CN116454951A - Light energy storage control system and method - Google Patents
Light energy storage control system and method Download PDFInfo
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- CN116454951A CN116454951A CN202310480871.7A CN202310480871A CN116454951A CN 116454951 A CN116454951 A CN 116454951A CN 202310480871 A CN202310480871 A CN 202310480871A CN 116454951 A CN116454951 A CN 116454951A
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- 238000010248 power generation Methods 0.000 claims abstract description 46
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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
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
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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
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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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- 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
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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
- H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
- H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
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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
- H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
- H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
- H02J3/144—Demand-response operation of the power transmission or distribution network
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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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
- 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
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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
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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
- Y02E70/00—Other energy conversion or management systems reducing GHG emissions
- Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin
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- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention relates to the technical field of photovoltaic power generation and energy storage, in particular to a light energy storage control system and a light energy storage control method. The method employs the system, which comprises: the energy storage module is connected with the photovoltaic power station and the power grid and is used for storing electric quantity; the photovoltaic power station acquisition module is used for acquiring geographic data and environmental data of the photovoltaic power station and photovoltaic panel installation information in real time; the power generation prediction module is used for predicting the power generation capacity of the photovoltaic power station according to the acquired data; the loss prediction module is used for collecting loss data of the energy storage module and calculating loss cost; the load prediction module is used for predicting the electricity consumption according to the historical data, the real-time data and the future data; and the energy storage decision module is used for controlling the energy storage module to store energy or supply energy, calculating the energy storage cost and determining the energy storage mode of the energy storage module by combining the future electricity demand. The technical scheme can realize the maximization of energy efficiency.
Description
Technical Field
The invention relates to the technical field of photovoltaic power generation and energy storage, in particular to a light energy storage control system and a light energy storage control method.
Background
With the continuous shortage of global energy supply and increasing importance of environmental problems, reasonable development and utilization of renewable energy have become an important issue. The development and utilization of renewable energy sources are important measures for improving energy supply capacity, improving energy structures, guaranteeing energy safety and gradually recovering natural environments, and have important significance for building a resource-saving environment-friendly society and realizing comprehensive, coordinated and sustainable development of an economic society.
Photovoltaic is a short term of solar photovoltaic power generation system, which is a power generation system that directly converts solar radiation energy into electric energy by utilizing the photovoltaic effect of solar cell semiconductor materials. The photovoltaic energy storage is used for storing electric energy generated by the photovoltaic system, and when the electric power of the photovoltaic system is insufficient, the electric power is externally provided through corresponding power dispatching.
One of the application purposes of the photovoltaic energy storage control system in the power grid is to cut peaks and fill valleys, namely, surplus electric quantity in low valley periods of electricity consumption at night is stored through an energy storage module, the stored electric quantity is fed back to the power grid side through an inverter (DC/AC) in the peak periods of electricity consumption at daytime, waste of electric energy is reduced, line loss can be reduced through the energy storage module, and service lives of circuits and equipment are prolonged.
However, photovoltaic energy storage is easily affected by factors such as weather conditions, illumination conditions, capacity configuration of an energy storage device and the like, instability exists in the aspects of power generation time, power generation intensity and the like, and energy efficiency maximization cannot be achieved only by simply charging and discharging according to time.
Disclosure of Invention
The invention aims at: the technical scheme can realize the maximization of energy efficiency.
In order to achieve the above purpose, the present invention provides a basic scheme: an optical energy storage control system comprising:
the energy storage module is connected with the photovoltaic power station and the power grid and is used for storing electric quantity;
the photovoltaic power station acquisition module is used for acquiring geographic data and environmental data of the photovoltaic power station and photovoltaic panel installation information in real time;
the power information acquisition module is used for acquiring power information of the energy storage module and power grid power information, wherein the power information of the energy storage module comprises the capacity of the energy storage module, and the power grid power information comprises the peak-valley condition of the power grid;
the power generation prediction module is used for predicting the power generation capacity of the photovoltaic power station according to the acquired data;
the loss prediction module is used for collecting loss data of the energy storage module and calculating loss cost;
the load prediction module is used for predicting the electricity consumption according to the historical data, the real-time data and the future data;
the energy storage decision module is used for controlling the energy storage module to store energy or supply energy, calculating the energy storage cost by combining the loss cost, and comprehensively deciding the optimal energy storage mode according to the future electricity demand.
The basic scheme has the beneficial effects that: according to the scheme, a photovoltaic power station acquisition module is used for acquiring a plurality of data of the photovoltaic power station, a power generation prediction module is used for predicting the power generation capacity of the photovoltaic power station, and meanwhile, the data can be combined with the power information of an energy storage module to be used for an energy storage decision module to calculate the energy storage cost.
The load prediction module can predict the electricity consumption, the energy storage decision module controls the energy storage module to store energy or supply energy according to the predicted electricity consumption and the generated energy, in the scheme, the energy storage module is connected with the photovoltaic power station and the power grid, and the energy storage module can obtain electric energy from the photovoltaic power station and the power grid to store energy, so that the energy storage cost can be effectively controlled by controlling the energy storage mode, namely the source proportion of the stored electric energy and the time machine, and the energy storage decision module can calculate the energy storage cost and select the optimal energy storage mode, so that the stored electric energy can meet the peak clipping and valley filling demands and the energy storage cost can be reduced.
The optimal energy storage mode of the scheme does not necessarily meet the economic optimality, but can also meet the electricity demand to the greatest extent under emergency, and the energy storage cost is reduced on the basis, for example, when some emergencies lead to about to power failure, the energy storage decision module can also obtain a rapid energy storage mode so as to store more electric energy as much as possible, be used by important electricity facilities and reduce the loss possibly caused by power failure.
As a preferred scheme, the power generation prediction module is used for collecting a historical data set of the photovoltaic power station, wherein the historical data set comprises historical data of a plurality of different photovoltaic power stations, the historical data comprises geographic data and environmental data, and the power generation prediction module is used for obtaining the historical data matched with the current photovoltaic power station; the power generation prediction module combines the geographic data and the environmental data of the current photovoltaic power station to obtain the predicted power generation amount.
Because the photovoltaic power station which is just built does not have enough historical data, the current data of the photovoltaic power station is matched with the near historical data by collecting the historical data set of the photovoltaic power station, and the data of the photovoltaic power station are predicted by the data so as to provide more accurate data reference for an energy storage decision module.
The energy storage system comprises an energy storage analysis module, a power supply module and a power supply module, wherein the energy storage analysis module is used for analyzing the preparation capacity required by the energy storage module, and a specific calculation formula is as follows:
wherein Wc is a reserve capacity required by the energy storage module, wf is a power consumption predicted value, SOC is a charge-discharge depth, η is a battery efficiency, and η is an inverter efficiency.
The energy storage module can be prepared better by analyzing the preparation capacity required by the energy storage module, and data reference is provided for subsequent maintenance and expansion.
Preferably, the loss prediction module is further configured to calculate a loss rate of the energy storage module.
The reliability of the energy storage module can be obtained by calculating the loss rate of the energy storage module, and whether maintenance or replacement is needed or not is judged, so that the performance of the energy storage module is always in a normal state, measures can be timely taken when abnormality is found, the effectiveness and the reliability of the system are ensured, and unnecessary loss can be avoided.
As a preferred scheme, the energy storage decision module comprises a cost calculation sub-module, wherein the cost calculation sub-module calculates the power generation cost of the photovoltaic power station according to the power information, and simultaneously combines the peak-valley period electricity price of the area where the energy storage module is located and the loss cost of the energy storage module to calculate and obtain the final energy storage cost.
By calculating the energy storage cost, the energy storage time and the energy storage mode can be planned better, the energy storage cost is reduced, and the energy efficiency of the energy storage system is kept to be maximized as much as possible.
As a preferable scheme, the historical data in the load prediction module is provided with a seasonal weight value, a time period weight value, a historical electricity consumption weight value and a historical weather weight value, and the electricity consumption historical prediction value is obtained through weighting; the future data is provided with weather forecast weight values, industrial and commercial energy consumption weight values and peak-valley forecast weight values, obtaining a future predicted value of the electricity consumption through weighting; the real-time data are provided with a real-time weather weight value, a real-time electricity consumption weight value, an industrial electricity consumption distribution weight value and a load prediction module, and a real-time correction value is obtained through weighting;
the load prediction module comprehensively predicts the electricity consumption of each period in the future according to the electricity consumption history predicted value and the electricity consumption future predicted value, and corrects the electricity consumption predicted value of the adjacent period in the future by utilizing the real-time correction value.
According to the scheme, the power consumption historical predicted value and the power consumption future predicted value are set, the final power consumption predicted value is obtained through weighting calculation on a plurality of different aspects, and the power consumption predicted value is corrected through the real-time correction value, so that data are more fit with reality, and more accurate data reference is conducted on the energy storage decision module.
The power grid prediction module is used for predicting power failure and power grid emergency, and sending a prediction result to the load prediction module so as to adjust the capacity of the energy storage module to be prepared.
The special condition of the power grid can be processed by predicting the power failure and the emergency of the power grid, and meanwhile, due to the special condition, the energy storage decision module does not consider the optimal economic cost any more after the power grid prediction module predicts the special condition, but obtains the fastest energy storage strategy, and the subsequent power consumption requirement is met as much as possible.
The energy storage decision-making module also comprises a priority judging sub-module which judges the priority of the electricity utilization facilities according to the actual electricity utilization requirement and provides electric energy for the electricity utilization facilities according to the priority.
Because the power supply quantity will drop by a wide margin or even temporarily interrupt after special circumstances take place, it is very important to rationally plan the stored electric quantity, and through judging the priority of electricity utilization facility, the electricity utilization of important facility can be guaranteed as far as possible, avoids causing more losses.
A light energy storage control method uses the light energy storage control system.
Drawings
Fig. 1 is a block diagram of an optical energy storage control system.
Detailed Description
The technical scheme of the application is further described in detail through the following specific embodiments:
example 1
An optical energy storage control system as shown in fig. 1, comprising:
the energy storage module is connected with the photovoltaic power station and the power grid, and is used for storing electric energy, and the energy storage module is formed by connecting a plurality of capacitor modules in series, and each capacitor module is formed by connecting a plurality of super capacitors in parallel and then connecting the super capacitors in series.
The photovoltaic power station acquisition module is used for acquiring geographic data and environmental data of the photovoltaic power station in real time and photovoltaic panel installation information, wherein the geographic data comprises altitude, topography, longitude and latitude and climate where the photovoltaic power station is located; the environmental information comprises radiance, sunshine hours, weather type, illumination intensity, wind power, wind direction and temperature and humidity; the weather types comprise sunny, cloudy, rainy, cloudy and the like; the geographic data comprise the altitude, the topography, the longitude and latitude and the climate of the photovoltaic power station; the photovoltaic panel installation information includes the number of photovoltaic panels and an installation angle.
The power information acquisition module is used for acquiring power information of the energy storage module and power grid power information, and the power information of the energy storage module comprises energy storage module capacity, energy storage module efficiency, energy storage module charging and discharging depth and inverter efficiency. The grid power information comprises grid peak-valley conditions and grid peak-valley electricity prices.
And the power generation prediction module is used for predicting the power generation amount of the photovoltaic power station. The power generation prediction module is used for collecting historical data sets of the photovoltaic power stations, the historical data sets comprise historical data of a plurality of different photovoltaic power stations, the historical data can comprise date, historical power generation amount, geographic data, environmental data and the like, and as part of photovoltaic power stations which are just built do not have sufficient historical data, the power generation prediction module is used for matching the data in the historical data sets according to the geographic data and the environmental data of the photovoltaic power stations connected with the current energy storage module, and the historical data closest to the current photovoltaic power stations are obtained. The power generation prediction module combines the geographic data and the environmental data of the current photovoltaic power station, and obtains the predicted power generation amount of the photovoltaic power station according to the closest historical data.
With the increase of the input operation time of the photovoltaic power station, the historical data stored by the current photovoltaic power station is more and more, and the power generation prediction module gradually replaces the closest historical data by utilizing the historical data stored by the current photovoltaic power station until the current historical data is completely replaced, so that the power generation prediction accuracy of the power generation prediction module on the current photovoltaic power station is higher and higher.
The loss prediction module is used for collecting loss data of the energy storage module and calculating loss cost of the energy storage module and loss rate of the energy storage module. The loss data comprises basic data and state data, wherein the basic data comprises the cost of the energy storage module, the rated capacity of the energy storage module, the efficiency loss generated by the combiner box and the direct current circuit, the alternating current line loss and the like, and the state data comprises the charge and discharge cycle times of the energy storage module, the efficiency loss generated by the photovoltaic array, the state of charge of the energy storage module at a certain moment, the variation of the state of charge between the two moments and the like.
And the load prediction module is used for predicting the electricity consumption according to the historical data, the real-time data and the future data. The load prediction module obtains a power consumption history predicted value by weighting the weight values in the historical data; the future data are provided with weather forecast weight values, industrial and commercial energy power consumption weight values and peak-valley forecast weight values, and the load forecast module obtains a power consumption future forecast value by using the weight values in the future data. The real-time data is provided with a real-time weather weight value, a real-time electricity consumption weight value, an industrial electricity consumption distribution weight value and a load prediction module which obtains a real-time correction value by weighting the weight value in the real-time data. The load prediction module comprehensively predicts the electricity consumption of each future period according to the electricity consumption history predicted value and the electricity consumption future predicted value, and corrects the electricity consumption predicted value of the future adjacent period by using the real-time correction value.
The energy storage analysis module is used for analyzing the capacity required to be prepared by the energy storage module, and the specific calculation formula is as follows:
wherein Wc is the capacity of the energy storage module to be prepared, wf is the predicted value of the power consumption, SOC is the depth of charge and discharge, η is the battery efficiency, and η is the inverter efficiency.
The energy storage decision module is used for controlling the energy storage module to be in an energy storage mode or an energy supply mode, when the energy storage module is in the energy storage mode, surplus electric energy is stored in the energy storage module, and when the energy storage module is in the energy supply mode, the electric quantity stored in the energy storage module feeds the stored electric quantity back to the power grid side through an inverter (DC/AC); and the energy storage mode of the energy storage module is determined according to the future electricity demand and the energy storage cost.
The energy storage decision-making module comprises a cost calculation sub-module, wherein the cost calculation sub-module calculates the power generation cost of the photovoltaic power station according to the power information, simultaneously combines the peak-valley period electricity price of the area where the energy storage module is positioned, the loss cost of the energy storage module and the like, calculates to obtain the final energy storage cost, decides whether to store energy according to the energy storage cost, and if so, the energy storage decision-making sub-module plans the optimal energy storage strategy according to the capacity required to be prepared by the energy storage module.
Example two
The distinguishing technical characteristics of the embodiment and the first embodiment are that the method further comprises a power grid prediction module for predicting power grid emergency such as power failure. The power grid prediction module monitors the announcement information of the local power grid in real time, when the emergency announcement such as power failure announcement is monitored, the power grid prediction module acquires the information such as affected areas, affected time, affected reasons and the like in the announcement information, predicts the required power consumption after power failure, sends the data to the load prediction module, and adjusts the capacity required to be prepared by the energy storage module.
The energy storage decision-making module further comprises a priority judging sub-module, wherein the priority judging sub-module judges the priority of the electricity utilization facilities according to the actual electricity utilization requirement and provides electric energy for the electricity utilization facilities according to the priority so as to ensure the effectiveness of electric energy supply. If facilities with higher electricity reliability requirements on hospitals, precision production lines and data centers are in power failure or accidents such as natural disasters, the energy storage device is required to supply reserved electric energy to important loads so as to avoid electric energy interruption in the fault repairing process and ensure continuous power supply of the important loads.
Example III
The distinguishing technical characteristics of this embodiment and embodiment one is that, the device further includes a charge-discharge control module, which is configured to divide the energy storage modules with similar loss rates into a group according to the loss rates, the higher the loss rate is, the lower the reliability of the energy storage modules is, and when the loss rate is too low, the whole group of energy storage modules are convenient to replace in batches. When the energy storage modules are controlled to charge and discharge, the energy storage modules are used as a group unit, and the energy storage modules in a certain group can be actively controlled to charge and discharge so as to actively control the loss rate of the energy storage modules.
The charging and discharging control module divides the energy storage module into a power supply group and a guarantee group by taking the group as a unit, and when the energy storage module is in a charging state, the guarantee group is charged preferentially, and then the power supply group is charged; when the energy storage module is in a discharging state, the electric energy stored in the power supply group is released preferentially, and then the electric energy stored in the power supply group is released; in the actual operation process, the energy storage module can not charge when the electric quantity is used up, so the scheme can improve the charge and discharge times of the power supply group, reduce the charge and discharge times of the guarantee group, ensure that the guarantee group has reliability, and the power supply group can also reach the service life as soon as possible for replacement. The new energy storage modules form a guarantee group after replacement, and the original guarantee group is automatically switched into a power supply group.
Example IV
The distinguishing technical features of the present embodiment and the first embodiment are that the load prediction module further includes a peak-valley prediction sub-module, configured to predict a peak-valley period and a corresponding peak-valley power consumption according to the historical power consumption situation, and also modify the predicted peak-valley period according to the data of the load prediction module. The peak-valley period is predicted, so that the power information acquisition module can acquire future power grid power information so as to grasp future power grid peak-valley conditions, and more accurately grasp surplus electric energy acquired from a power grid in the future and electric energy required by the power grid.
In one embodiment, the peak Gu Yuce sub-module is further configured to crawl business information, including historical capacity reports for each business and capacity forecast plans, and the number, type, and size of newly registered business. The peak Gu Yuce sub-module is used for integrating enterprises into corresponding power utilization time periods according to industrial and commercial information, and simultaneously predicting possible power utilization amount of the enterprises to be overlapped on the predicted power utilization amount of the time period, and the peak Gu Yuce sub-module is used for adjusting the predicted peak-valley time period and the predicted power utilization amount value of the peak valley according to new predicted power utilization conditions.
Example five
The distinguishing technical features of the present embodiment from the first embodiment are that the power generation prediction module further includes a power generation stability judgment sub-module for judging the stability of the generated power. The load prediction module further comprises a load stability judging sub-module for judging the stability of the power consumption. The energy storage decision module also comprises a parameter calling control sub-module which is used for controlling parameters called when the energy storage module makes a decision.
And the power generation stability judging sub-module is used for recording the operation history record of the photovoltaic power station, including daily power generation amount, weekly power generation amount, monthly power generation amount and the like, testing the power quality of the photovoltaic power generation system, detecting power generation fluctuation according to a test result, and testing the power quality including the indexes of voltage, current, frequency, phase and the like of the photovoltaic power station.
When fluctuation occurs, the operation history record of the photovoltaic power station is called, the generated energy stable reference threshold value is obtained according to the history record, the operation history record is updated after the daily operation time is over, and meanwhile the generated energy stable reference threshold value is adjusted; comparing the generated energy predicted by the generated energy prediction module with a generated energy stability reference threshold, and when the generated energy is lower than the generated energy stability reference threshold, judging that the generated energy stability is too low by the generated energy stability judging sub-module, and calling all parameters by the parameter calling control sub-module to assist the energy storage decision-making module in making a decision, so that the decision-making result of the energy storage decision-making module is better; and on the contrary, the power generation stability judging sub-module judges that the power generation amount is stable, and the parameter calling control sub-module simply calls the future power consumption requirement to finely tune the energy storage strategy according to the previously decided energy storage strategy so as to store energy. The scheme can save the calculation force resource and further optimize the energy consumption.
The load stability judging sub-module is used for recording the electricity consumption history record of the power grid, including daily electricity consumption, weekly electricity consumption, monthly electricity consumption and the like, obtaining an electricity consumption stability reference threshold according to the electricity consumption history record, comparing the electricity consumption predicted by the load predicting module with the electricity consumption stability reference threshold, judging that the electricity consumption stability is too low when the electricity consumption is lower than the electricity consumption stability reference threshold, otherwise, judging that the electricity consumption stability is higher, obtaining an electricity generation stability reference value adjusting parameter according to a specific difference value no matter whether the stability is lower or higher, adjusting the electricity generation stability reference threshold, for example, when the electricity consumption stability is reduced, ensuring the normal electricity consumption by using more stable electricity generation, so that the electricity generation stability reference threshold is adjusted to improve the requirement on the electricity consumption stability. The stability of generated energy has a key effect on maintaining the stability of a power system, and the problem of photovoltaic power generation in the operation process can be timely found and solved by analyzing the stability, so that the expansion of faults is avoided, the energy storage strategy can be timely adjusted, the power consumption requirement is further ensured, and in addition, the decision is better by adjusting the judgment of the stability of the generated energy according to the actual power consumption condition.
The foregoing is merely exemplary of the present invention, and the specific structures and features that are well known in the art are not described in any way herein, so that those skilled in the art will be aware of all the prior art to which the present invention pertains, and will be able to ascertain all of the prior art in this field, and with the ability to apply the conventional experimental means prior to this date, without the ability of those skilled in the art to perfect and practice this invention with their own skills, without the ability to develop certain typical known structures or methods that would otherwise be the obstacle to practicing this invention by those of ordinary skill in the art. It should be noted that modifications and improvements can be made by those skilled in the art without departing from the structure of the present invention, and these should also be considered as the scope of the present invention, which does not affect the effect of the implementation of the present invention and the utility of the patent. The protection scope of the present application shall be subject to the content of the claims, and the description of the specific embodiments and the like in the specification can be used for explaining the content of the claims.
Claims (9)
1. An optical energy storage control system, characterized in that: comprising the following steps:
the energy storage module is connected with the photovoltaic power station and the power grid and is used for storing electric quantity;
the photovoltaic power station acquisition module is used for acquiring geographic data and environmental data of the photovoltaic power station and photovoltaic panel installation information in real time;
the power generation prediction module is used for predicting the power generation capacity of the photovoltaic power station according to the acquired data;
the loss prediction module is used for collecting loss data of the energy storage module and calculating loss cost;
the load prediction module is used for predicting the electricity consumption according to the historical data, the real-time data and the future data;
the energy storage decision module is used for controlling the energy storage module to store energy or supply energy, calculating the energy storage cost by combining the loss cost, and comprehensively deciding the optimal energy storage mode according to the future electricity demand.
2. The optical energy storage control system of claim 1, wherein: the power generation prediction module is used for collecting historical data sets of the photovoltaic power stations, the historical data sets comprise historical data of a plurality of different photovoltaic power stations, the historical data comprise geographic data and environmental data, the power generation prediction module is used for obtaining the historical data matched with the current photovoltaic power station, and the power generation prediction module is used for obtaining the expected power generation capacity by combining the geographic data and the environmental data of the current photovoltaic power station.
3. The optical energy storage control system of claim 1, wherein: the system also comprises an energy storage analysis module, which is used for analyzing the preparation capacity required by the energy storage module, wherein the specific calculation formula is as follows:
wherein Wc is a reserve capacity required by the energy storage module, wf is a power consumption predicted value, SOC is a charge-discharge depth, η is a battery efficiency, and η is an inverter efficiency.
4. The optical energy storage control system of claim 1, wherein: the loss prediction module is also used for calculating the loss rate of the energy storage module.
5. The optical energy storage control system of claim 1, wherein: the energy storage decision module comprises a cost calculation sub-module, wherein the cost calculation sub-module calculates the power generation cost of the photovoltaic power station according to the power information, and simultaneously combines the peak-valley period electricity price of the area where the energy storage module is positioned and the loss cost of the energy storage module to calculate and obtain the final energy storage cost.
6. The optical energy storage control system of claim 1, wherein: the load prediction module is provided with a seasonal weight value, a time period weight value, a historical power consumption weight value and a historical weather weight value in historical data, and a power consumption historical predicted value is obtained through weighting; the future data are provided with weather forecast weight values, industrial and commercial energy power consumption weight values and peak-valley forecast weight values, and the future forecast values of the power consumption are obtained through weighting; the real-time data are provided with a real-time weather weight value, a real-time electricity consumption weight value, an industrial electricity consumption distribution weight value and a load prediction module, and a real-time correction value is obtained through weighting;
the load prediction module comprehensively predicts the electricity consumption of each period in the future according to the electricity consumption history predicted value and the electricity consumption future predicted value, and corrects the electricity consumption predicted value of the adjacent period in the future by utilizing the real-time correction value.
7. The optical energy storage control system of claim 1, wherein: the system also comprises a power grid prediction module which is used for predicting the emergency of the power grid and sending the prediction result to the load prediction module so as to adjust the capacity of the energy storage module which needs to be prepared.
8. The optical energy storage control system of claim 7, wherein: the energy storage decision-making module further comprises a priority judging sub-module, wherein the priority judging sub-module judges the priority of the electricity utilization facilities according to the actual electricity utilization requirement and provides electric energy for the electricity utilization facilities according to the priority.
9. A light energy storage control method is characterized in that: use of an optical energy storage control system as claimed in any one of claims 1-8.
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| CN117458568A (en) | 2024-01-26 |
| CN116454951B (en) | 2023-12-05 |
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