Comprehensive energy supply system operation state rapid detection method considering flexible binding of elements

Abstract

The invention discloses a comprehensive energy supply system operation state rapid detection method considering flexible binding of elements. Comprising the following steps: firstly, randomly generating an initial state merging factor according to the number of comprehensive energy supply elements in the comprehensive energy supply system; then, reconstructing the structure of the comprehensive energy supply system to obtain a state reconstruction system; quantifying the running state detection time of the current state reconstruction system by combining computer serial and parallel processing technologies to obtain system running state detection quantization time corresponding to the state merging factor; continuously changing the values of the state merging factors and obtaining the system operation state detection quantization time corresponding to each state merging factor, thereby obtaining an optimal state merging factor and an optimal state reconstruction system; and finally, detecting the operation state of the optimal state reconstruction system by adopting a general generation function method. Rapid detection of the running state of the comprehensive energy supply system is realized, and the calculation efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the field of integrated energy supply systems and relates to a method for detecting the operating status of an integrated energy supply system, and specifically relates to a method for quickly detecting the operating status of an integrated energy supply system taking flexible component binding into consideration. Background Art

[0002] An integrated energy supply system is an integrated energy system that integrates multiple energy sources, such as coal, oil, natural gas, electricity, and thermal energy, to achieve coordinated planning, optimized operation, and collaborative management among various heterogeneous energy subsystems to meet diverse energy needs, improve energy utilization efficiency, and promote sustainable energy development. The reliability of an integrated energy supply system refers to the ability of the energy supply system to withstand disturbances and continuously provide energy to users. Researching reliability assessment methods for integrated energy supply systems is of great significance for their planning, construction, and safe operation. To assess the reliability of an integrated energy supply system, it is necessary to conduct a detailed analysis of its operating status and calculate the system reliability based on each operating state of the system.

[0003] In order to improve the efficiency of integrated energy supply system operation status detection, existing integrated energy supply system operation status detection methods often use computer parallel processing technology. However, traditional integrated energy supply system operation status detection methods based on parallel processing technology often have the following problems: First, traditional parallel processing techniques typically select x components as a group and enter them into a single computer process for computation. The value of x is typically randomly chosen and can be any value. However, as the value of x increases, the computation time of each individual computer process increases, but the total number of computer processes required decreases. In other words, there exists an optimal x that minimizes the time required to detect system operating status. However, the traditional random selection of x makes it impossible to quantify and optimize the efficiency of current operating status detection methods, even with the use of parallel processing techniques.

[0004] Second, to match the number of computer processes used in parallel processing, the system size (including the number of components) is often limited. For example, if a computer only has eight processes, the number of system components must often be a multiple of eight to enable parallel processing. However, the scale of real-world engineering systems varies greatly, and system size cannot be limited. Therefore, how to rapidly detect the operating status of systems of any size is an urgent research issue. Summary of the Invention

[0005] To address the problems in the background technology, the present invention proposes a method for rapidly detecting the operating status of an integrated energy supply system that takes into account flexible component binding. The present invention uses a "parallel substructure-serial substructure-system" detection framework to achieve rapid detection of the operating status of the integrated energy supply system.

[0006] The technical solutions of the present invention are as follows: 1. A rapid detection method for the operating status of an integrated energy supply system considering flexible component binding Step 1: Randomly generate the initial state merging factor according to the number of integrated energy supply components in the integrated energy supply system; Step 2: Reconstruct the structure of the integrated energy supply system based on the current state merging factor to obtain the state reconstructed system; combine computer serial and parallel processing technology to quantify the operating state detection time of the current state reconstructed system to obtain the corresponding system operating state detection quantization time under the current state merging factor; Step 3: Continuously change the value of the state merging factor and repeat the second step to obtain the system operation state detection quantization time corresponding to each state merging factor. The state merging factor with the shortest system operation state detection quantization time is taken as the optimal state merging factor, thereby obtaining the optimal state reconstruction system; Step 4: Use the general generating function method to detect the operating status of the optimal state reconstruction system and complete the operating status detection of the integrated energy supply system.

[0007] In the second step, the structure of the integrated energy supply system is reconstructed based on the current state merging factor to obtain a state reconstruction system, specifically: S1: Divide the integrated energy supply system into several subsystems according to the value of the current state merging factor and form a first-level merged system, where each subsystem is composed of the same number of integrated energy supply components as the state merging factor; S2: Divide the current level merged system into several new subsystems according to the value of the current state merge factor, where each new subsystem is composed of the same number of subsystems in the current level merged system as the state merge factor, and the next level merged system is composed of several new subsystems; S3: Repeat S2 to divide the current level merged system and obtain a new level merged system until the number of subsystems in the latest level merged system is less than the current state merge factor, and the state reconstruction system includes all level merged systems.

[0008] In the second step, the operation state detection time of the current state reconstruction system is quantified by combining computer serial and parallel processing technology to obtain the corresponding system operation state detection quantization time under the current state merging factor, specifically: SP1: Determine the parallel processing time of each merged system based on the current state merge factor. The operating states of different merged systems are calculated using parallel processing technology. Combined with the number of merged systems at all levels in the current state reconstruction system, the parallel processing time of all merged systems in the current state reconstruction system is summed to obtain the first quantized time TQU1. SP2: Combine all the last-level merging systems into an end-merging system, calculate the serial and parallel operation time of the end-merging system and record it as the second quantization time TQU2; SP3: Calculate the product of the state merging factor x raised to the power of I and the number of the last-level merged systems, array_z[I], where I is the level of the last-level merged system. Then, subtract this product from the number of integrated energy supply components N in the integrated energy supply system to obtain the reconstruction residual factor A. If the reconstruction residual factor A = 0, the system operation state detection quantization time is the sum of the first quantization time TQU1 and the second quantization time TQU2. If the reconstruction residual factor A is 1 or an integer greater than or equal to 2, execute SP4. SP4: Calculate the third quantization time TQU3, the formula is as follows: TQU3= Np·Ns N T_parallel If the reconstruction residual factor A is 1, the system operation status detection quantization time is the sum of the first quantization time TQU1, the second quantization time TQU2 and the third quantization time TQU3; otherwise, execute SP5; SP5: The reconstructed residual system is composed of A components with the number of states Ns and the number of energy Np. The serial and parallel operation time of the reconstructed residual system is calculated and recorded as the fourth quantization time TQU4. The system operation status detection quantization time is the sum of the first quantization time TQU1, the second quantization time TQU2, the third quantization time TQU3 and the fourth quantization time TQU4.

[0009] The parallel processing time of the running state of each first-level merge system satisfies the following formula: Ux(x,Ns)=Np·T_parallel·(Ns x+1 -Ns 2 ) / (Ns-1) T_parallel=T_addition+T_muliplication Among them, Ux(x,Ns) represents the parallel processing time of the operating state of each first-level merged system; T_parallel is the parallel structure time factor, T_addition is the time for the computer to process and calculate a single operation, and T_muliplication is the time for the computer to process a single multiplication operation; Np is the energy number of the integrated energy supply element, and Ns is the state number of the integrated energy supply element.

[0010] 2. A rapid detection device for the operating status of an integrated energy supply system considering flexible component binding A state merging factor generating unit, used for generating a state merging factor; A state reconstruction system generating unit is used to reconstruct the structure of the integrated energy supply system based on each state merging factor to obtain a state reconstruction system; The system operation state detection quantization time calculation unit is used to combine computer serial and parallel processing technology to quantify the operation state detection time of each state reconstruction system and obtain the system operation state detection quantization time corresponding to each state merging factor; An optimal selection unit, used to determine an optimal state merging factor and an optimal state reconstruction system; The operating state detection unit is used to detect the operating state of the optimal state reconstruction system using a universal generating function method.

[0011] 3. A computer device The device includes a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, it implements the steps of the method for quickly detecting the operating status of an integrated energy supply system considering flexible component binding.

[0012] 4. A Computer-Readable Storage Medium The medium stores a computer program, which, when executed by a processor, implements the steps of a method for quickly detecting the operating status of an integrated energy supply system that considers flexible component binding.

[0013] 5. A computer program product The product includes a computer program / instruction, which, when executed by a processor, implements the steps of a method for quickly detecting the operating status of an integrated energy supply system that takes into account flexible component binding.

[0014] The beneficial effects of the present invention are: Compared with the existing methods, the method of the present invention proposes a state merging factor and a flexible component merging architecture based on the state merging factor, divides the system substructure related to the entire integrated energy supply system and parallel processing technology and serial processing technology, and provides a system structure classification basis for the quantification of the operating status detection time of an integrated energy supply system of any scale.

[0015] Compared with existing methods, the method of the present invention proposes an optimization model for the operation status detection time of an integrated energy supply system that integrates parallel processing technology and serial processing technology, optimizes the system substructure contained in a single computer process in parallel processing technology, and further reduces the time required for traditional parallel computing.

[0016] Compared with the existing methods, the method of the present invention adopts the three-level operation status detection framework of "system substructure based on parallel processing technology-system substructure based on serial processing technology-system" to establish the operation status distribution function of the integrated energy supply system based on the optimal solution of parallel processing calculation and the flexible merging architecture of components, so as to realize rapid detection of the operation status. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a logic block diagram of the method of the present invention.

[0018] Figure 2 It is a logic block diagram for solving the quantitative time of system operation status detection.

[0019] Figure 3 It is the optimization logic block diagram of the state merging factor.

[0020] Figure 4 It is the logic block diagram of the integrated energy supply system operation status detection in the fourth step.

[0021] Figure 5 It is a structural diagram of the integrated energy supply system. DETAILED DESCRIPTION

[0022] In order to enable those skilled in the art to better understand the present invention and thus to more clearly define the scope of protection claimed by the present invention, the present invention is described in detail below with respect to certain specific embodiments and drawings of the present invention. It should be noted that the following are only certain specific implementation methods of the present invention, which are only part of the embodiments of the present invention, wherein the specific and direct description of the relevant structures is only for the convenience of understanding the present invention, and the specific features do not naturally and directly limit the scope of implementation of the present invention. The conventional selections and replacements made by those skilled in the art under the guidance of the present invention, as well as the reasonable arrangement and combination of several technical features under the guidance of the present invention, should all be deemed to be within the scope of protection claimed by the present invention.

[0023] like Figure 1 As shown, the present invention proposes a method for quickly detecting the operating status of an integrated energy supply system considering flexible component binding, comprising the following steps: Step 1: Randomly generate an initial state merging factor based on the number of integrated energy supply components in the integrated energy supply system. The state merging factor is a positive integer greater than 1 and is less than the total number of integrated energy supply components. Step 2: Reconstruct the structure of the integrated energy supply system based on the current state merging factor to obtain a state-reconstructed system; combine computer serial and parallel processing technology (i.e., computer serial and parallel processing principles) to quantify the operating state detection time of the current state-reconstructed system and obtain the corresponding system operating state detection quantization time under the current state merging factor; like Figure 5 As shown, the integrated energy supply system is composed of N integrated energy supply elements connected in parallel, such as a combined heating, cooling and power trigeneration unit.

[0024] Computer serial processing technology involves breaking down a complex task into multiple, chronologically ordered subtasks, each of which is performed one after the other. Each subtask must wait for the previous one to complete before it can begin processing, and the final result of the entire task is the result of the last subtask processed. Computer parallel processing technology involves breaking down a complex task into multiple, concurrently executed subtasks, using multiple computer processes to simultaneously process these subtasks. Each computer process independently performs its own computational task, ultimately integrating the results of each subtask to produce the final result of the entire task.

[0025] Traditionally, computer serial processing technology is used to monitor the operating status of integrated energy supply systems. This involves treating the operating status monitoring of each component as subtasks. Subtask 1 monitors the operating status of the first and second components. Subtask 2, based on subtask 1, superimposes the operating status monitoring of the third component. This process is repeated iteratively until the Nth component is tested. Subtask 1 is calculated first, followed by subtask 2, and so on, and finally subtask N-1. The operating status monitoring result of subtask N-1 represents the operating status monitoring result of the entire integrated energy supply system. Traditionally, computer parallel processing technology is used to monitor the operating status of x (x is a random value) components as subtasks. Subtask 1 monitors the operating status from the first to the xth component. Subtask 2 monitors the operating status from the x+1th component to the 2xth component. This process is repeated iteratively until the final subtask is reached. Multiple subtasks can be assigned to multiple computer processes for parallel computation. After each subtask is computed, another subtask is required to integrate the operational status detection results of each subtask to obtain the operational status of the entire integrated energy supply system. This invention restructures the integrated energy supply system to optimize the number of components grouped into a single computer process in parallel processing technology.

[0026] In the second step, the structure of the integrated energy supply system is reconstructed based on the current state merging factor to obtain the state reconstruction system, specifically: S1: Divide the integrated energy supply system into several subsystems based on the current state merging factor and form a first-level merged system, where each subsystem is composed of the same number of integrated energy supply components as the state merging factor. After the division, if there are any remaining integrated energy supply components, their number must be less than the state merging factor, and these remaining integrated energy supply components do not form a subsystem. S2: Divide the current merged system into several new subsystems based on the current state merge factor. Each new subsystem is composed of the same number of subsystems in the current merged system as the state merge factor. After the division, if there are any remaining subsystems, their number must be less than the state merge factor. These remaining subsystems do not form a new subsystem. Several new subsystems form the next level merged system. S3: Repeat S2, partitioning the current merged system and obtaining a new merged system until the number of subsystems in the latest merged system is less than the current state merging factor. The state reconstructed system includes all merged systems, as well as the reconstructed residual system and the terminal merged system. The reconstructed residual system is the system composed of the components remaining after each partition; all the last merged systems are combined into a terminal merged system.

[0027] Specifically: First, the integrated energy supply system is divided into N integrated energy supply components into [N / x] first-level subsystems. [N / x] is the integer division of N by x. [N / x] is defined as the number of first-level subsystems in the first-level merged system, array_z[1]. Each first-level subsystem is recorded as a new component. x is the state merging factor, which is the number of components included in the calculation process of each computer process in parallel processing technology. Each first-level subsystem has x integrated energy supply components. After the first division, there may be N%x integrated energy supply components left. N%x is the remainder division of N by x.

[0028] Based on the first division, a second division is performed to divide the obtained array_z[1] first-level merged systems into [[N / x] / x] second-level merged systems, where [[N / x] / x] is the operation of dividing [N / x] by x and rounding it up. Now each second-level subsystem has x first-level subsystems. Then, the x first-level subsystems of each second-level subsystem are equivalent to a new component, so that after the second division, [[N / x] / x] new components will be obtained, and [[N / x] / x] is defined as the number of second-level subsystems, array_z[2]. Similarly, when the second division is performed, while [[N / x] / x] second-level subsystems are obtained, there may be [N / x]%x first-level subsystems left, where [N / x]%x is the operation of dividing [N / x] by x and taking the remainder.

[0029] The above division is repeated until the number of I-level merged systems array_z[I] obtained by the I-th division is less than x. Then the division is stopped and the first-level merged system, the second-level merged system, ..., the I-level merged system and their number are returned.

[0030] In the second step, the computer serial and parallel processing technology (i.e., the computer serial and parallel processing principle) is combined to quantify the operating state detection time of the current state reconstruction system, and the corresponding system operating state detection quantization time under the current state merging factor is obtained, such as Figure 2 As shown, specifically: SP1: Determine the parallel processing time of each merged system (i.e., parallel operation time) based on the current state merging factor. In this way, only the number of parallel operations needs to be known in the second step. The operating states of different merged systems are calculated using parallel processing technology. That is, a merged system in the current state reconstruction system is recorded as a computer process. Then, combined with the number of merged systems at all levels in the current state reconstruction system, the parallel processing time of all merged systems in the current state reconstruction system is summed to obtain the first quantized time TQU1, which satisfies , where p[j+1] is the number of parallel computations for the j+1th level merged system, Ux(x,Ns^(x^j)) represents the equivalent of x components with Ns^(x^j) states and Np energy resources to a new component (i.e., a merged system) using the universal production function method, and ^ represents the power. The time required for the operation status detection of the new component satisfies Ux(x,Ns^(x^j))=Np·T_parallel·((Ns^(x^j))) x+1 -(Ns^(x^j)) 2 ) / (Ns^(x^j)-1); M is the number of computer processes. A merged system is stored in a computer process for calculation, and M computer processes calculate in parallel. If array_z[j+1] is divisible by M, then the number of parallel calculations p[j+1] of the j+1th level merged system is: p[j+1]= array_z[j+1] / M If array_z[j+1] is not divisible by M, in order to ensure that the computational tasks of the j+1th level merge system array_z[j+1] are fully executed, the number of parallel computations p[j+1] of the j+1th level merge system is: Among them, array_z[j+1] is the number of j+1th level merged systems, Represents the rounding-down operation, and M is the number of computer processes for parallel computing.

[0031] For each k-level merge system, the parallel processing time T(k) for running status detection is:

[0032] Among them, Ux(x,Ns^(x^(k-1))) represents the time required for operating status detection of x components with Ns^(x^(k-1)) and Np energy being equivalent to a new component using the universal production function method; T_parallel is the parallel structure time factor, Ns^(x^(k-1)) is the number of states contained in each k-level merged system, and the number of states contained in each k-level merged system is calculated by the x k-1-level merged systems using the universal production function method.

