Submerged arc furnace production and energy system and submerged arc furnace load distribution method

Abstract

The invention relates to a submerged arc furnace production and energy system and a submerged arc furnace load distribution method. The method comprises the following steps that a production plan, a maintenance plan and new energy output data are obtained; predicting the load of the submerged arc furnace according to the production plan; determining production halt data of the submerged arc furnace according to the maintenance plan; unifying the data granularity of the new energy output data, the load prediction data and the production halt data, intercepting the data length according to the task requirement, and constructing a load distribution data set; and by taking maximization of the new energy utilization rate as an objective function, carrying out submerged arc furnace load distribution based on the load distribution data set. Compared with the prior art, the method has the advantages that the distribution scheme is automatically solved, and the new energy utilization rate can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of energy systems, and in particular to a submerged arc furnace production and energy system, and a submerged arc furnace load distribution method. Background Art

[0002] In the field of microgrid dispatching and control technology, it is necessary to dispatch and control a microgrid scenario with at least photovoltaic power stations, energy storage batteries and load power facilities. The main production field is the alloy smelting industry with ore-fired furnaces as the main power users. In such a microgrid scenario, the user's electricity source can be either in-grid electricity (photovoltaic power generation or energy storage battery electricity) or out-grid electricity (buying electricity from the external power grid, the sales electricity price of the external power grid has three types of prices: peak, valley and flat at different times of the day). Alloy smelting has the following production characteristics: 1. The production batch has a regular periodicity; 2. The efficiency of production can be controlled by multi-gear load regulation. The traditional load distribution is mainly manually distributed by operators based on experience: 1. Only the planning of production is considered, ignoring the maximum consumption of new energy; 2. Manual allocation based on experience cannot finely assess the pros and cons of its allocation strategy. There is no quantifiable indicator to measure the pros and cons of the operator's allocation strategy based on experience, and the reusability is poor. Summary of the invention

[0003] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and to provide a submerged arc furnace production and energy system, a submerged arc furnace load distribution method, and to provide a submerged arc furnace load distribution plan in combination with the prediction of new energy power supply capacity, so as to maximize the utilization rate of new energy.

[0004] The purpose of the present invention can be achieved by the following technical solutions:

[0005] A submerged arc furnace production and energy system based on new energy power supply includes a power transmission and distribution system, a renewable energy power generation system, an energy storage system and a submerged arc furnace production system, wherein the power transmission and distribution system is respectively connected to the renewable energy power generation system, the energy storage system and the submerged arc furnace production system.

[0006] The submerged arc furnace production and energy system also includes an energy control system, which includes:

[0007] A renewable energy power generation control system, used to control the operation of the renewable energy power generation system;

[0008] An energy storage control system, used to control the operation of the energy storage system;

[0009] A submerged arc furnace production control system, used to control the operation of the submerged arc furnace production system;

[0010] The integrated control system is used to perform integrated control of the ore-fired furnace production and energy system through the power transmission and distribution system, send control instructions to the renewable energy power generation control system and the ore-fired furnace production control system, and receive control feedback; receive dispatch instructions from the energy storage control system and provide feedback to the energy storage control system.

[0011] A method for distributing load of a submerged arc furnace with the goal of optimizing the utilization rate of new energy, the method is implemented based on the system as described above, and comprises the following steps:

[0012] Obtain production plans, maintenance plans and new energy output data;

[0013] Carry out load forecast of submerged arc furnace according to production plan;

[0014] Determine the shutdown data of the submerged arc furnace according to the maintenance plan;

[0015] Unify the data granularity of new energy output data, load forecast data, and shutdown data, and cut the data length according to task requirements to build a load distribution data set;

[0016] Taking the maximization of new energy utilization as the objective function, the load distribution of the ore-fired furnace is carried out based on the load distribution data set.

[0017] The new energy utilization rate is defined as the load distribution output of the ore-fired furnace divided by the new energy input.

