Energy storage and typical industrial load collaborative polymerization adjustable capacity evaluation method and medium

Abstract

The invention discloses an energy storage and typical industrial load collaborative polymerization adjustable capacity evaluation method and a medium, and the method comprises the steps: analyzing a cement production process and a polycrystalline silicon production process, and obtaining a corresponding production process analysis result; respectively determining corresponding state task diagrams according to the analysis results of the two production processes; respectively modeling a cement production process and a polycrystalline silicon production process according to the two state task diagrams; and determining a charging and discharging constraint condition of the pumped storage power station, constructing an aggregation adjustable capacity evaluation model according to a modeling result and the charging and discharging constraint condition, and solving the evaluation model to obtain the maximum adjustable capacity of power grid dispatching, thereby realizing aggregation adjustable capacity evaluation. The method can more accurately determine the production plan of each industrial load participating in power grid dispatching and the operation plan of the pumped storage unit on the premise of guaranteeing normal production, can realize adjustable potential aggregation of the energy storage side and the load side, and provides more theoretical basis for load and energy storage participating in a power grid peak regulation scene.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid dispatching, and in particular to an aggregate adjustable capacity evaluation method and medium for coordinated energy storage and typical industrial loads. Background Art

[0002] At present, the load side participating in grid dispatching mainly considers objects such as residential loads and commercial loads, while ignoring the adjustable potential of industrial loads. Industrial loads have the advantages of large power consumption, many transferable loads, centralized and easy transformation, and high participation enthusiasm, which meet the needs of load participation in grid dispatching. However, due to the complex operational problems in some aspects of the current industrial loads, it may cause excessive load adjustment, which will have a great impact on the normal production of enterprises, resulting in limited willingness of industrial enterprises to participate. Therefore, how to further explore the flexible adjustment resources of industrial loads and accurately evaluate the adjustable capacity of loads without affecting the normal production of enterprises as much as possible is an important problem that needs to be solved at present.

[0003] In the early stage, the research on load modeling and its regulation characteristics at home and abroad mainly focused 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 the modeling of cement production processes, but the research did not take into account that each process in the cement production process must be carried out in a fixed production order, and the regulation potential of cement load cannot be fully explored; there are also few studies on the modeling of polysilicon production processes, and the core of the research is still focused on reduction furnace equipment. The mutual coupling relationship between the various processes in the polysilicon production process is not considered, and the exploration of the adjustable potential of polysilicon load is insufficient. At the same time, as a current research hotspot, there is little research on energy storage and load-side collaborative participation in grid dispatching. Therefore, it is necessary to provide an adjustable capacity evaluation scheme for energy storage and load-side collaborative participation in grid dispatching that considers the coupling relationship between the production processes and electrical equipment and materials in the cement production process and polysilicon production process, as well as the coupling relationship between production processes. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems in the related art to a certain extent. To this end, the first purpose of the present invention is to provide a typical industrial load collaborative aggregate adjustable capacity assessment method, which can more accurately determine the production plan of each industrial load participating in the grid dispatching and the operation plan of the pumped storage unit under the premise of ensuring normal production, realize the aggregation of the adjustable potential of the energy storage side and the load side, and provide more theoretical basis for the load and energy storage to participate in the grid peak regulation scenario.

[0005] A second object of the present invention is to provide a computer-readable storage medium.

[0006] A third object of the present invention is to provide an electronic device.

[0007] To achieve the above object, the present invention is implemented through the following technical solutions:

[0008] A method for evaluating the aggregate adjustable capacity of energy storage and typical industrial loads, comprising:

[0009] Analyze the cement production process and polysilicon production process to obtain the corresponding production process analysis results;

[0010] Determine the corresponding state task diagrams according to the analysis results of the production processes of the two;

[0011] Modeling the cement production process and the polysilicon production process respectively according to their state task graphs;

[0012] Determine the charging and discharging constraints of the pumped storage power station, build an aggregated adjustable capacity evaluation model based on the modeling results and the charging and discharging constraints, and solve the evaluation model to obtain the maximum adjustable capacity of the power grid dispatch, thereby realizing the aggregated adjustable capacity evaluation.

[0013] Preferably, the step of analyzing the cement production process and the polysilicon production process to obtain corresponding production process analysis results comprises:

[0014] Each process of the cement production process and the polysilicon production process is analyzed to obtain the coupling relationship between each process of the cement production process and the polysilicon production process and materials, electrical equipment and whether the process task is a schedulable task.

[0015] Preferably, a state task diagram of the corresponding production process is determined according to the coupling relationship.

[0016] Preferably, the state task diagram includes task nodes and state nodes, wherein the task nodes include schedulable task nodes and unschedulable task nodes, and the task nodes indicate whether the corresponding process tasks are schedulable; the state nodes indicate different states of materials, and the states of materials include raw material states, intermediate product states, and final product states.

[0017] Preferably, the step of modeling the cement production process and the polysilicon production process comprises: determining decision variables and constraints of the cement production process and the polysilicon production process respectively.

[0018] Preferably, the decision variables of the cement production process and the polysilicon production process are respectively the operating status of each electrical equipment in the cement production process and the polysilicon production process in each scheduling period; the constraints of the cement production process include material balance constraints, power balance constraints, material storage constraints, cement output constraints and rotary kiln continuous operation constraints; the constraints of the polysilicon production process include material balance constraints, power balance constraints, material storage constraints, polysilicon output constraints, purification task start constraints and reduction task start constraints.

[0019] Preferably, the charging and discharging constraints of the pumped-storage power station include at least the charging and discharging electric power constraints of the pumped-storage power station, the overall discharge power constraints, the charging and discharging state constraints of each unit and the stored energy state constraints.

[0020] Preferably, the objective function of the aggregate adjustable capacity evaluation model is expressed as follows:

[0021]

[0022] Among them, C is the daily aggregate adjustable capacity of the pumped storage power station, cement plant and polysilicon plant, is the electricity consumption of the cement plant in period t, is the power consumption of the polysilicon plant in period t, is the power generation of the pumped storage power station in time period t, is the baseline load of the three aggregated in time period t, T is the total number of daily scheduling periods;

[0023] The constraints of the aggregate adjustable capacity assessment model include the charging and discharging constraints of the pumped storage power station, the constraints of the cement production process and the constraints of the polysilicon production process.

[0024] To achieve the above-mentioned purpose, the second aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the above-mentioned method for evaluating the aggregated adjustable capacity of energy storage in coordination with typical industrial loads is implemented.

[0025] To achieve the above-mentioned purpose, the third aspect of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the above-mentioned method for evaluating the aggregated adjustable capacity of energy storage and typical industrial loads is implemented.

[0026] The present invention has at least the following technical effects:

[0027] The present invention provides an evaluation scheme for adjustable capacity of load-storage collaboratively participating in grid dispatching, and specifically relates to an evaluation method for adjustable capacity of energy storage and typical flexible industrial load aggregation considering production process constraints. The method takes a new dry cement production process as an example, analyzes the entire cement production process, divides the processes based on storage settings, further determines the interactive relationship between each process and generated / consumed materials and occupied / released electrical equipment, and proposes various constraints of cement load in the production process. The method takes a modified Siemens polysilicon production process as an example, analyzes the entire polysilicon production process, divides the processes and further determines the interactive relationship between each process and materials and electrical equipment, and proposes various constraints of polysilicon load in the production process. For a pumped storage system, the method considers the limitations of the charging and discharging process of the unit device, and then constructs an adjustable capacity evaluation model with the maximum adjustable capacity of the pumped storage power station, cement load and polysilicon load as the optimization target. The evaluation model proposed in the present invention specifically analyzes the interactive relationship between each process and materials, electrical equipment, etc., as well as the coupling relationship between each process. It quantifies the mutual influence between multiple processes by constraining materials. It can more accurately determine the production plan of each industrial load participating in power grid dispatching and the operation plan of pumped-storage units under the premise of ensuring normal production, and realizes the aggregation of the adjustable potential of the energy storage side and the load side, providing more theoretical basis for the participation of load and energy storage in power grid peak regulation scenarios.

[0028] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 Flow chart of a method for evaluating the aggregated adjustable capacity of energy storage and typical industrial loads in accordance with an embodiment of the present invention.

[0030] Figure 2 The figure is a cement production flow chart of an embodiment of the present invention.

[0031] Figure 3 The polysilicon production flow chart of an embodiment of the present invention.

[0032] Figure 4 This is a state task network diagram of the cement production process according to an embodiment of the present invention.

[0033] Figure 5 The figure is a schematic diagram of the physical structure of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0034] The present embodiment is described in detail below, and examples of the embodiment 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 invention, and should not be construed as limiting the present invention.

[0035] In order to solve the technical problems described in the background technology, this embodiment provides an aggregated adjustable capacity evaluation method and medium for energy storage and typical industrial loads. This method mainly targets the problem of mutual influence of multiple processes in the production process of typical flexible industrial loads. The state task network method is used to model the cement and polysilicon production processes to cope with the interaction problems of industrial enterprises caused by strict process restrictions and production requirements in the production process, and pumped storage devices are added to further improve the adjustment flexibility of pumped storage and industrial load aggregation. The method can more accurately determine the production plan of each industrial load participating in the grid dispatching and the operation plan of the pumped storage unit under the premise of ensuring normal production, and realizes the aggregation of adjustable potential on the energy storage side and the load side, which can provide more theoretical basis for the participation of load and energy storage in the grid peak regulation scenario.

[0036] The following describes, with reference to the accompanying drawings, a method and medium for evaluating the aggregated adjustable capacity of energy storage and typical industrial loads in accordance with this embodiment.

[0037] Figure 1 Flow chart of the method for evaluating the aggregate adjustable capacity of energy storage and typical industrial loads in accordance with an embodiment of the present invention. Figure 1 As shown, the method includes:

[0038] Step S1: Analyze the cement production process and the polysilicon production process to obtain corresponding production process analysis results.

[0039] Among them, the steps of analyzing the cement production process and the polysilicon production process to obtain the corresponding production process analysis results include: analyzing each process of the cement production process and the polysilicon production process to obtain the coupling relationship between each process of the cement production process and the polysilicon production process and whether the materials, electrical equipment and process tasks are schedulable tasks.

[0040] Specifically, the cement production process and polysilicon production process are analyzed as follows:

[0041] (1) Analysis of cement production process

[0042] As a high-energy-consuming industrial user, cement plants consume a lot of electricity and have adjustable potential, but the production process has strict process restrictions, so the specific process of cement production must be clarified first. For the new dry cement production technology, the production process is as follows Figure 2As shown, it mainly includes six processes, namely raw material crushing, raw meal grinding, raw meal homogenization, fuel grinding, clinker burning and cement grinding. Storage facilities are set between each process, which makes the load adjustment of the cement plant more flexible.

[0043] 1) Raw Material Crushing (RMC)

[0044] The raw material crushing process crushes raw materials such as limestone, clay, and iron ore. The crushed raw materials are stored and pre-homogenized in the pre-homogenization yard according to scientific stacking and reclaiming technology. Considering the power consumption of each equipment, the core power-consuming equipment used in this process is the crusher, and the materials consumed are various raw materials for cement production, including limestone, iron ore, etc. The generated materials are small-particle raw materials after crushing.

[0045] 2) Raw Meal Grinding (RMG)

[0046] The raw material grinding process grinds the small-particle raw materials after drying until the raw material fine powder with appropriate particle size is obtained. The ground raw materials are stored in the raw material reserve. Considering the power consumption of each equipment, the core power-consuming equipment used in this process is the raw material grinding machine, which consumes small-particle raw materials and produces raw material fine powder.

[0047] 3) Raw Meal Homogenizing (RMH)

[0048] The raw material homogenization process homogenizes the fine raw material powder after grinding to make the raw material mixed evenly and maintain a stable state. The raw material homogenization warehouse realizes the integrated functions of stirring, homogenization and kiln material storage. Considering the power consumption of each equipment, the core power-consuming equipment used in this process is the raw material homogenization warehouse, the material consumed is the raw material powder, and the material generated is the raw material entering the kiln (i.e. kiln material).

[0049] 4) Fuel Powder Polishing (FPP)

[0050] The fuel grinding process grinds the crushed coal blocks to obtain coal powder, which is then used in the clinker burning process. Considering the power consumption of each device, the core power-consuming equipment used in this process is the coal mill, which consumes small-particle coal blocks and produces coal powder.

[0051] 5) Clinker Firing (CF)

[0052] The clinker burning process preheats and decomposes the raw materials entering the kiln and burns the clinker. The generated clinker is stored in the clinker warehouse after cooling. Considering the power consumption of each equipment, the core power-consuming equipment used in this process is the rotary kiln. Since the core power-consuming equipment rotary kiln system needs to work continuously under normal circumstances and cannot be shut down or transfer load, the clinker burning task is a non-schedulable task. The materials consumed are the raw materials entering the kiln and coal powder, and the generated materials are clinker.

[0053] 6) Cement Grinding (CG)

[0054] The cement grinding process grinds clinker, limestone, gypsum, etc. to obtain cement fine powder with appropriate particle size and stores it in the cement finished product warehouse. Considering the power consumption of each equipment, the core power-consuming equipment used in this process is the cement grinding machine, the materials consumed are clinker, limestone, gypsum, etc., and the generated material is the cement fine powder finished product.

[0055] (2) Analysis of polysilicon production process

[0056] As a typical industrial production user, polysilicon plants consume a lot of electricity and have a certain adjustable potential, but the production process has strict process restrictions. Therefore, it is necessary to first clarify the specific production process of polysilicon and analyze the interaction between each process and materials and electrical equipment in the production process. Figure 3 As shown, it mainly includes five processes: trichlorosilane synthesis, trichlorosilane purification, trichlorosilane reduction, tail gas recovery and silicon tetrachloride hydrogenation.

[0057] An analysis of the generation / consumption of materials and occupation / release of electrical equipment in each process is shown in Table 1.

[0058] Table 1 The interaction between each process and materials and electrical equipment in the polysilicon production process

[0059]

[0060] Step S2: Determine the corresponding state task diagrams according to the analysis results of the production processes of the two.

[0061] Among them, the state task diagram of the corresponding production process can be determined according to the coupling relationship determined in step S1. The state task diagram is a state task network (STN) block diagram, which includes two types of nodes: task nodes and state nodes, wherein the task node represents the processing operation, that is, whether the corresponding process task is schedulable, including schedulable task nodes and unschedulable task nodes; the state node represents the different states of the material, that is, the raw material, intermediate product and final product state. The two are connected by a connecting arc to represent the interactive relationship between tasks and states. That is, the state task network frame 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 S1, the state task network frame diagram of the cement production process can be drawn as follows: Figure 4 shown.

[0062] Among them, the raw material crushing task consumes raw materials such as limestone to generate intermediate small-particle raw materials; the raw material grinding task consumes intermediate small-particle raw materials to generate intermediate raw material fine powder; the raw material homogenization task consumes intermediate raw material fine powder to generate intermediate kiln material; the fuel grinding task consumes raw material small-particle coal blocks to generate intermediate coal powder; the unschedulable task clinker burning task consumes intermediate kiln material and coal powder to generate intermediate clinker; the cement grinding task consumes intermediate clinker to generate the final product cement. Since gypsum and other mixed materials involve fewer processes and sufficient reserves, their participation is not considered in the cement grinding task, but for the sake of process integrity, they are still represented in the STN block diagram.

[0063] Step S3: Model the cement production process and the polysilicon production process respectively according to their state task graphs.

[0064] The steps of modeling the cement production process and the polysilicon production process include: respectively determining the decision variables and constraint conditions of the cement production process and the polysilicon production process.

