Construction method of cement production optimization scheduling model of polymerization energy storage

Abstract

The invention discloses a construction method of a cement production optimization scheduling model based on aggregation energy storage, and the method comprises the steps: analyzing a cement production process, and determining electric equipment and material conditions in each production process; based on the analysis of the cement plant production process in the step 1, a state task net block diagram of the cement production process is drawn according to working procedures and material conditions; determining decision variables and constraint conditions in the cement production process; analyzing charging and discharging conditions of the pumped storage device of the cement plant, and determining constraint conditions of charging and discharging of the pumped storage device; and under the constraint conditions of the step 3 and the step 4, establishing a production optimization scheduling model by taking the decision variable as a model variable and taking the minimum daily electricity purchase cost of the cement plant as a target. The method fully considers the production process limitation and production task requirements of the cement plant, guides the pumped storage unit to generate power in the peak load period and charge in the valley load period, and guarantees the safe, stable and economical operation of the power system.

Description

Technical Field

[0001] The present invention belongs to the technical field of cement production, and in particular relates to a method for constructing an optimized scheduling model for cement production with aggregated energy storage. Background Art

[0002] Currently, load-side participation in grid dispatch primarily considers residential and commercial loads, while ignoring the adjustable potential of industrial loads. Industrial loads offer advantages such as high power consumption, a large number of transferable loads, ease of centralized transformation, and high participation enthusiasm, meeting the requirements for load participation in grid dispatch. However, due to the complex operational issues currently associated with industrial loads, these can lead to over-regulation, significantly impacting normal enterprise production and limiting industrial enterprises' willingness to participate. Therefore, further exploring the flexible regulation resources of industrial loads while minimizing disruption to normal enterprise production is a critical issue that needs to be addressed. Early research on load modeling and its regulation characteristics, both domestically and internationally, focused primarily on the power characteristics of specific loads, such as arc furnaces in steel production, reduction furnaces in polysilicon production, and ball mills in cement production. In recent years, some progress has been made in modeling the cement production process, but research has mainly focused on the "two grinding and one burning" area. It does not take into account that each process in the cement production process must be carried out in a fixed production order, and it is impossible to fully tap the regulatory potential of the cement load. At the same time, energy storage is a current research hotspot, but there is little research on its collaborative participation in grid scheduling with the load side. Therefore, it is necessary to develop a modeling method for the cement production process that can take into account the strict process restrictions in the production process and the pumped storage limitations of pumped storage devices. Summary of the Invention

[0003] The purpose of the present invention is to address the shortcomings of the existing technology and provide a method for constructing an optimized scheduling model for cement production with aggregated energy storage. This method models the cement production process to address the interaction difficulties of cement enterprises caused by strict process restrictions and production requirements in the production process, and adds constraints on pumped storage devices to further improve the regulatory flexibility of pumped storage and cement load aggregation.

[0004] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0005] A method for constructing a cement production optimization scheduling model with aggregate energy storage includes the following steps:

[0006] Step 1: Analyze the cement production process and determine the electrical equipment and materials used in each production process;

[0007] Step 2: Based on the analysis of the cement plant production process in step 1, draw a state task network diagram of the cement production process according to the process and material conditions;

[0008] Step 3: Based on the electrical equipment and material analysis results of each production process obtained in step 1 and the state task network diagram in step 2, determine the decision variables and constraints in the cement production process;

[0009] Step 4: Analyze the charging and discharging conditions of the cement plant pumped storage power station to determine the charging and discharging constraints of the pumped storage device;

[0010] Step 5: Under the constraints of steps 3 and 4, a production optimization scheduling model is established with the decision variables as model variables and the goal of minimizing the daily electricity purchase cost of the cement plant.

[0011] Furthermore, the cement production process includes raw material crushing RMC, raw meal grinding RMG, raw meal homogenization RMH, fuel grinding FPP, clinker burning CF and cement grinding CG.

[0012] Furthermore, the core electrical equipment in the raw material crushing process is the crusher, the core electrical equipment in the raw meal grinding process is the raw meal grinder, the core electrical equipment in the raw meal homogenization process is the raw meal homogenization storage, the core electrical equipment in the fuel grinding process is the coal mill, the core electrical equipment in the clinker burning process is the rotary kiln, and the core electrical equipment in the cement grinding process is the cement grinder.