[0018] The calculation method of the objective function of the load distribution of the blast furnace is as follows: determine the load prediction time length according to the prediction period and granularity, sum up the load values ​​allocated to all blast furnaces at each moment within the time length, obtain the total blast furnace load distribution output, sum up the new energy output load values ​​at each moment within the time length, obtain the total new energy input, divide the total blast furnace load distribution output by the new energy input to obtain the new energy utilization rate as the objective function.

[0019] The decision variable for the load distribution of the submerged arc furnace is the distributed load value of each submerged arc furnace at the current moment.

[0020] The constraints of the load distribution of the submerged arc furnace include: the difference between the sum of the assigned load values ​​of the designated submerged arc furnace and the new energy input is less than a preset threshold; the assigned load value of each submerged arc furnace is limited to the preset upper and lower limits of the predicted load value; the assigned load value of the submerged arc furnace that is shut down for maintenance is 0 at the corresponding time; the assigned load value of the submerged arc furnace at a certain time is less than the rated power of the submerged arc furnace.

[0021] For medium- and long-term load distribution, the medium- and long-term power supply capacity forecast curve is obtained from the renewable energy power generation side, the medium- and long-term maintenance plan of the load equipment is obtained from the facility management system, and the medium- and long-term intelligent production scheduling plan is obtained from the production management system. With the goal of maximizing the utilization rate of renewable energy and the load equipment maintenance plan and production scheduling plan as constraints, the optimal solution for the load distribution plan at the weekly / monthly granularity is automatically sought.

[0022] For the day-ahead load distribution plan, the 15-minute granular power supply capacity forecast curve is obtained from the renewable energy power generation side, the recent historical operating parameters of the blast furnace are obtained from the facility management system, and the day-ahead production plan is obtained from the production management system. With the goal of maximizing the utilization rate of renewable energy, the optimal solution for the day-ahead load distribution plan of each blast furnace is automatically obtained.

[0023] The SCIP solver is used to solve the objective function of the load distribution scenario.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] (1) The present invention uses an optimization algorithm to automatically find the optimal solution for the future allocation plan within the boundary conditions, with a high degree of automation. The optimal solution can be used as a target reference for operator adjustment, and the operator's work performance can be refined by comparing the gap between the manual allocation result and the optimal solution, and the operator's operating ability can be continuously trained and improved.

[0026] (2) The present invention combines the prediction of the power supply capacity of new energy sources to provide a plan for the load distribution of the ore-fired furnace. The system automatically calculates the plan and can be manually revised. It combines the capabilities of the automated algorithm with human experience and knowledge, making it more scientific and reliable.

[0027] (3) The automation algorithms and strategies of the present invention are reusable and can be quickly reused and promoted. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 is a flow chart of the method of the present invention;

[0029] Figure 2 It is a schematic diagram of the load distribution method of the present invention;

[0030] Figure 3 A schematic diagram of data acquisition in one embodiment;

[0031] Figure 4 This is a load distribution result diagram at different granularities in an embodiment. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0033] Unless otherwise defined, the technical terms or scientific terms involved in this application should be understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a kind of", "the" and the like involved in this application do not indicate a quantitative limitation, and may represent the singular or plural. The terms "include", "comprise", "have" and any of their variations involved in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units inherent to these processes, methods, products or devices. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that there may be three relationships, for example, "A and / or B" can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. The terms "first", "second", "third" and the like involved in the present application are merely used to distinguish similar objects and do not represent a specific ordering of the objects.

[0034] This embodiment first provides a submerged arc furnace production and energy system based on new energy power supply, including a power transmission and distribution system, a renewable energy power generation system, an energy storage system and a submerged arc furnace production system, wherein the power transmission and distribution system is respectively connected to the renewable energy power generation system, the energy storage system and the submerged arc furnace production system.

[0035] In one embodiment, the submerged arc furnace production and energy system further includes an energy control system, which includes:

[0036] A renewable energy power generation control system, used to control the operation of the renewable energy power generation system;

[0037] An energy storage control system, used to control the operation of the energy storage system;

[0038] A submerged arc furnace production control system, used to control the operation of the submerged arc furnace production system;

[0039] The integrated control system is used to perform integrated control of the ore-fired furnace production and energy system through the power transmission and distribution system, send control instructions to the renewable energy power generation control system and the ore-fired furnace production control system, and receive control feedback; receive dispatch instructions from the energy storage control system and provide feedback to the energy storage control system.

[0040] Based on the above system, this embodiment provides a method for distributing load of a submerged arc furnace with the goal of optimizing the utilization rate of new energy. Figure 1 As shown, the following steps are included:

[0041] S1, obtain production plan, maintenance plan and new energy output data;

[0042] S2, forecast the load of the submerged arc furnace according to the production plan;

[0043] S3, determine the shutdown data of the submerged arc furnace according to the maintenance plan;

[0044] S4, unifies the data granularity of new energy output data, load forecast data and shutdown data, and cuts the data length according to task requirements to build a load distribution data set;

[0045] S5, taking the maximization of new energy utilization as the objective function, performs load distribution of the submerged arc furnace based on the load distribution data set.

[0046] In this embodiment, the new energy utilization rate is defined as the load distribution output of the ore-fired furnace divided by the new energy input, that is, new energy utilization rate = load distribution output / new energy input × 100%.

[0047] like Figure 2 As shown in the figure, the load distribution of the submerged arc furnace takes the maximization of the utilization rate of new energy as the objective function, takes the output of new energy and the load forecast results of each submerged arc furnace as the data input, and solves the load distribution of the submerged arc furnace under the conditions of satisfying the rated power constraint and maintenance plan constraint of the submerged arc furnace. The objective function and constraint conditions are further explained in detail below.

[0048] The calculation method of the objective function of the load distribution of the submerged arc furnace is as follows: determine the load forecast time length according to the forecast period and granularity, sum up the load values ​​of all submerged arc furnaces at each moment within the time length, obtain the total submerged arc furnace load distribution output, sum up the new energy output load values ​​at each moment within the time length, obtain the total new energy input, and divide the total submerged arc furnace load distribution output by the new energy input to obtain the new energy utilization rate as the objective function. That is:

[0049]

[0050] Where i represents the number of the submerged arc furnace, and t represents the load forecast length. For example, if the medium- to long-term forecast is 3 days and the load with a particle size of 15 minutes, then t = 96*3 = 288, x t,i represents the load value assigned to the i-th furnace at the t-th point, e t Represents the output load value of renewable energy at the tth point.

[0051] The decision variable for the load distribution of the submerged arc furnace is the load value x of each submerged arc furnace at the current moment. t,1 、x t,2 、x t,3 , …, x t,i , where x t,i Represents the distributed load value of the i-th ore-arc furnace at time t.

[0052] The constraints of the load distribution of the submerged arc furnace include:

[0053] 1. The difference between the sum of the assigned load values ​​of the specified ore-fired furnace and the new energy input is less than the preset threshold, that is:

[0054] x t,1 +x t,2 +x t,3 +x t,4 -e t ≤c1, c1 is the specified distributed load less than the new energy output interval constant. In this embodiment, the submerged arc furnaces numbered 1-4 specified meet this constraint.

[0055] 2. The assigned load value of each submerged arc furnace is limited to the preset upper and lower limits of the predicted load value, namely:

[0056] LF t,i +c2 <x t,i <LF t,i +c3, c2, c3 are the upper and lower bounds of the load distribution range of the i-th ore-fired furnace based on the predicted load value, LF t,i is the predicted load value.

[0057] 3. The distributed load value of the submerged arc furnace that is shut down for maintenance at the corresponding time is 0, that is:

[0058] x t,i =0,t=P t , P t It means that the i-th furnace will be shut down for maintenance at point t.

