CN107766970A - A kind of micro-capacitance sensor planing method based on the performance of enterprises and Consumer's Experience - Google Patents
A kind of micro-capacitance sensor planing method based on the performance of enterprises and Consumer's Experience Download PDFInfo
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Abstract
The invention discloses a kind of micro-capacitance sensor planing method based on the performance of enterprises and Consumer's Experience, this method is included with the upper strata plan model of the minimum object function of Enterprise Integrated financial cost and the Bi-level Programming Models with lower floor's plan model of the minimum object function of user's outage cost expectation by establishing, due in Bi-level Programming Models, on, bi-directional data transmission be present in lower floor's plan model, the program results of upper strata plan model it is expected the user's outage cost for influenceing lower floor's plan model, and user's outage cost of lower floor's plan model it is expected after feeding back to upper strata plan model, program results will be influenceed again, and final program results will make upper strata plan model relative optimal with lower floor plan model, Bi-level Programming Models reach global optimum.Therefore, the present invention can take into account different interests demand between power supply enterprise and user, program results is had actual directive significance.
Description
Technical field
The invention belongs to Power System Planning technical field.It is more particularly to a kind of micro- based on the performance of enterprises and Consumer's Experience
Electric power network planning method.
Background technology
Distributing rationally for micro-capacitance sensor is the key problem for needing the micro-capacitance sensor design phase to consider, at present, domestic and international expert is
Certain research has been carried out to distributing rationally for micro-capacitance sensor.Wherein, for self micro-capacitance sensor, some researchs are main to consider that load lacks
Electric rate, and establish mixed economy cost minimization allocation models；And grid type micro-capacitance sensor is directed to, some researchs consider different self-balancings
Degree, redundancy, renewable energy utilization rate, and establish cost minimal configuration model.But these researchs are all based on to exchange mother
The micro-capacitance sensor of line network construction form, compared to exchange micro-capacitance sensor, direct-current grid is simple in construction, conversion links are few, energy utilization rate
Height, at the same DC micro-electric web frame system in be not present AC system in frequency stabilization, reactive power the problems such as, can ensure
The highly reliable power supply of system internal loading, has been widely used in the distributed generation system of Small And Medium Capacity.But currently for micro-
The achievement in research of network optimization configuration not using user as Interest Main Body, i.e., is not examined only using power supply enterprise as major benefit side
The Game Relationship of different interests demand between worry different subjects so that the actual directive significance of program results has been short of, and causes to be permitted
The micro-capacitance sensor engineering built up more, operation of losing money always, or even some micro-capacitance sensor engineerings have only been run the short time and just stopped transport,
The wasting of resources is not only caused, also hinders the marketization transformation of micro-capacitance sensor.
The content of the invention
It is an object of the invention to：A kind of micro- electricity of the Game Relationship of different interests demand between power supply enterprise and user is provided
Net Optimal Configuration Method, make program results that there is actual directive significance.
In order to realize foregoing invention purpose, the invention provides following technical scheme：
A kind of micro-capacitance sensor planing method based on the performance of enterprises and Consumer's Experience, it includes,
Step 1：Establish Bi-level Programming Models；
Wherein, the upper strata plan model in the Bi-level Programming Models is：
Object function：MinF=C1+C2+C3+C4+C5
Constraints：
In the object function, F be power supply enterprise mixed economy cost, C1For the cost of investment of micro-capacitance sensor, C2For micro- electricity
The O＆M cost of net, C3For the energetic interaction cost of micro-capacitance sensor and power distribution network, C4For the displacement cost of micro-capacitance sensor and power distribution network, C5
For environmental improvement cost；
In the constraints, N be distributed power source quantity, NmaxAllow the maximum for installing distributed power source for scene
Quantity；PDGFor the power output of distributed power source, PexPower, P are exchanged with power distribution network for micro-capacitance sensorloadFor load power, μ is micro-
Grid generation amount nargin；SOC (t) is t accumulator electric-quantity, SOCminAnd SOCmaxThe respectively lower limit of battery dump energy
Value and higher limit；PGCCThe power that interacts for micro-capacitance sensor with power distribution network, PGCC-rateFor micro-capacitance sensor work(is interacted with the maximum of power distribution network
Rate；
Lower floor's plan model in the Bi-level Programming Models is：
Object function：
In the object function,
F is user
Outage cost always it is expected；EEENSFor user's outage cost it is expected, Δ t be preset time section, EEENS 1It is receptible most for user
Small short of electricity expectation, EEENS 2It is expected for the receptible maximum short of electricity of user, IEARFor user's outage cost Assessment Rate；EEDNSFor micro- electricity
Net short of electricity it is expected；PsFor micro-capacitance sensor state s short of electricity amounts, ρLOLPFor short of electricity probability in preset time, M is that state sampling is total, m (s)
The number occurred for state s in sampling, Z are power shortage state collection in preset time；
Step 2：The Bi-level Programming Models are solved, make the upper strata plan model relative with lower floor's plan model
Optimal program results.
