WO2021203738A1 - 考虑需求侧资源分层分散控制的配电系统可靠性计算方法 - Google Patents

考虑需求侧资源分层分散控制的配电系统可靠性计算方法 Download PDF

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WO2021203738A1
WO2021203738A1 PCT/CN2020/138560 CN2020138560W WO2021203738A1 WO 2021203738 A1 WO2021203738 A1 WO 2021203738A1 CN 2020138560 W CN2020138560 W CN 2020138560W WO 2021203738 A1 WO2021203738 A1 WO 2021203738A1
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demand
state
reliability
considering
output
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PCT/CN2020/138560
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French (fr)
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刘敦楠
加鹤萍
王宣元
张�浩
刘蓁
李彦斌
刘明光
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华北电力大学
国网冀北电力有限公司
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Publication of WO2021203738A1 publication Critical patent/WO2021203738A1/zh

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION 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
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063Operations research, analysis or management
    • G06Q10/0639Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/001Methods to deal with contingencies, e.g. abnormalities, faults or failures
    • H02J3/0012Contingency detection
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION 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
    • G06Q50/00Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06Energy or water supply
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381Dispersed generators
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20The dispersed energy generation being of renewable origin
    • H02J2300/28The renewable source being wind energy

Definitions

  • the invention belongs to the technical field of power system reliability evaluation, and relates to a reliability calculation method of a power distribution system, in particular to a reliability calculation method of a power distribution system considering the hierarchical and decentralized control of demand-side resources.
  • Distributed power generation and demand-side loads in the smart grid such as the development of smart devices such as electric vehicles and air conditioners, and the penetration of information and communication technologies, provide demand-side resources including distributed generator demand-side loads to participate in the operation of the power system Condition.
  • demand-side resources in grid operation will bring a series of problems to the safe and reliable operation of the system. For example, once a hierarchical and decentralized control information communication system fails, it will be difficult for demand-side resources in the control area to participate in demand response, thereby affecting the reliability of system operation. Therefore, how to accurately evaluate the impact of hierarchical decentralized control considering information system failures and information delays on demand-side resources participating in the power system is crucial, and it is urgent to propose accurate and efficient reliability calculation methods.
  • the purpose of the present invention is to overcome the shortcomings of the prior art and propose a method for calculating the reliability of the distribution system considering the hierarchical and decentralized control of demand-side resources.
  • the Lz transformation method accurately calculates the reliability of the distribution system considering the hierarchical and decentralized control of demand-side resources.
  • a method for calculating the reliability of a distribution system considering the hierarchical and decentralized control of demand-side resources including the following steps:
  • Step 1 Establish a wind turbine output multi-state model and a wind turbine fault two-state model that consider the randomness of wind speed and the uncertainty of wind turbine failure respectively;
  • Step 2 Combining the wind turbine output multi-state model and the wind turbine fault two-state model established in step 1, establish a distributed wind power multi-state reliability model with multiple wind turbines;
  • Step 3 Establish the reliability model of the information communication system with hierarchical decentralized control considering random failures and information delay;
  • Step 4 Based on the information communication system reliability model of hierarchical decentralized control that considers random failures and information delay established in step 3, establish a demand-side resource reliability model that considers hierarchical decentralized control;
  • Step 5 According to the multi-state reliability model of distributed wind power with multiple wind turbines established in step 2 and the demand-side resource reliability model with hierarchical decentralized control established in step 4, the calculation of hierarchical decentralized control of demand-side load is considered. The reliability value of the distribution system is obtained, and the reliability analysis result of the distribution system is obtained.
  • step 1 includes:
  • t represents the time
  • PO k represents the output of the fan k when the wind speed is v(t)
  • v ci , v c , and v co respectively represent the cut-in wind speed, the rated wind speed and the cut-out wind speed
  • parameters a, b, and c respectively represent the relationship coefficients between the output of the first, second, and third fans and the wind speed
  • step 2 includes:
  • k represents the ordinal number of the wind turbines
  • K represents the total number of wind turbines
  • u represents the state of distributed wind power output
  • WF u represents the distributed wind power output at state u
  • the value of the distributed wind power random variable is WF u .
  • step 3 includes:
  • the i-th local controller fails to control the i-th demand-side resource area; at the same time, considering the control signal delay leading to the demand-side resource response delay ⁇ t lc , we get the Reliability model of the i-th demand-side resource area under the circumstance
  • ⁇ t lc represents the control signal delay time from the i-th local controller to the i-th demand-side resource area, Indicates the availability rate of the information communication system from the i-th local controller to the i-th demand side resource area;
  • z represents the state value of the random variable of the information communication system failure, z 1 means that the responding information communication system is working normally, z 0 indicates a failure of the information communication system;
  • ⁇ t cc represents the delay time of the control signal from the control center to the i-th local controller, Indicates the availability rate of the information communication system from the control center to the i-th local controller, where z represents the state value of the random variable, z 1 represents the normal operation of the responding information communication system, and z 0 represents the information communication system failure;
  • z represents the state value of the random variable of the information communication system failure
  • z 1 represents the normal operation of the responding information communication system
  • z 0 represents the information communication system failure
  • step 4 includes:
  • t represents time
  • t represents time
  • z represents the Lz transform representation of the response volume of the resource area on the demand side
  • z is used to represent the state value of the random variable of the response volume of the resource area on the demand side
  • the value representing the response amount of the resource area on the demand side of the random variable is A response indicating the amount of demand side resources to the i-th zone
  • Y i represents the i-th region in response to the amount of demand side resources state, demand side the i-th total resource region Y i th state of engagement
  • w represents the aggregated state of all demand-side resource areas, and there are a total of W states
  • DR w represents the response amount provided by all demand-side resource areas in state w
  • step 5 the following calculation formula is used to obtain the system reliability analysis result, and the power distribution system reliability analysis result includes the expected value of insufficient system power EENS(t) and the system availability rate AVAI(t):
  • S represents the set of possible system states
  • s is the element in S
  • L represents the demand for demand-side resources of the distribution system system
  • WF u represents the state of the distributed wind power in the distributed wind power multi-state reliability model
  • the output at u, DR w represents the value when the state of the demand side resource area response of the hierarchical decentralized control is w
  • p s (t) is the probability when the system state is s, which can be obtained by the combination of probabilities
  • EENS(t) Represents the expected value of system power shortage that varies with the operating time of the power distribution system
  • AVAI(t) represents the system availability rate that varies with the operating time of the system.
  • the present invention first establishes a wind turbine output multi-state model that considers the randomness of wind speed and a wind turbine failure two-state model that considers the uncertainty of wind turbine failure, and establishes a distributed wind power multi-state reliability model with multiple wind turbines; secondly, considers information For random failures and delays of communication systems, establish a hierarchical and decentralized control information communication system reliability model; on this basis, establish a demand-side resource reliability model that considers hierarchical decentralized control; finally, the calculation considers the demand-side load stratification Reliability index of distributed control power distribution system, analysis system reliability.
  • the present invention considers the impact of hierarchical and decentralized control information communication system on demand-side resources, analyzes the reliability of the corresponding power distribution system, has certain reference value for the construction of smart grid, and better analyzes and evaluates the performance in the new environment.
  • the reliability of the smart grid provides a scientific basis.
  • the present invention considers the impact of hierarchical and decentralized control information communication system on demand-side resources, analyzes the reliability of the corresponding power distribution system, has a certain reference value for the construction of smart grids, and better analyzes and evaluates the performance in the new environment.
  • the reliability of the smart grid provides a scientific basis.
  • the present invention takes the power distribution system considering the hierarchical and decentralized control of demand-side resources as an object, proposes an analytical method based on the Lz transformation, establishes a system multi-state reliability model, and quantitatively analyzes the time-varying reliability of the system, so as to accurately calculate and consider demand Reliability of distribution system with hierarchical and decentralized control of side resources.
  • Figure 1 is a schematic diagram of the hierarchical decentralized control method of the information communication system of the present invention
  • Figure 2 is a diagram of the multi-state reliability model of the distributed wind power system of the present invention.
  • FIG. 3 is a trend chart of AVAI in different scenarios of the system in an embodiment of the present invention.
  • Fig. 4 is a diagram of an expected power shortage (EENS) for a system running time of 100 hours in different scenarios of the system in an embodiment of the present invention.
  • EENS expected power shortage
  • the present invention is directed to a distribution system considering the hierarchical and decentralized control of demand-side resources, and provides a method for calculating the reliability of a distribution system that considers the hierarchical and decentralized control of demand-side resources, including the following steps:
  • Step 1 Establish a wind turbine output multi-state model and a wind turbine fault two-state model that consider the randomness of wind speed and the uncertainty of wind turbine failure respectively;
  • step 1 The specific steps of step 1 include:
  • t represents the time
  • PO k represents the output of the fan k when the wind speed is v(t)
  • v ci , v c , and v co respectively represent the cut-in wind speed, the rated wind speed and the cut-out wind speed
  • parameters a, b, and c respectively represent the relationship coefficients between the output of the first, second, and third fans and the wind speed
  • Step 2 Combining the wind turbine output multi-state model and the wind turbine fault two-state model established in step 1, establish a distributed wind power multi-state reliability model with multiple wind turbines;
  • step 2 The specific steps of step 2 include:
  • k represents the ordinal number of the wind turbines
  • K represents the total number of wind turbines
  • u represents the state of distributed wind power output
  • WF u represents the distributed wind power output at state u
  • Step 3 Establish the reliability model of the information communication system with hierarchical decentralized control considering random failures and information delay;
  • a system model considering the hierarchical and decentralized control of the information communication system is first established, as shown in Figure 1.
  • the system includes a two-layer model, the bottom layer is the control model of the local controller to the demand side resource area, and the upper layer is the control model of the control center to the local controller. Then, according to the established system model considering the hierarchical and distributed control of the information and communication system, the following methods are used to process the reliability model of the information and communication system
  • step 3 The specific steps of step 3 include:
  • the i-th local controller fails to control the i-th demand-side resource area; at the same time, considering the control signal delay leading to the demand-side resource response delay ⁇ t lc , we get the Reliability model of the i-th demand-side resource area under the circumstance
  • ⁇ t lc represents the control signal delay time from the i-th local controller to the i-th demand-side resource area, Indicates the availability rate of the information communication system from the i-th local controller to the i-th demand side resource area;
  • z represents the state value of the random variable of the information communication system failure, z 1 means that the responding information communication system is working normally, z 0 indicates a failure of the information communication system;
  • ⁇ t cc represents the delay time of the control signal from the control center to the i-th local controller, Indicates the availability rate of the information communication system from the control center to the i-th local controller, where z represents the state value of the random variable (information communication system failure), z 1 indicates that the responding information communication system is working normally, and z 0 indicates information communication System failure;
  • z represents the state value of the random variable of the information communication system failure
  • z 1 represents the normal operation of the responding information communication system
  • z 0 represents the information communication system failure
  • Step 4 Based on the information communication system reliability model of hierarchical decentralized control that considers random failures and information delay established in step 3, establish a demand-side resource reliability model that considers hierarchical decentralized control;
  • step 4 The specific steps of step 4 include:
  • t represents time
  • t represents time
  • z represents the Lz transform representation of the response volume of the resource area on the demand side
  • z is used to represent the state value of the random variable of the response volume of the resource area on the demand side
  • the value representing the response amount of the resource area on the demand side of the random variable is A response indicating the amount of demand side resources to the i-th zone
  • Y i represents the i-th region in response to the amount of demand side resources state, demand side the i-th total resource region Y i th state of engagement
  • w represents the aggregated state of all demand-side resource areas, and there are a total of W states
  • DR w represents the response amount provided by all demand-side resource areas in state w
  • Table response is the probability of DR w
  • Step 5 According to the multi-state reliability model of distributed wind power with multiple wind turbines established in step 2 and the demand-side resource reliability model with hierarchical decentralized control established in step 4, the calculation of hierarchical decentralized control of demand-side load is considered. The reliability value of the distribution system is obtained, and the reliability analysis result of the distribution system is obtained.
  • step 5 the following calculation formula is used to obtain the system reliability analysis result, and the power distribution system reliability analysis result includes the expected value of insufficient power of the system EENS(t) and the system availability rate AVAI(t):
  • S represents the set of possible system states
  • s is the element in S
  • L represents the demand for demand-side resources of the distribution system system
  • WF u represents the state of the distributed wind power in the distributed wind power multi-state reliability model
  • the output at u, DR w represents the value when the state of the demand side resource area response of the hierarchical decentralized control is w
  • p s (t) is the probability when the system state is s, which can be obtained by the combination of probabilities
  • EENS(t) Represents the expected value of system power shortage that varies with the operating time of the power distribution system
  • AVAI(t) represents the system availability rate that varies with the operating time of the system.
  • the power distribution system in this embodiment there are 10 wind turbines with a rated power of 2MW to form a distributed power generation subsystem.
  • the wind speed status and the corresponding wind turbine output status and status transfer rate are shown in Table 1.
  • the resource demand is 10MW.
  • the response amount and state transition rate are shown in Table 2.
  • the mean time to failure and mean time to repair of wind turbines and information and communication systems are shown in Table 3.
  • This embodiment analyzes the changes in the reliability analysis results of the power distribution system in different scenarios. Divided into three scenarios:
  • Scenario A Do not consider the delay of the information communication system
  • Scenario B The resource response delay on the demand side is 2 hours;
  • Scenario C The resource response delay on the demand side is 5 hours.
  • the reliability analysis results of the system at different points in time, the system availability (AVAI) and the expected value of insufficient power (EENS) are shown in Figure 3 and Figure 4. It can be seen from Figure 3 that in scenario A that does not consider the resource response delay on the demand side, the system availability (AVAI) decreases with the increase of the system running time; from the comparison of scenarios A, B, and C, It can be seen that when the demand side resources are not put into operation, the system reliability is lower than the put into operation scenario, that is, the information system delay has an impact on the system availability; when the demand side resources are put into operation, the system availability rate suddenly increases .
  • the invention can further improve the reliability analysis theory of the power system, has important significance for the theoretical analysis and engineering application of the power distribution system considering the hierarchical and decentralized control of demand-side resources, and has certain reference value for the engineering construction of the smart grid.
  • this application can be provided as methods, systems, or computer program products. Therefore, this application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, this application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.
  • computer-usable storage media including but not limited to disk storage, CD-ROM, optical storage, etc.
  • These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing equipment to work in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including the instruction device.
  • the device implements the functions specified in one process or multiple processes in the flowchart and/or one block or multiple blocks in the block diagram.
  • These computer program instructions can also be loaded on a computer or other programmable data processing equipment, so that a series of operation steps are executed on the computer or other programmable equipment to produce computer-implemented processing, so as to execute on the computer or other programmable equipment.
  • the instructions provide steps for implementing the functions specified in one process or multiple processes in the flowchart and/or one block or multiple blocks in the block diagram.

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Abstract

一种考虑需求侧资源分层分散控制的配电系统可靠性计算方法,包括以下步骤:步骤1、建立分别考虑风速随机性和风机故障不确定性的风机出力多状态模型和风机故障两状态模型;步骤2、建立含多个风机的分布式风电多状态可靠性模型;步骤3、建立考虑随机故障和信息延时的分层分散控制的信息通讯系统可靠性模型;步骤4、建立考虑分层分散控制的需求侧资源可靠性模型;步骤5、计算考虑需求侧负荷分层分散控制的配电系统可靠性值,获得配电系统可靠性分析结果。该方法能够精确计算考虑需求侧资源分层分散控制的配电系统可靠性。

Description

考虑需求侧资源分层分散控制的配电系统可靠性计算方法 技术领域
本发明属于电力系统可靠性评估技术领域,涉及配电系统可靠性计算方法,尤其是一种考虑需求侧资源分层分散控制的配电系统可靠性计算方法。
背景技术
智能电网中的分布式发电及需求侧负荷,如,电动汽车、空调等智能设备的发展以及信息通讯技术的渗透,为包括分布式发电机需求侧负荷在内的需求侧资源参与电力系统运行提供了条件。然而,需求侧资源参与电网运行会给系统安全可靠运行带来一系列问题。例如,分层分散控制的信息通讯系统一旦发生故障,使得控制区域的需求侧资源难以参与需求响应,从而影响系统运行的可靠性。因此,如何精确评估考虑信息系统故障及信息延时的分层分散控制对需求侧资源参与电力系统的影响至关重要,亟待提出精确高效的可靠性计算方法。
发明内容
本发明的目的在于克服现有技术的不足,提出一种考虑需求侧资源分层分散控制的配电系统可靠性计算方法,以考虑需求侧资源分层分散控制的配电系统为对象,能够利用Lz变换方法精确计算考虑需求侧资源分层分散控制的配电系统可靠性。
本发明解决其现实问题是采取以下技术方案实现的:
一种考虑需求侧资源分层分散控制的配电系统可靠性计算方法,包括以下步骤:
步骤1、建立分别考虑风速随机性和风机故障不确定性的风机出力多状态模型和风机故障两状态模型;
步骤2、结合步骤1所建立的风机出力多状态模型和风机故障两状态模型,建立含多个风机的分布式风电多状态可靠性模型;
步骤3、建立考虑随机故障和信息延时的分层分散控制的信息通讯系统可靠性模型;
步骤4、基于步骤3所建立的考虑随机故障和信息延时的分层分散控制的信息通讯系统可靠性模型,建立考虑分层分散控制的需求侧资源可靠性模型;
步骤5、根据步骤2所建立的含多个风机的分布式风电多状态可靠性模型和步骤4所建立的考虑分层分散控制的需求侧资源可靠性模型计算考虑需求侧负荷分层分散控制的配电系统可靠性值,获得配电系统可靠性分析结果。
而且,所述步骤1的具体步骤包括:
(1)将风速的随机性与风机出力的关系用如下公式表示:
Figure PCTCN2020138560-appb-000001
其中,t表示时间,PO k表示当风速为v(t)时风机k的出力;v ci,v c,v co分别表示切入风速、额定风速以及切出风速;
Figure PCTCN2020138560-appb-000002
表示风机k的额定出力;参数a,b,c分别表示第一、第二、第三风机出力与风速关系系数;
(2)由风速的随机性与风机出力的关系公式,利用Lz变换对上述公式处理得到考虑风速随机性的风机出力多状态模型:
Figure PCTCN2020138560-appb-000003
其中,t表示时间,
Figure PCTCN2020138560-appb-000004
表示风机k出力的Lz变换表示形式,j k表示风机k的出力状态,风机k共有J k个出力状态,
Figure PCTCN2020138560-appb-000005
表示在风机k出力状态在j k时的时变概率值;
Figure PCTCN2020138560-appb-000006
表示风机k在状态j k的出力,此处的z用来表示风机出力的随机变量状态值,
Figure PCTCN2020138560-appb-000007
表示风机出力的取值为
Figure PCTCN2020138560-appb-000008
(3)考虑风机故障不确定性的风机故障两状态模型如下表示:
Figure PCTCN2020138560-appb-000009
其中,
Figure PCTCN2020138560-appb-000010
为风机k故障的Lz变换表示形式,p r(t)表示风机k的可用概率,且0≤p r(t)≤1;当风机k发生故障时,p r(t)为0;此处的z表示风机故障的随机变量状态值,z 0表示风机发生故障使得风机出力为0。
而且,所述步骤2的具体步骤包括:
(1)综合考虑风速的随机性以及风机故障将风机出力多状态模型
Figure PCTCN2020138560-appb-000011
和风机故障两状态模型
Figure PCTCN2020138560-appb-000012
利用串联结构通用生成算子Ω s获得风机多状态可靠性模型,表示为
Figure PCTCN2020138560-appb-000013
Figure PCTCN2020138560-appb-000014
(2)再利用并联结构通用生成算子Ω p获得含K个相同风机的分布式风电多状态可靠性模型,表示为L wf(z,t):
Figure PCTCN2020138560-appb-000015
其中,k表示风机的序数,K表示风机的总数,u表示分布式风电出力的状态,且共有U个状态,WF u表示该分布式风电在状态u时出力,
Figure PCTCN2020138560-appb-000016
表示分布式风电出力为WF u时的概率,
Figure PCTCN2020138560-appb-000017
表示分布式风电随机变量的值为WF u
而且,所述步骤3的具体步骤包括:
(1)考虑信息通讯系统中的随机故障使得第i个本地控制器对第i个需求侧资源区的控制失效;同时,考虑控制信号延时导致需求侧资源的响应延时Δt lc,得到该情况下第i个需求侧资源区的可靠性模型
Figure PCTCN2020138560-appb-000018
Figure PCTCN2020138560-appb-000019
其中,Δt lc表示第i个本地控制器到第i个需求侧资源区的控制信号延迟时间,
Figure PCTCN2020138560-appb-000020
表示第i个本地控 制器到第i个需求侧资源区的信息通讯系统的可用率;此处的z表示信息通讯系统故障的随机变量状态值,z 1表示响应的信息通讯系统正常工作,z 0表示信息通讯系统的故障;
(2)考虑信息通讯系统中的随机故障使得控制中心对第i个本地控制器的控制失效,得到该情况下第i个用需求侧资源区的可靠性模型
Figure PCTCN2020138560-appb-000021
Figure PCTCN2020138560-appb-000022
其中,Δt cc表示控制中心到第i个本地控制器的控制信号延迟时间,
Figure PCTCN2020138560-appb-000023
表示控制中心到第i个本地控制器的信息通讯系统的可用率,此处的z表示随机变量状态值,z 1表示响应的信息通讯系统正常工作,z 0表示信息通讯系统的故障;
(3)考虑信息通讯系统中的分层分区控制随机故障的影响,利用串联结构通用生成算子Ω s获得第i个需求侧资源区的考虑随机故障和信息延时的分层分散控制的信息通讯系统可靠性模型
Figure PCTCN2020138560-appb-000024
Figure PCTCN2020138560-appb-000025
其中,z表示信息通讯系统故障的随机变量状态值,z 1表示响应的信息通讯系统正常工作,z 0表示信息通讯系统的故障。
而且,所述步骤4的具体步骤包括:
(1)将未考虑信息系统故障的需求侧资源响应量的可靠性模型
Figure PCTCN2020138560-appb-000026
表示为:
Figure PCTCN2020138560-appb-000027
其中,t表示时间,
Figure PCTCN2020138560-appb-000028
表示需求侧资源区响应量的Lz变换表示形式,此处的z用来表示需求侧资源区响应量的随机变量状态值,
Figure PCTCN2020138560-appb-000029
表示随机变量需求侧资源区响应量的取值为
Figure PCTCN2020138560-appb-000030
表示第i个需求侧资源区的响应量;y i表示第i个需求侧资源区响应量的状态,第i个需求侧资源区共有Y i个参与度状态;
Figure PCTCN2020138560-appb-000031
表示在第i个需求侧资源区的响应量在y i时的时变概率值;
(2)利用串联结构通用生成算子Ω s结合步骤3中的考虑随机故障和信息延时的分层分散控制的信息通讯系统可靠性模型和未考虑信息系统故障的需求侧资源响应量的可靠性模型获得考虑需求侧资源区响应量的可靠性模型,表示为
Figure PCTCN2020138560-appb-000032
Figure PCTCN2020138560-appb-000033
其中,t表示时间,
Figure PCTCN2020138560-appb-000034
表示需求侧资源区实际响应量的Lz变换表示形式;
(3)对于配电系统内的N个需求侧资源区,聚合后的需求侧资源可靠性模型L dr(z,t)表示为:
Figure PCTCN2020138560-appb-000035
其中,w表示所有需求侧资源区聚合后的状态,且共有W个状态,DR w表示所有需求侧资源区在状态w时提供的响应量,
Figure PCTCN2020138560-appb-000036
表示响应量为的DR w时的概率,
Figure PCTCN2020138560-appb-000037
表示聚合后需求侧资源区响应量作为随机变量的值为DR w
而且,所述步骤5的具体方法为:采用以下计算公式获得系统可靠性分析结果,配电系统可靠性分析结果包括系统电量不足期望值EENS(t)以及系统可用率AVAI(t):
Figure PCTCN2020138560-appb-000038
其中,S表示可能具有的系统状态集合,s为S中的元素;L表示配电系统系统对需求侧资源的需求量,WF u表示分布式风电多状态可靠性模型中分布式风电在状态为u时的出力,DR w表示分层分散控制的需求侧资源区响应量的状态为w时的值,p s(t)为系统状态为s时的概率,可由概率组合得到;EENS(t)表示随配电系统运行时间变化的系统电量不足期望值,AVAI(t)表示随系统运行时间变化的系统可用率。
本发明的优点和有益效果:
1、本发明首先建立考虑风速随机性的风机出力多状态模型和考虑风机故障不确定性的风机故障两状态模型,结合建立含多个风机的分布式风电多状态可靠性模型;其次,考虑信息通讯系统的随机故障和延时,建立分层分散控制的信息通讯系统可靠性模型;在此基础上,建立考虑分层分散控制的需求侧资源可靠性模型; 最后,计算考虑需求侧负荷分层分散控制的配电系统可靠性指标,分析系统可靠性。本发明考虑分层分散控制的信息通信系统对需求侧资源的影响,分析相应的配电系统可靠性,对智能电网的建设有一定的参考价值,为更好地分析及评估在新环境下的智能电网可靠性提供了科学依据。本发明考虑分层分散控制的信息通信系统对需求侧资源的影响,分析相应的配电系统可靠性,对智能电网的建设有一定的参考价值,为更好地分析及评估在新环境下的智能电网可靠性提供了科学依据。
2、本发明以考虑需求侧资源分层分散控制的配电系统为对象,提出基于Lz变换的解析方法,建立系统多状态可靠性模型,定量分析系统的时变可靠性,从而精确计算考虑需求侧资源分层分散控制的配电系统可靠性。
附图说明
图1是本发明的信息通讯系统分层分散控制方式示意图;
图2是本发明的分布式风电系统多状态可靠性模型图;
图3是本发明的实施例中系统不同场景下可用率(AVAI)趋势图;
图4是本发明的实施例中系统不同场景下系统运行时间为100小时的期望电量缺额(EENS)图。
具体实施方式
以下结合附图对本发明实施例作进一步详述:
本发明是针对考虑需求侧资源分层分散控制的配电系统,提供了一种考虑需求侧资源分层分散控制的配电系统可靠性计算方法,包括以下步骤:
步骤1、建立分别考虑风速随机性和风机故障不确定性的风机出力多状态模型和风机故障两状态模型;
所述步骤1的具体步骤包括:
(1)将风速的随机性与风机出力的关系用如下公式表示:
Figure PCTCN2020138560-appb-000039
其中,t表示时间,PO k表示当风速为v(t)时风机k的出力;v ci,v c,v co分别表示切入风速、额定风速以及切出风速;
Figure PCTCN2020138560-appb-000040
表示风机k的额定出力;参数a,b,c分别表示第一、第二、第三风机出力与风速关系系数;
(2)由风速的随机性与风机出力的关系公式,利用Lz变换对上述公式处理得到考虑风速随机性的风机出力多状态模型:
Figure PCTCN2020138560-appb-000041
其中,t表示时间,
Figure PCTCN2020138560-appb-000042
表示风机k出力的Lz变换表示形式,j k表示风机k的出力状态,风机k共有J k个出力状态,
Figure PCTCN2020138560-appb-000043
表示在风机k出力状态在j k时的时变概率值;
Figure PCTCN2020138560-appb-000044
表示风机k在状态j k的出力,此处的z用来表示风机出力的随机变量状态值,
Figure PCTCN2020138560-appb-000045
表示风机出力的取值为
Figure PCTCN2020138560-appb-000046
(3)考虑风机故障不确定性的风机故障两状态模型如下表示:
Figure PCTCN2020138560-appb-000047
其中,
Figure PCTCN2020138560-appb-000048
为风机k故障的Lz变换表示形式,p r(t)表示风机k的可用概率,且0≤p r(t)≤1;当风机k发生故障时,p r(t)为0;此处的z表示风机故障的随机变量状态值,z 0表示风机发生故障使得风机出力为0;
步骤2、结合步骤1所建立的风机出力多状态模型和风机故障两状态模型,建立含多个风机的分布式风电多状态可靠性模型;
所述步骤2的具体步骤包括:
(1)综合考虑风速的随机性以及风机故障将风机出力多状态模型
Figure PCTCN2020138560-appb-000049
和风机故障两状态模型
Figure PCTCN2020138560-appb-000050
利用串联结构通用生成算子Ω s获得风机多状态可靠性模型,表示为
Figure PCTCN2020138560-appb-000051
Figure PCTCN2020138560-appb-000052
(2)再利用并联结构通用生成算子Ω p获得含K个相同风机的分布式发电多状态可靠性模型,表示为L wf(z,t):
Figure PCTCN2020138560-appb-000053
其中,k表示风机的序数,K表示风机的总数,u表示分布式风电出力的状态,且共有U个状态,WF u表示该分布式风电在状态u时出力,
Figure PCTCN2020138560-appb-000054
表示分布式风电出力为WF u时的概率,
Figure PCTCN2020138560-appb-000055
表示分布式风电随机变量的值为WF u
步骤3、建立考虑随机故障和信息延时的分层分散控制的信息通讯系统可靠性模型;
在本实施例中,先建立考虑信息通讯系统分层分散控制的系统模型,如图1所示。该系统中包括两层模型,底层为本地控制器对需求侧资源区的控制模型,上层为控制中心对本地控制器的控制模型。再根据所建立的考虑信息通讯系统分层分散控制的系统模型采用以下方式进行处理获得信息通讯系统可靠性模型
Figure PCTCN2020138560-appb-000056
所述步骤3的具体步骤包括:
(1)考虑信息通讯系统中的随机故障使得第i个本地控制器对第i个需求侧资源区的控制失效;同时,考虑控制信号延时导致需求侧资源的响应延时Δt lc,得到该情况下第i个需求侧资源区的可靠性模型
Figure PCTCN2020138560-appb-000057
Figure PCTCN2020138560-appb-000058
其中,Δt lc表示第i个本地控制器到第i个需求侧资源区的控制信号延迟时间,
Figure PCTCN2020138560-appb-000059
表示第i个本地控制器到第i个需求侧资源区的信息通讯系统的可用率;此处的z表示信息通讯系统故障的随机变量状态值,z 1表示响应的信息通讯系统正常工作,z 0表示信息通讯系统的故障;
(2)考虑信息通讯系统中的随机故障使得控制中心对第i个本地控制器的控制失效,得到该情况下第i个用需求侧资源区的可靠性模型
Figure PCTCN2020138560-appb-000060
Figure PCTCN2020138560-appb-000061
其中,Δt cc表示控制中心到第i个本地控制器的控制信号延迟时间,
Figure PCTCN2020138560-appb-000062
表示控制中心到第i个本地控制器的信息通讯系统的可用率,此处的z表示随机变量状态值(信息通讯系统故障),z 1表示响应的信息通讯系统正常工作,z 0表示信息通讯系统的故障;
(3)考虑信息通讯系统中的分层分区控制随机故障的影响,利用串联结构通用生成算子Ω s获得第i个需求侧资源区的考虑随机故障和信息延时的分层分散控制的信息通讯系统可靠性模型
Figure PCTCN2020138560-appb-000063
Figure PCTCN2020138560-appb-000064
其中,z表示信息通讯系统故障的随机变量状态值,z 1表示响应的信息通讯系统正常工作,z 0表示信息通讯系统的故障。
步骤4、基于步骤3所建立的考虑随机故障和信息延时的分层分散控制的信息通讯系统可靠性模型,建立考虑分层分散控制的需求侧资源可靠性模型;
所述步骤4的具体步骤包括:
(1)将未考虑信息系统故障的需求侧资源响应量的可靠性模型
Figure PCTCN2020138560-appb-000065
表示为:
Figure PCTCN2020138560-appb-000066
其中,t表示时间,
Figure PCTCN2020138560-appb-000067
表示需求侧资源区响应量的Lz变换表示形式,此处的z用来表示需求侧资源区响应量的随机变量状态值,
Figure PCTCN2020138560-appb-000068
表示随机变量需求侧资源区响应量的取值为
Figure PCTCN2020138560-appb-000069
表示第i个需求侧资源区的响应量;y i表示第i个需求侧资源区响应量的状态,第i个需求侧资源区共有Y i个参与度状态;
Figure PCTCN2020138560-appb-000070
表示在第i个需求侧资源区的响应量在y i时的时变概率值;
(2)利用串联结构通用生成算子Ω s结合步骤3中的考虑随机故障和信息延时的分层分散控制的信息通讯系统可靠性模型和未考虑信息系统故障的需求侧资源响应量的可靠性模型获得考虑需求侧资源区响应量的可靠性模型,表示为
Figure PCTCN2020138560-appb-000071
Figure PCTCN2020138560-appb-000072
其中,t表示时间,
Figure PCTCN2020138560-appb-000073
表示需求侧资源区实际响应量的Lz变换表示形式;
(3)对于配电系统内的N个需求侧资源区,聚合后的需求侧资源可靠性模型L dr(z,t)表示为:
Figure PCTCN2020138560-appb-000074
其中,w表示所有需求侧资源区聚合后的状态,且共有W个状态,DR w表示所有需求侧资源区在状态w时提供的响应量,
Figure PCTCN2020138560-appb-000075
表响应量为的DR w时的概率,
Figure PCTCN2020138560-appb-000076
表示聚合后需求侧资源区响应量作为随机变量的值为DR w
步骤5、根据步骤2所建立的含多个风机的分布式风电多状态可靠性模型和步骤4所建立的考虑分层分散控制的需求侧资源可靠性模型计算考虑需求侧负荷分层分散控制的配电系统可靠性值,获得配电系统可靠性分析结果。
所述步骤5的具体方法为:采用以下计算公式获得系统可靠性分析结果,配电系统可靠性分析结果包括系统电量不足期望值EENS(t)以及系统可用率AVAI(t):
Figure PCTCN2020138560-appb-000077
Figure PCTCN2020138560-appb-000078
其中,S表示可能具有的系统状态集合,s为S中的元素;L表示配电系统系统对需求侧资源的需求量,WF u表示分布式风电多状态可靠性模型中分布式风电在状态为u时的出力,DR w表示分层分散控制的需求侧资源区响应量的状态为w时的值,p s(t)为系统状态为s时的概率,可由概率组合得到;EENS(t)表示随配电系统运行时间变化的系统电量不足期望值,AVAI(t)表示随系统运行时间变化的系统可用率。
下面结合具体的实施例,对本发明作进一步说明:
本实施例中的配电系统中有10台额定功率为2MW的风机构成分布式发电子系统,风速的状态以及对应 的风机出力状态和状态转移率如表1所示,配电系统对需求侧资源的需求量为10MW。系统中有4个可参与需求响应的需求侧资源区,其响应量及状态转移率如表2所示。风机以及信息通讯系统的平均故障时间以及平均维修时间如表3所示。
表1 风速/风机出力状态及状态转移率
转移率 0MW 0.5MW 1MW 1.5MW 2MW
0MW 0.039 0.013 0.008 0.018
0.5MW 0.365 0.151 0.045 0.097
1MW 0.122 0.220 0.192 0.155
1.5MW 0.038 0.093 0.185 0.359
2MW 0.016 0.012 0.016 0.067
表2 需求侧资源的备用容量及状态转移率
Figure PCTCN2020138560-appb-000079
表3 风机及信息通讯系统的可靠性参数
Figure PCTCN2020138560-appb-000080
本实施例分析不同场景下,配电系统可靠性分析结果的变化情况。分为三个场景:
场景A:不考虑信息通讯系统的延时;
场景B:需求侧资源响应延时为2小时;
场景C:需求侧资源响应延时为5小时。
本实施例按照发明内容描述的方法进行实施,具体进行可靠性分析计算步骤如下:
1)建立分别考虑风速随机性和风机故障不确定性的风机出力多状态模型和风机故障两状态模型;
2)结合风机出力多状态模型和风机故障两状态模型,建立含多个风机的分布式风电多状态可靠性模型,如图2所示;
3)建立考虑随机故障和信息延时的分层分散控制的信息通讯系统可靠性模型;
4)建立考虑分层分散控制的需求侧资源可靠性模型;
5)计算考虑需求侧负荷分层分散控制的配电系统可靠性指标。
根据以上步骤,不同时间点下,系统的可靠性分析结果系统可用率(AVAI)以及电量不足期望值(EENS)如图3和图4所示。从图3中可以看出,在不考虑需求侧资源响应延时的场景A中,系统可用率(AVAI)随系统运行时间的增大而减小;从场景A、B、C中的对比可以看出,当需求侧资源未投入系统运行时,系统可靠性低于投入运行的场景,即信息系统延时对系统可用率造成了影响;当需求侧资源投入运行后,系统可用率突然增大。从图4中可以看出,当系统运行时间为100小时时,需求侧资源响应延时较长的场景电量不足期望值明显高于需求侧资源响应延时较短的场景,由此也可以看出信息系统对考虑需求侧资源的配电系统可靠性重要影响。
本发明可进一步完善电力系统可靠性分析理论,对考虑需求侧资源分层分散控制的配电系统理论分析及工程应用具有重要意义,对智能电网的工程建设有一定的参考价值。
本领域内的技术人员应明白,本申请的实施例可提供为方法、系统、或计算机程序产品。因此,本申请可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且,本申请可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本申请是参照根据本申请实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器,使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中,使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品,该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上,使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理,从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。

Claims (6)

  1. 一种考虑需求侧资源分层分散控制的配电系统可靠性计算方法,其特征在于:包括以下步骤:
    步骤1、建立分别考虑风速随机性和风机故障不确定性的风机出力多状态模型和风机故障两状态模型;
    步骤2、结合步骤1所建立的风机出力多状态模型和风机故障两状态模型,建立含多个风机的分布式风电多状态可靠性模型;
    步骤3、建立考虑随机故障和信息延时的分层分散控制的信息通讯系统可靠性模型;
    步骤4、基于步骤3所建立的考虑随机故障和信息延时的分层分散控制的信息通讯系统可靠性模型,建立考虑分层分散控制的需求侧资源可靠性模型;
    步骤5、根据步骤2所建立的含多个风机的分布式风电多状态可靠性模型和步骤4所建立的考虑分层分散控制的需求侧资源可靠性模型计算考虑需求侧负荷分层分散控制的配电系统可靠性值,获得配电系统可靠性分析结果。
  2. 根据权利要求1所述的一种考虑需求侧资源分层分散控制的配电系统可靠性计算方法,其特征在于:所述步骤1的具体步骤包括:
    (1)将风速的随机性与风机出力的关系用如下公式表示:
    Figure PCTCN2020138560-appb-100001
    其中,t表示时间,PO k表示当风速为v(t)时风机k的出力;v ci,v c,v co分别表示切入风速、额定风速以及切出风速;
    Figure PCTCN2020138560-appb-100002
    表示风机k的额定出力;参数a,b,c分别表示第一、第二、第三风机出力与风速关系系数;
    (2)由风速的随机性与风机出力的关系公式,利用Lz变换对上述公式处理得到考虑风速随机性的风机出力多状态模型:
    Figure PCTCN2020138560-appb-100003
    其中,t表示时间,
    Figure PCTCN2020138560-appb-100004
    表示风机k出力的Lz变换表示形式,j k表示风机k的出力状态,风机k共有J k个出力状态,
    Figure PCTCN2020138560-appb-100005
    表示在风机k出力状态在j k时的时变概率值;
    Figure PCTCN2020138560-appb-100006
    表示风机k在状态j k的出力,此处的z用来表示风机出力的随机变量状态值,
    Figure PCTCN2020138560-appb-100007
    表示风机出力的取值为
    Figure PCTCN2020138560-appb-100008
    (3)考虑风机故障不确定性的风机故障两状态模型如下表示:
    Figure PCTCN2020138560-appb-100009
    其中,
    Figure PCTCN2020138560-appb-100010
    为风机k故障的Lz变换表示形式,p r(t)表示风机k的可用概率,且0≤p r(t)≤1;当风机k发生故障时,p r(t)为0;此处的z表示风机故障的随机变量状态值,z 0表示风机发生故障使得风机出力为0。
  3. 根据权利要求2所述的一种考虑需求侧资源分层分散控制的配电系统可靠性计算方法,其特征在于:所述步骤2的具体步骤包括:
    (1)综合考虑风速的随机性以及风机故障将风机出力多状态模型
    Figure PCTCN2020138560-appb-100011
    和风机故障两状态模型
    Figure PCTCN2020138560-appb-100012
    利用串联结构通用生成算子Ω s获得风机多状态可靠性模型,表示为
    Figure PCTCN2020138560-appb-100013
    Figure PCTCN2020138560-appb-100014
    (2)再利用并联结构通用生成算子Ω p获得含K个相同风机的分布式风电多状态可靠性模型,表示为L wf(z,t):
    Figure PCTCN2020138560-appb-100015
    其中,k表示风机的序数,K表示风机的总数,u表示分布式风电出力的状态,WF u表示该分布式风电在状态u时出力,
    Figure PCTCN2020138560-appb-100016
    表示分布式风电出力为WF u时的概率,
    Figure PCTCN2020138560-appb-100017
    表示分布式风电随机变量的值为 WF u
  4. 根据权利要求1所述的一种考虑需求侧资源分层分散控制的配电系统可靠性计算方法,其特征在于:所述步骤3的具体步骤包括:
    (1)考虑信息通讯系统中的随机故障使得第i个本地控制器对第i个需求侧资源区的控制失效;同时,考虑控制信号延时导致需求侧资源的响应延时Δt lc,得到该情况下第i个需求侧资源区的可靠性模型
    Figure PCTCN2020138560-appb-100018
    Figure PCTCN2020138560-appb-100019
    其中,Δt lc表示第i个本地控制器到第i个需求侧资源区的控制信号延迟时间,
    Figure PCTCN2020138560-appb-100020
    表示第i个本地控制器到第i个需求侧资源区的信息通讯系统的可用率;此处的z表示信息通讯系统故障的随机变量状态值,z 1表示响应的信息通讯系统正常工作,z 0表示信息通讯系统的故障;
    (2)考虑信息通讯系统中的随机故障使得控制中心对第i个本地控制器的控制失效,得到该情况下第i个用需求侧资源区的可靠性模型
    Figure PCTCN2020138560-appb-100021
    Figure PCTCN2020138560-appb-100022
    其中,Δt cc表示控制中心到第i个本地控制器的控制信号延迟时间,
    Figure PCTCN2020138560-appb-100023
    表示控制中心到第i个本地控制器的信息通讯系统的可用率,此处的z表示随机变量状态值,z 1表示响应的信息通讯系统正常工作,z 0表示信息通讯系统的故障;
    (3)考虑信息通讯系统中的分层分区控制随机故障的影响,利用串联结构通用生成算子Ω s获得第i个需求侧资源区的考虑随机故障和信息延时的分层分散控制的信息通讯系统可靠性模型
    Figure PCTCN2020138560-appb-100024
    Figure PCTCN2020138560-appb-100025
    其中,z表示信息通讯系统故障的随机变量状态值,z 1表示响应的信息通讯系统正常工作,z 0表示信息通讯系统的故障。
  5. 根据权利要求4所述的一种考虑需求侧资源分层分散控制的配电系统可靠性计算方法,其特征在于:所述步骤4的具体步骤包括:
    (1)将未考虑信息系统故障的需求侧资源响应量的可靠性模型
    Figure PCTCN2020138560-appb-100026
    表示为:
    Figure PCTCN2020138560-appb-100027
    其中,t表示时间,
    Figure PCTCN2020138560-appb-100028
    表示需求侧资源区响应量的Lz变换表示形式,此处的z用来表示需求侧资源区响应量的随机变量状态值,
    Figure PCTCN2020138560-appb-100029
    表示随机变量需求侧资源区响应量的取值为
    Figure PCTCN2020138560-appb-100030
    表示第i个需求侧资源区的响应量;y i表示第i个需求侧资源区响应量的状态,第i个需求侧资源区共有Y i个参与度状态;
    Figure PCTCN2020138560-appb-100031
    表示在第i个需求侧资源区的响应量在y i时的时变概率值;
    (2)利用串联结构通用生成算子Ω s结合步骤3中的考虑随机故障和信息延时的分层分散控制的信息通讯系统可靠性模型和未考虑信息系统故障的需求侧资源响应量的可靠性模型获得考虑需求侧资源区响应量的可靠性模型,表示为
    Figure PCTCN2020138560-appb-100032
    Figure PCTCN2020138560-appb-100033
    其中,t表示时间,
    Figure PCTCN2020138560-appb-100034
    表示需求侧资源区实际响应量的Lz变换表示形式;
    (3)对于配电系统内的N个需求侧资源区,聚合后的需求侧资源可靠性模型L dr(z,t)表示为:
    Figure PCTCN2020138560-appb-100035
    其中,w表示所有需求侧资源区聚合后的状态,且共有W个状态,DR w表示所有需求侧资源区在状态w时提供的响应量,
    Figure PCTCN2020138560-appb-100036
    表示响应量为的DR w时的概率,
    Figure PCTCN2020138560-appb-100037
    表示聚合后需求侧资源区响应量作为随机变量的值为DR w
  6. 根据权利要求1所述的一种考虑需求侧资源分层分散控制的配电系统可靠性计算方法,其特征在于:所述步骤5的具体方法为:采用以下计算公式获得系统可靠性分析结果,配电系统可靠性分析结果包括系统电量不足期望值EENS(t)以及系统可用率AVAI(t):
    Figure PCTCN2020138560-appb-100038
    Figure PCTCN2020138560-appb-100039
    其中,S表示可能具有的系统状态集合,s为S中的元素;L表示配电系统系统对需求侧资源的需求量,WF u表示分布式风电多状态可靠性模型中分布式风电在状态为u时的出力,DR w表示分层分散控制的需求侧资源区响应量的状态为w时的值,p s(t)为系统状态为s时的概率,可由概率组合得到;EENS(t)表示随配电系统运行时间变化的系统电量不足期望值,AVAI(t)表示随系统运行时间变化的系统可用率。
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