A method of determining a coal preparation plant loading plan

Abstract

This invention relates to the field of coal blending technology in coal preparation plants, specifically to a method for determining the loading plan of a coal preparation plant, comprising the following steps: First, obtaining basic information on the coal to be loaded and basic information on each coal bunker; Second, determining the value of the marketable coal to be loaded; Third, consolidating the coal bunkers according to the different coal qualities of the coal samples loaded, with the number of consolidated bunkers being j, where j≤9; Fourth, calculating the corresponding number of loading trips according to the standard coal price of the marketable coal from high to low. This invention, based on the coal quality requirements of the marketable coal to be loaded, combined with the coal quality indicators and coal inventory of each coal bunker, and guided by the value of the marketable coal, obtains the optimal recommended number of loading trips for different marketable coals through a multi-indicator coal blending algorithm. This invention is simple, can greatly reduce labor, can increase the output of various types of coal, maximize the marketable coal benefits of the coal preparation plant, and improve the economic efficiency of the coal preparation plant.

Description

Technical Field

[0001] This invention relates to the field of coal blending technology in coal preparation plants, specifically to a method for determining the loading plan of a coal preparation plant, applicable to the formulation of loading plans for large and medium-sized coal preparation plants. Background Technology

[0002] In the process of creating coal blending and loading plans, most coal preparation plants still rely on manual calculations or experience-based blending, resulting in low work efficiency and low blending accuracy. With numerous coal bunkers and diverse coal qualities, manual labor alone is insufficient. All of these factors hinder the improvement of the economic efficiency of coal preparation plants. Summary of the Invention

[0003] In order to overcome the shortcomings of the existing technology, the present invention provides a method for determining the loading plan of a coal preparation plant, which is applicable to the formulation of daily, monthly, quarterly or annual loading plans for large and medium-sized coal preparation plants.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] A method for determining a coal preparation plant loading schedule includes the following steps:

[0006] Step 1: Obtain basic information about the coal to be loaded onto the trucks and about each coal bunker;

[0007] Step 2: Determine the value of the coal loaded onto the truck;

[0008] Step 3: Based on the different coal qualities of the coal samples contained in the coal bunkers, the coal bunkers are consolidated. The number of consolidated coal bunkers is j, where j≤9;

[0009] Step 4: Calculate the number of loading trips corresponding to the prices of commercial coal and standard coal, from highest to lowest.

[0010] A further improvement of this invention is that the specific implementation method of the first step is as follows:

[0011] (1) Obtain the total number of loading trips ZZCTS;

[0012] (2) Obtain basic information on the loaded commercial coal, let k represent the kth type of commercial coal, including:

[0013] Names of commercial coal;

[0014] The selling price of raw coal is ¥Yk, yuan / ton;

[0015] Loading tonnage ZCDWk, tons;

[0016] Coal quality assessment indicators include:

[0017] Mtmink≤Mtmbk≤Mtmaxk;

[0018] Admink≤Admbk≤Admaxk;

[0019] Qmink≤Qmbk≤Qmaxk;

[0020] Where Mtmbk: the target total moisture content of the k-th type of coal, %; Mtmink: the minimum allowable total moisture content of the k-th type of coal, %; Mtmaxk: the maximum allowable total moisture content of the k-th type of coal, %;

[0021] Admbk: Target dry basis ash content of coal type k, %; Admink: Minimum allowable dry basis ash content of coal type k, %; Admaxk: Maximum allowable dry basis ash content of coal type k, %;

[0022] Qmbk: Target value of the received basis lower heating value of the k-th type of coal, kcal / kg; Qmink: Minimum allowable received basis lower heating value of the k-th type of coal, kcal / kg; Qmaxk: Maximum allowable received basis lower heating value of the k-th type of coal, kcal / kg.

[0023] (3) Obtain the storage and coal quality information of each coal bunker, where i represents the number of coal bunkers, including:

[0024] VGi: The amount of coal in the i-th coal bunker, in tons;

[0025] Mti: Total moisture content of the coal sample from the i-th coal bunker, %;

[0026] Adi: Dry basis ash content of the coal sample from the i-th coal bunker, %;

[0027] Qi: The received basis lower heating value of the coal sample from the i-th coal bunker, kcal / kg.

[0028] A further improvement of this invention is that the specific implementation method of the second step is as follows:

[0029] If the restrictions on commercial coal include calorific value, then the formula for calculating the standard coal price ¥Bk for different types of commercial coal loaded onto trucks is given in equations (1) to (3); if both minimum and maximum calorific values ​​are restricted, then...

[0030] ￥Bk=￥Yk*7000 / (0.5*(Qmink+Qmaxk)) (1)

[0031] If a minimum calorific value is limited, then

[0032] ￥Bk=￥Yk*7000 / Qmink (2)

[0033] If the maximum calorific value is limited, then

[0034] ￥Bk=￥Yk*7000 / Qmaxk (3).

[0035] A further improvement of this invention is that the specific implementation method of the second step is as follows:

[0036] If the limiting conditions for commercial coal do not include calorific value but only moisture and ash, the formula for calculating the standard coal price ￥Bk of different commercial coals loaded for shipment is shown in equations (4) to (8), where MtPk(%), AdPk(%), AarPk(%), and QPk(kcal / kg) represent the average total moisture, average dry basis ash, average received basis ash, and average received basis lower heating value of the kth type of commercial coal, respectively.

[0037] MtPk=0.5×(Mtmink+Mtmaxk) (4)

[0038] AdPk=0.5×(Admink+Admaxk) (5)

[0039]

[0040] QPk=K1×MtPk+K2×AarPk (7)

[0041] In equation (5), K1 and K2 are the influence coefficients of total moisture and received ash on calorific value, respectively;

[0042] ￥Bk=￥Yk*7000 / QPk (8)

[0043] Sort the coal according to its standard coal price (¥Bk) and input all the information about the coal:

[0044] Commodity Coal 1: ¥Y1, Mtmb1, Admb1, Qmb1, ZCDW1;

[0045] Commodity Coal 2: ¥Y2, Mtmb2, Admb2, Qmb2, ZCDW2;

[0046] ...

[0047] Commodity coal k:￥Yk,Mtmbk,Admbk,Qmbk,ZCDWk.

[0048] A further improvement of this invention is that K1 and K2 are derived from the coal quality test data of the corresponding coal preparation plant through analysis and regression, and the root mean square deviation of K1 and K2 from the actual tested received basis lower heating value is within 25 kcal / kg.

[0049] A further improvement of this invention is that the specific implementation method of the third step is as follows:

[0050] Let VGhj, Mthj, Aarhj, Qhj, and Adhj represent the coal quantity, total moisture, ash content on received basis, lower heating value on received basis, and ash content on dry basis of the integrated coal bunker, respectively.

[0051] If silo A contains a single washing product, then the corresponding information of the coal bunker will be directly transferred, as shown in equations (9) to (13).

[0052] VGh1=VG1 (9)

[0053] Mth1=Mt1 (10)

[0054] Aarh1=Aar1 (11)

[0055] Qh1=Q1 (12)

[0056] Adh1 = Ad1(13).

[0057] A further improvement of the present invention is that if both silo B and silo C contain the same coal preparation product, they are integrated. The information data of the integrated coal silo is shown in equations (14) to (18).

[0058] VGh2=VG2+ VG3 (14)

[0059] Mth2=(Mt2×VG2+Mt3×VG3) / (VG2+VG3) (15)

[0060] Aarh2=(Aar2×VG2+Aar3×VG3) / (VG3+VG3) (16)

[0061] Qh2=(Q2×VG2+Q3×VG3) / (VG2+VG3) (17)

[0062]

[0063] A further improvement of this invention is that if m silos from silo D to silo i contain the same coal preparation product, and m≥3, then they are integrated. The information data of the integrated coal silos are shown in equations (19) to (23).

[0064]

[0065]

[0066]

[0067]

[0068]

[0069] A further improvement of the present invention lies in that the specific implementation method of the fourth step is as follows:

[0070] (1) Solve the number of loading trips with the highest standard coal price of commercial coal

[0071] According to the coal quality and coal quantity requirements of commercial coal 1: ￥Y1, Mtmb1, Mtmax1, Mtmin1, Admb1, Admax1, Admin1, Qmb1, Qmax1, Qmin1, ZCDW1, find the maximum number of loading trips ZCTS1max of commercial coal 1;

[0072] Assume ZCTS1 = ZZCTS, and exhaustively enumerate each integrated coal bunker at a step size of Rjf = 0.01. Rj represents the mass ratio of the jth integrated coal bunker, and calculate the coal quantity VGNj1(t) required for each integrated coal bunker in the current state. The calculation of the coal quality indexes of the blended commercial coal and the coal quantity of each integrated coal bunker can be seen from Equation (24) to Equation (28):

[0073]

[0074]

[0075]

[0076]

[0077]

[0078] If the coal quality meets the coal quality assessment indexes of Claim 2 and the coal quantity of the integrated silo also meets the requirement VGNj1 ≤ VGj, it is a qualified working condition. At this time, the corresponding ZCTS1 is the maximum number of loading trips ZCTS1max of commercial coal 1;

[0079] If there is no qualified one, then ZCTS1 = ZZCTS - 1, and repeat the calculation of the coal quantity required for each bunker according to the aforementioned method. Do this repeatedly until a working condition with both qualified coal quantity and coal quality and its corresponding number of loading trips ZCTS1max are screened out. Select the one with the lowest calorific value as the best recommended method, and bring out the blending ratio of each integrated bunker, the required coal quantity of the integrated bunker, and the coal quality parameters after blending;

[0080] At this time, the remaining coal quantity VGSj1 of each integrated coal bunker = VGj - VGj1

[0081] If ZCTS1max < ZZCTS, then solve the number of loading trips with the second-highest commercial coal price;

[0082] (2) Solve the number of loading trips with the second-highest commercial coal price

[0083] Solve for the number of loading trips with the second-highest standard coal price of commercial coal in the same way as for the number of loading trips with the highest standard coal price of commercial coal, except that the coal storage volume and the number of loading trips of each integrated coal bunker vary;

[0084] According to the coal quality and coal quantity requirements of commercial coal 2: ￥Y2, Mtmb2, Mtmax2, Mtmin2, Admb2, Admax2, Admin2, Qmb2, Qmax2, Qmin2, ZCDW2, find the maximum number of loading trips ZCTS2max of commercial coal 2;

[0085] Exhaustively enumerate each integrated coal bunker at a step size of Rj = 0.01 for the mass ratio, and assume that ZCTS2 = ZZCTS - ZCTS1, and calculate the coal quantity VGNj2(t) required for each integrated coal bunker in the current state. The calculation of the coal quality indexes of the blended commercial coal and the coal quantity of each integrated coal bunker can be seen from Equation (29) to Equation (33):

[0086]

[0087]

[0088]

[0089]

[0090]

[0091] If the coal quality meets the coal quality assessment index and the coal quantity of the integrated silo also meets the requirement VGNj2 ≤ VGSj1, it is a qualified working condition;

[0092] If there is no qualified one, then ZCTS2 = ZCTS2 - 1, and repeat the calculation of the coal quantity required for each bunker according to the foregoing method. Do this repeatedly until a working condition with both qualified coal quantity and coal quality is screened out, as well as its corresponding number of loading trips ZCTS2max, and select the one with the lowest calorific value as the best recommended method, and bring out the blending ratio of each integrated bunker, the required coal quantity of the integrated bunker, and the coal quality parameters after blending;

[0093] At this time, the remaining coal quantity VGSj2 of each integrated coal bunker is VGSj1 - VGNj2

[0094] If ZCTS2 < ZZCTS - ZCTS1, then solve for the maximum number of loading trips of the commercial coal with the third-highest standard coal price;

[0095] (3) And so on, until the number of loading trips with the lowest standard coal price of commercial coal is solved, as well as its corresponding coal quality parameters and the blending ratio of the coal bunker.

[0096] The present invention has at least the following beneficial technical effects:

[0097] 1) Based on multiple constraints and multiple objective functions, a precise coal blending scheme was constructed.

[0098] 2) This invention can increase the output of specialty coal, maximize the commercial coal benefits of coal preparation plants, and improve the economic benefits of coal preparation plants. Detailed Implementation

[0099] Exemplary embodiments of this disclosure will now be described in more detail. While exemplary embodiments of this disclosure are given, it should be understood that this disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of this disclosure and to fully convey the scope of this disclosure to those skilled in the art. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other. The invention will now be described in detail with reference to the embodiments.

[0100] The present invention provides a method for determining a coal preparation plant loading plan, comprising the following steps:

[0101] Step 1: Obtain basic information about the coal to be loaded onto the trucks and about each coal bunker:

[0102] (1) Obtain the total number of loading trips ZZCTS (trips)

[0103] (2) Obtain basic information about the coal to be loaded (there are usually multiple types, where k represents the kth type of coal):

[0104] ①Name of commercial coal

[0105] ②Sales price of raw coal: ¥Yk (yuan / ton)

[0106] ③ Loading tonnage ZCDWk (tons)

[0107] ④ Coal quality assessment indicators (single or multiple selections allowed)

[0108] Mtmink≤Mtmbk(%)≤Mtmaxk

[0109] Admink≤Admbk(%)≤Admaxk

[0110] Qmink≤Qmbk(kcal / kg)≤Qmaxk

[0111] Mtmbk: Target total moisture content of type k coal; Mtmink: Minimum allowable total moisture content of type k coal; Mtmaxk: Maximum allowable total moisture content of type k coal.

[0112] Admbk: Target dry basis ash content of the k-th type of coal; Admink: Minimum allowable dry basis ash content of the k-th type of coal; Admaxk: Maximum allowable dry basis ash content of the k-th type of coal.

[0113] Qmbk: Target value of the received basis lower heating value of the k-th type of coal; Qmink: Minimum allowable received basis lower heating value of the k-th type of coal; Qmaxk: Maximum allowable received basis lower heating value of the k-th type of coal.

[0114] (3) Obtain the storage and coal quality information of each coal bunker, where i represents the number of coal bunkers, specifically including:

[0115] VGi: The amount of coal in the i-th coal bunker, in tons;

[0116] Mti: Total moisture content of the coal sample from the i-th coal bunker, %;

[0117] Adi: Dry basis ash content of the coal sample from the i-th coal bunker, %;

[0118] Qi: Lower heating value of coal sample from the i-th coal bunker, kcal / kg;

[0119] Step 2: Determine the value of the coal loaded onto the trucks.

[0120] (1) If the limiting conditions of commercial coal include calorific value, the formula for calculating the standard coal price ￥Bk of different commercial coals loaded for loading is shown in equations (1) to (3).

[0121] (1) If the minimum and maximum calorific values ​​are limited, then

[0122] ￥Bk=￥Yk*7000 / (0.5*(Qmink+Qmaxk)) (1)

[0123] If a minimum calorific value is limited, then

[0124] ￥Bk=￥Yk*7000 / Qmink (2).

[0125] If the maximum calorific value is limited, then

[0126] ￥Bk=￥Yk*7000 / Qmaxk (3).

[0127] (2) If the limiting conditions for commercial coal do not include calorific value but only moisture and ash content, the formula for calculating the standard coal price ￥Bk (yuan / t) of different commercial coals loaded onto the truck is shown in equations (4) to (8).

[0128] MtPk=0.5×(Mtmink+Mtmaxk) (4)

[0129] AdPk=0.5×(Admink+Admaxk) (5)

[0130]

[0131] QPk=K1×MtPk+K2×AarPk (7)

[0132] In equation (7), K1 and K2 are the influence coefficients of total moisture and ash content on calorific value, respectively. They can be obtained by regression analysis of coal quality test data from the corresponding coal preparation plant. The root mean square deviation of the actual tested net calorific value is within 25 kcal / kg.

[0133] ￥Bk=￥Yk*7000 / QPk (8)

[0134] Sort the coal according to its standard coal price (¥Bk) and input all the information about the coal:

[0135] Commodity Coal 1: ¥Y1, Mtmb1, Admb1, Qmb1, ZCDW1

[0136] Commodity Coal 2: ¥Y2, Mtmb2, Admb2, Qmb2, ZCDW2

[0137] ...

[0138] Commodity coal k:￥Yk,Mtmbk,Admbk,Qmbk,ZCDWk,

[0139] Step 3: Based on the different coal qualities of the coal samples contained in the coal bunkers, the coal bunkers are consolidated, resulting in j (j≤9) consolidated coal bunkers. VGhj, Mthj, Aarhj, Qhj, and Adhj represent the coal quantity (tons), total moisture (%), as-received ash content (%), as-received lower heating value (kcal / kg), and dry ash content (%) of the consolidated coal bunkers, respectively.

[0140] If silo A contains a single washing product, then the corresponding information of the coal bunker is directly transferred, as shown in equations (9) to (13).

[0141] VGh1=VG1 (9)

[0142] Mth1=Mt1 (10)

[0143] Aarh1=Aar1 (11)

[0144] Qh1=Q1 (12)

[0145] Adh1=Ad1 (13)

[0146] If both silos B and C contain the same coal preparation product, they are integrated. The information data of the integrated coal silos are shown in equations (14) to (18).

[0147] VGh2=VG2+ VG3 (14)

[0148] Mth2=(Mt2×VG2+Mt3×VG3) / (VG2+VG3) (15)

[0149] Aarh2=(Aar2×VG2+Aar3×VG3) / (VG3+VG3) (16)

[0150] Qh2=(Q2×VG2+Q3×VG3) / (VG2+VG3) (17)

[0151]

[0152] If m silos from silo D to silo i all contain the same coal preparation product, then they are integrated. The information data of the integrated coal silos can be found in equations (19) to (23).

[0153]

[0154]

[0155]

[0156]

[0157]

[0158] Step 4: Calculate the number of loading trips corresponding to the prices of commercial coal and standard coal, from highest to lowest.

[0159] (1) Solve for the number of loading trips that maximize the price of standard coal.

[0160] Based on the coal quality and quantity requirements of commodity coal 1: ￥Y1, Mtmb1, Mtmax1, Mtmin1, Admb1, Admax1, Admin1, Qmb1, Qmax1, Qmin1, ZCDW1, find the maximum number of loading trips ZCTS1max for commodity coal 1.

[0161] Exhaustive enumeration is performed on each integrated coal bunker with a mass ratio Rj = 1%, assuming ZCTS1 = ZZCTS, and the amount of coal VGNj1(t) required for each integrated coal bunker in the current state is calculated.

[0162] The calculation of coal quality indicators and coal quantity of each integrated coal bunker after blending is shown in equations (24) to (28):

[0163]

[0164]

[0165]

[0166]

[0167]

[0168] If the coal quality meets the coal quality assessment indicators of Claim 2 and the coal quantity in the integrated silo also meets the requirements (VGNj1 ≤ VGj), it is a qualified working condition, and the corresponding ZCTS1 at this time is the maximum number of loading trips ZCTS1max of commercial coal 1.

[0169] If there is no qualified one, then ZCTS1 = ZZCTS - 1, and calculate the coal quantity required for each silo repeatedly according to the foregoing method. In this way, until a working condition with both qualified coal quantity and quality is screened out, and its corresponding number of loading trips ZCTS1max, and select the one with the lowest calorific value as the best recommended method, and bring out the blending ratio of each integrated silo, the coal quantity required for the integrated silo, and the coal quality parameters after blending;

[0170] At this time, the remaining coal quantity VGSj1 of each integrated coal silo = VGj - VGj1

[0171] If ZCTS1max < ZZCTS, then solve for the number of loading trips with the second-highest price of commercial coal.

[0172] (2) Solve for the number of loading trips with the second-highest price of commercial coal.

[0173] Solve for the number of loading trips with the second-highest standard coal price of commercial coal in the same way as solving for the number of loading trips with the highest standard coal price of commercial coal, except that the coal storage quantity and the number of available loading trips of each integrated coal silo change.

[0174] According to the coal quality and coal quantity requirements of commercial coal 2: ¥Y2, Mtmb2, Mtmax2, Mtmin2, Admb2, Admax2, Admin2, Qmb2, Qmax2, Qmin2, ZCDW2, seek the maximum number of loading trips ZCTS2max of commercial coal 2.

[0175] Exhaustively list each integrated coal silo in steps of the mass ratio Rj = 0.0 (1%), and assume that ZCTS2 = ZZCTS - ZCTS1max, and calculate the coal quantity VGNj2(t) required for each integrated coal silo in the current state.

[0176] The calculation of the coal quality indicators of the blended commercial coal and the coal quantity of each integrated coal silo can be seen from Equation (29) to Equation (33):

[0177]

[0178]

[0179]

[0180]

[0181]

[0182] If the coal quality meets the coal quality assessment indicators of Claim 2 and the coal quantity in the combined silo also meets the requirements (VGNj2 ≤ VGSj1), it is a qualified working condition, and the corresponding ZCTS2 at this time is the maximum loading trips ZCTS2max of commercial coal 1.

[0183] If there is no qualified one, then ZCTS2 = ZCTS2 - 1, and calculate the required coal quantity for each silo repeatedly according to the foregoing method, and so on until a working condition with both qualified coal quantity and quality and its corresponding maximum loading trips ZCTS2max are selected. And select the one with the lowest calorific value as the best recommended method, and bring out the blending ratio of each integrated silo, the required coal quantity of the integrated silo, and the coal quality parameters after blending.

[0184] At this time, the remaining coal quantity VGSj2 of each integrated coal silo = VGSj1 - VGNj2

[0185] If ZCTS2 < ZZCTS - ZCTS1max, then solve for the maximum loading trips of the commercial coal with the third highest standard coal price.

[0186] (3) And so on until the loading trips of the commercial coal with the lowest price (sorted by standard coal price) are solved, as well as its corresponding coal quality parameters and the blending ratio of the coal silos.

[0187] Example

[0188] First step: Obtain the basic information required for loading and the basic information of each coal silo:

[0189] (1) Obtain the total number of loading trips ZZCTS (trips) [

[0190] (2) Obtain the basic information of the commercial coal for loading (usually there can be multiple types, where k represents the kth type of commercial coal):

[0191] ① Name of the commercial coal

[0192] ② Original coal sales unit price ￥Yk (yuan / ton)

[0193] ③ Loading tonnage ZCDWk (tons)

[0194] ④ Coal quality assessment indicators (can be single - selected or multiple - selected)

[0195] Mtmink ≤ Mtmbk (%) ≤ Mtmaxk

[0196] Admink≤Admbk(%)≤Admaxk

[0197] Qmink≤Qmbk(kcal / kg)≤Qmaxk

[0198] Mtmbk: Target total moisture content of type k coal; Mtmink: Minimum allowable total moisture content of type k coal; Mtmaxk: Maximum allowable total moisture content of type k coal.

[0199] Admbk: Target dry basis ash content of the k-th type of coal; Admink: Minimum allowable dry basis ash content of the k-th type of coal; Admaxk: Maximum allowable dry basis ash content of the k-th type of coal.

[0200] Qmbk: Target value of the received basis lower heating value of the k-th type of coal; Qmink: Minimum allowable received basis lower heating value of the k-th type of coal; Qmaxk: Maximum allowable received basis lower heating value of the k-th type of coal.

[0201] (3) Obtain the storage and coal quality information of each coal bunker, where i represents the number of coal bunkers, specifically including:

[0202] VGi: The amount of coal in the i-th coal bunker, in tons;

[0203] Mti: Total moisture content of the coal sample from the i-th coal bunker, %;

[0204] Adi: Dry basis ash content of the coal sample from the i-th coal bunker, %;

[0205] Qi: Lower heating value of coal sample from the i-th coal bunker, kcal / kg;

[0206] The total number of loading trips planned for this shipment is ZZCTS = 7. The basic requirements for the three types of commercial coal are as follows:

[0207]

[0208]

[0209] The basic information for each silo is as follows:

[0210] The amount of coal in the coal bunker, VGi(t). 7500 6200 5800 7000 8000 Mti (%) 14.8 15.7 15.9 18.3 18.5 Adi (%) 5.20 7.30 7.50 10.68 10.70 Qi (kcal / kg) 5972 5760 5731 5338 5322 Aari (%) 4.43 6.15 6.31 8.73 8.72

[0211] Step 2: Determine the value of the coal loaded onto the trucks.

[0212] (1) If the limiting conditions of commercial coal include calorific value, the formula for calculating the standard coal price ￥Bk of different commercial coals loaded for loading is shown in equations (1) to (3).

[0213] (1) If the minimum and maximum calorific values ​​are limited, then

[0214] ￥Bk=￥Yk*7000 / (0.5*(Qmink+Qmaxk)) (1)

[0215] If a minimum calorific value is limited, then

[0216] ￥Bk=￥Yk*7000 / Qmink (2).

[0217] If the maximum calorific value is limited, then

[0218] ￥Bk=￥Yk*7000 / Qmaxk (3).

[0219] (2) If the limiting conditions for commercial coal do not include calorific value but only moisture and ash content, the formula for calculating the standard coal price ￥Bk (yuan / t) of different commercial coals loaded onto the truck is shown in equations (4) to (8).

[0220] MtPk=0.5×(Mtmink+Mtmaxk) (4)

[0221] AdPk=0.5×(Admink+Admaxk) (5)

[0222]

[0223] QPk=K1×MtPk+K2×AarPk (7)

[0224] In equation (7), K1 and K2 are the influence coefficients of total moisture and ash content on calorific value, respectively. They can be obtained by regression analysis of coal quality test data from the corresponding coal preparation plant. The root mean square deviation of the actual tested net calorific value is within 25 kcal / kg.

[0225] ￥Bk=￥Yk*7000 / QPk (8)

[0226] Sort the coal according to its standard coal price (¥Bk) and input all the information about the coal:

[0227] Commodity Coal 1: ¥Y1, Mtmb1, Admb1, Qmb1, ZCDW1

[0228] Commodity Coal 2: ¥Y2, Mtmb2, Admb2, Qmb2, ZCDW2

[0229] ...

[0230] Commodity coal k:￥Yk,Mtmbk,Admbk,Qmbk,ZCDWk,

[0231] The restrictions on commercial coal in this case include calorific value. Therefore, the formula for calculating the standard coal price ￥Bk (yuan / t) for different types of commercial coal loaded onto trucks is shown in equation (1).

[0232] ￥Bk=￥Yk*7000 / (0.5*(Qmink+Qmaxk)) (1)

[0233] Commodity Coal 1: ¥B1=¥Y1*7000 / (0.5*(Qmin1+Qmax1))

[0234] =800*7000 / (0.5*(5850+6000))=945.15

[0235] Commodity Coal 2: ¥B2=¥Y1*7000 / (0.5*(Qmin2+Qmax2))

[0236] =720*7000 / (0.5*(5750+5850))=868.97

[0237] Commodity Coal 3: ¥B1=¥Y1*7000 / (0.5*(Qmin3+Qmax3))

[0238] =460*7000 / (0.5*(5200+5600))=596.30

[0239] Therefore, the value of the coal in this transaction is: Coal 1 > Coal 2 > Coal 3.

[0240] Step 3: Based on the different coal qualities of the coal samples contained in the coal bunkers, the coal bunkers are consolidated, resulting in j (j≤9) consolidated coal bunkers. VGhj, Mthj, Aarhj, Qhj, and Adhj represent the coal quantity (tons), total moisture (%), as-received ash content (%), as-received lower heating value (kcal / kg), and dry ash content (%) of the consolidated coal bunkers, respectively.

[0241] If silo A contains a single washing product, then the corresponding information of the coal bunker is directly transferred, as shown in equations (9) to (13).

[0242] VGh1=VG1 (9)

[0243] Mth1=Mt1 (10)

[0244] Aarh1=Aar1 (11)

[0245] Qh1=Q1 (12)

[0246] Adh1=Ad1 (13)

[0247] If both silos B and C contain the same coal preparation product, they are integrated. The information data of the integrated coal silos are shown in equations (14) to (18).

[0248] VGh2=VG2+ VG3 (14)

[0249] Mth2=(Mt2×VG2+Mt3×VG3) / (VG2+VG3) (15)

[0250] Aarh2=(Aar2×VG2+Aar3×VG3) / (VG3+VG3) (16)

[0251] Qh2=(Q2×VG2+Q3×VG3) / (VG2+VG3) (17)

[0252]

[0253] If m silos from silo D to silo i all contain the same coal preparation product, then they are integrated. The information data of the integrated coal silos can be found in equations (19) to (23).

[0254]

[0255]

[0256]

[0257]

[0258]

[0259] For this case, if a single piece of refined coal is found in silo 1, the corresponding information of the coal silo will be directly transferred, as shown in equations (7) to (11).

[0260] VGh1=VG1=7500(t) (7)

[0261] Mth1 = Mt1 = 14.8 (%) (8)

[0262] Aah1=Ad1=5.20(%) (9)

[0263] Qh1=Q1=5972(kcal / kg) (10)

[0264]

[0265] If both silos 2 and 3 are filled with fine coal, they will be integrated. The information data of the integrated coal silos can be found in equations (12) to (16).

[0266] VGh2=VG2+ VG3=6200+5800=12000(t) (12)

[0267]

[0268]

[0269]

[0270]

[0271] If both silos 4 and 5 contain mixed coal, they will be integrated. The information data of the integrated coal silos can be found in equations (12) to (16).

[0272] VGh3=VG4+VG5=7000+5800=15000(t) (12)

[0273]

[0274]

[0275]

[0276]

[0277] Step 4: Calculate the number of loading trips corresponding to the prices of commercial coal and standard coal, from highest to lowest.

[0278] (1) Solve for the number of loading trips that maximize the price of standard coal.

[0279] Based on the coal quality and quantity requirements of commodity coal 1: ￥Y1, Mtmb1, Mtmax1, Mtmin1, Admb1, Admax1, Admin1, Qmb1, Qmax1, Qmin1, ZCDW1, find the maximum number of loading trips ZCTS1max for commodity coal 1.

[0280] Exhaustive enumeration is performed on each integrated coal bunker with a mass ratio Rj = 1%, assuming ZCTS1 = ZZCTS, and the amount of coal VGNj1(t) required for each integrated coal bunker in the current state is calculated.

[0281] The calculation of coal quality indicators and coal quantity of each integrated coal bunker after blending is shown in equations (24) to (28):

[0282]

[0283]

[0284]

[0285]

[0286]

[0287] If the coal quality meets the coal quality assessment indicators of Claim 2 and the coal quantity in the integrated silo also meets the requirements (VGNj1 ≤ VGj), it is a qualified working condition. At this time, the corresponding ZCTS1 is the maximum number of loading trips ZCTS1max of Commercial Coal 1.

[0288] If there is no qualified one, then ZCTS1 = ZZCTS - 1, and calculate the coal quantity required for each silo repeatedly according to the aforementioned method. Repeat this process until a working condition with both qualified coal quantity and quality is screened out, as well as its corresponding maximum number of loading trips ZCTS1max, and select the one with the lowest calorific value as the best recommended method, and bring out the blending ratio of each integrated silo, the required coal quantity of the integrated silo, and the coal quality parameters after blending;

[0289] At this time, the remaining coal quantity VGSj1 of each integrated coal silo = VGj - VGj1

[0290] If ZCTS1max < ZZCTS, then solve for the number of loading trips with the second-highest price of commercial coal.

[0291] (2) Solve for the number of loading trips with the second-highest price of commercial coal.

[0292] Solve for the number of loading trips with the second-highest standard coal price of commercial coal in the same way as solving for the number of loading trips with the highest standard coal price of commercial coal, except that the coal storage quantity and the number of available loading trips of each integrated coal silo are different.

[0293] According to the coal quality and quantity requirements of Commercial Coal 2: ￥Y2, Mtmb , Mtmax2, Mtmin2, Admb2, Admax2, Admin2, Qmb2, Qmax2, Qmin2, ZCDW2, seek the maximum number of loading trips ZCTS2max of Commercial Coal 2.

[0294] Exhaustively list each integrated coal silo in steps of the mass ratio Rj = 0.0 (1%), and assume ZCTS2 = ZZCTS - ZCTS1max, and calculate the coal quantity VGNj2(t) required for each integrated coal silo in the current state.

[0295] The calculation of the coal quality indicators of the blended commercial coal and the coal quantity of each integrated coal silo can be seen from Equation (29) to Equation (33):

[0296]

[0297]

[0298]

[0299]

[0300]

[0301] If the coal quality meets the coal quality assessment index of Claim 2, and the coal quantity in the combined silo also meets the requirement (VGNj2 ≤ VGSj1), it is a qualified working condition. At this time, the corresponding ZCTS2 is the maximum number of loading trips ZCTS2max of Commercial Coal 1.

[0302] If there is no qualified one, then ZCTS2 = ZCTS2 - 1, and the coal quantity required for each silo is recalculated according to the foregoing method. Repeat this process until a working condition with both qualified coal quantity and quality is screened out, as well as its corresponding number of loading trips ZCTS2max. Then select the one with the lowest calorific value as the best recommended method, and bring out the blending ratio of each integrated silo, the coal quantity required for the integrated silo, and the coal quality parameters after blending.

[0303] At this time, the remaining coal quantity VGSj2 of each integrated coal silo = VGSj1 - VGNj2

[0304] If ZCTS2 < ZZCTS - ZCTS1max, then solve for the maximum number of loading trips of the commercial coal with the third highest standard coal price.

[0305] (3) And so on, until the number of loading trips of the commercial coal with the lowest price (sorted by standard coal price) is solved, as well as its corresponding coal quality parameters and the blending ratio of the coal silos.

[0306] First, solve for the maximum number of loading trips ZCTS1max of Commercial Coal 1.

[0307] According to the above calculation principle, it is calculated that ZCTS1max = 3, R1 = 0.55, R2 = 0.45, R3 = 0.00. It can not only meet the coal quality requirements but also the coal quantity requirements, and has the lowest calorific value among the feasible solutions. Therefore, it is determined as the loading plan for Commercial Coal 1. The specific calculation results are as follows:

[0308]

[0309]

[0310]

[0311]

[0312] VGNj1 = VGN11 = 3 × 4320 × 0.55 = 7128 (t) (26)

[0313] VGNj1 = VGN21 = 3 × 4320 × 0.45 = 5832 (t) (26)

[0314] VGNj1=VGN31=3×4320×0.00=0.00(t) (26)

[0315] At this time, the remaining coal quantity in each integrated coal bunker

[0316] VGS11=VGj-VGj1=VG1-VGj11=7500-7128=372(t)

[0317] VGS21=VGj-VGj1=VG2-VGj22=12000-5832=6168(t)

[0318] VGS31=VGj-VGj1=VG3-VGj33=15000-0=15000(t)

[0319] Then solve for the maximum number of loading trips for commodity coal 2, ZCTS2max.

[0320] Based on the above calculation principles, ZCTS2max = 1, R1 = 0.06, R2 = 0.87, and R3 = 0.07 are calculated to meet both coal quality and quantity requirements, and have the lowest calorific value among feasible options. Therefore, the loading scheme for commercial coal 2 is selected. The specific calculation results are as follows:

[0321]

[0322]

[0323]

[0324]

[0325] VGNj1=VGN12=1×4320×0.06=259.2(t) (26)

[0326] VGNj2=VGN22=1×4320×0.87=3758.4(t) (26)

[0327] VGNj3=VGN32=1×4320×0.07=302.4(t) (26)

[0328] At this time, the remaining coal quantity in each integrated coal bunker

[0329] VGS12=VGS11-VGN12=2402.4-259.2=112.8(t)

[0330] VGS22=VGS21-VGN22=9408-3758.4=2409.6(t)

[0331] VGS32=VGS21-VGN32=15000-302.4=14697.6(t)

[0332] Finally, the maximum number of loading trips for commodity coal 3, ZCTS3max, is calculated.

[0333] Based on the above calculation principles, ZCTS3max = 3, R1 = 0.00, R2 = 0.00, and R3 = 1.00. This satisfies both the coal quality and quantity requirements, and also represents the lowest calorific value among the feasible options. Therefore, the loading scheme for commercial coal 3 is selected. The specific calculation results are as follows:

[0334]

[0335]

[0336]

[0337]

[0338] VGNj1=VGN11=3×4320×0.00=0.0(t) (26)

[0339] VGNj2=VGN22=3×4320×0.00=0.0(t) (26)

[0340] VGNj3=VGN23=3×4320×1.00=12960.0(t) (26)

[0341] At this time, the remaining coal quantity in each integrated coal bunker

[0342] VGS13=VGS12-VGN13=112.8-0=112.8(t)

[0343] VGS23=VGS22-VGN23=2409.6-0.0=2409.6(t)

[0344] VGS33=VGS32-VGN33=14697.6-12960.0=1737.6(t)

[0345] The final recommended overall loading situation for commercial coal is as follows:

[0346]

[0347]

[0348] Although the present invention has been described in detail above with general descriptions and specific embodiments, modifications or improvements can be made to it, which will be obvious to those skilled in the art. Therefore, all such modifications or improvements made without departing from the spirit of the present invention fall within the scope of protection claimed by the present invention.

