CN106655285A - Iterative algorithm-based multi-energy complementary micro-grid optimization operation control system and method - Google Patents
Iterative algorithm-based multi-energy complementary micro-grid optimization operation control system and method Download PDFInfo
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- CN106655285A CN106655285A CN201611261524.1A CN201611261524A CN106655285A CN 106655285 A CN106655285 A CN 106655285A CN 201611261524 A CN201611261524 A CN 201611261524A CN 106655285 A CN106655285 A CN 106655285A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
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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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- Power Engineering (AREA)
- Air Conditioning Control Device (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention provides an iterative algorithm-based multi-energy complementary micro-grid optimization operation control system and method. The iterative algorithm-based multi-energy complementary micro-grid optimization operation control system is characterized by comprising a micro-grid and a control system thereof, an environmental monitoring machine and a distributed energy source output prediction module, wherein the distributed energy source output prediction module is connected with the micro-grid and the control system thereof and the environmental monitoring machine separately. According to the control system and method provided by the invention, a micro-source and a load can be monitored online, the load condition in the next period and the generating capacity of a photovoltaic machine, a wind turbine and the like are obtained in real time, the output conditions of distributed energy sources in the micro-grid in various periods are continuously corrected through an iterative algorithm, the optimal output of the distributed energy sources in the micro-grid in each period is optimized, the feasibility of the micro-grid is improved and the optimal economy is achieved.
Description
Technical field
The present invention relates to field of power, is to be related to a kind of micro- electricity of providing multiple forms of energy to complement each other based on iterative algorithm specifically
Network optimization operation control system and method.
Background technology
With the new-generation technology including the fossil fuel including the regenerative resources such as wind-powered electricity generation, photovoltaic and high-efficiency cleaning
Development, distributed energy DG day by day become meet load growth demand, reduce environmental pollution, improve comprehensive utilization rate of energy source and
A kind of effective way of power supply reliability.DG have the advantages that small investment, generation mode flexibly, can with environmental compatible, in distribution
It is widely used in net.
But single distributed energy electricity generation system all can be restricted by natural resources, can be by various distributed energies
Integrated, realized that multiple-energy-source is reasonably utilized, not only reduced cost, improve the stability and reliability of system output,
The range of application in market can also be expanded.Honourable combustion gas storage multi-energy complementary micro-grid is exactly the characteristics of utilizing this complementary, will be various
The technology that electricity generation system is integrated.
Load in multi-energy complementation micro-capacitance sensor exert oneself with each renewable micro- source it is affected by environment, with time variation and non-thread
Property, therefore the operation control of micro-capacitance sensor is complicated.It is at present basic to be optimized using off-line operation, instructed with offline operation result point
The cloth energy is exerted oneself.But the characteristic in the micro- source in microgrid inside, the when deformation and non-linear of state, this method is difficult to realize real
Optimization operation, so as to cause distributed energy undercapacity in microgrid or the situation of surplus of exerting oneself, microgrid is stablized
Operation and economy cause very big interference.So the on-line operation optimization using actual measurement in combination with prediction is necessary.
The content of the invention
It is an object of the invention to overcome the weak point of above-mentioned conventional art, there is provided a kind of multipotency based on iterative algorithm
Complementary micro-capacitance sensor optimization operation control system and method.Its objective is in the method using actual measurement in combination with prediction to following two
Hour internal loading and distribution type renewable energy EIAJ are predicted, and by alternative manner the optimal of controllable micro- source is calculated
Operating point, On-line Control is carried out to it, lowers micro-capacitance sensor operating cost.
The technical scheme is that：
A kind of multi-energy complementary micro-grid based on iterative algorithm optimizes operation control system, it is characterised in that：Including microgrid
And its control system, environmental monitoring machine and distributed energy are exerted oneself prediction module, distributed energy exert oneself prediction module respectively with
Microgrid and its control system and the connection of environmental monitoring machine.
The environmental data of future time is provided by environmental monitoring machine, comprising temperature, illumination, wind speed, is obtained in the time
Load and photovoltaic, the situation of exerting oneself of wind-driven generator.
A kind of concrete prioritization scheme, distributed energy prediction module of exerting oneself is exerted oneself including several following n distributed energies
Prediction module.
It is respectively used to predict exerting oneself for multiple hours distributed energies.
A kind of concrete prioritization scheme, distributed energy is exerted oneself, and to include that following one hour distributed energy is exerted oneself pre- for prediction module
Survey module and following two hours distributed energies are exerted oneself prediction module, following one hour distributed energy is exerted oneself and prediction module and is
Following two hours distributed energies are exerted oneself prediction module connection, and environmental monitoring machine and following one hour distributed energy are exerted oneself prediction
Module connects.
A kind of concrete prioritization scheme, distributed energy prediction module of exerting oneself includes digital signal processor, numeral letter
Number processor is connected by circuit prediction module of exerting oneself with environmental monitoring machine, microgrid and its control system and distributed energy respectively
Connect.
A kind of concrete prioritization scheme, microgrid and its control system include electric heating equipment and its control system and/or photovoltaic
And its control system and/or wind energy conversion system and its control system and/or natural gas internal combustion engine and its control system and/or battery and
Its control system and/or electric refrigeration plant and its control system and/or electric load and/or waste heat boiler and/or waste heat lithium bromide
And/or heat accumulation cistern and/or thermic load and/or the cold cistern of storage and/or refrigeration duty.
A kind of concrete prioritization scheme, electric heating equipment and its control system, photovoltaic and its control system, wind energy conversion system and its control
System processed, natural gas internal combustion engine and its control system, battery and its control system, electric refrigeration plant and its control system and electricity
Load is respectively connecting to power bus-bar.
A kind of concrete prioritization scheme, natural gas internal combustion engine and its control system are connected to heating power bus and/or cold power bus.
A kind of concrete prioritization scheme, electric heating equipment and its control system, heat accumulation cistern and thermic load are connected to heat
Power bus；Electric refrigeration plant and its control system, the cold cistern of storage and refrigeration duty are respectively connecting to cold power bus.
A kind of concrete prioritization scheme, electric heating equipment and its control system, photovoltaic and its control system, wind energy conversion system and its control
System processed, natural gas internal combustion engine and its control system, battery and its control system, electric refrigeration plant and its control system, storage
Hot cistern and its control system, store up cold cistern and its control system is exerted oneself instruction control.
A kind of multi-energy complementary micro-grid based on iterative algorithm optimizes progress control method, it is characterised in that including following
Step：
Step one：Following n moment distributed energy prediction module and extraneous communication, obtain environmental data and (n-1) moment
And its storage cool and thermal power data of following instant；
Step 2：The regenerative resource at n moment and the poor E of resident's electric load are obtained, if E>0, then generate electricity, meet level
Weighing apparatus；If E<0, to microgrid transmission energy；
Step 3：Judge what n moment and its following instant lacked with the presence or absence of electricity, if lacking, improve storage；If not lacking
It is weary, then the generating at n moment is reduced accordingly；
Step 4：Stopping criterion for iteration judgement, if reaching maximum iteration time, terminates iteration, during by the following n for obtaining
Microgrid and its control system are passed in the instruction of exerting oneself for carving each distributed energy；Otherwise iterations adds 1, goes to step 1.
The present invention can monitor micro- source and load on-line, and load condition and photovoltaic, wind energy conversion system of future time period etc. are obtained in real time
Can generated energy, by iterative algorithm, constantly amendment day part micro-capacitance sensor inside distributed energy is exerted oneself situation, optimization each
The optimal output of each distributed energy in period microgrid inside, improves the feasibility of micro-capacitance sensor, realizes Optimum Economic；
The inventive method reduces the interference of change due to environment to microgrid stable operation, while reduction of reasonably exerting oneself
The waste rate of energy, improves the economy of microgrid so that microgrid has more generalization.
With reference to the accompanying drawings and detailed description the invention will be further described.
Description of the drawings
Fig. 1 is the structural schematic block diagram of the present invention.
Fig. 2 is the microgrid and its control system figure of the present invention.
Fig. 3 is that the distributed energy of the present invention is exerted oneself prediction module figure.
Fig. 4 exerts oneself prediction module using distributed energy in iterative algorithm on-line prediction micro-capacitance sensor for distributed energy of the present invention
Source is exerted oneself procedure of operating mode figure.
Specific embodiment
Embodiment 1：As shown in Figure 1 to Figure 3, a kind of multi-energy complementary micro-grid optimization operation control system based on iterative algorithm
System, including microgrid and its control system 1, environmental monitoring machine 2 and distributed energy exert oneself prediction module, distributed energy is exerted oneself pre-
Survey module to be connected with microgrid and its control system 1 and environmental monitoring machine 2 respectively.
Distributed energy prediction module of exerting oneself is exerted oneself prediction module including several following n distributed energies.
Following n distributed energies exert oneself prediction module can be using the distributed energy of iterative algorithm circulation acquisition following (n-1)
Source exert oneself prediction module offer the (n-1)th moment cool and thermal power storage condition and prediction n-th hour all distributed energy afterwards
The cool and thermal power storage condition at the corresponding moment that prediction module of exerting oneself is provided, and according in these the n-th moment of data prediction micro-capacitance sensors
Portion each distributed energy is exerted oneself.
Distributed energy prediction module of exerting oneself includes that following one hour distributed energy is exerted oneself prediction module 3 and following two little
When distributed energy exert oneself prediction module 4, following one hour distributed energy is exerted oneself and prediction module 3 and was distributed for following two hours
Formula energy prediction module 4 of exerting oneself connects, and environmental monitoring machine 2 and following one hour distributed energy prediction module 3 of exerting oneself connects.
Distributed energy exerts oneself prediction module including digital signal processor, digital signal processor by circuit respectively with
Environmental monitoring machine, microgrid and its control system and distributed energy exert oneself prediction module connection.
Digital signal processor is TMS320f2818dsp chips 18, and circuit includes max485 circuits 19 and max485 circuits
20；TMS320f2818dsp chips 18 are connected respectively by max485 circuits 19, max485 circuits 20 with environmental monitoring machine 2, micro-
Net and its control system 1 and distributed energy exert oneself prediction module connection.
Distributed energy exert oneself prediction module carry out environmental data, previous moment and following sessions storage cool and thermal power remaining data
Communication and these data are processed using iterative algorithm, obtain the optimal output point of each distributed energy in microgrid inside,
And by the distributed energy for calculating exert oneself prediction instruction microgrid and its control system are conveyed to by max485.
Microgrid and its control system 1 include electric heating equipment and its control system 5 and/or photovoltaic and its control system 6 and/
Or wind energy conversion system and its control system 7 and/or natural gas internal combustion engine and its control system 8 and/or battery and its control system 9
And/or electric refrigeration plant and its control system 11 and/or electric load 10 and/or waste heat boiler 12 and/or waste heat lithium bromide 13 and/
Or heat accumulation cistern 14 and/or thermic load 15 and/or the cold cistern 16 of storage and/or refrigeration duty 17.
Additionally, above-mentioned each electricity generation system can also as needed select one of which or several.
Electric heating equipment and its control system 5, photovoltaic and its control system 6, wind energy conversion system and its control system 7, natural gas
Internal combustion engine and its control system 8, battery and its control system 9, electric refrigeration plant and its 10 points of control system 11 and electric load
Power bus-bar is not connected to it.
Natural gas internal combustion engine and its control system 8 are connected to heating power bus and/or cold power bus.
On the one hand the waste heat that natural gas internal combustion engine and its control system 8 send can be connected to heating power by waste heat boiler 12
Bus；On the other hand cold power bus can be connected to by waste heat lithium bromide 13；
Heat accumulation cistern 14 and thermic load 15 are connected to heating power bus；
Electric refrigeration plant and its control system 11, the cold cistern 16 of storage and refrigeration duty 17 are respectively connecting to cold power bus.
