CN113036823B - 一种分布式配电网优化重构方法 - Google Patents

一种分布式配电网优化重构方法 Download PDF

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CN113036823B
CN113036823B CN202110258112.7A CN202110258112A CN113036823B CN 113036823 B CN113036823 B CN 113036823B CN 202110258112 A CN202110258112 A CN 202110258112A CN 113036823 B CN113036823 B CN 113036823B
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CN113036823A (zh
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林明健
陈珩
徐凤铃
吴强
万信书
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Hainan Electric Power Industry Development Co ltd
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Electric Power Research Institute of Hainan Power Grid Co Ltd
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    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/48Controlling the sharing of the in-phase component
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/12Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
    • H02J3/14Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
    • H02J3/144Demand-response operation of the power transmission or distribution network
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/12Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
    • H02J3/16Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by adjustment of reactive power
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/24Arrangements for preventing or reducing oscillations of power in networks
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/26Arrangements for eliminating or reducing asymmetry in polyphase networks
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/50Controlling the sharing of the out-of-phase component
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/10Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02ATECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A30/00Adapting or protecting infrastructure or their operation
    • Y02A30/60Planning or developing urban green infrastructure
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02BCLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B70/00Technologies for an efficient end-user side electric power management and consumption
    • Y02B70/30Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
    • Y02B70/3225Demand response systems, e.g. load shedding, peak shaving
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/30Reactive power compensation
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/50Arrangements for eliminating or reducing asymmetry in polyphase networks
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04SSYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
    • Y04S20/20End-user application control systems
    • Y04S20/222Demand response systems, e.g. load shedding, peak shaving

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Abstract

本发明提供一种分布式配电网优化重构方法,所述方法包括:建立无功优化的配电网多目标优化重构模型,获得开关动作次数;在满足开关动作次数约束的前提下对配电网的电源和负荷变化趋势进行动态监测;在满足开关动作次数约束的前提下对配电网的电源和负荷不确定性进行动态监测;通过对配电网的电源和负荷变化趋势及不确定性的动态监测,对配电网的拓扑结构进行动态的调整。通过配电网优化重构方法可以在配电网的优化无功、电压的监测、各线路之间平稳运行、优化电网的拓扑结构和快速定位配电网故障提供指导意见,实现多目标优化的配电网重构,有效保障配电网的供电可靠性。

Description

一种分布式配电网优化重构方法
技术领域
本发明涉及配电网优化技术领域,尤其涉及一种分布式配电网优化重构方法。
背景技术
配电网是由架空线路、电缆、杆塔、配电变压器、隔离开关、无功补偿器及一些附属设施等组成的,目前的实际配电网重构过程中开关决策变量较多,严格的数学模型属于非线性非凸规划,为非确定性多项式难题。配电网重构和故障定位等问题目前多应用群智能优化算法求解,但优化过程中易生成大量不满足网络拓扑约束的不可行解,在配电网的多线路接入下配电网的电压、拓扑结构会发生变化,导致配电网的供电电压不足、不能有效保障配电网的供电安全性。
发明内容
鉴以此,本发明的目的在于提供一种分布式配电网优化重构方法,以解决现有技术出现的上述问题。
本发明采用的技术方案如下:
一种分布式配电网优化重构方法,所述方法包括:
建立无功优化的配电网多目标优化重构模型,获得开关动作次数;
在满足开关动作次数约束的前提下对配电网的电源和负荷变化趋势进行动态监测;
在满足开关动作次数约束的前提下对配电网的电源和负荷不确定性进行动态监测;
通过对配电网的电源和负荷变化趋势及不确定性的动态监测,对配电网的拓扑结构进行动态的调整;所述开关动作次数以最少为约束,所述无功优化的配电网多目标优化重构模型包括目标函数和约束条件,所述目标函数包括网络损耗指标、最大电压偏移指标、开关动作次数和功率因数合格率,所述约束条件包括支路电流约束、节点电压约束和网络拓扑约束,所述网络损耗指标的计算公式具体为:
Figure GDA0003744565480000021
式中,Nb为支路总数,Ri代表支路i的电阻,Pi、Qi分别为流过支路i的有功和无功功率,Ui为支路i末端电压;
所述最大电压偏移指标的计算公式具体为
Figure GDA0003744565480000022
式中,Np为节点总数,Urate代表的是指定电压幅值,Ui2为节点i电压;
所述开关动作次数的计算公式具体为:
Figure GDA0003744565480000023
式中,m为配电网中分段开关的数量,n为联络开关的数量,l为电容器开关的数量,kss,i、kts,j代表重构后分段开关及联络开关的状态;ktc,k,0和ktc,k,1代表重构前后电容器开关的状态;
所述功率因数合格率的计算公式具体为:
Figure GDA0003744565480000024
式中,n4为配电网中馈线的总条数,nq为配电网中馈线出线开关处功率因数合格的馈线条数,所述支路电流约束的计算公式具体为:
Ii≤Ii,max,i=1,2…Nb
式中,Ii,max为支路i的最大允许电流;
所述节点电压约束计算公式具体为:
Ui,min≤Ui≤Ui,max,i=1,2,…Np
式中,Ui,min,Ui,max为节点电压上下限;
所述网络拓扑约束计算公式具体为:
x∈G
式中,G为所有辐射状网络结构集合,针对无功优化的配电网多目标优化重构模型,采用多目标粒子群算法进行求解优化,在满足开关动作次数约束的前提下对一段时间内对配电网的电源和负荷变化趋势进行动态监测,具体为:
对负荷状态在各个时间段中进行标准化,其计算公式:
Figure GDA0003744565480000031
式中,Li(t)为时段t时负荷i的大小,Ltotal(t)为时段t时的总负荷大小,Di(t)代表该时段下负荷i标准化后的值,表达时段t时负荷i占总负荷的比重;
在所有负荷的标准化完成之后,计算单个负荷变化度:
ΔDi(t1,t2)=|Di(t1)-Di(t2)|
式中ΔDi(t1,t2)代表负荷i在时段t1和t2之间负荷变化度,那么时段t1,t2总的负荷分布变化度ΔD(t1,t2)表示为:
Figure GDA0003744565480000041
ΔD(t1,t2)的值越大,则在t1,t2两个时段内负荷变化幅度越大,m表示满足开关动作次数的数量,在满足开关动作次数约束的前提下对一段时间内对配电网的电源和负荷不确定性进行动态监测,具体为:
计算分布式电源接入节点的负荷分布变化度值时,在该节点原有负荷值的基础上叠加分布式电源的出力,假设节点i的分布式电源在时段t时的出力为DGi(t),原有负荷值为Loadi(t),则考虑分布式电源注入后的节点的负荷计算公式为:
Li(t)=Loadi(t)-DGi(t)。
与现有技术相比,本发明的有益效果是:
本发明提供一种分布式配电网优化重构方法,通过对配电网的电源和负荷变化趋势及不确定性的动态监测,对配电网的拓扑结构进行动态的调整,使得配电网在一段时间内达到最优运行状态,从而实现多目标优化的配电网的重构,能够有效提升配电网重构的优化的效果,从而能够更好地发挥配电网自身的潜力,而以较低的成本实现电网运行的经济性和安全性,具有很大的经济和社会效益,保障了配电网的安全运行。
附图说明
为了更清楚地说明本发明实施例中的技术方案,下面将对实施例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优选实施例,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,还可以根据这些附图获得其它的附图。
图1是本发明实施例一提供的一种分布式配电网优化重构方法原理示意图。
具体实施方式
以下结合附图对本发明的原理和特征进行描述,所列举实施例只用于解释本发明,并非用于限定本发明的范围。
实施例一
参照图1,本发明提供一种分布式配电网优化重构方法,所述方法包括:
建立无功优化的配电网多目标优化重构模型,获得开关动作次数;
在满足开关动作次数约束的前提下对配电网的电源和负荷变化趋势进行动态监测;
在满足开关动作次数约束的前提下对配电网的电源和负荷不确定性进行动态监测;
通过对配电网的电源和负荷变化趋势及不确定性的动态监测,对配电网的拓扑结构进行动态的调整,所述动态调整可以是对配电网的控制变量进行重新编码,或者是进行配电网络拓扑的结构进行重构保护等方式,通过调整实现多目标优化的配电网的重构,保障配电网的平稳运行。
所述开关动作次数以最少为约束,最少次数可以增加模型的稳定性。
作为一种优选的示例,所述网络损耗指标的计算公式具体为:
所述网络损耗指标的计算公式具体为:
Figure GDA0003744565480000051
式中,Nb为支路总数,Ri代表支路i的电阻,Pi、Qi分别为流过支路i的有功和无功功率,Ui为支路i末端电压;
所述最大电压偏移指标的计算公式具体为
Figure GDA0003744565480000061
式中,Np为节点总数,Urate代表的是指定电压幅值,Ui2为节点i电压;
所述开关动作次数的计算公式具体为:
Figure GDA0003744565480000062
式中,m为配电网中分段开关的数量,n为联络开关的数量,l为电容器开关的数量,kss,i、kts,j代表重构后分段开关及联络开关的状态;ktc,k,0和ktc,k,1代表重构前后电容器开关的状态;
所述功率因数合格率的计算公式具体为:
Figure GDA0003744565480000063
式中,n4为配电网中馈线的总条数,nq为配电网中馈线出线开关处功率因数合格的馈线条数,所述支路电流约束的计算公式具体为:
Ii≤Ii,max,i=1,2…Nb
式中,Ii,max为支路i的最大允许电流;
所述节点电压约束计算公式具体为:
Ui,min≤Ui≤Ui,max,i=1,2,…Np
式中,Ui,min,Ui,max为节点电压上下限;
所述网络拓扑约束计算公式具体为:
x∈G
式中,G为所有辐射状网络结构集合,通过以上参数的计算,无功优化的配电网多目标优化重构模型可以进行配电网的故障分析,以网络损耗最小、电压偏移率最小、开关操作次数最少、功率因素合格率最大为目标,建立无功优化的配电网多目标优化重构模型,可以提高模型的稳定性。
作为一种优选的示例,多目标粒子群优化算法采用外部粒子群存储搜索过程中的Pareto非支配解,同时使用自适应网格法评估外部粒子群中非支配解的空间位置分布密度,选择位置分布密度最小Pareto非支配解作为粒子群的gbest来引导粒子飞行,在尽量多地保存Pareto非支配解的同时使得Pareto最优前沿均匀分布,针对无功电压优化的配电网多目标优化模型,采用多目标粒子群算法进行求解优化,具体的求解优化步骤:
对于一个多目标优化问题min f(X),如果解X1与解X2的目标函数满足:
Figure GDA0003744565480000071
那么称解X1支配解X2,记作X1<X2并称X1为Pareto非支配解;
处理多目标多约束优化问题时,将解的约束满足情况与Pareto支配相结合,引出约束Pareto支配的概念:
(1)解X1为可行解而解X2为不可行解;
(2)当X1和X2都为不可行解时,X1对约束条件违背少;
(3)当X1和X2都为可行解时,满足要求;
当且仅当满足以上一个条件时,X1约束支配X2
此外,若X∈Ω,Ω为搜索空间,且不存在其他的X*∈Ω使得X>X*,则称X为Pareto最优解;多目标问题所有的Pareto最优解的集合称为Pareto最优解集;Pareto最优解集的目标值构成的区域,称为Pareto最优前沿。
作为一种优选的示例,各负荷都有各自不同的负荷曲线,如果简单采用各负荷大小的变化来表征负荷整体分布的变化存在不合理,因为在配电系统从一个时间到另一个时间可能出现负荷整体同一趋势的变化,在满足开关动作次数约束的前提下对配电网的电源和负荷变化趋势进行动态监测,具体为:
对负荷状态在各个时间段中进行标准化,其计算公式:
Figure GDA0003744565480000081
式中,Li(t)为时段t时负荷i的大小,Ltotal(t)为时段t时的总负荷大小,Di(t)代表该时段下负荷i标准化后的值,表达时段t时负荷i占总负荷的比重;
在所有负荷的标准化完成之后,计算单个负荷变化度:
ΔDi(t1,t2)=|Di(t1)-Di(t2)|
式中ΔDi(t1,t2)代表负荷i在时段t1和t2之间负荷变化度,那么时段t1,t2总的负荷分布变化度ΔD(t1,t2)表示为:
Figure GDA0003744565480000082
ΔD(t1,t2)的值越大,则在t1,t2两个时段内负荷变化幅度越大,m表示满足开关动作次数的数量,用标准化后的值来描述负荷的变化情况就显得合理,不会因为总负荷值的大小而掩盖了实际负荷的真实变化情况,在时间区间划分过程中需要确定一个负荷分布变化度的阈值ΔDmax作为时间区间划分的依据。
作为一种优选的示例,当配电网中含有分布式电源时,分布式电源出力会改变系统原有的负荷曲线,因此在处理含有分布式电源的配电网动态重构时需要考虑分布式电源出力的动态特性对系统负荷曲线的影响,在满足开关动作次数约束的前提下对配电网的电源和负荷不确定性进行动态监测,具体为:
计算分布式电源接入节点的负荷分布变化度值时,在该节点原有负荷值的基础上叠加分布式电源的出力,假设节点i的分布式电源在时段t时的出力为DGi(t),原有负荷值为Loadi(t),则考虑分布式电源注入后的节点的负荷计算公式为:
Li(t)=Loadi(t)-DGi(t),通过不确定性的重构改变配电网的拓扑结构,使得配电网达到最优的运行状态。
以上所述仅为本发明的较佳实施例,并不用以限制本发明,凡在本发明的精神和原则之内,所作的任何修改、等同替换、改进等,均应包含在本发明的保护范围之内。

Claims (1)

1.一种分布式配电网优化重构方法,其特征在于,所述方法包括:
建立无功优化的配电网多目标优化重构模型,获得开关动作次数;
在满足开关动作次数约束的前提下对配电网的电源和负荷变化趋势进行动态监测;
在满足开关动作次数约束的前提下对配电网的电源和负荷不确定性进行动态监测;
通过对配电网的电源和负荷变化趋势及不确定性的动态监测,对配电网的拓扑结构进行动态的调整;所述开关动作次数以最少为约束,所述无功优化的配电网多目标优化重构模型包括目标函数和约束条件,所述目标函数包括网络损耗指标、最大电压偏移指标、开关动作次数和功率因数合格率,所述约束条件包括支路电流约束、节点电压约束和网络拓扑约束,所述网络损耗指标的计算公式具体为:
Figure FDA0003744565470000011
式中,Nb为支路总数,Ri代表支路i的电阻,Pi、Qi分别为流过支路i的有功和无功功率,Ui为支路i末端电压;
所述最大电压偏移指标的计算公式具体为
Figure FDA0003744565470000012
式中,Np为节点总数,Urate代表的是指定电压幅值,Ui2为节点i电压;
所述开关动作次数的计算公式具体为:
Figure FDA0003744565470000013
式中,m为配电网中分段开关的数量,n为联络开关的数量,l为电容器开关的数量,kss,i、kts,j代表重构后分段开关及联络开关的状态;ktc,k,0和ktc,k,1代表重构前后电容器开关的状态;
所述功率因数合格率的计算公式具体为:
Figure FDA0003744565470000021
式中,n4为配电网中馈线的总条数,nq为配电网中馈线出线开关处功率因数合格的馈线条数,所述支路电流约束的计算公式具体为:
Ii≤Ii,max,i=1,2…Nb
式中,Ii,max为支路i的最大允许电流;
所述节点电压约束计算公式具体为:
Ui,min≤Ui≤Ui,max,i=1,2,…Np
式中,Ui,min,Ui,max为节点电压上下限;
所述网络拓扑约束计算公式具体为:
x∈G
式中,G为所有辐射状网络结构集合,针对无功优化的配电网多目标优化重构模型,采用多目标粒子群算法进行求解优化,在满足开关动作次数约束的前提下对一段时间内对配电网的电源和负荷变化趋势进行动态监测,具体为:
对负荷状态在各个时间段中进行标准化,其计算公式:
Figure FDA0003744565470000022
式中,Li(t)为时段t时负荷i的大小,Ltotal(t)为时段t时的总负荷大小,Di(t)代表该时段下负荷i标准化后的值,表达时段t时负荷i占总负荷的比重;
在所有负荷的标准化完成之后,计算单个负荷变化度:
ΔDi(t1,t2)=|Di(t1)-Di(t2)|
式中ΔDi(t1,t2)代表负荷i在时段t1和t2之间负荷变化度,那么时段t1,t2总的负荷分布变化度ΔD(t1,t2)表示为:
Figure FDA0003744565470000031
ΔD(t1,t2)的值越大,则在t1,t2两个时段内负荷变化幅度越大,m表示满足开关动作次数的数量,在满足开关动作次数约束的前提下对一段时间内对配电网的电源和负荷不确定性进行动态监测,具体为:
计算分布式电源接入节点的负荷分布变化度值时,在该节点原有负荷值的基础上叠加分布式电源的出力,假设节点i的分布式电源在时段t时的出力为DGi(t),原有负荷值为Loadi(t),则考虑分布式电源注入后的节点的负荷计算公式为:
Li(t)=Loadi(t)-DGi(t)。
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