Real-time power supply and coal cost calculation method and system applicable to coal loading in different warehouses and time periods

Abstract

The present invention discloses a method and system for calculating the real-time coal cost for power supply that is suitable for loading coal in different warehouses and time periods, including: obtaining data information on incoming coal from each coal mine and performing data fusion to calculate the weighted price of coal stored at each coal unloading point every day; obtaining the amount of added coal in each raw coal warehouse and each time period and the source of added coal through the fuel management and control system to form a coal queue structure; comparing and matching the coal queue structure with the real-time coal feeding amount of each coal feeder to achieve dynamic maintenance of the queue and obtain the coal price used by each coal feeder at the current moment; considering the benchmark on-grid electricity price and deep adjustment compensation electricity price, calculating the coal cost and power supply income. The method of the present invention can adapt to the real-time calculation of the coal cost for power supply under the current production strategy of loading coal in different warehouses and time periods in most power plants. The data is real-time and dynamic, reflecting the real-time production status. The calculation results can be flexibly set according to user requirements to issue statistical results in the load segment, and the statistical dimension accuracy is higher.

Description

Technical Field

[0001] The present invention relates to the technical field of coal management, and in particular to a real-time power supply and coal cost calculation method and system applicable to coal loading in separate compartments and time periods. Background Art

[0002] Currently, there are two main common methods. One is to calculate the annual and monthly average fuel costs for the plant based on annual and monthly fuel expenses and power supply statistics, using this average fuel cost as a proxy for the real-time fuel cost. The other is to conduct field experiments to obtain coal cost data for several typical operating points. Based on the data from these operating points, curves are fitted to infer data for other operating points. This method is relatively expensive and infrequent. It uses the external environmental data from the experiment to replace the annual environmental data, the coal quality data from the experiment to replace the annual coal quality data, and the coal loading and blending schemes and equipment wear from the experiment to replace the annual data.

[0003] With rising coal prices, many power plants are implementing coal blending. Under the production strategies of separate bunkers and time slots for coal loading, these two power generation cost accounting methods exhibit significant lags and static nature. To obtain more accurate real-time data to support production decisions, new statistical accounting methods and systems are urgently needed. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is that the existing statistical accounting method is difficult to provide reliable data support for power market bidding.

[0006] To solve the above technical problems, the present invention provides the following technical solution: a method for calculating the real-time power supply and coal burning cost applicable to coal loading in different warehouses and time periods, comprising:

[0007] Obtain coal data from each coal mine, perform data fusion, and calculate the weighted price of coal stored at each coal unloading point every day;

[0008] The fuel control system obtains the amount of coal added to each raw coal bin and each time period, as well as the source of the added coal, to form a coal queue structure;

[0009] Compare and match the coal queue structure with the real-time coal supply of each coal feeder to achieve dynamic maintenance of the queue and obtain the coal price used by each coal feeder at the current moment;

[0010] Taking into account the benchmark on-grid electricity price and deep adjustment compensation electricity price, calculate the coal-fired power supply cost and power supply revenue.

[0011] As a preferred solution of the method for calculating the real-time power supply and coal cost for coal loading in different warehouses and time periods according to the present invention, the coal data information of each coal mine includes price, quantity, coal unloading, real-time coal supply, and power supply; data is extracted from the fuel management and control system, and the coal price of each coal mine is calculated. Coal supply to each coal mine Coal unloading information, including the coal inventory at each unloading point and the daily unload volume i ;Record the weighted price of coal at each unloading point every day

[0012] Record the weighted price of coal at each coal unloading point on the previous day Record the amount of coal stored at each unloading point the previous day

[0013] As a preferred solution of the real-time power supply and coal burning cost calculation method applicable to the coal loading in different warehouses and time periods described in the present invention, the calculation of the weighted price of coal stored at each coal unloading point every day includes calculating the daily weighted price, combining the price and quantity of the coal unloading point on the previous day, and calculating the weighted price of the day; if multiple types of coal are unloaded to the same coal unloading point on the same day, it is necessary to consider the quantity and price of each type of coal and calculate the total coal unloading amount of each coal unloading point on the same day. and total price The formula is:

[0014]

[0015]

[0016] Calculate the weighted price of each coal unloading point on the day. The formula is:

[0017]

[0018] in, represents the weighted price of coal unloading point i today; represents the weighted price of coal unloading point i yesterday; It represents the total coal storage quantity of unloading point i yesterday; represents the weight of coal type m unloaded to unloading point i today; It represents the price of coal type m today; M represents the number of coal types unloaded today.

[0019] As a preferred solution of the real-time power supply and coal burning cost calculation method applicable to coal loading in different warehouses and time periods according to the present invention, the data fusion includes determining the location and type of sensors and evaluating their measurement accuracy and coverage;

[0020] Install sensors in their intended locations to ensure their stability and data transmission reliability; calibrate newly installed sensors and perform initial calibration to ensure the accuracy of sensor data; recalibrate regularly to integrate new sensor data into the existing data acquisition system:

[0021] Use data fusion algorithms to pre-process multi-source data, remove outliers and noise, and ensure data accuracy; use the fused data to optimize the calculation model for power supply and coal burning costs;

[0022] The coal flow data integration formula is expressed as:

[0023]

[0024] in, represents the coal feed rate of the sth sensor at time t;

[0025] The coal bunker height data integration formula is expressed as:

[0026]

[0027] in, represents the height of the c-th coal bunker at time t, and N is the number of sensors.

[0028] As a preferred embodiment of the method for calculating the real-time power supply and coal cost applicable to the coal loading by bin and time period of the present invention, the method of forming a coal queue structure includes obtaining data on the amount of coal added by each raw coal bin and each time period, and the source of the coal added, through a fuel management and control system, to construct an initial queue structure;

[0029] The coal-fired queue structure can be represented as an ordered set of triples, where each triple contains the time t i 、Coal source S i and the amount of increase in position W i :

[0030] Queue={(t1, S1, W1), (t2, S2, W2),..., (t n , S n , W n )}

[0031] Dynamic maintenance of queue structure

[0032] Get the real-time coal feeding amount. The real-time cumulative coal feeding amount of the coal machine at time t is expressed as:

[0033]

[0034] in, Represents the instantaneous coal flow rate of coal feeder i at time t′.

[0035] As a preferred solution of the method for calculating the real-time power supply and coal burning cost applicable to the coal feeding in different warehouses and time periods described in the present invention, the dynamic maintenance of the queue includes: Update the queue structure:

[0036] Determine the coal batch to be consumed, initially starting from the first batch in the queue. Once consumed, move on to the next batch.

[0037] Update the batch remaining quantity, and set the real-time cumulative coal feeding quantity of coal feeder i at time t If it is greater than the remaining amount W1 of the current batch, the formula for updating the queue structure is expressed as:

[0038]

[0039] like The coal-fired queue structure is expressed as:

[0040] Queue={(t2,S2,W2),...(t n S n ,W n )}

[0041] Otherwise, the increase in position amount is updated as:

[0042]

[0043] The update queue structure is represented as:

[0044]

[0045] in, represents the remaining amount of the updated batch i of coal; represents the remaining amount of the i-th batch of coal before updating; represents the real-time cumulative coal feeding amount of coal feeder i at time t; represents the remaining coal supply of coal feeder i after consuming the current batch of coal at time t;

[0046] Based on the real-time coal supply, determine the currently consumed coal batch k;

[0047]

[0048] in, represents the weighted average coal price of coal feeder i at time t; represents the price of the jth batch of coal in the queue; represents the amount of coal used by coal feeder i at time t in the jth batch;

[0049] Reinforcement learning optimization, defining states and actions, state s tIndicates the coal queue structure and coal supply at the current moment; action a t Indicates the coal batch selected for consumption;

[0050] The reward function formula is expressed as:

[0051] r t =-C fuel (t)+λ×Ef(t)-μ×EI(t)

[0052] The optimization objective formula is expressed as:

[0053]

[0054] Perform genetic algorithm optimization and define the fitness function

[0055] f(x)=-C fuel (t)+λ×Ef(t)-μ×EI(t)

[0056] Among them, π represents the strategy; * represents the optimal strategy γ represents the discount factor, which ranges from [0,1]; C fuel (t) represents the coal burning cost at time t; Ef(t) represents the equipment operating efficiency at time t; EI(t) represents the environmental impact at time t; λ represents the weight coefficient of efficiency; μ: the weight coefficient of environmental impact;

[0057] Randomly generate the initial population, each individual represents a possible coal queue usage strategy; evaluate the fitness of each individual, using the fitness function;

[0058] Based on the selection probability, individuals are selected from the current population for reproduction; two parent individuals are selected and crossover operation is performed to generate offspring individuals; offspring individuals are mutated according to the mutation rate to generate new individuals; some or all parent individuals are replaced with offspring individuals to form a new population; and iteration is repeated until the maximum number of iterations is reached.

[0059] As a preferred solution of the method for calculating the real-time power supply coal cost applicable to coal loading in different compartments and time periods according to the present invention, the calculation of the power supply coal cost and power supply income includes taking into account the coal consumption and coal price of each coal feeder;

[0060]

[0061] Among them, C fuel (t) represents the coal cost in the current period; represents the cumulative coal supply of coal feeder i at time t; represents the coal price of coal feeder i at time t; represents the cumulative power generation of generator set j at time t.

[0062] A real-time power supply and coal burning cost calculation system for coal loading in different warehouses and time periods, using any method described in the present invention, comprising:

[0063] The data collection module obtains coal data from each coal mine, performs data fusion, and calculates the weighted price of coal stored at each coal unloading point every day;

[0064] The coal queue structure module obtains the amount and source of coal added in each raw coal bin and each time period through the fuel control system to form a coal queue structure;

[0065] The dynamic queue maintenance module compares and matches the coal queue structure with the real-time coal supply of each coal feeder to achieve dynamic queue maintenance;

[0066] The cost calculation module takes into account the benchmark electricity price and deep adjustment compensation electricity price to calculate the coal-fired power supply cost and power supply revenue.

[0067] A computer device comprises: a memory and a processor; the memory stores a computer program, wherein the processor implements the steps of any one of the methods of the present invention when executing the computer program.

[0068] A computer-readable storage medium stores a computer program thereon, wherein the computer program, when executed by a processor, implements the steps of any one of the methods of the present invention.

[0069] The beneficial effects of the present invention are as follows: it can adapt to the real-time calculation of the cost of coal for power supply under the current coal loading strategy of most power plants in different warehouses and time periods. It provides reliable data support for bidding in the electricity spot market. The data is real-time and dynamic, reflecting the real-time production status, avoiding the lag of manual statistics and the static nature of experimental data. The calculation results can be flexibly set according to user requirements to produce statistical results in load segments, and the statistical dimension has higher accuracy. Taking into account the short-cycle bidding characteristics of the electricity spot market, from the perspective of real-time demand for quotations, a set of methods and systems for real-time calculation of the cost of coal for power supply has been constructed, which breaks through the lagging status of cost management in terms of timeliness, transforms the traditional ex post mode of cost management into a new real-time model, and realizes cost forecasting and feedback more accurately and timely. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. Those skilled in the art can also derive other drawings based on these drawings without inventive effort. Among them:

[0071] Figure 1 This is an overall flow chart of a method for calculating the real-time power supply and coal burning cost for loading coal in different compartments and time periods, provided by the first embodiment of the present invention;

[0072] Figure 2 A diagram of an on-site coal storage module for a real-time coal power supply and combustion cost calculation method applicable to coal loading in different warehouses and time periods, provided in the first embodiment of the present invention;

[0073] Figure 3 A diagram of an actual data module for adding coal to a warehouse in accordance with a first embodiment of the present invention, showing a method for calculating the cost of coal for power supply and combustion by using a method for calculating the cost of coal for supplying coal by warehouse and time period;

[0074] Figure 4 A profitability graph for each load segment of a real-time power supply and coal burning cost calculation method for loading coal in different compartments and time periods, provided in accordance with the second embodiment of the present invention. DETAILED DESCRIPTION

[0075] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0076] Example 1

[0077] Reference Figure 1 , which is an embodiment of the present invention, provides a real-time coal cost calculation method for power supply applicable to coal loading in different warehouses and time periods, including:

[0078] S1: Obtain the coal data information of each coal mine for data fusion, calculate the weighted price of coal stored at each coal unloading point every day, and collect the platform parameters of the cloud service end.

