CN-121981522-A - Micro-grid risk assessment method taking power supply equivalent radius as quantization parameter

CN121981522ACN 121981522 ACN121981522 ACN 121981522ACN-121981522-A

Abstract

The invention discloses a micro-grid risk assessment method taking a power supply equivalent radius as a quantification parameter, which comprises the following steps of S1, dividing a micro-grid into k layers according to a micro-grid topological structure and voltage levels, collecting active power of each node in each layer, equipment operation data and climate environment parameters of a micro-grid area, calculating a reliable factor and average load density, S2, calculating a standardized sensitivity index of the risk assessment factor and a correlation coefficient of the risk assessment factor based on the reliable factor, S3, screening key risk assessment factors which have obvious influence on a power supply range, calculating a key risk assessment factor weight, S4, quantifying a risk assessment model by combining the key risk assessment factors and the key risk assessment factor weight to obtain an equivalent radius of the power supply range of the micro-grid, abstracting the micro-grid system into interconnected layer nodes, intuitively reflecting the maximum power supply range of the system under different risk conditions through power supply radius change, and realizing quantitative management of risk assessment.

Inventors

ZHOU HANG
LI ZHONGZHONG
CUI JIANZHAO
FU LINBEI
LI SIFAN
MA LIHONG
QIN DAN
LI JUNHUA

Assignees

海南电网有限责任公司

Dates

Publication Date: 20260505
Application Date: 20251226

Claims (9)

1. The micro-grid risk assessment method taking the equivalent radius of power supply as a quantization parameter is characterized by comprising the following steps of: S1, dividing a micro-grid into k layers according to a micro-grid topological structure and voltage levels, collecting active power of each node in each layer, equipment operation data and climate environment parameters of a micro-grid area, and calculating the reliability factors and average load densities of each node in each layer according to the active power, the equipment operation data and the climate environment parameters; s2, calculating a standardized sensitivity index of the risk assessment factor and a correlation coefficient of the risk assessment factor and the reliability factor based on the reliability factor; S3, screening out key risk assessment factors with obvious influence on a power supply range according to the standardized sensitivity index and the correlation coefficient, and calculating the weight of the key risk assessment factors; s4, constructing a risk assessment model, quantifying the risk assessment model by combining the key risk assessment factors and the key risk assessment factor weights, and obtaining the equivalent radius of the micro-grid power supply range according to the quantified risk assessment model.
2. The method for evaluating risk of a micro-grid with the equivalent radius of electricity supply as a quantization parameter according to claim 1, wherein the equipment operation data comprises equipment accumulated operation time, equipment type, equipment characteristic life parameter and equipment shape parameter; the climate environment parameters of the micro-grid area comprise temperature, rainfall and wind speed.
3. A method of evaluating risk of a microgrid having an equivalent radius of electricity supply as a quantization parameter according to claim 2, wherein said calculating a reliability factor and an average load density of each node in each level from said active power, said equipment operation data and said climate environment parameters comprises: S101, calculating service life reliability of equipment according to the equipment operation data, wherein a calculation formula of the service life reliability is as follows: Wherein, the For the sake of life reliability, For the characteristic lifetime parameter of the device, For the shape parameters of the device, the shape parameters, t is the accumulated running time of the equipment; S102, calculating an environment correction factor according to the climate environment parameter, and correcting the service life reliability of equipment according to the environment correction factor; The environmental correction factor calculation formula is as follows: Wherein, the The method comprises the steps that an environment correction factor is adopted, T is the temperature of an area where equipment is located, J is the rainfall of the area where the equipment is located, and I is the wind speed of the area where the equipment is located; In order to be a temperature sensitivity coefficient, For the coefficient of sensitivity to rainfall, As the wind speed sensitivity coefficient, For the temperature reference threshold value, For the rainfall reference threshold value, For the wind speed reference threshold value, Indicating that T is higher than T ref to reduce device reliability, Indicating that J exceeds the reference rainfall threshold J ref a reliability penalty is incurred, Indicating that I exceeds I ref would not pose additional risk to the device; the calculation formula of the service life reliability of the correction equipment according to the environment correction factor is as follows: Wherein, the The service life reliability of the corrected equipment is improved; S103, obtaining serial nodes and parallel nodes of each node in each level based on a micro-grid topological structure, and calculating the reliability of the serial nodes and the reliability of the parallel nodes according to the service life reliability of equipment, wherein the calculation formula of the reliability of the serial nodes is as follows: Wherein, the For the reliability of the series node, L a ' is the life reliability of the a-th device in the series path, The number of devices that are in a serial path; the calculation formula of the reliability of the parallel node is as follows: Wherein, the For parallel node reliability, L b ' is the life reliability of the equipment of the b-th parallel branch, The number of parallel branches; S104, calculating the reliability factor of each node in each level according to the reliability of the series node and the reliability of the parallel node, wherein the calculation formula is as follows: Wherein, the Is the reliability factor of the kth level p-th node, For the reliability of the series node, The reliability of the parallel nodes is that A is the number of the serial nodes, and B is the number of the parallel nodes; s105, calculating average load density according to the active power, wherein a calculation formula of the average load density is as follows: wherein p is the average load density, And S is the total area of the power supply area of the micro-grid, wherein S is the active power of the ith node. .
4. The method for evaluating risk of a micro-grid with the equivalent radius of electricity supply as a quantization parameter according to claim 1, wherein the risk evaluation factors comprise node voltage deviation, critical equipment failure rate, operation maintenance period, extreme weather occurrence frequency and critical load proportion.
5. The method for evaluating risk of a micro-grid using an equivalent radius of electricity as a quantization parameter according to claim 4, wherein the calculating a normalized sensitivity index of a risk evaluation factor comprises: normalizing the various risk assessment factor values and the reliable factors, wherein a normalized calculation formula is as follows: Wherein, the For the original value of the type i risk assessment factor, For the minimum of this type of risk factor on all nodes, For the maximum value of this type of risk factor on all nodes, For the minimum of this type of risk factor on all nodes, For the normalized risk factor value, Is the reliability factor of the kth level p-th node, As a reliability factor after normalization, At the maximum value of the reliability factor, Is the minimum of the reliability factor; The variable quantity of various risk assessment factors and the variable quantity of reliable factors are calculated, and the calculation formula is as follows: Wherein, the For the amount of change in various risk assessment factors, Normalized values of the risk assessment factors of the first class at time j, Normalized values of the risk assessment factors of the first class at the moment j-1, The p-th node of the k-th level of W k,p,j 'normalizes the reliable factor at the moment j, and the p-th node of the k-th level of W k,p,j-1 ' normalizes the reliable factor at the moment j-1; Calculating a standardized sensitivity coefficient, wherein the calculation formula is as follows: Wherein, the To normalize the sensitivity coefficient, Δf l 'is the variation of various risk assessment factors, and Δw k,p ' is the variation of the reliability factor.
6. The method for evaluating risk of a micro-grid with the equivalent radius of electricity supply as the quantization parameter according to claim 4, wherein the calculation formula of the correlation coefficient between the risk evaluation factor and the node reliability factor of each level is: Wherein P is l,j The j-th parameter value for the type i risk assessment factor, Is the mean value of the risk factors of the class i, For the reliability of the k-th level node, Is the mean value of the reliability of the nodes of the k-th level, and n is the number of samples.
7. The method for evaluating risk of a micro-grid with the equivalent radius of power supply as a quantization parameter according to claim 1, wherein the step of screening out key risk evaluation factors with significant influence on the power supply range according to the standardized sensitivity index and the correlation coefficient, and calculating the weight of the key risk evaluation factors comprises the following steps: Taking absolute value |H k,l | from the correlation coefficient, sorting the absolute value and the standardized sensitivity coefficient, and grading according to the sorting result; When the I H k,l I is more than or equal to 0.70 and the SSI k,l is more than or equal to 0.6, the risk assessment factors are closely related to the reliability of the nodes, and the correlation coefficient values are classified into one level; when H k,l is more than or equal to 0.40 and less than or equal to 0.70 or SSI k,l is more than or equal to 0.3 and less than or equal to 0.6, a certain relation exists between the risk assessment factors and the reliability of the nodes, and the correlation coefficient values are classified into two stages; When |h k,l | <0.40 and SSI k,l < 0.3, it means that the risk assessment factor has a weak effect on node reliability, removing the factor; Calculating weighted scores of the key risk assessment factors obtained through screening, and carrying out normalization processing to obtain weights of the key risk assessment factors: Where s kl is the score of the kth level class i key risk assessment factor and ω kl is the normalized weight.
8. The method for evaluating risk of a micro-grid with power supply equivalent radius as quantization parameter according to claim 4, wherein said quantizing the risk evaluation model by combining the key risk evaluation factors and the key risk evaluation factor weights comprises: And classifying the node voltage deviation, the key equipment fault rate, the operation and maintenance period and the weather occurrence frequency into negative indexes, and calculating a normalized value of the negative indexes, wherein a calculation formula is as follows: Wherein, the Normalized values for the class i risk assessment factors of the k-th hierarchy, The original value of the class i risk assessment factor of the k-th hierarchy, Is the minimum value of the class i risk assessment factor for the k-th hierarchy, Is the maximum value of the risk assessment factors of the type I of the k hierarchy. And classifying the key load proportion into a forward index, and calculating a normalized value of the forward index, wherein a calculation formula is as follows: Calculating a risk degree evaluation value of each level node according to the normalized value of the key risk evaluation factor, quantifying a risk evaluation model according to the risk degree evaluation value of each level node, wherein the calculation formula of the risk degree evaluation value is as follows: Wherein Q k is the risk degree evaluation value of the kth level, f kl is the normalized value of the first class risk factor of the kth level, and ω kl is the corresponding weight thereof.
9. The method for evaluating risk of a micro-grid by taking an equivalent radius of power supply as a quantization parameter according to claim 8, wherein the obtaining the equivalent radius of the power supply range of the micro-grid according to the quantized risk evaluation model comprises the following steps: Computing each of the levels The effective output power is calculated according to the effective output power, and then the equivalent radius is calculated according to the effective output power of the whole micro-grid; The calculation formula of the effective output power of the node is as follows: Wherein, P i eff is node effective output power, P i is node i active power, W k,p is normalized node reliability factor, Q i is normalized risk degree evaluation value of the level of the node, and the risk degree evaluation value of the level of the node is taken; The calculation formula of the integral effective output power of the micro-grid is as follows: S eff is the whole effective output power of the micro-grid; the calculation formula of the equivalent radius is as follows: wherein S eff is the effective output power of the whole micro-grid, R is the equivalent radius, A is the equivalent coverage area of the micro-grid, and p is the average load density.

Description

Micro-grid risk assessment method taking power supply equivalent radius as quantization parameter Technical Field The invention relates to the technical field of power control, in particular to a micro-grid risk assessment method taking an equivalent radius of power supply as a quantization parameter. Background The micro-grid is used as a novel distributed power system concept, is composed of a photovoltaic power source, a wind power source, a miniature hydropower source and other distributed power sources, a load, an energy storage device and an energy management and control system, and can flexibly operate in an island mode or a grid-connected mode. In the grid-connected operation mode, the micro-grid can cooperate with the main grid to provide auxiliary support and standby capability, so that the stability and reliability of the whole power system are improved, and in the island mode, the micro-grid can continuously ensure the power supply of local loads even in severe weather or in the case of main grid faults. Since the micro-grid is usually close to the load side, the micro-grid has remarkable advantages in power supply in remote areas, islands and population dispersion areas, the problem of last kilometers of a large power grid can be effectively relieved, and meanwhile, the power quality and the power supply reliability are improved. However, the micro-grid system internally comprises various types of distributed power supplies, energy storage devices and control strategies, and the running state of the micro-grid system is influenced by various factors, so that the running risk of the micro-grid system is complex and variable. At present, the risk assessment method for the micro-grid is concentrated on single equipment, single node or local operation parameters, and lacks a complete assessment system and an analysis model capable of quantifying the overall system operation risk. Disclosure of Invention Aiming at the prior art, the invention aims to provide a micro-grid risk assessment method taking the equivalent radius of power supply as a quantization parameter, which mainly solves the technical problems in the background art. In order to achieve the above object, the technical solution of the embodiment of the present invention is as follows: A micro-grid risk assessment method taking an equivalent radius of power supply as a quantization parameter comprises the following steps: S1, dividing a micro-grid into k layers according to a micro-grid topological structure and voltage levels, collecting active power of each node in each layer, equipment operation data and climate environment parameters of a micro-grid area, and calculating the reliability factors and average load densities of each node in each layer according to the active power, the equipment operation data and the climate environment parameters; s2, calculating a standardized sensitivity index of the risk assessment factor and a correlation coefficient of the risk assessment factor and the reliability factor based on the reliability factor; S3, screening out key risk assessment factors with obvious influence on a power supply range according to the standardized sensitivity index and the correlation coefficient, and calculating the weight of the key risk assessment factors; s4, constructing a risk assessment model, quantifying the risk assessment model by combining the key risk assessment factors and the key risk assessment factor weights, and obtaining the equivalent radius of the micro-grid power supply range according to the quantified risk assessment model. Optionally, the device operation data includes a device accumulated operation time, a device type, a device characteristic lifetime parameter, and a device shape parameter; the climate environment parameters of the micro-grid area comprise temperature, rainfall and wind speed. Optionally, the calculating the reliability factor and the average load density of each node in each level according to the active power, the equipment operation data and the climate environment parameters includes: S101, calculating service life reliability of equipment according to the equipment operation data, wherein a calculation formula of the service life reliability is as follows: Wherein, the For the sake of life reliability,For the characteristic lifetime parameter of the device,For the shape parameters of the device, the shape parameters, t is the accumulated running time of the equipment; S102, calculating an environment correction factor according to the climate environment parameter, and correcting the service life reliability of equipment according to the environment correction factor; The environmental correction factor calculation formula is as follows: Wherein, the The method comprises the steps that an environment correction factor is adopted, T is the temperature of an area where equipment is located, J is the rainfall of the area where the equipment is located, and I is the wind spe