WO2020082409A1 - 一种输配电网非迭代的分解协调动态调度方法 - Google Patents

一种输配电网非迭代的分解协调动态调度方法 Download PDF

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WO2020082409A1
WO2020082409A1 PCT/CN2018/113461 CN2018113461W WO2020082409A1 WO 2020082409 A1 WO2020082409 A1 WO 2020082409A1 CN 2018113461 W CN2018113461 W CN 2018113461W WO 2020082409 A1 WO2020082409 A1 WO 2020082409A1
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distribution network
transmission
power
transmission grid
grid
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PCT/CN2018/113461
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English (en)
French (fr)
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吴文传
王彬
蔺晨晖
张伯明
孙宏斌
郭庆来
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清华大学
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Priority to US16/736,313 priority Critical patent/US11239658B2/en
Publication of WO2020082409A1 publication Critical patent/WO2020082409A1/zh

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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/001—Methods to deal with contingencies, e.g. abnormalities, faults or failures
    • H02J3/00125—Transmission line or load transient problems, e.g. overvoltage, resonance or self-excitation of inductive loads
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/007—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/48—Controlling the sharing of the in-phase component
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • 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
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
    • 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
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • 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
    • 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
    • Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
    • Y04S40/20—Information technology specific aspects, e.g. CAD, simulation, modelling, system security

Definitions

  • the feedback of this application relates to a non-iterative decomposition and coordination dynamic scheduling method for transmission and distribution networks, which belongs to the technical field of power system operation control.
  • the applicant's patent with application number 201710087438.1 discloses a dynamic economic dispatch method for transmission and distribution network coordination based on multi-parameter programming. This method uses repeated iterations between transmission and distribution networks to perform transmission and distribution.
  • the disadvantage of dynamic scheduling of grid coordination is that iterative iterations between transmission and distribution networks require continuous information interaction, which is highly dependent on communication between transmission and distribution networks, and the implementation of methods is susceptible to communication failures and blockages. influences.
  • the purpose of feedback in this application is to propose a non-iterative decomposition and coordination dynamic scheduling method for transmission and distribution networks, to improve the existing scheduling method of transmission and distribution networks, without repeated iterations between transmission and distribution networks, to coordinate the dynamic scheduling of transmission and distribution
  • the problem is solved and the global optimal solution is obtained through two limited information interactions between the transmission network and the distribution network.
  • the non-iterative decomposition and coordination dynamic scheduling method for transmission and distribution network proposed by the feedback of this application includes the following steps:
  • i is any node in the transmission grid or distribution network
  • T represents the set of dynamic scheduling moments
  • G represents the set of nodes where the generator set in the transmission grid or distribution network
  • DIST represents the distribution network number set
  • pg i, t represents the active power of the generator set connected to node i in the transmission grid or distribution network at the dynamic dispatch time t
  • the superscript trans represents the transmission grid
  • the superscript dist represents the distribution network with number k
  • the function C i ( ⁇ ) Represents the generating cost function of the generator set connected to node i, which is expressed by a quadratic function as:
  • a 0, i , a 1, i and a 2, i represent the constant term coefficient, the first term coefficient and the second term coefficient of the power generation cost of the generator set connected to the node i, the constant term coefficient, the first term coefficient and the The quadratic coefficient is the inherent parameter of the generator set;
  • B represents the set of boundary nodes connecting the transmission grid and the distribution grid in the transmission grid
  • D represents the set of load nodes in the transmission grid or distribution network
  • PD i, t represents the load connected to the node i at the dynamic scheduling time t Predictive value
  • n is the line number
  • PL n is the transmission capacity of any line n in the transmission grid
  • SF ni represents the transfer distribution factor from node i to line n
  • the transfer distribution factor is the grid topology parameter, obtained from the grid dispatch center
  • the rotation reserve constraints are:
  • ru i, t and rd i, t are the rotation capacity of the generator set connected to the node i and the reserve capacity of the rotation down at the dynamic scheduling time t, respectively
  • RU i and RD i are the power generation of the connection node i
  • ⁇ t is the time interval of dynamic dispatch
  • the value of the time interval is determined by the power dispatch demand
  • PG i are the upper limit and the lower limit of active power of the generator set connected to node i, respectively
  • SRU t and SRD t are the upward rotation reserve capacity requirement and downward rotation reserve capacity requirement of the transmission grid or distribution network, respectively;
  • the constraint conditions for the climbing of the generator set in the transmission grid are:
  • the active power constraints of the generator set in the transmission grid are:
  • the constraint conditions of power flow in the distribution network are:
  • i: i ⁇ j represents the set of head-end nodes whose end node is the branch of node j, p i ⁇ j, t represents the active power flow from node i to node j in the distribution network, l i ⁇ j , t represents the active power loss from node i to node j in the distribution network, Represents the active power input of node j in the distribution network, N dist, k represents the set of node numbers of the distribution network, and the active power input of node j And active power loss l i ⁇ j, t are calculated by the following two equations:
  • PL i ⁇ j represents the transmission capacity of line i ⁇ j in the distribution network
  • the active power constraints of the generator set in the distribution network are:
  • the boundary constraint condition is the balance between the active power transmitted by the transmission network to the distribution network and the active power received by the distribution network during each dispatch period, expressed as:
  • I (k) represents the node connected to the distribution network k in the transmission grid
  • the function C trans () represents the objective function of the transmission grid
  • the function Represents the objective function of distribution network k at the time t of dynamic dispatch
  • X trans and Respectively represent the constraint set of transmission grid and distribution network k at dynamic dispatch time t
  • Represents boundary constraints where Respectively, the transmission network variable coefficient, the distribution network variable coefficient and the constant coefficient in the dynamic scheduling time t of the distribution network k and the boundary conditions of the transmission grid are extracted from the constraint coefficients in the above step (1-2-3),
  • the extraction method is: the constraints in step (1-2-3) are Corresponds to 2 lines in Neutral The corresponding columns are 1 and -1 in the two rows, and the rest are 0, Neutral The corresponding columns are -1 and 1 in the two rows, and the rest are 0, Is 0, DIST stands for the distribution network number set, and T stands for the dispatch period set
  • each distribution network independently solves the distribution network cost function as follows:
  • Matrix of quadratic coefficients Represents the constraint condition of the distribution network k at the dynamic dispatch time t and the boundary constraint condition of the distribution network k and the transmission grid, that is, the constraints in steps (1-2-2)-(1-2-3) Is the coefficient matrix of the variable of the distribution network k at the time t of dynamic dispatch, The coefficient matrix of the input power variable of the transmission network k from the transmission grid at the time t of dynamic dispatch, Is the constant term in the constraint;
  • step (3-1-7) Upper bound of the sub-interval of power input from the transmission grid in the distribution network calculated in step (3-1-5) above The upper bound of the power input from the transmission grid in the distribution network calculated in the above step (3-1-2) To compare if Then the power sub-interval input from the transmission grid in the generated distribution network and the local cost function of the distribution grid in each sub-interval are transferred to the transmission grid, and step (3-2) is performed if Then increase u by 1 and return to step (3-1-4);
  • the transmission grid calculates the dispatching strategy of the transmission grid according to the power sub-intervals input from the transmission grid in each dispatching period of the distribution grid in step (3-1) above;
  • the physical meaning is the local optimal cost of the sub-interval of the distribution network after linearization
  • the local cost function of the distribution network generated for step (3-1-6), Is the boundary of the sub-interval of power input from the transmission grid in the distribution network;
  • CB v (p b ) is the local cost function of each distribution network corresponding to the above set C v in each dispatch period The sum of
  • ( ⁇ x trans , ⁇ p b ) is the decreasing direction
  • step (3-2-4) and step (3-3) for transmission and distribution networks respectively
  • the dispatch plan component in is distributed to each power plant under its jurisdiction, and each power plant uses automatic control methods to track and execute the generator set according to the dispatch plan to achieve non-iterative decomposition and coordinated dynamic dispatch of the transmission and distribution network.
  • the feedback method of the present application can solve the problem of coordinated dynamic scheduling of transmission and distribution networks in a non-iterative way of decomposition and coordination to ensure the information privacy security of transmission grid and distribution network operators.
  • the proposed non-iterative decomposition and coordination algorithm does not require repeated iterations between transmission and distribution networks, and the optimal scheduling parameters can be obtained only through limited two information interactions, compared to the traditional synchronous type that requires iterative decomposition
  • the coordination algorithm reduces the dependence on communication and the complexity of the algorithm, and has a higher stability of algorithm execution, which is more conducive to practical application.
  • the non-iterative decomposition and coordination dynamic scheduling method for transmission and distribution network proposed by the feedback of this application includes the following steps:
  • i is any node in the transmission grid or distribution network
  • T represents the set of dynamic scheduling moments
  • G represents the set of nodes where the generator set in the transmission grid or distribution network
  • DIST represents the distribution network number set
  • pg i, t represents the active power of the generator set connected to node i in the transmission grid or distribution network at the dynamic dispatch time t
  • the superscript trans represents the transmission grid
  • the superscript dist represents the distribution network with number k
  • the function C i ( ⁇ ) Represents the generating cost function of the generator set connected to node i, which is expressed by a quadratic function as:
  • a 0, i , a 1, i and a 2, i represent the constant term coefficient, the first term coefficient and the second term coefficient of the power generation cost of the generator set connected to the node i, the constant term coefficient, the first term coefficient and the The quadratic coefficient is the inherent parameter of the generator set, which can be obtained from the generator nameplate;
  • B represents the set of boundary nodes connecting the transmission grid and the distribution grid in the transmission grid
  • D represents the set of load nodes in the transmission grid or distribution network
  • PD i, t represents the load connected to the node i at the dynamic scheduling time t Predictive value
  • n is the line number
  • PL n is the transmission capacity of any line n in the transmission grid
  • SF ni represents the transfer distribution factor from node i to line n
  • the transfer distribution factor is the grid topology parameter, obtained from the grid dispatch center
  • the rotation reserve constraints are:
  • ru i, t and rd i, t are the rotation capacity of the generator set connected to the node i and the reserve capacity of the rotation down at the dynamic scheduling time t, respectively
  • RU i and RD i are the power generation of the connection node i
  • ⁇ t is the time interval of dynamic dispatch
  • the value of the time interval is determined by the power dispatch demand
  • the value is 1 hour or 15 minutes
  • PG i are the upper limit and the lower limit of active power of the generator set connected to node i, respectively
  • SRU t and SRD t are the upward rotation reserve capacity requirement and downward rotation reserve capacity requirement of the transmission grid or distribution network, respectively;
  • the constraint conditions for the climbing of the generator set in the transmission grid are:
  • the active power constraints of the generator set in the transmission grid are:
  • the constraint conditions of power flow in the distribution network are:
  • i: i ⁇ j represents the set of head-end nodes whose end node is the branch of node j, p i ⁇ j, t represents the active power flow from node i to node j in the distribution network, l i ⁇ j , t represents the active power loss from node i to node j in the distribution network, Represents the active power input of node j in the distribution network, N dist, k represents the set of node numbers of the distribution network, and the active power input of node j And active power loss l i ⁇ j, t are calculated by the following two equations:
  • PL i ⁇ j represents the transmission capacity of line i ⁇ j in the distribution network
  • the active power constraints of the generator set in the distribution network are:
  • the boundary constraint condition is the balance between the active power transmitted by the transmission network to the distribution network and the active power received by the distribution network during each dispatch period, expressed as:
  • I (k) represents the node connected to the distribution network k in the transmission grid
  • the function C trans () represents the objective function of the transmission grid
  • the function Represents the objective function of distribution network k at the time t of dynamic dispatch
  • X trans and Respectively represent the constraint set of transmission grid and distribution network k at dynamic dispatch time t
  • Represents boundary constraints where Respectively, the transmission network variable coefficient, the distribution network variable coefficient and the constant coefficient in the dynamic scheduling time t of the distribution network k and the boundary conditions of the transmission grid are extracted from the constraint coefficients in the above step (1-2-3),
  • the extraction method is: the constraints in step (1-2-3) are Corresponds to 2 lines in Neutral The corresponding columns are 1 and -1 in the two rows, and the rest are 0, Neutral The corresponding columns are -1 and 1 in the two rows, and the rest are 0, Is 0, DIST stands for the distribution network number set, and T stands for the dispatch period set;
  • step (3) Solve the matrix-based dynamic scheduling model of transmission and distribution network coordination obtained in step (2) above.
  • the specific steps are as follows:
  • each distribution network independently solves the distribution network cost function as follows:
  • Matrix of quadratic coefficients Represents the constraint condition of the distribution network k at the dynamic dispatch time t and the boundary constraint condition of the distribution network k and the transmission grid, that is, the constraint conditions in steps (1-2-2)-(1-2-3), where Is the coefficient matrix of the variable of the distribution network k at the time t of dynamic dispatch, The coefficient matrix of the input power variable of the transmission network k from the transmission grid at the time t of dynamic dispatch, Is the constant term in the constraint;
  • step (3-1-7) Upper bound of the sub-interval of power input from the transmission grid in the distribution network calculated in step (3-1-5) above The upper bound of the power input from the transmission grid in the distribution network calculated in the above step (3-1-2) To compare if Then the power sub-interval input from the transmission grid in the generated distribution network and the local cost function of the distribution grid in each sub-interval are transferred to the transmission grid, and step (3-2) is performed Then increase u by 1 and return to step (3-1-4);
  • the transmission grid calculates the dispatching strategy of the transmission grid according to the power sub-intervals input from the transmission grid in each dispatching period of the distribution grid in step (3-1) above;
  • the physical meaning is the local optimal cost of the sub-interval of the distribution network after linearization
  • the local cost function of the distribution network generated for step (3-1-6), Is the boundary of the sub-interval of power input from the transmission grid in the distribution network;
  • CB v (p b ) is the local cost function of each distribution network corresponding to the above set C v in each dispatch period The sum of
  • ( ⁇ x trans , ⁇ p b ) is the decreasing direction
  • step (3-2-4) and step (3-3) for transmission and distribution networks respectively
  • the dispatch plan component in is distributed to each power plant under its jurisdiction, and each power plant uses automatic control methods to track and execute the generator set according to the dispatch plan to achieve non-iterative decomposition and coordinated dynamic dispatch of the transmission and distribution network.

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Abstract

本申请反馈涉及一种输配电网非迭代的分解协调动态调度方法，属于电力系统运行技术领域。本方法整合了输电网和配电网的动态调度模型，并将输配电网协同的动态调度模型以矩阵的形式表示。针对矩阵形式的输配协同动态调度模型，各个配电网计算局部最优成本关于边界注入功率的函数，传递给输电网，输电网结合各个配电网的局部最优成本函数进行全局优化，下发优化得到的各个配电网边界注入功率，再由各个配电网进行独立调度。本申请反馈方法不需要输电网和配电网之间的反复迭代，采用异步式架构，低了对通信的依赖与算法复杂性，有着较高的算法执行稳定性，利于实际应用。

Description

一种输配电网非迭代的分解协调动态调度方法
相关申请的交叉引用
本申请要求清华大学于2018年10月22日提交的、发明名称为“一种输配电网非迭代的分解协调动态调度方法”的、中国专利申请号“201811227076.2”的优先权。
技术领域
本申请反馈涉及一种输配电网非迭代的分解协调动态调度方法，属于电力系统运行控制技术领域。
背景技术
分布式电源与主动配电网的发展对电网运行带来了诸多挑战，输电网和配电网协同的调度成为了发展趋势。由于输电网和配电网分别属于独立的运营商管理，输电网和配电网协同的调度难以集中式开展，因此，需要发展输配电网分解协调动态调度方法。已有的大部分输配电网分解协调动态调度方法需要输电网和配电网之间的反复信息交互迭代，属于同步式分解协调方法。异步式分解协调动态调度方法的优点在于不需要输配电网之间的迭代，对信息交互与通信依赖较小。
本申请人提出的申请号为201710087438.1的专利，公开了一种基于多参数规划的输配电网协调的动态经济调度方法，该方法采用输电网和配电网之间反复迭代的形式来进行输配电网协调的动态调度，其缺点在于，输配电网之间的反复迭代需要持续的信息交互，对输电网和配电网之间通信的依赖性很高，方法的执行易受到通信故障、阻塞等影响。
发明内容
本申请反馈的目的是提出一种输配电网非迭代的分解协调动态调度方法，对已有的输配电网的调度方法进行改进，无需输配电网之间的反复迭代，将输配协调动态调度问题分解求解，通过输电网和配电网间两次有限的信息交互来获得全局最优解。
本申请反馈提出的输配电网非迭代的分解协调动态调度方法，包括以下步骤：
(1)建立一个输配电网协调的动态调度模型，该模型由目标函数和约束条件构成，包括：
(1-1)动态调度模型的目标函数：
以输电网和配电网的总发电成本为动态调度的目标函数为：
Figure PCTCN2018113461-appb-000001
上式中，i为输电网或配电网中的任意节点，T代表动态调度时刻集合，G代表输电网或配电网中发电机组所在节点集合，DIST代表配电网编号集合，pg i,t代表输电网或配电网中连接节点i的发电机组在动态调度时刻t的有功功率，上标 trans代表输电网，上标 dist,k代表编号为k的配电网，函数C i(·)代表连接节点i的发电机组的发电成本函数，该成本函数用二次函数表示为：
Figure PCTCN2018113461-appb-000002
上式中，a 0,i、a 1,i和a 2,i分别代表连接节点i的发电机组的发电成本常数项系数、一次项系数和二次项系数，常数项系数、一次项系数和二次项系数为发电机组固有参数；
(1-2)动态调度模型的约束条件，包括：
(1-2-1)输电网模型约束条件，
其中的有功功率平衡约束条件为：
Figure PCTCN2018113461-appb-000003
上式中，B代表输电网中的输电网与配电网相互连接的边界节点集合，
Figure PCTCN2018113461-appb-000004
代表在动态调度时刻t，输电网从边界节点i传送到配电网的有功功率，D代表输电网或配电网中负荷节点集合，PD i,t代表在动态调度时刻t连接节点i的负荷预测值；
其中的输电网中线路传输容量的约束条件为：
Figure PCTCN2018113461-appb-000005
上式中，n为线路编号，PL n表示输电网中任意线路n的传输容量，SF n-i代表节点i到线路n的转移分布因子，转移分布因子为电网拓扑参数，从电网调度中心获取，L是输电网中所有线路编号的集合；
其中的旋转备用约束条件为：
Figure PCTCN2018113461-appb-000006
Figure PCTCN2018113461-appb-000007
Figure PCTCN2018113461-appb-000008
上式中，ru i,t和rd i,t分别为在动态调度时刻t，连接节点i的发电机组向上旋转备用容量和向下旋转备用容量，RU i和RD i分别为连接节点i的发电机组向上爬坡速率和向下爬坡速率，Δt为动态调度的时间间隔，时间间隔的取值由电力调度需求确定，
Figure PCTCN2018113461-appb-000009
和 PG i分别为连接节点i的发电机组的有功功率上限和有功功率下限，SRU t和SRD t分别为输电网或配电网的向上旋转备用的容量需求和向下旋转备用的容量需求；
其中的输电网中发电机组的爬坡约束条件为：
Figure PCTCN2018113461-appb-000010
其中的输电网中发电机组的有功功率约束条件为：
Figure PCTCN2018113461-appb-000011
(1-2-2)配电网模型约束条件：
其中的配电网潮流约束条件为：
Figure PCTCN2018113461-appb-000012
上式中，i:i→j表示末端节点为节点j的支路的首端节点集合，p i→j,t表示配电网中，节点i向节点j的有功功率潮流，l i→j,t表示配电网中节点i向节点j的有功功率损耗，
Figure PCTCN2018113461-appb-000013
表示配电网中节点j的有功功率输入，N dist,k表示配电网节点编号集合，节点j的有功功率输入
Figure PCTCN2018113461-appb-000014
和有功功率损耗l i→j,t分别通过下面两式计算：
Figure PCTCN2018113461-appb-000015
Figure PCTCN2018113461-appb-000016
上式中，
Figure PCTCN2018113461-appb-000017
为输电网向配电网k在动态调度时刻t的传输功率，
Figure PCTCN2018113461-appb-000018
和
Figure PCTCN2018113461-appb-000019
分别表示配电网中从节点i→节点j线路上的有功功率潮流展开点和无功功率潮流展开点，
Figure PCTCN2018113461-appb-000020
表示节点i的电压展开点，上述各展开点从电网调度中心的历史相近负荷水平下线路对应的运行数据中选取，R i→j表示线路i→j的电阻；
其中的配电网线路传输容量约束条件为：
Figure PCTCN2018113461-appb-000021
上式中，PL i→j表示配电网中线路i→j的传输容量；
其中的配电网中发电机组有功功率约束条件为：
Figure PCTCN2018113461-appb-000022
(1-2-3)输电网与配电网模型连接的边界约束条件：
边界约束条件即在每个调度时段输电网向配电网传输的有功功率与配电网接收的有功功率之间的平衡，表示为：
Figure PCTCN2018113461-appb-000023
上式中，I(k)表示输电网中与配电网k相连的节点；
(2)将上述步骤(1)建立的输配电网协调的动态调度模型转化为矩阵形式，将输配电网协调的动态调度模型中的输电网模型变量记为向量x trans，配电网k在动态调度时刻t的变量记为向量
Figure PCTCN2018113461-appb-000024
则输配电网协调的动态调度模型的矩阵形式如下：
Figure PCTCN2018113461-appb-000025
满足：
x trans∈X trans
Figure PCTCN2018113461-appb-000026
Figure PCTCN2018113461-appb-000027
上式中，函数C trans()表示输电网的目标函数，函数
Figure PCTCN2018113461-appb-000028
表示配电网k在动态调度时刻t的目标函数，X trans和
Figure PCTCN2018113461-appb-000029
分别表示输电网和配电网k在动态调度时刻t的约束集合，
Figure PCTCN2018113461-appb-000030
表示边界约束条件，其中的
Figure PCTCN2018113461-appb-000031
分别为配电网k在动态调度时刻t与输电网边界条件中的输电网变量系数、配电网变量系数和常量系数，由上述步骤(1-2-3)中的约束系数中提取得到，提取方法为：步骤(1-2-3)中的约束在
Figure PCTCN2018113461-appb-000032
中对应2行，
Figure PCTCN2018113461-appb-000033
中与
Figure PCTCN2018113461-appb-000034
相对应的列在两行中分别为1和-1，其余为0，
Figure PCTCN2018113461-appb-000035
中与
Figure PCTCN2018113461-appb-000036
相对应的列在两行中分别为-1和1，其余为0，
Figure PCTCN2018113461-appb-000037
为0，DIST代表配电网编号集合，T代表调度时段集合；
(3)求解上述步骤(2)得到的矩阵形式的输配电网协调的动态调度模型，具体步骤 如下：
(3-1)在配电网侧，由每个配电网独立求解配电网的成本函数，步骤如下：
(3-1-1)将配电网单时段调度问题表示为以下优化问题：
Figure PCTCN2018113461-appb-000038
满足：
Figure PCTCN2018113461-appb-000039
上式中，
Figure PCTCN2018113461-appb-000040
为步骤(1-1)中的目标函数中配电网项
Figure PCTCN2018113461-appb-000041
的二次系数矩阵，
Figure PCTCN2018113461-appb-000042
表示配电网k在动态调度时刻t的约束条件以及配电网k和输电网的边界约束条件，即步骤(1-2-2)-(1-2-3)中的约束条件，其中
Figure PCTCN2018113461-appb-000043
为配电网k在动态调度时刻t的变量的系数矩阵，
Figure PCTCN2018113461-appb-000044
配电网k在动态调度时刻t从输电网的输入功率变量的系数矩阵，
Figure PCTCN2018113461-appb-000045
为约束条件中的常数项；
(3-1-2)计算配电网各个时段内对从输电网输入的功率的需求范围，其中每个时段对从输电网输入的功率的需求下界为下面优化问题中
Figure PCTCN2018113461-appb-000046
的解：
Figure PCTCN2018113461-appb-000047
满足：
Figure PCTCN2018113461-appb-000048
每个时段对从输电网输入的功率的需求上界为下面优化问题中
Figure PCTCN2018113461-appb-000049
的解：
Figure PCTCN2018113461-appb-000050
满足：
Figure PCTCN2018113461-appb-000051
求解上述优化问题，计算得到配电网在各个时段内对从输电网输入的功率的下界和上界，分别记为
Figure PCTCN2018113461-appb-000052
和
Figure PCTCN2018113461-appb-000053
(3-1-3)初始化时，设配电网中成本函数计算次数u＝1，并设配电网中从输电网输入的功率子区间下界
Figure PCTCN2018113461-appb-000054
(3-1-4)取微小偏移量e＝1×10 -3，令
Figure PCTCN2018113461-appb-000055
将
Figure PCTCN2018113461-appb-000056
代入上述步骤(3-1-1)的优化问题中，对步骤(3-1-1)的优化问题中的约束条件进行判断，将起作用的约束，即最优解处不等式
Figure PCTCN2018113461-appb-000057
中两侧相等的行用下标() A表示，将不起作用约束，即最优解处不等式
Figure PCTCN2018113461-appb-000058
中两侧不相等的行用下标() I表示；
(3-1-5)计算配电网中从输电网输入的功率子区间上界
Figure PCTCN2018113461-appb-000059
该上界通过求解下面的 优化问题得到，其最优目标函数值为配电网中从输电网输入的功率子区间上界
Figure PCTCN2018113461-appb-000060
Figure PCTCN2018113461-appb-000061
满足：
Figure PCTCN2018113461-appb-000062
(3-1-6)计算属于配电网中从输电网输入的功率子区间
Figure PCTCN2018113461-appb-000063
的配电网局部成本函数
Figure PCTCN2018113461-appb-000064
该函数表示为：
Figure PCTCN2018113461-appb-000065
上式中：
Figure PCTCN2018113461-appb-000066
(3-1-7)将上述步骤(3-1-5)计算得到的配电网中从输电网输入的功率子区间上界
Figure PCTCN2018113461-appb-000067
与上述步骤(3-1-2)计算得到的配电网中从输电网输入的功率上界
Figure PCTCN2018113461-appb-000068
进行比较，若
Figure PCTCN2018113461-appb-000069
Figure PCTCN2018113461-appb-000070
则将生成的配电网中从输电网输入的功率子区间与每个子区间的配电网局部成本函数传给输电网，并进行步骤(3-2)，若
Figure PCTCN2018113461-appb-000071
则将u增加1，返回步骤(3-1-4)；
(3-2)输电网根据上述步骤(3-1)的配电网在每个调度时段中从输电网输入的功率子区间，计算得到输电网的调度策略；
(3-2-1)初始化时，设定求解步数v初始化为1，求解下述优化问题，并将优化问题的最优解记为
Figure PCTCN2018113461-appb-000072
其中向量
Figure PCTCN2018113461-appb-000073
由所有配电网在每一个调度时段的注入功率
Figure PCTCN2018113461-appb-000074
组成，向量
Figure PCTCN2018113461-appb-000075
对应下述优化问题中向量x trans在最优解处的取值：
Figure PCTCN2018113461-appb-000076
满足：
Figure PCTCN2018113461-appb-000077
Figure PCTCN2018113461-appb-000078
上式中，
Figure PCTCN2018113461-appb-000079
是中间变量，物理含义为线性化后的配电网子区间局部最优成本，
Figure PCTCN2018113461-appb-000080
代 表配电网k在动态调度时刻t的子区间数目，
Figure PCTCN2018113461-appb-000081
与
Figure PCTCN2018113461-appb-000082
的定义如下式：
Figure PCTCN2018113461-appb-000083
上式中，
Figure PCTCN2018113461-appb-000084
为步骤(3-1-6)生成的配电网局部成本函数，
Figure PCTCN2018113461-appb-000085
为配电网中从输电网输入的功率子区间的边界；
(3-2-2)从上述步骤(3-1-6)的配电网中从输电网输入的功率子区间
Figure PCTCN2018113461-appb-000086
中，找到包含上述最优解
Figure PCTCN2018113461-appb-000087
的配电网子区间，将所有包含上述最优解
Figure PCTCN2018113461-appb-000088
的配电网子区间构成一个集合，记作C v；
(3-2-3)利用下式，求解最优解
Figure PCTCN2018113461-appb-000089
minC trans(x trans)+CB v(p b)
满足：Dx trans+Ep b≤f
p b∈C v
上式中，
Figure PCTCN2018113461-appb-000090
CB v(p b)是每个配电网在每个调度时段内与上述集合C v相对应的局部成本函数
Figure PCTCN2018113461-appb-000091
的加和；
(3-2-4)根据上述步骤(3-2-3)的最优解
Figure PCTCN2018113461-appb-000092
得到输配电网成本函数的下降方向，根据下降方向得到输配电网成本下降量的目标函数：
Figure PCTCN2018113461-appb-000093
满足：
Figure PCTCN2018113461-appb-000094
||Δx trans|| ∞≤e,||Δp b|| ∞≤e
式中，(Δx trans,Δp b)为下降方向，
Figure PCTCN2018113461-appb-000095
为函数C trans在
Figure PCTCN2018113461-appb-000096
的梯度，
Figure PCTCN2018113461-appb-000097
为函数CB v在
Figure PCTCN2018113461-appb-000098
的梯度，e为一个足够小的正数，取值为1×10 -3；
对输配电网成本下降量的目标函数进行判断，若目标函数值大于或等于0，则得到输配电网成本最优解
Figure PCTCN2018113461-appb-000099
进行步骤(3-3)，若目标函数值小于0，根据下式计算
Figure PCTCN2018113461-appb-000100
Figure PCTCN2018113461-appb-000101
将v增加1，返回步骤(3-2-2)；
(3-3)每个配电网从上述步骤(3-2-4)输电网成本最优解
Figure PCTCN2018113461-appb-000102
中的向量
Figure PCTCN2018113461-appb-000103
得到配电网各自调度时段的分量
Figure PCTCN2018113461-appb-000104
利用下式，计算得到配电网模型变量
Figure PCTCN2018113461-appb-000105
Figure PCTCN2018113461-appb-000106
Figure PCTCN2018113461-appb-000107
(4)输电网和配电网分别将步骤(3-2-4)、步骤(3-3)计算得到的最优解
Figure PCTCN2018113461-appb-000108
中的调度计划分量下发至所管辖的各个电厂，各个电厂依据调度计划对发电机组采用自动控制方法追踪执行，实现输配电网非迭代的分解协调动态调度。
本申请反馈提出的输配电网非迭代的分解协调动态调度方法，其优点是：
本申请反馈方法能够将输配电网协同动态调度问题以分解协调的非迭代方式进行求解，保障输电网和配电网运营商各自的信息隐私安全。同时所提出的非迭代的分解协调算法无需要输电网和配电网之间的反复迭代，仅通过有限的两次信息交互即可获得最优调度参数，相比于传统同步式需要迭代的分解协调算法，降低了对通信的依赖与算法复杂性，有较高的算法执行稳定性，更利于实际应用。
具体实施方式
本申请反馈提出的输配电网非迭代的分解协调动态调度方法，包括以下步骤：
(1)建立一个输配电网协调的动态调度模型，该模型由目标函数和约束条件构成，包括：
(1-1)动态调度模型的目标函数：
以输电网和配电网的总发电成本为动态调度的目标函数为：
Figure PCTCN2018113461-appb-000109
上式中，i为输电网或配电网中的任意节点，T代表动态调度时刻集合，G代表输电网或配电网中发电机组所在节点集合，DIST代表配电网编号集合，pg i,t代表输电网或配电网中连接节点i的发电机组在动态调度时刻t的有功功率，上标 trans代表输电网，上标 dist,k代表编号为k的配电网，函数C i(·)代表连接节点i的发电机组的发电成本函数，该成本函数用二次函数表示为：
Figure PCTCN2018113461-appb-000110
上式中，a 0,i、a 1,i和a 2,i分别代表连接节点i的发电机组的发电成本常数项系数、一次项系数和二次项系数，常数项系数、一次项系数和二次项系数为发电机组固有参数，可以从发电机铭牌获取；
(1-2)动态调度模型的约束条件，包括：
(1-2-1)输电网模型约束条件，
其中的有功功率平衡约束条件为：
Figure PCTCN2018113461-appb-000111
上式中，B代表输电网中的输电网与配电网相互连接的边界节点集合，
Figure PCTCN2018113461-appb-000112
代表在动态调度时刻t，输电网从边界节点i传送到配电网的有功功率，D代表输电网或配电网中负荷节点集合，PD i,t代表在动态调度时刻t连接节点i的负荷预测值；
其中的输电网中线路传输容量的约束条件为：
Figure PCTCN2018113461-appb-000113
上式中，n为线路编号，PL n表示输电网中任意线路n的传输容量，SF n-i代表节点i到线路n的转移分布因子，转移分布因子为电网拓扑参数，从电网调度中心获取，L是输电网中所有线路编号的集合；
其中的旋转备用约束条件为：
Figure PCTCN2018113461-appb-000114
Figure PCTCN2018113461-appb-000115
Figure PCTCN2018113461-appb-000116
上式中，ru i,t和rd i,t分别为在动态调度时刻t，连接节点i的发电机组向上旋转备用容量和向下旋转备用容量，RU i和RD i分别为连接节点i的发电机组向上爬坡速率和向下爬坡速率，Δt为动态调度的时间间隔，时间间隔的取值由电力调度需求确定，取值为1小时或15分钟，
Figure PCTCN2018113461-appb-000117
和 PG i分别为连接节点i的发电机组的有功功率上限和有功功率下限，SRU t和SRD t分别为输电网或配电网的向上旋转备用的容量需求和向下旋转备用的容量需求；
其中的输电网中发电机组的爬坡约束条件为：
Figure PCTCN2018113461-appb-000118
其中的输电网中发电机组的有功功率约束条件为：
Figure PCTCN2018113461-appb-000119
(1-2-2)配电网模型约束条件：
其中的配电网潮流约束条件为：
Figure PCTCN2018113461-appb-000120
上式中，i:i→j表示末端节点为节点j的支路的首端节点集合，p i→j,t表示配电网中，节点i向节点j的有功功率潮流，l i→j,t表示配电网中节点i向节点j的有功功率损耗，
Figure PCTCN2018113461-appb-000121
表示配电网中节点j的有功功率输入，N dist,k表示配电网节点编号集合，节点j的有功功率输入
Figure PCTCN2018113461-appb-000122
和有功功率损耗l i→j,t分别通过下面两式计算：
Figure PCTCN2018113461-appb-000123
Figure PCTCN2018113461-appb-000124
上式中，
Figure PCTCN2018113461-appb-000125
为输电网向配电网k在动态调度时刻t的传输功率，
Figure PCTCN2018113461-appb-000126
和
Figure PCTCN2018113461-appb-000127
分别表示配电网中从节点i→节点j线路上的有功功率潮流展开点和无功功率潮流展开点，
Figure PCTCN2018113461-appb-000128
表示节点i的电压展开点，上述各展开点从电网调度中心的历史相近负荷水平下线路对应的运行数据中选取，R i→j表示线路i→j的电阻；
其中的配电网线路传输容量约束条件为：
Figure PCTCN2018113461-appb-000129
上式中，PL i→j表示配电网中线路i→j的传输容量；
其中的配电网中发电机组有功功率约束条件为：
Figure PCTCN2018113461-appb-000130
(1-2-3)输电网与配电网模型连接的边界约束条件：
边界约束条件即在每个调度时段输电网向配电网传输的有功功率与配电网接收的有功功率之间的平衡，表示为：
Figure PCTCN2018113461-appb-000131
上式中，I(k)表示输电网中与配电网k相连的节点；
(2)将上述步骤(1)建立的输配电网协调的动态调度模型转化为矩阵形式，将输配电网协调的动态调度模型中的输电网模型变量记为向量x trans，配电网k在动态调度时刻t的变量记为向量
Figure PCTCN2018113461-appb-000132
则输配电网协调的动态调度模型的矩阵形式如下：
Figure PCTCN2018113461-appb-000133
满足：
x trans∈X trans
Figure PCTCN2018113461-appb-000134
Figure PCTCN2018113461-appb-000135
上式中，函数C trans()表示输电网的目标函数，函数
Figure PCTCN2018113461-appb-000136
表示配电网k在动态调度时刻t的目标函数，X trans和
Figure PCTCN2018113461-appb-000137
分别表示输电网和配电网k在动态调度时刻t的约束集合，
Figure PCTCN2018113461-appb-000138
表示边界约束条件，其中的
Figure PCTCN2018113461-appb-000139
分别为配电网k在动态调度时刻t与输电网边界条件中的输电网变量系数、配电网变量系数和常量系数，由上述步骤(1-2-3)中的约束系数中提取得到，提取方法为：步骤(1-2-3)中的约束在
Figure PCTCN2018113461-appb-000140
中对应2行，
Figure PCTCN2018113461-appb-000141
中与
Figure PCTCN2018113461-appb-000142
相对应的列在两行中分别为1和-1，其余为0，
Figure PCTCN2018113461-appb-000143
中与
Figure PCTCN2018113461-appb-000144
相对应的列在两行中分别为-1和1，其余为0，
Figure PCTCN2018113461-appb-000145
为0，DIST代表配电网编号集合，T代表调度时段集合；
(3)求解上述步骤(2)得到的矩阵形式的输配电网协调的动态调度模型，具体步骤如下：
(3-1)在配电网侧，由每个配电网独立求解配电网的成本函数，步骤如下：
(3-1-1)将配电网单时段调度问题表示为以下优化问题：
Figure PCTCN2018113461-appb-000146
满足：
Figure PCTCN2018113461-appb-000147
上式中，
Figure PCTCN2018113461-appb-000148
为步骤(1-1)中的目标函数中配电网项
Figure PCTCN2018113461-appb-000149
的二次系数矩阵，
Figure PCTCN2018113461-appb-000150
表示配电网k在动态调度时刻t的约束条件以及配电网k和输电网的边界约束条件，即步骤(1-2-2)-(1-2-3)中的约束条件，其中
Figure PCTCN2018113461-appb-000151
为配电网k在 动态调度时刻t的变量的系数矩阵，
Figure PCTCN2018113461-appb-000152
配电网k在动态调度时刻t从输电网的输入功率变量的系数矩阵，
Figure PCTCN2018113461-appb-000153
为约束条件中的常数项；
(3-1-2)计算配电网各个时段内对从输电网输入的功率的需求范围，其中每个时段对从输电网输入的功率的需求下界为下面优化问题中
Figure PCTCN2018113461-appb-000154
的解：
Figure PCTCN2018113461-appb-000155
满足：
Figure PCTCN2018113461-appb-000156
每个时段对从输电网输入的功率的需求上界为下面优化问题中
Figure PCTCN2018113461-appb-000157
的解：
Figure PCTCN2018113461-appb-000158
满足：
Figure PCTCN2018113461-appb-000159
求解上述优化问题，计算得到配电网在各个时段内对从输电网输入的功率的下界和上界，分别记为
Figure PCTCN2018113461-appb-000160
和
Figure PCTCN2018113461-appb-000161
(3-1-3)初始化时，设配电网中成本函数计算次数u＝1，并设配电网中从输电网输入的功率子区间下界
Figure PCTCN2018113461-appb-000162
(3-1-4)取微小偏移量e＝1×10 -3，令
Figure PCTCN2018113461-appb-000163
将
Figure PCTCN2018113461-appb-000164
代入上述步骤(3-1-1)的优化问题中，基于优化结果中每一个约束是否起作用，对步骤(3-1-1)的优化问题中的约束条件进行判断，其中每一行分类为起作用约束和不起作用约束，将起作用的约束，即最优解处不等式
Figure PCTCN2018113461-appb-000165
中两侧相等的行用下标() A表示，将不起作用约束，即最优解处不等式
Figure PCTCN2018113461-appb-000166
中两侧不相等的行用下标() I表示；
(3-1-5)计算配电网中从输电网输入的功率子区间上界
Figure PCTCN2018113461-appb-000167
该上界通过求解下面的优化问题得到，其最优目标函数值为配电网中从输电网输入的功率子区间上界
Figure PCTCN2018113461-appb-000168
Figure PCTCN2018113461-appb-000169
满足：
Figure PCTCN2018113461-appb-000170
(3-1-6)计算属于配电网中从输电网输入的功率子区间
Figure PCTCN2018113461-appb-000171
的配电网局部成本 函数
Figure PCTCN2018113461-appb-000172
该函数表示为：
Figure PCTCN2018113461-appb-000173
上式中：
Figure PCTCN2018113461-appb-000174
(3-1-7)将上述步骤(3-1-5)计算得到的配电网中从输电网输入的功率子区间上界
Figure PCTCN2018113461-appb-000175
与上述步骤(3-1-2)计算得到的配电网中从输电网输入的功率上界
Figure PCTCN2018113461-appb-000176
进行比较，若
Figure PCTCN2018113461-appb-000177
Figure PCTCN2018113461-appb-000178
则将生成的配电网中从输电网输入的功率子区间与每个子区间的配电网局部成本函数传给输电网，并进行步骤(3-2)，若
Figure PCTCN2018113461-appb-000179
则将u增加1，返回步骤(3-1-4)；
(3-2)输电网根据上述步骤(3-1)的配电网在每个调度时段中从输电网输入的功率子区间，计算得到输电网的调度策略；
(3-2-1)初始化时，设定求解步数v初始化为1，求解下述优化问题，并将优化问题的最优解记为
Figure PCTCN2018113461-appb-000180
其中向量
Figure PCTCN2018113461-appb-000181
由所有配电网在每一个调度时段的注入功率
Figure PCTCN2018113461-appb-000182
组成，向量
Figure PCTCN2018113461-appb-000183
对应下述优化问题中向量x trans在最优解处的取值：
Figure PCTCN2018113461-appb-000184
满足：
Figure PCTCN2018113461-appb-000185
Figure PCTCN2018113461-appb-000186
上式中，
Figure PCTCN2018113461-appb-000187
是中间变量，物理含义为线性化后的配电网子区间局部最优成本，
Figure PCTCN2018113461-appb-000188
代表配电网k在动态调度时刻t的子区间数目，
Figure PCTCN2018113461-appb-000189
与
Figure PCTCN2018113461-appb-000190
的定义如下式：
Figure PCTCN2018113461-appb-000191
上式中，
Figure PCTCN2018113461-appb-000192
为步骤(3-1-6)生成的配电网局部成本函数，
Figure PCTCN2018113461-appb-000193
为配电网中从输电网输入的功率子区间的边界；
(3-2-2)从上述步骤(3-1-6)的配电网中从输电网输入的功率子区间
Figure PCTCN2018113461-appb-000194
中，找到包含上述最优解
Figure PCTCN2018113461-appb-000195
的配电网子区间，将所有包含上述最优解
Figure PCTCN2018113461-appb-000196
的配电网 子区间构成一个集合，记作C v；
(3-2-3)利用下式，求解最优解
Figure PCTCN2018113461-appb-000197
Figure PCTCN2018113461-appb-000198
满足：Dx trans+Ep b≤f
p b∈C v
上式中，
Figure PCTCN2018113461-appb-000199
CB v(p b)是每个配电网在每个调度时段内与上述集合C v相对应的局部成本函数
Figure PCTCN2018113461-appb-000200
的加和；
(3-2-4)根据上述步骤(3-2-3)的最优解
Figure PCTCN2018113461-appb-000201
得到输配电网成本函数的下降方向，根据下降方向得到输配电网成本下降量的目标函数：
Figure PCTCN2018113461-appb-000202
满足：
Figure PCTCN2018113461-appb-000203
||Δx trans|| ∞≤e,||Δp b|| ∞≤e
式中，(Δx trans,Δp b)为下降方向，
Figure PCTCN2018113461-appb-000204
为函数C trans在
Figure PCTCN2018113461-appb-000205
的梯度，
Figure PCTCN2018113461-appb-000206
为函数CB v在
Figure PCTCN2018113461-appb-000207
的梯度，e为一个足够小的正数，取值为1×10 -3；
对输配电网成本下降量的目标函数进行判断，若目标函数值大于或等于0，则得到输配电网成本最优解
Figure PCTCN2018113461-appb-000208
进行步骤(3-3)，若目标函数值小于0，根据下式计算
Figure PCTCN2018113461-appb-000209
Figure PCTCN2018113461-appb-000210
将v增加1，返回步骤(3-2-2)；
(3-3)每个配电网从上述步骤(3-2-4)输电网成本最优解
Figure PCTCN2018113461-appb-000211
中的向量
Figure PCTCN2018113461-appb-000212
得到配电网各自调度时段的分量
Figure PCTCN2018113461-appb-000213
分量
Figure PCTCN2018113461-appb-000214
利用下式，计算得到配电网模型变量
Figure PCTCN2018113461-appb-000215
Figure PCTCN2018113461-appb-000216
Figure PCTCN2018113461-appb-000217
(4)输电网和配电网分别将步骤(3-2-4)、步骤(3-3)计算得到的最优解
Figure PCTCN2018113461-appb-000218
中的调度计划分量下发至所管辖的各个电厂，各个电厂依据调度计划对发电机组采用自动控制方法追踪执行，实现输配电网非迭代的分解协调动态调度。

