JP2019067066A - Waste disposal plan computing method and waste disposal plan computing device - Google Patents

Abstract

To provide a waste disposal plan computing method and a waste disposal plan computing device capable of automatically calculating a waste disposal plan to maximize power sale revenue in an incineration plant in a short computing time.SOLUTION: The waste disposal plan computing device is configured to: accept input of a predicted value of a power sale price, a predicted value of a heat generation amount of waste, and a predicted value of a waste introduction amount for every second period shorter than a first period; output a planned amount of waste disposal for every third period shorter than the first period in such a manner that the planned amount of waste disposal satisfies constraints and maximizes power sale revenue of generated power in the first period; accept input of at least a planned amount for every third period and a predicted value of sale price of the generated power for every fourth period shorter than the third period; and output a planned amount of waste for every fourth period in such a manner that the planned amount of waste satisfies the constraints and maximizes the power sale revenue of the generated power in the third period.SELECTED DRAWING: Figure 3

Description

  The present invention relates to a waste disposal plan computing method and a waste disposal plan computing device for computing a planned amount of waste disposal in an incineration plant.

  BACKGROUND Conventionally, an incineration plant including an incinerator that incinerates waste is known. In such an incineration plant, a generator is provided that generates electric power using steam generated when incinerating waste in the incinerator, and the electric power generated by the electric generator is used in the incineration plant, There is one that can sell power and obtain an operating income (see, for example, Patent Document 1).

  In the operation of such an incineration plant, in order to reduce the operation cost of the incineration plant, it is desirable to formulate a waste treatment plan so as to maximize the power sale income.

  However, the operation of the incineration plant needs to consider several constraints, such as limiting the load on the incinerator, limiting the capacity of the storage tank that stores waste, stopping the incinerator or generator, and continuous operation. is there. Moreover, these constraints are in a relation of affecting each other. For example, reducing the load on the incinerator (reducing the incineration rate) may increase the volume of waste in the storage tank. For this reason, it is difficult to formulate the amount of waste to be handled manually manually while satisfying the constraint conditions without relying on the knowledge and experience of an experienced plant operator. In addition, it takes a lot of time to formulate a treatment plan in a long period such as one year.

JP 2000-297613 A JP, 2005-284388, A

  Therefore, it is desirable to calculate such a waste disposal plan using a computer. Finding a solution that maximizes or minimizes an objective function under given constraints is called an optimization problem, and various calculation methods for solving the optimization problem have been established. However, in order to develop a more detailed treatment plan in a long period, the number of variables to be determined becomes enormous (for example, when determining the throughput per hour, the number of variables to be determined is 365 × 24 = 8760), it is impossible to obtain a solution in a realistic operation time simply by applying one operation method.

  For example, in Patent Document 2 above, as a method for optimizing the operation schedule of the power generation plant, it is disclosed that the optimization operation is performed using a predetermined operation pattern. However, since the incineration plant needs not only the power generation but also the continuous treatment of wastes, the optimization operation based on the operation pattern of the generator can not obtain an optimal solution.

  Therefore, in the current incineration plant, actively controlling the amount of incineration (changing the incineration rate) is not performed.

  Therefore, the present invention provides a waste disposal plan computing method and waste disposal plan computing device capable of automatically calculating a waste disposal plan that maximizes power sale revenue in an incineration plant in a short computing time. The purpose is to

  In order to solve the problem, a waste disposal plan calculation method according to an aspect of the present invention includes an incinerator for incinerating waste, and waste heat generated when the waste is incinerated in the incinerator. And calculating a waste disposal plan of the generated power for each of a second period shorter than the first period. Value, the predicted value of the calorific value of waste, and the predicted value of the amount of waste carried in are input, and the constraints on the operation performance of the incineration plant are satisfied, and the sale of power generated in the first period is sold. Performing a first optimization operation to output a planned amount of waste processing for each third period shorter than the first period so as to maximize income; and processing for each third period Planned amount and shorter than the third period The fourth is to input at least the predicted value of the selling price of the generated power for each of the four periods, satisfy the constraint, and maximize the selling income of the generated power in the third period, Performing a second optimization operation, outputting the planned amount of waste treatment for each period of

  According to the above method, the first period is divided into the shorter second period, and the optimization operation of the third period unit shorter than the first period is performed, and then the third period is further shortened. It is divided into the fourth period, and the optimization operation in the fourth period unit is performed. Therefore, the number of divisions of the period can be reduced in each optimization operation, and the number of variables in each optimization operation can be reduced. Therefore, the calculation time in each optimization calculation can be shortened, and as a result, the calculation time for calculating the processing planned amount for each fourth period for the first period can be suppressed to a realistic time. From the above, it is possible to automatically calculate the waste disposal plan which maximizes the power sale income in a short calculation time. In addition, even if the amount of waste disposal deviates from the original waste disposal plan in actual operation, local recalculation can be easily performed.

  The waste treatment plan calculation method inputs the treatment plan amount for each of the fourth period and the predicted value of the selling price of the generated power for each fifth period shorter than the fourth period, and Performing a third optimization calculation step of outputting a planned amount of processing for each of the fifth period so as to satisfy the constraint conditions and maximize the sale income of generated power in the fourth period; May be included. By dividing the period into multiple stages, the amount of computation in each stage can be reduced. Also, by segmenting the period, local recalculation can be performed on a more suitable period basis.

  The first period is a period of 1 year or more, and the second period and the third period are each 1 week or more and less than the first period, and the fourth period is a period of 1 week or more. The period may be one day or more and less than the third period, and the fifth period may be one hour or more and less than the fourth period.

  In the third optimization operation, at least a part of the constraint condition may be omitted. Regarding the Constraint Condition Considered in the First Optimization Operation By not setting the constraint condition in the third optimization operation, it is possible to further reduce the amount of operation while maintaining high accuracy of the operation result.

  The third period is a period longer than the second period, and the constraint condition is satisfied in the first optimization calculation, and power sales revenue of the generated power in the first period is maximized. To calculate the processing plan amount for each second period, and output the processing plan amount for each third period based on the calculated processing plan amount for each second period. Good. As a result, since it is possible to output the processing plan amount for each desired period (that is, the third period different from the second period) as the intermediate output, the long-term plan to the medium-term plan and the short-term plan It can be formulated easily in the flow.

  The constraint conditions include upper and lower limit values of incineration amount per unit time of the incinerator, upper and lower limit values of capacity of a storage tank for temporarily storing wastes to be input to the incinerator, the incinerator or the power generation It may include at least one of a machine stop period and an upper limit value of a continuous operation period of the incinerator.

  The incineration plant may have a plurality of incinerators, and may calculate an operation / stop state in each incinerator in each of the third periods in the first optimization calculation. In this way, it is possible to calculate a comprehensive waste disposal plan based on the operation plans of a plurality of incinerators.

  The first period is a period corresponding to a calendar, and a plurality of the second period, the third period, and the fourth period are obtained by dividing the first period by a predetermined number of each. The plurality of divided periods may have calendar information corresponding to the first period. The optimization operation can be performed on the basis of finer prediction values in accordance with the season and the time zone.

  A waste disposal plan computing device according to another aspect of the present invention uses an incinerator for incinerating waste, and steam generated by waste heat generated when the waste is incinerated in the incinerator. A waste treatment plan computing device in an incineration plant including the generator for generating power, wherein the predicted value of the selling price of the generated power for each second period shorter than the first period, the calorific value of the waste And the predicted value of the amount of waste carried in are input so as to satisfy the constraints on the operation performance of the incineration plant, and to maximize the sales revenue of the generated power in the first period. A first optimization calculation unit for outputting a processing schedule amount for each third period shorter than the first period, a processing schedule amount for each third period, and a period shorter than the third period Forecast value of selling price of generated power every fourth period, A second optimization that outputs at least the processing planning amount for each fourth period so as to at least input, satisfy the constraint, and maximize sales revenue of generated power in the third period. And an arithmetic unit.

  According to the above configuration, the first period is divided into the shorter second period, and the optimization operation of the third period unit shorter than the first period is performed, and then the third period is further shortened. It is divided into the fourth period, and the optimization operation in the fourth period unit is performed. Therefore, the number of divisions of the period can be reduced in each optimization operation, and the number of variables in each optimization operation can be reduced. Therefore, the calculation time in each optimization calculation can be shortened, and as a result, the calculation time for calculating the processing planned amount for each fourth period for the first period can be suppressed to a realistic time. From the above, it is possible to automatically calculate the waste disposal plan which maximizes the power sale income in a short calculation time. In addition, even if the amount of waste disposal deviates from the original waste disposal plan in actual operation, local recalculation can be easily performed.

  According to the present invention, it is possible to provide a waste disposal plan computing method and waste disposal plan computing device capable of automatically calculating a waste disposal plan that maximizes power sale revenue in an incineration plant in a short computing time. can do.

It is a schematic block diagram which shows the incineration plant used as the object of the waste disposal plan calculation method which concerns on one embodiment of this invention. FIG. 2 is a block diagram showing a schematic configuration of a waste disposal plan computing device according to one embodiment of the present invention. FIG. 3 is a schematic view showing a flow of optimization calculation processing in the present embodiment. FIG. 4 is a graph conceptually showing the result of the second optimization operation in the present embodiment. FIG. 5A is a graph conceptually showing the result of the third optimization calculation based on the daily processing schedule shown in FIG. FIG. 5B is a graph conceptually showing the result of the third optimization calculation based on the daily processing schedule shown in FIG. FIG. 6 is a schematic diagram showing a flow of optimization calculation processing in the modification of the present embodiment.

  Hereinafter, a waste disposal plan calculation method according to an embodiment of the present invention will be described. First, an example of the incineration plant as a premise will be described.

  FIG. 1 is a schematic configuration view showing an incineration plant which is a target of the waste disposal plan calculation method according to the embodiment of the present invention. The incineration plant 1 comprises an incinerator 2 having a furnace chamber 3 for incineration of waste using an oxygen-containing gas, and a steam recovery device for recovering waste heat as steam from incinerator exhaust gas discharged from the incinerator 2 And the boiler 4 which is. A hopper 5 and a dust collector 6 are disposed on the side of the incinerator 2 opposite to the boiler 4, and from the boiler 4, an exhaust path 7 of the exhaust gas extends to the chimney 8. Although not shown in the drawings, the exhaust path 7 is provided with an economizer, a temperature reducing tower, a dust collector and a blower in this order from the upstream side.

  On the opposite side to the furnace chamber 3 of the hopper 5, a storage tank (waste pit) 9 for temporarily storing waste to be introduced into the incinerator 2 is provided. A crane 10 is provided above the storage tank 9. The wastes stored in the storage tank 9 are introduced into the hopper 5 by the crane 10. The dust collector 6 feeds the waste introduced into the hopper 5 into the furnace chamber 3 of the incinerator 2 by intermittently operating at predetermined intervals (for example, 0.5 to 3 minutes).

  The incinerator 2 has a stoker provided below the furnace chamber 3. The stoker functions as a means for transporting waste. The stoker has a dry stoker 11, a combustion stoker 12 and a post-combustion stoker 13 sequentially from the side close to the dust collector 6. That is, these stokers 11 to 13 are arranged in the moving direction of the waste. Under the drying, combustion and post-combustion stokers 11 to 13, air boxes 14 to 16 are provided, respectively. Furthermore, the incinerator 2 has a recombustion chamber 17 continuous with the furnace chamber 3 between the furnace chamber 3 and the boiler 4. Although the combustion stoker 12 is one stage in the illustrated example, two or more stages may be provided. The drying, combustion and post-combustion stokers 11 to 13 operate intermittently at different intervals, for example.

  In the furnace chamber 3, combustion gas is generated by the thermal decomposition and partial oxidation reaction of the waste, and the combustion gas is burned together with the waste. The reburning chamber 17 is for completely burning the combustion gas flowing out of the furnace chamber 3. After burning the waste, the ash is discharged from an outlet 18 provided adjacent to the post-combustion stoker 13.

  In the boiler 4, steam is generated by the exhaust gas (exhaust heat) discharged from the incinerator 2. More specifically, as shown in FIG. 1, the boiler 4 includes a radiation chamber 19 disposed above the reburning chamber 17, a first flue 20 in which the radiation chamber 19 and the upper portion communicate with each other, and a first flue 20 and the 2nd flue 21 which lower parts communicate. Steam generated from waste heat in the boiler 4 is sent to a turbine 22 connected to a generator 23 and used for power generation. The electric power generated by the generator 23 is used in the incineration plant 1. In addition, surplus power is sold to a power company. Most of the exhaust gas that has passed through the boiler 4 is discharged from the chimney 8 to the atmosphere after flowing through the exhaust path 7.

  In addition, in FIG. 1, although the incineration plant 1 is illustrated as a structure which has one incineration plant, the incineration plant 1 may be equipped with several incineration plant (incinerator 2).

  The selling price of electricity to a power company fluctuates depending on the season, time, and the like. For example, the selling price tends to be higher in summer (July to September) compared to other periods. In addition, the calorific value per unit amount of waste also changes depending on the season, time, and the like because the state of the waste changes due to humidity, temperature, and the like. For example, the calorific value per unit amount of waste decreases because the amount of water contained in the waste increases in summer. Further, the amount of waste carried into the storage tank 9 changes from time to time.

  On the other hand, the disposal of wastes in the incineration plant 1 has operational limitations. For example, upper and lower limit value of incineration amount per unit time of incinerator 2, upper and lower limit value of capacity of storage tank 9, stop period (maintenance period) of incinerator 2 or generator 23, and continuous operation of incinerator 2 There is an upper limit value of the period, etc. At least one of these constraints can be constraints for optimizing the waste processing amount described later.

  The upper limit value of the incineration amount and the upper limit value of the capacity of the storage tank 9 are previously determined for each incineration plant 1 as a value indicating the performance upper limit of the incineration plant 1. The lower limit value of the incineration amount and the lower limit value of the capacity of the storage tank 9 are previously determined for each incineration plant 1 as a minimum value necessary for the incinerator 2 to continuously perform the waste incineration operation. The shutdown period of the incinerator 2 is determined as, for example, X times a year, Y-day shutdown at one time, etc., as constraints on the maintenance of the incinerator 2. The same applies to the stop period of the generator 23. The continuous operation period of the incinerator 2 is predetermined to maintain the capacity of the incinerator 2.

  FIG. 2 is a block diagram showing a schematic configuration of a waste disposal plan computing device according to one embodiment of the present invention. A waste disposal plan computing device (hereinafter sometimes simply referred to as computing device) 31 shown in FIG. 2 includes an input unit 32, a storage unit 33, a computing unit 34, and an output unit 35. The configurations 31 to 35 mutually transmit data via the bus 36. The arithmetic unit 31 may be configured by a control unit and a control computer (not shown) in the incineration system 1 or may be configured as a computer independent of it. The arithmetic device 1 may be configured by a computer that can communicate with the control device in the incineration system 1.

  The input unit 32 is configured as an input device that allows the user to input information such as a predicted value of the sale price for each predetermined period, a predicted value of the calorific value of waste, and a predicted value of the amount of waste carried in. The storage unit 33 stores the information input from the input unit 32. In addition, in the storage unit 33, constraints and an optimization calculation program regarding the operation performance of the incineration plant described later are stored in advance. The constraint conditions may be settable or changeable from the input unit 32.

  The calculation unit 34 executes optimization calculation processing to calculate the planned amount of waste processing in the first period (for example, one year) based on various types of information stored in the storage unit 33. For this purpose, the operation unit 34 executes the optimization operation program to obtain the input information acquisition unit 41, the first optimization operation unit 42, the second optimization operation unit 43, and the third optimization operation unit. It exerts the function of 44 mag.

  The input information acquisition unit 41 acquires necessary input values to perform each of first to third optimization calculations to be described later. More specifically, the input information acquisition unit 41 receives input of information such as a predicted value of the sale price for each predetermined period, a predicted value of the calorific value of waste, and a predicted value of the amount of carried in waste. These predicted values may be values based on past actual results (actual values) or may be values calculated by a predetermined operation (such as simulation). The predicted value of the sale price may be a proposed or determined value of the purchase price by a predetermined organization (such as a power company).

  The input information acquisition unit 41 may acquire the value input from the input unit 32 as it is, or may acquire the value by reading out the information stored in the storage unit 33. Each optimization calculation unit 42 to 44 satisfies the constraint condition using the input information and the constraint condition stored in the storage unit 3 and maximizes the selling income of generated power. To calculate the processing schedule for each shorter period.

  The first optimization calculation unit 42 receives the predicted value for each second period shorter than the first period, and satisfies the constraint condition using the constraint condition, and generates power in the first period. In order to maximize the power sales revenue of the power, the planned processing volume per third period shorter than the first period is output. The second optimization calculation unit 43 predicts the above-described prediction for each fourth period, which is shorter than the third period, with respect to each of the processing planning amounts for each third period calculated by the first optimization calculation unit 42. A value is input, and using the above constraint conditions, the planned treatment volume for each fourth period is output so as to satisfy the constraint conditions and maximize the sale income of generated power in the third period. . The third optimization calculation unit 44 sells power for each fifth period, which is shorter than the fourth period, for each of the processing planned amounts for each fourth period calculated by the second optimization calculation unit 43. The forecasted value of the price is input, and the processing schedule quantity for each fifth period is used to satisfy the constraint conditions using the above-mentioned constraint conditions and maximize the sales revenue of the generated power in the fourth period. Output

  The output unit 35 outputs the calculation result in the calculation unit 34. For example, the output unit 35 causes the display device (not shown) connected to the arithmetic device 1 to display the planned processing amount according to each period.

  Hereinafter, a specific example of the optimization calculation process will be described. FIG. 3 is a schematic view showing a flow of optimization calculation processing in the present embodiment. In the example of FIG. 3, the aspect which calculates the processing plan quantity for every hour for 1 year is illustrated. That is, in the present embodiment, the first period is set to one year. The first period (one year) is a period corresponding to the calendar.

  First, the input information acquisition unit 41 acquires the predicted value of the power sale price for each week, the predicted value of the waste heat generation amount for each week, and the predicted value of the amount of waste carried in each week. That is, in the present embodiment, the second period is set to one week. Here, each weekly forecast value means a weekly forecast value when one year is divided into 52 weeks. That is, the number of the three types of prediction values acquired by the input information acquisition unit 41 is 52 (52 × 3 = 156) from the prediction value of the first week to the prediction value of the 52nd week. As a result, for example, the predicted value of the selling price in the first week and the predicted value of the selling price in the second week may be different from each other.

  Furthermore, the input information acquisition unit 41 reads the constraint condition from the storage unit 33. The first optimization calculation unit 42 satisfies the read constraint conditions, and the first optimization calculation unit 42 is longer than the second period (one week) so as to maximize selling income of generated power for the first period (one year). A first optimization operation is performed to calculate the processing schedule amount for each of the three periods (January) (step S1). In the present embodiment, the first optimization operation unit 42 first satisfies the read constraint conditions, and maximizes the sale income of generated power during the first period (one year). Calculate the amount of planned processing every 2 periods (one week).

  The first optimization operation is calculated as a mixed integer non-linear programming problem. The first optimization operation unit 42 executes an operation using linear programming and an operation using metaheuristics in order to efficiently obtain a solution to this problem.

  Linear programming is a solution when the objective function and the constraints can be described in linear form. The solution obtained by linear programming has advantages such as being always a solution that optimizes the objective function and performing calculation at high speed. However, linear programming has the disadvantage that it is difficult to handle integers, which must all be expressed in linear form. In addition, in linear programming, there is also a disadvantage that the operation time increases exponentially as the number of variables increases.

  Meta-heuristics is a solution that aims to find better solutions in realistic time by heuristics. Meta-heuristics has the advantage of being able to obtain any solution regardless of the computation time. However, metaheuristics has the disadvantage that there is no guarantee that the obtained solution is the optimal solution, and since random search is performed, some computing time is required to obtain a better solution. is there.

  In the present embodiment, a solution close to the optimum solution can be obtained in a short time by performing the first optimization operation by combining these solutions. That is, the first optimization operation is performed by recursively performing an operation using linear programming and selecting an optimal result from among them. In the first optimization operation, an objective function for obtaining the monthly processing schedule amount is a formula for calculating operation income and can be described in a linear form. That is, the objective function in the first optimization operation is expressed by the following equation.

Here, Q1 represents the annual revenue from electricity sales (yen), _{q i} denotes the predicted value of the electricity sale price of each week (yen / kWh), _{W i,} the amount of power sold of each week (kWh) G _i indicates a weekly waste disposal amount (ton), and α _i and β _i indicate a performance index of the incineration plant 1 determined from the weekly waste heat value and temperature etc. . α _i and β _i may be determined in consideration of the performance of the incinerator 2 or the boiler 4, the steam supply to a heat utilization facility (not shown), the power consumption in the incineration plant 1, and the like. i is an index indicating each week in one year, i = 1, 2, ..., 52 (or 53). Accordingly, the number of variables to be determined in the first optimizing operation (waste quantity G _{i weekly)} becomes 52 (or 53).

  Further, among the constraint conditions, upper and lower limit values of incineration amount per unit time of incinerator 2, upper and lower limit values of capacity of storage tank 9, and upper limit value of continuous operation period of incinerator 2 are all in linear form. Can be described by Therefore, in the first optimization operation, the objective function for obtaining the monthly processing schedule and the above-mentioned one of the constraints are calculated by linear programming.

  On the other hand, since it is difficult to describe the stop period of the incinerator 2 or the generator 23 in the linear form among the constraint conditions, the stop period is calculated by a search based on metaheuristics.

As described above, the first optimization calculation unit 42 outputs the waste processing amount G _i every week (every i) that maximizes the annual power sale income Q1. The waste treatment amount G _i of each week, a plurality of processing plans amount divided weekly along the one year calendar.

  In the present embodiment, in the case where the first optimization calculation is performed on the incineration plant 1 provided with a plurality of (for example, two) incinerators 2, the first optimization operation unit 42 performs the second optimization operation. The plan of the operation / stop status of each incinerator 2 for each period (one week) is calculated. Among the above constraint conditions, the shutdown period of the incinerator 2 and the upper limit value of the continuous operation period of the incinerator 2 are individually set for each incinerator 2. Therefore, in consideration of these factors, the first optimization operation unit 42 performs operation in consideration of when to stop each incinerator 2 or how many units are to be stopped in order to maximize the annual power sale income Q. I do. The first optimization calculation unit 42 outputs a plan of the operation / stop status of each incinerator 2 on a weekly basis. In this way, it is possible to calculate a comprehensive waste disposal plan based on the operation plan of the plurality of incinerators 2.

  In addition, as a result of the first optimization calculation, the capacity of the storage tank 9 (the accumulated amount of waste) for each week is calculated and output.

  The amount of treatment plan for each week (for one year) calculated by the first optimization calculation unit 42 and the operation / stop status of each incinerator 2 for each week (for one year) are the second optimization It is used in the operation. In the present embodiment, before the second optimization calculation is performed, the first planned processing amount for each second period (one week) is converted into the first planned processing amount for each third period (January). The period conversion process is performed (step S1a).

