CN-122022256-A - Distributed energy running state sensing method and system based on climate toughness

CN122022256ACN 122022256 ACN122022256 ACN 122022256ACN-122022256-A

Abstract

The invention discloses a distributed energy running state sensing method and a system based on weather toughness, which relate to the technical field of distributed energy, and comprise the steps of calculating regional risk indexes according to weather partitions, combining weather disaster intensity indexes with weather toughness indexes, screening key nodes based on node exposure indexes and node importance indexes, evaluating data credibility and correcting deviation through model deviation indexes and neighborhood consistency indexes, judging running states according to weather pressure indexes and toughness margin indexes, and connecting the modules by signals.

Inventors

TANG LINXIANG
LI XINYAO
Peng Daicheng
ZHANG YIXUAN

Assignees

东北大学秦皇岛分校

Dates

Publication Date: 20260512
Application Date: 20251225

Claims (10)

1. The distributed energy running state sensing method based on the climate toughness is characterized by comprising the following steps of; Step S1, collecting extreme precipitation, extreme wind speed and extreme temperature as weather disaster indexes, selecting a maximum value as a disaster intensity index according to the ratio of a weather model predicted value to a reference value, calculating a weather toughness index by combining an adaptability index, a transformation capacity index, an exposure index and a sensitivity index, and evaluating the weather toughness level of a region; step S2, calculating a node exposure index, evaluating the node exposure based on the weather disaster influence time proportion, calculating a node importance index through a load contribution ratio and a topology influence factor, obtaining a node comprehensive score based on the node exposure index and the node importance index, comparing the node comprehensive score with a screening threshold, and screening key nodes; step S3, calculating a model deviation index and a neighborhood consistency index, evaluating the reliability of node data, setting a threshold value, judging whether the measured data is abnormal, and if so, carrying out data correction by adopting the average value of a model predicted value and a neighborhood average measured value; And S4, judging the node operation state according to the weather pressure index and the toughness margin index, and dividing the node operation state into three types of normal state, early warning state and emergency state according to the node pressure and the toughness margin.
2. The climate toughness-based distributed energy operation state sensing method according to claim 1, wherein the disaster intensity index is calculated by the following formula: wherein the subscript r denotes an area number, Is the predicted value of the extreme precipitation, Is a reference value for precipitation, Is the predicted value of the extreme wind speed, Is a reference value for the wind speed, Is a predicted value of the extreme temperature deviation, Is a temperature reference value.
3. The climate toughness based distributed energy operation state sensing method according to claim 2, wherein the climate toughness index is calculated by the following formula: Wherein, the method comprises the steps of, Is an index of the ability to adapt to the situation, Is the transformation capability index of the plant, Is an index of the degree of exposure, Is the sensitivity index; The fitness index is calculated by the following formula: Wherein, the method comprises the steps of, Is the input of the electric power toughness of people, Is the ratio of the energy storage capacity to the standby capacity, Is the emergency response duration level; The transformation ability index is calculated by the following formula: Wherein, the method comprises the steps of, Is the permeability of the renewable energy source, and the water is mixed with the water, Is an index of the modernization degree of the infrastructure; the exposure index is calculated by the following formula: Wherein, the method comprises the steps of, Is the area of the region located in the high risk area, Is the total area of the region; The sensitivity index is calculated by the following formula: Wherein, the method comprises the steps of, Is the population density of the person, Is the degree of aging of the infrastructure.
4. The climate toughness-based distributed energy operation state sensing method according to claim 2, wherein the regional risk index is calculated by the following formula: Wherein, the method comprises the steps of, Is an index of the intensity of the disaster, Is a climate toughness index, and sets a risk threshold based on the zone risk index to divide the high risk zone, the medium risk zone, and the low risk zone.
5. The climate toughness-based distributed energy operation state sensing method according to claim 1, wherein the node exposure index is calculated by the following formula: Wherein, the method comprises the steps of, Is the sum of the time that node i is affected by the weather hazard during the planning period, Is the total duration of the planning period.
6. The climate toughness-based distributed energy operation state sensing method according to claim 5, wherein the node importance index is calculated by the following formula: Wherein, the method comprises the steps of, Is the load contribution ratio of node i, Is the topology influencing factor of node i; The load contribution ratio is calculated by the following formula: Wherein, the method comprises the steps of, Is the average load or installed capacity of the node i, The total load or the total capacity of the loader of all the distributed energy nodes; the topology influence factor is calculated by the following formula: Wherein, the method comprises the steps of, Is the mid-range centrality of node i, Is the maximum median centrality; The node exposure evaluation module also calculates a node synthesis score by a product of the node exposure index and the node importance index, the node synthesis score calculated by the following formula: Wherein, the method comprises the steps of, Is an index of the exposure of the node, And setting a screening threshold value to screen key nodes based on the node comprehensive score.
7. The climate toughness-based distributed energy operation state sensing method according to claim 1, wherein the model deviation index is calculated by the following formula: Wherein, the method comprises the steps of, Is the measurement of node i at time t, Is the model predictive value of the node i at the time t; the neighborhood relevance index is calculated by the following formula: Wherein, the method comprises the steps of, Is the average measurement of the neighbor nodes of node i at time t.
8. The method for sensing the running state of the distributed energy source based on the climate toughness according to claim 7, wherein a model deviation threshold value and a neighborhood consistency threshold value are set to judge whether the measured data is abnormal, if so, the average value of a model predicted value and a neighborhood average measured value is adopted to carry out data correction, and the data correction is calculated by the following formula: Wherein, the method comprises the steps of, Is a model predictive value of the model, and, Is a neighborhood average measurement.
9. The climate toughness-based distributed energy operation state sensing method according to claim 1, wherein the climate pressure index is calculated by the following formula: Wherein, the method comprises the steps of, Is the load or pressure forecast of node i at time t, Is the design margin for node i; The toughness margin index is calculated by the following formula: Wherein, the method comprises the steps of, Is the toughness capability of node i at time t; Dividing the operation state into a normal state, an early warning state and an emergency state according to the relation between the weather pressure index and the toughness margin index, when And is also provided with When it is in normal state And is also provided with The emergency state is the emergency state, and the rest is the early warning state.
10. A climate toughness based distributed energy operation state sensing system for implementing the climate toughness based distributed energy operation state sensing method according to any of claims 1-9, characterized in that; The climate disaster assessment module is used for collecting extreme precipitation, extreme wind speed and extreme temperature as climate disaster indexes, selecting a maximum value as a disaster intensity index according to the ratio of a climate model predicted value to a reference value, calculating a climate toughness index by combining an adaptability index, a transformation capacity index, an exposure index and a sensitivity index, and assessing the climate toughness level of an area; the node exposure evaluation module is used for calculating a node exposure index, evaluating the node exposure based on the weather disaster influence time proportion, calculating a node importance index through a load contribution ratio and a topology influence factor, obtaining a node comprehensive score based on the node exposure index and the node importance index, comparing the node comprehensive score with a screening threshold value, and screening key nodes; Calculating a model deviation index and a neighborhood consistency index, evaluating the reliability of node data, setting a threshold value, judging whether the measured data is abnormal or not, and if so, carrying out data correction by adopting the average value of a model predicted value and a neighborhood average measured value; The operation state judging module judges the node operation state according to the weather pressure index and the toughness margin index, and classifies the node operation state into three types of normal state, early warning state and emergency state according to the node pressure and the toughness margin.

Description

Distributed energy running state sensing method and system based on climate toughness Technical Field The invention relates to the technical field of distributed energy, in particular to a climate toughness-based distributed energy running state sensing method and system. Background With the rapid development of distributed energy sources, the operation state sensing of the distributed energy sources is important to the guarantee of energy source supply safety. However, global climate change exacerbations lead to extreme climate events such as storms, typhoons, high temperature frequency, and pose a serious threat to distributed energy systems. In the prior art, the distributed energy running state sensing method focuses on conventional running parameter monitoring and lacks in-depth integrated analysis on climate disaster factors. For example, traditional methods fail to effectively combine climate model predictive data with regional toughness capability assessment, resulting in risk identification hysteresis and inaccurate assessment; In the aspect of node monitoring, the topology importance and the exposure degree of the nodes in the network are often ignored based on single dimension of capacity or geographic position, so that the monitored resource allocation is unreasonable, in addition, the data acquisition process is easy to be interfered by weather to generate abnormality, but the existing deviation correcting mechanism is imperfect, and the state judgment reliability is affected. Therefore, a method and a system capable of integrating the climate toughness and realizing the accurate state sensing are needed to improve the adaptability and the operation toughness of the distributed energy source under the extreme climate. The present invention proposes a solution to the above-mentioned problems. Disclosure of Invention In order to overcome the above-mentioned drawbacks of the prior art, embodiments of the present invention provide a method and a system for sensing a distributed energy operating state based on climate toughness, so as to solve the problems set forth in the background art. In order to achieve the above purpose, the present invention provides the following technical solutions: the distributed energy running state sensing method based on the climate toughness comprises the following steps; Step S1, collecting extreme precipitation, extreme wind speed and extreme temperature as weather disaster indexes, selecting a maximum value as a disaster intensity index according to the ratio of a weather model predicted value to a reference value, calculating a weather toughness index by combining an adaptability index, a transformation capacity index, an exposure index and a sensitivity index, and evaluating the weather toughness level of a region; step S2, calculating a node exposure index, evaluating the node exposure based on the weather disaster influence time proportion, calculating a node importance index through a load contribution ratio and a topology influence factor, obtaining a node comprehensive score based on the node exposure index and the node importance index, comparing the node comprehensive score with a screening threshold, and screening key nodes; step S3, calculating a model deviation index and a neighborhood consistency index, evaluating the reliability of node data, setting a threshold value, judging whether the measured data is abnormal, and if so, carrying out data correction by adopting the average value of a model predicted value and a neighborhood average measured value; And S4, judging the node operation state according to the weather pressure index and the toughness margin index, and dividing the node operation state into three types of normal state, early warning state and emergency state according to the node pressure and the toughness margin. In a preferred embodiment, step S1 comprises the following: the disaster intensity index is calculated by the following formula: wherein the subscript r denotes an area number, Is the predicted value of the extreme precipitation,Is a reference value for precipitation,Is the predicted value of the extreme wind speed,Is a reference value for the wind speed,Is a predicted value of the extreme temperature deviation,Is a temperature reference value; The climate toughness index is calculated by the following formula: Wherein, the method comprises the steps of, Is an index of the ability to adapt to the situation,Is the transformation capability index of the plant,Is an index of the degree of exposure,Is the sensitivity index; The fitness index is calculated by the following formula: Wherein, the method comprises the steps of, Is the input of the electric power toughness of people,Is the ratio of the energy storage capacity to the standby capacity,Is the emergency response duration level; The transformation ability index is calculated by the following formula: Wherein, the method comprises the steps of, Is the permeability of the