CN110289642A - A kind of power distribution network layering method for optimizing scheduling based on exponential penalty function - Google Patents
A kind of power distribution network layering method for optimizing scheduling based on exponential penalty function Download PDFInfo
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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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- 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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
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Abstract
The present invention designs a kind of power distribution network layering method for optimizing scheduling based on exponential penalty function.This method is used to solve the problems, such as the coordination optimization of the power distribution network scheduling hierarchical system containing more microgrids, the selection of layering, interlayer consistency variable including the power distribution network containing more microgrids, the proposition for carrying out consistency modeling and coordination optimization strategy to power distribution network based on exponential penalty function method.The scheduling system containing the power distribution network of more microgrids is divided into distribution scheduling layer and microgrid dispatch layer by structure by this method.Corresponding constraint condition and objective function are established according to each layer of operational objective；Transaction based on power distribution network and microgrid chooses intermediate variable as interlayer consistency variable；Based on exponential penalty function method, consistency modeling is carried out to distribution in conjunction with the consistency variable of tie-line power transmission；Finally power distribution network scheduling hierarchical system is coordinated and optimized based on consistency model, the system of obtaining meets optimal solution when constraint condition.
Description
Technical field
The present invention relates to the technical fields of electric network coordination Optimized Operation, and in particular to a kind of distribution based on exponential penalty function
Net layering method for optimizing scheduling.
Background technique
New energy power generation technology is fast-developing in recent years, cause using new energy as the power supply of prime energy as distribution
Formula power supply largely accesses power grid, and multiagent trend is integrally presented in power grid.The access of distributed generation resource keeps the operation of power grid cleverer
It is living, the utilization rate of the energy is improved, operation of power networks reliability is increased.Active distribution network containing more micro-capacitance sensors is relative to traditional distribution
Net has a more flexible power flowcontrol, and being capable of distributed generation resource, controllable burden, energy storage device in active management power distribution network
Deng.Due to the unstability of distributed generation resource power output, traditional centralized optimization scheduling can no longer meet the tune of active distribution network
Degree demand.Power distribution network also exposes many problems in this development process.First, urban power consumption substantial increase,
Requirement for power supply reliability is increasingly harsh, causes blindly to invest to result in waste of resources, in cost to increase reliability
It rises.Second, the loss of outage of power grid causes investment to be greater than benefit, brings no small loss using selling benefit as evaluation criteria.Institute
It is the difficult point of power distribution network scheduling with, the reliability and economy of power grid, the relationship both balanced is needed to combine and is scheduled
Optimization, and reinforce application of its method in dispatching of power netwoks.Therefore, containing the active distribution network Optimal Scheduling of more micro-capacitance sensors
It is the hot spot of many researchers' researchs.
Theory of hierarchies is the theory that a complication system is carried out to data hierarchy using the method for hierarchical clustering.These data
With good class discrimination ability and it is suitble to classify, can be effectively applied to Data Mining.The theoretical maximum of hierarchy optimization is excellent
Gesture is that it can be there are many under constraint condition, obtain the optimal solution that a various aspects are coordinated mutually.The consistency problem of system is first
It was suggested before this in computer science, and was then gradually extended to other such as engineering, management, statistics fields.So-called one
Cause property refers to that in a polycomponent system, the quantity of state of all subsystems is consistent.Individual, communication topology and response are one
The basic three elements of cause property, are also consistency protocol.Consistency protocol, which refers to, to interact between intelligent body in complication system
Rule, it describes the process of information exchange between each intelligent body and its neighbor node.Based on consistency analysis layering power distribution network
Optimization problem is to solve the important means of the Optimal Scheduling in power distribution network.Exponential penalty function algorithm is by penalty function with index
Form is introduced into optimization object function.Exponential penalty function, which solves optimization problem, has computational efficiency height, functional assessment few and effective
Often, the advantages such as CPU operation time is few.
Summary of the invention
Technical problem to be solved by the invention is to provide a kind of, and the power distribution network based on exponential penalty function is layered optimizing scheduling
Distribution network system is layered and dispatches by method, finds interlayer consistency variable and carries out the modeling of interlayer consistency, and penalizes letter with index
Several methods optimizes scheduling to hierarchical system.The form of interlayer consistency variable exponential penalty function is updated to by the present invention
Each layer objective function considers also to have carried out interlayer coordination while each layer target.
