based on the condensate water system. BACKGROUND

[0002] With a large amount of new energy power generation being connected to the grid in China, thermal power generating units gradually change from main energy to regulating energy, and at the same time, due to the intermittency and instability of new energy, thermal power generating units need to undertake the arduous task of load regulation. Therefore, how to enable thermal power generating units to quickly and flexibly regulate unit load to meet the demand of load change is one of the key research directions in the field. SUMMARY

[0003] The present application aims to at least partly solve one of the technical problems in the related art.

[0004] To this end, the first aspect of the present application provides a condensate water system, comprising:

[0005] a condenser, a condensate water pump, a No. 7 low-pressure heater, a No. 6 low-pressure heater, a No. 5 low-pressure heater, a deaerator, a first regulating valve and a second regulating valve, wherein

[0006] a first end of the condenser is connected to a first end of the condensate water pump;

[0007] a second end of the condensate water pump is connected to a first end of the No. 7 low-pressure heater, and a third end of the condensate water pump is connected to a first end of the deaerator through a large bypass; wherein a first regulating valve is arranged on the large bypass;

[0008] a second end of the No. 7 low-pressure heater is connected to a first end of the No. 6 low-pressure heater;

[0009] a second end of the No. 6 low-pressure heater is connected to a first end of the No. 5 low-pressure heater, and a third end of the No. 6 low-pressure heater is connected to a second end of the deaerator through a small bypass; wherein the second regulating valve is arranged on the small bypass;

[0010] a second end of the No. 5 low-pressure heater is connected to a third end of the deaerator.

[0011] In some embodiments of the present application, the system further comprises a condensate water recirculation regulating valve, wherein

[0012] a fourth end of the condensate water pump is connected to a second end of the condenser through a condensate water recirculation loop; the condensate water recirculation regulating valve is arranged on the condensate water recirculation loop.

[0013] The second aspect of the application provides a control method based on a condensate water system, the condensate water system being the system of the first aspect, the method comprising:

[0014] obtaining operating parameters of a plurality of devices in the condensate water system;

[0015] obtaining an optimal solution set according to the operating parameters of the plurality of devices by a particle swarm multi-objective optimization algorithm, wherein the optimal solution set comprises an optimal heat, an optimal load change amount, and corresponding condensate water flow rates through the No. 5 low-pressure heater, the No. 6 low-pressure heater, and the No. 7 low-pressure heater;

[0016] obtaining a first adjustment instruction of the first adjusting valve and a second adjustment instruction of the second adjusting valve according to the optimal solution set;

[0017] adjusting the opening degree of the first adjusting valve according to the first adjustment instruction, and adjusting the opening degree of the second adjusting valve according to the second adjustment instruction.

[0018] In some embodiments of the application, the operating parameters of the plurality of devices in the condensate water system comprise: enthalpy value of the No. 5 heater feedwater outlet, enthalpy value of the condensate water pump outlet condensate water, enthalpy value of the No. 6 heater feedwater outlet, enthalpy value of the No. 7 heater feedwater outlet, unit power under variable conditions, condensate water flow rate under variable conditions, unit power under initial conditions, and condensate water flow rate under initial conditions.

[0019] In some embodiments of the application, the particle swarm multi-objective optimization algorithm comprises: initializing population parameters, wherein the population parameters comprise population quantity, solution quantity in a Pareto solution set, iteration number, and inertia weight; establishing a description of each particle position, solving an optimization target, and obtaining a fitness value of each particle. Randomly selecting part of particles in the particle swarm to perform mutation operation, determining the dominance relationship of the particles before and after mutation, and retaining non-dominated solutions; comparing the dominance relationship between each particle and its historical individual optimal solution, and updating the non-dominated individual optimal solution; judging the dominance relationship between the particles and each solution in the current Pareto solution set, and storing the non-dominated solution set; determining a group leader particle according to a grid method and a roulette method, judging whether the Pareto front converges or not; if the Pareto front converges, completing the iteration optimization process; if the Pareto front does not converge, updating the position and speed of each particle; after updating the speed and position of each particle, returning to the step of establishing a description of each particle position, solving an optimization target, and obtaining a fitness value of each particle.

