CN118052650A - Shared energy storage transaction method, system, electronic equipment and storage medium - Google Patents
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Abstract
The invention discloses a shared energy storage transaction method, a system, electronic equipment and a storage medium, and relates to the field of shared energy storage transaction; preprocessing the acquired data; analyzing user demand information by using the trained large language model, and determining the charge and discharge behaviors and the charge and discharge capacity demands of the user; and determining an objective function and constraint conditions of the shared energy storage transaction process, establishing a linear programming problem according to the objective function and the constraint conditions, and solving. According to the invention, a large language model is adopted, and based on historical data, recognition keywords, semantic structures and context information analysis are carried out through training and pattern matching of massive text data, so that the charge and discharge behaviors and charge and discharge capacity requirements of a user are determined from demand information provided by the user, and the accuracy and efficiency of shared energy storage transaction are improved.
Description
Technical Field
The present invention relates to the field of shared energy storage transactions, and in particular, to a shared energy storage transaction method, system, electronic device, and storage medium.
Background
With the rapid development of economy, the whole society has put higher and higher requirements on power supply reliability. Under the current situation of the strong development of new energy, the installed capacity of the new energy steadily rises, but the development of the new energy faces some challenges due to the influence of various factors such as the peak regulation capacity of a system, market mechanisms and the like, including the problems of difficult energy consumption, limited contribution to electric energy, poor power generation scheduling flexibility, strong price volatility and the like. In order to solve the problem of new energy consumption, energy storage technology is considered as a key technology for solving the problem. Shared energy storage is a technology that enables energy storage devices and energy resources to be shared and transacted. The intelligent energy management system is connected with a plurality of distributed energy storage systems, idle energy storage capacity and energy resources are brought into a centralized management platform, and monitoring, control and optimization of energy storage equipment are achieved through the intelligent energy management system.
In recent years, large language models, which are models with huge scale parameters and powerful language generation capability constructed based on deep learning and natural language processing techniques, have been developed rapidly. The method can understand and generate the natural language text, and has the capabilities of multiple language tasks such as dialogue, question and answer, translation, abstract generation and the like. The core of a large language model is a neural network structure in which multiple layers of transformation and representation learning modules are used to model and predict an input language sequence. Through large-scale training data and optimization algorithms, the large language model can learn rich language knowledge and semantic understanding capability.
The existing shared energy storage transaction method has the problems of inaccurate energy demand matching and low transaction efficiency. Traditional algorithms and models do not fully utilize the complex information of energy demand and supply, and a more intelligent method is needed.
Disclosure of Invention
The invention aims to provide a shared energy storage transaction method, a system, electronic equipment and a storage medium, so as to improve the accuracy and efficiency of the shared energy storage transaction.
In order to achieve the above object, the present invention provides the following solutions:
a shared energy storage transaction method, comprising:
acquiring demand information, real-time electricity price data and energy storage equipment information of a user in an electric power system; the demand information of the user comprises the demand of the user on the electric energy and the amount of the electric energy required to be stored in the energy storage equipment; the energy storage equipment information comprises charge and discharge efficiency of a shared energy storage system and running cost of shared energy storage system equipment;
Preprocessing the demand information of the user, the real-time electricity price data and the energy storage equipment information to obtain processed demand information of the user, processed real-time electricity price data and processed energy storage equipment information;
Determining the charge and discharge behaviors and the charge and discharge capacities of the user by utilizing a trained large language model according to the processed demand information of the user; the trained large language model is obtained by training the large language model by utilizing the demand information of a training user and the charge and discharge behaviors and the charge and discharge capacities of the training user;
According to the running cost of the processed shared energy storage system equipment, the charging and discharging efficiency of the processed shared energy storage system, the processed real-time electricity price data, the charging and discharging behaviors and the charging and discharging capacities of the users, establishing a linear programming problem taking the maximum total income of the shared energy storage system as an objective function, and taking the sum of the electric power of the input shared energy storage system and the charging and discharging power of the processed shared energy storage system and the electric quantity of the energy storage system at the time t equal to the electric quantity of the energy storage system at the time t-1 and the sum of the charging and discharging power of the energy storage equipment service and the power selling and surfing power of the energy storage system as constraint conditions; the charge and discharge power of the energy storage equipment service is determined according to the charge and discharge behavior and the charge and discharge capacity of the user;
And solving the linear programming problem by using a CPLEX solver, and determining the service power of the energy storage equipment so as to carry out energy storage transaction according to the service power of the energy storage equipment.
