A coordinated scheduling optimization method for thickening and dehydration process

Abstract

The present invention discloses a coordinated scheduling optimization method for a thickening and dehydration process, and relates to the technical field of thickening and dehydration. The method optimizes the coordinated scheduling of the thickening and dehydration process by using an established coordinated scheduling optimization model. Under the premise of ensuring the safe and stable operation of the equipment, the underflow concentration and the step electricity price are comprehensively considered, and the ore discharge and filtration time are reasonably arranged to minimize the production energy consumption cost. The present invention can accurately predict the underflow concentration of the thickener, and effectively improve the underflow concentration under the premise of ensuring the safe and stable operation of the thickening and dehydration process; the coordinated scheduling optimization model proposed by the present invention can predict the best ore discharge and filtration scheme based on the initial underflow concentration of the day, so as to assist the operator in control, reduce the operating time of the equipment during the peak period of electricity consumption, and significantly reduce energy consumption economic indicators.

Description

Technical Field

[0001] The present invention relates to the technical field of thickening dehydration, and in particular to a coordinated scheduling optimization method for a thickening dehydration process. Background Art

[0002] Mineral processing is the process of recovering high-grade minerals from poor, fine and mixed ores. It is a typical process industry process with a complex production mechanism and numerous process links. Each process influences and couples each other. The thickening and dehydration process is one of the very important processes, which plays a role in increasing the concentration of ore pulp, separating solids from liquids, and regulating the impact of production disturbances in upstream processes on downstream processes. The thickening and dehydration process mainly includes equipment such as thickeners, filter presses, agitator tanks, underflow pumps and filter press pumps. The thickener is a device that increases the concentration of ore pulp based on gravity sedimentation and is the key equipment in the process. The filter press is a device that separates solids and liquids based on pressure to further increase the concentration of ore pulp.

[0003] Through the research on the optimization control of the thickening and dehydration process in recent years, the optimization control problem of this process has been solved to a certain extent, and the process performance of this process has been improved. However, due to the complexity of the site, the main detection variables of the thickener have not been detected online, such as the underflow concentration, and the current operating status of the thickening and dehydration process cannot be understood. The production operation is blind, and because variables such as underflow concentration cannot be detected online, the operating status of the thickener is unknown, the thickener and the filter press cannot coordinate production, the production operation is disordered, and the tiered electricity price factor is not considered, resulting in low production efficiency and high energy consumption economic indicators of the thickening and dehydration process.

[0004] The thickening and dehydration process requires that the energy consumption economic indicators be reduced under the premise of meeting safety and process requirements. The main energy-consuming equipment in the thickening and dehydration process are thickeners, underflow pumps, mixing tanks and filter press pumps. However, in order to thicken the slurry, the thickener motor is kept running continuously for 24 hours, and the energy consumption economic indicators of the thickener remain basically unchanged. Therefore, only the underflow pump, filter press pump and mixing tank affect the energy consumption economic indicators of the thickening and dehydration process, and the energy consumption economic indicators can be reduced by deciding the ore discharge and filter press time of the thickening and dehydration process. The underflow concentration is the key variable of the thickening and dehydration process. The greater the underflow concentration, the smaller the underflow pump running time and the filter press pump running time, so the power consumption of the thickening and dehydration process is also smaller. However, the electricity price in the thickening and dehydration process is a tiered electricity price, and the electricity price changes over time. Therefore, if you only pursue the discharge of ore when the underflow concentration is high, the power consumption is reduced, but the energy consumption economic indicators are not necessarily reduced.

[0005] At present, there is no research on the optimization method of energy-saving scheduling under disordered operation of the thickening dehydration process. Factory operators mainly rely on their own experience to make adjustments, which often leads to problems such as high energy consumption and low safety, which seriously restricts the industrialization process of the thickening dehydration process and thus affects the comprehensive economic benefits. Summary of the invention

[0006] In view of this, the present invention provides a coordinated scheduling optimization method for a thickening dehydration process, which optimizes the coordinated scheduling of the thickening dehydration process by using an established coordinated scheduling optimization model. Under the premise of ensuring safe and stable operation of the equipment, the underflow concentration and the tiered electricity price are comprehensively considered, and the ore discharge and filtration time is reasonably arranged to minimize the production energy consumption cost.

