AU2020100796A4 - Method for analyzing operation reliability of multi-state power generation system based on decision diagram - Google Patents

Method for analyzing operation reliability of multi-state power generation system based on decision diagram Download PDF

Info

Publication number
AU2020100796A4
AU2020100796A4 AU2020100796A AU2020100796A AU2020100796A4 AU 2020100796 A4 AU2020100796 A4 AU 2020100796A4 AU 2020100796 A AU2020100796 A AU 2020100796A AU 2020100796 A AU2020100796 A AU 2020100796A AU 2020100796 A4 AU2020100796 A4 AU 2020100796A4
Authority
AU
Australia
Prior art keywords
state
power generation
generation system
decision diagram
transfer
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
AU2020100796A
Inventor
Heping JIA
Genzhu LI
Yanbin Li
Dunnan LIU
Mingguang Liu
Guangyu QIN
Xiaofeng Xu
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
North China Electric Power University
Original Assignee
North China Electric Power University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by North China Electric Power University filed Critical North China Electric Power University
Application granted granted Critical
Publication of AU2020100796A4 publication Critical patent/AU2020100796A4/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Energy or water supply
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Landscapes

  • Business, Economics & Management (AREA)
  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Economics (AREA)
  • Public Health (AREA)
  • Water Supply & Treatment (AREA)
  • General Health & Medical Sciences (AREA)
  • Human Resources & Organizations (AREA)
  • Marketing (AREA)
  • Primary Health Care (AREA)
  • Strategic Management (AREA)
  • Tourism & Hospitality (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The present invention relates to a method for analyzing operation reliability of a multi-state power generation system based on a decision diagram, comprising the following steps: step 1. establishing a multi-state power generation system model with reserve according to collected multi-state power generation system characteristic data; step 2. establishing a multi-state decision diagram of a power generation system according to the multi-state power generation system model with reserve established in step 1; and step 3. calculating the occurrence probability of a reliability path in the multi-state decision diagram of the power generation system established in step 2, and calculating the operation reliability of the power generation system according to the occurrence probability of the reliability path in the multi-state decision diagram of the power system. The present invention can be used for power supply systems with different state transfer rates or different state transfer time distributions. Generator sets 321 Number of generator sets States of generator sets Capacities of states of - Generatorsets generator sets /System for analyzing operation reliability of a multi-state power generation system 1. Modeling of a multi-state generator set 2. Establishment of a multi-state decision diagram of a system 3. Calculation of occurrence probability of a reliability path in the decision diagram State transfer 4. Calculation of system operation reliability characteristics of the sets System 0 in the operating mode load State transfer demand characteristics of the sets Firststate in the reserve mode transfer Generator Generator A set 1: 1-+2 esetoN r l-2 0 [setJN: Operation reliability of the multi-state power generation system • •Load ( demand

Description

METHOD FOR ANALYZING OPERATION RELIABILITY
OF MULTI-STATE POWER GENERATION SYSTEM BASED
ON DECISION DIAGRAM
TECHNICAL FIELD
[0001] The present invention belongs to the technical field of power system risk assessment, relates to a method for analyzing operation reliability of a power generation system, and particularly relates to a method for analyzing operation reliability of a multi-state power generation system based on a decision diagram.
BACKGROUND OF THE PRESENT INVENTION
[0002] In the power generation system, operating reserves are generally configured widely to improve the operation reliability of the system, wherein the operating reserves include a rotating reserve or a non-rotating reserve provided by generator sets. Due to quick response of quick start-stop units, the non-rotating reserve can be provided by quick start-stop units such as gas units. The unit in the rotating reserve and the online unit are operated synchronously. Once the online unit fails, the unit in the rotating reserve can be quickly put into operation, but the unit in the rotating reserve has more energy consumption during the reserve. Since the unit in the rotating reserve and the online operating unit are operated simultaneously, the unit in the rotating reserve usually has the same failure rate as the online unit. A thermal power generating unit in the non-rotating reserve state may be that a boiler is in the operating state and the generator is not operated, so as to reduce the energy consumption during the reserve and achieve quick start. Since the environment of the non-rotating reserve unit is different from that of the online operating unit, the failure rate of the non-rotating reserve unit is generally smaller than that of the online unit. [0003] It can be seen that the rotating reserve unit and the non-rotating reserve unit are comprehensively considered, and have different state transfer rates or different state transfer time distributions in the reserve mode and the operating mode. The traditional method for analyzing the operation reliability of the power generation system has a certain application scope and cannot be directly used in power generation systems with different state transfer rates or different state transfer time distributions. Therefore, it is necessary to propose a method for analyzing the
2020100796 20 May 2020 operation reliability of the power generation system in consideration of different reserve characteristics.
SUMMARY OF PRESENT INVENTION
[0004] The purpose of the present invention is to overcome the defects of the prior art, and to propose a method for analyzing operation reliability of a multi-state power generation system based on a decision diagram, which can be used for power supply systems with different state transfer rates or different state transfer time distributions.
[0005] The present invention solves the real problems by adopting the following technical solutions:
[0006] A method for analyzing operation reliability of a multi-state power generation system based on a decision diagram comprises the following steps: [0007] step 1. establishing a multi-state power generation system model with reserve according to collected multi-state power generation system characteristic data;
[0008] step 2. establishing a multi-state decision diagram of a power generation system according to the multi-state power generation system model with reserve established in step 1;
[0009] step 3. calculating the occurrence probability of a reliability path in the multi-state decision diagram of the power generation system established in step 2, and calculating the operation reliability of the power generation system according to the occurrence probability of the reliability path in the multi-state decision diagram of the power system.
[0010] Moreover, specific steps of the step 1 comprise:
[0011] (1) analyzing the states of generator sets to obtain the multi-state characteristic data of each generator set, comprising: the number of the generator sets, the states of the generator sets, the capacities of different states, and the state transfer rates of the generator sets in different modes;
[0012] (2) according to the collected multi-state power generation system characteristic data, establishing the multi-state power generation system model with reserve as follows: the state transfer time distribution of the generator sets in an operating mode and a reserve mode can follow any distribution, and a cumulative probability density function, a probability density function and a reliability function are respectively F(t), f(t) and R(t) = 1- F(t); if the state transfer time distribution of
2020100796 20 May 2020 the generator sets follows Weibull distribution, then F(t) = 1 - exp - (t / and /(0 = A_exp -(t/crf a and β a L J, wherein represent a scale parameter and a shape parameter of Weibull distribution respectively.
[0013] Moreover, specific steps of the step 2 comprise:
[0014] (1) representing a value of a node in the multi-state decision diagram of the power generation system by a ternary variable which mainly represents states and modes of the generator sets and an available power generation capacity of the system:
[0015] representing the ternary variable of the b-th branch after the e-th state J/b _ transfer of the system as e L e ’ e ’ e J, sb
[0016] wherein e represents the state of the generator set represented by the b-th Mb branch of the system decision diagram after the e-th state transfer; e represents the mode of the generator set represented by the b-th branch of the system decision cb diagram after the e-th state transfer; and e represents the available power generation capacity of the system represented by the b-th branch of the system decision diagram after the e-th state transfer;
5°=[1 11
[0017] (2) setting the state of the generator set as 0 I’·’ J, the mode as
K = [1^1,0^0] k N-k and the available power generation capacity of the system as
N
CJ=ZG‘ /=1 at the initial operation time of system;
[0018] wherein 1 represents that the generator set is in the operating mode; 0 represents that the generator set is in the reserve mode; k represents the number of the generator sets in the operating mode in the system at the initial operation time of the system; and G- represents the capacity of the i-th generator set in the first state; [0019] (3) when the power generation system generates the first state transfer, the first state transfer can occur in any generator set from state 1 to state 2; thus, a root node of the decision diagram has N branches, wherein the b-th branch (b=l,..., N) represents that the b-th generator set is transferred from state 1 to state 2;
2020100796 20 May 2020
[0020] for the b-th branch, representing the state of the generator set in the ternary 5i=[U4,2,U] variable of the decision diagram as h ' N~b , wherein the mode of the generator set is determined by the capacity of the state of the generator set and a system load demand, that is, if the b-th generator set is transferred from state 1
G1 G2 (capacity is b) to state 2 (capacity is b ), the total capacity of the system becomes:
N
P = Gt 2 + Σ G ‘ i=l,+h
[0021] (4) after the generator set in the system generates the first state transfer, the generator set possibly generating the second state transfer, wherein if the second state transfer of the system occurs in the p-th element and the state is transferred to a next state, the available system capacity 2 after the second state transfer is:
Figure AU2020100796A4_D0001
+ Σ G'’P = b i=\,i*p + Gl+ f G},p*b cp
[0022] wherein 2 represents the available system capacity after the second state
G2 G2 transfer; p and p represent the available capacities when the /?-th element is in (j1 a third state and the second state; * represents the available capacity when the z-th
G2 element is in the first state; and b represents the available capacity when the b-th element is in the second state;
[0023] (5) calculating the third and the fourth state transfers of the power generation system in an iterative manner, and the establishment of the decision diagram is stopped until no state transfer element exists in the system or the power generation capacity of the system cannot meet the system load demand after the state transfer.
[0024] Moreover, specific steps of calculating the occurrence probability of the reliability path in the multi-state decision diagram of the power generation system in the step 3 comprise:
2020100796 20 May 2020
[0025] (1) for a system which only generates two state transfers and the path is for the first generator set to generate two consecutive state transfers, using the following formula to calculate the occurrence probability of the path in which the first generator set generates two consecutive state transfers:
τ τ
Path^T) = J J// (i, - ti)^_2(T)-R^_2(T)dtidt2
Z|
[0026] wherein 711' represents the probability density function of the transfer of the z -th element from state 7 to state ^7 ; ^7~7+1 represents a function that the reliability of the transfer of the 1 -th element from state J to state (·/ 1) changes with time t, and can be obtained by the corresponding probability (t\ density function 77; T represents the system operation time; θ represents the initial operation time of system; represents the time when the system generates the first state transfer; and represents the time when the system generates the second state transfer;
[0027] (2) for a system which only generates two state transfer processes, and the second generator set generates the first state transfer and the first generator set generates the second state transfer, using the following formula to calculate the occurrence probability of the path:
τ τ
J f // (/ K, (T -12)// (/ )λ/3 (T -1,)«,/ (T) · C (T)dt,dt2 /
[0028] (3) for a system which does not generate any state transfer process during the system operation time, using the following formula to calculate the available probability of the path:
p^(T)=A_2(O-C(O
[0029] Moreover, a formula for calculating the operation reliability of the power generation system in the step 3 is:
R(T) = XPath„(T) h
[0030] wherein T represents the system operation time; 7?(T) represents the
2020100796 20 May 2020 operation reliability value of the system; and Pathh (Τ') represents the occurrence probability of the h-th path in the decision diagram.
[0031] The present invention has the following advantages and beneficial effects: [0032] 1. The present invention considers the multi-state characteristics of the generator sets during operation, accurately analyzes the operation reliability of the multi-state generator sets based on the decision diagram method, and considers that the generator sets in different modes in the power generation system have different state transfer time distributions for analysis, thereby proposing the method for analyzing the operation reliability of the multi-state power generation system in consideration of the reserve. The method proposed by the present invention is applicable to the power generation system with any state transfer distribution, and makes up for the defects of the traditional method for analyzing the reliability of the power generation system. The power generation system is used as an important component of the power system. The method and system for analyzing the reliability of the power generation system proposed by the present invention have an important role in ensuring the safe and reliable operation of the power system.
DESCRIPTION OF THE DRAWINGS
[0033] Fig. 1 is a processing flow chart of the present invention;
[0034] Fig. 2 is a structural diagram of a power generation system of the present invention;
[0035] Fig. 3 is a processing flow chart in a specific embodiment of the present invention; and
[0036] Fig. 4 is a diagram of system reliability value results under different probabilities of successful reserve starting in a specific embodiment of the present invention.
DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS
[0037] The embodiments of the present invention are further described below in detail with reference to the drawings:
[0038] A method for analyzing operation reliability of a multi-state power generation system based on a decision diagram, as shown in Fig. 1, comprises the following steps:
[0039] Step 1. establishing a multi-state power generation system model with reserve according to collected multi-state power generation system characteristic
2020100796 20 May 2020 data.
[0040] Specific steps of the step 1 comprise:
[0041] (1) analyzing the states of generator sets to obtain the multi-state characteristic data of each generator set, comprising: the number of the generator sets, the states of the generator sets, the capacities of different states, and the state transfer rates of the generator sets in two different modes, i.e., a reserve mode and an operating mode;
[0042] (2) according to the collected multi-state power generation system characteristic data, establishing the multi-state power generation system model with reserve as follows: the state transfer time distribution of the generator sets in an operating mode and a reserve mode can follow any distribution, and a cumulative probability density function, a probability density function and a reliability function are respectively F(t), f(t) and R(t) 1 - F(t); if the state transfer time distribution of the generator sets follows Weibull distribution, then F(f) = 1 - exp -(t / af and f(t) = -^-exp -(t/ctf a anj β a L , wherein represent a scale parameter and a shape parameter of Weibull distribution respectively.
[0043] The structure of the power generation system is shown in Fig. 2.
[0044] In the present embodiment, as shown in Fig. 3, the proposed power generation system model with operating reserve is composed of five multi-state generator sets in a parallel structure, including an online operation set, a rotating reserve set and a non-rotating reserve set.
[0045] The multi-state characteristics of the generator sets are shown in Fig. 3. The power generation system is composed of five generator sets, and each generator set is divided into three states. Different capacities of generator sets 1,2, and 3 in the three states are 20MW, 10MW, and 0MW; different capacities of generator sets 4 and 5 in the three states are 10MW, 5MW and 0MW; the state transfer distribution of the generator sets follows Weibull distribution, wherein a and @ represent the scale parameter and the shape parameter of the Weibull distribution respectively.
[0046] Step 2. establishing a multi-state decision diagram of a power generation system according to the multi-state power generation system model with reserve established in step 1.
2020100796 20 May 2020
Specific steps of the step 2 comprise:
[0047] (1) representing a value of a node in the multi-state decision diagram of the power generation system by a ternary variable which mainly represents states and modes of the generator sets and an available power generation capacity of the system:
[0048] representing the ternary variable of the b-th branch after the e-th state transfer of the system as
Vb =[Sb,Mb,Cb] sb
[0049] wherein e represents the state of the generator set represented by the b-th
Mb branch of the system decision diagram after the e-th state transfer; e represents the mode of the generator set represented by the b-th branch of the system decision cb diagram after the e-th state transfer; and e represents the available power generation capacity of the system represented by the b-th branch of the system decision diagram after the e-th state transfer;
5° =[1 ... 11
[0050] (2) setting the state of the generator set as 0 I’·’ J, the mode as <=[1^1,0^0] k N~k and the available power generation capacity of the system as <Τ=Σς' !=1 at the initial operation time of system;
[0051] wherein 1 represents that the generator set is in the operating mode; 0 represents that the generator set is in the reserve mode; k represents the number of the generator sets in the operating mode in the system at the initial operation time of the system; and G\ represents the capacity of the i-th generator set in the first state;
[0052] (3) when the power generation system generates the first state transfer, for the b-th branch, representing the state of the generator set in the ternary variable of the decision diagram as h ' N~b , wherein the mode of the generator set is determined by the capacity of the state of the generator set and a system load demand, that is, if the b-th generator set is transferred from state 1 (capacity is b)
G2 to state 2 (capacity is b ), the total capacity of the system becomes:
2020100796 20 May 2020 =g,; + f °;
i=l,i^b
[0053] (4) after the generator set in the system generates the first state transfer, the generator set possibly generating the second state transfer, wherein if the second state transfer of the system occurs in the P -th element and the state is transferred to a cp next state, the available system capacity 2 after the second state transfer is:
Figure AU2020100796A4_D0002
+ Σ G',’P=b i=l,+p + G>+ Σ G‘,p*b cp
[0054] wherein 2 represents the available system capacity after the second state gP g~ transfer; p and p represent the available capacities when the /?-th element is in
G^ a third state and the second state; * represents the available capacity when the z-th
G2 element is in the first state; and b represents the available capacity when the b-th element is in the second state;
[0055] (5) calculating the third and the fourth state transfers of the power generation system in an iterative manner, and the establishment of the decision diagram is stopped until no state transfer element exists in the system or the power generation capacity of the system cannot meet the system load demand after the state transfer.
[0056] Step 3. calculating the occurrence probability of a reliability path in the multi-state decision diagram of the power generation system established in step 2, and calculating the operation reliability of the power generation system according to the occurrence probability of the reliability path in the multi-state decision diagram of the power system.
[0057] The reliability of the power generation system is determined by the sum of the occurrence probabilities of the paths in the system decision diagram. Each path in the system decision diagram represents the number of times of different state transfers of the generator sets. The occurrence probability of each path in the decision diagram is calculated by the following mode:
[0058] Specific steps of calculating the occurrence probability of the reliability path ίο
2020100796 20 May 2020 in the multi-state decision diagram of the power generation system in the step 3 comprise:
[0059] (1) For a system which only generates two state transfers and the path is for the first generator set to generate two consecutive state transfers, using the following formula to calculate the occurrence probability of the path in which the first generator set generates two consecutive state transfers:
τ τ
Path,(T) = \\f/AtdfL,02-td^AT>)--^-2(T)dt,dt2 /,
[0060] wherein 7 7+1 represents the probability density function of the transfer of the z -th element from state 1 to state U ) · j 711 represents a function that the reliability of the transfer of the z -th element from state 1 to state changes with time t, and can be obtained by the corresponding probability f' (t\ density function 7-7+1 ; T represents the system operation time; θ represents the initial operation time of system; represents the time when the system generates the first state transfer; and represents the time when the system generates the second state transfer.
[0061] In the present embodiment,
T T
Pathfn 0 /, _
[0062] (2) For a system which only generates two state transfer processes, and the second generator set generates the first state transfer and the first generator set generates the second state transfer, using the following formula to calculate the occurrence probability of the path:
τ τ f f χ/ (z2 (7 -tpffiMRUT (T)dt,dt2 /,
[0063] In the present embodiment, the occurrence probability of the path τ τ is0'' .
[0064] (3) For a system which does not generate any state transfer process during
2020100796 20 May 2020 the system operation time, using the following formula to calculate the available probability of the path:
Pat\(T) = C(T)-C(O
[0065] In the present embodiment, path^n=xmCcOXmCcm5 .
r . (0
[0066] wherein J j 7+1 v 7 represents the probability density function of the transfer of the z -th element from state to state ; ^7-7+1 represents a function that the reliability of the transfer of the z -th element from state J to state 0 changes with time t, and can be obtained by the corresponding probability density function 7-7+1 ; T represents the system operation time; θ represents the initial operation time of system; represents the time when the system generates the first state transfer; and represents the time when the system generates the second state transfer.
[0067] A formula for calculating the operation reliability of the power generation system in the step 3 is:
R(T) = ^Pathh(T) h
[0068] wherein T represents the system operation time; 7?(T) represents the operation reliability value of the system; and Pathh (Τ') represents the occurrence probability of the h-th path in the decision diagram.
[0069] In the present embodiment, the reliability value of the multi-state power generation system that changes with time is finally calculated, as shown in Fig. 4. The figure shows the reliability value of the power generation system that changes with time under different probabilities of successful starting of the reserve sets. It can be seen from the figure that, when the system operation time is 100 days, when the probabilities of successful starting of the reserve sets are respectively 1, 0.9 and 0.8, the system reliability values are respectively 0.8430, 0.8059 and 0.7688. The system reliability values are decreased with the increase of the system operation time. The probabilities of successful starting of the reserve sets affect the system reliability
2020100796 20 May 2020 values. If the probabilities of successful starting are higher, the system reliability values are higher.
[0070] The working principle of the present invention is as follows:
[0071] The present invention proposes a method for analyzing the reliability of the power generation system based on the decision diagram with respect to the multi-state power generation system that considers different types of operating reserves. Considering that the environment of the non-rotating reserve set is different from that of the online operating set and the failure rate of the non-rotating reserve set is generally smaller than the failure rate of the online operating set, the present invention proposes consideration of the number of the generator sets, the states of the generator sets, the capacities of the states of the generator sets, the system load demand, and the state transfer time distribution of the non-rotating reserve set and the online set and proposes the method for analyzing the reliability of the power generation system based on the decision diagram. By calculating the occurrence probability of each path in the system decision diagram, the operation reliability value of the multi-state power generation system is obtained.
[0072] It shall be emphasized that the embodiments of the present invention are illustrative and not limiting. Therefore, the present invention includes, but not limited to the embodiments in the Detailed Description. Any other embodiments obtained by those skilled in the art according to the technical solutions of the present invention also belong to the protection scope of the present invention.

Claims (5)

  1. We claim:
    1. A method for analyzing operation reliability of a multi-state power generation system based on a decision diagram, comprising the following steps:
    step 1. establishing a multi-state power generation system model with reserve according to collected multi-state power generation system characteristic data;
    step 2. establishing a multi-state decision diagram of a power generation system according to the multi-state power generation system model with reserve established in step 1;
    step 3. calculating the occurrence probability of a reliability path in the multi-state decision diagram of the power generation system established in step 2, and calculating the operation reliability of the power generation system according to the occurrence probability of the reliability path in the multi-state decision diagram of the power system.
    2. The method for analyzing operation reliability of the multi-state power generation system based on the decision diagram according to claim 1, wherein specific steps of the step 1 comprise:
    (1) analyzing the states of generator sets to obtain the multi-state characteristic data of each generator set, comprising: the number of the generator sets, the states of the generator sets, the capacities of different states, and the state transfer rates of the generator sets in different modes;
  2. (2) according to the collected multi-state power generation system characteristic data, establishing the multi-state power generation system model with reserve as follows: the state transfer time distribution of the generator sets in an operating mode and a reserve mode can follow any distribution, and a cumulative probability density function, a probability density function and a reliability function are respectively F(t), f(t) and R(t) = 1- F(t); if the state transfer time distribution of the generator sets follows Weibull distribution, then
    F(/) = l-exp -(//a and /(0 = ^^exp -(//a/ ct anq a L J, wherein β
    represent a scale parameter and a shape parameter of Weibull distribution respectively.
    3. The method for analyzing operation reliability of the multi-state power generation system based on the decision diagram according to claim 1, wherein
    2020100796 20 May 2020 specific steps of the step 2 comprise:
    (1) representing a value of a node in the multi-state decision diagram of the power generation system by a ternary variable which mainly represents states and modes of the generator sets and an available power generation capacity of the system:
    representing the ternary variable of the b-th branch after the e-th state transfer of thesystemas = [She,Mhe,Cb], wherein Sb e represents the state of the generator set represented by the b-th branch of the system decision diagram after the e-th state transfer; Mb represents the mode of the generator set represented by the b-th branch of the system decision diagram after the e-th state transfer; and Cb represents the available power generation capacity of the system represented by the b-th branch of the system decision diagram after the e-th state transfer;
    5° =[1 ... 11 (2) setting the state of the generator set as 0 L J , the mode as <=[1^1,0^0] k N-k and the available power generation capacity of the system as !=1 at the initial operation time of system;
    wherein 1 represents that the generator set is in the operating mode; 0 represents that the generator set is in the reserve mode; k represents the number of the generator sets in the operating mode in the system at the initial operation time of the system; and G\ represents the capacity of the i-th generator set in the first state;
  3. (3) when the power generation system generates the first state transfer, for the b-th branch, representing the state of the generator set in the ternary variable of the ^=^1,2,1^,] decision diagram as h ] N~b , wherein the mode of the generator set is determined by the capacity of the state of the generator set and a system load demand, that is, if the b-th generator set is transferred from state 1 (capacity is b) to state 2
    G^ (capacity is b ), the total capacity of the system becomes:
    C,‘ = G; + Σ G' i=l,i^b
    2020100796 20 May 2020
  4. (4) after the generator set in the system generates the first state transfer, the generator set possibly generating the second state transfer, wherein if the second state transfer of the system occurs in the P -th element and the state is transferred to a next state, the available system capacity C2 after the second state transfer is:
    C+ Σ G'-p=b ,p _ j /=1, 2 — ' N wherein C2 represents the available system capacity after the second state transfer; Gp and Gp represent the available capacities when the /?-th element is in a third state and the second state; G) represents the available capacity when the z-th element is in the first state; and G^ represents the available capacity when the b-th element is in the second state;
  5. (5) calculating the third and the fourth state transfers of the power generation system in an iterative manner, and the establishment of the decision diagram is stopped until no state transfer element exists in the system or the power generation capacity of the system cannot meet the system load demand after the state transfer.
    4. The method for analyzing operation reliability of the multi-state power generation system based on the decision diagram according to claim 1, wherein specific steps of calculating the occurrence probability of the reliability path in the multi-state decision diagram of the power generation system in the step 3 comprise:
    (1) for a system which only generates two state transfers and the path is for the first generator set to generate two consecutive state transfers, using the following formula to calculate the occurrence probability of the path in which the first generator set generates two consecutive state transfers:
    Path, (T) = J J ff (/, )ff (Z2 - Z, )Rf (Τ’) · C (T)dt,dt, wherein represents the probability density function of the transfer of the i -th element from state j to state (j +1); Ry-j+i 0) represents a function that the reliability of the transfer of the i -th element from state j to state (j +1) changes with time t, and can be obtained by the corresponding probability density
    2020100796 20 May 2020 function fj_j+x(t); T represents the system operation time; 0 represents the initial operation time of system; represents the time when the system generates the first state transfer; and t2 represents the time when the system generates the second state transfer;
    (2) for a system which only generates two state transfer processes, and the second generator set generates the first state transfer and the first generator set generates the second state transfer, using the following formula to calculate the occurrence probability of the path:
    τ τ
    Jf (t2 )R2_2(T -t2 )P2(t, (T -1, (T)· C (T)dt,dt2
    0 /, (3) for a system which does not generate any state transfer process during the system operation time, using the following formula to calculate the available probability of the path:
    Pathh(T) = RUTy-R^Ty
    5. The method for analyzing operation reliability of the multi-state power generation system based on the decision diagram according to claim 1, wherein a formula for calculating the operation reliability of the power generation system in the step 3 is:
    R(T) = YPath„(T) h
    wherein p represents the system operation time; R(T} represents the operation reliability value of the system; and pafli (/) rePresents occurrence probability of the h-th path in the decision diagram.
AU2020100796A 2020-01-09 2020-05-20 Method for analyzing operation reliability of multi-state power generation system based on decision diagram Active AU2020100796A4 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202010021499.X 2020-01-09
CN202010021499.XA CN111259520B (en) 2020-01-09 2020-01-09 Decision diagram-based multi-state power generation system operation reliability analysis method

