Automatic construction method of power grid daily consumption model considering distributed photovoltaic

Abstract

The application provides an automatic construction method of a power grid daily consumption model considering distributed photovoltaics, which comprises the following steps: establishing a mapping relationship of low-voltage distributed photovoltaics to a transformer substation bus, establishing a mapping relationship of low-voltage distributed photovoltaics and centralized photovoltaics, fitting low-voltage distributed photovoltaic output prediction data, processing power grid bus load prediction data, and constructing a power grid daily consumption analysis model, and compared with the prior art, the method solves the problem that it is difficult to control low-voltage distributed photovoltaics in the power grid consumption analysis work, makes the power grid operation arrangement work controllable from the whole for low-voltage distributed photovoltaics, and provides technical support for mastering the total amount of new energy operation attributes and new energy consumption analysis.

Description

Technical Field

[0001] This invention relates to the field of power grid operation safety analysis technology, specifically a method for automatically constructing a day-ahead grid absorption model that takes into account distributed photovoltaic power. Background Technology

[0002] With the large-scale grid connection of new energy sources, the power grid has developed into a "three-dimensional, multi-source" grid with high, medium, and low voltages. The high proportion of new energy sources has brought about problems in the operation and management of my country's power grid. In order to accurately grasp the attributes of new energy sources under the new power system, the original equivalent modeling and analysis methods for power grids below 220 kV are no longer suitable for the new situation where power sources are gradually being deployed to power grids of 110 kV and below on a large scale. It is necessary to conduct simulation modeling of the distribution network and simultaneously consider the modeling of distributed photovoltaic power.

[0003] The problem of grid absorption analysis is particularly prominent in 220 kV and above power grids, with numerous 220 kV main transformers backfeeding, leading to frequent heavy overloads on critical transmission sections. The main reason for this is the grid connection of low-voltage distributed photovoltaic (PV) power, necessitating a grid-wide perspective for renewable energy absorption analysis. However, grid simulation analysis cannot provide detailed models of large-scale distributed PV, and detailed modeling would compromise accuracy. Currently, grid operation analysis primarily focuses on absorption analysis for tomorrow's (day-ahead) work; therefore, constructing an effective grid absorption analysis model is an urgent problem to be solved.

[0004] Content of this invention

[0005] The purpose of this invention is to address the problem that the day-ahead grid absorption analysis model cannot take into account low-voltage distributed photovoltaic power generation, and to provide an automatic construction method for a day-ahead grid absorption model that takes into account distributed photovoltaic power generation to solve the above problem.

[0006] To solve the above problems, the technical solution adopted by the present invention is as follows:

[0007] Automatic construction methods for grid day-ahead absorption models considering distributed photovoltaic power include:

[0008] Step 1: Establish the mapping relationship between low-voltage distributed photovoltaic power and the substation busbar;

[0009] Step 2: Establish the mapping relationship between low-voltage distributed photovoltaic and centralized photovoltaic systems;

[0010] Step 3: Fit the predicted output data of low-voltage distributed photovoltaic power generation;

[0011] Step 4: Processing of power grid bus load forecast data;

[0012] Step 5: Construct a day-ahead power grid absorption analysis model.

[0013] Furthermore, in step one, the specific operation of establishing the mapping relationship between the low-voltage distributed photovoltaic system and the substation busbar is as follows:

[0014] Data on 380 / 220V grid-connected low-voltage distributed photovoltaic, substations, lines, distribution areas, and user ledgers are obtained from the power marketing business system, and a data model of "low-voltage distributed photovoltaic - distribution area - distribution network line - substation" is formed through the relationship between them.

[0015] The primary equipment model of the substation is obtained from the dispatch automation system, including distribution network outgoing lines, switches and busbar equipment. Based on the equipment topology connection relationship, a data model of "substation-in-station 10 / 20kV busbar-in-station distribution network line" is formed. The substation and distribution network line shared by the two are used as mapping relationships to form the relationship between low-voltage distributed photovoltaic and the 10 / 20kV busbar in the substation, which serves as the mapping relationship from low-voltage distributed photovoltaic to the busbar in the substation.

[0016] Furthermore, in step two, the specific operation of establishing the mapping relationship between low-voltage distributed photovoltaic and centralized photovoltaic is as follows:

[0017] Based on the principle of geographical proximity, a mapping relationship is established between low-voltage distributed photovoltaic (PV) systems located near centralized PV systems. According to the "transformer area - low-voltage distributed PV" relationship, the geographical location of the transformer is taken as the geographical location of the low-voltage distributed PV systems. A circle is drawn with the geographical location of the centralized PV system collected manually as the center, and the radius is customized according to actual needs. Through the point and surface intersection algorithm of geographic space, all low-voltage distributed PV systems fall within the circle of the centralized PV system. This establishes a mapping relationship between low-voltage distributed PV and centralized PV systems. Based on the ratio of their installed capacities, the equivalent output coefficient g of low-voltage distributed PV is formed: distributed PV capacity ÷ centralized PV capacity.

[0018] Furthermore, in step three, the specific operation of fitting the low-voltage distributed photovoltaic power output prediction data is as follows:

[0019] The system obtains irradiance, power output prediction, and day-ahead prediction data (15-minute cycle) of centralized photovoltaic power from the scheduling photovoltaic power prediction system. The equivalent power output coefficient is formed by the mapping relationship in step two and automatically fitted to calculate the low-voltage distributed photovoltaic power output prediction p = g × centralized photovoltaic power output prediction.

[0020] Furthermore, in step four, the processing of the power grid bus load forecast data is specifically carried out as follows:

[0021] By setting the grid absorption model to the 10 / 20kV bus side rules, all buses that need to participate in load forecasting are identified. First, the equivalent load data connected to the bus is obtained from the dispatch automation system. Taking the load forecast time point as the dividing point, the data from 0:00 to the current time point tomorrow is directly reused from 0:00 to the current time point today. The data from the current time point tomorrow to 23:45 is directly reused from the current time point yesterday to 23:45. This forms the bus load forecast data f for the previous 96 points. Second, based on the mapping relationship from low-voltage distributed photovoltaic to the substation bus in step one, combined with the low-voltage distributed photovoltaic output forecast data in step three, the actual user load connected to the bus is directly calculated as y = p + f.

[0022] By combining meteorological temperature and system load forecast data, the final predicted data y of actual user load connected to the bus is determined through manual correction.

[0023] Furthermore, in step five, the specific steps for constructing the day-ahead power grid absorption analysis model are as follows:

[0024] Based on the primary equipment status and topology model in the power control cloud platform, a power flow calculation model PSD-BPA for 10 / 20kV and above power grids is automatically generated. On this model, real user load data y connected to the bus, predicted output p of low-voltage distributed photovoltaic power, and manually compiled day-ahead power generation plans of centrally dispatched units are superimposed to form a day-ahead power grid absorption model covering distributed photovoltaic power.

[0025] The beneficial effects of the present invention are as follows: The automatic construction method for the grid day-ahead absorption model of distributed photovoltaic power provided by the present invention solves the problem of difficulty in controlling low-voltage distributed photovoltaic power in grid absorption analysis compared with the prior art, and enables the grid operation arrangement to be globally controllable over low-voltage distributed photovoltaic power, providing technical support for mastering the operation attributes of all new energy sources and analyzing new energy absorption. Attached Figure Description

[0026] Figure 1 This is a flowchart illustrating the automatic construction method for the grid day-ahead absorption model of distributed photovoltaic power, as described in this invention. Detailed Implementation

[0027] The present invention will now be described in conjunction with specific embodiments, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar components or components having the same or similar functions throughout.

[0028] The directional terms used in this invention, such as up, down, left, right, front, back, inside, outside, front, back, side, etc., are merely for reference to the accompanying drawings. The embodiments and directional terms used in the following description with reference to the accompanying drawings are exemplary and are only used to explain this invention, and should not be construed as limiting this invention. Furthermore, the various specific processes and materials provided in this invention are examples that those skilled in the art will recognize for the application of other processes and / or the use of other materials.

[0029] Please see Figure 1 , Figure 1 This is a flowchart illustrating the automatic construction method for the grid day-ahead absorption model of distributed photovoltaic power, as described in this invention.

[0030] Automatic construction methods for grid day-ahead absorption models considering distributed photovoltaic power include:

[0031] Step 1: Establish the mapping relationship between low-voltage distributed photovoltaic power and the substation busbar;

[0032] The specific steps are as follows:

[0033] Data on 380 / 220V grid-connected low-voltage distributed photovoltaic, substations, lines, distribution areas, and user ledgers are obtained from the power marketing business system, and a data model of "low-voltage distributed photovoltaic - distribution area - distribution network line - substation" is formed through the relationship between them.

[0034] The primary equipment model of the substation is obtained from the dispatch automation system, including distribution network outgoing lines, switches and busbar equipment. Based on the equipment topology connection relationship, a data model of "substation-in-station 10 / 20kV busbar-in-station distribution network line" is formed. The substation and distribution network line shared by the two are used as mapping relationships to form the relationship between low-voltage distributed photovoltaic and the 10 / 20kV busbar in the substation, which serves as the mapping relationship from low-voltage distributed photovoltaic to the busbar in the substation.

[0035] Step 2: Establish the mapping relationship between low-voltage distributed photovoltaic and centralized photovoltaic systems;

[0036] The specific steps are as follows:

[0037] Based on the principle of geographical proximity, a mapping relationship is established between low-voltage distributed photovoltaic (PV) systems located near centralized PV systems. According to the "transformer area - low-voltage distributed PV" relationship, the geographical location of the transformer is taken as the geographical location of the low-voltage distributed PV systems. A circle is drawn with the geographical location of the centralized PV system collected manually as the center, and the radius is customized according to actual needs. Through the point and surface intersection algorithm of geographic space, all low-voltage distributed PV systems fall within the circle of the centralized PV system. This establishes a mapping relationship between low-voltage distributed PV and centralized PV systems. Based on the ratio of their installed capacities, the equivalent output coefficient g of low-voltage distributed PV is formed: distributed PV capacity ÷ centralized PV capacity.

[0038] Step 3: Fit the predicted output data of low-voltage distributed photovoltaic power generation;

[0039] The specific steps are as follows:

[0040] The system obtains irradiance, power output prediction, and day-ahead prediction data (15-minute cycle) of centralized photovoltaic power from the scheduling photovoltaic power prediction system. The equivalent power output coefficient is formed by the mapping relationship in step two and automatically fitted to calculate the low-voltage distributed photovoltaic power output prediction p = g × centralized photovoltaic power output prediction.

[0041] Step 4: Processing of power grid bus load forecast data;

[0042] The specific steps are as follows:

[0043] By setting the grid absorption model to the 10 / 20kV bus side rules, all buses that need to participate in load forecasting are identified. First, the equivalent load data connected to the bus is obtained from the dispatch automation system. Taking the load forecast time point as the dividing point, the data from 0:00 to the current time point tomorrow is directly reused from 0:00 to the current time point today. The data from the current time point tomorrow to 23:45 is directly reused from the current time point yesterday to 23:45. This forms the bus load forecast data f for the previous 96 points. Second, based on the mapping relationship from low-voltage distributed photovoltaic to the substation bus in step one, combined with the low-voltage distributed photovoltaic output forecast data in step three, the actual user load connected to the bus is directly calculated as y = p + f.

[0044] By combining meteorological temperature and system load forecast data, the final predicted data y of actual user load connected to the bus is determined through manual correction.

[0045] Step 5: Construct a day-ahead power grid absorption analysis model.

[0046] The specific steps are as follows:

[0047] Based on the primary equipment status and topology model in the power control cloud platform, a power flow calculation model PSD-BPA for 10 / 20kV and above power grids is automatically generated. On this model, real user load data y connected to the bus, predicted output p of low-voltage distributed photovoltaic power, and manually compiled day-ahead power generation plans of centrally dispatched units are superimposed to form a day-ahead power grid absorption model covering distributed photovoltaic power.

[0048] The beneficial effects of the present invention are as follows: The automatic construction method for the grid day-ahead absorption model of distributed photovoltaic power provided by the present invention solves the problem of difficulty in controlling low-voltage distributed photovoltaic power in grid absorption analysis compared with the prior art, and enables the grid operation arrangement to be globally controllable over low-voltage distributed photovoltaic power, providing technical support for mastering the operation attributes of all new energy sources and analyzing new energy absorption.

[0049] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An automatic construction method for a grid day-ahead absorption model considering distributed photovoltaic power, characterized in that, include: Step 1: Establish the mapping relationship between low-voltage distributed photovoltaic power and the substation busbar. The specific operation is as follows: Data on 380 / 220V grid-connected low-voltage distributed photovoltaic, substations, lines, distribution areas, and user ledgers are obtained from the power marketing business system, and a data model of "low-voltage distributed photovoltaic - distribution area - distribution network line - substation" is formed through the relationship between them. The primary equipment model of the substation is obtained from the dispatch automation system, including distribution network outgoing lines, switches and busbar equipment. Based on the equipment topology connection relationship, a data model of "substation-in-station 10 / 20kV busbar-in-station distribution network line" is formed. The substation and distribution network line shared by the two are used as mapping relationship to form the relationship between low-voltage distributed photovoltaic and the 10 / 20kV busbar in the substation, which serves as the mapping relationship from low-voltage distributed photovoltaic to the busbar in the substation. Step 2: Establish the mapping relationship between low-voltage distributed photovoltaic and centralized photovoltaic systems; Step 3: Fit the predicted output data of low-voltage distributed photovoltaic power generation; Step 4: Processing of power grid bus load forecast data; Step 5: Construct a day-ahead power grid absorption analysis model.

2. The method for automatically constructing a day-ahead grid absorption model considering distributed photovoltaic power according to claim 1, characterized in that, In step two, establishing the mapping relationship between low-voltage distributed photovoltaic and centralized photovoltaic systems is specifically carried out as follows: Based on the principle of geographical proximity, a mapping relationship is established between low-voltage distributed photovoltaic (PV) systems located near centralized PV systems. According to the "transformer area - low-voltage distributed PV" relationship, the geographical location of the transformer is taken as the geographical location of the low-voltage distributed PV systems. A circle is drawn with the geographical location of the centralized PV system collected manually as the center, and the radius is customized according to actual needs. Through the point and surface intersection algorithm of geographic space, all low-voltage distributed PV systems fall within the circle of the centralized PV system. This establishes a mapping relationship between low-voltage distributed PV and centralized PV systems. Based on the ratio of their installed capacities, the equivalent output coefficient g of low-voltage distributed PV is formed: distributed PV capacity ÷ centralized PV capacity.

3. The method for automatically constructing a day-ahead grid absorption model considering distributed photovoltaic power according to claim 2, characterized in that, In step three, the specific operation of fitting the low-voltage distributed photovoltaic power output prediction data is as follows: The system obtains irradiance, power output prediction, and day-ahead prediction data for centralized photovoltaic power from the scheduling photovoltaic power prediction system. The equivalent power output coefficient is formed by the mapping relationship in step two. The low-voltage distributed photovoltaic power output prediction p = g × centralized photovoltaic power output prediction is automatically fitted and calculated.

4. The method for automatically constructing a grid day-ahead absorption model considering distributed photovoltaic power according to claim 3, characterized in that, In step four, the processing of the power grid bus load forecast data is carried out as follows: By setting the grid absorption model to the 10 / 20kV bus side rules, all buses that need to participate in load forecasting are identified. First, the equivalent load data connected to the bus is obtained from the dispatch automation system. Taking the load forecast time point as the dividing point, the data from 0:00 tomorrow to the time point directly reuses the data from 0:00 today to the time point, and the data from the time point tomorrow to 23:45 directly reuses the data from the time point yesterday to 23:

45. This forms the bus load forecast data f for the previous 96 points. Second, based on the mapping relationship from low-voltage distributed photovoltaic to the substation bus in step one, combined with the low-voltage distributed photovoltaic output forecast data in step three, the actual user load connected to the bus is directly calculated as y=p+f. By combining meteorological temperature and system load forecast data, the final predicted data y of actual user load connected to the bus is determined through manual correction.

5. The method for automatically constructing a grid day-ahead absorption model considering distributed photovoltaic power according to claim 4, characterized in that, In step five, the specific operation of constructing the day-ahead power grid absorption analysis model is as follows: Based on the primary equipment status and topology model in the power dispatching cloud platform, a power flow calculation model PSD-BPA for 10 / 20kV and above power grids is automatically generated. On this model, real user load data y connected to the bus, predicted output p of low-voltage distributed photovoltaic power, and manually compiled day-ahead power generation plans of centrally dispatched units are superimposed to form a day-ahead power grid absorption model that covers distributed photovoltaic power.

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