CN110391673B - 高比例风电下考虑需求侧响应的多时段主动配网重构方法 - Google Patents

高比例风电下考虑需求侧响应的多时段主动配网重构方法 Download PDF

Info

Publication number
CN110391673B
CN110391673B CN201910596398.2A CN201910596398A CN110391673B CN 110391673 B CN110391673 B CN 110391673B CN 201910596398 A CN201910596398 A CN 201910596398A CN 110391673 B CN110391673 B CN 110391673B
Authority
CN
China
Prior art keywords
power
node
load
constraint
distribution network
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201910596398.2A
Other languages
English (en)
Other versions
CN110391673A (zh
Inventor
林振智
章博
刘晟源
章天晗
韩畅
杨莉
文福拴
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Zhejiang University ZJU
Original Assignee
Zhejiang University ZJU
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Zhejiang University ZJU filed Critical Zhejiang University ZJU
Priority to CN201910596398.2A priority Critical patent/CN110391673B/zh
Publication of CN110391673A publication Critical patent/CN110391673A/zh
Application granted granted Critical
Publication of CN110391673B publication Critical patent/CN110391673B/zh
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06Energy or water supply
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/04Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
    • H02J3/06Controlling transfer of power between connected networks; Controlling sharing of load between connected 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
    • H02J3/12Circuit 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
    • 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
    • H02J3/28Arrangements for balancing of the load in a network by storage of energy
    • H02J3/386
    • 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
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2310/00The network for supplying or distributing electric power characterised by its spatial reach or by the load
    • H02J2310/50The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads
    • H02J2310/56The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads characterised by the condition upon which the selective controlling is based
    • H02J2310/62The condition being non-electrical, e.g. temperature
    • H02J2310/64The condition being economic, e.g. tariff based load management
    • 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
    • Y02E10/00Energy generation through renewable energy sources
    • Y02E10/70Wind energy
    • Y02E10/76Power conversion electric or electronic aspects
    • 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
    • Y02E70/00Other energy conversion or management systems reducing GHG emissions
    • Y02E70/30Systems combining energy storage with energy generation of non-fossil origin
    • 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
    • Y04S10/00Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
    • 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
    • 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
    • Y04S50/00Market activities related to the operation of systems integrating technologies related to power network operation or related to communication or information technologies
    • Y04S50/16Energy services, e.g. dispersed generation or demand or load or energy savings aggregation

Landscapes

  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Business, Economics & Management (AREA)
  • Health & Medical Sciences (AREA)
  • Economics (AREA)
  • Marketing (AREA)
  • General Health & Medical Sciences (AREA)
  • Human Resources & Organizations (AREA)
  • Water Supply & Treatment (AREA)
  • Primary Health Care (AREA)
  • Strategic Management (AREA)
  • Tourism & Hospitality (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Public Health (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

本发明涉及一种高比例风电接入下考虑需求侧响应的多时段主动配网重构方法,其包括步骤:确定配电系统中负荷和风机的随机模型;考虑电力价格弹性系数的用户用电负荷需求侧响应方法,通过电力价格弹性系数确定电力用户需求侧响应后的负荷量;构建基于Distflow潮流模型的二阶锥配网重构模型。其可以为电力系统的配网重构策略提供相应的决策依据。

Description

高比例风电下考虑需求侧响应的多时段主动配网重构方法
技术领域
本发明涉及电力系统领域,特别是涉及一种高比例风电接入下考虑需求侧响应的多时段主动配网重构方法,所述的高比例风电是指风机出力占总负荷的比例达到30%及以上。
背景技术
配网重构是一种通过改变配电系统拓扑结构来提高系统可靠性和经济型的优化技术。目前,我国正在大力发展高比例新能源发电,在配电系统中接入大量的电动汽车(Electrical Vehicle,EV)、光伏电源(Photovoltaic,PV)、风电机组(Wind Turbine,WT)和各种储能系统(Energy Storage System,ESS),配电系统中的分布式电源(DistributedGeneration,DG)的渗透率越来越高,这些具有不确定性的DG大量接入对配电系统的主动重构也提出了越来越高的要求。
目前综合考虑新能源渗透率和需求侧响应对配网重构影响的研究还不多。另外,在配网重构算法方面,虽然启发式算法在配网重构中得到了广泛的应用,但采用启发式算法求解的结果可能是局部最优解,不能保证结果的全局最优性。
发明内容
基于此,为了在电力系统中获得更好的配网重构效果,本发明提出了一种高比例风电接入下考虑需求侧响应的多时段主动配网重构方法。
一种高比例风电接入下考虑需求侧响应的多时段主动配网重构方法,包括如下步骤:
1)确定配电系统中负荷和风机的随机模型;
2)考虑电力价格弹性系数的用户用电负荷需求侧响应方法,通过电力价格弹性系数确定电力用户需求侧响应后的负荷量;
3)构建基于Distflow潮流模型的二阶锥配网重构模型。
上述技术方案中,步骤1)中提出了确定了配电系统中负荷和风机的随机模型,具体如下:
a)负荷随机模型
在配网重构中,负荷的不确定性往往会给配网重构结果造成很大的影响。现有的文献多采用正态分布来近似拟合负荷的不确定性,负荷的有功和无功功率的概率密度函数可以表示为:
Figure GDA0002724056970000021
Figure GDA0002724056970000022
式中,Ph和Qh分别为节点h的有功和无功功率;
Figure GDA0002724056970000023
Figure GDA0002724056970000024
分别为负荷有功和无功功率的数学期望;
Figure GDA0002724056970000025
Figure GDA0002724056970000026
分别为负荷有功和无功功率的标准差,其值可采用负荷预测数据通过概率统计方法来确定。
b)考虑随机性的风电模型
风速概率模型,符合Weibull分布,概率密度函数可描述为:
Figure GDA0002724056970000027
式中,v为风速,单位为m/s;c为尺度参数,体现了该地区风电场的平均风速;k为形状参数,反映了风速分布的特性,取值范围通常在1.8到2.3之间。不同地区有不同的尺度参数和形状参数。
基于风速概率模型,风电机组的运行状态可以分为停机状态(零输出场景)、欠额定状态(欠额定输出场景)和额定状态(额定输出场景)三种。风机的输出功率可表示为:
Figure GDA0002724056970000031
式中,vci为切入风速;vr为额定风速;vco为切出风速;Pr为风力发电机的额定输出功率。
步骤2)中考虑电力价格弹性系数,确定用户用电负荷需求侧响应后的负荷量,方法为:
需求侧响应是指电力用户根据价格信号或激励机制做出响应,以此改变用户的常规电力消费行为。本文基于电力价格弹性系数对价格激励性负荷进行调控,实现电力负荷的“削峰填谷”,根据地区的电能需求弹性系数来确定采用分时电价后的负荷需求变化量。
电力负荷的弹性系数可以表示为在一定时期内电价变化引起的用户用电需求量变化的百分比,考虑需求侧响应的负荷约束可以用下式表示:
Figure GDA0002724056970000032
Figure GDA0002724056970000033
Figure GDA0002724056970000034
式中,T是划分的总时段;N为总节点数目;ξτ为用户的电力价格弹性系数;τ表示用户的类型,τcom,τind和τres分别表示商业、工业和居民用户;
Figure GDA0002724056970000035
为节点i时刻t需求侧响应前后电价的变化,单位为元/(kW·h);
Figure GDA0002724056970000036
为节点i时刻t需求侧响应前后用电需求量的变化量,单位为kW·h;
Figure GDA0002724056970000037
Figure GDA0002724056970000038
分别为节点i时刻t需求侧响应前后的电价;
Figure GDA0002724056970000041
Figure GDA0002724056970000042
分别表示需求侧响应前后节点i时刻t的负荷量;ρτ,peak和ρτ,valley分别为τ类负荷的峰、谷电价;Tpeak和Tvalley分别为峰、谷电价所属的时间区间。
步骤3)中构建了基于Distflow潮流和二阶锥模型构建混合整数二阶锥规划(Mixed Integer Second-Order Cone Programming,MISOCP)问题,提高了模型的求解效率,具体如下:
a)目标函数
本文考虑的配网重构模型以社会利益最大化为目标函数,包含网损费用、弃风费用和开关费用,即:
Figure GDA0002724056970000043
式中,C是配网重构模型的总费用;T是划分的总时段;ΔT为各个时段的长度;ψb表示配电系统中含联络线的所有支路集合;iij,t是t时段流经支路ij的电流;rij是支路ij的等效电阻;
Figure GDA0002724056970000044
是网络中接入风机的节点的集合;
Figure GDA0002724056970000045
是i节点t时刻风机的预测出力,
Figure GDA0002724056970000046
是i节点t时刻风机接入电网的实际功率;αij,0和αij为0-1变量,分别表示网络初始状态下和配网重构后支路ij的开断状况,其值等于1表示支路ij闭合,其值等于0表示支路ij开断;C1、C2和C3分别表示网损费用、开关费用和弃风费用单价。
b)约束条件
i)Distflow潮流约束
Distflow潮流模型是一种从支路功率出发建立的潮流方程,相比于传统的基于节点功率的潮流计算法,Distflow潮流模型更适用于辐射状配电系统的潮流计算。Distflow潮流方程可以表示为:
Figure GDA0002724056970000047
Figure GDA0002724056970000048
Figure GDA0002724056970000049
Figure GDA0002724056970000051
Figure GDA0002724056970000052
Figure GDA0002724056970000053
式中,Pij,t和Qij,t分别为t时刻支路ij上流过的有功功率和无功功率;rij和xij分别为支路ij的电阻和电抗;Iij,t为t时刻支路ij上流过的电流;Pj,t和Qj,t为t时刻节点i和节点j注入的有功功率和无功功率;
Figure GDA0002724056970000054
Figure GDA0002724056970000055
分别为j节点t时刻注入的负荷有功功率和无功功率;
Figure GDA0002724056970000056
Figure GDA0002724056970000057
分别为j节点t时刻注入的风电有功功率和无功功率;
Figure GDA0002724056970000058
Figure GDA0002724056970000059
分别为j节点t时刻储能系统(Energy Storage System,ESS)的充电功率和放电功率;Ui,t和Uj,t分别为节点i和节点j的电压幅值;ω(j)为配电系统中与节点j相邻但不在节点j到根节点路径上的节点集合。
但由于在配网重构中网络拓扑的不断变化,集合ω(j)也不断变化;传统的Distflow潮流模型不再适用。考虑配网重构特性,假定配电系统中所有的开关均闭合,配网重构问题相当于选择其中部分开关断开的问题,根据配电系统网络辐射状的约束,对传统Distflow潮流模型进行改进,通过引入线路开断变量αij对潮流方程进行松弛,引入变量
Figure GDA00027240569700000510
Figure GDA00027240569700000511
对潮流约束进行等价变换,采用大M法、不等式约束及二阶锥方法进行进一步松弛,得到改进后的Distflow潮流方程如下:
Figure GDA00027240569700000512
Figure GDA00027240569700000513
ijM1≤Pij,t≤αijM1
ijM2≤Qij,t≤αijM2
ijM3≤Iij,t≤αijM3
Figure GDA00027240569700000514
Figure GDA00027240569700000515
Figure GDA00027240569700000516
Figure GDA0002724056970000061
Figure GDA0002724056970000062
式中,f(j)和s(j)分别表示配电系统中节点j的父节点和子节点的集合;M1,M2,M3和M4为足够大的正数,通常取大于10。
ii)节点电压约束
配网重构要求重构后各节点的电压和支路的电流要限制在允许范围内,结合公式(14)-(15),节点电压约束和支路电流约束可以表示为
Figure GDA0002724056970000063
Figure GDA0002724056970000064
Figure GDA0002724056970000065
式中,
Figure GDA0002724056970000066
Figure GDA0002724056970000067
分别表示t时刻节点i允许的电压最小值和最大值;Ωn为平衡节点集合;
Figure GDA0002724056970000068
表示t时刻线路ij允许通过的最大电流。
iii)风机出力约束
配电系统中接入的风机发电量要满足一定的范围约束,即实际接入配电系统的风电量不能超过其允许出力的上下限。风机出力约束可以表示为
Figure GDA0002724056970000069
式中,
Figure GDA00027240569700000610
Figure GDA00027240569700000611
分别为节点i时刻t风机出力的下限和上限。
iv)储能约束
ESS运行约束包含充放电状态约束、储电容量约束、充放电功率约束和日允许充放电次数约束,其分别为:
Figure GDA00027240569700000612
Figure GDA00027240569700000613
Figure GDA00027240569700000614