Optionally, the objective function is:
maxI＝Ishare+Isell-Coperate；
Wherein, I is the total income of the shared energy storage system; i share is the benefit obtained by providing service for the shared energy storage system; i sell is the electricity selling benefit of the shared energy storage system; c operate is the running cost of the processed shared energy storage system equipment; p share,t is the charge and discharge power to provide the energy storage device service; k t is a value correction coefficient; mu share,t is the unit price of energy storage service; p sell,t is the electricity selling and internet power of the energy storage system; mu sell,t is the processed real-time electricity price data.
Optionally, the constraint condition is:
Pin,t＝Pout,t+Pstorage,t；
Ei,t＝Ei,t-1+Pshare,t+Psell,t；
Wherein P in,t is the input shared energy storage system electric power; p out,t is the output shared energy storage system electric power; p storage,t is the charge and discharge power of the processed shared energy storage system; e i,t is the electric quantity of the energy storage system at the time t; e i,t-1 is the electric quantity of the energy storage system at the time t-1; p share,t is the charge and discharge power to provide the energy storage device service; p sell,t is the electricity selling and internet power of the energy storage system.
Optionally, preprocessing the demand information, the real-time electricity price data, the energy storage device information, the energy supply history data and the environmental factor data of the user to obtain processed demand information, processed real-time electricity price data, processed energy storage device information, processed energy supply history data and processed environmental factor data of the user, which specifically includes:
Carrying out data cleaning on the demand information of the user, the real-time electricity price data, the energy storage equipment information, the energy supply historical data and the environmental factor data to obtain cleaned demand information, cleaned real-time electricity price data, cleaned energy storage equipment information, cleaned energy supply historical data and cleaned environmental factor data;
And performing data dimension reduction on the cleaned demand information, the cleaned real-time electricity price data, the cleaned energy storage equipment information, the cleaned energy supply historical data and the cleaned environment factor data by using a principal component analysis method to obtain the processed demand information, the processed real-time electricity price data, the processed energy storage equipment information, the processed energy supply historical data and the processed environment factor data of the user.
A shared energy storage transaction system, comprising:
the data acquisition module is used for acquiring the demand information, the real-time electricity price data and the energy storage equipment information of the user in the power system; the demand information of the user comprises the demand of the user on the electric energy and the amount of the electric energy required to be stored in the energy storage equipment; the energy storage equipment information comprises charge and discharge efficiency of a shared energy storage system and running cost of shared energy storage system equipment;
The preprocessing module is used for preprocessing the demand information of the user, the real-time electricity price data and the energy storage equipment information to obtain processed demand information of the user, processed real-time electricity price data and processed energy storage equipment information;
The information extraction module is used for determining the charge and discharge behaviors and the charge and discharge capacity of the user by utilizing the trained large language model according to the processed demand information of the user; the trained large language model is obtained by training the large language model by utilizing the demand information of a training user and the charge and discharge behaviors and the charge and discharge capacities of the training user;
The linear programming problem establishing module is used for establishing a linear programming problem taking the total income of the shared energy storage system as an objective function to the maximum extent according to the running cost of the processed shared energy storage system equipment, the charging and discharging efficiency of the processed shared energy storage system, the processed real-time electricity price data, the charging and discharging behaviors of the user and the charging and discharging capacity, and taking the sum of the electric power of the input shared energy storage system and the charging and discharging power of the processed shared energy storage system and the electric quantity of the energy storage system at the time t equal to the electric quantity of the energy storage system at the time t-1 and the sum of the charging and discharging power of the energy storage equipment service and the electricity selling and surfing power of the energy storage system as constraint conditions;
and the resolving module is used for solving the linear programming problem by using a CPLEX solver, and determining the service power of the energy storage equipment so as to conduct energy storage transaction according to the service power of the energy storage equipment.
An electronic device, comprising: the system comprises a memory and a processor, wherein the memory is used for storing a computer program, and the processor runs the computer program to enable the electronic equipment to execute the shared energy storage transaction method.