Claims (1)

  1. 一种输配电网非迭代的分解协调动态调度方法，其特征在于该方法包括以下步骤：
    (1)建立一个输配电网协调的动态调度模型，该模型由目标函数和约束条件构成，包括：
    (1-1)动态调度模型的目标函数：
    以输电网和配电网的总发电成本为动态调度的目标函数为：
    Figure PCTCN2018113461-appb-100001
    上式中，i为输电网或配电网中的任意节点，T代表动态调度时刻集合，G代表输电网或配电网中发电机组所在节点集合，DIST代表配电网编号集合，pg i,t代表输电网或配电网中连接节点i的发电机组在动态调度时刻t的有功功率，上标 trans代表输电网，上标 dist,k代表编号为k的配电网，函数C i(·)代表连接节点i的发电机组的发电成本函数，该成本函数用二次函数表示为：
    Figure PCTCN2018113461-appb-100002
    上式中，a 0,i、a 1,i和a 2,i分别代表连接节点i的发电机组的发电成本常数项系数、一次项系数和二次项系数，常数项系数、一次项系数和二次项系数为发电机组固有参数；
    (1-2)动态调度模型的约束条件，包括：
    (1-2-1)输电网模型约束条件，
    其中的有功功率平衡约束条件为：
    Figure PCTCN2018113461-appb-100003
    上式中，B代表输电网中的输电网与配电网相互连接的边界节点集合，
    Figure PCTCN2018113461-appb-100004
    代表在动态调度时刻t，输电网从边界节点i传送到配电网的有功功率，D代表输电网或配电网中负荷节点集合，PD i,t代表在动态调度时刻t连接节点i的负荷预测值；
    其中的输电网中线路传输容量的约束条件为：
    Figure PCTCN2018113461-appb-100005
    上式中，n为线路编号，PL n表示输电网中任意线路n的传输容量，SF n-i代表节点i到 线路n的转移分布因子，转移分布因子为电网拓扑参数，从电网调度中心获取，L是输电网中所有线路编号的集合；
    其中的旋转备用约束条件为：
    Figure PCTCN2018113461-appb-100006
    Figure PCTCN2018113461-appb-100007
    Figure PCTCN2018113461-appb-100008
    上式中，ru i,t和rd i,t分别为在动态调度时刻t，连接节点i的发电机组向上旋转备用容量和向下旋转备用容量，RU i和RD i分别为连接节点i的发电机组向上爬坡速率和向下爬坡速率，Δt为动态调度的时间间隔，时间间隔的取值由电力调度需求确定，
    Figure PCTCN2018113461-appb-100009
    和 PG i分别为连接节点i的发电机组的有功功率上限和有功功率下限，SRU t和SRD t分别为输电网或配电网的向上旋转备用的容量需求和向下旋转备用的容量需求；
    其中的输电网中发电机组的爬坡约束条件为：
    Figure PCTCN2018113461-appb-100010
    其中的输电网中发电机组的有功功率约束条件为：
    Figure PCTCN2018113461-appb-100011
    (1-2-2)配电网模型约束条件：
    其中的配电网潮流约束条件为：
    Figure PCTCN2018113461-appb-100012
    上式中，i:i→j表示末端节点为节点j的支路的首端节点集合，p i→j,t表示配电网中，节点i向节点j的有功功率潮流，l i→j,t表示配电网中节点i向节点j的有功功率损耗，
    Figure PCTCN2018113461-appb-100013
    表示配电网中节点j的有功功率输入，N dist,k表示配电网节点编号集合，节点j的有功功率输入
    Figure PCTCN2018113461-appb-100014
    和有功功率损耗l i→j,t分别通过下面两式计算：
    Figure PCTCN2018113461-appb-100015
    Figure PCTCN2018113461-appb-100016
    上式中，
    Figure PCTCN2018113461-appb-100017
    为输电网向配电网k在动态调度时刻t的传输功率，
    Figure PCTCN2018113461-appb-100018
    和
    Figure PCTCN2018113461-appb-100019
    分别表示配电网中从节点i→节点j线路上的有功功率潮流展开点和无功功率潮流展开点，
    Figure PCTCN2018113461-appb-100020
    表示节点i的电压展开点，上述各展开点从电网调度中心的历史相近负荷水平下线路对应的运行数据中选取，R i→j表示线路i→j的电阻；
    其中的配电网线路传输容量约束条件为：
    Figure PCTCN2018113461-appb-100021
    上式中，PL i→j表示配电网中线路i→j的传输容量；
    其中的配电网中发电机组有功功率约束条件为：
    Figure PCTCN2018113461-appb-100022
    (1-2-3)输电网与配电网模型连接的边界约束条件：
    边界约束条件即在每个调度时段输电网向配电网传输的有功功率与配电网接收的有功功率之间的平衡，表示为：
    Figure PCTCN2018113461-appb-100023
    上式中，I(k)表示输电网中与配电网k相连的节点；
    (2)将上述步骤(1)建立的输配电网协调的动态调度模型转化为矩阵形式，将输配电网协调的动态调度模型中的输电网模型变量记为向量x trans，配电网k在动态调度时刻t的变量记为向量
    Figure PCTCN2018113461-appb-100024
    则输配电网协调的动态调度模型的矩阵形式如下：
    Figure PCTCN2018113461-appb-100025
    满足：
    x trans∈X trans
    Figure PCTCN2018113461-appb-100026
    Figure PCTCN2018113461-appb-100027
    上式中，函数C trans()表示输电网的目标函数，函数
    Figure PCTCN2018113461-appb-100028
    表示配电网k在动态调度时刻t的目标函数，X trans和
    Figure PCTCN2018113461-appb-100029
    分别表示输电网和配电网k在动态调度时刻t的约束集合，
    Figure PCTCN2018113461-appb-100030
    表示边界约束条件，其中的
    Figure PCTCN2018113461-appb-100031
    分别为配电网k在动态调度时刻t与输电网边界条件中的输电网变量系数、配电网变量系数和常量系数，由上述步骤(1-2-3)中的约束系数中提取得到，提取方法为：步骤(1-2-3)中的约束在
    Figure PCTCN2018113461-appb-100032
    中对应2行，
    Figure PCTCN2018113461-appb-100033
    中与
    Figure PCTCN2018113461-appb-100034
    相对应的列在两行中分别为1和-1，其余为0，
    Figure PCTCN2018113461-appb-100035
    中与
    Figure PCTCN2018113461-appb-100036
    相对应的列在两行中分别为-1和1，其余为0，
    Figure PCTCN2018113461-appb-100037
    为0，DIST代表配电网编号集合，T代表调度时段集合；
    (3)求解上述步骤(2)得到的矩阵形式的输配电网协调的动态调度模型，具体步骤如下：
    (3-1)在配电网侧，由每个配电网独立求解配电网的成本函数，步骤如下：
    (3-1-1)将配电网单时段调度问题表示为以下优化问题：
    Figure PCTCN2018113461-appb-100038
    满足：
    Figure PCTCN2018113461-appb-100039
    上式中，
    Figure PCTCN2018113461-appb-100040
    为步骤(1-1)中的目标函数中配电网项
    Figure PCTCN2018113461-appb-100041
    的二次系数矩阵，
    Figure PCTCN2018113461-appb-100042
    表示配电网k在动态调度时刻t的约束条件以及配电网k和输电网的边界约束条件，即步骤(1-2-2)-(1-2-3)中的约束条件，其中
    Figure PCTCN2018113461-appb-100043
    为配电网k在动态调度时刻t的变量的系数矩阵，
    Figure PCTCN2018113461-appb-100044
    配电网k在动态调度时刻t从输电网的输入功率变量的系数矩阵，
    Figure PCTCN2018113461-appb-100045
    为约束条件中的常数项；
    (3-1-2)计算配电网各个时段内对从输电网输入的功率的需求范围，其中每个时段对从输电网输入的功率的需求下界为下面优化问题中
    Figure PCTCN2018113461-appb-100046
    的解：
    Figure PCTCN2018113461-appb-100047
    满足：
    Figure PCTCN2018113461-appb-100048
    每个时段对从输电网输入的功率的需求上界为下面优化问题中
    Figure PCTCN2018113461-appb-100049
    的解：
    Figure PCTCN2018113461-appb-100050
    满足：
    Figure PCTCN2018113461-appb-100051
    求解上述优化问题，计算得到配电网在各个时段内对从输电网输入的功率的下界和上界，分别记为
    Figure PCTCN2018113461-appb-100052
    和
    Figure PCTCN2018113461-appb-100053
    (3-1-3)初始化时，设配电网中成本函数计算次数u＝1，并设配电网中从输电网输入的功率子区间下界
    Figure PCTCN2018113461-appb-100054
    (3-1-4)取微小偏移量e＝1×10 -3，令
    Figure PCTCN2018113461-appb-100055
    将
    Figure PCTCN2018113461-appb-100056
    代入上述步骤(3-1-1) 的优化问题中，对步骤(3-1-1)的优化问题中的约束条件进行判断，将起作用的约束，即最优解处不等式
    Figure PCTCN2018113461-appb-100057
    中两侧相等的行用下标() A表示，将不起作用约束，即最优解处不等式
    Figure PCTCN2018113461-appb-100058
    中两侧不相等的行用下标() I表示；
    (3-1-5)计算配电网中从输电网输入的功率子区间上界
    Figure PCTCN2018113461-appb-100059
    该上界通过求解下面的优化问题得到，其最优目标函数值为配电网中从输电网输入的功率子区间上界
    Figure PCTCN2018113461-appb-100060
    Figure PCTCN2018113461-appb-100061
    满足：
    Figure PCTCN2018113461-appb-100062
    (3-1-6)计算属于配电网中从输电网输入的功率子区间
    Figure PCTCN2018113461-appb-100063
    的配电网局部成本函数
    Figure PCTCN2018113461-appb-100064
    该函数表示为：
    Figure PCTCN2018113461-appb-100065
    上式中：
    Figure PCTCN2018113461-appb-100066
    (3-1-7)将上述步骤(3-1-5)计算得到的配电网中从输电网输入的功率子区间上界
    Figure PCTCN2018113461-appb-100067
    与上述步骤(3-1-2)计算得到的配电网中从输电网输入的功率上界
    Figure PCTCN2018113461-appb-100068
    进行比较，若
    Figure PCTCN2018113461-appb-100069
    Figure PCTCN2018113461-appb-100070
    则将生成的配电网中从输电网输入的功率子区间与每个子区间的配电网局部成本函数传给输电网，并进行步骤(3-2)，若
    Figure PCTCN2018113461-appb-100071
    则将u增加1，返回步骤(3-1-4)；
    (3-2)输电网根据上述步骤(3-1)的配电网在每个调度时段中从输电网输入的功率子区间，计算得到输电网的调度策略；
    (3-2-1)初始化时，设定求解步数v初始化为1，求解下述优化问题，并将优化问题的最优解记为
    Figure PCTCN2018113461-appb-100072
    其中向量
    Figure PCTCN2018113461-appb-100073
    由所有配电网在每一个调度时段的注入功率
    Figure PCTCN2018113461-appb-100074
    组成，向量
    Figure PCTCN2018113461-appb-100075
    对应下述优化问题中向量x trans在最优解处的取值：
    Figure PCTCN2018113461-appb-100076
    满足：
    Figure PCTCN2018113461-appb-100077
    Figure PCTCN2018113461-appb-100078
    上式中，
    Figure PCTCN2018113461-appb-100079
    是中间变量，物理含义为线性化后的配电网子区间局部最优成本，
    Figure PCTCN2018113461-appb-100080
    代表配电网k在动态调度时刻t的子区间数目，
    Figure PCTCN2018113461-appb-100081
    与
    Figure PCTCN2018113461-appb-100082
    的定义如下式：
    Figure PCTCN2018113461-appb-100083
    Figure PCTCN2018113461-appb-100084
    上式中，
    Figure PCTCN2018113461-appb-100085
    为步骤(3-1-6)生成的配电网局部成本函数，
    Figure PCTCN2018113461-appb-100086
    为配电网中从输电网输入的功率子区间的边界；
    (3-2-2)从上述步骤(3-1-6)的配电网中从输电网输入的功率子区间
    Figure PCTCN2018113461-appb-100087
    中，找到包含上述最优解
    Figure PCTCN2018113461-appb-100088
    的配电网子区间，将所有包含上述最优解
    Figure PCTCN2018113461-appb-100089
    的配电网子区间构成一个集合，记作C v；
    (3-2-3)利用下式，求解最优解
    Figure PCTCN2018113461-appb-100090
    min C trans(x trans)+CB v(p b)
    满足：Dx trans+Ep b≤f
    p b∈C v
    上式中，
    Figure PCTCN2018113461-appb-100091
    CB v(p b)是每个配电网在每个调度时段内与上述集合C v相对应的局部成本函数
    Figure PCTCN2018113461-appb-100092
    的加和；
    (3-2-4)根据上述步骤(3-2-3)的最优解
    Figure PCTCN2018113461-appb-100093
    得到输配电网成本函数的下降方向，根据下降方向得到输配电网成本下降量的目标函数：
    Figure PCTCN2018113461-appb-100094
    满足：
    Figure PCTCN2018113461-appb-100095
    ||Δx trans|| ∞≤e,||Δp b|| ∞≤e
    式中，(Δx trans,Δp b)为下降方向，
    Figure PCTCN2018113461-appb-100096
    为函数C trans在
    Figure PCTCN2018113461-appb-100097
    的梯度，
    Figure PCTCN2018113461-appb-100098
    为函数CB v在
    Figure PCTCN2018113461-appb-100099
    的梯度，e为一个足够小的正数，取值为1×10 -3；
    对输配电网成本下降量的目标函数进行判断，若目标函数值大于或等于0，则得到输 配电网成本最优解
    Figure PCTCN2018113461-appb-100100
    进行步骤(3-3)，若目标函数值小于0，根据下式计算
    Figure PCTCN2018113461-appb-100101
    Figure PCTCN2018113461-appb-100102
    将v增加1，返回步骤(3-2-2)；
    (3-3)每个配电网从上述步骤(3-2-4)输电网成本最优解
    Figure PCTCN2018113461-appb-100103
    中的向量
    Figure PCTCN2018113461-appb-100104
    得到配电网各自调度时段的分量
    Figure PCTCN2018113461-appb-100105
    分量
    Figure PCTCN2018113461-appb-100106
    利用下式，计算得到配电网模型变量
    Figure PCTCN2018113461-appb-100107
    Figure PCTCN2018113461-appb-100108
    Figure PCTCN2018113461-appb-100109
    (4)输电网和配电网分别将步骤(3-2-4)、步骤(3-3)计算得到的最优解
    Figure PCTCN2018113461-appb-100110
    中的调度计划分量下发至所管辖的各个电厂，各个电厂依据调度计划对发电机组采用自动控制方法追踪执行，实现输配电网非迭代的分解协调动态调度。
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113644682A (zh) * 2021-07-14 2021-11-12 国网河北省电力有限公司电力科学研究院 高渗透有源配电网多台区协同管控方法、装置和终端设备

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110880758B (zh) * 2019-11-22 2021-01-01 清华大学 电力系统中输电网与配电网的分解协调最优潮流控制方法
CN111654025B (zh) * 2020-06-12 2021-10-08 国网河北省电力有限公司经济技术研究院 考虑配网间互联的输配一体化协调调度方法

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2016074187A1 (en) * 2014-11-13 2016-05-19 The University Of Hong Kong Fast generation adjustment algorithm for energy management system
CN106953358A (zh) * 2017-04-20 2017-07-14 国网江西省电力公司电力科学研究院 一种主动配电网优化调度策略确定方法
CN107069706A (zh) * 2017-02-17 2017-08-18 清华大学 一种基于多参数规划的输配电网协调的动态经济调度方法

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7085660B2 (en) * 2003-05-13 2006-08-01 Siemens Power Transmission & Distribution, Inc. Energy management system in a power and distribution system
US20130338843A1 (en) * 2012-06-18 2013-12-19 Reza Iravani Systems, methods and controllers for control of power distribution devices and systems
CN107482633B (zh) * 2017-08-22 2020-03-31 东南大学 一种适用于辐射状配电网的非迭代区间潮流算法

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2016074187A1 (en) * 2014-11-13 2016-05-19 The University Of Hong Kong Fast generation adjustment algorithm for energy management system
CN107069706A (zh) * 2017-02-17 2017-08-18 清华大学 一种基于多参数规划的输配电网协调的动态经济调度方法
CN106953358A (zh) * 2017-04-20 2017-07-14 国网江西省电力公司电力科学研究院 一种主动配电网优化调度策略确定方法

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
YU, LIJIE ET AL.: "Study on Optimal Dispatching of Flexible DC Distribution Networks", PRECISE MANUFACTURING & AUTOMATION, no. 1, 25 February 2018 (2018-02-25) *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113644682A (zh) * 2021-07-14 2021-11-12 国网河北省电力有限公司电力科学研究院 高渗透有源配电网多台区协同管控方法、装置和终端设备
CN113644682B (zh) * 2021-07-14 2023-08-25 国网河北省电力有限公司电力科学研究院 高渗透有源配电网多台区协同管控方法、装置和终端设备

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