CN-121997034-A - Method for analyzing voltage influence of distributed photovoltaic on power distribution network

CN121997034ACN 121997034 ACN121997034 ACN 121997034ACN-121997034-A

Abstract

The invention relates to the technical field of power system analysis and discloses a method for analyzing the voltage influence of distributed photovoltaic on a power distribution network. The method comprises the steps of collecting geographical position coordinates and real-time output data of distributed photovoltaic access points, calculating node load curve data and network impedance parameters of a power distribution network, generating a photovoltaic load coupling characteristic data set by calculating dynamic coupling coefficients, then, based on the data set, extracting data, grouping according to a topological hierarchy structure, marking evaluation sections to form a hierarchical evaluation frame set, then, selecting data for each evaluation section, analyzing the influence of photovoltaic output fluctuation on node voltage by combining a time sequence production simulation method, evaluating a voltage stable state, identifying voltage out-of-limit risk points to form a set, and finally, analyzing node relations to generate power distribution network voltage safety early warning information and storing the power distribution network voltage safety early warning information. The method can comprehensively analyze influence, accurately identify risks, generate effective early warning and ensure safe and stable operation of the power distribution network.

Inventors

ZHANG XIANGYU
SONG ZHIBIN
WANG ZHENG
XU ZHENBO
XUE LEI
SHEN ZEYUAN
HU ZESHENG
QIU JUE

Assignees

国网山西省电力有限公司经济技术研究院

Dates

Publication Date: 20260508
Application Date: 20260409

Claims (10)

1. A method for analyzing voltage influence of distributed photovoltaic on a power distribution network, the method comprising: Collecting geographic position coordinates and real-time output data of distributed photovoltaic access points, synchronously obtaining load curve data and network impedance parameters of power distribution network nodes, associating the photovoltaic access points, calculating dynamic coupling coefficients between photovoltaic output and load demands, and generating a photovoltaic load coupling characteristic data set; Based on the photovoltaic load coupling characteristic data set, extracting dynamic coupling coefficients and node voltage measured values, performing grouping processing according to a topological hierarchy structure of the power distribution network, and marking a transformer area hierarchy evaluation section and a medium-voltage circuit hierarchy evaluation section to form a hierarchical evaluation framework set; selecting a historical operation data sequence and limit working condition scene data aiming at each evaluation section in the hierarchical evaluation framework set, analyzing the influence degree of photovoltaic output fluctuation on node voltage by combining a time sequence production simulation method, calculating a voltage deviation amplitude, evaluating a voltage stable state, and generating a hierarchical voltage influence analysis result; Identifying nodes of which the voltage out-of-limit risk value exceeds a preset risk threshold value and is positioned in a key hierarchy section from the hierarchy voltage influence analysis result, and collecting the nodes to form a voltage out-of-limit risk point set; Based on the voltage out-of-limit risk point set, analyzing an electrical distance relation and a voltage influence propagation path between nodes, marking nodes with higher diffusion risks, and generating power distribution network voltage safety early warning information; and storing the power distribution network voltage safety precaution information for later calling.
2. The method of claim 1, wherein the correlating photovoltaic access points and calculating a dynamic coupling coefficient between photovoltaic output and load demand comprises: Collecting photovoltaic output time series data and load demand time series data, and obtaining an initial coupling coefficient by calculating the change trend matching degree of the two sequences in the same time period; Introducing real-time meteorological data comprising cloud coverage and ambient temperature to dynamically correct an initial coupling coefficient, and simultaneously carrying out weighted adjustment by combining a load type composition proportion to obtain a dynamic coupling coefficient value, wherein the load type comprises a resident load, a commercial load and an industrial load.
3. The method of claim 2, wherein forming the hierarchical set of evaluation frameworks comprises: dividing nodes into a transformer area level and a line level according to the topological structure of the power distribution network, wherein the transformer area level corresponds to a low-voltage distribution transformer power supply area, and the line level corresponds to a medium-voltage distribution line section; defining evaluation parameters for each level, and generating a level evaluation parameter table, wherein the evaluation parameters comprise short circuit capacity and impedance ratio; And labeling each evaluation section based on the hierarchy evaluation parameter table, and distinguishing a normal evaluation section and an important evaluation section.
4. The method for analyzing the influence of the distributed photovoltaic on the voltage of the power distribution network according to claim 3, wherein the method for analyzing the influence degree of the photovoltaic output fluctuation on the node voltage by combining the time sequence production simulation method comprises the following steps: calling a photovoltaic output and load change sequence in historical operation data, and simulating a typical daily operation scene; extracting a photovoltaic output extremum and a load extremum under a limit working condition by adopting an extremum theory, and calculating the fluctuation range of the node voltage under the conditions of the photovoltaic output extremum and the load extremum; and evaluating the voltage deviation risk caused by the photovoltaic fluctuation by comparing the voltage fluctuation range with the safety limit value.
5. The method for analyzing voltage influence of distributed photovoltaic on a power distribution network according to claim 4, wherein calculating the voltage deviation amplitude comprises: selecting node voltage data in the evaluation section, and calculating the deviation absolute value of the actual measurement value and the rated value; Counting the distribution condition of absolute values of the deviation on a time sequence, and determining the duration time and the occurrence frequency of the voltage deviation; combining the absolute value, duration and occurrence frequency of the deviation, and synthesizing a voltage deviation amplitude index.
6. The method of claim 5, wherein identifying nodes from the hierarchical voltage impact analysis result that have voltage out-of-limit risk values exceeding a preset risk threshold and are located in critical hierarchical sections comprises: Acquiring voltage out-of-limit probability data in a hierarchical voltage influence analysis result; comparing the voltage threshold crossing probability with a preset risk threshold value, and screening out nodes exceeding the threshold value; And checking whether the nodes exceeding the threshold value are positioned in a key hierarchy section, and confirming to include the voltage out-of-limit risk point set, wherein the key hierarchy section comprises important nodes of a platform hierarchy or hub nodes of a line hierarchy.
7. The method of claim 6, wherein analyzing the electrical distance relationship and the voltage-affected propagation path between nodes comprises: calculating an electrical distance value between nodes based on the impedance parameters of the power distribution network; constructing an electrical distance matrix to reflect the electrical coupling strength between the nodes; in combination with the voltage-affected propagation paths, node pairs with short electrical distances are identified as potential-affected propagation paths.
8. The method of claim 7, wherein the marking nodes with higher risk of diffusion comprises: extracting a set of voltage out-of-limit risk points from an electrical distance matrix adjacent nodes with the electrical distance of the middle node smaller than a set threshold value; evaluating the voltage sensitivity value of the adjacent nodes, and screening nodes with high sensitivity; the selected nodes are marked as points with higher diffusion risk.
9. The method for analyzing voltage influence of distributed photovoltaic on a power distribution network according to claim 8, wherein generating power distribution network voltage safety precaution information comprises: integrating the voltage out-of-limit risk point set and the marked diffusion risk point position information; Generating a detailed description for each risk point location, including a location identification, a risk level and an influence range; Formatting a voltage out-of-limit risk point set, marked diffusion risk point position information and a detailed description structured early warning report of each risk point position.
10. The method of claim 9, wherein storing the power distribution network voltage safety precaution information for subsequent recall comprises: storing the early warning information into a database system, and establishing an index to facilitate inquiry; setting an information updating mechanism, and automatically refreshing early warning contents when new data is input; The interface power supply and distribution management system is provided for accessing early warning information in real time.

Description

Method for analyzing voltage influence of distributed photovoltaic on power distribution network Technical Field The invention relates to the technical field of power system analysis, in particular to a method for analyzing the voltage influence of distributed photovoltaic on a power distribution network. Background With the rapid development of global economy, the energy demand continues to rise, and traditional non-renewable energy sources such as coal, petroleum, natural gas and the like face the problems of increasingly reduced reserves, serious environmental pollution, large price fluctuation and the like. These non-renewable energy sources are formed in nature for hundreds of millions of years, cannot be recovered in a short period, and with large-scale development and utilization, the reserves are smaller and smaller, and the day of exhaustion is always available. Taking petroleum as an example, global petroleum reserves are gradually reduced, exploitation difficulty and cost are continuously increased, and meanwhile, a large amount of greenhouse gases and pollutants are generated by burning the petroleum, so that the environment is seriously damaged. Under such a background, energy transformation is urgent, and renewable energy has become an important direction of global energy development due to advantages such as cleanliness and sustainability. Distributed photovoltaics have evolved rapidly in recent years as an important component of renewable energy sources. The solar energy is utilized to generate electricity, and heat generated by hydrogen fusion reaction in the sun is converted into electric energy through a photovoltaic effect. The distributed photovoltaic power generation has the economic characteristics of relatively small installed capacity, small disposable investment, short construction period, low investment risk and the like, almost generates no pollutant in the power generation process, has little pollution to the ecological environment, and is a green and environment-friendly power generation mode. In addition, the distributed photovoltaic is generally built by building integration and building additional construction forms, and building roofs, empty spaces and the like can be fully utilized, so that the distributed photovoltaic is greatly helpful for saving land resources. According to the data of the national energy bureau, the capacity of the new installation of the photovoltaic in the national industry and commerce of 2024 reaches 88.6GW, and the capacity is increased by 68% in the same ratio, and the new installation of the photovoltaic accounts for 32% of the total installation of the photovoltaic, so that the new installation of the photovoltaic becomes a key engine for promoting the growth of the industry. The new nationally-increased grid-connected capacity reaches 16088 kilowatts in total in three seasons before 2024, and the same ratio is increased by 24.8%, wherein the distributed photovoltaic installation reaches 8522 kilowatts, and the vigorous activity and huge potential of the distributed photovoltaic market are fully revealed. The traditional power distribution network is mainly a power transmission and distribution system from a transformer substation to an end user, the structure of the power distribution network is mainly radial, multi-section single-connection, multi-section multi-connection, the voltage level is generally lower, and the power distribution network is mainly responsible for distributing high-voltage electric energy to the user after reducing the voltage. The system has the characteristics of large load change, low construction cost, high operation and maintenance cost, direct service for users and the like. However, with the massive access of distributed photovoltaics, the structure and operating characteristics of the distribution network have changed significantly, gradually changing into a multi-power structure. The distributed photovoltaic has the characteristics of intermittence and randomness, and the generated power is greatly influenced by factors such as illumination intensity, weather and the like. For example, on overcast days or at night, the light is insufficient, the distributed photovoltaic power generation power is reduced to zero, and during a sunny period, the power generation power is greatly increased. Meanwhile, the load of the power distribution network also has uncertainty, and the power consumption habits and power consumption requirements of different users are different, so that load fluctuation is large. The uncertainty of the two components is overlapped with each other, and a plurality of challenges are brought to the operation of the power distribution network. When the power generated by the distributed photovoltaic power generation is larger, the voltage of the access point can be increased and even exceeds the rated voltage range, and when the power generated is smaller, the voltage can be reduced, so that the nor