CN104538991B

CN104538991B - Interconnected network dominant eigenvalues control method

Info

Publication number: CN104538991B
Application number: CN201410834029.XA
Authority: CN
Inventors: 李卫东; 孙乔; 沈硕; 巴宇; 张琳; 程凯
Original assignee: Dalian University of Technology
Current assignee: Dalian University of Technology
Priority date: 2014-12-27
Filing date: 2014-12-27
Publication date: 2016-11-30
Anticipated expiration: 2034-12-27
Also published as: CN104538991A

Abstract

The invention discloses a kind of interconnected network dominant eigenvalues control method, include the steps of determining that interconnected network arbitrary interconnection l exchange power more limitation Δ P_l；According to interconnection l exchange power more limitation Δ P_l, show that interconnection l two side system A, B are respective and treat adjusting power total amount Δ P_AWith Δ P_B, Δ P_A=Δ P_B=Δ P_l；Determine the region participating in interconnection l exchange power adjustments in system A and B；The present invention, while elimination interconnection is out-of-limit, recovers the safe operation of the ACE in each region, beneficially electrical network, while interregional cooperation, embodies whose responsible fairness doctrine who causes.

Description

Interconnected network dominant eigenvalues control method

Technical field

The present invention relates to a kind of interconnected network dominant eigenvalues control method.

Background technology

Electricity Demand and energy resources concentrate on east, coastal area, south and the Northwest respectively, therefore must So require the trans-regional transmission of electricity of extensive distance, and along with electric power industry development, extra-high voltage grid construction, with And clean energy resource is grid-connected in a large number, transmission of electricity safety trans-regional to China's electrical network brings new challenge.Interregional contact The trnamission capacity of line should perform according to interconnection scheduled net interchange, if there is deviation outside the plan, is then easily caused Tie line Power is out-of-limit, serious threat security of system.Especially for extra-high voltage interconnection, interconnection The exchange out-of-limit impact causing system of power is even more serious.Therefore, the most effective tie--line control strategy Particularly significant, when finding the most in limited time, pull it back to power limit by taking some measures, such as region Between and region in generate electricity and redistribute, reduce or excise load etc. of transmitting electricity.Prior art mainly has three kinds of sides Formula processes the out-of-limit problem with circuit overload of Tie line Power, and one of which is the regulation method of operation, The concrete prevention and control scheme that uses, reduces unit output the most in advance and limits customer charge, and this mode is just Often limit unit output under ruuning situation, the transmission capacity of circuit can be reduced, make to send out transmission of electricity resource and all can not obtain To fully using；Another is for installing automatic safety device mode, by the real-time monitoring to Line Flow, Realize controlling rapidly when circuit overload to specify unit to be adjusted, and then the transmission of circuit can be given full play to Ability, but the unit that this mode participates in regulation is single, controls difficulty bigger；A kind of sensitivity is also had to control Mode, is to utilize the differential relationship of some physical quantity in system, obtains dependent variable and independent variable sensitivity Method, Power System Analysis with control in be widely used, specifically, when interconnection occur Exchange power more in limited time, is exerted oneself the sensitivity to each bar circuit effective power flow by analyzing each generated power, Select suitable electromotor, the electromotor selected is carried out power reallocation and then eliminates out-of-limit, this side Formula has an advantage that the electromotor node calculating that speed is fast, economy strong and participating in regulation is few, but due to The electromotor finding sensitivity maximum in whole system is adjusted, therefore not in view of inside regional Requirement of balance, power system be by several regions couple form, district control deviation ACE shows each region Perform the situation of generation schedule, understand, by ACE, the responsibility size that each region is out-of-limit to dominant eigenvalues, often Needs guarantee district control deviation ACE as far as possible in individual region is in a scope the least, or makes Region control inclined Difference ACE is the direction that beneficially system frequency is recovered, if being therefore adjusted only in accordance with sensitivity and not considering The ACE in each region, then there will be the recovery of extra-high voltage dominant eigenvalues but the circuit of a large amount of low-voltage-grade is out-of-limit Situation, and originally cause the out-of-limit region of extra-high voltage Tie line Power, be likely to be due to intra-zone and send out Motor is little and be not involved in regulation to the sensitivity of out-of-limit circuit, and certain region is the mistake in other region always on the contrary It is responsible for by mistake, does not differentiates between the responsibility size that each region is out-of-limit to Tie line Power, in units of electromotor, Choose electromotor regulation big to out-of-limit circuit sensitivity in whole system, it is impossible to embody the fairness doctrine.

Summary of the invention

The present invention is directed to the proposition of problem above, and develop a kind of interconnected network dominant eigenvalues control method.

The technological means of the present invention is as follows:

A kind of interconnected network dominant eigenvalues control method, comprises the steps:

Step 1: determine interconnected network arbitrary interconnection l exchange power more limitation Δ P_l, l=1,2 ... L；

Step 2: according to interconnection l exchange power more limitation Δ P_l, draw interconnection l two side system A, B each Treat adjusting power total amount Δ P_AWith Δ P_B,-Δ P_A=Δ P_B=Δ P_l；System A includes n region, and system B includes m Individual region；

Step 3: determine in system A and B participate in interconnection l exchange power adjustments region:

1. the district control deviation ACE in each region in system A is calculated_i, and the region in each region in system B Control deviation ACE_j, wherein i=1,2 ... n, j=1,2 ... m；

2. difference DELTA P between interconnection l actual exchange power and scheduled net interchange is obtained_T=P_T-P₀, definition Tie line Power P_TOutflow system A is positive direction, and inflow system A is negative direction, wherein P₀For interconnection Scheduled net interchange；

3. to ACE_i·ΔP_TResult compare with 0, if ACE_i·ΔP_T< 0, then region i is not involved in contact Line l exchanges power adjustments, if ACE_i·ΔP_T> 0, the most right | ACE_i| compare with dead band threshold value, if | ACE_i| More than dead band threshold value, then region i participates in interconnection l and exchanges power adjustments；If | ACE_i| less than or equal to dead band door Threshold value, then region i is not involved in interconnection l and exchanges power adjustments；

To ACE_j·ΔP_TResult compare with 0, if ACE_j·ΔP_T> 0, then region j is not involved in interconnection L exchanges power adjustments, if ACE_j·ΔP_T< 0, the most right | ACE_j| compare with dead band threshold value, if | ACE_j| big In dead band threshold value, then region j participates in interconnection l and exchanges power adjustments；If | ACE_j| less than or equal to dead band threshold Value, then region j is not involved in interconnection l and exchanges power adjustments；

Step 4: according to formulaDetermine the power adjustments amount Δ P of region i_FiIf power is adjusted Joint amount Δ P_Fi> 0, then power adjustments direction is for flowing out region i, if power adjustments amount Δ P_Fi< 0, then power adjustments Direction is inflow region i, wherein Δ P_AAdjusting power total amount, ACE is treated for system A_iRegion control for region i Deviation, ∑_A| ACE | is inclined for the Region control in the region of all participation interconnection l exchange power adjustments in system A Difference sum；

