CN110112741A - High permeability photovoltaic power distribution network Optimization Scheduling based on electric power electric transformer - Google Patents
High permeability photovoltaic power distribution network Optimization Scheduling based on electric power electric transformer Download PDFInfo
- Publication number
- CN110112741A CN110112741A CN201910230043.1A CN201910230043A CN110112741A CN 110112741 A CN110112741 A CN 110112741A CN 201910230043 A CN201910230043 A CN 201910230043A CN 110112741 A CN110112741 A CN 110112741A
- Authority
- CN
- China
- Prior art keywords
- power
- electric
- photovoltaic
- pet
- transformer
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000009826 distribution Methods 0.000 title claims abstract description 30
- 238000005457 optimization Methods 0.000 title claims abstract description 27
- 230000035699 permeability Effects 0.000 title claims abstract description 10
- 238000010248 power generation Methods 0.000 claims abstract description 25
- 238000013178 mathematical model Methods 0.000 claims abstract description 11
- 238000000034 method Methods 0.000 claims description 14
- 230000005611 electricity Effects 0.000 claims description 9
- 238000009434 installation Methods 0.000 claims description 4
- 230000005540 biological transmission Effects 0.000 claims description 3
- 239000011159 matrix material Substances 0.000 claims description 3
- 230000009466 transformation Effects 0.000 claims description 2
- 230000009467 reduction Effects 0.000 abstract description 4
- 238000013461 design Methods 0.000 abstract description 3
- 238000004088 simulation Methods 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 230000007812 deficiency Effects 0.000 description 2
- 238000004146 energy storage Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 150000001875 compounds Chemical class 0.000 description 1
- 238000011217 control strategy Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000005622 photoelectricity Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000004904 shortening Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Classifications
-
- 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
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
-
- H02J3/383—
-
- 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
- H02J3/48—Controlling the sharing of the in-phase component
-
- 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
- H02J3/50—Controlling the sharing of the out-of-phase component
-
- 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]
-
- 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
Abstract
The present invention relates to a kind of high permeability photovoltaic power distribution network Optimization Scheduling based on electric power electric transformer, includes the following steps: 1) to establish the mathematical model of photovoltaic DC-to-AC converter Yu electric power electric transformer Collaborative Control according to distribution network electric energy quality standard；2) variable in mathematical model is divided into two classes, respectively PET configuration and PET and PV inverter controlled power, optimal scheduling is carried out to the two variables respectively, is converted into rank schedule optimization and lower rank power regulation.The design of the invention is scientific and reasonable, can adjust the active power and reactive power of photovoltaic DC-to-AC converter, reduces the operating cost and power loss of photovoltaic power generation unit, avoids the power reduction of photovoltaic power generation unit, improves working efficiency.
Description
Technical field
The invention belongs to electric power network technique fields, are related to power distribution network Optimization Scheduling, in particular to a kind of based on electric power electricity
The high permeability photovoltaic power distribution network Optimization Scheduling of sub- transformer.
Background technique
In order to cope with global energy crisis and environmental pollution, need to send out renewable energy, especially wind energy and solar energy
Electric resources are included in power grid.Therefore, the reliable and safe operation of electric system is constantly subjected to seriously pay close attention to.However, traditional distribution
The design of feeder line is to maintain one-way power to flow to residential block.As the households such as roof photovoltaic panel and minitype wind power turbine can
The popularity rate of renewable source of energy generation equipment is continuously improved, and solving power quality and integrity problem becomes particularly important, especially
When renewable energy is more than local electricity needs.The one kind for improving grid stability possible solution it is by energy storage device
It is integrated into power system network: the energy storage that low demand period is generated, for using later, it is ensured that between making full use of
It has a rest the available energy.
In recent years, with the development of power electronic technique and semiconductor technology, grid-connected photovoltaic system has great importance.
