A method for evaluating substation flood control capability based on real-time data

Abstract

The present application discloses a method for evaluating the flood control capacity of a substation based on real-time data, including: establishing a multi-dimensional influencing factor system; establishing a numerical quantification model of the floor area and safe water depth based on the multi-dimensional influencing factor system; constructing a risk level assessment model; obtaining data of factors affecting the actual flood situation; obtaining a preliminary risk assessment level based on the risk level assessment model, and making preliminary deployment of flood control materials; obtaining a real-time water depth for safe operation of substation equipment based on the numerical quantification model of the floor area and safe water depth; calculating the real-time water depth of the substation; comparing the real-time water depth of the substation with the water depth for safe operation of the substation equipment, and evaluating the flood control capacity of the substation. The present invention improves the real-time perception of the flood control capacity and risks of the substation, and improves the scientific configuration level of flood control materials, personnel, and equipment.

Description

Technical Field

[0001] The invention belongs to the technical field of power grid disaster prevention and mitigation, and relates to a method for evaluating the flood prevention capacity of a substation based on real-time data. Background Art

[0002] As an important facility for power grid operation and production, the normal operation of the substation is a necessary condition for ensuring safe and reliable power supply. If flood prevention work is not done well, it will have a great impact on the normal operation of the substation. Therefore, doing a good job of flood prevention is an important part of ensuring the safe and normal power supply of the substation. In the operation and management of the substation, the flood prevention work mainly has the following problems:

[0003] First, when classifying the flood risk levels of substations of different voltage levels, factors such as the geographical environment, hydrological characteristics, and rainstorm distribution characteristics around the substations are not fully considered;

[0004] Second, flood prevention work during the peak summer period is often carried out passively based on management and operation experience. At present, the evaluation of substation flood prevention capacity is mainly achieved by static evaluation using engineering methods and experience methods, which is not timely enough to support the current lean management requirements.

[0005] Third, most of the current substation flood prevention online monitoring devices use a single, outdated intuitive observation method, which can only monitor the precipitation conditions in the substation. There is no comprehensive analysis of the substation's water storage capacity, drainage capacity, and precipitation forecast information, and it cannot meet the requirements for predicting the flood prevention risk situation of substation equipment.

[0006] In the construction process of the power industry, substations are very important components. In the operation and management of substations, it is very difficult to effectively carry out flood prevention work. In order to effectively carry out substation flood prevention management, most substations use flood prevention online monitoring devices as auxiliary devices for flood prevention management. However, the existing substation flood prevention online monitoring devices do not provide much data and information, and cannot provide much guarantee for the realization of specific work goals. Summary of the invention

[0007] In order to address the deficiencies in the prior art, the present application provides a method for evaluating the flood control capacity of a substation based on real-time data.

[0008] In order to achieve the above object, the present invention adopts the following technical solution:

[0009] A method for evaluating the flood control capability of a substation based on real-time data comprises the following steps:

[0010] Step 1: Classify the factors affecting the flood situation of substations and establish a multi-dimensional influencing factor system;

[0011] Step 2: Obtain data on different substation footprints and safe water depth for substation equipment operation, and combine the influencing factors of step 1 to establish a numerical quantitative model of footprint and safe water depth based on a multi-dimensional influencing factor system;

[0012] Step 3: Construct a risk level assessment model based on the multi-dimensional influencing factor system and historical substation flood prevention experience;

[0013] Step 4: Obtain the area of ​​the substation to be evaluated and obtain the actual flood influencing factor data according to the multi-dimensional influencing factor evaluation system;

[0014] Step 5: Input the data of actual flood situation influencing factors into the risk level assessment model to obtain the preliminary risk assessment level and make preliminary deployment of flood control materials;

[0015] Step 6: The area of ​​the substation to be evaluated and the data of the factors affecting the actual flood situation are input into the numerical quantification model of the area and safe water depth to obtain the real-time safe operation water depth of the substation equipment;

[0016] Step 7: Calculate the precipitation of the substation based on the area of ​​the substation to be evaluated and the actual flood influencing factors, and calculate the real-time water accumulation depth of the substation based on the storage capacity and drainage capacity of the substation;

[0017] Step 8: Compare the real-time water accumulation depth of the substation with the safe operation water accumulation depth of the substation equipment obtained in step 6 to evaluate the flood control capability of the substation.