According to a kind of specific embodiment, the micro-capacitance sensor planing method of the invention based on the performance of enterprises and Consumer's Experience
The step of two in, when solving the Bi-level Programming Models, according to the KK-T conditions of lower floor's plan model, the upper strata is advised
Model and lower floor planning mould decoupling are drawn, the Bi-level Programming Models is converted into single level programming model；Wherein, on described
Under conditions of planning that the quantity N of distributed power source in layer model is given, the Lagrangian of lower floor's plan model is：
Wherein, ρ=ρLOLP-ρLOLP_max；Therefore, the KK-T conditions of lower floor's plan model are：
According to a kind of specific embodiment, the micro-capacitance sensor planing method of the invention based on the performance of enterprises and Consumer's Experience
The step of two in, by the upper strata plan model and the lower floor planning mould decoupling after, asked with reference to ant group algorithm and genetic algorithm
Solve program results；Wherein, ant group algorithm is the initial solution that genetic algorithm provides.
Compared with prior art, beneficial effects of the present invention：
The present invention is included with the upper strata plan model of the minimum target of Enterprise Integrated financial cost and with user by establishing
Outage cost it is expected the Bi-level Programming Models of lower floor's plan model of minimum target, due in Bi-level Programming Models, upper and lower layer
There is bi-directional data transmission in plan model, the program results of upper strata plan model damages the user's short of electricity for influenceing lower floor's plan model
Be overdue schedule time prestige, and user's outage cost of lower floor's plan model it is expected after feeding back to upper strata plan model, will influence program results again,
And final program results will make upper strata plan model relative optimal with lower floor plan model, Bi-level Programming Models reach it is global most
It is excellent.Therefore, the present invention can take into account different interests demand between power supply enterprise and user, make program results that there is actual guidance to anticipate
Justice.
Brief description of the drawings：
Fig. 1 is the flow chart of the present invention；
Fig. 2 is a kind of grid type direct-current grid structural representation of practical application；
Fig. 3 is wind speed curve figure of the grid type direct-current grid in practical application in Fig. 2；
Fig. 4 is illumination curve map of the grid type direct-current grid in practical application in Fig. 2；
Fig. 5 is load chart of the grid type direct-current grid in practical application in Fig. 2.
Embodiment
With reference to test example and embodiment, the present invention is described in further detail.But this should not be understood
Following embodiment is only limitted to for the scope of the above-mentioned theme of the present invention, it is all that this is belonged to based on the technology that present invention is realized
The scope of invention.
Flow chart of the invention with reference to shown in Fig. 1；Wherein, the micro-capacitance sensor of the invention based on the performance of enterprises and Consumer's Experience
Planing method includes：
Step 1：Bi-level Programming Models are established, Bi-level Programming Models include upper strata plan model and lower floor's plan model.