[0033] M computer processes are started to perform parallel computations on the operating status of each merged system. The operating status detection time of each merged system is quantified based on the universal production function method. Based on the universal production function method, the operating status of any x integrated energy supply components or x new components can be equivalent to the operating status of a merged system. The parallel processing time of the operating status of each first-level merged system satisfies the following formula: Ux(x,Ns)=Np·T_parallel·(Ns x+1 -Ns 2 ) / (Ns-1) T_parallel=T_addition+T_muliplication Among them, Ux(x,Ns) represents the parallel processing time of the operating status of each first-level merged system, that is, the time required for detecting the operating status of x components with x states and Np energies, which are equivalent to a new component using the universal production function method; T_parallel is the parallel structure time factor, T_addition is the time for a single computer processing and calculation, and T_muliplication is the time for a single computer processing multiplication operation; Np is the energy number of the integrated energy supply component, and Ns is the number of states of the integrated energy supply component.

[0034] SP2: All the last-level merging systems are combined into an end-merging system. The running state of the end-merging system is calculated using serial processing technology. The serial operation time of the running state of the end-merging system is calculated (so that only the number of serial operations needs to be known in the second step) and recorded as the second quantization time TQU2, satisfying , Ux( ) represents the computer's operation time calculation function; the second quantized time TQU2 quantizes the operating status detection time of the array_z[I] level I merged systems that is equivalent to a new component's operating status.

[0035] SP3: Calculate the product of the state merging factor x raised to the power of I and the number of the last-level merging systems, array_z[I], where I is the level of the last-level merging system, that is, the number of divisions in the generation process of the state reconstruction system; then subtract the product from the number of integrated energy supply elements N in the integrated energy supply system to obtain the reconstruction residual factor A; if the reconstruction residual factor A = 0, the system operation state detection quantization time is the sum of the first quantization time TQU1 and the second quantization time TQU2, that is, the fourth quantization time TQU4 and the third quantization time TQU3 are both 0; if the reconstruction residual factor A is 1 or an integer greater than or equal to 2, execute SP4; SP4: Calculate the third quantization time TQU3, the formula is as follows: TQU3= Np·Ns N T_parallel If the reconstruction residual factor A is 1, the system operation status detection quantization time is the sum of the first quantization time TQU1, the second quantization time TQU2 and the third quantization time TQU3, that is, the fourth quantization time TQU4 is 0; otherwise, execute SP5; SP5: The reconstructed residual system is composed of A elements with the number of states Ns and the number of energy Np. The serial and parallel operation time of the reconstructed residual system is calculated and recorded as the fourth quantization time TQU4, TQU4=Ux(A,Ns)=Np·T_parallel·(Ns A+1 -Ns 2 ) / (Ns-1), Ux(A,Ns) represents the time required for the operation status detection of a new component using the universal production function method, which is equivalent to A components with Ns states and Np energy. The quantized time for the system operation status detection is T total It is the sum of the first quantization time TQU1, the second quantization time TQU2, the third quantization time TQU3 and the fourth quantization time TQU4.

[0036] In summary, if A=0, then: T total =TQU1+TQU2 If A=1, then: T total =TQU1+TQU2+TQU3 If A is an integer greater than or equal to 2, then: T total =TQU1+TQU3+TQU2+TQU4 Step 3: Continuously change the value of the state merging factor and repeat the second step to obtain the corresponding system operation state detection quantization time under each state merging factor, and take the state merging factor with the least system operation state detection quantization time as the optimal state merging factor, and obtain the optimal state reconstruction system (that is, the structure of the integrated energy supply system is reconstructed based on the optimal state merging factor); the value of the state merging factor determines how many components are selected as a group to enter a computer process, and the optimal solution can minimize the detection time required for the operation state of the integrated energy supply system under any scale, such as Figure 3 As shown. The constraints in the optimization process include x ≥ 2 and x ∈ Z, where Z represents an integer; Ns ≥ 2 and Ns ∈ Z, where Ns is the number of states of a single integrated energy supply element; I satisfies .

[0037] Step 4: Use the general generating function method to detect the operating status of the optimal state reconstruction system and complete the operating status detection of the integrated energy supply system.

[0038] like Figure 4 As shown, the fourth step is specifically: 41) The parallel computing system substructure related to computer parallel processing technology in the operation status analysis of the integrated energy supply system obtained by the first step is used to establish array_z[I] "I whole" operation status distribution functions using the general production function method and parallel processing technology.

[0039] In the second step, under the flexible component merging architecture based on the state merging factor, the integrated energy supply system is divided into array_z[1] first-level merging systems. Each first-level merging system consists of x integrated energy supply components. The operating state distribution function of the a-th first-level merging system is established using the general production function method:

[0040] Among them, U 1整,a (z) represents the first a The operating status distribution function of the first-level merged system, a =1,…,array_z[1]; Represents a single integrated energy supply element i Considering energy under state v The output power, i =1,…,x, v =1,…,Np; Represents a single integrated energy supply element i The probability of being in state Ji; Ns is the state number of the integrated energy supply element i, and Np is the state number of the integrated energy supply element i Energy number; (S 1整,a+1) indicates the a The number of states of the first-level merged system, Indicates the a A first-level merged system is in state J1. a Considering energy v The output power of J1 is a =0,…,S 1整,a ; Indicates the a A first-level merged system is in state J1. a The probability of x is the state merging factor obtained in the third step.

[0041] array_z[1] first-level merged systems require M computer processes to calculate p[1] times simultaneously to calculate the running state distribution function U of array_z[1] first-level merged systems. 1整,a (z) are all calculated.

[0042] The running state distribution function U of the array_z[1] first-level merged system 1整,a After all (z) are calculated, the array_z[1] first-level merged systems are divided a second time to obtain array_z[2] second-level merged systems. Each second-level merged system is composed of x first-level merged systems. The operating state distribution function of the ath second-level merged system is established using the general production function method:

[0043] Among them, U 2整,a (z) represents the operating state distribution function of the a-th secondary merged system in the form of a general production function. a =1,…,array_z[2] ;(S 1整,l +1) represents the number of the a-th secondary merge system l The number of states of a first-level merged system; Indicates the first l A first-level merged system is in state J1. l Considering energy v The output power of J1 is l =0,…,S 1整,l ; Indicates the first l A first-level merged system is in state J1. l The probability of Indicates that the a-th secondary merge system is in state J2. a Considering energy v The output power of J2 is a=0,…,S 2整,a ;(S 2整,a +1) represents the state number of the a-th secondary merge system, Indicates that the a-th secondary merge system is in state J2. a The probability of the next.

[0044] array_z[2] two-level merged systems require M computer processes to calculate p[2] times simultaneously to calculate the running state distribution function U of array_z[2] two-level merged systems. 2整,a (z) are all calculated.

[0045] Continue to divide in sequence until array_z[I-1] I-1 level merged system operation status distribution function U I-1整,a (z) are calculated. Perform the first division of array_z[I-1] I-1 level merged systems to obtain array_z[I] I-1 level merged systems. array_z[I] is less than x, which means that the next division based on the flexible component merge architecture is not necessary. Each I-1 level merged system consists of x I-1 level merged systems. Use the general production function method to establish the operating state distribution function of the a-th I-1 level merged system: Among them, U I整,a (z) represents the operating state distribution function of the a-th level I merged system expressed in the form of a general production function. a =1,…,array_z[I];(S I-1整,l +1) represents the number of the a-th level I combined system l The number of states of the I-1 level merged system; Indicates the first l The I-1 level merged system is in state JI-1. l Considering energy v Output power, JI-1, l =0,…,S I-1整,l ; Indicates the first l The I-1 level merged system is in state JI-1. l The probability of Indicates that the a-th level I merge system is in state JI, a Considering energy v The output power (S I整,a +1) represents the number of states of the a-th level I merged system, JI is the whole number, a =0,…,S I整,a ; Indicates that the a-th level I merge system is in state JI, a The probability of the next.

[0046] The array_z[I] level I merged systems require M computer processes to calculate p[I] times simultaneously to calculate the running state distribution function U of the array_z[I] level I merged systems. I整,a (z) are all calculated.

[0047] 42) array_z[I] level 1 merging systems are connected in parallel. The array_z[I] level 1 merging systems are connected in parallel to form an end-merging system. The operating state distribution function of the end-merging system is established using the general production function method and serial processing technology:

[0048] Among them, U 整 (z) represents the operating state distribution function of the terminal merging system expressed in the form of a general production function; (S I整,l +1) indicates the l The number of states of the I-level merge system, in this step l =1,…,array_z[I]; Indicates the l A level I merged system is in state JI. l Considering energy v The output power, JI, l =0,…,S I整,l ; Indicates the l A level I merged system is in state JI. l The probability of The energy of the terminal merging system in state J is considered v The output power (S 整 +1) represents the number of states of the terminal merging system, J=0,…,S 整 ; represents the probability that the terminal merging system is in state J.

[0049] 43) After A integrated energy supply elements are connected in parallel, they are equivalent to the reconstructed residual system. The operating state distribution function of the reconstructed residual system is established using the general production function method and serial processing technology: Among them, U 余 (z) represents the operating state distribution function of the reconstructed residual system expressed in the form of a general production function; Represents the considered energy of comprehensive energy supply component i in state Ji vThe output power of Ji=1,…,Ns, this step i =1,…,A; represents the probability of the integrated energy supply element i being in state Ji; (s+1) represents the number of states that make up the integrated energy supply element; Represents the remaining energy required to reconstruct the remaining system in state J v The output power (S 余 +1) represents the number of states of the reconstructed residual system, J remainder = 0,…,S 余 ; Represents the probability that the new comprehensive energy supply component _Yu remains in state J.

[0050] 44) Based on the operating state distribution function U of the terminal merging system in 42) 整 (z) and 43) the operating state distribution function U of the reconstructed residual system 余 (z) Using the general production function method and serial processing technology to establish the operating state distribution function of the integrated energy supply system:

[0051] Wherein, U(z) represents the operating state distribution function of the integrated energy supply system expressed in the form of a universal production function; Indicates the energy considered by the integrated energy supply system in state J v The output power (S 系 +1) represents the state number of the integrated energy supply system, J = 0,…,S 系 ; Represents the probability of the integrated energy supply system in state J.

[0052] Based on the operating status distribution function of the integrated energy supply system in 44), combined with the needs of the integrated energy supply system, the reliability evaluation of the integrated energy supply system can be carried out, and then the scheduling of the integrated energy supply system can be optimized.

[0053] The following is a rapid test of the operating status of an integrated energy supply system consisting of different numbers of CHP units connected in parallel. During the experiment, each CHP unit has three performance characteristics: heat, electricity, and gas. Each CHP unit has five states. Four computer processes are used to quickly test the operating status of the integrated energy supply system, which takes into account flexible component binding.

[0054] For integrated energy supply systems consisting of 10, 20, and 30 CHP units connected in parallel, the optimal state consolidation factor x is 2. For an integrated energy supply system consisting of 40 CHP units connected in parallel, the optimal state consolidation factor x is 3. Table 1 shows a comparison of the efficiency of the method proposed in this invention and the traditional method. As can be seen from Table 1, the method proposed in this invention significantly shortens the time required for operating state detection.

[0055] Table 1 is a comparison table of the efficiency of the method proposed by the present invention and the traditional method

[0056] The present invention also proposes a device for quickly detecting the operating status of an integrated energy supply system taking into account flexible component binding, comprising: A state merging factor generating unit, used for generating a state merging factor; A state reconstruction system generating unit is used to reconstruct the structure of the integrated energy supply system based on each state merging factor to obtain a state reconstruction system; The system operation state detection quantization time calculation unit is used to combine computer serial and parallel processing technology to quantify the operation state detection time of each state reconstruction system and obtain the system operation state detection quantization time corresponding to each state merging factor; An optimal selection unit, used to determine an optimal state merging factor and an optimal state reconstruction system; The operating state detection unit is used to detect the operating state of the optimal state reconstruction system using a universal generating function method.

[0057] The present invention also proposes a computer device, which includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the steps of a method for quickly detecting the operating status of an integrated energy supply system that takes into account flexible binding of components.

[0058] The present invention also proposes a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the computer program implements the steps of a method for quickly detecting the operating status of an integrated energy supply system taking into account flexible binding of components.

[0059] The present invention also proposes a computer program product, which includes a computer program / instruction, which, when executed by a processor, implements the steps of a method for quickly detecting the operating status of an integrated energy supply system taking into account flexible component binding.

Claims

1. A method for quickly detecting the operating status of an integrated energy supply system considering flexible component binding, characterized in that: The following steps are involved: Step 1: Randomly generate the initial state merging factor according to the number of integrated energy supply components in the integrated energy supply system; Step 2: Reconstruct the structure of the integrated energy supply system based on the current state merging factor to obtain the state reconstruction system; Combining computer serial and parallel processing technology, the operating state detection time of the current state reconstruction system is quantified to obtain the corresponding system operating state detection quantization time under the current state merging factor; Step 3: Continuously change the value of the state merging factor and repeat the second step to obtain the system operation state detection quantization time corresponding to each state merging factor. The state merging factor with the shortest system operation state detection quantization time is taken as the optimal state merging factor, thereby obtaining the optimal state reconstruction system; Step 4: Use the general generating function method to detect the operating status of the optimal state reconstruction system and complete the operating status detection of the integrated energy supply system.

2. A method for rapid detection of the operating status of an integrated energy supply system considering flexible component binding according to claim 1, characterized in that: In the second step, the structure of the integrated energy supply system is reconstructed based on the current state merging factor to obtain a state reconstruction system, specifically: S1: Divide the integrated energy supply system into several subsystems according to the value of the current state merging factor and form a first-level merged system, where each subsystem is composed of the same number of integrated energy supply components as the state merging factor; S2: Divide the current level merged system into several new subsystems according to the value of the current state merge factor, where each new subsystem is composed of the same number of subsystems in the current level merged system as the state merge factor, and the next level merged system is composed of several new subsystems; S3: Repeat S2 to divide the current level merged system and obtain a new level merged system until the number of subsystems in the latest level merged system is less than the current state merge factor, and the state reconstruction system includes all level merged systems.

3. A method for rapid detection of the operating status of an integrated energy supply system considering flexible component binding according to claim 1, characterized in that: In the second step, the operation state detection time of the current state reconstruction system is quantified by combining computer serial and parallel processing technology to obtain the corresponding system operation state detection quantization time under the current state merging factor, specifically: SP1: Determine the parallel processing time of each merged system based on the current state merge factor. The operating states of different merged systems are calculated using parallel processing technology. Combined with the number of merged systems at all levels in the current state reconstruction system, the parallel processing time of all merged systems in the current state reconstruction system is summed to obtain the first quantized time TQU1. SP2: Combine all the last-stage merging systems into an end-merging system, calculate the serial and parallel operation time of the end-merging system and record it as the second quantization time TQU2; SP3: Calculate the product of the state merging factor x to the power of I and the number of the last-level merged systems array_z[I], where I is the level of the last-level merged system; Then, the number N of integrated energy supply elements in the integrated energy supply system is subtracted from the product to obtain the reconstruction residual factor A. If the reconstruction residual factor A = 0, the system operation status detection quantization time is the sum of the first quantization time TQU1 and the second quantization time TQU2. If the reconstruction residual factor A is 1 or an integer greater than or equal to 2, execute SP4. SP4: Calculate the third quantization time TQU3, the formula is as follows: TQU3= Np·Ns N ·T_parallel If the reconstruction residual factor A is 1, the system operation status detection quantization time is the sum of the first quantization time TQU1, the second quantization time TQU2 and the third quantization time TQU3; otherwise, execute SP5; SP5: The reconstructed residual system is composed of A components with the number of states Ns and the number of energy Np. The serial and parallel operation time of the reconstructed residual system is calculated and recorded as the fourth quantization time TQU4. The system operation status detection quantization time is the sum of the first quantization time TQU1, the second quantization time TQU2, the third quantization time TQU3 and the fourth quantization time TQU4.

4. A method for rapid detection of the operating status of an integrated energy supply system considering flexible component binding according to claim 3, characterized in that: The parallel processing time of each of the first-level merging systems satisfies the following formula: Ux(x,Ns)=Np·T_parallel·(Ns x+1 -Ns 2 ) / (Ns-1) T_parallel=T_addition+T_muliplication Among them, Ux(x,Ns) represents the parallel processing time of each first-level merged system; T_parallel is the parallel structure time factor, T_addition is the time for the computer to process and calculate a single operation, and T_muliplication is the time for the computer to process a single multiplication operation; Np is the energy number of the integrated energy supply element, and Ns is the state number of the integrated energy supply element.

5. A device for quickly detecting the operating status of an integrated energy supply system taking into account flexible component binding, characterized in that: include: A state merging factor generating unit, used for generating a state merging factor; A state reconstruction system generating unit is used to reconstruct the structure of the integrated energy supply system based on each state merging factor to obtain a state reconstruction system; The system operation state detection quantization time calculation unit is used to combine computer serial and parallel processing technology to quantify the operation state detection time of each state reconstruction system and obtain the system operation state detection quantization time corresponding to each state merging factor; An optimal selection unit, used to determine an optimal state merging factor and an optimal state reconstruction system; The operating state detection unit is used to detect the operating state of the optimal state reconstruction system using a universal generating function method.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of a method for quickly detecting the operating status of an integrated energy supply system considering flexible component binding as described in any one of claims 1 to 4 are implemented.

7. 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 a method for quickly detecting the operating status of an integrated energy supply system considering flexible component binding as described in any one of claims 1 to 4 are implemented.

8. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, the steps of a method for quickly detecting the operating status of an integrated energy supply system considering flexible component binding as described in any one of claims 1 to 4 are implemented.

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