New energy consumption potential assessment method and device for direct supply polycrystalline silicon production line

Abstract

The invention provides a new energy consumption potential assessment method and device for a direct supply polycrystalline silicon production line, and relates to the technical field of new energy consumption potential assessment. The method comprises the following steps: on the basis of production parameters of a polycrystalline silicon production line, constructing a corresponding production model for each link of a technological process of the polycrystalline silicon production line, and associating the production models of all links to obtain a polycrystalline silicon full-process production model; determining a new energy power generation power reference curve of the polycrystalline silicon production line based on historical power generation power data of a wind and light power generation station near the polycrystalline silicon production line; and constructing constraint conditions based on the polycrystalline silicon full-process production model and the new energy power generation power reference curve, and constructing a target function by taking the maximum new energy installed capacity which can be consumed by the polycrystalline silicon production line as an optimization target to obtain a new energy consumption potential evaluation model. According to the new energy consumption potential evaluation model, accurate evaluation of the new energy consumption potential of the direct supply polycrystalline silicon production line can be realized, and investment waste and power generation resource loss are avoided.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of new energy consumption potential evaluation, in particular to a new energy consumption potential evaluation method and device for a direct supply polysilicon production line. BACKGROUND

[0002] With the rapid development of the new energy industry, using the roof of a polysilicon factory and idle land inside and outside the factory to construct new energy power sources to form a new energy "self-generation and self-use" or green electricity direct connection energy supply new mode has become an important energy mode for future polysilicon production.

[0003] However, wind and light power sources have power generation fluctuations, and in this mode, wind and light can only be consumed by the factory, and a large construction scale can easily lead to power abandonment. Therefore, it is necessary to accurately estimate the new energy consumption potential of the entire factory under the consideration of the adjustable capacity of each link in the factory to avoid investment waste and power generation resource loss. SUMMARY

[0004] The present disclosure provides a new energy consumption potential evaluation method and device for a direct supply polysilicon production line to accurately evaluate the new energy consumption potential of polysilicon and avoid investment waste and power generation resource loss.

[0005] To achieve the above-mentioned purpose, the technical solution adopted by the present disclosure is as follows: The present disclosure provides a new energy consumption potential evaluation method for a direct supply polysilicon production line, comprising: based on the production parameters of the polysilicon production line to be evaluated, a corresponding production model is constructed for each link of the process flow of the polysilicon production line, and the production models of all links are associated to obtain a polysilicon full-process production model; based on the historical power generation data of the wind power station and the photovoltaic power station near the polysilicon production line, a new energy power generation power reference curve of the polysilicon production line is determined; based on the polysilicon full-process production model and the new energy power generation power reference curve, a constraint condition is constructed, and a target function is constructed with the maximum new energy installed capacity that can be consumed by the polysilicon production line as the optimization objective to obtain a new energy consumption potential evaluation model; based on the new energy consumption potential evaluation model, the new energy consumption potential of the polysilicon production line is evaluated.

[0006] In some embodiments of the present disclosure, the new energy power generation power reference curve is: , wherein, P(t) is the new energy power at time t, is the wind power capacity proportion in the new energy field station to be configured for polysilicon, and are the selected wind power station installed capacity and photovoltaic power station installed capacity, respectively, and respectively are the power generation of the wind power station and the power generation of the photovoltaic station at the i-th year time t.

[0007] In some embodiments of the present disclosure, the constraint conditions include a power balance constraint, a power relationship model constraint, a new energy utilization rate constraint, and a polysilicon process production model constraint.

[0008] In some embodiments of the present disclosure, the power balance constraint includes: , wherein, is the actual new energy consumption power at time t, is the power supply of the power grid at time t, is the power consumption of the polysilicon production line at time t.

[0009] In some embodiments of the present disclosure, the power relationship model constraint includes: , wherein, is the actual new energy consumption power at time t, is the new energy power at time t, is the to-be-built photovoltaic installed capacity, is the to-be-built wind power installed capacity, is the maximum new energy power generation capacity, is the power supply of the power grid at time t, is the power consumption of the polysilicon production line at time t, , , , , respectively are the power consumption of the trichlorosilane synthesis link, the power consumption of the trichlorosilane rectification and purification link, the power consumption of the trichlorosilane reduction link, and the power consumption of the tail gas recovery link, the power consumption of the silicon tetrachloride hydrogenation link, and the main product yield ratio coefficient of the hydrogen chloride synthesis link, , , , , respectively are the yield of trichlorosilane of the trichlorosilane synthesis link at time t, the yield of high-concentration trichlorosilane of the trichlorosilane rectification and purification link at time t, the yield of elemental silicon of the trichlorosilane reduction link at time t, the yield of silicon tetrachloride of the silicon tetrachloride hydrogenation link at time t, and the yield of hydrogen chloride of the hydrogen chloride synthesis link at time t.

[0010] In some embodiments of the present disclosure, the new energy utilization rate constraint includes: , wherein, is the actual new energy consumption power at time t, is the minimum value of the new energy utilization rate, is the to-be-built photovoltaic installed capacity, is the to-be-built wind power installed capacity, is the new energy power at time t.

[0011] In some embodiments of the present disclosure, the polysilicon full-process production model constraints include: trichlorosilane synthesis link production model constraints, including: input-output material relationship constraints, upper and lower yield constraints, and continuous operation time length constraints; trichlorosilane rectification purification link production model constraints, including: input-output material relationship constraints, upper and lower yield constraints, trichlorosilane buffer storage model constraints, and continuous operation time length constraints; trichlorosilane reduction link production model constraints, including: input-output material relationship constraints, upper and lower yield constraints, and yield model constraints; tail gas recovery link production model constraints, including: input-output material relationship constraints; silicon tetrachloride hydrogenation link production model constraints, including: input-output material relationship constraints; hydrogen chloride synthesis link production model constraints, including: material balance constraints.

[0012] In some embodiments of the present disclosure, the new energy installed capacity includes a photovoltaic installed capacity and a wind power installed capacity, and the objective function includes: , wherein, is the to-be-built photovoltaic installed capacity, is the to-be-built wind power installed capacity.

[0013] In some embodiments of the present disclosure, based on the new energy consumption potential evaluation model, the new energy consumption potential of the polysilicon production line is evaluated, including: obtaining a target new energy utilization rate; based on the new energy consumption potential evaluation model, determining the maximum new energy installed capacity of the polysilicon production line under the target new energy utilization rate, to evaluate the new energy consumption potential of the polysilicon production line.

[0014] In a second aspect of the present disclosure, a new energy consumption potential evaluation device for a direct supply polysilicon production line is provided, including: a production model construction unit, configured to construct a corresponding production model for each link of a process flow of a polysilicon production line based on production parameters of the polysilicon production line to be evaluated, and associate the production models of all links to obtain a polysilicon full-process production model; a benchmark curve determination unit, configured to determine a new energy power benchmark curve of the polysilicon production line based on historical power generation data of wind power stations and photovoltaic stations near the polysilicon production line; an evaluation model construction unit, configured to construct a constraint condition based on the polysilicon full-process production model and the new energy power benchmark curve, and construct an objective function with the maximum new energy installed capacity that can be consumed by the polysilicon production line as an optimization target to obtain a new energy consumption potential evaluation model; and an evaluation unit, configured to evaluate the new energy consumption potential of the polysilicon production line based on the new energy consumption potential evaluation model.

[0015] Compared with the prior art, this disclosure has the following beneficial effects: The renewable energy consumption potential assessment method for direct-supply polysilicon production lines disclosed herein constructs a renewable energy consumption potential assessment model. This model uses maximizing renewable energy installed capacity as the objective function and establishes a production model encompassing the entire polysilicon production process within constraints. Constraints such as input / output material balance and upper / lower limits for output are established for each stage, along with power constraints based on the ratio of power consumption to the main product constants for each stage. This model fully leverages the adjustable power consumption potential of the production process, avoiding calculation errors caused by treating industrial load as a fixed value in traditional methods. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a method for assessing the potential for renewable energy consumption in a direct-supply polysilicon production line, as provided in this embodiment of the disclosure. Figure 2 This is a schematic diagram of a polysilicon production process provided in an embodiment of this disclosure; Figure 3 This is a flowchart illustrating a method for evaluating the potential of new energy consumption based on a new energy consumption potential assessment model provided in this embodiment of the disclosure; Figure 4 This is a technical flowchart of a method for assessing the potential for new energy consumption in a direct-supply polysilicon production line, provided in this embodiment of the disclosure. Figure 5 This is a structural block diagram of a new energy consumption potential assessment device for direct supply to polysilicon production lines provided in this embodiment of the disclosure. Detailed Implementation

[0017] The present disclosure will now be further described with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present disclosure and should not be construed as limiting the scope of protection of the present disclosure. It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of this application.

[0018] The acquisition, transmission, storage, use, and processing of data in this disclosed technical solution comply with relevant national laws and regulations. In the embodiments of this disclosure, certain existing industry solutions such as software, components, and models may be mentioned. These should be considered exemplary, intended only to illustrate the feasibility of implementing the technical solution of this disclosure, and do not imply that the applicant has already used or necessarily used such solutions.

[0019] All terms used in this disclosure have the same meaning as understood by one of ordinary skill in the art to which this disclosure pertains, unless otherwise specifically defined. It should also be understood that terms defined in general dictionaries should be interpreted as having meanings consistent with their meanings in the context of the relevant art, and not as idealized or highly formalized, unless expressly defined herein.

[0020] Polysilicon production is a typical energy-intensive industry and the largest energy-consuming sector in the silicon industry chain. Producing one ton of polysilicon requires approximately 56,000 to 58,000 kilowatt-hours of electricity, far exceeding the 500 to 800 kilowatt-hours required for short-process steel smelting. Currently, polysilicon production mainly relies on self-owned power plants and the power grid, resulting in high costs and environmental concerns. Therefore, there is significant potential for green electricity substitution in the polysilicon production process.

[0021] Under new models such as direct green electricity connection and self-generation and self-consumption of new energy in industrial parks, industrial enterprises can build distributed photovoltaics on the rooftops of factory buildings and construct distributed or centralized new energy power stations on land inside and outside the park. The new energy power stations can supply electricity to the factory, partially replacing the power supply from the grid and the power supply from the factory's own generating units, thereby improving economic efficiency and reducing the carbon intensity of products.

[0022] However, wind and solar power generation is subject to fluctuations, and under this model, wind and solar power can only be consumed by the plant area. Excessive construction scale can easily lead to power curtailment. Therefore, it is necessary to determine the construction scale of the renewable energy power station while considering the adjustability of each link within the plant, clarifying the plant's overall renewable energy consumption potential, and avoiding investment waste and loss of power generation resources.

[0023] Existing studies mainly focus on energy consumption modeling of the multi-stage production process of polysilicon, often assuming that all electricity comes from the grid. They also tend to prioritize minimizing the factory's electricity costs, without considering the requirement to maximize the absorption of new energy sources. This makes it difficult to conduct energy consumption analysis of polysilicon factories and to assess the potential for new energy absorption.

[0024] Based on this, this disclosure provides a method for assessing the potential for new energy consumption in direct supply polysilicon production lines.

[0025] Figure 1 This is a flowchart illustrating a method for assessing the potential for renewable energy consumption in a direct-supply polysilicon production line, as provided in this embodiment. Figure 1 As shown, the method for assessing the new energy consumption potential of the direct-supply polysilicon production line includes the following steps S11 to S14.

[0026] Step S11: Based on the production parameters of the polysilicon production line to be evaluated, construct corresponding production models for each link of the polysilicon production line process, and link the production models of all links to obtain the polysilicon full-process production model.

[0027] In one possible implementation, the process flow of the polysilicon production line may include: a trichlorosilane synthesis stage, a trichlorosilane distillation and purification stage, a trichlorosilane reduction stage, a tail gas recovery stage, a silicon tetrachloride hydrogenation stage, and a hydrogen chloride synthesis stage. The entire process is as follows: In the trichlorosilane synthesis stage, metallurgical silicon and hydrogen chloride (HCl) are reacted to synthesize low-purity trichlorosilane gas SiHCl3 (hereinafter referred to as TCS in this embodiment); the trichlorosilane gas generated in the trichlorosilane synthesis stage enters the trichlorosilane distillation and purification stage, where, through processes such as reboiling, condensation, and reflux, higher-purity TCS is extracted from the low-purity trichlorosilane gas; in the trichlorosilane reduction stage, using the TCS produced in the trichlorosilane distillation and purification stage as the main raw material, hydrogen is added, and through a reduction reaction and chemical vapor deposition, elemental silicon is deposited on the silicon core; the tail gas… The recovery process involves collecting the tail gas from the trichlorosilane reduction process, and then dry-processing it to separate hydrogen, silicon tetrachloride (SiCl4, hereinafter referred to as STC), TCS, and HCl gas. TCS and hydrogen are then fed into the trichlorosilane distillation and purification process. In the silicon tetrachloride hydrogenation process, the STC obtained from the tail gas recovery process is used to regenerate trichlorosilane TCS via cold hydrogenation technology. The generated TCS is then returned to the trichlorosilane distillation and purification process. Finally, the hydrogen chloride synthesis process uses the hydrogen and chlorine obtained from the tail gas recovery process to synthesize hydrogen chloride, which is then used in the TCS synthesis process.

[0028] For example, in one specific embodiment, such as Figure 2 As shown, the entire polycrystalline silicon production process is as follows: In the TCS synthesis stage, silicon powder and HCl are reacted to synthesize low-purity TCS. The low-purity TCS enters the TCS distillation purification stage, through processes such as reboiling, condensation, and reflux, to extract higher-purity TCS from the lower-purity TCS, obtaining high-purity TCS, which is then buffered and temporarily stored. The buffered TCS enters the TCS reduction stage, where hydrogen is added, and through reduction reaction and chemical vapor deposition, polycrystalline silicon is obtained. In the tail gas recovery stage, the tail gas from the TCS reduction stage is collected and, through dry recovery, hydrogen, STC, TCS, and HCl gases are separated. The separated TCS gas and hydrogen are input into the TCS distillation purification stage. The separated STC undergoes the STC hydrogenation stage, using cold hydrogenation technology to regenerate TCS. The generated TCS is then returned to the TCS distillation purification stage. The separated hydrogen and chlorine are synthesized into HCl through the hydrogen chloride synthesis stage, which is used in the TCS synthesis stage.

[0029] It should be noted that the polysilicon full-process production model was established using the modified Siemens method. That is, based on the above process flow, models such as material input and output relationships and intermediate product storage constraints were established for each link, and then the operation models of all links constituted the polysilicon full-process production model.

[0030] Step S12: Based on the historical power generation data of wind farms and photovoltaic power plants near the polysilicon production line, determine the new energy power generation benchmark curve of the polysilicon production line.

[0031] In one possible implementation, historical power generation curves of wind farms and photovoltaic power plants near the polysilicon production line are collected to obtain historical power generation data of wind farms and photovoltaic power plants near the polysilicon production line. Then, by taking the average power at each moment, a new energy power generation benchmark curve for the polysilicon production line is formed.

[0032] For example, in one specific embodiment, historical power generation curves of wind farms and photovoltaic farms near the polysilicon production line are collected to obtain 8760 hours of power data recorded for three years for each farm. By taking the average power at each moment, a typical benchmark curve of new energy power generation is generated.

[0033] Specifically, the baseline curve for new energy power generation is as follows: In the formula, Let the new energy power be at time t. The percentage of wind power capacity in the polysilicon-equipped new energy power stations to be configured. and These refer to the selected wind farm installed capacity and photovoltaic farm installed capacity, respectively. and These represent the power generation of the wind farm and the power generation of the photovoltaic farm at time t in year i, respectively.

[0034] Step S13: Based on the polysilicon full-process production model and the new energy power generation benchmark curve, construct the constraint conditions, and construct the objective function with the maximum new energy installed capacity that the polysilicon production line can absorb as the optimization objective, to obtain the new energy absorption potential assessment model.

[0035] In some embodiments of this disclosure, the installed capacity of new energy sources includes photovoltaic installed capacity and wind power installed capacity, and the objective function includes: In the formula, For the photovoltaic installation capacity to be built, This refers to the wind power capacity to be built.

[0036] In some embodiments of this disclosure, the constraints include power balance constraints, power relationship model constraints, new energy utilization rate constraints, and polysilicon process production model constraints.

[0037] Specifically, power balance constraints include: In the formula, The actual renewable energy consumption power at time t. Let be the power supplied by the power grid at time t. The power consumption of the polysilicon production line at time t.

[0038] Specifically, the constraints of the power relationship model include: In the formula, The actual renewable energy consumption power at time t. Let the new energy power be at time t. For the photovoltaic installation capacity to be built, For the wind power installed capacity to be built, For the maximum power generation capacity of new energy sources, Let be the power supplied by the power grid at time t. The power consumption of the polysilicon production line at time t. , , , , These are the power consumption ratios to the main product yields for the following stages: trichlorosilane synthesis, trichlorosilane distillation and purification, trichlorosilane reduction and tail gas recovery, silicon tetrachloride hydrogenation, and hydrogen chloride synthesis. , , , , The figures represent the yields of trichlorosilane at time t in the trichlorosilane synthesis stage, the high-concentration trichlorosilane yield at time t in the trichlorosilane distillation and purification stage, the elemental silicon yield at time t in the trichlorosilane reduction stage, the silicon tetrachloride yield at time t in the silicon tetrachloride hydrogenation stage, and the hydrogen chloride yield at time t in the hydrogen chloride synthesis stage. It should be noted that since the capacity of the tail gas recovery stage is proportional to the yield of the main product in the reduction stage, the power consumption of the tail gas recovery stage is included in the power consumption of the reduction stage, and the power consumption coefficient of this stage is incorporated into the coefficient of the reduction stage. middle.

[0039] In the above formula, the first formula indicates that the actual power absorbed by new energy sources must be less than the maximum power generation capacity of new energy sources and greater than 0. The maximum power generation capacity of new energy sources is the product of the sum of the installed capacity of wind power and photovoltaic power to be solved and the typical benchmark curve. The second formula indicates that the power supply to the public grid must be greater than 0, indicating that new energy sources cannot be supplied to the public grid and can only be used by the polysilicon production process. The third formula indicates that the power consumption of polysilicon production is the sum of the power consumption of the aforementioned stages.

[0040] Specifically, the constraints on the utilization rate of new energy sources include: In the formula, The actual renewable energy consumption power at time t. This is the minimum requirement for the utilization rate of new energy sources. For the photovoltaic installation capacity to be built, For the wind power installed capacity to be built, Let be the renewable energy power at time t. It should be noted that the minimum renewable energy utilization rate can be determined by the polysilicon manufacturer itself, and the summation time range in the formula is 8760 hours per year.

[0041] Specifically, the constraints of the polysilicon full-process production model include: production model constraints for the trichlorosilane synthesis stage, production model constraints for the trichlorosilane distillation and purification stage, production model constraints for the trichlorosilane reduction stage, production model constraints for the tail gas recovery stage, production model constraints for the silicon tetrachloride hydrogenation stage, and production model constraints for the hydrogen chloride synthesis stage.

[0042] The production model constraints for the trichlorosilane synthesis process include input-output material relationship constraints, upper and lower limits of output constraints, and continuous operation duration constraints, as detailed below.

[0043] 1) Input / output material relationship: , In the formula, Let TCS be the output of the TCS generation process at time t. Let be the amount of silicon powder (Si) used at time t. The amount of hydrogen chloride (HCl) used at time t is given. and The figures represent the weights of TCS produced per unit weight of silicon powder (Si) and hydrogen chloride (HCl).

[0044] 2) Production limits: , In the formula, and These represent the minimum and maximum output of TCS per unit time, respectively.

[0045] 3) Continuous runtime constraint (this constraint describes the requirement that the continuous runtime after the TCS synthesis phase starts running must not be less than the minimum runtime limit): , In the formula, Let t be the duration that the TCS synthesis process has been running at time t. This is the minimum runtime limit for the TCS synthesis process; and This is a 0-1 variable representing the running status of the TCS synthesis process at times t-1 and t.

[0046] Since the TCS gas produced in the TCS synthesis stage generally goes directly into the next stage of TCS distillation and purification, there is almost no buffer capacity for temporarily storing TCS between the two stages. Therefore, there is no material storage model in this stage (there is a material storage model after the next stage of TCS distillation and purification).

[0047] The production model constraints for the trichlorosilane distillation and purification process include input-output material relationship constraints, upper and lower limits of output constraints, trichlorosilane buffer storage model constraints, and continuous operation duration constraints, as detailed below.

[0048] 1) Input / output material relationship: , In the formula, This refers to the yield of high-concentration TCS at time t during the distillation and purification process. , The figures represent the TCS production at time t for the STC hydrogenation and tail gas recovery stages, respectively. The STC hydrogenation and tail gas recovery stages will be modeled below. and The figures represent the weight of high-precision TCS that can be purified per unit weight of TCS produced in the TCS production process and the STC hydrogenation process, respectively.

[0049] 2) Production limits: , In the formula, and These represent the minimum and maximum yields of TCS per unit time during the distillation and purification process, respectively.

[0050] 3) High-purity TCS buffer storage model (This constraint characterizes the operational constraints of the TCS buffer storage tank between the TCS distillation and purification stage and the TCS reduction stage): , In the formula, Let TCS be the buffer size after the TCS distillation and purification process at time t. The amount of TCS used in the TCS restoration process at time t; and These are the upper and lower limits of the storage capacity in the TCS temporary storage area. This represents the initial storage amount in the TCS temporary storage slot at the initial moment.

[0051] 4) Continuous operating time constraint (This constraint describes the requirement that the continuous operating time of the TCS distillation and purification process must not be less than the minimum operating time limit after it starts operating): , In the formula, Let t be the duration of the TCS distillation and purification process at time t. Minimum operating time limit for the TCS distillation and purification process; and This is a 0-1 variable representing the operating status of the TCS distillation and purification process at times t-1 and t.

[0052] The production model constraints for the trichlorosilane reduction process include input / output material relationship constraints, upper and lower limits of output constraints, and output model constraints, as detailed below.

[0053] 1) Input / output material relationship: , In the formula, The yield of elemental silicon (Si) at time t during the reduction process. Let be the amount of hydrogen input in the TCS reduction process at time t. and These represent the weight of elemental silicon produced per unit weight of TCS and hydrogen during the reduction process, respectively.

[0054] 2) Production limits: , In the formula, and These represent the minimum and maximum yields of elemental silicon per unit time during the reduction process, respectively.

[0055] 3) Production Constraint Model (This constraint describes the total amount of elemental silicon produced in the reduction process, which must meet order demand): , In the formula, The total production cycle is one year. This represents the total demand for elemental silicon orders during this period.

[0056] The production model constraint for the exhaust gas recovery process is the input-output material relationship constraint, as detailed below.

[0057] 1) Input / output material relationship: , In the formula, , , , Let be the weight of hydrogen, STC, TCS, and HCl produced in the tail gas recovery stage at time t; the yield of the above materials is directly proportional to the tail gas volume, and the tail gas volume is directly proportional to the elemental silicon yield in the reduction stage. Proportional , , , Unit weight Production of hydrogen, STC, TCS, and HCl.

[0058] The exhaust gas recovery capacity matches the capacity of the TCS reduction stage, eliminating the need for production-constrained processes. Furthermore, the products from the exhaust gas recovery stage directly enter subsequent stages without intermediate storage; therefore, the production model for this stage consists solely of material input-output relationships.

[0059] The production model constraint for the silicon tetrachloride hydrogenation process is the input-output material relationship constraint, as detailed below.

[0060] The STC hydrogenation process uses cold hydrogenation technology to regenerate trichlorosilane (TCS) from silicon tetrachloride (STC) recovered from the tail gas. The generated TCS is then returned to the TCS distillation and purification process. The capacity of this process matches the output of the tail gas recovery. Therefore, the model for this process only has material input and output material relationship constraints.

[0061] 1) Input / output material relationship: , In the formula, Let TCS be the output of the STC hydrogenation process at time t. For STC production in the exhaust gas recovery process, The output of TCS per unit weight of STC.

[0062] The production model constraint for the hydrogen chloride synthesis process is a material balance constraint, as detailed below.

[0063] This step uses hydrogen and chlorine recovered from the tail gas to synthesize hydrogen chloride, which is then used in the TCS synthesis step. The production characteristics of this step are characterized by material balance constraints.

[0064] 1) Material balance constraints: , In the formula, Let t be the amount of hydrogen used in the HCl synthesis process. Let t be the hydrogen chloride yield in the hydrogen chloride synthesis process. This represents the weight of hydrogen chloride that can be produced per unit weight of hydrogen gas during the hydrogen chloride synthesis process.

[0065] The first formula indicates that the amount of hydrogen used in the reduction stage plus the amount of hydrogen used in the hydrogen chloride synthesis stage equals the amount of hydrogen recovered from the tail gas; the second formula indicates that the production of hydrogen chloride is proportional to the amount of hydrogen input; the third formula indicates that the amount of hydrogen chloride input to the TCS synthesis stage equals the amount of hydrogen chloride synthesized from hydrogen chloride plus the amount of hydrogen chloride recovered from the tail gas.

[0066] The above six constraints together constitute the production model constraints for the polysilicon modified Siemens process production line.

[0067] Step S14: Based on the new energy consumption potential assessment model, assess the new energy consumption potential of the polysilicon production line.

[0068] In one possible implementation, such as Figure 3 As shown, the new energy consumption potential of polysilicon production lines is evaluated based on the new energy consumption potential assessment model, including the following steps S21 to S22.

[0069] Step S21: Obtain the target new energy utilization rate.

[0070] Step S22: Based on the new energy consumption potential assessment model, determine the maximum new energy installed capacity of the polysilicon production line under the target new energy utilization rate, so as to assess the new energy consumption potential of the polysilicon production line.

[0071] During the project planning phase, solving the aforementioned new energy consumption potential assessment model yields the maximum wind and solar power installed capacity of polysilicon enterprises under fixed new energy utilization rate requirements. Enterprises can then understand the new energy consumption potential of their production processes. It should be noted that this new energy consumption potential assessment model can be solved using mature commercial optimization software, such as the Gurobi Optimizer, the CPLEX Optimization Studio (IBM ILOG CPLEX Optimization Studio), or the MOSEK Optimizer. This disclosure does not specifically limit or describe these methods.

[0072] This new energy consumption potential assessment model, under the premise of meeting the production characteristics and energy demand of polysilicon process flow, optimizes the production arrangement of multiple links and solves the new energy installed capacity that can be matched with polysilicon production lines under different new energy utilization rates, so as to achieve an accurate assessment of the new energy consumption potential of polysilicon production lines.

[0073] The renewable energy consumption potential assessment method for direct-supply polysilicon production lines provided in this disclosure considers the adjustable power consumption capability of polysilicon production lines and combines it with the entire production process of polysilicon production lines to construct a renewable energy consumption potential assessment model for polysilicon production lines. Then, through this renewable energy consumption potential assessment model, the maximum configurable renewable energy installed capacity under a specific renewable energy utilization rate is solved, and the maximum renewable energy installed capacity is used to assess the renewable energy consumption potential of polysilicon production lines. This achieves an accurate assessment of the renewable energy consumption potential of polysilicon production lines, determines the construction scale of renewable energy power plants, clarifies the renewable energy consumption potential of the entire plant, and avoids investment waste and power generation resource loss.

[0074] Based on this, this disclosure also provides a technical flowchart of a method for assessing the potential for new energy consumption in direct supply polysilicon production lines.

[0075] Figure 4 This is a technical flowchart of a method for assessing the potential for renewable energy consumption in a direct-supply polysilicon production line, provided in an embodiment of this disclosure. Figure 4 As shown, the technical process for assessing the new energy consumption potential of direct-supply polysilicon production lines includes the following steps: The first step is to collect basic parameters and production requirements for the polysilicon production line; The second step is to model the production characteristics of each stage of the polysilicon production line. After the models of multiple stages are combined, a full-process production model of the polysilicon production line is established. The third step is to generate a typical benchmark curve for new energy power generation based on the historical power generation data of the new energy sources in the location of the polysilicon production line. The fourth step is to develop a new energy consumption potential assessment model for polysilicon production lines and solve for the maximum installed capacity of new energy under the requirement of fixed new energy utilization rate.

[0076] For ease of understanding, the specific steps of the new energy consumption potential assessment method for direct-supply polysilicon production lines provided in this disclosure are explained below with reference to specific embodiments. The specific steps are as follows: Step 1: Collect production parameters and output requirements of the polysilicon production line to build a polysilicon production process model. This includes the parameters listed in Table 1.

[0077] Step 2: Construct a production model for the trichlorosilane (TCS) synthesis process. Based on the production characteristics and process flow of the TCS synthesis process, and combined with the collected production parameters, construct a model for the input-output material balance constraints, output limits, and continuous operation duration constraints of this process.

[0078] Step 3: Construct a production model for the TCS distillation and purification process. Based on the production characteristics and process flow of the TCS distillation and purification process, and combined with the collected production parameters for this process, construct the input-output material balance constraints, output limits, high-purity TCS buffer storage constraints, and continuous operation duration constraints for this process, thus completing the construction of the production model for this process.

[0079] Step 4: Construct a production model for the TCS reduction process. Based on the production characteristics and process flow of the TCS reduction process, and combined with the collected production parameters for this process, construct the input-output material balance constraints, output upper and lower constraints, and output demand constraints for this process, thus completing the construction of the production model for this process.

[0080] Step 5: Construct a production model for the exhaust gas recovery process. Based on the production characteristics and process flow of the exhaust gas recovery process, and combined with the collected production parameters for this process, construct the input and output material balance constraints for this process, thus completing the construction of the production model for this process.

[0081] Step Six: Construct a production model for the STC hydrogenation process. Based on the production characteristics and process flow of the STC hydrogenation process, and combined with the collected production parameters for this process, construct the input and output material balance constraints for this process, thus completing the construction of the production model for this process.

[0082] Step 7: Construct a production model for the hydrogen chloride synthesis process. Based on the production characteristics and process flow of the hydrogen chloride synthesis process, and combined with the collected production parameters for this process, construct the input and output material balance constraints for this process, thus completing the construction of the production model for this process.

[0083] It should be noted that steps two through seven are steps for constructing a complete polysilicon production model.

[0084] Step 8: Collect historical power generation curves from wind and solar power plants near the polysilicon production line. Record 8760 hours of power data for each plant over three years. By averaging the power at each moment, generate a typical benchmark curve for new energy power generation. Step Nine: Collect calculation parameters for the new energy consumption potential assessment model of polysilicon production lines, including the ratio coefficients of power consumption to main product output in the TCS synthesis, distillation and purification, reduction, STC hydrogenation, and hydrogen chloride synthesis stages, as well as the minimum new energy utilization rate expected by the enterprise.

[0085] Step 10: Construct a model to assess the renewable energy absorption potential of the polysilicon production line. This model is an optimization model, with the objective function being to maximize the renewable energy construction capacity; constraints include power balance constraints, power relationship models, renewable energy utilization rate constraints, and the polysilicon production line production model.

[0086] Step 11: Using a computer and the Gurobi solver, solve the absorption assessment model established in Step 10 to obtain the maximum installed capacity of new energy that the production line can absorb.

[0087] This disclosure, after refining the modeling of the production characteristics of multiple stages in the polysilicon production process, constructs a new energy consumption potential assessment model, which can fully consider the power consumption adjustment capability of the polysilicon production line and realize the solution of the scale of new energy construction in the planning stage.

[0088] Based on this, the present disclosure also provides a device for assessing the potential for new energy consumption in direct supply to polysilicon production lines.

[0089] Figure 5This is a structural block diagram of a new energy consumption potential assessment device for direct supply to polysilicon production lines provided in this disclosure embodiment. Figure 5 As shown, the new energy consumption potential assessment device 100 for the direct supply polysilicon production line includes a production model construction unit 110, a baseline curve determination unit 120, an assessment model construction unit 130, and an assessment unit 140.

[0090] Among them, the production model construction unit 110 is used to construct corresponding production models for each link of the polysilicon production line process based on the production parameters of the polysilicon production line to be evaluated, and to associate the production models of all links to obtain the polysilicon full-process production model.

[0091] Among them, the reference curve determination unit 120 is used to determine the new energy power generation reference curve of the polysilicon production line based on the historical power generation data of wind farms and photovoltaic farms near the polysilicon production line.

[0092] Among them, the evaluation model construction unit 130 constructs constraints based on the polysilicon full-process production model and the new energy power generation benchmark curve, and constructs an objective function with the maximum new energy installed capacity that the polysilicon production line can absorb as the optimization objective, thus obtaining the new energy absorption potential evaluation model.

[0093] Among them, the evaluation unit 140 is used to evaluate the new energy consumption potential of polysilicon production lines based on the new energy consumption potential evaluation model.

[0094] For details and benefits of the new energy consumption potential assessment device for direct-supply polysilicon production lines provided in this disclosure, please refer to the above description of the new energy consumption potential assessment method for direct-supply polysilicon production lines, which will not be repeated here.

[0095] It should be noted that the terms "first," "second," and similar terms used in this disclosure do not indicate any order, quantity, or importance, but are merely used to distinguish different parts. Terms such as "including" or "contains" mean that the element preceding the word covers the element listed after the word, and do not exclude the possibility of covering other elements as well.

[0096] Finally, it should be noted that the above content is only used to illustrate the technical solution of this disclosure, and is not intended to limit the scope of protection of this disclosure. Simple modifications or equivalent substitutions made by those skilled in the art to the technical solution of this disclosure do not depart from the substance and scope of the technical solution of this disclosure.

Claims

1. A method for assessing the potential for renewable energy consumption in direct-supply polysilicon production lines, characterized in that, include: Based on the production parameters of the polysilicon production line to be evaluated, a corresponding production model is constructed for each step of the process flow of the polysilicon production line, and the production models of all steps are linked together to obtain the full process production model of polysilicon. Based on the historical power generation data of wind farms and photovoltaic power plants near the polysilicon production line, a new energy power generation benchmark curve for the polysilicon production line is determined. Based on the polysilicon full-process production model and the new energy power generation benchmark curve, constraints are constructed, and the objective function is constructed with the maximum new energy installed capacity that the polysilicon production line can absorb as the optimization objective, thus obtaining the new energy absorption potential assessment model. The potential for new energy absorption of the polysilicon production line is evaluated based on the aforementioned new energy absorption potential assessment model.

2. The method for assessing the potential for new energy consumption in direct-supply polysilicon production lines according to claim 1, characterized in that, The reference curve for new energy power generation is as follows: ， In the formula, Let the new energy power be at time t. The percentage of wind power capacity in the polysilicon-equipped new energy power stations to be configured. and These refer to the selected wind farm installed capacity and photovoltaic farm installed capacity, respectively. and These represent the power generation of the wind farm and the power generation of the photovoltaic farm at time t in year i, respectively.

3. The method for assessing the potential for new energy consumption in direct-supply polysilicon production lines according to claim 1, characterized in that, The constraints include power balance constraints, power relationship model constraints, new energy utilization rate constraints, and polysilicon process production model constraints.

4. The method for assessing the potential for new energy consumption in direct-supply polysilicon production lines according to claim 3, characterized in that, The power balance constraints include: ， In the formula, The actual renewable energy consumption power at time t. Let be the power supplied by the power grid at time t. The power consumption of the polysilicon production line at time t.

5. The method for assessing the potential for new energy consumption in direct-supply polysilicon production lines according to claim 3, characterized in that, The constraints of the power relationship model include: ， In the formula, The actual renewable energy consumption power at time t. Let the new energy power be at time t. For the photovoltaic installation capacity to be built, For the wind power installed capacity to be built, For the maximum power generation capacity of new energy sources, Let be the power supplied by the power grid at time t. The power consumption of the polysilicon production line at time t. , , , , These are the power consumption ratios to the main product yields for the following stages: trichlorosilane synthesis, trichlorosilane distillation and purification, trichlorosilane reduction and tail gas recovery, silicon tetrachloride hydrogenation, and hydrogen chloride synthesis. , , , , The yields of trichlorosilane in the trichlorosilane synthesis stage at time t, the yield of high-concentration trichlorosilane in the trichlorosilane distillation and purification stage at time t, the yield of elemental silicon in the trichlorosilane reduction stage at time t, the yield of silicon tetrachloride in the silicon tetrachloride hydrogenation stage at time t, and the yield of hydrogen chloride in the hydrogen chloride synthesis stage at time t.

6. The method for assessing the potential for new energy consumption in direct-supply polysilicon production lines according to claim 3, characterized in that, The constraints on the utilization rate of new energy sources include: ， In the formula, The actual renewable energy consumption power at time t. This is the minimum requirement for the utilization rate of new energy sources. For the photovoltaic installation capacity to be built, For the wind power installed capacity to be built, Let be the power of the new energy source at time t.

7. The method for assessing the potential for new energy consumption in direct-supply polysilicon production lines according to claim 3, characterized in that, The constraints of the polysilicon end-process production model include: The production model constraints for the trichlorosilane synthesis process include: input and output material relationship constraints, upper and lower limits of output constraints, and continuous operation duration constraints. The production model constraints for the trichlorosilane distillation and purification process include: input and output material relationship constraints, production upper and lower limits constraints, trichlorosilane buffer storage model constraints, and continuous operation duration constraints. The production model constraints for the trichlorosilane reduction process include: input and output material relationship constraints, upper and lower limits of output constraints, and output model constraints. Production model constraints for the exhaust gas recovery process include: input and output material relationship constraints; The production model constraints for the silicon tetrachloride hydrogenation process include: input and output material relationship constraints; Constraints in the production model for hydrogen chloride synthesis include: material balance constraints.

8. The method for assessing the potential for new energy consumption in a direct-supply polysilicon production line according to any one of claims 1-7, characterized in that, The installed capacity of new energy sources includes photovoltaic installed capacity and wind power installed capacity, and the objective function includes: ， In the formula, For the photovoltaic installation capacity to be built, This refers to the wind power capacity to be built.

9. The method for assessing the potential for new energy consumption in direct-supply polysilicon production lines according to claim 1, characterized in that, The assessment of the new energy absorption potential of the polysilicon production line based on the new energy absorption potential assessment model includes: Achieve target new energy utilization rate; Based on the new energy consumption potential assessment model, the maximum new energy installed capacity of the polysilicon production line under the target new energy utilization rate is determined in order to assess the new energy consumption potential of the polysilicon production line.

10. A device for assessing the potential for new energy consumption in a direct-supply polysilicon production line, characterized in that, include: The production model construction unit is used to construct a corresponding production model for each step of the process flow of the polysilicon production line to be evaluated based on the production parameters of the polysilicon production line to be evaluated, and to associate the production models of all steps to obtain the full process production model of polysilicon. The reference curve determination unit is used to determine the new energy power generation reference curve of the polysilicon production line based on the historical power generation data of wind farms and photovoltaic farms near the polysilicon production line. The evaluation model construction unit constructs constraints based on the polysilicon full-process production model and the new energy power generation benchmark curve, and constructs an objective function with the maximum new energy installed capacity that the polysilicon production line can absorb as the optimization objective, thereby obtaining a new energy absorption potential evaluation model. An evaluation unit is used to evaluate the new energy absorption potential of the polysilicon production line based on the new energy absorption potential evaluation model.

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