A source-load collaborative optimization method considering heterogeneous industrial load power regulation characteristics

Abstract

This application relates to the field of power technology and discloses a source-load coordinated optimization method considering the power regulation characteristics of heterogeneous industrial loads. It includes constructing a cement industry load production process model using a state-task network method, determining the production constraints that the cement industry load must meet to participate in power system demand response based on this model, constructing a dynamic model of electrolytic aluminum load regulation based on the electrolytic cell heat balance equation, determining the constraints that the electrolytic aluminum load must meet to participate in power system demand response based on this model, minimizing the power system operating cost as the objective function, setting constraints on the power system side, using the electrolytic aluminum load to compensate for the power response deviation generated when the cement industry load participates in power system regulation, and solving for the source-load coordinated optimization result. This application improves the safety and reliability of the power system.

Description

Technical Field

[0001] This application relates to the field of power technology, and in particular to a source-load collaborative optimization method that considers the power regulation characteristics of heterogeneous industrial loads. Background Technology

[0002] Currently, research on strategies for high-energy-consuming industrial loads to participate in power system demand response only studies the dispatching strategies and production planning of single loads, without considering the significant differences in power regulation characteristics among diverse and heterogeneous industrial loads. This leads to deviations between expected and actual responses, weakening the safety and reliability of the power system. Summary of the Invention

[0003] In view of this, this application provides a source-load collaborative optimization method that takes into account the power regulation characteristics of heterogeneous industrial loads.

[0004] This application discloses a source-load collaborative optimization method considering the power regulation characteristics of heterogeneous industrial loads, which includes: Step 1: Construct a discrete adjustable high-energy-consuming industrial load power model: The state-task network method is used to construct a cement industry load production process model. Based on this model, the production constraints that the cement industry load must meet to participate in the power system demand response are determined. The production constraints include material balance constraints, first output constraints, storage constraints, rotary kiln continuous working state constraints, and first load power balance constraints. Step 2: Construct a continuously adjustable high-energy-consuming industrial load power model: Construct a dynamic model for electrolytic aluminum load regulation based on the electrolytic cell heat balance equation. Based on this model, determine the constraints that the electrolytic aluminum load must meet to participate in the power system demand response. The constraints include temperature-power coupling constraints, temperature constraints, second production constraints, voltage ramping constraints, and second load power balance constraints. Step 3: Formulate a source-load synergistic optimization strategy that takes into account heterogeneous industrial loads: Take the power system operating cost as the objective function and minimize the objective function. At the same time, set constraints on the power system side. Use the electrolytic aluminum load that meets the constraints in Step 2 to compensate for the power response deviation generated when the cement industry load that meets the production constraints in Step 1 participates in power system regulation. Solve for the optimization result of source-load synergy. The constraints on the power system side include power system power balance constraints, photovoltaic and wind power output constraints, thermal power output and ramping constraints.

[0005] Furthermore, the material balance constraint in step 1 is: material m exist t The available quantity for a given time period is determined by the materials. m exist t The available quantity in the -1 time period, t The quantity generated at the start of the time period, and the materials at...t Composition of consumption at the start of the time period; The first production constraint is that the daily cement production meets the daily delivery requirements determined by the daily order volume. Mathematically, this is expressed as the quality difference of cement at the beginning and end of the demand response period matching the daily production demand. The storage constraint is that the storage amount of materials in each stage of cement production is between the lower limit and the upper limit of storage. The continuous working state constraint of the rotary kiln means that the rotary kiln equipment is always in working state during the demand response period. The first load power balance constraint is the load of the cement industry at t The total power consumption during the period is t The sum of the power consumption of all electrical devices during the time period.

[0006] Furthermore, the expression for the material balance constraint is: (1) in, m Indicates materials, Indicates the production process. t Indicates time period, M For material quality, For the production process The total number of devices, Variables are 0-1, representing the production process. The start / stop status of the equipment. For the production process Rated power of a single production unit per unit time - material conversion coefficient For the production process Rated power of a single production unit For the production process The mass of materials generated or consumed by a single production unit; rated power - material conversion factor for production processes. The ratio of the output per unit time of a single production unit to its rated power; The expression for the production constraint is: (2) in, and These refer to the quality of the cement product at the beginning and end of the demand response period, respectively. The daily production demand for cement is determined by the daily order volume. The expression for the storage constraint is: (3) in, and Materials mThe lower and upper limits of warehousing; The expression for the continuous operation state constraint of the rotary kiln is: (4) in, For the first The operating status of the rotary kiln. This refers to the number of rotary kiln platforms; The expression for the load power balance constraint is: (5) in, This is the load on the cement industry.

[0007] Furthermore, in step 2, the temperature-power coupling constraint is constructed based on the first law of thermodynamics. The heat input, heat dissipation, and heat consumption caused by production of the electrolytic cell satisfy the thermal balance relationship. The theoretical energy consumption of the electrolytic aluminum chemical reaction process is derived from the first law of thermodynamics. The heat dissipation of the electrolytic cell includes two parts: heat dissipation through the alumina coating and heat dissipation through the carbon block lining. The heat dissipation per unit time is calculated using the corresponding heat transfer formula.

[0008] Furthermore, the expression for the temperature-power coupling constraint is: (6) in, , These are the specific heat capacity and mass of aluminum, respectively. This refers to the electrolysis temperature. , , These are the heat input, heat dissipation, and heat consumption caused by production per unit time, respectively. According to the first law of thermodynamics, the theoretical energy consumption of the electrolytic aluminum chemical reaction process is: (7) The heat dissipation through the alumina coating per unit time is: (8) in, For the area of ​​the alumina coating, For air temperature, To characterize the combined coefficient of convective and radiative heat transfer between the alumina coating and air, It is a constant. It is the Stefan-Boltzmann constant. Emissivity of solid surface; The heat dissipation of the electrolytic cell per unit time through the sidewall crust and carbon blocks is: (9) in, The area of ​​the side wall of the electrolytic capacitor is... To characterize the composite coefficient of convective and radiative heat transfer between the molten electrolyte and air, The heat transfer coefficient between the molten electrolyte and the sidewall crust is given. The heat dissipation coefficient from the surface of the electrolytic cell shell to the air; and These are the thicknesses of the sidewall crust and the carbon block liner, respectively. and These are the heat transfer rates of the sidewall crust and the carbon block lining, respectively.

[0009] Furthermore, in step 2, the temperature constraint is that the electrolysis temperature is between the set upper and lower boundaries; The second production constraint is that the daily output of electrolytic aluminum meets the rated output requirement, which is jointly determined by the electrolytic aluminum production coefficient, the number of electrolytic cells, the electrolysis efficiency, and the electrolysis current. The voltage ramp constraint is that the DC voltage on the secondary side of the converter transformer is between the upper and lower boundaries, and the voltage change rate does not exceed the set upper and lower ramp rates. The second load power balance constraint is that all electrolytic cells are connected in series to ensure the same electrolysis current, and that the specifications, structure and process of each electrolytic cell are consistent, and the power of each electrolytic cell is equal.

[0010] Furthermore, the expression for the temperature constraint is: (10) in, yes t Electrolysis temperature during the period and These are the upper and lower boundaries of the electrolysis temperature, respectively. The expression for the production constraint is: (11) in, It is the electrolytic aluminum production coefficient. It is the number of electrolytic cells. It is the electrolysis efficiency. It is the electrolysis current; It is to regulate the output within the time interval t. It is the output that controls the total duration T; The expression for the voltage ramp-up constraint is: (12) in, It is the DC voltage on the secondary side of the converter transformer. and These are the upper and lower boundaries of the DC voltage. and These are the up and down ramp rates of the DC voltage, respectively. The expression for the input power of each electrolytic cell, i.e., the heat input per unit time, is: (13) in, This refers to the load power of electrolytic aluminum.