[0020] In some embodiments of this application, obtaining the first regulating command of the first regulating valve and the second regulating command of the second regulating valve based on the optimal solution set includes: obtaining the large bypass flow rate and the small bypass flow rate based on the optimal solution set; and obtaining the first regulating command of the first regulating valve and the second regulating command of the second regulating valve based on the large bypass flow rate and the small bypass flow rate.

[0021] In some embodiments of this application, the method further includes: in response to a unit load being lower than a preset threshold, controlling the condensate from the outlet of the condensate pump to circulate to the condenser by adjusting the condensate recirculation regulating valve.

[0022] A third aspect of this application provides a control device based on a condensate system, wherein the condensate system is the system described in the first aspect above, and the device includes:

[0023] The first acquisition module is used to acquire the operating parameters of multiple devices in the condensate system;

[0024] The optimization algorithm module is used to obtain the optimal solution set based on the operating parameters of the multiple devices through a particle swarm optimization algorithm. The optimal solution set includes the optimal heat, the optimal load change, and the corresponding condensate flow rate through low-pressure heater No. 5 and condensate flow rate through low-pressure heaters No. 6 and No. 7.

[0025] The second acquisition module is used to acquire the first adjustment command of the first control valve and the second adjustment command of the second control valve according to the optimal solution set;

[0026] The large bypass control module is used to adjust the opening degree of the first regulating valve according to the first regulating command;

[0027] The small bypass control module is used to adjust the opening degree of the second regulating valve according to the second regulating command.

[0028] In some embodiments of this application, the optimization algorithm module is specifically used for:

[0029] Initialize the population parameters; wherein the population parameters include the population size, the number of solutions in the Pareto solution set, the number of iterations, and the inertia weight; establish the position description of each particle, solve the optimization objective, and obtain the fitness value of each particle.

[0030] Randomly select part of the particle population to perform mutation operation, determine the dominance relationship before and after mutation, and retain the non-dominated solution; compare the dominance relationship between each particle and its historical individual optimal solution, update the non-dominated individual optimal solution; judge the dominance relationship between the particle and each solution in the current Pareto solution set, and store the non-dominated solution set; determine the group leader particle according to the grid method and the roulette method, and judge whether the Pareto front converges; if the Pareto front converges, the iterative optimization process is completed; if the Pareto front does not converge, update the position and speed of each particle; after updating the speed and position of each particle, return to the step of establishing the position description of each particle, solving the optimization target, and obtaining the fitness value of each particle.

[0031] In some embodiments of the present application, the device further comprises a condensate water recirculation control module for controlling the circulation of condensate water at the outlet of the condensate water pump to the condenser by adjusting the condensate water recirculation regulating valve in response to the unit load being lower than a preset threshold.

[0032] According to the condensate water system of the embodiments of the present application, the condensate water can directly enter the deaerator through the large bypass without being heated by the No. 7 low-pressure heater, the No. 6 low-pressure heater, and the No. 5 low-pressure heater, thereby maximizing the adjustment potential of the unit and reducing the instability of the condensate water system caused by the dramatic fluctuation of the deaerator water level to a certain extent while adjusting the load. The present application can also make the condensate water directly enter the deaerator through the small bypass without being heated by the No. 5 low-pressure heater, thereby adjusting the unit load more accurately and economically.

[0033] Additional aspects and advantages of the present application will be in part apparent and in part pointed out hereinafter in the description. BRIEF DESCRIPTION OF DRAWINGS

[0034] The above and / or additional aspects and advantages of the present application will become apparent and be readily appreciated from the following description, taken in conjunction with the accompanying drawings, in which:

[0035] Figure 1 A schematic diagram of a condensate water system according to an embodiment of the present application is provided.

[0036] Figure 2 A flowchart of a control method based on a condensate water system according to an embodiment of the present application is provided.

[0037] Figure 3 A method flowchart for obtaining an optimal solution set by a particle swarm multi-objective optimization algorithm according to an embodiment of the present application is provided.

[0038] Figure 4 A schematic diagram of a control device based on a condensate water system according to an embodiment of the present application is provided. DETAILED DESCRIPTION

[0039] Embodiments of the present application are described below in detail, examples of which are shown in the accompanying drawings, wherein the same or similar notations represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and are intended to explain the present application, and cannot be understood as a limitation of the present application.

[0040] The present application proposes a condensate water system and a control method based on the condensate water system. Specifically, the condensate water system and the control method based on the condensate water system of the embodiments of the present application are described below with reference to the accompanying drawings.

[0041] Figure 1 A schematic diagram of a condensate water system provided by the embodiments of the present application is shown in FIG. 1. As shown in FIG. 1, the condensate water system includes a condenser 101, a condensate water pump 102, a No. 7 low-pressure heater 103, a No. 6 low-pressure heater 104, a No. 5 low-pressure heater 105, a deaerator 106, a first regulating valve 107, and a second regulating valve 108. Figure 1

[0042] The first end of the condenser 101 is connected to the first end of the condensate water pump 102.

[0043] The second end of the condensate water pump 102 is connected to the first end of the No. 7 low-pressure heater 103, and the third end of the condensate water pump 102 is connected to the first end of the deaerator 106 through a large bypass. The first regulating valve 107 is arranged on the large bypass.

[0044] The second end of the No. 7 low-pressure heater 103 is connected to the first end of the No. 6 low-pressure heater 104.

[0045] The second end of the No. 6 low-pressure heater 104 is connected to the first end of the No. 5 low-pressure heater 105, and the third end of the No. 6 low-pressure heater 104 is connected to the second end of the deaerator 106 through a small bypass. The second regulating valve 108 is arranged on the small bypass.

[0046] The second end of the No. 5 low-pressure heater 105 is connected to the third end of the deaerator 106.

[0047] It should be noted that the second end of the condensate water pump 102 and the third end of the condensate water pump 102 can be the same end, the second end of the No. 6 low-pressure heater 104 and the third end of the No. 6 low-pressure heater 104 can be the same end, and the first end of the deaerator 106, the second end of the deaerator 106, and the third end of the deaerator 106 can be the same end.

[0048] ​In some embodiments of the present application, the condensate water system can further comprise a condensate water recirculation regulating valve 109, wherein the fourth end of the condensate water pump 102 is connected to the second end of the condenser 101 through a condensate water recirculation loop. The condensate water recirculation regulating valve 109 is arranged on the condensate water recirculation loop. It should be noted that the first end of the condenser 101 and the second end of the condenser 101 can be the same end.

[0049] According to the condensate water system of the embodiments of the present application, the condensate water can directly enter the deaerator through the large bypass without being exchanged by the No. 7 low-pressure heater, the No. 6 low-pressure heater, and the No. 5 low-pressure heater, thereby maximizing the adjustment potential of the unit and reducing the instability of the condensate water system caused by the dramatic fluctuation of the deaerator water level to a certain extent while adjusting the load. The present application can also make the condensate water directly enter the deaerator through the small bypass without being exchanged by the No. 5 low-pressure heater, thereby adjusting the unit load more accurately and economically.

[0050] Figure 2 A flowchart of a control method based on a condensate water system is provided for the embodiments of the present application. It should be noted that the method can be applied to the condensate water system described in any of the above embodiments. As shown in Figure 2 The control method based on the condensate water system provided by the embodiments of the present application can comprise the following steps:

[0051] Step 201, obtaining the operating parameters of a plurality of devices in the condensate water system.

[0052] Step 202, obtaining an optimal solution set by a particle swarm multi-objective optimization algorithm according to the operating parameters of the plurality of devices.

[0053] The optimal solution set comprises an optimal heat, an optimal load change amount, and the corresponding condensate water flow rate through the No. 5 low-pressure heater and the condensate water flow rate through the No. 6 low-pressure heater and the No. 7 low-pressure heater.

[0054] It should be noted that the heat recovery system can comprise the No. 7 low-pressure heater, the No. 6 low-pressure heater, the No. 5 low-pressure heater, and the deaerator. During the process of adjusting the unit load by throttling the condensate water, the heat provided by the heat recovery system and the load change amount are in a contradictory and coexisting relationship, so the heat provided by the heat recovery system and the load change amount can be used as the optimization target to balance the relationship between them. According to the operating parameters of the plurality of devices, the optimal solution set is obtained by the particle swarm multi-objective optimization algorithm, that is, the optimal matching between the energy utilization rate and the condensate water system load adjustment capacity is achieved.

[0055] In some embodiments of the present application, the operating parameters of the plurality of devices in the condensate water system can include a 5th heater feedwater outlet enthalpy, a condensate water pump outlet condensate water enthalpy, a 6th heater feedwater outlet enthalpy, a 7th heater feedwater outlet enthalpy, a unit power under variable conditions, a condensate water flow under variable conditions, a unit power under initial conditions, and a condensate water flow under initial conditions.

[0056] As an example, the implementation process of obtaining the optimal solution set by the particle swarm multi-objective optimization algorithm can refer to Figure 3 . Figure 3 The method flowchart for obtaining the optimal solution set by the particle swarm multi-objective optimization algorithm proposed in the embodiments of the present application is shown in Figure 3 , which can include the following steps:

[0057] Step 301, initialize population parameters. The population parameters include the population size, the number of solutions in the Pareto solution set, the number of iterations, and the inertia weight.

[0058] Step 302, establish a particle position description, solve the objective function, and obtain the fitness value of each particle.

[0059] As an example, the objective function can refer to formula (1) and formula (2).

[0060] F1=maxQ=max((D wc5 h w5 -D wc5 h wc )+D wc (h w6 -h w7 )+D wc (h w7 -h wc )) (1)

[0061]

[0062] Wherein, Q is the heat provided by the 5th low-pressure heater, the 6th low-pressure heater, and the 7th low-pressure heater, ΔNe is the load change, D wc5 is the condensate water flow through the 5th low-pressure heater, h w5 is the 5th heater feedwater outlet enthalpy, h wc is the condensate water pump outlet condensate water enthalpy, D wc is the condensate water flow through the 6th low-pressure heater and the 7th low-pressure heater, h w6 is the 6th heater feedwater outlet enthalpy, h w7 is the 7th heater feedwater outlet enthalpy, is the unit power under variable conditions, is the condensate water flow under variable conditions, P0 is the unit power under the initial operating condition, P0 is the unit power under the initial operating condition, i P0 is the unit power under the initial operating condition,

[0063] In step 303, a part of the particle population is randomly selected for mutation operation, the dominance relationship before and after mutation is determined, and the non-dominated solution is reserved.

[0064] In step 304, the dominance relationship between each particle and its historical individual optimal solution is compared, and the non-dominated individual optimal solution is updated.

[0065] In step 305, the dominance relationship between the particle and each solution in the current Pareto solution set is judged, and the non-dominated solution set is stored.

[0066] In step 306, the population leader particle is determined according to the grid method and the roulette method, and it is judged whether the Pareto front converges; if the Pareto front converges, the iterative optimization process is completed; if the Pareto front does not converge, step 307 is executed.

[0067] In step 307, the position and velocity of each particle are updated.

[0068] As an example, the velocity and position of each particle can be calculated by formula (3) and formula (4).

[0069]

[0070]

[0071] In the formula: P0 is the unit power under the initial operating condition, P0 is the unit power under the initial operating condition, P0 is the unit power under the initial operating condition, k P0 is the unit power under the initial operating condition,

[0072] Therefore, through steps 301-307, the optimal solution set can be obtained according to the operating parameters of multiple devices through the particle swarm multi-objective optimization algorithm, that is, the optimal heat between energy utilization rate and condensate system regulation load capacity, the optimal load change amount, and the corresponding condensate flow through the No. 5 low-pressure heater and the condensate flow through the No. 6 low-pressure heater and the No. 7 low-pressure heater are realized.

[0073] In step 203, the first adjustment instruction of the first adjustment valve and the second adjustment instruction of the second adjustment valve are obtained according to the optimal solution set.

[0074] In some embodiments of the present application, the first adjustment instruction for controlling the opening of the first adjustment valve and the second adjustment instruction for controlling the opening of the second adjustment valve are obtained according to the condensate flow through the No. 5 low-pressure heater, the condensate flow through the No. 6 low-pressure heater and the No. 7 low-pressure heater in the optimal solution set, and the flow characteristics of the first adjustment valve and the second adjustment valve. The opening of the first adjustment valve is adjusted according to the first adjustment instruction, and the opening of the second adjustment valve is adjusted according to the second adjustment instruction.

[0075] In step 204, the opening of the first adjustment valve is adjusted according to the first adjustment instruction, and the opening of the second adjustment valve is adjusted according to the second adjustment instruction.