Wherein, the upper strata plan model in Bi-level Programming Models is：
Object function：MinF=C1+C2+C3+C4+C5
Constraints：
And in object function, F be power supply enterprise mixed economy cost, C1For the cost of investment of micro-capacitance sensor, C2For micro-capacitance sensor
O＆M cost, C3For the energetic interaction cost of micro-capacitance sensor and power distribution network, C4For the displacement cost of micro-capacitance sensor and power distribution network, C5For
Environmental improvement cost；
In constraints, N be distributed power source quantity, NmaxAllow the maximum quantity for installing distributed power source for scene；
PDGFor the power output of distributed power source, PexPower, P are exchanged with power distribution network for micro-capacitance sensorloadFor load power, μ is micro-capacitance sensor
Generated energy nargin；SOC (t) is t accumulator electric-quantity, SOCminAnd SOCmaxRespectively the lower limit of battery dump energy and
Higher limit；PGCCThe power that interacts for micro-capacitance sensor with power distribution network, PGCC-rateFor micro-capacitance sensor power is interacted with the maximum of power distribution network.
Lower floor's plan model in Bi-level Programming Models is：
Object function：
Moreover, in object function,
F is user
Outage cost always it is expected；EEENSFor user's outage cost it is expected, Δ t be preset time section, EEENS 1It is receptible most for user
Small short of electricity expectation, EEENS 2It is expected for the receptible maximum short of electricity of user, IEARFor user's outage cost Assessment Rate；EEDNSFor micro- electricity
Net short of electricity it is expected；PsFor micro-capacitance sensor state s short of electricity amounts, ρLOLPFor short of electricity probability in preset time, M is that state sampling is total, m (s)
The number occurred for state s in sampling, Z are power shortage state collection in preset time.
Step 2：The Bi-level Programming Models that solution procedure one is established, make upper strata plan model and lower floor's plan model phase
To optimal.Because in Bi-level Programming Models, there is bi-directional data transmission, the planning of upper strata plan model in upper and lower layer plan model
As a result the user's outage cost for influenceing lower floor's plan model it is expected, and user's outage cost of lower floor's plan model it is expected feedback
To the plan model of upper strata, program results will be influenceed again, and final program results will be such that upper strata plan model is planned with lower floor
Model is relatively optimal, and Bi-level Programming Models reach global optimum.Therefore, the present invention can take into account different between power supply enterprise and user
Interests demand, make program results that there is actual directive significance.
A kind of grid type direct-current grid structural representation of practical application with reference to shown in Fig. 2；Wherein, micro-grid system
In distributed power source include wind-driven generator, photovoltaic array, battery, diesel-driven generator and grid-connected transverter.Meanwhile wind-force
Generator unit rated capacity is 30kW, and photovoltaic array component single group rated capacity is 30kW, the specified appearance of diesel-driven generator separate unit
Measure as 30kW, the single group rated capacity of battery is 10kWh, and system life cycle management is 20 years, discount rate 6%, electric power storage
The charge and discharge efficiency in pond is 85%.The facility information of specific micro-grid system is as shown in table 1.Moreover, enable diesel-driven generator
When, caused pollutant and greenhouse gases relevant parameter is as shown in table 2.
Table 1：Micro-grid system facility information table
Table 2：Pollutant and greenhouse gases relevant parameter table
Meanwhile when micro-capacitance sensor and power distribution network progress energetic interaction, using tou power price charging, electric price parameter is as shown in table 3,
Wherein the peak period is 7:00—11:00、19:00—23:00, usually section is 11:00—19:00, the paddy period is 23:00—7:
00。
Table 3：Electric price parameter table
Therefore, can be obtained according to above- mentioned information：
The cost of investment C of micro-capacitance sensor1'=CwtNwt+CpvNpv+CesNes+CdeNde+CGCC.Wherein, Cwt、Cpv、CesAnd CdePoint
Wei not wind-driven generator, photovoltaic array, initial outlay cost (including the equipment purchase expense of battery and diesel-driven generator separate unit
And mounting cost)；Nwt、Npv、Nes、NdeRespectively wind-driven generator, photovoltaic array, battery and diesel-driven generator quantity；CGCC
For grid-connected transverter initial outlay cost；fcrFor coefficient of depreciation, it is defined as fcr=r (1+r)n/[(1+r)n- 1], n is the full longevity
Service life in cycle is ordered, r is discount rate.