Claims

1. A method for determining the loading plan of a coal preparation plant, characterized in that, Includes the following steps: Step 1: Obtain the basic information of the coal to be loaded onto the trucks and the basic information of each coal bunker; the specific implementation method is as follows: (1) Obtain the total number of loading trips ZZCTS; (2) Obtain basic information on the loaded commercial coal, let k represent the kth type of commercial coal, including: Names of commercial coal; The unit price of raw coal is ¥Yk, yuan / ton; Loading tonnage ZCDWk, tons; Coal quality assessment indicators include: Mtmink≤Mtmbk≤Mtmaxk; Admink≤Admbk≤Admaxk; Qmink≤Qmbk≤Qmaxk; Where Mtmbk: the target total moisture content of the k-th type of coal, %; Mtmink: the minimum allowable total moisture content of the k-th type of coal, %; Mtmaxk: the maximum allowable total moisture content of the k-th type of coal, % Admbk: Target dry basis ash content for coal type k, %; Admink: Minimum allowable dry basis ash content for coal type k, %; Admaxk: Maximum allowable dry basis ash content for coal type k, % Qmbk: Target value of the received basis lower heating value of the k-th type of coal, kcal / kg; Qmink: Minimum allowable received basis lower heating value of the k-th type of coal, kcal / kg; Qmaxk: Maximum allowable received basis lower heating value of the k-th type of coal, kcal / kg. (3) Obtain the storage and coal quality information of each coal bunker, where i represents the number of coal bunkers, including: VGi: The amount of coal in the i-th coal bunker, in tons; Mti: Total moisture content of the coal sample from the i-th coal bunker, % Adi: Dry basis ash content of the coal sample from the i-th coal bunker, % Qi: Lower heating value of coal sample from the i-th coal bunker, kcal / kg; Step 2: Determine the value of the coal loaded onto the truck; Step 3: Based on the different coal qualities of the coal samples contained in the coal bunkers, the coal bunkers are consolidated. The number of consolidated coal bunkers is j, where j≤9; Step 4: Calculate the corresponding number of loading trips based on the price of commercial coal (from highest to lowest); the specific implementation method is as follows: (1) Determine the number of loading trips that maximize the price of standard coal. Based on the coal quality and quantity requirements of commodity coal 1: ￥Y1, Mtmb1, Mtmax1, Mtmin1, Admb1, Admax1, Admin1, Qmb1, Qmax1, Qmin1, ZCDW1, find the maximum number of loading trips ZCTS1max for commodity coal 1. Assuming ZCTS1=ZZCTS, each integrated coal bunker is enumerated in steps with a mass ratio Rj=0.01, where Rj represents the mass percentage of the j-th integrated coal bunker. The amount of coal VGNj1 required by each integrated coal bunker in the current state is calculated. The coal quality indicators of the blended commercial coal and the amount of coal in each integrated coal bunker are calculated as shown in equations (24) to (28). （24） （25） （26） （27） （28） If the coal quality meets the coal quality assessment indicators and the coal quantity in the integrated silo also meets the requirement VGNj1≤VGhj, then it is a qualified working condition. At this time, the corresponding ZCTS1 is the maximum number of loading trips for commercial coal 1, ZCTS1max. If there is no qualified one, then ZCTS1 = ZZCTS - 1, and calculate the coal quantity required for each bin repeatedly according to the foregoing method. In this way, until a working condition with both qualified coal quantity and coal quality is screened out, and its corresponding number of loading trips ZCTS1max, and select the one with the lowest calorific value as the best recommended method, and bring out the blending ratio of each integrated bin, the coal quantity required for the integrated bin, and the coal quality parameters after blending; At this time, the remaining coal quantity VGSj1 of each integrated coal bin = VGhj - VGNj1 If ZCTS1max < ZZCTS, then solve for the number of loading trips with the second-highest commercial coal price; (2)Solve for the number of loading trips with the second-highest commercial coal price Solve for the number of loading trips with the second-highest standard coal price of commercial coal in the same way as solving for the number of loading trips with the highest standard coal price of commercial coal, except that the coal storage quantity and the number of loadable trips of each integrated coal bin are changed; According to the coal quality and coal quantity requirements of commercial coal 2: ￥Y2, Mtmb2, Mtmax2, Mtmin2, Admb2, Admax2, Admin2, Qmb2, Qmax2, Qmin2, ZCDW2, seek the maximum number of loading trips ZCTS2max of commercial coal 2; Exhaustively list each integrated coal bin with a step size of Rj = 0.01 in terms of mass ratio, and assume ZCTS2 = ZZCTS - ZCTS1, and calculate the coal quantity VGNj2 required for each integrated coal bin in the current state. The calculation of the coal quality indexes of the commercial coal after blending and the coal quantity of each integrated coal bin is shown in Equations (29) to (33): （29） （30） （31） （32） （33） Among them, VGhj, Mthj, Aarhj, and Qhj respectively represent the coal quantity, total moisture, ash content on as-received basis, and low calorific value on as-received basis of the integrated coal bin; When the coal quality meets the coal quality assessment indexes and the coal quantity of the integrated silo also meets the requirement VGNj2 ≤ VGSj1, it is a qualified working condition; If there is no qualified one, then ZCTS2 = ZCTS2 - 1, and calculate the coal quantity required for each bin repeatedly according to the foregoing method. In this way, until a working condition with both qualified coal quantity and coal quality is screened out, and its corresponding number of loading trips ZCTS2max, and select the one with the lowest calorific value as the best recommended method, and bring out the blending ratio of each integrated bin, the coal quantity required for the integrated bin, and the coal quality parameters after blending; At this time, the remaining coal quantity VGSj2 of each integrated coal bin = VGSj1 - VGNj2 If ZCTS2 < ZZCTS - ZCTS1, then solve for the maximum number of loading trips of the commercial coal with the third-highest standard coal price; [[ID= 2. The method for determining the loading plan of a coal preparation plant according to claim 1, characterized in that, ​ ​ ￥Bk=￥Yk 7000 / (0.5 (Qmink+Qmaxk))(1) ​ ￥Bk=￥Yk 7000 / Qmink(2) ​ Bk = Yk 7000 / Qmaxk (3).

3. The method for determining the loading plan of a coal preparation plant according to claim 2, characterized in that, ​ If the restrictions on commercial coal do not include calorific value but only moisture and ash, the formula for calculating the standard coal price ￥Bk of different commercial coals loaded onto the truck is shown in equations (4) to (8), where MtPk (%), AdPk (%), AarPk (%), and QPk (kcal / kg) represent the average total moisture, average dry basis ash, average received basis ash, and average received basis lower heating value of the kth type of commercial coal, respectively. MtPk=0.5×(Mtmink+Mtmaxk)(4) AdPk=0.5×(Admink+Admaxk)(5) （6） QPk=K1×MtPk+K2×AarPk(7) In equation (5), K1 and K2 are the influence coefficients of total moisture and received ash on calorific value, respectively; Bk = Yk 7000 / QPk (8) Sort the coal according to its standard coal price (¥Bk) and input all the information about the coal: Commodity Coal 1: ¥Y1, Mtmb1, Admb1, Qmb1, ZCDW1; Commodity Coal 2: ¥Y2, Mtmb2, Admb2, Qmb2, ZCDW2; …… Commodity coal k: ￥Yk, Mtmbk, Admbk, Qmbk, ZCDWk.

4. The method for determining the loading plan of a coal preparation plant according to claim 3, characterized in that, K1 and K2 were derived from the coal quality test data of the corresponding coal preparation plant through regression analysis, and their root mean square deviation from the actual measured received lower heating value was within 25 kcal / kg.

5. The method for determining a coal preparation plant loading plan according to claim 3, characterized in that, The specific implementation method for the third step is as follows: Let Adhj represent the dry basis ash content of the coal bunker after integration; If silo A contains a single washing product, then the corresponding information of the coal bunker is directly transferred, as shown in equations (9) to (13). VGh1=VG1(9) （10） （11） Qh1=Q1(12) Adh1=Ad1(13).

6. The method for determining a coal preparation plant loading plan according to claim 5, characterized in that, If both silos B and C contain the same coal preparation product, they are integrated. The information data of the integrated coal silos are shown in equations (14) to (18). VGh2=VG2+ VG3 (14) （15） （16） （17） （18）。 7. The method for determining a coal preparation plant loading plan according to claim 6, characterized in that, If there are m silos from silo D to silo i that all contain the same coal preparation product, and m≥3, then they are integrated. The information data of the integrated coal silos can be found in equations (19) to (23). （19） （20） （21） （22） （23）。

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