Evaluation method, device and equipment of power supply reliability and storage medium

Abstract

The invention discloses a power supply reliability assessment method and device, equipment and a storage medium, relates to the technical field of power supply management, and can improve the accuracy of power supply reliability assessment. According to the specific scheme, evaluation indexes of multiple dimensions corresponding to a to-be-evaluated power system are obtained, the evaluation indexes are used for evaluating the power supply reliability of the power system, and the dimensions comprise a power supply-demand relation, power market stability, energy safety and environmental factors; determining a target weight of each evaluation index by using a preset entropy weight method, a CRITIC method and a standard deviation method; according to each evaluation index, the target weight of each evaluation index and a preset TOPSIS comprehensive evaluation method, evaluating reliability results of power supply of each power system under different operation days; and based on a preset grading rule and the reliability result, determining the reliability level of the power supply of each power system under different operation days.

Description

Technical Field

[0001] The present application relates to the technical field of power supply management, and in particular to a method, device, equipment and storage medium for evaluating power supply reliability. Background Art

[0002] With the rapid economic development and the continuous growth of electricity demand, power supply has become an important task, and the construction of a power supply reliability evaluation system is one of the important means to achieve this goal. Power supply reliability is an important way to evaluate the power supply guarantee capability and power market risks. It reflects the operation and risk level of the power market by comprehensively considering multiple factors such as power supply and demand balance, market stability, energy security, and power purchase and sales. The construction of a power supply reliability evaluation system can effectively improve the transparency of the power market, enhance the confidence of market participants, and promote the healthy development of electricity. Therefore, the accurate evaluation of power supply reliability has become an urgent problem to be solved. Summary of the invention

[0003] The present application provides a method, device, equipment and storage medium for evaluating the reliability of power supply, which can improve the accuracy of the evaluation of the reliability of power supply.

[0004] In order to achieve the above objectives, this application adopts the following technical solutions:

[0005] In a first aspect of an embodiment of the present application, a method for evaluating power supply reliability is provided, the method comprising:

[0006] Acquire evaluation indicators of multiple dimensions corresponding to the power system to be evaluated, wherein the evaluation indicators are used to evaluate the power supply reliability of the power system, and the dimensions include: power supply and demand relationship, power market stability, energy security and environmental factors;

[0007] Using the preset entropy weight method, CRITIC method and standard deviation method, determine the target weight of each evaluation indicator;

[0008] According to each of the evaluation indicators, the target weight of each of the evaluation indicators and the preset TOPSIS comprehensive evaluation method, the reliability results of the power supply of each of the power systems on different operation days are evaluated;

[0009] Based on the preset classification rules and the reliability results, the reliability level of the power supply of each of the power systems on different operating days is determined.

[0010] As a possible implementation method, the evaluation indicators of the power supply and demand relationship dimension corresponding to the power system to be evaluated are obtained, including:

[0011] Obtaining a self-powered power coverage rate of the power system, where the self-powered power coverage rate indicates the ratio of self-generated power to power consumption in a time period in a power system of a region without external power purchase;

[0012] Acquire a balancing capability index of the power system, where the balancing capability index is used to indicate the ability of the power system to maintain a balance between power supply and demand when facing an emergency;

[0013] Obtaining a peak supply-demand ratio of the power system, wherein the peak supply-demand ratio is used to indicate the supply-demand adequacy of the power spot market during peak hours;

[0014] Based on the self-power supply coverage rate, the balancing capability index and the peak supply-demand ratio, an evaluation index of the power supply and demand relationship dimension is constructed.

[0015] As a possible implementation method, the evaluation indicators of the power market stability dimension corresponding to the power system to be evaluated are obtained, including:

[0016] Obtaining the electricity price correlation of the electricity market, where the electricity price correlation is used to indicate the correlation between the clearing electricity price change trends of two adjacent regions;

[0017] Obtaining the proportion of the clearing price of the electricity market reaching the price limit, wherein the proportion of the clearing price reaching the price limit is used to indicate the proportion of time periods in a day when the market clearing price reaches the price ceiling;

[0018] Based on the electricity price correlation and the proportion of the clearing price of the electricity market reaching the price limit, an evaluation index of the electricity market stability dimension is constructed.

[0019] As a possible implementation method, the evaluation indicators of the energy security dimension corresponding to the power system to be evaluated are obtained, including:

[0020] Obtaining an energy self-sufficiency rate of a region corresponding to the power system, where the energy self-sufficiency rate is used to indicate the proportion of energy in a current region in the total energy consumption of the region;

[0021] To obtain diversity in the energy supply of the said region;

[0022] Based on the energy self-sufficiency rate and the diversity of the energy supply, an evaluation index of the energy security dimension is constructed.

[0023] As a possible implementation method, the evaluation indicators of the environmental factor dimension corresponding to the power system to be evaluated are obtained, including:

[0024] Obtaining the amount of water flowing into the area corresponding to the power system;

[0025] Acquiring the temperature of the area corresponding to the power system;

[0026] An evaluation index of the environmental factor dimension is constructed based on the water inflow and the temperature.

[0027] As a possible implementation method, the preset entropy weight method, CRITIC method and standard deviation method are used to determine the target weight of each evaluation indicator, including:

[0028] Determine the first weight of each evaluation index by using the entropy weight method;

[0029] Determine the second weight of each evaluation index by using the CRITIC method;

[0030] Determining the third weight of each evaluation index by using the standard deviation method;

[0031] After weighted averaging the first weight, the second weight and the third weight corresponding to each evaluation indicator, the target weight of each evaluation indicator is obtained.

[0032] As a possible implementation method, the reliability results of the power supply of each power system on different operation days are evaluated according to each evaluation indicator, the target weight of each evaluation indicator and the preset TOPSIS comprehensive evaluation method, including:

[0033] Converting a plurality of power systems to be evaluated and the evaluation indexes into an initial matrix, and performing forward processing on the initial matrix to obtain an evaluation matrix;

[0034] Converting each evaluation index in the evaluation matrix into a very large index and performing standardization processing to obtain a standardized matrix;

[0035] Determine a first gap between the vector corresponding to each of the evaluation indicators and the best evaluation indicator in the standardized matrix, and a second gap between the vector corresponding to each of the evaluation indicators and the worst evaluation indicator;

[0036] Based on the first gap and the second gap, determining the degree of proximity of the object to be evaluated to the optimal power supply reliability;

[0037] A reliability result of the power system is determined based on the proximity.

[0038] In a second aspect of an embodiment of the present application, a device for evaluating reliability of power supply is provided, the device comprising:

[0039] An acquisition module is used to acquire evaluation indicators of multiple dimensions corresponding to the power system to be evaluated, wherein the evaluation indicators are used to evaluate the power supply reliability of the power system, and the dimensions include: power supply and demand relationship, power market stability, energy security and environmental factors;

[0040] The first determination module is used to determine the target weight of each evaluation indicator by using a preset entropy weight method, a CRITIC method and a standard deviation method;

[0041] An evaluation module, used to evaluate the reliability results of power supply of each power system on different operation days according to each evaluation indicator, the target weight of each evaluation indicator and a preset TOPSIS comprehensive evaluation method;

[0042] The second determination module is used to determine the reliability level of the power supply of each of the power systems on different operating days based on a preset classification rule and the reliability result.

[0043] According to a third aspect of an embodiment of the present application, there is provided an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the method for evaluating the reliability of power supply in the first aspect of an embodiment of the present application is implemented.

[0044] According to a fourth aspect of the embodiments of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method for evaluating the reliability of electric power supply described in the first aspect of the embodiments of the present application is implemented.

[0045] The beneficial effects brought by the technical solution provided by the embodiment of the present application include at least:

[0046] The method for evaluating the reliability of power supply provided in the embodiment of the present application obtains evaluation indicators of multiple dimensions corresponding to the power system to be evaluated, and the evaluation indicators are used to evaluate the reliability of power supply of the power system, and the dimensions include: power supply and demand relationship, power market stability, energy security and environmental factors; uses the preset entropy weight method, CRITIC method and standard deviation method to determine the target weight of each of the evaluation indicators; evaluates the reliability results of power supply of each of the power systems on different operating days according to each of the evaluation indicators, the target weight of each of the evaluation indicators and the preset TOPSIS comprehensive evaluation method; determines the reliability level of power supply of each of the power systems on different operating days based on the preset grading rules and the reliability results, which can improve the accuracy of power supply reliability evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A flowchart of a method for evaluating power supply reliability provided in an embodiment of the present application;

[0048] Figure 2 A structural diagram of a power supply reliability assessment device provided in an embodiment of the present application;

[0049] Figure 3A schematic diagram of the internal structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0050] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0051] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present disclosure, unless otherwise specified, "plurality" means two or more.

[0052] Additionally, the use of “based on” or “according to” is meant to be open and inclusive, as a process, step, calculation, or other action “based on” or “according to” one or more conditions or values ​​may, in practice, be based on additional conditions or beyond values.

[0053] With the rapid economic development and the continuous growth of electricity demand, power supply has become an important task, and the construction of a power supply reliability evaluation system is one of the important means to achieve this goal. Power supply reliability is an important way to evaluate the power supply guarantee capability and power market risks. It reflects the operation and risk level of the power market by comprehensively considering multiple factors such as power supply and demand balance, market stability, energy security, and power purchase and sales. The construction of a power supply reliability evaluation system can effectively improve the transparency of the power market, enhance the confidence of market participants, and promote the healthy development of electricity. Therefore, the accurate evaluation of power supply reliability has become an urgent problem to be solved.

[0054] In order to solve the above problems, the present application provides a method for evaluating the reliability of power supply, such as Figure 1 As shown, the method comprises the following steps:

[0055] Step 101: Obtain evaluation indicators of multiple dimensions corresponding to the power system to be evaluated.

[0056] The evaluation index is used to evaluate the reliability of power supply of the power system, and the dimensions include: power supply and demand relationship, power market stability, energy security and environmental factors;

[0057] Step 102: Determine the target weight of each evaluation indicator by using the preset entropy weight method, CRITIC method and standard deviation method.

[0058] Step 103: Evaluate the reliability results of the power supply of each power system on different operation days according to each evaluation indicator, the target weight of each evaluation indicator and a preset TOPSIS comprehensive evaluation method.

[0059] Step 104: Determine the reliability level of the power supply of each of the power systems on different operating days based on a preset classification rule and the reliability result.

[0060] It is understandable that in step 101, evaluation indicators at various levels are proposed from four dimensions: power supply and demand relationship, power market stability, energy security, and environmental factors. The adequacy, flexibility, and emergency response capabilities of the power system directly affect the reliability of power supply. The present invention constructs an evaluation index system for power supply security capability from four dimensions: power supply and demand relationship, power market stability, energy security, and environmental factors.

[0061] The method for evaluating the reliability of power supply provided in the embodiment of the present application obtains evaluation indicators of multiple dimensions corresponding to the power system to be evaluated, and the evaluation indicators are used to evaluate the reliability of power supply of the power system, and the dimensions include: power supply and demand relationship, power market stability, energy security and environmental factors; uses the preset entropy weight method, CRITIC method and standard deviation method to determine the target weight of each of the evaluation indicators; evaluates the reliability results of power supply of each of the power systems on different operating days according to each of the evaluation indicators, the target weight of each of the evaluation indicators and the preset TOPSIS comprehensive evaluation method; determines the reliability level of power supply of each of the power systems on different operating days based on the preset grading rules and the reliability results, which can improve the accuracy of power supply reliability evaluation.

[0062] Optionally, obtaining evaluation indicators of the power supply and demand relationship dimension corresponding to the power system to be evaluated, including:

[0063] Obtaining a self-powered power coverage rate of the power system, where the self-powered power coverage rate indicates the ratio of self-generated power to power consumption in a time period in a power system of a region without external power purchase;

[0064] Acquire a balancing capability index of the power system, where the balancing capability index is used to indicate the ability of the power system to maintain a balance between power supply and demand when facing an emergency;

[0065] Obtaining a peak supply-demand ratio of the power system, wherein the peak supply-demand ratio is used to indicate the supply-demand adequacy of the power spot market during peak hours;

[0066] Based on the self-power supply coverage rate, the balancing capability index and the peak supply-demand ratio, an evaluation index of the power supply and demand relationship dimension is constructed.

[0067] Among them, the electricity supply and demand relationship reflects the relationship between supply and demand in the electricity market, which directly affects the stable operation of the market. Three indicators, namely self-power supply coverage rate, balancing capacity index and peak supply and demand ratio, are defined for evaluation.

[0068] Specifically, the self-power supply coverage rate refers to the ratio of self-generated electricity to electricity consumption within a certain period of time in a certain area without considering external power purchases. It can reflect the degree of matching between the power generation capacity of the power system in the area and the power supply and demand relationship. The higher the self-power supply coverage rate, the stronger the system's own power supply capacity and the stronger its power supply guarantee capacity.

[0069]

[0070] In the formula, is the self-generated electricity on trading day t.

[0071] The balancing capacity index refers to the ability of the power system to maintain a balance between power supply and demand when facing emergencies. The index is defined by the ratio of the power system's reserve capacity (that is, the difference between the system's installed capacity and the power load) to the peak load. The larger the value, the stronger the reserve capacity is in terms of the power system's ability to balance emergencies and the greater the reliability of power supply.

[0072]

[0073] Where P t peak represents the peak load on trading day t.

[0074] The peak supply-demand ratio reflects the supply and demand situation in the electricity spot market during peak hours. A higher peak supply-demand ratio score indicates that the pilot area has a higher degree of electricity supply and demand abundance during peak hours.

[0075]

[0076]

[0077] In the formula, is the supply-demand ratio of the ith period on day t, is the peak supply-demand ratio on day t; is the declared power generation capacity in the ith period on day t, It represents the actual transmitted power in the i-th period on day t. The transmitted power in the sending area is positive, and the transmitted power in the receiving area is negative.

[0078] Optionally, obtain the evaluation index of the power market stability dimension corresponding to the power system to be evaluated, including:

[0079] Obtaining the electricity price correlation of the electricity market, where the electricity price correlation is used to indicate the correlation between the clearing electricity price change trends of two adjacent regions;

[0080] Obtaining the proportion of the clearing price of the electricity market reaching the price limit, wherein the proportion of the clearing price reaching the price limit is used to indicate the proportion of time periods in a day when the market clearing price reaches the price ceiling;

[0081] Based on the electricity price correlation and the proportion of the clearing price of the electricity market reaching the price limit, an evaluation index of the electricity market stability dimension is constructed.

[0082] The stability of the electricity market reflects the stability and risks of the electricity market operation. Its construction needs to consider factors such as transaction price fluctuations and market stratification in the electricity market.

[0083] Electricity price correlation, this indicator determines the supply reliability of region k by comparing the correlation between the clearing electricity price of region k and the clearing electricity price change trend of adjacent region l. Generally speaking, when region k and region l show a positive correlation and a large correlation, it means that the supply and demand relationship of the two regions is similar and there is a competitive relationship, and the supply reliability will be reduced; when there is a strong negative correlation, it means that the supply and demand relationship of the two regions is complementary, and the supply and demand of the region can be balanced through peak-shifting power purchases, thereby enhancing the reliability of power supply.

[0084]

[0085] In the formula, ρ kl Represents the correlation coefficient of electricity prices between area k and area l.

[0086] The proportion of clearing prices reaching the price limit is intended to reflect the proportion of time periods when the market clearing price reaches the price ceiling on day t. The higher the evaluation score of the proportion of clearing prices reaching the price ceiling, it indicates that the proportion of time periods when the spot market clearing price reaches the price ceiling in the pilot area is in a reasonable range.

[0087]

[0088]

[0089] Where RT i,t It is the ratio of the real-time market clearing price on the power generation side reaching the price limit at time i on day t, and I is the number of time periods.

[0090] Optionally, obtain the evaluation indicators of the energy security dimension corresponding to the power system to be evaluated, including:

[0091] Obtaining an energy self-sufficiency rate of a region corresponding to the power system, where the energy self-sufficiency rate is used to indicate the proportion of energy in a current region in the total energy consumption of the region;

[0092] To obtain diversity in the energy supply of the said region;

[0093] Based on the energy self-sufficiency rate and the diversity of the energy supply, an evaluation index of the energy security dimension is constructed.

[0094] The energy security index is one of the important indicators that reflects the reliability and safety of electricity supply. Its construction needs to consider factors such as regional energy self-sufficiency rate and regional energy supply diversity.

[0095] Regional energy self-sufficiency rate. The economic development level and resource endowment of different regions are different. In order to reduce the impact of emergencies on power supply, the receiving region will avoid risks by signing medium- and long-term agreements. Therefore, the regional energy self-sufficiency rate S is defined. k,t As one of the indicators to measure energy security, it refers to the proportion of energy in the current region to the total energy consumption in the region. When a region has a high energy self-sufficiency rate, it means that the region has a high risk resistance at this time, has a low dependence on external energy in the short term, and has a relatively stable and reliable energy supply, which is conducive to improving the reliability of power supply.

[0096]

[0097] In the formula, are the energy self-sufficiency, energy reserves and total energy demand of region k on trading day t respectively.

[0098] Diversity of regional energy supply. If a region’s energy supply relies on a single energy source, such as over-reliance on natural gas, it may lead to insufficient power supply in the region when encountering problems such as natural gas supply interruption or price fluctuation, resulting in reduced reliability of power supply. Therefore, by analogy with Shannon entropy, we define regional energy supply diversity H k for:

[0099]

[0100] Where N e Represents the number of energy types in the primary energy consumption process, P i It represents the proportion of the consumption of the i-th energy in the primary energy consumption structure, which essentially reflects the weighted average of the proportion of each energy consumption in the primary energy consumption process. The range of H value is greater than or equal to 0, and the higher the value, the more equal the proportion of various energy sources in primary energy consumption and the more diverse the types.

[0101] Optionally, obtain evaluation indicators of environmental factor dimensions corresponding to the power system to be evaluated, including:

[0102] Obtaining the amount of water flowing into the area corresponding to the power system;

[0103] Acquiring the temperature of the area corresponding to the power system;

[0104] An evaluation index of the environmental factor dimension is constructed based on the water inflow and the temperature.

[0105] Among them, the environmental factors include water volume and temperature.

[0106] The extremely hot and dry weather in the summer of a certain year caused a certain area to face a severe power supply situation. Therefore, the water inflow is an extremely critical indicator for hydropower stations. Since it is difficult to obtain accurate data, the expert scoring method is used to quantify it, as shown in the following table.

[0107] Table 1 Experts' optimism rating range for water supply

[0108] Water flow evaluation Very optimistic More optimistic generally Less optimistic Not optimistic score 100 75 50 25 0

[0109] In the context of climate change, the rapid increase in electricity consumption in the whole society, the interference of extreme weather events such as high temperature and drought in summer, the electricity demand of various industries continues to rise, the power supply form becomes tighter, the pressure on power supply is increased, and the supply reliability will decrease. The expert score is used to score the optimism of the temperature on the dispatch day t, and the score assignment is as follows:

[0110] Table 2 Experts' optimism rating range for ambient temperature

[0111] Ambient temperature optimism Very optimistic More optimistic generally Less optimistic Not optimistic score 100 75 50 25 0

[0112] Optionally, the use of a preset entropy weight method, CRITIC method and standard deviation method to determine the target weight of each evaluation indicator includes:

[0113] Determine the first weight of each evaluation index by using the entropy weight method;

[0114] Determine the second weight of each evaluation index by using the CRITIC method;

[0115] Determining the third weight of each evaluation index by using the standard deviation method;

[0116] After weighted averaging the first weight, the second weight and the third weight corresponding to each evaluation indicator, the target weight of each evaluation indicator is obtained.

[0117] In the actual implementation process, the original data is first converted into standardized data. ij , and calculate the information entropy of the j-th indicator according to the following formula:

[0118]

[0119] In the formula, m is the number of evaluated objects, n is the number of evaluation indicators, Finally, calculate the entropy weight w of the jth indicator 1j :

[0120]

[0121] The correlation coefficient of the evaluation index matrix is ​​calculated by using the obtained evaluation index correlation coefficient standardization matrix. Then the volatility and conflict between the jth index and other indexes can be calculated and expressed using the standard deviation, that is, E ij is the correlation coefficient between evaluation indexes i and j. The amount of information represented by the jth index is C j The calculation is as follows:

[0122]

[0123] In the formula, σ j is the standard deviation of the jth evaluation index. Finally, the CRITIC weight w of the jth index is calculated. 2j :

[0124]

[0125] Calculate the mean of the jth indicator Then calculate the standard deviation σ of the jth indicator j ,Finally, the formula for calculating the weight is as follows:

[0126]

[0127] After the weights are obtained by the above three weighting methods, the present invention uses the following formula to calculate the combined weight of the j-th indicator:

[0128]

[0129] In the formula, β is the weight coefficient. The present invention assumes that the CRITIC weighting method and the standard deviation method have equal importance.

[0130] Optionally, evaluating the reliability results of the power supply of each of the power systems on different operating days according to each of the evaluation indicators, the target weight of each of the evaluation indicators and a preset TOPSIS comprehensive evaluation method includes:

[0131] Converting a plurality of power systems to be evaluated and the evaluation indexes into an initial matrix, and performing forward processing on the initial matrix to obtain an evaluation matrix;

[0132] Converting each evaluation index in the evaluation matrix into a very large index and performing standardization processing to obtain a standardized matrix;

[0133] Determine a first gap between the vector corresponding to each of the evaluation indicators and the best evaluation indicator in the standardized matrix, and a second gap between the vector corresponding to each of the evaluation indicators and the worst evaluation indicator;

[0134] Based on the first gap and the second gap, determining the degree of proximity of the object to be evaluated to the optimal power supply reliability;

[0135] A reliability result of the power system is determined based on the proximity.

[0136] In the actual execution process, the initial matrix is ​​constructed and normalized according to the evaluation object.

[0137] Assume that the evaluation matrix X of the multi-index evaluation problem is ij ] m×n , the matrix has m evaluation objects and n evaluation indicators:

[0138]

[0139] Unified indicator types. The present invention converts all data corresponding to very small indicators, intermediate indicators, and interval indicators into very large indicators.

[0140] In order to prevent the dimensions of each indicator from affecting the comprehensive evaluation method, the present invention performs data standardization on the indicators that have been converted into extremely large-scale indicators. When the coefficient of variation of the indicators is relatively different, standardization methods based on the degree of dispersion such as the z-score method, the median method or the extreme value method can be used.

[0141]

[0142] Reasonably calculate and determine the indicator weight w j It is the key to apply the TOPSIS comprehensive evaluation method.

[0143] Calculate the gap between each evaluation index and the best and worst vectors.

[0144]

[0145] The best solution is Z + The maximum value of each column element in is composed of Z. - The minimum value of each column element in w j is the weight of the j-th attribute.

[0146] Calculate the degree of closeness between the evaluation object and the optimal solution.

[0147]

[0148] In the formula, is the closeness between the ith target and the optimal target, is the closeness between the ith target and the worst target. i The larger the value, the better the evaluation object.

[0149] The calculation process for classifying the reliability of power supply is as follows:

[0150] The degree of closeness between the evaluation object obtained by the TOPSIS comprehensive evaluation method and the optimal solution is the power supply reliability score, and the value of this score is between 0 and 1. By referring to existing technologies and expert opinions, as well as based on the empirical data of actual power production, a mapping relationship between power supply reliability and evaluation level is established, and the power supply reliability level is divided into 5 levels, as shown in Table 3.

[0151] Table 3 Supply reliability and related information

[0152]

[0153] Table 4 Power supply reliability index data for different operating days in a certain area

[0154] Indicator name D1 D2 D3 D4 D5 Self-powered coverage 0.42 0.15 0.32 0.85 0.43 Balance Ability Index 0.2543 0.4523 0.7652 0.9786 0.2476 Peak supply-demand ratio 0.8494 0.6527 0.2356 0.8874 0.7985 Electricity price relevance 0.8001 0.7082 0.4525 0.0423 0.7834 Clearance reaches limit price ratio 0.6721 0.5623 0.1145 0.0876 0.1523 Regional energy self-sufficiency rate 0.12 0.24 0.16 0.56 0.87 Diversity of regional energy supply 1.272 0.6533 0.9856 1.5672 0.9845 Water Optimism 32 42 51 35 43 Temperature Optimism 33 23 24 27 35

[0155] The present invention will be further described below in conjunction with specific embodiments.

[0156] This embodiment uses the actual power grid operation data of a certain area as a reference, selects different operation days to evaluate the power supply reliability, and records them as D1, D2, D3, D4, and D5 respectively. The specific evaluation process is as shown in the attached figure. Figure 1 The power supply reliability evaluation indexes on different operation days are calculated through measured data, and the index data are shown in Table 4.

[0157] The combined weights of the power supply reliability index are obtained according to the entropy weight-CRITIC-standard deviation method. The calculation results are shown in Table 5:

[0158] Table 5 Weight calculation results of each method

[0159]

[0160] According to the combined weights of the power supply reliability indicators of each region calculated above, the TOPSIS comprehensive evaluation method was used to obtain the comprehensive evaluation results. At the same time, according to the actual operation of the power market and combined with expert experience, the power supply guarantee capability was scored, ranked and the supply reliability was evaluated for the five operation days. The final results are shown in Table 6.

[0161] Table 6 Evaluation results of power supply reliability on different operating days

[0162]

[0163] From the evaluation results in Table 6, it can be found that only the calculation result of D3 is inconsistent with the expert score. Since the score of D3 is 0.3962, which is close to the lower limit of "good", the error is within an acceptable range, so the difference between the two scores is small. In general, the accuracy of the power supply guarantee credibility evaluation results obtained by this method reaches 80%, which shows that the method proposed in the present invention combines three weight calculation methods, and on this basis, the TOPSIS method is used to calculate the credibility score of each indicator. The evaluation results are highly accurate, which provides a reference for the dispatching center to grasp the power supply situation in the entire region, and has great practical significance.

[0164] like Figure 2 As shown, the embodiment of the present application further provides a device for evaluating the reliability of power supply, the device comprising:

[0165] An acquisition module 11 is used to acquire evaluation indicators of multiple dimensions corresponding to the power system to be evaluated, wherein the evaluation indicators are used to evaluate the power supply reliability of the power system, and the dimensions include: power supply and demand relationship, power market stability, energy security and environmental factors;

[0166] The first determination module 12 is used to determine the target weight of each evaluation indicator by using a preset entropy weight method, a CRITIC method and a standard deviation method;

[0167] An evaluation module 13 is used to evaluate the reliability results of the power supply of each power system on different operation days according to each evaluation indicator, the target weight of each evaluation indicator and a preset TOPSIS comprehensive evaluation method;

[0168] The second determination module 14 is used to determine the reliability level of the power supply of each of the power systems on different operating days based on a preset classification rule and the reliability result.

[0169] In one embodiment, the acquisition module 11 is specifically used for:

[0170] Obtaining a self-powered power coverage rate of the power system, where the self-powered power coverage rate indicates the ratio of self-generated power to power consumption in a time period in a power system of a region without external power purchase;

[0171] Acquire a balancing capability index of the power system, where the balancing capability index is used to indicate the ability of the power system to maintain a balance between power supply and demand when facing an emergency;

[0172] Obtaining a peak supply-demand ratio of the power system, wherein the peak supply-demand ratio is used to indicate the supply-demand adequacy of the power spot market during peak hours;

[0173] Based on the self-power supply coverage rate, the balancing capability index and the peak supply-demand ratio, an evaluation index of the power supply and demand relationship dimension is constructed.

[0174] In one embodiment, the acquisition module 11 is specifically used for:

[0175] Obtaining the electricity price correlation of the electricity market, where the electricity price correlation is used to indicate the correlation between the clearing electricity price change trends of two adjacent regions;

[0176] Obtaining the proportion of the clearing price of the electricity market reaching the price limit, wherein the proportion of the clearing price reaching the price limit is used to indicate the proportion of time periods in a day when the market clearing price reaches the price ceiling;

[0177] Based on the electricity price correlation and the proportion of the clearing price of the electricity market reaching the price limit, an evaluation index of the electricity market stability dimension is constructed.

[0178] In one embodiment, the acquisition module 11 is specifically used for:

[0179] Obtaining an energy self-sufficiency rate of a region corresponding to the power system, where the energy self-sufficiency rate is used to indicate the proportion of energy in a current region in the total energy consumption of the region;

[0180] To obtain diversity in the energy supply of the said region;

[0181] Based on the energy self-sufficiency rate and the diversity of the energy supply, an evaluation index of the energy security dimension is constructed.

[0182] In one embodiment, the acquisition module 11 is specifically used for:

[0183] Obtaining the amount of water flowing into the area corresponding to the power system;

[0184] Acquiring the temperature of the area corresponding to the power system;

[0185] An evaluation index of the environmental factor dimension is constructed based on the water inflow and the temperature.

[0186] In one embodiment, the first determining module 12 is specifically configured to:

[0187] Determine the first weight of each evaluation index by using the entropy weight method;

[0188] Determine the second weight of each evaluation index by using the CRITIC method;

[0189] Determining the third weight of each evaluation index by using the standard deviation method;

[0190] After weighted averaging the first weight, the second weight and the third weight corresponding to each evaluation indicator, the target weight of each evaluation indicator is obtained.

[0191] In one embodiment, the evaluation module 13 is specifically used for:

[0192] Converting a plurality of power systems to be evaluated and the evaluation indexes into an initial matrix, and performing forward processing on the initial matrix to obtain an evaluation matrix;

[0193] Converting each evaluation index in the evaluation matrix into a very large index and performing standardization processing to obtain a standardized matrix;

[0194] Determine a first gap between the vector corresponding to each of the evaluation indicators and the best evaluation indicator in the standardized matrix, and a second gap between the vector corresponding to each of the evaluation indicators and the worst evaluation indicator;

[0195] Based on the first gap and the second gap, determining the degree of proximity of the object to be evaluated to the optimal power supply reliability;

[0196] A reliability result of the power system is determined based on the proximity.

[0197] The power supply reliability assessment device provided in this embodiment can execute the power supply reliability assessment method embodiment, and its implementation principle and technical effect are similar, which will not be elaborated here.

[0198] For the specific definition of the power supply reliability assessment device, please refer to the definition of the power supply reliability assessment method mentioned above, which will not be repeated here. Each module in the above-mentioned power supply reliability assessment device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor of the electronic device in the form of hardware, or can be stored in the memory of the electronic device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0199] The executor of the method for evaluating the reliability of electric power supply provided in the embodiment of the present application may be an electronic device, which may be a computer device, a terminal device, a server or a server cluster, and the embodiment of the present application does not specifically limit this.

[0200] Figure 3 This is a schematic diagram of the internal structure of an electronic device provided in an embodiment of the present application. Figure 3As shown, the electronic device includes a processor and a memory connected via a system bus. The processor is used to provide computing and control capabilities. The memory may include a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The computer program can be executed by the processor to implement the steps of the power supply reliability evaluation method provided in each of the above embodiments. The internal memory provides a cache operating environment for the operating system and the computer program in the non-volatile storage medium.

[0201] Those skilled in the art will understand that Figure 3 The internal structure diagram of the electronic device shown in the figure is only a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the electronic device to which the scheme of the present application is applied. The specific electronic device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0202] In another embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method for evaluating the reliability of power supply as in the embodiment of the present application are implemented.

[0203] In another embodiment of the present application, a computer program product is also provided. The computer program product includes computer instructions. When the computer instructions are executed on the power supply reliability assessment device, the power supply reliability assessment device executes each step of the power supply reliability assessment method in the method flow shown in the above method embodiment.

[0204] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using a software program, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loading and executing computer execution instructions on a computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server, data center, etc. that contains one or more servers that can be integrated with a medium. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a DVD), or a semiconductor medium (eg, a solid state disk (SSD)).

[0205] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0206] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for evaluating the reliability of power supply, characterized in that: The method comprises: Acquire evaluation indicators of multiple dimensions corresponding to the power system to be evaluated, wherein the evaluation indicators are used to evaluate the power supply reliability of the power system, and the dimensions include: power supply and demand relationship, power market stability, energy security and environmental factors; Using the preset entropy weight method, CRITIC method and standard deviation method, determine the target weight of each evaluation indicator; According to each of the evaluation indicators, the target weight of each of the evaluation indicators and the preset TOPSIS comprehensive evaluation method, the reliability results of the power supply of each of the power systems on different operation days are evaluated; Based on the preset classification rules and the reliability results, the reliability level of the power supply of each of the power systems on different operating days is determined.

2. The method according to claim 1, characterized in that Obtain the evaluation indicators of the power supply and demand relationship dimension corresponding to the power system to be evaluated, including: Obtaining a self-powered power coverage rate of the power system, where the self-powered power coverage rate indicates the ratio of self-generated power to power consumption in a time period in a power system of a region without external power purchase; Acquire a balancing capability index of the power system, where the balancing capability index is used to indicate the ability of the power system to maintain a balance between power supply and demand when facing an emergency; Obtaining a peak supply-demand ratio of the power system, wherein the peak supply-demand ratio is used to indicate the supply-demand adequacy of the power spot market during peak hours; Based on the self-power supply coverage rate, the balancing capability index and the peak supply-demand ratio, an evaluation index of the power supply and demand relationship dimension is constructed.

3. The method according to claim 1, characterized in that Obtain the evaluation indicators of the power market stability dimension corresponding to the power system to be evaluated, including: Obtaining the electricity price correlation of the electricity market, where the electricity price correlation is used to indicate the correlation between the clearing electricity price change trends of two adjacent regions; Obtaining the proportion of the clearing price of the electricity market reaching the price limit, wherein the proportion of the clearing price reaching the price limit is used to indicate the proportion of time periods in a day when the market clearing price reaches the price ceiling; Based on the electricity price correlation and the proportion of the clearing price of the electricity market reaching the price limit, an evaluation index of the electricity market stability dimension is constructed.

4. The method according to claim 1, characterized in that: Obtain the evaluation indicators of the energy security dimension corresponding to the power system to be evaluated, including: Obtaining an energy self-sufficiency rate of a region corresponding to the power system, where the energy self-sufficiency rate is used to indicate the proportion of energy in a current region in the total energy consumption of the region; To obtain diversity in the energy supply of the said region; Based on the energy self-sufficiency rate and the diversity of the energy supply, an evaluation index of the energy security dimension is constructed.

5. The method according to claim 1, characterized in that Obtain the evaluation indicators of the environmental factor dimensions corresponding to the power system to be evaluated, including: Obtaining the amount of water flowing into the area corresponding to the power system; Acquiring the temperature of the area corresponding to the power system; An evaluation index of the environmental factor dimension is constructed based on the water inflow and the temperature.

6. The method according to claim 1, characterized in that The method of using the preset entropy weight method, CRITIC method and standard deviation method to determine the target weight of each evaluation indicator includes: Determine the first weight of each evaluation index by using the entropy weight method; Determine the second weight of each evaluation index by using the CRITIC method; Determining the third weight of each evaluation index by using the standard deviation method; After weighted averaging the first weight, the second weight and the third weight corresponding to each evaluation indicator, the target weight of each evaluation indicator is obtained.

7. The method according to claim 1, characterized in that According to each of the evaluation indicators, the target weight of each of the evaluation indicators and the preset TOPSIS comprehensive evaluation method, the reliability results of the power supply of each of the power systems on different operation days are evaluated, including: Converting a plurality of power systems to be evaluated and the evaluation indexes into an initial matrix, and performing forward processing on the initial matrix to obtain an evaluation matrix; Converting each evaluation index in the evaluation matrix into a very large index and performing standardization processing to obtain a standardized matrix; Determine a first gap between the vector corresponding to each of the evaluation indicators and the best evaluation indicator in the standardized matrix, and a second gap between the vector corresponding to each of the evaluation indicators and the worst evaluation indicator; Based on the first gap and the second gap, determining the degree of proximity of the object to be evaluated to the optimal power supply reliability; A reliability result of the power system is determined based on the proximity.

8. A device for evaluating the reliability of power supply, characterized in that: The device comprises: An acquisition module is used to acquire evaluation indicators of multiple dimensions corresponding to the power system to be evaluated, wherein the evaluation indicators are used to evaluate the power supply reliability of the power system, and the dimensions include: power supply and demand relationship, power market stability, energy security and environmental factors; The first determination module is used to determine the target weight of each evaluation indicator by using a preset entropy weight method, a CRITIC method and a standard deviation method; An evaluation module, used to evaluate the reliability results of power supply of each power system on different operation days according to each evaluation indicator, the target weight of each evaluation indicator and a preset TOPSIS comprehensive evaluation method; The second determination module is used to determine the reliability level of the power supply of each of the power systems on different operating days based on a preset classification rule and the reliability result.

9. An electronic device, characterized in that: The invention comprises a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the method for evaluating the reliability of power supply according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the method for evaluating the reliability of power supply according to any one of claims 1 to 7 is implemented.

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