CN115065104A - Micro-grid multi-energy integrated dispatching system - Google Patents
Micro-grid multi-energy integrated dispatching system Download PDFInfo
- Publication number
- CN115065104A CN115065104A CN202210972927.6A CN202210972927A CN115065104A CN 115065104 A CN115065104 A CN 115065104A CN 202210972927 A CN202210972927 A CN 202210972927A CN 115065104 A CN115065104 A CN 115065104A
- Authority
- CN
- China
- Prior art keywords
- power
- curve
- power generation
- generation device
- energy
- 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.)
- Granted
Links
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
- H02J3/38—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
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
-
- 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
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00001—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
-
- 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
- H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
-
- 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
- H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
- H02J3/241—The oscillation concerning frequency
-
- 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
-
- 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
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/22—The renewable source being solar energy
- H02J2300/24—The renewable source being solar energy of photovoltaic origin
-
- 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
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/28—The renewable source being wind energy
-
- 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
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P80/00—Climate change mitigation technologies for sector-wide applications
- Y02P80/10—Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier
- Y02P80/14—District level solutions, i.e. local energy networks
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Human Computer Interaction (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses a micro-grid multi-energy integrated dispatching system, which belongs to the technical field of micro-grid control and specifically comprises the following steps: the data acquisition module is used for acquiring the power generation power and the environmental data of the renewable energy power generation device; the cloud platform generates a change curve of the generated power and the environmental data along with historical time, and marks the change curve as a historical change curve; generating a curve of the environmental data changing with the future time; the power prediction module is used for comparing the historical change curve with a change curve of environmental data along with future time to obtain a generated power prediction curve; a power scheduling module for obtaining a future time period t 1 Average generated power in the grid and setting the micro-grid to be in the future time period t 1 The rated output power in the micro-grid is controlled by the power storage device to regulate the output power of the micro-grid; the invention realizes the stable scheduling of the output power of the micro-grid and avoids the influence of the output power fluctuation on the main grid.
Description
Technical Field
The invention relates to the technical field of microgrid control, in particular to a microgrid multi-energy integrated dispatching system.
Background
The micro-grid is also called a distributed energy island system, is a small power generation and distribution system formed by collecting a distributed power supply, an energy storage device, an energy conversion device and a protection device, is an autonomous system capable of realizing self control, protection and management, and can be operated in a grid-connected mode with an external main grid or in an isolated mode. The independent micro-grid is an important component of an intelligent power grid, a main power supply is required to support voltage and frequency stability in the power grid, the independent micro-grid comprises photovoltaic power generation, photo-thermal power generation, wind power generation, diesel power generation and the like, and the energy storage device comprises a super capacitor, a flywheel, a storage battery and the like. The micro-grid is connected to the user side, and has the characteristics of low cost, low voltage, low pollution and the like. The micro-grid can be connected with a large power grid for operation, and can also be disconnected from the main grid for independent operation when the power grid fails or needs.
Because the generated power of new energy such as photovoltaic, light and heat and wind-powered electricity generation often has intermittence, these renewable energy power generation are influenced by weather factor, generally all are the power of intermittent type nature electricity generation, and because the generated energy dispersion, so generally all be distributed power source, the distributed power source of intermittent type nature electricity generation directly merges into main power grid, can cause serious influence to the operation and the stability of electric wire netting, so need a little electric wire netting multi-energy integrated scheduling system for the generated power of renewable energy power generation facility in the future certain time in the prediction little electric wire netting, carry out stable scheduling to little electric wire netting's output according to the generated power.
Disclosure of Invention
The invention aims to provide a micro-grid multi-energy integrated dispatching system, which solves the following technical problems:
because the generated power of new energy such as photovoltaic, light and heat and wind-powered electricity generation often has intermittence, these renewable energy power generation receive the influence of weather factor, generally are the power of intermittent type nature electricity generation, and because the generating energy dispersion, so generally all be distributed power source, the distributed power source of intermittent type nature electricity generation directly merges into main power grid, can cause serious influence to the operation and the stability of electric wire netting, so need a dispatch system of stable little electric wire netting output.
The purpose of the invention can be realized by the following technical scheme:
a microgrid multi-energy integrated dispatching system for controlling a microgrid connected to a main power grid, comprising:
the data acquisition module is used for acquiring the power generation power and the environmental data of the renewable energy power generation device, and the multi-energy power generation device comprises a renewable energy power generation device and a fossil energy power generation device;
the cloud platform is used for storing the generated power and the environmental data of the renewable energy power generation device and respectively generating a generated power historical change curve and an environmental data historical change curve; acquiring weather forecast and generating a change curve of environmental data along with future time;
a power prediction module for extracting a future time period t 1 The method comprises the steps that an internal environment data change curve along with time is marked as a first change curve, a curve segment with the highest similarity to the first change curve in an environment data historical change curve is extracted, the curve segment is marked as a second change curve, and a generated power historical change curve in the same time period as the second change curve is extracted and marked as a generated power prediction curve;
a power scheduling module for obtaining a future time period t according to the generated power prediction curve 1 Average generated power in the micro-grid, setting the average generated power as the future time period t 1 When the actual power generation power is lower than the rated output power, the energy storage device releases the electric quantity to maintain the rated output power.
As a further scheme of the invention: the power optimization module is further included, and the processing process of the power optimization module is as follows:
when the actual power generation power of the renewable energy power generation device is higher than the rated output power and the energy storage device reaches the upper limit of electric quantity storage, the connection between the renewable energy power generation device and the microgrid is cut off, and the fossil energy power generation device is started to generate electricity together with the fossil energy device and the energy storage device to maintain the output power;
and when the actual power generation power of the renewable energy power generation device is lower than the rated output power and the energy storage device does not output extra electric quantity, starting the fossil energy power generation device, and jointly generating power through the fossil energy device and the renewable energy power generation device to maintain the output power.
As a further scheme of the invention: renewable energy power generation facility that data acquisition module gathered includes photovoltaic power generation facility, light and heat power generation facility and wind power generation set, fossil energy power generation facility is diesel power generation facility, the environmental data that data acquisition module gathered includes wind speed, illumination intensity and temperature, photovoltaic power generation facility with light and heat power generation facility's generated power and illumination intensity and temperature positive correlation, wind power generation facility's generated power and wind speed positive correlation.
As a further scheme of the invention: the process of the power generation power prediction curve obtained by the power prediction module is as follows:
fitting the first change curve to obtain a first fitted curve; and extracting m sections of sub-curves in the historical change curve, which are different in date and same in time period as the first change curve, wherein m is a positive integer, fitting the sub-curves respectively to obtain fitted sub-curves, comparing the fitted sub-curves with the first fitted curve respectively in similarity, extracting the fitted sub-curve with the highest similarity to the first fitted curve, and marking the fitted sub-curve as a second fitted curve.
As a further scheme of the invention: the specific process of fitting the first change curve and the sub-curve by the power prediction module is as follows:
fitting by using a least square parabola, and respectively obtaining N points in the first change curve and the sub-curve at fixed intervals, wherein N is a positive integer, and the parabola fitting function formula is as follows:
Y=At 2 +Bt+C，
y is environment data, t is time, A, B and C are solved by the formula:
as a further scheme of the invention: the cloud platform classifies the generated power and the environmental data according to the collected date, and when the power prediction module extracts the sub-curves which are different in date and the same in time period as the first change curve, the power prediction module preferentially extracts the sub-curves which are different in year and the same in day as the first change curve, and the sub-curves which are the same in month as the first change curve are extracted in the second best.
As a further scheme of the invention: the cloud platform acquires weather forecast data in real time, updates the change curve of the environmental data along with future time, and converts the time period t 1 Set to be the same as the distribution interval of the weather forecast.
As a further scheme of the invention: the power prediction module is further used for acquiring the next time period t of the microgrid 1 The power scheduling module sets the next time period t 1 And will follow the next time period t 1 And sending the rated output power data to a main power grid dispatching center.
The invention has the beneficial effects that:
(1) according to the method, the historical environmental data and the future environmental data of the area where the renewable energy device is located are respectively fitted to obtain a fitting curve, interference is eliminated, and comparison is facilitated, so that the generation power of the renewable energy power generation device in a certain time in the future is predicted according to historical big data, the rated output power of the microgrid is set, the generation power of the renewable energy is regulated and controlled through the energy storage device and the fossil energy power generation device, stable regulation and control of the output power of the microgrid are achieved, the influence of the generation power fluctuation of the renewable energy on a main power grid is avoided, and the renewable energy can be utilized to the maximum extent.
Drawings
The invention will be further described with reference to the accompanying drawings.
Fig. 1 is a schematic block diagram of a microgrid multi-energy integrated dispatching system according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the present invention is a micro grid multi-energy integrated dispatching system for controlling a micro grid connected to a main grid, including:
the data acquisition module is used for acquiring the power generation power and the environmental data of the renewable energy power generation device, and the multi-energy power generation device comprises a renewable energy power generation device and a fossil energy power generation device;
the cloud platform is used for storing the generated power and the environmental data of the renewable energy power generation device and respectively generating a generated power historical change curve and an environmental data historical change curve; acquiring weather forecast and generating a change curve of environmental data along with future time;
a power prediction module for extracting the future time period t 1 The method comprises the steps that an internal environment data change curve along with time is marked as a first change curve, a curve section with the highest similarity with the first change curve in an environment data historical change curve is extracted and marked as a second change curve, and a generating power historical change curve in the same time period as the second change curve is extracted and marked as a generating power prediction curve;
a power scheduling module for obtaining a future time period t according to the generated power prediction curve 1 Average power generation function in the systemRate, setting average generated power to microgrid for future time period t 1 When the actual power generation power is lower than the rated output power, the energy storage device releases the electric quantity to maintain the rated output power.
The photovoltaic, photo-thermal, wind power and other new energy sources often have intermittence, the renewable energy sources are generally power sources for intermittent generation due to the influence of weather factors, and the power sources are dispersed, so the distributed power sources are generally distributed power sources, and the distributed power sources for intermittent generation are directly merged into a main power grid and can seriously affect the operation and stability of the power grid, so a microgrid multi-energy source integrated scheduling system is needed for predicting the generated power of a renewable energy source power generation device in the microgrid in a certain time in the future and stably scheduling the output power of the microgrid according to the generated power;
the method comprises the steps of acquiring and recording historical power generation power and environmental data of renewable energy, generating a curve of the environmental data changing along with time, acquiring the environmental data related to the renewable energy power generation device according to weather forecast sent by a weather station in real time, generating a curve of the environmental data changing along with future time, setting a power prediction time scale to be 1 hour according to interval time of the weather forecast issued by the weather station, so that when the weather forecast is updated next time, a prediction period is just finished, and a new change curve is generated again; in order to remove interference and facilitate comparison, the future change curve of the environmental data and the historical change curve of the environmental data are respectively subjected to fitting processing, so that 1 hour with the most similar degree to the environmental data curve of 1 hour in the future is obtained in the historical change curve, the change of the generating power of 1 hour at the time is set as the change of the generating power of the renewable energy power generation device of 1 hour in the future, the average power of 1 hour is obtained and is used as the rated output power of 1 hour in the future of the microgrid, and the electric quantity output by the renewable energy is regulated and controlled through the energy storage device, so that the stability of the output power of the microgrid is realized, the operation of a main power grid is not influenced, and the renewable energy can be utilized as much as possible.
In a preferred embodiment of the present invention, the system further includes a power optimization module, and the processing procedure of the power optimization module is:
when the actual power generation power of the renewable energy power generation device is higher than the rated output power and the energy storage device reaches the upper limit of electric quantity storage, the connection between the renewable energy power generation device and the microgrid is cut off, and the fossil energy power generation device is started to generate electricity together with the fossil energy device and the energy storage device to maintain the output power;
when the actual power generation power of the renewable energy power generation device is lower than the rated output power and the energy storage device does not output extra electric quantity, the fossil energy power generation device is started, and the fossil energy device and the renewable energy power generation device jointly generate electricity to maintain the output power;
because of the complexity of a weather system, the possibility that historical environmental data is completely the same as current environmental data is low, and the power generation device is also lost along with the passage of time, even if the environmental data is completely consistent, the power generation power is not necessarily the same, the situation may cause the difference between the actual output power and the rated output power of the microgrid, although the energy storage device can make up for the difference, the accumulated electric quantity or the consumed electric quantity can also reach the capacity limit of the energy storage device after long-term accumulation, at the moment, the energy storage device cannot play a role in adjusting the output power, the fluctuating power can influence the normal operation of the microgrid and a main power grid, the invention jointly adjusts the output power of the microgrid by controlling the energy storage device and the fossil energy power generation device, and because the power generation power of the fossil energy power generation device is relatively stable, the micro-grid power supply system is not influenced by the outside, so that the output power of the micro-grid can be supplemented or dominant to protect the grid.
In another preferred embodiment of the present invention, the renewable energy power generation device collected by the data collection module includes a photovoltaic power generation device, a photo-thermal power generation device and a wind power generation device, the fossil energy power generation device is a diesel power generation device, the environmental data collected by the data collection module includes wind speed, illumination intensity and temperature, the power generation powers of the photovoltaic power generation device and the photo-thermal power generation device are positively correlated with the illumination intensity and the temperature, and the power generation power of the wind power generation device is positively correlated with the wind speed;
due to the self characteristics of renewable energy sources, photovoltaic power generation and photo-thermal power generation are mainly influenced by illumination intensity and temperature, wind power generation is influenced by wind speed, the change of the data is collected, and the change curve of each factor and the power generation power is respectively established.
In another preferred embodiment of the present invention, the process of matching and obtaining the generated power prediction curve by the power prediction module is:
fitting the first change curve to obtain a first fitted curve; extracting m sections of sub-curves in the historical change curve, wherein the sub-curves are different in date and same in time period with the first change curve, m is a positive integer, fitting the sub-curves respectively to obtain fitting sub-curves, comparing the fitting sub-curves with the first fitting curve respectively in similarity, extracting the fitting sub-curve with the highest similarity with the first fitting curve, and marking the fitting sub-curve as a second fitting curve;
in order to remove interference and facilitate comparison, curve fitting is carried out on the first change curve, the historical change curve is divided into m sections of sub-curves which are different in date from the first change curve and are in the same time period, the illumination intensity, the temperature and the wind speed in the same time period are relatively close, the possibility that environmental data are similar is high, then the sub-curves are respectively fitted, the fitted sub-curves are respectively compared with the first fitted curve in the similarity degree, then 1 hour which is closest to the environmental data in the future 1 hour is obtained in the historical change curve, the change of the generated power in the current 1 hour is set as the change of the generated power of the renewable energy power generation device in the future 1 hour, and therefore a generated power prediction curve is obtained.
In a preferred case of this embodiment, the specific process of fitting the first variation curve and the sub-curve by the power prediction module is as follows:
fitting by using a least square parabola, and respectively obtaining N points in the first change curve and the sub-curve at fixed intervals, wherein N is a positive integer, and the parabola fitting function formula is as follows:
Y=At 2 +Bt+C，
y is environment data, t is time, A, B and C are solved by the formula:
the magnitude of the change in environmental data, such as temperature, light intensity and wind speed, over time is relatively small, so a least squares parabola is used to fit the first change curve and the sub-curve.
In another preferred case of this embodiment, the cloud platform classifies the generated power and the environmental data according to a date of collection, and the power prediction module preferentially extracts a sub-curve that is different from the first variation curve in year but same as the first variation curve in time period when extracting a sub-curve that is different from the first variation curve in date but same as the first variation curve in time period, and preferably extracts a sub-curve that is different from the first variation curve in month;
the cloud platform is also used for taking charge of the statistics work of the year, month and day of the environmental data.
In another preferred embodiment of the present invention, the cloud platform acquires weather forecast data in real time, updates a time variation curve of the environmental data with the future time, and converts the time period t to a time period t 1 Setting the interval to be the same as the release interval of the weather forecast;
and the power prediction time scale is set to be 1 hour according to the interval time of the weather station for issuing the weather forecast, so that the next time the weather forecast is updated, the power prediction period is just finished, and each weather forecast corresponds to a new power generation power change curve.
In another preferred embodiment of the present invention, the power prediction module is further configured to obtain a power generation prediction curve of the microgrid in a next hour, and the power scheduling module sets a rated output power of the microgrid in the next hour and sends data of the rated output power of the microgrid in the next hour to the main power grid scheduling center;
the power generation power of the renewable energy source changes along with the change of time in one day, so different rated output powers are set according to the change of environmental data at different times so as to exert the maximum efficiency of the renewable energy source, and the numerical value of the rated output power is sent to the main power grid every hour to inform the main power grid to change the power generation power and balance the whole power grid.
While one embodiment of the present invention has been described in detail, the description is only a preferred embodiment of the present invention and should not be taken as limiting the scope of the invention. All equivalent changes and modifications made within the scope of the present invention shall fall within the scope of the present invention.
Claims (8)
1. A microgrid multi-energy integrated dispatching system is used for controlling a microgrid connected with a main power grid, and is characterized by comprising:
the data acquisition module is used for acquiring the power generation power and the environmental data of the renewable energy power generation device, and the multi-energy power generation device comprises a renewable energy power generation device and a fossil energy power generation device;
the cloud platform is used for storing the generated power and the environmental data of the renewable energy power generation device and respectively generating a historical generated power change curve and a historical environmental data change curve; acquiring weather forecast and generating a change curve of environmental data along with future time;
a power prediction module for extracting the future time period t 1 The method comprises the steps that a change curve of internal environment data along with future time is marked as a first change curve, a curve segment with the highest similarity to the first change curve in the historical change curve of the environment data is extracted, the curve segment is marked as a second change curve, and a generation power historical change curve in the same period as the second change curve is extracted and marked as a generation power prediction curve;
a power scheduling module for obtaining a future time period t according to the generated power prediction curve 1 Average generated power in the grid, setting the average generated power as the micro grid in the future time period t 1 When the actual generated power is higher than the rated output power, the energy storage device stores redundant generated electricity, and when the actual generated power is lower than the rated output powerAnd when the rated output power is achieved, the energy storage device releases electric quantity to maintain the rated output power.
2. The microgrid multi-energy source integration dispatching system of claim 1, further comprising a power optimization module, wherein the processing procedure of the power optimization module is as follows:
when the actual power generation power of the renewable energy power generation device is higher than the rated output power and the energy storage device reaches the upper limit of electric quantity storage, the connection between the renewable energy power generation device and the microgrid is cut off, and the fossil energy power generation device is started to generate electricity together with the fossil energy device and the energy storage device to maintain the output power;
and when the actual power generation power of the renewable energy power generation device is lower than the rated output power and the energy storage device does not output extra electric quantity, starting the fossil energy power generation device, and jointly generating power through the fossil energy device and the renewable energy power generation device to maintain the output power.
3. The microgrid multi-energy integrated dispatching system of claim 1, wherein the renewable energy power generation device collected by the data collection module comprises a photovoltaic power generation device, a photo-thermal power generation device and a wind power generation device, the fossil energy power generation device is a diesel power generation device, the environmental data collected by the data collection module comprises wind speed, illumination intensity and temperature, the power generation power of the photovoltaic power generation device and the photo-thermal power generation device is positively correlated with the illumination intensity and the temperature, and the power generation power of the wind power generation device is positively correlated with the wind speed.
4. The microgrid multi-energy source integration dispatching system as claimed in claim 1, wherein the process of acquiring the generated power prediction curve by the power prediction module is as follows:
fitting the first change curve to obtain a first fitted curve; and extracting m sections of sub-curves in the historical change curve, which are different in date and same in time period as the first change curve, wherein m is a positive integer, fitting the sub-curves respectively to obtain fitted sub-curves, comparing the fitted sub-curves with the first fitted curve respectively in similarity, extracting the fitted sub-curve with the highest similarity to the first fitted curve, and marking the fitted sub-curve as a second fitted curve.
5. The microgrid multi-energy source integration dispatching system according to claim 4, wherein the specific process of fitting the first variation curve and the sub-curve by the power prediction module is as follows:
fitting by using a least square parabola, and respectively obtaining N points in the first change curve and the sub-curve at fixed intervals, wherein N is a positive integer, and the parabola fitting function formula is as follows:
Y=At 2 +Bt+C，
y is environment data, t is time, A, B and C are solved by the formula:
6. the microgrid multi-energy integration scheduling system of claim 4, wherein the cloud platform classifies the generated power and the environmental data according to the date of collection, and the power prediction module preferentially extracts a sub-curve of a same year and a same day as the first variation curve and less preferentially extracts a sub-curve of a same month as the first variation curve when extracting a sub-curve of a different date and a same time period as the first variation curve.
7. The microgrid multi-energy integrated scheduling system of claim 1, wherein the cloud platform acquires weather forecast data in real time, updates a curve of the environmental data changing with future time, and divides the time period t into a plurality of time periods 1 Is set to react with the gasLike the distribution interval of the forecasts.
8. The microgrid multi-energy integrated dispatching system of claim 1, wherein the power prediction module is further configured to obtain a next time period t of the microgrid 1 The power scheduling module sets the next time period t 1 And will follow the next time period t 1 And sending the rated output power data to a main power grid dispatching center.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210972927.6A CN115065104B (en) | 2022-08-15 | 2022-08-15 | Micro-grid multi-energy integrated dispatching system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210972927.6A CN115065104B (en) | 2022-08-15 | 2022-08-15 | Micro-grid multi-energy integrated dispatching system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115065104A true CN115065104A (en) | 2022-09-16 |
| CN115065104B CN115065104B (en) | 2022-11-01 |
Family
ID=83207834
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210972927.6A Active CN115065104B (en) | 2022-08-15 | 2022-08-15 | Micro-grid multi-energy integrated dispatching system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115065104B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115953042A (en) * | 2023-03-10 | 2023-04-11 | 山东创宇环保科技有限公司 | Distributed energy optimization control management method based on expert system |
| CN116413509A (en) * | 2023-06-05 | 2023-07-11 | 江苏扬子鑫福造船有限公司 | Power monitoring and adjusting method for high-capacity cold box system |
| CN116979570A (en) * | 2023-09-20 | 2023-10-31 | 天津电力工程监理有限公司 | Micro-grid hybrid energy storage method, system and device |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2011140565A1 (en) * | 2010-05-07 | 2011-11-10 | Advanced Energy Industries, Inc. | Systems and methods for forecasting solar power |
| CN102419394A (en) * | 2011-09-02 | 2012-04-18 | 电子科技大学 | Wind/solar power prediction method with variable prediction resolution |
| CN103390902A (en) * | 2013-06-04 | 2013-11-13 | 国家电网公司 | Photovoltaic power station super short term power prediction method based on least square method |
| CN103455716A (en) * | 2013-08-23 | 2013-12-18 | 国家电网公司 | Ultra-short-term wind power prediction-based voltage stability margin calculation method for power system |
| CN104184141A (en) * | 2013-05-24 | 2014-12-03 | 株式会社日立制作所 | Renewable energy power generation control method and device |
| CN109462231A (en) * | 2018-11-15 | 2019-03-12 | 合肥工业大学 | Optimization of Load Dispatching method, system and the storage medium of resident's micro-capacitance sensor |
-
2022
- 2022-08-15 CN CN202210972927.6A patent/CN115065104B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2011140565A1 (en) * | 2010-05-07 | 2011-11-10 | Advanced Energy Industries, Inc. | Systems and methods for forecasting solar power |
| CN102419394A (en) * | 2011-09-02 | 2012-04-18 | 电子科技大学 | Wind/solar power prediction method with variable prediction resolution |
| CN104184141A (en) * | 2013-05-24 | 2014-12-03 | 株式会社日立制作所 | Renewable energy power generation control method and device |
| CN103390902A (en) * | 2013-06-04 | 2013-11-13 | 国家电网公司 | Photovoltaic power station super short term power prediction method based on least square method |
| CN103455716A (en) * | 2013-08-23 | 2013-12-18 | 国家电网公司 | Ultra-short-term wind power prediction-based voltage stability margin calculation method for power system |
| CN109462231A (en) * | 2018-11-15 | 2019-03-12 | 合肥工业大学 | Optimization of Load Dispatching method, system and the storage medium of resident's micro-capacitance sensor |
Non-Patent Citations (1)
| Title |
|---|
| 蔡祯祺: "基于数值天气预报NWP修正的BP神经网络风电功率短期预测研究", 《中国优秀硕士论文电子期刊网》 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115953042A (en) * | 2023-03-10 | 2023-04-11 | 山东创宇环保科技有限公司 | Distributed energy optimization control management method based on expert system |
| CN115953042B (en) * | 2023-03-10 | 2023-05-26 | 山东创宇环保科技有限公司 | Expert system-based distributed energy optimization control management method |
| CN116413509A (en) * | 2023-06-05 | 2023-07-11 | 江苏扬子鑫福造船有限公司 | Power monitoring and adjusting method for high-capacity cold box system |
| CN116413509B (en) * | 2023-06-05 | 2023-08-29 | 江苏扬子鑫福造船有限公司 | Power monitoring and adjusting method for high-capacity cold box system |
| CN116979570A (en) * | 2023-09-20 | 2023-10-31 | 天津电力工程监理有限公司 | Micro-grid hybrid energy storage method, system and device |
| CN116979570B (en) * | 2023-09-20 | 2024-01-05 | 天津电力工程监理有限公司 | Micro-grid hybrid energy storage method, system and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115065104B (en) | 2022-11-01 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN115065104B (en) | Micro-grid multi-energy integrated dispatching system | |
| Ghosh et al. | Distribution voltage regulation through active power curtailment with PV inverters and solar generation forecasts | |
| CN116454951B (en) | Light energy storage control system and method | |
| CN102427244A (en) | Large-scale photovoltaic wind power information accessing system | |
| CN105337415A (en) | Regional power grid dispatching system and method based on prediction control | |
| CN113224843A (en) | Active support type wind-solar-storage integrated power control system and energy distribution method thereof | |
| CN110601254B (en) | Wind power plant energy storage optimization configuration method and system considering dynamic current-carrying characteristics | |
| CN111384719A (en) | Peak clipping and valley filling optimized scheduling method for distributed energy storage power station during photovoltaic grid connection | |
| CN107832869A (en) | A kind of generated power forecasting method of wind-power electricity generation and photovoltaic generation | |
| CN101950980A (en) | Capacity configuration method of energy storing device for regulating and controlling synchronization of distributed photovoltaic power supply | |
| CN110492529A (en) | A kind of more lotus coordinated control systems of coastal multi-source and method considering sea water desalination | |
| Almihat et al. | Design and implementation of Hybrid Renewable energy (PV/Wind/Diesel/Battery) Microgrids for rural areas | |
| Qachchachi et al. | Optimal power flow for a hybrid AC/DC microgrid | |
| CN111262270A (en) | Light, diesel and storage hybrid power generation system | |
| CN117013522A (en) | Comprehensive energy system scheduling optimization method considering distributed power supply and gas-electricity cooperation | |
| CN112350435A (en) | Virtual power plant management and control device based on micro-grid group and electric power controllable load | |
| CN109494794B (en) | Regional distributed energy storage optimization scheduling method and device | |
| CN115276088B (en) | Thermal power station heat storage capacity optimal configuration method in combined power generation system | |
| CN108683211B (en) | Virtual power plant combination optimization method and model considering distributed power supply volatility | |
| Sathishkumar et al. | Adaptive power management strategy-based optimization and estimation of a renewable energy storage system in stand-alone microgrid with machine learning and data monitoring | |
| Iqbal et al. | Analysis and comparison of various control strategy of hybrid power generation a review | |
| CN115600838A (en) | Hydropower station regulating capacity evaluation method, equipment and medium | |
| CN114759614A (en) | Multi-energy system robust optimization scheduling strategy based on game theory | |
| CN211606121U (en) | Peak-regulating frequency-modulating system for mine heating furnace gas participating in renewable energy micro-grid | |
| CN211606120U (en) | Novel wind-light-gas-storage multi-energy complementary power generation system |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |