CN108063447B - Improved power storage modulation method for load power valley filling in power grid valley period - Google Patents
Improved power storage modulation method for load power valley filling in power grid valley period Download PDFInfo
- Publication number
- CN108063447B CN108063447B CN201711119287.XA CN201711119287A CN108063447B CN 108063447 B CN108063447 B CN 108063447B CN 201711119287 A CN201711119287 A CN 201711119287A CN 108063447 B CN108063447 B CN 108063447B
- Authority
- CN
- China
- Prior art keywords
- power grid
- power
- load
- valley
- correlation coefficient
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 22
- 230000005611 electricity Effects 0.000 claims description 39
- 238000004364 calculation method Methods 0.000 claims description 12
- 238000010276 construction Methods 0.000 claims 1
- 230000007547 defect Effects 0.000 abstract description 3
- 238000010248 power generation Methods 0.000 description 5
- 238000004146 energy storage Methods 0.000 description 3
- 238000013461 design Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000002699 waste material Substances 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000003111 delayed effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000005728 strengthening Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
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
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
-
- H02J3/386—
-
- 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
- Y02E10/70—Wind energy
- Y02E10/76—Power conversion electric or electronic aspects
-
- 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)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses an improved power storage modulation method for load power valley filling in an underestimation period of a power grid, and belongs to the technical field of intelligent power grids. Aiming at the defects in the prior art, the power storage device is taken as a load and is connected into a power grid to increase the total load of the power grid in the valley period, so that the air volume is reduced. The method can ensure that renewable energy sources can be fully utilized, greatly reduces the operation cost of the power grid, has economical efficiency, and can ensure continuous safe and stable operation of the power grid.
Description
Technical Field
The invention belongs to the technical field of intelligent power grids, and particularly relates to an improved power storage modulation method for load power valley filling in a power grid underestimation period.
Background
The power grid development faces huge challenges due to the constraints of gradually increasing peak-valley difference of the current power utilization, higher power quality requirement, large-scale grid connection of renewable energy sources and safety and stability of the power grid. The electricity storage technology can realize the functions of peak clipping and valley filling, smooth renewable energy output and grid frequency modulation in the power grid and can be used as a standby power supply. Therefore, the energy storage technology can help the power station to realize stable and sustainable power generation and can also take the energy supply role of base charge power, so that the energy storage system is an important component of a power grid.
The load fluctuation adjustment is an important content of peak clipping and valley filling of a power grid, the energy storage system is used for peak clipping and valley filling in the power grid, part of loads are supplied by the electricity storage system during peak power utilization, and part of electric energy is stored by the electricity storage system during low power consumption, so that the peak-valley difference of the power utilization is reduced, a load curve is relatively flat, the upgrading of the system capacity is delayed, the utilization efficiency of equipment is improved, and the economic operation of the power grid is facilitated.
The following methods are often adopted for power grid valley filling in the power system: in the prior art, as for the improvement of electricity consumption of a user side, namely 'design and prototype system realization of a user side energy management system', electricity prices of a power grid in a valley period are reduced in the valley period of power grid load by adjusting electricity price strategies in different periods, and a user is stimulated to increase the electricity consumption, so that the purpose of filling the valley of the power grid is realized. However, the method is passive, the load at the user side cannot be estimated, and the electricity price in the low valley period of the power grid is difficult to set, so that the reliability of safe and stable operation of the power grid is greatly reduced.
In the prior art, the power grid wind abandoning condition evaluation method based on peak regulation capability analysis has the disadvantages that the power consumption is low in the off-peak period of the power grid, so that the power generation capacity of the power grid can only be reduced for safe and stable operation of the power grid, and the power generation capacity of the power grid is reduced by a large amount of wind abandoning. The method has uncertainty, and the air abandon amount is different in different time periods due to different weather, and the method has the biggest defect that a large amount of renewable energy is wasted, so that the operation cost of the power grid is greatly improved.