A kind of power distribution network layering method for optimizing scheduling based on exponential penalty function, specific implementation step are as follows:
Step 1, the power distribution network containing more micro-capacitance sensors is layered, combing layering scheduling system framework, including power distribution network and
The objective function and constraint condition of micro-capacitance sensor；
Step 2, the consistency variable of interlayer is chosen；
Step 3, exponential penalty function method is proposed；
Step 4, consistency modeling is carried out to hierarchical system with exponential penalty function method, hierarchical system is dispatched to power distribution network
It is coordinated and optimized.
Further, in the step 1, the objective function of power distribution network is the electric cost of power distribution network internal load, network loss
Cost and the sum of with the Transaction Income of micro-capacitance sensor；
In formula,It is total power purchase power from power distribution network to all micro-capacitance sensors and sale of electricity power, and For purchase electricity price from power distribution network to all micro-capacitance sensors and sale of electricity electricity price,For with
Total load inside power grid,For total network loss of power distribution network,It is power distribution network to the sale of electricity electricity price of power distribution network internal load.
Further, in the step 1, distribution stratum reticulare constraint condition specifically, if power distribution network is to major network power purchase, power distribution network
It is equal to power distribution network to the sum of the sale of electricity power and the total load of power distribution network of micro-capacitance sensor, total network loss to the power purchase power of major network；If matching
Power grid to major network sale of electricity, power distribution network to the sale of electricity power of major network be equal to power purchase power from power distribution network to micro-capacitance sensor and power distribution network it is total
The difference of load, total network loss；
In the current situation, the physical constraint for considering major network operational safety and step-down transformer, does not allow power distribution network generally
Electric energy is provided to major network via step-down transformer, therefore,
In formula,Indicate the maximum transmission power of transmission line between power distribution network and major network；
Consider Line Flow and the node voltage constraint of power distribution network safety,
In formula,WithThe upper and lower limit of transimission power between respectively power distribution network node a, b,With
The respectively upper and lower limit of power distribution network node c voltage；
Maximum of the maximum exchange power of power distribution network and micro-capacitance sensor i no more than transmission line of electricity between power distribution network and micro-capacitance sensor
Transimission power and the maximum of micro-capacitance sensor i are outer by power；
In formula, qdm,iPower is exchanged with micro-capacitance sensor i for power distribution network,It is power distribution network to the power purchase of micro-capacitance sensor i
Power and sale of electricity power,The maximum transmission power of transmission line of electricity between power distribution network and micro-capacitance sensor i,For micro-capacitance sensor i
Consider that the maximum of its safe operation is outer by power.
Further, in the step 1, micro-capacitance sensor is optimal for target with economy, optimization and power distribution network, new energy, storage
Transaction between energy and load, objective function are
maxCmic,i (9)
FS,i=pS,iqS,i,* (11)
FG,i=pG,iqG,i (12)
In formula, under be designated as i variable indicate it is related to micro-capacitance sensor i,For the sale of electricity function of micro-capacitance sensor i internally load
Rate,Purchase electricity price and sale of electricity electricity price of the micro-capacitance sensor i to power distribution network are respectively indicated,Respectively indicate micro-capacitance sensor
Power purchase power and sale of electricity power of the i to power distribution network, pS,iIndicate energy storage unit operating cost, qS,i,*Indicate energy storage discharge/charge electric work
Rate, pG,iIndicate new energy specific power cost, qG,iIndicate the new energy power output of micro-capacitance sensor i, FS,iAnd FG,iRespectively indicate micro- electricity
Net the storage energy operation cost and new energy power output cost of i.
Further, in the step 1, micro-capacitance sensor layer constraint condition specifically includes:
Micro-capacitance sensor i power-balance constraint:
In formula, qS,i,dchAnd qS,i,chFor energy storage electric discharge and charge power in micro-capacitance sensor i；
Micro-capacitance sensor trend constraint and voltage constrain:
In formula,WithThe upper and lower limit of transimission power between respectively micro-capacitance sensor i interior joint z and node u,
WithFor the upper and lower limit run on node z；
The units limits of new energy j in micro-capacitance sensor i:
In formula,WithFor the maximum power and minimum power of new energy j in micro-capacitance sensor i；
The power constraint of energy storage in micro-capacitance sensor i:
In formula,WithThe maximum value of energy storage electric discharge and charge power in respectively micro-capacitance sensor i；
Same energy storage cannot be charged and discharged simultaneously in the same period, then qS,i,dchWith qS,i,chMeet
qS,i,dchqS,i,ch=0 (20)
Further, in the step 2, power distribution network repeatedly kicks into row Power Exchange by transmission line of electricity and micro-capacitance sensor faciation, matches
Power grid is to the sale of electricity power and power purchase power of micro-capacitance sensor groupWithSale of electricity power and power purchase of the micro-capacitance sensor i to power distribution network
Power isWithDefinitionWith all micro-capacitance sensors to the power purchase power of power distribution networkFor shared variable,With
Sale of electricity power of all micro-capacitance sensors to power distribution networkFor shared variable；
It is each to need to guarantee that power distribution network is equal to the sale of electricity power of each micro-capacitance sensor for distribution stratum reticulare and micro-capacitance sensor layer independent optimization
To the power purchase power of power distribution network, introduce consistency constraint condition is a micro-capacitance sensor
Further, it in the step 3, introduces exponential penalty function exponential penalty function (EPF)
In formula,WithIt is multiplier,WithIt is punishment parameter, e is Euler
Constant,WithInitial value be any positive number, can update as the following formula:
Punishment parameterWithArbitrary value can be given.
Further, in the step 4, consider consistency constraint (21-22), then the Optimized model of distribution stratum reticulare becomes
In formula, min fd(rd) represent formula (1), gd(rd)≤0 represents formula (2)-(3), (5)-(8), hd(rdThe generation of)=0
Table formula (4), then layer by layer optimizing is used, so that system is optimal.
What the present invention reached has the beneficial effect that theory of hierarchies of the invention can successfully manage traditional centralized optimization scheduling
Insurmountable problem, such as the economy and safety of balance power grid, it is contemplated that the main need of all main bodys in electric system
It asks, and is balanced, it is optimal to reach comprehensive benefit.Association index penalty function method, the present invention improve the calculating of optimization problem
Efficiency reduces the operation duration of CPU.
Detailed description of the invention
Fig. 1 is that power distribution network of the present invention is layered method for optimizing scheduling flow chart.
Specific embodiment
Technical solution of the present invention is described in further detail with reference to the accompanying drawings of the specification.
A kind of power distribution network layering method for optimizing scheduling based on exponential penalty function, specific implementation step are as follows:
Step 1, the power distribution network containing more micro-capacitance sensors is layered, combing layering scheduling system framework, including power distribution network and
The objective function and constraint condition of micro-capacitance sensor.
In the step 1, the objective function of power distribution network be the electric cost of power distribution network internal load, Web-based exercise and with it is micro-
The sum of Transaction Income of power grid.
In formula,It is total power purchase power from power distribution network to all micro-capacitance sensors and sale of electricity power, and For purchase electricity price from power distribution network to all micro-capacitance sensors and sale of electricity electricity price,For with
Total load inside power grid,For total network loss of power distribution network,It is power distribution network to the sale of electricity electricity price of power distribution network internal load.
Distribution stratum reticulare constraint condition specifically, if power distribution network, to major network power purchase, power distribution network is equal to the power purchase power of major network
Power distribution network is to the sum of the sale of electricity power and the total load of power distribution network of micro-capacitance sensor, total network loss；If power distribution network is to major network sale of electricity, power distribution network
It is equal to power purchase power from power distribution network to micro-capacitance sensor and the total load of power distribution network, the difference of total network loss to the sale of electricity power of major network.
In the current situation, the physical constraint for considering major network operational safety and step-down transformer, does not allow power distribution network generally
Electric energy is provided to major network via step-down transformer, therefore,
In formula,Indicate the maximum transmission power of transmission line between power distribution network and major network.
Consider Line Flow and the node voltage constraint of power distribution network safety,
In formula,WithThe upper and lower limit of transimission power between respectively power distribution network node a, b,With
The respectively upper and lower limit of power distribution network node c voltage.
Maximum of the maximum exchange power of power distribution network and micro-capacitance sensor i no more than transmission line of electricity between power distribution network and micro-capacitance sensor
Transimission power and the maximum of micro-capacitance sensor i are outer by power.
In formula, qdm,iPower is exchanged with micro-capacitance sensor i for power distribution network,It is power distribution network to the power purchase of micro-capacitance sensor i
Power and sale of electricity power,The maximum transmission power of transmission line of electricity between power distribution network and micro-capacitance sensor i,For micro-capacitance sensor i
Consider that the maximum of its safe operation is outer by power.
Micro-capacitance sensor is optimal for target with economy, optimization and the transaction between power distribution network, new energy, energy storage and load,
Its objective function is
maxCmic,i (9)
FS,i=pS,iqS,i,* (11)
FG,i=pG,iqG,i (12)
In formula, under be designated as i variable indicate it is related to micro-capacitance sensor i,For the sale of electricity function of micro-capacitance sensor i internally load
Rate,Purchase electricity price and sale of electricity electricity price of the micro-capacitance sensor i to power distribution network are respectively indicated,Respectively indicate micro-capacitance sensor
Power purchase power and sale of electricity power of the i to power distribution network, pS,iIndicate energy storage unit operating cost, qS,i,*Indicate energy storage discharge/charge electric work
Rate, pG,iIndicate new energy specific power cost, qG,iIndicate the new energy power output of micro-capacitance sensor i, FS,iAnd FG,iRespectively indicate micro- electricity
Net the storage energy operation cost and new energy power output cost of i.
Micro-capacitance sensor layer constraint condition specifically includes:
Micro-capacitance sensor i power-balance constraint:
In formula, qS,i,dchAnd qS,i,chFor energy storage electric discharge and charge power in micro-capacitance sensor i；
Micro-capacitance sensor trend constraint and voltage constrain:
In formula,WithThe upper and lower limit of transimission power between respectively micro-capacitance sensor i interior joint z and node u,
WithFor the upper and lower limit run on node z.
The units limits of new energy j in micro-capacitance sensor i:
In formula,WithFor the maximum power and minimum power of new energy j in micro-capacitance sensor i.
The power constraint of energy storage in micro-capacitance sensor i:
In formula,WithThe maximum value of energy storage electric discharge and charge power in respectively micro-capacitance sensor i.
Same energy storage cannot be charged and discharged simultaneously in the same period, then qS,i,dchWith qS,i,chMeet
qS,i,dchqS,i,ch=0 (20)
Step 2, the consistency variable of interlayer is chosen.
In the step 2, power distribution network repeatedly kicks into row Power Exchange, power distribution network Xiang Wei electricity by transmission line of electricity and micro-capacitance sensor faciation
Net group sale of electricity power and power purchase power beWithMicro-capacitance sensor i is to the sale of electricity power and power purchase power of power distribution network
WithDefinitionWith all micro-capacitance sensors to the power purchase power of power distribution networkFor shared variable,With all micro-capacitance sensors
To the sale of electricity power of power distribution networkFor shared variable.
It is each to need to guarantee that power distribution network is equal to the sale of electricity power of each micro-capacitance sensor for distribution stratum reticulare and micro-capacitance sensor layer independent optimization
To the power purchase power of power distribution network, introduce consistency constraint condition is a micro-capacitance sensor
Step 3, exponential penalty function method is proposed.
In the step 3, introduce exponential penalty function exponential penalty function (EPF)
In formula,WithIt is multiplier,WithIt is punishment parameter, e is Euler
Constant,WithInitial value be any positive number, can update as the following formula:
Punishment parameterWithArbitrary value can be given.
Step 4, consistency modeling is carried out to hierarchical system with exponential penalty function method, hierarchical system is dispatched to power distribution network
It is coordinated and optimized.
In the step 4, consider consistency constraint (21-22), then the Optimized model of distribution stratum reticulare becomes
In formula, min fd(rd) represent formula (1), gd(rd)≤0 represents formula (2)-(3), (5)-(8), hd(rdThe generation of)=0
Table formula (4), then layer by layer optimizing is used, so that system is optimal.
The foregoing is merely better embodiment of the invention, protection scope of the present invention is not with above embodiment
Limit, as long as those of ordinary skill in the art's equivalent modification or variation made by disclosure according to the present invention, should all be included in power
In the protection scope recorded in sharp claim.
Claims (8)
1. a kind of power distribution network based on exponential penalty function is layered method for optimizing scheduling, it is characterised in that: specific implementation step is as follows:
Step 1, the power distribution network containing more micro-capacitance sensors is layered, combing layering scheduling system framework, including power distribution network and micro- electricity
The objective function and constraint condition of net；
Step 2, the consistency variable of interlayer is chosen；
Step 3, exponential penalty function method is proposed；
Step 4, consistency modeling is carried out to hierarchical system with exponential penalty function method, power distribution network scheduling hierarchical system is carried out
Coordination optimization.
2. a kind of power distribution network based on exponential penalty function according to claim 1 is layered method for optimizing scheduling, feature exists
In: in the step 1, the objective function of power distribution network is electric cost, Web-based exercise and and the micro-capacitance sensor of power distribution network internal load
The sum of Transaction Income；
In formula,It is total power purchase power from power distribution network to all micro-capacitance sensors and sale of electricity power, and For purchase electricity price from power distribution network to all micro-capacitance sensors and sale of electricity electricity price,For with
Total load inside power grid,For total network loss of power distribution network,It is power distribution network to the sale of electricity electricity price of power distribution network internal load.
3. a kind of power distribution network based on exponential penalty function according to claim 1 is layered method for optimizing scheduling, feature exists
In: in the step 1, distribution stratum reticulare constraint condition specifically, if power distribution network is to major network power purchase, power purchase function of the power distribution network to major network
Rate is equal to power distribution network to the sum of the sale of electricity power and the total load of power distribution network of micro-capacitance sensor, total network loss；If power distribution network to major network sale of electricity,
Power distribution network to the sale of electricity power of major network be equal to power purchase power from power distribution network to micro-capacitance sensor and the total load of power distribution network, total network loss it
Difference；
In the current situation, consider major network operational safety and step-down transformer physical constraint, do not allow generally power distribution network via
Step-down transformer provides electric energy to major network, therefore,
In formula,Indicate the maximum transmission power of transmission line between power distribution network and major network；
Consider Line Flow and the node voltage constraint of power distribution network safety,
In formula,WithThe upper and lower limit of transimission power between respectively power distribution network node a, b,WithRespectively
For the upper and lower limit of power distribution network node c voltage；
Maximum transmitted of the maximum exchange power of power distribution network and micro-capacitance sensor i no more than transmission line of electricity between power distribution network and micro-capacitance sensor
The maximum of power and micro-capacitance sensor i are outer by power；
In formula, qdm,iPower is exchanged with micro-capacitance sensor i for power distribution network,For power purchase power from power distribution network to micro-capacitance sensor i with
Sale of electricity power,The maximum transmission power of transmission line of electricity between power distribution network and micro-capacitance sensor i,It is considered for micro-capacitance sensor i
The maximum of safe operation is outer by power.
4. a kind of power distribution network based on exponential penalty function according to claim 1 is layered method for optimizing scheduling, feature exists
In: in the step 1, micro-capacitance sensor is optimal for target with economy, between optimization and power distribution network, new energy, energy storage and load
Transaction, objective function is
maxCmic,i (9)
FS,i=pS,iqS,i,* (11)
FG,i=pG,iqG,i (12)
In formula, under be designated as i variable indicate it is related to micro-capacitance sensor i,For the sale of electricity power of micro-capacitance sensor i internally load,Purchase electricity price and sale of electricity electricity price of the micro-capacitance sensor i to power distribution network are respectively indicated,Respectively indicate micro-capacitance sensor i to
The power purchase power and sale of electricity power of power distribution network, pS,iIndicate energy storage unit operating cost, qS,i,*Indicate energy storage charge/discharge power,
pG,iIndicate new energy specific power cost, qG,iIndicate the new energy power output of micro-capacitance sensor i, FS,iAnd FG,iRespectively indicate micro-capacitance sensor i
Storage energy operation cost and new energy contribute cost.
5. a kind of power distribution network based on exponential penalty function according to claim 1 is layered method for optimizing scheduling, feature exists
In: in the step 1, micro-capacitance sensor layer constraint condition specifically includes:
Micro-capacitance sensor i power-balance constraint:
In formula, qS,i,dchAnd qS,i,chFor energy storage electric discharge and charge power in micro-capacitance sensor i；
Micro-capacitance sensor trend constraint and voltage constrain:
In formula,WithThe upper and lower limit of transimission power between respectively micro-capacitance sensor i interior joint z and node u,With
For the upper and lower limit run on node z；
The units limits of new energy j in micro-capacitance sensor i:
In formula,WithFor the maximum power and minimum power of new energy j in micro-capacitance sensor i；
The power constraint of energy storage in micro-capacitance sensor i:
In formula,WithThe maximum value of energy storage electric discharge and charge power in respectively micro-capacitance sensor i；
Same energy storage cannot be charged and discharged simultaneously in the same period, then qS,i,dchWith qS,i,chMeet
qS,i,dchqS,i,ch=0 (20).
6. a kind of power distribution network based on exponential penalty function according to claim 1 is layered method for optimizing scheduling, feature exists
In: in the step 2, power distribution network repeatedly kicks into row Power Exchange by transmission line of electricity and micro-capacitance sensor faciation, and power distribution network is to micro-capacitance sensor group
Sale of electricity power and power purchase power beWithMicro-capacitance sensor i is to the sale of electricity power and power purchase power of power distribution networkWithDefinitionWith all micro-capacitance sensors to the power purchase power of power distribution networkFor shared variable,With all micro-capacitance sensors to
The sale of electricity power of power distribution networkFor shared variable；
It is each micro- to need to guarantee that power distribution network is equal to the sale of electricity power of each micro-capacitance sensor for distribution stratum reticulare and micro-capacitance sensor layer independent optimization
To the power purchase power of power distribution network, introduce consistency constraint condition is power grid
。
7. a kind of power distribution network based on exponential penalty function according to claim 1 is layered method for optimizing scheduling, feature exists
In: in the step 3, introduce exponential penalty function exponential penalty function (EPF)
In formula,WithIt is multiplier,WithIt is punishment parameter, e is Euler's constant,WithInitial value be any positive number, can update as the following formula:
Punishment parameterWithArbitrary value can be given.
8. a kind of power distribution network based on exponential penalty function according to claim 1 is layered method for optimizing scheduling, feature exists
In: in the step 4, consider consistency constraint (21-22), then the Optimized model of distribution stratum reticulare becomes
In formula, min fd(rd) represent formula (1), gd(rd)≤0 represents formula (2)-(3), (5)-(8), hd(rd)=0 represents public affairs
Formula (4), then layer by layer optimizing is used, so that system is optimal.
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| CN113285458A (en) * | 2021-06-11 | 2021-08-20 | 燕山大学 | Decomposition and coordination method and system for economic dispatching of active power distribution network comprising multiple micro-grids |
| CN113991753A (en) * | 2021-12-01 | 2022-01-28 | 山东科技大学 | Optimal scheduling method and system for power transmission network structure |
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| CN108734350A (en) * | 2018-05-17 | 2018-11-02 | 燕山大学 | A kind of independent method for solving with combined dispatching of the power distribution network containing micro-capacitance sensor |
| CN109713732A (en) * | 2019-01-17 | 2019-05-03 | 南京邮电大学 | A kind of method of more micro-capacitance sensors and power distribution network coordination optimization scheduling |
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| CN111555370A (en) * | 2020-05-20 | 2020-08-18 | 云南电网有限责任公司电力科学研究院 | Power distribution network layered coordination scheduling method and device based on cloud edge coordination |
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| CN113991753A (en) * | 2021-12-01 | 2022-01-28 | 山东科技大学 | Optimal scheduling method and system for power transmission network structure |
| CN113991753B (en) * | 2021-12-01 | 2023-07-11 | 山东科技大学 | Power transmission network structure optimization scheduling method and system |
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