WO2021212724A1 - 有源配电网实时仿真模型的分解方法和装置 - Google Patents

有源配电网实时仿真模型的分解方法和装置 Download PDF

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WO2021212724A1
WO2021212724A1 PCT/CN2020/113692 CN2020113692W WO2021212724A1 WO 2021212724 A1 WO2021212724 A1 WO 2021212724A1 CN 2020113692 W CN2020113692 W CN 2020113692W WO 2021212724 A1 WO2021212724 A1 WO 2021212724A1
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real
sub
network
time
simulation model
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French (fr)
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盛万兴
张怀天
刘科研
孟晓丽
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中国电力科学研究院有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
    • G06F30/18—Network design, e.g. design based on topological or interconnect aspects of utility systems, piping, heating ventilation air conditioning [HVAC] or cabling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2113/00—Details relating to the application field
    • G06F2113/04—Power grid distribution networks

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  • This application relates to the field of power system simulation technology, for example, to a decomposition method and device of a real-time simulation model of an active distribution network.
  • the distribution network is characterized by its large scale, numerous nodes, complex equipment, and diverse operation modes. protrude.
  • the distribution network covers a variety of equipment such as loads, transformers, circuit breakers, ring main cabinets, etc., as well as a large number of power electronic equipment such as distributed power sources, energy storage components, and static var compensators; on the other hand, power distribution
  • the network has developed from the original single-power radial structure and hand-in-hand wiring mode to dual-power ring network and multi-power grid wiring mode, resulting in the continuous expansion of the scale of the distribution network, the number of nodes has greatly increased, and the degree of complexity is also exponential
  • the rise in form has put forward higher requirements and challenges for the real-time simulation technology of complex distribution networks.
  • the decomposition method of active distribution network real-time simulation model is one of the effective methods to solve the real-time simulation problem of distribution network.
  • Model decomposition is based on the idea of grouping into groups.
  • the distribution network is decomposed into a number of sub-networks, and a state space system is decomposed into two or more state space groups. Each state space group The group solves the corresponding state space matrix.
  • Combining model decomposition and parallel computing, multi-processor parallel computing based on the decomposition model can effectively reduce the computational burden of one processor, increase the simulation scale, and achieve rapid simulation of complex distribution networks.
  • related technologies generally decompose the real-time simulation model of the active distribution network with a large scale or contain a large number of power electronic devices manually. Specifically, the decomposition of the real-time simulation model of the active distribution network is realized through the manual installation interface. Strong, time-consuming, serious waste of resources, and inaccurate decomposition results.
  • This application provides a decomposition method of a real-time simulation model of an active distribution network, including:
  • the sub-network is allocated to each real-time simulator through the interface, and the nodes in the sub-network are adjusted based on the average resource utilization rate of all real-time simulators.
  • this application also provides a decomposition device for a real-time simulation model of an active distribution network, including:
  • the determining module is configured to determine the number of pre-decomposed networks and pre-decomposition nodes based on the number of real-time simulators and the number of switching devices in the real-time simulation model of the active distribution network;
  • the decomposition module is configured to pre-decompose the active distribution network real-time simulation model based on the number of pre-decomposed networks and pre-decomposition nodes to obtain multiple sub-networks, and install interfaces at the pre-decomposition nodes;
  • the adjustment module is configured to allocate the sub-network to each real-time simulator through the interface, and adjust the nodes in the sub-network based on the average resource utilization of all real-time simulators.
  • Fig. 1 is a flow chart of a decomposition method of an active distribution network real-time simulation model in an embodiment of the present invention
  • Figure 2 is a simplified topology diagram of a controllable voltage inverter in an embodiment of the present invention
  • Figure 3 is a structural diagram of a photovoltaic grid-connected power generation unit in an embodiment of the present invention.
  • FIG. 4 is a schematic diagram of parallel simulation of multiple real-time simulators in an embodiment of the present invention.
  • Figure 5 is a structural diagram of a 10kV voltage distribution network in an embodiment of the present invention.
  • FIG. 6 is a circuit structure diagram of a real-time simulation model of an active distribution network in an embodiment of the present invention.
  • FIG. 7 is a circuit structure diagram of a real-time simulation model of an active distribution network after decomposition in an embodiment of the present invention.
  • FIG. 8 is a circuit structure diagram of a real-time simulation model of an active distribution network after differentiation in an embodiment of the present invention
  • Figure 9 is a schematic diagram of a voltage-type ITM interface in an embodiment of the present invention.
  • Fig. 10 is a schematic diagram of a current-type ITM interface in an embodiment of the present invention.
  • the first embodiment of the present application provides a decomposition method of a real-time simulation model of an active distribution network.
  • the specific process is shown in Fig. 1, and the process is as follows:
  • S101 Determine the number of pre-decomposed networks and pre-decomposition nodes based on the number of real-time simulators and the number of switching devices in the real-time simulation model of the active distribution network;
  • S102 Based on the number of pre-decomposed networks and pre-decomposition nodes, pre-decompose the real-time simulation model of the active distribution network to obtain multiple sub-networks, and install interfaces at the pre-decomposition nodes;
  • S103 Assign the sub-network to each real-time simulator through the interface, and adjust the nodes in the sub-network based on the average resource utilization rate of all real-time simulators.
  • the first embodiment of the present application takes the controllable voltage inverter shown in Fig. 2 as an example.
  • S a , S b , S c are the apparent power of A, B, and C phases respectively
  • u ab is the AB phase line voltage on the AC side of the inverter
  • u bc is the BC phase line voltage on the AC side of the inverter
  • U ca is the AC phase line voltage on the AC side of the inverter.
  • the photovoltaic grid-connected power generation unit shown in FIG. 3 is taken as an example.
  • the direct current generated by the photovoltaic array usually needs to be converted into alternating current through a power electronic converter before it can be connected to the grid.
  • Photovoltaic grid-connected power generation units include photovoltaic arrays, power electronic converters, maximum power controllers and grid-connected controllers, as shown in Figure 3.
  • P mpp is the reference value of the output power of the photovoltaic array when the irradiance is 1kW/m 2 at the first temperature
  • T is the current temperature
  • I rr is the current irradiance
  • F T is the current output power coefficient
  • E FF is the current efficiency coefficient
  • P PV is the output power of the photovoltaic array
  • S PV is the apparent power of the photovoltaic array
  • P n and Q n are the active power and reactive power output by the inverter, respectively.
  • the transient simulation of the distribution network is to solve the differential-algebraic equations, the solution scale is large, and the solution speed is slow.
  • a simulation mechanism of multiple real-time simulators is adopted, as shown in Fig. 4.
  • RTDS is a real-time simulator.
  • the network to be simulated is decomposed into multiple sub-networks, and the sub-networks are connected by communication lines.
  • Each sub-network is assigned to a real-time simulator, and the solution results of multiple real-time simulators are shared through the communication line, reducing large-scale complex power distribution
  • the solution scale of the network realizes system-level parallel simulation.
  • FIG. 5 shows a 10kV voltage level distribution network structure diagram.
  • UPOC is a reactive power compensator.
  • the 10kV voltage level distribution network includes a distribution network and multiple distributed power generation units connected to the network (such as Photovoltaics, wind power, gas turbines, fuel cells, etc.), energy storage, load, considering the large scale of the solution of a single distributed power generation (energy storage) unit, the distribution network should be decomposed from a large number of distributed power generation (energy storage) units Solve.
  • the number of real-time simulators is not less than 4, the number of pre-decomposed networks n is taken as 4; when the number of real-time simulators is less than 4, the number of pre-decomposed networks n is taken as the number of real-time simulators.
  • the number of distributed power sources included in each sub-network is selected based on the number of system matrices, and the pre-decomposition node is selected based on the number of distributed power sources included in each sub-network and a preset decomposition principle.
  • the uniformity of the decomposition of the active distribution network real-time simulation model and the number of decomposition nodes directly affect the speed of parallel computing, which is an important factor affecting the parallel performance of the simulation.
  • the real-time simulation model of the active distribution network is decomposed into n sub-networks.
  • the real-time simulator When performing real-time simulation, the real-time simulator will pre-compute each switch state and store the node admittance matrix obtained by the pre-computation.
  • the value of the node admittance matrix k obtained by the real-time simulator pre-calculation will reach 2 48 , which requires a huge storage space and calculation amount of the real-time simulator, which may cause the real-time simulator to be unable to complete all of them within one step.
  • the real-time simulation model of the active distribution network cannot be simulated in real time.
  • the four sub-networks are calculated on different real-time simulators, and the number of node admittance matrices obtained by pre-calculation is 2 12 , which reduces the burden of real-time simulator calculations and also expands the simulation scale.
  • the real-time simulation model of the active distribution network is pre-decomposed according to the preset decomposition principle, and the number of distributed power generation (energy storage) units contained in each sub-network is set to ⁇ /n.
  • the preset decomposition principles include: 1) Phase Divide the distributed power sources of neighboring nodes into one sub-network; 2) If the interval between one of the nodes in the pre-decomposed sub-network and other nodes exceeds the preset maximum node interval, divide the node into other sub-networks; The maximum node interval is set based on the topology structure of the real-time simulation model of the active distribution network.
  • the interface installed at the pre-decomposition node includes a voltage-type ITM interface or a current-type ITM interface.
  • the interface in this embodiment adopts the ideal transformer model (ideal transformer model, ITM) interface.
  • ITM is based on the substitution theorem, using a controlled voltage source and The controlled current source is used as the signal receiving device to receive the voltage or current signal on the opposite side of the interface to realize the decomposition of the real-time simulation model of the active distribution network.
  • This embodiment pre-decomposes the real-time simulation model of the active distribution network shown in FIG. 6, and the circuit structure diagram of the real-time simulation model of the active distribution network after decomposition is shown in FIG.
  • the real-time simulation model is decomposed into sub-network 1 and sub-network 2.
  • subnet 1 is equivalent to subnet 2 with a controlled current source, and the controlled current source current is equal to the measured line current i of subnet 2;
  • subnet 2 is equivalent to subnet 1 with a controlled voltage source ,
  • the voltage of the controlled voltage source is equal to the measured interface voltage u of the subnet 1.
  • Adopting ITM only requires two variables of the sub-network: (1) the interface voltage u of the sub-network 1 is used as the control signal input of the controlled voltage source in the sub-network 2; (2) the line current i of the sub-network 2 is used as the sub-network 1 Control signal input of the controlled current source. Since the controlled current source cannot be directly connected in series with the inductive element, and the controlled voltage source cannot be directly connected in parallel with the capacitive element, it is necessary to perform differential processing on the controlled current source and the controlled voltage source.
  • the difference equation of the inductance volt-ampere characteristic can be obtained as: in,
  • the difference equation of the capacitance volt-ampere characteristic can be obtained as: in,
  • i km is the current of the inductor (capacitor) branch
  • u k and um are the voltages to ground on both sides of the inductor (capacitor), respectively.
  • ITM interface after differential processing is shown in Figure 8.
  • ITM interfaces are divided into voltage-type ITM interfaces as shown in Figure 9 and current-type ITM interfaces as shown in Figure 10.
  • E l (t) and E 2 (t) are subnet 1 and subnet respectively
  • Z l and Z 2 are the Thevenin equivalent impedances of subnet 1 and subnet 2, respectively.
  • the interface voltage u 1 of subnet 1 is transmitted to the controlled voltage source control terminal of subnet 2 after a step delay, and the interface current i 2 of subnet 2 is directly transmitted to subnet 1 Controlled current source control terminal; for the current-type ITM interface, the interface voltage u 2 of subnet 2 is directly transmitted to the controlled voltage source control terminal of subnet 1, and the interface current i 1 of subnet 1 is delayed by a step It is transmitted to the current source control terminal of sub-network 2.
  • Adjust the sub-network based on the average resource utilization of all real-time simulators including:
  • the resource utilization rate of the real-time simulator is greater than the average resource utilization rate.
  • the nodes containing distributed power sources in the sub-network corresponding to the average resource utilization rate are divided into the sub-networks corresponding to the resource utilization rate of the real-time simulator less than the average resource utilization rate, so that each real-time simulator
  • the resource utilization rate is equal to or as close as possible to the average resource utilization rate, and kept within an appropriate range, neither too high nor too low.
  • the average resource utilization of all real-time simulators is calculated as follows:
  • e avg represents the average resource utilization of the real-time simulator
  • Resource represents all real-time simulations
  • a storage device
  • m E m represents a real-time resource utilization of the emulator.
  • the real-time simulator solves the state space matrix of each sub-network, including:
  • Each real-time simulator initializes the sub-networks allocated by itself, and obtains the initial state of each sub-network;
  • Each real-time simulator solves the state space matrix of each sub-network based on the initial state of each sub-network to obtain the voltage signal and current signal of each sub-network;
  • Each sub-network updates its own state space matrix based on the voltage signal and current signal obtained by the exchange, and returns to step 2) to continue the solution until the end of the simulation.
  • Each real-time emulator initializes its assigned sub-network, including:
  • the initial value of the three-phase voltage of the opposite sub-network is obtained from the opposite sub-network, and the three-phase current of the local sub-network is sent to the opposite sub-network.
  • the number of pre-decomposed networks and pre-decomposition nodes are determined based on the number of real-time simulators and the number of switching devices in the real-time simulation model of the active distribution network;
  • the number of pre-decomposed networks and the pre-decomposition nodes are pre-decomposed on the active distribution network real-time simulation model to obtain multiple sub-networks, and interfaces are installed at the pre-decomposition nodes; the sub-networks are allocated to each real-time network through the interfaces
  • the simulator and adjusts the nodes in the sub-network based on the average resource utilization of all real-time simulators, can objectively decompose the real-time simulation model of the active distribution network, greatly shorten the decomposition time, and consider the real-time simulator
  • the average resource utilization rate of saves resources, adjusts the sub-networks obtained by pre-decomposition, and improves the accuracy of decomposition;
  • the technical solution provided by this application determines the number of node admittance matrices based on the number of switching devices in the active distribution network real-time simulation model, and intelligently decomposes the active distribution network real-time simulation model into several sub-networks, that is, a state space system is automatically decomposed into Several state space groups, each state space group solves the corresponding state space matrix, which greatly improves the calculation efficiency;
  • each real-time simulator corresponds to a sub-network, realizes the parallel calculation of multiple real-time simulators, can make full use of the resource utilization rate of the real-time simulator, maximize the real-time simulation speed of the distribution network, and expand the distribution network.
  • Network real-time simulation scale
  • the technical solution provided in this application improves the electromagnetic transient simulation capability of the distribution network, and provides technical support for the operation analysis, equipment research and development, and dispatch control of the distribution network.
  • Embodiment 2 of the present application also provides a decomposition device for a real-time simulation model of an active distribution network, including:
  • the determining module is configured to determine the number of pre-decomposed networks and pre-decomposition nodes based on the number of real-time simulators and the number of switching devices in the real-time simulation model of the active distribution network;
  • the decomposition module is configured to pre-decompose the real-time simulation model of the active distribution network to obtain multiple sub-networks based on the number of pre-decomposed networks and pre-decomposition nodes, and install interfaces at the pre-decomposition nodes;
  • the adjustment module is configured to allocate the sub-network to each real-time simulator through an interface, and adjust the nodes in the sub-network based on the average resource utilization of all real-time simulators.
  • the number of distributed power sources included in each sub-network is selected based on the number of system matrices, and the pre-decomposition node is selected based on the number of distributed power sources included in each sub-network and a preset decomposition principle.
  • the preset decomposition principles include:
  • the distributed power sources of adjacent nodes are divided into a sub-network
  • the maximum node interval is set based on the topology of the active distribution network real-time simulation model.
  • the adjustment module includes:
  • the determining unit is configured to determine the resource utilization rate of each real-time simulator according to the process of solving the state space matrix of each sub-network by the real-time simulator;
  • the calculation unit is configured to calculate the average resource utilization rate of all real-time simulators based on the resource utilization rate of each real-time simulator;
  • the adjustment unit is configured to divide the nodes containing distributed power sources in the sub-network corresponding to the real-time simulator's resource utilization rate greater than the average resource utilization rate into the sub-networks corresponding to the real-time simulator resource utilization rate being less than the average resource utilization rate, so that The resource utilization of each real-time simulator is equal to or as close as possible to the average resource utilization.
  • the calculation unit calculates the average resource utilization of all real-time simulators as follows:
  • e avg represents the average resource utilization of all real-time simulators
  • Resource represents the total storage space of all real-time simulators
  • Utilization represents the total amount of computing tasks of all real-time simulators
  • n represents the number of real-time simulator
  • Uti m represents the m-th real memory space of the emulator
  • m E m represents a real-time resource utilization of the emulator.
  • the specific configuration of the computing unit is:
  • Each real-time simulator initializes the sub-networks allocated by itself, and obtains the initial state of each sub-network;
  • Each real-time simulator solves the state space matrix of each sub-network based on the initial state of each sub-network to obtain the voltage signal and current signal of each sub-network;
  • Each sub-network updates its own state space matrix based on the voltage signal and current signal obtained by the exchange, and returns to step 2) to continue the solution until the end of the simulation.
  • the interface includes a voltage-type ITM interface or a current-type ITM interface.
  • the specific configuration of the computing unit is:
  • the initial value of the three-phase voltage of the opposite sub-network is obtained from the opposite sub-network, and the three-phase current of the local sub-network is sent to the opposite sub-network.
  • each part of the above device is divided into various modules or units by function and described separately.
  • the functions of each module or unit can be implemented in the same or multiple software or hardware.
  • 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 can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, read-only memory CD-ROM, optical storage, etc.) containing computer-usable program codes. .
  • 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

一种有源配电网实时仿真模型的分解方法和装置，所述方法包括：基于有源配电网实时仿真模型中实时仿真器的数目和开关器件数目确定预分解的网络数和预分解节点（S101）；基于所述预分解的网络数和预分解节点，对有源配电网实时仿真模型进行预分解得到多个子网络，并在预分解节点处加装接口（S102）；通过所述接口将子网络分配给每个实时仿真器，并基于所有实时仿真器的平均资源利用率对子网络内的节点进行调整（S103）。

Description

有源配电网实时仿真模型的分解方法和装置
本申请要求在2020年04月21日提交中国专利局、申请号为202010316298.2的中国专利申请的优先权，以上申请的全部内容通过引用结合在本申请中。
技术领域
本申请涉及电力系统仿真技术领域，例如涉及一种有源配电网实时仿真模型的分解方法和装置。
背景技术
随着国家电网公司配电网建设和改造工作的推进，大量新型设备如分布式电源、电动汽车等接入配电网，配电网规模庞大、节点众多、设备繁杂、运行方式多样的特点日益突出。一方面，配电网涵盖了负荷、变压器、断路器、环网柜等多种设备，同时包含大量分布式电源、储能元件、静止无功补偿器等电力电子设备；另一方面，配电网从原有的单电源辐射状结构、手拉手接线方式发展为双电源环网、多电源网格状接线方式，造成配电网在规模上不断扩大，节点数大大增加，复杂程度也呈现指数形式上升，对复杂配电网的实时仿真技术提出了更高的要求和挑战。
有源配电网实时仿真模型分解方法是解决配电网实时仿真问题的有效手段之一。模型分解是基于分组分群的思想，对配电网进行模型分解处理，将配电网分解成若干个子网络，将一个状态空间系统分解为两个或多个状态空间群组，每个状态空间群组对相应的状态空间矩阵进行求解。将模型分解和并行计算相结合，通过基于分解模型的多处理器并行计算可以有效减轻一个处理器的计算负担，提高仿真规模，实现复杂配电网的快速仿真。但是相关技术一般通过手动方式对规模较大或含有大量电力电子器件的有源配电网实时仿真模型进行分解，具体是通过手动加装接口实现有源配电网实时仿真模型的分解，主观性强，耗时长，资源浪费严重，分解结果不准确。
发明内容
本申请提供一种有源配电网实时仿真模型的分解方法，包括：
基于有源配电网实时仿真模型中实时仿真器的数目和开关器件数目确定预分解的网络数和预分解节点；
基于所述预分解的网络数和预分解节点，对有源配电网实时仿真模型进行预分解得到多个子网络，并在预分解节点处加装接口；
通过所述接口将所述子网络分配给每个实时仿真器，并基于所有实时仿真器的平均资源利用率对所述子网络内的节点进行调整。
基于同一申请构思，本申请还提供一种有源配电网实时仿真模型的分解装置，包括：
确定模块，配置为基于有源配电网实时仿真模型中实时仿真器的数目和开关器件数目确定预分解的网络数和预分解节点；
分解模块，配置为基于所述预分解的网络数和预分解节点，对有源配电网实时仿真模型进行预分解得到多个子网络，并在预分解节点处加装接口；
调整模块，配置为通过所述接口将所述子网络分配给每个实时仿真器，并基于所有实时仿真器的平均资源利用率对所述子网络内的节点进行调整。
附图说明
图1是本发明实施例中有源配电网实时仿真模型的分解方法流程图；
图2是本发明实施例中可控电压型逆变器的简化拓扑结构图；
图3是本发明实施例中光伏并网发电单元结构图；
图4是本发明实施例中多实时仿真器并行仿真示意图；
图5是本发明实施例中10kV电压等级配电网结构图；
图6是本发明实施例中有源配电网实时仿真模型电路结构图；
图7是本发明实施例中分解后的有源配电网实时仿真模型电路结构图；
图8是本发明实施例中差分化后的有源配电网实时仿真模型电路结构图；
图9是本发明实施例中电压型ITM接口原理图；
图10是本发明实施例中电流型ITM接口原理图。
具体实施方式
下面结合附图对本申请作进一步详细说明。
实施例一
本申请实施例一提供了一种有源配电网实时仿真模型的分解方法，具体流程如图1所示，过程如下：
S101：基于有源配电网实时仿真模型中实时仿真器的数目和开关器件数目确定预分解的网络数和预分解节点；
S102：基于预分解的网络数和预分解节点，对有源配电网实时仿真模型进行预分解得到多个子网络，并在预分解节点处加装接口；
S103：通过接口将子网络分配给每个实时仿真器，并基于所有实时仿真器的平均资源利用率对子网络内的节点进行调整。
基于有源配电网实时仿真模型中实时仿真器的数目和开关器件数目确定预分解的网络数和预分解节点，包括：
1)基于有源配电网实时仿真模型中分布式电源的数目和实时仿真器的数目确定预分解的网络数；
光伏、风机、燃料电池、微型燃气轮机等分布式电源均需要通过电力电子变流器接入电网，以解决不同电压等级、频率以及交直流系统间的能量传递问题。包含电力电子变流器的设备元件的暂态模型对实时仿真器计算量的需求，是影响预分解网络数的重要因素。
本申请实施例一以图2所示的可控电压型逆变器为例，在同一时刻，假定可控电压型逆变器的每相中只有一个开关器件导通，定义S k(k＝a，b，c)为桥臂的开关函数：
Figure PCTCN2020113692-appb-000001
根据图2所示的拓扑结构，可得逆变器交流侧相线电压与直流侧电压U dc的关系如下：
Figure PCTCN2020113692-appb-000002
上式中，S a、S b、S c分别为A、B、C相的视在功率，u ab为逆变器交流侧AB相线电压，u bc为逆变器交流侧BC相线电压，u ca为逆变器交流侧AC相线电压。
本申请实施例一以图3所示的光伏并网发电单元为例，光伏阵列产生的直流电，通常需要经过电力电子变流器转换成交流电才能接入电网。光伏并网发电单元包括光伏阵列、电力电子变流器、最大功率控制器和并网控制器，如图3所示。图3中，P mpp是第一温度下辐照度为1kW/m 2时光伏阵列输出功率的基准值；T为当前温度，I rr为当前辐照度，F T为当前输出功率系数，E FF为当前效率系数，P PV为光伏阵列的输出功率，S PV为光伏阵列的视在功率，P n和Q n分别为逆变器输出的有功功率和无功功率。
电力电子变流器开关器件数量众多且开关状态相互耦合，大量的预计算需要实时仿真器具有较大的存储空间和较强的计算能力，这给模型的实时化带来了困难。
配电网的暂态仿真为求解微分-代数方程组，解算规模大，求解速度慢。为实现实时仿真，采用多实时仿真器仿真机制，如图4所示，图4中，RTDS为实时仿真器。将待仿真的网络分解为多个子网络，子网络之间通过通讯线连接，每个子网络分配给一个实时仿真器，多个实时仿真器的解算结果通过通讯线共享，降低大规模复杂配电网的求解规模，实现系统级并行仿真。
图5示出一10kV电压等级配电网结构图，图5中，UPOC为无功补偿器，10kV电压等级配电网包括配电网络以及接于该网络上的多个分布式发电单元(如光伏、风电、燃气轮机、燃料电池等)、储能、负荷，考虑到单个分布式发电(储能)单元的解算规模较大，应将配电网络与大量分布式发电(储能)单元分解求解。当实时仿真器的数量不少于4个时，预分解的网络数n取为4；当实时仿真器的数量少于4个时，预分解的网络数n取为实时仿真器的数量。
2)通过有源配电网实时仿真模型中开关器件数目确定有源配电网的系统矩阵数目；
3)基于系统矩阵数目选取每个子网络包含的分布式电源数目，并基于每个子网络包含的分布式电源数目和预设的分解原则选取预分解节点。
有源配电网实时仿真模型分解的均匀程度和分解节点数目直接影响并行计算的速度，是影响仿真并行性能的重要因素。按照预分解节点，将有源配电网实时仿真模型分解为n个子网络。
在进行实时仿真时，实时仿真器会对每种开关状态进行预计算并且存储预 计算所得到的节点导纳矩阵。对于采用图2所示的电压型逆变器的分布式发电(储能)单元，每个单元所包含的开关器件数为6个，对应的节点导纳矩阵数目为2 6＝64个。
以图5所示的10kV电压等级配电网为例，有源配电网实时仿真模型中分布式发电(储能)单元的总数Δ＝8。不对有源配电网实时仿真模型进行分解，作为一个状态空间系统进行解算时，有x(t+Δt)＝A kx(t)+B ku(t+Δt),k＝1,2,...，其中，x，u分别为状态变量和输入矢量，A k，B k分别为第k个开关序列所对应的状态矩阵。实时仿真器预计算所得到的节点导纳矩阵数目k的取值将达到2 48个，这需要实时仿真器巨大的存储空间和计算量，可能导致实时仿真器无法在一个步长内完成所有的计算，最终不能对有源配电网实时仿真模型进行实时仿真。
本实施例对有源配电网实时仿真模型进行分解，每个子网络包含的分布式发电(储能)单元数为8/4＝2，分解结果如图5中虚线框所示。将一个有源配电网实时仿真模型分解为4个子网络，4个实时仿真器并行计算：
x 1(t+Δt)＝A k1x 1(t)+B k1u 1(t+Δt),k 1＝1,2,...,2 12
x 2(t+Δt)＝A k2x 2(t)+B k2u 2(t+Δt),k 2＝1,2,...,2 12
x 3(t+Δt)＝A k3x 3(t)+B k3u 3(t+Δt),k 3＝1,2,...,2 12
x 4(t+Δt)＝A k4x 4(t)+B k4u 4(t+Δt),k 4＝1,2,...,2 12
4个子网络分别在不同的实时仿真器上进行计算，则预计算所得到的节点导纳矩阵数目为2 12，减少了实时仿真器运算时的负担，同时也扩大了仿真规模。
统计配电网中分布式发电(储能)单元的总数为Δ。对有源配电网实时仿真模型按照预设的分解原则进行预分解，设定每个子网络包含的分布式发电(储能)单元数为Δ/n，预设的分解原则包括：1)相邻节点的分布式电源划分到一个子网络中；2)若预分解后的子网络中的其中一个节点与其他节点间隔超过预设的最大节点间隔，则将该节点划分到其他子网络中；最大节点间隔基于有源配电网实时仿真模型的拓扑结构设定。
在预分解节点处加装的接口包括电压型ITM接口或电流型ITM接口，本实施例中的接口采用理想变压器模型(ideal transformer model，ITM)接口，ITM基于替代定理，利用受控电压源和受控电流源作为信号接收装置，接收接口对侧的电压或电流信号，实现有源配电网实时仿真模型的分解。
本实施例对图6所示的有源配电网实时仿真模型进行预分解，分解后的有源配电网实时仿真模型电路结构图如图7所示，在虚线处将有源配电网实时仿真模型分解为子网络1和子网络2。基于替代定理，子网络1中用受控电流源等效子网络2，受控电流源电流等于测量得到的子网络2的线路电流i；子网络2中用受控电压源等效子网络1，受控电压源电压等于测量得到的子网络1接口电压u。采用ITM仅需要子网络的2个变量：(1)子网络1的接口电压u，作为子网络2中受控电压源的控制信号输入；(2)子网络2的线路电流i，作为子网络1中受控电流源的控制信号输入。由于受控电流源不能直接和电感元件串联，受控电压源不能直接和电容元件并联，所以需要对受控电流源和受控电压源进行差分处理。
采用隐式梯形积分法可得电感伏安特性的差分方程为：
Figure PCTCN2020113692-appb-000003
其中，
Figure PCTCN2020113692-appb-000004
Figure PCTCN2020113692-appb-000005
同理，可得电容伏安特性的差分方程为：
Figure PCTCN2020113692-appb-000006
其中，
Figure PCTCN2020113692-appb-000007
式中，i km为电感(电容)支路电流，u k、u m分别为电感(电容)两侧对地电压。
差分化处理后ITM接口如图8所示。根据接口类型的不同，ITM接口分为如图9所示的电压型ITM接口和如图10所示的电流型ITM接口，E l(t)、E 2(t)分别为子网络1和子网络2的戴维南等效电压，Z l、Z 2分别为子网络1和子网络2的戴维南等效阻抗。对于电压型ITM接口，子网络1的接口电压u 1，经过一个步长的延时后传输给子网络2受控电压源控制端，子网络2的接口电流i 2，直接传输给子网络1受控电流源控制端；对于电流型ITM接口，子网络2的接口电压u 2，直接传输给子网络1受控电压源控制端，子网络1的接口电流i 1经过一个步长延时后传输给子网络2电流源控制端。
基于所有实时仿真器的平均资源利用率对子网络进行调整，包括：
根据实时仿真器对每个子网络的状态空间矩阵进行求解的过程确定每个实时仿真器的资源利用率；
基于每个实时仿真器的资源利用率计算所有实时仿真器的平均资源利用率；
将实时仿真器的资源利用率大于平均资源利用率对应的子网络中包含分布式电源的节点划分到实时仿真器的资源利用率小于平均资源利用率对应的子网络中，使每个实时仿真器的资源利用率与平均资源利用率相等或尽可能接近，且保持在适当的范围内，既不过高，也不过低。
所有实时仿真器的平均资源利用率按下式计算：
Figure PCTCN2020113692-appb-000008
式中，e avg表示实时仿真器的平均资源利用率；Resource表示所有实时仿真
Figure PCTCN2020113692-appb-000009
器的存储空间；e m表示第m个实时仿真器的资源利用率。
实时仿真器对每个子网络的状态空间矩阵进行求解，包括：
1)每个实时仿真器对自身所分配的子网络进行初始化，得到每个子网络的初始状态；
2)每个实时仿真器基于每个子网络的初始状态，对每个子网络的状态空间矩阵进行求解，得到每个子网络的电压信号和电流信号；
3)基于不同子网络之间的接口关系和接口类型交换相邻子网络的电压信号和电流信号；
4)每个子网络基于交换得到的电压信号和电流信号对自身的状态空间矩阵进行更新，返回步骤2)继续求解，直至仿真结束。
每个实时仿真器对自身所分配的子网络进行初始化，包括：
若采用电压型ITM接口，从对侧子网络获取对侧子网络的三相电流初始值，并将本侧子网络的三相电压送入对侧子网络；
若采用电流型ITM接口，从对侧子网络获取对侧子网络的三相电压初始值， 并将本侧子网络的三相电流送入对侧子网络。
本申请提供的有源配电网实时仿真模型的分解方法中，基于有源配电网实时仿真模型中实时仿真器的数目和开关器件数目确定预分解的网络数和预分解节点；基于所述预分解的网络数和预分解节点，对有源配电网实时仿真模型进行预分解得到多个子网络，并在预分解节点处加装接口；通过所述接口将所述子网络分配给各个实时仿真器，并基于所有实时仿真器的平均资源利用率对所述子网络内的节点进行调整，能够客观的分解有源配电网实时仿真模型，大大缩短了分解时间，且考虑了实时仿真器的平均资源利用率，节省了资源，对预分解得到的子网络进行调整，提高了分解准确性；
本申请提供的技术方案通过有源配电网实时仿真模型中开关器件数目确定节点导纳矩阵数目，将有源配电网实时仿真模型智能分解成若干个子网络，即将一个状态空间系统自动分解为若干个状态空间群组，每个状态空间群组对相应的状态空间矩阵进行求解，大大提高了计算效率；
本申请提供的技术方案每个实时仿真器对应一个子网络，实现多个实时仿真器的并行计算，能够充分利用实时仿真器的资源利用率，最大程度提高配电网实时仿真速度，扩大配电网实时仿真规模；
本申请提供的技术方案提高了配电网电磁暂态仿真能力，为配电网的运行分析、装备研发、调度控制等提供技术支持。
实施例二
基于同一申请构思，本申请实施例二还提供一种有源配电网实时仿真模型的分解装置，包括：
确定模块，配置为基于有源配电网实时仿真模型中实时仿真器的数目和开关器件数目确定预分解的网络数和预分解节点；
分解模块，配置为基于预分解的网络数和预分解节点，对有源配电网实时仿真模型进行预分解得到多个子网络，并在预分解节点处加装接口；
调整模块，配置为通过接口将子网络分配给每个实时仿真器，并基于所有实时仿真器的平均资源利用率对子网络内的节点进行调整。
确定模块具体配置为：
基于有源配电网实时仿真模型中分布式电源的数目和实时仿真器的数目确定预分解的网络数；
通过有源配电网实时仿真模型中开关器件数目确定有源配电网的系统矩阵数目；
基于系统矩阵数目选取每个子网络包含的分布式电源数目，并基于每个子网络包含的分布式电源数目和预设的分解原则选取预分解节点。
预设的分解原则包括：
相邻节点的分布式电源划分到一个子网络中；
若预分解后的子网络中的其中一个节点与其他节点间隔超过预设的最大节点间隔，则将该节点划分到其他子网络中；
其中，最大节点间隔基于有源配电网实时仿真模型的拓扑结构设定。
调整模块包括：
确定单元，配置为根据实时仿真器对每个子网络的状态空间矩阵进行求解的过程确定每个实时仿真器的资源利用率；
计算单元，配置为基于每个实时仿真器的资源利用率计算所有实时仿真器的平均资源利用率；
调整单元，配置为将实时仿真器的资源利用率大于平均资源利用率对应的子网络中包含分布式电源的节点划分到实时仿真器的资源利用率小于平均资源利用率对应的子网络中，使每个实时仿真器的资源利用率与平均资源利用率相等或尽可能接近。
计算单元按下式计算所有实时仿真器的平均资源利用率：
Figure PCTCN2020113692-appb-000010
式中，e avg表示所有实时仿真器的平均资源利用率；Resource表示所有实时仿真器的总存储空间；Utilization表示所有实时仿真器的总计算任务量，
Figure PCTCN2020113692-appb-000011
n表示实时仿真器的数目；Uti m表示第m个实时仿真器的存储空间；e m表示第m个实时仿真器的资源利用率。
计算单元具体配置为：
1)每个实时仿真器对自身所分配的子网络进行初始化，得到每个子网络的初始状态；
2)每个实时仿真器基于每个子网络的初始状态，对每个子网络的状态空间矩阵进行求解，得到每个子网络的电压信号和电流信号；
3)基于不同子网络之间的接口关系和接口类型交换相邻子网络的电压信号和电流信号；
4)每个子网络基于交换得到的电压信号和电流信号对自身的状态空间矩阵进行更新，返回2)步骤继续求解，直至仿真结束。
接口包括电压型ITM接口或电流型ITM接口。
计算单元具体配置为：
若采用电压型ITM接口，从对侧子网络获取对侧子网络的三相电流初始值，并将本侧子网络的三相电压送入对侧子网络；
若采用电流型ITM接口，从对侧子网络获取对侧子网络的三相电压初始值，并将本侧子网络的三相电流送入对侧子网络。
为了描述的方便，以上装置的各部分以功能分为各种模块或单元分别描述。当然，在实施本申请时可以把各模块或单元的功能在同一个或多个软件或硬件中实现。
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、只读存储器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。
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Claims (16)

  1. 一种有源配电网实时仿真模型的分解方法，包括：
    基于有源配电网实时仿真模型中实时仿真器的数目和开关器件数目确定预分解的网络数和预分解节点；
    基于所述预分解的网络数和预分解节点，对有源配电网实时仿真模型进行预分解得到多个子网络，并在预分解节点处加装接口；
    通过所述接口将所述子网络分配给每个实时仿真器，并基于所有实时仿真器的平均资源利用率对所述子网络内的节点进行调整。
  2. 根据权利要求1所述的有源配电网实时仿真模型的分解方法，其中，所述基于有源配电网实时仿真模型中实时仿真器的数目和开关器件数目确定预分解的网络数和预分解节点，包括：
    基于有源配电网实时仿真模型中分布式电源的数目和实时仿真器的数目确定预分解的网络数；
    通过有源配电网实时仿真模型中开关器件数目确定有源配电网的系统矩阵数目；
    基于系统矩阵数目选取每个子网络包含的分布式电源数目，并基于每个子网络包含的分布式电源数目和预设的分解原则选取预分解节点。
  3. 根据权利要求2所述的有源配电网实时仿真模型的分解方法，其中，所述预设的分解原则包括：
    相邻节点的分布式电源划分到一个子网络中；
    若预分解后的子网络中的其中一个节点与其他节点间隔超过预设的最大节点间隔，则将该节点划分到其他子网络中；
    其中，所述最大节点间隔基于有源配电网实时仿真模型的拓扑结构设定。
  4. 根据权利要求1、2或3所述的有源配电网实时仿真模型的分解方法，其中，所述基于所有实时仿真器的平均资源利用率对所述子网络内的节点进行调整，包括：
    根据实时仿真器对每个子网络的状态空间矩阵进行求解的过程确定每个实时仿真器的资源利用率；
    基于每个实时仿真器的资源利用率计算所有实时仿真器的平均资源利用率；
    将实时仿真器的资源利用率大于平均资源利用率对应的子网络中包含分布式电源的节点划分到实时仿真器的资源利用率小于平均资源利用率对应的子网络中，使每个实时仿真器的资源利用率与平均资源利用率相等。
  5. 根据权利要求4所述的有源配电网实时仿真模型的分解方法，其中，所述所有实时仿真器的平均资源利用率按下式计算：
    Figure PCTCN2020113692-appb-100001
    式中，e avg表示所有实时仿真器的平均资源利用率；Resource表示所有实时仿真器的总存储空间；Utilization表示所有实时仿真器的总计算任务量，
    Figure PCTCN2020113692-appb-100002
    n表示实时仿真器的数目；Uti m表示第m个实时仿真器的存储空间；e m表示第m个实时仿真器的资源利用率。
  6. 根据权利要求4或5所述的有源配电网实时仿真模型的分解方法，其中，所述实时仿真器对每个子网络的状态空间矩阵进行求解包括：
    1)每个实时仿真器对自身所分配的子网络进行初始化，得到每个子网络的初始状态；
    2)每个实时仿真器基于每个子网络的初始状态，对每个子网络的状态空间矩阵进行求解，得到每个子网络的电压信号和电流信号；
    3)基于不同子网络之间的接口关系和接口类型交换相邻子网络的电压信号和电流信号；
    4)每个子网络基于交换得到的电压信号和电流信号对自身的状态空间矩阵进行更新，返回步骤2)继续求解，直至仿真结束。
  7. 根据权利要求6所述的有源配电网实时仿真模型的分解方法，其中，所述接口包括电压型ITM接口或电流型ITM接口。
  8. 根据权利要求7所述的有源配电网实时仿真模型的分解方法，其中，所述每个实时仿真器对自身所分配的子网络进行初始化，包括：
    在采用电压型ITM接口的情况下，从对侧子网络获取对侧子网络的三相电流初始值，并将本侧子网络的三相电压送入对侧子网络；
    在采用电流型ITM接口的情况下，从对侧子网络获取对侧子网络的三相电压初始值，并将本侧子网络的三相电流送入对侧子网络。
  9. 一种有源配电网实时仿真模型的分解装置，包括：
    确定模块，配置为基于有源配电网实时仿真模型中实时仿真器的数目和开关器件数目确定预分解的网络数和预分解节点；
    分解模块，配置为基于所述预分解的网络数和预分解节点，对有源配电网实时仿真模型进行预分解得到多个子网络，并在预分解节点处加装接口；
    调整模块，配置为通过所述接口将所述子网络分配给每个实时仿真器，并基于所有实时仿真器的平均资源利用率对所述子网络内的节点进行调整。
  10. 根据权利要求9所述的有源配电网实时仿真模型的分解装置，其中，所述确定模块配置为：
    基于有源配电网实时仿真模型中分布式电源的数目和实时仿真器的数目确定预分解的网络数；
    通过有源配电网实时仿真模型中开关器件数目确定有源配电网的系统矩阵数目；
    基于系统矩阵数目选取每个子网络包含的分布式电源数目，并基于每个子网络包含的分布式电源数目和预设的分解原则选取预分解节点。
  11. 根据权利要求10所述的有源配电网实时仿真模型的分解装置，其中，所述预设的分解原则包括：
    相邻节点的分布式电源划分到一个子网络中；
    若预分解后的子网络中的其中一个节点与其他节点间隔超过预设的最大节点间隔，则将该节点划分到其他子网络中；
    其中，所述最大节点间隔基于有源配电网实时仿真模型的拓扑结构设定。
  12. 根据权利要求9、10或11所述的有源配电网实时仿真模型的分解装置，其中，所述调整模块包括：
    确定单元，配置为根据实时仿真器对每个子网络的状态空间矩阵进行求解的过程确定每个实时仿真器的资源利用率；
    计算单元，配置为基于每个实时仿真器的资源利用率计算所有实时仿真器的平均资源利用率；
    调整单元，配置为将实时仿真器的资源利用率大于平均资源利用率对应的子网络中包含分布式电源的节点划分到实时仿真器的资源利用率小于平均资源利用率对应的子网络中，使实时仿真器的资源利用率与平均资源利用率相等。
  13. 根据权利要求12所述的有源配电网实时仿真模型的分解装置，其中，所述计算单元按下式计算实时仿真器的平均资源利用率：
    Figure PCTCN2020113692-appb-100003
    式中，e avg表示实时仿真器的平均资源利用率；Resource表示所有实时仿真器的总存储空间；Utilization表示所有实时仿真器的总计算任务量，
    Figure PCTCN2020113692-appb-100004
    n表示实时仿真器的数目；Uti m表示第m个实时仿真器的存储空间；e m表示第m个实时仿真器的资源利用率。
  14. 根据权利要求12或13所述的有源配电网实时仿真模型的分解装置，其中，所述计算单元配置为：
    1)每个实时仿真器对自身所分配的子网络进行初始化，得到每个子网络的初始状态；
    2)每个实时仿真器基于每个子网络的初始状态，对每个子网络的状态空间矩阵进行求解，得到每个子网络的电压信号和电流信号；
    3)基于不同子网络之间的接口关系和接口类型交换相邻子网络的电压信号和电流信号；
    4)每个子网络基于交换得到的电压信号和电流信号对自身的状态空间矩阵进行更新，返回步骤2)继续求解，直至仿真结束。
  15. 根据权利要求14所述的有源配电网实时仿真模型的分解装置，其中，所述接口包括电压型ITM接口或电流型ITM接口。
  16. 根据权利要求15所述的有源配电网实时仿真模型的分解装置，其中，所述计算单元配置为：
    在采用电压型ITM接口的情况下，从对侧子网络获取对侧子网络的三相电流初始值，并将本侧子网络的三相电压送入对侧子网络；
    在采用电流型ITM接口的情况下，从对侧子网络获取对侧子网络的三相电压初始值，并将本侧子网络的三相电流送入对侧子网络。
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