[0007] To this end, the present invention provides the following technical solutions:

[0008] A coordinated scheduling optimization method for a thickening and dehydration process, comprising:

[0009] Step 1: Obtain the data set required for building the model; the data set includes the initial underflow concentration, the change of the ore storage volume inside the thickener, the soft measurement value of the underflow concentration during ore discharge, and the running time of the underflow pump of each cabinet;

[0010] Step 2: Establishing an important indicator model for the thickening and dehydration process according to the data set; the important indicator model includes: an underflow concentration prediction model for predicting the underflow concentration value when the ore is discharged at the next moment, an underflow pump and filter press pump operation time prediction model for predicting the operation time of each device when the ore is discharged at the current moment, and an energy consumption economic indicator model for each device for calculating the power loss cost of each device in the production process;

[0011] Step 3: Establish a coordinated scheduling optimization model for the thickening-filter pressing process based on mixed integer programming; wherein the objective function of the coordinated scheduling optimization model is to minimize the energy consumption economic index of each device in the production process; the constraints of the coordinated scheduling optimization model include: constraints on the opening time of each device, constraints on the operating time of each device determined by the underflow concentration value obtained by the underflow concentration prediction model and the operating time of each device obtained by the underflow pump and filter press pump operating time prediction model, constraints on the closing time of each device, linearization and constraints of the tiered electricity price, constraints on the processing of bilinear problems of the objective function, and constraints on equipment safety;

[0012] Step 4: Solve the objective function of the coordinated scheduling optimization model under the constraints to obtain the best equipment operation plan, so as to reasonably arrange the start and stop of equipment and reduce equipment energy consumption.

[0013] Furthermore, the objective function of the coordinated scheduling optimization model is:

[0014]

[0015] Among them, the value of I is 3, which indicates the total number of equipment required for the process, 1 is the underflow pump, 2 is the filter press pump, and 3 is the mixing tank; N is the number of filter press cabinets planned for the day; J is the number of tiered electricity price segments, P jis the electricity price in the jth period, Tp j is the starting time of the tiered electricity price in the jth period, where Tp J+1 The end time of the day; E i Ts is the power consumption per unit of equipment i; i,n Tf is the start time of the equipment i in the nth cabinet; i,n is the end time of equipment i in the nth cabinet; vs i,n,j Used to determine whether the device i in the nth cabinet is turned on in the jth period, vf i,n,j Used to determine whether the device i in the nth cabinet is turned off in the jth period, ψ i,n,j for vs i,n,j With vf i,n,j The product of .

[0016] Furthermore, a bottom flow concentration prediction model is established, including:

[0017] Statistical initial underflow concentration C UF,0 , Change of thickener stock volume Δm T and the soft measurement value C of bottom flow concentration during ore drawing UF，T Based on the operation data of the company, a prediction model for the change of the internal ore volume within T minutes, the initial underflow concentration and the underflow concentration after T minutes was established based on the partial least squares method:

[0018] C UF,T =e·C UF,0 +f·Δm T +g;

[0019] Δm T =T·m in -(i-1)M;

[0020] Among them, e, f, g are model parameters, C UF,0 is the initial underflow concentration, M is the filter press volume per cabinet, m in is the unit feed amount, and i represents the number of filter press cabinets.

[0021] Furthermore, an underflow pump operation time model is established, including:

[0022] Statistical soft measurement value C of bottom flow concentration during ore drawing UF，T And the running time of each cabinet underflow pump D UF The operating data of the underflow pump shows that within the range of underflow concentration, the underflow pump operating time is linear, and the underflow pump operating time is:

[0023] D UF =a UF ·C UF,T +b UF ;

[0024] Among them, a UF and bUF is the model parameter.

[0025] Furthermore, a filter press pump operation time model is established, including:

[0026] During the ore discharge and filtration process of each cabinet, the volume of slurry pumped into the mixing tank by the underflow pump is the same as the volume of slurry pumped out of the mixing tank by the filter press pump. The running time of the filter press pump is:

[0027]

[0028] Among them, D PF is the filter press pump operating time, Q UF is the underflow pump flow rate, Q PF is the filter press pump flow rate.

[0029] Furthermore, an economic indicator model of energy consumption of each device is established, including:

[0030] The energy consumption economic index of the underflow pump in the nth cabinet is:

[0031]

[0032] Among them, E UF is the unit power consumption of the underflow pump, P(t) is the step electricity price at time t;

[0033] The energy consumption economic index of the filter press pump in the nth cabinet is:

[0034]

[0035] Among them, E PF The unit power consumption of the filter press pump;

[0036] The energy consumption economic index of the mixing tank in the nth cabinet is:

[0037]

[0038] Among them, E MT It is the unit power consumption of the stirring tank.