[0079] Furthermore, the coal data information of each coal mine includes price, quantity, coal unloading, real-time coal supply, and power supply; data is extracted from the fuel control system, and the coal price of each coal mine is Coal supply to each coal mine Coal unloading information, including coal inventory and daily unloading volume at each unloading point Record the weighted price of coal at each unloading point every day

[0080] Furthermore, the weighted coal price of each coal unloading point on the previous day is recorded. Record the amount of coal stored at each unloading point the previous day

[0081] Furthermore, we will increase the number and accuracy of sensors. We will evaluate the existing sensor network and determine the specific locations and types of sensors that need to be added, such as coal bunker height sensors and coal feeder real-time flow sensors. We will purchase and install high-precision sensors to ensure they can accurately measure the required data. We will calibrate the newly installed sensors to ensure data accuracy and consistency. We will also integrate the new sensor data into the existing data collection system to ensure real-time data synchronization and updates.

[0082] Furthermore, the formula expresses:

[0083]

[0084] in, represents the coal feed rate of the sth sensor at time t; represents the height of the c-th coal bunker at time t, and N is the number of sensors.

[0085] Furthermore, if Figure 2 As shown, the calculation of the weighted price of coal stored at each coal unloading point every day includes calculating the daily weighted price, combining the price and quantity of the coal unloading point on the previous day to calculate the weighted price of the day; if multiple types of coal are unloaded to the same coal unloading point on the same day, it is necessary to consider the quantity and price of each type of coal and calculate the total coal unloading quantity of each coal unloading point on the same day. and total price The formula is:

[0086]

[0087] Furthermore, the weighted price of each coal unloading point on the day is calculated using the formula:

[0088]

[0089] in, represents the weighted price of coal unloading point i today; represents the weighted price of coal unloading point i yesterday; It represents the total coal storage quantity of unloading point i yesterday; represents the weight of coal type m unloaded to unloading point i today; It represents the price of coal type m today; M represents the number of coal types unloaded today.

[0090] It should be noted that by analyzing daily coal arrival and unloading data, and obtaining the weighted price of coal for each unloading and ignition, and by matching the quantity and source of coal added to each raw coal bunker, the coal queue structure of each raw coal bunker is determined. Combined with real-time data on coal feeder delivery and the amount of electricity generated by the unit, the unit's coal power supply costs are calculated in real time. Furthermore, the power supply revenue can be calculated by combining the benchmark on-grid electricity price and deep-slope adjustment compensation price.

[0091] S2: Obtain the added coal quantity and source of each raw coal bin and each time period through the fuel control system to form a coal queue structure.

[0092] Furthermore, the data fusion includes determining the location and type of sensors and evaluating their measurement accuracy and coverage.

[0093] Furthermore, the location and type of sensors that need to be added are determined to enhance the coal bunker height and coal feeder real-time flow.

[0094] Furthermore, install sensors in predetermined locations to ensure their stability and reliability of data transmission; calibrate newly installed sensors and perform initial calibration to ensure the accuracy of sensor data; recalibrate regularly to ensure the accuracy and consistency of sensors after long-term use; and integrate new sensor data into existing data acquisition systems.

[0095] Furthermore, the data sources that need to be integrated, such as meteorological data and coal quality data, are determined; data interfaces are established to ensure that data from different data sources can be transmitted and integrated in real time.

[0096] Furthermore, data fusion algorithms are used to pre-process multi-source data, remove outliers and noise, and ensure data accuracy.

[0097] Furthermore, the fused data is used to optimize the calculation model of coal-fired power supply costs.

[0098] Furthermore, the coal flow rate data integration formula is expressed as:

[0099]

[0100] in, Represents the coal feed rate of the sth sensor at time t.

[0101] Furthermore, the coal bunker height data integration formula is expressed as:

[0102]

[0103] in, represents the height of the c-th coal bunker at time t, and N is the number of sensors.

[0104] It should be noted that the raw coal bunker (each unit is equipped with multiple units) is an intermediate storage device for coal before it enters the coal feeder. After the coal enters the raw coal bunker, it follows the first-in-first-out principle and is naturally stratified to form a queue structure. Because coal prices are currently high, most power plants are implementing a production strategy of loading coal in different bunkers and time periods according to their power generation plans in order to reduce production costs. Therefore, the coal structure and price in different raw coal bunkers are different; the coal structure and price in the same coal bunker are also different in different time periods. The fuel management and control system obtains the amount of coal added in each raw coal bunker and each time period, as well as the source of the added coal (which unloading point the coal comes from), to form a coal queue structure.

[0105] S3: Compare and match the coal queue structure with the real-time coal supply of each coal feeder to achieve dynamic maintenance of the queue and obtain the coal price used by each coal feeder at the current moment.

[0106] Furthermore, the formation of the coal-fired queue structure includes obtaining data on the amount of coal added to each raw coal bin and each time period, and the source of the coal added, through the fuel control system, such as Figure 3 As shown, build the initial queue structure.

[0107] Furthermore, the coal queue structure can be represented as an ordered set of triples, where each triple contains the time t i 、Coal source S i and the amount of increase in position W i .

[0108] Queue={(t1, S1, W1), (t2, S2, W2),..., (t n , S n , W n )}

[0109] Furthermore, the dynamic maintenance of the queue structure can obtain the real-time coal feeding amount. The real-time cumulative coal feeding amount of the coal machine at time t is expressed as:

[0110]

[0111] in, Represents the instantaneous coal flow rate of coal feeder i at time t′.

[0112] Furthermore, the dynamic maintenance of the queue includes: Update the queue structure.

[0113] Furthermore, the coal batches to be consumed are determined, and consumption starts initially from the first batch in the queue. If consumption is completed, it is transferred to the next batch.

[0114] Furthermore, to update the batch remaining quantity, let the real-time cumulative coal feeding quantity of coal feeder i at time t be If it is greater than the remaining amount W1 of the current batch, the formula for updating the queue structure is expressed as:

[0115]

[0116] Furthermore, if The coal-fired queue structure is expressed as:

[0117] Queue={(t2, S2, W2), ..., (t n ,S n ,W n )}

[0118] Furthermore, otherwise the increase in position amount is updated as:

[0119]

[0120] Furthermore, the update queue structure is represented as:

[0121]

[0122] in, represents the remaining amount of the updated batch i of coal; represents the remaining amount of the i-th batch of coal before updating; represents the real-time cumulative coal feeding amount of coal feeder i at time t; It represents the remaining coal supply of coal feeder i after consuming the current batch of coal at time t;.

[0123] Furthermore, based on the real-time coal supply, the currently consumed coal batch k is determined.

[0124]

[0125] in, represents the weighted average coal price of coal feeder i at time t; represents the price of the jth batch of coal in the queue; It represents the amount of coal used by coal feeder i at time t in the jth batch.

[0126] Furthermore, reinforcement learning optimization defines states and actions, and states s t Indicates the coal queue structure and coal supply at the current moment; action a t Indicates the coal batch selected for consumption.

[0127] Furthermore, the reward function formula is expressed as:

[0128] r t =-C fuel (t)+λ×Ef(t)-u×EI(t)

[0129] Furthermore, the optimization objective formula is expressed as:

[0130]

[0131] Going further, perform genetic algorithm optimization and define the fitness function:

[0132] f(x)=-C fuel (t)+λ×Ef(t)-μ×El(t)

[0133] Among them, π represents the strategy; * represents the optimal strategy γ represents the discount factor, which ranges from [0,1]; C fuel (t) represents the coal burning cost at time t; Ef(t) represents the equipment operating efficiency at time t; EI(t) represents the environmental impact at time t; λ represents the weight coefficient of efficiency; μ: the weight coefficient of environmental impact.

[0134] It should be noted that the initial population is randomly generated, and each individual represents a possible coal queue usage strategy; the fitness of each individual is evaluated and calculated using the fitness function; based on the selection probability, individuals are selected from the current population for reproduction; two parent individuals are selected and a crossover operation is performed to generate offspring individuals; the offspring individuals are mutated according to the mutation rate to generate new individuals; some or all parent individuals are replaced with offspring individuals to form a new population; and the iteration is repeated until the maximum number of iterations is reached.

[0135] S4: Considering the benchmark on-grid electricity price and deep adjustment compensation electricity price, calculate the coal-fired power supply cost and power supply revenue.

[0136] Furthermore, the calculation of the power supply coal cost and power supply income includes that the coal cost calculation needs to take into account the coal consumption and coal price of each coal feeder.

[0137]

[0138] Furthermore, C fuel (t) represents the coal cost in the current period; represents the cumulative coal supply of coal feeder i at time t; represents the coal price of coal feeder i at time t; represents the cumulative power generation of generator set j at time t.

[0139] It should be noted that the system calculates the coal consumption of each coal feeder every minute and gradually deducts this consumption from the coal queue structure until the current batch of raw coal is consumed. Once the current batch of raw coal is consumed, the system automatically switches to the price of the next batch of raw coal. This step is consistent with the current production strategy of loading coal in different bins and time periods. It is significantly different from the model algorithm that assumes that all raw coal bins (coal feeders) use the same coal, and it is also significantly different from the model algorithm that assumes that a coal feeder uses the same type of coal throughout the day. Because each coal feeder may start and stop at any time according to production scheduling, the queue structure must be dynamically mapped based on actual start and stop consumption.

[0140] On the other hand, this embodiment also provides a real-time power supply and coal cost calculation system applicable to coal loading in different warehouses and time periods, which includes:

[0141] The data collection module obtains the coal data information of each coal mine, performs data fusion, and calculates the weighted price of coal stored at each coal unloading point every day.

[0142] The coal-fired queue structure module obtains the added coal quantity and source of each raw coal bin and each time period through the fuel management and control system to form a coal-fired queue structure.

[0143] The queue dynamic maintenance module compares and matches the coal-fired queue structure with the real-time coal supply of each coal feeder to achieve dynamic maintenance of the queue.

[0144] The cost calculation module takes into account the benchmark electricity price and deep adjustment compensation electricity price to calculate the coal-fired power supply cost and power supply revenue.

[0145] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0146] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0147] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0148] It should be understood that various parts of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0149] Example 2, reference Figure 4 This is an embodiment of the present invention, which provides a real-time power supply and coal burning cost calculation method suitable for coal loading in different warehouses and time periods. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0150] Assuming that 100 tons of coal are added to coal bunker A at time t1-t2, and 200 tons are added at time t3-t4, and the coal level in coal bunker A is 11 meters at time t1, it is estimated that the coal stored in coal bunker A at time t1 is 110+(11-8)×50=260 tons (the estimation method provided by the owner is 110 tons for coal levels below 8 meters and 50 tons for every meter above 8 meters). According to the cumulative coal volume of the coal feeder, when coal feeder A consumes 260 tons of coal, the coal used at this time is the coal added at time t1-t2.

[0151] Known conditions (provided by each factory based on their actual situation): benchmark electricity price 0.42 yuan / kWh, deep adjustment quotation_first tier 0.16 yuan / kWh, deep adjustment quotation_second tier 0.375 yuan / kWh, fixed cost of power generation yuan / kWh.

[0152] The coal cost for power generation (yuan / MWh) for the current time period has been calculated by the system in the previous step. Paid peak-shaving electricity is the ungenerated electricity generated when the average load factor of a thermal power plant within each paid peak-shaving interval is lower than the paid peak-shaving benchmark. Currently, deep peak-shaving is generally divided into two tiers: 30%-40% of rated load and 40%-50% of rated load. Loads above 50% are not compensated for deep peak-shaving.

[0153] When the average load is ≥50% of the rated load, the profit = benchmark electricity price * 1000 - power generation coal cost - power generation fixed cost * 1000

[0154] When 40% rated load ≤ average load < 50% rated load, profit = (benchmark electricity price * 1000 * average load + (50% rated load - average load) * deep adjustment quotation_first tier * 1000) / average load - power generation coal cost - power generation fixed cost * 1000

[0155] When the average load is less than 40% of the rated load, the profit = (benchmark electricity price * 1000 * average load + (50% rated load - 40% rated load) * deep adjustment quotation_first tier * 1000 + (40% rated load - average load) * deep adjustment quotation_second tier * 1000) / average load - power generation coal cost - power generation fixed cost * 1000

[0156] A certain plant has realized real-time calculation of power supply coal cost by using the system of the present invention, and compared with the test and calculation data of the plant ( Figure 2), the two are close, and at the same time, the economic feasibility of participating in deep regulation compensation is verified, so that the quotation is more based on evidence (benchmark electricity price 400 yuan / MWh, standard coal unit price 844 yuan / MWh, first-tier deep regulation compensation price 300 yuan / MWh, second-tier deep regulation compensation price 650 yuan / MWh). The present invention calculates in real time, and there is no need to make assumptions about the ambient temperature, coal quality information, boiler efficiency, and steam turbine generator efficiency remaining stable. All changes in external factors are reflected in the calculation results and can be used throughout the year. Compared with experimental data, it avoids the disadvantage of using one-time experimental data to estimate the data for the whole year.

[0157] Table 1 Comparison of power plant experimental data and system calculation results

[0158]

[0159]

[0160] This set of test data was obtained through on-site testing conducted by the plant at a renowned power and thermal engineering institute. This data was collected at only a few characteristic load points, and the curves fitted based on these limited load points were used to infer the unit's performance under other loads. Furthermore, the test data only represents the unit's efficiency under the conditions of equipment effectiveness during the test period. This data can only be generalized to the entire year under the assumption that the unit equipment is wear-free, requires no maintenance, and maintains constant environmental factors. Given the significant differences between winter and summer operating conditions and the inevitable wear and tear of equipment, this assumption would clearly lead to significant data distortion. Using this experimental data to guide year-round unit operation would necessitate regular retesting and increased testing at varying loads, which would be prohibitively expensive.

[0161] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A real-time coal cost calculation method for power supply with coal loading in different warehouses and time periods, characterized by: include: Obtain coal data from each coal mine, perform data fusion, and calculate the weighted price of coal stored at each coal unloading point every day; The fuel control system obtains the amount of coal added to each raw coal bin and each time period, as well as the source of the added coal, to form a coal queue structure; Compare and match the coal queue structure with the real-time coal supply of each coal feeder to achieve dynamic maintenance of the queue and obtain the coal price used by each coal feeder at the current moment; Considering the benchmark on-grid electricity price and deep adjustment compensation electricity price, calculate the coal burning cost and power supply revenue; The forming of the coal queue structure includes obtaining data on the amount of coal added to each raw coal bin and each time period and the source of coal added through the fuel management and control system to construct an initial queue structure; The coal-fired queue structure can be represented as an ordered set of triples, where each triple contains the time t i 、Coal source S i and the amount of increase in position W i , the queue formula is expressed as: Queue={(t1,S1,W1),(t2,S2,W2),…,(t n ,S n ,W n )} The queue structure is dynamically maintained to obtain the real-time coal feeding amount. The real-time cumulative coal feeding amount of the coal machine at time t is expressed as: in, represents the instantaneous coal flow rate of coal feeder i at time t′; The dynamic maintenance of the queue includes: Update the queue structure: Determine the coal batch to be consumed, initially starting from the first batch in the queue. Once consumed, move on to the next batch. Update the batch remaining quantity, and set the real-time cumulative coal feeding quantity of coal feeder i at time t If it is greater than the remaining amount W1 of the current batch, the formula for updating the queue structure is expressed as: like The coal-fired queue structure is expressed as: Queue={(t2,S2,W2),…,(t n ,S n ,W n )} Otherwise, the increase in position amount is updated as: The update queue structure is represented as: in, represents the remaining amount of the updated batch i of coal; represents the remaining amount of the i-th batch of coal before updating; represents the real-time cumulative coal feeding amount of coal feeder i at time t; represents the remaining coal supply of coal feeder i after consuming the current batch of coal at time t; Based on the real-time coal supply, determine the currently consumed coal batch k; in, represents the weighted average coal price of coal feeder i at time t; represents the price of the jth batch of coal in the queue; represents the amount of coal used by coal feeder i at time t in the jth batch; Reinforcement learning optimization, defining states and actions, state s t Indicates the coal queue structure and coal supply at the current moment; action a t Indicates the coal batch selected for consumption; The reward function formula is expressed as: r t =-C fuel (t)+λ×Ef(t)-μ×EI(t) The optimization objective formula is expressed as: Perform genetic algorithm optimization and define the fitness function, which is expressed as follows: f(x)=-C fuel (t)+λ×Ef(t)-μ×EI(t) Among them, π represents the strategy; * represents the optimal strategy γ represents the discount factor, which ranges from [0,1]; C fuel (t) represents the coal cost at time t; Ef(t) represents the equipment operating efficiency at time t; EI(t) represents the environmental impact at time t; λ represents the weight coefficient of efficiency; μ represents the weight coefficient of environmental impact; Randomly generate the initial population, each individual represents a possible coal queue usage strategy; evaluate the fitness of each individual, using the fitness function; Based on the selection probability, individuals are selected from the current population for reproduction; two parent individuals are selected and crossover operation is performed to generate offspring individuals; offspring individuals are mutated according to the mutation rate to generate new individuals; some or all parent individuals are replaced with offspring individuals to form a new population; and iteration is repeated until the maximum number of iterations is reached.

2. The method for calculating the real-time power supply and coal burning cost applicable to coal loading in different warehouses and time periods as claimed in claim 1 is characterized by: The coal data information of each coal mine includes price, quantity, coal unloading, real-time coal supply, and power supply; data is extracted from the fuel management and control system, and the coal price of each coal mine is Coal supply to each coal mine Coal unloading information, including the coal inventory at each unloading point and the daily unload volume i ;Record the weighted price of coal at each unloading point every day Record the weighted price of coal at each coal unloading point on the previous day Record the amount of coal stored at each unloading point the previous day 3. The real-time power supply and coal burning cost calculation method applicable to coal loading in different warehouses and time periods as claimed in claim 2 is characterized by: The calculation of the weighted price of coal stored at each coal unloading point on a daily basis includes calculating the daily weighted price, combining the price and quantity of the coal unloading point on the previous day to calculate the weighted price of the current day; If multiple types of coal are unloaded at the same unloading point on the same day, the total unloading volume of each unloading point on that day needs to be calculated taking into account the quantity and price of each type of coal. and total price The formula is: Calculate the weighted price of each coal unloading point on the day. The formula is: in, represents the weighted price of coal unloading point i today; represents the weighted price of coal unloading point i yesterday; It represents the total coal storage quantity of unloading point i yesterday; represents the weight of coal type m unloaded to unloading point i today; represents the price of coal type m today; M represents the number of types of coal unloaded today.

4. The method for calculating the real-time power supply and coal burning cost applicable to coal loading in different warehouses and time periods as claimed in claim 3 is characterized by: The data fusion includes determining the location and type of sensors and evaluating the accuracy and coverage of their measurements; Install sensors in predetermined locations to ensure stability and data transmission reliability; calibrate newly installed sensors and perform initial calibration to ensure accuracy of sensor data; Regular recalibration to integrate new sensor data into existing data acquisition systems: Use data fusion algorithms to pre-process multi-source data, remove outliers and noise, and ensure data accuracy; use the fused data to optimize the calculation model for power supply and coal burning costs; The coal flow data integration formula is expressed as: in, represents the coal feed rate of the sth sensor at time t; The coal bunker height data integration formula is expressed as: in, represents the height of the c-th coal bunker at time t, and N represents the number of sensors.

5. The method for calculating the real-time power supply and coal burning cost applicable to coal loading in different warehouses and time periods as claimed in claim 4 is characterized by: The calculation of the power supply coal cost and power supply income includes that the coal cost calculation needs to take into account the coal consumption and coal price of each coal feeder; Among them, C fuel (t) represents the coal cost in the current period; represents the cumulative coal supply of coal feeder i at time t; represents the coal price of coal feeder i at time t; represents the cumulative power generation of generator set j at time t.

6. A real-time power supply and coal cost calculation system for coal loading in different warehouses and time periods, using the method according to any one of claims 1 to 5, characterized in that: The data collection module obtains coal data from each coal mine, performs data fusion, and calculates the weighted price of coal stored at each coal unloading point every day; The coal queue structure module obtains the amount and source of coal added in each raw coal bin and each time period through the fuel control system to form a coal queue structure; The dynamic queue maintenance module compares and matches the coal queue structure with the real-time coal supply of each coal feeder to achieve dynamic queue maintenance; The cost calculation module takes into account the benchmark electricity price and deep adjustment compensation electricity price to calculate the coal-fired power supply cost and power supply revenue.

7. A computer device comprising: memory and processor; The memory stores a computer program, characterized in that when the processor executes the computer program, the steps of the real-time power supply and coal burning cost calculation method applicable to coal loading in different warehouses and time periods as described in any one of claims 1-5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for calculating the real-time power supply and coal burning cost applicable to coal loading in different warehouses and time periods as described in any one of claims 1 to 5 are implemented.

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