The O＆M cost of micro-capacitance sensorWherein, Cwt om、
Cpv om、Ces omAnd Cde omThe operation of wind-driven generator, photovoltaic cell, battery and diesel-driven generator is tieed up respectively in unit power
Protect cost；Pwt、Ppv、PesAnd PdeThe respectively reality output work(of wind-driven generator, photovoltaic cell, battery, diesel-driven generator
Rate；CGCC omFor the operation and maintenance cost of grid-connected transverter.
The energetic interaction cost of micro-capacitance sensor and power distribution networkΔ t is preset time section (list
Position：h)；T is the total hop count of annual timing statisticses in system life cycle management, wherein, Csold、CbuyRespectively system is sold to power distribution network
The expense of electricity and power purchase.
Because the life of storage battery is shorter, less than life cycle management.Therefore, the displacement cost of micro-capacitance sensor and power distribution networkWherein,For the displacement cost of battery in life cycle management.
By emission greenhouse gas and pollutant when diesel-driven generator is run, year environmental improvement cost is producedWherein, CejFor the environmental value of jth item pollutant unit power；M is pollutant
With greenhouse gases species.
In order to embody the game mechanism of dual layer resist, build following 3 scenes and be compared.
Scene 1：Using the mixed economy cost minimization of enterprise as object function, user's outage cost it is expected to be set to constrain
Condition, no more than 10000 units.
Scene 2：Minimum it is expected as object function using user's outage cost, by the mixed economy of system investments operation enterprise
Cost is set to constraints, no more than 550,000 yuan.
Scene 3：Solved using the Bi-level Programming Models of the present invention.Based on above parameter, using GA-ACO algorithms (heredity-
Ant group algorithm) solve, it is as shown in table 4 to finally obtain different program resultses.
Table 4：The program results table of scene 1~3
As can be seen from Table 4, though scene 1 can realize that the mixed economy cost minimization of enterprise (is reduced than this paper program results
11.41%), but user's outage cost it is expected that larger (575.89%) higher than this paper program results, may cause user power utilization body
It is low to test satisfaction, low to enterprises service satisfaction, the good relationship for being unfavorable for enterprise and user develops.Scene 2 can guarantee that user
Outage cost it is expected to reach minimum (not short of electricity), but the mixed economy cost of enterprise is huge (than the increase of this paper program results
37.57%) it is, totally unfavorable to enterprise.
Therefore, the program results obtained using micro-capacitance sensor planing method of the present invention based on the performance of enterprises and Consumer's Experience,
Can be when the mixed economy cost increasing degree that enterprise puts into be relatively small, user's outage cost it is expected to be obviously reduced, favorably
Satisfaction and lifting to enterprise's satisfaction are experienced in user power utilization.
Claims (3)
- A kind of 1. micro-capacitance sensor planing method based on the performance of enterprises and Consumer's Experience, it is characterised in that including,Step 1：Establish Bi-level Programming Models；Wherein, the upper strata plan model in the Bi-level Programming Models is：Object function：Min F=C1+C2+C3+C4+C5Constraints：In the object function, F be power supply enterprise mixed economy cost, C1For the cost of investment of micro-capacitance sensor, C2For micro-capacitance sensor O＆M cost, C3For the energetic interaction cost of micro-capacitance sensor and power distribution network, C4For the displacement cost of micro-capacitance sensor and power distribution network, C5For ring Border treatment cost；In the constraints, N be distributed power source quantity, NmaxAllow the maximum quantity for installing distributed power source for scene； PDGFor the power output of distributed power source, PexPower, P are exchanged with power distribution network for micro-capacitance sensorloadFor load power, μ is micro-capacitance sensor Generated energy nargin；SOC (t) is t accumulator electric-quantity, SOCminAnd SOCmaxRespectively the lower limit of battery dump energy and Higher limit；PGCCThe power that interacts for micro-capacitance sensor with power distribution network, PGCC-rateFor micro-capacitance sensor power is interacted with the maximum of power distribution network；Lower floor's plan model in the Bi-level Programming Models is：Object function：In the object function,F is user's short of electricity Loss is total it is expected；EEENSFor user's outage cost it is expected, Δ t be preset time section, EEENS 1It is receptible minimum scarce for user Electricity expectation, EEENS 2It is expected for the receptible maximum short of electricity of user, IEARFor user's outage cost Assessment Rate；EEDNSLacked for micro-capacitance sensor Electricity it is expected；PsFor micro-capacitance sensor state s short of electricity amounts, ρLOLPFor short of electricity probability in preset time, M is state sampling sum, and m (s) is to take out The number that state s occurs in sample, Z are power shortage state collection in preset time；Step 2：The Bi-level Programming Models are solved, obtain making the upper strata plan model relative with lower floor's plan model Optimal program results.
- 2. the micro-capacitance sensor planing method based on the performance of enterprises and Consumer's Experience as claimed in claim 1, it is characterised in that step In two, when solving the Bi-level Programming Models, according to the KK-T conditions of lower floor's plan model, by the upper strata plan model With lower floor planning mould decoupling, the Bi-level Programming Models are made to be converted into single level programming model；Wherein, the planning layer on described Under conditions of the quantity N of distributed power source is given in model, the Lagrangian of lower floor's plan model is：<mrow> <mi>L</mi> <mrow> <mo>(</mo> <mi>N</mi> <mo>)</mo> </mrow> <mo>=</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>&Delta;</mi> <mi>t</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>T</mi> </munderover> <msub> <mi>&rho;</mi> <mrow> <mi>L</mi> <mi>O</mi> <mi>L</mi> <mi>P</mi> </mrow> </msub> <mo>&times;</mo> <msub> <mi>P</mi> <mi>s</mi> </msub> <mo>&times;</mo> <mi>&Delta;</mi> <mi>t</mi> <mo>&times;</mo> <msub> <mi>I</mi> <mrow> <mi>E</mi> <mi>A</mi> <mi>R</mi> </mrow> </msub> <mo>-</mo> <mi>&lambda;</mi> <mi>&rho;</mi> </mrow>Wherein, ρ=ρLOLP-ρLOLP_max；Therefore, the KK-T conditions of lower floor's plan model are：<mrow> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <munderover> <mo>&Sigma;</mo> <mrow> <mi>&Delta;</mi> <mi>t</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>T</mi> </munderover> <msub> <mi>P</mi> <mi>s</mi> </msub> <mo>&times;</mo> <mi>&Delta;</mi> <mi>t</mi> <mo>&times;</mo> <msub> <mi>I</mi> <mrow> <mi>E</mi> <mi>A</mi> <mi>R</mi> </mrow> </msub> <mo>-</mo> <mi>&lambda;</mi> <mo>=</mo> <mn>0</mn> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mi>&lambda;</mi> <mrow> <mo>(</mo> <msub> <mi>&rho;</mi> <mrow> <mi>L</mi> <mi>O</mi> <mi>L</mi> <mi>P</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>&rho;</mi> <mrow> <mi>L</mi> <mi>O</mi> <mi>L</mi> <mi>P</mi> <mo>_</mo> <mi>max</mi> </mrow> </msub> <mo>)</mo> </mrow> <mo>=</mo> <mn>0</mn> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mi>&lambda;</mi> <mo>&GreaterEqual;</mo> <mn>0</mn> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>.</mo> </mrow>
- 3. the micro-capacitance sensor planing method based on the performance of enterprises and Consumer's Experience as claimed in claim 2, it is characterised in that by institute After stating upper strata plan model and lower floor planning mould decoupling, program results is solved with reference to ant group algorithm and genetic algorithm；Wherein, Ant group algorithm is the initial solution that genetic algorithm provides.
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