[0065] In this embodiment, the decision variables of the cement production process and the polysilicon production process are respectively the operating status of each electrical equipment in the cement production process and the polysilicon production process in each scheduling period; the constraint conditions of the cement production process include material balance constraints, power balance constraints, material storage constraints, cement output constraints and rotary kiln continuous operation constraints; the constraint conditions of the polysilicon production process include material balance constraints, power balance constraints, material storage constraints, polysilicon output constraints, purification task start constraints and reduction task start constraints.

[0066] Specifically, through the analysis of step S1 and step S2, the cement production process constraints based on the state task graph can be constructed, which can be expressed as:

[0067] (1) Decision variables

[0068] The decision variables are the operating status of each electrical equipment in the cement production process during each scheduling period:

[0069]

[0070] In the formula, represents the operating status of the i-th core electrical equipment of task k in the cement production process in time period t, 1 indicates that the equipment is in working state, 0 indicates that the equipment is in shutdown state, RMC, RMG, RMH, FPP, CF and CG represent different process tasks as described in step S1.

[0071] (2) Constraints

[0072] 1) Material balance constraints

[0073]

[0074] in, It represents the available quantity of state substance n in time period t during cement production process, where t is 0, is the initial quantity of state substance n in the cement production process, It represents the number of state objects n generated or consumed by a single core device of task k in the cement production process in time period t (positive value indicates generation, negative value indicates consumption), It represents the total number of core equipment in working state for task k in time period t in cement production process, K1 represents the total number of cement production tasks, T represents the total number of daily scheduling time periods, and N1 represents the total number of objects in state during cement production process.

[0075] 2) Power balance constraints

[0076]

[0077] in, represents the power consumption of the cement plant in time period t, It represents the power consumption of a single core device of task k in the cement production process during time period t.

[0078] 3) Material storage constraints

[0079]

[0080] Among them, LB1 n Indicates the storage lower limit of state substance n in the cement production process, UB1 n It represents the storage upper limit of state substance n in the cement production process.

[0081] 4) Cement production constraints

[0082]

[0083] in, represents the quantity of cement, the final product of the cement production process, at the end of the scheduling period T, LB1 represents the initial quantity of cement, the final product of the cement production process, at the beginning of the scheduling period. p,final Indicates the daily production requirement of cement.

[0084] 5) Constraints on continuous operation of rotary kiln

[0085] 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:

[0086]

[0087] in, It represents the operating status of the rotary kiln system, the core electrical equipment for clinker burning in the cement production process, 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.

[0088] By proposing production process constraints, this modeling method ensures that the cement plant can meet its production process restrictions and production task requirements while adjusting its production plan to participate in the optimal scheduling of the power grid without affecting normal production.

[0089] Furthermore, through the analysis of step S1 and step S2, the polysilicon production process constraints based on the state task graph can be constructed, which is expressed as:

[0090] (1) Decision variables

[0091] The decision variables are the operating status of each electrical equipment in the polysilicon production process during each scheduling period:

[0092]

[0093] in, It represents the operating status of the i-th core power-consuming equipment of task k in the polysilicon production process in time period t. 1 indicates that the equipment is in working state, and 0 indicates that the equipment is in shutdown state. SF, DC, RF, CDI and HR represent different process tasks in the polysilicon production process.

[0094] (2) Constraints

[0095] 1) Material balance constraints

[0096]

[0097] in, It represents the available quantity of state object n in time period t during the polysilicon production process, where t is 0. is the initial number of state objects n in the polysilicon production process, It indicates the number of state objects n generated or consumed by a single core device of task k in the polysilicon production process in time period t (positive value indicates generation, negative value indicates consumption). It represents the total number of core devices in working state during task k in time period t in the polysilicon production process, K2 represents the total number of polysilicon production tasks, and N2 is the total number of objects in state during the polysilicon production process.

[0098] 2) Power balance constraints

[0099]

[0100] in, represents the power consumption of the polysilicon plant in time period t, represents the power consumption of a single core device of task k in the polysilicon production process during time period t, It represents the total number of core devices in working state during task k in time period t in the polysilicon production process.

[0101] 3) Material storage constraints

[0102]

[0103] Among them, LB2 n Indicates the storage lower limit of state object n in the polysilicon production process, UB2 n It represents the storage upper limit of state object n in the polysilicon production process.

[0104] 4) Polysilicon production constraints

[0105]

[0106] in, It represents the quantity of high-purity polysilicon, the final product of the polysilicon production process, at the end of the scheduling period T. LB2 represents the initial quantity of high-purity polysilicon, the final product of the polysilicon production process, at the beginning of the scheduling period. p,final Represents the daily production requirement of high-purity polysilicon.

[0107] 5) Purification task startup constraints

[0108] To ensure the safety of the production process, the purification (DC) task can only be started after the synthesis (SF) task has started and there is enough chlorosilane liquid in the storage tank. This constraint can be expressed as:

[0109]

[0110]

[0111] in, Indicates the start and stop status of the distillation tower, the core power-consuming equipment for the purification task in the polysilicon production process, in time period t. Indicates that the distillation tower is in working state during time period t, Indicates that the distillation tower is in shutdown state during time period t; LB21 indicates the minimum inventory of chlorosilane liquid in the storage tank when the purification task begins. Indicates the inventory of chlorosilane liquid, It represents the total number of core devices in working state in the synthesis task during the polysilicon production process in time period t.

[0112] 6) Restore task startup constraints

[0113] In order to ensure the safety of the production process, the reduction (RF) task can only be started when the supply of high-purity trichlorosilane is sufficient. The mathematical expression of this constraint is:

[0114]

[0115] in, Indicates the start and stop status of the reduction furnace, the core electrical equipment for the reduction task in the polysilicon production process, in time period t. Indicates that the reduction furnace is in working state during period t, Indicates that the reduction furnace is in shutdown state during period t; LB22 indicates the minimum stock of high-purity trichlorosilane in the storage tank when the reduction task starts. Indicates the supply amount of high-purity trichlorosilane.

[0116] Step S4: Determine the charging and discharging constraints of the pumped storage power station, construct an aggregated adjustable capacity evaluation model based on the modeling results and the charging and discharging constraints, and solve the evaluation model to obtain the maximum adjustable capacity of the power grid dispatch, thereby realizing the aggregated adjustable capacity evaluation.

[0117] Among them, the charging and discharging constraints of the pumped-storage power station at least include the charging and discharging electric power constraints of the pumped-storage power station, the overall discharge power constraints, the charging and discharging state constraints of each unit and the storage energy state constraints.

[0118] In this embodiment, assuming that the day-ahead scheduling step is δ and the total number of daily scheduling periods is T, the objective function for maximizing the adjustable capacity of the pumped storage power station, cement plant, and polysilicon plant in period t is expressed as follows:

[0119]

[0120] Among them, C is the daily aggregate adjustable capacity of the pumped storage power station, cement plant and polysilicon plant, is the electricity consumption of the cement plant in period t, is the power consumption of the polysilicon plant in period t, is the power generation of the pumped storage power station in time period t, is the baseline load of the three aggregated in time period t, which is obtained by calculating the average load of the three days before the dispatch day.

[0121] In this embodiment, the constraints of the aggregate adjustable capacity evaluation model include the charging and discharging constraints of the pumped storage power station, the constraints of the cement production process, and the constraints of the polysilicon production process.

[0122] (1) Charging and discharging constraints of pumped storage power stations

[0123] 1) Charging and discharging power constraints of pumped storage power stations

[0124]

[0125] in, is the discharge power of the i-th unit in the pumped storage power station in the t-th 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 i-th pumped storage unit in the t-th 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.

[0126]

[0127] in, is the charging power of the i-th unit in the pumped storage power station in the t-th period, It represents the constant charging power of each unit in the pumped storage power station. is the charging state of the i-th unit in the t-th period, Indicates that it is in charging state. Indicates not charging.

[0128] 2) Overall discharge power constraints

[0129]

[0130] in, is the total discharge power of the pumped-storage power station, that is, the power generation of the pumped-storage power station in time period t.

[0131] 3) Constraints on the charging and discharging status of each unit

[0132]

[0133] in, is the charging state of the jth unit in the tth period. This constraint is used to ensure that the charging and discharging states of each unit in the pumped storage power station are consistent.

[0134] 4) Storage energy state constraints

[0135]

[0136] Among them, EUB s 、ELB s are the upper and lower limits of the energy that can be stored in the pumped storage power station, η is the charge-discharge conversion efficiency of the pumped storage unit, τ represents the time period, E0 represents the initial storage energy value of the pumped storage power station, represents the discharge power of the i-th unit in the pumped storage power station in the τ-th period, It represents the charging power of the i-th unit in the pumped storage power station in the τ-th time period.

[0137] 5) Final energy constraint

[0138]

[0139] This constraint is used to ensure that the water level of the pumped storage unit remains unchanged after a single day of scheduling.

[0140] (2) Constraints in cement production process

[0141] As mentioned above, it is specifically expressed as:

[0142]

[0143] (3) Constraints of polysilicon production process

[0144] As mentioned above, it is specifically expressed as:

[0145]

[0146] In summary, the present invention models the typical industrial load cement and polysilicon production process, further explores its potential for participating in grid interaction under the premise of ensuring the normal production of industrial load, and aggregates the adjustable capacity of the pumped storage device on the energy storage side to realize the overall adjustable capacity evaluation of the pumped storage unit, cement plant load and polysilicon plant load taking into account production restrictions. Specifically, for cement plants, the present invention takes into account that the load adjustment capacity is closely related to the storage capacity, so the whole process can be divided into multiple processes according to the storage setting. Although each process involves a variety of equipment, there is no storage device between the equipment in the same process, so it is necessary to meet the constraint of simultaneous operation, and it can be considered as a whole to reduce the complexity of the model; at the same time, considering that the power consumption of the core power-consuming equipment in each process is much higher than that of the remaining equipment, the core power-consuming equipment in each process is used instead of the overall equipment for representation; and, using the state task network method, the material is abstracted into a state and the process is abstracted into a task, and the situation of each process generating / consuming materials and occupying / releasing equipment is clarified, and the constraints such as material quantity, production tasks, and equipment operation requirements are constructed to determine the production plan arrangement of the enterprise. In addition, for polysilicon loads, the present invention adopts a similar idea, divides the entire production process of polysilicon enterprises into multiple processes, and uses the state task network method to characterize the interaction between each process and materials and equipment to establish production process constraints. Based on all the above constraints, and considering the power, state, and energy constraints of the pumped storage system during its charging and discharging process, an aggregated adjustable capacity evaluation model for energy storage and typical flexible industrial loads is constructed. Solving this model can obtain the maximum adjustable capacity of each time period, and obtain the production plan arrangement of cement plants and polysilicon plants under the maximum adjustable capacity of each time period, as well as the charging and discharging plan of pumped storage units. Therefore, by constructing a model that takes into account the production process constraints of cement enterprises and polysilicon enterprises and the charging and discharging restrictions of pumped-storage units under time-of-use electricity prices, it is possible to provide a comprehensive production plan arrangement with the largest adjustable capacity, which will minimize the impact on the normal production of cement enterprises and polysilicon enterprises and ensure the safety of pumped-storage equipment. This includes the production plan of cement enterprises, the production plan of polysilicon plants, and the charging and discharging plan of pumped-storage units. This can guide enterprises to produce in staggered and peak-avoiding manner, and pumped-storage units to discharge during peak load periods and pump during trough periods, which is conducive to achieving peak shaving and valley filling, ensuring the safe, stable and economical operation of the power system, while promoting the consumption of new energy, reducing the amount of wind and solar power abandoned, and providing a theoretical basis for enterprises and pumped-storage devices to participate in grid peak regulation.

[0147] Furthermore, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aggregated adjustable capacity assessment method for the coordinated energy storage and typical industrial loads provided by the above-mentioned methods.

[0148] Figure 5The following is a schematic diagram of the physical structure of an electronic device. Figure 5 As shown, the electronic device may include: a processor 210, a communication interface 220, a memory 230 and a communication bus 240, wherein the processor 210, the communication interface 220 and the memory 230 communicate with each other through the communication bus 240. The processor 210 may call the logic instructions in the memory 230 to execute the aforementioned aggregated adjustable capacity assessment method for energy storage and typical industrial load collaboration.

[0149] In addition, the logic instructions in the above-mentioned memory 230 can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0150] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0151] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0152] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for evaluating the aggregate adjustable capacity of energy storage and typical industrial loads, characterized in that: include: Analyze the cement production process and polysilicon production process to obtain the corresponding production process analysis results; Determine the corresponding state task diagrams according to the analysis results of the production processes of the two; Modeling the cement production process and the polysilicon production process respectively according to their state task graphs; Determine the charging and discharging constraints of the pumped storage power station, build an aggregated adjustable capacity evaluation model based on the modeling results and the charging and discharging constraints, and solve the evaluation model to obtain the maximum adjustable capacity of the power grid dispatch, thereby realizing the aggregated adjustable capacity evaluation.

2. The method for evaluating the aggregate adjustable capacity of energy storage and typical industrial loads according to claim 1, characterized in that: The step of analyzing the cement production process and the polysilicon production process to obtain corresponding production process analysis results comprises: Each process of the cement production process and the polysilicon production process is analyzed to obtain the coupling relationship between each process of the cement production process and the polysilicon production process and materials, electrical equipment and whether the process task is a schedulable task.

3. The method for evaluating the aggregate adjustable capacity of energy storage and typical industrial loads as claimed in claim 2, characterized in that: A state task diagram corresponding to the production process is determined according to the coupling relationship.

4. The method for evaluating the aggregate adjustable capacity of energy storage and typical industrial loads as claimed in claim 3 is characterized in that: The state task diagram includes task nodes and state nodes, wherein the task nodes include schedulable task nodes and unschedulable task nodes, and the task nodes indicate whether the corresponding process tasks are schedulable; the state nodes indicate different states of materials, and the states of materials include raw material states, intermediate product states, and final product states.

5. The method for evaluating the aggregate adjustable capacity of energy storage and typical industrial loads as claimed in claim 4, characterized in that: The step of modeling the cement production process and the polysilicon production process includes: determining decision variables and constraints of the cement production process and the polysilicon production process respectively.

6. The method for evaluating the aggregate adjustable capacity of energy storage and typical industrial loads as claimed in claim 5, characterized in that: The decision variables of the cement production process and the polysilicon production process are respectively the operating status of each electrical equipment in the cement production process and the polysilicon production process in each scheduling period; the constraints of the cement production process include material balance constraints, power balance constraints, material storage constraints, cement output constraints and rotary kiln continuous operation constraints; the constraints of the polysilicon production process include material balance constraints, power balance constraints, material storage constraints, polysilicon output constraints, purification task start constraints and reduction task start constraints.

7. The method for evaluating the aggregate adjustable capacity of energy storage and typical industrial loads as claimed in claim 6, characterized in that: The charging and discharging constraints of the pumped-storage power station at least include the charging and discharging electric power constraints of the pumped-storage power station, the overall discharge power constraints, the charging and discharging state constraints of each unit and the stored energy state constraints.

8. The method for evaluating the aggregate adjustable capacity of energy storage and typical industrial loads as claimed in claim 7, characterized in that: The objective function of the aggregate adjustable capacity evaluation model is expressed as follows: Among them, C is the daily aggregate adjustable capacity of the pumped storage power station, cement plant and polysilicon plant, is the electricity consumption of the cement plant in period t, is the power consumption of the polysilicon plant in period t, is the power generation of the pumped storage power station in time period t, is the baseline load of the three aggregated in time period t, T is the total number of daily scheduling periods; The constraints of the aggregate adjustable capacity assessment model include the charging and discharging constraints of the pumped storage power station, the constraints of the cement production process and the constraints of the polysilicon production process.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for evaluating the aggregated adjustable capacity of energy storage and typical industrial loads in coordination as described in any one of claims 1 to 8 is implemented.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, it implements the aggregated adjustable capacity assessment method for the coordinated energy storage and typical industrial loads as described in any one of claims 1-8.

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