[0013] Furthermore, in the state task network diagram of step 2, raw material crushing, raw meal grinding, raw meal homogenization, fuel grinding, and cement grinding are classified as schedulable tasks, and clinker burning is classified as an unschedulable task.

[0014] Furthermore, it is characterized in that the decision variables in the cement production process in step 3 are the operating status of each core electrical equipment in each scheduling period, which is expressed as:

[0015]

[0016] Where: Represents the operating status of the i-th core power-consuming equipment of task k in time period t.

[0017] Furthermore, in step 3, constraints are established based on the material balance in the production process, the power balance of core electrical equipment, material storage, output, and continuous operation of the rotary kiln.

[0018] Furthermore, the constraints in step 3 are specifically:

[0019] Material balance constraints:

[0020]

[0021] Where: represents the available quantity of state object n in time period t, where is the initial number of state objects n, It represents the number of state objects n generated or consumed by a single core power-consuming device of task k in time period t. represents the total number of core power-consuming devices in working state for task k in time period t;

[0022] Power balance constraints:

[0023]

[0024] Where: represents the electricity consumption of the cement plant in period t, represents the power consumption of a single core power-consuming device of task k in time period t, represents the total number of core power-consuming devices in working state for task k in time period t;

[0025] Storage constraints:

[0026]

[0027] Where: LB n Indicates the storage lower limit of state object n, UB n Indicates the storage limit of state object n, Indicates the storage capacity of state object n;

[0028] Output constraints:

[0029]

[0030] Where: represents the quantity of final product cement at the end of the scheduling period T, represents the initial quantity of the final product cement at the beginning of the scheduling period, LB p,final Indicates the daily production requirement of cement;

[0031] Constraints on continuous operation of rotary kiln:

[0032] The rotary kiln equipment has been in continuous working state during the scheduling period:

[0033]

[0034] Where: Indicates the operating status of the rotary kiln system, the core electrical equipment for clinker burning, in time period t. Indicates that the rotary kiln is in working state during time period t. It means that the rotary kiln is in shutdown state during time period t.

[0035] Furthermore, in step 4, constraint conditions are established based on the charge and discharge power of the pumped storage power station, the overall discharge power, the storage energy limit, and the end-of-day energy limit.

[0036] Furthermore, the constraints established in step 4 are specifically:

[0037] ① Discharging and charging power constraints of pumped storage power stations

[0038]

[0039] Where: is the discharge power of the kth unit in the pumped storage power station in the tth period, They represent the upper and lower limits of the discharge power of each unit in the pumped storage power station, is the discharge state of the kth pumped storage unit in the tth period, Indicates that it is in the discharge state. Indicates that it is not in the discharge state, K is the number of units in the pumped storage power station;

[0040]

[0041] Where: is the charging power of the kth unit in the pumped storage power station in the tth period, Indicates the constant charging power of each unit in the pumped storage power station, is the charging state of the kth pumped storage unit in the tth period, Indicates that it is in charging state. Indicates that it is not in charging state;

[0042] ②Power equality constraint

[0043]

[0044] Where: is the overall discharge power of the pumped storage power station, that is, the power generation of the pumped storage power station in time period t;

[0045] ③Charge and discharge state constraints

[0046]

[0047] Where, represents the discharge state of the kth pumped storage unit in the tth period, represents the charging state of the jth pumped storage unit in the tth period; this formula ensures that the charging and discharging states of each unit in the pumped storage power station are consistent;

[0048] ④Energy state constraints of pumped storage power stations

[0049]

[0050] Where: EUB s 、ELB s are the upper and lower limits of the energy that can be stored in a pumped storage power station, η is the charge-discharge conversion efficiency of the pumped storage unit, represents the charging power of the kth unit in the pumped storage power station in the τth period, represents the discharge power of the kth unit in the pumped storage power station in the τth period, and E0 represents the initial energy of the pumped storage power station;

[0051] ⑤ Final energy constraint

[0052]

[0053] This formula ensures that the water level of the pumped storage unit remains unchanged after a single day of scheduling.

