CN110378590A - Based on the multiple-energy-source microgrid efficiency of operation evaluation method for improving DEA Model - Google Patents
Based on the multiple-energy-source microgrid efficiency of operation evaluation method for improving DEA Model Download PDFInfo
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Abstract
The present invention relates to one kind based on improvement DEA (Data Envelopment Analysis, DEA) the multiple-energy-source microgrid efficiency of operation evaluation method of model, it is characterized by comprising the following steps: step S1: building multiple-energy-source microgrid efficiency of operation evaluation index system；Step S2: according to multiple-energy-source microgrid efficiency of operation evaluation index system, static three stage DEA models are constructed；Step S3: according to static three stage DEA models, building improves three stage DEA models of dynamic；Step S4: according to three stage DEA moulds of dynamic, overall merit is carried out to multiple-energy-source microgrid efficiency of operation, obtains efficiency rating report.The present invention proposes improved three stage of dynamic DEA method on the basis of traditional DEA method, can obtain comprehensively and effectively multiple-energy-source microgrid efficiency of operation evaluation.
Description
Technical field
The present invention relates to energy sources balance fields, and in particular to a kind of micro- based on the multiple-energy-source for improving DEA Model
Net efficiency of operation evaluation method.
Background technique
Current China is putting forth effort to push energy revolution, constructs modern energy economic system, and integrated energy system is recognized
For the key technology support platform for being promotion energy revolution.As the important carrier of the landing of integrated energy system at this stage, multipotency
The operation of source microgrid should also be as using energy revolution as guiding.
The construction of integrated energy system/multiple-energy-source microgrid and development undoubtedly need to put into a large amount of manpower, material resources and financial resources, in order to
In the key node for pushing the benefit clearly having been achieved with during the landing practice of multiple-energy-source microgrid and the following needs to be promoted, also
Need to study the evaluation method of multiple-energy-source microgrid operation benefits.In this context, multiple-energy-source of the research assessment towards energy revolution
The method of microgrid operation benefits, the development for guidance multiple-energy-source microgrid and integrated energy system, strives for policy economy environment,
Have great importance.
Summary of the invention
In view of this, the purpose of the present invention is to provide a kind of based on the multiple-energy-source microgrid for improving DEA Model
Efficiency of operation evaluation method,
To achieve the above object, the present invention adopts the following technical scheme:
A kind of multiple-energy-source microgrid efficiency of operation evaluation method based on improvement DEA Model, including walk as follows
It is rapid:
Step S1: building multiple-energy-source microgrid efficiency of operation evaluation index system；
Step S2: according to multiple-energy-source microgrid efficiency of operation evaluation index system, static three phase data Envelope Analysis are constructed
Model；
Step S3: according to static three phase data Envelope Analysis models, building improves three phase data Envelope Analysis of dynamic
Model；
Step S4: according to three phase data Envelope Analysis models of dynamic, synthesis is carried out to multiple-energy-source microgrid efficiency of operation and is commented
Valence obtains assessment outcomes.
Further, evaluation index system described in step S1 specifically includes following index: cost of investment, the internal rate of return (IRR),
Investment payback time, abandonment rate abandon light rate, line loss per unit, can call load proportion, block can requirement forecasting accuracy rate, coupling turn
Change efficiency, autonomous device transmission and storage efficiency, primary energy utilization ratio, terminal energy sources utilization rate, pollutant emission rate, the energy
It supplies reliability, energy supply stability, user satisfaction, comprehensive energy and services popularization rate.Index system classification specifically:
(1) according to the general features of multiple-energy-source microgrid, whole indexs are divided into business efficiency, energy efficiency, service water
Flat three categories, business efficiency are used to portray the investment and situation of Profit of project, and energy efficiency is used for analysis system using energy source feelings
Condition, service level index is for reflecting system to the support degree of comprehensive energy users all kinds of in the garden；
(2) according to the basic demand of efficiency rating, index is divided into input pointer and two class of output-index, input pointer
It is the index for representing system operation primary condition, output-index is then to need to obtain by analog simulation or system actual operation
, index that represent system operation result；
(3) according to index value situation, the target setting that value is the bigger the better is positive index, and value is the smaller the better
Index is determined as negative sense index；
(4) index that index value is single fixed value is determined as Static State Index, index value changes, at any time not
With value in the period, different indexs is determined as dynamic indicator.
Further, the step S2 specifically:
Step S21: based on three phase data Envelope Analysis models, for each equipment in micro- energy net, own
The vector of evaluation index is Hj=(h1j,h2j,...,hoj)T, wherein positive index is set as G, negative sense index is set as B, positive index
Vector can be expressed as Gj=(g1j,g2j,...,glj)T, the vector of negative sense index is Bj=(b1j,b2j,...,bwj)T, j is
Each device numbering in micro- energy net, dimension J, o are the number of all evaluation indexes, and dimension O, l are positive index
Number, dimension L, w are the number of negative sense index, dimension W.Then the efficiency value of j-th of micro- energy net equipment can pass through
Following model solution obtains:
First stage model:
minε (2)
In above-mentioned model, ε indicates the efficiency of j-th of micro- energy net equipment, λiIndicate the weight of each index.
Step S22: establishing second stage model on the basis of above-mentioned model, to weaken the influence of negative sense index.
Second stage model:
minε (7)
Step S23: integration is optimized to second stage model, phase III model can be obtained.
Phase III model:
αo>=0 (o=1 ..., O) (16)
βl>=0 (l=1 ..., L) (17)
Wherein, the parameter alpha added in (14) and (15)oWith βlAnd δwFor the influence coefficient of different indexs, by solving the
The device efficiency value of required solution can be obtained in Three-stage Model.
Further, the step S3 specifically:
According to static three phase data Envelope Analysis models, if Xij,tIt indicates for j-th of micro- energy net equipment in the time
I-th of input pointer of section t, Xij,t,gFor positive index, Xij,t,bFor negative sense index, Yrj,tFor r-th of output-index, Yrj,t,g
For positive index, Yrj,t,bFor negative sense index.Zfj,tIndicate j-th of micro- energy net equipment in the index value parameter of time period t,
Reflected index value variable quantity with a upper period compared with of the index in time period t；If a total of T period, input
It index total m, output-index total n, index variable quantity total F, takes:
Then energy net equipment micro- for j-th, there is the objective function of dynamic data envelope analysis model are as follows:
Constraint condition are as follows:
Wherein, ξi、ψrAnd ζfThe respectively efficiency value coefficient of input variable, output variable and variable quantity, requires ξ hereini
≥εj、ψr≥εj, ζf≥εj, formula (20) to (23) is the model of input pointer guiding, take output-index as the model of guiding are as follows:
Further, the step S4 specifically:
The efficiency under dynamic condition is obtained according to step S3 Chinese style (20)~(23) and formula (24)~(27) model solution
Value coefficient: ξi,op、ψr,opAnd ζf,op, then it is directed to j-th of micro- energy net equipment, in the efficiency of time period t are as follows:
The gross efficiency of j-th of micro- energy net equipment are as follows:
Compared with the prior art, the invention has the following beneficial effects:
The present invention proposes improved three phase data Envelope Analysis of dynamic on the basis of traditional data envelope analysis method
Method can obtain comprehensively and effectively multiple-energy-source microgrid efficiency of operation evaluation；For guidance multiple-energy-source microgrid and integrated energy system
Development, strive for policy economy environment, it may have important meaning.
Detailed description of the invention
Fig. 1 is the method for the present invention flow chart；
Fig. 2 is that each garden can call load proportion data in one embodiment of the invention；
Fig. 3 is each garden block load prediction accurate rate in one embodiment of the invention；
Fig. 4 is each garden primary energy utilization ratio in one embodiment of the invention；
Fig. 5 is each garden terminal energy sources utilization rate in one embodiment of the invention；
Fig. 6 is each garden energy supply reliability in one embodiment of the invention；
Fig. 7 is each garden energy supply stability in one embodiment of the invention；
Fig. 8 be in one embodiment of the invention each garden in different time sections efficiency of operation.
Specific embodiment
The present invention will be further described with reference to the accompanying drawings and embodiments.
Referring to Fig.1, the present invention provide it is a kind of based on improve DEA Model multiple-energy-source microgrid efficiency of operation comment
Valence method, includes the following steps:
Step S1: building multiple-energy-source microgrid efficiency of operation evaluation index system；
Step S2: according to multiple-energy-source microgrid efficiency of operation evaluation index system, static three phase data Envelope Analysis are constructed
Model；
Step S3: according to static three phase data Envelope Analysis models, building improves three phase data Envelope Analysis of dynamic
Model；
Step S4: according to three phase data Envelope Analysis models of dynamic, synthesis is carried out to multiple-energy-source microgrid efficiency of operation and is commented
Valence obtains assessment outcomes.
In the present embodiment, evaluation index described in step S1 is classified specifically:
(1) according to the general features of multiple-energy-source microgrid, whole indexs are divided into business efficiency, energy efficiency, service water
Flat three categories, business efficiency are used to portray the investment and situation of Profit of project, and energy efficiency is used for analysis system using energy source feelings
Condition, service level index is for reflecting system to the support degree of comprehensive energy users all kinds of in the garden；
(2) according to the basic demand of efficiency rating, index is divided into input pointer and two class of output-index, input pointer
It is the index for representing system operation primary condition, output-index is then to need to obtain by analog simulation or system actual operation
, index that represent system operation result；
(3) according to index value situation, the target setting that value is the bigger the better is positive index, and value is the smaller the better
Index is determined as negative sense index；
(4) index that index value is single fixed value is determined as Static State Index, index value changes, at any time not
With value in the period, different indexs is determined as dynamic indicator.
The System of Comprehensive Evaluation constructed in step S1 of the present invention is as shown in table 1.
1 assessment indicator system of table
Wherein, (1) can call load proportion.Represent the specific gravity that whole loads are accounted for for the load of calling.Load can be called
Refer to and required according to system call, reduces load within the defined period with smooth peakload, or improve load level
To dissolve the load of clean energy resource.
(2) block energy requirement forecasting accuracy rate.Deep block subdivision is carried out to system, is being carried out with energy requirement forecasting
When, to each block being predicted with energy demand in each period.The index value is whole blocks all
With the average value of energy requirement forecasting accuracy rate in period.
(3) transfer efficiency is coupled.Refer to the transfer efficiency in integrated energy system between the energy such as water, electricity, heat, gas.
(4) autonomous device transmission and storage efficiency.The index represents the energy and deducts transmission in transmission process for equipment
Storage efficiency during the efficiency of transmission and energy stores of loss, release.
(5) energy supply reliability.Represent the index of systems stay power capability, calculation method and power supply reliability class
Seemingly, it is the extension of power supply reliability index:
Wherein, SR is energy supply reliability, TSStop for user's energy that is averaged for time, TTFor the time during statistics.As long as
There are a kind of terminal energy sources to stop supplying, is considered as the energy and stops supplying.
(6) energy supply stability.The index of describing system energy supply quality, it is contemplated that do not have universality also at present
Index portray for stabilizability, therefore calculated using voltage stability index.
(7) comprehensive energy services popularization rate.The specific gravity of the total user of user Zhan of comprehensive energy service is participated in system.
In the present embodiment, the step S2 specifically:
Step S21: based on three phase data Envelope Analysis models, for each equipment in micro- energy net, own
The vector of evaluation index is Hj=(h1j,h2j,...,hoj)T, wherein positive index is set as G, negative sense index is set as B, positive index
Vector can be expressed as Gj=(g1j,g2j,...,glj)T, the vector of negative sense index is Bj=(b1j,b2j,...,bwj)T, j is
Each device numbering in micro- energy net, dimension J, o are the number of all evaluation indexes, and dimension O, l are positive index
Number, dimension L, w are the number of negative sense index, dimension W.Then the efficiency value of j-th of micro- energy net equipment can pass through
Following model solution obtains:
First stage model:
minε (2)
In above-mentioned model, ε indicates the efficiency of j-th of micro- energy net equipment, λiIndicate the weight of each index.
Step S22: establishing second stage model on the basis of above-mentioned model, to weaken the influence of negative sense index.
Second stage model:
minε (7)
Step S23: integration is optimized to second stage model, phase III model can be obtained.
Phase III model:
αo>=0 (o=1 ..., O) (16)
βl>=0 (l=1 ..., L) (17)
Wherein, the parameter alpha added in (14) and (15)oWith βlAnd δwFor the influence coefficient of different indexs, by solving the
The device efficiency value of required solution can be obtained in Three-stage Model.
In the present embodiment, the step S3 specifically:
According to static three phase data Envelope Analysis models, if Xij,tIt indicates for j-th of micro- energy net equipment in the time
I-th of input pointer of section t, Xij,t,gFor positive index, Xij,t,bFor negative sense index, Yrj,tFor r-th of output-index, Yrj,t,g
For positive index, Yrj,t,bFor negative sense index.Zfj,tIndicate j-th of micro- energy net equipment in the index value parameter of time period t,
Reflected index value variable quantity with a upper period compared with of the index in time period t；If a total of T period, input
It index total m, output-index total n, index variable quantity total F, takes:
Then energy net equipment micro- for j-th, there is the objective function of dynamic data envelope analysis model are as follows:
Constraint condition are as follows:
Wherein, ξi、ψrAnd ζfThe respectively efficiency value coefficient of input variable, output variable and variable quantity, requires ξ hereini
≥εj、ψr≥εj, ζf≥εj, formula (20) to (23) is the model of input pointer guiding, take output-index as the model of guiding are as follows:
Further, the step S4 specifically:
The efficiency under dynamic condition is obtained according to step S3 Chinese style (20)~(23) and formula (24)~(27) model solution
Value coefficient: ξi,op、ψr,opAnd ζf,op, then it is directed to j-th of micro- energy net equipment, in the efficiency of time period t are as follows:
The gross efficiency of j-th of micro- energy net equipment are as follows:
The present embodiment selects four, East China, and typically the garden containing distributed wind-powered electricity generation, photovoltaic and cogeneration units is made
For object, DEA Model is solved using CPLEX, the efficiency of operation of each garden is evaluated.
1, basic data
By acquisition, the Static State Index data for obtaining four gardens are as shown in table 2, and dynamic indicator data are shown in attached drawing Fig. 2 extremely
Fig. 7.
Each garden Static State Index evaluation index data of table 2
2, calculated result
Based on three phase data Envelope Analysis models of improvement proposed by the present invention, achievement data is substituted into model, is transported
It is calculated with Matlab software, the efficiency value that can obtain each scheme Static State Index is as shown in table 3, from calculated result it is found that only dividing
In the case where analysing Static State Index, the efficiency highest of garden 2.
Each scheme Static State Index efficiency value of table 3
On this basis, dynamic indicator data substitution model can be solved to obtain each scheme in effect in different time periods
For rate as shown in attached drawing 8, each scheme dynamic indicator gross efficiency is shown in Table 4.
Each scheme dynamic indicator efficiency value of table 4
By table 4 as it can be seen that the dynamic indicator efficiency value of garden 1 is best.Take the static efficiency and dynamic efficiency of four gardens
Average value, can obtain 1 efficiency of garden is 0.987, and garden 2 is 0.989, and garden 3 is 0.947, and garden 4 is 0.946.From calculated result
As can be seen that the comprehensive operation efficiency highest of garden 1.
3, the efficiency of operation key influence factor identification based on sensitivity analysis
After solving and obtaining the efficiency value of different gardens, should also further analyzing influence garden efficiency of operation it is main because
Element provides reference to promote the benefit of similar garden.Therefore, the present invention is by gross efficiency εtotalIt is set as the index of sensitivity analysis,
Influence degree when each index changes in its possible range to gross efficiency value is studied, by neglecting greatly for this influence degree
For sensitivity coefficient and solved.Sensitivity coefficient absolute value is bigger, illustrates influence of the value of the index to gross efficiency value
Also bigger.
According to the basic step and method of single factor analysis in sensitivity analysis, due to input and output-index calculation method
It is identical, for this sentences input pointer, choose a certain index Xij,t, other index values are constant, in Xij,tVariation delta Xij,t
Under the influence of, the variable quantity of gross efficiency value is Δ εtotal.Index of the invention is divided into two class of Static State Index and dynamic indicator, it is contemplated that
Dynamic indicator is list entries and Static State Index is definite value, more to calculated result bring to exclude dynamic indicator data
It influences, the present invention is by dynamic indicator and Static State Index separate computations, when the sensitivity coefficient calculated result of dynamic indicator is each
Between section sensitivity coefficient average value.When index is Static State Index, then there is index Xij,tSensitivity coefficient ρxij,tAre as follows:
When index is dynamic indicator:
The present invention is analysis object with the highest garden 2 of efficiency, by by the changing values of different indexs substitute into formula (30) into
Row calculates, and the sensitivity coefficient that can obtain Static State Index is shown in Table 5.
5 Static State Index sensitivity coefficient of table
The conclusion in terms of calculated result available two: being to represent multiple-energy-source microgrid to carry out polymorphic type energy coupling on the one hand
Close transformation efficiency index sensitivity coefficient be up to 1.976, all indexs of taking the lead in race, due to multiple-energy-source microgrid to provide multiple forms of energy to complement each other, it is more
Energy coupling is coordinated to be main feature, therefore improving the mutual transfer efficiency between various energy resources is to improve the operation of multiple-energy-source microgrid
The key of efficiency.On the other hand, user satisfaction and comprehensive energy service popularization rate respectively reach 1.382 and 1.273, and explanation changes
The use of kind user can be experienced, and promote level of customer service, and promote the important handgrip of multiple-energy-source microgrid efficiency of operation.
Dynamic indicator value is substituted into formula (10) and (31), the sensitivity coefficient of dynamic indicator can be obtained are as follows:
6 dynamic indicator sensitivity coefficient of table
By calculated result it is found that can call load proportion is the most dynamically referred on garden efficiency of operation influence
Mark, primary energy utilization ratio and terminal energy sources utilization rate are only second to that load proportion can be called.Therefore, during system operation,
Whether the multiple-energy-source microgrid that existing garden system or the present invention construct requires sufficiently to call the comprehensive use of user can provide
It improves non-renewable energy to reduce system peak load, consumption clean energy resource, while by providing multiple forms of energy to complement each other and distributing rationally and utilizes in source
Rate and terminal energy sources utilization rate.
The foregoing is merely presently preferred embodiments of the present invention, all equivalent changes done according to scope of the present invention patent with
Modification, is all covered by the present invention.
Claims (5)
1. a kind of based on the multiple-energy-source microgrid efficiency of operation evaluation method for improving DEA Model, which is characterized in that packet
Include following steps:
Step S1: building multiple-energy-source microgrid efficiency of operation evaluation index system；
Step S2: according to multiple-energy-source microgrid efficiency of operation evaluation index system, static three phase data Envelope Analysis models are constructed；
Step S3: according to static three phase data Envelope Analysis models, building improves three phase data Envelope Analysis models of dynamic；
Step S4: according to three phase data Envelope Analysis models of dynamic, overall merit is carried out to multiple-energy-source microgrid efficiency of operation, is obtained
To assessment outcomes.
2. according to claim 1 based on the multiple-energy-source microgrid efficiency of operation evaluation side for improving DEA Model
Method, it is characterised in that:
Step S1: the evaluation index system specifically includes following index: cost of investment, the internal rate of return (IRR), investment payback time, abandoning
Wind rate abandons light rate, line loss per unit, can call load proportion, block energy requirement forecasting accuracy rate, coupling transfer efficiency, independently set
Standby transmission and storage efficiency, primary energy utilization ratio, terminal energy sources utilization rate, pollutant emission rate, energy supply reliability, energy
Source supplies stability, user satisfaction, comprehensive energy and services popularization rate；The evaluation index classification specifically:
(1) according to the general features of multiple-energy-source microgrid, whole indexs are divided into business efficiency, energy efficiency, service level three
Major class, business efficiency are used to portray the investment and situation of Profit of project, and energy efficiency is used for analysis system using energy source situation, clothes
Horizontal index of being engaged in is for reflecting system to the support degree of comprehensive energy users all kinds of in the garden；
(2) according to the basic demand of efficiency rating, index is divided into input pointer and two class of output-index, input pointer is generation
The index of table system operation primary condition, output-index be then need to obtain by analog simulation or system actual operation, generation
The index of table system operation result；
(3) according to index value situation, the target setting that value is the bigger the better is positive index, the smaller the better index of value
It is determined as negative sense index；
(4) index that index value is single fixed value is determined as Static State Index, index value changes, at any time when different
Between in section the different index of value be determined as dynamic indicator.
3. according to claim 1 based on the multiple-energy-source microgrid efficiency of operation evaluation side for improving DEA Model
Method, it is characterised in that: the step S2 is specifically included:
Step S21: based on three phase data Envelope Analysis models, for each equipment in micro- energy net, all evaluations
The vector of index is Hj=(h1j,h2j,...,hoj)T, wherein positive index is set as G, negative sense index is set as B, positive index to
Amount can be expressed as Gj=(g1j,g2j,...,glj)T, the vector of negative sense index is Bj=(b1j,b2j,...,bwj)T, j is micro- energy
Each device numbering in the net of source, dimension J, o are the number of all evaluation indexes, and dimension O, l are the number of positive index,
Its dimension is L, and w is the number of negative sense index, dimension W.Then the efficiency value of j-th of micro- energy net equipment can pass through following mould
Type solves to obtain:
First stage model:
minε (2)
In above-mentioned model, ε indicates the efficiency of j-th of micro- energy net equipment, λiIndicate the weight of each index.
Step S22: establishing second stage model on the basis of above-mentioned model, to weaken the influence of negative sense index.
Second stage model:
minε (7)
Step S23: integration is optimized to second stage model, phase III model can be obtained.
Phase III model:
αo>=0 (o=1 ..., O) (16)
βl>=0 (l=1 ..., L) (17)
Wherein, the parameter alpha added in (14) and (15)oWith βlAnd δwFor the influence coefficient of different indexs, pass through solution third rank
The device efficiency value of required solution can be obtained in segment model.
4. according to claim 1 based on the multiple-energy-source microgrid efficiency of operation evaluation side for improving DEA Model
Method, it is characterised in that: the step S3 is specifically included:
According to static three phase data Envelope Analysis models, if Xij,tIt indicates for j-th of micro- energy net equipment in time period t
I-th of input pointer, Xij,t,gFor positive index, Xij,t,bFor negative sense index, Yrj,tFor r-th of output-index, Yrj,t,gFor forward direction
Index, Yrj,t,bFor negative sense index.Zfj,tJ-th of micro- energy net equipment is indicated in the index value parameter of time period t, reflection refers to
Variable quantity of the index value compared with upper period when being marked on time period t；If a total of T period, the total m of input pointer
It is a, it output-index total n, index variable quantity total F, takes:
Then energy net equipment micro- for j-th, there is the objective function of dynamic data envelope analysis model are as follows:
Constraint condition are as follows:
Wherein, ξi、ψrAnd ζfThe respectively efficiency value coefficient of input variable, output variable and variable quantity, requires ξ hereini≥εj、
ψr≥εj, ζf≥εj, formula (20) to (23) is the model of input pointer guiding, take output-index as the model of guiding are as follows:
5. according to claim 4 based on the multiple-energy-source microgrid efficiency of operation evaluation side for improving DEA Model
Method, it is characterised in that: the step S4 specifically:
The efficiency value system under dynamic condition is obtained according to step S3 Chinese style (20)~(23) and formula (24)~(27) model solution
Number: ξi,op、ψr,opAnd ζf,op, then it is directed to j-th of micro- energy net equipment, in the efficiency of time period t are as follows:
The gross efficiency of j-th of micro- energy net equipment are as follows:
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