CN116432437A - Comprehensive evaluation method and system for photovoltaic power generation unit - Google Patents
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Abstract
The invention provides a comprehensive evaluation method and a comprehensive evaluation system for a photovoltaic power generation unit, wherein the comprehensive evaluation method comprises the following steps: according to different subjective weighting methods and objective weighting methods, calculating basic weighting coefficients corresponding to various weighting methods of evaluation indexes in a preset comprehensive evaluation system of the photovoltaic power generation unit; calculating the combination weight of the evaluation index through an optimization model based on the basic weight coefficient; dividing the quantization interval of the basic data corresponding to the evaluation index, calculating the probability value of each basic data falling in the quantization interval, and calculating the comprehensive evaluation result of the photovoltaic power generation unit based on the probability value, the combination weight and the preset evaluation index quantization value corresponding to each quantization interval; according to the invention, the combination weight of the evaluation index is calculated by taking the minimum identification information as the objective function through the optimization model, so that the reasonable and scientific evaluation index weight can be obtained, and the comprehensive evaluation result of the photovoltaic power generation unit is more reliable based on the reasonable and scientific evaluation index weight.
Description
Technical Field
The invention belongs to the technical field of photovoltaic power generation evaluation, and particularly relates to a comprehensive evaluation method and system for a photovoltaic power generation unit.
Background
With the increasing importance of society on environmental protection and the continuous improvement of technological level, the technical level of solar photovoltaic power generation is greatly improved, and solar photovoltaic resources become a main energy source for production and life in a plurality of countries in the world. Solar energy is taken as a green and environment-friendly clean energy source, the application prospect is widely seen, the total amount of resources is quite rich, but the utilization of the solar energy is greatly influenced by conditions such as climate, geographic position and the like, and the energy density is low, so that the utilization of the solar energy also faces a plurality of difficulties.
The installation ratio of the photovoltaic power generation in the power grid is rapidly increased, the influence on the safe and stable operation of the traditional power system is increasingly remarkable, the photovoltaic power station is required to have high-quality technical performance, and grid connection friendliness and auxiliary supporting capacity of the power grid are important characteristics capable of adapting to a novel power system in the future. Meanwhile, the economic performance and the social environment are also important factors influencing the development of the photovoltaic power generation industry, and the advantages and disadvantages of the photovoltaic power generation performance directly influence the electricity-measuring cost of the construction and operation of the photovoltaic power station, the income condition of an investor, the carbon emission content and the like. Therefore, comprehensive evaluation and transverse comparison are carried out on the photovoltaic power station from multiple dimensions such as the technical performance, economic benefit and social environmental impact of the photovoltaic power station, so that investors can fully master the comprehensive performance of the photovoltaic power station, and judgment basis is provided for improving technology, active markets and optimizing policies. In addition, a comprehensive and reasonable evaluation system is a basis for developing comprehensive evaluation of the photovoltaic power generation unit, a scientific and effective evaluation method is a way for realizing effective landing of comprehensive evaluation of the photovoltaic power generation unit, and research and proposal of a comprehensive performance evaluation technology which is compatible with all parties and convenient to implement are needed to be researched and put forward, so that continuous and rapid healthy development of the photovoltaic industry is better supported.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a comprehensive evaluation method of a photovoltaic power generation unit, which comprises the following steps:
according to different subjective weighting methods and objective weighting methods, calculating basic weighting coefficients corresponding to various weighting methods of evaluation indexes in a preset comprehensive evaluation system of the photovoltaic power generation unit;
calculating the combination weight of the evaluation index through an optimization model based on the basic weight coefficient;
dividing the basic data corresponding to the evaluation indexes into quantization intervals, calculating probability values of the basic data falling in the quantization intervals, and calculating comprehensive evaluation results of the photovoltaic power generation units based on the probability values, the combination weights and the preset evaluation index quantization values corresponding to the quantization intervals;
the optimization model is constructed by taking the minimum identification information as an objective function.
