Method for optimizing the flexible constraints of an electric power system
원문보기
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
G06Q-050/06
G06F-017/50
G06F-001/26
G05F-001/66
G05B-013/04
G06F-017/10
G05B-017/02
출원번호
US-0470504
(2014-08-27)
등록번호
US-9720431
(2017-08-01)
우선권정보
CN-2014 1 0250893 (2014-06-06)
발명자
/ 주소
Wang, Chengmin
Sun, Weiqing
Yi, Tao
Li, Hongzhong
Liu, Yong
Duan, Jianmin
Xiao, Dingyao
출원인 / 주소
SHANGHAI JIAO TONG UNIVERSITY
대리인 / 주소
Hamre, Schumann, Mueller & Larson, P.C.
인용정보
피인용 횟수 :
0인용 특허 :
11
초록▼
A method for optimizing the flexible constraints of an electric power system includes a step S1 of expressing the total power generation cost of the electric power system by using the sum of quadratic functions of active power outputs of all generator sets in the system and constructing an objective
A method for optimizing the flexible constraints of an electric power system includes a step S1 of expressing the total power generation cost of the electric power system by using the sum of quadratic functions of active power outputs of all generator sets in the system and constructing an objective function, a step S2 of selecting a multi-dimensional flexible optimization model or a flexible power generation cost optimization model according to the practical situation of the electric power system and the practical purpose of optimization, a step S3 of determining the operating conditions of the electric power system, and a step S4 of carrying out load flow calculation.
대표청구항▼
1. A method for optimizing flexible constraints of an electric power system, comprising: expressing a total power generation cost f′ of the electric power system by a sum of quadratic functions of active power outputs of all generator sets in the system in a flexible formula as follows: f′=∑i=1Ng(a
1. A method for optimizing flexible constraints of an electric power system, comprising: expressing a total power generation cost f′ of the electric power system by a sum of quadratic functions of active power outputs of all generator sets in the system in a flexible formula as follows: f′=∑i=1Ng(aiPGi2+biPGi+ci)=f0+δfΔf,(1) wherein Ng represents a total number of generators of the system, i=1, 2, . . . , Ng , and ai, bi and ci are power generation coefficients of a generator set i; PGi is an active power of the generator i; f0 represents a minimum expected value of the total power generation cost of the system, Δf represents an acceptable maximum increment of the total power generation cost of the system; δf is a flexible index of a power generation cost of the system, and a numerical area of the flexible index is as follows: δf ε[0,1];selecting a multi-dimensional flexible optimization model or a flexible power generation cost optimization model according to a practical situation of the electric power system and a practical purpose of optimization;determining an operating conditions, including a power grid structure, and voltages and powers of the generators, of the electric power system;carrying out load flow calculation based on the operating conditions of the electric power system; andcarrying out corresponding optimization calculation according to the flexible multi-dimensional or flexible power generation cost model selected in the selecting step to obtain a comprehensive flexible optimization result or an optimal power generation cost, if the load flow calculation is successful, and if the load flow calculation fails, carrying out corresponding optimization calculation according to an optimal load curtailment model to obtain an optimal load curtailment. 2. The method of claim 1, wherein the multi-dimensional flexible optimization model is as follows: minf(δ)=δf2+1N∑k=1NδLk2-1Ng∑i=1NgδGi2-1N∑k=1Nδvk2-1L∑l=1LδFl2s.t.∑i=1Ng(aiPGi2+biPGi+ci)=f0+δfΔfPGk-Vk∑j∈kVj(Gkjcosθkj+Bkjsinθkj)=PLk-δLk-ΔPLkQGk-Vk∑j∈kVj(Gkjsinθkj-Bkjcosθkj)=QLk-δLkΔQLkPGimin+δGiΔPGimin≤PGi≤PGimax-δGiΔPGimaxQGimin+δGiΔQGimin≤QGi≤QGimax-δGiΔQGimaxVkmin+δVkΔVkmin≤Vk≤Vkmax-δVkΔVkmaxSl≤Slmax-δFlΔSlmax0≤δf,δLk,δGi,δVk,δFl≤1i=1,2,…,Ng;k,j=1,2,…,N;l=1,2,…,L(2)wherein δLk represents a flexible load index of a node k, δGi represents a flexible index of a power output of generator i, δVk represents a flexible voltage index of the node k, δFl represents the flexible load flow index of line l, N represents the total number of the nodes of the system, L represents a total number of lines of the system, PGk and QGk represent an active power and a reactive power of the node k, respectively, PLk and QLk, represent an active load and a reactive load of the node k, respectively, Vk and Vj represent voltages of the nodes k and j, respectively, Gkj, Bkj and θkj represent electric conductance, electrical susceptibility, and phase angle difference between the nodes k and j, respectively, ΔPLk and ΔQLk represent deviations of the active load and the reactive load of the node k, respectively, PGi, PGimax and PGimin represent the active power of the generator i and an upper and a lower limits of the active power, respectively, δPGimax and δPGimin represent a maximum allowable threshold-crossing values of PGimax and PGimin, respectively, QGi, QGimax and QGimin represent a reactive power of the generator i and an upper and a lower limits of the reactive power, respectively, δQGimax and δQGimin represent a maximum allowable threshold-crossing values of, QGimax and QGimin, respectively, Vk, Vkmax and Vkmin represent a voltage of the node k and an upper and a lower limits of the voltage, respectively, δVkmax and δVkmin represent a maximum allowable threshold-crossing values of, Vkmax and Vkmin respectively, Sl and Slmax represent a load flow value and a threshold of the line l, respectively, and δSlmax represents a maximum allowable threshold-crossing value of Slmax. 3. The method of claim 1, wherein the flexible power generation cost optimization model is as follows: minf(δ)=δf2s.t.∑i=1Ng(aiPGi2+biPGi+ci)=f0+δfΔfPGk-Vk∑j∈kVj(Gkjcosθkj+Bkjsinθkj)=PLkQGk-Vk∑j∈kVj(Gkjsinθkj-Bkjcosθkj)=QLkPGimin≤PGi≤PGimaxQGimin≤QGi≤QGimaxVkmin≤Vk≤VkmaxSl≤Slmax0≤δf≤1i=1,2,…,Ng;k,j=1,2,…,N;l=1,2,…,L,(3)wherein N represents a total number of the nodes of the system, L represents a total number of lines of the system, PGk, and QGk, represent an active power and a reactive power of a node k, respectively, PLk and QLk represent an active load and a reactive load of the node k, respectively, Vk and Vj represent voltages of the nodes k and j, respectively, Gkj, Bkj and θkj represent electric conductance, electrical susceptibility, and phase angle difference between the nodes k and j, respectively, PGi, PGimax and PGiminrepresent an active power of the generator i and an upper and a lower limits of the active power, respectively, QGi, QGimax and QGimin represent a reactive power of the generator i and an upper and a lower limits of the reactive power, respectively, Vk, Vkmax and Vkminrepresents a voltage of the node k and an upper and a lower limits of the voltage, respectively, and Sl and Slmax represent a load flow value and a threshold of the line l, respectively. 4. The method of claim 1, wherein the optimal load curtailment is as follows: min∑k=1NδLkΔPLks.t.PGk-Vk∑j∈kVj(Gkjcosθkj+Bkjsinθkj)=PLk-δLkΔPLkQGk-Vk∑j∈kVj(Gkjsinθkj-Bkjcosθkj)=QLk-δLkΔQLkPGimin≤PGi≤PGimaxQGimin≤QGi≤QGimaxVkmin≤Vk≤VkmaxSl≤Slmaxi=1,2,…,Ng;k,j=1,2,…,N;l=1,2,…,L,(4)wherein δLK represents a flexible load index of a node k, N represents a total number of nodes of the system, L represents a total number of lines of the system, PGk and QGkrepresent an active power and a reactive power of the node k, respectively, PLk and QLkrepresent an active load and a reactive load of the node k, respectively, Vk and Vj represent voltages of the nodes k and j, respectively, and Gkj, Bkj and θkj represent electric conductance, electrical susceptibility and phase angle difference between the nodes k and j, respectively, ΔPLk and ΔQLk represent deviations of the active load and the reactive load of the node k, respectively, PGi, PGimax and PGimin represent an active power of the generator i and an upper and a limits of the active power, respectively, QGi, QGimax and QGimin represent a reactive power of the generator i and an upper and a lower limits of the reactive power, respectively, Vk , Vkmax and Vkmin represent a voltage of the node k and an upper and a lower limits of the voltage, respectively, and Sl and Slmax represent a load flow value and a threshold of the line l, respectively. 5. The method of claim 1, wherein the corresponding optimization specifically comprises: constructing a Lagrange objective function according to the corresponding multi-dimensional flexible, power generation cost flexible or optimal load curtailment model,obtaining a Kuhn-Tucker condition corresponding to the optimal solution of the Lagrange objective function, andsolving by virtue of a newton method to obtain the optimal solution of the model.
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