CN118100301A - New energy transmission and distribution collaborative digestion operation auxiliary decision-making system - Google Patents
New energy transmission and distribution collaborative digestion operation auxiliary decision-making system Download PDFInfo
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Abstract
The invention discloses a new energy transmission and distribution collaborative digestion operation auxiliary decision-making system, which relates to the field of new energy transmission and distribution collaboration, and comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for collecting electric power energy historical data and instant data and processing the data; the analysis module is used for acquiring the data processed by the acquisition module, analyzing and predicting future power demand data, and calculating an energy optimal allocation strategy according to the future power demand data; and the processing module is used for acquiring the energy optimal allocation strategy obtained by the analysis module and generating an energy allocation adjustment schedule. The invention has the beneficial effects that: according to the invention, through collecting and analyzing the electric power energy data and generating the energy distribution adjustment schedule, the electric power energy distribution ratio is monitored and regulated in real time, so that the power grid can rapidly respond to the change of the demand and other emergency conditions, the energy distribution in the power grid is managed more efficiently, and the reliability and stability of the power grid are improved.
Description
Technical Field
The invention relates to the technical field of new energy transmission and distribution coordination, in particular to a computer device and a new energy transmission and distribution coordination and digestion operation auxiliary decision-making system.
Background
New energy refers to renewable energy sources, such as solar energy, wind energy, water energy and other environment-friendly low-carbon energy forms, the new energy sources are widely used in various fields of power generation, transportation, heat supply and the like, transmission and distribution cooperation refers to cooperation operation and management between two parts of transmission and distribution in a power system, the power system is generally divided into a transmission system and a distribution system, the transmission system is responsible for transmitting power from a power plant to each distribution station, the distribution system is responsible for transmitting power from the distribution station to final electric equipment such as families, factories and commercial buildings, in the prior art, power network management generally depends on scattered systems and processes, including independent power demand prediction, energy distribution planning and power grid operation control, the systems often lack deep integration, information island is caused, efficiency and flexibility of power grid operation are reduced, cooperation between the energy sources is lack optimization, and the prior art has obvious limitations in improving power grid operation efficiency, optimizing energy distribution and coping with complex changing power grid demands.
Disclosure of Invention
The invention is provided in view of the problems existing in the existing new energy transmission and distribution collaborative digestion operation auxiliary decision-making system.
The problem to be solved by the present invention is therefore that the prior art has significant limitations in terms of improving the operating efficiency of the grid, optimizing the energy distribution and coping with the complex changing grid requirements.
In order to solve the technical problems, the invention provides the following technical scheme: the new energy transmission and distribution collaborative digestion operation auxiliary decision-making system comprises a data analysis unit, wherein the data analysis unit is used for collecting and analyzing various data;
the data processing unit is connected with the data analysis unit through an electric signal and used for controlling and executing the analyzed data.
As a preferable scheme of the new energy transmission and distribution collaborative digestion operation auxiliary decision-making system, the invention comprises the following steps: the data analysis unit comprises an acquisition module, an analysis module and a processing module, wherein the acquisition module is used for collecting and processing historical data and instant data of electric power energy, the analysis module is used for acquiring the data processed by the acquisition module, analyzing and predicting future electric power demand data and calculating an energy optimal allocation strategy, and the processing module is used for acquiring the energy optimal allocation strategy obtained by the analysis module and generating an energy allocation adjustment schedule.
As a preferable scheme of the new energy transmission and distribution collaborative digestion operation auxiliary decision-making system, the invention comprises the following steps: the data processing unit comprises a control module and an execution module, wherein the control module is used for displaying collected data, an energy optimal allocation strategy and an energy allocation adjustment schedule, the control module is connected with other modules through a network, manages and adjusts the data to generate a final energy allocation adjustment schedule, the execution module is used for executing the final energy allocation adjustment schedule, and the execution module is connected with the power generation equipment and the energy storage equipment and controls the operation of the equipment.
As a preferable scheme of the new energy transmission and distribution collaborative digestion operation auxiliary decision-making system, the invention comprises the following steps: the acquisition module collects historical data and instant data of electric power energy, wherein the historical data and the instant data comprise power generation cost and performance data of the electric power energy, energy storage cost and performance data and historical and instant power demand data, and the processing of the data comprises data integrity checking, data cleaning, format conversion and data compression.
