CN107086568A - A kind of optimal support unit localization method of power system decomposed based on forecast failure - Google Patents
A kind of optimal support unit localization method of power system decomposed based on forecast failure Download PDFInfo
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- CN107086568A CN107086568A CN201710347116.6A CN201710347116A CN107086568A CN 107086568 A CN107086568 A CN 107086568A CN 201710347116 A CN201710347116 A CN 201710347116A CN 107086568 A CN107086568 A CN 107086568A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/001—Methods to deal with contingencies, e.g. abnormalities, faults or failures
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Abstract
The invention discloses a kind of optimal support unit localization method of power system decomposed based on forecast failure.For electric power grid frequency stabilization, some units that decisive role is played to electricity net safety stable need to be chosen.The present invention considers the different forecast failures of power network, sets up to minimize power system security constrained optimum tide model of the generating set climbing capacity as target；Use forecast failure decomposition method by the model decomposition for normal operating mode under subproblem under primal problem and each forecast failure method of operation；The solution of above-mentioned security constraint optimal load flow model is realized by the subproblem under the primal problem under iterative normal operating mode and each forecast failure method of operation；The minimum generating set climbing capacity transformation amount of gained is solved according to step, the generating set of transformation amount non-zero is subjected to sort descending accordingly, the optimal support unit of decreasing priority is designated as successively in order, exports as a result.The present invention has preferable applicability, preferably meets actual demand.
Description
Technical field
The invention belongs to technical field of power systems, specifically a kind of power system decomposed based on forecast failure is most
Excellent support unit localization method.
Background technology
Current power builds fast-developing, one side various regions power source construction projects still rapid growth, wind-powered electricity generation, the proportion of nuclear power
Rise year by year；On the other hand a plurality of extra high voltage line is built up, it is transregional come capacitance accounting improve constantly.While national economy is
Structural adjustment is carried out, society's electricity consumption structure there occurs larger change therewith.The increasingly increase of power network daily load curve, thermoelectricity
Unit is declined to a great extent using hourage, and when unit operation load reduction, unit heat consumption is substantially increased, unit efficiency significantly under
Drop.Therefore when fired power generating unit is declined to a great extent using hourage, the underrun of Large-scale fire-electricity unit long-time turns into electricity market
New normality when, it is necessary to consider the fm capacity of large-scale thermal power machine group.
Under the demand background, thermal power generation unit requirement ensures the safety of oneself first, while occurring in major network different
Ability with certain aid in treatment accident during reason condition.Primary frequency function exactly thermal power generation unit occurs different in power network
The spinning reserve capacity quick response frequency of steam turbine and boiler heat storage and unit is made full use of to change in the case of often, to make up electricity
Net generates electricity with load difference away from electric power grid frequency stabilization.Therefore, some machines that decisive role is played to electricity net safety stable need to be chosen
Group, is used as the subject of implementation of above-mentioned support function.
The content of the invention
In consideration of it, it is an object of the present invention to according to the different power networks in the case of each extra-high voltage landing point failure in power network
Response characteristic, the position of the optimal power supply strong point in each region when providing electric network fault according to region, to determine depth frequency modulation
The optimal unit optimum selection supported, is the transformation target of frequency modulation function as possessing height plus going out.
The present invention is realized using following scheme：It is a kind of to be positioned based on the optimal unit of supporting of power system that forecast failure is decomposed
Method, it is characterised in that comprise the following steps：
Step 1)：Load the steady-state load flow data of power system, the security constraint data of generator, bus and circuit, hair
Motor climbing capacity data and power network forecast failure set data；
Step 2)：Load flow calculation under power network normal mode, obtains initial launch point；
Step 3)：Based on step 1) -2) the data obtained, set up to minimize electric power of the generating set climbing capacity as target
System security constraint optimal load flow model；
Step 4)：Based on step 3) gained model, use forecast failure decomposition method by the model decomposition for normal operation
Primal problem and the subproblem under each forecast failure method of operation, solve the primal problem under normal operating mode under mode；
Step 5)：Based on step 4) acquired results, the subproblem under each forecast failure method of operation is solved successively, and is generated
Corresponding additional inequality constraints, adds step 4) described in primal problem in；
Step 6)：Calculate step 4 in adjacent two-wheeled iteration) solve primal problem optimum results increment size, if its
Less than given threshold value, then to step 7)；Otherwise return to step 5) continue iterative；
Step 7)：According to step 4) the minimum generating set climbing capacity transformation amount of gained, by the generator of transformation amount non-zero
Group carries out sort descending accordingly, is designated as the optimal support unit of decreasing priority successively in order, exports as a result.
Further, the step 3) particular content be：To minimize generating set climbing capacity transformation amount as optimization
Power flow equation after target, and the transformation of generating set climbing capacity under power network normal operating mode and all forecast failure modes
For equality constraint, with the generator Climing constant under power network normal operating mode and all forecast failure methods of operation, generator
Active power output constraint, generator reactive units limits, node voltage amplitude, which are constrained, and circuit is thermally-stabilised is constrained to inequality constraints,
Set up one group of Non-linear Optimal Model.
Further, described Non-linear Optimal Model is specific as follows：
1) object function
In formula,The respectively transformation amount of the positive and negative climbing capacities of generating set i；For normal operation side
The active power output of balancing generator group under formula；wi, p is respectively the weight coefficient of climbing capacity transformation amount and network loss；SGFor generator
The set of group；
2) equality constraint
Equality constraint is the power flow equation under different running method：
In formula, variable subscript represents the method for operation, wherein 0 represents normal operating mode, other represent forecast failure operation
Mode；SkFor the set of the forecast failure method of operation；SBFor the set of bus；
UiFor bus i voltage magnitude, i ∈ SB；UjFor bus j voltage magnitude；PGi, QGiRespectively generating set i's
It is active and it is idle exert oneself, i ∈ SG；PLi, QLiRespectively bus i active and load or burden without work, i ∈ SG；δijFor between bus ij
Phase angle difference；λkFor the load growth factor under method of operation k, for describing the fluctuation of load and its with the growth of national economy；The real and imaginary parts of corresponding element respectively in bus admittance matrix；
3) inequality constraints
Inequality constraints includes generating set Climing constant
In formula,The original positive and negative climbing capacities of respectively generating set i；Issued for normal operating mode
Group of motors i active power output,For the active power output of generating set i under method of operation k；
And other operation constraints, including node voltage constraint, generated power and idle units limits and Line Flow
Constraint
In formula, FijFor the trend between bus i to bus j on circuit；The upper and lower line of each variable is represented to strain respectively
The upper and lower bound of amount.
Further, the step 4) particular content be：By step 3) Non-linear Optimal Model set up is decomposed into 1
The primal problem of individual correspondence normal operating mode and the subproblem of some forecast failure methods of operation of correspondence.
Further, the particular content of primal problem is：
1) object function
In formula,The respectively transformation amount of the positive and negative climbing capacities of generating set i；For normal operation side
The active power output of balancing generator group under formula；wi, p is respectively the weight coefficient of climbing capacity transformation amount and network loss；SGFor generator
The set of group；
2) equality constraint
Equality constraint is the power flow equation under normal operating mode
In formula, variable subscript 0 represents normal operating mode, SBFor the set of bus；
UiFor bus i voltage magnitude, i ∈ SB；UjFor bus j voltage magnitude；PGi, QGiRespectively generating set i's
It is active and it is idle exert oneself, i ∈ SG；PLi, QLiRespectively bus i active and load or burden without work, i ∈ SG；δijFor between bus ij
Phase angle difference；λ0For the load growth factor under normal operating mode, for describing the fluctuation of load and its with the increasing of national economy
It is long；Gij, BijThe real and imaginary parts of corresponding element respectively in bus admittance matrix；
3) inequality constraints
Inequality constraints includes node voltage constraint, generated power and idle units limits, Line Flow constraint：
In formula, FijFor the trend between bus i to bus j on circuit；The upper and lower line of each variable is represented to strain respectively
The upper and lower bound of amount.
The step 5) in, the particular content of subproblem is corresponding to k-th of forecast failure：
1) object function
In formula,The positive and negative climbing capacity slack variables of respectively generating set i；
2) equality constraint
Equality constraint is the power flow equation under forecast failure method of operation k
In formula, SBFor the set of bus；UiFor bus i voltage magnitude, i ∈ SB；UjFor bus j voltage magnitude；PGi,
QGiThe active and idle of respectively generating set i is exerted oneself, i ∈ SG；PLi, QLiRespectively bus i active and load or burden without work, i ∈
SG；δijFor the phase angle difference between bus ij；λkFor the load growth factor under method of operation k, for describe load fluctuation and
Its with national economy growth； The real and imaginary parts of corresponding element respectively in bus admittance matrix；
3) inequality constraints
Inequality constraints includes the unit ramp loss after relaxation
In formula,The original positive and negative climbing capacities of respectively generating set i；
Unit climbing capacity slack variable is constrained：
And other operation constraints, including the constraint of forecast failure method of operation k lower nodes voltage, generated power and idle
Units limits and Line Flow constraint：
In formula, FijFor the trend between bus i to bus j on circuit；The upper and lower line of each variable is represented to strain respectively
The upper and lower bound of amount.
Further, optimization problem corresponding to above-mentioned forecast failure method of operation k is solved, if optimization aim J non-zeros, give birth to
Into following inequality constraints, add step 4) in primal problem inequality constraints in：
In formula, u0,To control variable (including busbar voltage amplitude etc.) and step 4 under normal operating mode) in ask
The numerical value for the corresponding control variable that solution primal problem is obtained；T represents transposition；
Respectively step 4) in solve the transformations of the positive and negative climbing capacities of generating set i that primal problem is obtained
The numerical value of amount；
μ,The respectively dual variable of equality constraint, the inequality that the constraint of climbing capacity lower limit and the upper limit are constrained is about
The dual variable of beam.
By implementing above-mentioned steps, the unit that decisive role is played to electricity net safety stable can be accurately positioned, phase is set up
The priority orders of unit are answered, the optimal support unit in the case of power network different faults are located, and give unit climbing energy
The optimal modification scheme of power, the security feature after electric network fault is met with minimum cost.
Brief description of the drawings
Fig. 1 is FB(flow block) of the invention.
Embodiment
Below in conjunction with the accompanying drawings and embodiment the present invention will be further described.
The present embodiment provides a kind of method of electrical power system transient catastrophe failure screening, as shown in figure 1, including following step
Suddenly：
Step (1)：Load the steady-state load flow data of power system, the security constraint number of the element such as generator, bus, circuit
According to, existing generator climbing capacity data, and power network forecast failure set data；
Step (2)：Load flow calculation under power network normal mode, obtains initial launch point；
Step (3)：Based on step (1)-(2) the data obtained, set up to minimize generating set climbing capacity as target
Power system security constrained optimum tide model；
Step (4)：Based on model obtained by step (3), use forecast failure decomposition method by the model decomposition for normal fortune
Primal problem and the subproblem under each forecast failure method of operation under line mode；Solve the primal problem under normal operating mode；
Step (5)：Based on step (4) acquired results, the subproblem under each forecast failure method of operation is solved successively, and it is raw
Into corresponding additional inequality constraints, add in step (4) described primal problem；
Step (6)：The increment size that step (4) in adjacent 2 wheel iteration solves the optimum results of primal problem is calculated, if its
Less than given threshold value, then to step (7)；Otherwise return to step (5) continues iterative；
Step (7)：According to minimum generating set climbing capacity transformation amount obtained by step (4), by the generating of transformation amount non-zero
Unit carries out sort descending accordingly, is designated as the optimal support unit of decreasing priority successively in order, exports as a result.
In the present embodiment, the step (3) is specifically, to minimize generating set climbing capacity transformation amount as optimization mesh
Mark, the power flow equation in terms of and after the transformation of generating set climbing capacity under power network normal operating mode and all forecast failure modes
For equality constraint, with the generator Climing constant under power network normal operating mode and all forecast failure methods of operation, generator
The security constraints such as active power output constraint, the constraint of generator reactive units limits, node voltage amplitude, the thermally-stabilised constraint of circuit is not
Equality constraint, sets up one group of Non-linear Optimal Model, specific as follows：
1) object function
In formula,The respectively transformation amount of the positive and negative climbing capacities of generating set i；For normal operation side
The active power output of balancing generator group under formula；wi, p is respectively the weight coefficient of climbing capacity transformation amount and network loss；SGFor generator
The set of group.
2) equality constraint
Equality constraint is the power flow equation under different running method
In formula, variable subscript represents the method for operation, wherein 0 represents normal operating mode, other represent forecast failure operation
Mode；SkFor the set of the forecast failure method of operation；SBFor the set of bus；
UiFor bus i voltage magnitude, i ∈ SB；UjFor bus j voltage magnitude；PGi, QGiRespectively generating set i's
It is active and it is idle exert oneself, i ∈ SG；PLi, QLiRespectively bus i active and load or burden without work, i ∈ SG；δijFor between bus ij
Phase angle difference；λkFor the load growth factor under method of operation k, for describing the fluctuation of load and its with the growth of national economy；The real and imaginary parts of corresponding element respectively in bus admittance matrix.
3) inequality constraints
Inequality constraints includes unit ramp loss
In formula,The original positive and negative climbing capacities of respectively generating set i；Issued for normal operating mode
Group of motors i active power output,For the active power output of generating set i under method of operation k；
And other operation constraints, including node voltage constraint, generated power and idle units limits, Line Flow are about
Beam etc.：
In formula, FijFor the trend between bus i to bus j on circuit；The upper and lower line of each variable is represented to strain respectively
The upper and lower bound of amount.
In the present embodiment, the step (4) is specially：The Non-linear Optimal Model that step (3) is set up is decomposed into 1
The primal problem of individual correspondence normal operating mode and the subproblem of some forecast failure methods of operation of correspondence.Wherein, primal problem is specific
For：
1) object function
In formula, variable implication is same as described above.
2) equality constraint
Equality constraint is the power flow equation under normal operating mode
In formula, variable subscript 0 represents normal operating mode, SBFor the set of bus；
UiFor bus i voltage magnitude, i ∈ SB；UjFor bus j voltage magnitude；PGi, QGiRespectively generating set i's
It is active and it is idle exert oneself, i ∈ SG；PLi, QLiRespectively bus i active and load or burden without work, i ∈ SG；δijFor between bus ij
Phase angle difference；λ0For the load growth factor under normal operating mode, for describing the fluctuation of load and its with the increasing of national economy
It is long；Gij, BijThe real and imaginary parts of corresponding element respectively in bus admittance matrix.
3) inequality constraints
Inequality constraints includes node voltage constraint, generated power and idle units limits, Line Flow constraint etc.：
In formula, FijFor the trend between bus i to bus j on circuit；The upper and lower line of each variable is represented to strain respectively
The upper and lower bound of amount；
And a series of inequality constraints generated by step (5).
In the present embodiment, the step (5) is specially：Subproblem corresponding to k-th of forecast failure is specially：
1) object function
In formula,The positive and negative climbing capacity slack variables of respectively generating set i；
2) equality constraint
Equality constraint is the power flow equation under forecast failure method of operation k.
In formula, SBFor the set of bus；UiFor bus i voltage magnitude, i ∈ SB；UjFor bus j voltage magnitude；PGi,
QGiThe active and idle of respectively generating set i is exerted oneself, i ∈ SG；PLi, QLiRespectively bus i active and load or burden without work, i ∈
SG；δijFor the phase angle difference between bus ij；λkFor the load growth factor under method of operation k, for describe load fluctuation and
Its with national economy growth； The real and imaginary parts of corresponding element respectively in bus admittance matrix.
3) inequality constraints
Inequality constraints includes the unit ramp loss after relaxation
In formula,The original positive and negative climbing capacities of respectively generating set i；
Unit climbing capacity slack variable is constrained：
And other operation constraints, including the constraint of forecast failure method of operation k lower nodes voltage, generated power and idle
Units limits, Line Flow constraint etc.：
In formula, FijFor the trend between bus i to bus j on circuit；The upper and lower line of each variable is represented to strain respectively
The upper and lower bound of amount.
Optimization problem corresponding to above-mentioned forecast failure method of operation k is solved, if optimization aim J non-zeros, generation is following not
Equality constraint, is added in step (4) in the inequality constraints set of primal problem：
In formula, u0,To control variable and step 4 under normal operating mode) in solve that primal problem obtains it is corresponding
Control the numerical value of variable；T represents transposition；
Respectively step 4) in solve the transformations of the positive and negative climbing capacities of generating set i that primal problem is obtained
The numerical value of amount；
μ,The respectively dual variable of equality constraint, the inequality that the constraint of climbing capacity lower limit and the upper limit are constrained is about
The dual variable of beam.
By implementing above-mentioned steps, the optimal modification scheme of unit climbing capacity is given, and it is full with minimum cost accordingly
Security feature after foot electric network fault.As a result, above-mentioned specific implementation step give it is optimal under power network different faults
Support unit.
It the foregoing is only presently preferred embodiments of the present invention, all equalizations done according to claims of the present invention protection domain
Change and modification, should all belong to the covering scope of the present invention.
Claims (7)
1. a kind of optimal support unit localization method of power system decomposed based on forecast failure, it is characterised in that including following step
Suddenly：
Step 1)：Load the steady-state load flow data of power system, the security constraint data of generator, bus and circuit, generator
Climbing capacity data and power network forecast failure set data；
Step 2)：Load flow calculation under power network normal mode, obtains initial launch point；
Step 3)：Based on step 1) -2) the data obtained, set up to minimize power system of the generating set climbing capacity as target
Security constraint optimal load flow model；
Step 4)：Based on step 3) gained model, use forecast failure decomposition method by the model decomposition for normal operating mode
Lower primal problem and the subproblem under each forecast failure method of operation, solve the primal problem under normal operating mode；
Step 5)：Based on step 4) acquired results, the subproblem under each forecast failure method of operation is solved successively, and is generated corresponding
Additional inequality constraints, add step 4) described in primal problem in；
Step 6)：Calculate step 4 in adjacent two-wheeled iteration) solve primal problem optimum results increment size, if it is less than
Given threshold value, then to step 7)；Otherwise return to step 5) continue iterative；
Step 7)：According to step 4) the minimum generating set climbing capacity transformation amount of gained, by the generating set evidence of transformation amount non-zero
This carries out sort descending, is designated as the optimal support unit of decreasing priority successively in order, exports as a result.
2. the power system optimal support unit localization method according to claim 1 decomposed based on forecast failure, it is special
Levy and be,
The step 3) particular content be：To minimize generating set climbing capacity transformation amount as optimization aim, and generate electricity
Power flow equation after the transformation of unit climbing capacity under power network normal operating mode and all forecast failure modes is equality constraint, with
Power network normal operating mode and generator Climing constant under all forecast failure methods of operation, generated power units limits,
Generator reactive units limits, node voltage amplitude, which are constrained, and circuit is thermally-stabilised is constrained to inequality constraints, sets up one group of non-thread
Property Optimized model.
3. the power system optimal support unit localization method according to claim 2 decomposed based on forecast failure, it is special
Levy and be,
Described Non-linear Optimal Model is specific as follows：
1) object function
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2) equality constraint
Equality constraint is the power flow equation under different running method：
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</mrow>
In formula, variable subscript represents the method for operation, wherein 0 represents normal operating mode, other represent the forecast failure method of operation；
SkFor the set of the forecast failure method of operation；SBFor the set of bus；
UiFor bus i voltage magnitude, i ∈ SB；UjFor bus j voltage magnitude；PGi, QGiRespectively generating set i active and
It is idle to exert oneself, i ∈ SG；PLi, QLiRespectively bus i active and load or burden without work, i ∈ SG；δijFor the phase angle difference between bus ij；
λkFor the load growth factor under method of operation k, for describing the fluctuation of load and its with the growth of national economy；
The real and imaginary parts of corresponding element respectively in bus admittance matrix；
3) inequality constraints
Inequality constraints includes generating set Climing constant
<mrow>
<msubsup>
<mi>&Pi;</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mo>-</mo>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>&Delta;&Pi;</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mo>-</mo>
</msubsup>
<mo>&le;</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mi>k</mi>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mn>0</mn>
</msubsup>
<mo>&le;</mo>
<msubsup>
<mi>&Pi;</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mo>+</mo>
</msubsup>
<mo>+</mo>
<msubsup>
<mi>&Delta;&Pi;</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mo>+</mo>
</msubsup>
<mo>,</mo>
<mi>i</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>G</mi>
</msub>
<mo>,</mo>
<mi>k</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>k</mi>
</msub>
<mo>,</mo>
</mrow>
In formula,The original positive and negative climbing capacities of respectively generating set i；For generator under normal operating mode
Group i active power output,For the active power output of generating set i under method of operation k；
And other operation constraints, including node voltage constraint, generated power and idle units limits and Line Flow constraint
<mrow>
<msubsup>
<munder>
<mi>U</mi>
<mo>&OverBar;</mo>
</munder>
<mi>i</mi>
<mi>k</mi>
</msubsup>
<mo>&le;</mo>
<msubsup>
<mi>U</mi>
<mi>i</mi>
<mi>k</mi>
</msubsup>
<mo>&le;</mo>
<msubsup>
<mover>
<mi>U</mi>
<mo>&OverBar;</mo>
</mover>
<mi>i</mi>
<mi>k</mi>
</msubsup>
<mo>,</mo>
<mi>i</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>B</mi>
</msub>
<mo>,</mo>
<mi>k</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>k</mi>
</msub>
<mo>,</mo>
</mrow>
<mrow>
<msub>
<munder>
<mi>P</mi>
<mo>&OverBar;</mo>
</munder>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
</msub>
<mo>&le;</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mi>k</mi>
</msubsup>
<mo>&le;</mo>
<msub>
<mover>
<mi>P</mi>
<mo>&OverBar;</mo>
</mover>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
</msub>
<mo>,</mo>
<mi>i</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>G</mi>
</msub>
<mo>,</mo>
<mi>k</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>k</mi>
</msub>
<mo>,</mo>
</mrow>
<mrow>
<msub>
<munder>
<mi>Q</mi>
<mo>&OverBar;</mo>
</munder>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
</msub>
<mo>&le;</mo>
<msubsup>
<mi>Q</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mi>k</mi>
</msubsup>
<mo>&le;</mo>
<msub>
<mover>
<mi>Q</mi>
<mo>&OverBar;</mo>
</mover>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
</msub>
<mo>,</mo>
<mi>i</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>G</mi>
</msub>
<mo>,</mo>
<mi>k</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>k</mi>
</msub>
<mo>,</mo>
</mrow>
<mrow>
<msub>
<munder>
<mi>F</mi>
<mo>&OverBar;</mo>
</munder>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>&le;</mo>
<msubsup>
<mi>F</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mi>k</mi>
</msubsup>
<mo>&le;</mo>
<msub>
<mover>
<mi>F</mi>
<mo>&OverBar;</mo>
</mover>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>,</mo>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>B</mi>
</msub>
<mo>,</mo>
<mi>k</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>k</mi>
</msub>
<mo>,</mo>
</mrow>
In formula, FijFor the trend between bus i to bus j on circuit；The upper and lower line of each variable is represented to dependent variable respectively
Upper and lower bound.
4. the power system optimal support unit localization method according to claim 3 decomposed based on forecast failure, it is special
Levy and be,
The step 4) particular content be：By step 3) Non-linear Optimal Model set up is decomposed into 1 correspondence and normally transports
The primal problem of line mode and the subproblem of some forecast failure methods of operation of correspondence.
5. the power system optimal support unit localization method according to claim 4 decomposed based on forecast failure, it is special
Levy and be,
The particular content of primal problem is：
1) object function
<mrow>
<mi>m</mi>
<mi>i</mi>
<mi>n</mi>
<mrow>
<mo>(</mo>
<munder>
<mi>&Sigma;</mi>
<mrow>
<mi>i</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>G</mi>
</msub>
</mrow>
</munder>
<msub>
<mi>w</mi>
<mi>i</mi>
</msub>
<mo>(</mo>
<mrow>
<msubsup>
<mi>&Delta;&Pi;</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mo>+</mo>
</msubsup>
<mo>+</mo>
<msubsup>
<mi>&Delta;&Pi;</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mo>-</mo>
</msubsup>
</mrow>
<mo>)</mo>
<mo>+</mo>
<msubsup>
<mi>pP</mi>
<mrow>
<mi>G</mi>
<mi>s</mi>
</mrow>
<mn>0</mn>
</msubsup>
<mo>)</mo>
</mrow>
<mo>,</mo>
</mrow>
In formula,The respectively transformation amount of the positive and negative climbing capacities of generating set i；For under normal operating mode
The active power output of balancing generator group；wi, p is respectively the weight coefficient of climbing capacity transformation amount and network loss；SGFor generating set
Set；
2) equality constraint
Equality constraint is the power flow equation under normal operating mode
<mrow>
<mrow>
<mo>(</mo>
<mrow>
<mn>1</mn>
<mo>+</mo>
<msup>
<mi>&lambda;</mi>
<mn>0</mn>
</msup>
</mrow>
<mo>)</mo>
</mrow>
<msubsup>
<mi>P</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mn>0</mn>
</msubsup>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mrow>
<mn>1</mn>
<mo>+</mo>
<msup>
<mi>&lambda;</mi>
<mn>0</mn>
</msup>
</mrow>
<mo>)</mo>
</mrow>
<msubsup>
<mi>P</mi>
<mrow>
<mi>L</mi>
<mi>i</mi>
</mrow>
<mn>0</mn>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>U</mi>
<mi>i</mi>
<mn>0</mn>
</msubsup>
<munder>
<mi>&Sigma;</mi>
<mrow>
<mi>j</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>B</mi>
</msub>
</mrow>
</munder>
<msubsup>
<mi>U</mi>
<mi>j</mi>
<mn>0</mn>
</msubsup>
<mrow>
<mo>(</mo>
<mrow>
<msubsup>
<mi>G</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mn>0</mn>
</msubsup>
<msubsup>
<mi>cos&delta;</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mn>0</mn>
</msubsup>
<mo>+</mo>
<msubsup>
<mi>B</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mn>0</mn>
</msubsup>
<msubsup>
<mi>sin&delta;</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mn>0</mn>
</msubsup>
</mrow>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mn>0</mn>
<mo>,</mo>
</mrow>
2
<mrow>
<msubsup>
<mi>Q</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mn>0</mn>
</msubsup>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>+</mo>
<msup>
<mi>&lambda;</mi>
<mn>0</mn>
</msup>
<mo>)</mo>
</mrow>
<msubsup>
<mi>Q</mi>
<mrow>
<mi>L</mi>
<mi>i</mi>
</mrow>
<mn>0</mn>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>U</mi>
<mi>i</mi>
<mn>0</mn>
</msubsup>
<munder>
<mo>&Sigma;</mo>
<mrow>
<mi>j</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>B</mi>
</msub>
</mrow>
</munder>
<msubsup>
<mi>U</mi>
<mi>j</mi>
<mn>0</mn>
</msubsup>
<mrow>
<mo>(</mo>
<msubsup>
<mi>G</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mn>0</mn>
</msubsup>
<msubsup>
<mi>sin&delta;</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mn>0</mn>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>B</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mn>0</mn>
</msubsup>
<msubsup>
<mi>cos&delta;</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mn>0</mn>
</msubsup>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mn>0</mn>
<mo>,</mo>
</mrow>
In formula, variable subscript 0 represents normal operating mode, SBFor the set of bus；
UiFor bus i voltage magnitude, i ∈ SB；UjFor bus j voltage magnitude；PGi, QGiRespectively generating set i active and
It is idle to exert oneself, i ∈ SG；PLi, QLiRespectively bus i active and load or burden without work, i ∈ SG；δijFor the phase angle difference between bus ij；
λ0For the load growth factor under normal operating mode, for describing the fluctuation of load and its with the growth of national economy；Gij, Bij
The real and imaginary parts of corresponding element respectively in bus admittance matrix；
3) inequality constraints
Inequality constraints includes node voltage constraint, generated power and idle units limits, Line Flow constraint：
<mrow>
<msubsup>
<munder>
<mi>U</mi>
<mo>&OverBar;</mo>
</munder>
<mi>i</mi>
<mi>k</mi>
</msubsup>
<mo>&le;</mo>
<msubsup>
<mi>U</mi>
<mi>i</mi>
<mi>k</mi>
</msubsup>
<mo>&le;</mo>
<msubsup>
<mover>
<mi>U</mi>
<mo>&OverBar;</mo>
</mover>
<mi>i</mi>
<mi>k</mi>
</msubsup>
<mo>,</mo>
<mi>i</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>B</mi>
</msub>
<mo>,</mo>
<mi>k</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>k</mi>
</msub>
<mo>,</mo>
</mrow>
<mrow>
<msub>
<munder>
<mi>P</mi>
<mo>&OverBar;</mo>
</munder>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
</msub>
<mo>&le;</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mi>k</mi>
</msubsup>
<mo>&le;</mo>
<msub>
<mover>
<mi>P</mi>
<mo>&OverBar;</mo>
</mover>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
</msub>
<mo>,</mo>
<mi>i</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>G</mi>
</msub>
<mo>,</mo>
<mi>k</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>k</mi>
</msub>
<mo>,</mo>
</mrow>
<mrow>
<msub>
<munder>
<mi>Q</mi>
<mo>&OverBar;</mo>
</munder>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
</msub>
<mo>&le;</mo>
<msubsup>
<mi>Q</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mi>k</mi>
</msubsup>
<mo>&le;</mo>
<msub>
<mover>
<mi>Q</mi>
<mo>&OverBar;</mo>
</mover>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
</msub>
<mo>,</mo>
<mi>i</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>G</mi>
</msub>
<mo>,</mo>
<mi>k</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>k</mi>
</msub>
<mo>,</mo>
</mrow>
<mrow>
<msub>
<munder>
<mi>F</mi>
<mo>&OverBar;</mo>
</munder>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>&le;</mo>
<msubsup>
<mi>F</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mi>k</mi>
</msubsup>
<mo>&le;</mo>
<msub>
<mover>
<mi>F</mi>
<mo>&OverBar;</mo>
</mover>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>,</mo>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>B</mi>
</msub>
<mo>,</mo>
<mi>k</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>k</mi>
</msub>
<mo>,</mo>
</mrow>
In formula, FijFor the trend between bus i to bus j on circuit；The upper and lower line of each variable is represented to dependent variable respectively
Upper and lower bound.
6. the power system optimal support unit localization method according to claim 5 decomposed based on forecast failure, it is special
Levy and be,
The step 5) in, the particular content of subproblem is corresponding to k-th of forecast failure：
1) object function
<mrow>
<mi>min</mi>
<mi> </mi>
<mi>J</mi>
<mo>=</mo>
<munder>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>G</mi>
</msub>
</mrow>
</munder>
<mrow>
<mo>(</mo>
<msubsup>
<mi>&beta;</mi>
<mi>i</mi>
<mrow>
<mi>k</mi>
<mo>+</mo>
</mrow>
</msubsup>
<mo>+</mo>
<msubsup>
<mi>&beta;</mi>
<mi>i</mi>
<mrow>
<mi>k</mi>
<mo>-</mo>
</mrow>
</msubsup>
<mo>)</mo>
</mrow>
<mo>,</mo>
</mrow>
In formula,The positive and negative climbing capacity slack variables of respectively generating set i；
2) equality constraint
Equality constraint is the power flow equation under forecast failure method of operation k
<mrow>
<mrow>
<mo>(</mo>
<mrow>
<mn>1</mn>
<mo>+</mo>
<msup>
<mi>&lambda;</mi>
<mi>k</mi>
</msup>
</mrow>
<mo>)</mo>
</mrow>
<msubsup>
<mi>P</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mi>k</mi>
</msubsup>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mrow>
<mn>1</mn>
<mo>+</mo>
<msup>
<mi>&lambda;</mi>
<mi>k</mi>
</msup>
</mrow>
<mo>)</mo>
</mrow>
<msubsup>
<mi>P</mi>
<mrow>
<mi>L</mi>
<mi>i</mi>
</mrow>
<mi>k</mi>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>U</mi>
<mi>i</mi>
<mi>k</mi>
</msubsup>
<munder>
<mi>&Sigma;</mi>
<mrow>
<mi>j</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>B</mi>
</msub>
</mrow>
</munder>
<msubsup>
<mi>U</mi>
<mi>j</mi>
<mi>k</mi>
</msubsup>
<mrow>
<mo>(</mo>
<mrow>
<msubsup>
<mi>G</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mi>k</mi>
</msubsup>
<msubsup>
<mi>cos&delta;</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mi>k</mi>
</msubsup>
<mo>+</mo>
<msubsup>
<mi>B</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mi>k</mi>
</msubsup>
<msubsup>
<mi>sin&delta;</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mi>k</mi>
</msubsup>
</mrow>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mn>0</mn>
<mo>,</mo>
</mrow>
<mrow>
<msubsup>
<mi>Q</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mi>k</mi>
</msubsup>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>+</mo>
<msup>
<mi>&lambda;</mi>
<mi>k</mi>
</msup>
<mo>)</mo>
</mrow>
<msubsup>
<mi>Q</mi>
<mrow>
<mi>L</mi>
<mi>i</mi>
</mrow>
<mi>k</mi>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>U</mi>
<mi>i</mi>
<mi>k</mi>
</msubsup>
<munder>
<mo>&Sigma;</mo>
<mrow>
<mi>j</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>B</mi>
</msub>
</mrow>
</munder>
<msubsup>
<mi>U</mi>
<mi>j</mi>
<mi>k</mi>
</msubsup>
<mrow>
<mo>(</mo>
<msubsup>
<mi>G</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mi>k</mi>
</msubsup>
<msubsup>
<mi>sin&delta;</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mi>k</mi>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>B</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mi>k</mi>
</msubsup>
<msubsup>
<mi>cos&delta;</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mi>k</mi>
</msubsup>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mn>0</mn>
<mo>,</mo>
</mrow>
In formula, SBFor the set of bus；UiFor bus i voltage magnitude, i ∈ SB；UjFor bus j voltage magnitude；PGi, QGiPoint
Not Wei the active and idle of generating set i exert oneself, i ∈ SG；PLi, QLiRespectively bus i active and load or burden without work, i ∈ SG；δij
For the phase angle difference between bus ij；λkFor the load growth factor under method of operation k, for describing the fluctuation of load and its with state
The growth of people's economy； The real and imaginary parts of corresponding element respectively in bus admittance matrix；
3) inequality constraints
Inequality constraints includes the unit ramp loss after relaxation
<mrow>
<msubsup>
<mi>&Pi;</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mo>-</mo>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>&Delta;&Pi;</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mo>-</mo>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>&beta;</mi>
<mi>i</mi>
<mrow>
<mi>k</mi>
<mo>-</mo>
</mrow>
</msubsup>
<mo>&le;</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mi>k</mi>
</msubsup>
<mo>-</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mn>0</mn>
</msubsup>
<mo>&le;</mo>
<msubsup>
<mi>&Pi;</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mo>+</mo>
</msubsup>
<mo>+</mo>
<msubsup>
<mi>&Delta;&Pi;</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mo>+</mo>
</msubsup>
<mo>+</mo>
<msubsup>
<mi>&beta;</mi>
<mi>i</mi>
<mrow>
<mi>k</mi>
<mo>+</mo>
</mrow>
</msubsup>
<mo>,</mo>
<mi>i</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>G</mi>
</msub>
<mo>,</mo>
</mrow>
3
In formula,The original positive and negative climbing capacities of respectively generating set i；
Unit climbing capacity slack variable is constrained：
<mrow>
<mn>0</mn>
<mo>&le;</mo>
<msubsup>
<mi>&beta;</mi>
<mi>i</mi>
<mrow>
<mi>k</mi>
<mo>-</mo>
</mrow>
</msubsup>
<mo>,</mo>
<mn>0</mn>
<mo>&le;</mo>
<msubsup>
<mi>&beta;</mi>
<mi>i</mi>
<mrow>
<mi>k</mi>
<mo>+</mo>
</mrow>
</msubsup>
<mo>,</mo>
<mi>i</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>G</mi>
</msub>
<mo>,</mo>
</mrow>
And other operation constraints, including the constraint of forecast failure method of operation k lower nodes voltage, generated power and idle exert oneself
Constraint and Line Flow constraint：
<mrow>
<msub>
<munder>
<mi>P</mi>
<mo>&OverBar;</mo>
</munder>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
</msub>
<mo>&le;</mo>
<msubsup>
<mi>P</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mi>k</mi>
</msubsup>
<mo>&le;</mo>
<msub>
<mover>
<mi>P</mi>
<mo>&OverBar;</mo>
</mover>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
</msub>
<mo>,</mo>
<mi>i</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>G</mi>
</msub>
<mo>,</mo>
</mrow>
<mrow>
<msub>
<munder>
<mi>Q</mi>
<mo>&OverBar;</mo>
</munder>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
</msub>
<mo>&le;</mo>
<msubsup>
<mi>Q</mi>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
<mi>k</mi>
</msubsup>
<mo>&le;</mo>
<msub>
<mover>
<mi>Q</mi>
<mo>&OverBar;</mo>
</mover>
<mrow>
<mi>G</mi>
<mi>i</mi>
</mrow>
</msub>
<mo>,</mo>
<mi>i</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>G</mi>
</msub>
<mo>,</mo>
</mrow>
<mrow>
<msub>
<munder>
<mi>F</mi>
<mo>&OverBar;</mo>
</munder>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>&le;</mo>
<msubsup>
<mi>F</mi>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
<mi>k</mi>
</msubsup>
<mo>&le;</mo>
<msub>
<mover>
<mi>F</mi>
<mo>&OverBar;</mo>
</mover>
<mrow>
<mi>i</mi>
<mi>j</mi>
</mrow>
</msub>
<mo>,</mo>
<mi>i</mi>
<mo>,</mo>
<mi>j</mi>
<mo>&Element;</mo>
<msub>
<mi>S</mi>
<mi>B</mi>
</msub>
<mo>,</mo>
</mrow>
In formula, FijFor the trend between bus i to bus j on circuit；The upper and lower line of each variable is represented to dependent variable respectively
Upper and lower bound.
7. the power system optimal support unit localization method according to claim 6 decomposed based on forecast failure, it is special
Levy and be,
Optimization problem corresponding to above-mentioned forecast failure method of operation k is solved, if optimization aim J non-zeros, generation such as lower inequality
Constraint, add step 4) in primal problem inequality constraints in：
In formula, u0,To control variable and step 4 under normal operating mode) in solve the corresponding control that primal problem is obtained
The numerical value of variable；T represents transposition；
Respectively step 4) in solve the transformation amounts of positive and negative climbing capacities of generating set i that primal problem is obtained
Numerical value；
μ,The respectively dual variable of equality constraint, the inequality constraints that the constraint of climbing capacity lower limit and the upper limit are constrained
Dual variable.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108808738A (en) * | 2018-05-29 | 2018-11-13 | 国电南瑞科技股份有限公司 | A kind of power grid security Corrective control method considering constraint priority |
| CN109586275A (en) * | 2018-10-18 | 2019-04-05 | 清华大学 | The quick start method and device of alternating current-direct current combined hybrid system electromagnetic transient simulation |
| CN110336590A (en) * | 2019-07-23 | 2019-10-15 | 广东电网有限责任公司 | A kind of Fault Locating Method of power telecom network, device and equipment |
| CN110556824A (en) * | 2019-08-23 | 2019-12-10 | 广西电网有限责任公司 | Power transmission capacity improving method based on bus splitting |
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| CN102684224A (en) * | 2012-05-25 | 2012-09-19 | 浙江大学 | Unit combination method for resolving and considering wind power volatility |
| CN106096751A (en) * | 2016-05-15 | 2016-11-09 | 国电南瑞科技股份有限公司 | Consider that new forms of energy access and participate in Short Term Generation Schedules arrangement and standby Optimal Configuration Method with Demand Side Response |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN102684224A (en) * | 2012-05-25 | 2012-09-19 | 浙江大学 | Unit combination method for resolving and considering wind power volatility |
| CN106096751A (en) * | 2016-05-15 | 2016-11-09 | 国电南瑞科技股份有限公司 | Consider that new forms of energy access and participate in Short Term Generation Schedules arrangement and standby Optimal Configuration Method with Demand Side Response |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108808738A (en) * | 2018-05-29 | 2018-11-13 | 国电南瑞科技股份有限公司 | A kind of power grid security Corrective control method considering constraint priority |
| CN108808738B (en) * | 2018-05-29 | 2021-07-13 | 国电南瑞科技股份有限公司 | Power grid safety correction control method considering constraint priority |
| CN109586275A (en) * | 2018-10-18 | 2019-04-05 | 清华大学 | The quick start method and device of alternating current-direct current combined hybrid system electromagnetic transient simulation |
| CN109586275B (en) * | 2018-10-18 | 2020-07-07 | 清华大学 | Quick starting method and device for electromagnetic transient simulation of alternating current-direct current hybrid system |
| CN110336590A (en) * | 2019-07-23 | 2019-10-15 | 广东电网有限责任公司 | A kind of Fault Locating Method of power telecom network, device and equipment |
| CN110556824A (en) * | 2019-08-23 | 2019-12-10 | 广西电网有限责任公司 | Power transmission capacity improving method based on bus splitting |
| CN110556824B (en) * | 2019-08-23 | 2024-08-23 | 广西电网有限责任公司 | Power transmission capacity improving method based on bus splitting |
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