[0039] Furthermore, the constraints on the start time of each device include: the start time of the filter press pump of the nth cabinet cannot be earlier than the ore discharge time of the cabinet and cannot be later than the ore discharge time of the next cabinet, and the start time of the filter press pump of the last cabinet cannot be later than the end time of the day;

[0040] The operating time constraints of each device include: the operating time of the underflow pump and filter press pump of the nth cabinet is not allowed to exceed the maximum operating time of each device; the operating time of the agitator tank of the last cabinet is the difference between the closing time of the filter press pump and the opening time of the underflow pump; except for the operating time constraint of the agitator tank of the Nth cabinet, the agitator tank cannot stop operating during the ore discharge and filter press process, and its closing time is determined by the current production situation; if the filter press pump operates across cabinets, the operating time of the agitator tank is the difference between the ore discharge time of the next cabinet and the opening time of the agitator tank of the current cabinet; otherwise, the operating time of the agitator tank is the difference between the closing time of the filter press pump of the current cabinet and the opening time of the agitator tank of the current cabinet; the filter press pump of the last cabinet is not allowed to operate across cabinets;

[0041] The constraints on the closing time of each device include: the closing time of each device in the Nth cabinet is the sum of the opening time and the running time; the closing time of the filter press pump except the Nth cabinet, if the filter press pump operates across cabinets, the closing time of the filter press pump is not allowed to exceed the closing time of the ore discharge filter press on the same day; otherwise, it is not allowed to exceed the ore discharge time of the next cabinet; the ending time of the equipment i in the nth cabinet is not allowed to exceed the starting time of the equipment i in the next cabinet;

[0042] The tiered electricity price is to divide the day into J time periods with the electricity price change time as the critical time point Tp, and to divide the day into J time periods with the end time Tp as the critical time point Tp. end Stored in the J+1th position of Tp; introduce zero-one variables vs and vf to determine whether the start and end time of the device are in the jth time period;

[0043] The constraints of the step-by-step electricity price processing include: if the start time of the nth cabinet equipment i is in the jth time period, the current time is not allowed to exceed the time critical point between the current time period and the next time period; if the start time of the nth cabinet equipment i is in the jth time period, the start time must be greater than the time critical point between the current time period and the previous time period, otherwise, it must be greater than the time critical point between the current time period and the next time period; if the start time of the nth cabinet equipment i is in the first time period, the start time must be greater than Tp1, that is, the start time of the day, otherwise, it must be greater than the time critical point between the first time period and the second time period; the start time of the nth cabinet equipment i can only appear once;

[0044] The constraints of the objective function bilinear problem include:

[0045] Equipment safety constraints include: the time of ore discharge from the current cabinet is not allowed to exceed the time of ore discharge from the next cabinet; the time of ore discharge from any cabinet is not allowed to exceed the end of the process on the day; the underflow concentration of the thickener must be within the safe range at any time.

[0046] Advantages and positive effects of the present invention:

[0047] The present invention studies the coordinated scheduling optimization method for the problems of disordered production operation and high energy consumption in the ore dressing workshop of a gold mine plant. The method can realize the accurate prediction of the underflow concentration of the thickener and effectively improve the underflow concentration under the premise of ensuring the safe and stable operation of the thickening and dehydration process. The coordinated scheduling optimization model proposed in the present invention can predict the best ore discharge and filtration scheme according to the initial underflow concentration of the day, so as to assist the operator in control, reduce the operating time of the equipment during the peak period of electricity consumption, and significantly reduce the energy consumption economic indicators. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0049] Figure 1 This is the process flow chart of the thickening dehydration process;

[0050] Figure 2 This is a comparison chart between the soft measurement value and the predicted value of the bottom flow concentration;

[0051] Figure 3 This is a comparison chart between the actual running time of the underflow pump and the predicted value;

[0052] Figure 4 This is a schematic diagram comparing the optimal solution with the tiered electricity price;

[0053] Figure 5 This is a comparison chart of the bottom flow concentration when discharging ore in each cabinet before and after optimization. DETAILED DESCRIPTION

[0054] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only 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.

[0055] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0056] In the embodiment of the present invention, a 30m diameter peripheral transmission thickener and a plate and frame filter press are used, such as Figure 1 As shown, the process flow of the dense dehydration process is as follows:

[0057] The feed of the thickener is the concentrate selected during the flotation process. The concentrate scraped from the flotation column flows into the concentrate pump pool, and then is sent to the thickener through the slurry pump. The center of the thickener is the feed well. The concentrate selected from the flotation is sent to the central feed well for buffering and mixing, and then flows into the thickener to settle under the action of gravity. The travel motor is driven by the hydraulic system, driving the rake frame to rotate around the center along the track on the outer wall of the thickener. The scraper under the rake frame stirs the mud layer to promote the concentration of the slurry and the movement of the bottom outflow to the center position. There is an overflow trough on the upper layer of the thickener, and the upper layer of clean water flows out through the overflow trough and returns to the upstream process, and the clean water is reused. When the bottom concentration reaches a certain value, the thickener bottom flow pump is turned on, and the thickened slurry is pumped into the mixing tank through the pipeline. When the amount of ore in the mixing tank reaches a certain amount, the filter press pump of the filter press pumps the slurry into the filter press for filtration, and the filter cake after filtration is sent to the next process. Although the thickener is fed continuously, the bottom flow of the thickener and the filtration of the filter press are batch production. The weight of the filter cake in each cabinet of the filter press is about 20 tons (the concentration is 90% to 94%).

[0058] In view of the above-mentioned thickening and dehydration process, an embodiment of the present invention provides a coordinated scheduling optimization method for the thickening and dehydration process, the method comprising:

[0059] Step 1: Obtain the data set required for model building; the data set includes the initial underflow concentration C UF,0 , Change of ore storage volume inside thickener Δm T , soft measurement value C of bottom flow concentration during ore drawing UF，T And the running time of each cabinet underflow pump T UF ;

[0060] Step 2: Establish an important indicator prediction model for the thickening and dehydration process according to the data set; the important indicator prediction model includes: an underflow concentration prediction model, an underflow pump operation time model, a filter press pump operation time model and an energy consumption economic indicator model for each device; wherein, the underflow concentration prediction model is used to predict the underflow concentration value when the ore is discharged at the next moment; the underflow pump and filter press pump operation time prediction model is used to predict the operation time of each device when the ore is discharged at the current moment; the above prediction models provide accurate future information for the coordinated scheduling optimization model proposed in the present invention; the energy consumption economic indicator model is used to calculate the power loss cost of each device in the production process, and is the main body of the objective function of the coordinated scheduling optimization model; wherein:

[0061] Establishing the bottom flow concentration prediction model: Statistical initial bottom flow concentration C UF,0 , Change of thickener stock volume Δm T and the soft measurement value C of bottom flow concentration during ore drawing UF，T Based on the operation data of the company, a prediction model for the change of the internal ore volume within T minutes, the initial underflow concentration and the underflow concentration after T minutes was established based on the partial least squares method:

[0062] C UF,T =e·C UF,0 +f·Δm T +g (1)

[0063] Δm T =T·m in -(i-1)M (2)

[0064] Among them, e, f, g are model parameters, C UF,0 is the initial underflow concentration, M is the filter press volume per cabinet, m in is the unit feed amount, and i represents the number of filter press cabinets.

[0065] Establish the bottom flow pump operation time model: Statistical soft measurement value C of bottom flow concentration during ore discharge UF，T And the running time of each cabinet underflow pump D UF According to the operating data, within the range of underflow concentration, the underflow pump operation time can be considered linear, that is:

[0066] D UF =a UF ·C UF,T +b UF (3)

[0067] Among them, a UF and b UF is the model parameter.

[0068] Establish a filter press pump operation time model: During the ore pressing process of each cabinet, the volume of slurry pumped into the mixing tank by the underflow pump is the same as the volume of slurry pumped out of the mixing tank by the filter press pump, so the filter press pump operation time is:

[0069]

[0070] Among them, D PF is the filter press pump operating time, Q UF is the underflow pump flow rate, Q PF is the filter press pump flow rate.

[0071] Establish the energy consumption economic indicator model for each equipment:

[0072] The energy consumption economic index of the underflow pump in the nth cabinet is:

[0073]

[0074] Among them, E UF is the unit power consumption of the underflow pump, and P(t) is the step electricity price at time t.

[0075] The energy consumption economic index of the filter press pump in the nth cabinet is:

[0076]

[0077] Among them, E PF It is the unit power consumption of filter press pump.

[0078] The energy consumption economic index of the mixing tank in the nth cabinet is:

[0079]

[0080] Among them, E MT It is the unit power consumption of the stirring tank.

[0081] Step 3: Based on mixed integer programming, a coordinated scheduling optimization model for the thickening-filter pressing process is established; wherein the objective function of the coordinated scheduling optimization model is to minimize the energy consumption economic index of each equipment in the production process:

[0082]

[0083] Among them, the value of I is 3, which indicates the total number of equipment required for the process, 1 is the underflow pump, 2 is the filter press pump, and 3 is the mixing tank; N is the number of filter press cabinets planned for the day; J is the number of tiered electricity price segments, P j is the electricity price in the jth period, Tp j is the starting time of the tiered electricity price in the jth period, where Tp J+1 The end time of the day; E i Ts is the power consumption per unit of equipment i; i,n Tf is the start time of the equipment i in the nth cabinet; i,n is the end time of equipment i in the nth cabinet; vs i,n,jUsed to determine whether the device i in the nth cabinet is turned on in the jth period, vf i,n,j Used to determine whether the device i in the nth cabinet is turned off in the jth period, ψ i,n,j for vs i,n,j With vf i,n,j The product of

