技术领域technical field
本发明涉及配用电领域，更具体的说，涉及一种计算配用电系统网损和可靠性的方法及系统。The invention relates to the field of power distribution and consumption, and more particularly, to a method and system for calculating the network loss and reliability of a power distribution and consumption system.
背景技术Background technique
智能配用电系统与传统配电网在运行特性方面有较大的差异，产生差异的主要原因是智能配用电系统中增加了新型配用电设备，如增加了分布式电源、储能装置、电动汽车充放电站等。The intelligent power distribution system is quite different from the traditional power distribution network in terms of operating characteristics. The main reason for the difference is that new power distribution equipment has been added to the intelligent power distribution system, such as the addition of distributed power sources and energy storage devices. , Electric vehicle charging and discharging stations, etc.
在智能配用电系统中增加了新型配用电设备后，整个配用电系统的网损和可靠性等数据会发生改变。现有技术中，在欲增加新型配用电设备时，首先会计算增加了该新型配用电设备后的网损和可靠性等数据，计算网损和可靠性等数据时，会设定欲增加的新型配用电设备的出力或用电是固定不变的，但是实际上，欲增加的新型配用电设备的出力或用电是随着时间或负载值而不断变化的，如分布式光伏电源的出力是随着时间不断变化的，进而使得现有技术中智能配用电系统在欲增加新型配用电设备时，计算得到的增加了该新型配用电设备后的网损和可靠性等数据不准确。After a new type of power distribution equipment is added to the intelligent power distribution system, the network loss and reliability data of the entire power distribution system will change. In the prior art, when a new type of power distribution and consumption equipment is to be added, the network loss and reliability data after the new type of power distribution and consumption equipment are added are first calculated. The output or power consumption of the new power distribution equipment added is fixed, but in fact, the output or power consumption of the new power distribution equipment to be added is constantly changing with time or load value. The output of the photovoltaic power source is constantly changing with time, so that when the intelligent power distribution system in the prior art wants to add a new type of power distribution equipment, the calculated network loss and reliability of the new type of power distribution equipment are increased. Data such as sex are inaccurate.
发明内容SUMMARY OF THE INVENTION
有鉴于此，本发明提供一种计算配用电系统网损和可靠性的方法及系统，以解决现有技术中智能配用电系统在欲增加新型配用电设备时，计算得到的增加了该新型配用电设备后的网损和可靠性等数据不准确的问题。In view of this, the present invention provides a method and system for calculating the network loss and reliability of a power distribution system, so as to solve the problem of increasing the calculated power loss when a new type of power distribution equipment is to be added to the intelligent power distribution system in the prior art. The problem of inaccurate data such as network loss and reliability after the new power distribution equipment.
为解决上述技术问题，本发明采用了如下技术方案：In order to solve the above-mentioned technical problems, the present invention adopts the following technical solutions:
一种计算配用电系统网损和可靠性的方法，包括：A method for calculating network loss and reliability of a power distribution system, comprising:
构建配用电模型；其中，所述配用电模型中包括已有配用电设备的电路结构模型和待增配用电设备的电路结构模型；Building a power distribution model; wherein the power distribution model includes a circuit structure model of the existing power distribution equipment and a circuit structure model of the power equipment to be added;
获取已有配用电设备的历史运行数据，以及所述待增配用电设备的配用电数学模型；其中，所述配用电数学模型为所述待增配用电设备的出力数学模型或用电数学模型；Obtain the historical operation data of the existing electrical equipment and the mathematical model of the electrical equipment to be added; wherein the mathematical model of the electrical equipment to be added is the output mathematical model of the electrical equipment to be added or electricity mathematical model;
基于所述配用电数学模型，确定所述待增配用电设备的预测运行数据；其中，所述待增配用电设备的预测运行数据随时间或负载值变化；Determine the predicted operation data of the electric equipment to be added based on the mathematical model of distribution and consumption; wherein the predicted operation data of the electric equipment to be added changes with time or load value;
根据所述配用电模型、所述已有配用电设备的历史运行数据和所述待增配用电设备的预测运行数据，计算所述配用电模型的运行参数；Calculate the operating parameters of the power distribution model according to the power distribution model, the historical operation data of the existing power distribution equipment, and the predicted operation data of the to-be-added power equipment;
其中，所述配用电模型的运行参数包括潮流计算结果、网损值和可靠性系数。Wherein, the operating parameters of the power distribution model include power flow calculation results, network loss values and reliability coefficients.
优选地，根据所述配用电模型、所述已有配用电设备的历史运行数据和所述待增配用电设备的预测运行数据，计算所述配用电模型的运行参数，包括：Preferably, the operating parameters of the power distribution model are calculated according to the power distribution model, the historical operation data of the existing power distribution equipment, and the predicted operation data of the power equipment to be added, including:
确定多个时间断面；Determine multiple time sections;
确定每一所述时间断面对应的已有配用电设备的历史运行数据中的历史运行子数据以及所述待增配用电设备的预测运行数据中的预测运行子数据；Determining the historical operation sub-data in the historical operation data of the existing electric power distribution equipment corresponding to each time section and the predicted operation sub-data in the predicted operation data of the electric equipment to be added;
基于所述配用电模型、每一所述时间断面对应的历史运行子数据以及预测运行子数据，计算所述配用电模型的运行参数。Based on the power distribution model, historical operation sub-data and predicted operation sub-data corresponding to each of the time sections, the operating parameters of the power distribution model are calculated.
优选地，基于所述配用电模型、每一所述时间断面对应的历史运行子数据以及预测运行子数据，计算所述配用电模型的运行参数，包括：Preferably, based on the power distribution model, the historical operation sub-data corresponding to each of the time sections, and the predicted operation sub-data, the operating parameters of the power distribution model are calculated, including:
基于所述配用电模型、每一所述时间断面对应的历史运行子数据以及预测运行子数据，构建每一所述时间断面对应的电路结构图；Based on the power distribution model, the historical operation sub-data and the predicted operation sub-data corresponding to each of the time sections, constructing a circuit structure diagram corresponding to each of the time sections;
根据每一所述时间断面对应的电路结构图，进行潮流计算，得到潮流计算结果；According to the circuit structure diagram corresponding to each said time section, carry out the power flow calculation, and obtain the power flow calculation result;
依据潮流计算结果、每一所述时间断面对应的历史运行子数据以及预测运行子数据，计算得到每一所述时间断面对应的子网损值和可靠性子系数；According to the power flow calculation result, the historical operation sub-data and the predicted operation sub-data corresponding to each of the time sections, the sub-network loss value and the reliability sub-coefficient corresponding to each of the time sections are calculated and obtained;
基于每一所述时间断面对应的子网损值和可靠性子系数，计算所述配用电模型的网损值和可靠性系数。Based on the sub-network loss value and reliability sub-coefficient corresponding to each of the time sections, the network loss value and reliability coefficient of the distribution and consumption model are calculated.
优选地，基于每一所述时间断面对应的子网损值和可靠性子系数，计算所述配用电模型的网损值和可靠性系数，包括：Preferably, based on the sub-network loss value and reliability sub-coefficient corresponding to each of the time sections, the network loss value and reliability coefficient of the power distribution model are calculated, including:
将每一所述时间断面对应的子网损值进行积分运算，得到所述配用电模型的网损值；Integrate the sub-network loss value corresponding to each time section to obtain the network loss value of the power distribution model;
将每一所述时间断面对应的可靠性子系数中，对应的数值最小的可靠性子系数作为所述可靠性系数。Among the reliability sub-coefficients corresponding to each time section, the reliability sub-coefficient with the smallest corresponding value is used as the reliability coefficient.
优选地，在所述基于每一所述时间断面对应的子网损值和可靠性子系数，计算所述配用电模型的网损值和可靠性系数的步骤之后，还包括：Preferably, after the step of calculating the network loss value and reliability coefficient of the power distribution model based on the sub-network loss value and reliability sub-coefficient corresponding to each of the time sections, the method further includes:
将所述网损值与所述配用电模型的历史网损值进行比较，得到第一比较结果；Comparing the network loss value with the historical network loss value of the power distribution model to obtain a first comparison result;
将所述可靠性系数与所述配用电模型的历史可靠性系数进行比较，得到第二比较结果；comparing the reliability coefficient with the historical reliability coefficient of the power distribution model to obtain a second comparison result;
依据所述第一比较结果和所述第二比较结果，确定增加所述待增配用电设备的优劣性结果。According to the first comparison result and the second comparison result, a result of the pros and cons of adding the electric equipment to be added is determined.
一种计算配用电系统网损和可靠性的系统，包括：A system for calculating network loss and reliability of power distribution system, including:
模型构建模块，用于构建配用电模型；其中，所述配用电模型中包括已有配用电设备的电路结构模型和待增配用电设备的电路结构模型；A model building module for constructing a power distribution model; wherein, the power distribution model includes a circuit structure model of the existing power distribution equipment and a circuit structure model of the power distribution equipment to be added;
信息获取模块，用于获取已有配用电设备的历史运行数据，以及所述待增配用电设备的配用电数学模型；其中，所述配用电数学模型为所述待增配用电设备的出力数学模型或用电数学模型；The information acquisition module is used to acquire the historical operation data of the existing electrical equipment and the mathematical model of the electrical equipment to be added; wherein, the electrical distribution mathematical model is the electrical equipment to be added. Output mathematical model or electricity consumption mathematical model of electrical equipment;
数据确定模块，用于基于所述配用电数学模型，确定所述待增配用电设备的预测运行数据；其中，所述待增配用电设备的预测运行数据随时间或负载值变化；a data determination module, configured to determine the predicted operation data of the electric equipment to be added based on the mathematical model of electric distribution; wherein the predicted operation data of the electric equipment to be added changes with time or load value;
参数计算模块，用于所述配用电模型、根据所述已有配用电设备的历史运行数据和所述待增配用电设备的预测运行数据，计算所述配用电模型的运行参数；A parameter calculation module, used for the power distribution model to calculate the operating parameters of the power distribution model according to the historical operation data of the existing power distribution equipment and the predicted operation data of the to-be-added power equipment ;
其中，所述配用电模型的运行参数包括潮流计算结果、网损值和可靠性系数。Wherein, the operating parameters of the power distribution model include power flow calculation results, network loss values and reliability coefficients.
优选地，所述参数计算模块包括：Preferably, the parameter calculation module includes:
时间确定子模块，用于确定多个时间断面；The time determination submodule is used to determine multiple time sections;
数据确定子模块，用于确定每一所述时间断面对应的已有配用电设备的历史运行数据中的历史运行子数据以及所述待增配用电设备的预测运行数据中的预测运行子数据；A data determination sub-module is used to determine the historical operation sub-data in the historical operation data of the existing electric power distribution equipment corresponding to each time section and the predicted operation sub-data in the predicted operation data of the electric equipment to be added. data;
参数计算子模块，用于所述配用电模型、基于每一所述时间断面对应的历史运行子数据以及预测运行子数据，计算所述配用电模型的运行参数。The parameter calculation sub-module is used for the power distribution and consumption model to calculate the operation parameters of the power distribution and consumption model based on the historical operation sub-data and the predicted operation sub-data corresponding to each of the time sections.
优选地，所述参数计算子模块包括：Preferably, the parameter calculation submodule includes:
结构图构建单元，用于基于所述配用电模型、每一所述时间断面对应的历史运行子数据以及预测运行子数据，构建每一所述时间断面对应的电路结构图；a structure diagram construction unit, configured to construct a circuit structure diagram corresponding to each of the time sections based on the power distribution model, the historical operation sub-data and the predicted operation sub-data corresponding to each of the time sections;
第一计算单元，用于根据每一所述时间断面对应的电路结构图，进行潮流计算，得到潮流计算结果；a first calculation unit, configured to perform power flow calculation according to the circuit structure diagram corresponding to each time section, and obtain a power flow calculation result;
第二计算单元，用于依据潮流计算结果、每一所述时间断面对应的历史运行子数据以及预测运行子数据，计算得到每一所述时间断面对应的子网损值和可靠性子系数；The second calculation unit is configured to calculate the sub-network loss value and the reliability sub-coefficient corresponding to each of the time sections according to the power flow calculation result, the historical operation sub-data and the predicted operation sub-data corresponding to each of the time sections;
第三计算单元，用于基于每一所述时间断面对应的子网损值和可靠性子系数，计算所述配用电模型的网损值和可靠性系数。The third calculation unit is configured to calculate the network loss value and the reliability coefficient of the power distribution model based on the sub-network loss value and the reliability sub-coefficient corresponding to each of the time sections.
优选地，所述第三计算单元包括：Preferably, the third computing unit includes:
计算子单元，用于将每一所述时间断面对应的子网损值进行积分运算，得到所述配用电模型的网损值；a calculation subunit, configured to perform an integral operation on the sub-network loss value corresponding to each of the time sections to obtain the network loss value of the power distribution model;
系数确定子单元，用于将每一所述时间断面对应的可靠性子系数中，对应的数值最小的可靠性子系数作为所述可靠性系数。The coefficient determination sub-unit is configured to use the reliability sub-coefficient with the smallest value among the reliability sub-coefficients corresponding to each time section as the reliability coefficient.
优选地，还包括：Preferably, it also includes:
第一比较子单元，用于第三计算单元基于每一所述时间断面对应的子网损值和可靠性子系数，计算所述配用电模型的网损值和可靠性系数后，将所述网损值与所述配用电模型的历史网损值进行比较，得到第一比较结果；The first comparison sub-unit is used for the third calculation unit to calculate the network loss value and reliability coefficient of the power distribution model based on the sub-network loss value and reliability sub-coefficient corresponding to each of the time sections, and then calculate the Comparing the network loss value with the historical network loss value of the power distribution model to obtain a first comparison result;
第二比较子单元，用于将所述可靠性系数与所述配用电模型的历史可靠性系数进行比较，得到第二比较结果；a second comparison subunit, configured to compare the reliability coefficient with the historical reliability coefficient of the power distribution model to obtain a second comparison result;
结果确定子单元，用于依据所述第一比较结果和所述第二比较结果，确定增加所述待增配用电设备的优劣性结果。The result determination subunit is configured to determine the pros and cons of adding the electric equipment to be added according to the first comparison result and the second comparison result.
相较于现有技术，本发明具有以下有益效果：Compared with the prior art, the present invention has the following beneficial effects:
本发明提供了一种计算配用电系统网损和可靠性的方法及系统，本发明中基于所述配用电数学模型，确定所述待增配用电设备的预测运行数据，其中，所述待增配用电设备的预测运行数据随时间或负载值变化，即预测运行数据是根据新增用电设备的使用情况得到的数据，符合新增用电设备的运行状态，这样计算得到的网损和可靠性等数据就符合智能配用电系统的实际情况，进而计算得到的网损和可靠性等数据的准确度较高。The present invention provides a method and system for calculating the network loss and reliability of a power distribution system. In the present invention, the predicted operation data of the to-be-distributed power equipment is determined based on the power distribution mathematical model. The predicted operation data of the electric equipment to be added changes with time or load value, that is, the predicted operation data is the data obtained according to the usage of the newly added electric equipment, which is in line with the operation state of the newly added electric equipment. Data such as network loss and reliability are in line with the actual situation of the intelligent power distribution system, and the calculated data such as network loss and reliability are more accurate.
附图说明Description of drawings
为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据提供的附图获得其他的附图。In order to explain the embodiments of the present invention or the technical solutions in the prior art more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only It is an embodiment of the present invention. For those of ordinary skill in the art, other drawings can also be obtained according to the provided drawings without creative work.
图1为本发明实施例提供的计算配用电系统网损和可靠性的方法流程图；FIG. 1 is a flowchart of a method for calculating network loss and reliability of a power distribution system provided by an embodiment of the present invention;
图2为本发明实施例提供的一种风速曲线的示意图；2 is a schematic diagram of a wind speed curve provided by an embodiment of the present invention;
图3为本发明实施例提供的一种风机功率特性曲线的示意图；3 is a schematic diagram of a fan power characteristic curve according to an embodiment of the present invention;
图4为本发明实施例提供的一种非线性通用电池模型的电路结构示意图；4 is a schematic diagram of a circuit structure of a nonlinear universal battery model provided by an embodiment of the present invention;
图5为本发明实施例提供的方法中步骤S4具体流程的流程图；5 is a flowchart of a specific process of step S4 in the method provided by the embodiment of the present invention;
图6为本发明实施例提供的方法中步骤S43具体流程的流程图；6 is a flowchart of a specific process of step S43 in the method provided by the embodiment of the present invention;
图7为本发明实施例提供的分布式电源以及负荷时间变化趋势和上下调节容量边界的示意图；7 is a schematic diagram of a distributed power source and a load time change trend and an upper and lower adjustment capacity boundary provided by an embodiment of the present invention;
图8为本发明实施例提供的计算配用电系统网损和可靠性的系统的结构示意图。FIG. 8 is a schematic structural diagram of a system for calculating network loss and reliability of a power distribution and consumption system according to an embodiment of the present invention.
具体实施方式Detailed ways
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.
如图1所示，本发明实施例提供了一种计算配用电系统网损和可靠性的方法，可以包括：As shown in FIG. 1, an embodiment of the present invention provides a method for calculating network loss and reliability of a power distribution system, which may include:
S1、构建配用电模型；S1. Build a power distribution model;
其中，配用电模型中包括已有配用电设备的电路结构模型和待增配用电设备的电路结构模型。The power distribution model includes the circuit structure model of the existing power distribution equipment and the circuit structure model of the power distribution equipment to be added.
具体的，已有配用电设备可以包括以下三类：Specifically, the existing electrical distribution equipment can include the following three categories:
(1)以网络线路连接为基础的配电网网架模型；(1) Distribution network grid model based on network line connection;
(2)以时间序列断面分析为基础的时序模型,如风机、光伏等；(2) Time series models based on time series section analysis, such as wind turbines, photovoltaics, etc.;
以时间序列断面分析为基础的时序模型，是指配用电设备的有功或无功功率曲线随时间变化。如配用电设备为分布式电源中的光伏，光伏的有功出力与光照强度有关，即与时间有关，光伏的无功与输出电压有关，即也与时间有关。The time series model based on time series cross-sectional analysis refers to the change of the active or reactive power curve of the electrical equipment over time. For example, the power distribution equipment is photovoltaic in the distributed power source, the active power output of photovoltaic is related to the light intensity, that is, related to time, and the reactive power of photovoltaic is related to the output voltage, that is, related to time.
(3)以事件发生为单位影响系统运行状态的事件类模型,如电动汽车充放电桩、储能装置、友好型负荷等。其中，友好型负荷包括可中断负荷和可调度负荷。(3) The event-based model that affects the operating state of the system in units of events, such as electric vehicle charging and discharging piles, energy storage devices, friendly loads, etc. Among them, friendly load includes interruptible load and schedulable load.
以事件发生为单位影响系统运行状态的事件类模型是指配用电设备的功率曲线与负荷特性有关。如配用电设备为储能装置(如飞轮储能、超级电容等)，储能装置的运行方式有充电、放电和闲置三种状态，储能装置与是否有负载等有关。The event-type model that affects the system operating state with the occurrence of events as the unit refers to the power curve of the assigned electrical equipment is related to the load characteristics. For example, the power distribution equipment is an energy storage device (such as flywheel energy storage, super capacitor, etc.), the operation mode of the energy storage device has three states of charging, discharging and idle, and the energy storage device is related to whether there is a load or not.
待增配用电设备包括时序类模型，如光伏、风机等，也可以是事件类模型，如电动汽车充放电站、储能装置等。The electrical equipment to be added includes time series models, such as photovoltaics, wind turbines, etc., and event models, such as electric vehicle charging and discharging stations, energy storage devices, etc.
需要说明的是，已有配用电设备和待增配用电设备的数量不做限制，可以为一个或多个。It should be noted that there is no limit to the number of existing electrical equipment for distribution and electrical equipment to be added, which can be one or more.
S2、获取已有配用电设备的历史运行数据，以及所述待增配用电设备的配用电数学模型；S2. Acquire historical operation data of the existing electrical equipment and the mathematical model of the electrical equipment to be added;
其中，所述待增配用电设备的配用电数学模型包括出力数学模型和用电数学模型；具体为根据用电设备区分使用，当待增配用电设备为光伏或风机等时序类模型时，配用电数学模型为出力数学模型，当待增配用电设备为储能装置或电动汽车充放电站等事件类模型时，配用电数学模型为用电数学模型。Wherein, the mathematical model of power distribution and consumption of the electric equipment to be added includes an output mathematical model and a power consumption mathematical model; specifically, it is used according to the distinction of the electric equipment, and when the electric equipment to be added is a time series model such as a photovoltaic or a fan When the power distribution mathematical model is the output mathematical model, when the electric equipment to be added is an event model such as an energy storage device or an electric vehicle charging and discharging station, the power distribution mathematical model is the power consumption mathematical model.
需要说明的是，构建所述待增配用电设备的配用电数学模型包括：It should be noted that the construction of the electrical distribution mathematical model of the to-be-distributed electrical equipment includes:
当待增配用电设备不同时，构建的配用电数学模型不同，具体如何下：When the electrical equipment to be added is different, the mathematical models of electrical distribution and consumption are different. The details are as follows:
一、分布式电源1. Distributed power supply
1.光伏1. Photovoltaic
通过建立太阳辐射强度的时序模型，利用光电转换关系得到光伏出力模型；By establishing the time series model of solar radiation intensity, the photovoltaic output model is obtained by using the photoelectric conversion relationship;
(1)太阳辐射强度模型(1) Solar radiation intensity model
对于地面上处于纬度为经度为λ的观测者而言，在某一时刻观测到的太阳的天顶角θ(太阳高度角的余角)和方位角α可以用下列方程来计算：For the ground at latitude of For an observer with longitude λ, the zenith angle θ (the complement angle of the sun's altitude) and azimuth α observed at a certain moment can be calculated by the following equations:
其中，δ为太阳赤纬(日地中心连线与赤道平面的夹角)，变化于±23°27'之间。ω为时角，为观测点的经圈与太阳重合后(即当地正午)地球自转的角度，每天从0°至360°，正午时刻时角为0°。Among them, δ is the declination of the sun (the angle between the line connecting the center of the sun and the earth and the equatorial plane), which varies between ±23°27'. ω is the hour angle, which is the angle of the earth's rotation after the meridian circle of the observation point coincides with the sun (that is, the local noon), from 0° to 360° every day, and the hour angle at noon is 0°.
在日出和日落时刻，θ为90°。从上面的公式可以看出：At sunrise and sunset, θ is 90°. As can be seen from the above formula:
其中，ω0和α0分别为日出和日落时刻的太阳时角和方位角，随地点和季节(δ)而不同。例如，对于北半球的春(秋)分日，δ＝0，ω0＝±90°，α0＝90°和270°，即日夜等长，太阳从正东方升起，从正西方落下；对于夏至日，δ＝23.5°，在处，ω0＝±180°，说明北极圈内全天太阳不落。Among them, ω0 and α0 are the solar hour angle and azimuth angle at sunrise and sunset, respectively. and season (δ). For example, for the spring (autumn) equinox in the northern hemisphere, δ = 0, ω0 = ±90°, α0 = 90° and 270°, that is, the day and night are of equal length, and the sun rises from the due east and sets due to the west; for The summer solstice, δ=23.5°, at , ω0 =±180°, indicating that the sun does not set in the Arctic Circle all day long.
把365天对应于区间[0,2π]，取D为一年中的日数(1月1日，D等于1；12月31日，D＝365)，则The 365 days correspond to the interval [0, 2π], and D is the number of days in a year (January 1, D is equal to 1; December 31, D=365), then
其中，X是日期调整系数，用来标记一年中某一天的地球公转太阳位置的影响。Among them, X is the date adjustment factor, which is used to mark the influence of the position of the earth's revolution and the sun on a certain day of the year.
太阳赤纬δ为：The sun's declination δ is:
δ＝0.006894-0.399512cos X+0.072075sin X-0.006799cos(2X)δ=0.006894-0.399512cos X+0.072075sin X-0.006799cos(2X)
+0.000896sin(2X)-0.002689cos(3X)+0.001516sin(3X) (6)+0.000896sin(2X)-0.002689cos(3X)+0.001516sin(3X) (6)
日地距离dm为：The sun-earth distance dm is:
dm＝1.000109+0.033494cos X+0.001472sin Xdm =1.000109+0.033494cos X+0.001472sin X
+0.000768cos(2X)+0.000079sin(2X) (7)+0.000768cos(2X)+0.000079sin(2X) (7)
由于不同时刻太阳处于不同的高度，入射的大气上界水平面的太阳辐照度应该为：Since the sun is at different heights at different times, the incident solar irradiance on the horizontal plane of the upper boundary of the atmosphere should be:
其中，S0为大气上界与日光垂直平面上的太阳积分辐照度，d为日地距离，随地球公转变化，d0为日地平均距离(1.496×108km，是地球在3月21-22日和9月22-23日达到的日地平均距离，近日点时：1.47×108km，远日点时：1.52×108km)，称为太阳常数，世界气象组织的最佳值定为1367±7W/m2。Among them, S0 is the solar integral irradiance on the vertical plane between the upper boundary of the atmosphere and the sun, d is the distance between the sun and the earth, which varies with the earth’s revolution, and d0 is the average distance between the sun and the earth (1.496×108 km, which is the distance between the earth and the earth in March The average distance between the sun and the earth reached on 21-22 and September 22-23, at perihelion: 1.47×108 km, at aphelion: 1.52×108 km), called the solar constant, the World Meteorological Organization The optimum value of 1367±7W/m2 is set.
大气透明度P为：Atmospheric transparency P is:
式中：P2为年平均大气透明度。In the formula: P2 is the annual average atmospheric transparency.
经过大气层后的太阳辐射强度Pn为：The solar radiation intensity Pn after passing through the atmosphere is:
Pn＝S0Pm (11)Pn=S0 Pm (11)
其中，m为大气质量数。where m is the air mass number.
(2)光伏系统的输出(2) Output of photovoltaic system
PPV＝Pn*η*S*ηinv (12)PPV =Pn*η*S*ηinv (12)
其中，η为光伏阵列的效率，S为光伏阵列的光照面积，ηinv为逆变器的效率。公式12即可为光伏的配用电数学模型。Among them, η is the efficiency of the photovoltaic array, S is the light area of the photovoltaic array, and ηinv is the efficiency of the inverter. Equation 12 can be the mathematical model of photovoltaic power distribution.
光伏的配用电数学模型，根据研究目的和需求，可以得出各个时间尺度的光伏出力曲线。The mathematical model of photovoltaic power distribution and consumption, according to the research purpose and demand, can obtain photovoltaic output curves of various time scales.
2.风机2. Fan
风力发电设备的出力时序特性与规划地区风力资源有直接关系，不同季节的风速日变化也有明显不同。风机出力与风速曲线密不可分，系统的有功功率输出取决于风速大小。首先利用风速模型生成风速时间序列，再通过相应的风速－风电功率函数关系得到风电时间序列。基于实时的风速变化曲线，建立的风机时序模型更加精准化和实用化。The output timing characteristics of wind power generation equipment are directly related to the wind resources in the planning area, and the daily variation of wind speed in different seasons is also significantly different. The output of the fan is inseparable from the wind speed curve, and the active power output of the system depends on the wind speed. First, the wind speed model is used to generate the wind speed time series, and then the wind power time series is obtained through the corresponding wind speed-wind power function relationship. Based on the real-time wind speed change curve, the established fan timing model is more accurate and practical.
(1)风速曲线(1) Wind speed curve
风向和风速的时空分布非常复杂，呈现出极强的随机性，风速Vwind的变化曲线如图2所示，其变化没有任何规律，且频率非常快，很难对风速进行准确的预测。国内外学者对风速的概率分布进行了大量研究，并建立了各种概率分布模型来描述风速的变化。其中Weibull分布形式简单，与实际风速统计分布拟合较好，得到广泛应用。本发明采用该分布建立风速的概率模型，具体如下：The temporal and spatial distribution of wind direction and wind speed is very complex, showing strong randomness. The change curve of wind speed Vwind is shown in Figure 2. The change has no regularity and the frequency is very fast, so it is difficult to accurately predict the wind speed. Scholars at home and abroad have done a lot of research on the probability distribution of wind speed, and established various probability distribution models to describe the change of wind speed. Among them, the Weibull distribution has a simple form and fits well with the actual wind speed statistical distribution, so it is widely used. The present invention adopts this distribution to establish a probability model of wind speed, which is specifically as follows:
分布函数为：The distribution function is:
概率密度函数为：The probability density function is:
式中，c和k分别为Weibull分布的尺度参数和形状参数；尺度参数c反映该风电场的平均风速，V是给定风速，单位m/s。In the formula, c and k are the scale parameter and shape parameter of Weibull distribution, respectively; the scale parameter c reflects the average wind speed of the wind farm, and V is the given wind speed, in m/s.
(2)风机出力模型(2) Fan output model
风电机组的运行特性导致风机的出力随风速变化而变化，但风机的输出功率与风速并不是简单的线性关系。当实际风速小于风电机组的切入风速或大于切出风速时，风机的出力由于风能不足和风速过大导致其输出功率为零；当实际风速位于切入、切出风速之间时，风机的出力在风电机组额定功率的限制下随着风速不断变化。The operating characteristics of the wind turbine cause the output of the fan to change with the wind speed, but the output power of the fan is not a simple linear relationship with the wind speed. When the actual wind speed is less than the cut-in wind speed of the wind turbine or greater than the cut-out wind speed, the output of the fan is zero due to insufficient wind energy and excessive wind speed; when the actual wind speed is between the cut-in and cut-out wind speeds, the output of the fan is between Under the limit of the rated power of the wind turbine, it changes continuously with the wind speed.
理论中一般采用分段的二次函数来反映风机的出力随风速变化的规律，如图3所示。In theory, a segmented quadratic function is generally used to reflect the law that the output of the fan varies with the wind speed, as shown in Figure 3.
式中：Vci、Vr、Vco分别为风电机组的切入风速、额定风速和切出风速；Pr为风电机组的额定功率，常数A、B、C为风机的输出功率特性曲线参数，由下式计算：In the formula: Vci, Vr and Vco are the cut-in wind speed, rated wind speed and cut-out wind speed of the wind turbine respectively; Pr is the rated power of the wind turbine, and the constants A, B and C are the output power characteristic curve parameters of the wind turbine, which are calculated by the following formula :
基于随时间变化的风速曲线，可以得出实时的风机出力模型。即风机的配用电数学模型。采用风机出力的时序模型，可以仿真得到风机出力随时间变化的曲线，真实反映风机的随机性和间歇性。Based on the time-varying wind speed curve, a real-time fan output model can be derived. That is, the mathematical model of the power distribution of the fan. Using the time series model of the fan output, the curve of the fan output with time can be simulated, which truly reflects the randomness and intermittency of the fan.
二、储能装置2. Energy storage device
建立储能系统的充放电模型如下：The charging and discharging model of the energy storage system is established as follows:
充电模型：Charging model:
放电模型：Discharge model:
式中：Pbat(t)表示储能系统第t小时的充电或放电功率，Ebat(t)表示储能系统第t小时的储存的能量；Pch-max和Pdch-max分别表示储能系统的最大充电功率和最大放电功率；Emax和Emin分别表示储能系统的最小容量和最大容量限制。In the formula: Pbat (t) represents the charging or discharging power of the energy storage system in the t hour, Ebat (t) represents the energy stored in the energy storage system in the t hour; Pch-max and Pdch-max represent the storage energy, respectively. The maximum charging power and maximum discharging power of the energy storage system; Emax and Emin represent the minimum capacity and maximum capacity limit of the energy storage system, respectively.
储能装置的充放电模型即为储能装置的配用电数学模型。The charging and discharging model of the energy storage device is the mathematical model of the power distribution and consumption of the energy storage device.
基于多时空尺度的建模方法，与分布式能源相结合，可以实现对储能装置充电和放电功率的实时控制，以满足配电网的运行要求。Modeling methods based on multi-temporal and spatial scales, combined with distributed energy sources, can realize real-time control of the charging and discharging power of energy storage devices to meet the operational requirements of the distribution network.
三、电动汽车3. Electric vehicles
1.电池模型1. Battery model
电池模型可以描述电池工作时的外特性，采用的电池模型是一个与恒定电阻相串联的可控电压源，如图4所示，该模型将SoC作为状态参数，SoC与电池状态相关，用来指示电池的荷电状态，又称剩余电量，计算方法为：The battery model can describe the external characteristics of the battery when it is working. The battery model used is a controllable voltage source connected in series with a constant resistance, as shown in Figure 4. The model uses SoC as a state parameter, and the SoC is related to the battery state. Indicates the state of charge of the battery, also known as the remaining capacity, calculated as:
其中，Qr、Qc分别为电池剩余电量和总电量。Among them, Qr and Qc are the remaining power and total power of the battery, respectively.
图4中，E为电池空载电压；E0为电池额定电压；K为极化电压；Q为电池容量；R为电池内阻；i为电池放电电流；Vbatt为电池端电压；A为指数幅值；B为时间常数，U为可控电压源，R为内阻。电池端电压Vbatt及充电功率P可以通过一个与荷电状态SoC相关的非线性方程得到：In Figure 4, E is the no-load voltage of the battery; E0 is the rated voltage of the battery; K is the polarization voltage;Q is the battery capacity; R is the battery internal resistance; i is the battery discharge current; Exponential amplitude; B is the time constant, U is the controllable voltage source, and R is the internal resistance. The battery terminal voltage Vbatt and the charging power P can be obtained by a nonlinear equation related to the state of charge SoC:
式中，i为电池放电电流；t是时间；通过该模型可以对不同类型电动汽车充电功率及其SOC变化进行仿真。In the formula, i is the battery discharge current; t is the time; through this model, the charging power and SOC changes of different types of electric vehicles can be simulated.
2.电动汽车充电负荷2. Electric vehicle charging load
初始SoC：电动汽车充电前，电池的剩余电量与已行驶的距离有关，设电动汽车每天行驶的距离为d，可以行驶的最大距离为dr，则充电前的SoC可利用式(22)得到：Initial SoC: Before the electric vehicle is charged, the remaining power of the battery is related to the distance traveled. Let the distance traveled by the electric vehicle every day be d, and the maximum distance that can be traveled is dr, then the SoC before charging can be obtained by formula (22):
其中，d可通过交通部门的统计数据获得；dr可利用电池容量Qb与电动汽车每公里能耗Ce的比值计算得到。Among them, d can be obtained from the statistical data of the transportation department; dr can be calculated from the ratio of the battery capacity Qb to the energy consumption Ce per kilometer of the electric vehicle.
不同类型电动汽车的电池容量Qb不同，每公里的能耗Ce也不相同。经研究表明，每种类型电动汽车的电池容量Qb在一定范围内服从正态分布，每公里的能耗Ce在一定范围内分散分布，其概率密度函数如式(23)，(24)所示：The battery capacity Qb of different types of electric vehicles is different, and the energy consumption Ce per kilometer is also different. Studies have shown that the battery capacity Qb of each type of electric vehicle obeys a normal distribution within a certain range, and the energy consumption Ce per kilometer is distributed within a certain range. Show:
其中，μ为平均值，σ为标准差，x1和x2为Qb的上下限，x为电池容量；a和b为Ce的范围。Among them, μ is the average value, σ is the standard deviation, x1 and x2 are the upper and lower limits of Qb , x is the battery capacity; a and b are the ranges of Ce.
充电时刻：电动汽车开始充电时刻主要取决于车主的出行习惯和行驶特性，同时还会受到各种不确定性因素的影响，因此，开始充电时刻具有随机性。电动汽车开始充电时刻直接受最后一次出行返回时刻的影响，根据2001年美国交通部对全美车辆的调查统计结果显示，开始充电时刻满足如下的分布，其概率密度函数，即配用电数学模型如式(25)所示：Charging time: The charging time of an electric vehicle mainly depends on the travel habits and driving characteristics of the owner, and is also affected by various uncertain factors. Therefore, the charging time is random. The charging time of an electric vehicle is directly affected by the return time of the last trip. According to the 2001 U.S. Department of Transportation survey on vehicles in the United States, the charging time satisfies the following distribution. Its probability density function, that is, the mathematical model of electricity distribution and consumption Formula (25) shows:
其中，μs＝17.6h，σs＝3.4h。Among them, μs =17.6h, σs =3.4h.
3.V2G控制下的充放电模型3. Charge-discharge model under V2G control
假设可调度电动汽车的开始充放电时刻在其一天的充放电时间段内满足均匀分布，开始充电时刻的概率密度函数fc(x)与开始放电时刻的概率密度函数fD(x)分别为：Assuming that the start charging and discharging time of the dispatchable electric vehicle satisfies a uniform distribution in its one-day charging and discharging time period, the probability density function fc (x) at the start charging time and the probability density function fD (x) at the start discharging time are respectively :
可调度电动汽车日行驶里程的概率密度函数满足正态分布：The probability density function of the daily mileage of dispatchable electric vehicles satisfies the normal distribution:
其中μM＝16.58，σM＝6.57。where μM =16.58 and σM =6.57.
电动汽车的充放电功率特性通过蒙特卡罗随机抽样方法来实现数值仿真。The charging and discharging power characteristics of electric vehicles are numerically simulated by Monte Carlo random sampling method.
基于以上对电动汽车的时序建模，可以得到其24h放电和充电功率的曲线，将电动汽车并入配电网中，进行时序的电压分析和网损计算，为研究电动汽车并网对可靠性的影响及其接纳能力提供了模型基础。Based on the above sequence modeling of electric vehicles, the 24h discharge and charging power curves can be obtained. The electric vehicles are integrated into the distribution network, and the voltage analysis and network loss calculation of the time series are carried out. In order to study the reliability of electric vehicles connected to the grid The impact of and its receptive capacity provide the basis for the model.
S3、基于所述配用电数学模型，确定所述待增配用电设备的预测运行数据；所述待增配用电设备的预测运行数据随时间或负载值变化。S3. Determine the predicted operation data of the electric equipment to be added based on the mathematical model of distribution and consumption; the predicted operation data of the electric equipment to be added changes with time or load value.
具体的，配用电数学模型给出了出力值随时间、出力值随负载值、用电量随时间的变化情况。基于配用电数学模型可以预测一段时间的预测运行数据。Specifically, the mathematical model of power distribution and consumption gives the changes of output value with time, output value with load value, and electricity consumption with time. Based on the mathematical model of electricity distribution, the forecast operation data for a period of time can be predicted.
如当待增配用电设备为光伏时，配用电数学模型为出力模型，待增配用电设备的预测运行数据随时间变化，预测运行数据可以为不同时间产生的光伏能量。For example, when the electrical equipment to be added is photovoltaic, the mathematical model of electrical distribution is the output model, and the predicted operation data of the electrical equipment to be added changes with time, and the predicted operation data can be the photovoltaic energy generated at different times.
S4、根据配用电数学模型、已有配用电设备的历史运行数据和待增配用电设备的预测运行数据，计算所述配用电模型的运行参数。如图5所示，具体包括以下步骤：S4. Calculate the operating parameters of the power distribution and consumption model according to the mathematical model of power distribution and consumption, the historical operation data of the existing power distribution and consumption equipment, and the predicted operation data of the power distribution and consumption equipment to be added. As shown in Figure 5, it specifically includes the following steps:
步骤S4可以包括：Step S4 may include:
S41、确定多个时间断面；S41. Determine multiple time sections;
其中，以某一段时间T作为研究对象，通过对时间序列进行分割，在其中按照相同的时间间隔抽取m个连续时间断面Ti(i＝0，1，…，m-1)，对m个时间断面分别进行研究。确定的时间断面可以是年、月、日、小时、分钟等。优选地，可以以小时作为时间断面，一年可以分为8760个时间断面。Among them, taking a certain period of time T as the research object, by dividing the time series, m continuous time sections Ti (i=0, 1, . . . , m-1) are extracted according to the same time interval. Sections are studied separately. The determined time section can be year, month, day, hour, minute, etc. Preferably, hours can be used as time sections, and a year can be divided into 8760 time sections.
需要说明的是，确定的时间断面是以配用电模型为基础来确定的时间断面。即配用电模型中必须包括待增配用电设备的电路结构模型。It should be noted that the determined time section is a time section determined based on the distribution and consumption model. That is, the power consumption model must include the circuit structure model of the power consumption equipment to be added.
S42、确定每一时间断面对应的已有配用电设备的历史运行数据中的历史运行子数据以及所述待增配用电设备的预测运行数据中的预测运行子数据；S42, determining the historical operation sub-data in the historical operation data of the existing electric power distribution equipment corresponding to each time section and the predicted operation sub-data in the predicted operation data of the electric equipment to be added;
具体的，时间断面确定后，就需要确定分析每一时间断面所使用的数据。将已有配用电设备的历史运行数据中与时间断面对应的历史时间断面的数据作为历史运行子数据。Specifically, after the time section is determined, it is necessary to determine the data used for analyzing each time section. The data of the historical time section corresponding to the time section in the historical operation data of the existing power distribution equipment is taken as the historical operation sub-data.
举例来说，假设时间断面为2018年6月20日这一天中的12点，若获取的历史运行数据为2017年1月1日-2018年1月1日之间的数据，则将2018年6月20日这一天中的12点的数据作为时间断面为2018年6月20日这一天中的12点的历史运行子数据。For example, assuming that the time section is 12:00 on June 20, 2018, if the obtained historical operation data is the data between January 1, 2017 and January 1, 2018, the 2018 The data at 12:00 on the day of June 20 is used as the historical operation sub-data of the time section at 12:00 on the day of June 20, 2018.
所述待增配用电设备的预测运行数据为预测的未来的数据，如预测的2018年1月1日-2019年1月1日之间的运行数据，假设时间断面为2018年6月20日这一天中的12点，则将待增配用电设备的预测运行数据中的2018年6月20日这一天中的12点的数据作为预测运行子数据。The predicted operation data of the electric equipment to be added is the predicted future data, such as the predicted operation data between January 1, 2018 and January 1, 2019, assuming that the time section is June 20, 2018 At 12 o'clock in the day, the data at 12 o'clock in the day of June 20, 2018 in the predicted operation data of the electric equipment to be added will be used as the predicted operation sub-data.
需要说明的是，此处是以历史运行数据中的某一数据作为时间断面对应的已有配用电设备的数据，还可以使用已有配用电设备的配用电模型来预测时间断面的数据作为时间断面对应的已有配用电设备的数据。It should be noted that here, a certain data in the historical operation data is used as the data of the existing power distribution equipment corresponding to the time section, and the power distribution model of the existing power distribution equipment can also be used to predict the time section. The data is taken as the data of the existing power distribution equipment corresponding to the time section.
S43、基于配用电数学模型、每一时间断面对应的历史运行子数据以及预测运行子数据，计算所述配用电模型的运行参数。其中，所述配用电模型的运行参数包括潮流计算结果、网损值和可靠性系数。S43. Calculate the operation parameters of the electricity distribution and consumption model based on the mathematical model of electricity distribution and consumption, the historical operation sub-data corresponding to each time section, and the predicted operation sub-data. Wherein, the operating parameters of the power distribution model include power flow calculation results, network loss values and reliability coefficients.
如图6所示，步骤S43具体包括以下步骤：As shown in Figure 6, step S43 specifically includes the following steps:
S431、基于配用电数学模型、每一时间断面对应的历史运行子数据以及预测运行子数据，构建每一时间断面对应的电路结构图；S431 , constructing a circuit structure diagram corresponding to each time section based on the mathematical model of power distribution and consumption, the historical operation sub-data corresponding to each time section, and the predicted operation sub-data;
具体的，每一时间断面对应的历史运行子数据以及预测运行子数据已知后，可以根据历史运行子数据来确定已有配用电设备的电路结构，以及根据预测运行子数据来确定待增配用电设备的电路结构，其中，电路结构可以是由电阻、电感和电抗等电子元件组成。Specifically, after the historical operation sub-data and the predicted operation sub-data corresponding to each time section are known, the circuit structure of the existing electric power distribution equipment can be determined according to the historical operation sub-data, and the to-be-added operation sub-data can be determined according to the predicted operation sub-data. The circuit structure of electrical equipment, wherein the circuit structure can be composed of electronic components such as resistance, inductance and reactance.
已有配用电设备的电路结构和待增配用电设备的电路结构确定后，就可以根据已有配用电设备和待增配用电设备的连接结构，确定时间断面对应的电路结构图。After the circuit structure of the existing electrical equipment and the circuit structure of the electrical equipment to be added are determined, the circuit structure diagram corresponding to the time section can be determined according to the connection structure of the existing electrical equipment and the electrical equipment to be added. .
S432、根据每一时间断面对应的电路结构图，进行潮流计算，得到潮流计算结果；S432, perform power flow calculation according to the circuit structure diagram corresponding to each time section, and obtain a power flow calculation result;
潮流计算，指在给定电力系统网络拓扑、元件参数和发电、负荷参量条件下，计算有功功率、无功功率及电压在电力网中的分布；Power flow calculation refers to calculating the distribution of active power, reactive power and voltage in the power grid under the given power system network topology, component parameters and power generation and load parameters;
具体的，潮流计算的具体过程可以包括：Specifically, the specific process of power flow calculation may include:
在智能配用电系统中，分布式电源的引入会使得PV、PI类型节点增多，对于前推回代法，处理PV节点类型负荷困难，需对PV节点进行处理，求解智能配用电系统潮流的算法，达到潮流收敛的目的。In the intelligent power distribution system, the introduction of distributed power sources will increase the number of PV and PI types of nodes. For the forward push-back method, it is difficult to deal with the type load of PV nodes. It is necessary to process the PV nodes to solve the power flow of the intelligent power distribution system. algorithm to achieve the purpose of power flow convergence.
首先将PV节点类型的DG(分布式发电装置)可看作电压控制的电流源。为了保持PV节点类型DG的电压幅值恒定，需要确定合适的无功功率和无功电流注入，因此问题转化为对每个PV类型的DG节点寻找无功注入电流，使每个节点的电压幅值与额定值相等，DG为同步发电机对称运行时只存在正序电流和正序电压。本实施例通过计算PV节点电压正序分量幅值和额定幅值之差，求出注入PV节点的正序电流幅值，对PV节点进行无功补偿，这样将DG由PV节点运行模型转换为PQ节点运行模型。具体步骤如下：First, a DG (distributed power generation device) of the PV node type can be regarded as a voltage-controlled current source. In order to keep the voltage amplitude of the PV node type DG constant, it is necessary to determine the appropriate reactive power and reactive current injection, so the problem turns into finding the reactive injection current for each PV type DG node, so that the voltage amplitude of each node is The value is equal to the rated value, DG is only positive sequence current and positive sequence voltage when the synchronous generator runs symmetrically. In this embodiment, by calculating the difference between the amplitude of the positive sequence component of the voltage of the PV node and the rated amplitude, the amplitude of the positive sequence current injected into the PV node is obtained, and the reactive power compensation is performed on the PV node. In this way, the DG is converted from the PV node operating model to The PQ node runs the model. Specific steps are as follows:
设定DG初始三相总有功功率P和端电压正序分量幅值Usc为一定值，初始无功功率Q为零，按上述潮流算法，收敛后计算PV节点端电压正序分量幅值和额定电压幅值，判断其差值是否在允许误差范围内。如果幅值差在允许误差范围内，则PV节点的电压收敛于初始设定值；如果幅值差超过允许的误差范围，则PV节点通过注入无功电流进行补偿，使电压维持在允许范围内，无功注入正序电流按下式计算：Set DG initial three-phase total active power P and terminal voltage positive sequence component amplitude Usc to a certain value, initial reactive power Q is zero, according to the above power flow algorithm, after convergence, calculate the PV node terminal voltage positive sequence component amplitude and rated value Voltage amplitude, determine whether the difference is within the allowable error range. If the amplitude difference is within the allowable error range, the voltage of the PV node converges to the initial set value; if the amplitude difference exceeds the allowable error range, the PV node compensates by injecting reactive current to keep the voltage within the allowable range , the reactive power injection positive sequence current is calculated as follows:
ZvΔIq＝ΔUv (29)Zv ΔIq =ΔUv (29)
式中：ΔIq为无功注入正序电流向量；Zv为正序灵敏度阻抗矩阵，其维数等于PV节点数，对角线元素为各PV节点到根节点间支路的所有正序阻抗和，非对角线元素为PV节点i和PV节点j到根节点间相同支路的所有正序阻抗和；ΔUv为PV节点正序电压与额定电压幅值差向量。In the formula: ΔIq is the reactive power injection positive sequence current vector; Zv is the positive sequence sensitivity impedance matrix, the dimension of which is equal to the number of PV nodes, and the diagonal elements are all positive sequence impedances of the branches between each PV node and the root node. and, the off-diagonal element is the sum of all positive sequence impedances of the same branch between PV node i and PV node j to the root node; ΔUv is the amplitude difference vector between the positive sequence voltage of the PV node and the rated voltage.
将各相无功注入电流加到第i个节点的初始注入电流中，再重新进行潮流计算，检查新的电压幅值差。如果迭代计算中PV节点DG的无功注入功率超出规定限额，为保证电源设备的安全运行，应限制无功注入功率为额定最小值或最大值。Add the reactive power injection current of each phase to the initial injection current of the i-th node, and then re-calculate the power flow to check the new voltage amplitude difference. If the reactive power injection of the PV node DG in the iterative calculation exceeds the specified limit, in order to ensure the safe operation of the power supply equipment, the reactive power injection power should be limited to the rated minimum or maximum value.
综上所述，用了基于电流补偿的前推回代法作为求解智能配用电系统的潮流算法，处理了前推回代法处理PV节点困难的弱点，达到潮流收敛的目的。To sum up, the forward-backward substitution method based on current compensation is used as the power flow algorithm to solve the intelligent power distribution system, which solves the weakness of the forward-backward substitution method which is difficult to deal with PV nodes, and achieves the purpose of power flow convergence.
对于其他PQ节点的新型业务，潮流分析思路如下：For new services of other PQ nodes, the power flow analysis ideas are as follows:
分布式电源、储能装置、电动汽车充放电站以及可控负荷等智能电网新型业务的最大特点是在一定程度上可以接受系统运行调度的命令，参与系统需求侧响应的过程，在尽可能保障用户用电舒适度的前提下，实现负荷有功和无功的优化调节。负荷有功和无功之间的数学关系可通过功率因数来确定，与不同用电设备的自身物理属性及其电力电子接口控制器相关。由于潮流计算反应的是一个时间断面的系统特性，因此可以将储能设备和分布式电源的出力综合视为一个出力源，即一个特殊的PQ节点。然而与传统负荷不同的是，该PQ节点具有一定的上调容量和下调容量的能力，且与时间、空间都存在较强的耦合关系，适合于时序潮流计算的应用，如图7所示。The biggest feature of new smart grid businesses such as distributed power sources, energy storage devices, electric vehicle charging and discharging stations, and controllable loads is that they can accept the command of system operation and scheduling to a certain extent, participate in the process of system demand side response, and ensure as much as possible. On the premise of the user's comfort of electricity consumption, the optimal adjustment of load active and reactive power is realized. The mathematical relationship between the active and reactive power of the load can be determined by the power factor, which is related to the physical properties of different electrical equipment and its power electronic interface controller. Since the power flow calculation reflects the system characteristics of a time section, the output of the energy storage device and the distributed power source can be integrated as an output source, that is, a special PQ node. However, unlike the traditional load, the PQ node has a certain capacity to increase and decrease the capacity, and has a strong coupling relationship with time and space, which is suitable for the application of time series power flow calculation, as shown in Figure 7.
通过此类可调PQ模型，具有如下优点：With such a tunable PQ model, there are the following advantages:
可以实现潮流计算的收敛：即当潮流较大无法达到收敛时，通过在上下调节容量范围内优化P、Q的数值，达到潮流收敛的目的；The convergence of power flow calculation can be realized: that is, when the power flow is too large to achieve convergence, the value of P and Q can be optimized within the range of the upper and lower adjustment capacity to achieve the purpose of power flow convergence;
鉴于此类负荷的时间分布特性，非常适合与时序潮流和概率潮流相结合，达到评估电网安全性的目的。In view of the time distribution characteristics of such loads, it is very suitable to be combined with time series power flow and probabilistic power flow to achieve the purpose of evaluating power grid security.
S433、依据潮流计算结果、每一时间断面对应的历史运行子数据以及预测运行子数据，计算得到每一时间断面对应的子网损值和可靠性子系数；S433, according to the power flow calculation result, the historical operation sub-data corresponding to each time section, and the predicted operation sub-data, calculate and obtain the sub-network loss value and reliability sub-coefficient corresponding to each time section;
具体的，针对每一时间断面，均计算得到一个子网损值和可靠性子系数。Specifically, for each time section, a sub-network loss value and a reliability sub-coefficient are calculated.
假设配用电模型中包括光伏、电动汽车充放电站和配电网，电动汽车充放电站为待增配用电设备。Assume that the power distribution model includes photovoltaics, electric vehicle charging and discharging stations, and the distribution network, and the electric vehicle charging and discharging stations are the power equipment to be added.
则光伏的历史运行子数据可以是出力曲线，电动汽车充放电站的预测运行子数据可以是负荷数据，如充电次数、充电时间等数据。配电网的历史运行子数据可以是电压等级、有无变压器等数据。Then the historical operation sub-data of photovoltaic can be output curve, and the predicted operation sub-data of electric vehicle charging and discharging station can be load data, such as charging times, charging time and other data. The historical operation sub-data of the distribution network can be data such as voltage level, presence or absence of transformers, etc.
计算子网损值可以采用节点等效功率法，具体如下：The node equivalent power method can be used to calculate the sub-network loss, as follows:
结合时序潮流的理论，以时序潮流计算模型为基础，针对确定网架结构的智能配用电系统，考虑分布式电源出力的随机性、间歇性，针对不同时间断面，进行配电网运行潮流计算。对各时间断面下进行网损计算，遍历各时间断面总结得到系统时序网损分布。之后在将各个时间断面下的网损加以总结，得到属于该时间区间的网损结果。在时序潮流的基础上，节点等效功率法可以弥补其数据同步性差的缺点，适于智能配电网的网损计算。Combined with the theory of time series power flow, based on the time series power flow calculation model, for the intelligent power distribution system that determines the grid structure, considering the randomness and intermittency of distributed power output, the power flow calculation of distribution network operation is carried out for different time sections. . The network loss is calculated under each time section, and the system time series network loss distribution is obtained by traversing each time section and summarizing it. Afterwards, the network loss under each time section is summarized, and the network loss result belonging to the time interval is obtained. On the basis of time series power flow, the node equivalent power method can make up for the disadvantage of poor data synchronization, and is suitable for network loss calculation of smart distribution network.
计算可靠性子系数可以采用蒙特卡洛模拟法和故障模式影响分析法。具体如下：The reliability sub-coefficient can be calculated by Monte Carlo simulation method and failure mode effect analysis method. details as follows:
蒙特卡洛模拟法作为智能配用电系统状态选择的分析方法。蒙特卡洛模拟法是指通过计算机产生的随机数对元件的状态进行抽样，进而组合得到整个系统的状态。于新型业务接入的智能配用电系统，采用蒙特卡洛模拟法进行可靠性评估有着诸多优势：第一，蒙特卡洛模拟法容易模拟负荷随机波动、元件随机故障、气候随机变化等随机因素和系统的矫正控制策略，计算结果更加贴近实际。第二，在满足一定计算精度的要求下，蒙特卡洛模拟法的抽样次数与系统的规模无关，因此特别适用于新型复合复杂系统的可靠性评估。第三，除了能够计算表征系统平均性能的指标外，蒙特卡洛模拟法还能获得可靠性指标的概率分布，评估结果更加全面。第四，蒙特卡洛法的模拟过程非常简单和直观，易于被工程技术人员理解和掌握。综上所述，本项目采用蒙特卡洛模拟法作为智能配用电系统状态选择的分析方法。Monte Carlo simulation method is used as an analysis method for state selection of intelligent power distribution system. The Monte Carlo simulation method refers to sampling the state of the components through random numbers generated by the computer, and then combining to obtain the state of the entire system. For the intelligent power distribution and consumption system connected to new services, the use of Monte Carlo simulation method for reliability assessment has many advantages: First, the Monte Carlo simulation method is easy to simulate random factors such as random fluctuations of loads, random failures of components, and random changes in climate. And the corrective control strategy of the system, the calculation results are closer to reality. Second, the sampling times of the Monte Carlo simulation method have nothing to do with the scale of the system under the requirement of certain calculation accuracy, so it is especially suitable for the reliability evaluation of new complex complex systems. Third, in addition to the ability to calculate the indicators that characterize the average performance of the system, the Monte Carlo simulation method can also obtain the probability distribution of the reliability indicators, and the evaluation results are more comprehensive. Fourth, the simulation process of Monte Carlo method is very simple and intuitive, and is easy to be understood and mastered by engineers and technicians. To sum up, this project adopts the Monte Carlo simulation method as the analysis method for the state selection of the intelligent power distribution system.
对于新型业务接入的智能配用电系统，采用故障模式影响分析法进行系统状态可靠性评估有着诸多优势：第一，配电系统中元件类型和负荷点都比较多，不同元件故障影响可能不同；即使是同一元件故障，对不同位置的负荷点也有着不同的影响，有必要对故障影响进行详细分析；第二，对于辐射型网络一般只考虑一阶故障影响，故障模式影响表可能只是一个简单的故障分析矩阵或某一故障对可靠性指标的增量值，如果采用一些快速搜索技术进行分析，例如故障遍历、故障扩散等，并不会增加太多计算量；第三，FMEA法是其它一些故障分析法的基础，例如最小割集法、可靠性框图等方法中都包含影响分析的过程。综上所述，本项目采用故障模式影响分析法作为智能配用电系统状态评估的分析方法。For the intelligent power distribution system connected to new services, there are many advantages to use the failure mode impact analysis method to evaluate the reliability of the system state. First, there are many types of components and load points in the power distribution system, and the failure effects of different components may be different. ;Even if the same component fails, it will have different effects on the load points at different locations, and it is necessary to analyze the failure effects in detail; Second, for the radial network, only the first-order failure effects are generally considered, and the failure mode effect table may only be a A simple fault analysis matrix or the incremental value of a certain fault to the reliability index, if some fast search techniques are used for analysis, such as fault traversal, fault diffusion, etc., it will not increase the amount of calculation too much; third, the FMEA method is The basis of some other failure analysis methods, such as the minimum cut set method, reliability block diagram and other methods, all contain the process of impact analysis. In summary, this project adopts the failure mode impact analysis method as the analysis method for the status assessment of the intelligent power distribution and consumption system.
S434、基于每一所述时间断面对应的子网损值和可靠性子系数，计算所述配用电模型的网损值和可靠性系数；S434, based on the sub-network loss value and reliability sub-coefficient corresponding to each of the time sections, calculate the network loss value and reliability coefficient of the power distribution model;
可选的，在本实施例的基础上，步骤S434可以包括：Optionally, on the basis of this embodiment, step S434 may include:
1)将每一所述时间断面对应的子网损值进行积分运算，得到所述配用电模型的网损值；1) Integrate the sub-network loss value corresponding to each described time section to obtain the network loss value of the power distribution model;
具体的，不同时间断面的子网损值可以构成一条子网损值变化曲线，根据该曲线进行积分计算，得到总网损值，即为配用电模型的网损值。Specifically, the sub-network loss values of different time sections can form a sub-network loss value change curve, and the integral calculation is performed according to the curve to obtain the total network loss value, which is the network loss value of the power distribution model.
2)将每一所述时间断面对应的可靠性子系数中，对应的数值最小的可靠性子系数作为所述可靠性系数。2) Among the reliability sub-coefficients corresponding to each time section, the corresponding reliability sub-coefficient with the smallest value is used as the reliability coefficient.
具体的，得到每一所述时间断面对应的可靠性子系数后，选取最小的可靠性子系数作为配用电模型的可靠性系数。Specifically, after obtaining the reliability sub-coefficient corresponding to each time section, the smallest reliability sub-coefficient is selected as the reliability coefficient of the power distribution model.
需要说明的是，本实施例中仅给出了一种计算网损值和可靠性系数的方法，此外，还可以采用其余方法计算网损值和可靠性系数。It should be noted that only one method for calculating the network loss value and the reliability coefficient is given in this embodiment, and other methods may also be used to calculate the network loss value and the reliability coefficient.
可选的，进一步，执行步骤S434后，还可以包括：Optionally, further, after step S434 is performed, it may further include:
1)将所述网损值与所述配用电模型的历史网损值进行比较，得到第一比较结果；1) Compare the network loss value with the historical network loss value of the power distribution model to obtain a first comparison result;
2)将所述可靠性系数与所述配用电模型的历史可靠性系数进行比较，得到第二比较结果；2) comparing the reliability coefficient with the historical reliability coefficient of the power distribution model to obtain a second comparison result;
3)依据所述第一比较结果和所述第二比较结果，确定增加所述待增配用电设备的优劣性结果。3) According to the first comparison result and the second comparison result, determine the pros and cons of adding the electric equipment to be added.
其中，历史网损值和历史可靠性系数是基于不添加待增配用电设备的配用电模型的历史运行数据计算得到的。Among them, the historical network loss value and historical reliability coefficient are calculated based on the historical operation data of the power distribution model without adding the power equipment to be added.
若网损值大于历史网损值，说明加入待增配用电设备后，会增大网损；若网损值小于历史网损值，说明加入待增配用电设备后，会降低网损。If the network loss value is greater than the historical network loss value, it means that the network loss will increase after adding the electrical equipment to be added; if the network loss value is smaller than the historical network loss value, it means that the network loss will be reduced after adding the electrical equipment to be added. .
若可靠性系数大于历史可靠性系数，说明加入待增配用电设备后，可靠性增强；若可靠性系数小于历史可靠性系数，说明加入待增配用电设备后，可靠性降低。If the reliability coefficient is greater than the historical reliability coefficient, it means that the reliability is enhanced after adding the electrical equipment to be added; if the reliability coefficient is smaller than the historical reliability coefficient, it means that the reliability is reduced after adding the electrical equipment to be added.
基于网损值与历史网损值的第一比较结果，以及可靠性系数和历史可靠性系数的第二比较结果，来确定加入待增配用电设备的利弊，进而确定是否需要加入待增配用电设备。Based on the first comparison result of the network loss value and the historical network loss value, and the second comparison result of the reliability coefficient and the historical reliability coefficient, determine the advantages and disadvantages of adding the electric equipment to be added, and then determine whether it is necessary to add the power consumption to be added. Electrical equipment.
需要说明的是，是否加入待增配用电设备还可以依据加入待增配用电设备后，当地用户的用电情况以及加入待增配用电设备对当地经济效益的影响程度来确定。It should be noted that whether to add the electric equipment to be added can also be determined according to the electricity consumption of local users after the addition of the electric equipment to be added and the degree of impact of the addition of the electric equipment to be added on the local economic benefits.
本实施例中给出了一种计算网损值和可靠性系数的方法，进而就可以根据本实施例中的方法来计算网损值和可靠性系数，进而分析是否需要加入该待增配用电设备。This embodiment provides a method for calculating the network loss value and reliability coefficient, and then the network loss value and reliability coefficient can be calculated according to the method in this embodiment, and then it is analyzed whether it is necessary to add the to-be-added configuration electrical equipment.
本实施例中，可以在确定时间断面后，依据每一时间断面对应的数据计算得到配用电模型的运行参数，以确定配用电模型的运行状态是否正常。In this embodiment, after determining the time sections, the operating parameters of the power distribution and consumption model can be calculated according to the data corresponding to each time section, so as to determine whether the operating state of the power distribution and consumption model is normal.
本实施例中，基于所述配用电数学模型，确定所述待增配用电设备的预测运行数据，其中，所述待增配用电设备的预测运行数据随时间或负载值变化，即预测运行数据是根据新增用电设备的使用情况得到的数据，符合新增用电设备的运行状态，这样计算得到的网损和可靠性等数据就符合智能配用电系统的实际情况，进而计算得到的网损和可靠性等数据的准确度较高。In this embodiment, the predicted operation data of the electric equipment to be added is determined based on the mathematical model of distribution and consumption, wherein the predicted operation data of the electric equipment to be added changes with time or load value, that is, The predicted operation data is the data obtained according to the usage of the newly added electrical equipment, which is in line with the operating status of the newly added electrical equipment, so that the calculated network loss and reliability data are in line with the actual situation of the intelligent power distribution system, and then The accuracy of the calculated data such as network loss and reliability is high.
可选的，与上述方法相对应，本发明的另一实施例中提供了一种计算配用电系统网损和可靠性的系统，如图8所示，可以包括：Optionally, corresponding to the above method, another embodiment of the present invention provides a system for calculating the network loss and reliability of a power distribution system, as shown in FIG. 8 , which may include:
模型构建模块101，用于构建配用电模型；其中，所述配用电模型中包括已有配用电设备的电路结构模型和待增配用电设备的电路结构模型；The model building module 101 is used to build a power distribution model; wherein, the power distribution model includes a circuit structure model of the existing power distribution equipment and a circuit structure model of the power distribution equipment to be added;
信息获取模块102，用于获取已有配用电设备的历史运行数据，以及所述待增配用电设备的配用电数学模型；其中，所述配用电数学模型为所述待增配用电设备的出力数学模型或用电数学模型；The information acquisition module 102 is used to acquire the historical operation data of the existing electrical equipment and the mathematical model of the electrical equipment to be added; wherein, the mathematical model of electrical distribution is the electrical equipment to be added. Output mathematical model or electricity mathematical model of electrical equipment;
数据确定模块103，用于基于所述配用电数学模型，确定所述待增配用电设备的预测运行数据；其中，所述待增配用电设备的预测运行数据随时间或负载值变化；A data determination module 103, configured to determine the predicted operation data of the electric equipment to be added based on the mathematical model of electric distribution; wherein the predicted operation data of the electric equipment to be added changes with time or load value ;
参数计算模块104，用于根据所述配用电模型、所述已有配用电设备的历史运行数据和所述待增配用电设备的预测运行数据，计算所述配用电模型的运行参数，其中，所述配用电模型的运行参数包括潮流计算结果、网损值和可靠性系数。The parameter calculation module 104 is configured to calculate the operation of the power distribution model according to the power distribution model, the historical operation data of the existing power distribution equipment, and the predicted operation data of the power distribution equipment to be added. parameters, wherein the operating parameters of the power distribution model include power flow calculation results, network loss values and reliability coefficients.
本实施例中，基于所述配用电数学模型，确定所述待增配用电设备的预测运行数据，其中，所述待增配用电设备的预测运行数据随时间或负载值变化，即预测运行数据是根据新增用电设备的使用情况得到的数据，符合新增用电设备的运行状态，这样计算得到的网损和可靠性等数据就符合智能配用电系统的实际情况，进而计算得到的网损和可靠性等数据的准确度较高。In this embodiment, the predicted operation data of the electric equipment to be added is determined based on the mathematical model of distribution and consumption, wherein the predicted operation data of the electric equipment to be added changes with time or load value, that is, The predicted operation data is the data obtained according to the usage of the newly added electrical equipment, which is in line with the operating status of the newly added electrical equipment, so that the calculated network loss and reliability data are in line with the actual situation of the intelligent power distribution system, and then The accuracy of the calculated data such as network loss and reliability is high.
需要说明的是，本实施例中的各个模块的工作过程，请参照上述实施例中的相应说明，在此不再赘述。It should be noted that, for the working process of each module in this embodiment, please refer to the corresponding description in the foregoing embodiment, which will not be repeated here.
可选的，在上述参数计算装置的实施例的基础上，所述参数计算模块包括：Optionally, on the basis of the embodiment of the above parameter calculation device, the parameter calculation module includes:
时间确定子模块，用于确定多个时间断面；The time determination submodule is used to determine multiple time sections;
数据确定子模块，用于确定每一所述时间断面对应的已有配用电设备的历史运行数据中的历史运行子数据以及所述待增配用电设备的预测运行数据中的预测运行子数据；A data determination sub-module is used to determine the historical operation sub-data in the historical operation data of the existing electric power distribution equipment corresponding to each time section and the predicted operation sub-data in the predicted operation data of the electric equipment to be added. data;
参数计算子模块，用于基于所述配用电模型、每一所述时间断面对应的历史运行子数据以及预测运行子数据，计算所述配用电模型的运行参数。A parameter calculation sub-module is configured to calculate the operation parameters of the power distribution model based on the power distribution model, historical operation sub-data and predicted operation sub-data corresponding to each of the time sections.
本实施例中，可以在确定时间断面后，依据每一时间断面对应的数据计算得到配用电模型的运行参数，以确定配用电模型的运行状态是否正常。In this embodiment, after determining the time sections, the operating parameters of the power distribution and consumption model can be calculated according to the data corresponding to each time section, so as to determine whether the operating state of the power distribution and consumption model is normal.
需要说明的是，本实施例中的各个模块和子模块的工作过程，请参照上述实施例中的相应说明，在此不再赘述。It should be noted that, for the working process of each module and sub-module in this embodiment, please refer to the corresponding description in the above-mentioned embodiment, which will not be repeated here.
可选的，在上一实施例的基础上，所述参数计算子模块还包括：Optionally, on the basis of the previous embodiment, the parameter calculation submodule further includes:
结构图构建单元，用于基于所述配用电模型、每一所述时间断面对应的历史运行子数据以及预测运行子数据，构建每一所述时间断面对应的电路结构图；a structure diagram construction unit, configured to construct a circuit structure diagram corresponding to each of the time sections based on the power distribution model, the historical operation sub-data and the predicted operation sub-data corresponding to each of the time sections;
第一计算单元，用于根据每一所述时间断面对应的电路结构图，进行潮流计算，得到潮流计算结果；a first calculation unit, configured to perform power flow calculation according to the circuit structure diagram corresponding to each time section, and obtain a power flow calculation result;
第二计算单元，用于依据潮流计算结果、每一所述时间断面对应的历史运行子数据以及预测运行子数据，计算得到每一所述时间断面对应的子网损值和可靠性子系数；The second calculation unit is configured to calculate the sub-network loss value and the reliability sub-coefficient corresponding to each of the time sections according to the power flow calculation result, the historical operation sub-data and the predicted operation sub-data corresponding to each of the time sections;
第三计算单元，用于基于每一所述时间断面对应的子网损值和可靠性子系数，计算所述配用电模型的网损值和可靠性系数；a third calculation unit, configured to calculate the network loss value and reliability coefficient of the power distribution model based on the sub-network loss value and reliability sub-coefficient corresponding to each of the time sections;
进一步，所述第三计算单元包括：Further, the third computing unit includes:
计算子单元，用于将每一所述时间断面对应的子网损值进行积分运算，得到所述配用电模型的网损值；a calculation subunit, configured to perform an integral operation on the sub-network loss value corresponding to each of the time sections to obtain the network loss value of the power distribution model;
系数确定子单元，用于将每一所述时间断面对应的可靠性子系数中，对应的数值最小的可靠性子系数作为所述可靠性系数。The coefficient determination sub-unit is configured to use the reliability sub-coefficient with the smallest value among the reliability sub-coefficients corresponding to each time section as the reliability coefficient.
进一步，所述第三计算单元还包括：Further, the third computing unit also includes:
第一比较子单元，用于第三计算单元基于每一所述时间断面对应的子网损值和可靠性子系数，计算所述配用电模型的网损值和可靠性系数后，将所述网损值与所述配用电模型的历史网损值进行比较，得到第一比较结果；The first comparison sub-unit is used for the third calculation unit to calculate the network loss value and reliability coefficient of the power distribution model based on the sub-network loss value and reliability sub-coefficient corresponding to each of the time sections, and then calculate the Comparing the network loss value with the historical network loss value of the power distribution model to obtain a first comparison result;
第二比较子单元，用于将所述可靠性系数与所述配用电模型的历史可靠性系数进行比较，得到第二比较结果；a second comparison subunit, configured to compare the reliability coefficient with the historical reliability coefficient of the power distribution model to obtain a second comparison result;
结果确定子单元，用于依据所述第一比较结果和所述第二比较结果，确定增加所述待增配用电设备的优劣性结果。The result determination subunit is configured to determine the pros and cons of adding the electric equipment to be added according to the first comparison result and the second comparison result.
本实施例中给出了一种计算网损值和可靠性系数的方法，进而就可以根据本实施例中的方法来计算网损值和可靠性系数，进而分析是否需要加入该待增配用电设备。This embodiment provides a method for calculating the network loss value and reliability coefficient, and then the network loss value and reliability coefficient can be calculated according to the method in this embodiment, and then it is analyzed whether it is necessary to add the to-be-added configuration electrical equipment.
需要说明的是，本实施例中的各个模块、子模块、单元和子单元的工作过程，请参照上述实施例中的相应说明，在此不再赘述。It should be noted that, for the working process of each module, sub-module, unit and sub-unit in this embodiment, please refer to the corresponding description in the above-mentioned embodiment, and details are not repeated here.
可选的，在上述计算网损值和可靠性系数的方法及系统的实施例的基础上，本发明的另一实施例提供了一种计算配用电系统网损和可靠性的电子设备，其特征在于，包括：存储器和处理器；Optionally, on the basis of the above embodiments of the method and system for calculating a network loss value and a reliability coefficient, another embodiment of the present invention provides an electronic device for calculating the network loss and reliability of a power distribution and consumption system, It is characterized in that, it comprises: a memory and a processor;
其中，所述存储器用于存储程序；Wherein, the memory is used to store programs;
处理器调用程序并用于：The processor invokes the program and is used to:
构建配用电模型；其中，所述配用电模型中包括已有配用电设备的电路结构模型和待增配用电设备的电路结构模型；Building a power distribution model; wherein the power distribution model includes a circuit structure model of the existing power distribution equipment and a circuit structure model of the power equipment to be added;
获取已有配用电设备的历史运行数据，以及所述待增配用电设备的配用电数学模型；其中，所述配用电数学模型为所述待增配用电设备的出力数学模型或用电数学模型；Obtain the historical operation data of the existing electrical equipment and the mathematical model of the electrical equipment to be added; wherein the mathematical model of the electrical equipment to be added is the output mathematical model of the electrical equipment to be added or electricity mathematical model;
基于所述配用电数学模型，确定所述待增配用电设备的预测运行数据；其中，所述待增配用电设备的预测运行数据随时间或负载值变化；Determine the predicted operation data of the electric equipment to be added based on the mathematical model of distribution and consumption; wherein the predicted operation data of the electric equipment to be added changes with time or load value;
根据所述配用电模型、所述已有配用电设备的历史运行数据和所述待增配用电设备的预测运行数据，计算所述配用电模型的运行参数。The operating parameters of the power distribution model are calculated according to the power distribution model, the historical operation data of the existing power distribution equipment, and the predicted operation data of the to-be-added power equipment.
本实施例中，基于所述配用电数学模型，确定所述待增配用电设备的预测运行数据，其中，所述待增配用电设备的预测运行数据随时间或负载值变化，即预测运行数据是根据新增用电设备的使用情况得到的数据，符合新增用电设备的运行状态，这样计算得到的网损和可靠性等数据就符合智能配用电系统的实际情况，进而计算得到的网损和可靠性等数据的准确度较高。In this embodiment, the predicted operation data of the electric equipment to be added is determined based on the mathematical model of distribution and consumption, wherein the predicted operation data of the electric equipment to be added changes with time or load value, that is, The predicted operation data is the data obtained according to the usage of the newly added electrical equipment, which is in line with the operating status of the newly added electrical equipment, so that the calculated network loss and reliability data are in line with the actual situation of the intelligent power distribution system, and then The accuracy of the calculated data such as network loss and reliability is high.
对所公开的实施例的上述说明，使本领域专业技术人员能够实现或使用本发明。对这些实施例的多种修改对本领域的专业技术人员来说将是显而易见的，本文中所定义的一般原理可以在不脱离本发明的精神或范围的情况下，在其它实施例中实现。因此，本发明将不会被限制于本文所示的这些实施例，而是要符合与本文所公开的原理和新颖特点相一致的最宽的范围。The above description of the disclosed embodiments enables any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
| Application Number | Priority Date | Filing Date | Title |
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| CN201811196743.5ACN109193643B (en) | 2018-10-15 | 2018-10-15 | Method and system for calculating power distribution and distribution system network loss and reliability |
| Application Number | Priority Date | Filing Date | Title |
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| CN201811196743.5ACN109193643B (en) | 2018-10-15 | 2018-10-15 | Method and system for calculating power distribution and distribution system network loss and reliability |
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| CN109193643Atrue CN109193643A (en) | 2019-01-11 |
| CN109193643B CN109193643B (en) | 2021-09-21 |
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| CN201811196743.5AActiveCN109193643B (en) | 2018-10-15 | 2018-10-15 | Method and system for calculating power distribution and distribution system network loss and reliability |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111581196A (en)* | 2020-04-29 | 2020-08-25 | 深圳市双合电气股份有限公司 | Supply and distribution power grid intelligent data acquisition and arrangement system based on intelligent factory framework |
| CN111709587A (en)* | 2020-06-22 | 2020-09-25 | 国网山西省电力公司电力科学研究院 | State Probabilistic Evaluation Method of Distribution System Based on Probability-Sequence Uncertainty |
| CN116826815A (en)* | 2023-08-28 | 2023-09-29 | 深圳海辰储能控制技术有限公司 | Charging management method based on battery module, energy manager and related medium |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100100250A1 (en)* | 2003-08-08 | 2010-04-22 | Electric Power Group, Llc | Real-time performance monitoring and management system |
| CN102088209A (en)* | 2011-03-15 | 2011-06-08 | 河海大学 | Self-healing control method of distribution network |
| CN102651049A (en)* | 2011-02-23 | 2012-08-29 | 河北省电力研究院 | Method for calculating loss reducing rate of newly built transformer station of electric power system |
| CN103530823A (en)* | 2013-10-25 | 2014-01-22 | 湖南大学 | Comprehensive microgrid planning and design evaluation system based on OTFN-AHP |
| CN104732340A (en)* | 2015-03-12 | 2015-06-24 | 国家电网公司 | Auxiliary power grid planning decision-making method based on annual time scales |
| CN107301472A (en)* | 2017-06-07 | 2017-10-27 | 天津大学 | Distributed photovoltaic planing method based on scene analysis method and voltage-regulation strategy |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100100250A1 (en)* | 2003-08-08 | 2010-04-22 | Electric Power Group, Llc | Real-time performance monitoring and management system |
| CN102651049A (en)* | 2011-02-23 | 2012-08-29 | 河北省电力研究院 | Method for calculating loss reducing rate of newly built transformer station of electric power system |
| CN102088209A (en)* | 2011-03-15 | 2011-06-08 | 河海大学 | Self-healing control method of distribution network |
| CN103530823A (en)* | 2013-10-25 | 2014-01-22 | 湖南大学 | Comprehensive microgrid planning and design evaluation system based on OTFN-AHP |
| CN104732340A (en)* | 2015-03-12 | 2015-06-24 | 国家电网公司 | Auxiliary power grid planning decision-making method based on annual time scales |
| CN107301472A (en)* | 2017-06-07 | 2017-10-27 | 天津大学 | Distributed photovoltaic planing method based on scene analysis method and voltage-regulation strategy |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111581196A (en)* | 2020-04-29 | 2020-08-25 | 深圳市双合电气股份有限公司 | Supply and distribution power grid intelligent data acquisition and arrangement system based on intelligent factory framework |
| CN111709587A (en)* | 2020-06-22 | 2020-09-25 | 国网山西省电力公司电力科学研究院 | State Probabilistic Evaluation Method of Distribution System Based on Probability-Sequence Uncertainty |
| CN116826815A (en)* | 2023-08-28 | 2023-09-29 | 深圳海辰储能控制技术有限公司 | Charging management method based on battery module, energy manager and related medium |
| CN116826815B (en)* | 2023-08-28 | 2023-12-26 | 深圳海辰储能控制技术有限公司 | Charging management method based on battery module, energy manager and related medium |
| Publication number | Publication date |
|---|---|
| CN109193643B (en) | 2021-09-21 |
| Publication | Publication Date | Title |
|---|---|---|
| CN107425520B (en) | A Three-Phase Interval State Estimation Method for Active Distribution Networks with Uncertainty of Node Injection Power | |
| CN113964885A (en) | Reactive active prediction and control technology of power grid based on situation awareness | |
| CN107294122A (en) | A kind of mixed energy storage system is layered dynamic control method | |
| CN111762057B (en) | Intelligent charging and discharging management method for V2G electric vehicle in regional microgrid | |
| CN109193643A (en) | A kind of method and system calculating distribution system network loss and reliability | |
| Wei et al. | Study on characteristics evaluation index of renewable power output and application on renewable energy development planning | |
| CN106557867B (en) | Photovoltaic power generation probability model modeling method suitable for medium and long time scale power grid analysis | |
| CN104158217A (en) | Output power fluctuation characteristic description method for clustered wind-solar combined power generation system | |
| CN106856331B (en) | Grid-connected performance testing method for wind-solar combined power generation system | |
| CN115344995A (en) | Energy carrying capacity evaluation method, device, computer equipment and storage medium | |
| Murugesan et al. | Cost optimization of PV-diesel systems in nanogrid using LJ Cuckoo search and its application in mobile towers | |
| Wang et al. | Adequacy assessment of generating systems incorporating wind, PV and energy storage | |
| Wang et al. | Research on high proportion renewable energy of hybrid energy storage containing hydrogen storage | |
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