Electric heating equipment and its control system 5, photovoltaic and its control system 6, wind energy conversion system and its control system 7, natural gas
Internal combustion engine and its control system 8, battery and its control system 9, electric refrigeration plant and its control system 10, heat accumulation cistern and
Its control system 14, stores up cold cistern and its control system 16 is exerted oneself instruction control.
A kind of multi-energy complementary micro-grid based on iterative algorithm optimizes progress control method, it is characterised in that including following
Step：
Step one：Following n moment distributed energy prediction module obtains environment number by max485 circuits and extraneous communication
According to and n-1 moment and its following instant storage cool and thermal power data；
Step 2：Obtain the regenerative resource at n moment and the difference of resident's electric load, formula citing：
E=Eload-PV-Pwind, wherein EloadTo obtain data, PVFor photovoltaic and its power output of control system 6, Pwind
For wind energy conversion system and its power output of control system 7.
If E>0, then gas engine generating, unconditionally meets electric equilibrium；If E<0, to microgrid transmission energy, can be deposited with battery
Storage is got up, and also can be heated by electricity, and electric refrigeration plant applies to heating power bus, cold power bus；
Step 3：Judge what n moment and its following instant lacked with the presence or absence of electricity, if lacking, improve gas engine and generate electricity
Gas consumption, is stored with battery, is easy to n moment and the electric peak regulation of following instant to use；If having no lack of, n is reduced accordingly
The gas engine generating gas consumption at moment；
Step 4：Judge the situation that n moment and its following instant lack with the presence or absence of cold air, if lacking, improve combustion gas
Mechanism cold gas consumption, while starting electric refrigeration plant auxiliary cooling, unnecessary cold is stored with cold accumulating pond, when being easy to follow-up
The cool tone peak at quarter is used；If having no lack of, the gas engine refrigeration gas consumption at n moment is reduced accordingly；
Step 5：Judge the situation that n moment and its following instant lack with the presence or absence of hot gas, if lacking, improve combustion gas
The hot gas consumption of mechanism, while starting electric heating equipment auxiliary heating, unnecessary heat is stored with heat storage pool, when being easy to follow-up
The hot peak regulation carved is used；If having no lack of, the gas engine refrigeration gas consumption at n moment is reduced accordingly；
Step 6：Stopping criterion for iteration judgement, if reaching maximum iteration time, terminates iteration, during by the following n for obtaining
Microgrid and its control system are passed in the instruction of exerting oneself for carving each distributed energy；Otherwise iterations adds 1, goes to step 1；
The distributed energy of present invention prediction module of exerting oneself can in real time obtain online the environmental data of future time instance, obtain
The situation of change of photovoltaic, wind-driven generator and load.The distributed energy of day part is exerted oneself and entered by circuit between prediction module
The communication of row cool and thermal power storage condition, and constantly correct exerting oneself for distributed energy using iterative algorithm.
Claims (10)
1. a kind of multi-energy complementary micro-grid based on iterative algorithm optimizes operation control system, it is characterised in that：Including microgrid and
Its control system, environmental monitoring machine and distributed energy are exerted oneself prediction module, distributed energy exert oneself prediction module respectively with it is micro-
Net and its control system and the connection of environmental monitoring machine.
2. the multi-energy complementary micro-grid based on iterative algorithm according to claim 1 optimizes operation control system, its feature
It is：Distributed energy prediction module of exerting oneself is exerted oneself prediction module including several following n distributed energies.
3. the multi-energy complementary micro-grid based on iterative algorithm according to claim 1 optimizes operation control system, its feature
It is：Distributed energy prediction module of exerting oneself includes that following one hour distributed energy is exerted oneself prediction module and following two little time-divisions
The cloth energy is exerted oneself prediction module, and following one hour distributed energy is exerted oneself prediction module and for following two hours distributed energies
Prediction module of exerting oneself connects, and environmental monitoring machine and following one hour distributed energy are exerted oneself prediction module connection.
4. the multi-energy complementary micro-grid based on iterative algorithm according to claim 1 optimizes operation control system, its feature
It is：Distributed energy exerts oneself prediction module including digital signal processor, digital signal processor by circuit respectively with ring
Border monitoring machine, microgrid and its control system and distributed energy exert oneself prediction module connection.
5. the multi-energy complementary micro-grid optimization operation based on iterative algorithm according to one of claim 1-4 controls system
System, it is characterised in that：Microgrid and its control system include electric heating equipment and its control system and/or photovoltaic and its control system
And/or wind energy conversion system and its control system and/or natural gas internal combustion engine and its control system and/or battery and its control system
And/or electric refrigeration plant and its control system and/or electric load and/or waste heat boiler and/or waste heat lithium bromide and/or heat accumulation storage
Pond and/or thermic load and/or the cold cistern of storage and/or refrigeration duty.
6. the multi-energy complementary micro-grid based on iterative algorithm according to claim 5 optimizes operation control system, its feature
It is：Electric heating equipment and its control system, photovoltaic and its control system, wind energy conversion system and its control system, natural gas internal combustion engine
And its control system, battery and its control system, electric refrigeration plant and its control system and electric load are respectively connecting to electric power
Bus.
7. the multi-energy complementary micro-grid based on iterative algorithm according to claim 5 optimizes operation control system, its feature
It is：Natural gas internal combustion engine and its control system are connected to heating power bus and/or cold power bus, electric heating equipment and its control system
System, heat accumulation cistern and thermic load are connected to heating power bus.
8. the multi-energy complementary micro-grid based on iterative algorithm according to claim 5 optimizes operation control system, its feature
It is：Electric refrigeration plant and its control system, the cold cistern of storage and refrigeration duty are respectively connecting to cold power bus.
9. the multi-energy complementary micro-grid based on iterative algorithm according to claim 5 optimizes operation control system, its feature
It is：Electric heating equipment and its control system, photovoltaic and its control system, wind energy conversion system and its control system, natural gas internal combustion engine
And its control system, battery and its control system, electric refrigeration plant and its control system, heat accumulation cistern and its control system
System, stores up cold cistern and its control system is exerted oneself instruction control.
10. a kind of multi-energy complementary micro-grid based on iterative algorithm optimizes progress control method, it is characterised in that including following step
Suddenly：
Step one：Following n moment distributed energy prediction module and extraneous communication, obtain environmental data and (n-1) moment and its
The storage cool and thermal power data of following instant；
Step 2：The regenerative resource at n moment and the poor E of resident's electric load are obtained, if E>0, then generate electricity, meet electric equilibrium；If E
<0, to microgrid transmission energy；
Step 3：Judge what n moment and its following instant lacked with the presence or absence of electricity, if lacking, improve storage；If having no lack of,
The generating at n moment is then reduced accordingly；
Step 4：Stopping criterion for iteration judgement, if reaching maximum iteration time, terminates iteration, and the following n moment obtained is each
Microgrid and its control system are passed in the instruction of exerting oneself of distributed energy；Otherwise iterations adds 1, goes to step 1.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102361328A (en) * | 2011-10-25 | 2012-02-22 | 中国科学技术大学 | Wind and light complement distributed micro-grid system for comprehensively utilizing commercial power |
| CN104269849A (en) * | 2014-10-17 | 2015-01-07 | 国家电网公司 | Energy managing method and system based on building photovoltaic micro-grid |
| CN104283308A (en) * | 2013-07-10 | 2015-01-14 | 北京中电建投微电网科技有限公司 | Smart central strategy control system for micro-grid |
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2016
- 2016-12-30 CN CN201611261524.1A patent/CN106655285A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102361328A (en) * | 2011-10-25 | 2012-02-22 | 中国科学技术大学 | Wind and light complement distributed micro-grid system for comprehensively utilizing commercial power |
| CN104283308A (en) * | 2013-07-10 | 2015-01-14 | 北京中电建投微电网科技有限公司 | Smart central strategy control system for micro-grid |
| CN104269849A (en) * | 2014-10-17 | 2015-01-07 | 国家电网公司 | Energy managing method and system based on building photovoltaic micro-grid |
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Application publication date: 20170510 |