The system can be divided into single-stage and two-stage power conversion system.In single level system, DC/DC converter is eliminated, system is improved
Efficiency, reduce the cost of system.However, MPPT maximum power point tracking and DC/AC conversion must all be realized by inverter.Cause
This, is very important using suitable inverter control method.And the defect and deficiency of the prior art are as follows: traditional low pressure and
The electrical equipments such as switch, the transformer of medium pressure grade can not since house photovoltaic power generation unit and electric car access power grid extensively
The integration for effectively realizing DC generation unit and load, cannot replace middle pressure/low-tension transformer, forms AC and DC mixing and matches
Electric system.The prior art cannot receive scheduling signals well, adjust the direction of trend and speed in power grid, reach power grid operation
The control target of quotient's setting.The reliability of traditional power grid (radial or netted) and flexibility can not be accomplished well.
In conclusion for a kind of method of photovoltaic unit cooperative optimization, if requiring the reliability and spirit of raising power grid
Activity is vital.
By the retrieval to patent document, patent document identical with present patent application is not found.
Summary of the invention
It is an object of the invention to overcome the deficiencies of the prior art and provide a kind of Thief zones based on electric power electric transformer
Rate photovoltaic power distribution network Optimization Scheduling.This method can adjust the active power and reactive power of photovoltaic DC-to-AC converter, reduce light
The operating cost and power loss of overhead generator group, avoid the power reduction of photovoltaic power generation unit.
The present invention solves its technical problem and is achieved through the following technical solutions:
A kind of high permeability photovoltaic power distribution network Optimization Scheduling based on electric power electric transformer, it is characterised in that: should
Method includes the following steps:
1) according to distribution network electric energy quality standard, multiple objective function, power flow equation, electric system are constrained based on voltage deviation
The constraint of operational reliability, photovoltaic DC-to-AC converter and electric power electric transformer operational limit, establishes photovoltaic DC-to-AC converter and power electronics
The mathematical model of transformer Collaborative Control；
2) variable in mathematical model is divided into two classes, respectively PET configuration and PET and PV inverter controlled power, point
It is other that optimal scheduling is carried out to the two variables, it is converted into rank schedule optimization and lower rank power regulation.
Moreover, the mathematical model of the photovoltaic DC-to-AC converter and electric power electric transformer Collaborative Control are as follows:
Wherein: ρe1For the electricity price of t moment；
PLdIt (t) is first wife's net system net power load；
ρVIt (t) is the operating cost of photovoltaic power generation；
PVi(t) add up photovoltaic power generation quantity for i bus；
PLsIt (t) is the total-power loss of t moment；
Δ t is a few days ago optimal to be proposed allocation optimum with electric power electric transformer and control associated photovoltaic power generation
Dispatch 1 hour time interval of defined；
PijAnd QijThe active power and reactive power transmitted on branch respectively between bus I and j；
|Vi| for the voltage swing on bus i；
RijFor the resistance on branch i, j.
Moreover, the power flow equation, Operation of Electric Systems reliability, photovoltaic DC-to-AC converter and electric power electric transformer run pole
The constraint condition of limit are as follows:
(Vi min)2≤Vi r(t)2+Vi im(t)2≤(Vi max)2
Wherein: IijFor branch current；
GijAnd BijFor power grid admittance matrix；
UjFor branch voltage；
IijmaxFor the maximum current of transmission line of electricity；
Vi minAnd Vi maxThe respectively lower and upper limit value of busbar voltage；
Vi rAnd Vi imThe respectively real and imaginary parts of busbar voltage.