[0054] Furthermore, the production optimization scheduling model established in step 5 is:

[0055] Assuming that the day-ahead dispatching step size is δ and the total number of daily dispatching periods is T, the objective function for minimizing the daily electricity purchase cost of the cement plant is as follows:

[0056]

[0057] Where: C is the daily electricity purchase cost of the cement plant, is the time-of-use electricity price corresponding to the local period t stipulated by the cement enterprise, is the electricity consumption of the cement enterprise in period t, that is, the sum of the electricity consumption of each core power-consuming equipment in period t in the decision variable, is the power generation of the pumped storage power station in time period t.

[0058] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention utilizes the state-task network method to abstract materials into states and processes into tasks, clarifies the situations of each process generating / consuming materials and occupying / releasing equipment, constructs constraints such as material quantity, production tasks, and equipment operation requirements, and at the same time aggregates the peak-shaving resources of the pumped-storage device, guiding the cement plant to actively adjust the production plan to perform staggered and peak-avoiding production without affecting normal production, guiding the pumped-storage unit to generate electricity during peak load periods and charge during valley load periods without affecting equipment safety, and further tapping its potential for participating in grid interaction while ensuring normal production of the cement plant. At the same time, the present invention aggregates the adjustable capacity of the pumped-storage device on the energy storage side, and realizes the overall aggregation optimization of the pumped-storage unit and the cement plant load taking into account production constraints, which is conducive to achieving peak shaving and valley filling, ensuring the safe, stable and economical operation of the power system, and at the same time promoting the consumption of new energy and reducing the amount of wind and solar power abandoned. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 This is a flow chart of a method for constructing a cement production optimization scheduling model with polymer energy storage according to an embodiment of the present invention;

[0060] Figure 2 This is a production flow chart of the dry process cement production technology according to an embodiment of the present invention;

[0061] Figure 3 This is a state task network diagram of the cement production process according to an embodiment of the present invention. DETAILED DESCRIPTION

[0062] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0063] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0064] The present invention will be further described below with reference to specific examples, but they are not intended to limit the present invention.

[0065] The power demand response method based on the discontinuous production process and storage capacity of cement enterprises only conducts statistical analysis on the interruptible equipment in the cement production process, and collects the average operating time and operating power of each equipment as the basis to complete the setting of constraints. However, cement plants often contain multiple production lines, involving a large number of equipment and complex types. The statistical workload is large, and a large number of variables need to be set, and the solution speed is correspondingly reduced. At the same time, there are a large number of auxiliary equipment with low power and weak regulation capabilities. Therefore, how to model the cement production process while taking into account the solution accuracy and solution speed is a problem that needs further research; at the same time, how to further consider the coordination of cement plants and other equipment (such as energy storage units, new energy units, etc.) to achieve source-grid-load-storage integration and further tap the overall regulation potential is also a problem that needs to be solved. In view of the above problems in the prior art, the embodiment of the present invention discloses a method for constructing a cement production optimization scheduling model with aggregated energy storage, such as Figure 1 As shown, the following steps are included:

[0066] Step 1: Analyze the cement production process and determine the electrical equipment and materials used in each production process;

[0067] As a high-energy-consuming industrial user, cement plants consume large amounts of electricity and have adjustable potential. However, the production process has strict process restrictions, so the specific process of cement production must be clarified first. For the new dry process cement production technology, the production process is as follows: Figure 2 As shown in the figure, it mainly includes six processes: raw material crushing, raw material grinding, raw material homogenization, fuel grinding, clinker burning and cement grinding. Storage facilities are set up between each process to make the load adjustment of the cement plant more flexible. Specifically, each process is as follows:

[0068] (1) Raw material crushing (RMC)

[0069] The raw material crushing process crushes raw materials such as limestone, clay, and iron ore. The crushed raw materials are then stored and pre-homogenized in a pre-homogenization yard using scientific stacking and reclaiming techniques. Considering the power consumption of each piece of equipment, the core power-consuming equipment in this process is the crusher. The materials consumed are various raw materials for cement production, including limestone and iron ore, and the resulting material is small, crushed raw materials.

[0070] (2) Raw meal grinding (RMG)

[0071] The raw meal grinding process grinds the dried small-particle raw materials until a fine raw meal powder of the appropriate particle size is obtained. The ground raw meal is then stored in a raw meal storage tank. Considering the power consumption of each device, the core power-consuming equipment in this process is the raw meal grinder. It consumes small-particle raw materials and produces fine raw meal powder.

[0072] (3) Raw meal homogenizing (RMH)

[0073] The raw meal homogenization process homogenizes the ground raw meal to achieve a uniform and stable mix. The raw meal homogenization silo integrates mixing, homogenization, and kiln charge storage. Considering the power consumption of each device, the core power-consuming equipment in this process is the raw meal homogenization silo. It consumes raw meal powder and produces raw meal (i.e., kiln charge).

[0074] (4) Fuel powder polishing (FPP)

[0075] The fuel grinding process grinds the crushed coal into pulverized coal for use in the clinker burning process. Considering the power consumption of various equipment, the core power-consuming equipment in this process is the coal mill, which consumes small-particle coal and produces pulverized coal.

[0076] (5) Clinker firing (CF)

[0077] The clinker firing process preheats and decomposes the raw meal entering the kiln, then fires it into clinker. The resulting clinker is cooled and stored in a clinker silo. Considering the power consumption of each device, the core power-consuming equipment in this process is the rotary kiln. Because this core power-consuming rotary kiln system must operate continuously under normal circumstances and cannot be shut down or shifted, the clinker firing task is considered a non-schedulable task. The raw meal and pulverized coal are consumed, and clinker is produced.

[0078] (6) Cement grinding (CG)

[0079] The cement grinding process grinds clinker, limestone, gypsum, and other materials into fine cement powder of appropriate particle size, which is then stored in the finished cement product warehouse. Considering the power consumption of each device, the core power-consuming equipment in this process is the cement grinder. The materials consumed are clinker, limestone, gypsum, and other materials, and the final product is fine cement powder.

[0080] Step 2: Based on the analysis of the cement plant production process in step 1, draw a state task network diagram of the cement production process according to the process and material conditions;

[0081] In this embodiment, the state task network (STN) diagram contains two types of nodes, task nodes and state nodes, where task nodes represent processing operations, including schedulable tasks and unschedulable tasks; state nodes represent different states of materials, namely raw materials, intermediate products and final products; the two are connected by connecting arcs to represent the interactive relationship between tasks and states, that is, the state task network diagram abstracts the process and materials into tasks and states respectively, and describes the flow of materials. Based on the analysis of the cement plant production process in step 1, the state task network diagram of the cement production process can be drawn as follows: Figure 3 .

[0082] The raw material crushing task consumes raw materials such as limestone to produce the intermediate small-particle raw materials; the raw meal grinding task consumes the intermediate small-particle raw materials to produce the intermediate raw meal fine powder; the raw meal homogenization task consumes the intermediate raw meal fine powder to produce the intermediate kiln charge; the fuel grinding task consumes the raw material small-particle coal to produce the intermediate pulverized coal; the unschedulable clinker burning task consumes the intermediate kiln charge and pulverized coal to produce the intermediate clinker; and the cement grinding task consumes the intermediate clinker to produce the final product, cement. Because gypsum and other mixed materials involve fewer processes and have sufficient reserves, they are not considered in the cement grinding task; however, they are still represented in the STN diagram for process completeness. This state-task network diagram abstracts materials into states and processes into tasks. This diagram clearly illustrates the generation and consumption of materials, occupation, and electrical equipment by each process.

[0083] Step 3: Based on the analysis results of step 1 and the state task network diagram in step 2, determine the constraints in the cement production process;

[0084] Through the analysis of steps 1 and 2, the decision variables and constraints in the cement production process are determined, which can be expressed as follows:

[0085] (1) Decision variables

[0086] The decision variables are the operating status of each core power-consuming equipment in each scheduling period, that is, the operating status of the core power-consuming equipment in each process in step 1, which can be expressed as:

[0087]

[0088] Where: It represents the operating status of the i-th core power-consuming device of task k in time period t, where 1 indicates that the device is in working state and 0 indicates that the device is in shutdown state.

[0089] (2) Analyze the material usage, storage conditions, and production load of the cement production process and construct the following constraints:

[0090] 1) Material balance constraints

[0091]

[0092] Where: represents the available quantity of state object n in time period t, where is the initial number of state objects n, It represents the amount of state object n generated or consumed by a single core power-consuming device of task k in time period t (positive value indicates generation, negative value indicates consumption). represents the total number of core power-consuming devices in working state during task k in time period t, N represents the total number of state objects, and T represents the total scheduling time;

[0093] 2) Power balance constraints

[0094]

[0095] Where: represents the electricity consumption of the cement plant in period t, represents the power consumption of a single core power-consuming device of task k in time period t, represents the total number of core power-consuming devices in working state for task k in time period t;

[0096] 3) Storage constraints

[0097]

[0098] Where: LBn Indicates the storage lower limit of state object n, UB n Indicates the storage limit of state object n, Indicates the storage capacity of state object n;

[0099] 4) Output constraints

[0100]

[0101] Where: represents the quantity of final product cement at the end of the scheduling period T, represents the initial quantity of the final product cement at the beginning of the scheduling period, LB p,final Indicates the daily production requirement of cement;

[0102] 5) Constraints on continuous operation of rotary kiln

[0103] Since the rotary kiln system must work continuously under normal circumstances, except for occasional inventory control shutdowns when cement demand is low, there are only one or two shutdowns for planned maintenance each year. Therefore, the rotary kiln equipment should be in continuous working condition during the scheduling period:

[0104]

[0105] Where: Indicates the operating status of the rotary kiln system, the core electrical equipment for clinker burning, in time period t. Indicates that the rotary kiln is in working state during time period t. It means that the rotary kiln is in shutdown state during time period t.

[0106] By proposing production process constraints, it is possible to ensure that cement plants can meet their production process restrictions and production task requirements while adjusting their production plans to participate in power grid optimization scheduling, without affecting normal production.

[0107] Step 4: Analyze the charging and discharging conditions of the cement plant's pumped storage device to determine the charging and discharging constraints of the pumped storage device;

[0108] The working conditions of the cement plant pumped storage device are analyzed, and the constraints of its pumped storage charging and discharging are fully considered, specifically:

[0109] ① Discharging and charging power constraints of pumped storage power stations

[0110]

[0111] Where: is the discharge power of the kth unit in the pumped storage power station in the tth period, They represent the upper and lower limits of the discharge power of each unit in the pumped storage power station, is the discharge state of the kth pumped storage unit in the tth period, Indicates that it is in the discharge state. Indicates that it is not in the discharge state, K is the number of units in the pumped storage power station;

[0112]

[0113] Where: is the charging power of the kth unit in the pumped storage power station in the tth period, Indicates the constant charging power of each unit in the pumped storage power station, is the charging state of the kth pumped storage unit in the tth period, Indicates that it is in charging state. Indicates that it is not in charging state;

[0114] ②Power equality constraint

[0115]

[0116] Where: is the overall discharge power of the pumped storage power station, that is, the power generation of the pumped storage power station in time period t;

[0117] ③Charge and discharge state constraints

[0118]

[0119] Where, represents the discharge state of the kth pumped storage unit in the tth period, represents the charging state of the jth pumped storage unit in the tth period;

[0120] This formula ensures that the charge and discharge status of each unit in the pumped storage power station is consistent;

[0121] ④Energy state constraints of pumped storage power stations

[0122]

[0123] Where: EUB s 、ELB s are the upper and lower limits of the energy that can be stored in a pumped storage power station, η is the charge-discharge conversion efficiency of the pumped storage unit, represents the charging power of the kth unit in the pumped storage power station in the τth period, represents the discharge power of the kth unit in the pumped storage power station in the τth period, and E0 represents the initial energy of the pumped storage power station;

[0124] ⑤ Final energy constraint

[0125]

[0126] This formula ensures that the water level of the pumped storage unit remains unchanged after a single day of scheduling.

[0127] Step 5: Under the constraints of Steps 3 and 4, a production optimization scheduling model is established with the decision variables in Step 3 as model variables and the goal of minimizing the daily electricity purchase cost of the cement plant;

[0128] In this embodiment, the day-ahead scheduling step size is δ, the total number of daily scheduling periods is T, and the production optimization scheduling model is constructed with the goal of minimizing the daily electricity purchase cost of the cement plant, which is expressed as follows:

[0129]

[0130] Where: C is the daily electricity purchase cost of the cement plant, is the time-of-use electricity price corresponding to the local period t stipulated by the cement enterprise, is the electricity consumption of the cement enterprise in time period t, that is, the sum of the electricity consumption of each power-consuming equipment in the decision variable at time t, is the power generation of the pumped storage power station in time period t.

[0131] The cement production process constraints given in step 3 are specifically expressed as:

[0132]

[0133] The charge and discharge constraints of the pumped storage device given in step 4 are:

[0134]

[0135] Based on the above constraints, the production optimization scheduling model is optimized to solve the decision variables, which can obtain the operating time and status of each electrical equipment in each scheduling time period. Based on the solution results, the enterprise controls the start and stop time of each electrical equipment to achieve the goal of minimizing electricity costs.

[0136] This embodiment fully considers the mutual influence of various processes in the cement production process, accurately proposes the production process restrictions and production task requirements of the cement plant, and at the same time aggregates the side peak-shaving resources of pumped storage, guiding the cement plant to actively adjust the production plan to perform staggered and peak-avoiding production without affecting normal production, and guiding the pumped storage units to generate electricity during peak load periods and charge during low load periods without affecting equipment safety, which is conducive to achieving peak shaving and valley filling, ensuring the safe, stable and economical operation of the power system, and at the same time promoting the consumption of new energy and reducing the amount of wind and solar power curtailment.

[0137] The above are only preferred embodiments of the present invention and do not limit the implementation mode and protection scope of the present invention. For those skilled in the art, it should be aware that all solutions obtained by equivalent substitutions and obvious changes made using the contents of the present invention specification should be included in the protection scope of the present invention.

Claims

1. A method for constructing an optimal scheduling model for cement production with aggregate energy storage, characterized in that: The steps include: Step 1: Analyze the cement production process and determine the electrical equipment and materials used in each production process; Step 2: Based on the analysis of the cement plant production process in step 1, a state task network diagram of the cement production process is drawn according to the process and material conditions; Step 3: Based on the electrical equipment and material analysis results in each production process obtained in step 1 and the state task network diagram in step 2, determine the decision variables and constraints in the cement production process; Step 4: Analyze the charging and discharging conditions of the cement plant pumped storage power station to determine the constraint conditions for charging and discharging of the pumped storage power station; Step 5: Under the constraints of Steps 3 and 4, a production optimization scheduling model is established with the decision variables as model variables and the goal of minimizing the daily electricity purchase cost of the cement plant.

2. The method for constructing an optimal scheduling model for cement production with polymer energy storage according to claim 1, characterized in that: The cement production process includes raw material crushing RMC, raw meal grinding RMG, raw meal homogenization RMH, fuel grinding FPP, clinker burning CF and cement grinding CG.

3. The method for constructing an optimal scheduling model for cement production with polymer energy storage according to claim 2, characterized in that: The core electrical equipment in the raw material crushing process is the crusher, the core electrical equipment in the raw meal grinding process is the raw meal grinder, the core electrical equipment in the raw meal homogenization process is the raw meal homogenization storage, the core electrical equipment in the fuel grinding process is the coal mill, the core electrical equipment in the clinker burning process is the rotary kiln, and the core electrical equipment in the cement grinding process is the cement grinder.

4. The method for constructing an optimal scheduling model for cement production with polymer energy storage according to claim 2, characterized in that: In the state task network diagram drawn in step 2, raw material crushing, raw material grinding, raw material homogenization, fuel grinding, and cement grinding are classified as schedulable tasks, and clinker burning is classified as an unschedulable task.

5. The method for constructing an optimal scheduling model for cement production with polymer energy storage according to claim 3, characterized in that: The decision variables in the cement production process in step 3 are the operating status of each core power-consuming equipment in each scheduling period, expressed as: Where: Represents the operating status of the i-th core power-consuming equipment of task k in time period t.

6. The method for constructing an optimal scheduling model for cement production with polymer energy storage according to claim 3, characterized in that: In step 3, constraints are established based on the material balance in the production process, the power balance of core power-consuming equipment, material storage, output, and continuous operation of the rotary kiln.

7. The method for constructing an optimal scheduling model for cement production with polymer energy storage according to claim 6, characterized in that: The specific constraints are: Material balance constraints: Where: represents the available quantity of state object n in time period t, where is the initial number of state objects n, It represents the number of state objects n generated or consumed by a single core power-consuming device of task k in time period t. represents the total number of core power-consuming devices in working state for task k in time period t; Power balance constraints: Where: represents the power consumption of the cement plant in time period t, represents the power consumption of a single core power-consuming device of task k in time period t, represents the total number of core power-consuming devices in working state for task k in time period t; Storage constraints: Where: LB n Indicates the storage lower limit of state object n, UB n Indicates the storage limit of state object n, Indicates the storage capacity of state object n; Production Constraints: Where: represents the quantity of final product cement at the end of the scheduling period T, represents the initial quantity of the final product cement at the beginning of the scheduling period, LB p,final Indicates the daily production requirement of cement; Constraints on continuous operation of rotary kiln: The rotary kiln equipment has been in continuous working state during the dispatching period: Where: Indicates the operating status of the rotary kiln system, the core electrical equipment for clinker burning, in time period t. Indicates that the rotary kiln is in working state during time period t. It means that the rotary kiln is in shutdown state during time period t.

8. The method for constructing an optimal scheduling model for cement production with polymer energy storage according to claim 1, characterized in that: In step 4, constraints are established based on the charging and discharging power of the pumped storage power station, the overall discharge power, the storage energy limit and the end-of-day energy limit.

9. The method for constructing an optimal scheduling model for cement production with polymer energy storage according to claim 8, characterized in that: The constraints established in step 4 are as follows: ① Discharging and charging power constraints of pumped storage power stations: Where: is the discharge power of the kth unit in the pumped storage power station in the tth period, They represent the upper and lower limits of the discharge power of each unit in the pumped storage power station. is the discharge state of the kth pumped storage unit in the tth period, Indicates that it is in the discharge state. It indicates that it is not in the discharging state, and K is the number of units in the pumped storage power station; Where: is the charging power of the kth unit in the pumped storage power station in the tth period, It represents the constant charging power of each unit in the pumped storage power station. is the charging state of the kth pumped storage unit in the tth period, Indicates that it is in charging state. Indicates that it is not in charging state; ②Power equation constraint: Where: is the overall discharge power of the pumped storage power station, that is, the power generation of the pumped storage power station in time period t; ③Charge and discharge state constraints: In the formula, represents the discharge state of the kth pumped storage unit in the tth period, represents the charging state of the jth pumped storage unit in the tth period; this formula ensures that the charging and discharging states of each unit in the pumped storage power station are consistent; ④Energy state constraints of pumped storage power station: Where: EUB s 、ELB s are the upper and lower limits of the energy that can be stored in a pumped storage power station, η is the charge-discharge conversion efficiency of the pumped storage unit, represents the charging power of the kth unit in the pumped storage power station in the τth period, represents the discharge power of the kth unit in the pumped storage power station in the τth period, and E0 represents the initial energy of the pumped storage power station; ⑤ Final energy constraint: This formula ensures that the water level of the pumped storage unit remains unchanged after a single day of scheduling.

10. The method for constructing an optimal scheduling model for cement production with polymer energy storage according to claim 1, characterized in that: The production optimization scheduling model established in step 5 is: Assuming that the day-ahead dispatching step length is δ and the total number of daily dispatching periods is T, the objective function for minimizing the daily electricity purchase cost of the cement plant is as follows: Where: C is the daily electricity purchase cost of the cement plant, is the time-of-use electricity price corresponding to the time period t stipulated by the local cement enterprise, is the electricity consumption of the cement enterprise in time period t, that is, the sum of the electricity consumption of each core power-consuming equipment in the decision variable at time t, is the power generation of the pumped storage power station in time period t.

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