[0011] Furthermore, the objective function in step 3 encompasses the operating costs of photovoltaic, wind, and thermal power, the adjustment costs of electrolytic aluminum load and cement industry load, and also includes the unit penalty costs of curtailment of solar and wind power and carbon emissions, as well as the cost coefficient of deep peak shaving for thermal power generation. The difference between the actual output and the predicted output of photovoltaic and wind power in the objective function takes into account the curtailment penalties, the actual output of thermal power is combined with the rated power and the deep peak shaving coefficient to calculate the relevant costs, and the adjustment costs of electrolytic aluminum and cement industry loads are determined by the difference in power consumption before and after regulation.

[0012] Furthermore, the expression for minimizing the objective function is:

[0013] (14) in, , , , and These are the operating costs for photovoltaic, wind power, thermal power, electrolytic aluminum loads, and cement industry loads, respectively. , and These are the unit penalties for curtailing solar power, wind power, and carbon emissions; , and These are the unit costs of thermal power generation, energy storage operation, and load regulation in the cement industry, respectively. and The predicted power outputs for photovoltaic and wind power are respectively. and These are the actual outputs of photovoltaic and wind power, respectively. and These are the actual output and rated power of thermal power plants, respectively. This refers to the peak-shaving coefficient for thermal power plants. and These are the power consumption figures for electrolytic aluminum loads that are subject to regulation and those that are not. and These refer to the electricity consumption of the cement industry, which is subject to load regulation and which is not.

[0014] Furthermore, the power system power balance constraint in step 3 is to ensure that the power system maintains power balance at all times, and its expression is: (15) The expressions for the photovoltaic and wind power output constraints are as follows: (16) (17) The expressions for the thermal power output and ramping constraints are as follows: (18) (19) in, and These are the lower and upper limits of thermal power output, respectively. ; and These are the lower and upper limits of the ramp-up capacity of thermal power plants, respectively. To adjust the time step.

[0015] By adopting the above-mentioned technical solution, this application has the following advantages: it considers the significant differences in power regulation characteristics among diverse and heterogeneous industrial loads, avoids deviations between expected and actual responses, and improves the safety and reliability of the power system. For diverse and heterogeneous industrial loads, understanding their power response characteristics and formulating corresponding coordinated control strategies helps to accurately respond to the power regulation needs of the power system, thereby significantly improving the power grid's supply guarantee pressure and economy. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments recorded in the embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings.

[0017] Figure 1 This is a schematic flowchart of a source-load collaborative optimization method considering the power regulation characteristics of heterogeneous industrial loads according to an embodiment of this application. Figure 2 This is a schematic diagram of the cement industry load production process according to an embodiment of this application; Figure 3 This is a schematic diagram of the thermal balance of the electrolytic cell in an embodiment of this application. Detailed Implementation

[0018] The present application will be further described in conjunction with the accompanying drawings and embodiments. The described embodiments are only some, not all, of the embodiments of the present application. All other embodiments obtained by those skilled in the art should fall within the protection scope of the embodiments of the present application.

[0019] Terminology Explanation: Discrete adjustable high-energy-consuming industrial loads refer to a type of load in high-energy-consuming industries where the power consumption adjustment is limited and countable. These loads participate in the power system demand response by controlling the start-up and shutdown status of electrical equipment, inevitably resulting in response deviations. The cement industry load is a typical example of a discrete adjustable industrial load.

[0020] Continuously adjustable high-energy-consuming industrial loads refer to a type of load in high-energy-consuming industrial loads where the power consumption adjustment can be arbitrarily selected within an adjustable range and cannot be listed. Electrolytic aluminum loads are typical continuously adjustable industrial loads. This application considers the material input-output relationships, electrical attributes of electrical equipment, and coupling between various stages in the production process of heterogeneous industrial loads. Based on the state-task network method, the production constraints that need to be met during the power adjustment process of discrete adjustable industrial loads are determined. Based on the thermal balance relationship of the electrolytic cell, the production constraints that need to be met during the power adjustment process of continuously adjustable industrial loads are determined, and a power model for subsequent industrial loads is constructed. Based on the equipment control methods and power regulation characteristics in the production process, a power system source-load collaborative optimization strategy considering heterogeneous industrial loads is proposed. At the same time, considering that some loads have similar characteristics and production constraints, this method is also applicable to other discrete / continuously adjustable industrial loads.

[0021] High-energy-consuming industrial loads, as ideal load-side adjustable resources, are considered crucial for improving grid flexibility. Researching the electricity consumption characteristics and power regulation strategies of different heterogeneous industrial loads is a prerequisite for their participation in demand response. This method first derives, based on the production process and electricity consumption characteristics of heterogeneous industrial loads, considering the material input-output relationships of each production stage, the electrical attributes of electrical equipment, and the coupling between different stages, detailing discrete and interconnected adjustable industrial load power models. Then, taking into account the discrete and continuous characteristics of power regulation in heterogeneous industrial loads, a source-load collaborative optimization strategy for power systems involving heterogeneous industrial loads is proposed. With the goal of minimizing power system cost, the output of each generator unit and the production plan of industrial load equipment are solved.

[0022] See Figure 1 This application provides an embodiment of a source-load collaborative optimization method considering the power regulation characteristics of heterogeneous industrial loads, which includes the following steps: S1: Constructing a discrete adjustable high-energy-consuming industrial load power model: A state-task network method is used to construct a cement industry load production process model. Based on this model, the production constraints that the cement industry load must meet to participate in the power system demand response are determined. The production constraints include material balance constraints, first output constraints, storage constraints, rotary kiln continuous working state constraints, and first load power balance constraints.

[0023] Specifically, as a typical discrete adjustable high-energy-consuming industrial load, the cement manufacturing process, including raw material crushing, raw meal grinding, raw meal homogenization, fuel grinding, and cement grinding, are all interruptible production stages. Correspondingly, the electrical equipment such as crushers, vertical roller mills, mixing homogenizers, ball mills, and coal mills can all be shut down. Discrete adjustable high-energy-consuming loads have the following characteristics: discrete power consumption, intermittent and continuous production behavior, no inertia in the production process, a limited number of production equipment, and high power consumption per unit.

[0024] In the cement industry, the start-up and shutdown states of electrical equipment are determined by material utilization and the sequence of production processes. Therefore, this application uses the State Task Network (STN) method to construct a production process model for the cement industry load. The modeling results are as follows: Figure 2 As shown.

[0025] based on Figure 2 The STN model of the cement production process shown can be used to further determine the production constraints that must be met when the cement industry load participates in the power system demand response. Its mathematical expression is as follows: a) Material balance constraints materials m exist t The available quantity for a given period (in the cement manufacturing industry, this is the material quantity) is determined by the material. m exist t The available quantity in the -1 time period, t The quantity generated at the start of the time period, and the materials at... t The consumption amount at the start of the time period consists of three parts, which can be represented as: (1) In the formula, the subscript m Indicates materials, Indicates the production process. t Indicates a time period; M For material quality, For the production process The total number of devices, Variables are 0-1, representing the production process. The start / stop status of the equipment. For the production process Rated power of a single production unit per unit time - material conversion coefficient For the production process The rated power of a single production unit. Therefore That is, the production process. i The mass of materials generated or consumed by a single production unit, with rated power minus the material conversion factor, represents the production process. The ratio of the output per unit time of a single production equipment to its rated power.

[0026] b) First production constraint To participate in power system demand response without affecting the normal production of the cement plant, it is necessary to ensure that the final daily cement production meets the daily delivery requirements, which can be expressed as: (2) In the formula, and These refer to the quality of the cement product at the beginning and end of the demand response period, respectively. The daily production demand for cement is determined by the daily order volume.

[0027] c) Storage constraints Each stage of cement production has its own storage facility, allowing for independent start-up and shutdown of electrical equipment in different production stages. This eliminates the need for strict adherence to the production flow, increasing the flexibility of the cement industry's workload. However, the storage capacity of each material is limited. Therefore, upper limits need to be set for stored materials. Simultaneously, to ensure the safety and reliability of cement production, minimum storage constraints also need to be set, which can be expressed as: (3) In the formula, and Materials m The lower and upper limits of warehousing.

[0028] d) Constraints on continuous operation of rotary kiln Clinker calcination is a core step in the entire cement manufacturing process. The corresponding rotary kiln system must operate continuously, except for one or two routine maintenance shutdowns per year. Therefore, the rotary kiln equipment should always be operational during the cement industry's demand response period, which can be expressed as: (4) In the formula, For the first The operating status of the rotary kiln. This refers to the number of rotary kiln platforms.

[0029] e) First load power balance constraint Cement industry load t The total power consumption during the period is t The sum of the power consumption of all devices during a given time period can be expressed as: (5) in, This is the load on the cement industry.

[0030] S2: Construct a continuously adjustable high-energy-consuming industrial load power model: Construct a dynamic model for electrolytic aluminum load regulation based on the electrolytic cell heat balance equation. Based on this model, determine the constraints that electrolytic aluminum load must meet to participate in the power system demand response. The constraints include temperature-power coupling constraints, temperature constraints, second production constraints, voltage ramping constraints, and second load power balance constraints.

[0031] Specifically, as a typical continuously adjustable high-energy-consuming industrial load, 97% of the electricity consumption in an electrolytic aluminum load is concentrated in the electrolysis process, with the key electrical equipment being the electrolytic cell, and the power supply cannot be interrupted during each electrolysis process. Continuously adjustable high-energy-consuming loads have the following characteristics: continuous power consumption, continuous and variable production rate, and continuous internal reaction process.

[0032] The energy consumption of electrolytic aluminum production mainly plays two roles: one part is used to maintain the stable temperature required for the electrolytic reaction, providing a suitable environment for the chemical reaction; the other part directly participates in the electrolytic reaction, promoting the reduction of metal oxides. Therefore, this application constructs a dynamic model for electrolytic aluminum load regulation based on the electrolytic cell heat balance equation, such as... Figure 2 As shown.

[0033] a) Temperature-power coupling constraint based on Figure 3 The schematic diagram of the electrolytic cell's thermal balance shown can further determine the temperature-power coupling constraint that must be satisfied when the electrolytic aluminum load participates in the power system's demand response. Its mathematical expression is as follows: (6) In the formula, , These are the specific heat capacity and mass of aluminum, respectively. This refers to the electrolysis temperature. , , These represent the heat input, heat dissipation, and heat consumption per unit time, respectively. According to the first law of thermodynamics, the theoretical energy consumption of the electrolytic aluminum chemical reaction process is: (7) The entire bottom of the electrolytic cell is covered with insulating and refractory materials, resulting in almost no heat loss compared to the alumina coating and carbon block lining. Therefore, heat dissipation in the electrolytic cell mainly consists of two parts: heat dissipation through the alumina coating and heat dissipation through the carbon block lining. The heat dissipation through the alumina coating per unit time is: (8) In the formula, For the area of ​​the alumina coating, For air temperature, To characterize the combined coefficient of convective and radiative heat transfer between the alumina coating and air, It is a constant. It is the Stefan-Boltzmann constant. This represents the blackness of a solid surface, typically 0.82.

[0034] The amount of heat dissipated by the electrolytic cell per unit time through the sidewall crust and carbon blocks can be expressed as: (9) In the formula, The area of ​​the side wall of the electrolytic capacitor is... To characterize the composite coefficient of convective and radiative heat transfer between the molten electrolyte and air, The heat transfer coefficient between the molten electrolyte and the sidewall crust is given. The heat dissipation coefficient from the surface of the electrolytic cell shell to the air; and These are the thicknesses of the sidewall crust and the carbon block liner, respectively. and These are the heat transfer rates of the sidewall crust and the carbon block lining, respectively.

[0035] b) Temperature constraint (10) In the formula, yes t Electrolysis temperature during the period and These are the upper and lower boundaries of the electrolysis temperature, respectively.

[0036] c) Second production constraint (11) In the formula, It is the electrolytic aluminum production coefficient. It is the number of electrolytic cells. It is the electrolysis efficiency. It is the electrolysis current; It is to regulate the output within the time interval t. It is the output that controls the total duration T.

[0037] d) Voltage ramp-up constraints (12) In the formula, It is the DC voltage on the secondary side of the converter transformer. and These are the upper and lower boundaries of the DC voltage. and These represent the up and down ramp rates of the DC voltage.

[0038] e) Second load power balance constraint All electrolytic cells are connected in series to ensure the same electrolytic current. Furthermore, due to identical specifications, structure, and process, each electrolytic cell also has almost the same voltage. Therefore, the power allocated to each electrolytic cell is almost equal, which can be expressed as: (13) In the formula, For electrolytic aluminum load power, S3: Formulate a source-load coordinated optimization strategy that takes into account heterogeneous industrial loads: take the power system operating cost as the objective function and minimize the objective function, while setting constraints on the power system side. Use the electrolytic aluminum load that meets the constraints in S2 to compensate for the power response deviation generated when the cement industry load that meets the production constraints in S1 participates in power system regulation, and solve for the optimization result of source-load coordination; the constraints on the power system side include power system power balance constraints, photovoltaic and wind power output constraints, thermal power output and ramping constraints.

[0039] Specifically, this application proposes a source-load coordinated optimization strategy for power systems involving heterogeneous industrial loads. The goal is to minimize power system costs, and the optimization results for source-load coordination are obtained. Cement industry loads are typical discrete adjustable loads, and their regulation involves controlling the start-up and shutdown states of electrical equipment. When participating in power system regulation, response deviations inevitably occur. Utilizing continuously adjustable loads, such as electrolytic aluminum loads, to compensate for these power response deviations is an effective method to solve this problem.

[0040] a) Objective function This strategy aims to minimize the cost of the power system and can be expressed as:

[0041] (14) In the formula, , , , and These are the operating costs for photovoltaic, wind power, thermal power, electrolytic aluminum loads, and cement industry loads, respectively. , and These are the unit penalties for curtailing solar power, wind power, and carbon emissions; , and These are the unit costs of thermal power generation, energy storage operation, and load regulation in the cement industry, respectively. and The predicted power outputs for photovoltaic and wind power are respectively. and These are the actual outputs of photovoltaic and wind power, respectively. and These are the actual output and rated power of thermal power plants, respectively. This refers to the peak-shaving coefficient for thermal power plants. and These are the power consumption figures for electrolytic aluminum loads that are subject to regulation and those that are not. and These refer to the electricity consumption of the cement industry, which is subject to load regulation and which is not.

[0042] b) Constraints A power system that maintains power balance at all times can be represented as: (15) The fact that the output of photovoltaic and wind power does not exceed the predicted value can be expressed as: (16) (17) Thermal power output and ramping constraints can be expressed as: (18) (19) In the formula, and These are the lower and upper limits of thermal power output, respectively. ; and These are the lower and upper limits of the ramp-up capacity of thermal power plants, respectively. To adjust the time step.

[0043] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application and not to limit them. Although this application has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of this application. Any modifications or equivalent substitutions that do not depart from the spirit and scope of this application should be covered within the protection scope of the claims of this application.

Claims

1. A source-load collaborative optimization method considering heterogeneous industrial load power regulation characteristics, characterized in that, include: Step 1: Construct a discrete adjustable high-energy-consuming industrial load power model: The state-task network method is used to construct a cement industry load production process model. Based on this model, the production constraints that the cement industry load must meet to participate in the power system demand response are determined. The production constraints include material balance constraints, first output constraints, storage constraints, rotary kiln continuous working state constraints, and first load power balance constraints. Step 2: Construct a continuously adjustable high-energy-consuming industrial load power model: Construct a dynamic model for electrolytic aluminum load regulation based on the electrolytic cell heat balance equation. Based on this model, determine the constraints that the electrolytic aluminum load must meet to participate in the power system demand response. The constraints include temperature-power coupling constraints, temperature constraints, second production constraints, voltage ramping constraints, and second load power balance constraints. Step 3: Formulate a source-load synergistic optimization strategy that takes into account heterogeneous industrial loads: Take the power system operating cost as the objective function and minimize the objective function. At the same time, set constraints on the power system side. Use the electrolytic aluminum load that meets the constraints in Step 2 to compensate for the power response deviation generated when the cement industry load that meets the production constraints in Step 1 participates in power system regulation. Solve for the optimization result of source-load synergy. The constraints on the power system side include power system power balance constraints, photovoltaic and wind power output constraints, thermal power output and ramping constraints.

2. The method according to claim 1, characterized in that, The material balance constraint in step 1 is: material m At t The available quantity of periods is composed of the available quantity of material m At t - the available quantity of periods, the generated quantity at the start of periods, the consumed quantity of material at the start of periods t At t the start of periods, the consumed quantity of material at the start of periods The first production constraint is that the daily cement production meets the daily delivery requirements determined by the daily order volume. Mathematically, this is expressed as the quality difference of cement at the beginning and end of the demand response period matching the daily production demand. The storage constraint is that the storage amount of materials in each stage of cement production is between the lower limit and the upper limit of storage. The continuous working state constraint of the rotary kiln means that the rotary kiln equipment is always in working state during the demand response period. The first load power balance constraint is the total power consumption of the cement industry load in t the time period. The second load power balance constraint is the sum of the power consumption of all the power consuming devices in the time period. t the time period. The second load power balance constraint is the sum of the power consumption of all the power consuming devices in the time period.

3. The method of claim 2, wherein, The expression for the material balance constraint is: (1) wherein, m represents a material, represents a production stage, t represents a time period, M is the mass of the material, is the number of devices in the production stage , is a 0-1 variable indicating the on-off state of the device in the production stage , is the rated power-material conversion coefficient of a single production device in the production stage , is the rated power of a single production device in the production stage , is the mass of the material generated or consumed by a single production device in the production stage ; the rated power-material conversion coefficient is the ratio of the unit time output of a single production device in the production stage to the rated power. The expression for the production constraint is: (2) wherein, and respectively are the mass of the product cement at the start and end of the demand response period; is the daily production demand of cement, determined by the order volume of the day; The expression for the storage constraint is: (3) wherein, and are the lower and upper limits of the storage of the material m respectively. The expression for the continuous operation state constraint of the rotary kiln is: (4) wherein, is the first the operating state of the rotary kiln station, is the number of rotary kiln stations; The expression for the load power balance constraint is: (5) in, This is the load on the cement industry.

4. The method according to claim 1, characterized in that, In step 2, the temperature-power coupling constraint is constructed based on the first law of thermodynamics. The heat input, heat dissipation and heat consumption caused by production of the electrolytic cell satisfy the thermal balance relationship. The theoretical energy consumption of the electrolytic aluminum chemical reaction process is derived from the first law of thermodynamics. The heat dissipation of the electrolytic cell includes two parts: heat dissipation through the alumina coating and heat dissipation through the carbon block lining. The heat dissipation per unit time is calculated by the corresponding heat transfer formula.

5. The method according to claim 4, characterized in that, The expression for the temperature-power coupling constraint is: (6) in, , These are the specific heat capacity and mass of aluminum, respectively. This refers to the electrolysis temperature. , , These are the heat input, heat dissipation, and heat consumption caused by production per unit time, respectively. According to the first law of thermodynamics, the theoretical energy consumption of the electrolytic aluminum chemical reaction process is: (7) The heat dissipation through the alumina coating per unit time is: (8) in, The area of ​​the alumina coating is... For air temperature, To characterize the combined coefficient of convective and radiative heat transfer between the alumina coating and air, It is a constant. It is the Stefan-Boltzmann constant. Emissivity of solid surface; The heat dissipation of the electrolytic cell per unit time through the sidewall crust and carbon blocks is: (9) in, The area of ​​the side wall of the electrolytic capacitor is... To characterize the composite coefficient of convective and radiative heat transfer between the molten electrolyte and air, The heat transfer coefficient between the molten electrolyte and the sidewall crust is given. The heat dissipation coefficient from the surface of the electrolytic cell shell to the air; and These are the thicknesses of the sidewall crust and the carbon block liner, respectively. and These are the heat transfer rates of the sidewall crust and the carbon block lining, respectively.