Moreover, the optimal scheduling step of the PET configuration and PET and PV inverter controlled power are as follows:
A) optimal location for finding electric power electric transformer is sent to the optimization of next stage as input parameter；
B) using the configuration of electric power electric transformer and power regulation as decision variable, overall goal is retouched with equation
It states:
Wherein:WithThe respectively power flow of two AC terminals of PET；
WithIt is the trend of respectively high voltage direct current terminal and low-voltage direct terminal；
For power loss of the PET in I bus；
Wherein:The power termination of electric power electric transformer low-voltage alternating-current terminal is connected to for i bus；
The power termination of direct current terminal is connected to for photovoltaic power generation；
WithRespectively in j bus, power source loads be connected to electric power electric transformer low-voltage alternating-current terminal and
The power termination of direct current terminal；
LCi,PET∈{0,1}
Wherein: LCi,PETIt indicates whether PET is located at bus i, and defines binary variable in this algorithm:
Wherein:WithThe respectively minimum and maximum electric power electric transformer of plan installation in the power system
Quantity；
C) under the configuration parameter that algorithm provides on upper layer, the power regulation of PET and PV inverter is realized in low order optimization:
Wherein:For the decision variable for indicating lower stage, in each time interval
It solves；
Wherein:For the rated capacity of photovoltaic DC-to-AC converter；
WithThe respectively active power and reactive power of PV unit k；
Tan θ is the limitation to the plant capacity factor connecting with distribution feeder；
For the power loss of power electronics interface.
The advantages and benefits of the present invention are:
1, dispatching method of the invention carrys out reasonable reformation distribution with electric power electric transformer, extensive to photovoltaic etc. is integrated
Renewable Energy Resources realize that the maximization of economy and environment plays a significant role to the maximum extent.
2, dispatching method of the invention passes through PET, active power and the reactive power for adjusting photovoltaic DC-to-AC converter, to greatest extent
Ground reduces the cost and power loss of test distribution network.
3, dispatching method of the invention is effectively communicated to the engineer in practice, and is applied to the demonstration item of actual environment
In mesh, there is directive significance to practice operation.
4, the design of the invention is scientific and reasonable, can adjust the active power and reactive power of photovoltaic DC-to-AC converter, reduces photovoltaic
The operating cost and power loss of generating set avoid the power reduction of photovoltaic power generation unit, improve working efficiency.
Detailed description of the invention
Fig. 1 be the embodiment of the present invention in electric power electric transformer be mounted on DC/AC power generation and load middle pressure/it is low
The structural schematic diagram being press-fitted in power grid；
Fig. 2 is the coordination optimization algorithm flow chart proposed in the embodiment of the present invention；
Fig. 3 is the 33 bus distribution network figures with the PET bus that PV is integrated and updates in the embodiment of the present invention；
Fig. 4 a) be the embodiment of the present invention 1 load and photovoltaic power generation day power profile, Fig. 4 b) be that the present invention is real
Apply the load and photovoltaic power generation day power profile of a scheme 2；
Fig. 5 a) be different situations of the embodiment of the present invention under scheme 1 day voltage distribution graph, Fig. 5 b) be the embodiment of the present invention
The day voltage distribution graph of scheme 2 under different situations；
Fig. 6 a) be power loss figure corresponding to different costs, Fig. 6 b under different situations of the embodiment of the present invention) it is the present invention
The voltage pattern of the forward position Pareto and 33 node power distribution nets in varied situations under embodiment different situations；
Fig. 7 a) be the active power loss figure of 33 node power distribution net of the embodiment of the present invention in varied situations, Fig. 7 b) it is this
The power loss curve figure of 33 node power distribution nets in varied situations in inventive embodiments.
Specific embodiment
Below by specific embodiment, the invention will be further described, and it is not limit that following embodiment, which is descriptive,
Qualitatively, this does not limit the scope of protection of the present invention.
A kind of high permeability photovoltaic power distribution network Optimization Scheduling based on electric power electric transformer, innovation exist
In: this method comprises the following steps:
1) according to distribution network electric energy quality standard, multiple objective function, power flow equation, electric system are constrained based on voltage deviation
The constraint of operational reliability, photovoltaic DC-to-AC converter and electric power electric transformer operational limit, establishes photovoltaic DC-to-AC converter and power electronics
The mathematical model of transformer Collaborative Control；
2) variable in mathematical model is divided into two classes, respectively PET configuration and PET and PV inverter controlled power, point
It is other that optimal scheduling is carried out to the two variables, it is converted into rank schedule optimization and lower rank power regulation.
The mathematical model of photovoltaic DC-to-AC converter and electric power electric transformer Collaborative Control are as follows:
Wherein: ρe1For the electricity price of t moment；
PLdIt (t) is first wife's net system net power load；
ρVIt (t) is the operating cost of photovoltaic power generation；
PVi(t) add up photovoltaic power generation quantity for i bus；
PLsIt (t) is the total-power loss of t moment；
Δ t is a few days ago optimal to be proposed allocation optimum with electric power electric transformer and control associated photovoltaic power generation
Dispatch 1 hour time interval of defined；
PijAnd QijThe active power and reactive power transmitted on branch respectively between bus I and j；
|Vi| for the voltage swing on bus i；
RijFor the resistance on branch i, j.
The constraint of power flow equation, Operation of Electric Systems reliability, photovoltaic DC-to-AC converter and electric power electric transformer operational limit
Condition are as follows:
(Vi min)2≤Vi r(t)2+Vi im(t)2≤(Vi max)2
Wherein: IijFor branch current；
GijAnd BijFor power grid admittance matrix；
UjFor branch voltage；
IijmaxFor the maximum current of transmission line of electricity；
Vi minAnd Vi maxThe respectively lower and upper limit value of busbar voltage；
Vi rAnd Vi imThe respectively real and imaginary parts of busbar voltage.
The optimal scheduling step of PET configuration and PET and PV inverter controlled power are as follows:
A) optimal location for finding electric power electric transformer is sent to the optimization of next stage as input parameter；
B) using the configuration of electric power electric transformer and power regulation as decision variable, overall goal is retouched with equation
It states:
Wherein:WithThe respectively power flow of two AC terminals of PET；
WithIt is the trend of respectively high voltage direct current terminal and low-voltage direct terminal；
For power loss of the PET in I bus；
Wherein:The power termination of electric power electric transformer low-voltage alternating-current terminal is connected to for i bus；
The power termination of direct current terminal is connected to for photovoltaic power generation；
WithRespectively in j bus, power source loads be connected to electric power electric transformer low-voltage alternating-current terminal and
The power termination of direct current terminal；
LCi,PET∈{0,1}
Wherein: LCi,PETIt indicates whether PET is located at bus i, and defines binary variable in this algorithm:
Wherein:WithThe respectively minimum and maximum electric power electric transformer of plan installation in the power system
Quantity；
C) under the configuration parameter that algorithm provides on upper layer, the power regulation of PET and PV inverter is realized in low order optimization:
Wherein:For the decision variable for indicating lower stage, in each time interval
It solves；
Wherein:For the rated capacity of photovoltaic DC-to-AC converter；
WithThe respectively active power and reactive power of PV unit k；
Tan θ is the limitation to the plant capacity factor connecting with distribution feeder；
For the power loss of power electronics interface.
In the present embodiment, electric power electric transformer is mounted on to middle pressure/low-voltage distribution of DC/AC power generation and load
In net, as shown in Figure 1.
Simulation study, the influence that analysis photovoltaic power generation is permeated on a large scale, optimization algorithm are carried out using the power distribution network of 33 nodes
Process is as shown in Fig. 2, simulation parameter is as shown in table 1.
1 simulation parameter table of table
| Name variable | Variable size |
| PV (22 node) | 0.5MW |
| PV (25 node) | 1.5MW |
| PV (30 node) | 1.0MW |
| PV (33 node) | 1.5MW |
| TS1 | 1.0MW |
| TS2 | 1.0MW |
| Electricity price | 0.8CNY/kwh |
| f1 | 0.3 |
| f2 | 0.08MW |
By in 4 buses of photovoltaic cells installation in a network, time series is emulated.As shown in figure 3, will reflect day
The coefficient of load curve multiplies calculating burden with power and load or burden without work.Initial load is equivalent to load-carrying water shown in coefficient 0.85
It is flat.The position candidate of PET configuration is the bus for being mounted with photovoltaic power generation and DC load, such as the charging base of electric car
Infrastructure.In view of the budget of power grid upgrading, it is assumed that two traditional transformers will be replaced by PET.
Tolerance interval of the voltage domain between 0.95~1.05pU is considered in the present embodiment.For the test macro of research.
Voltage limitation is strict implement, it means that excessive PV power generation.Midday sun must be reduced, to influence photovoltaic power generation
Utilization rate.In the present embodiment, for different control methods, emulation has been carried out to several situations and has been compared:
Situation 1: without the case of PV integral, as additional reference case；
Situation 2: the case where photovoltaic DC-to-AC converter real power control, being only adjusted photovoltaic DC-to-AC converter active power, to meet
The constraint of Operation of Electric Systems；
Situation 3: the active and reactive control situation of photovoltaic DC-to-AC converter, wherein active and reactive constrained by photovoltaic invertor operation
It is adjusted；
Situation 4: photovoltaic DC-to-AC converter power regulation cooperates PET configuration.
It loads section and photovoltaic power generation section is as shown in Figure 4.According to the different target that NSGA-II optimization problem is set, choosing
Take two schemes to be compared: scheme 1 (S1) indicates to reduce the control variables collection of cost, scheme 2 (S2) expression reduction power
The control variable of loss.
In the case where photovoltaic DC-to-AC converter active power controller, only the active power of photovoltaic DC-to-AC converter is adjusted.Base
In Fig. 3, the photovoltaic power generation of shortening is reduced, photovoltaic power generation can be further reduced by introducing electric power electric transformer.For light
The case where lying prostrate inverter active power and Reactive Power Control, can be by its active power and inactivity all by photovoltaic DC-to-AC converter
Operation constraint be adjusted.Total-power loss can be reduced using Reactive-power control in same scheme, as shown in Figure 4.
After NSGA-II optimization, the forward position Pareto can be described；Photovoltaic DC-to-AC converter power regulation and power electronics transformation
The case where device compound and cooperation, first or second objective function selects the two schemes under different situations according to figure 5.It is large-scale
The integrated electric power electric transformer auxiliary control strategy of photoelectricity provides optimal fitness function, and two targets can reach
Better lower value.
In Fig. 6, the active power of each bus shows the absorptivity of photovoltaic, especially in the maximum photovoltaic power generation time
In interval, the absorptivity of photovoltaic can be significantly improved by introducing electric power electric transformer, by the way that photovoltaic DC-to-AC converter is adjusted flexibly
Active power and reactive power can reduce power consumption.
Although disclosing the embodiment of the present invention and attached drawing for the purpose of illustration, those skilled in the art can be managed
Solution: do not departing from the present invention and spirit and scope of the appended claims in, various substitutions, changes and modifications be all it is possible,
Therefore, the scope of the present invention is not limited to the embodiment and attached drawing disclosure of that.
Claims (4)
1. a kind of high permeability photovoltaic power distribution network Optimization Scheduling based on electric power electric transformer, it is characterised in that: the party
Method includes the following steps:
1) according to distribution network electric energy quality standard, multiple objective function, power flow equation, Operation of Electric Systems are constrained based on voltage deviation
Photovoltaic DC-to-AC converter and power electronics transformation are established in the constraint of reliability, photovoltaic DC-to-AC converter and electric power electric transformer operational limit
The mathematical model of device Collaborative Control；
2) variable in mathematical model is divided into two classes, respectively PET configuration and PET and PV inverter controlled power, it is right respectively
The two variables carry out optimal scheduling, are converted into rank schedule optimization and lower rank power regulation.
2. the high permeability photovoltaic power distribution network Optimization Scheduling according to claim 1 based on electric power electric transformer,
It is characterized by: the mathematical model of the photovoltaic DC-to-AC converter and electric power electric transformer Collaborative Control are as follows:
Wherein: ρe1For the electricity price of t moment；
PLdIt (t) is first wife's net system net power load；
ρVIt (t) is the operating cost of photovoltaic power generation；
PVi(t) add up photovoltaic power generation quantity for i bus；
PLsIt (t) is the total-power loss of t moment；
Δ t is is proposed allocation optimum with electric power electric transformer and the associated photovoltaic power generation optimal scheduling a few days ago of control
1 hour time interval of defined；
PijAnd QijThe active power and reactive power transmitted on branch respectively between bus I and j；
|Vi| for the voltage swing on bus i；
RijFor the resistance on branch i, j.
3. the high permeability photovoltaic power distribution network Optimization Scheduling according to claim 1 based on electric power electric transformer,
It is characterized by: the power flow equation, Operation of Electric Systems reliability, photovoltaic DC-to-AC converter and electric power electric transformer operational limit
Constraint condition are as follows:
(Vi min)2≤Vi r(t)2+Vi im(t)2≤(Vi max)2
Wherein: IijFor branch current；
GijAnd BijFor power grid admittance matrix；
UjFor branch voltage；
IijmaxFor the maximum current of transmission line of electricity；
Vi minAnd Vi maxThe respectively lower and upper limit value of busbar voltage；
Vi rAnd Vi imThe respectively real and imaginary parts of busbar voltage.
4. the high permeability photovoltaic power distribution network Optimization Scheduling according to claim 1 based on electric power electric transformer,
It is characterized by: the optimal scheduling step of the PET configuration and PET and PV inverter controlled power are as follows:
A) optimal location for finding electric power electric transformer is sent to the optimization of next stage as input parameter；
B) using the configuration of electric power electric transformer and power regulation as decision variable, overall goal is described with equation:
Wherein:WithThe respectively power flow of two AC terminals of PET；
WithIt is the trend of respectively high voltage direct current terminal and low-voltage direct terminal；
For power loss of the PET in I bus；
Wherein:The power termination of electric power electric transformer low-voltage alternating-current terminal is connected to for i bus；
The power termination of direct current terminal is connected to for photovoltaic power generation；
WithRespectively in j bus, power source loads are connected to electric power electric transformer low-voltage alternating-current terminal and direct current
The power termination of terminal；
LCi,PET∈{0,1}
Wherein: LCi,PETIt indicates whether PET is located at bus i, and defines binary variable in this algorithm:
Wherein:WithThe respectively minimum and maximum electric power electric transformer quantity of plan installation in the power system；
C) under the configuration parameter that algorithm provides on upper layer, the power regulation of PET and PV inverter is realized in low order optimization:
Wherein:For the decision variable for indicating the lower stage, asked in each time interval
Solution；
Wherein:For the rated capacity of photovoltaic DC-to-AC converter；
WithThe respectively active power and reactive power of PV unit k；
Tan θ is the limitation to the plant capacity factor connecting with distribution feeder；
For the power loss of power electronics interface.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910230043.1A CN110112741A (en) | 2019-03-26 | 2019-03-26 | High permeability photovoltaic power distribution network Optimization Scheduling based on electric power electric transformer |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910230043.1A CN110112741A (en) | 2019-03-26 | 2019-03-26 | High permeability photovoltaic power distribution network Optimization Scheduling based on electric power electric transformer |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110112741A true CN110112741A (en) | 2019-08-09 |
Family
ID=67484648
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910230043.1A Pending CN110112741A (en) | 2019-03-26 | 2019-03-26 | High permeability photovoltaic power distribution network Optimization Scheduling based on electric power electric transformer |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110112741A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110729817A (en) * | 2019-10-30 | 2020-01-24 | 西安交通大学 | Power distribution network voltage coordination control system and control method thereof |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109004691A (en) * | 2018-07-13 | 2018-12-14 | 天津大学 | Ac/dc Power Systems containing electric power electric transformer Optimization Scheduling a few days ago |
| CN109066822A (en) * | 2018-07-18 | 2018-12-21 | 清华大学 | A kind of multi-point dispersion formula distribution system dispatching method based on electric power electric transformer |
-
2019
- 2019-03-26 CN CN201910230043.1A patent/CN110112741A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109004691A (en) * | 2018-07-13 | 2018-12-14 | 天津大学 | Ac/dc Power Systems containing electric power electric transformer Optimization Scheduling a few days ago |
| CN109066822A (en) * | 2018-07-18 | 2018-12-21 | 清华大学 | A kind of multi-point dispersion formula distribution system dispatching method based on electric power electric transformer |
Non-Patent Citations (1)
| Title |
|---|
| SHUANG GAO: "Coordinated optimal dispatch of photovoltaic units with updated power electronic transformer", 《ENERGY PROCEDIA》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110729817A (en) * | 2019-10-30 | 2020-01-24 | 西安交通大学 | Power distribution network voltage coordination control system and control method thereof |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Paska et al. | Hybrid power systems–An effective way of utilising primary energy sources | |
| Nema et al. | A current and future state of art development of hybrid energy system using wind and PV-solar: A review | |
| Zhang et al. | Energy management of PV-diesel-battery hybrid power system for island stand-alone micro-grid | |
| CN106786625B (en) | Power distribution network voltage coordination control method based on distributed energy supply system interaction capability | |
| CN111952958A (en) | Power distribution network flexible soft switch optimal configuration method considering control mode conversion | |
| Shahzad et al. | Model predictive control strategies in microgrids: A concise revisit | |
| Abdelkarim et al. | Supersession of large penetration photovoltaic power transients using storage batteries | |
| CN110112741A (en) | High permeability photovoltaic power distribution network Optimization Scheduling based on electric power electric transformer | |
| CN116885772A (en) | Optimal scheduling method for wind power-photovoltaic-pumped storage-thermal power combined operation system | |
| Rajkumar et al. | A novel solar PV equipped flexible AC/DC microgrid based energy management for effective residential power distribution | |
| Juelsgaard et al. | Loss minimization and voltage control in smart distribution grid | |
| Makhanya et al. | A Distributed Standalone Solar PV and Battery Energy Storage System DC Microgrid | |
| Safitri et al. | Integrated arrangement of advanced power electronics through hybrid smart grid system | |
| Attia | Impact of photovoltaic microgrid system on renewable energy building | |
| Su et al. | A Data-Driven Multi-Time Scale Coordinated Economic Dispatch Model for Flexible Interconnection Low-voltage Distribution Station Areas | |
| CN113541178A (en) | Offshore wind farm grid-connected system | |
| Kasturi et al. | Analysis of photovoltaic & battery energy storage system impacts on electric distribution system efficacy | |
| Zhou et al. | A Study on Source-Network-Demand Coordinated Expansion Planning of the Sending Power System Considering DC Transmission and Hydro-Solar Complementary | |
| Joshi et al. | A Resilient Hybrid Renewable Energy System for DC Microgrid with Inclusion of the Energy Storage | |
| He et al. | Application of AC/DC Hybrid System in Industrial Park Scenario | |
| Gu et al. | Impacts of residential PV and BESS on distribution network performance | |
| Adefarati et al. | Impact of PV Systems and Battery Storage in Hybrid Power Systems with Grid Connection | |
| Saabit et al. | Virtual Power Plant Implementation and Cost Minimization for Retail Industry | |
| Cui et al. | Photovoltaic grid-connected control system based on improved genetic algorithm and its implementation | |
| Nivetha et al. | Energy Management Based on Virtual Generation in DC Micro Grid Using Solar Power |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190809 |