[0084] Mixed integer programming refers to an integer programming problem in which some decision variables are restricted to integers. The equipment operation and energy consumption problems in the thickening-filter pressing process can be attributed to mixed integer programming problems. Therefore, in the embodiment of the present invention, a coordinated scheduling optimization model for the thickening-filter pressing process is established based on mixed integer programming. In this objective function, E is the unit power consumption of the equipment, that is, power, P is the electricity price at that moment, and the rest is used to calculate the length of time a certain equipment runs at a certain electricity price, power (kw) × time (h) = kilowatt-hour (kw / h), which is generally used to calculate the power consumption of the machine.

[0085] The constraints of the coordinated scheduling optimization model include: constraints on the start time of each device, constraints on the operation time of each device, constraints on the shutdown time of each device, constraints on the processing of tiered electricity prices, constraints on the processing of bilinear problems of the objective function, and constraints on equipment safety;

[0086] Step 4: Coordinate and schedule the thickening filter pressing process according to the coordinated scheduling optimization model. Under the premise of ensuring the safe and stable operation of the equipment, comprehensively consider the underflow concentration and the tiered electricity price, and reasonably arrange the ore discharge and filter pressing time to minimize the production energy consumption cost.

[0087] The coordination and dispatching here mainly constrains the switch time and operation time of each device through the equipment operation law, and after establishing the coordination and dispatching optimization model, the computer will automatically solve the best equipment operation plan, so as to reasonably arrange the start and stop of the equipment and reduce the energy consumption of the equipment. In order to achieve the technical effect of minimizing the operation time of the equipment during the peak period of electricity price when the underflow concentration meets the standard, especially the operation time of the filter press pump during the peak period of electricity price, because the filter press pump has high power and high power consumption.

[0088] The following describes the constraints of the coordinated scheduling optimization model:

[0089] (1) Constrain the startup time of each device:

[0090]

[0091]

[0092] Ts i,n ≤T end ,n=N,i=2 (10)

[0093]

[0094] Among them, T n is the time of placing ore in the nth cabinet, T end The end of the day.

[0095] Formula (10) indicates the start time of the underflow pump and the agitation tank of the nth cabinet, i.e., the ore discharge time of the nth cabinet.

[0096] Formulas (11)-(13) indicate that the start time of the filter press pump of the nth cabinet cannot be earlier than the time when the ore is released from the cabinet and cannot be later than the time when the ore is released from the next cabinet. The start time of the filter press pump of the last cabinet cannot be later than the end time of the day.

[0097] (2) Constrain the operating time of each device:

[0098]

[0099]

[0100]

[0101]

[0102]

[0103] D i,n =Tf i-1,n -Ts i-2,n ,i=3,n=N (17)

[0104]

[0105]

[0106]

[0107]

[0108]

[0109]

[0110]

[0111]

[0112]

[0113] Wp n =0,n=N (27)

[0114] Among them, formulas (14)-(17) are given by formulas (1)-(4) and are used to constrain the operating time of the underflow pump and filter press pump in each cabinet.

[0115] Formula (18) indicates that the operating time of the underflow pump and filter press pump in the nth cabinet is not allowed to exceed the maximum operating time D of each device. max , prevent the mixing tank from overflowing or idling, thus ensuring the safe operation of the equipment, D max Determined by formula (30):

[0116]

[0117] Where V is the maximum storage volume of the stirring tank, Q i is the traffic of device i.

[0118] Formula (19) constrains the running time of the last tank agitator to be the difference between the filter press pump closing time and the underflow pump opening time, Ts i,n , Tf i,n They represent the opening and closing time of the device i in the nth cabinet respectively.

[0119] Formula (20) is the operating time constraint of the agitator tank except the Nth cabinet. The agitator tank cannot stop operating during the ore discharge and filter pressing process. Its closing time is determined by the current production situation and needs to be constrained. The rules for determining the operating time of the agitator tank are described as follows: If the filter press pump operates across cabinets (that is, the filter press pump is turned on in the current cabinet and turned off after the ore discharge time of the next cabinet), the operating time of the agitator tank is the difference between the ore discharge time of the next cabinet and the opening time of the agitator tank of the current cabinet; otherwise, the operating time of the agitator tank is the difference between the closing time of the filter press pump of the current cabinet and the opening time of the agitator tank of the current cabinet, as shown in formula (31):

[0120]

[0121] Among them, Wp n is a binary variable. If the filter pump operates across cabinets, Wp n =1; otherwise, Wp n = 0. Let Z n =Wp n ·Tf 2,n , Y n =Wp n ·T n+1 That is, we get formula (20).

[0122] Formulas (21)-(28) are used to process Z n , Y n The bilinear problem.

[0123] Formula (29) constrains the Nth cabinet Wp n =0, that is, the filter press pump in the last cabinet is not allowed to operate across cabinets.

[0124] (3) Constrain the shutdown time of each device:

[0125]

[0126]

[0127]

[0128]

[0129]

[0130] Formula (32) constrains the shutdown time of each device in the Nth cabinet to be the sum of the startup time and the operating time.

[0131] Formula (33) is used to constrain the closing time of the filter press pump except for the Nth cabinet. The rule is: if the filter press pump operates across cabinets, the end time of the filter press pump is not allowed to exceed the end time of the ore discharge filter press on the same day; otherwise, it is not allowed to exceed the ore discharge time of the next cabinet. As shown in formula (37):

[0132]

[0133] Introducing Y n That is, we get formula (33).

[0134] Formula (34) indicates that the end time of the device i in the nth cabinet is not allowed to exceed the start time of the device i in the next cabinet.

[0135] Formulas (35)-(36) are also used to constrain the shutdown time of each device. Although it is not necessary, it can tighten the constraints and speed up the solution of the model.

[0136] (4) Linearization processing method and constraints of tiered electricity prices:

[0137] The tiered electricity price adopted by the present invention is as follows:

[0138]

[0139] Taking the moment when the electricity price changes as the critical time point Tp, the day is divided into J time periods, and the end time of the day is T end Stored in the J+1th position of Tp; introduce zero-one variables vs and vf to determine whether the start and end times of the device are in the jth time period.

[0140] The constraints on the tiered electricity price are as follows:

[0141]

[0142]

[0143]

[0144]

[0145]

[0146]

[0147]

[0148]

[0149]

[0150]

[0151]

[0152]

[0153]

[0154]

[0155]

[0156]

[0157]

[0158]

[0159] Formulas (39)-(47) are used to constrain the starting time of the device i in the nth cabinet.

[0160] Constraint rule of formula (39): If the start time of the device i in the nth cabinet is in the jth time period, the current time is not allowed to exceed the time critical point between the current time period and the next time period.

[0161] Formula (40) is derived from the following formula:

[0162]

[0163] in:

[0164]

[0165]

[0166] Constraint rule: If the opening time of the equipment i in the nth cabinet does not occur before the jth time period, that is The constraint takes effect when When the opening time of the equipment i in the nth cabinet is in the jth time period, the opening time must be greater than the critical point between the current time period and the previous time period; otherwise, it must be greater than the critical point between the current time period and the next time period.

[0167] Formula (41) indicates that if the start time of the device i in the nth cabinet is in the first time period, the start time must be greater than Tp1, that is, the start time of the day; otherwise, it must be greater than the critical point between the first time period and the second time period.

[0168] Formulas (42)-(45) are used to process Ωs i,n,j The bilinear problem.

[0169] Formula (46) indicates that the start time of device i in the nth cabinet can only occur once.

[0170] Formula (47) is used to constrain vs i,n,j ,φs i,n,j The value range of .

[0171] Formulas (48)-(56) are used to constrain the end time of the device i in the nth cabinet, and the specific description is the same as the start time.

[0172] (5) Bilinear problem processing constraints of objective function:

[0173]

[0174]

[0175]

[0176]

[0177] Formulas (60)-(63) are used to deal with the bilinear problem of the objective function, where:

[0178]

[0179] (6) Equipment safety constraints:

[0180]

[0181]

[0182] C UF ≤C UFmax (65)

[0183] C UF ≥C UFmin (66)

[0184] Formula (65) imposes a mandatory constraint that the current cabinet ore-releasing time is not allowed to exceed the next cabinet ore-releasing time.

[0185] Formula (66) indicates that the time for releasing ore from any cabinet is not allowed to exceed the end time of the process on that day.

[0186] Formulas (67)-(68) indicate that the thickener underflow concentration must be within a safe range at any time.

[0187] The power of each device in the embodiment of the present invention is shown in Table 1:

[0188] Table 1

[0189]

[0190]

[0191] The best ore discharge and filter pressing schemes predicted by the present invention are shown in Tables 2, 3 and 4, which are the operation schemes of the underflow pump, the filter press pump and the stirring tank within 24 hours, respectively, including the opening time and closing time of each device, that is, the operating time, and the time unit is minutes. For example, the second row of Table 2 shows that during the production process of the first cabinet on the same day, the underflow pump was opened at 74.3 minutes on the same day and closed at 98.3 minutes, and the operating time was 24 minutes.

[0192] Table 2

[0193]

[0194]

[0195] Table 3

[0196]

[0197]

[0198] Table 4

[0199]

[0200]

[0201] For the convenience of analysis, the comparison chart of the optimal equipment operation plan and the tiered electricity price is as follows: Figure 4 As shown, at position 1, the electricity price is low. This method will continuously release ore for filtration while ensuring that the underflow concentration meets the standard, and store ore after the electricity price rises. Since the filter press pump has high power and high energy consumption, the filtration process of the current cabinet at positions 2 and 3 will be arranged after the electricity price is reduced, reducing the operating time of high-energy-consuming equipment during peak electricity consumption periods, thereby effectively reducing energy consumption economic indicators.

[0202] Figure 4 The underflow concentration and energy consumption economic indicators before and after the scheduling optimization are compared with Table 5. The feed volume of the thickener is 420 tons before and after the optimization, the number of filter press cabinets required is 21, and the underflow concentration is 65% when taking over. Figure 5 This is a comparison of the bottom flow concentration operation curves before and after the application of ore discharge. Due to the unreasonable arrangement of the ore discharge and filtration time before optimization, the bottom flow concentration of the thickener is low, which in turn increases the ore discharge and filtration time and increases the energy consumption economic index. Table 2 compares the 24-hour average ore discharge bottom flow concentration and energy consumption economic index data before and after optimization. After optimization, the average ore discharge bottom flow concentration increased by 13.5% compared with before optimization, and the energy consumption economic index decreased by 40%.

[0203] Table 5

[0204]

[0205] From the perspective of specific operating conditions, the optimization method of the present invention comprehensively considers the impact of underflow concentration and tiered electricity prices on energy consumption economic indicators, and greatly improves the underflow concentration of the thickener and effectively reduces energy consumption economic indicators while ensuring the safe and stable operation of the thickening and dehydration process. According to the experimental data of specific examples, it can be seen that the underflow concentration prediction model and the operation time model of each equipment are accurate in prediction and can meet the requirements of actual industrial production; the optimization effect finally implemented shows that the ore release time solved by the mixed integer linear programming model of the present invention is reasonable and feasible, which not only takes into account the safety and energy consumption of the process, but also fully considers the adaptability of the on-site operators to the method of the present invention.

[0206] In the several embodiments provided by the present invention, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0207] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0208] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0209] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0210] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A coordinated scheduling optimization method for a thickening and dehydration process, characterized in that: include: Step 1: Obtain the data set required for building the model; the data set includes the initial underflow concentration, the change of the ore storage volume inside the thickener, the soft measurement value of the underflow concentration during ore discharge, and the running time of the underflow pump of each cabinet; Step 2: Establishing an important indicator model for the thickening and dehydration process according to the data set; the important indicator model includes: an underflow concentration prediction model for predicting the underflow concentration value when the ore is discharged at the next moment, an underflow pump and filter press pump operation time prediction model for predicting the operation time of each device when the ore is discharged at the current moment, and an energy consumption economic indicator model for each device for calculating the power loss cost of each device in the production process; Step 3: Establish a coordinated scheduling optimization model for the thickening-filter pressing process based on mixed integer programming; wherein the objective function of the coordinated scheduling optimization model is to minimize the energy consumption economic index of each device in the production process; the constraints of the coordinated scheduling optimization model include: constraints on the opening time of each device, constraints on the operating time of each device determined by the underflow concentration value obtained by the underflow concentration prediction model and the operating time of each device obtained by the underflow pump and filter press pump operating time prediction model, constraints on the closing time of each device, linearization and constraints of the tiered electricity price, constraints on the processing of bilinear problems of the objective function, and constraints on equipment safety; Step 4: Solve the objective function of the coordinated scheduling optimization model under the constraints to obtain the optimal equipment operation plan, so as to reasonably arrange the start and stop of equipment and reduce equipment energy consumption; The objective function of the coordinated scheduling optimization model is: Among them, the value of I is 3, which indicates the total number of equipment required for the process, 1 is the underflow pump, 2 is the filter press pump, and 3 is the mixing tank; N is the number of filter press cabinets planned for the day; J is the number of tiered electricity price segments, P j is the electricity price in the jth period, Tp j is the starting time of the tiered electricity price in the jth period, where Tp J+1 The end time of the day; E i Ts is the power consumption per unit of equipment i; i,n Tf is the start time of the equipment i in the nth cabinet; i,n is the end time of equipment i in the nth cabinet; vs i,n,j Used to determine whether the device i in the nth cabinet is turned on in the jth period, vf i,n,j Used to determine whether the device i in the nth cabinet is turned off in the jth period, ψ i,n,j for vs i,n,j With vf i,n,j The product of Establish a bottom flow concentration prediction model, including: Statistical initial underflow concentration C UF,0 , Change of thickener stock volume Δm T and the soft measurement value C of bottom flow concentration during ore drawing UF，T Based on the operation data of the company, a prediction model for the change of the internal ore volume within T minutes, the initial underflow concentration and the underflow concentration after T minutes was established based on the partial least squares method: C UF,T =e·C UF,0 +f·Δm T +g; Δm T =T·m in -(i-1)M; Among them, e, f, g are model parameters, C UF,0 is the initial underflow concentration, M is the filter press volume per cabinet, m in is the unit feed amount, i represents the number of filter press cabinets; Model the underflow pump run time, including: Statistical soft measurement value C of bottom flow concentration during ore drawing UF，T And the running time of each cabinet underflow pump D UF The operating data of the underflow pump shows that within the range of underflow concentration, the underflow pump operating time is linear, and the underflow pump operating time is: D UF =a UF ·C UF,T +b UF ; Among them, a UF and b UF are model parameters; Build a filter press pump run time model including: During the ore discharge and filtration process of each cabinet, the volume of slurry pumped into the mixing tank by the underflow pump is the same as the volume of slurry pumped out of the mixing tank by the filter press pump. The running time of the filter press pump is: Among them, D PF is the filter press pump operating time, Q UF is the underflow pump flow rate, Q PF is the filter press pump flow rate; Establish energy consumption economic indicator models for each device, including: The energy consumption economic index of the underflow pump in the nth cabinet is: Among them, E UF is the unit power consumption of the underflow pump, P(t) is the step electricity price at time t; The energy consumption economic index of the filter press pump in the nth cabinet is: Among them, E PF The unit power consumption of the filter press pump; The energy consumption economic index of the mixing tank in the nth cabinet is: Among them, E MT It is the unit power consumption of the stirring tank.

2. The coordinated scheduling optimization method for a thickening and dehydration process according to claim 1 is characterized in that: The constraints on the start time of each device include: the start time of the filter press pump of the nth cabinet cannot be earlier than the ore discharge time of the cabinet and cannot be later than the ore discharge time of the next cabinet, and the start time of the filter press pump of the last cabinet cannot be later than the end time of the day; The operating time constraints of each device include: the operating time of the underflow pump and filter press pump of the nth cabinet is not allowed to exceed the maximum operating time of each device; the operating time of the agitator tank of the last cabinet is the difference between the closing time of the filter press pump and the opening time of the underflow pump; except for the operating time constraint of the agitator tank of the Nth cabinet, the agitator tank cannot stop operating during the ore discharge and filter press process, and its closing time is determined by the current production situation; if the filter press pump operates across cabinets, the operating time of the agitator tank is the difference between the ore discharge time of the next cabinet and the opening time of the agitator tank of the current cabinet; otherwise, the operating time of the agitator tank is the difference between the closing time of the filter press pump of the current cabinet and the opening time of the agitator tank of the current cabinet; the filter press pump of the last cabinet is not allowed to operate across cabinets; The constraints on the closing time of each device include: the closing time of each device in the Nth cabinet is the sum of the opening time and the running time; the closing time of the filter press pump except the Nth cabinet, if the filter press pump operates across cabinets, the closing time of the filter press pump is not allowed to exceed the closing time of the ore discharge filter press on the same day; otherwise, it is not allowed to exceed the ore discharge time of the next cabinet; the ending time of the equipment i in the nth cabinet is not allowed to exceed the starting time of the equipment i in the next cabinet; The tiered electricity price is to divide the day into J time periods with the electricity price change time as the critical time point Tp, and to divide the day into J time periods with the end time Tp as the critical time point Tp. end Stored in the J+1th position of Tp; introduce zero-one variables vs and vf to determine whether the start and end time of the device are in the jth time period; The constraints of the step-by-step electricity price processing include: if the start time of the nth cabinet equipment i is in the jth time period, the current time is not allowed to exceed the time critical point between the current time period and the next time period; if the start time of the nth cabinet equipment i is in the jth time period, the start time must be greater than the time critical point between the current time period and the previous time period, otherwise, it must be greater than the time critical point between the current time period and the next time period; if the start time of the nth cabinet equipment i is in the first time period, the start time must be greater than Tp1, that is, the start time of the day, otherwise, it must be greater than the time critical point between the first time period and the second time period; the start time of the nth cabinet equipment i can only appear once; The constraints of the objective function bilinear problem include: Equipment safety constraints include: the time of ore discharge from the current cabinet is not allowed to exceed the time of ore discharge from the next cabinet; the time of ore discharge from any cabinet is not allowed to exceed the end of the process on the day; the underflow concentration of the thickener must be within the safe range at any time.

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