6. The method according to claim 1, characterized in that, In step 2, the temperature constraint is that the electrolysis temperature is between the set upper and lower boundaries; The second production constraint is that the daily output of electrolytic aluminum meets the rated output requirement, which is jointly determined by the electrolytic aluminum production coefficient, the number of electrolytic cells, the electrolysis efficiency, and the electrolysis current. The voltage ramp constraint is that the DC voltage on the secondary side of the converter transformer is between the upper and lower boundaries, and the voltage change rate does not exceed the set upper and lower ramp rates. The second load power balance constraint is that all electrolytic cells are connected in series to ensure the same electrolysis current, and that the specifications, structure and process of each electrolytic cell are consistent, and the power of each electrolytic cell is equal.

7. The method according to claim 6, characterized in that, The expression for the temperature constraint is: (10) in, yes t Electrolysis temperature during the period and These are the upper and lower boundaries of the electrolysis temperature, respectively. The expression for the second production constraint is: (11) in, It is the electrolytic aluminum production coefficient. It is the number of electrolytic cells. It is the electrolysis efficiency. It is the electrolysis current; It is to regulate the output within the time interval t. It is the output that controls the total duration T; The expression for the voltage ramp-up constraint is: (12) in, It is the DC voltage on the secondary side of the converter transformer. and These are the upper and lower boundaries of the DC voltage. and These are the up and down ramp rates of the DC voltage, respectively. The expression for the input power of each electrolytic cell, i.e., the heat input per unit time, is: (13) in, This refers to the load power of electrolytic aluminum.

8. The method according to claim 1, characterized in that, The objective function in step 3 covers the operating costs of photovoltaic, wind power, and thermal power, the adjustment costs of electrolytic aluminum load and cement industry load, and also includes the unit penalty costs of curtailment of solar and wind power and carbon emissions, as well as the cost coefficient of deep peak shaving of thermal power. The difference between the actual output and the predicted output of photovoltaic and wind power in the objective function takes into account the curtailment penalties. The actual output of thermal power is combined with the rated power and the deep peak shaving coefficient to calculate the relevant costs. The adjustment costs of electrolytic aluminum and cement industry load are determined by the difference in power consumption before and after regulation.

9. The method according to claim 8, characterized in that, The expression for minimizing the objective function is: (14) in, , , , and These are the operating costs for photovoltaic, wind power, thermal power, electrolytic aluminum loads, and cement industry loads, respectively. , and These are the unit penalties for curtailing solar power, wind power, and carbon emissions; , and These are the unit costs of thermal power generation, energy storage operation, and load regulation in the cement industry, respectively. and The predicted power outputs for photovoltaic and wind power are respectively. and These are the actual outputs of photovoltaic and wind power, respectively. and These are the actual output and rated power of thermal power plants, respectively. This refers to the peak-shaving coefficient for thermal power plants. and These are the power consumption figures for electrolytic aluminum loads that are subject to regulation and those that are not. and These refer to the electricity consumption of the cement industry, which is subject to load regulation and which is not.

10. The method according to claim 9, characterized in that, In step 3, the power system power balance constraint is to ensure that the power system maintains power balance at all times, and its expression is: (15) The expressions for the photovoltaic and wind power output constraints are as follows: (16) (17) The expressions for the thermal power output and ramping constraints are as follows: (18) (19) in, and These are the lower and upper limits of thermal power output, respectively. ; and These are the lower and upper limits of the ramp-up capacity of thermal power plants, respectively. To adjust the time step.

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