  That is, in the first period conversion process, the first optimization calculation unit 42 adds up the scheduled processing amounts for each week on a monthly basis to calculate the scheduled processing amounts for each month. For example, the first optimization calculation unit 42 adds up the planned treatment quantities for each week from the first week to the fifth week to calculate the planned treatment quantity for January, and the fifth to ninth weeks Calculate the planned processing volume for February by adding the planned processing volume for each week. The waste disposal amount for each month calculated in this manner is a plurality of planned treatment amounts obtained by dividing a year into a month according to a calendar. The first optimization calculation unit 42 divides the planned processing volume for each week into days and divides them into January and February, or simply divides them into two in a week (fifth week) that spans the months. Processing may be performed to distribute between January and February.

  By performing such first period conversion processing, it is possible to output the processing plan amount for each desired period (that is, January) as an intermediate output, so one operation from the long-term plan to the medium-term plan and the short-term plan is performed. Can easily be formulated in the flow of

  Further, in the first period conversion processing, the first optimization calculation unit 42 divides the operation / stop status of each incinerator 2 every week into the operation / stop status of each incinerator 2 every day. Convert.

  The monthly processing plan amount calculated by the first optimization calculation unit 42 and the operation / stop status of each incinerator 2 for each day are temporarily stored in the storage unit 33. The second optimization calculation unit 43 performs a second optimization calculation on each of the monthly processing plan amounts calculated by the first optimization calculation unit 42.

  At the time of the second optimization calculation, the input information acquisition unit 41 acquires the monthly processing plan amount calculated by the first optimization calculation unit 42 and the operation / stop status of each incinerator 2 for each day, and The daily sales price forecast value, the daily waste heating value forecast value, and the daily waste import amount forecast value are acquired. That is, in the present embodiment, the fourth period is set to one day.

  Here, when the input information acquisition unit 41 acquires one of a plurality of monthly processing plan amounts, each forecast for each day for which the calendar corresponds to the month (for example, June) in the acquired one processing plan amount Get the value. That is, each of the processing plan amounts for each month output in the first optimization calculation is one of 12 periods obtained by dividing one year into each month, and has corresponding calendar information. For example, when the input information acquisition unit 41 acquires the processing plan amount for June output by the first optimization calculation for the second optimization calculation, the input information acquisition unit 41 combines the processing amount from June 1 to June. Each predicted value for each day up to 30 days (three predicted values for a total of 90 predicted values for 30 days) are acquired. By setting the input value according to the period (third period) in which the optimization operation is performed, the optimization operation can be performed based on a finer predicted value according to the season or the time zone.

  Furthermore, the input information acquisition unit 41 reads the constraint condition from the storage unit 33. The second optimization calculation unit 43 satisfies the read constraint conditions, and maximizes selling income of generated power in the fourth period (one day) shorter than the third period (January). A second optimization calculation is performed to calculate a processing schedule amount for each fourth period (one day) (step S2).

  In the second optimization calculation, the second optimization calculation unit 43 may perform calculation by omitting at least a part of the constraint conditions. More specifically, the second optimization calculation unit 43 may omit the stop period of the incinerator 2 or the generator and the upper limit value of the continuous operation period of the incinerator 2 among the constraint conditions. Regarding Constraint Conditions Considered in the First Optimization Operation In the second optimization operation, the influence on the stringency of the solution in the second optimization operation is small even if the constraint condition is not used. Therefore, by omitting such constraint conditions, it is possible to further reduce the amount of computation while maintaining high accuracy of the computation result.

  Similar to the first optimization operation, the second optimization operation is also computed as a mixed integer non-linear programming problem. Similar to the first optimization operation unit 42, the second optimization operation unit 43 executes an operation using linear programming and an operation using metaheuristics. That is, the second optimization operation unit 43 sets the year (first period) in the first optimization operation to month (third period) and week (second period) to day (fourth period). The same operation is performed except changing to. For example, the objective function in the second optimization operation is expressed by the following equation.

Here, Q2 indicates monthly power sale income (yen), q _j indicates daily sale price forecast value (yen / kWh), and W _j indicates daily power sale amount (kWh) , G _j indicate the daily waste processing amount (ton), and α _j and β _j indicate the performance index of the generator 23 determined from the daily heat generation amount of the waste and the temperature and the like. j is an index indicating each day of the input month, and j = 1, 2,..., J (J is the last day of the month). Therefore, the number of variables to be determined (the daily waste processing amount G _j ) in the second optimization calculation is J (any of 28 to 31).

As described above, the second optimization calculation unit 43 outputs the daily (every j) waste processing amount G _j that maximizes the power sale income Q 2 of the month. The daily waste disposal amount G _j obtained in this manner is output together with calendar information corresponding to the original one-year calendar information. Further, the second optimization calculation unit 43 outputs a plan of the operation / stop status in each incinerator 2 for each fourth period (one day). In addition, since the operation / stop condition in each incinerator 2 on a daily basis is calculated by the first period conversion process, the second optimization calculation unit 43 may not calculate this again. Furthermore, as a result of the second optimization operation, the daily capacity (the amount of accumulated waste) of the storage tank 9 is calculated and output. The second optimization calculation unit 43 performs the second optimization calculation every month for 12 months (12 times), so that the daily waste processing amount G _j in one year, the operation of each incinerator 2 / The planning of the shutdown situation and the daily capacity of the reservoir 9 are calculated.

  As described above, by using the calculation result in the first optimization calculation as an input to the second optimization calculation unit 43, daily processing without worrying about other months in the second optimization calculation The planned amount can be calculated.

  The daily processing plan amount calculated by the second optimization calculation unit 43 and the operation / stop status of each incinerator 2 for each day are temporarily stored in the storage unit 33. The third optimization calculation unit 43 performs the third optimization calculation on each of the daily processing plan amounts calculated by the second optimization calculation unit 43.

  At the time of the third optimization calculation, the input information acquisition unit 41 operates the daily treatment plan amount calculated by the second optimization calculation unit 43 and the operation of each incinerator 2 stored in the storage unit 33 for each day In addition to acquiring the stop status, the forecast value of the selling price for each hour is acquired. That is, in the present embodiment, the fifth period is set to one hour. Here, when the input information acquisition unit 41 acquires one of a plurality of planned processing amounts for each of a plurality of days, the input information acquisition unit 41 for each time when the calendar corresponds to a day (for example, June 1) in the acquired one planned processing amount. Get forecast value of selling price. That is, each of the daily processing plan amounts output in the second optimization calculation is one of 365 periods obtained by dividing a year into days, and has corresponding calendar information. For example, when the input information acquisition unit 41 acquires the processing plan amount for June 1 output by the second optimization calculation for the third optimization calculation, the input information acquisition unit 41 The forecast value (24 hours, ie, 24 forecast values) of the selling price every hour from 0 o'clock to 24 o'clock is acquired.

  Furthermore, the input information acquisition unit 41 reads the constraint condition from the storage unit 33. The third optimization operation unit 44 satisfies the read constraint conditions and maximizes selling income of generated power in the fifth period (one hour) shorter than the fourth period (one day). A third optimization calculation is performed to calculate a processing schedule amount for each fifth period (one hour) (step S3).

  The third optimization operation is also calculated in the same manner as the first optimization operation and the second optimization operation. However, in the third optimization operation, the third optimization operation unit 44 performs the operation while omitting at least a part of the constraint conditions. More specifically, the third optimization operation unit 44 performs an operation using the upper and lower limit values of the incineration amount per unit time of the incinerator 2 among the above-described constraint conditions as the constraint condition in the third optimization operation. . Regarding Constraint Conditions Considered in the First Optimization Operation and the Second Optimization Operation In the third optimization operation, the influence on the stringency of the solution in the third optimization operation is small even if the constraint condition is not set. Therefore, by omitting such constraint conditions, it is possible to further reduce the amount of computation while maintaining high accuracy of the computation result.

  Note that instead of omitting the above-described constraint conditions, constraint conditions on the operation procedure of the incinerator 2 may be added as constraint conditions in the third optimization calculation. For example, the third optimization operation requires at least 2 hours to start up (load up) or down (load down) the incinerator 2, and maintain the state for at least 3 hours after the load up, etc. You may add as a constraint condition in.

  As a result, the third optimization operation executes only the operation using linear programming. The objective function in the third optimization operation is expressed by the following equation.

Here, Q3 indicates the power sale income (yen) of the day, q _k indicates the forecast value of the power sale price per hour (yen / kWh), and W _k indicates the power sale amount per hour (kWh) G _k indicates the waste disposal amount (ton) per hour, and α _k and β _k indicate the performance index of the incineration plant 1 determined from the waste calorific value per hour and the air temperature etc. . k is an index indicating each time on the input day, and k = 1, 2,. Therefore, the number of variables to be determined in the third optimization operation (waste disposal amount G _k per hour) is 24.

As described above, the third optimization calculation unit 44 outputs the waste processing amount G _k for each time (every k) that maximizes the power sale income Q3 of the day. The third optimization calculation unit 44 performs the third optimization calculation for each day in December (J × 12 times), and calculates the hourly waste disposal amount G _k in one year. The waste disposal amount G _k for each time obtained in this manner is output together with calendar information corresponding to the original one-year calendar information.

  As described above, by using the calculation result in the second optimization calculation as an input to the third optimization calculation unit 44, it is possible to set the third optimization calculation every time without worrying about other days. The amount of processing plan can be calculated.

  FIG. 4 is a graph conceptually showing the result of the second optimization operation in the present embodiment. Note that this graph (including the graphs of FIG. 5A and FIG. 5B described later) is a conceptual graph for showing the tendency of the optimization calculation, and is not a graph showing an actual calculation result. FIG. 4 exemplifies a graph showing the amount of planned treatment in June. In the graph of FIG. 4, the horizontal axis is taken on a day (June 1 to June 30), and the forecast value of the selling price for each day is represented by a line graph of a two-dot chain line, And a daily processing plan amount, which is the second optimization calculation result, is represented by a bar graph.

  As shown in FIG. 4, the planned daily treatment volume obtained as a result of the second optimization operation decreases as the predicted daily selling price and / or the daily estimated waste heat generation value decreases. There is a tendency that as the predicted values become higher, they increase.

  FIGS. 5A and 5B are graphs conceptually showing the results of the third optimization calculation based on the daily processing schedule shown in FIG. The graph of FIG. 5A shows the result of the third optimization calculation based on the processing schedule amount of June 8 shown in FIG. 4, and the graph of FIG. 5B shows the processing schedule amount of June 13 shown in FIG. 8 shows the result of the third optimization operation based on

  In the graphs of FIGS. 5A and 5B, the horizontal axis represents time (from 0 o'clock to 24 o'clock), the predicted value of the sale price for each hour is represented by a line graph of a two-dot chain line, The amount of planned processing for each time is represented by a solid line graph. As shown in FIGS. 5A and 5B, the planned processing volume per hour obtained as a result of the third optimization operation is also smaller as the predicted value of the selling price per hour is lower, as in the graph of FIG. There is a tendency that the higher the predicted value, the more it becomes.

  However, the graph of FIG. 5A (graph of June 8) and the graph of FIG. 5B (graph of June 13) differ in the total amount of planned treatment for the day (that is, the length of the bar graph in FIG. 4). . Therefore, in the graph of FIG. 5B in which the amount of planned processing for each day is larger, the amount of planned processing for each time is a graph shifted upward as a whole compared with the graph of FIG. 5A. Thus, in the optimization calculation according to the present embodiment, when obtaining the amount of planned processing for each hour in each day in the third optimization calculation, the daily processing plan which is the calculation result of the second optimization calculation. Each value of quantity is used. For this reason, it is not necessary to consider the amount of planned processing on a day other than the day to be calculated in the third optimization calculation. This is also true for the relationship between the first optimization operation and the second optimization operation.

  As described above, according to the above aspect, the first period (one year) is divided into shorter second periods (every week), and the third period (January) unit shorter than the first period is used. After the optimization operation is performed, the third period is further divided into shorter fourth periods (every day), and the optimization operation is performed in units of the fifth period (one hour) in which the fourth period is further shorter. It will be. Therefore, the number of divisions of the period can be reduced in each optimization operation, and the number of variables to be determined in one optimization operation can be reduced. Therefore, the calculation time in each optimization calculation can be shortened, and as a result, the calculation time for calculating the processing schedule amount for each fifth period for the first period can be suppressed to a realistic time.

  From the above, it is possible to automatically calculate a waste disposal plan that maximizes the power sale income in a short calculation time, regardless of the experience or intuition of the operator. Further, by performing the first to third optimization operations, the amount of operations in each stage can be reduced by dividing the period into multiple stages.

  In addition, since the planned treatment volume is output independently for each period unit (every month, every day, every hour), the waste disposal amount deviates from the initial waste disposal plan in actual operation. Also, local recalculation can be easily performed. For example, although the incineration plant 1 was operated based on the yearly waste treatment plan calculated in advance from January, the difference between the planned treatment amount and the actual treatment amount at the time of March is a predetermined amount or more In the event of a failure, the April waste treatment plan (the second optimization operation and the third optimization operation) can be recalculated to eliminate or reduce the difference. In this way, partial plans (medium-term plans, short-term plans) in the long-term plans can be easily recalculated (corrected), so partial corrections can be made to return to the initial treatment plan. Furthermore, the period of the processing schedule amount output by each optimization operation in the present embodiment is subdivided into month (week), day, and time, so that local recalculation can be performed in a more preferable period unit. Can be done with

  In the above embodiment, the prediction values for each period unit input to the optimization calculation units 42 to 44 may use independent prediction values. Instead of this, second and third period conversion processing is performed to calculate the predicted value for each longer period unit using the predicted value for each shorter period unit, and the calculated predicted value for each calculated period unit is supported. May be input to the optimization calculation units 42 to 43.

  For example, as shown in FIG. 3, the second optimization calculation unit 43 may use the fourth forecast value of the sale price every fifth period (one hour) input to the third optimization calculation unit 44. A second period conversion process is performed to convert into a predicted value of the sale price every period (one day) of (step S2a). In this case, the second optimization calculation unit 43 calculates the forecast value of the power sale price for each day by adding up the forecast values of the power sale price for each hour for one day and taking the average.

  In addition, the first optimization calculation unit 42 predicts the sale price for each fourth period (one day) input to the second optimization calculation unit 43, the predicted value of the heat generation amount of the waste, and discards it. A third period conversion process of converting the predicted value of the carried-in amount into each predicted value for each second period (one week) is executed (step S1b). In this case, the first optimization calculation unit 42 sums up the forecast value of the selling price every day and the forecasting value of the waste heat value for one week, and takes the average to forecast the selling price every week. Calculate the value and the predicted value of waste heat value. Further, the first optimization calculation unit 42 adds up the predicted value of the daily amount of waste carried in for one week, and calculates the predicted value of the weekly amount of waste carried in.

  Thus, the amount of input data can be reduced by calculating part of the input values input to the optimization calculation units 42 to 44 from the input values in a shorter period by calculation.

  As mentioned above, although embodiment of this invention was described, this invention is not limited to the said embodiment, A various improvement, change, and correction are possible within the range which does not deviate from the meaning.

  For example, in the above embodiment, the incineration plant 1 having the stoker-type incinerator 2 is illustrated as a target of the waste treatment plan calculation, but the steam generated when the waste is incinerated in the incinerator is used If it is the incineration plant provided with the generator which performs electric power generation, it will not be restricted to this. For example, it is also possible to apply the waste disposal plan calculation method of the present invention to an incineration plant having a fluidized bed incinerator.

  Moreover, the objective function in the said embodiment and a constraint condition are illustrations, and are not limited above. The objective function may be changed, or parameters may be added as appropriate. For example, the objective function may be a profit obtained by subtracting the running cost of the incineration plant 1 from the power sale income. The running cost includes, for example, the consumption cost of the facility utility such as fly ash processing chemical, slaked lime, activated carbon, and the cost for starting or stopping the incinerator 2. For example, if the number of start-up or shut-down times of the incinerator 2 is different even if the power sale income is the same, a difference occurs in the profit obtained. For this reason, it is possible to make the obtained profit higher by performing the optimization calculation in which not only the selling income but also the running cost are simultaneously considered.

  Further, as the constraint conditions, part of the above-described constraint conditions may be used as the constraint condition, or constraint conditions other than the above may be added.

  Further, in the above embodiment, as each predicted value input to the first to third optimization calculation units 42 to 44, a value corresponding to the calendar of the planned processing amount to be calculated is used. It is not limited. For example, it is good also as a predicted value which inputs a fixed value irrespective of corresponding period, such as an average value in each predicted value.

  In the above embodiment, the first period is one year, the second period is one week, the third period is January, the fourth period is one day, and the fifth period is one hour. However, the present invention is not limited to this, and each period can be set variously. For example, the first period is set to a period of 1 year or more, the second period and the third period are set to a period of 1 week or more and less than the first period, and the fourth period is A period of one day or more and less than the third period may be set, and the fifth period may be set to a period of one hour or more and less than the fourth period.

  Further, in the above embodiment, the process planning amount for each second period (one week) calculated by the first optimization calculation is changed to the process planning amount for each third period (January) Although the period conversion process of 1 is performed and the aspect which makes the processing plan amount for every said 2nd period the input of 2nd optimization calculation was illustrated, it is not restricted to this. For example, the planned processing volume for each second period calculated by the first optimization calculation may be used as the input of the second optimization calculation as it is. That is, the third period may be the same as the second period.

  In the above embodiment, the first to third optimization calculations (three-stage optimization calculations) are illustrated. However, two-step optimization calculations (first optimization calculation and second calculation) are described. The optimization operation of 4) or the optimization operation of four or more stages (the fourth and subsequent optimization operations) may be performed.

  For example, FIG. 6 is a schematic view showing a flow of optimization calculation processing in a modification of the present embodiment. The present modified example is different from the above-described embodiment (example in FIG. 3) in that it calculates a process planning amount for each hour in a year by performing a two-stage optimization operation. That is, the first optimization calculation unit 42 receives the predicted value of the power sale price on a daily basis, the predicted value of the calorific value of waste on a daily basis, and the predicted value of the amount of waste carried in on a daily basis. A first optimization operation is performed to output a daily planned amount of processing so as to satisfy the constraint conditions and maximize the power sales revenue of the generated power in one year using the constraint conditions. That is, in the present variation, the first period is one year, and the second and third periods are one day.

  Further, the second optimization calculation unit 43 inputs the predicted value of the sale price per hour for each of the planned processing amounts for each day, and satisfies the constraint conditions using the above constraint conditions, and A second optimization operation is performed to output a planned amount of processing per hour so as to maximize the sale of power generation on a daily basis. That is, in the present modification, the fourth period is one hour.

  Also in this modification, the number of variables to be determined in each optimization operation can be reduced. Therefore, the calculation time in each optimization calculation can be shortened, and as a result, it is possible to suppress the time to calculate the processing schedule amount for one hour for one year to a realistic time.

  In the present modification, as in the above embodiment, a part of the constraint conditions when performing the second optimization operation can be omitted. In the present modification, the constraint condition for performing the second optimization calculation is only the upper and lower limit values of the incineration amount per unit time of the incinerator. Thus, as in the third optimization calculation in the above-described embodiment, it is possible to further reduce the calculation amount and calculation time in the second optimization calculation of this modification.

  The present invention provides a waste disposal plan computing method and waste disposal plan computing device capable of automatically calculating a waste disposal plan that maximizes power sale revenue in an incineration plant in a short computing time. Useful for

DESCRIPTION OF SYMBOLS 1 incineration plant 2 incinerator 9 storage tank 23 generator 31 waste disposal plan calculation apparatus 42 1st optimization calculating part 43 2nd optimization calculating part 44 3rd optimization calculating part

Claims (9)

Waste treatment in an incineration plant equipped with an incinerator for incinerating waste, and a generator for generating electricity using steam generated by exhaust heat generated when incineration treatment of waste in the incinerator It is a plan calculation method, and
Forecast value of selling price of generated power for every second period shorter than the first period, predicted value of calorific value of waste, and predicted value of the amount of waste carried in, and operation of the incineration plant Output a planned amount of waste processing for each third period shorter than the first period so as to satisfy performance constraints and maximize sales revenue of generated power in the first period. Performing a first optimization operation,
At least input of the planned processing amount for each of the third period and the predicted value of the selling price of the generated power for each of the fourth period shorter than the third period, and satisfying the constraint, and Performing a second optimization operation to output a planned amount of waste processing for each of the fourth periods so as to maximize the sale of power generation power in the third period. Object processing plan calculation method.   The planned processing amount for each fourth period and the predicted value of the selling price of the generated power for each fifth period shorter than the fourth period are input, and the constraint condition is satisfied, and The discard according to claim 1, further comprising the step of: performing a third optimization operation to output a planned amount of processing for each of the fifth periods so as to maximize the sale of power generation power in the four periods. Object processing plan calculation method. The first period is a period of one year or more,
The second period and the third period are periods of one week or more and less than the first period, respectively.
The fourth period is a period of one day or more and less than the third period,
The waste disposal plan computing method according to claim 2, wherein the fifth period is a period of one hour or more and less than the fourth period.   The waste disposal plan operation method according to claim 2 or 3, wherein at least a part of the constraint condition is omitted in the third optimization operation. The third period is a period longer than the second period,
In the first optimization operation,
Calculating a planned amount of processing for each of the second periods so as to satisfy the constraint conditions and maximize the sale of power generation power in the first period;
The waste treatment plan computing method according to any one of claims 1 to 4, wherein the planned treatment quantity for each third period is output based on the calculated treatment plan amount for each second period.   The constraint conditions include upper and lower limit values of incineration amount per unit time of the incinerator, upper and lower limit values of capacity of a storage tank for temporarily storing wastes to be input to the incinerator, the incinerator or the power generation The waste disposal plan operation method according to any one of claims 1 to 5, including at least one of an outage period of a machine and an upper limit value of a continuous operation period of the incinerator. The incineration plant has a plurality of incinerators,
The waste disposal plan operation method according to any one of claims 1 to 6, wherein in the first optimization operation, an operation / stop status in each incinerator for each of the third periods is calculated. The first period corresponds to a calendar, and
The second period, the third period, and the fourth period are one of a plurality of periods in which the first period is divided by a predetermined number of each.
The waste disposal plan operation method according to any one of claims 1 to 7, wherein each of the plurality of divided periods has calendar information corresponding to the first period. Waste treatment in an incineration plant equipped with an incinerator for incinerating waste, and a generator for generating electricity using steam generated by exhaust heat generated when incineration treatment of waste in the incinerator A plan computing device,
The predicted value of the selling price of the generated power for each second period shorter than the first period, the predicted value of the calorific value of waste, and the predicted value of the amount of waste carried in are input, and the operation of the incineration plant is performed Outputting a processing planning quantity for each third period shorter than the first period so as to satisfy performance constraints and maximize sales revenue of generated power in the first period; Optimization operation unit of
At least input of the planned processing amount for each of the third period and the predicted value of the selling price of the generated power for each of the fourth period shorter than the third period, and satisfying the constraint, and Waste treatment plan calculation, comprising: a second optimization calculation unit that outputs a planned treatment quantity for each of the fourth periods so as to maximize sales of power generation power in the third period; apparatus.

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