Publications (1)

Publication Number Publication Date
AU2020100796A4 true AU2020100796A4 (en) 2020-06-25

Family

ID=70954079

Family Applications (1)

Application Number Title Priority Date Filing Date
AU2020100796A Active AU2020100796A4 (en) 2020-01-09 2020-05-20 Method for analyzing operation reliability of multi-state power generation system based on decision diagram

Country Status (2)

Country Link
CN (1) CN111259520B (en)
AU (1) AU2020100796A4 (en)

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106056305B (en) * 2016-06-14 2020-04-03 中国电力工程顾问集团中南电力设计院有限公司 Power generation system reliability rapid evaluation method based on state clustering
CN106202717A (en) * 2016-07-06 2016-12-07 浙江大学 A kind of degeneration system risk probability computational methods based on multimode tree
CN107292019A (en) * 2017-06-16 2017-10-24 浙江大学 A kind of computational methods of fail-safe analysis containing back-up system based on polymorphic decision diagram

Also Published As

Publication number Publication date
CN111259520B (en) 2022-03-25
CN111259520A (en) 2020-06-09

Similar Documents

Publication Publication Date Title
WO2016026355A1 (en) Voltage sag simulation and evaluation method of active power distribution grid
CN112800683B (en) System short-circuit current level evaluation method and system based on convolutional neural network
Li et al. A machine learning-based reliability evaluation model for integrated power-gas systems
Huang et al. Adaptive static equivalences for active distribution networks with massive renewable energy integration: a distributed deep reinforcement learning approach
Jia et al. Reliability analysis of common cause failure multistate system based on CUGF
Zhang et al. A Unified and Flexible Framework of Imperfect Debugging Dependent SRGMs with Testing-Effort.
AU2020100796A4 (en) Method for analyzing operation reliability of multi-state power generation system based on decision diagram
CN114997566A (en) Power grid blocking risk assessment method and system considering node connectivity loss
CN112751336B (en) Comprehensive energy system risk assessment method considering source load fluctuation
Aguilar et al. Predicting probabilistic wind power generation using nonparametric techniques
Tieyan et al. Integrated load forecasting model of multi-energy system based on Markov chain improved neural network
Fu et al. Statistical machine learning model for uncertainty planning of distributed renewable energy sources in distribution networks
Duan et al. High performance computing (hpc) for advanced power system studies
Hossain et al. Efficient learning of voltage control strategies via model-based deep reinforcement learning
Munir et al. Meta-Reinforcement Learning for Proactive Energy Demand Scheduling in Smart City with Edge Computing
Zhu et al. Probabilistic load flow with wind farms using a frequency and duration method
Wang et al. Logistic regression with variable fractional gradient descent method
Zheng et al. Random fuzzy power flow analysis for power system considering the uncertainties of renewable energy and load demands
Kulkarni et al. Investigation of Transmission Line Outage Impact Under Heavy Wind Penetration on LOLE Metric
LU503839B1 (en) Rapid reliability control method and device for ac power system based on state similarity
Ji et al. Probabilistic optimal power flow considering the dependence of multiple wind farms using pair diffusive kernel copula
Gao et al. Mechanism Enhanced Data-Driven Method for Reliability Improvement of Load Margin Estimation
Kotagiri et al. Combined Economic And Emission Dispatch Using Artificial Neural Network
Bui et al. Deep Reinforcement Learning-Based Operation of Distribution Systems Using Surrogate Model
Li et al. A critical note of major parameter extraction methods for proton exchange membrane fuel cell (PEMFC)

Legal Events

Date Code Title Description
FGI Letters patent sealed or granted (innovation patent)