CN115632396A - Photovoltaic energy storage system for air compression station - Google Patents
Photovoltaic energy storage system for air compression station Download PDFInfo
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- CN115632396A CN115632396A CN202211363806.8A CN202211363806A CN115632396A CN 115632396 A CN115632396 A CN 115632396A CN 202211363806 A CN202211363806 A CN 202211363806A CN 115632396 A CN115632396 A CN 115632396A
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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
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- 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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- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
The invention discloses a photovoltaic energy storage system for an air compression station, and relates to the technical field of new energy. The power prediction module inputs the environmental parameters into a preset photovoltaic prediction model to obtain the predicted output power of the photovoltaic power generation system; the photovoltaic control module controls the working modes of the energy storage module and the grid-connected inverter according to the predicted output power and the average load of the air compression station; the energy storage module stores electric energy of a photovoltaic power generation system and/or an external power grid system, or outputs the stored electric energy to the air compression station; the grid-connected inverter inputs the electric energy of the photovoltaic power generation system into an external power grid system, or inputs the electric energy of the external power grid system into the air compression station and/or the energy storage module. The predicted output power of the photovoltaic power generation system in the next period can be predicted through the input of the environmental parameters and the preset photovoltaic prediction model, the working modes of the energy storage module and the grid-connected inverter are accurately controlled according to the predicted output power and the average load of the air compression station, and the utilization rate of energy generated by the photovoltaic power generation system is improved.
Description
Technical Field
The invention relates to the technical field of new energy, in particular to a photovoltaic energy storage system for an air compression station.
Background
The compressed air is used as the most environment-friendly power source in industrial production, is widely applied to industries such as medicine, food, machinery, electronics, plastic, textile, electric power, building materials and the like, and is used as a power source for spraying, stirring, conveying and the like. The air compression station is one of the necessary infrastructures for each plant.
However, the air compression station is often the largest energy consumption facility of an enterprise or a factory, and the energy input of the enterprise can be reduced through the photovoltaic power generation system. But the utilization rate of the energy generated by the photovoltaic power generation system of the air compression station in the prior art is low.
Disclosure of Invention
The invention aims to solve the problems of the background technology, and provides a photovoltaic energy storage system for an air compression station.
The purpose of the invention can be realized by the following technical scheme:
the embodiment of the invention provides a photovoltaic energy storage system for an air compression station, which comprises a power prediction module, an energy storage module, a photovoltaic control module and a grid-connected inverter; wherein:
the power prediction module is used for acquiring environmental parameters of the photovoltaic power generation system according to a preset period, inputting the environmental parameters into a preset photovoltaic prediction model and obtaining the predicted output power of the next period of the photovoltaic power generation system;
the photovoltaic control module is used for controlling the working modes of the energy storage module and the grid-connected inverter according to the predicted output power and the average load of the air compression station;
the energy storage module is used for storing electric energy of the photovoltaic power generation system and/or an external power grid system or outputting the stored electric energy to the air compression station;
the grid-connected inverter is used for inputting the electric energy of the photovoltaic power generation system into the external power grid system, or inputting the electric energy of the external power grid system into the air compression station and/or the energy storage module.
Optionally, the system further comprises an offline training module; the photovoltaic prediction model comprises a weather identification submodel and a power prediction submodel;
the off-line training module is used for acquiring historical power generation data of the photovoltaic power generation system, classifying the historical power generation data by using a fuzzy kernel clustering algorithm, constructing a weather recognition sub-model by using a Support Vector Machine (SVM), and constructing a power prediction sub-model by using a Support Vector Regression (SVR); the historical power generation data comprises environmental parameters and actual output power of each preset period in a historical time period.
Optionally, the environmental parameters include irradiation change data and temperature change data in a preset period; the off-line module comprises a feature extraction module, a fuzzy kernel clustering module, an SVM module and an SVR module;
the feature extraction module is used for determining an environment feature vector corresponding to each preset period according to the environment parameters;
the fuzzy kernel clustering module is used for classifying the environmental characteristic vectors corresponding to the preset periods by using a fuzzy kernel clustering algorithm to obtain weather classification results;
the SVM module is used for constructing a weather identification submodel by using a Support Vector Machine (SVM) and a weather classification result;
and the SVR module is used for corresponding the weather classification result to the actual output power and constructing a power prediction sub-model by using a support vector regression SVR.
Optionally, the environmental feature vector of each preset period includes at least one of a maximum irradiance, a maximum temperature, a maximum irradiance fluctuation value, an average irradiance fluctuation value, a standard deviation irradiance fluctuation, and a maximum value of a third derivative of the irradiance variation data within the preset period.
Optionally, the photovoltaic control module is configured to:
judging the size relationship between the predicted output power and the average load of the air compression station;
if the predicted output power is larger than the average load of the air compression station, controlling the energy storage module to be in an input energy storage working mode, and after the energy storage module reaches a preset charging state, controlling the grid-connected inverter to be in an output working mode, and inputting the electric energy of the photovoltaic power generation system into the external power grid system;
and if the predicted output power is smaller than the average load of the air compression station, controlling the energy storage module to be in an output discharge working mode, controlling the grid-connected inverter to be in an input working mode after the energy storage module reaches a preset discharge state, and inputting the electric energy of the external power grid system into the air compression station.
Optionally, the photovoltaic control module is further configured to:
in the power consumption valley period of the external power grid system, if the energy storage module is detected not to reach the preset charging state, the energy storage module is controlled to be in an input energy storage working mode, the grid-connected inverter is controlled to be in the input working mode, and the external power grid system is used for charging the energy storage module.
Optionally, the system further comprises a cogeneration module;
the waste heat power generation module is used for recycling waste heat by using high-temperature steam generated by the air compression station to generate electric energy to be stored in the energy storage module.
The embodiment of the invention provides a photovoltaic energy storage system for an air compression station, which comprises a power prediction module, an energy storage module, a photovoltaic control module and a grid-connected inverter; wherein: the power prediction module is used for acquiring environmental parameters of the photovoltaic power generation system according to a preset period, inputting the environmental parameters into a preset photovoltaic prediction model and obtaining the predicted output power of the next period of the photovoltaic power generation system; the photovoltaic control module is used for controlling the working modes of the energy storage module and the grid-connected inverter according to the predicted output power and the average load of the air compression station; the energy storage module is used for storing electric energy of the photovoltaic power generation system and/or an external power grid system or outputting the stored electric energy to the air compression station; the grid-connected inverter is used for inputting the electric energy of the photovoltaic power generation system into the external power grid system, or inputting the electric energy of the external power grid system into the air compression station and/or the energy storage module. The predicted output power of the photovoltaic power generation system in the next period can be predicted through the input of the environmental parameters and the preset photovoltaic prediction model, the working modes of the energy storage module and the grid-connected inverter are accurately controlled according to the predicted output power and the average load of the air compression station, and the utilization rate of energy generated by the photovoltaic power generation system is improved.
Drawings
The invention will be further described with reference to the accompanying drawings.
Fig. 1 is a system block diagram of a photovoltaic energy storage system for an air compression station according to an embodiment of 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.
The embodiment of the invention provides a photovoltaic energy storage system for an air compression station. Referring to fig. 1, fig. 1 is a system block diagram of a photovoltaic energy storage system for an air compression station according to an embodiment of the present invention. The system comprises a power prediction module, an energy storage module, a photovoltaic control module and a grid-connected inverter; wherein:
the power prediction module is used for acquiring environmental parameters of the photovoltaic power generation system according to a preset period, inputting the environmental parameters into a preset photovoltaic prediction model and obtaining the predicted output power of the next period of the photovoltaic power generation system;
the photovoltaic control module is used for controlling the working modes of the energy storage module and the grid-connected inverter according to the predicted output power and the average load of the air compression station;
the energy storage module is used for storing electric energy of the photovoltaic power generation system and/or an external power grid system or outputting the stored electric energy to the air compression station;
the grid-connected inverter is used for inputting the electric energy of the photovoltaic power generation system into the external power grid system, or inputting the electric energy of the external power grid system into the air compression station and/or the energy storage module.
According to the photovoltaic energy storage system for the air compression station, the predicted output power of the photovoltaic power generation system in the next period can be predicted through the input of the environmental parameters and the preset photovoltaic prediction model, the working modes of the energy storage module and the grid-connected inverter are accurately controlled according to the predicted output power and the average load of the air compression station, and the utilization rate of energy generated by the photovoltaic power generation system is improved.
In one implementation, the energy storage module may use mechanical energy storage (pumped water energy storage, compressed air energy storage, and flywheel energy storage), electromagnetic energy storage (superconducting energy storage and super capacitor energy storage), electrochemical energy storage (lead-acid battery, sodium-sulfur battery, lithium ion battery, flow battery, and electrolyte hydrogen production energy storage), and the like.
In one embodiment, the system further comprises an offline training module; the photovoltaic prediction model comprises a weather identification submodel and a power prediction submodel;
the off-line training module is used for acquiring historical power generation data of the photovoltaic power generation system, classifying the historical power generation data by using a fuzzy kernel clustering algorithm, constructing a weather recognition sub-model by using a Support Vector Machine (SVM), and constructing a power prediction sub-model by using a Support Vector Regression (SVR); the historical power generation data comprises environmental parameters and actual output power of each preset period in a historical time period.
In one implementation, the environmental parameter may be historical meteorological data including irradiance intensity, temperature, wind speed and direction, and the like.
In one embodiment, the environmental parameters include irradiation change data and temperature change data within a preset period; the off-line module comprises a feature extraction module, a fuzzy kernel clustering module, an SVM module and an SVR module;
the characteristic extraction module is used for determining an environment characteristic vector corresponding to each preset period according to the environment parameters;
the fuzzy kernel clustering module is used for classifying the environmental characteristic vectors corresponding to the preset periods by using a fuzzy kernel clustering algorithm to obtain weather classification results;
the SVM module is used for constructing a weather identification submodel by using a Support Vector Machine (SVM) and a weather classification result;
and the SVR module is used for corresponding the weather classification result to the actual output power and constructing a power prediction submodel by using a support vector regression SVR.
In one implementation, the radiation intensity and temperature variations have a large impact on the instantaneous power generation of the photovoltaic power plant. The embodiment of the invention selects the irradiation intensity and the temperature to predict the predicted output power of the photovoltaic power generation system.
In one embodiment, the environmental feature vector for each preset period includes at least one of a maximum irradiance, a maximum temperature, a maximum irradiance fluctuation value, an average irradiance fluctuation value, a standard deviation irradiance fluctuation, and a maximum value of a third derivative of the irradiance variation data within the preset period.
In one implementation, the maximum irradiance, the maximum fluctuation value of irradiance, the average value of irradiance fluctuation and the standard deviation of irradiance fluctuation in each preset period can be determined through the irradiation change data. The irradiance fluctuation of the irradiance change data can be characterized by a first derivative of the irradiance change data, and generally the irradiance change data is discrete data with a fixed sampling rate, and a first difference of the irradiance change data can be used to replace the first derivative. And averaging the first-order difference of the irradiation change data to obtain an irradiance fluctuation average value. The third derivative of the irradiation change data can also be solved by using difference, the third derivative of the irradiation change data is more sensitive to rapid weather change, and the environmental characteristic vector comprises the maximum value of the third derivative of the irradiation change data, which is used as the maximum value of the third derivative of the irradiation change data, so that the accuracy of the photovoltaic prediction model can be improved.
In one embodiment, the photovoltaic control module is configured to:
judging the size relation between the predicted output power and the average load of the air compression station;
if the predicted output power is larger than the average load of the air compression station, controlling the energy storage module to be in an input energy storage working mode, and after the energy storage module reaches a preset charging state, controlling the grid-connected inverter to be in an output working mode, and inputting the electric energy of the photovoltaic power generation system into the external power grid system;
and if the predicted output power is smaller than the average load of the air compression station, controlling the energy storage module to be in an output discharge working mode, and after the energy storage module reaches a preset discharge state, controlling the grid-connected inverter to be in an input working mode, and inputting the electric energy of the external power grid system into the air compression station.
In one implementation, the energy storage module reaches a preset charging state, that is, the current electric energy storage amount of the energy storage module reaches a preset percentage of the maximum storage amount, and the preset percentage is set by a technician according to actual conditions.
In one implementation, since the load of the air compression station is relatively stable, the load of the current air compression station can be characterized by the average load of the air compression station. If the predicted output power is larger than the average load of the air compression station, it is indicated that the predicted generating capacity of the photovoltaic power generation system is enough to meet the electric energy demand of the air compression station, and the residual electric energy exists, the energy storage module can be controlled to store the residual electric energy to the energy storage module for an input energy storage working mode. When the energy storage module reaches the preset charging state and has residual electric energy, the residual electric energy can be input into an external power grid system in order to avoid the excessive charging of the energy storage module.
In one embodiment, the photovoltaic control module is further configured to:
in the power consumption valley period of the external power grid system, if the energy storage module is detected not to reach the preset charging state, the energy storage module is controlled to be in an input energy storage working mode, the grid-connected inverter is controlled to be in the input working mode, and the external power grid system is used for charging the energy storage module.
In one implementation, during the electricity consumption valley period of the external power grid system, the energy storage module which does not reach the preset charging state is charged through the external power grid system, so that the energy cost of an enterprise can be reduced.
In one embodiment, the system further comprises a waste heat power generation module;
and the waste heat power generation module is used for recycling waste heat by using high-temperature steam generated by the air compression station, and generating electric energy to be stored in the energy storage module.
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 (7)
1. A photovoltaic energy storage system for an air compression station is characterized by comprising a power prediction module, an energy storage module, a photovoltaic control module and a grid-connected inverter; wherein:
the power prediction module is used for acquiring environmental parameters of the photovoltaic power generation system according to a preset period, inputting the environmental parameters into a preset photovoltaic prediction model and obtaining the predicted output power of the photovoltaic power generation system in the next period;
the photovoltaic control module is used for controlling the working modes of the energy storage module and the grid-connected inverter according to the predicted output power and the average load of the air compression station;
the energy storage module is used for storing electric energy of the photovoltaic power generation system and/or an external power grid system or outputting the stored electric energy to the air compression station;
the grid-connected inverter is used for inputting the electric energy of the photovoltaic power generation system into the external power grid system, or inputting the electric energy of the external power grid system into the air compression station and/or the energy storage module.
2. The photovoltaic energy storage system for the air compression station is characterized by further comprising an offline training module; the photovoltaic prediction model comprises a weather identification submodel and a power prediction submodel;
the off-line training module is used for acquiring historical power generation data of the photovoltaic power generation system, classifying the historical power generation data by using a fuzzy kernel clustering algorithm, constructing a weather recognition sub-model by using a Support Vector Machine (SVM), and constructing a power prediction sub-model by using a Support Vector Regression (SVR); the historical power generation data comprises environmental parameters and actual output power of each preset period in a historical time period.
3. The photovoltaic energy storage system for the air compression station is characterized in that the environmental parameters comprise irradiation change data and temperature change data in a preset period; the off-line module comprises a feature extraction module, a fuzzy kernel clustering module, an SVM module and an SVR module;
the characteristic extraction module is used for determining an environment characteristic vector corresponding to each preset period according to the environment parameters;
the fuzzy kernel clustering module is used for classifying the environmental characteristic vectors corresponding to the preset periods by using a fuzzy kernel clustering algorithm to obtain a weather classification result;
the SVM module is used for constructing a weather identification submodel by using a Support Vector Machine (SVM) and a weather classification result;
and the SVR module is used for corresponding the weather classification result to the actual output power and constructing a power prediction sub-model by using a support vector regression SVR.
4. The photovoltaic energy storage system for the air compression station, according to claim 3, wherein the environmental feature vector of each preset period comprises at least one of maximum irradiance, maximum temperature, maximum irradiance fluctuation value, average irradiance fluctuation value, standard deviation irradiance fluctuation and maximum value of third derivative of irradiance change data in the preset period.
5. The photovoltaic energy storage system for the air compression station is characterized in that the photovoltaic control module is used for:
judging the size relation between the predicted output power and the average load of the air compression station;
if the predicted output power is larger than the average load of the air compression station, controlling the energy storage module to be in an input energy storage working mode, and after the energy storage module reaches a preset charging state, controlling the grid-connected inverter to be in an output working mode, and inputting the electric energy of the photovoltaic power generation system into the external power grid system;
and if the predicted output power is smaller than the average load of the air compression station, controlling the energy storage module to be in an output discharge working mode, and after the energy storage module reaches a preset discharge state, controlling the grid-connected inverter to be in an input working mode, and inputting the electric energy of the external power grid system into the air compression station.
6. The photovoltaic energy storage system for the air compression station is characterized in that the photovoltaic control module is further used for:
in the power consumption valley period of the external power grid system, if the energy storage module is detected not to reach the preset charging state, the energy storage module is controlled to be in an input energy storage working mode, the grid-connected inverter is controlled to be in the input working mode, and the energy storage module is charged by using the electric energy of the external power grid system.
7. The photovoltaic energy storage system for the air compression station is characterized by further comprising a waste heat power generation module;
the waste heat power generation module is used for recycling waste heat by using high-temperature steam generated by the air compression station to generate electric energy to be stored in the energy storage module.
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| CN102769302A (en) * | 2012-07-10 | 2012-11-07 | 江苏辉伦太阳能科技有限公司 | Photovoltaic grid-connected inverter with stored energy management and load-power-based output functions |
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| US10409925B1 (en) * | 2012-10-17 | 2019-09-10 | Clean Power Research, L.L.C. | Method for tuning photovoltaic power generation plant forecasting with the aid of a digital computer |
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Patent Citations (4)
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| CN102769302A (en) * | 2012-07-10 | 2012-11-07 | 江苏辉伦太阳能科技有限公司 | Photovoltaic grid-connected inverter with stored energy management and load-power-based output functions |
| US10409925B1 (en) * | 2012-10-17 | 2019-09-10 | Clean Power Research, L.L.C. | Method for tuning photovoltaic power generation plant forecasting with the aid of a digital computer |
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