Preferably, the calculating, based on the basic weight coefficient, the combination weight of the evaluation index through an optimization model includes:
and inputting the basic weight coefficient into an objective function of the optimization model, and solving the optimization model through a Lagrange multiplier method to obtain the combination weight of the evaluation index.
Preferably, the objective function is as follows:
wherein w is j Combining weight w for j-th evaluation index lj The basic weight coefficient of the j-th evaluation index of the first weighting method is p, the total number of the weighting methods is p, and n is the number of the evaluation indexes.
Preferably, the dividing the quantization interval of the basic data corresponding to the evaluation index, calculating a probability value of each of the basic data falling in the quantization interval, and calculating a comprehensive evaluation result of the photovoltaic power generation unit based on the probability value, the combination weight and the quantization value of the preset evaluation index corresponding to each quantization interval, including:
basic data of the photovoltaic power generation unit to be evaluated on each preset long time scale are obtained;
carrying out quantization classification on basic data corresponding to the evaluation index within the limit value of the evaluation index, determining each quantization interval, and obtaining a preset evaluation index quantization value on each quantization interval;
counting probability values of the basic data falling in the quantization interval;
and calculating the comprehensive evaluation result of the photovoltaic power generation unit based on the probability value, the combination weight and the evaluation index quantized value.
Preferably, the calculation formula of the comprehensive evaluation result is as follows:
wherein R is the comprehensive evaluation result, beta i Quantized value P for the i-th quantization interval i (j) Probability value, w, of occurrence of jth evaluation index in ith quantization interval j The j-th evaluation index combination weight is that m is the number of evaluation index quantization intervals and n is the number of evaluation indexes.
Based on the same inventive concept, the invention also provides a comprehensive evaluation system of the photovoltaic power generation unit, which comprises:
the system comprises a basic weight calculation module, a combination weight module and a comprehensive evaluation result module;
the basic weight calculation module is used for calculating basic weight coefficients corresponding to various weighting methods of evaluation indexes in a preset comprehensive evaluation system of the photovoltaic power generation unit according to different subjective weighting methods and objective weighting methods;
the combination weight module is used for calculating the combination weight of the evaluation index through an optimization model based on the basic weight coefficient;
the comprehensive evaluation result module is used for dividing quantization intervals of basic data corresponding to the evaluation indexes, calculating probability values of the basic data falling in the quantization intervals, and calculating comprehensive evaluation results of the photovoltaic power generation units based on the probability values, the combination weights and the preset evaluation index quantization values corresponding to the quantization intervals;
the optimization model is constructed by taking the minimum identification information as an objective function.
Preferably, the combination weight module is specifically configured to:
and inputting the basic weight coefficient into an objective function of the optimization model, and solving the optimization model through a Lagrange multiplier method to obtain the combination weight of the evaluation index.
Preferably, the objective function of the combined weight module is as follows:
wherein w is j Combining weight w for j-th evaluation index lj The basic weight coefficient of the j-th evaluation index of the first weighting method is p, the total number of the weighting methods is p, and n is the number of the evaluation indexes.
Preferably, the comprehensive evaluation result module is specifically configured to:
basic data of the photovoltaic power generation unit to be evaluated on each preset long time scale are obtained;
carrying out quantization classification on basic data corresponding to the evaluation index within the limit value of the evaluation index, determining each quantization interval, and obtaining a preset evaluation index quantization value on each quantization interval;
counting probability values of the basic data falling in the quantization interval;
and calculating the comprehensive evaluation result of the photovoltaic power generation unit based on the probability value, the combination weight and the evaluation index quantized value.
Preferably, the calculation formula of the comprehensive evaluation result module is as follows:
wherein R is the comprehensive evaluation result, beta i Quantized value P for the i-th quantization interval i (j) Probability value, w, of occurrence of jth evaluation index in ith quantization interval j The j-th evaluation index combination weight is that m is the number of evaluation index quantization intervals and n is the number of evaluation indexes.
Compared with the closest prior art, the invention has the following beneficial effects:
the invention provides a comprehensive evaluation method and a comprehensive evaluation system for a photovoltaic power generation unit, wherein the comprehensive evaluation method comprises the following steps: according to different subjective weighting methods and objective weighting methods, calculating basic weighting coefficients corresponding to various weighting methods of evaluation indexes in a preset comprehensive evaluation system of the photovoltaic power generation unit; calculating the combination weight of the evaluation index through an optimization model based on the basic weight coefficient; dividing the basic data corresponding to the evaluation indexes into quantization intervals, calculating probability values of the basic data falling in the quantization intervals, and calculating comprehensive evaluation results of the photovoltaic power generation units based on the probability values, the combination weights and the preset evaluation index quantization values corresponding to the quantization intervals; the optimization model is constructed by taking the minimum identification information as an objective function; according to the invention, the combination weight of the evaluation index is calculated by taking the minimum identification information as the objective function through the optimization model, so that the reasonable and scientific evaluation index weight can be obtained, and the comprehensive evaluation result of the photovoltaic power generation unit is more reliable based on the reasonable and scientific evaluation index weight.
Drawings
FIG. 1 is a schematic flow chart of a comprehensive evaluation method of a photovoltaic power generation unit provided by the invention;
FIG. 2 is a block diagram of a comprehensive evaluation system of a photovoltaic power generation unit provided by the invention;
fig. 3 is a schematic diagram of a comprehensive evaluation system of a photovoltaic power generation unit provided by the invention.
Detailed Description
The following describes the embodiments of the present invention in further detail with reference to the drawings.
Example 1:
the comprehensive evaluation method of the photovoltaic power generation unit provided by the invention is shown in figure 1, and comprises the following steps:
step 1: according to different subjective weighting methods and objective weighting methods, calculating basic weighting coefficients corresponding to various weighting methods of evaluation indexes in a preset comprehensive evaluation system of the photovoltaic power generation unit;
step 2: calculating the combination weight of the evaluation index through an optimization model based on the basic weight coefficient;
step 3: dividing the basic data corresponding to the evaluation indexes into quantization intervals, calculating probability values of the basic data falling in the quantization intervals, and calculating comprehensive evaluation results of the photovoltaic power generation units based on the probability values, the combination weights and the preset evaluation index quantization values corresponding to the quantization intervals;
the optimization model is constructed by taking the minimum identification information as an objective function.
Before the steps are carried out, a comprehensive evaluation system of the photovoltaic power generation unit shown in fig. 2 is arranged, the comprehensive evaluation system of the photovoltaic power generation unit is served for the feasibility of operation and project evaluation of the photovoltaic power station, so that the comprehensive consideration of solar radiation conditions and geographic conditions, scheme design of the photovoltaic power generation system, economic benefits brought to investment enterprises, influence on society, influence on ecological environment and other factors is carried out, the comprehensive evaluation system is mainly divided into technical performance indexes, economic benefit indexes and first-level indexes of social environment benefits, evaluation indexes are arranged under the first-level indexes, and the first-level indexes only divide and classify the evaluation indexes and do not participate in calculation of the evaluation indexes;
the technical performance indexes generate corresponding evaluation indexes including a low voltage ride through index, a high voltage ride through index, a frequency supporting capacity index, an active control capacity index, a reactive power response capacity index, a voltage deviation index, a voltage unbalance degree index, a current harmonic index, a flicker index and a power generation efficiency index according to the characteristics of the power generation unit such as reliability, product operation characteristics and comprehensive conversion efficiency;
the evaluation indexes corresponding to the economic benefit indexes comprise a power station investment cost index, an electricity price index, a unit electric quantity income index, sales tax and additional indexes, an energy saving and consumption reduction condition index, an internal income ratio index, an investment recovery period index, an asset liability ratio index, a fund balance ratio index and a leveling degree electric cost index, and the economic benefit indexes are mainly focused on the leveling degree electric cost and the initial investment of tens of millions by taking certain relevance and difference of the indexes into consideration and have obvious regional or policy properties, wherein the former represents cost expectation of the whole life cycle of the project, and the latter represents cost expectation of the initial stage of the project construction;
the social environment index is analyzed from the whole life cycle of the project, and the influence of the photovoltaic power generation unit on the social environment is mainly emission generated by transportation and construction in the construction process of the photovoltaic power station, exhaust gas and wastewater emission and energy consumption in the power generation process of the photovoltaic power station, pollutant emission generated in the operation process of the photovoltaic power station and the like. Considering that the photovoltaic power station has corresponding contribution in the aspect of saving land resources or compositely utilizing land resources, the social environment index takes the unit installed capacity generating capacity as a calculation basis to convert the standard coal saving index;
specifically, step 1 includes: the method for determining the index weight of the evaluation index in the comprehensive evaluation system of the photovoltaic power generation unit comprises a subjective weighting method and an objective weighting method, wherein the subjective weighting method and the objective weighting method have the advantages and disadvantages, and currently, weight calculation methods such as a sequence diagram method, a factor analysis method, an entropy weighting method, a variation coefficient method, a data network analysis method, a fuzzy evaluation method, an analytic hierarchy process, an adjacent index comparison method, a Delphi method and the like are commonly used;
the subjective weighting method is an expert judging method, and has the advantages that a plurality of decision-making experts reasonably determine the sequence of the attribute weights according to the actual decision-making problem or own knowledge experience, and the discrete degree of expert decision is observed through calculating the mean value and the variance, so that the situation that the attribute weights are contrary to the actual importance degree of the attribute is generally avoided, and the subjective intention of an evaluation main body is more closed; the method has the defects that the decision or evaluation result has stronger subjective randomness and limitation, and the burden on a decision maker is increased;
the objective weighting method has the advantages that the weight is determined by utilizing the relation between the original data, so that the objective weighting method has strong objectivity and mathematical theoretical support; the disadvantage is that the subjective intention of the decision maker is not considered, and the situation that the weight result is inconsistent with the subjective intention or actual situation of people can occur in the calculation. In theory, in multi-attribute decision, the least important attribute may have the largest weight, but the most important attribute does not necessarily have the largest weight, and the most important attribute depends on the actual decision problem, has poor generality and participatability of a decision maker, does not consider the subjective intention of the decision maker, and has large calculation amount;
based on basic data corresponding to each evaluation index in a comprehensive evaluation system of a photovoltaic power generation unit, when calculating a subjective basic weight coefficient, constructing a judgment matrix corresponding to each subjective weighting method according to decision expert judgment experience, calculating the subjective basic weight coefficient of the evaluation index, and when calculating an objective basic weight coefficient, calculating objective basic weight coefficients according to different objective weighting methods based on basic data corresponding to each evaluation index, and respectively calculating to obtain more than two subjective basic weight coefficients and objective basic weight coefficients; the comprehensive evaluation system of the photovoltaic power generation unit is constructed by selecting the evaluation index of the comprehensive evaluation system of the photovoltaic power generation unit according to basic principles such as comprehensiveness, systematicness, importance, operability, fairness, combination of qualitative and quantitative properties and the like, and different subjective weighting methods and objective weighting methods are adopted, so that the subjective preference of a decision maker is considered, the objectivity of the actual quantity characteristics is considered, and the subsequent combination weight is more scientific;
specifically, step 2 includes:
and constructing an optimization model by taking the minimum identification information as an objective function, wherein the objective function is as follows:
wherein w is j Combining weight w for j-th evaluation index lj The basic weight coefficient of the j-th evaluation index of the first basic weight weighting method is p, the total category number of the basic weighting method is p, and n is the number value of the evaluation index.
The constraints of the objective function are as follows:
inputting the basic weight coefficient of each evaluation index calculated in the step 1 into an optimization model, solving the optimization model through a Lagrange multiplier method, and calculating the combination weight of the evaluation index, wherein the calculation formula of the combination weight is as follows:
wherein w is j The invention uses the minimum discrimination information to integrate and analyze the existing statistical data by using the minimum discrimination information of the prior distribution and the target distribution as the target function when a decision maker only grasps the prior probability distribution or part of statistical information, so that the target distribution is closest to the probability distribution under the condition of meeting various constraint conditions, the judgment is made on the rule of the whole distribution, the minimum discrimination information is used as the target function by optimizing a model, and the combination weight of the evaluation index is calculated, thereby being beneficial to obtaining reasonable and scientific evaluation index weight based onReasonable and scientific evaluation index weight enables the comprehensive evaluation result of the photovoltaic power generation unit to be more reliable;
specifically, step 3 includes:
according to a preset long time scale, basic data corresponding to each evaluation index in a comprehensive evaluation system of the photovoltaic power generation unit are divided, the basic data on each long time scale are determined, and the comprehensive evaluation system is comprehensively established according to various standards and specifications on the basis of quantifiable index systems, so that the comprehensive evaluation system has theoretic and practical properties. Aiming at the proposed comprehensive evaluation system of the photovoltaic power generation unit, the inverter outputs dynamic reactive current and voltage change ratio values K1 and K2 during the fault ride-through period of the low voltage ride-through index and the high voltage ride-through index with reference to GB/T37408-2019 technical requirements of photovoltaic power generation grid-connected inverters; the frequency supporting capability index refers to the rapid frequency response qualification rate of the ' northwest regulation [ 2018 ] 225 and the ' grid-connected power primary frequency modulation technical regulation and test guidance ' of GB/T40595-2021; the active control capability index refers to the control deviation value of active power of GB/T40289-2021 technical requirement of photovoltaic power station power control system; reactive response capability refers to dynamic reactive response time of GB/T37408-2019 technical requirement of photovoltaic power generation grid-connected inverter; the voltage deviation index refers to the voltage deviation limit value of GB/T29321-2012 reactive compensation technical Specification of photovoltaic power station; the voltage unbalance index refers to the voltage unbalance limit value of GB/T15543-2008 electric energy quality three-phase voltage unbalance; the current harmonic index refers to the total harmonic distortion rate of GB/T14549-1993 electric energy quality public grid harmonic; the flicker index refers to a long-time flicker limit value of GB/T12326-2008 electric energy quality voltage fluctuation and flicker; the power generation efficiency index, the leveling degree electricity cost index and the unit ten-million initial investment index refer to the data statistics experience value of the photovoltaic power station; the standard coal saving index is calculated by the power generation amount of unit installed capacity, and the limit values of the 13 evaluation indexes are shown in the table 1:
table 1 evaluation index limit
The basic data corresponding to the evaluation index is quantized and classified into five quantization interval grades of high quality, good, general, qualified and unqualified in sequence within the limit value of the evaluation index, and the quantization classification of the evaluation index is shown in table 2:
table 2 evaluation index quantization and grading table
Presetting quantization values for the five quantization interval levels, quantizing a classification matrix of the photovoltaic power generation unit according to the evaluation index quantization classification table to different time scales, calculating probability values of each basic data falling in the quantization interval, and summarizing the probability values of all the basic data falling in the quantization interval to form a basic data probability matrix of the photovoltaic power generation unit in different time scales, wherein the probability values of all the basic data falling in the quantization interval are represented by the following formula:
wherein X is a basic data probability matrix, P m (n) is a probability value for the nth index to occur within the mth quantization interval;
based on the probability value, the combination weight and the quantized value of the evaluation index corresponding to each quantized interval, the comprehensive evaluation result of the photovoltaic power generation unit is calculated, and the calculation formula is as follows:
wherein R is the comprehensive evaluation result, beta i Quantized value P for the i-th quantization interval i (j) Probability value, w, of occurrence of jth evaluation index in ith quantization interval j The combination weight of the j-th evaluation index is that m is the number of quantization intervals of the evaluation index, and n is the number value of the evaluation index;
table 3 is an evaluation result classification table as follows:
TABLE 3 evaluation result ranking Table
According to the interval classification of the evaluation result R judged in the table 3, the larger and the better the evaluation result R is, the comprehensive evaluation method for the photovoltaic power generation unit has the advantages of being convenient to implement and capable of supporting the continuous and rapid healthy development of the photovoltaic industry better.
Example 2:
based on the same inventive concept, the invention also provides a comprehensive evaluation system of the photovoltaic power generation unit, as shown in fig. 3, comprising:
the system comprises a basic weight calculation module, a combination weight module and a comprehensive evaluation result module;
the basic weight calculation module is used for calculating basic weight coefficients corresponding to various weighting methods of evaluation indexes in a preset comprehensive evaluation system of the photovoltaic power generation unit according to different subjective weighting methods and objective weighting methods;
the combination weight module is used for calculating the combination weight of the evaluation index through an optimization model based on the basic weight coefficient;
the comprehensive evaluation result module is used for dividing quantization intervals of basic data corresponding to the evaluation indexes, calculating probability values of the basic data falling in the quantization intervals, and calculating comprehensive evaluation results of the photovoltaic power generation units based on the probability values, the combination weights and the preset evaluation index quantization values corresponding to the quantization intervals;
the optimization model is constructed by taking the minimum identification information as an objective function.
Further, the combination weight module is specifically configured to:
and inputting the basic weight coefficient into an objective function of the optimization model, and solving the optimization model through a Lagrange multiplier method to obtain the combination weight of the evaluation index.
Further, the objective function of the combined weight module is as follows:
wherein w is j Combining weight w for j-th evaluation index lj The basic weight coefficient of the j-th evaluation index of the first weighting method is p, the total number of the weighting methods is p, and n is the number of the evaluation indexes.
Further, the comprehensive evaluation result module is specifically configured to:
basic data of the photovoltaic power generation unit to be evaluated on each preset long time scale are obtained;
carrying out quantization classification on basic data corresponding to the evaluation index within the limit value of the evaluation index, determining each quantization interval, and obtaining a preset evaluation index quantization value on each quantization interval;
counting probability values of the basic data falling in the quantization interval;
and calculating the comprehensive evaluation result of the photovoltaic power generation unit based on the probability value, the combination weight and the evaluation index quantized value.
Further, the calculation formula of the comprehensive evaluation result module is as follows:
wherein R is the comprehensive evaluation result, beta i Quantized value P for the i-th quantization interval i (j) Probability value, w, of occurrence of jth evaluation index in ith quantization interval j The j-th evaluation index combination weight is that m is the number of evaluation index quantization intervals and n is the number of evaluation indexes.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the scope of protection thereof, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that various changes, modifications or equivalents may be made to the specific embodiments of the application after reading the present invention, and these changes, modifications or equivalents are within the scope of protection of the claims appended hereto.
Claims (10)
1. The comprehensive evaluation method of the photovoltaic power generation unit is characterized by comprising the following steps of:
according to different subjective weighting methods and objective weighting methods, calculating basic weighting coefficients corresponding to various weighting methods of evaluation indexes in a preset comprehensive evaluation system of the photovoltaic power generation unit;
calculating the combination weight of the evaluation index through an optimization model based on the basic weight coefficient;
dividing the basic data corresponding to the evaluation indexes into quantization intervals, calculating probability values of the basic data falling in the quantization intervals, and calculating comprehensive evaluation results of the photovoltaic power generation units based on the probability values, the combination weights and the preset evaluation index quantization values corresponding to the quantization intervals;
the optimization model is constructed by taking the minimum identification information as an objective function.
2. The method of claim 1, wherein the calculating, based on the base weight coefficients, combining weights of the evaluation index by an optimization model comprises:
and inputting the basic weight coefficient into an objective function of the optimization model, and solving the optimization model through a Lagrange multiplier method to obtain the combination weight of the evaluation index.
3. The method of claim 2, wherein the objective function is as follows:
wherein w is j Combining weight w for j-th evaluation index lj The basic weight coefficient of the j-th evaluation index of the first weighting method is p, the total number of the weighting methods is p, and n is the number of the evaluation indexes.
4. The method according to claim 1, wherein the dividing the quantization interval of the basic data corresponding to the evaluation index, calculating a probability value of each of the basic data falling in the quantization interval, and calculating the comprehensive evaluation result of the photovoltaic power generation unit based on the probability value, the combination weight, and the quantization value of the evaluation index corresponding to each quantization interval, includes:
basic data of the photovoltaic power generation unit to be evaluated on each preset long time scale are obtained;
carrying out quantization classification on basic data corresponding to the evaluation index within the limit value of the evaluation index, determining each quantization interval, and obtaining a preset evaluation index quantization value on each quantization interval;
counting probability values of the basic data falling in the quantization interval;
and calculating the comprehensive evaluation result of the photovoltaic power generation unit based on the probability value, the combination weight and the evaluation index quantized value.
5. The method of claim 4, wherein the comprehensive evaluation result is calculated as follows:
wherein R is the comprehensive evaluation result, beta i Quantized value P for the i-th quantization interval i (j) Probability value, w, of occurrence of jth evaluation index in ith quantization interval j The j-th evaluation index combination weight is that m is the number of evaluation index quantization intervals and n is the number of evaluation indexes.
6. A photovoltaic power generation unit comprehensive evaluation system, characterized by comprising:
the system comprises a basic weight calculation module, a combination weight module and a comprehensive evaluation result module;
the basic weight calculation module is used for calculating basic weight coefficients corresponding to various weighting methods of evaluation indexes in a preset comprehensive evaluation system of the photovoltaic power generation unit according to different subjective weighting methods and objective weighting methods;
the combination weight module is used for calculating the combination weight of the evaluation index through an optimization model based on the basic weight coefficient;
the comprehensive evaluation result module is used for dividing quantization intervals of basic data corresponding to the evaluation indexes, calculating probability values of the basic data falling in the quantization intervals, and calculating comprehensive evaluation results of the photovoltaic power generation units based on the probability values, the combination weights and the preset evaluation index quantization values corresponding to the quantization intervals;
the optimization model is constructed by taking the minimum identification information as an objective function.
7. The system of claim 6, wherein the combining weight module is specifically configured to:
and inputting the basic weight coefficient into an objective function of the optimization model, and solving the optimization model through a Lagrange multiplier method to obtain the combination weight of the evaluation index.
8. The system of claim 7, wherein the objective function of the combined weight module is as follows:
wherein w is j Combining weight w for j-th evaluation index lj For the first method of weightingThe basic weight coefficient of the j-th evaluation index, p is the total category number of the weighting method, and n is the number value of the evaluation index.
9. The system of claim 6, wherein the comprehensive evaluation result module is specifically configured to:
basic data of the photovoltaic power generation unit to be evaluated on each preset long time scale are obtained;
carrying out quantization classification on basic data corresponding to the evaluation index within the limit value of the evaluation index, determining each quantization interval, and obtaining a preset evaluation index quantization value on each quantization interval;
counting probability values of the basic data falling in the quantization interval;
and calculating the comprehensive evaluation result of the photovoltaic power generation unit based on the probability value, the combination weight and the evaluation index quantized value.
10. The system of claim 9, wherein the comprehensive evaluation result of the comprehensive evaluation result module is calculated as follows:
wherein R is the comprehensive evaluation result, beta i Quantized value P for the i-th quantization interval i (j) Probability value, w, of occurrence of jth evaluation index in ith quantization interval j The j-th evaluation index combination weight is that m is the number of evaluation index quantization intervals and n is the number of evaluation indexes.
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| CN117522167B (en) * | 2023-11-21 | 2024-05-24 | 国网青海省电力公司清洁能源发展研究院 | Photovoltaic power station active supporting capability evaluation method and device |
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