Intelligent power grid online planning system and planning method

Abstract

The invention relates to the technical field of smart power grids, in particular to a smart power grid online planning system and method, and the system comprises a data receiving module, a data processing module, a rule pre-judgment module, a planning module and an output module. The data processing module comprises a data cleaning module, a data conversion module, a data mining module and a high power consumption type data classification module, and the data receiving module is used for receiving power grid data including power grid equipment information and power consumption data in various fields. Power grid data are processed through the data cleaning module, the data conversion module, the data mining module and the high-power-consumption type data classification module, online planning of the intelligent power grid is achieved, the planning efficiency is improved, the labor cost is reduced, in addition, the system has the advantages of being high in prediction precision and high in self-adaptive capacity, and the method is suitable for popularization and application. And intelligent power grid planning requirements in different scenes can be met.

Description

Technical Field

[0001] The present invention relates to the technical field of smart grids, and in particular to a smart grid online planning system and a planning method. Background Art

[0002] As we all know, with the transformation of energy structure and the opening of power market, smart grid has become an inevitable trend of future power grid development. Smart grid planning is of great significance to improving the operating efficiency and stability of power system. However, traditional power grid planning methods have problems such as low planning efficiency and high labor cost, which cannot meet the needs of rapid development of modern power grid. Therefore, it is necessary to propose solutions to this technical problem. Summary of the invention

[0003] 1. Technical issues to be solved

[0004] In view of the deficiencies in the prior art, the present invention provides a smart grid online planning system and a planning method.

[0005] (II) Technical solution

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a smart grid online planning system, comprising a data receiving module, a data processing module, a rule prediction module, a planning module and an output module, the data processing module comprising a data cleaning module, a data conversion module, a data mining module and a high power consumption type data classification module, the data receiving module is used to receive power grid data, including power grid equipment information and electricity consumption data in various fields, the data processing module processes the received power grid data, and processes the power grid data through the data cleaning module, the data conversion module, the data mining module and the high power consumption type data classification module, the rule prediction module performs rule prediction based on the processed power grid data and performs power demand forecasting, the planning module performs smart grid planning based on the rule prediction results, performs power supply planning, power grid topology optimization and scheduling plan formulation, the output module outputs the planning results, and performs a planning scheme report and a visual interface.

[0007] The present invention also provides a smart grid online planning method, comprising the following steps:

[0008] Step 1: Receive power grid equipment data through the data receiving module;

[0009] Step 2: Process the received power grid data, including data cleaning, data conversion and data mining;

[0010] Step 3: The data receiving module is connected to the power consumption network platform and the power consumption data is calculated;

[0011] Step 4: The high power consumption type data classification module classifies and counts the high power consumption areas:

[0012] To collect statistics on the cumulative efficiency of electric vehicles in the electric vehicle field and predict the amount of electricity required for charging electric vehicles in the future;

[0013] Collect statistics on summer and winter electricity consumption in previous years and predict future summer and winter electricity consumption;

[0014] Statistics are collected on the inflow and outflow of population in each city, and historical electricity consumption per capita in each city is calculated based on historical electricity consumption data;

[0015] Count the changes in large factories and calculate the expected power consumption of the factories;

[0016] Step 5: Carry out smart grid planning based on the rule prediction results, including power supply planning, optimization, and scheduling plan formulation;

[0017] Step 6: Output the planning results, including the planning scheme report and visualization interface.

[0018] Furthermore, the present invention is improved in that the planning result in the above step 6 is sent to each power grid equipment terminal through the power consumption network platform.

[0019] Furthermore, the present invention is improved in that the planning in the above step 5 is classified into low-voltage power grid planning and high-voltage power grid planning.

[0020] Furthermore, the present invention is improved in that the planning in the above step 5 also includes power grid topology, and the power grid topology includes radial, ring or mesh.

[0021] Furthermore, the present invention is improved in that the planning method in the above step 5 also includes a heuristic algorithm.

[0022] (III) Beneficial effects

[0023] Compared with the prior art, the present invention provides a smart grid online planning system and planning method, which have the following beneficial effects:

[0024] The smart grid online planning system and planning method realize the online planning of the smart grid, improve the planning efficiency and reduce the labor cost. In addition, the present invention has the advantages of high prediction accuracy and strong adaptability, and can adapt to the smart grid planning needs in different scenarios. The high power consumption type data classification module is used to classify and count the high power consumption areas, which can greatly optimize and predict the trend of the future large-scale electricity consumption proportion, so as to better plan the prediction and planning for the high power consumption areas in the future. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a schematic diagram of the system of the present invention;

[0026] Figure 2 This is a schematic diagram of the operation flow of the data processing module of the system of the present invention;

[0027] Figure 3 It is a schematic diagram of the operation of the system planning module of the present invention. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] See also Figure 1-3 The present invention is an online planning system for a smart grid, comprising a data receiving module, a data processing module, a rule prediction module, a planning module and an output module, wherein the data processing module comprises a data cleaning module, a data conversion module, a data mining module and a high power consumption type data classification module, the data receiving module is used to receive power grid data, including power grid equipment information and power consumption data in various fields, the data processing module processes the received power grid data, and processes the power grid data through the data cleaning module, the data conversion module, the data mining module and the high power consumption type data classification module, the rule prediction module performs rule prediction based on the processed power grid data and performs power demand forecasting, the planning module performs smart grid planning based on the rule prediction results, performs power supply planning, power grid topology optimization and scheduling plan formulation, the output module outputs the planning results, and performs planning scheme reports and visual interfaces.

[0030] The present invention also provides a smart grid online planning method, comprising the following steps:

[0031] Step 1: Receive power grid equipment data through the data receiving module;

[0032] Step 2: Process the received power grid data, including data cleaning, data conversion and data mining;

[0033] Step 3: The data receiving module is connected to the power consumption network platform and the power consumption data is calculated;

[0034] Step 4: The high power consumption type data classification module classifies and counts the high power consumption areas:

[0035] To collect statistics on the cumulative efficiency of electric vehicles in the electric vehicle field and predict the amount of electricity required for charging electric vehicles in the future;

[0036] Collect statistics on summer and winter electricity consumption in previous years and predict future summer and winter electricity consumption;

[0037] Statistics are collected on the inflow and outflow of population in each city, and historical electricity consumption per capita in each city is calculated based on historical electricity consumption data;

[0038] Count the changes in large factories and calculate the expected power consumption of the factories;

[0039] Step 5: Carry out smart grid planning based on the rule prediction results, including power supply planning, optimization, and scheduling plan formulation;

[0040] Step 6: Output the planning results, including the planning scheme report and visualization interface.

[0041] In this solution, the planning results in the above step 6 are sent to each power grid equipment terminal through the power network platform. The power network platform can ensure that the planning results are accurately sent to each equipment terminal, avoiding errors or omissions that may occur in traditional transmission methods.

[0042] In this solution, the planning in the above step 5 is classified into low-voltage power grid planning and high-voltage power grid planning. The voltage levels of low-voltage power grid and high-voltage power grid are different, and the requirements for equipment are also different. Separate management is more convenient for operation, which can better play the role of equipment and better classify and plan the power grid system.

[0043] In this scheme, the planning in the above step 5 also includes power grid topology, and the power grid topology includes radial, ring or mesh. The advantages of the radial power grid are simplicity, clarity and easy operation, but when the load is heavy, the line utilization rate is low. The advantages of the ring power grid are line redundancy and high reliability, but the investment cost is high and the operation is more complicated. The advantages of the mesh power grid are line redundancy and high reliability, but the investment cost is high and the operation is complicated, which can facilitate personnel to use the corresponding power grid topology according to their needs.

[0044] In this scheme, the planning method in the above step 5 also includes a heuristic algorithm, and the power grid system is planned by a heuristic algorithm. The heuristic algorithm includes two strategies: a branch switching strategy and a sequential switch opening strategy. The branch switching strategy reconfigures the initial radial network by exchanging the switch states of the switch pairs, and introduces a sequential switch opening strategy of the initial grid network, in which the switches in the loop are strategically opened until the optimal radial configuration is obtained.

[0045] The data receiving module receives the data of the power grid equipment, processes the received power grid data, including data cleaning, data conversion and data mining, links the data receiving module to the power consumption network platform and performs power consumption data exchange. The high power consumption type data classification module classifies and counts the high power consumption areas: the cumulative efficiency of electric vehicles in the electric vehicle field is counted and the power required for charging electric vehicles in the future is predicted; the power consumption in summer and winter in previous years is counted and the power consumption in summer and winter in the future is predicted; the inflow and outflow of population in each city is counted, and the per capita power consumption of each city is counted based on historical power consumption data; the changes of large factories are counted and the expected power consumption of the factories is calculated. According to the predicted results of the rules, smart grid planning is carried out, including power supply planning, optimization, and scheduling plan formulation. The planning is classified into low-voltage power grid planning and high-voltage power grid planning. The voltage levels of low-voltage power grids and high-voltage power grids are different, and the requirements for equipment are also different. Separate management is more convenient for operation, which can better play the role of equipment and better classify and plan the power grid system. The planning also includes power grid topology, which includes radial, ring, and The advantages of radial power grid are simplicity, clarity and convenience of operation, but when the load is heavy, the utilization rate of the line is low. The advantages of ring power grid are line redundancy and high reliability, but the investment cost is high and the operation is complicated. The advantages of mesh power grid are line redundancy and high reliability, but the investment cost is high and the operation is complicated. The power grid system is planned by heuristic algorithm. The heuristic algorithm is branch exchange strategy and sequential switch opening strategy. The branch exchange strategy reconfigures the initial radial network by exchanging the switch state of the switch pair, and introduces the sequential switch opening strategy of the initial grid network, in which the switches in the loop are strategically opened until the optimal radial configuration is obtained. The planning results are output, including planning scheme report and visualization interface. The planning results are sent to each power grid equipment terminal through the power network platform to ensure that all equipment can receive the latest planning instructions in time. The power network platform can ensure that the planning results are accurately sent to each equipment terminal, avoiding errors or omissions that may occur in traditional transmission methods. The power network platform has high flexibility and can send planning results in a customized manner according to different needs and scenarios to meet the needs of different situations.

[0046] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A smart grid online planning system, characterized in that: It includes a data receiving module, a data processing module, a rule prediction module, a planning module and an output module. The data processing module includes a data cleaning module, a data conversion module, a data mining module and a high power consumption type data classification module. The data receiving module is used to receive power grid data, including power grid equipment information and electricity consumption data in various fields. The data processing module processes the received power grid data and processes the power grid data through the data cleaning module, the data conversion module, the data mining module and the high power consumption type data classification module. The rule prediction module performs rule prediction based on the processed power grid data and predicts power demand. The planning module performs smart grid planning based on the rule prediction results, performs power supply planning, power grid topology optimization and scheduling plan formulation. The output module outputs the planning results and makes a planning scheme report and a visual interface.

2. A smart grid online planning method, characterized in that: The following steps are involved: Step 1: Receive power grid equipment data through the data receiving module; Step 2: Process the received power grid data, including data cleaning, data conversion and data mining; Step 3: The data receiving module is connected to the power consumption network platform and the power consumption data is calculated; Step 4: The high power consumption type data classification module classifies and counts the high power consumption areas: To collect statistics on the cumulative efficiency of electric vehicles in the electric vehicle field and predict the amount of electricity required for charging electric vehicles in the future; Collect statistics on summer and winter electricity consumption in previous years and predict future summer and winter electricity consumption; Statistics are collected on the inflow and outflow of population in each city, and historical electricity consumption per capita in each city is calculated based on historical electricity consumption data; Count the changes in large factories and calculate the expected power consumption of the factories; Step 5: Carry out smart grid planning based on the rule prediction results, including power supply planning, optimization, and scheduling plan formulation; Step 6: Output the planning results, including the planning scheme report and visualization interface.

3. A smart grid online planning system and planning method according to claim 2, characterized in that: The planning results in step 6 above are sent to each power grid equipment terminal through the power consumption network platform.

4. A smart grid online planning system and planning method according to claim 3, characterized in that: The planning in the above step 5 is classified into low voltage grid planning and high voltage grid planning.

5. A smart grid online planning system and planning method according to claim 4, characterized in that: The planning in the above step 5 also includes the grid topology, and the grid topology includes radial, ring or mesh.

6. A smart grid online planning system and planning method according to claim 5, characterized in that: The planning method in the above step 5 also includes a heuristic algorithm.

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