Method for evaluating toughness of wind-light power generation system in case of multiple wind-light extreme events

Abstract

A method for evaluating toughness of a wind-light power generation system in case of encountering a plurality of wind-light extreme events comprises the following steps: step 1, determining encountering stages of two extreme events by simulating operation processes of the wind-light power generation system in case of encountering water in different time periods of the two extreme events; step 2, according to different encounter stages of the two extreme events, carrying out toughness index quantification on a resisting stage, an adapting stage and a recovering stage of the water-wind-light power generation system; and step 3, performing comprehensive toughness evaluation on the water-wind-light power generation system in the stage encountering two extreme events. According to the method, encountering of a single extreme event or multiple extreme events in different stages is quantified, toughness quantification of output exceeding the load demand of the water-wind-light power generation system is considered according to resource characteristics and output limitation, reference is provided for toughness quantification of the water-wind-light power generation system, and the method has certain popularization value.

Description

Technical Field

[0001] The present invention relates to the field of power system resilience assessment, and in particular to a method for assessing the resilience of a wind-solar power generation system encountering multiple wind-solar extreme events. Background Art

[0002] With the formulation of the "carbon peak and carbon neutrality" goals, a high proportion of new energy has become a prominent feature of the future development of the power system. The water, wind and solar power generation system formed by the coordinated operation of hydropower, wind power and photovoltaics can effectively alleviate the impact of new energy on the grid. Water, wind and light are natural resources and are more susceptible to environmental impacts. In recent years, affected by climate change, extreme weather such as high temperatures, blizzards and heavy rains have occurred frequently, and the stable operation of water, wind and solar power generation systems has ushered in severe challenges. Resilience is one of the key indicators to measure the stable operation performance of a power system under the impact of extreme events. The stronger the resilience of the water, wind and solar power generation system, the stronger the extreme events such as high temperatures, blizzards and heavy rains that it can withstand; therefore, it is particularly important to quantify the resilience of the water, wind and solar power generation system.

[0003] Therefore, it is necessary to design a method for assessing the resilience of wind-solar power generation systems under multiple wind-solar extreme events to overcome the above problems. Summary of the invention

[0004] In order to avoid the above problems, a method for assessing the resilience of wind and solar power generation systems encountering multiple wind and solar extreme events is provided. The method has simple structure, convenient operation, flexibility and practicality, and can accurately detect the size and location of lesions, providing better preparation and more accurate basis for subsequent treatment.

[0005] The present invention provides a method for assessing the resilience of a wind-solar power generation system when multiple wind-solar extreme events occur, comprising the following steps:

[0006] Step 1, by simulating the operation process of the hydropower generation system encountered by two extreme events at different time periods, determine the encounter stages of the two extreme events;

[0007] Step 2: According to the different encounter stages of the two extreme events, the resilience indicators of the hydropower, wind and solar power generation systems are quantified in the resistance stage, adaptation stage and recovery stage;

[0008] Step 3: Conduct a comprehensive resilience assessment of the hydropower, wind and solar power generation systems during the period of encountering two extreme events.

[0009] Preferably, resilience is evaluated in the resistance stage, adaptation stage, and recovery stage through vulnerability, robustness, and recovery, respectively.

[0010] Preferably, the period from the occurrence of an extreme event to the restoration of the hydro-wind-solar power generation system to normal is divided into a resistance stage, an adaptation stage and a recovery stage according to the change of the absolute deviation percentage complement; wherein the absolute deviation percentage complement calculation formula is:

[0011]

[0012] Where |η| is the complement of the absolute deviation percentage, output is the output of the hydro-wind-solar power generation system, and load is the load.

[0013] Preferably, the resistance phase is a phase in which the absolute deviation percentage complement is reduced, the adaptation phase is a phase in which the absolute deviation percentage complement remains unchanged, and the recovery phase is a phase in which the absolute deviation percentage complement is increased.

[0014] Preferably, when a second extreme event occurs during the resistance phase of the first extreme event, the resilience assessment includes the following specific steps:

[0015] a. Resistance stage t1-t2: The first extreme event occurs at time t1, and then the absolute deviation percentage complement of the hydropower generation system starts to decrease from |η|0. During the decrease, it encounters the second extreme event, and the absolute deviation percentage complement continues to decrease, reaching the minimum at time t2 |η| m , the vulnerability is measured as follows:

[0016] R F =|η|0-|η| m ,

[0017] ΔR F =|η| m / |η|0;

[0018] Where |η|0 is the complement of the absolute deviation percentage at the initial time t1, |η| m is the complement of the absolute deviation percentage at time t2, R F is the absolute value of vulnerability. The larger the value, the more vulnerable the system is. F is the relative value of vulnerability, ranging from [0,1]. The smaller the value, the more vulnerable the system is.

[0019] b. Adaptation stage t2-t3: At t2, the absolute deviation percentage complement of the hydro-wind-solar power generation system drops to the minimum |η| m , and continues until time t3, the robustness measure is as follows:

[0020]

[0021] Where |η| t is the complement of the absolute deviation percentage at a certain time t, R Ris the absolute value of robustness. The larger the value, the stronger the system robustness. R is the relative value of robustness, ranging from [0,1]. The larger the value, the stronger the system robustness.

[0022] c. Recovery phase t3-t4: The system starts to recover at t3 and returns to normal operation at t4. The recovery is measured as follows:

[0023] R RP =t4-t3,

[0024] ΔR RP =1-(t4-t3) / (t4-t1);

[0025] In the formula, R RP is the absolute value of recovery. The smaller the value, the shorter the system recovery time, that is, the stronger the recovery. RP It is the relative value of recovery, and its value range is [0,1]. The larger the value is, the smaller the ratio of system recovery time to the entire extreme event duration is, that is, the stronger the recovery is.

[0026] Preferably, when a second extreme event occurs during the adaptation phase of the first extreme event, the resilience assessment includes the following specific steps:

[0027] a. Resistance stage t1~t2,t1 ′ ~t2 ′ :The first extreme event occurs at time t1, and then the absolute deviation percentage complement of the hydropower generation system starts to decrease from |η|0, and reaches a certain value at time t2, entering the adaptation stage. In the adaptation stage t1 ′ When the second extreme event occurs at time t2, the absolute deviation percentage complement continues to decrease. ′ The moment drops to the minimum |η| m , the vulnerability is measured as follows:

[0028] R F =|η|0-|η| m ,

[0029] ΔR F =|η| m / |η|0;

[0030] Where |η|0 is the complement of the absolute deviation percentage at the initial time t0, |η| m t2 ′ The complement of the absolute deviation percentage at the moment, R F is the absolute value of vulnerability. The larger the value, the more vulnerable the system is. Fis the relative value of vulnerability, ranging from [0,1]. The smaller the value, the more vulnerable the system is.

[0031] b. Adaptation stage t2~t1 ′ ,t2 ′ ~t3: Absolute deviation percentage complement t2 in the defense phase ′ At this moment, the value drops to the minimum and lasts until t3. The robustness measure is as follows:

[0032]

[0033] Where |η| t is the complement of the absolute deviation percentage at a certain time t, R R is the absolute value of robustness. The larger the value, the stronger the system robustness. R is the relative value of robustness, ranging from [0,1]. The larger the value, the stronger the system robustness.

[0034] c. Recovery phase t3-t4: The system starts to recover at t3 and returns to normal operation at t4. The recovery is measured as follows:

[0035] R RP =t4-t3,

[0036] ΔR RP =1-(t4-t3) / (t4-t1);

[0037] In the formula, R RP is the absolute value of recovery. The smaller the value, the shorter the system recovery time, that is, the stronger the recovery. RP It is the relative value of recovery, and its value range is [0,1]. The larger the value is, the smaller the ratio of system recovery time to the entire extreme event duration is, that is, the stronger the recovery is.

[0038] Preferably, when a second extreme event occurs during the recovery phase of the first extreme event, the resilience assessment includes the following specific steps:

[0039] a. Resistance stage t1~t2,t1 ′ ~t2 ′ :The first extreme event occurs at time t1, and then the absolute deviation percentage complement of the hydropower generation system starts to decrease from |η|0, and reaches a certain value at time t2, entering the adaptation stage. At time t3, the system begins to recover. In the recovery stage t1 ′ When the second extreme event occurs at time t2, the absolute deviation percentage complement continues to decrease. ′ The moment drops to the minimum |η| m , the vulnerability is measured as follows:

[0040] R F =|η|0-|η| m ,

[0041] ΔR F =|η| m / |η|0;

[0042] Where |η|0 is the complement of the absolute deviation percentage at the initial time t0, |η| m t2 ′ The complement of the absolute deviation percentage at the moment, R F is the absolute value of vulnerability. The larger the value, the more vulnerable the system is. F is the relative value of vulnerability, ranging from [0,1]. The smaller the value, the more vulnerable the system is.

[0043] b. Adaptation stage t2~t3,t2 ′ ~t ′ 3: When t2 drops to a certain value, the system enters the adaptation phase. At t3, the system begins to recover. ′ The moment drops to the minimum |η| m , enter the adaptation phase again, t ′ At time 3, the system starts to recover again, and the robustness is measured as follows:

[0044]

[0045] Where |η| t is the complement of the absolute deviation percentage at a certain time t, R R is the absolute value of robustness. The larger the value, the stronger the system robustness. R is the relative value of robustness, ranging from [0,1]. The larger the value, the stronger the system robustness.

[0046] c. Recovery phase t3~t1 ′ ,t ′ 3~t4: At t3, the system starts to recover and enters the recovery phase. In the recovery phase t1 ′ The second extreme event is always encountered, t ′ At time t3, the system starts to recover again, and returns to normal operation at time t4. The measure of recovery is as follows:

[0047] R RP =(t4-t ′ 3)+(t1 ′ -t3),

[0048] ΔR RP =1-((t4-t ′ 3)+(t1 ′-t3)) / (t4-t1);

[0049] In the formula, R RP is the absolute value of recovery. The smaller the value, the shorter the system recovery time, that is, the stronger the recovery. RP It is the relative value of recovery, and its value range is [0,1]. The larger the value is, the smaller the ratio of system recovery time to the entire extreme event duration is, that is, the stronger the recovery is.

[0050] Preferably, the resilience of the hydro-wind-solar power generation system is comprehensively evaluated, and a weighted method is used to calculate the specific value of the resilience of the hydro-wind-solar power generation system as a whole, as shown below:

[0051] R=ω F ×ΔR F +ω R ×ΔR R +ω RP ×ΔR RP ;

[0052] In the formula, ω F is the vulnerability weight, ω R is the robustness weight, ω RP is the weight of recovery, and R is the comprehensive evaluation value of resilience. The larger the value is, the stronger the resilience of the system is.

[0053] Compared with the prior art, the present invention has the following beneficial effects: the present invention is mainly used for quantifying the resilience of water, wind and solar power generation systems when multiple extreme events occur, wherein the absolute deviation percentage complement is used as the resilience index, and a comprehensive evaluation is performed from the resistance stage, adaptation stage and recovery stage to quantitatively characterize the resilience of water, wind and solar power generation systems; compared with traditional quantitative resilience characterization, from the perspective of quantitative characterization method, the present invention combines staged quantification of resilience with comprehensive evaluation to quantitatively characterize the resilience of water, wind and solar power generation systems; from the perspective of extreme events considered, the present invention considers the quantitative characterization of the resilience of water, wind and solar power generation systems when multiple extreme events occur. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is a schematic diagram of the overall process of a preferred embodiment of the present invention;

[0055] Figure 2 It is a schematic diagram of the absolute deviation percentage complement process of a hydro-wind-solar power generation system under a single extreme event in a preferred embodiment of the present invention;

[0056] Figure 3 It is a schematic diagram of the absolute deviation percentage complement process of the hydro-wind-solar power generation system when encountering two extreme events in the resistance stage according to a preferred embodiment of the present invention;

[0057] Figure 4It is a schematic diagram of the absolute deviation percentage complement process of the hydro-wind-solar power generation system when encountering two extreme events in the adaptation stage according to a preferred embodiment of the present invention;

[0058] Figure 5 It is a schematic diagram of the absolute deviation percentage complement process of the hydro-wind-solar power generation system when encountering two extreme events in the recovery phase according to a preferred embodiment of the present invention;

[0059] Figure 6 This is a schematic diagram of the power output process of a hydro-wind-solar power generation system when encountering two extreme events in the recovery phase of a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be described below in conjunction with the embodiments of the present invention and the accompanying drawings.

[0061] like Figure 1 As shown, a method for assessing the resilience of a wind-solar power generation system when multiple wind-solar extreme events occur includes the following steps:

[0062] Step 1, by simulating the operation process of the hydropower generation system encountered by two extreme events at different time periods, determine the encounter stages of the two extreme events;

[0063] Step 2: According to the different encounter stages of the two extreme events, the resilience indicators of the hydropower, wind and solar power generation systems are quantified in the resistance stage, adaptation stage and recovery stage;

[0064] Step 3: Conduct a comprehensive resilience assessment of the hydropower, wind and solar power generation systems during the period of encountering two extreme events.

[0065] Among them, the period from the occurrence of extreme events to the restoration of the hydropower generation system to normal is divided into the resistance stage, the adaptation stage and the recovery stage according to the change of the absolute deviation percentage complement; the calculation formula of the absolute deviation percentage complement is:

[0066]

[0067] Where |η| is the complement of the absolute deviation percentage, output is the output of the hydro-wind-solar power generation system, and load is the load.

[0068] The resilience of the resistance stage, adaptation stage, and recovery stage is evaluated through vulnerability, robustness, and recovery, respectively. The process of absolute deviation percentage complementation from the occurrence of a single extreme event to the restoration of the hydropower generation system to normal is divided into three stages: resistance, adaptation, and recovery. The characterization of resilience in each stage can be quantitatively characterized by vulnerability, robustness, and recovery. The quantification of the resilience of the hydropower generation system encountering two extreme events is based on a single extreme event.

[0069] Specifically, the defense phase is the phase where the absolute deviation percentage complement decreases, the adaptation phase is the phase where the absolute deviation percentage complement remains unchanged, and the recovery phase is the phase where the absolute deviation percentage complement increases. There are three specific situations:

[0070] Scenario 1: When a second extreme event occurs during the first extreme event resistance phase, resilience assessment includes the following specific steps:

[0071] a. Resistance stage t1-t2: The first extreme event occurs at time t1, and then the absolute deviation percentage complement of the hydropower generation system starts to decrease from |η|0. During the decrease, it encounters the second extreme event, and the absolute deviation percentage complement continues to decrease, reaching the minimum at time t2 |η| m , the vulnerability is measured as follows:

[0072] R F =|η|0-|η| m ,

[0073] ΔR F =|η| m / |η|0;

[0074] Where |η|0 is the complement of the absolute deviation percentage at the initial time t1, |η| m is the complement of the absolute deviation percentage at time t2, R F is the absolute value of vulnerability. The larger the value, the more vulnerable the system is. F is the relative value of vulnerability, ranging from [0,1]. The smaller the value, the more vulnerable the system is.

[0075] b. Adaptation stage t2-t3: At t2, the absolute deviation percentage complement of the hydro-wind-solar power generation system drops to the minimum |η| m , and continues until time t3, the robustness measure is as follows:

[0076]

[0077] Where |η| t is the complement of the absolute deviation percentage at a certain time t, R R is the absolute value of robustness. The larger the value, the stronger the system robustness. R is the relative value of robustness, ranging from [0,1]. The larger the value, the stronger the system robustness.

[0078] c. Recovery phase t3-t4: The system starts to recover at t3 and returns to normal operation at t4. The recovery is measured as follows:

[0079] R RP =t4-t3,

[0080] ΔR RP =1-(t4-t3) / (t4-t1);

[0081] In the formula, R RP is the absolute value of recovery. The smaller the value, the shorter the system recovery time, that is, the stronger the recovery. RP It is the relative value of recovery, and its value range is [0,1]. The larger the value is, the smaller the ratio of system recovery time to the entire extreme event duration is, that is, the stronger the recovery is.

[0082] Scenario 2: When a second extreme event occurs during the adaptation phase of the first extreme event, resilience assessment includes the following specific steps:

[0083] a. Resistance stage t1~t2,t1 ′ ~t2 ′ :The first extreme event occurs at time t1, and then the absolute deviation percentage complement of the hydropower generation system starts to decrease from |η|0, and reaches a certain value at time t2, entering the adaptation stage. In the adaptation stage t1 ′ When the second extreme event occurs at time t2, the absolute deviation percentage complement continues to decrease. ′ The moment drops to the minimum |η| m , the vulnerability is measured as follows:

[0084] R F =|η|0-|η| m ,

[0085] ΔR F =|η| m / |η|0;

[0086] Where |η|0 is the complement of the absolute deviation percentage at the initial time t0, |η| m t2 ′ The complement of the absolute deviation percentage at the moment, R F is the absolute value of vulnerability. The larger the value, the more vulnerable the system is. F is the relative value of vulnerability, ranging from [0,1]. The smaller the value, the more vulnerable the system is.

[0087] b. Adaptation stage t2~t1 ′ ,t2 ′ ~t3: The first extreme event enters the resistance phase from t2 and lasts until t1 ′ , encountering the second extreme event and entering the defense stage for the second time, the absolute deviation percentage complement t2 ′ At this moment, the value drops to the minimum and lasts until t3. The robustness measure is as follows:

[0088]

[0089] Where |η| t is the complement of the absolute deviation percentage at a certain time t, R R is the absolute value of robustness. The larger the value, the stronger the system robustness. R is the relative value of robustness, ranging from [0,1]. The larger the value, the stronger the system robustness.

[0090] c. Recovery phase t3-t4: The system starts to recover at t3 and returns to normal operation at t4. The recovery is measured as follows:

[0091] R RP =t4-t3,

[0092] ΔR RP =1-(t4-t3) / (t4-t1);

[0093] In the formula, R RP is the absolute value of recovery. The smaller the value, the shorter the system recovery time, that is, the stronger the recovery. RP It is the relative value of recovery, and its value range is [0,1]. The larger the value is, the smaller the ratio of system recovery time to the entire extreme event duration is, that is, the stronger the recovery is.

[0094] Scenario 3: When a second extreme event occurs during the recovery phase of the first extreme event, the resilience assessment includes the following specific steps:

[0095] a. Resistance stage t1~t2,t1 ′ ~t2 ′ :The first extreme event occurs at time t1, and then the absolute deviation percentage complement of the hydropower generation system starts to decrease from |η|0, and reaches a certain value at time t2, entering the adaptation stage. At time t3, the system begins to recover. In the recovery stage t1 ′ When the second extreme event occurs at time t2, the absolute deviation percentage complement continues to decrease. ′ The moment drops to the minimum |η| m , the vulnerability is measured as follows:

[0096] R F =|η|0-|η| m ,

[0097] ΔR F =|η| m / |η|0;

[0098] Where |η|0 is the complement of the absolute deviation percentage at the initial time t0, |η| m t2′ The complement of the absolute deviation percentage at the moment, R F is the absolute value of vulnerability. The larger the value, the more vulnerable the system is. F is the relative value of vulnerability, ranging from [0,1]. The smaller the value, the more vulnerable the system is.

[0099] b. Adaptation stage t2~t3,t2 ′ ~t ′ 3: When t2 drops to a certain value, the system enters the adaptation phase. At t3, the system begins to recover. ′ The moment drops to the minimum |η| m , enter the adaptation phase again, t ′ At time 3, the system starts to recover again, and the robustness is measured as follows:

[0100]

[0101] Where |η| t is the complement of the absolute deviation percentage at a certain time t, R R is the absolute value of robustness. The larger the value, the stronger the system robustness. R is the relative value of robustness, ranging from [0,1]. The larger the value, the stronger the system robustness.

[0102] c. Recovery phase t3~t1 ′ ,t ′ 3~t4: At t3, the system starts to recover and enters the recovery phase. In the recovery phase t1 ′ The second extreme event is always encountered, t ′ At time t3, the system starts to recover again, and returns to normal operation at time t4. The measure of recovery is as follows:

[0103] R RP =(t4-t ′ 3)+(t1 ′ -t3),

[0104] ΔR RP =1-((t4-t ′ 3)+(t1 ′ -t3)) / (t4-t1);

[0105] In the formula, R RP is the absolute value of recovery. The smaller the value, the shorter the system recovery time, that is, the stronger the recovery. RP It is the relative value of recovery, and its value range is [0,1]. The larger the value is, the smaller the ratio of system recovery time to the entire extreme event duration is, that is, the stronger the recovery is.

[0106] Finally, the resilience of the hydropower, wind and solar power generation system is comprehensively evaluated, and the specific value of the resilience of the hydropower, wind and solar power generation system is calculated as a whole using a weighted method, as shown below:

[0107] R=ω F ×ΔR F +ω R ×ΔR R +ω RP ×ΔR RP ;

[0108] In the formula, ω F is the vulnerability weight, ω R is the robustness weight, ω RP is the weight of recovery, and R is the comprehensive evaluation value of resilience. The larger the value is, the stronger the resilience of the system is.

[0109] like Figure 1-6 As shown, the embodiment of the present invention provides a method for quantitatively characterizing the resilience of a hydropower wind-solar power generation system under multiple extreme events using the deviation percentage complement based on the quantitative characterization of the resilience of a single extreme event. The absolute deviation percentage complement process of the hydropower wind-solar power generation system under a single extreme event is as follows Figure 2 shown.

[0110] Taking two extreme events as an example, the encounter may occur in the resistance, adaptation or recovery stage, such as Figure 3 , 4 , 5. The present invention takes two extreme events in the recovery phase as an example to illustrate. Figure 6 It can be seen that when the second extreme event occurs during the recovery phase of the first extreme event, the system will go through the three stages of resistance, adaptation, and recovery again, and finally return to the normal operation phase. The difference is that its recovery time is divided into two parts. The specific steps are as follows:

[0111] a. Defense phase (9:00-10:00, 12:00-13:00): Figure 6 It can be seen that the period from 9 to 10 is the resistance stage of the first extreme event, and the period from 12 to 13 is the resistance stage of the second extreme event. At 9 o'clock (in hours), the wind power output of the hydro-wind-solar power generation system dropped sharply, and the absolute deviation percentage complement began to decrease from 100%. Then the hydro-wind-solar power generation system resisted, and it dropped to 88.8% at 10 o'clock. At 12 o'clock, the photovoltaic output increased sharply, causing the hydro-wind-solar power generation system to exceed the load demand, which also posed a certain threat to the stability of the system. At this time, it dropped to a minimum of 87.1% at 13 o'clock. The vulnerability measurement is as follows:

[0112] R F1 =100-88.8=11.2,

[0113] ΔR F1 =88.8 / 100=0.888,

[0114] R F2 =100-87.1=12.9,

[0115] ΔR F2 =87.1 / 100=0.871;

[0116] b. Adaptation stage (10:00-11:00, 13:00-14:00): 10:00-11:00 is the adaptation stage of the first extreme event, and 13:00-14:00 is the adaptation stage of the second extreme event. At 10:00, the hydro-wind-solar power generation system entered the adaptation stage, and at 11:00, the system's absolute deviation percentage complement dropped to 89.2%. When encountering the second extreme event, at 13:00, the absolute deviation percentage complement of the hydro-wind-solar power generation system in the second adaptation stage dropped to a lower level, and the absolute deviation percentage complement was 86.3% and lasted until 14:00. This stage reflects the robustness of the hydro-wind-solar power generation system, and its measurement is as follows:

[0117]

[0118] ΔR R1 =89.2 / 100=0.892,

[0119]

[0120] ΔR R2 =86.3 / 100=0.863,

[0121] c. Recovery phase (11:00-12:00, 14:00-16:00): 11:00-12:00 is the recovery phase of the first extreme event, and 14:00-16:00 is the recovery phase of the second extreme event. The recovery metrics are as follows:

[0122] R RP1 =12-11=1,

[0123] R RP2 =19-14=5,

[0124] R RP′ =1+5=6,

[0125] ΔR RP′ =1-6 / 10=0.4,

[0126] Comprehensive evaluation (9:00-16:00), such as Figure 6As shown, the sum of the two extreme events in the entire stage is controlled to be 1. According to empirical settings, the weights of the resistance stage 2, adaptation stage 2, and recovery stage are given as 0.4, 0.3, and 0.4 respectively.

[0127] R ′ =0.4×0.871+0.3×0.863+0.4×0.4=0.77

[0128] In summary, in this embodiment, single extreme events and multiple extreme events encountered at different stages are quantified respectively, and the occurrence of extreme weather, the sharp increase in wind and solar power output, the minimum output limit of the hydro-wind-solar power generation system, and the resilience quantification of the hydro-wind-solar power generation system output exceeding the load demand are taken into account, which provides a reference for the quantification of the resilience of the hydro-wind-solar power generation system.

[0129] The overall process diagram of the present invention is as follows Figure 1 shown.

[0130] The present invention is mainly applied to the resilience of water, wind and solar power generation systems under extreme events, wherein the complement of the absolute deviation percentage is used as a resilience index to quantitatively characterize the resilience of water, wind and solar power generation systems from the resistance stage, adaptation stage, recovery stage and comprehensive evaluation. According to the above example calculation, compared with a single extreme event, multiple extreme events are encountered at different stages, making the water, wind and solar power generation system more fragile and less robust, and according to a comprehensive evaluation, the resilience of the entire system is weaker. The present invention quantifies the occurrence of single extreme events and multiple extreme events at different stages, and considers the quantification of the resilience of the water, wind and solar power generation system when the output exceeds the load demand based on resource characteristics and output limitations, which provides a reference for the quantification of the resilience of the water, wind and solar power generation system and has certain promotion value.

[0131] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for assessing the resilience of a wind-solar power generation system when multiple wind-solar extreme events occur, characterized in that: The steps include: Step 1, by simulating the operation process of the hydropower generation system encountered by two extreme events at different time periods, determine the encounter stages of the two extreme events; Step 2: According to the different encounter stages of the two extreme events, the resilience indicators of the hydropower, wind and solar power generation systems are quantified in the resistance stage, adaptation stage and recovery stage; Step 3: Conduct a comprehensive resilience assessment of the hydropower, wind and solar power generation systems during the period of encountering two extreme events.

2. The method for assessing the resilience of a wind-solar power generation system when multiple wind-solar extreme events occur as claimed in claim 1, characterized in that: Resilience is assessed in the defense stage, adaptation stage, and recovery stage through vulnerability, robustness, and recovery, respectively.

3. The method for assessing the resilience of a wind-solar power generation system under multiple wind-solar extreme events as claimed in claim 1, characterized in that: The period from the occurrence of an extreme event to the restoration of the hydropower, wind and solar power generation system to normal is divided into the resistance stage, the adaptation stage and the recovery stage according to the change of the absolute deviation percentage complement; the calculation formula of the absolute deviation percentage complement is: Where |η| is the complement of the absolute deviation percentage, output is the output of the hydro-wind-solar power generation system, and load is the load.

4. The method for assessing the resilience of a wind-solar power generation system when multiple wind-solar extreme events occur as claimed in claim 3, characterized in that: The resistance stage is the stage where the absolute deviation percentage complement decreases, the adaptation stage is the stage where the absolute deviation percentage complement remains unchanged, and the recovery stage is the stage where the absolute deviation percentage complement increases.

5. The method for assessing the resilience of a wind-solar power generation system when multiple wind-solar extreme events occur as claimed in claim 3, characterized in that: When encountering a second extreme event during the first extreme event resistance phase, resilience assessment includes the following specific steps: a. Resistance stage t1-t2: The first extreme event occurs at time t1, and then the absolute deviation percentage complement of the hydropower generation system starts to decrease from |η|0. During the decrease, it encounters the second extreme event, and the absolute deviation percentage complement continues to decrease, reaching the minimum at time t2 |η| m , the vulnerability is measured as follows: R F =|η|0-|η| m , ΔR F =|η| m / |η|0; Where |η|0 is the complement of the absolute deviation percentage at the initial time t1, |η| m is the complement of the absolute deviation percentage at time t2, R F is the absolute value of vulnerability. The larger the value, the more vulnerable the system is. F is the relative value of vulnerability, ranging from [0,1]. The smaller the value, the more vulnerable the system is. b. Adaptation stage t2-t3: At t2, the absolute deviation percentage complement of the hydro-wind-solar power generation system drops to the minimum |η| m , and continues until time t3, the robustness measure is as follows: Where |η| t is the complement of the absolute deviation percentage at a certain time t, R R is the absolute value of robustness. The larger the value, the stronger the system robustness. R is the relative value of robustness, ranging from [0,1]. The larger the value, the stronger the system robustness. c. Recovery phase t3-t4: The system starts to recover at t3 and returns to normal operation at t4. The recovery is measured as follows: R RP =t4-t3, ΔR RP =1-(t4-t3) / (t4-t1); In the formula, R RP is the absolute value of recovery. The smaller the value, the shorter the system recovery time, that is, the stronger the recovery. RP It is the relative value of recovery, and its value range is [0,1]. The larger the value is, the smaller the ratio of system recovery time to the entire extreme event duration is, that is, the stronger the recovery is.

6. The method for assessing the resilience of a wind-solar power generation system when multiple wind-solar extreme events occur as claimed in claim 3, characterized in that: When encountering a second extreme event during the adaptation phase of the first extreme event, resilience assessment includes the following specific steps: a. Resistance stage t1~t2,t1 ′ ~t2 ′ :The first extreme event occurs at time t1, and then the absolute deviation percentage complement of the hydropower generation system starts to decrease from |η|0, and reaches a certain value at time t2, entering the adaptation stage. In the adaptation stage t1 ′ When the second extreme event occurs at time t2, the absolute deviation percentage complement continues to decrease. ′ The moment drops to the minimum |η| m , the vulnerability is measured as follows: R F =|η|0-|η| m , ΔR F =|η| m / |η|0; Where |η|0 is the complement of the absolute deviation percentage at the initial time t0, |η| m t2 ′ The complement of the absolute deviation percentage at the moment, R F is the absolute value of vulnerability. The larger the value, the more vulnerable the system is. F is the relative value of vulnerability, ranging from [0,1]. The smaller the value, the more vulnerable the system is. b. Adaptation stage t2~t1 ′ ,t2 ′ ~t3: Absolute deviation percentage complement t2 in the defense phase ′ At this moment, the value drops to the minimum and lasts until t3. The robustness measure is as follows: Where |η| t is the complement of the absolute deviation percentage at a certain time t, R R is the absolute value of robustness. The larger the value, the stronger the system robustness. R is the relative value of robustness, ranging from [0,1]. The larger the value, the stronger the system robustness. c. Recovery phase t3-t4: The system starts to recover at t3 and returns to normal operation at t4. The recovery is measured as follows: R RP =t4-t3, ΔR RP =1-(t4-t3) / (t4-t1); In the formula, R RP is the absolute value of recovery. The smaller the value, the shorter the system recovery time, that is, the stronger the recovery. RP It is the relative value of recovery, and its value range is [0,1]. The larger the value is, the smaller the ratio of system recovery time to the entire extreme event duration is, that is, the stronger the recovery is.

7. The method for assessing the resilience of a wind-solar power generation system under multiple wind-solar extreme events as claimed in claim 3, characterized in that: When encountering a second extreme event during the recovery phase of the first extreme event, resilience assessment includes the following specific steps: a. Resistance stage t1~t2,t1 ′ ~t2 ′ :The first extreme event occurs at time t1, and then the absolute deviation percentage complement of the hydropower generation system starts to decrease from |η|0, and reaches a certain value at time t2, entering the adaptation stage. At time t3, the system begins to recover. In the recovery stage t1 ′ When the second extreme event occurs at time t2, the absolute deviation percentage complement continues to decrease. ′ The moment drops to the minimum |η| m , the vulnerability is measured as follows: R F =|η|0-|η| m , ΔR F =|η| m / |η|0; Where |η|0 is the complement of the absolute deviation percentage at the initial time t0, |η| m t2 ′ The complement of the absolute deviation percentage at the moment, R F is the absolute value of vulnerability. The larger the value, the more vulnerable the system is. F is the relative value of vulnerability, ranging from [0,1]. The smaller the value, the more vulnerable the system is. b. Adaptation stage t2~t3,t2 ′ ~t ′ 3: When t2 drops to a certain value, the system enters the adaptation phase. At t3, the system starts to recover. ′ The moment drops to the minimum |η| m , enter the adaptation phase again, t ′ At time 3, the system starts to recover again, and the robustness is measured as follows: Where |η| t is the complement of the absolute deviation percentage at a certain time t, R R is the absolute value of robustness. The larger the value, the stronger the system robustness. R is the relative value of robustness, ranging from [0,1]. The larger the value, the stronger the system robustness. c. Recovery phase t3~t1 ′ ,t ′ 3~t4: At t3, the system starts to recover and enters the recovery phase. In the recovery phase t1 ′ The second extreme event is always encountered, t ′ At time t3, the system starts to recover again, and returns to normal operation at time t4. The measure of recovery is as follows: R RP =(t4-t ′ 3)+(t1 ′ -t3), ΔR RP =1-((t4-t ′ 3)+(t1 ′ -t3)) / (t4-t1); In the formula, R RP is the absolute value of recovery. The smaller the value, the shorter the system recovery time, that is, the stronger the recovery. RP It is the relative value of recovery, and its value range is [0,1]. The larger the value is, the smaller the ratio of system recovery time to the entire extreme event duration is, that is, the stronger the recovery is.

8. The method for assessing the resilience of a wind-solar power generation system under multiple wind-solar extreme events as claimed in any one of claims 5 to 7, characterized in that: Comprehensively evaluate the resilience of the hydropower, wind and solar power generation system, and use a weighted method to calculate the specific value of the resilience of the hydropower, wind and solar power generation system as a whole, as shown below: R=ω F ×ΔR F +oh R ×ΔR R +oh RP ×ΔR RP ; In the formula, ω F is the vulnerability weight, ω R is the robustness weight, ω RP is the weight of recovery, and R is the comprehensive evaluation value of resilience. The larger the value is, the stronger the resilience of the system is.

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