A computer readable storage medium storing a computer program which when executed by a processor implements the shared energy storage transaction method described above.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
According to the shared energy storage transaction method, the shared energy storage transaction system, the electronic equipment and the storage medium, real-time electricity price data, user demand information and energy storage equipment information in the electric power system are obtained; preprocessing the acquired data; analyzing user demand information by using the trained large language model, and determining the charge and discharge behaviors and the charge and discharge capacity demands of the user; determining an objective function of a shared energy storage transaction process; the method comprises the steps of determining constraint conditions in a shared energy storage transaction process, establishing a linear programming problem according to an objective function and the constraint conditions, solving the linear programming problem, and performing recognition keywords, semantic structures and contextual information analysis by training and pattern matching of massive text data based on historical data, so that the charge and discharge behaviors and charge and discharge capacity requirements of a user are determined from requirement information provided by the user, the precision and efficiency of the shared energy storage transaction are improved, and the change of the power grid requirement can be responded better.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a shared energy storage transaction method provided by the invention;
Fig. 2 is a flow chart of the shared energy storage transaction method in practical application.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide a shared energy storage transaction method, a system, electronic equipment and a storage medium, so as to improve the accuracy and efficiency of the shared energy storage transaction.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
Example 1
As shown in fig. 1 and 2, the shared energy storage transaction method provided by the invention includes:
step 101: acquiring demand information, real-time electricity price data and energy storage equipment information of a user in an electric power system; the demand information of the user comprises the demand of the user on the electric energy and the amount of the electric energy required to be stored in the energy storage equipment; the energy storage device information comprises charge and discharge efficiency of the shared energy storage system and running cost of the shared energy storage system.
In practical application, energy supply history data, real-time electricity price data, user demand information, energy storage equipment information and other environmental factor data capable of influencing energy storage transaction in the power system are obtained.
The energy storage device information comprises the number of the energy storage devices, the maximum capacity of the energy storage devices, the charge and discharge efficiency of the energy storage devices and the use cost of the energy storage devices.
Other environmental factor data that can affect energy storage transactions include weather, temperature, rainfall, and solar time.
Step 102: and preprocessing the demand information of the user, the real-time electricity price data and the energy storage equipment information to obtain processed demand information of the user, processed real-time electricity price data and processed energy storage equipment information.
In practical applications, the acquired data is preprocessed. The data preprocessing comprises data cleaning and data dimension reduction, wherein the data cleaning comprises the operation of removing null values and abnormal values in a data set, and the data dimension reduction adopts a principal component analysis method to screen variables with little influence on the energy storage transaction amount.
Step 103: determining the charge and discharge behaviors and the charge and discharge capacities of the user by utilizing a trained large language model according to the processed demand information of the user; the trained large language model is obtained by training the large language model by utilizing the demand information of the training user and the charge and discharge behaviors and the charge and discharge capacities of the training user.
In practical application, the large language model is utilized to analyze the user demand information and determine the charge and discharge behaviors and the charge and discharge capacity demands of the user.
The large language model is based on historical data (demand information of training users), text information related to energy storage transaction in the historical data is input into a transducer framework, words and positions in the text are encoded, global relevance of the words in text vectors is established through a self-attention mechanism of the transducer framework, and then recognition of keywords and analysis of semantic structures and context key information are achieved. Therefore, the charge and discharge behaviors and the charge and discharge capacity requirements of the user are determined from the requirement information provided by the user.
Step 104: according to the running cost of the processed shared energy storage system equipment, the charging and discharging efficiency of the processed shared energy storage system, the processed real-time electricity price data, the charging and discharging behaviors and the charging and discharging capacities of the users, establishing a linear programming problem taking the maximum total income of the shared energy storage system as an objective function, and taking the sum of the electric power of the input shared energy storage system and the charging and discharging power of the processed shared energy storage system and the electric quantity of the energy storage system at the time t equal to the electric quantity of the energy storage system at the time t-1 and the sum of the charging and discharging power of the energy storage equipment service and the power selling and surfing power of the energy storage system as constraint conditions; and the charge and discharge power of the energy storage equipment service is determined according to the charge and discharge behavior and the charge and discharge capacity of the user.
In a practical application, an objective function of a shared energy storage transaction process is determined. Specifically, the objective function formula of the energy storage sharing transaction process is expressed as follows:
maxI＝Ishare+Isell-Coperate。
Wherein: i is the total income of the shared energy storage system; i share is the benefit obtained by providing service for the shared energy storage system; i sell is the electricity selling benefit of the shared energy storage system; c operate is the running cost of the processed shared energy storage system equipment; p share,t is the charge and discharge power to provide the energy storage device service; k t is a value correction coefficient; mu share,t is the unit price of energy storage service; p sell,t is the electricity selling and internet power of the energy storage system; mu sell,t is the processed real-time electricity price data.
Constraints of the shared energy storage transaction process are determined. Specifically, the constraint condition formula of the energy storage sharing transaction process is expressed as follows:
Pin,t＝Pout,t+Pstorage,t。
Ei,t＝Ei,t-1+Pshare,t+Psell,t。
Wherein: p in,t is the input shared energy storage system electric power; p out,t is the output shared energy storage system electric power; p storage,t is the charge and discharge power of the processed shared energy storage system; e i,t is the electric quantity of the energy storage system at the time t; e i,t-1 is the electric quantity of the energy storage system at the time t-1.
Step 105: and solving the linear programming problem by using a CPLEX solver, and determining the service power of the energy storage equipment so as to carry out energy storage transaction according to the service power of the energy storage equipment.
In practical application, the linear programming problem is solved, and the service power of the energy storage equipment corresponding to the maximum benefit is the required solving result. And solving the linear programming problem by adopting a CPLEX solver, thereby obtaining an optimal shared energy storage scheduling scheme.
The invention provides a shared energy storage transaction method, which adopts a large language model, is based on historical data, and performs recognition keywords, semantic structures and context information analysis through training and pattern matching of massive text data, so that the charge and discharge behaviors and charge and discharge capacity requirements of a user are determined from demand information provided by the user, the precision and efficiency of shared energy storage transaction are improved, and the change of the power grid requirements can be responded better.
Example two
In order to perform a corresponding method of the above embodiments to achieve the corresponding functions and technical effects, a shared energy storage transaction system is provided below, including:
The data acquisition module is used for acquiring the demand information, the real-time electricity price data and the energy storage equipment information of the user in the power system; the demand information of the user comprises the demand of the user on the electric energy and the amount of the electric energy required to be stored in the energy storage equipment; the energy storage device information comprises charge and discharge efficiency of the shared energy storage system and running cost of the shared energy storage system.
The preprocessing module is used for preprocessing the demand information of the user, the real-time electricity price data and the energy storage equipment information to obtain the processed demand information of the user, the processed real-time electricity price data and the processed energy storage equipment information.
The information extraction module is used for determining the charge and discharge behaviors and the charge and discharge capacity of the user by utilizing the trained large language model according to the processed demand information of the user; the trained large language model is obtained by training the large language model by utilizing the demand information of the training user and the charge and discharge behaviors and the charge and discharge capacities of the training user.
The linear programming problem establishing module is used for establishing a linear programming problem taking the total income of the shared energy storage system as an objective function to the maximum extent according to the running cost of the processed shared energy storage system equipment, the charging and discharging efficiency of the processed shared energy storage system, the processed real-time electricity price data, the charging and discharging behaviors of the user and the charging and discharging capacity, and taking the sum of the electric power of the input shared energy storage system and the charging and discharging power of the processed shared energy storage system, and the electric quantity of the energy storage system at the time t, which is equal to the electric quantity of the energy storage system at the time t-1, and the sum of the charging and discharging power of the energy storage equipment service and the electricity selling and surfing power of the energy storage system, as constraint conditions.
And the resolving module is used for solving the linear programming problem by using a CPLEX solver, and determining the service power of the energy storage equipment so as to conduct energy storage transaction according to the service power of the energy storage equipment.
Example III
The invention provides an electronic device, comprising: the shared energy storage transaction system comprises a memory and a processor, wherein the memory is used for storing a computer program, and the processor runs the computer program to enable the electronic equipment to execute the shared energy storage transaction method of the first embodiment.
Example IV
The present invention provides a computer readable storage medium storing a computer program which when executed by a processor implements the shared energy storage transaction method of embodiment one.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (7)
1. A shared energy storage transaction method, comprising:
acquiring demand information, real-time electricity price data and energy storage equipment information of a user in an electric power system; the demand information of the user comprises the demand of the user on the electric energy and the amount of the electric energy required to be stored in the energy storage equipment; the energy storage equipment information comprises charge and discharge efficiency of a shared energy storage system and running cost of shared energy storage system equipment;
Preprocessing the demand information of the user, the real-time electricity price data and the energy storage equipment information to obtain processed demand information of the user, processed real-time electricity price data and processed energy storage equipment information;
Determining the charge and discharge behaviors and the charge and discharge capacities of the user by utilizing a trained large language model according to the processed demand information of the user; the trained large language model is obtained by training the large language model by utilizing the demand information of a training user and the charge and discharge behaviors and the charge and discharge capacities of the training user;
According to the running cost of the processed shared energy storage system equipment, the charging and discharging efficiency of the processed shared energy storage system, the processed real-time electricity price data, the charging and discharging behaviors and the charging and discharging capacities of the users, establishing a linear programming problem taking the maximum total income of the shared energy storage system as an objective function, and taking the sum of the electric power of the input shared energy storage system and the charging and discharging power of the processed shared energy storage system and the electric quantity of the energy storage system at the time t equal to the electric quantity of the energy storage system at the time t-1 and the sum of the charging and discharging power of the energy storage equipment service and the power selling and surfing power of the energy storage system as constraint conditions; the charge and discharge power of the energy storage equipment service is determined according to the charge and discharge behavior and the charge and discharge capacity of the user;
And solving the linear programming problem by using a CPLEX solver, and determining the service power of the energy storage equipment so as to carry out energy storage transaction according to the service power of the energy storage equipment.
2. The shared energy storage transaction method according to claim 1, wherein the objective function is:
maxI＝Ishare+Isell-Coperate；
Wherein, I is the total income of the shared energy storage system; i share is the benefit obtained by providing service for the shared energy storage system; i sell is the electricity selling benefit of the shared energy storage system; c operate is the running cost of the processed shared energy storage system equipment; p share,t is the charge and discharge power to provide the energy storage device service; k t is a value correction coefficient; mu share,t is the unit price of energy storage service; p sell,t is the electricity selling and internet power of the energy storage system; mu sell,t is the processed real-time electricity price data.
3. The shared energy storage transaction method according to claim 1, wherein the constraints are:
Pin,t＝Pout,t+Pstorage,t；
Ei,t＝Ei,t-1+Pshare,t+Psell,t；
Wherein P in,t is the input shared energy storage system electric power; p out,t is the output shared energy storage system electric power; p storage,t is the charge and discharge power of the processed shared energy storage system; e i,t is the electric quantity of the energy storage system at the time t; e i,t-1 is the electric quantity of the energy storage system at the time t-1; p share,t is the charge and discharge power to provide the energy storage device service; p sell,t is the electricity selling and internet power of the energy storage system.
4. The shared energy storage transaction method according to claim 1, wherein preprocessing the user's demand information, the real-time electricity rate data, the energy storage device information, the energy supply history data, and the environmental factor data to obtain the user's processed demand information, the processed real-time electricity rate data, the processed energy storage device information, the processed energy supply history data, and the processed environmental factor data specifically includes:
Carrying out data cleaning on the demand information of the user, the real-time electricity price data, the energy storage equipment information, the energy supply historical data and the environmental factor data to obtain cleaned demand information, cleaned real-time electricity price data, cleaned energy storage equipment information, cleaned energy supply historical data and cleaned environmental factor data;
And performing data dimension reduction on the cleaned demand information, the cleaned real-time electricity price data, the cleaned energy storage equipment information, the cleaned energy supply historical data and the cleaned environment factor data by using a principal component analysis method to obtain the processed demand information, the processed real-time electricity price data, the processed energy storage equipment information, the processed energy supply historical data and the processed environment factor data of the user.
5. A shared energy storage transaction system, comprising:
the data acquisition module is used for acquiring the demand information, the real-time electricity price data and the energy storage equipment information of the user in the power system; the demand information of the user comprises the demand of the user on the electric energy and the amount of the electric energy required to be stored in the energy storage equipment; the energy storage equipment information comprises charge and discharge efficiency of a shared energy storage system and running cost of shared energy storage system equipment;
The preprocessing module is used for preprocessing the demand information of the user, the real-time electricity price data and the energy storage equipment information to obtain processed demand information of the user, processed real-time electricity price data and processed energy storage equipment information;
The information extraction module is used for determining the charge and discharge behaviors and the charge and discharge capacity of the user by utilizing the trained large language model according to the processed demand information of the user; the trained large language model is obtained by training the large language model by utilizing the demand information of a training user and the charge and discharge behaviors and the charge and discharge capacities of the training user;
The linear programming problem establishing module is used for establishing a linear programming problem taking the total income of the shared energy storage system as an objective function to the maximum extent according to the running cost of the processed shared energy storage system equipment, the charging and discharging efficiency of the processed shared energy storage system, the processed real-time electricity price data, the charging and discharging behaviors of the user and the charging and discharging capacity, and taking the sum of the electric power of the input shared energy storage system and the charging and discharging power of the processed shared energy storage system and the electric quantity of the energy storage system at the time t equal to the electric quantity of the energy storage system at the time t-1 and the sum of the charging and discharging power of the energy storage equipment service and the electricity selling and surfing power of the energy storage system as constraint conditions;
and the resolving module is used for solving the linear programming problem by using a CPLEX solver, and determining the service power of the energy storage equipment so as to conduct energy storage transaction according to the service power of the energy storage equipment.
6. An electronic device, comprising: a memory for storing a computer program, and a processor that runs the computer program to cause the electronic device to perform the shared energy storage transaction method of any of claims 1-4.
7. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when executed by a processor, implements the shared energy storage transaction method of any of claims 1-4.
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