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基于协同进化算法求解寡头电力市场均衡_杨彦.pdf
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详细说明：:建立并分析了考虑网络约束且能考虑需求方策略竞价的电力市场线性供给函数模型, 在该
市场框架中, 独立系统运行员通过求解最优潮流来确定发电安排以及节点电价, 市场策略性参与者
通过竞标来追求最大利润。运用协同进化算法求取市场均衡, 协同进化算法系一种智能代理仿真
方法, 借鉴了生态系统中协同进化机制的理念。多个算例被用来验证协同进化算法的有效性, 实验
结果表明如果市场存在纯策略均衡, 该算法均能够快速收敛到均衡点, 运用简便且具有较强的搜索
能力。200933(18)
电力系疣自动化
市场出清
8]
G1
当前最优策略
C1(Pc1)=0.01P1+10P
G2
染色体
出清结果对应策略当前最优策略
2(Pe2)=0.01P2+10Pc2,
DI
B1(PD)=-0.04Pi+30P1
参与者1
参与者
参与者N
节点1
节点2
DI
Fig. 1 Species i individual fitness valuing process
G2
t∈T
H
Fig 2 2-bus text system
2~4
G2
2.2
DI
G1
G2
(1.150,1.150)。
k
13.828(MW°h),Gl,
G2,D1
(101.073MW
f(k,k)≥f(k,k)k∈S,(16)
101.073MW,201.146MW),
101.073MW。
[8]
(14)
best best
IWMGindividual welfare maximization
L
80MW
18」IWM
G1
G2
G1 DI
(1.571,0.857),
8.858(MW°h),G1D1
(100.00MW,100.001MW),
[9 IWM
3.1
L max 80M W.
[89
[9 IWM
6
C1 C2
DI
16
[8-9
l,2
kmi0.2,kmx10.0;
G1 G2
DI
50
L
r Imax
0.90
0.05。
200MW
Gl. G2, DI
(1.131,1.131,0.866),
100
(91.028MW,91.028MW,182.057MW),
13.374/(MW°h)。
ISO
OPF
10
21941-2018ChinaAcademicJournalElectronicPublishingHouse.Allrightsreservedhttp://www.cnki.net
2
0.001),
Table 2 Results of market clearing in equilibrium states
12
/MW
(MWh)-1)
(361.837,
236.014146.836(21.118,21.118
(1.134,1.082188.863,
3.3
21.118)
[7
314.685)
(122.964
(1.336,1.252286.687
1-2
PG
1.0.1.0)
228.808,
25.000
21.695,29.149
25.422)
Pg2
67
180.843)
节点3
节点1
(1.314,1.158216.275,
(21.452,24.245,
25.000
0.903,0.775)203.025,
22.849
145.637)
(348.572,
(1.128,1.075174.476
节点2
0.953,0.938)226.602139.472
20.855,20.855,
20.855)
296.446)
(G1,G2,D1,D2)
Fig 3 3 bus text sy stem
(G1,G2,D1,D2)
(1,2,3)
Table 1 Coefficients of demand and firm s cost function
Pc
b(阝)
500 M W,Lmax= 25 W
GI
0.01
15.00
G2
0.008
18.00
DI
0.08
40.00
2
1-2
D2
0.06
40.00
DI
2116.793h,D2
1658.139/h
PGI= PG2=L
500MW
G1 G2
(1.134,1.082),
7:
P
P
500MW,Lm=1000MW。
PG1- PG2-500M W
Lmax= 25M w
C1 C2
(1.336,1.252)
1-2
1,2)
DI
2094.124
h D2
981.134
IWM
6,7,
?1994-2018cHinaAcademicJournalelEctronicPublishingHouse.Allrightsreservedhttp://www.cnki.net
200933(18)
电力系疣自动化
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46,2018ChinaaCademicJournalElectronicPublishingHouse.Allrightsreservedhttp://www.cnki.net
A Rev iew of Optimization Allocation of Distributed Generations Embedded in Power Grid
WANG Shouxiang, WANG Hui, Cal Sheng xia
(1. Key L abo ratory of Power System Simula tion and Control of Ministry of Education. Tianjin Universit
Tianjin 300072, China; 2. Nankai U niv ersity, Tian jin 300071, China)
Abstract: With the smart grid becoming the foas of current study, distributed generations (dg s)as o ne of the main functions
in smart grid are increasing ly w idely appl ied in pow er sy stems, and the optimal allocation of dgs has become particularly
cruciaL. A review is made of the optimal allocation of dg, w ith its curre nt development at ho me and abroad summed up and
analyzed. Some common optim izatio n al location models are given, especially those of comprehens ive multi-objective
optimiz ation based on sing le o bjec tive o ptimization. O ptimization allocation methods are boiled do wn to analy tic metho ds
heuristic methods, and probability optimization methods plus those for multro bjective optimization. Finally, optimizat
allocation of dgs in the micro-grid is discussed. w ith the future development of dg and micro-grid optimizat io n projected.
This work is supported by National Natural Science Foundation of China ( No. 50777047, 50837001)and Program for
New Century Excellent Talents in U nive rsitv (No. NCET-070602)
Key words: distribu led ge nera Lion; optimal alloca lion Imulti-objecLive optimization micro grid op limia lion smart grid
(上接第46页 continued from page46)
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edu. cn
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张尧(1948—),男,通信作者,博士,教授,博士生导
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师,辶要研究方向:巳力系统安全与稳定、电力市场。
CHEN Haor ong, YANG Yan, ZHANG Yao. Realiz a ion of E mail: epyzhang scut.edu.cn
A Coevolutionary Approach to Calculate Equilibrium for Oligopol istic Electricity Mar
YANG Yan, CHEN Haoyong, ZHANG Yao, WANG Yeping, JING Zhaoxia, TAN Ke
South China u nive rsity of Techno lo gy, Guangzhou 510640 China)
Abstract:A linear supply functio n equi librium( LSFE) model conside ring netw ork co nstraints and dem and side bid ding for
oligo po listic electricity market is presented. In this market model the iso solves an optimal pow er flow for d is pa tching
generation and de te rm ining nodal prices, and par ticipants w ill choo se their bids to seek the maximum profits. Developed from
agent- ba sed simu lation methods, the coevo lutio nary appro ach simula tes the oo evolutionary mechanis m in nature a nd ado pts the
notions of ecos ys tem. It is employed to calcula te the n ash equilibrium point in this work. Numerical examples are used to
valida te the effcctiveness of the propo sed method. Simulation results show that the robust and flex ible of the coev olution ary
approach. It can co verge to pure strategy equilibrium rapidly if it exists
Key words: electricity market Nash equilibrium netw ork constraints, linear supply function equilibrium, coev olutionary
appro ach
?1994-2018chinaAcademicJournalElectronicPublishingHouse.Allrightsreservedhttp://www.cnki.net
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