[0076] In order to prevent the condensate pump from having too little water under low load operating conditions, in some embodiments of the present application, the control method based on the condensate system proposed in the present application can also control the condensate pump outlet condensate to circulate to the condenser by adjusting the condensate recirculation adjustment valve when the unit load is lower than a preset threshold, to ensure safe operation of the unit.

[0077] According to the control method based on the condensate system according to the embodiments of the present application, the heat provided by the regenerative system and the load change amount are taken as the optimization target according to the operating parameters of the plurality of devices, and the optimal solution set is obtained through the particle swarm multi-objective optimization algorithm, that is, the optimal matching between the energy utilization rate and the condensate system load adjustment capability is achieved. The opening of the first adjustment valve and the opening of the second adjustment valve are adjusted based on the optimal solution set to control the condensate flow through the large bypass and the condensate flow through the small bypass, thereby achieving the purpose of quickly and flexibly adjusting the unit load.

[0078] Figure 4 A schematic diagram of a control device based on a condensate system according to an embodiment of the present application is provided. It should be noted that the condensate system can be any of the condensate systems described above. As shown in FIG. 4, the control device based on the condensate system includes a first acquisition module 401, an optimization algorithm module 402, a second acquisition module 403, a large bypass control module 404, and a small bypass control module 405. Figure 4

[0079] The first acquisition module 401 is configured to acquire operating parameters of a plurality of devices in the condensate system.

[0080] ​The optimization algorithm module 402 is configured to obtain an optimal solution set by using a particle swarm multi-objective optimization algorithm according to the operating parameters of the plurality of devices. The optimal solution set includes an optimal heat, an optimal load change amount, and corresponding condensate water flow rates flowing through the No. 5 low-pressure heater and the No. 6 low-pressure heater and the No. 7 low-pressure heater.

[0081] In some embodiments of the present application, the optimization algorithm module 402 is specifically configured to: initialize population parameters, wherein the population parameters include a population size, a number of solutions in a Pareto solution set, a number of iterations, and an inertia weight; establish a description of positions of particles, solve an optimization target, and obtain fitness values of the particles; randomly select some particles in the particle group to perform mutation operations, determine a dominance relationship between the particles before and after mutation, and retain non-dominated solutions; compare a dominance relationship between each particle and a historical individual optimal solution of the particle, and update the non-dominated individual optimal solution; determine a dominance relationship between the particle and each solution in the current Pareto solution set, and store a non-dominated solution set; determine a group leader particle according to a grid method and a roulette method, and determine whether a Pareto front converges; if the Pareto front converges, an iterative optimization process is completed; if the Pareto front does not converge, positions and velocities of the particles are updated; after the velocities and the positions of the particles are updated, the step of establishing the description of the positions of the particles, solving the optimization target, and obtaining the fitness values of the particles is returned.

[0082] The second acquisition module 403 is configured to acquire a first adjustment instruction of the first adjustment valve and a second adjustment instruction of the second adjustment valve according to the optimal solution set.

[0083] The large bypass control module 404 is configured to adjust an opening degree of the first adjustment valve according to the first adjustment instruction.

[0084] The small bypass control module 405 is configured to adjust an opening degree of the second adjustment valve according to the second adjustment instruction.

[0085] In some embodiments of the present application, the control device based on the condensate water system can further include a condensate water recirculation control module configured to control condensate water at an outlet of a condensate water pump to circulate to a condenser by adjusting a condensate water recirculation adjustment valve when a unit load is lower than a preset threshold.

[0086] As to the device in the above embodiments, specific manners in which each module performs operations have been described in detail in the embodiments of the method, and thus will not be described in detail here.

[0087] According to the control device based on the condensate water system, according to the operation parameters of the plurality of devices, the heat provided by the heat recovery system and the load change amount are taken as the optimization target, and through the particle swarm multi-objective optimization algorithm, the optimal solution set is obtained, that is, the optimal matching between the energy utilization rate and the condensate water system regulation load capacity is realized. Based on the opening of the first regulating valve and the opening of the second regulating valve in the optimal solution set, the condensate water flow through the large bypass and the condensate water flow through the small bypass are controlled, so as to realize the purpose of quickly and flexibly regulating the unit load.

[0088] In the description of the specification, the description of the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the description of the specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. In addition, the person skilled in the art can combine and combine the different embodiments or examples described in the specification and the features of the different embodiments or examples without contradiction.

[0089] In addition, the terms "first", "second" are only for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "a plurality of" is at least two, for example, two, three, etc., unless otherwise specifically limited.

[0090] Any process or method descriptions in flow charts or described elsewhere herein can be understood as representing code modules, segments, or portions of code that include one or more executable instructions for implementing specific logic functions (or steps) in the process, and the various preferred embodiments of the application include additional implementations in which the order of the steps can be changed, including use of simultaneous or substantially simultaneous steps, and additional or different steps can be used, in the embodiments of the application, as will be understood by those skilled in the art.

[0091] 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, and those skilled in the art can make changes, modifications, replacements and variations to the above embodiments within the scope of the present application.

Claims

1. A control method based on a condensate water system, characterized by, The condensate system comprises a condenser, a condensate pump, a No. 7 low-pressure heater, a No. 6 low-pressure heater, a No. 5 low-pressure heater, a deaerator, a first regulating valve and a second regulating valve, wherein the first end of the condenser is connected with the first end of the condensate pump; the second end of the condensate pump is connected with the first end of the No. 7 low-pressure heater, and the third end of the condensate pump is connected with the first end of the deaerator through a large bypass; the first regulating valve is arranged on the large bypass; the second end of the No. 7 low-pressure heater is connected with the first end of the No. 6 low-pressure heater; the second end of the No. 6 low-pressure heater is connected with the first end of the No. 5 low-pressure heater, and the third end of the No. 6 low-pressure heater is connected with the second end of the deaerator through a small bypass; the second regulating valve is arranged on the small bypass; the second end of the No. 5 low-pressure heater is connected with the third end of the deaerator; the system further comprises a condensate recirculation regulating valve, wherein the fourth end of the condensate pump is connected with the second end of the condenser through a condensate recirculation loop; the condensate recirculation regulating valve is arranged on the condensate recirculation loop; the method comprises: obtaining operating parameters of multiple devices in a condensate system; obtaining an optimal solution set by a particle swarm multi-objective optimization algorithm according to the operating parameters of the multiple devices; wherein the optimal solution set comprises optimal heat, optimal load variation, and corresponding condensate flow rates through the No. 5 low-pressure heater, the No. 6 low-pressure heater and the No. 7 low-pressure heater; obtaining a first regulating instruction of the first regulating valve and a second regulating instruction of the second regulating valve according to the optimal solution set; adjusting the opening degree of the first regulating valve according to the first regulating instruction, and adjusting the opening degree of the second regulating valve according to the second regulating instruction; the operating parameters of the multiple devices in the condensate system comprise: enthalpy value of 5th heater feedwater outlet, enthalpy value of condensate pump outlet condensate, enthalpy value of 6th heater feedwater outlet, enthalpy value of 7th heater feedwater outlet, unit power under variable working conditions, condensate flow rate under variable working conditions, unit power under initial working conditions and condensate flow rate under initial working conditions.

2. The method of claim 1, wherein, the particle swarm multi-objective optimization algorithm comprises: initializing population parameters; wherein the population parameters comprise population number, solution number in a Pareto solution set, iteration number, inertia weight; establishing a description of each particle position, solving an optimization target, and obtaining fitness values of each particle; randomly selecting part of particles in the particle swarm to perform mutation operation, determining the dominance relationship of particles before and after mutation, and retaining non-dominated solutions; comparing the dominance relationship between each particle and the historical individual optimal solution of the particle, and updating the non-dominated individual optimal solution; judging the dominance relationship between the particle and each solution in the current Pareto solution set, and storing a non-dominated solution set; determining a group leader particle according to a grid method and a roulette method, judging whether the Pareto front converges or not; if the Pareto front converges, the iteration optimization process is completed; if the Pareto front does not converge, the position and speed of each particle are updated. After the positions and velocities of the particles are updated, the step of returning to the step of establishing the position description of each particle, solving the optimization target, and obtaining the fitness value of each particle is performed.

3. The method of claim 1, wherein, The first adjustment instruction of the first adjustment valve and the second adjustment instruction of the second adjustment valve are obtained according to the optimal solution set, and the method comprises the steps of: According to the optimal solution set, the large bypass flow and the small bypass flow are obtained. According to the large bypass flow and the small bypass flow, the first adjustment instruction of the first adjustment valve and the second adjustment instruction of the second adjustment valve are obtained.

4. The method of claim 1, wherein, The method further comprises: In response to the unit load being lower than a preset threshold, the condensate water circulating to the condenser at the condensate water pump outlet is controlled by adjusting the condensate water recirculation adjustment valve.

5. A control device based on a condensate water system, characterized by, The condensate water system comprises a condenser, a condensate water pump, a No. 7 low-pressure heater, a No. 6 low-pressure heater, a No. 5 low-pressure heater, a deaerator, a first adjustment valve and a second adjustment valve, wherein the first end of the condenser is connected with the first end of the condensate water pump; the second end of the condensate water pump is connected with the first end of the No. 7 low-pressure heater, and the third end of the condensate water pump is connected with the first end of the deaerator through a large bypass; the first adjustment valve is arranged on the large bypass; the second end of the No. 7 low-pressure heater is connected with the first end of the No. 6 low-pressure heater; the second end of the No. 6 low-pressure heater is connected with the first end of the No. 5 low-pressure heater, and the third end of the No. 6 low-pressure heater is connected with the second end of the deaerator through a small bypass; the second adjustment valve is arranged on the small bypass; the second end of the No. 5 low-pressure heater is connected with the third end of the deaerator; the system further comprises a condensate water recirculation adjustment valve, wherein the fourth end of the condensate water pump is connected with the second end of the condenser through a condensate water recirculation circuit; the condensate water recirculation adjustment valve is arranged on the condensate water recirculation circuit; and the device comprises: A first acquisition module is configured to acquire operation parameters of a plurality of devices in a condensate water system. An optimization algorithm module is configured to obtain an optimal solution set by using a particle swarm multi-objective optimization algorithm according to the operation parameters of the plurality of devices; the optimal solution set comprises an optimal heat, an optimal load variation, and corresponding condensate water flow rates through the No. 5 low-pressure heater, the No. 6 low-pressure heater and the No. 7 low-pressure heater. A second acquisition module is configured to obtain a first adjustment instruction of the first adjustment valve and a second adjustment instruction of the second adjustment valve according to the optimal solution set. A large bypass control module is configured to adjust the opening degree of the first adjustment valve according to the first adjustment instruction. A small bypass control module is configured to adjust the opening degree of the second adjustment valve according to the second adjustment instruction. The operation parameters of the plurality of devices in the condensate water system comprise an enthalpy value of a feedwater outlet of a No. 5 heater, an enthalpy value of condensate water at an outlet of a condensate water pump, an enthalpy value of a feedwater outlet of a No. 6 heater, an enthalpy value of a feedwater outlet of a No. 7 heater, a unit power under a variable working condition, a condensate water flow rate under the variable working condition, a unit power under an initial working condition and a condensate water flow rate under the initial working condition.

6. The apparatus of claim 5, wherein, The optimization algorithm module is specifically configured to: Initialize population parameters; wherein the population parameters include population size, number of solutions in the Pareto solution set, iteration number, inertia weight; Establish a description of the position of each particle, solve the optimization objective, and obtain the fitness value of each particle; Randomly select part of the particles in the particle group to perform mutation operation, determine the dominance relationship before and after mutation, and retain non-dominated solutions; Compare the dominance relationship between each particle and its historical individual optimal solution, and update the non-dominated individual optimal solution; Determine the dominance relationship between the particle and each solution in the current Pareto solution set, and store the non-dominated solution set; Determine the group leader particle according to the grid method and the roulette method, and determine whether the Pareto front converges; if the Pareto front converges, the iterative optimization process is completed; if the Pareto front does not converge, update the position and speed of each particle; After updating the position and speed of each particle, return to the step of establishing a description of the position of each particle, solving the optimization objective, and obtaining the fitness value of each particle.

7. The apparatus of claim 5, wherein, The device further comprises a condensate water recirculation control module for controlling the circulation of condensate water at the outlet of the condensate pump to the condenser by adjusting the condensate water recirculation regulating valve in response to the unit load being lower than a preset threshold.

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