Figure GDA0002724056970000071
式中,
Figure GDA0002724056970000072
Figure GDA0002724056970000073
为0-1变量,分别表示节点i时刻t储能的充、放电状态;
Figure GDA0002724056970000074
为充放电功率最大值;
Figure GDA0002724056970000075
表示节点i时刻tESS的储电容量;
Figure GDA0002724056970000076
表示ESS可存储的最大电量;ηch和ηdis分别表示ESS的充、放电效率;
Figure GDA0002724056970000077
表示日内ESS充放电最大次数。
v)开关次数约束
配电系统中的开关都有使用寿命,频繁的开断往往会减少开关的寿命。因此,有必要对配网重构中开关的开断次数进行限制,以此来提高电力系统运行的经济性,开关次数约束可以表示为
Figure GDA0002724056970000078
式中,
Figure GDA0002724056970000079
为配电系统中所有开关在全时段允许开断的最大次数;αij,0为网络的初始开关状态。
vi)配电系统连通性和辐射性约束
配网重构需要保证重构后的配电系统的连通性,且不存在孤岛和环网。配电系统连通性和辐射性约束可表示为
Figure GDA00027240569700000710
βijji=αij
Figure GDA00027240569700000711
β1j=0
式中,n为配电系统的支路数;βij为0、1变量,i节点为j节点的父节点时取1,否则取0;Ni表示配网中的节点集合。
本发明在高比例风电接入的情况下提出了考虑需求侧响应的多时段主动配网重构策略,综合考虑网损、弃风和开关费用,确定配电系统拓扑、ESS充放电功率和分时峰谷电价,有效利用需求侧响应策略和ESS,进一步降低配电系统运行费用,减少弃风率,为配电系统确定峰谷电价提供参考;在求解算法方面,本发明基于混合整数二阶锥规划对配网重构模型进行求解,通过松弛和变量替换,建立基于Distflow潮流模型的MISOCP问题,可以在YALMIP平台上利用CPLEX求解器直接求解。相比于传统的智能算法,本发明的方法不易陷入局部最优,准确性更高。
本发明的有益效果是:
1)综合考虑分布式电源、储能系统,有利于配网消纳新能源,在一定程度上提高了社会效益。
2)考虑需求侧响应对配网重构的影响,在峰谷电价的基础上,采用电价弹性系数对价格激励型负荷进行平抑,将峰谷价格做为决策变量,优化最优峰谷价格,给电价决策者提供参考;实现负荷的“削峰填谷”,实现社会利益最大化的目标。
3)将配网重构模型转化成二阶锥形式的凸优化模型求解,相比于遗传算法、粒子群算法等传统人工智能方法,求解结果更加准确。
附图说明
图1为实施例的一种高比例风电接入下考虑需求侧响应的多时段主动配网重构方法示意图;
图2是IEEE33节点配电系统模型;
图3是风机有功出力曲线;
图4是各节点多时段电压曲线;
图5是需求侧响应前后负荷曲线;
图6是风机1出力曲线;
图7是风机2出力曲线;
图8是ESS出力曲线。
具体实施方式
为了更好地理解本发明的目的、技术方案以及技术效果,以下结合附图对本发明进行进一步的讲解说明。
参考图1,图1为实施例的一种高比例风电接入下考虑需求侧响应的多时段主动配网重构方法,包括如下步骤:
S10,确定了配电系统中负荷和风机的随机模型;在一个实施例中:
a)负荷随机模型
在配网重构中,负荷的不确定性往往会给配网重构结果造成很大的影响。现有的文献多采用正态分布来近似拟合负荷的不确定性,负荷的有功和无功功率的概率密度函数可以表示为:
Figure GDA0002724056970000091
Figure GDA0002724056970000092
式中,Ph和Qh分别为节点h的有功和无功功率;
Figure GDA0002724056970000093
Figure GDA0002724056970000094
分别为负荷有功和无功功率的数学期望;
Figure GDA0002724056970000095
Figure GDA0002724056970000096
分别为负荷有功和无功功率的标准差,其值可采用负荷预测数据通过概率统计方法来确定。
b)考虑随机性的风电模型
风速概率模型,符合Weibull分布,概率密度函数可描述为:
Figure GDA0002724056970000097
式中,v为风速,单位为m/s;c为尺度参数,体现了该地区风电场的平均风速;k为形状参数,反映了风速分布的特性,取值范围通常在1.8到2.3之间。不同地区有不同的尺度参数和形状参数。
基于风速概率模型,风电机组的运行状态可以分为停机状态(零输出场景)、欠额定状态(欠额定输出场景)和额定状态(额定输出场景)三种。风机的输出功率可表示为:
Figure GDA0002724056970000101
式中,vci为切入风速;vr为额定风速;vco为切出风速;Pr为风力发电机的额定输出功率。
S20,考虑电力价格弹性系数的用户用电负荷需求侧响应方法;在一个实施例中:
需求侧响应是指电力用户根据价格信号或激励机制做出响应,以此改变用户的常规电力消费行为。本文基于电力价格弹性系数对价格激励性负荷进行调控,实现电力负荷的“削峰填谷”,根据地区的电能需求弹性系数来确定采用分时电价后的负荷需求变化量。
电力负荷的弹性系数可以表示为在一定时期内电价变化引起的用户用电需求量变化的百分比,考虑需求侧响应的负荷约束可以用下式表示:
Figure GDA0002724056970000102
Figure GDA0002724056970000103
Figure GDA0002724056970000104
式中,T是划分的总时段;N为总节点数目;ξτ为用户的电力价格弹性系数;τ表示用户的类型,τcom,τind和τres分别表示商业、工业和居民用户;
Figure GDA0002724056970000111
为节点i时刻t需求侧响应前后电价的变化,单位为元/(kW·h);
Figure GDA0002724056970000112
为节点i时刻t需求侧响应前后用电需求量的变化量,单位为kW·h;
Figure GDA0002724056970000113
Figure GDA0002724056970000114
分别为节点i时刻t需求侧响应前后的电价;
Figure GDA0002724056970000115
Figure GDA0002724056970000116
分别表示需求侧响应前后节点i时刻t的负荷量;ρτ,peak和ρτ,valley分别为τ类负荷的峰、谷电价;Tpeak和Tvalley分别为峰、谷电价所属的时间区间。
S30,构建了基于Distflow潮流模型的二阶锥配网重构模型;在一个实施例中:
a)目标函数
本文考虑的配网重构模型以社会利益最大化为目标函数,包含网损费用、弃风费用和开关费用,即:
Figure GDA0002724056970000117
式中,C是配网重构模型的总费用;T是划分的总时段;ΔT为各个时段的长度;ψb表示配电系统中含联络线的所有支路集合;iij,t是t时段流经支路ij的电流;rij是支路ij的等效电阻;
Figure GDA0002724056970000118
是网络中接入风机的节点的集合;
Figure GDA0002724056970000119
是i节点t时刻风机的预测出力,
Figure GDA00027240569700001110
是i节点t时刻风机接入电网的实际功率;αij,0和αij为0-1变量,分别表示网络初始状态下和配网重构后支路ij的开断状况,其值等于1表示支路ij闭合,其值等于0表示支路ij开断;C1、C2和C3分别表示网损费用、开关费用和弃风费用单价。
b)约束条件
i)Distflow潮流约束
Distflow潮流模型是一种从支路功率出发建立的潮流方程,相比于传统的基于节点功率的潮流计算法,Distflow潮流模型更适用于辐射状配电系统的潮流计算。Distflow潮流方程可以表示为:
Figure GDA0002724056970000121
Figure GDA0002724056970000122
Figure GDA0002724056970000123
Figure GDA0002724056970000124
Figure GDA0002724056970000125
Figure GDA0002724056970000126
式中,Pij,t和Qij,t分别为t时刻支路ij上流过的有功功率和无功功率;rij和xij分别为支路ij的电阻和电抗;Iij,t为t时刻支路ij上流过的电流;Pj,t和Qj,t为t时刻节点i和节点j注入的有功功率和无功功率;
Figure GDA0002724056970000127
Figure GDA0002724056970000128
分别为j节点t时刻注入的负荷有功功率和无功功率;
Figure GDA0002724056970000129
Figure GDA00027240569700001210
分别为j节点t时刻注入的风电有功功率和无功功率;
Figure GDA00027240569700001211
Figure GDA00027240569700001212
分别为j节点t时刻储能系统(Energy Storage System,ESS)的充电功率和放电功率;Ui,t和Uj,t分别为节点i和节点j的电压幅值;ω(j)为配电系统中与节点j相邻但不在节点j到根节点路径上的节点集合。
但由于在配网重构中网络拓扑的不断变化,集合ω(j)也不断变化;传统的Distflow潮流模型不再适用。考虑配网重构特性,假定配电系统中所有的开关均闭合,配网重构问题相当于选择其中部分开关断开的问题,根据配电系统网络辐射状的约束,对传统Distflow潮流模型进行改进,通过引入线路开断变量αij对潮流方程进行松弛,引入变量
Figure GDA00027240569700001213
Figure GDA00027240569700001214
对潮流约束进行等价变换,采用大M法、不等式约束及二阶锥方法进行进一步松弛,得到改进后的Distflow潮流方程如下:
Figure GDA00027240569700001215
Figure GDA00027240569700001216
ijM1≤Pij,t≤αijM1
ijM2≤Qij,t≤αijM2
ijM3≤Iij,t≤αijM3
Figure GDA0002724056970000131
Figure GDA0002724056970000132
Figure GDA0002724056970000133
Figure GDA0002724056970000134
Figure GDA0002724056970000135
式中,f(j)和s(j)分别表示配电系统中节点j的父节点和子节点的集合;M1,M2,M3和M4为足够大的正数,通常取大于10。
ii)节点电压约束
配网重构要求重构后各节点的电压和支路的电流要限制在允许范围内,结合公式(14)-(15),节点电压约束和支路电流约束可以表示为
Figure GDA0002724056970000136
Figure GDA0002724056970000137
Figure GDA0002724056970000138
式中,
Figure GDA0002724056970000139
Figure GDA00027240569700001310
分别表示t时刻节点i允许的电压最小值和最大值;Ωn为平衡节点集合;
Figure GDA00027240569700001311
表示t时刻线路ij允许通过的最大电流。
iii)风机出力约束
配电系统中接入的风机发电量要满足一定的范围约束,即实际接入配电系统的风电量不能超过其允许出力的上下限。风机出力约束可以表示为
Figure GDA00027240569700001312
式中,
Figure GDA00027240569700001313
Figure GDA00027240569700001314
分别为节点i时刻t风机出力的下限和上限。
iv)储能约束
ESS运行约束包含充放电状态约束、储电容量约束、充放电功率约束和日允许充放电次数约束,其分别为:
Figure GDA0002724056970000141
Figure GDA0002724056970000142
Figure GDA0002724056970000143
Figure GDA0002724056970000144
式中,
Figure GDA0002724056970000145
Figure GDA0002724056970000146
为0-1变量,分别表示节点i时刻t储能的充、放电状态;
Figure GDA0002724056970000147
为充放电功率最大值;
Figure GDA0002724056970000148
表示节点i时刻tESS的储电容量;
Figure GDA0002724056970000149
表示ESS可存储的最大电量;ηch和ηdis分别表示ESS的充、放电效率;
Figure GDA00027240569700001410
表示日内ESS充放电最大次数。
v)开关次数约束
配电系统中的开关都有使用寿命,频繁的开断往往会减少开关的寿命。因此,有必要对配网重构中开关的开断次数进行限制,以此来提高电力系统运行的经济性,开关次数约束可以表示为
Figure GDA00027240569700001411
式中,
Figure GDA00027240569700001412
为配电系统中所有开关在全时段允许开断的最大次数;αij,0为网络的初始开关状态。
vi)配电系统连通性和辐射性约束
配网重构需要保证重构后的配电系统的连通性,且不存在孤岛和环网。配电系统连通性和辐射性约束可表示为
Figure GDA00027240569700001413
βijji=αij
Figure GDA0002724056970000151
β1j=0
式中,n为配电系统的支路数;βij为0、1变量,i节点为j节点的父节点时取1,否则取0;Ni表示配网中的节点集合。
在IEEE33节点配电系统的基础上对模型进行分析,如图2所示,该系统的基准电压为12.66kV,基准功率为10MW,母线1为平衡节点,电压为1.0pu且最大的承受电压为1.05pu,最小为0.90pu,线路最大电流均为300A。在节点12和
节点25接入风机,风机采用定功率因数发电,功率因数恒等于0.95。在节点20接入ESS。根据某市现行峰谷电价策略,设定用电峰时段Tpeak为8:00-22:00,谷时段Tvalley为22:00-8:00。基于风力概率模型,采用蒙特卡洛抽样方法对风速进行抽样,确定风机1和风机2的出力曲线,如图3所示。
利用CPLEX和YALMIP对本发明采用的模型进行求解,结果如表1所示,在30%的风电渗透率下,求解出的IEEE33节点配电系统网损费用、弃风费用和开关费用的总成本为552.8459元,此时,系统的网损率为1.59%,弃风率为0.70%。系统断开开关为7、9、28、32和34,此时模型优化出的峰时电价和谷时电价分别为0.542(元/kW·h)和0.428(元/kW·h)。
表1 IEEE-33节点配电系统的优化结果
Figure GDA0002724056970000152
此时,配电系统各节点24小时的电压曲线如图4所示,可以看出,各节点的电压标幺值均在0.98和1.00之间,满足配电系统电压约束。图5为需求侧响应前后的负荷曲线,可以看出,采用了需求侧响应策略后的负荷相比于需求侧响应前,峰谷差和负荷波动均有了较大的改善。
从图6和图7风机出力曲线可以看出,风机1的出力被配电系统完全消纳,风机2在时段4的出力未被配电系统完全消纳。这是因为在时段4处于凌晨时段,该时段处于用电低谷时段,且一般为一天内用电最少的时段之一,此时配电系统负荷较少,大量的风电接入不仅不能起到平抑负荷的作用,反而加剧了系统负荷的峰谷差,不利于配电系统的功率平衡,导致时段4的风电不能完全消纳。图8反映了接入配电系统中的ESS充放电状态,从图8可以看出,储能充电集中0:00-5:00和8:00-10:00,大多处于用电低谷时段;放电状态主要集中在6:00-8:00和16:00-24:00,多属于用电高峰时段,体现了ESS“削峰填谷”的作用。

Claims (2)

1.高比例风电下考虑需求侧响应的多时段主动配网重构方法,其特征在于,包括如下步骤:
1)确定配电系统中负荷和风机的随机模型;
2)考虑电力价格弹性系数的用户用电负荷需求侧响应方法,通过电力价格弹性系数确定电力用户需求侧响应后的负荷量;
3)构建基于Distflow潮流模型的二阶锥配网重构模型;
所述的确定配电系统中负荷和风机的随机模型为:提出考虑随机性的负荷和风机模型,具体如下:
a)负荷随机模型
采用正态分布来近似拟合负荷的不确定性,负荷的有功和无功功率的概率密度函数表示为:
Figure FDA0002724056960000011
Figure FDA0002724056960000012
式中,Ph和Qh分别为节点h的有功和无功功率;
Figure FDA0002724056960000013
Figure FDA0002724056960000014
分别为负荷有功和无功功率的数学期望;
Figure FDA0002724056960000015
Figure FDA0002724056960000016
分别为负荷有功和无功功率的标准差;
b)考虑随机性的风电模型
风速概率模型,符合Weibull分布,概率密度函数可描述为:
Figure FDA0002724056960000017
式中,v为风速,单位为m/s;c为尺度参数,k为形状参数;
风机的输出功率可表示为:
Figure FDA0002724056960000021
式中,vci为切入风速;vr为额定风速;vco为切出风速;Pr为风力发电机的额定输出功率;
构建基于Distflow潮流模型的二阶锥配网重构模型,具体如下:
a)目标函数
配网重构模型以社会利益最大化为目标函数,包含网损费用、弃风费用和开关费用,即:
Figure FDA0002724056960000022
式中,C是配网重构模型的总费用;ΔT为各个时段的长度;ψb表示配电系统中含联络线的所有支路集合;iij,t是t时段流经支路ij的电流;rij是支路ij的等效电阻;
Figure FDA0002724056960000029
是网络中接入风机的节点的集合;
Figure FDA0002724056960000023
是i节点t时刻风机的预测出力,
Figure FDA0002724056960000024
是i节点t时刻风机接入电网的实际功率;αij,0和αij为0-1变量,分别表示网络初始状态下和配网重构后支路ij的开断状况,其值等于1表示支路ij闭合,其值等于0表示支路ij开断;C1、C2和C3分别表示网损费用、开关费用和弃风费用单价;
b)约束条件
i)Distflow潮流约束
Distflow潮流方程表示为:
Figure FDA0002724056960000025
Figure FDA0002724056960000026
Figure FDA0002724056960000027
Figure FDA0002724056960000028
Figure FDA0002724056960000031
Figure FDA0002724056960000032
式中,Pij,t和Qij,t分别为t时刻支路ij上流过的有功功率和无功功率;rij和xij分别为支路ij的电阻和电抗;Iij,t为t时刻支路ij上流过的电流;Pj,t和Qj,t为t时刻节点i和节点j注入的有功功率和无功功率;
Figure FDA0002724056960000033
Figure FDA0002724056960000034
分别为j节点t时刻注入的负荷有功功率和无功功率;
Figure FDA0002724056960000035
Figure FDA0002724056960000036
分别为j节点t时刻注入的风电有功功率和无功功率;
Figure FDA0002724056960000037
Figure FDA0002724056960000038
分别为j节点t时刻储能系统的充电功率和放电功率;Ui,t和Uj,t分别为节点i和节点j的电压幅值;ω(j)为配电系统中与节点j相邻但不在节点j到根节点路径上的节点集合;
考虑配网重构特性,假定配电系统中所有的开关均闭合,配网重构问题相当于选择其中部分开关断开的问题,根据配电系统网络辐射状的约束,对传统Distflow潮流模型进行改进,通过引入线路开断变量αij对潮流方程进行松弛,引入变量
Figure FDA0002724056960000039
Figure FDA00027240569600000310
对潮流约束进行等价变换,采用大M法、不等式约束及二阶锥方法进行进一步松弛,得到改进后的Distflow潮流方程如下:
Figure FDA00027240569600000311
Figure FDA00027240569600000312
ijM1≤Pij,t≤αijM1
ijM2≤Qij,t≤αijM2
ijM3≤Iij,t≤αijM3
Figure FDA00027240569600000313
Figure FDA00027240569600000314
Figure FDA00027240569600000315
Figure FDA00027240569600000316
Figure FDA00027240569600000317
式中,f(j)和s(j)分别表示配电系统中节点j的父节点和子节点的集合;M1,M2,M3和M4为正数;
ii)节点电压约束
配网重构要求重构后各节点的电压和支路的电流要限制在允许范围内,节点电压约束和支路电流约束表示为
Figure FDA0002724056960000041
Figure FDA0002724056960000042
Figure FDA0002724056960000043
式中,
Figure FDA0002724056960000044
Figure FDA0002724056960000045
分别表示t时刻节点i允许的电压最小值和最大值;Ωn为平衡节点集合;
Figure FDA0002724056960000046
表示t时刻线路ij允许通过的最大电流;
iii)风机出力约束
配电系统中接入的风机发电量要满足:实际接入配电系统的风电量不能超过其允许出力的上下限,风机出力约束表示为
Figure FDA0002724056960000047
式中,
Figure FDA0002724056960000048
Figure FDA0002724056960000049
分别为节点i时刻t风机出力的下限和上限;
iv)储能约束
ESS运行约束包含充放电状态约束、储电容量约束、充放电功率约束和日允许充放电次数约束,其分别为:
Figure FDA00027240569600000410
Figure FDA00027240569600000411
Figure FDA00027240569600000412
Figure FDA00027240569600000413
式中,
Figure FDA0002724056960000051
Figure FDA0002724056960000052
为0-1变量,分别表示节点i时刻t储能的充、放电状态;
Figure FDA0002724056960000053
为充放电功率最大值;
Figure FDA0002724056960000054
表示节点i时刻tESS的储电容量;
Figure FDA0002724056960000055
表示ESS可存储的最大电量;ηch和ηdis分别表示ESS的充、放电效率;
Figure FDA0002724056960000056
表示日内ESS充放电最大次数;
v)开关次数约束
开关次数约束表示为
Figure FDA0002724056960000057
式中,
Figure FDA0002724056960000058
为配电系统中所有开关在全时段允许开断的最大次数;
vi)配电系统连通性和辐射性约束
配网重构需要保证重构后的配电系统的连通性,且不存在孤岛和环网,配电系统连通性和辐射性约束表示为
Figure FDA0002724056960000059
βijji=αij
Figure FDA00027240569600000510
β1j=0
式中,n为配电系统的支路数;βij为0、1变量,i节点为j节点的父节点时取1,否则取0;Ni表示配网中的节点集合。
2.根据权利要求1所述的高比例风电下考虑需求侧响应的多时段主动配网重构方法,其特征在于,考虑电力价格弹性系数的用户用电负荷需求侧响应方法,通过电力价格弹性系数确定电力用户需求侧响应后的负荷量,具体如下:
电力负荷的弹性系数可以表示为在一定时期内电价变化引起的用户用电需求量变化的百分比,考虑需求侧响应的负荷约束,用下式表示:
Figure FDA00027240569600000511
Figure FDA0002724056960000061
Figure FDA0002724056960000062
式中,T是划分的总时段;N为总节点数目;ξτ为用户的电力价格弹性系数;τ表示用户的类型,τcom,τind和τres分别表示商业、工业和居民用户;
Figure FDA0002724056960000063
为节点i时刻t需求侧响应前后电价的变化,单位为元/(kW·h);
Figure FDA0002724056960000064
为节点i时刻t需求侧响应前后用电需求量的变化量,单位为kW·h;
Figure FDA0002724056960000065
Figure FDA0002724056960000066
分别为节点i时刻t需求侧响应前后的电价;
Figure FDA0002724056960000067
Figure FDA0002724056960000068
分别表示需求侧响应前后节点i时刻t的负荷量;ρτ,peak和ρτ,valley分别为τ类负荷的峰、谷电价;Tpeak和Tvalley分别为峰、谷电价所属的时间区间。
CN201910596398.2A 2019-07-03 2019-07-03 高比例风电下考虑需求侧响应的多时段主动配网重构方法 Active CN110391673B (zh)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910596398.2A CN110391673B (zh) 2019-07-03 2019-07-03 高比例风电下考虑需求侧响应的多时段主动配网重构方法

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910596398.2A CN110391673B (zh) 2019-07-03 2019-07-03 高比例风电下考虑需求侧响应的多时段主动配网重构方法

Publications (2)

Publication Number Publication Date
CN110391673A CN110391673A (zh) 2019-10-29
CN110391673B true CN110391673B (zh) 2020-12-15

Family

ID=68286139

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910596398.2A Active CN110391673B (zh) 2019-07-03 2019-07-03 高比例风电下考虑需求侧响应的多时段主动配网重构方法

Country Status (1)

Country Link
CN (1) CN110391673B (zh)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110932259B (zh) * 2019-11-21 2020-11-10 国网江苏省电力有限公司南通供电分公司 考虑多场景模型及需求侧响应策略的配网重构方法
CN110718938B (zh) * 2019-11-22 2020-12-22 华北电力大学 基于普里姆算法的含高比例分布式电源配网重构方法
CN117767305B (zh) * 2023-12-29 2024-06-11 四川大学 一种考虑需求响应和动态重构的配电网保供方法

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2010103348A1 (en) * 2009-03-09 2010-09-16 Abb Technology Ltd System and method for real-time feeder reconfiguration for load balancing in distribution system automation
CN102945296A (zh) * 2012-10-15 2013-02-27 河海大学 一种需求响应视角下的配电网不确定性重构建模方法
CN105023058A (zh) * 2015-07-07 2015-11-04 天津大学 一种同时考虑开关动作的配电网智能软开关运行优化方法
CN105474523A (zh) * 2013-08-30 2016-04-06 埃森哲环球服务有限公司 用于配电网络重配置的系统、方法和装置及有形计算机可读介质

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2010103348A1 (en) * 2009-03-09 2010-09-16 Abb Technology Ltd System and method for real-time feeder reconfiguration for load balancing in distribution system automation
CN102945296A (zh) * 2012-10-15 2013-02-27 河海大学 一种需求响应视角下的配电网不确定性重构建模方法
CN105474523A (zh) * 2013-08-30 2016-04-06 埃森哲环球服务有限公司 用于配电网络重配置的系统、方法和装置及有形计算机可读介质
CN105023058A (zh) * 2015-07-07 2015-11-04 天津大学 一种同时考虑开关动作的配电网智能软开关运行优化方法

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
主动配电网重构与孤岛划分研究;朱俊澎;《中国博士学位论文全文数据库 工程科技II辑》;20190115;第32-40页 *
卞栋.需求响应视角下的配电网不确定性重构模型.《电力系统自动化》.2013,第37卷(第24期),第31-36页. *
考虑场景联合概率的主动配电网运行重构策略;马晨霄;《电测与仪表》;20181211;第1-8页 *
需求响应视角下的配电网不确定性重构模型;卞栋;《电力系统自动化》;20131225;第37卷(第24期);第31-36页 *
马晨霄.考虑场景联合概率的主动配电网运行重构策略.《电测与仪表》.2018,第1-8页. *

Also Published As

Publication number Publication date
CN110391673A (zh) 2019-10-29

Similar Documents

Publication Publication Date Title
CN110391673B (zh) 高比例风电下考虑需求侧响应的多时段主动配网重构方法
CN112202165B (zh) 平衡负荷的考虑多场景模型及需求侧响应策略的配网重构方法
CN114707403B (zh) 基于抽水蓄能调节的地区配电网多能源协调优化调度方法
CN108512238B (zh) 基于需求侧响应的智能家居两阶段优化调度方法
Ciabattoni et al. Artificial bee colonies based optimal sizing of microgrid components: A profit maximization approach
Bayat et al. A purpose-oriented shuffled complex evolution optimization algorithm for energy management of multi-microgrid systems considering outage duration uncertainty
CN111224422A (zh) 一种基于可靠性的微电网分布式电源配置方法及系统
Xu et al. Optimal scheduling of microgrid with consideration of demand response in smart grid
CN116961008A (zh) 计及电力弹簧与负荷需求响应的微电网容量双层优化方法
CN114862163B (zh) 综合能源系统优化调度方法
CN114188980B (zh) 一种考虑储能装置的透明微网群经济运行域生成方法
CN109286186A (zh) 一种主动配电网优化重构方法
Baneshi et al. Microgrid optimal planning in two functional modes grid connected and the intentional islanding
Tian-qiong et al. A short-term joint optimal dispatching method of wind farms, photovoltaic generations, hydropower stations and gas power plants
Nugraha et al. Optimization of capacity and operational scheduling for grid-tied microgrid using pumped-storage hydroelectricity and photovoltaic
Zhang et al. Optimization Method of User-Side Energy Storage Capacity Considering Typical Daily Load Characteristics
Yu Research on coordinating optimization strategy of integrated energy system based on multi-agent consistency theory
Jadallah Multi-object model for the hybrid wind-solar power generation with energy storage and inverter access capacity configuration
Liu et al. Micro grid energy management based on two-stage robust optimization
Wu et al. Incremental distribution network planning with energy storage
Zhang Study on the Effects of Different Measures in Promoting Renewable Energy Consumption
Chi et al. Multi-Objective Joint Planning Method of Distributed Photovoltaic and Battery Energy Storage System Based on NSGA-III Algorithm
Han et al. Research on the Optimal Scheduling Strategy of Energy Storage Plants for Peak-shaving and Valley-filling
Ábelová et al. Modelling of Battery Energy Storage Systems for Predictive Control in Microgrid Applications
Kaci et al. Influence of battery storage on selfconsumption of residential photovoltaic systems in a mediterranean climate

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant