CN107276122A - Adapt to the grid-connected peak regulation resource transfer decision-making technique of extensive regenerative resource - Google Patents
Adapt to the grid-connected peak regulation resource transfer decision-making technique of extensive regenerative resource Download PDFInfo
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- 230000033228 biological regulation Effects 0.000 title claims abstract description 203
- 238000000034 method Methods 0.000 title claims abstract description 28
- 230000001172 regenerating effect Effects 0.000 title claims abstract description 17
- 238000005457 optimization Methods 0.000 claims abstract description 16
- 238000000714 time series forecasting Methods 0.000 claims abstract description 15
- 238000010248 power generation Methods 0.000 claims abstract description 12
- 239000003245 coal Substances 0.000 claims description 82
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- 239000000446 fuel Substances 0.000 claims description 21
- 230000005611 electricity Effects 0.000 claims description 19
- 239000007789 gas Substances 0.000 claims description 19
- 230000001105 regulatory effect Effects 0.000 claims description 13
- 238000006243 chemical reaction Methods 0.000 claims description 5
- 239000003949 liquefied natural gas Substances 0.000 claims description 5
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 claims description 4
- 201000004384 Alopecia Diseases 0.000 claims description 3
- 239000002737 fuel gas Substances 0.000 claims description 3
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- 230000029087 digestion Effects 0.000 description 3
- 238000012163 sequencing technique Methods 0.000 description 3
- 230000009194 climbing Effects 0.000 description 2
- 238000002485 combustion reaction Methods 0.000 description 2
- 238000005553 drilling Methods 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 239000000567 combustion gas Substances 0.000 description 1
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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
- H02J3/381—Dispersed generators
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- H02J3/382—
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- H02J3/383—
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- H02J3/386—
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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
-
- 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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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
- Y02E10/76—Power conversion electric or electronic aspects
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Abstract
The grid-connected peak regulation resource transfer decision-making technique of extensive regenerative resource, including step are adapted to the invention discloses a kind of：Obtain sequential workload demand P in the specific time period of given areaL, determine the peak regulation demand A of power dispatching stationt；Determine that Wind turbines time series forecasting is exerted oneself PWExerted oneself P with solar power generation unit time series forecastingS；Determine that peak regulation resource M can be used in systemi, determine all kinds of peak regulation resource MiAdjustable metrics range, peak capacity DMiWith corresponding peak regulation cost CMi, build mixed integer optimization model；Obtain the peak regulation resource transfer order of optimization in specific time period.The present invention is by setting up every kind of peak regulation means technical/economical models and cost model, build the mixed integer optimization model using economy as target, the optimal peak regulation resource transfer amount of cost benefit is obtained by solving model and order is called, regenerative resource is adapted to power system efficiently to dissolve, improving peak load regulation network ability has preferable actual directive significance and application value.
Description
Technical field
The present invention relates to the technical field of electric power sunykatuib analysis, and in particular to adapts to the grid-connected tune of extensive regenerative resource
Peak resource transfer decision-making technique.
Background technology
With the large-scale development of the regenerative resources such as wind-powered electricity generation, solar energy, its randomness and intermittence are pacified to power system
The influence of full stable operation is increasingly highlighted.The access of extensive new energy causes the peak regulation pressure of systems face increasingly to increase, especially
It is that the anti-peak-shaving capability of wind-powered electricity generation becomes apparent from adding the difficulty of peak load regulation network.
Limited by endowment of resources, China's power supply architecture is based on the poor coal electricity of flexible modulation ability, peak-load regulating ability
It is weaker, cause the regenerative resources such as honourable water to be dissolved limited.The factor of influence wind electricity digestion can be classified as two aspects, and one is to disappear
Receive in terms of ability, include system fading margin ability, transmitting capacity of the electric wire netting etc. as long as determining the factor of a regional wind electricity digestion capability；
In terms of two are level of dissolving, refer mainly to whether take full advantage of the peak regulation resource of system, can the limited peak regulation resource of science decision
The amount of calling and call order, can determine realize that the maximization of regenerative resource is dissolved under existing objective condition.
There is randomness in calling for current China peak regulation resource, the discretion of scheduling is very big, cause all kinds of peak regulations to provide
Source is called has gap with actual demand situation, is largely because the rational peak regulation resource transfer decision process of missing.
The scheduling of science decision peak-load regulating resource is, it is necessary to solve the problems, such as following several respects：
(1) how available peak regulation resource in accurate and scientific definition system；
(2) how Technical Economy modeling and peak regulation Cost Modeling are carried out to all types of peak regulation resources；
(3) scientific and reasonable dispatching decision-making model how is built, helps scheduling institution accurately to realize the optimal feelings of economy
Dissolved to greatest extent under condition regenerative resource.
But do not propose that related suitable model and method can be under Unified frames to all kinds of peak regulation resources still at present
Technical and economic peculiarities are described and quantify its peak regulation cost, can also be realized to peak regulation resource transfer amount without specific method
With the decision-making for calling order.
The content of the invention
The present invention proposes a kind of grid-connected peak regulation resource transfer decision system of extensive regenerative resource of adaptation, based on mixing
Integer optimization method obtains the optimal peak regulation resource transfer capacity of economy and calls order, improves extensive regenerative resource and connects
The reasonability and science of peak regulation scheduling of resource in the case of entering, improve the regenerative resource digestion capability of system.On solving
Technical problem is stated, the technical solution adopted in the present invention there is provided a kind of grid-connected peak regulation of extensive regenerative resource that adapts to and provide
Decision-making technique is called in source, is comprised the following steps：
Obtain sequential workload demand P in the specific time period of given areaL, determine the specific region power dispatching station specific
Period peak regulation demand At；Determine that the time series forecasting of Wind turbines is exerted oneself PWExerted oneself P with the time series forecasting of solar power generation unitS；Really
Determine that peak regulation resource M can be used in systemiAnd its operation characteristic, according to correspondence peak regulation resource MiSafety and stability and economy constraint bar
Part, determines all kinds of peak regulation resource MiAdjustable metrics range and peak capacity DMi, and every kind of peak regulation resource MiCorresponding peak regulation into
This CMi, and build mixed integer optimization model；Obtain the peak regulation resource transfer order of optimization in specific time period；Wherein i=1,2,
3...n。
In the above-mentioned methods, the peak regulation demand AtFormula specific as follows：
If the initial time of specific time period is t0, the sequential workload demand of initial time isFinish time is t, is terminated
The sequential workload demand at moment isAnd power dispatching station is in moment t0Predict moment t peak capacity demand AtFor：
In formula, work as AtFor timing, peak regulation demand in representative works as AtDuring to bear, lower peak regulation demand is represented.
In the above-mentioned methods, the time series forecasting of the Wind turbines is exerted oneself PWFormula specific as follows：
In formula, a represents this area's wind power plant number；B represents the number of blower fan in g-th of wind power plant；Represent this area
H in g-th of wind power plantgTheory of the Fans under the moment prediction of wind speed is exerted oneself；
The time series forecasting of solar power generation unit is exerted oneself PSFormula specific as follows：
In formula, c represents this area's solar power station number；D represents of photovoltaic electrification component in g-th of solar power station
Number；Represent h in g-th of this area solar power stationgReason of the individual photovoltaic electrification component under moment prediction intensity of illumination
By exerting oneself.
In the above-mentioned methods, the peak regulation resource MiIncluding：Coal group of motors, Gas Generator Set, conventional hydropower unit, draw water storage
Can unit, nuclear power generating sets, abandon wind and abandon light, Demand Side Response and exerted oneself with interconnection.
In the above-mentioned methods, all kinds of peak regulation resource MiAdjustable metrics range, peak capacity DMiAnd corresponding cost mould
Type CMiFormula specific as follows：
It regard coal group of motors as peak regulation means M1, the available upper peak modulation capacity N of coal group of motorsupSpecially following formula：
In formula,Maximum can use of coal group of motors is represented to exert oneself,Coal group of motors is represented currently to exert oneself；
The available lower peak modulation capacity N of coal group of motorsdownSpecially following formula：
In formula,Minimum can use of coal group of motors is represented to exert oneself；
The upper peak regulation cost C of coal group of motorsM1upIt is fuel consumption cost, formula specific as follows：
In formula, β represents coal group of motors coal consumption function,Represent that unit existsWhen the unit exerted oneself
Coal consumption, wherein PM1,t0For initial time unit output,That is initial time is exerted oneself+gone up peak capacity, that is, currently
Moment exerts oneself；Represent peak capacity in the coal group of motors that t is called；
The lower peak regulation cost C of coal group of motorsM1downIt is due to the unit coal consumption increase cost for forcing down and exerting oneself and bringing, uses following formula
Represent：
In formula,Represent the unit coal consumption that unit is exerted oneself in initial time；Represent that unit existsWhen the unit coal consumption exerted oneself,Represent that current coal group of motors is exerted oneself,Represent the coal group of motors that t is called
Lower peak capacity；
It regard Gas Generator Set as peak regulation means M2, the available upper peak modulation capacity N of Gas Generator SetupSpecially following formula：
In formula,Maximum can use of coal group of motors is represented to exert oneself,Coal group of motors is represented currently to exert oneself；
The available lower peak modulation capacity N of coal group of motorsdownSpecially following formula：
According to actual schedule demand, Gas Generator Set considers the different peak modulation capacities of liquefied natural gas and general gas, liquefaction
Natural gas is provided mainly to start and stop peak regulation form, therefore the upper peak regulation cost of Gas Generator Set is fuel consumption cost, lower peak regulation into
This is 0；
It regard conventional hydropower unit as peak regulation means M3, it is divided into radial-flow type water power and adjustable water power, wherein radial-flow type water
Electricity is not involved in peak regulation, can adjust water power dry season participation peak regulation, it calls peak capacityReservoir level constraint, tool need to be met
Body is as follows：
In formula, WtoRepresent the initial water level of reservoir, WminRepresent reservoir lowest water level, WmaxReservoir peak level is represented, η is
Water amount of power generating conversion coefficient；
Conventional adjustable water power up-regulation peak cost is 0, when water occurs abandoning in lower peak regulation, lower peak regulation cost formula specific as follows：
In formula,Represent that unit abandons water cost, PcurWater is abandoned in expression；
It regard pump-storage generator as peak regulation means M4, it is necessary to upper and lower reservoir level constraint is met, it is specific as follows：
In formula, WtoRepresent the initial water level of reservoir, WminRepresent reservoir lowest water level, WmaxReservoir peak level is represented,
DM4,tTo call the peak capacity that pumped storage unit is participated in；
Pump-storage generator peak regulation cost with take out hair loss represent, lower peak regulation cost CM4Formula specific as follows：
CM4=(1- α) β DM4,t
In formula, α is that pumped storage unit takes out hair conversion efficiency, and β is the specified unit coal consumption of coal group of motors；
It regard nuclear power generating sets as peak regulation means M5, peak regulation cost is consumption fuel cost, lower peak regulation cost on nuclear power generating sets
For 0；The upper specific formula of peak regulation cost is as follows：
In formula, ω represents nuclear power unit of fuel cost, DM5,tRepresent peak capacity on nuclear power；
Wind will be abandoned and abandon light as peak regulation means M6, when peak regulation can not be met, wind is abandoned, light is abandoned and is exerted oneself fortune by equal proportion drop
OK, and peak regulation cost formula specific as follows：
In formula,Light peak regulation power is abandoned for the wind of abandoning that calls, and λ abandons light unit cost to abandon wind；
It regard Demand Side Response as peak regulation means M7, and peak regulation cost formula specific as follows：
In formula,The peak capacity participated in for dispatching requirement side resource response, μ is that Demand Side Response unit is called into
This；
Interconnection is exerted oneself and is used as peak regulation means M8, it is set to this grade of schedulable circuit with interconnection outside area and higher level dispatches
Two kinds of circuit, higher level's scheduling circuit is set to non-scheduling or low priority is called, it is considered at a time got in touch with by adjusting
After line plan is exerted oneself, proper timing it will need to be returned after with plan deviation electricity.
In the above-mentioned methods, all kinds of peak regulation resource MiPeak-load regulating equilibrium constraint need to be met, the system is adjusted
Peak equilibrium constraint formula specific as follows：
Wherein,For all kinds of peak regulation resource transfer capacity,For wind, light renewable energy power generation prediction output deviation.
In the above-mentioned methods, the mixed integer optimization model contains decision variable, constraints and object function three
Part, wherein decision variable are all kinds of peak regulation resource MiThe peak capacity provided in the feature period；Constraints is peak-load regulating
Equilibrium constraint and safety and stability and economy constraints；Object function is peak-load regulating totle drilling cost.
In the above-mentioned methods, the object function includes object function when object function is with lower peak regulation during upper peak regulation；
Object function takes out hair for the electric peak regulation fuel consumption cost of coal, fuel gas generation fuel consumption cost, pumped storage during upper peak regulation
Cost depletions, nuclear power fuel consuming cost and Demand Side Response cost sum, formula specific as follows：
During lower peak regulation object function be coal electricity drop when unit of force coal consumption increase cost, conventional motor group abandon water peak regulation into
This, pumped storage takes out hair cost depletions, abandons wind and abandon peak regulation resources costs under light cost and Demand Side Response cost sum, other types and be
0, represented with following formula：
The present invention is built using economy as mesh by setting up every kind of peak regulation means technical/economical models and cost model
Target mixed integer optimization model, obtains the optimal peak regulation resource transfer amount of cost benefit by solving model and calls order,
Regenerative resource is adapted to power system efficiently to dissolve, improving peak load regulation network ability has preferable actual directive significance and application
Value.
Brief description of the drawings
The method flow diagram that Fig. 1 provides for the present invention；
Flow chart is embodied for the method that the present invention is provided in Fig. 2.
Embodiment
The present invention is described in detail with reference to embodiment and Figure of description.
As shown in figure 1, adapting to the grid-connected peak regulation resource transfer decision-making of extensive regenerative resource the invention provides a kind of
Method, comprises the following steps：
Sequential workload demand P in S1, acquisition given area specific time periodL, determine that the specific region power dispatching station exists
Specific time period peak regulation demand At。
Assuming that the initial time of specific time period is t0, the sequential workload demand of initial time isFinish time is t, knot
The sequential workload demand at beam moment isAnd power dispatching station is in moment t0Predict moment t peak capacity demand At
For：
In formula, work as AtFor timing, peak regulation demand in representative works as AtDuring to bear, lower peak regulation demand is represented.
S2, determine that the time series forecasting of Wind turbines is exerted oneself PWExerted oneself P with the time series forecasting of solar power generation unitS。
The time series forecasting of Wind turbines is exerted oneself PWFormula specific as follows：
In formula, a represents this area's wind power plant number；B represents the number of blower fan in g-th of wind power plant；Represent this area
H in g-th of wind power plantgTheory of the Fans under the moment prediction of wind speed is exerted oneself.
The time series forecasting of solar power generation unit is exerted oneself PSFormula specific as follows：
In formula, c represents this area's solar power station number；D represents of photovoltaic electrification component in g-th of solar power station
Number；Represent h in g-th of this area solar power stationgReason of the individual photovoltaic electrification component under moment prediction intensity of illumination
By exerting oneself.
S3, determine that peak regulation resource M can be used in systemiAnd its operation characteristic, according to correspondence peak regulation resource MiSafety and stability and
Economy constraints, determines all kinds of peak regulation resource MiAdjustable metrics range and peak capacity DMi, and every kind of peak regulation resource Mi
Corresponding peak regulation cost CMi(wherein i=1,2,3...n), and build mixed integer optimization model.Solution is waken up with a start to Optimized model
Obtain peak regulation resource calls order and the amount of calling.
The peak regulation resource that peak regulation is participated in the present embodiment includes but is not limited to coal group of motors, Gas Generator Set, conventional hydropower machine
Group, pump-storage generator, nuclear power generating sets, abandon wind and abandon light, Demand Side Response and exerted oneself with interconnection, and corresponding safety and stability and
Economy constraints be respectively peak regulation Constraints of Equilibrium, units limits, reservoir dynamic capacity constraint, abandon wind abandon light constraint, unit
Power constraint, the continuous start and stop constraint of unit and the actual schedule of climbing, which are run, to be constrained.
First determine that the sequencing theory for obtaining Wind turbines in the special time of given area is exerted oneself P firstF, normal power supplies machine
The operation characteristic and sequential workload demand P of groupL, wherein,
The sequencing theory of Wind turbines is exerted oneself PFFormula specific as follows：
In formula, a represents this area's wind power plant number；B represents the number of blower fan in g-th of wind power plant；Represent this area
H in g-th of wind power plantgTheory of the Fans under the moment wind friction velocity is exerted oneself.
Sequential workload demand PLIt is the history sequential load curve and search time of the corresponding period based on this area
The load peak of the prediction of section, which is calculated, to be obtained, formula specific as follows：
In formula,It is historical load, KfIt is the load peak for the prediction for studying the period, KhIt is historical load peak value.
The characteristic that is operated together of above-mentioned all kinds of peak regulation resources mainly includes the available P that exerts oneself of unit maximum in systemC,max, it is minimum
The P that exerts oneself can be usedC,min, the parameter such as unit climbing rate；The wherein available sum of exerting oneself of normal power supplies unit maximum should be greater than load and connection
The maximum of winding thread plan electricity sent outside sum, and leave the maximum of certain positive spare capacity, then this area's normal power supplies unit
The P that exerts oneself can be usedC,maxIt is shown below：
In formula, I represents the number of units of this area's normal power supplies unit, PCi,maxSkill can be used by representing the maximum of i-th conventional power unit
Art is exerted oneself, PL(t)Represent the load power of t this area, Pt,plan(t) represent that t tie line plan sends power, R outside+Table
Show positive spare capacity.It should be noted that normal power supplies refer to the power supply in addition to wind-powered electricity generation and solar power generation, it that is to say that peak regulation is provided
All resources in source in addition to wind, light and load side are responded.
First, it regard coal group of motors as peak regulation means M1, the available upper peak modulation capacity N of coal group of motorsupSpecially following formula：
In formula,Maximum can use of coal group of motors is represented to exert oneself,Coal group of motors is represented currently to exert oneself.
The available lower peak modulation capacity N of coal group of motorsdownSpecially following formula：
In formula, PM1,minMinimum can use of coal group of motors is represented to exert oneself.Above-mentioned upper peak modulation capacity represents adjustable with lower peak modulation capacity
Metrics range.
Required according to actual schedule, coal group of motors is divided into this grade of scheduling unit dispatches unit, this level scheduling unit with higher level
It is set to high priority to call, higher level's scheduling unit is set to non-scheduling or low priority is called.Coal group of motors considers denitration
Load rationally sets peak regulation cost with throwing the steady combustion load difference of oil, shows that lower peak regulation calls the preferential coal group of motors that allows in order
Denitration load is down to, and throws the steady combustion load of oil and is used as unconventional regulating measure, therefore, the upper peak regulation cost C of coal group of motorsM1upIt is
Fuel consumption cost, formula specific as follows：
In formula, β represents coal group of motors coal consumption function,Represent that unit existsWhen the list exerted oneself
Position coal consumption, wherein PM1,t0For initial time unit output,That is initial time is exerted oneself+gone up peak capacity, that is,
Current time exerts oneself；Represent peak capacity in the coal group of motors that t is called.
The lower peak regulation cost C of coal group of motorsM1downIt is due to the unit coal consumption increase cost for forcing down and exerting oneself and bringing, uses following formula
Represent：
In formula,Represent the unit coal consumption that unit is exerted oneself in initial time；Represent that unit existsWhen the unit coal consumption exerted oneself,Represent that current coal group of motors is exerted oneself,Represent the coal group of motors that t is called
Lower peak capacity.
2nd, it regard Gas Generator Set as peak regulation means M2, the available upper peak modulation capacity N of Gas Generator SetupSpecially following formula：
In formula,Maximum can use of coal group of motors is represented to exert oneself,Coal group of motors is represented currently to exert oneself.
The available lower peak modulation capacity N of coal group of motorsdownSpecially following formula：
According to actual schedule demand, Gas Generator Set considers LNG (Liquefied Nature Gas, liquefied natural gas) and general
The different peak modulation capacities of logical combustion gas, LNG is provided mainly to start and stop peak regulation form, and general gas is set to continuously adjust.
The upper peak regulation cost of Gas Generator Set is fuel consumption cost, and lower peak regulation cost is 0.
3rd, it regard conventional hydropower unit as peak regulation means M3, it is divided into radial-flow type water power and adjustable water power, wherein radial-flow type
Water power is not involved in peak regulation, can adjust water power dry season participation peak regulation, it calls peak capacity DM3,tReservoir level constraint need to be met,
It is specific as follows：
In formula, WtoRepresent the initial water level of reservoir, WminRepresent reservoir lowest water level, WmaxReservoir peak level is represented, η is
Water amount of power generating conversion coefficient.
Conventional adjustable water power up-regulation peak cost is 0, and lower peak regulation occurs abandoning water peak regulation cost formula specific as follows at present：
In formula,Represent that unit abandons water cost, PcurWater is abandoned in expression.
4th, it regard pump-storage generator as peak regulation means M4, it is similar with conventional hydropower, it is necessary to meet upper and lower reservoir level
Constraint, it is specific as follows：
In formula, WtoRepresent the initial water level of reservoir, WminRepresent reservoir lowest water level, WmaxReservoir peak level is represented,
DM4,tTo call the peak capacity that pumped storage unit is participated in.
Pump-storage generator possesses two kinds of operating modes of drawing water and generate electricity, and adjustable extent is completely sent out from full hair-like state of drawing water to generating electricity
State, pump-storage generator peak regulation cost is specially to take out hair cost depletions, is mainly embodied in pumping operation mode, therefore upper peak regulation cost
For 0, lower peak regulation cost CM4Formula specific as follows：
CM4=(1- α) β DM4,t
In formula, α is that pumped storage unit takes out hair conversion efficiency, and β is the specified unit coal consumption of coal group of motors.
5th, nuclear power generating sets are regard as peak regulation means M5, peak regulation cost is consumption fuel cost, lower peak regulation generation on nuclear power generating sets
The reduction of table nuclear power is exerted oneself, and lower peak regulation cost is 0, but nuclear power generating sets peak regulation considers that need to shift to an earlier date the long period is prepared；Upper peak regulation
The specific formula of cost is as follows：
In formula, ω represents nuclear power unit of fuel cost, DM5,tRepresent peak capacity on nuclear power.
6th, wind will be abandoned and abandon light as peak regulation means M6, when peak regulation can not be met, abandon wind, abandon light by equal proportion drop exert oneself
Operation, and peak regulation cost formula specific as follows：
In formula,Light peak regulation power is abandoned for the wind of abandoning that calls, and λ abandons light unit cost to abandon wind.
7th, it regard Demand Side Response as peak regulation means M7, and call Demand Side Response resources costs formula specific as follows：
In formula,The peak capacity participated in for dispatching requirement side resource response, μ is that Demand Side Response unit is called into
This.
8th, interconnection is exerted oneself and is used as peak regulation means M8, this grade of schedulable circuit and higher level are set to interconnection outside area
Two kinds of circuit is dispatched, higher level's scheduling circuit is set to non-scheduling or low priority is called, it is considered to after connection line load is supported
Continuous " going back electricity " effect, i.e., need to proper timing will be with plan afterwards after at a time being exerted oneself by adjusting tie line plan
Deviation electricity is returned.
Above-mentioned all kinds of peak regulation resource Mi need to be considered outside safety and stability and economy constraints, are also needed to meet peak-load regulating and are put down
Weigh constraints, to ensure the systematic electricity equilibrium of supply and demand, peak-load regulating equilibrium constraint formula specific as follows：
Wherein,For all kinds of peak regulation resource transfer capacity,Output deviation is predicted for wind, light renewable energy power generation,
AtFor peak regulation demand.
Mixed integer optimization model contains decision variable, wherein three parts of constraints and object function, decision variable
For all kinds of peak regulation resource MiThe peak capacity provided in the feature period；Constraints be said system peak regulation equilibrium constraint with
Safety and stability and economy constraints.Object function is peak-load regulating totle drilling cost, and object function includes target during upper peak regulation
Object function when function is with lower peak regulation, object function disappears for the electric peak regulation fuel consumption cost of coal, fuel gas generation fuel during upper peak regulation
Consume cost, nuclear power fuel consuming cost and Demand Side Response cost sum, formula specific as follows：
During lower peak regulation object function be coal electricity drop when unit of force coal consumption increase cost, conventional motor group abandon water peak regulation into
This, pumped storage takes out hair cost depletions, abandons wind and abandon peak regulation resources costs under light cost and Demand Side Response cost sum, other types and be
0, represented with following formula：
S4, all kinds of peak regulation resource M will be callediPeak regulation cost CMiExport, obtain by sequence from small to large with peak capacity
The peak regulation resource transfer order of optimization in specific time period, wherein call cost minimization is optimal peak regulation resource.
Illustrate the specific implementation step of the present embodiment below, as shown in Fig. 2 comprising the following steps：
S11, determine specific region power dispatching station in specific time period peak regulation demand At。
S12, the sequencing theory for obtaining Wind turbines are exerted oneself PW, solar power generation unit time series forecasting exert oneself PS, conventional electricity
The operation characteristic and sequential workload demand P of source unitL。
S13, determine that peak regulation resource M can be used in systemi。
S14, determine each peak regulation resource MiOperation characteristic, each peak regulation resource M is determined according to dispatching requirementiAdjustable metrics range
And build corresponding cost model.
S15, determine each peak regulation resource MiThe safety and stability and economy constraints that need to be met when calling.
S16, determine all kinds of peak regulation resource MiPeak regulation cost CMi, target letter when when determining upper peak regulation respectively with lower peak regulation
Number.
S17, structure mixed integer optimization model.
S18, solving model, all kinds of peak regulation resource M are called by sequence output from small to largeiPeak regulation cost CMiHold with peak regulation
Amount.
S19, end
The method that the present invention is provided implements simple clear, sets up every kind of peak regulation means technical/economical models and cost model,
And then mixed integer optimization model of the structure using economy as target, the optimal peak regulation of cost benefit is obtained by solving model and provided
The source amount of calling and call order, adapting to regenerative resource to power system efficiently dissolves, improve peak load regulation network ability have it is preferable
Actual directive significance and application value.
The present invention is not limited to above-mentioned preferred forms, and anyone should learn that the knot made under the enlightenment of the present invention
Structure changes, and the technical schemes that are same or similar to the present invention are each fallen within protection scope of the present invention.
Claims (8)
1. adapt to the grid-connected peak regulation resource transfer decision-making technique of extensive regenerative resource, it is characterised in that comprise the following steps：
Obtain sequential workload demand P in the specific time period of given areaL, determine the specific region power dispatching station in specific time period
Peak regulation demand At；Determine that the time series forecasting of Wind turbines is exerted oneself PWExerted oneself P with the time series forecasting of solar power generation unitS；It is determined that being
Peak regulation resource M can be used in systemiAnd its operation characteristic, according to correspondence peak regulation resource MiSafety and stability and economy constraints, really
Fixed all kinds of peak regulation resource MiAdjustable metrics range and peak capacity DMi, and every kind of peak regulation resource MiCorresponding peak regulation cost CMi,
And build mixed integer optimization model；Obtain the peak regulation resource transfer order of optimization in specific time period；Wherein i=1,2,3...n.
2. the method as described in claim 1, it is characterised in that the peak regulation demand AtFormula specific as follows：
If the initial time of specific time period is t0, the sequential workload demand of initial time isFinish time is t, finish time
Sequential workload demand beAnd power dispatching station is in moment t0Predict moment t peak capacity demand AtFor：
<mrow>
<msub>
<mi>A</mi>
<mi>t</mi>
</msub>
<mo>=</mo>
<msub>
<mi>P</mi>
<msub>
<mi>L</mi>
<mrow>
<mi>t</mi>
<mn>0</mn>
</mrow>
</msub>
</msub>
<mo>-</mo>
<msub>
<mi>P</mi>
<msub>
<mi>L</mi>
<mi>t</mi>
</msub>
</msub>
</mrow>
In formula, work as AtFor timing, peak regulation demand in representative works as AtDuring to bear, lower peak regulation demand is represented.
3. the method as described in claim 1, it is characterised in that the time series forecasting of the Wind turbines is exerted oneself PWFormula specific as follows：
<mrow>
<msub>
<mi>P</mi>
<mi>W</mi>
</msub>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>g</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>a</mi>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<msub>
<mi>h</mi>
<mi>g</mi>
</msub>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>b</mi>
</munderover>
<msub>
<mi>P</mi>
<msub>
<mi>h</mi>
<mi>g</mi>
</msub>
</msub>
</mrow>
In formula, a represents this area's wind power plant number；B represents the number of blower fan in g-th of wind power plant；Represent this area g
H in individual wind power plantgTheory of the Fans under the moment prediction of wind speed is exerted oneself；
The time series forecasting of solar power generation unit is exerted oneself PSFormula specific as follows：
<mrow>
<msub>
<mi>P</mi>
<mi>S</mi>
</msub>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>g</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>c</mi>
</munderover>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<msub>
<mi>h</mi>
<mi>g</mi>
</msub>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>d</mi>
</munderover>
<msub>
<mi>P</mi>
<msub>
<mi>h</mi>
<mi>g</mi>
</msub>
</msub>
</mrow>
In formula, c represents this area's solar power station number；D represents the number of photovoltaic electrification component in g-th of solar power station；Represent h in g-th of this area solar power stationgTheory of the individual photovoltaic electrification component under moment prediction intensity of illumination
Exert oneself.
4. the method as described in claim 1, it is characterised in that the peak regulation resource MiIncluding：Coal group of motors, Gas Generator Set, often
Rule Hydropower Unit, pump-storage generator, nuclear power generating sets, abandon wind and abandon light, Demand Side Response and exerted oneself with interconnection.
5. method as claimed in claim 4, it is characterised in that all kinds of peak regulation resource MiAdjustable metrics range, peak capacity
DMiAnd corresponding cost model CMiFormula specific as follows：
It regard coal group of motors as peak regulation means M1, the available upper peak modulation capacity N of coal group of motorsupSpecially following formula：
<mrow>
<msub>
<mi>N</mi>
<mrow>
<mi>u</mi>
<mi>p</mi>
</mrow>
</msub>
<mo>=</mo>
<msub>
<mi>P</mi>
<mrow>
<msub>
<mi>M</mi>
<mn>1</mn>
</msub>
<mo>,</mo>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
</mrow>
</msub>
<mo>-</mo>
<msub>
<mi>P</mi>
<mrow>
<msub>
<mi>M</mi>
<mn>1</mn>
</msub>
<mo>,</mo>
<msub>
<mi>t</mi>
<mn>0</mn>
</msub>
</mrow>
</msub>
</mrow>
In formula,Maximum can use of coal group of motors is represented to exert oneself,Coal group of motors is represented currently to exert oneself；
The available lower peak modulation capacity N of coal group of motorsdownSpecially following formula：
<mrow>
<msub>
<mi>N</mi>
<mrow>
<mi>d</mi>
<mi>o</mi>
<mi>w</mi>
<mi>n</mi>
</mrow>
</msub>
<mo>=</mo>
<msub>
<mi>P</mi>
<mrow>
<msub>
<mi>M</mi>
<mn>1</mn>
</msub>
<mo>,</mo>
<msub>
<mi>t</mi>
<mn>0</mn>
</msub>
</mrow>
</msub>
<mo>-</mo>
<msub>
<mi>P</mi>
<mrow>
<msub>
<mi>M</mi>
<mn>1</mn>
</msub>
<mo>,</mo>
<mi>min</mi>
</mrow>
</msub>
</mrow>
In formula,Minimum can use of coal group of motors is represented to exert oneself；
The upper peak regulation cost C of coal group of motorsM1upIt is fuel consumption cost, formula specific as follows：
<mrow>
<msub>
<mi>C</mi>
<mrow>
<mi>M</mi>
<mn>1</mn>
<mi>U</mi>
<mi>P</mi>
</mrow>
</msub>
<mo>=</mo>
<msub>
<mi>&beta;</mi>
<msub>
<mi>P</mi>
<mrow>
<mi>M</mi>
<mn>1</mn>
<mo>,</mo>
<mi>t</mi>
<mn>0</mn>
</mrow>
</msub>
</msub>
<mo>+</mo>
<msubsup>
<mi>D</mi>
<mrow>
<mi>M</mi>
<mn>1</mn>
<mo>,</mo>
<mi>t</mi>
</mrow>
<mo>+</mo>
</msubsup>
<mo>&CenterDot;</mo>
<msubsup>
<mi>D</mi>
<mrow>
<mi>M</mi>
<mn>1</mn>
<mo>,</mo>
<mi>t</mi>
</mrow>
<mo>+</mo>
</msubsup>
</mrow>
1
In formula, β represents coal group of motors coal consumption function,Represent that unit existsWhen the unit coal consumption exerted oneself,
Wherein PM1,t0For initial time unit output,I.e. initial time is exerted oneself+gone up peak capacity, that is, current time
Exert oneself；Represent peak capacity in the coal group of motors that t is called；
The lower peak regulation cost C of coal group of motorsM1downIt is due to the unit coal consumption increase cost for forcing down and exerting oneself and bringing, is represented with following formula：
<mrow>
<msub>
<mi>C</mi>
<mrow>
<mi>M</mi>
<mn>1</mn>
<mi>d</mi>
<mi>o</mi>
<mi>w</mi>
<mi>n</mi>
</mrow>
</msub>
<mo>=</mo>
<mrow>
<mo>(</mo>
<msub>
<mi>&beta;</mi>
<msub>
<mi>P</mi>
<mrow>
<mi>M</mi>
<mn>1</mn>
<mo>,</mo>
<mi>t</mi>
<mn>0</mn>
</mrow>
</msub>
</msub>
<mo>+</mo>
<msubsup>
<mi>D</mi>
<mrow>
<mi>M</mi>
<mn>1</mn>
<mo>,</mo>
<mi>t</mi>
</mrow>
<mo>-</mo>
</msubsup>
<mo>-</mo>
<msub>
<mi>&beta;</mi>
<msub>
<mi>P</mi>
<mrow>
<mi>M</mi>
<mn>1</mn>
<mo>,</mo>
<mi>t</mi>
<mn>0</mn>
</mrow>
</msub>
</msub>
<mo>)</mo>
</mrow>
<mrow>
<mo>(</mo>
<msub>
<mi>P</mi>
<mrow>
<mi>M</mi>
<mn>1</mn>
</mrow>
</msub>
<mo>+</mo>
<msubsup>
<mi>D</mi>
<mrow>
<mi>M</mi>
<mn>1</mn>
<mo>,</mo>
<mi>t</mi>
</mrow>
<mo>-</mo>
</msubsup>
<mo>)</mo>
</mrow>
</mrow>
In formula,Represent the unit coal consumption that unit is exerted oneself in initial time；Represent that unit exists
When the unit coal consumption exerted oneself,Represent that current coal group of motors is exerted oneself,Represent that peak regulation holds under the coal group of motors that t is called
Amount；
It regard Gas Generator Set as peak regulation means M2, the available upper peak modulation capacity N of Gas Generator SetupSpecially following formula：
<mrow>
<msub>
<mi>N</mi>
<mrow>
<mi>u</mi>
<mi>p</mi>
</mrow>
</msub>
<mo>=</mo>
<msub>
<mi>P</mi>
<mrow>
<msub>
<mi>M</mi>
<mn>2</mn>
</msub>
<mo>,</mo>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
</mrow>
</msub>
<mo>-</mo>
<msub>
<mi>P</mi>
<mrow>
<msub>
<mi>M</mi>
<mn>2</mn>
</msub>
<mo>,</mo>
<msub>
<mi>t</mi>
<mn>0</mn>
</msub>
</mrow>
</msub>
</mrow>
In formula,Maximum can use of coal group of motors is represented to exert oneself,Coal group of motors is represented currently to exert oneself；
The available lower peak modulation capacity N of coal group of motorsdownSpecially following formula：
<mrow>
<msub>
<mi>N</mi>
<mrow>
<mi>d</mi>
<mi>o</mi>
<mi>w</mi>
<mi>n</mi>
</mrow>
</msub>
<mo>=</mo>
<msub>
<mi>P</mi>
<mrow>
<msub>
<mi>M</mi>
<mn>2</mn>
</msub>
<mo>,</mo>
<msub>
<mi>t</mi>
<mn>0</mn>
</msub>
</mrow>
</msub>
<mo>-</mo>
<msub>
<mi>P</mi>
<mrow>
<msub>
<mi>M</mi>
<mn>2</mn>
</msub>
<mo>,</mo>
<mi>min</mi>
</mrow>
</msub>
</mrow>
According to actual schedule demand, Gas Generator Set considers the different peak modulation capacities of liquefied natural gas and general gas, and liquefaction is natural
Gas is provided mainly to start and stop peak regulation form, therefore the upper peak regulation cost of Gas Generator Set is fuel consumption cost, and lower peak regulation cost is
0；
It regard conventional hydropower unit as peak regulation means M3, it is divided into radial-flow type water power and adjustable water power, wherein radial-flow type water power is not joined
With peak regulation, water power dry season participation peak regulation is can adjust, it calls peak capacityReservoir level constraint need to be met, specifically such as
Under：
<mrow>
<msub>
<mi>W</mi>
<mrow>
<mi>m</mi>
<mi>i</mi>
<mi>n</mi>
</mrow>
</msub>
<mo>&le;</mo>
<msub>
<mi>W</mi>
<msub>
<mi>t</mi>
<mn>0</mn>
</msub>
</msub>
<mo>+</mo>
<msub>
<mi>&eta;D</mi>
<mrow>
<msub>
<mi>M</mi>
<mn>3</mn>
</msub>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<mo>&le;</mo>
<msub>
<mi>W</mi>
<mrow>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
</mrow>
</msub>
</mrow>
In formula, WtoRepresent the initial water level of reservoir, WminRepresent reservoir lowest water level, WmaxReservoir peak level is represented, η is generating
Water interaction coefficient；
Conventional adjustable water power up-regulation peak cost is 0, when water occurs abandoning in lower peak regulation, lower peak regulation cost formula specific as follows：
In formula,Represent that unit abandons water cost, PcurWater is abandoned in expression；
It regard pump-storage generator as peak regulation means M4, it is necessary to upper and lower reservoir level constraint is met, it is specific as follows：
<mrow>
<msub>
<mi>W</mi>
<mrow>
<mi>m</mi>
<mi>i</mi>
<mi>n</mi>
</mrow>
</msub>
<mo>&le;</mo>
<msub>
<mi>W</mi>
<msub>
<mi>t</mi>
<mn>0</mn>
</msub>
</msub>
<mo>+</mo>
<msub>
<mi>&eta;D</mi>
<mrow>
<msub>
<mi>M</mi>
<mn>3</mn>
</msub>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<mo>&le;</mo>
<msub>
<mi>W</mi>
<mrow>
<mi>m</mi>
<mi>a</mi>
<mi>x</mi>
</mrow>
</msub>
</mrow>
In formula, WtoRepresent the initial water level of reservoir, WminRepresent reservoir lowest water level, WmaxRepresent reservoir peak level, DM4,tFor
The peak capacity for calling pumped storage unit to participate in；
Pump-storage generator peak regulation cost with take out hair loss represent, lower peak regulation cost CM4Formula specific as follows：
CM4=(1- α) β DM4,t
In formula, α is that pumped storage unit takes out hair conversion efficiency, and β is the specified unit coal consumption of coal group of motors；
It regard nuclear power generating sets as peak regulation means M5, peak regulation cost is consumption fuel cost on nuclear power generating sets, and lower peak regulation cost is 0；On
The specific formula of peak regulation cost is as follows：
<mrow>
<msub>
<mi>C</mi>
<mrow>
<msub>
<mi>M</mi>
<mn>5</mn>
</msub>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<mo>=</mo>
<msub>
<mi>&omega;D</mi>
<mrow>
<mi>M</mi>
<mn>5</mn>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
</mrow>
In formula, ω represents nuclear power unit of fuel cost, DM5,tRepresent peak capacity on nuclear power；
Wind will be abandoned and abandon light as peak regulation means M6, when peak regulation can not be met, wind is abandoned, light is abandoned and is exerted oneself operation by equal proportion drop, and tune
Peak cost formula specific as follows：
<mrow>
<msub>
<mi>C</mi>
<mrow>
<msub>
<mi>M</mi>
<mn>6</mn>
</msub>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<mo>=</mo>
<msub>
<mi>&lambda;D</mi>
<mrow>
<msub>
<mi>M</mi>
<mn>6</mn>
</msub>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
</mrow>
In formula,Light peak regulation power is abandoned for the wind of abandoning that calls, and λ abandons light unit cost to abandon wind；
It regard Demand Side Response as peak regulation means M7, and peak regulation cost formula specific as follows：
<mrow>
<msub>
<mi>C</mi>
<mrow>
<msub>
<mi>M</mi>
<mn>7</mn>
</msub>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<mo>=</mo>
<msub>
<mi>&mu;D</mi>
<mrow>
<msub>
<mi>M</mi>
<mn>7</mn>
</msub>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
</mrow>
In formula,The peak capacity participated in for dispatching requirement side resource response, μ is that Demand Side Response unit calls cost；
Interconnection is exerted oneself and is used as peak regulation means M8, this grade of schedulable circuit and higher level's scheduling circuit are set to interconnection outside area
Two kinds, higher level's scheduling circuit is set to non-scheduling or low priority is called, it is considered at a time by adjusting interconnection meter
Mark after power, proper timing will need to be returned after with plan deviation electricity.
6. method as claimed in claim 4, it is characterised in that all kinds of peak regulation resource MiPeak-load regulating balance need to be met about
Beam condition, the peak-load regulating equilibrium constraint formula specific as follows：
<mrow>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mn>8</mn>
</munderover>
<msub>
<mi>D</mi>
<mrow>
<msub>
<mi>M</mi>
<mi>i</mi>
</msub>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
<mo>+</mo>
<msubsup>
<mi>E</mi>
<mrow>
<mi>r</mi>
<mi>e</mi>
<mi>n</mi>
</mrow>
<mi>t</mi>
</msubsup>
<mo>=</mo>
<msub>
<mi>A</mi>
<mi>t</mi>
</msub>
</mrow>
Wherein,For all kinds of peak regulation resource transfer capacity,For wind, light renewable energy power generation prediction output deviation.
7. the method as described in claim 1, it is characterised in that the mixed integer optimization model contains decision variable, constraint
Condition and three parts of object function, wherein decision variable are all kinds of peak regulation resource MiThe peak capacity provided in the feature period；
Constraints is peak-load regulating equilibrium constraint and safety and stability and economy constraints；Object function is that peak-load regulating is total
Cost.
8. method as claimed in claim 7, it is characterised in that the object function includes object function and downward during upper peak regulation
Object function during peak；
Object function takes out hair loss for the electric peak regulation fuel consumption cost of coal, fuel gas generation fuel consumption cost, pumped storage during upper peak regulation
Cost, nuclear power fuel consuming cost and Demand Side Response cost sum, formula specific as follows：
<mfenced open = "" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<mi>min</mi>
<mi> </mi>
<msub>
<mi>Z</mi>
<mrow>
<mi>u</mi>
<mi>p</mi>
</mrow>
</msub>
</mrow>
</mtd>
<mtd>
<mrow>
<msub>
<mi>Z</mi>
<mrow>
<mi>u</mi>
<mi>p</mi>
</mrow>
</msub>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mn>8</mn>
</munderover>
<msub>
<mi>C</mi>
<mrow>
<msub>
<mi>M</mi>
<mi>i</mi>
</msub>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
Object function is that coal electricity drops peak regulation cost when unit of force coal consumption increase cost, conventional motor group abandon water, taken out during lower peak regulation
It is 0 that storage, which takes out hair cost depletions, abandons wind to abandon peak regulation resources costs under light cost and Demand Side Response cost sum, other types, is used
Following formula is represented：
<mfenced open = "" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<mi>min</mi>
<mi> </mi>
<msub>
<mi>Z</mi>
<mrow>
<mi>d</mi>
<mi>o</mi>
<mi>w</mi>
<mi>n</mi>
</mrow>
</msub>
</mrow>
</mtd>
<mtd>
<mrow>
<msub>
<mi>Z</mi>
<mrow>
<mi>d</mi>
<mi>o</mi>
<mi>w</mi>
<mi>n</mi>
</mrow>
</msub>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>i</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mn>8</mn>
</munderover>
<msub>
<mi>C</mi>
<mrow>
<msub>
<mi>M</mi>
<mi>i</mi>
</msub>
<mo>,</mo>
<mi>t</mi>
</mrow>
</msub>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
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| CN108206539A (en) * | 2018-01-10 | 2018-06-26 | 云南电网有限责任公司电力科学研究院 | A kind of renewable energy power generation distribution network planning method |
| CN109038689A (en) * | 2018-09-13 | 2018-12-18 | 中国南方电网有限责任公司电网技术研究中心 | A kind of ultra-short term Optimization Scheduling of electric system |
| CN109755970A (en) * | 2019-03-29 | 2019-05-14 | 广东电网有限责任公司 | A kind of energy-saving scheduling method, system, equipment and computer readable storage medium |
| CN110112767A (en) * | 2019-03-19 | 2019-08-09 | 华北电力大学 | The polymorphic Demand-side load of wide area participates in the lotus source optimization control method of peak-load regulating |
| CN110417004A (en) * | 2019-07-12 | 2019-11-05 | 国网甘肃省电力公司经济技术研究院 | A kind of extra-high voltage alternating current-direct current sending end power grid multi-source coordination peak regulation potentiality computation model |
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| CN114421469A (en) * | 2022-01-26 | 2022-04-29 | 中国大唐集团科学技术研究院有限公司中南电力试验研究院 | Method for identifying and counting peak shaving frequency of turbonator under deep peak shaving working condition |
| CN114818095A (en) * | 2022-06-30 | 2022-07-29 | 武昌理工学院 | Green building elastic constraint energy-saving optimization method |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102479350A (en) * | 2010-11-25 | 2012-05-30 | 国网能源研究院 | New-energy large-scale grid connection based electric power analysis system and method thereof |
| CN103762619A (en) * | 2014-02-12 | 2014-04-30 | 国家电网公司 | Nuclear power involvement grid peak shaving judging method based on grid peak shaving capacity balancing |
| CN106684928A (en) * | 2016-11-26 | 2017-05-17 | 国网河南省电力公司电力科学研究院 | Calculation method of power grid peak regulation margin based on peak regulation cost |
| KR20170059726A (en) * | 2015-11-23 | 2017-05-31 | 한국전기연구원 | System for Testing Function of Distributed Resources and Method using thereof |
-
2017
- 2017-06-26 CN CN201710495182.8A patent/CN107276122B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102479350A (en) * | 2010-11-25 | 2012-05-30 | 国网能源研究院 | New-energy large-scale grid connection based electric power analysis system and method thereof |
| CN103762619A (en) * | 2014-02-12 | 2014-04-30 | 国家电网公司 | Nuclear power involvement grid peak shaving judging method based on grid peak shaving capacity balancing |
| KR20170059726A (en) * | 2015-11-23 | 2017-05-31 | 한국전기연구원 | System for Testing Function of Distributed Resources and Method using thereof |
| CN106684928A (en) * | 2016-11-26 | 2017-05-17 | 国网河南省电力公司电力科学研究院 | Calculation method of power grid peak regulation margin based on peak regulation cost |
Cited By (17)
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| CN108206539A (en) * | 2018-01-10 | 2018-06-26 | 云南电网有限责任公司电力科学研究院 | A kind of renewable energy power generation distribution network planning method |
| CN109038689A (en) * | 2018-09-13 | 2018-12-18 | 中国南方电网有限责任公司电网技术研究中心 | A kind of ultra-short term Optimization Scheduling of electric system |
| CN109038689B (en) * | 2018-09-13 | 2021-11-05 | 南方电网科学研究院有限责任公司 | Ultra-short-term optimal scheduling method for power system |
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| CN110112767B (en) * | 2019-03-19 | 2023-05-30 | 华北电力大学 | Load source optimization control method for peak regulation of wide-area polymorphic demand side load participation system |
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| CN114421469A (en) * | 2022-01-26 | 2022-04-29 | 中国大唐集团科学技术研究院有限公司中南电力试验研究院 | Method for identifying and counting peak shaving frequency of turbonator under deep peak shaving working condition |
| CN114421469B (en) * | 2022-01-26 | 2024-05-10 | 中国大唐集团科学技术研究院有限公司中南电力试验研究院 | Method for identifying and counting peak regulation frequency of steam turbine generator under deep peak regulation working condition |
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| CN114818095B (en) * | 2022-06-30 | 2022-09-20 | 武昌理工学院 | Green building elastic constraint energy-saving optimization method |
| CN117638874A (en) * | 2023-11-07 | 2024-03-01 | 国网四川省电力公司经济技术研究院 | New energy system cost determination method based on source network charge storage collaborative optimization |
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