[0018] The present invention further includes the following preferred embodiments:

[0019] Preferably, in step 1, the factors affecting the flood situation of the substation are divided into disaster-prone environmental factors, disaster-causing factor factors, and disaster-bearing body factors.

[0020] Preferably, the disaster-prone environmental factors include climate conditions, topography, soil and vegetation, hydrological conditions, and potential risks of mountain torrents and mud-rock flows;

[0021] The disaster-causing factors include precipitation, temperature, and wind speed;

[0022] The disaster-prone factors include voltage level, drainage and water storage capacity within the facilities, and the amount of flood control material reserves.

[0023] Preferably, in step 2, water pressure and water level sensors are installed in the substation to monitor the safe operation water depth of substation equipment under different substations and influencing factors. Combined with the corresponding substation area and influencing factors, based on the membership theory of fuzzy mathematics, the qualitative evaluation is converted into a quantitative evaluation, and a quantitative conversion model of the qualitative description is established. Combined with expert experience, each influencing factor is scored, and fuzzy evaluation, entropy analysis and other methods are used to obtain a numerical quantification model of the area and safe water depth based on a multi-dimensional influencing factor system.

[0024] Preferably, the water level sensor is installed in a cable trench in the station, 50 to 100 cm above the ground.

[0025] Preferably, in step 3, rating standards for each indicator are set, and a Bayesian algorithm model based on machine learning is used to rate each indicator. In combination with the indicator rating weights set based on the impact on the flood control capabilities of power grid equipment and facilities, a risk level assessment model is constructed to achieve dynamic risk rating.

[0026] Preferably, in step 3, based on membership analysis, entropy method and analytic hierarchy process, a multi-influencing quantity assessment model for flood control of power grid equipment and facilities is obtained as a risk level assessment model, specifically:

[0027] Step 3.1: Set up an evaluation index system based on substation flood influencing factors, including: the first-level index is u i =(i=1,2,3), secondary index of disaster-prone environment; secondary index of carrier, construct fuzzy evaluation state set;

[0028] Step 3.2: Construct a flood control capability evaluation set V = (V1, V2, V3), which represents safety, general, and abnormal respectively;

[0029] Step 3.3: Normalize the indicators at all levels.

[0030] Step 3.4: Quantify the qualitative data;

[0031] Step 3.5: Set the membership function and weight of each indicator, and construct a multi-influence assessment model for flood control of power grid equipment and facilities as a risk level assessment model.

[0032] Preferably, in step 3.4, a number between 0 and 1 is used as a quantization score to quantify the qualitative data.

[0033] Preferably, in step 7, the calculation formula for the substation precipitation is:

[0034] Q1=S·h1

[0035] Q1 is the precipitation volume of the substation, unit: m 3 ;

[0036] S is the area of ​​the substation, unit: m 2 ;

[0037] h1 is the actual monitoring data of precipitation, unit: m.

[0038] The calculation formula for substation water storage capacity Q2 and substation discharge capacity Q3 is:

[0039] Q2=A·B·L

[0040] Q3=V·H

[0041] Where A is the length of the water storage tank, unit: m;

[0042] B is the width of the water storage tank, unit: m;

[0043] L is the height of the water storage tank, unit: m;

[0044] V is the drainage pump flow rate, unit: m 3 / H;

[0045] H is the working time of the drainage pump, unit: hour.

[0046] The calculation formula for the real-time water depth of the substation is:

[0047] h2=Q4 / S / 1000

[0048] h2 is the actual water depth in the station, unit: mm;

[0049] Q4 is the actual water volume of the substation in real time, unit: m 3 ;

[0050] Q4=Q1-Q2-Q3

[0051] Q4 is the actual water volume of the substation in real time, unit: m 3 ;

[0052] S is the area of ​​the substation, unit: m 2 .

[0053] Preferably, in step 8, the power grid remote control center platform compares the real-time water accumulation depth of the substation with the safe operation water accumulation depth of the substation equipment obtained in step 6, evaluates the flood prevention capability of the substation, and performs flood prevention based on the initially deployed flood prevention materials.

[0054] Beneficial effects achieved by this application:

[0055] The present invention uses engineering design methods to calculate the flood control capacity of substations based on information such as the area of ​​substations and the depth of water accumulation for safe operation of substation equipment. On this basis, real-time monitoring data of precipitation is introduced to complete the theoretical calculation of the depth of water accumulation in substations. Finally, the water storage capacity and drainage capacity of substations are introduced to finally realize the dynamic evaluation of flood control capacity of substations.

[0056] For substations threatened by heavy rainfall, the present invention comprehensively considers multiple factors such as cumulative rainfall monitoring data, substation water storage capacity, drainage capacity, etc., to achieve dynamic assessment of substation flood control capabilities and risks, judges danger and divides danger levels according to relevant indicators, which is conducive to the scientific formulation of flood control emergency plans and the effective organization of rapid response. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 It is a flow chart of a method for evaluating flood control capability of a substation based on real-time data of the present invention;

[0058] Figure 2 It is a numerical quantification model of the floor area and safe water accumulation depth of the present invention;

[0059] Figure 3 It is a flow chart of the risk level assessment model construction method 1 of the present invention;

[0060] Figure 4 It is a flow chart of the risk level assessment model construction method 2 of the present invention. DETAILED DESCRIPTION

[0061] The present application is further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the protection scope of the present application.

[0062] like Figure 1 As shown, a method for evaluating the flood control capability of a substation based on real-time data of the present invention comprises the following steps:

[0063] Step 1: Classify the factors affecting the flood situation of substations and establish a multi-dimensional influencing factor system;

[0064] During the specific implementation, the factors affecting the flood situation of substations are divided into disaster-prone environmental factors, disaster-causing factor factors, and disaster-bearing body factors.

[0065] The disaster-prone environmental factors include climate conditions, topography, soil and vegetation, hydrological conditions, and potential risks of mountain torrents and mud-rock flows;

[0066] The disaster-causing factors include precipitation, temperature, and wind speed;

[0067] The disaster-prone factors include voltage level, drainage and water storage capacity within the facilities, and the amount of flood control material reserves.

[0068] As shown in Table 1.

[0069] Table 1 Factors affecting flood conditions in substations

[0070]

[0071] Step 2: Obtain data on different substation footprints and safe water depth for substation equipment operation, and combine the influencing factors of step 1 to establish a numerical quantitative model of footprint and safe water depth based on a multi-dimensional influencing factor system;

[0072] like Figure 2 As shown in the figure, by installing water pressure and water level sensors in the substation to monitor the safe operation water depth of substation equipment under different substations and influencing factors, the area of ​​the substation is obtained through the topographic factors and site selection of different substations. Combined with the disaster-bearing body factor index and disaster-pregnant environmental factor index obtained in step 1, these two types of factors are combined with the obtained values ​​of the safe operation water depth and area of ​​the substation equipment to be tested. The hierarchical analysis method is used to assign the weights of the indicators at all levels to the topography and landforms, storage and drainage capacity and other qualitative factors in the flood influencing factors according to the experts, and the judgment matrix is ​​constructed by pairwise comparison according to the nine-scale method. The assignment comparison method is shown in Table 2. The relative importance is quantitatively processed. The processed data is combined with the substation ground area and safe water depth data to establish a numerical quantitative model of the area and safe water depth of multiple flood control influencing factors. , The numerical quantitative model of the area and safe water depth based on the multi-dimensional influencing factor system is obtained.

[0073] The water level sensor is installed in the cable trench in the station, 50 to 100 cm above the ground. The specific installation point depends on the depth of the drainage pump placement pool in the cable trench; there is no specific model.

[0074] Table 2 Nine-scale method

[0075] Scale value Scale meaning 1 <![CDATA[a i with a j Equally important]]> 3 <![CDATA[a i Than a j Slightly important]]> 5 <![CDATA[a i Than a j Very important]]> 7 <![CDATA[a i Than a j Strongly important]]> 9 <![CDATA[a i Than a j Extremely important<!-- 4 --> ]]> 2,4,6,8 The middle value of adjacent judgments reciprocal <![CDATA[a ji =1 / a ij ]]>

[0076] Step 3: Construct a risk level assessment model based on the multi-dimensional influencing factor system and historical substation flood prevention experience;

[0077] In step 3, you can use method 1:

[0078] Set rating standards for each indicator, use a Bayesian algorithm model based on machine learning to rate each indicator, and combine the indicator rating weights set based on the impact on the flood control capabilities of power grid equipment and facilities to build a risk level assessment model and achieve dynamic risk rating.

[0079] Figure 3 The input is the level index of the factors affecting the flood situation of the substation, and the output is the flood control risk level of the substation.

[0080] Method 2: Based on membership analysis, entropy method and hierarchical analysis method, a multi-influence evaluation model for flood control of power grid equipment and facilities is obtained as a risk level evaluation model. Specifically:

[0081] Step 3.1: Set up an evaluation index system based on substation flood influencing factors, including: the first-level index is u i =(i=1,2,3), the secondary index of disaster-prone environment is u 1j =(j=1,2,3,4,5); the secondary index of the disaster factor is u 2j =(j=1,2,3); the secondary index of the carrier is u 3j =(j=1,2,3), construct a fuzzy evaluation state set.

[0082] Step 3.2: Construct a flood control capability evaluation set V = (V1, V2, V3), which represents safety, general, and abnormal respectively.

[0083] Step 3.3: Refer to the objective factor data such as the power grid safety manual, substation construction specifications, and equipment performance indicators, and normalize the indicators at all levels in combination with subjective factors.

[0084] Step 3.4: For qualitative data such as topography, hydrological conditions, and vegetation conditions, use numbers between 0 and 1 as quantitative scores to quantify the qualitative data.

[0085] The smaller the value, the worse the performance of the indicator; the larger the value, the better the performance of the indicator.

[0086] The formula is as follows:

[0087] For indicators with larger values, the formula is:

[0088] For indicators where smaller is better,

[0089] Where: are the maximum and minimum values ​​of the jth indicator respectively;

[0090] x i ' j is x ij Normalized value.

[0091] Step 3.5: Set the membership function and weight of each indicator, and construct a multi-influence assessment model for flood control of power grid equipment and facilities as a risk level assessment model.

[0092] For indicators with larger values, the better, if a substation A t (t=1,2,…,N) About flood control capability level Vk (k=1,2,3)The larger the better the quantitative index u ij The actual value of y tij Not less than this index at level V k The standard value under the Gauss membership function is adopted, and its membership function is: Where: f(x,σ,c) is the membership function; x is the decision indicator; σ and c are the two parameters of the Gauss membership function, and σ is 0.3.

[0093] Method 3: Combination and correction of method 1 and method 2.

[0094] Step 4: Obtain the area of ​​the substation to be evaluated and obtain the actual flood influencing factor data according to the multi-dimensional influencing factor evaluation system;

[0095] Step 5: Input the data of actual flood situation influencing factors into the risk level assessment model to obtain the preliminary risk assessment level and make preliminary deployment of flood control materials;

[0096] Step 6: The area of ​​the substation to be evaluated and the data of the factors affecting the actual flood situation are input into the numerical quantification model of the area and safe water depth to obtain the real-time safe operation water depth of the substation equipment;

[0097] Step 7: Calculate the precipitation of the substation based on the area of ​​the substation to be evaluated and the actual flood influencing factors, and calculate the real-time water accumulation depth of the substation based on the storage capacity and drainage capacity of the substation;

[0098] The calculation formula for substation precipitation is:

[0099] Q1=S·h1

[0100] Q1 is the precipitation volume of the substation, unit: m 3 ;

[0101] S is the area of ​​the substation, unit: m 2 ;

[0102] h1 is the actual monitoring data of precipitation, unit: m.

[0103] The calculation formula for substation water storage capacity Q2 and substation discharge capacity Q3 is:

[0104] Q2=A·B·L

[0105] Q3=V·H

[0106] Where A is the length of the water storage tank, unit: m;

[0107] B is the width of the water storage tank, unit: m;

[0108] L is the height of the water storage tank, unit: m;

[0109] V is the drainage pump flow rate, unit: m 3 / H;

[0110] H is the working time of the drainage pump, unit: hour.

[0111] The calculation formula for the real-time water depth of the substation is:

[0112] h2=Q4 / S / 1000

[0113] h2 is the actual water depth in the station, unit: mm;

[0114] Q4 is the actual water volume of the substation in real time, unit: m 3 ;

[0115] Q4=Q1-Q2-Q3

[0116] Q4 is the actual water volume of the substation in real time, unit: m 3 ;

[0117] S is the area of ​​the substation, unit: m 2 .

[0118] Step 8: Compare the real-time water accumulation depth of the substation with the safe operation water accumulation depth of the substation equipment obtained in step 6 to evaluate the flood control capability of the substation.

[0119] During the specific implementation, the power grid remote control center platform compares the real-time water accumulation depth of the substation with the safe operation water accumulation depth of the substation equipment obtained in step 6, evaluates the flood prevention capacity of the substation, and carries out flood prevention based on the initially allocated flood prevention materials.

[0120] Furthermore, when the material reserves in the station are insufficient to cope with the situation, that is, when the actual water depth in the station reaches a certain threshold, an emergency request for help is sent through the front end of the substation to the back end power grid flood control system, thereby achieving rapid deployment of flood control materials.

[0121] The applicant of the present invention has made a detailed explanation and description of the implementation examples of the present invention in conjunction with the drawings in the specification. However, those skilled in the art should understand that the above implementation examples are only preferred implementation schemes of the present invention, and the detailed description is only to help readers better understand the spirit of the present invention, but not to limit the scope of protection of the present invention. On the contrary, any improvements or modifications based on the inventive spirit of the present invention should fall within the scope of protection of the present invention.

Claims

1. A method for evaluating substation flood control capability based on real-time data, characterized in that: The method comprises the following steps: Step 1: Classify the factors affecting the flood situation of substations and establish a multi-dimensional influencing factor system. Specifically: The factors affecting the flood situation of substations are divided into disaster-prone environmental factors, disaster-causing factors, and disaster-bearing body factors; The disaster-prone environmental factors include climate conditions, topography, soil and vegetation, hydrological conditions, and potential risks of mountain torrents and mud-rock flows; The disaster-causing factors include precipitation, temperature, and wind speed; The disaster-bearing body factors include voltage level, drainage and water storage capacity within the facility, and the amount of flood control material reserves; Step 2: Obtain data on different substation footprints and safe water depth for substation equipment operation, and establish a numerical quantitative model of footprint and safe water depth based on a multi-dimensional influencing factor system based on the influencing factors in step 1. Specifically: By installing water pressure and water level sensors in the substation to monitor the safe operation water depth of substation equipment under different substations and influencing factors, combined with the corresponding substation area and influencing factors, according to the membership theory of fuzzy mathematics, the qualitative evaluation is converted into a quantitative evaluation, and a quantitative conversion model of qualitative description is established. In combination with expert experience, each influencing factor is scored, and fuzzy evaluation, entropy analysis and other methods are used to obtain a numerical quantitative model of the area and safe water depth based on a multi-dimensional influencing factor system. Step 3: Based on the multi-dimensional influencing factor system and historical substation flood prevention experience, a risk level assessment model is constructed. Specifically: Based on the membership analysis, entropy method and analytic hierarchy process, a multi-influencing evaluation model for flood control of power grid equipment and facilities is obtained as a risk level evaluation model. Specifically: Step 3.1: Set up an evaluation index system based on substation flood influencing factors, including: the first-level index is u i =(i=1,2,3), secondary index of disaster-prone environment; secondary index of carrier, construct fuzzy evaluation state set; Step 3.2: Construct a flood control capability evaluation set V = (V1, V2, V3), which represents safety, general, and abnormal respectively; Step 3.3: Normalize the indicators at all levels; Step 3.4: Quantify the qualitative data; Step 3.5: Set the membership function and weight of each indicator, and construct a multi-influencing evaluation model for flood control of power grid equipment and facilities as a risk level evaluation model; Step 4: Obtain the area of ​​the substation to be evaluated and obtain the actual flood influencing factor data according to the multi-dimensional influencing factor evaluation system; Step 5: Input the data of actual flood situation influencing factors into the risk level assessment model to obtain the preliminary risk assessment level and make preliminary deployment of flood control materials; Step 6: The area of ​​the substation to be evaluated and the data of the factors affecting the actual flood situation are input into the numerical quantification model of the area and safe water depth to obtain the real-time safe operation water depth of the substation equipment; Step 7: Calculate the precipitation of the substation based on the area of ​​the substation to be evaluated and the actual flood influencing factors, and calculate the real-time water accumulation depth of the substation based on the storage capacity and drainage capacity of the substation; Step 8: Compare the real-time water accumulation depth of the substation with the safe operation water accumulation depth of the substation equipment obtained in step 6 to evaluate the flood control capability of the substation.

2. The method for evaluating the flood control capability of a substation based on real-time data according to claim 1, characterized in that: The water level sensor is installed in the cable trench in the station, 50 to 100 cm above the ground.

3. The method for evaluating the flood control capability of a substation based on real-time data according to claim 1 is characterized in that: In step 3, the rating standards for each indicator are set, and the Bayesian algorithm model based on machine learning is used to rate each indicator. Combined with the indicator rating weights set based on the impact on the flood control capacity of power grid equipment and facilities, a risk level assessment model is constructed to achieve dynamic risk rating.

4. The method for evaluating the flood control capability of a substation based on real-time data according to claim 1 is characterized in that: In step 3.4, the qualitative data is quantified using numbers between 0 and 1 as quantitative scores.

5. The method for evaluating the flood control capability of a substation based on real-time data according to claim 1, characterized in that: In step 7, the calculation formula for substation precipitation is: Q1=S·h1 Q1 is the precipitation volume of the substation, unit: m 3 ; S is the area of ​​the substation, unit: m 2 ; h1 is the actual monitoring data of precipitation, unit: m; The calculation formula for substation water storage capacity Q2 and substation discharge capacity Q3 is: Q2=A·B·L Q3=V·H Where A is the length of the water storage tank, unit: m; B is the width of the water storage tank, unit: m; L is the height of the water storage tank, unit: m; V is the drainage pump flow rate, unit: m 3 / H; H is the working time of the drainage pump, unit: hour; The calculation formula for the real-time water depth of the substation is: h2=Q4 / S / 1000 h2 is the actual water depth in the station, unit: mm; Q4 is the actual water volume of the substation in real time, unit: m 3 ; Q4=Q1-Q2-Q3 Q4 is the actual water volume of the substation in real time, unit: m 3 ; S is the area of ​​the substation, unit: m 2 .

6. The method for evaluating the flood control capability of a substation based on real-time data according to claim 1, characterized in that: In step 8, the power grid remote control center platform compares the real-time water depth of the substation with the safe operation water depth of the substation equipment obtained in step 6, evaluates the flood prevention capacity of the substation, and carries out flood prevention based on the initially allocated flood prevention materials.

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