Disclosure of Invention
Aiming at the defects in the prior art, the invention takes the power storage device as a load and connects the load into the power grid to increase the total load of the power grid in the valley period, thereby reducing the air abandon amount. And the storage capacity of the power storage device in the valley period of the power grid can be determined by a curve fitting method, so that renewable energy can be fully utilized, the operation cost of the power grid is greatly reduced, the method is economical, and the continuous safe and stable operation of the power grid can be ensured.
The method constructs a power grid load valley load fitting curve, and performs corresponding mathematical modeling on time and power grid load effective power on the premise of acquiring data of the current temperature, humidity, abandoned wind electric quantity, wind speed and the number of generators of the power grid, and finally establishes a function so as to draw the required power grid load valley fitting curve. And determining the power needed to be stored by the power grid in the valley period of the power grid through the determined curve.
In order to achieve the purpose, the invention adopts the following technical scheme to realize the purpose:
1) data acquisition: and fitting a power grid valley period curve of which P changes along with T to the time (T), the temperature (T), the humidity (H), the abandoned wind power quantity (W), the number of generators (N), the wind speed (V) and the power grid load effective power (P) at a specific moment.
2): calculating an external correlation coefficient, an internal correlation coefficient and an internal and external correlation coefficient:
the influence degree of the external factors (such as temperature, humidity, wind speed and the like) of the power grid on the power grid is an external correlation coefficient which is expressed by alpha
Finding an external correlation coefficient alpha
The influence degree of the internal factors (such as the abandoned wind power, the number of generators and the like) of the power grid on the power grid is an internal correlation coefficient, and beta is used for representing
Calculating an internal correlation coefficient beta
The mutual influence degree between the internal factors (such as the abandoned wind power, the number of generators and the like) of the power grid and the external factors (such as the temperature, the humidity, the wind speed and the like) of the power grid is an internal and external correlation coefficient, and is represented by delta
Calculating the internal and external correlation coefficient delta
3) Load curve model establishment and parameter calculation in the valley period:
the load curve model of the power grid during the valley period is
(P,t)＝At2+ Bt + C (t 0 <15 min)
Model parameter A calculation
Model parameter B calculation
Model parameter c calculation
P(t)＝At2+ Bt + C (t 0 <15 min)
The load curve of the power grid at the valley period is obtained.
4) The electricity consumption at the time of the power grid valley is less than the normal power generation amount of the power grid, so that a great amount of waste of power grid resources is caused. And providing a dispatching basis for the power grid according to the obtained power grid valley period fitting curve, and transferring the flexible load to the valley period to achieve the purpose of filling the valley. Determining the power of the electricity storage load to be increased at a certain moment of the power grid, and knowing that the total active power generated by the power grid at a certain moment is Pf(t), calculating the power of the electricity storage load needing to be increased by the power grid at a certain valley moment to be P' (t)
P′(t)＝Pf(t) -P (t) (0 < t <15 min)
5) Considering the loss in the electricity storage process, theta is the actual electricity storage efficiency of the electricity storage device, and the actual electricity storage power in the valley period of the electricity storage device is P' (t)
P '(t) ═ theta.P' (t) (0 < t <15 min)
Advantageous effects
The invention determines the electricity storage power of the electricity storage device at the off-peak time section through data acquisition and determining the load curve at the off-peak time section, thereby achieving the purpose of filling the off-peak of the power grid, strengthening the electricity generation control and system optimization of the local area and having great practicability and economy.
Drawings
FIG. 1 is a flow chart of a power storage modulation method for load power valley filling during the power grid valley period
FIG. 2 is a load fitting curve of a power grid during a low-ebb period
Detailed Description
As shown in fig. 1, first, the data of temperature, humidity, abandoned wind power, wind speed and generator number are known, then the external correlation coefficient α, the internal correlation coefficient β and the internal and external correlation coefficient σ are calculated from the data, and then the function P ═ At of time and the effective power of the load of the power grid is calculated from all the known data2And (6) A, B, C of the parameter of + Bt + C, so that a final function is established, a required power grid load valley fitting curve is drawn, and the actual electricity storage power in the power grid valley period is determined according to the determined fitting curve.
The method comprises the following specific steps: 1) data acquisition: and fitting a power grid valley period curve of which P changes along with T to the time (T), the temperature (T), the humidity (H), the abandoned wind power (W), the number of generators (N), the wind speed (V) and the power grid load effective power (P) at a specific moment.
2): calculating an external correlation coefficient, an internal correlation coefficient and an internal and external correlation coefficient:
the influence degree of the external factors (such as temperature, humidity, wind speed and the like) of the power grid on the power grid is an external correlation coefficient which is expressed by alpha
Finding an external correlation coefficient alpha
The influence degree of the internal factors (such as the abandoned wind power, the number of generators and the like) of the power grid on the power grid is an internal correlation coefficient, and beta is used for representing
Calculating an internal correlation coefficient beta
The mutual influence degree between the internal factors (such as the abandoned wind power, the number of generators and the like) of the power grid and the external factors (such as the temperature, the humidity, the wind speed and the like) of the power grid is an internal and external correlation coefficient, and is represented by delta
Calculating the internal and external correlation coefficient delta
3) Load curve model establishment and parameter calculation in the valley period:
the load curve model of the power grid during the valley period is
(P,t)＝At2+ Bt + C (t 0 <15 min)
Model parameter A calculation
Model parameter B calculation
Model parameter c calculation
The load curve at the trough time is
P(t)＝At2+ Bt + C (t 0 <15 min)
The load curve of the power grid at the valley period is obtained.
4) The electricity consumption at the time of the power grid valley is less than the normal power generation amount of the power grid, so that a great amount of waste of power grid resources is caused. And providing a dispatching basis for the power grid according to the obtained power grid valley period fitting curve, and transferring the flexible load to the valley period to achieve the purpose of filling the valley. Determining the power of the electricity storage load to be increased at a certain moment of the power grid, and knowing that the total active power generated by the power grid at a certain moment is Pf(t), calculating the power of the electricity storage load needing to be increased by the power grid at a certain valley moment to be P' (t)
P′(t)＝Pf(t) -P (t) (0 < t <15 min)
5) Considering the loss in the electricity storage process, theta is the actual electricity storage efficiency of the electricity storage device, and the actual electricity storage power in the valley period of the electricity storage device is P' (t)
P '(t) ═ theta.P' (t) (0 < t <15 min)
Collecting data of temperature, humidity, abandoned wind power, wind speed and number of generators in a certain area during the valley time of a power grid, substituting the collected data into a formula to calculate an external correlation coefficient alpha, an internal correlation coefficient beta and an internal correlation coefficient sigma of the local area, and then collecting the data, the external correlation coefficient alpha and the internal correlation coefficient sigmaCalculating parameters A, B, C of the function of local area time and effective power of the power grid load by the number beta and the internal and external correlation coefficients sigma, thereby establishing a final function and drawing a required power grid load valley fitting curve P ═ At2And determining the electricity storage power of the power grid in the valley period according to the determined fitting curve.
Specific examples are as follows: 100 generators are arranged in a certain power grid, the active power of a certain day is 300MW, the abandoned wind power is 20MW, the temperature is 25 ℃, the humidity is 50%, the wind speed is 2.5m/s, the actual power storage rate of the power grid power storage device is 80%, and the power storage power of the power grid power storage device in the valley period is calculated.
Solution: internal correlation coefficient
Internal correlation coefficient beta
Internal and external correlation coefficient delta
Parameter A of power grid low-valley load fitting curve
Parameter B of load fitting curve of power grid during valley period
Parameter C of power grid valley time period valley fitting curve
Obtaining a load fitting curve of the power grid in the valley period as
P＝14t2-84t +200 (0 < t <15 min)
When t is equal to 3, P' (15) is equal to Pf(15)-P(15)＝400MW-74MW＝326MW
P″(15)＝80％·326MW＝260.8MW
According to the display of the current power storage device, the stored power is 280MW, so that the error is 6.86%, which is smaller than that of the existing device, and the device has higher application value.
The specific embodiments are given above, but the present invention is not limited to the described embodiments. The basic idea of the present invention lies in the above basic scheme, and it is obvious to those skilled in the art that no creative effort is needed to design various modified models, formulas and parameters according to the teaching of the present invention. Variations, modifications, substitutions and changes may be made to the embodiments without departing from the principles and spirit of the invention, which is further within the scope of the invention.
Claims (3)
1. An improved electricity storage modulation method for filling load power in a power grid valley period is characterized in that an electricity storage device is taken as a load and is connected into a power grid to increase the total load of the power grid valley period, so that the air abandoning amount is reduced; the storage capacity of the power storage device in the low valley period of the power grid can be determined by a curve fitting method; the construction of the power grid low-valley load fitting curve is that on the premise of carrying out data acquisition on the current temperature, humidity, abandoned wind electric quantity, wind speed and the number of generators of a power grid, corresponding mathematical modeling is carried out on time and the effective power of the power grid load, and a function is finally established, so that the required power grid load low-valley fitting curve is drawn; determining the power required to be stored by the power grid in the off-peak period of the power grid through the determined curve;
the method comprises the following specific steps:
1) data acquisition: fitting a power grid trough time curve of which P changes along with T to time T, temperature T, humidity H, abandoned wind electricity quantity W, the number N of generators, wind speed V and power grid load effective power P at a specific moment through the quantities;
2) calculating an external correlation coefficient, an internal correlation coefficient and an internal and external correlation coefficient:
the influence degree of the external factors of the power grid on the power grid is an external correlation coefficient, and the external correlation coefficient alpha is calculated by using alpha as a representation
The influence degree of the internal factors of the power grid on the power grid is an internal correlation coefficient which is expressed by beta
Calculating an internal correlation coefficient beta
The mutual influence degree between the internal factors of the power grid and the external factors of the power grid is an internal and external correlation coefficient, and is represented by delta
Calculating the internal and external correlation coefficient delta
3) Load curve model establishment and parameter calculation in the valley period:
the load curve model of the power grid during the valley period is
(P，t)＝At2T is more than Bt + C O and less than 15 minutes
Model parameter A calculation
Model parameter B calculation
Model parameter c calculation
The load curve of the power grid at the valley period is obtained;
4) providing a dispatching basis for the power grid according to the obtained power grid low-valley period fitting curve, and transferring the flexible load to the low-valley period to achieve the purpose of filling the valley; determining the power of the electricity storage load to be increased at a certain moment of the power grid, and knowing that the total active power generated by the power grid at a certain moment is Pf(t), calculating the power of the electricity storage load needing to be increased by the power grid at a certain valley moment to be P' (t)
P′(t)＝Pf(t)-P(t) O<t<15 minutes
5) Since the loss in the electricity storage process is considered, theta is the actual electricity storage efficiency of the electricity storage device, and the actual electricity storage power of the electricity storage device in the underestimation period is P' (t)
P "(t) ═ θ · P' (t) O < t <15 minutes.
2. The improved power storage modulation method for valley filling of load power during the valley period of the power grid as claimed in claim 1, wherein the external factors of the power grid in the second step include: temperature, humidity, wind speed.
3. The improved power storage modulation method for power grid valley time load power valley filling as claimed in claim 2, wherein the grid internal factors of the second step include: abandon wind electric quantity, generator number.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711119287.XA CN108063447B (en) | 2017-11-14 | 2017-11-14 | Improved power storage modulation method for load power valley filling in power grid valley period |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711119287.XA CN108063447B (en) | 2017-11-14 | 2017-11-14 | Improved power storage modulation method for load power valley filling in power grid valley period |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108063447A CN108063447A (en) | 2018-05-22 |
| CN108063447B true CN108063447B (en) | 2021-05-11 |
Family
ID=62134798
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711119287.XA Active CN108063447B (en) | 2017-11-14 | 2017-11-14 | Improved power storage modulation method for load power valley filling in power grid valley period |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108063447B (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103268366A (en) * | 2013-03-06 | 2013-08-28 | 辽宁省电力有限公司电力科学研究院 | Combined wind power prediction method suitable for distributed wind power plant |
| CN103580044A (en) * | 2013-10-17 | 2014-02-12 | 华中科技大学 | Capacity allocation method of multi-wind power plant energy storage device for dealing with wind power fluctuation |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9614374B2 (en) * | 2009-11-02 | 2017-04-04 | General Electric Company | Method for controlling energy storage system |
-
2017
- 2017-11-14 CN CN201711119287.XA patent/CN108063447B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103268366A (en) * | 2013-03-06 | 2013-08-28 | 辽宁省电力有限公司电力科学研究院 | Combined wind power prediction method suitable for distributed wind power plant |
| CN103580044A (en) * | 2013-10-17 | 2014-02-12 | 华中科技大学 | Capacity allocation method of multi-wind power plant energy storage device for dealing with wind power fluctuation |
Non-Patent Citations (1)
| Title |
|---|
| "多时间尺度的电池储能***建模及分析应用";陆秋瑜等;《中国电机工程学报》;20130605;第33卷(第16期);86-93 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108063447A (en) | 2018-05-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110350523B (en) | Multi-energy complementary optimization scheduling method based on demand response | |
| CN103762589B (en) | A kind of new forms of energy capacity ratio hierarchy optimization method in electrical network | |
| CN102694391B (en) | Day-ahead optimal scheduling method for wind-solar storage integrated power generation system | |
| CN111525627B (en) | Day-ahead scheduling method for flexible direct-current transmission system with pumped storage and new energy power generation | |
| CN113708365B (en) | Virtual power plant energy management and control optimization method and system based on end-to-end cloud architecture | |
| CN103824134A (en) | Two-stage optimized dispatching method for virtual power plant | |
| CN110350518B (en) | Power grid energy storage capacity demand assessment method and system for peak shaving | |
| CN111899125B (en) | Optimized modeling operation method, device and medium of comprehensive energy system | |
| CN112583051B (en) | Optimized scheduling model construction method of variable-speed pumped storage unit in regional power grid | |
| CN115333110A (en) | Power distribution network-microgrid group collaborative distributed optimization scheduling method and system based on ADMM | |
| CN110867907B (en) | Power system scheduling method based on multi-type power generation resource homogenization | |
| CN207339296U (en) | A kind of distributed photovoltaic power generation energy storage management control system | |
| CN105426985B (en) | Urban distribution network voltage distribution optimization method suitable for roof photovoltaic access | |
| CN104239960A (en) | Electricity generating schedule optimizing method considering pump storage unit | |
| CN108429280B (en) | Wide-area virtual frequency control method and system for passive power grid | |
| CN114118787A (en) | Dispatching optimization method for urban distributed source network load storage based on LSTM algorithm | |
| CN110739710A (en) | Method and device for coordinated scheduling of multiple energy types based on optimization algorithm | |
| CN108063447B (en) | Improved power storage modulation method for load power valley filling in power grid valley period | |
| CN116822866A (en) | Power grid regulation and control demand calculation method and system for load side resources | |
| Han et al. | Analysis of economic operation model for virtual power plants considering the uncertainties of renewable energy power generation | |
| CN111160653B (en) | Distributed energy storage system wind power consumption capability monitoring method based on cloud computing | |
| CN107528352A (en) | A kind of power distribution network active optimization method based on regenerative resource high permeability | |
| CN109524998B (en) | Combined dispatching method for wind power thermal power and water pumping energy storage station | |
| Liu et al. | Micro grid energy management based on two-stage robust optimization | |
| CN109245133B (en) | Energy storage regulation and control method for microgrid, electronic equipment and computer readable storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |