CN106532753A - Electric power system energy storage control method of large-scale photovoltaic access - Google Patents
Electric power system energy storage control method of large-scale photovoltaic access Download PDFInfo
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- CN106532753A CN106532753A CN201611137318.XA CN201611137318A CN106532753A CN 106532753 A CN106532753 A CN 106532753A CN 201611137318 A CN201611137318 A CN 201611137318A CN 106532753 A CN106532753 A CN 106532753A
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- photovoltaic
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- 238000004146 energy storage Methods 0.000 title claims abstract description 70
- 238000000034 method Methods 0.000 title claims abstract description 14
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 22
- 230000005540 biological transmission Effects 0.000 claims abstract description 16
- 238000010248 power generation Methods 0.000 claims abstract description 13
- 238000007599 discharging Methods 0.000 claims abstract description 4
- 230000009977 dual effect Effects 0.000 claims description 15
- 238000005070 sampling Methods 0.000 claims description 12
- 230000005611 electricity Effects 0.000 claims description 9
- 239000003990 capacitor Substances 0.000 claims description 3
- 238000001514 detection method Methods 0.000 abstract 1
- 238000005516 engineering process Methods 0.000 description 5
- 230000000694 effects Effects 0.000 description 3
- 230000001172 regenerating effect Effects 0.000 description 3
- 206010068052 Mosaicism Diseases 0.000 description 2
- 210000004027 cell Anatomy 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 description 2
- 210000003765 sex chromosome Anatomy 0.000 description 2
- 230000000087 stabilizing effect Effects 0.000 description 2
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 239000001257 hydrogen Substances 0.000 description 1
- 229910052739 hydrogen Inorganic materials 0.000 description 1
- 230000002045 lasting effect Effects 0.000 description 1
- 239000003345 natural gas Substances 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
Classifications
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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
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
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- H02J3/383—
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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
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
-
- 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
- Y02E70/00—Other energy conversion or management systems reducing GHG emissions
- Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
- Supply And Distribution Of Alternating Current (AREA)
- Photovoltaic Devices (AREA)
Abstract
The invention discloses an electric power system energy storage control method of large-scale photovoltaic access. The method comprises following steps that step 1, a photovoltaic power station is connected into a power transmission network and a power distribution network according to output voltage grade, a power-type energy storage system is configured in the power distribution network and an energy-type energy storage system is configured in the power distribution network; step 2, the power-type energy storage system adopts a double moving average algorithm to calculate an energy storage charging and discharging strategy, and stabilize short-time fluctuation of output power of the photovoltaic power station accessed to the power distribution network; and step 3, the energy-type energy storage system firstly carries out power generation detection on the photovoltaic power station accessed to the power transmission network and the power distribution network, carries out load prediction on the load accessed to the power distribution network so as to obtain a predicted photovoltaic output curve and a predicted load curve, then adopts a prediction control method, makes a daily operation plan, stores energy during photovoltaic power releasing period and generates power during load period at night.
Description
Technical field
The present invention relates to energy internet arena, and in particular to the power system energy storage control that a kind of large-scale photovoltaic is accessed
Method.
Background technology
Energy the Internet is with power system as core, based on the Internet and other Latest Information technologies, to be distributed
Formula regenerative resource is main primary energy, with the other systems close-coupled such as natural gas network, transportation network and answering for being formed
Miscellaneous many network flow systems.Five big intension of energy the Internet is：1) support from fossil energy to regenerative resource to change；2) support big rule
Mould distributed energy is accessed；3) support that extensive hydrogen energy storage and other energy storage devices are accessed；4) using Internet technology transformation electricity
Force system；5) support the transition to electrified traffic.
The extensive regenerative resource such as photovoltaic generation is generated electricity by way of merging two or more grid systems and has become the development trend of Future Power System, and
It is inherently required that energy the Internet is realized.With photovoltaic generation, in power system, installed capacity proportion is increasing, it
Impact to Power System Planning, emulation, scheduling, control also causes people greatly to pay close attention to, and particularly large-scale photovoltaic generates electricity and is
System is incorporated to the weight that the short-time rating fluctuation for bringing of power system and the unbalanced problem that day and night generates electricity increasingly obtain researchers
Depending on.
Energy storage technology can solve the randomness of renewable energy power generation and fluctuation sex chromosome mosaicism to a great extent, but short
Shi Bodong's stabilizes, and is still weak in terms of the balancing the load of region.
The content of the invention
The technical problem to be solved in the present invention is to provide the power system energy storage control method that a kind of large-scale photovoltaic is accessed,
Randomness and fluctuation sex chromosome mosaicism that prior art solves renewable energy power generation using energy storage technology can be solved, but in short-term
What is fluctuated stabilizes, and the problem being still weak in terms of the balancing the load of region.
The present invention is achieved through the following technical solutions：
The power system energy storage control method that a kind of large-scale photovoltaic is accessed, comprises the following steps：
Step 1：Photo-voltaic power generation station is respectively connected to into power transmission network and power distribution network according to output voltage grade, is configured in power distribution network
Power-type energy-storage system, in power transmission network configuration energy type energy-storage system；
Step 2：The power-type energy-storage system calculates energy storage discharge and recharge strategy using dual moving averages algorithm, to distribution
The photo-voltaic power generation station output short-time fluctuations that net is accessed are stabilized；
Step 3：The energy type energy-storage system first carries out generating electricity pre- to the photo-voltaic power generation station that power transmission network and power distribution network are accessed
Survey, load prediction is carried out to the load that power distribution network is accessed, respectively obtain prediction photovoltaic power curve and prediction load curve, then adopt
With forecast Control Algorithm, day operation planning is formulated, period energy storage is sent in photovoltaic, generate electricity in the night load period.
The further scheme of the present invention is that the computing formula of the dual moving averages algorithm in the step 2 is：
Wherein y1, y2... yt... ynFor the time serieses in the sampling period, MtFor the moving averages of time t in the sampling period
Value, MMtFor the dual sliding average of time t in the sampling period, N is moving averages algorithm span.
The further scheme of the present invention is that the form of the power-type energy-storage system includes super capacitor energy-storage, flywheel storage
The battery energy storage of energy, superconducting energy storage and fast charging and discharging.
The further scheme of the present invention is that the form of the energy type energy-storage system includes water-storage, compressed air storage
Energy and high capacity cell energy storage.
Present invention advantage compared with prior art is：
First, power-type energy storage is adopted to middle-size and small-size photovoltaic generating system in power distribution network, to the medium-and-large-sized photovoltaic generation of power transmission network
System adopts energy type energy storage, adopts different energy-storage systems to different electric pressures；For power distribution network level energy-storage system is adopted
Energy-storage system discharge and recharge strategy is calculated with dual moving averages algorithm, realizes photovoltaic output work being accessed to 35kV and following power distribution network
Rate short-time fluctuations are stabilized, and the sampling period shortens half, stabilize effect more preferably, the photovoltaic system output that can be more smoothed
Power；
2nd, for power transmission network energy-storage system draws the discharge and recharge scheduling meter of such energy-storage system using forecast Control Algorithm
Draw, realize to sending stabilizing and realizing the region load balancing for power transmission network photovoltaic output；Power distribution network level energy-storage system and
Cooperation between power transmission network level energy-storage system, realizes reducing and send impact of the power to major network, while increased this area
The grid connection capacity of new forms of energy.
Description of the drawings
Fig. 1 is the power grid architecture schematic diagram of the present invention.
Fig. 2 stabilizes ripple effect comparison diagram for moving averages algorithm with dual moving averages algorithm.
Specific embodiment
The power system energy storage control method that a kind of large-scale photovoltaic is accessed, comprises the following steps：
Step 1：As shown in figure 1, the middle-size and small-size photo-voltaic power generation station by output voltage grade for 0.38KV, 10KV, 35KV connects
Enter power distribution network, big-and-middle-sized photo-voltaic power generation station of the output voltage grade for 110KV, 220KV is accessed into power transmission network；Configure in power distribution network
Power-type energy-storage system, the form of the power-type energy-storage system include super capacitor energy-storage, flywheel energy storage, superconducting energy storage and
The battery energy storage of fast charging and discharging, it is second level to continue the discharge and recharge time, with power density is big, fast response time, cycle life
Long the features such as, but its capacity is relatively small；In power transmission network configuration energy type energy-storage system, the form of the energy type energy-storage system
Including water-storage, compressed-air energy storage and high capacity cell energy storage, its lasting discharge and recharge time is minute level, with higher
Energy density, but cycle life is shorter, is unsuitable for frequently discharge and recharge conversion.
Step 2：The power-type energy-storage system calculates energy storage discharge and recharge strategy using dual moving averages algorithm, to distribution
The photo-voltaic power generation station output short-time fluctuations that net is accessed are stabilized, and reduce impact of the short-time rating fluctuation to system；It is described
The computing formula of dual moving averages algorithm is：
Wherein y1, y2... yt... ynFor the time serieses in the sampling period, MtFor the moving averages of time t in the sampling period
Value, MMtFor the dual sliding average of time t in the sampling period, N is moving averages algorithm span.
If the sampling period of common moving averages algorithm is 600 seconds, dual moving averages algorithm is with 300 seconds as sampling week
Phase, simulation calculation is carried out by taking the middle-size and small-size photovoltaic generating systems of somewhere 600kW as an example, the time is one day summer 10:00-15:00,
Weather is cloudy, stabilizes rear photovoltaic output as shown in Fig. 2 tying by moving averages algorithm and the contrast of dual moving averages algorithm
Close the data in following table, it can be seen that dual moving averages algorithm stabilizes effect to photovoltaic system output short-time fluctuations
More preferably, the photovoltaic system output that energy-storage system more can be smoothed can be controlled using dual moving averages algorithm.
Step 3：The energy type energy-storage system first carries out generating electricity pre- to the photo-voltaic power generation station that power transmission network and power distribution network are accessed
Survey, load prediction is carried out to the load that power distribution network is accessed, respectively obtain prediction photovoltaic power curve and prediction load curve, then adopt
With forecast Control Algorithm, day operation planning is formulated, period energy storage is sent in photovoltaic, generated electricity in the night load period, realize to falling
Send stabilizing and absorbing for power transmission network photovoltaic output, it is ensured that the load balancing of this area, while reduce power is sent to major network
Impact, and increase the grid connection capacity of new forms of energy.
Claims (4)
1. the power system energy storage control method that a kind of large-scale photovoltaic is accessed, it is characterised in that comprise the following steps：
Step 1：Photo-voltaic power generation station is respectively connected to into power transmission network and power distribution network according to output voltage grade, power is configured in power distribution network
Type energy-storage system, in power transmission network configuration energy type energy-storage system；
Step 2：The power-type energy-storage system calculates energy storage discharge and recharge strategy using dual moving averages algorithm, and power distribution network is connect
The photo-voltaic power generation station output short-time fluctuations for entering are stabilized；
Step 3：The energy type energy-storage system first carries out generating prediction to the photo-voltaic power generation station that power transmission network and power distribution network are accessed, right
The load that power distribution network is accessed carries out load prediction, respectively obtains prediction photovoltaic power curve and prediction load curve, then using pre-
Control method is surveyed, day operation planning is formulated, period energy storage is sent in photovoltaic, generate electricity in the night load period.
2. the power system energy storage control method that a kind of large-scale photovoltaic as claimed in claim 1 is accessed, it is characterised in that：Institute
The computing formula for stating the dual moving averages algorithm in step 2 is：
；
Wherein y1, y2... yt... ynFor the time serieses in the sampling period, MtFor the sliding average of time t in the sampling period,
MMtFor the dual sliding average of time t in the sampling period, N is moving averages algorithm span.
3. the power system energy storage control method that a kind of large-scale photovoltaic as claimed in claim 1 is accessed, it is characterised in that：Institute
The form for stating power-type energy-storage system includes the battery of super capacitor energy-storage, flywheel energy storage, superconducting energy storage and fast charging and discharging
Energy storage.
4. the power system energy storage control method that a kind of large-scale photovoltaic as claimed in claim 1 is accessed, it is characterised in that：Institute
The form for stating energy type energy-storage system includes water-storage, compressed-air energy storage and high capacity cell energy storage.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201611137318.XA CN106532753A (en) | 2016-12-09 | 2016-12-09 | Electric power system energy storage control method of large-scale photovoltaic access |
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| CN201611137318.XA CN106532753A (en) | 2016-12-09 | 2016-12-09 | Electric power system energy storage control method of large-scale photovoltaic access |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107910884A (en) * | 2017-12-06 | 2018-04-13 | 国网山东省电力公司济南供电公司 | Battery energy storage stabilizes the On-Line Control Method of the big climbing event of photovoltaic generation |
| CN110932296A (en) * | 2019-12-16 | 2020-03-27 | 合肥阳光新能源科技有限公司 | Energy storage control method and device and virtual power plant |
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| CN103424620A (en) * | 2013-08-08 | 2013-12-04 | 华南理工大学 | 10kV distribution network harmonic source identification method based on time sequence relevancy |
| CN103580052A (en) * | 2013-11-27 | 2014-02-12 | 上海空间电源研究所 | Compound energy storage power station for active distribution network and power distribution method of compound energy storage power station |
| US8942959B2 (en) * | 2012-03-29 | 2015-01-27 | Mitsubishi Electric Research Laboratories, Inc. | Method for predicting outputs of photovoltaic devices based on two-dimensional fourier analysis and seasonal auto-regression |
| CN104617590A (en) * | 2014-07-18 | 2015-05-13 | 国网上海市电力公司 | Microgrid energy optimization method based hybrid energy storage dispatching under different time scales |
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2016
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| US8942959B2 (en) * | 2012-03-29 | 2015-01-27 | Mitsubishi Electric Research Laboratories, Inc. | Method for predicting outputs of photovoltaic devices based on two-dimensional fourier analysis and seasonal auto-regression |
| CN103424620A (en) * | 2013-08-08 | 2013-12-04 | 华南理工大学 | 10kV distribution network harmonic source identification method based on time sequence relevancy |
| CN103580052A (en) * | 2013-11-27 | 2014-02-12 | 上海空间电源研究所 | Compound energy storage power station for active distribution network and power distribution method of compound energy storage power station |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107910884A (en) * | 2017-12-06 | 2018-04-13 | 国网山东省电力公司济南供电公司 | Battery energy storage stabilizes the On-Line Control Method of the big climbing event of photovoltaic generation |
| CN107910884B (en) * | 2017-12-06 | 2019-08-23 | 国网山东省电力公司济南供电公司 | Battery energy storage stabilizes the On-Line Control Method of the big climbing event of photovoltaic power generation |
| CN110932296A (en) * | 2019-12-16 | 2020-03-27 | 合肥阳光新能源科技有限公司 | Energy storage control method and device and virtual power plant |
| CN110932296B (en) * | 2019-12-16 | 2021-12-14 | 合肥阳光新能源科技有限公司 | Energy storage control method and device and virtual power plant |
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Application publication date: 20170322 |