CN109492889A - A kind of method for building up and system of energy conservation service project influence property Integrated Evaluation Model - Google Patents
A kind of method for building up and system of energy conservation service project influence property Integrated Evaluation Model Download PDFInfo
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Abstract
The invention discloses the method for building up and system of a kind of energy conservation service project influence property Integrated Evaluation Model, it is related to energy-saving effect evaluation areas, the described method includes: being influenced on energy conservation service project on user side, grid side influences and Generation Side influence is analyzed, building influence property index evaluation system；Based on the influence property index evaluation system, judgment matrix is established using analytic hierarchy process (AHP)；It is modified using weighted value of the entropy assessment to each index in the judgment matrix；Establish energy conservation service project influence property Integrated Evaluation Model.The embodiment of the present invention influences grid side by analysis energy conservation service project, user side influences, supply side influences, building influence property index evaluation system, and integrated use analytic hierarchy process (AHP) and entropy assessment, it establishes more with objectivity and scientific Integrated Evaluation Model, provides reference for the influence property comprehensive assessment of energy conservation service project.
Description
Technical Field
The invention relates to the field of energy-saving effect evaluation, in particular to a method and a system for establishing an energy-saving service project influence comprehensive evaluation model.
Disclosure of Invention
The energy-saving service industry in China is in a rapid development stage, and the service range mainly covers the fields of electric power, buildings and traffic at present. On the user side, improving energy efficiency through various energy saving technologies and services is one of the main forms of energy saving service projects. The number of energy-saving service enterprises is increased in a large scale, and the influence brought by energy-saving service projects is increased day by day.
At present, an energy-saving service company belonging to a power grid company is one of important components of an energy-saving service market, the business emphasis of the energy-saving service company is mainly in the aspect of power saving, and with the increase of energy-saving service projects, the influence of the energy-saving service company on a power grid and the whole power system cannot be ignored. Currently, most energy-saving service projects pay attention to the cost, energy-saving effect and benefits of a single project, and the influence of a plurality of energy-saving service projects in an area on an electric power system is not comprehensively and effectively evaluated.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a method and a system for establishing an energy-saving service project influence comprehensive evaluation model, which can provide reference for scientific evaluation of energy-saving service project influence. The invention can be realized by the following technical scheme:
in a first aspect, a method for establishing an energy-saving service item influence comprehensive evaluation model is provided, the method comprising the steps of:
analyzing the influence of the energy-saving service project on a user side, the influence of a power grid side and the influence of a power generation side, and constructing an influential index evaluation system;
establishing a judgment matrix by adopting an analytic hierarchy process based on the influential index evaluation system;
correcting the weight value of each index in the judgment matrix by adopting an entropy weight method;
and establishing an energy-saving service project influence comprehensive evaluation model.
Further, the analyzing the user-side influence of the energy-saving service item includes:
and dividing the user side load into four types of electric loads: determining, shifting and valley-filling type electric loads and adjustable type electric loads;
based on the energy efficiency power plant theory, analyzing the influence of the energy-saving service project on the theoretical capacity and the peak clipping capacity of various user loads respectively; and
and analyzing the reduction of the power consumption of the user side by the energy-saving service item.
Further, the analyzing the influence of the energy-saving service item on the power grid side includes:
and analyzing the influence of the energy-saving service project on the power transmission and distribution reserve capacity, the system peak regulation characteristic and the power grid frequency modulation.
Further, the analyzing the influence of the energy-saving service item on the system peak shaving characteristics includes:
and judging the influence of the energy efficiency power plant on the peak regulation characteristic of the power grid by comparing the system peak regulation capacity and the system peak regulation capacity ratio before and after the service of the energy efficiency power plant.
Further, the analyzing the influence of the energy-saving service item on the power generation side includes:
and analyzing the influence of the energy-saving service project on installed capacity, pollutant emission and carbon emission.
Further, the establishing of the judgment matrix by using an analytic hierarchy process based on the influential index evaluation system comprises:
establishing a hierarchical structure model diagram based on the influential index evaluation system;
constructing a judgment matrix based on a hierarchical structure model diagram, wherein matrix elements in the judgment matrix are relative importance coefficients obtained by pairwise comparison of relative importance degrees of two factors corresponding to the matrix elements in the judgment matrix;
and carrying out index weight calculation and consistency check on the judgment matrix.
Further, the modifying the index weight value in the determination matrix by using the entropy weight method includes:
standardizing the judgment matrix to obtain a standardized judgment matrix;
calculating entropy values of all indexes in the standardized judgment matrix;
calculating difference coefficients of all indexes in the standardized judgment matrix;
and calculating the index weight value of each index in the standardized judgment matrix.
Further, the comprehensive evaluation model for influence of the energy-saving service items is as follows:
wherein, E-impact assessment value; xj-a normalized value of the jth grid side impact indicator; y isj-a normalized value of the jth user-side impact indicator; zj-normalised value of the jth supply side influence indicator; SXj-the weight of the grid side influencing the jth index; SY (simple and easy) to usej-the user side influences the weight of the jth index; SZj-the weight of the generating side influencing the jth index; lambda-key index adjustment factor, which takes the value 1 or 0.
In a second aspect, a system for establishing an energy-saving service item impact comprehensive assessment model is provided, the system being configured to execute the method for establishing an energy-saving service item impact comprehensive assessment model according to any one of the first aspect.
Through the technical scheme, the method and the system for establishing the comprehensive evaluation model of the influence of the energy-saving service items on the power grid side are characterized in that a comprehensive evaluation index system of the influence of the energy-saving service items on the power grid side power transmission and distribution reserve capacity, the influence of power grid peak regulation, the influence of power grid frequency modulation, the influence of user side load regulation characteristics, the influence of power consumption, the influence of installed capacity of the power generation side, the influence of pollutant emission, the influence of carbon emission and the like is established by analyzing the influence of the energy-saving service items on the power grid side power transmission and distribution reserve capacity, and a hierarchical analysis method and an entropy weight method are comprehensively applied, wherein the weight is initially determined by using a hierarchical analysis method theory, then the index weight is corrected by using an objective weighting method and an entropy method, the advantages of the two methods are fully utilized, and the comprehensive evaluation model with objectivity and scientificity is established, and providing a reference for comprehensive evaluation of influence of the energy-saving service items.
Drawings
Fig. 1 is a flowchart of a method for establishing an energy-saving service item impact comprehensive evaluation model according to an embodiment of the present invention;
fig. 2 is a flowchart of a power grid frequency modulation influence analysis provided in the embodiment of the present invention;
FIG. 3 is a diagram of a hierarchical model provided in accordance with an embodiment of the present invention;
fig. 4 is a diagram of a hierarchical structure according to an embodiment of the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it should be apparent that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention mainly aims at the current situations that the power energy-saving service industry is rapidly developed, energy-saving service projects are rapidly increased, and the influence of the energy-saving service projects on a power system is scientifically and effectively evaluated, and provides a method for establishing an energy-saving service project influence comprehensive evaluation model.
Fig. 1 is a flowchart of a method for establishing an energy-saving service item influence comprehensive assessment model according to an embodiment of the present invention, and as shown in fig. 1, the method for establishing an energy-saving service item influence comprehensive assessment model includes the following steps:
step 101, analyzing the influence of the energy-saving service project on a user side, a power grid side and a power generation side, and constructing an influential index evaluation system.
In this embodiment, the enterprise to be evaluated may be determined by obtaining the enterprise name input by the user, or may be determined in other manners, which is not limited in the present invention.
Wherein, the impact of the energy-saving service item on the user side is analyzed, and the process may include:
the user side load is divided into four types of electric loads: the method comprises the following steps of determining an electric load, randomly using the electric load, shifting peaks and filling valleys and adjusting the electric load;
based on the energy efficiency power plant theory, analyzing the influence of the energy-saving service project on the theoretical capacity and the peak clipping capacity of various user loads respectively; and
and analyzing the reduction of the power consumption of the user side by the energy-saving service item.
In this embodiment, the implementation of the energy saving service item may change the type and the adjustment characteristic of the user side load.
Based on the energy efficiency power plant theory, the influence of the implementation of the energy-saving service project on different power loads is analyzed as follows:
① deterministic electrical load
The deterministic power load is formed by packaging n energy-saving technologies, wherein the operation conditions of all devices are determined, for example, power devices which continuously operate in an enterprise or power devices which regularly operate in the enterprise, so the theoretical capacity of the device is as follows:
wherein, ClDetermining the theoretical capacity of the electrical load; pciThe total power of the equipment before the modification of the ith energy-saving project; pjiFor the ith energy-saving projectThe total power of the modified equipment.
The peak clipping capacity is as follows:
wherein, CxPeak clipping capacity for deterministic electrical loads; pcimaxThe load of the peak load before the electricity saving is changed for the ith energy saving technology; pjimaxThe peak load after the electricity-saving transformation is performed on the ith type energy-saving technology.
② random electric load
The random electric load is formed by packaging n energy-saving technologies, and the operation of each energy-saving device has randomness, so the theoretical capacity is as follows:
wherein, ClThe theoretical capacity of random electric load; pciPeak load before power saving modification for the ith energy saving technology; pjiThe peak load after the electricity-saving transformation is performed on the ith type energy-saving technology.
The peak clipping capacity is as follows:
wherein, Cxα for random peak clipping capacity of electric loadiTransforming the equipment operation concurrence rate for the ith type energy-saving technology; pciThe peak load of the equipment before the electricity-saving transformation is carried out on the ith type energy-saving technology; pjiAnd the peak load of the equipment after the power saving transformation is performed on the ith type energy-saving technology.
③ electric load for peak load shifting
Power utilization with peak shifting and valley fillingThe load is formed by packaging n energy-saving technologies, the energy-saving technology transfers the load requirement in a certain time period to other time periods only through the installation and use of peak shifting equipment, the electric quantity is not saved, but the effect of saving electric power is achieved, so the theoretical capacity C of the energy-saving technology isl0, peak clipping capacity:
wherein, CxThe peak load clipping capacity is a peak shifting valley filling type electric load clipping capacity; pciThe total plant power diverted for the peak and valley shifting plant.
④ adjustable type electric load
With the development of energy storage, especially electricity energy storage service, a large-scale electricity energy storage project can support part of electricity load in a short time, the part of load is the electricity load of interruptible equipment, the method is characterized in that the electricity demand of a power grid in a peak period is reduced through the interruptible load, namely, the interruptible equipment does not run in the peak period, the method mainly comprises electricity load management measures such as interruptible load and demand side response, and the maximum load reduction of the electricity load can be regarded as the theoretical capacity of the electricity load. Therefore, the theoretical capacity and the peak clipping capacity are as follows:
wherein, Cl、CxRespectively representing the theoretical capacity and peak clipping capacity of the electrical load; pciThe total power of the equipment can be effectively interrupted in the peak time period of the power grid.
In this embodiment, based on the energy efficiency power plant theory, the analysis of the energy consumption of the energy saving service project on the user side is as follows:
after being reformed by various energy-saving technologies, the direct influence of the user side is generally the reduction of the power consumption and the reduction of the economic cost, and the evaluation method takes the reduction of the power consumption as the evaluation basis
ΔW＝Wex-Waf
Wherein Δ W is the amount of power saved by the user side in the evaluation period, WexIn order to evaluate the power consumption in a time period before adopting various energy-saving technologies, WafThe power consumption in the time period is evaluated by the user side after adopting various energy-saving technologies.
In this embodiment, the effect of the energy-saving service project on the power grid side is analyzed as follows:
(1) annual power saving and avoiding of power transmission and distribution reserve capacity on the grid side
Annual energy saving quantity of electricity Δ W on the grid sideTComprises the following steps:
in the formula, NTIs the grid loss rate.
Can avoid power transmission and distribution capacity delta PTComprises the following steps:
in the formula, KTThe power transmission and distribution spare capacity coefficient.
(2) Influence of peak regulation characteristic on power grid
The system adjustable capacity is the maximum output force minus the minimum output force of the system. System peak shaving capacity ratio: the adjustable capacity of all the running units in the system accounts for the ratio of the rated total capacity of the units.
The peak shaving capacity of the system before and after the energy-saving service is implemented is shown as follows:
P0＝max(CL(t))-min(CL(t))
in the formula, CL(t) generating power by the generator set;
the specific formula of the peak-shaving capacity ratio of the system before construction of the energy efficiency power plant is as follows:
in the formula, CL(t) is the power output of the generator set, CLNThe rated installed capacity of the generator set.
The peak regulation capacity of the system after construction of the energy efficiency power plant is shown as follows:
P1＝max(CL(t)+C(t))-min(CL(t)+C(t))
in the formula, CL(t) is the output of a generator set, and C (t) is the output of an energy efficiency power plant;
the peak regulation capacity ratio of the system after construction of the energy efficiency power plant is shown as follows:
in the formula, CL(t) power output of the generator set, C (t) power output of the energy efficiency power plant, CLNRated installed capacity for a generator set, CNCapacity is built for energy efficient power plants.
The influence of the energy efficiency power plant on the system peak regulation characteristic is judged by comparing the system peak regulation capacity and the system peak regulation capacity ratio before and after the energy efficiency power plant is constructed, the analysis flow is shown in fig. 2, and fig. 2 is a flow chart of power grid frequency modulation influence analysis provided by the embodiment of the invention.
(3) Influence on frequency modulation of the power grid
After the energy efficiency power plant is put into operation, the power fluctuation of the energy efficiency power plant is injected into an original dynamic system capable of maintaining the power balance, and the power balance of the existing power grid can be influenced to different degrees. Considering the frequency reliability of the power grid from the load side, the frequency static characteristic of the load needs to be considered, when the system frequency changes, the active load of the system changes, and assuming that the output power of the generator set is unchanged in a short time, the output of the energy efficiency power plant can assist in adjusting the active load of the system, so that the frequency deviation of the system is kept not to exceed the allowable range.
Therefore, through the analysis, the frequency modulation calculation of the energy efficiency power plant mainly calculates the adjustable load capacity of the energy efficiency power plant to judge the frequency modulation effect of the energy efficiency power plant, and the adjustable load capacity formula of the energy efficiency power plant is as follows:
in the formula, PNFor the active load of the system,. DELTA.f is the frequency variation, fNAt a rated frequency, KDThe load frequency adjustment effect coefficient is generally 1-3.
In this embodiment, the effect of the energy saving service project on the power generation side is analyzed as follows:
(1) the power generation side can avoid the installed capacity
① year electricity generation
Annual energy production W of energy-efficient power plantGThe annual energy saving of the actual energy-efficient power plant is
In the formula, NGThe power consumption rate of the power plant.
② installed capacity
Installed capacity P of energy-efficient power plantGThat is, the avoidable installed capacity of the energy efficient power plant, essentially the installed capacity of the actual generator set reduced due to the energy efficient power plant constructionAnd (4) demand.
In the formula, KG is a system spare capacity coefficient.
③ hours of power generation
Number of electricity generation hours T of energy efficiency power plant converted by installed capacity of energy efficiency power plantGAnd the annual utilization hours of the generator set of the conventional power plant are different.
TG＝WG/PG
TGThe smaller the value of (A) is, the stronger the peak regulation capability of the energy efficiency power plant is, while the larger the annual utilization hours of the generator set of the conventional power plant is, the higher the utilization rate of the generator set is.
④ service rate
The energy efficiency power plant power consumption rate is the extra power consumption generated after energy-saving transformation divided by the annual power generation capacity, such as the power consumption of a frequency converter increased by frequency conversion transformation or the power consumption of reactive equipment increased by reactive compensation transformation.
l＝Δq/WG
In the formula, l is the plant power consumption rate of the energy-efficiency power plant, Δ q is the annual power consumption of the additionally purchased equipment for energy-saving transformation, and if no additional equipment is added, the plant power consumption rate is 0.
⑤ equivalent generating capacity
The energy efficiency power plant is equivalent to a conventional thermal power plant, and the electricity saving capability/the electricity generating capability of the energy efficiency power plant is represented according to the electricity generating capacity of the energy efficiency power plant converted from the annual electricity generating capacity of the energy efficiency power plant, and is different from the installed capacity.
P′G≈WG/TGC
Of formula (II) to (III)'GFor energy efficient power plantsEquivalent generating capacity; t isGCThe average annual utilization hours of the regional conventional coal-fired units.
(2) Impact of pollutant emissions
① equivalent coal saving
COAL＝ΔWT·Nm
In the formula, COAL is the saving amount of equivalent fire COAL; n is a radical ofmThe average power supply coal consumption of the region is realized.
② equivalent year pollutant discharge reducing amount
According to GB13223-2011 pollutant emission standard of thermal power plant and related documents, the method for determining that CO can be avoided from discharging pollutants in an energy-efficient power plant2、SO2、NOxPM10, wherein:
wherein CO, SO, NO and PM are respectively CO2、SO2、NOxThe amount of PM10 discharged; n is a radical ofCO2、NSO2、NNOx、NPMAre each CO2、SO2、NOxEmission rate of PM 10; kSO2、 KNOxAre each SO2、NOxThe desulfurization and denitrification efficiency.
(3) Influence of carbon emissions
The equivalent coal saving amount is as follows:
C＝COAL·Cm
in the formula, COAL is the saving amount of equivalent fire COAL; n is a radical ofmIs the regional average carbon emission coefficient.
In this embodiment, an influential index evaluation system is constructed, and the process may include:
the influence of the power grid side, the influence of the user side and the influence of the power generation side are first-level indexes for influence evaluation, wherein each first-level index contains 2-3 second-level indexes, the indexes comprise indexes such as power transmission and distribution reserve capacity influence, power grid peak regulation influence, load regulation characteristics and pollutant emission impression, and finally 8 second-level indexes are formed.
In the embodiment of the invention, the influence of the energy-saving service project on the user side, the power grid side and the power generation side is analyzed to construct an influence index evaluation system, so that the influence of the energy-saving service project can be evaluated more comprehensively through different influence indexes in the following process.
And 102, establishing a judgment matrix by adopting an analytic hierarchy process based on the influential index evaluation system.
Because an Analytic Hierarchy Process (AHP) needs to take a multi-target problem to be researched as a system research, a decision system needs to be layered firstly, then a judgment matrix is established according to the importance degree of each relevant factor, and finally each index weight is obtained through a set of quantitative calculation method, so as to provide a basis for final decision.
In this embodiment, based on the influence index evaluation system, an analytic hierarchy process is used to establish the determination matrix, and the process may include:
based on the influential index evaluation system, the establishment of the judgment matrix by adopting an analytic hierarchy process comprises the following steps:
establishing a hierarchical structure model diagram based on an influential index evaluation system;
constructing a judgment matrix based on the hierarchical structure model diagram, wherein matrix elements in the judgment matrix are relative importance coefficients obtained by comparing two factors corresponding to the matrix elements in the judgment matrix in pairs with relative importance degrees;
and performing index weight calculation and consistency check on the judgment matrix.
Specifically, the process of step 102 may include:
① a hierarchical model is constructed, which is classified according to reasonable logic relationship, the target layer is the highest layer of the model, the hierarchical model is the initial target of the hierarchical analysis, the standard layer is the middle layer of the hierarchical model to represent the constraint condition for realizing the initial target, the scheme layer is the lowest layer of the model to represent the scheme and measure realized by the target, and the hierarchical model diagram with subordination relationship is formed by connecting the layers, which is shown in fig. 3.
②, constructing a judgment matrix, ak-B, is constructed by setting the relationship between ak in the A-layer factors and B1, B2, …, B n, as shown in the following Table 1:
TABLE 1 decision matrix
| ak | B1 | B2 | … | Bn |
| B1 | b11 | b12 | … | b1n |
| B2 | b21 | b22 | … | b2n |
| … | … | … | … | … |
| Bn | bn1 | bn2 | … | bnn |
The decision matrix has the following properties: 1, bii ═ 1; bij 1/bji; bij ≧ 0(i, j ═ 1,2, …, n).
And the matrix elements in the judgment matrix are relative importance coefficients obtained after comparing the relative importance degrees of two factors corresponding to the matrix elements in the judgment matrix pairwise.
③ index weight calculation and consistency check, according to the judgment matrix, the characteristic vector omega corresponding to the maximum characteristic root lambda max of the judgment matrix can be obtained, and the calculation formula is:
Pω＝λmaxω
wherein, P is a judgment matrix; ω — a feature vector corresponding to λ max; λ max — maximum characteristic root of P.
The obtained feature vectors are subjected to normalization processing, namely, the importance ranking of the evaluation indexes, namely, the weight distribution of each index.
To check whether the resulting weight distribution is reasonable, a consistency check is performed, the formula being:
wherein, CI-judges the consistency index of the matrix; RI-random consistency index of judgment matrix.
When CR <0.1, the inconsistency degree is considered to be in an allowable range, otherwise, the consistency is not satisfactory, and a judgment matrix needs to be adjusted to meet the consistency requirement.
And 103, correcting the weight value of each index in the judgment matrix by adopting an entropy weight method.
In this embodiment, after each index value is obtained by an analytic hierarchy process, the obtained data is corrected by an entropy weight method.
Specifically, the process of step 103 may include:
standardizing the judgment matrix to obtain a standardized judgment matrix;
calculating entropy values of all indexes in the standardized judgment matrix;
calculating difference coefficients of all indexes in the standardized judgment matrix;
and calculating the index weight value of each index in the standardized judgment matrix.
More specifically, the process of step 103 may include the following:
① data processing, and setting the judgment matrix constructed by the analytic hierarchy process as Pij' normalizing to obtain a matrix Pij。
And (3) forward index standardization:
and (3) reverse index standardization:
② calculating the entropy e of the j indexj。
Wherein,
③ calculating the difference coefficient g of j indexj。
Wherein,
④ calculating the weight ω of the j indexj。
⑤ calculates the final weight Sj after correction.
And step 104, establishing an energy-saving service project influence comprehensive evaluation model.
In this embodiment, the comprehensive evaluation model for influence of the energy saving service item is as follows:
wherein, E-impact assessment value; xj-a normalized value of the jth grid side impact indicator; y isj-a normalized value of the jth user-side impact indicator; zj-normalised value of the jth supply side influence indicator; SXj-the weight of the grid side influencing the jth index; SY (simple and easy) to usej-the user side influences the weight of the jth index; SZj-the weight of the generating side influencing the jth index; lambda-key index adjustment factor, which takes the value 1 or 0.
The method for establishing the comprehensive evaluation model of the influence of the energy-saving service project provided by the embodiment of the invention establishes a comprehensive evaluation index system of the influence of the energy-saving service project on the power transmission and distribution reserve capacity of the power grid side, the influence of the power grid peak regulation, the influence of the power grid frequency regulation, the influence of the load regulation characteristic of the user side, the influence of the power consumption, the influence of the installed capacity of the power generation side, the influence of pollutant emission, the influence of carbon emission and the like by analyzing the influence of the energy-saving service project on the power grid side, the influence of the user side and the influence of the power supply side, and comprehensively applies an analytic hierarchy process, firstly, preliminarily determining the weight by using a hierarchical analysis method theory, then correcting the index weight by using an objective weighting method entropy weight method, fully utilizing the advantages of the two methods, establishing a comprehensive evaluation model with more objectivity and scientificity, and providing reference for the comprehensive evaluation of the influence of the energy-saving service items.
The technical solution of the embodiment of the present invention is further described below by taking an energy saving project of a certain power grid energy saving service company as an example.
According to the influence analysis of the energy-saving service project on the user side, the power grid side and the power supply side, the influence of the power grid side, the influence of the user side and the influence of the power generation side are established as primary indexes for influence evaluation, wherein each primary index contains 2-3 secondary indexes including indexes such as power transmission and distribution reserve capacity influence, power grid peak regulation influence, load regulation characteristics and pollutant emission impression, and finally 8 secondary indexes are formed. The impact evaluation index system constructed can be seen in table 2 below:
TABLE 2 influence evaluation index System
(1) AHP (analytic hierarchy Process) preliminary determination of weights
According to the constructed influence evaluation index system, a constructed hierarchy chart is shown in fig. 4.
(2) Structural judgment matrix
Through project investigation and data statistics, pairwise judgment matrixes of an energy efficiency power plant influence comprehensive evaluation index system are shown in tables 3-6.
TABLE 3 layer A-B decision matrix
| A | B1 | B2 | B3 |
| B1 | 1 | 2 | 3.5 |
| B2 | 1/2 | 1 | 2 |
| B3 | 2/7 | 1/2 | 1 |
TABLE 4B 1-C layer decision matrix
| B1-C | C11 | C12 | C13 |
| C11 | 1 | 3 | 5 |
| C12 | 1/3 | 1 | 2 |
| C13 | 1/5 | 1/2 | 1 |
TABLE 5B 2-C layer decision matrix
| B2-C | C21 | C22 |
| C21 | 1 | 2 |
| C22 | 1/2 | 1 |
TABLE 6B 3-C layer decision matrix
| B3-C | C31 | C32 | C33 |
| C31 | 1 | 3 | 5 |
| C32 | 1/3 | 1 | 4 |
| C33 | 1/5 | 1/4 | 1 |
(3) AHP weight calculation
And respectively calculating the weights of the primary indexes and the secondary indexes to finally obtain the AHP comprehensive weight of each index, as shown in table 7.
TABLE 7 ANP weight calculation
(4) Consistency check
The random consistency ratio CR values were calculated as shown in table 8.
TABLE 8 decision matrix CR values
| Judgment matrix | A-B | B1-C | B3-C |
| CR value | 0.0019 | 0.0036 | 0.0825 |
From table 8, it can be seen that CR were all less than 0.1, i.e., the decision matrix passed the consistency check.
In order to make up for the subjectivity of the comprehensive benefit evaluation index determined by the analytic hierarchy process, the objective weighting method, namely the entropy weighting method, is adopted to correct the weight obtained by the AHP method, and the interference of subjective randomness on the weighting result of the AHP is weakened, so that the weight of each index is obtained more accurately. The detailed process of entropy weight correction will now be described by taking the weight of the index of the layer A-B as an example.
(1) And (5) standardizing the AHP judgment matrix. Because the indexes of the A-B layers are all positive indexes, namely the larger the indexes are, the better the indexes are, the AHP judgment matrix is standardized, so that the values of all elements of the new matrix are all [0,1], and the processed matrix is shown as a table 9.
TABLE 9A-B layer normalization matrix
| A | B1 | B2 | B3 |
| B1 | 1.000000 | 1.000000 | 1.000000 |
| B2 | 0.300000 | 0.333333 | 0.400000 |
| B3 | 0.000000 | 0.000000 | 0.000000 |
(2) Substituting the related parameters into the entropy values e of the calculation indexes B1, B2 and B31，e2，e3。
(3) Substituting the related parameters into a formula to calculate the difference coefficient g of the indexes B1, B2 and B31，g2， g3。
Ee＝e1+e2+e3＝0.4917+0.5119+0.5446+1.5482
(4) The weights ω 1, ω 2, and ω 3 of the indices B1, B2, and B3 are 0.3501, 0.3362, and 0.3137, respectively. Obtaining the index weights S of the corrected B1, B2 and B31，S2，S3。
Similarly, the final weight values of the indexes of each layer can be obtained by correcting the indexes of the B1-C, B2-C and B3-C layers by using an AHP-entropy weight method, and the final results are shown in Table 10.
TABLE 10 AHP-entropy weight method comprehensive determination of final weights
The final correction result shows that the AHP-entropy method weakens the subjective randomness and the weighted deviation caused by insufficient samples, the proper adjustment is carried out on the premise of ensuring the larger weight of important indexes, and the scientific and effective evaluation of the influence of the energy-saving service project on the power system can be ensured.
According to the 8 indexes and the comprehensive weight thereof, in combination with the specific requirements of each index, selecting the influence of the power grid side as a key index, and the rest of the indexes are non-key indexes, and establishing a final comprehensive evaluation model of the influence of the energy-saving service project as follows:
wherein, E-impact assessment value; xj-a normalized value of the jth grid side impact indicator; y isj-a normalized value of the jth user-side impact indicator; zj-normalised value of the jth supply side influence indicator; SXj-the weight of the grid side influencing the jth index; SY (simple and easy) to usej-the user side influences the weight of the jth index; SZj-the weight of the generating side influencing the jth index; lambda-key index adjustment factor, which takes the value 1 or 0.
The larger the E value of the comprehensive evaluation model is, the larger the influence of the energy-saving service item is, and conversely, the smaller the influence of the energy-saving service item is.
In addition, the embodiment of the invention also provides a system for establishing the comprehensive evaluation model of the influence of the energy-saving service item, and the system is used for executing the method for establishing the comprehensive evaluation model of the influence of the energy-saving service item.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program instructing relevant hardware, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a magnetic disk, an optical disk, or the like.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, but rather as the subject matter of the invention is to be construed in all aspects and as broadly as possible, and all changes, equivalents and modifications that fall within the true spirit and scope of the invention are therefore intended to be embraced therein.
Claims (9)
1. A method for establishing an energy-saving service item influence comprehensive evaluation model is characterized by comprising the following steps:
analyzing the influence of the energy-saving service project on a user side, the influence of a power grid side and the influence of a power generation side, and constructing an influential index evaluation system;
establishing a judgment matrix by adopting an analytic hierarchy process based on the influential index evaluation system;
correcting the weight value of each index in the judgment matrix by adopting an entropy weight method;
and establishing an energy-saving service project influence comprehensive evaluation model.
2. The method of claim 1, wherein analyzing the user-side impact of energy saving service items comprises:
and dividing the user side load into four types of electric loads: determining, shifting and valley-filling type power loads and adjustable type power loads;
based on the energy efficiency power plant theory, analyzing the influence of the energy-saving service project on the theoretical capacity and the peak clipping capacity of various user loads respectively; and
and analyzing the reduction of the power consumption of the user side by the energy-saving service item.
3. The method of claim 1, wherein analyzing grid-side impact of energy saving services comprises:
and analyzing the influence of the energy-saving service project on the power transmission and distribution reserve capacity, the system peak regulation characteristic and the power grid frequency modulation.
4. The method of claim 3, wherein analyzing the impact of energy saving service items on system peak shaving characteristics comprises:
and judging the influence of the energy efficiency power plant on the peak regulation characteristic of the power grid by comparing the system peak regulation capacity and the system peak regulation capacity ratio before and after the service of the energy efficiency power plant.
5. The method of claim 1, wherein analyzing the impact of energy saving services on the power generation side comprises:
and analyzing the influence of the energy-saving service project on installed capacity, pollutant emission and carbon emission.
6. The method according to any one of claims 1 to 5, wherein the establishing a judgment matrix by using an analytic hierarchy process based on the influential index evaluation system comprises:
establishing a hierarchical structure model diagram based on the influential index evaluation system;
constructing a judgment matrix based on a hierarchical structure model diagram, wherein matrix elements in the judgment matrix are relative importance coefficients obtained by pairwise comparison of relative importance degrees of two factors corresponding to the matrix elements in the judgment matrix;
and carrying out index weight calculation and consistency check on the judgment matrix.
7. The method of claim 1, wherein modifying the indicator weight values in the decision matrix using an entropy weight method comprises:
standardizing the judgment matrix to obtain a standardized judgment matrix;
calculating entropy values of all indexes in the standardized judgment matrix;
calculating difference coefficients of all indexes in the standardized judgment matrix;
and calculating the index weight value of each index in the standardized judgment matrix.
8. The method of claim 1, wherein the energy-saving service item impact comprehensive assessment model is:
wherein, E-impact assessment value; xj-a normalized value of the jth grid side impact indicator; y isj-a normalized value of the jth user-side impact indicator; zj-a normalized value of the jth supply side influence indicator; SXj-the weight of the grid side influencing the jth index; SY (simple and easy) to usej-the user side influences the weight of the jth index; SZj-the weight of the generating side influencing the jth index; lambda-Key fingerAnd the value of the standard adjustment factor is 1 or 0.
9. An establishment system of an energy-saving service item influence comprehensive assessment model, characterized in that the system is used for executing the establishment method of the energy-saving service item influence comprehensive assessment model according to any one of claims 1 to 8.
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