[0059] 4. The distributed load value of the submerged arc furnace at a certain moment is less than the rated power of the submerged arc furnace, that is:

[0060] 0≤x t,i ≤Cap, Cap is the rated power of the electric arc furnace.

[0061] like Figure 3 As shown in the figure, for medium- and long-term load distribution, the medium- and long-term power supply capacity prediction curve is obtained from the renewable energy power generation side, the medium- and long-term maintenance plan of the load equipment is obtained from the facility management system (for example, during what time period, certain submerged arc furnaces are shut down for maintenance), and the medium- and long-term intelligent production scheduling plan is obtained from the production management system (the intelligent production scheduling of the production management system will give scheduling suggestions based on market information and order conditions, such as the recommended daily output of tons). With the goal of maximizing the utilization rate of renewable energy, and with the maintenance plan of the load equipment and the production scheduling plan as constraints, the optimal solution for the load distribution plan at the weekly / monthly granularity is automatically sought. For the day-ahead load distribution plan, the power supply capacity prediction curve at the 15-minute granularity of the day-ahead is obtained from the renewable energy power generation side, the recent historical operating parameters of the submerged arc furnace are obtained from the facility management system (these parameters can be used to find the most suitable load arrangement for each submerged arc furnace when distributing the load to the furnace), and the day-ahead production plan is obtained from the production management system. With the goal of maximizing the utilization rate of renewable energy, the optimal solution for the load distribution plan of each submerged arc furnace on the day-ahead is automatically sought.

[0062] In a preferred embodiment, the time granularity of the day-ahead load distribution plan can also be refined: in combination with the operating load forecast curve of each ore-fired furnace, the time granularity of the day-ahead load distribution plan automatically generated can be further refined, such as Figure 4 As shown, the gap between the actual operating load and the planned load can be reduced, further reducing the waste of new energy.

[0063] This embodiment uses the SCIP (Solving Constraint Integer Programs) solver to solve the objective function of the load distribution scenario. The solution process using the SCIP solver is mainly divided into the following steps:

[0064] The first step is to timestamp and align the granularity of the data source according to the requirements;

[0065] The second step is to create a model object;

[0066] The third step is to create decision variables;

[0067] The fourth step is to create the objective function;

[0068] The fifth step is to create constraints;

[0069] Step 6: Solve the model;

[0070] The seventh step is to obtain the solution allocation result and output it.

[0071] The load distribution scheme obtained by the present invention can improve the control ability of the electric arc furnace operators and machines on the electric arc furnace, and achieve the maximum approximation of the utilization rate of new energy; it can also provide specific quantifiable indicators for the evaluation of the operating ability of the electric arc furnace operators. The advantage is that the same set of planning core algorithms is used for intraday, day-ahead, or medium- and long-term. The multi-granularity demand algorithm for the task can also automatically resample the data to meet the needs, input the configuration information such as the length and granularity of the load to be allocated, the new energy output data, the production scheduling information, and the maintenance plan information into the planning algorithm. The algorithm automatically pre-processes the data from multiple sources, and then inputs the processed algorithm into the planning algorithm. The planning algorithm performs load allocation optimization solution through the optimization solver.

[0072] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A submerged arc furnace production and energy system based on new energy power supply, characterized in that: It includes a power transmission and distribution system, a renewable energy power generation system, an energy storage system and an ore-fired furnace production system, wherein the power transmission and distribution system is connected to the renewable energy power generation system, the energy storage system and the ore-fired furnace production system respectively.

2. The submerged arc furnace production and energy system based on renewable energy power supply according to claim 1 is characterized in that: The submerged arc furnace production and energy system also includes an energy control system, which includes: A renewable energy power generation control system, used to control the operation of the renewable energy power generation system; An energy storage control system, used to control the operation of the energy storage system; A submerged arc furnace production control system, used to control the operation of the submerged arc furnace production system; The integrated control system is used to perform integrated control of the ore-fired furnace production and energy system through the power transmission and distribution system, send control instructions to the renewable energy power generation control system and the ore-fired furnace production control system, and receive control feedback; receive dispatch instructions from the energy storage control system and provide feedback to the energy storage control system.

3. A method for distributing load of a submerged arc furnace with the goal of optimizing the utilization rate of new energy, characterized in that: The method is implemented based on the system as described in any one of claims 1-2, and comprises the following steps: Obtain production plans, maintenance plans and new energy output data; Carry out load forecast of submerged arc furnace according to production plan; Determine the shutdown data of the submerged arc furnace according to the maintenance plan; Unify the data granularity of new energy output data, load forecast data, and shutdown data, and cut the data length according to task requirements to build a load distribution data set; Taking the maximization of new energy utilization as the objective function, the load distribution of the ore-fired furnace is carried out based on the load distribution data set.

4. A method for distributing load of a submerged arc furnace with the goal of optimizing the utilization rate of new energy as claimed in claim 3, characterized in that: The new energy utilization rate is defined as the load distribution output of the ore-fired furnace divided by the new energy input.

5. A method for distributing load of a submerged arc furnace with the goal of optimizing the utilization rate of new energy as claimed in claim 4, characterized in that: The calculation method of the objective function of the load distribution of the blast furnace is as follows: determine the load prediction time length according to the prediction period and granularity, sum up the load values ​​allocated to all blast furnaces at each moment within the time length, obtain the total blast furnace load distribution output, sum up the new energy output load values ​​at each moment within the time length, obtain the total new energy input, divide the total blast furnace load distribution output by the new energy input to obtain the new energy utilization rate as the objective function.

6. A method for distributing load of a submerged arc furnace with the goal of optimizing the utilization rate of new energy as claimed in claim 3, characterized in that: The decision variable for the load distribution of the submerged arc furnace is the distributed load value of each submerged arc furnace at the current moment.

7. A method for distributing load of a submerged arc furnace with the goal of optimizing the utilization rate of new energy as claimed in claim 3, characterized in that: The constraints of the load distribution of the submerged arc furnace include: the difference between the sum of the assigned load values ​​of the designated submerged arc furnace and the new energy input is less than a preset threshold; the assigned load value of each submerged arc furnace is limited to the preset upper and lower limits of the predicted load value; the assigned load value of the submerged arc furnace that is shut down for maintenance is 0 at the corresponding time; the assigned load value of the submerged arc furnace at a certain time is less than the rated power of the submerged arc furnace.

8. The method for distributing load of a submerged arc furnace with the goal of optimizing the utilization rate of new energy as claimed in claim 3, characterized in that: For medium- and long-term load distribution, the medium- and long-term power supply capacity forecast curve is obtained from the renewable energy power generation side, the medium- and long-term maintenance plan of the load equipment is obtained from the facility management system, and the medium- and long-term intelligent production scheduling plan is obtained from the production management system. With the goal of maximizing the utilization rate of renewable energy and the load equipment maintenance plan and production scheduling plan as constraints, the optimal solution for the load distribution plan at the weekly / monthly granularity is automatically sought.

9. The method for distributing load of a submerged arc furnace with the goal of optimizing the utilization rate of new energy as claimed in claim 3, characterized in that: For the day-ahead load distribution plan, the 15-minute granular power supply capacity forecast curve is obtained from the renewable energy power generation side, the recent historical operating parameters of the blast furnace are obtained from the facility management system, and the day-ahead production plan is obtained from the production management system. With the goal of maximizing the utilization rate of renewable energy, the optimal solution for the day-ahead load distribution plan of each blast furnace is automatically obtained.

10. The method for distributing load of a submerged arc furnace with the goal of optimizing the utilization rate of new energy as claimed in claim 3, characterized in that: The SCIP solver is used to solve the objective function of the load distribution scenario.

Images