According to formulaDetermine the power adjustments amount Δ P of region j_FjIf, power adjustments amount ΔP_Fj> 0, then power adjustments direction is for flowing out region j, if power adjustments amount Δ P_Fj< 0, then power adjustments side To for inflow region j, wherein Δ P_BAdjusting power total amount, ACE is treated for system B_jRegion control for region j Deviation, ∑_B| ACE | is inclined for the Region control in the region of all participation interconnection l exchange power adjustments in system B Difference sum；

Further, also there are after step 4 following steps:

Step 5: the effective power flow calculating interconnection l is exerted oneself to the generating set k in region i in system A is meritorious Sensitivity A_l-k, the generating set h in region j in system B is gained merit by the effective power flow calculating interconnection l The sensitivity A of power_l-h, wherein k=1,2 ... K, h=1,2 ... H；

Step 6: determine the regulated quantity Δ G that in system A, in the i of region, each generating set is exerted oneself_k, and in system B The regulated quantity Δ G that in the j of region, each generating set is exerted oneself_h, wherein k=1,2 ... K, h=1,2 ... H；

Further, minimum for target to determine region i in system A with the generating set number that participates in power adjustments The regulated quantity Δ G that interior each generating set is exerted oneself_k, and system B in each generating set is exerted oneself in the j of region regulation Amount Δ G_h；

Optimized model corresponding to described target is:

\{\begin{matrix} MinN \\ s . t . Σ_{k = 1}^{K} Δ G_{k} + Σ_{h = 1}^{H} Δ G_{h} = 0 \\ {G_{k}}^{\min} \leq Δ G_{k} + {G_{k}}^{0} \leq {G_{k}}^{\max} \\ {G_{h}}^{\min} \leq Δ G_{h} + {G_{h}}^{0} \leq {G_{h}}^{\max} \\ {G_{k}}^{d} \cdot t \leq Δ G_{k} \leq {G_{k}}^{u} \cdot t \\ {G_{h}}^{d} \cdot t \leq Δ G_{h} \leq {G_{h}}^{u} \cdot t \\ | {P_{l}}^{0} + Δ G_{k} \cdot A_{l - k} | \leq {P_{l}}^{\max} \\ | {P_{l}}^{0} + Δ G_{h} \cdot A_{l - h} | \leq {P_{l}}^{\max} \\ ΣΔ G_{k (k &Element; i)} = Δ P_{Fi} = \frac{Δ P_{A} \cdot | {ACE}_{i} |}{Σ_{A} | ACE |} \\ ΣΔ G_{h (h &Element; j)} = Δ P_{Fj} = \frac{Δ P_{A} \cdot | {ACE}_{j} |}{Σ_{B} | ACE |} \end{matrix};

Wherein Min N be object function,

\{\begin{matrix} s . t . Σ_{k = 1}^{K} Δ G_{k} + Σ_{h = 1}^{H} Δ G_{h} = 0 \\ {G_{k}}^{\min} \leq Δ G_{k} + {G_{k}}^{0} \leq {G_{k}}^{\max} \\ {G_{h}}^{\min} \leq Δ G_{h} + {G_{h}}^{0} \leq {G_{h}}^{\max} \\ {G_{k}}^{d} \cdot t \leq Δ G_{k} \leq {G_{k}}^{u} \cdot t \\ {G_{h}}^{d} \cdot t \leq Δ G_{h} \leq {G_{h}}^{u} \cdot t \\ | {P_{l}}^{0} + Δ G_{k} \cdot A_{l - k} | \leq {P_{l}}^{\max} \\ | {P_{l}}^{0} + Δ G_{h} \cdot A_{l - h} | \leq {P_{l}}^{\max} \\ ΣΔ G_{k (k &Element; i)} = Δ P_{Fi} = \frac{Δ P_{A} \cdot | {ACE}_{i} |}{Σ_{A} | ACE |} \\ ΣΔ G_{h (h &Element; j)} = Δ P_{Fj} = \frac{Δ P_{A} \cdot | {ACE}_{j} |}{Σ_{B} | ACE |} \end{matrix}

For constraints, N for participating in The generating set number of power adjustments, G_k ^minLower limit of exerting oneself, G for generating set k_k ^maxFor going out of generating set k The power upper limit, G_k ⁰For initially the exerting oneself of generating set k, G_k ^dClimbing rate lower limit, G for generating set k_k ^uFor The climbing rate upper limit of generating set k, A_l-kGenerating set k in the i of region is gained merit by the effective power flow for interconnection l The sensitivity exerted oneself, G_h ^minLower limit of exerting oneself, G for generating set h_h ^maxFor generating set h the upper limit of exerting oneself, G_h ⁰For initially the exerting oneself of generating set h, G_h ^dClimbing rate lower limit, G for generating set h_h ^uFor generating set h The climbing rate upper limit, A_l-hFor the effective power flow of interconnection l generating set h in the j of region gained merit exert oneself sensitive Degree, P_l ⁰Initial exchange power, P for interconnection l_l ^maxExchange power limit, t for interconnection l are that power is adjusted The joint time；

Further, each generating set in the i of region is determined in system A with power adjustments shortest time for target The regulated quantity Δ G exerted oneself_k, and system B in each generating set is exerted oneself in the j of region regulated quantity Δ G_h；

Optimized model corresponding to described target is:

\{\begin{matrix} Mint \\ s . t . Σ_{k = 1}^{K} Δ G_{k} + Σ_{h = 1}^{H} Δ G_{h} = 0 \\ {G_{k}}^{\min} \leq Δ G_{k} + {G_{k}}^{0} \leq {G_{k}}^{\max} \\ {G_{h}}^{\min} \leq Δ G_{h} + {G_{h}}^{0} \leq {G_{h}}^{\max} \\ {G_{k}}^{d} \cdot t \leq Δ G_{k} \leq {G_{k}}^{u} \cdot t \\ {G_{h}}^{d} \cdot t \leq Δ G_{h} \leq {G_{h}}^{u} \cdot t \\ | {P_{l}}^{0} + Δ G_{k} \cdot A_{l - k} | \leq {P_{l}}^{\max} \\ | {P_{l}}^{0} + Δ G_{h} \cdot A_{l - h} | \leq {P_{l}}^{\max} \\ ΣΔ G_{k (k &Element; i)} = Δ P_{Fi} = \frac{Δ P_{A} \cdot | {ACE}_{i} |}{Σ_{A} | ACE |} \\ ΣΔ G_{h (h &Element; j)} = Δ P_{Fj} = \frac{Δ P_{A} \cdot | {ACE}_{j} |}{Σ_{B} | ACE |} \end{matrix};

Wherein, Min t be object function,

\{\begin{matrix} s . t . Σ_{k = 1}^{K} Δ G_{k} + Σ_{h = 1}^{H} Δ G_{h} = 0 \\ {G_{k}}^{\min} \leq Δ G_{k} + {G_{k}}^{0} \leq {G_{k}}^{\max} \\ {G_{h}}^{\min} \leq Δ G_{h} + {G_{h}}^{0} \leq {G_{h}}^{\max} \\ {G_{k}}^{d} \cdot t \leq Δ G_{k} \leq {G_{k}}^{u} \cdot t \\ {G_{h}}^{d} \cdot t \leq Δ G_{h} \leq {G_{h}}^{u} \cdot t \\ | {P_{l}}^{0} + Δ G_{k} \cdot A_{l - k} | \leq {P_{l}}^{\max} \\ | {P_{l}}^{0} + Δ G_{h} \cdot A_{l - h} | \leq {P_{l}}^{\max} \\ ΣΔ G_{k (k &Element; i)} = Δ P_{Fi} = \frac{Δ P_{A} \cdot | {ACE}_{i} |}{Σ_{A} | ACE |} \\ ΣΔ G_{h (h &Element; j)} = Δ P_{Fj} = \frac{Δ P_{A} \cdot | {ACE}_{j} |}{Σ_{B} | ACE |} \end{matrix}

For constraints, G_k ^minFor The lower limit of exerting oneself of generating set k, G_k ^maxThe upper limit of exerting oneself, G for generating set k_k ⁰Initial for generating set k Exert oneself, G_k ^dClimbing rate lower limit, G for generating set k_k ^uThe climbing rate upper limit, A for generating set k_l-kFor The effective power flow of interconnection l generating set k in the i of region is gained merit exert oneself sensitivity, G_h ^minFor generating set h Lower limit of exerting oneself, G_h ^maxThe upper limit of exerting oneself, G for generating set h_h ⁰For initially the exerting oneself of generating set h, G_h ^d Climbing rate lower limit, G for generating set h_h ^uThe climbing rate upper limit, A for generating set h_l-hFor having of interconnection l Merit trend generating set h in the j of region is gained merit exert oneself sensitivity, P_l ⁰For interconnection l initial exchange power, P_l ^maxExchange power limit, t for interconnection l are the power adjustments time；

Further, minimum for target to determine system A with the exert oneself absolute value sum of regulated quantity of each generating set The regulated quantity Δ G that in middle region i, each generating set is exerted oneself_k, and system B in the j of region each generating set exert oneself Regulated quantity Δ G_h；

Optimized model corresponding to described target is:

\{\begin{matrix} Min Σ_{k = 1}^{K} | Δ G_{k} | + Σ_{h = 1}^{H} | Δ G_{h} | \\ s . t . Σ_{k = 1}^{K} Δ G_{k} + Σ_{h = 1}^{H} Δ G_{h} = 0 \\ {G_{k}}^{\min} \leq Δ G_{k} + {G_{k}}^{0} \leq {G_{k}}^{\max} \\ {G_{h}}^{\min} \leq Δ G_{h} + {G_{h}}^{0} \leq {G_{h}}^{\max} \\ {G_{k}}^{d} \cdot t \leq Δ G_{k} \leq {G_{k}}^{u} \cdot t \\ {G_{h}}^{d} \cdot t \leq Δ G_{h} \leq {G_{h}}^{u} \cdot t \\ | {P_{l}}^{0} + Δ G_{k} \cdot A_{l - k} | \leq {P_{l}}^{\max} \\ | {P_{l}}^{0} + Δ G_{h} \cdot A_{l - h} | \leq {P_{l}}^{\max} \\ ΣΔ G_{k (k &Element; i)} = Δ P_{Fi} = \frac{Δ P_{A} \cdot | {ACE}_{i} |}{Σ_{A} | ACE |} \\ ΣΔ G_{h (h &Element; j)} = Δ P_{Fj} = \frac{Δ P_{A} \cdot | {ACE}_{j} |}{Σ_{B} | ACE |}; \end{matrix}

Wherein,

Min Σ_{k = 1}^{K} Δ G_{k} + Σ_{h = 1}^{H} Δ G_{h}

For object function,

\{\begin{matrix} s . t . Σ_{k = 1}^{K} Δ G_{k} + Σ_{h = 1}^{H} Δ G_{h} = 0 \\ {G_{k}}^{\min} \leq Δ G_{k} + {G_{k}}^{0} \leq {G_{k}}^{\max} \\ {G_{h}}^{\min} \leq Δ G_{h} + {G_{h}}^{0} \leq {G_{h}}^{\max} \\ {G_{k}}^{d} \cdot t \leq Δ G_{k} \leq {G_{k}}^{u} \cdot t \\ {G_{h}}^{d} \cdot t \leq Δ G_{h} \leq {G_{h}}^{u} \cdot t \\ | {P_{l}}^{0} + Δ G_{k} \cdot A_{l - k} | \leq {P_{l}}^{\max} \\ | {P_{l}}^{0} + Δ G_{h} \cdot A_{l - h} | \leq {P_{l}}^{\max} \\ ΣΔ G_{k (k &Element; i)} = Δ P_{Fi} = \frac{Δ P_{A} \cdot | {ACE}_{i} |}{Σ_{A} | ACE |} \\ ΣΔ G_{h (h &Element; j)} = Δ P_{Fj} = \frac{Δ P_{A} \cdot | {ACE}_{j} |}{Σ_{B} | ACE |} \end{matrix}

For constraint Condition, G_k ^minLower limit of exerting oneself, G for generating set k_k ^maxThe upper limit of exerting oneself, G for generating set k_k ⁰For sending out Initially the exerting oneself of group of motors k, G_k ^dClimbing rate lower limit, G for generating set k_k ^uClimbing for generating set k The rate upper limit, A_l-kFor the effective power flow of interconnection l generating set k in the i of region gained merit exert oneself sensitivity, G_h ^min Lower limit of exerting oneself, G for generating set h_h ^maxThe upper limit of exerting oneself, G for generating set h_h ⁰At the beginning of generating set h Begin exert oneself, G_h ^dClimbing rate lower limit, G for generating set h_h ^uThe climbing rate upper limit, A for generating set h_l-hFor The effective power flow of interconnection l generating set h in the j of region is gained merit exert oneself sensitivity, P_l ⁰At the beginning of interconnection l Begin exchange power, P_l ^maxExchange power limit, t for interconnection l are the power adjustments time；

Further, determine in system A in the i of region so that the coal consumption amount sum of each generating set is minimum for target The regulated quantity Δ G that each generating set is exerted oneself_k, and system B in each generating set is exerted oneself in the j of region regulated quantity ΔG_h；

Optimized model corresponding to described target is:

\{\begin{matrix} Min Σ_{k = 1}^{K} [a_{k} {(Δ G_{k} + {G_{k}}^{0})}^{2} + b_{k} (Δ G_{k} + {G_{k}}^{0}) + c_{k}] + Σ_{h = 1}^{H} [a_{h} {(Δ G_{h} + {G_{h}}^{0})}^{2} + b_{h} (Δ G_{h} + {G_{h}}^{0}) + c_{h}] \\ s . t . Σ_{k = 1}^{K} Δ G_{k} + Σ_{h = 1}^{H} Δ G_{h} = 0 \\ {G_{k}}^{\min} \leq Δ G_{k} + {G_{k}}^{0} \leq {G_{k}}^{\max} \\ {G_{h}}^{\min} \leq Δ G_{h} + {G_{h}}^{0} \leq {G_{h}}^{\max} \\ {G_{k}}^{d} \cdot t \leq Δ G_{k} \leq {G_{k}}^{u} \cdot t \\ {G_{h}}^{d} \cdot t \leq Δ G_{h} \leq {G_{h}}^{u} \cdot t \\ | {P_{l}}^{0} + Δ G_{k} \cdot A_{l - k} | \leq {P_{l}}^{\max} \\ | {P_{l}}^{0} + Δ G_{h} \cdot A_{l - h} | \leq {P_{l}}^{\max} \\ ΣΔ G_{k (k &Element; i)} = Δ P_{Fi} = \frac{Δ P_{A} \cdot | {ACE}_{i} |}{Σ_{A} | ACE |} \\ ΣΔ G_{h (h &Element; j)} = Δ P_{Fj} = \frac{Δ P_{A} \cdot | {ACE}_{j} |}{Σ_{B} | ACE |} \end{matrix}

Wherein,

Min [Σ_{k = 1}^{K} a_{k} {(Δ G_{k} + {G_{k}}^{0})}^{2} + b_{k} (Δ G_{k} + {G_{k}}^{0}) + c_{k}] + [Σ_{h = 1}^{H} a_{h} {(Δ G_{h} + {G_{h}}^{0})}^{2} + b_{h} (Δ G_{h} + {G_{h}}^{0}) + c_{h}]

For target Function,

\{\begin{matrix} s . t . Σ_{k = 1}^{K} Δ G_{k} + Σ_{h = 1}^{H} Δ G_{h} = 0 \\ {G_{k}}^{\min} \leq Δ G_{k} + {G_{k}}^{0} \leq {G_{k}}^{\max} \\ {G_{h}}^{\min} \leq Δ G_{h} + {G_{h}}^{0} \leq {G_{h}}^{\max} \\ {G_{k}}^{d} \cdot t \leq Δ G_{k} \leq {G_{k}}^{u} \cdot t \\ {G_{h}}^{d} \cdot t \leq Δ G_{h} \leq {G_{h}}^{u} \cdot t \\ | {P_{l}}^{0} + Δ G_{k} \cdot A_{l - k} | \leq {P_{l}}^{\max} \\ | {P_{l}}^{0} + Δ G_{h} \cdot A_{l - h} | \leq {P_{l}}^{\max} \\ ΣΔ G_{k (k &Element; i)} = Δ P_{Fi} = \frac{Δ P_{A} \cdot | {ACE}_{i} |}{Σ_{A} | ACE |} \\ ΣΔ G_{h (h &Element; j)} = Δ P_{Fj} = \frac{Δ P_{A} \cdot | {ACE}_{j} |}{Σ_{B} | ACE |} \end{matrix}

For constraints, G_k ^minFor the lower limit of exerting oneself of generating set k, G_k ^maxFor the upper limit of exerting oneself of generating set k, G_k ⁰For initially exerting oneself of generating set k, G_k ^dFor generating set k's Climbing rate lower limit, G_k ^uFor the climbing rate upper limit of generating set k, A_l-kFor the effective power flow of interconnection l to region i Middle generating set k gains merit the sensitivity exerted oneself, G_h ^minFor the lower limit of exerting oneself of generating set h, G_h ^maxFor electromotor The upper limit of exerting oneself of group h, G_h ⁰For initially exerting oneself of generating set h, G_h ^dFor the climbing rate lower limit of generating set h, G_h ^uFor the climbing rate upper limit of generating set h, A_l-hFor the effective power flow of interconnection l to generating set h in the j of region The meritorious sensitivity exerted oneself, a_k、b_k、c_kFor the economic parameters of generating set k, a_h、b_h、c_hFor electromotor The economic parameters of group h, P_l ⁰Initial exchange power, P for interconnection l_l ^maxFor interconnection l exchange power limit, T is the power adjustments time.

Owing to have employed technique scheme, the interconnected network dominant eigenvalues control method that the present invention provides, According to each region, the responsibility that Tie line Power is out-of-limit is determined the region of participation power adjustments, and combines Generating set each in interconnected network is gained merit the sensitivity exerted oneself by the effective power flow of interconnection, and each region District control deviation ACE, is associated power adjustments amount with district control deviation ACE, is eliminating interconnection more While limit, recover the safe operation of the ACE in each region, beneficially electrical network, same in interregional cooperation Time, embody whose responsible fairness doctrine who causes.

Accompanying drawing explanation

Fig. 1 is the flow chart of the method for the invention；

Fig. 2 is that step 3 of the present invention determines the region participating in interconnection l exchange power adjustments in system A Flow chart；

Fig. 3 is that step 3 of the present invention determines the region participating in interconnection l exchange power adjustments in system B Flow chart；

Fig. 4 is the regional compartmentalization schematic diagram of simulated example of the present invention.

Detailed description of the invention

A kind of interconnected network dominant eigenvalues control method as shown in Figure 1, Figure 2 and Figure 3, including walking as follows Rapid:

Further, also there are after step 4 following steps:

Optimized model corresponding to described target is:

\{\begin{matrix} MinN \\ s . t . Σ_{k = 1}^{K} Δ G_{k} + Σ_{h = 1}^{H} Δ G_{h} = 0 \\ {G_{k}}^{\min} \leq Δ G_{k} + {G_{k}}^{0} \leq {G_{k}}^{\max} \\ {G_{h}}^{\min} \leq Δ G_{h} + {G_{h}}^{0} \leq {G_{h}}^{\max} \\ {G_{k}}^{d} \cdot t \leq Δ G_{k} \leq {G_{k}}^{u} \cdot t \\ {G_{h}}^{d} \cdot t \leq Δ G_{h} \leq {G_{h}}^{u} \cdot t \\ | {P_{l}}^{0} + Δ G_{k} \cdot A_{l - k} | \leq {P_{l}}^{\max} \\ | {P_{l}}^{0} + Δ G_{h} \cdot A_{l - h} | \leq {P_{l}}^{\max} \\ ΣΔ G_{k (k &Element; i)} = Δ P_{Fi} = \frac{Δ P_{A} \cdot | {ACE}_{i} |}{Σ_{A} | ACE |} \\ ΣΔ G_{h (h &Element; j)} = Δ P_{Fj} = \frac{Δ P_{A} \cdot | {ACE}_{j} |}{Σ_{B} | ACE |} \end{matrix};

Wherein Min N be object function,

\{\begin{matrix} s . t . Σ_{k = 1}^{K} Δ G_{k} + Σ_{h = 1}^{H} Δ G_{h} = 0 \\ {G_{k}}^{\min} \leq Δ G_{k} + {G_{k}}^{0} \leq {G_{k}}^{\max} \\ {G_{h}}^{\min} \leq Δ G_{h} + {G_{h}}^{0} \leq {G_{h}}^{\max} \\ {G_{k}}^{d} \cdot t \leq Δ G_{k} \leq {G_{k}}^{u} \cdot t \\ {G_{h}}^{d} \cdot t \leq Δ G_{h} \leq {G_{h}}^{u} \cdot t \\ | {P_{l}}^{0} + Δ G_{k} \cdot A_{l - k} | \leq {P_{l}}^{\max} \\ | {P_{l}}^{0} + Δ G_{h} \cdot A_{l - h} | \leq {P_{l}}^{\max} \\ ΣΔ G_{k (k &Element; i)} = Δ P_{Fi} = \frac{Δ P_{A} \cdot | {ACE}_{i} |}{Σ_{A} | ACE |} \\ ΣΔ G_{h (h &Element; j)} = Δ P_{Fj} = \frac{Δ P_{A} \cdot | {ACE}_{j} |}{Σ_{B} | ACE |} \end{matrix}

Optimized model corresponding to described target is:

\{\begin{matrix} Mint \\ s . t . Σ_{k = 1}^{K} Δ G_{k} + Σ_{h = 1}^{H} Δ G_{h} = 0 \\ {G_{k}}^{\min} \leq Δ G_{k} + {G_{k}}^{0} \leq {G_{k}}^{\max} \\ {G_{h}}^{\min} \leq Δ G_{h} + {G_{h}}^{0} \leq {G_{h}}^{\max} \\ {G_{k}}^{d} \cdot t \leq Δ G_{k} \leq {G_{k}}^{u} \cdot t \\ {G_{h}}^{d} \cdot t \leq Δ G_{h} \leq {G_{h}}^{u} \cdot t \\ | {P_{l}}^{0} + Δ G_{k} \cdot A_{l - k} | \leq {P_{l}}^{\max} \\ | {P_{l}}^{0} + Δ G_{h} \cdot A_{l - h} | \leq {P_{l}}^{\max} \\ ΣΔ G_{k (k &Element; i)} = Δ P_{Fi} = \frac{Δ P_{A} \cdot | {ACE}_{i} |}{Σ_{A} | ACE |} \\ ΣΔ G_{h (h &Element; j)} = Δ P_{Fj} = \frac{Δ P_{A} \cdot | {ACE}_{j} |}{Σ_{B} | ACE |} \end{matrix};

Wherein, Min t be object function,

\{\begin{matrix} s . t . Σ_{k = 1}^{K} Δ G_{k} + Σ_{h = 1}^{H} Δ G_{h} = 0 \\ {G_{k}}^{\min} \leq Δ G_{k} + {G_{k}}^{0} \leq {G_{k}}^{\max} \\ {G_{h}}^{\min} \leq Δ G_{h} + {G_{h}}^{0} \leq {G_{h}}^{\max} \\ {G_{k}}^{d} \cdot t \leq Δ G_{k} \leq {G_{k}}^{u} \cdot t \\ {G_{h}}^{d} \cdot t \leq Δ G_{h} \leq {G_{h}}^{u} \cdot t \\ | {P_{l}}^{0} + Δ G_{k} \cdot A_{l - k} | \leq {P_{l}}^{\max} \\ | {P_{l}}^{0} + Δ G_{h} \cdot A_{l - h} | \leq {P_{l}}^{\max} \\ ΣΔ G_{k (k &Element; i)} = Δ P_{Fi} = \frac{Δ P_{A} \cdot | {ACE}_{i} |}{Σ_{A} | ACE |} \\ ΣΔ G_{h (h &Element; j)} = Δ P_{Fj} = \frac{Δ P_{A} \cdot | {ACE}_{j} |}{Σ_{B} | ACE |} \end{matrix}

Optimized model corresponding to described target is:

\{\begin{matrix} Min Σ_{k = 1}^{K} | Δ G_{k} | + Σ_{h = 1}^{H} | Δ G_{h} | \\ s . t . Σ_{k = 1}^{K} Δ G_{k} + Σ_{h = 1}^{H} Δ G_{h} = 0 \\ {G_{k}}^{\min} \leq Δ G_{k} + {G_{k}}^{0} \leq {G_{k}}^{\max} \\ {G_{h}}^{\min} \leq Δ G_{h} + {G_{h}}^{0} \leq {G_{h}}^{\max} \\ {G_{k}}^{d} \cdot t \leq Δ G_{k} \leq {G_{k}}^{u} \cdot t \\ {G_{h}}^{d} \cdot t \leq Δ G_{h} \leq {G_{h}}^{u} \cdot t \\ | {P_{l}}^{0} + Δ G_{k} \cdot A_{l - k} | \leq {P_{l}}^{\max} \\ | {P_{l}}^{0} + Δ G_{h} \cdot A_{l - h} | \leq {P_{l}}^{\max} \\ ΣΔ G_{k (k &Element; i)} = Δ P_{Fi} = \frac{Δ P_{A} \cdot | {ACE}_{i} |}{Σ_{A} | ACE |} \\ ΣΔ G_{h (h &Element; j)} = Δ P_{Fj} = \frac{Δ P_{A} \cdot | {ACE}_{j} |}{Σ_{B} | ACE |}; \end{matrix}

Wherein,

Min Σ_{k = 1}^{K} Δ G_{k} + Σ_{h = 1}^{H} Δ G_{h}

For object function,

\{\begin{matrix} s . t . Σ_{k = 1}^{K} Δ G_{k} + Σ_{h = 1}^{H} Δ G_{h} = 0 \\ {G_{k}}^{\min} \leq Δ G_{k} + {G_{k}}^{0} \leq {G_{k}}^{\max} \\ {G_{h}}^{\min} \leq Δ G_{h} + {G_{h}}^{0} \leq {G_{h}}^{\max} \\ {G_{k}}^{d} \cdot t \leq Δ G_{k} \leq {G_{k}}^{u} \cdot t \\ {G_{h}}^{d} \cdot t \leq Δ G_{h} \leq {G_{h}}^{u} \cdot t \\ | {P_{l}}^{0} + Δ G_{k} \cdot A_{l - k} | \leq {P_{l}}^{\max} \\ | {P_{l}}^{0} + Δ G_{h} \cdot A_{l - h} | \leq {P_{l}}^{\max} \\ ΣΔ G_{k (k &Element; i)} = Δ P_{Fi} = \frac{Δ P_{A} \cdot | {ACE}_{i} |}{Σ_{A} | ACE |} \\ ΣΔ G_{h (h &Element; j)} = Δ P_{Fj} = \frac{Δ P_{A} \cdot | {ACE}_{j} |}{Σ_{B} | ACE |} \end{matrix}

Optimized model corresponding to described target is:

\{\begin{matrix} Min Σ_{k = 1}^{K} [a_{k} {(Δ G_{k} + {G_{k}}^{0})}^{2} + b_{k} (Δ G_{k} + {G_{k}}^{0}) + c_{k}] + Σ_{h = 1}^{H} [a_{h} {(Δ G_{h} + {G_{h}}^{0})}^{2} + b_{h} (Δ G_{h} + {G_{h}}^{0}) + c_{h}] \\ s . t . Σ_{k = 1}^{K} Δ G_{k} + Σ_{h = 1}^{H} Δ G_{h} = 0 \\ {G_{k}}^{\min} \leq Δ G_{k} + {G_{k}}^{0} \leq {G_{k}}^{\max} \\ {G_{h}}^{\min} \leq Δ G_{h} + {G_{h}}^{0} \leq {G_{h}}^{\max} \\ {G_{k}}^{d} \cdot t \leq Δ G_{k} \leq {G_{k}}^{u} \cdot t \\ {G_{h}}^{d} \cdot t \leq Δ G_{h} \leq {G_{h}}^{u} \cdot t \\ | {P_{l}}^{0} + Δ G_{k} \cdot A_{l - k} | \leq {P_{l}}^{\max} \\ | {P_{l}}^{0} + Δ G_{h} \cdot A_{l - h} | \leq {P_{l}}^{\max} \\ ΣΔ G_{k (k &Element; i)} = Δ P_{Fi} = \frac{Δ P_{A} \cdot | {ACE}_{i} |}{Σ_{A} | ACE |} \\ ΣΔ G_{h (h &Element; j)} = Δ P_{Fj} = \frac{Δ P_{A} \cdot | {ACE}_{j} |}{Σ_{B} | ACE |} \end{matrix}

Wherein,

Min [Σ_{k = 1}^{K} a_{k} {(Δ G_{k} + {G_{k}}^{0})}^{2} + b_{k} (Δ G_{k} + {G_{k}}^{0}) + c_{k}] + [Σ_{h = 1}^{H} a_{h} {(Δ G_{h} + {G_{h}}^{0})}^{2} + b_{h} (Δ G_{h} + {G_{h}}^{0}) + c_{h}]

For target Function,

\{\begin{matrix} s . t . Σ_{k = 1}^{K} Δ G_{k} + Σ_{h = 1}^{H} Δ G_{h} = 0 \\ {G_{k}}^{\min} \leq Δ G_{k} + {G_{k}}^{0} \leq {G_{k}}^{\max} \\ {G_{h}}^{\min} \leq Δ G_{h} + {G_{h}}^{0} \leq {G_{h}}^{\max} \\ {G_{k}}^{d} \cdot t \leq Δ G_{k} \leq {G_{k}}^{u} \cdot t \\ {G_{h}}^{d} \cdot t \leq Δ G_{h} \leq {G_{h}}^{u} \cdot t \\ | {P_{l}}^{0} + Δ G_{k} \cdot A_{l - k} | \leq {P_{l}}^{\max} \\ | {P_{l}}^{0} + Δ G_{h} \cdot A_{l - h} | \leq {P_{l}}^{\max} \\ ΣΔ G_{k (k &Element; i)} = Δ P_{Fi} = \frac{Δ P_{A} \cdot | {ACE}_{i} |}{Σ_{A} | ACE |} \\ ΣΔ G_{h (h &Element; j)} = Δ P_{Fj} = \frac{Δ P_{A} \cdot | {ACE}_{j} |}{Σ_{B} | ACE |} \end{matrix}

Interconnected network interconnection quantity of the present invention is L, arbitrary interconnection l connection system A and system B, system A Treat adjusting power total amount Δ P_AAdjusting power total amount Δ P is treated equal to system B_BOpposite number each other；System A includes n Region, system B includes that m region, region i are any region in system A, the number of generating set in the i of region Amount is any region in system B for K, region j, and in the j of region, the quantity of generating set is H；In each region Node can be electromotor node, load bus etc., when interconnection occurs more in limited time, at load level not On the premise of change, needing exerts oneself to generating set again is allocated, and makes trend reasonable layout, with by out-of-limit Tie line Power be withdrawn in safety range；System A is connected by interconnection with system B, definition Tie line Power P_TOutflow system A is positive direction, and inflow system A is negative direction, it is assumed that interconnection is square To out-of-limit 30MW, then supply falls short of demand to mean system B, and system A has carried out unplanned support to it, Returned to by dominant eigenvalues in prescribed limit, then system A needs minimizing 30MW to exert oneself, and system B increases 30MW Exert oneself, regulate like this, Tie line Power can be retracted in theory；Sensitivity A_l-kDescribe generating set Linear pass between the effective power flow that the active power of k node injection and this active power are distributed in interconnection l System；Sensitivity A_l-hDescribe active power and this active power that generating set h node injects in interconnection l Linear relationship between the effective power flow of distribution；Interconnected network arbitrary interconnection l exchange power more limitation Δ P_lPass through Load flow calculation draws；Described interconnection can be extra-high voltage interconnection；Each generating set is exerted oneself the exhausted of regulated quantity Value is the knots modification that each generating set is exerted oneself.

Whom the present invention during each region distribution regulation power, mainly follows and whom causes be responsible in system A or system B The fairness doctrine, simultaneously take account of each region and meet the situation of evaluation index, and take into account the damage of generating set Consumption；In T standard, responsibility degree index isWherein η_iResponsibility for region i Degree, K_iFrequency bias coefficient, K for region i_jFrequency bias coefficient, Δ P for region j_TReal for interconnection l Difference between border exchange power and scheduled net interchange, ACE_iControl deviation, L for region i_pFor interconnection The control accuracy of exchange power；Responsibility degree η is understood by above formula_iWith ACE_i·ΔP_TIt is directly proportional, works as η_i> 0, ACE_i With Δ P_TJack per line (result of product is just), shows that the out-of-limit of Tie line Power is had a responsibility for by region i；When η_i< 0, ACE_iWith Δ P_TContrary sign (result of product is negative), shows the region i recovery to Tie line Power Having contribution, based on the fairness doctrine, power adjustments work should be undertaken by the region causing interconnection out-of-limit, and press According to district control deviation ACE size according to pro rata distribution regulated quantity.

IEEE118 node standard test system is used to emulate as an example below, IEEE118 standard testing System has 118 nodes, 179 circuits.First 118 node systems are carried out region division, divides base In principle be that between each node of intra-zone, between electrical couplings critical node strong, interregional, electrical couplings is weak, Wherein between intra-zone node electrical couplings to show as by force zone radius little, between interregional critical node electrically The weak electrical distance shown as between the critical node of region of coupling is big, and Fig. 4 shows simulated example of the present invention 118 nodes as shown in Figure 4, are divided into system A and system B by regional compartmentalization schematic diagram, and system A comprises 3 Individual region, system B includes 4 regions, is respectively provided with several nodes in each region, and system A, B pass through 6 Bar interconnection is connected, and the upper and lower bound that interconnection 96 wherein exchanges power sets less so that it is out-of-limit； In standard test system, outside dehumidifying stream calculation desired data, give on the exerting oneself of each generating set Limit and lower limit of exerting oneself, generating set economic parameters etc., concurrently set interconnection trend bound, each electromotor The data such as the climbing rate of group.

Under normal circumstances, interconnection all leaves bigger transmission capacity, by each bar interconnection during emulation when using Exchange power upper limit is set to the twice of initial trend, and exchange lower limit is the opposite number of the upper limit, wherein, node The initial trend of the interconnection 96 between 38 and node 65 is-138MW, and exchange power upper limit is set to 110MW, Exchange lower limit is set to-110MW, then interconnection 96 exchanges power more limitation Δ P_lFor-28MW, by all Group of motors regards fired power generating unit, and the climbing rate of steam turbine is the 20% of change rated capacity per minute, the most each Generating set climbing calibration be the generator output upper limit ± 20% (the climbing rate upper limit and climbing rate lower limit).

According to the primary data of standard test system, calculate each regional generation summation in system A and system B, Each region load summation and each area power vacancy；According to the order of magnitude of each area power vacancy, be given Each regional planning exchange performance number, thus obtain the ACE in each region, table 1 gives according to standard testing system The region parameter table that system primary data draws.

The region parameter table that table 1. draws according to standard test system primary data.

