Industrial load characteristic multi-time scale scheduling method for high-proportion wind power

Abstract

The invention discloses an industrial load characteristic multi-time scale scheduling method for high-proportion wind power, and relates to the technical field of wind power scheduling. According to the multi-time-scale scheduling method provided by the invention, the printing and dyeing load and the polycrystalline silicon load are respectively scheduled before and within the day by considering industrial load characteristics, and the uncertainty caused by high-proportion wind power access can be efficiently dealt with. The influence of wind power fluctuation on the system can be reduced by performing long-period scheduling in the day and optimizing the production plan of the industrial load; and rapid response to short-term demand fluctuation is ensured by intra-day real-time scheduling. According to the method, dispatching of wind power, industrial loads and energy storage resources can be flexibly coordinated, the wind power absorption capacity is improved, the wind curtailment risk can be reduced, meanwhile, the stability, reliability and economical efficiency of a power system are improved, and the potential of high-proportion renewable energy sources is fully exerted.

Description

Technical Field

[0001] The present invention discloses a multi-time-scale scheduling method for industrial load characteristics for high-proportion wind power, which relates to the technical field of wind power scheduling. Background Art

[0002] As an important renewable energy source, wind energy has developed rapidly globally in recent years. Compared with traditional fossil fuel power generation, wind energy has significant advantages of being clean, environmentally friendly and renewable. However, the intermittent and volatile characteristics of wind power pose many challenges in the process of grid connection and consumption. The output power of wind power is greatly affected by wind speed changes, resulting in unstable power generation and making it difficult to achieve a good match with the grid load. This imbalance between supply and demand causes the phenomenon of "wind curtailment" in some periods, that is, although there is sufficient wind power resources, due to low grid load or inflexible scheduling, part of the wind power cannot be connected to the grid for utilization, seriously restricting the further development of the wind power industry. Therefore, it is necessary to increase the flexibility of the grid load to reduce wind curtailment. Summary of the Invention

[0003] Aiming at the problems of the existing technology, the present invention provides a multi-time-scale scheduling method and device for industrial load characteristics for high-proportion wind power. The technical solutions adopted are as follows: In a first aspect, a multi-time-scale scheduling method for industrial load characteristics for high-proportion wind power, the method includes: S1, establishing a load scheduling model; S11, establishing a printing and dyeing load scheduling model according to the printing and dyeing production process through time constraints, allocation constraints and production deadline constraints; S12, establishing a polysilicon load scheduling model by analyzing the temperature change of the polysilicon rod according to the polysilicon rod and reaction gas; S2, establishing a multi-time-scale scheduling strategy; S21, performing a day-ahead scheduling model on the printing and dyeing load, thermal power units, and pumped-storage energy storage power stations according to multi-scenario stochastic programming; S22, establishing an intraday optimal scheduling model according to the objective function and constraint conditions.

[0004] In some implementation manners, the S11 specifically includes: S111, performing time constraints according to the end time of the previous process of the order before the migration process being earlier than the start time of the subsequent process; S112, performing allocation constraints according to any process of any order not being able to switch equipment after starting production; S113, performing production deadline constraints according to the order being completed before the final completion deadline; S114. Perform aggregation modeling based on the production power of the same production equipment at the same moment, and use the printing and dyeing load as the day-ahead scheduling.

[0005] In some implementation manners, in S21, the constraint conditions include power balance constraint, printing and dyeing production constraint, thermal power unit constraint, pumped storage constraint, wind power constraint, and load shedding and wind curtailment constraints.

[0006] In some implementation manners, in S22, the constraint conditions include power balance constraint and polysilicon load constraint.

[0007] In a second aspect, an embodiment of the present invention provides an industrial load characteristic multi-time scale scheduling device for high proportion of wind power. The device includes: A load module, configured to establish a load scheduling model, specifically including: A printing and dyeing unit, configured to establish a printing and dyeing load scheduling model according to the printing and dyeing production process through time constraint, allocation constraint, and production deadline constraint; A polysilicon unit, configured to establish a polysilicon load scheduling model by analyzing the temperature change of the polysilicon rod based on the polysilicon rod and reaction gas; A strategy module, configured to establish a multi-time scale scheduling strategy, specifically including: A day-ahead scheduling unit, configured to perform a day-ahead scheduling model in the printing and dyeing load, thermal power unit, and pumped storage energy storage power station through multi-scenario stochastic programming; An intra-day scheduling unit, configured to establish an intra-day optimal scheduling model according to the objective function and constraint conditions.

[0008] In some implementation manners, the printing and dyeing unit specifically includes: A time constraint subunit, configured to perform time constraint according to that the end time of the previous process of the order before the migration process is earlier than the start time of the subsequent process; An allocation constraint subunit, configured to perform allocation constraint according to that any process of any order cannot switch equipment after starting production; A deadline constraint subunit, configured to perform production deadline constraint according to that the order needs to be completed before the final completion deadline; A modeling aggregation subunit, configured to perform aggregation modeling based on the production power of the same production equipment at the same moment, and use the printing and dyeing load as the day-ahead scheduling.

[0009] In some implementation manners, in the day-ahead scheduling unit, the constraint conditions include power balance constraint, printing and dyeing production constraint, thermal power unit constraint, pumped storage constraint, wind power constraint, and load shedding and wind curtailment constraints.

[0010] In some implementations, in the intraday scheduling unit, the constraint conditions include power balance constraints and polysilicon load constraints.

[0011] In a third aspect, an embodiment of the present invention provides an electronic device, including a memory and a processor, where the memory is used to store one or more computer instructions. When the one or more computer instructions are executed by the processor, the method described in the first aspect above is implemented.

[0012] In a fourth aspect, an embodiment of the present invention provides a computer storage medium. A computer program is stored in the computer-readable storage medium. When the computer program is executed by a processor, the method described in the first aspect is implemented.

[0013] One or more embodiments of the present invention can at least bring the following beneficial effects: The beneficial effects of the present invention are as follows: The multi-time scale scheduling method proposed by the present invention, by considering the industrial load characteristics, schedules the printing and dyeing load and the polysilicon load respectively on a day-ahead and intraday basis, and can efficiently cope with the uncertainties brought by the high proportion of wind power access. By performing long-term scheduling on a day-ahead basis and optimizing the production plan of industrial loads, the impact of wind power fluctuations on the system can be reduced; while the intraday real-time scheduling ensures a rapid response to short-term demand fluctuations. The method of the present invention can flexibly coordinate the scheduling of wind power, industrial loads, and energy storage resources, improve the wind power consumption capacity, reduce the risk of wind curtailment, and at the same time improve the stability, reliability, and economy of the power system, and fully exert the potential of high proportion of renewable energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0015] Figure 1 is a flowchart of a multi-time scale scheduling method for industrial load characteristics for high proportion of wind power provided by an embodiment of the present invention; Figure 2 is a schematic diagram of the relationship between day-ahead and intraday scheduling provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0016] Next, in combination with the accompanying drawings in the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Usually, the components of the embodiments of the present invention described and shown in the accompanying drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed present invention, but only represents the selected embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0017] Embodiment 1: Figure 1 The flowchart of a multi-time scale scheduling method for industrial load characteristics for a high proportion of wind power is shown. As Figure 1 shown, the multi-time scale scheduling method for industrial load characteristics for a high proportion of wind power provided in this embodiment includes: S1. Establish a load scheduling model; S11. According to the printing and dyeing production process, establish a printing and dyeing load scheduling model through time constraints, allocation constraints, and production deadline constraints; S12. According to the polysilicon rod and reaction gas, establish a polysilicon load scheduling model by analyzing the temperature change of the polysilicon rod; S2. Establish a multi-time scale scheduling strategy; S21. According to multi-scenario stochastic programming, perform a day-ahead scheduling model for printing and dyeing loads, thermal power units, and pumped storage energy storage power stations; S22. Establish an intraday optimization scheduling model according to the objective function and constraint conditions.

[0018] Further, the specific content of S11 includes: S111. According to the end time of the previous process of the order being earlier than the start time of the next process before the migration process, perform time constraints; To ensure the normal progress of the production process, the end time of order i on the previous process must be earlier than the start time on the next process: (1) In the formula, is the start time of order i on process l; is the end time of order i on process l - 1. I is the set of workpieces, ; is the set of equipment used by order i. Ul is the set of all production equipment for process l. is the processing time of order i on equipment u. is a binary variable, which is 1 when order i uses equipment u in process l, and 0 otherwise. For any process, the subsequent order cannot start processing until the previous order is completed: (2) The start time of the subsequent order in adjacent processing orders should be greater than or equal to the total time spent by the previous order to complete processing on the process. M is a sufficiently large number. i and j are different orders. is the start time of order j in process l; is the end time of order i in process l; Xijl is a binary variable. When order i has a direct subsequent order, that is, orders i and j are adjacent orders processed on the same equipment, the value of Xijl is 1, otherwise it is 0.

[0019] S112, according to the fact that any process of any order cannot switch equipment after starting production, perform allocation constraints; Any process of any order cannot switch equipment after starting production and can only be completed by one equipment.

[0020] (3) In the formula, is a binary variable, which is 1 when order i uses equipment u for processing, and 0 otherwise.

[0021] S113, according to the order to be completed before the final deadline, perform production deadline constraints; The order should complete the task before the final deadline (4) In the formula, is the final deadline of each order as specified; is the start time of order i in the last process; Ulast is the set of production equipment for the last process.

[0022] S114, according to the production power of the same production equipment at the same moment, perform aggregation modeling and take the printing and dyeing load as the day-ahead scheduling.

[0023] In the production management of the industrial park, in order to comprehensively understand the production load situation of the industrial park, it is necessary to aggregate the production equipment in the park. Specifically, aggregate the same production equipment in the production park. This process can effectively reflect the production load levels of different equipment, help optimize resource allocation and improve production efficiency. As shown in the following formula: (5) In the formula, is the total power of the same production equipment n at time t; Production power of device n at time t In the printing and dyeing production, equipment such as dye vats, stenter machines, and dryers have relatively long preheating times and cooling times, and the production process in the printing and dyeing industry requires strict time and temperature control. Once a certain process is started, stopping or adjusting the load midway may lead to process failures or product quality problems. The short time scale within a day may cause the equipment to fail to respond to production plan adjustments in a timely manner, and it is necessary to formulate a plan in advance on the day before. Therefore, the printing and dyeing load is regarded as a day-ahead scheduling resource.

[0024] Next, according to S12, in the reduction furnace, the power supply system generates heat Qin through the polysilicon rod. Qout1 is used to heat the reaction gas, Qout2 is the heat absorbed by the reaction, and Qout3 is the heat dissipated from the polysilicon rod, which is the heat lost through the furnace wall and the chassis sheath. However, in current research, only the reaction gas temperature is input as a constant. However, the reaction gas temperature is strongly correlated with the silicon rod temperature, and as the temperature of the polysilicon rod changes, the reaction gas temperature will also change. This article will take the polysilicon rod and the reaction gas as the research objects and conduct a detailed analysis of the temperature change of the polysilicon rod. In this process, it is assumed that the furnace wall temperature is a fixed value.

[0025] The heat calculation for the power supply system to heat the silicon rod is shown in Equation (6): (6) In the formula, is the heat input by the power supply system, is the input power of the power supply system, and U and I are the input voltage and current of the power supply system. is the unit time.

[0026] The heat absorbed by the endothermic reaction is relatively fixed, and the relationship between the heat absorbed by the reaction and the radiative heat dissipation is shown in the following formula (7) Heat of the polysilicon rod heating the gas The calculation is shown in (8): (8) In the formula, is the intake velocity of the mixed gas, is the area of the intake port, is the density of the mixed gas, is the specific heat capacity of the reaction gas, is the temperature of the reaction gas.

[0027] Heat dissipation of the silicon rod The calculation is shown in (9): (9) In the formula, is the heat dissipation coefficient of polysilicon, r is the radius of the polysilicon rod, and L is the length of the polysilicon rod. is the equivalent area of polysilicon. is the temperature of the polysilicon rod. is the temperature of the furnace wall. is the cooling water inflow rate.

[0028] Heat dissipation of reaction gas : (10) In the formula, is the heat dissipation coefficient of the reaction gas, is the contact area between the gas and the furnace wall Taking the polysilicon rod as the research object: The heat of the polysilicon rod includes the heat Qin provided by the power supply system, the heat Qout1 for the polysilicon rod to heat the reaction gas, the heat Qout2 absorbed by the gas-phase reaction, and the heat Qout3 dissipated from the polysilicon rod to the furnace wall. Taking the polysilicon rod as the research object, studying its heat exchange and heat loss with other media, the heat calculation formula is as follows: (11) In the formula, is the specific heat capacity of the mixed gas, is the mass of the mixed gas, is the temperature change of the polysilicon rod.

[0029] After sorting, the expression of the temperature of the polysilicon rod changing with time can be obtained: (12) Taking the reaction gas as the research object: The heat of the reaction gas includes the heat Qout1 for the polysilicon rod to heat the reaction gas, the heat Qout2 absorbed by the gas-phase deposition reaction, and the heat Qout4 dissipated from the reaction gas to the furnace wall. Taking the polysilicon rod as the research object, studying its heat exchange and heat loss with other media, its heat calculation can be expressed as: (13) In the formula, is the specific heat capacity of the polysilicon rod, is the mass of the mixed gas, is the temperature change of the mixed gas.

[0030] After sorting, the expression of the temperature of the reaction gas changing with time can be obtained: (14) Steady-state model Taking the right side of Equation (12) and Equation (14) as 0, that is, the temperatures of the polysilicon rod and the reaction gas in the reduction furnace do not change with time. At this time, the reduction furnace reaches a steady state, that is: (15) (16) Polysilicon load model After obtaining the relationships between polysilicon and reaction gas varying with time, by taking the differences of the two equations (12) and (14) with respect to time respectively, for simplicity of calculation, take to be 1 h.

[0031] (17) (18) By arranging equations (17) and (18), we can obtain (19) (20) (21) (22) (23) (24) Assume that the radius of the silicon rod increases linearly with time, then the product of ρg·v1·S1 remains unchanged, that is, the mass of the reaction gas introduced per unit time is approximately equal. Since the polysilicon reduction furnace responds quickly to the scheduling, in this paper, the polysilicon rod is taken as the intraday scheduling resource, and a 4-hour rolling optimization period is adopted. Since the deposition rate of polysilicon is relatively small, usually 10 - 16 μm / min, therefore, it is assumed that the radius of the polysilicon rod remains unchanged within the current scheduling period (4 hours) and the radius is updated in the next period. At the end of each period, the radius of the polysilicon rod increases by about 2.4 mm. That is, it can be considered that Sp remains unchanged within a scheduling period. Therefore, a, b, c, d, and e are all constants. Equation (19) describes that the temperature of the polysilicon rod is related not only to the input power but also to the temperature of the silicon rod at the previous moment.

[0032] The power-temperature coupling can be expressed by the following equation: (25) (26) (27) (28) In the formula, I is the set of reduction furnaces of silicon rods with the same radius, and T is the time period. The maximum adjustable load of the polysilicon reduction furnace can be determined through temperature constraints and power constraints. and are the lower and upper limits of the silicon rod temperature.

[0033] Through the above calculations, the maximum adjustable power of the reduction furnace at the safe operating temperature can be obtained.

[0034] That is, the power constraint is (29) In the formula, is the maximum adjustable power of the polysilicon load.

[0035] Since the reduction furnace has a fast adjustment speed, it is used as an intra-day demand response resource.

[0036] Next, according to S2, a multi-time scale scheduling strategy is established; A day-ahead scheduling strategy is formulated according to S21; In the day-ahead stage, a multi-scenario stochastic programming method is used. The multi-scenario stochastic programming method can fully consider future uncertainty factors. By planning under multiple possible scenarios, the robustness and flexibility of decision-making are improved. The day-ahead demand response resources include printing and dyeing loads, thermal power units, and pumped storage power stations.

[0037] Specifically, it includes: S211, establish the objective function (30) (31) In the formula, is the total day-ahead operating cost of the system; , , , respectively represent the costs of thermal power units, pumped storage, wind curtailment and load shedding, and demand response loads; Ns is the number of scenarios; G is the number of thermal power units; is the occurrence probability of scenario s; , , are the cost coefficients of thermal power units, and Rg is the start-stop cost coefficient of thermal power units; is the charge and discharge power of pumped storage at time t under scenario s; is the cost function of pumped storage; is the operating state of unit i at time t under scenario s; , are the increased and decreased loads of the printing and dyeing factory at time t under scenario s; , are the compensation costs for the increase and decrease of the printing and dyeing load; , are the wind curtailment and load shedding powers at time t under scenario s; , are the load shedding and wind curtailment costs.

[0038] S212, Constraints include: Power balance constraint: (32) Where, is the wind power output at time t in scenario s; is the system load at time t; Printing and dyeing production constraint: The printing and dyeing industry provides demand response load by adjusting the production process before the final delivery deadline, and the printing and dyeing production constraint satisfies formulas (1)-(5).

[0039] Thermal power unit constraint: The constraints of thermal power units are output constraints and ramping constraints; (33) (34) Where, is a binary variable representing the start-stop state of thermal power unit i at time t in scenario s, 1 for start-up and vice versa for shutdown. and are the minimum and maximum output powers of thermal power unit i. is the maximum load regulation speed of thermal power unit i at each time step.

[0040] Pumped storage constraint: The constraint conditions of pumped storage power stations are mainly the water storage capacity constraint of the reservoir, the ramping rate constraint, and the operating state constraint.

[0041] (35) (36) (37) Where, and are the upper and lower limits of the power of the pumped storage power station for power injection and extraction; and are the upper and lower limits of the water storage capacity of the pumped storage power station; is the ramping rate of the pumped storage power station.

[0042] Wind power constraint: The consumption of wind power needs to be less than the predicted value and satisfy the following constraints; (38) Where, is the predicted wind power output at time t in scenario s.

[0043] Load shedding and wind curtailment constraints: The load shedding and wind rejection volume should be lower than the day-ahead prediction and meet the following constraints; (39) (40) In the formula, and are the predicted wind power output and system load.

[0044] Next, according to S22, an intraday optimal scheduling model is established; S221, establish the objective function; (58) (59) In the formula, Nb is the number of reduction furnaces participating in the response; is the compensation price for the polysilicon load participating in the demand response; is the power of the polysilicon load of the m-th reduction furnace participating in the demand response at time t in scenario s. Since the intraday time accuracy is 15 minutes, the objective function needs to be multiplied by 1 / 4.

[0045] S222, establish the constraint conditions, including: Power balance constraint: (60) Polysilicon load constraint: The polysilicon constraint adopts equations (25)-(30) Other constraints: The constraints of thermal power units, pumped storage, load shedding and wind rejection are the same as those of the day-ahead scheduling model and will not be elaborated here.

[0046] Embodiment 2: This embodiment provides an industrial load characteristic multi-time scale scheduling device for high-proportion wind power. The device includes: A load module for establishing a load scheduling model, specifically including, A printing and dyeing unit for establishing a printing and dyeing load scheduling model according to the printing and dyeing production process through time constraints, distribution constraints and production deadline constraints; A polysilicon unit for establishing a polysilicon load scheduling model according to the polysilicon rod and reaction gas by analyzing the temperature change of the polysilicon rod; A strategy module for establishing a multi-time scale scheduling strategy, specifically including, A day-ahead scheduling unit for performing a day-ahead scheduling model on the printing and dyeing load, thermal power units, and pumped storage energy storage power stations according to multi-scenario stochastic programming; An intraday scheduling unit for establishing an intraday optimal scheduling model according to an objective function and constraint conditions.

[0047] Further, the printing and dyeing unit specifically includes: A time constraint subunit for performing time constraints according to the end time of the previous process of the order before the migration process being earlier than the start time of the subsequent process; An allocation constraint subunit for performing allocation constraints according to any process of any order not being able to switch equipment after starting production; A deadline constraint subunit for performing production deadline constraints according to the order being required to be completed before the final completion deadline; A modeling aggregation subunit for performing aggregation modeling according to the production power of the same production equipment at the same moment and taking the printing and dyeing load as the day-ahead scheduling.

[0048] Further, in the day-ahead scheduling unit, the constraint conditions include power balance constraints, printing and dyeing production constraints, thermal power unit constraints, pumped storage constraints, wind power constraints, and load shedding and wind curtailment constraints.

[0049] Further, in the intraday scheduling unit, the constraint conditions include power balance constraints and polysilicon load constraints.

[0050] Embodiment 3: This embodiment also provides an electronic device including a memory and a processor, where the memory is used to store one or more computer instructions, and when the one or more computer instructions are executed by the processor, the method of Embodiment 1 is implemented; In practical applications, the processor can be implemented by an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a controller, a microcontroller unit (MCU), a microprocessor, or other electronic components, and is used to execute the method in the above embodiments.

[0051] The method implemented in this embodiment is as shown in the content of Embodiment 1.

[0052] Embodiment 4: This embodiment also provides a computer storage medium. A computer program is stored in the computer-readable storage medium. When the computer program is executed by one or more processors, the method of Embodiment 1 is implemented; Among them, the computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof. For example, static random access memory (SRAM for short), electrically erasable programmable read-only memory (EEPROM for short), erasable programmable read-only memory (EPROM for short), programmable read-only memory (PROM for short), read-only memory (ROM for short), magnetic memory, flash memory, magnetic disk or optical disk.

[0053] The method implemented in this embodiment is as shown in the content of Embodiment 1.

[0054] In several embodiments provided by the embodiments of the present invention, it should be understood that the disclosed systems and methods can also be implemented in other ways. The system and method embodiments described above are merely illustrative.

[0055] It should be noted that in this article, the terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects and do not necessarily describe a specific order or sequence. The term "comprising", "including" or any other variant thereof is intended to cover a non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of another identical element in the process, method, article or device including the element.

[0056] Although the disclosed embodiments of the present invention are as above, the content described is only an embodiment for facilitating the understanding of the present invention and is not used to limit the present invention. Any person skilled in the art within the technical field of the present invention can make any modifications and changes in the form of implementation and details without departing from the spirit and scope disclosed by the present invention. However, the scope of patent protection of the present invention shall still be subject to the scope defined by the appended claims.

Claims

1. A multi-time scale scheduling method for industrial load characteristics with high proportion of wind power, characterized in that: The method comprises: S1, establish load dispatch model; S11, according to the printing and dyeing production process, a printing and dyeing load scheduling model is established through time constraints, allocation constraints and production deadline constraints; S12, establishing a polysilicon load scheduling model by analyzing the temperature change of the polysilicon rods according to the polysilicon rods and the reaction gas; S2, establish a multi-time scale scheduling strategy; S21, based on multi-scenario stochastic planning, conducts day-ahead dispatch model on printing and dyeing loads, thermal power units, and pumped-storage power stations; S22, establishing an intraday optimization scheduling model based on the objective function and constraints.

2. The method according to claim 1, characterized in that The S11 specifically includes: S111, according to the order, the end time of the previous process of the migration process is earlier than the start time of the next process, and the time constraint is performed; S112, performing allocation constraints according to the fact that any process of any order cannot switch equipment after production starts; S113, according to which the order must be completed before the final completion deadline, production deadline constraints are imposed; S114, clustering and modeling are performed based on the production power of the same type of production equipment at the same time, and the printing and dyeing load is used as the day-ahead scheduling.

3. The method according to claim 1, characterized in that In S21, the constraints include power balance constraints, printing and dyeing production constraints, thermal power unit constraints, pumped storage constraints, wind power constraints, and load shedding and wind abandonment constraints.

4. The method according to claim 3, characterized in that In S22, the constraint conditions include power balance constraint and polysilicon load constraint.

5. A multi-time scale scheduling device for industrial load characteristics with high proportion of wind power, characterized in that: The device comprises: Load module, used to establish load scheduling model, including: The printing and dyeing unit is used to establish a printing and dyeing load scheduling model according to the printing and dyeing production process through time constraints, allocation constraints and production deadline constraints; A polysilicon unit, used to establish a polysilicon load scheduling model by analyzing the temperature change of the polysilicon rods according to the polysilicon rods and the reaction gas; The strategy module is used to establish multi-time scale scheduling strategies, including: The day-ahead dispatching unit is used to perform day-ahead dispatching models on printing and dyeing loads, thermal power units, and pumped-storage power stations based on multi-scenario stochastic planning; The intraday scheduling unit is used to establish an intraday optimization scheduling model based on the objective function and constraints.

6. The device according to claim 5, characterized in that The printing and dyeing unit specifically comprises: The time constraint subunit is used to impose time constraints based on the fact that the end time of the previous process of the migration process is earlier than the start time of the next process of the order; The allocation constraint subunit is used to make allocation constraints according to the fact that any process of any order cannot switch equipment after starting production; The deadline constraint subunit is used to constrain the production deadline according to the order being completed before the final completion deadline; The modeling aggregation subunit is used to aggregate and model the production power of the same type of production equipment at the same time, and use the printing and dyeing load as the day-ahead scheduling.

7. The device according to claim 5, characterized in that In the day-ahead dispatch unit, the constraints include power balance constraints, printing and dyeing production constraints, thermal power unit constraints, pumped storage constraints, wind power constraints, and load shedding and wind abandonment constraints.

8. The device according to claim 7, characterized in that In the intraday scheduling unit, the constraints include power balance constraints and polysilicon load constraints.

9. An electronic device, characterized in that: The invention comprises a memory and a processor, wherein the memory is used to store one or more computer instructions, wherein the one or more computer instructions, when executed by the processor, implement the method as described in any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it is used to implement the method as described in any one of claims 1 to 4 above.

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