As a preferable scheme of the new energy transmission and distribution collaborative digestion operation auxiliary decision-making system, the invention comprises the following steps: after the analysis module acquires the data processed by the acquisition module, historical power demand data and instant power demand data are extracted, and future power demand data are predicted through analysis of the data:
Where Y t is the power demand data at the predicted time t, μ is a model constant, And θ is the autoregressive term and moving average term parameters, respectively, and ε is the error term.
As a preferable scheme of the new energy transmission and distribution collaborative digestion operation auxiliary decision-making system, the invention comprises the following steps: the analysis module calculates energy optimal allocation strategy from the current time to the t time according to the data after calculating the future power demand data:
Wherein minZ represents the minimum power generation cost, a i and b i are power generation cost coefficients of energy sources in the ith energy source, c is an energy storage cost coefficient, P i,t is the power generation amount of the ith energy source at t time, 0 is less than or equal to P i,t≤Max Pi,t,Max Pi,t is the maximum power generation amount of the ith energy source at t time, S t is the total energy storage amount at t time, S t≤Max St,Max St is the maximum energy storage amount at t time, note that various energy source t time optimal power generation amounts P i,t are solved, optimal operation amounts S t and minimum power generation cost minZ of the energy storage device are determined, the optimal power generation amounts and optimal operation amounts of various energy sources are determined through calculation, an integrated energy source optimal distribution strategy is formed by adjusting and combining each energy source power generation amount and operation amount according to the calculation result, and power demand data Y t1 and predicted power demand data Y t are compared and verified by the energy source optimal distribution strategy:
∑iPi,t+St+St-1＝Yt1
if Y t1＝Yt represents that the optimal power generation amount and the optimal operation amount of various energy sources in the energy source optimal allocation strategy are correct, the energy source optimal allocation strategy is correct, and the analysis module obtains the energy source optimal allocation strategy;
If Y t1≠Yt represents the calculation errors of the optimal power generation amount and the optimal operation amount of various energy sources in the energy source optimal distribution strategy, the analysis module solves the optimal power generation amount and the optimal operation amount of various energy sources through formulas again, and performs comparison verification with the predicted power demand data until Y t1＝Yt, and then the analysis module obtains the energy source optimal distribution strategy.
As a preferable scheme of the new energy transmission and distribution collaborative digestion operation auxiliary decision-making system, the invention comprises the following steps: the analysis module calculates an energy optimal allocation strategy from the current time to the time t through a formula and then sends the energy optimal allocation strategy to the processing module, and the processing module sorts the energy optimal allocation strategy according to the energy optimal allocation strategy and the instant energy allocation ratio according to the time sequence to generate an energy allocation adjustment schedule.
As a preferable scheme of the new energy transmission and distribution collaborative digestion operation auxiliary decision-making system, the invention comprises the following steps: the control module acquires the energy distribution adjustment schedule generated by the processing module, and then displays the data collected by the acquisition module and the energy optimal distribution strategy calculated by the analysis module to staff for checking and management, so that modification confirmation is facilitated.
As a preferable scheme of the new energy transmission and distribution collaborative digestion operation auxiliary decision-making system, the invention comprises the following steps: the control module is connected with other modules through a network and provides a centralized platform for workers to control the other modules or manage and adjust data, monitors the working states of the other modules in real time, and allows the workers to customize the display content and display format of the control module.
As a preferable scheme of the new energy transmission and distribution collaborative digestion operation auxiliary decision-making system, the invention comprises the following steps: and the execution module regulates and controls the power generation equipment and the energy storage equipment in real time according to the content after receiving the final energy distribution regulation schedule sent by the control module so as to achieve the energy distribution ratio in the regulation schedule.
The invention has the beneficial effects that: according to the invention, through collecting and analyzing the electric power energy data and generating the energy distribution adjustment schedule, the electric power energy distribution ratio is monitored and regulated in real time, so that the power grid can rapidly respond to the change of the demand and other emergency conditions, the energy distribution in the power grid is managed more efficiently, and the reliability and stability of the power grid are improved.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic structural view of the present invention.
FIG. 2 is a flow chart of the present invention.
Detailed Description
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 specific embodiments thereof which are illustrated in the appended drawings.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present invention is not limited to the specific embodiments disclosed below.
Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
Example 1
Referring to fig. 1 and 2, a first embodiment of the present invention provides a new energy transmission and distribution collaborative digestion operation auxiliary decision-making system, which includes the following contents:
The data analysis unit is used for collecting and analyzing various data;
The data processing unit is connected with the data analysis unit through an electric signal and is used for controlling and executing the analyzed data.
The data analysis unit comprises an acquisition module, an analysis module and a processing module, wherein the acquisition module is used for collecting and processing historical data and instant data of electric power energy, the analysis module is used for acquiring the data processed by the acquisition module, analyzing and predicting future electric power demand data, calculating an energy optimal allocation strategy, and the processing module is used for acquiring the energy optimal allocation strategy obtained by the analysis module and generating an energy allocation adjustment schedule.
The data processing unit comprises a control module and an execution module, wherein the control module is used for displaying collected data, an energy optimal allocation strategy and an energy allocation adjustment schedule, the control module is connected with other modules through a network, the control module manages and adjusts the data to generate a final energy allocation adjustment schedule, the execution module is used for executing the final energy allocation adjustment schedule, and the execution module is connected with the power generation equipment and the energy storage equipment and controls the operation of the equipment.
Further, the acquisition module is used for collecting the historical data and the instant data of the electric power energy source and processing the data;
Specifically, the acquisition module collects power energy historical data and instant data including power energy generation cost and performance data, energy storage cost and performance data, and historical and instant power demand data, and processes the data including checking data integrity, data cleaning, format conversion, and data compression.
The power energy power generation cost data collected by the acquisition module comprise power generation cost and performance data of different energy types, wherein the power generation cost and the performance data comprise various energy types in new energy and traditional energy, the power generation cost and the performance data are determined according to specific conditions of power generation equipment, the energy storage cost and the performance data comprise energy storage equipment cost, energy storage performance parameters, energy storage capacity limit and the like, the power generation cost and the performance data are determined according to specific conditions of the energy storage equipment, and the historical and instant power demand data are obtained by collecting historical and instant power demand.
The analysis module is used for analyzing and predicting the future power demand data according to the data processed by the acquisition module and calculating an energy optimal allocation strategy according to the future power demand data;
specifically, after the analysis module acquires the data processed by the module, historical power demand data and instant power demand data are extracted, and future power demand data are predicted through analysis of the data:
Wherein Y t is the power demand data of the predicted time t, mu is a model constant, epsilon is an error term, and is set by a worker, And theta is the autoregressive term and the moving average term parameter respectively, and is obtained through collected historical data.
The power demand prediction provides key input for calculation of an optimal energy distribution strategy through historical power demand data and instant power demand data, so that energy distribution is more accurate and efficient, an analysis module can continuously optimize a prediction model along with the time and data update, the energy distribution strategy is continuously improved, data-driven support is provided for power grid operators and decision makers, and the power grid operators and decision makers can make more reasonable decisions based on actual and predicted data.
Further, the analysis module calculates the energy optimal allocation strategy from the current time to the t time after calculating the future power demand data:
Wherein minZ represents the minimum power generation cost, a i and b i are power generation cost coefficients of energy sources in the ith energy source, c is an energy storage cost coefficient, P i,t is the generated energy of the ith energy source at t time, 0 is less than or equal to P i,t≤Max Pi,t,Max Pi,t is the maximum generated energy of the ith energy source at t time, S t is the total stored energy at t time, S t≤Max St,Max St is the maximum stored energy at t time, various energy source t time optimal generated energy sources P i,t are solved, optimal operation quantity S t and minimum power generation cost minZ of the energy storage device are calculated, the optimal generated energy and the optimal operation quantity of various energy sources at the minimum power generation cost are determined through calculation, an integrated energy source optimal distribution strategy is formed by adjusting and combining each energy source generated energy and the operation quantity according to the calculation result, and power demand data Y t1 and predicted power demand data Y t are compared and verified through the energy source optimal distribution strategy:
∑iPi,t+St+St-1＝Yt
if Y t1＝Yt represents that the optimal power generation amount and the optimal operation amount of various energy sources in the energy source optimal allocation strategy are correct, the energy source optimal allocation strategy is correct, and the analysis module obtains the energy source optimal allocation strategy;
If Y t1≠Yt represents the calculation errors of the optimal power generation amount and the optimal operation amount of various energy sources in the energy source optimal distribution strategy, the analysis module solves the optimal power generation amount and the optimal operation amount of various energy sources through formulas again, and performs comparison verification with the predicted power demand data until Y t1＝Yt, and then the analysis module obtains the energy source optimal distribution strategy.
The optimal power generation amount and the energy storage amount of various energy t time are obtained under the minimum power generation cost, so that the proportion between the power generation amount and the energy storage amount of various energy sources is determined, an energy optimal distribution strategy is formed, the calculated optimal power generation amount and the calculated optimal operation amount of various energy sources are beneficial to utilizing various energy sources to the greatest extent, waste is reduced, renewable energy sources and traditional energy sources can be combined and used more efficiently due to the fact that the determination of the energy distribution ratio is used for determining renewable energy sources and traditional energy sources, and the new energy source is generally lower than the traditional energy sources.
The processing module is used for acquiring the energy optimal allocation strategy obtained by the analysis module and generating an energy allocation adjustment schedule;
Specifically, the analysis module calculates an energy optimal allocation strategy from the current time to the time t through a formula and then sends the energy optimal allocation strategy to the processing module, and the processing module sorts the energy optimal allocation strategy according to the energy optimal allocation strategy and the instant energy allocation ratio according to the time sequence to generate an energy allocation adjustment schedule.
The analysis module calculates the energy optimal allocation strategy from the current time to the t time through a formula, and the analysis module calculates according to time, so that the generated energy optimal allocation strategy is different at different times, the finally generated energy optimal allocation strategy is a plurality of coherent energy optimal allocation strategies, the analysis module sends the allocation strategies to the processing module, the processing module orders the allocation strategies according to time sequence and automatically generates an energy allocation adjustment schedule to send to the control module, the control module is convenient for a worker to check, the execution module can identify the strategies more easily to automatically execute, the energy allocation adjustment efficiency is improved, and the work efficiency is improved.
The control module is used for displaying the collected data, the optimal energy allocation strategy and the energy allocation adjustment schedule, and is connected with other modules through a network, and workers manage and adjust the data through the control module to generate a final energy allocation adjustment schedule;
Specifically, after the control module acquires the energy distribution adjustment schedule generated by the processing module, the control module combines the data collected by the acquisition module and the energy optimal distribution strategy calculated by the analysis module to be displayed to a worker for checking and management:
If the staff confirms that the generated energy distribution adjustment schedule does not need to be adjusted, the control module generates a final energy distribution adjustment schedule, the final energy distribution adjustment schedule is stored in a database and is sent to an execution module for automatic execution after being attached with an electronic signature of the staff, and the real-time monitoring is kept by the acquisition module and the analysis module in the execution process and is sent to the control module for being displayed to the staff for checking;
if the worker considers that the generated energy distribution adjustment schedule needs to be adjusted, the control module provides data in real time to assist the worker to adjust the content of the energy distribution adjustment schedule, after adjustment, the control module generates a modified energy distribution strategy and calculates modified energy generation cost through a formula, the modified energy generation cost is compared with the original planned energy generation cost, if the modified energy generation cost is equal to the original planned energy generation cost, the worker is prompted to currently modify the energy distribution strategy to be optimal, the worker confirms that the modified plan is sent to the execution module by the control platform to generate a final energy distribution adjustment schedule to be automatically executed, if the modified energy generation cost is greater than the original planned energy generation cost, the worker is prompted that the optimized content exists in the current modified energy distribution strategy, the worker continues to adjust the modified energy distribution strategy, if the worker directly confirms the scheme, the control platform generates the final energy distribution adjustment schedule from the modified content of the worker, and the electronic signature and the timestamp of the worker are stored in the database to be synchronously sent to the execution module to be automatically executed;
If the worker considers that the currently generated energy allocation adjustment schedule is unavailable, the control module directly sends a self-checking instruction to the acquisition module and the analysis module to detect whether the module is abnormal or not, if the module is not detected to be abnormal, data are collected again to analyze and generate a new energy optimal allocation strategy, the new energy optimal allocation strategy is sent to the processing module, the processing module directly sends the new energy optimal allocation strategy to the control module, the control module displays the received energy optimal allocation strategy to the worker to check and assist the worker to generate the energy allocation adjustment schedule, and the control module compares the energy generation cost calculated by the energy allocation adjustment schedule with the optimal scheme generation cost to assist the worker to adjust until the energy generation cost is optimal or the worker directly confirms to generate the final energy allocation adjustment schedule.
The control module combines the energy distribution adjustment schedule generated by the processing module and the data collected by the acquisition module, provides a comprehensive information view for the staff, enables the staff to comprehensively know the system state, including the instant power demand, the energy supply condition and the planned execution condition, provides a real-time data auxiliary and feedback mechanism when the staff thinks that the energy distribution adjustment schedule needs to be adjusted, supports the rapid adjustment of the plan, can calculate and display the adjusted energy power generation cost, enables the staff to evaluate the adjustment effect and cost benefit, continuously receives real-time data in the execution process, ensures the real-time monitoring and adjustment of the execution, and provides comprehensive data integration, real-time dynamic adjustment, decision support and the reliability and automatic execution monitoring of the system.
The control module is connected with other modules through a network and provides a centralized platform for workers to control the other modules or manage and adjust data, monitors the working states of the other modules in real time, and allows the workers to customize the display content and display format of the control module.
The execution module is used for executing the final energy distribution adjustment schedule, connecting the power generation equipment and the energy storage equipment and controlling the operation of the equipment;
Specifically, after receiving the final energy distribution adjustment schedule sent by the control module, the execution module regulates and controls the power generation equipment and the energy storage equipment in real time according to the content to achieve the energy distribution ratio in the adjustment schedule.
In summary, by collecting and analyzing the electric power energy data and generating an energy distribution adjustment schedule, the electric power energy distribution ratio is monitored and regulated in real time, so that the power grid can rapidly respond to the change of the demand and other emergency conditions, the energy distribution in the power grid is managed more efficiently, and the reliability and the stability of the power grid are improved
Example 2
For the second embodiment of the present invention, this embodiment is different from the previous embodiment in that:
Preferably, the functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium.
Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method of the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium may even be paper or other suitable medium upon which the program is printed, as the program may be electronically captured, via, for instance, optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner, if necessary, and then stored in a computer memory.
It is to be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
Example 3
For the third example of the present invention, which is different from the first two examples, the comparison results are shown in tables 1 and 2, as demonstrated by comparing the present invention with the prior art in order to verify the advantageous effects of the method of the present invention.
Table 1: the invention compares with the prior art to demonstrate the table
Table 2: comparative table of the invention with the prior art experiment
| Data accuracy rate | Efficiency of adjustment | User experience | |
| The invention is that | 97.4％ | Extremely high | 9.8 |
| Prior Art | 89.6％ | In (a) | 9.1 |
In summary, compared with the prior art, the scheme of the invention has remarkable improvements in the aspects of data processing, prediction method, decision support, system interaction, automatic execution and monitoring, system reliability, cost efficiency and the like, and shows the advancement and practicability in the field of intelligent power grid management.
It should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention may be modified or substituted without departing from the spirit and scope of the technical solution of the present invention, which is intended to be covered in the scope of the claims of the present invention.
Claims (10)
1. A new energy transmission and distribution collaborative digestion operation auxiliary decision-making system is characterized in that: comprising the steps of (a) a step of,
The data analysis unit is used for collecting and analyzing various data;
the data processing unit is connected with the data analysis unit through an electric signal and used for controlling and executing the analyzed data.
2. The new energy transmission and distribution collaborative digestion operation auxiliary decision-making system according to claim 1, which is characterized in that: the data analysis unit comprises an acquisition module, an analysis module and a processing module, wherein the acquisition module is used for collecting and processing historical data and instant data of electric power energy, the analysis module is used for acquiring the data processed by the acquisition module, analyzing and predicting future electric power demand data and calculating an energy optimal allocation strategy, and the processing module is used for acquiring the energy optimal allocation strategy obtained by the analysis module and generating an energy allocation adjustment schedule.
3. The new energy transmission and distribution collaborative digestion operation auxiliary decision-making system according to claim 1 or 2, which is characterized in that: the data processing unit comprises a control module and an execution module, wherein the control module is used for displaying collected data, an energy optimal allocation strategy and an energy allocation adjustment schedule, the control module is connected with other modules through a network, manages and adjusts the data to generate a final energy allocation adjustment schedule, the execution module is used for executing the final energy allocation adjustment schedule, and the execution module is connected with the power generation equipment and the energy storage equipment and controls the operation of the equipment.
4. The new energy transmission and distribution collaborative digestion operation auxiliary decision-making system according to claim 3, wherein: the acquisition module collects historical data and instant data of electric power energy, wherein the historical data and the instant data comprise power generation cost and performance data of the electric power energy, energy storage cost and performance data and historical and instant power demand data, and the processing of the data comprises data integrity checking, data cleaning, format conversion and data compression.
5. The new energy transmission and distribution collaborative digestion operation auxiliary decision-making system according to claim 4, which is characterized in that: after the analysis module acquires the data processed by the acquisition module, historical power demand data and instant power demand data are extracted, and future power demand data are predicted through analysis of the data:
Where Y t is the power demand data at the predicted time t, μ is a model constant, And θ is the autoregressive term and moving average term parameters, respectively, and ε is the error term.
6. The new energy transmission and distribution collaborative digestion operation auxiliary decision-making system according to claim 5, wherein the system comprises: the analysis module calculates energy optimal allocation strategy from current time to t time after calculating future power demand data:
Wherein minZ represents the minimum power generation cost, a i and b i are power generation cost coefficients of energy sources in the ith energy source, c is an energy storage cost coefficient, P i,t is the generated energy of the ith energy source at t time, 0 is less than or equal to P i,t≤Max Pi,t,Max Pi,t is the maximum generated energy of the ith energy source at t time, S t is the total stored energy at t time, S t≤Max St,Max St is the maximum stored energy at t time, various energy source t time optimal generated energy P i,t is solved, optimal operation amount S t and minimum power generation cost minZ of the energy storage device are obtained, the optimal generated energy and optimal operation amount of various energy sources under the minimum power generation cost are determined through calculation, an integrated energy source optimal distribution strategy is formed by adjusting and combining each energy source generated energy and operation amount according to the calculation result, and comparison verification is carried out on power demand data Y t1 and predicted power demand data Y t calculated by the energy source optimal distribution strategy:
∑iPi,t+St+St-1＝Yt1
if Y t1＝Yt represents that the optimal power generation amount and the optimal operation amount of various energy sources in the energy source optimal allocation strategy are correct, the energy source optimal allocation strategy is correct, and the analysis module obtains the energy source optimal allocation strategy;
If Y t1≠Yt represents the calculation errors of the optimal power generation amount and the optimal operation amount of various energy sources in the energy source optimal distribution strategy, the analysis module solves the optimal power generation amount and the optimal operation amount of various energy sources through formulas again, and performs comparison verification with the predicted power demand data until Y t1＝Yt, and then the analysis module obtains the energy source optimal distribution strategy.
7. The new energy transmission and distribution collaborative digestion operation auxiliary decision-making system according to claim 6, wherein the system comprises: the analysis module calculates an energy optimal allocation strategy from the current time to the time t through a formula and then sends the energy optimal allocation strategy to the processing module, and the processing module sorts the energy optimal allocation strategy according to the energy optimal allocation strategy and the instant energy allocation ratio according to the time sequence to generate an energy allocation adjustment schedule.
8. The new energy transmission and distribution collaborative digestion operation auxiliary decision-making system according to claim 7, wherein: the control module acquires the energy distribution adjustment schedule generated by the processing module, and then displays the data collected by the acquisition module and the energy optimal distribution strategy calculated by the analysis module to staff for checking and management, so that modification confirmation is facilitated.
9. The new energy transmission and distribution collaborative digestion operation auxiliary decision-making system according to claim 8, wherein: the control module is connected with other modules through a network and provides a centralized platform for workers to control the other modules or manage and adjust data, monitors the working states of the other modules in real time, and allows the workers to customize the display content and display format of the control module.
10. The new energy transmission and distribution collaborative digestion operation auxiliary decision-making system according to claim 9, wherein: and the execution module regulates and controls the power generation equipment and the energy storage equipment in real time according to the content after receiving the final energy distribution regulation schedule sent by the control module so as to achieve the energy distribution ratio in the regulation schedule.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311733018.8A CN118100301A (en) | 2023-12-15 | 2023-12-15 | New energy transmission and distribution collaborative digestion operation auxiliary decision-making system |
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