Region	Generating summation	Load summation	Power shortage	Scheduled net interchange	ACE
						1	632	768	-136	-100	-36
2	588	298	290	300	-10
						3	67	488	-421	-400	-21
4	1456	1199	257	100	157
						5	629	911	-282	-200	-82
6	966	490	476	400	76
						7	142	326	-184	-100	-84

By the of step 3 3. step judge whether each region participates in the exchange power adjustments of interconnection l, by table 1 Middle data understand, in system A, and ACE₁·ΔP_T、ACE₂·ΔP_TAnd ACE₃·ΔP_TIt is all higher than 0, is therefore In system A, three regions are all out-of-limit responsible to the power of interconnection 96, in systemb, and region 4 correspondence ACE₄·ΔP_T< 0, the ACE of region 6 correspondence₆·ΔP_T< 0, therefore region 4 and the power of region 6 interconnection 96 Out-of-limit responsible, the ACE of region 5 correspondence₅·ΔP_T> 0, the ACE of region 7 correspondence₇·ΔP_T> 0, the most right Out-of-limit in the power of interconnection 96, region 5 and region 7 do not have responsibility, the two region to be not involved in regulation； The dead band threshold value of district control deviation is set to 10MW, as can be known from the table data | ACE₂| it is not more than dead band threshold Value, therefore region 2 be not involved in regulation, by treat adjusting power total amount participate in regulation region in ACE ratio After distribution, obtain the power adjustments amount in each region, as shown in table 2.

The power adjustments amount in each region of table 2..

Region	Power adjustments amount
		1	19
2	0
		3	11
4	-20
		5	0
6	-10
		7	0

The regulation that each generating set is exerted oneself is determined for target so that the generating set number that participates in power adjustments is minimum Amount, specifically, the regulation of exerting oneself of each electromotor node in the region of the exchange power adjustments participating in interconnection 96 Amount is as shown in table 3.

Table 3. participates in the regulated quantity of exerting oneself of each electromotor node in the region of power adjustments.

Be can be seen that by data in table 3,8 generating sets having 4 regions participate in power adjustments, wherein Region 1 and region 6 respectively only have a generating set exert oneself change, and region 3 and region 4 are respectively arranged with 3 Platform generating set participates in regulation, and the regulated quantity that each generating set is exerted oneself and generating set are exerted oneself the upper limit, climbing rate Constraint with Tie line Power limit value has relation.

Table 4 shows prime area control deviation ACE in each region in simulated example_i, and carry out the present invention District control deviation ACE after power adjustments_i', contrast understands and is retracting contact by the control method of the present invention While line is out-of-limit, the recovery for district control deviation is highly beneficial.

Prime area control deviation ACE in each region of table 4._i, and the district control deviation after power adjustments ACE_i' tables of data.

Region	ACE_i	ACE_i′
			1	-36	-17
2	-10	-10
			3	-21	-10
4	157	137
			5	-82	-82
6	76	66
			7	-84	-84

Separately below with power adjustments shortest time, each generating set exert oneself the absolute value sum of regulated quantity minimum, And the coal consumption amount sum of each generating set is minimum carries out the regulated quantity Δ G that each generating set is exerted oneself for target_k、 ΔG_hDetermination, obtain emulating data comparison.

Table 5. carries out each generating set with different target and exerts oneself the emulation data obtained after regulated quantity determines.

Table 6. carries out each generating set with different target and exerts oneself the emulation data (percentage ratio obtained after regulated quantity determines Form).

Data in analytical table 5 and table 6, it is seen then that determine that each generating set is exerted oneself with different target function Regulated quantity Δ G_k、ΔG_h, the impact on consumption is the least, wherein, to participate in the generating set of power adjustments Number minimum for target with each generating set exert oneself the absolute value sum of regulated quantity minimum for consumption during target and Time is essentially identical, but regulating time is longer.Therefore, generally can choose each generating set to exert oneself tune The absolute value sum of joint amount is minimum for target, needs to eliminate immediately more to prescribe a time limit when the situation is critical, can choose power Regulating time is the shortest for target.

By above-mentioned simulation process, it can be seen that the dominant eigenvalues control method that the present invention proposes and strategy root According to each region, the responsibility that dominant eigenvalues is out-of-limit is determined the region of participation power adjustments, and combines interconnection Generating set each in interconnected network is gained merit the sensitivity exerted oneself, and the Region control in each region by effective power flow Deviation ACE, is associated power adjustments amount with district control deviation ACE, while elimination interconnection is out-of-limit, Recover the safe operation of the ACE in each region, beneficially electrical network.

The present invention distributes regulated quantity in units of region, the region causing Tie line Power out-of-limit be responsible for Regulation, the region that responsibility is big undertakes regulation task more, and the district control deviation ACE in region can show each district Territory performs the situation of generation schedule, understands, by ACE, the responsibility size that each region is out-of-limit to interconnection, this Bright eliminate out-of-limit while, the ACE in each region can be recovered to a certain extent, the reasonable benefit/risk of electrical network is transported Row is highly beneficial, sensitivity is combined with control deviation ACE in region, same in interregional cooperation Time, embody whose responsible fairness doctrine who causes.

The above, the only present invention preferably detailed description of the invention, but protection scope of the present invention not office Being limited to this, any those familiar with the art is in the technical scope that the invention discloses, according to this The technical scheme of invention and inventive concept thereof in addition equivalent or change, all should contain the protection in the present invention Within the scope of.

Claims

1. an interconnected network dominant eigenvalues control method, it is characterised in that comprise the steps:

2. difference DELTA P between interconnection l actual exchange power and scheduled net interchange is obtained_T=P_T-P₀, definition Interconnection l actual exchange power P_TOutflow system A is positive direction, and inflow system A is negative direction, wherein P₀For Interconnection scheduled net interchange；

3. to ACE_i·ΔP_TResult compare with 0, if ACE_i·ΔP_T< 0, then region i is not involved in contact Line l exchanges power adjustments, if ACE_i·ΔP_T＞ 0 is the most right | ACE_i| compare with dead band threshold value, if | ACE_i| More than dead band threshold value, then region i participates in interconnection l and exchanges power adjustments；If | ACE_i| less than or equal to dead band door Threshold value, then region i is not involved in interconnection l and exchanges power adjustments；

To ACE_j·ΔP_TResult compare with 0, if ACE_j·ΔP_T＞ 0, then region j is not involved in interconnection L exchanges power adjustments, if ACE_j·ΔP_T< 0, the most right | ACE_j| compare with dead band threshold value, if | ACE_j| big In dead band threshold value, then region j participates in interconnection l and exchanges power adjustments；If | ACE_j| less than or equal to dead band threshold Value, then region j is not involved in interconnection l and exchanges power adjustments；

Step 4: according to formulaDetermine the power adjustments amount Δ P of region i_FiIf power is adjusted Joint amount Δ P_Fi＞ 0, then power adjustments direction is for flowing out region i, if power adjustments amount Δ P_Fi< 0, then power adjustments Direction is inflow region i, wherein Δ P_AAdjusting power total amount, ACE is treated for system A_iRegion control for region i Deviation, ∑_A| ACE | is inclined for the Region control in the region of all participation interconnection l exchange power adjustments in system A Difference sum；

According to formulaDetermine the power adjustments amount Δ P of region j_FjIf, power adjustments amount ΔP_Fj＞ 0, then power adjustments direction is for flowing out region j, if power adjustments amount Δ P_Fj< 0, then power adjustments side To for inflow region j, wherein Δ P_BAdjusting power total amount, ACE is treated for system B_jRegion control for region j Deviation, ∑_B| ACE | is inclined for the Region control in the region of all participation interconnection l exchange power adjustments in system B Difference sum.

Interconnected network dominant eigenvalues control method the most according to claim 1, it is characterised in that in step Also there are after rapid 4 following steps:

Step 6: determine the regulated quantity Δ G that in system A, in the i of region, each generating set is exerted oneself_k, and in system B The regulated quantity Δ G that in the j of region, each generating set is exerted oneself_h, wherein k=1,2 ... K, h=1,2 ... H.

Interconnected network dominant eigenvalues control method the most according to claim 2, it is characterised in that with ginseng Minimum with the generating set number of power adjustments determine in system A that each generating set in the i of region is exerted oneself for target Regulated quantity Δ G_k, and system B in each generating set is exerted oneself in the j of region regulated quantity Δ G_h；

Optimized model corresponding to described target is:

Wherein N is to participate in the generating set number of power adjustments, G_k ^minLower limit of exerting oneself, G for generating set k_k ^max The upper limit of exerting oneself, G for generating set k_k ⁰For initially the exerting oneself of generating set k, G_k ^dFor climbing of generating set k Ratio of slope lower limit, G_k ^uThe climbing rate upper limit, A for generating set k_l-kFor the effective power flow of interconnection l in the i of region Generating set k gain merit exert oneself sensitivity, G_h ^minLower limit of exerting oneself, G for generating set h_h ^maxFor generating set The upper limit of exerting oneself of h, G_h ⁰For initially the exerting oneself of generating set h, G_h ^dClimbing rate lower limit, G for generating set h_h ^u The climbing rate upper limit, A for generating set h_l-hGenerating set h in the j of region is had by the effective power flow for interconnection l Sensitivity that merit is exerted oneself, P_l ⁰Initial exchange power, P for interconnection l_l ^maxExchange power for interconnection l limits Value, t are the power adjustments time.

Interconnected network dominant eigenvalues control method the most according to claim 2, it is characterised in that with merit Rate regulating time is the shortest determines the regulated quantity Δ G that in system A, in the i of region, each generating set is exerted oneself for target_k、 And the regulated quantity Δ G that in system B, in the j of region, each generating set is exerted oneself_h；

Optimized model corresponding to described target is:

Wherein G_k ^minLower limit of exerting oneself, G for generating set k_k ^maxThe upper limit of exerting oneself, G for generating set k_k ⁰For Initially the exerting oneself of generating set k, G_k ^dClimbing rate lower limit, G for generating set k_k ^uFor climbing of generating set k The ratio of slope upper limit, A_l-kFor the effective power flow of interconnection l generating set k in the i of region gained merit exert oneself sensitivity, G_h ^minLower limit of exerting oneself, G for generating set h_h ^maxThe upper limit of exerting oneself, G for generating set h_h ⁰For generating set h Initially exert oneself, G_h ^dClimbing rate lower limit, G for generating set h_h ^uThe climbing rate upper limit, A for generating set h_l-h For the effective power flow of interconnection l generating set h in the j of region gained merit exert oneself sensitivity, P_l ⁰For interconnection l's Initial exchange power, P_l ^maxExchange power limit, t for interconnection l are the power adjustments time.

Interconnected network dominant eigenvalues control method the most according to claim 2, it is characterised in that with respectively Generating set exert oneself the absolute value sum of regulated quantity minimum for target to determine in system A each electromotor in the i of region The regulated quantity Δ G that group is exerted oneself_k, and system B in each generating set is exerted oneself in the j of region regulated quantity Δ G_h；

Optimized model corresponding to described target is:

Interconnected network dominant eigenvalues control method the most according to claim 2, it is characterised in that with respectively The coal consumption amount sum of generating set is minimum determines the tune that in system A, in the i of region, each generating set is exerted oneself for target Joint amount Δ G_k, and system B in each generating set is exerted oneself in the j of region regulated quantity Δ G_h；

Optimized model corresponding to described target is:

\{\begin{matrix} \begin{matrix} M i n & Σ_{k = 1}^{K} [a_{k} {({ΔG}_{k} + {G_{k}}^{0})}^{2} + b_{k} ({ΔG}_{k} + {G_{k}}^{0}) + c_{k}] + Σ_{h = 1}^{H} [a_{h} {({ΔG}_{h} + {G_{h}}^{0})}^{2} + b_{h} ({ΔG}_{h} + {G_{h}}^{0}) + c_{h}] \\ s . t . & Σ_{k = 1}^{K} {ΔG}_{k} + Σ_{h = 1}^{H} {ΔG}_{h} = 0 \end{matrix} \\ \begin{matrix} {G_{k}}^{\min} \leq {ΔG}_{k} + {G_{k}}^{0} \leq {G_{k}}^{\max} \\ {G_{h}}^{\min} \leq {ΔG}_{h} + {G_{h}}^{0} \leq {G_{h}}^{\max} \\ {G_{k}}^{d} \cdot t \leq {ΔG}_{k} \leq {G_{k}}^{u} \cdot t \\ {G_{h}}^{d} \cdot t \leq {ΔG}_{h} \leq {G_{h}}^{u} \cdot t \\ | P_{l}^{0} + {ΔG}_{k} \cdot A_{l - k} | \leq P_{l}^{\max} \\ | P_{l}^{0} + {ΔG}_{h} \cdot A_{l - h} | \leq P_{l}^{\max} \\ Σ {ΔG}_{k (k &Element; i)} = {ΔP}_{F i} = \frac{{ΔP}_{A} \cdot | {ACE}_{i} |}{Σ_{A} | A C E |} \\ Σ {ΔG}_{h (h &Element; j)} = {ΔP}_{F j} = \frac{{ΔP}_{B} \cdot | {ACE}_{j} |}{Σ_{B} | A C E |} \end{matrix} \end{matrix}

Wherein G_k ^minFor the lower limit of exerting oneself of generating set k, G_k ^maxFor the upper limit of exerting oneself of generating set k, G_k ⁰For Generating set k initially exerts oneself, G_k ^dFor the climbing rate lower limit of generating set k, G_k ^uFor climbing of generating set k The ratio of slope upper limit, A_l-kGenerating set k in the i of region gained merit the sensitivity exerted oneself for the effective power flow of interconnection l, G_h ^minFor the lower limit of exerting oneself of generating set h, G_h ^maxFor the upper limit of exerting oneself of generating set h, G_h ⁰For generating set h Initially exert oneself, G_h ^dFor the climbing rate lower limit of generating set h, G_h ^uFor the climbing rate upper limit of generating set h, A_l-h Generating set h in the j of region gained merit the sensitivity exerted oneself for the effective power flow of interconnection l, a_k、b_k、c_kFor sending out The economic parameters of group of motors k, a_h、b_h、c_hFor the economic parameters of generating set h, P_l ⁰At the beginning of interconnection l Begin exchange power, P_l ^maxExchange power limit, t for interconnection l are the power adjustments time.