CN109327042A - A kind of micro-grid multi-energy joint optimal operation method - Google Patents

A kind of micro-grid multi-energy joint optimal operation method Download PDF

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CN109327042A
CN109327042A CN201811129669.5A CN201811129669A CN109327042A CN 109327042 A CN109327042 A CN 109327042A CN 201811129669 A CN201811129669 A CN 201811129669A CN 109327042 A CN109327042 A CN 109327042A
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energy storage
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CN109327042B (en
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高辉
宋乐
宋伟
曹佳男
虞小辉
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Nanjing Post and Telecommunication University
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/76—Power conversion electric or electronic aspects

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The present invention relates to a kind of micro-grid multi-energy joint optimal operation methods, including step 1, contributed based on powering device under different scenes situation and energy storage device operating status, build the physical model of multi-energy system；Step 2 establishes micro-grid multi-energy system each unit mathematical model, including wind-driven generator model, photovoltaic power generation model, micro turbine model, fuel cell mode and energy storage model；Step 3, the minimum target of comprehensive cost run with system are comprehensively considered the coupled characteristic between operation constraint, system security constraint and the multiple-energy-source of each DG, establish micro-grid multi-energy Optimal Operation Model；Step 4 solves micro-grid multi-energy Optimized model based on backward Dynamic Programming, obtains microgrid multiple-energy-source combined optimization operation reserve.The present invention can satisfy the operation demand under different scenes, provide electricity, heat coordination optimization scheduling scheme in the operation of different scenes for comprehensive energy microgrid, overall operation efficiency is higher, and economic benefit is more preferable.

Description

A kind of micro-grid multi-energy joint optimal operation method
Technical field
The present invention relates to a kind of micro-grid multi-energy joint optimal operation methods, belong to micro-capacitance sensor Optimized Operation device neck Domain.
Background technique
Contain photovoltaic, wind-powered electricity generation, energy storage, earth source heat pump, solar energy thermal-power-generating, fuel gas generation, biomass power generation in micro-capacitance sensor Equal multiple types distribution type renewable energy, distributed generation resource permeability is high, and the new energy such as photovoltaic, wind-powered electricity generation go out fluctuation compared with Greatly, network topology is complicated, brings biggish challenge to the flexible controllable scheduling of active distribution network.It can comprehensively consider various Factor, how the operational plan of reasonable arrangement these micro batteries, guarantee that micro-capacitance sensor all meets burden requirement in different periods, together The high-quality operation of Shi Shixian micro-capacitance sensor is an outstanding problem in micro-capacitance sensor research.
Summary of the invention
The technical problem to be solved by the present invention is to overcome the deficiencies of the prior art and provide a kind of micro-grid multi-energy connection Optimization Scheduling is closed, establishes micro-grid multi-energy joint optimal operation model, microgrid multi-energy system can promote energy step Using, reduce pollutant emission, enhancing energy supplying system economic benefit, it is short that the energy caused by rapid economic development is effectively relieved It lacks and environmental degradation problem.
The present invention provides a kind of micro-grid multi-energy joint optimal operation method, includes the following steps,
Step 1, contributed based on powering device under different scenes situation and energy storage device operating status, build multiple-energy-source system The physical model of system；
Step 2 establishes micro-grid multi-energy system each unit mathematical model, including wind-driven generator model, photovoltaic power generation Model, micro turbine model, fuel cell mode and energy storage model；
Step 3, the minimum comprehensive cost run using system comprehensively consider operation constraint, the system safety of each DG as target Coupled characteristic between constraint and multiple-energy-source, establishes micro-grid multi-energy Optimal Operation Model；Wherein, DG is distributed electrical Source, including photovoltaic, wind-force, fuel cell, micro turbine；
Step 4: micro-grid multi-energy Optimized model being solved based on backward Dynamic Programming, obtains microgrid multiple-energy-source Combined optimization operation reserve.
As further technical solution of the present invention, the physical model of multi-energy system includes distribution in the step 1 Renewable energy, cogeneration unit, hot energy storage, electric energy storage and other controllability distributed generation resources, the multi-energy system are same When at least provided for load heat, electric energy supply, and between electric power networks and ther mal network be based on the mutual coupling of cogeneration units phase It closes；To guarantee heat, the equilibrium of supply and demand of electric flux, electric load aspect, when electric energy surplus in system, by batteries to store energy simultaneously Received or be transported to outward low-voltage network, starting backup power source is supported when electric energy deficiency；In terms of thermic load, Miniature gas turbine utilizes the advantage of its cogeneration synthesis high efficiency, and to meet the needs of thermic load, power output should be according to being System carrys out integrated decision-making in the thermoelectricity load ratio of day part and the price of the various energy, when miniature gas turbine heat supply surplus, It is received by hot energy storage, avoids the waste of resource；When miniature gas turbine heat supply deficiency, by external additional combustion boiler and hot energy storage It is supplemented simultaneously.
Further, the specific steps of the step 2 are as follows: establish respectively wind-driven generator model, photovoltaic power generation model, Micro turbine model, fuel cell mode, energy storage model；
Step 2.1, the wind-driven generator model,
The probability density function expression formula of the wind speed statistics description of wind-driven generator are as follows:
In formula, v is wind speed；K and c is two important parameters of Weibull distribution, and k is form parameter, k > 0；C is known as Scale parameter, c > 1；
The output power P of wind-driven generatorWTFollowing piecewise function relationship approximate representation can be used in relationship between wind speed v:
In formula, vin、vn、voutIt respectively cuts wind speed, limit wind speed, cut-out wind speed；PrFor blower rated power；aWT、 bWT、cWTThree u can be fitted to obtain according to wind-driven generator wind speed-power characteristic；
Step 2.2, the photovoltaic power generation model,
The factors such as photovoltaic power generation output power and sunlight exposure intensity, environment temperature are closely related, according to statistics, 1~ In 10h Intensity of the sunlight can approximation regard Beta distribution as, probability density function can be expressed as follows:
In formula, Γ is Gamma function, G and GmaxPractical intensity of illumination and maximum illumination respectively in this period of time Intensity；α and β is the form parameter of Be-ta distribution, and the μ value that can be averaged by the intensity of illumination in this period of time and standard deviation sigma obtain It arrives；
The output power of photovoltaic cell can be equal to real by the output under its standard test condition, intensity of illumination, environment temperature Intensity of illumination under the operating condition of border is obtained by formula (4) comparison estimation:
In formula, the physical quantity of the STC containing subscript is the operating parameter under standard test condition；GSTCFor under standard test condition Intensity of the sunlight, be taken as 1000W/m2；TSTCFor standard reference temperature；T is the surface Working Temperature of solar cell.
The probability density distribution of the output power of photovoltaic generating system can be obtained by formula (3) and formula (4) synthesis are as follows:
Step 2.3, the micro turbine model:
When miniature gas turbine work in cogeneration of heat and power mode, the related mathematical modulo of coupled thermomechanics relationship and burnup Type may be expressed as:
In formula, QMTFor combustion turbine exhaustion excess heat；PeFor the electrical power of miniature gas turbine output；ηeFor combustion gas hair Electrical efficiency；η1For miniature gas turbine radiation loss coefficient；QHEThe heating capacity provided for gas turbine flue gas waste heat；KHEFor bromine The heating efficiency of cold；VMTFor the amount of natural gas of gas turbine consumption；LHVfFor natural gas underground heat calorific value, it is taken as 9.7KWh/ m3；△ t is the time interval between scheduling twice；
According to formula (6), Thermal Synthetic, Electricity Federation produce total benefit, the operation gross efficiency η of miniature gas turbineMTIt can be counted by formula (7) It calculates:
In formula, mfFor the flow of natural gas；
After the total operational efficiency for determining miniature gas turbine, the operating cost C of miniature gas turbineMTIt can state are as follows:
In formula, cgasFor the price of natural gas；
Step 2.4, the fuel cell mode:
Fuel cell can be obtained by the power-efficient curve matching of its factory, acquire the operational efficiency of fuel cell Afterwards, burnup cost CFCIt approximate can be calculated by formula (9):
In formula, PFCIt (t) is the output power of fuel cell；ηFCFor the generating efficiency of fuel cell；
Step 2.5, the energy storage model:
Energy-storage system is the important component in microgrid, in energy storage charge and discharge process, charged shape of the energy storage in the t period The discharge and recharge and electricity attenuation hourly of the state-of-charge, [t-1, t] period battery of state (SOC) and t-1 period It is related.When energy storage is charged, the SOC of t period be may be expressed as:
When energy storage is discharged, the SOC of t period be may be expressed as:
In formula, SocIt (t) is state-of-charge of the energy storage in t moment；σ is the self-discharge rate of energy storage；ηcAnd ηdRespectively energy storage Charging and discharging efficiency；Pch,tFor the energy storage charge power of t period；Pch,tFor the energy storage discharge power of t period；EbatFor storage It can capacity.
Further, the specific steps of the step 3 are as follows:
Step 3.1 establishes objective function,
Burnup expense, maintenance cost, the amortization charge, the rejection penalty of pollutant effulent, boiler of each DG are comprehensively considered Power trade situation between afterburning expense and microgrid and bulk power grid, with the minimum target of system integrated operation expense, simultaneously The operation restrict of consideration system security constraint and each equipment establishes Optimized Operation mathematical model, the objective function table of model It states as follows:
In formula, NTFor traffic control it is total when number of segment；NDCFor the number of distributed generation resource； Cf(·)、COM(·)、Cdp (·)、Ceav() is respectively burnup cost, maintenance cost, depreciable cost and disposal of pollutants cost that DG is run；PGi,tIt is Electrical power of the i distributed generation resource in the t period；NBFor the quantity of additional combustion boiler；ηBjFor j-th of boiler efficiency；HBj,tIt is Thermal power of the j boiler in t live shell；Pgrid,tPower is exchanged in the t period between microgrid and major network；Cpp(·)、Isp(·) Respectively microgrid is in cost from the t period to bulk power grid power purchase and sale of electricity income；
Step 3.2, constraint condition
System meets following constraint condition when running:
1. electrical power Constraints of Equilibrium:
In formula, PL,tFor the electric load power of t period.
2. heating power balance constrains:
3. distributed generation resource goes out the constraint of activity of force bound:
In formula,WithThe minimum and maximum output power of respectively i-th distributed generation resource；
The Climing constant 4. distributed generation resource is contributed:
In formula, RD and RU are respectively schedulable distributed generation resource climbing rate Lower Limit Amplitude hourly and the climbing rate upper limit Amplitude；
5. tie-line power transmission limits:
In formula,WithThe minimum and maximum function for allowing to transmit as agreed respectively between microgrid and bulk power grid Rate；
6. the state-of-charge of energy storage constrains:
In formula,WithThe respectively state-of-charge lower limit and upper limit value of energy storage；
7. the SOC of traffic control end period should be equal to the SOC of start periods to guarantee that energy storage meets operation in next day:
SOc, t=0=SOc, t=T (19)
8. energy storage charge-discharge electric power is limited range and energy-storage battery itself technology by its state-of-charge in traffic control The influence of limitation, maximum charge-discharge electric power can state are as follows:
In formula,WithThe respectively maximum charge and discharge power of energy storage permission；WithRespectively energy storage The maximum charge and discharge current of permission；VbatFor energy storage end voltage；PinvFor energy-storage system inverter capacity；
9. the quantity of heat storage of hot energy storage constrains:
10. in formula,WithThe lower limit and upper limit value of the quantity of heat storage of respectively hot energy storage；
The quantity of heat storage that hot storage energy operation dispatches the last period should be equal to the quantity of heat storage of start periods:
EHSS, t=0=EHss, t=T (22)
The constraint of hot energy storage output power:
In formula,WithThe lower limit and the upper limit of respectively hot energy storage output power.
Further, the step 4.2 method particularly includes:
Enable xkFor state variable, the power output of unit can be dispatched；ukFor decision variable, the power output of unit can be dispatched Adjustment amount；Function vk(xk,uk) it is stage indicial equation, i.e. comprehensive cost in traffic control；Function xk+1=g (xk,uk) be State transition equation, the i.e. iterative equation of the iterative equation of adjacent time interval unit output and energy storage SOC, then microgrid Optimized Operation Solution equation are as follows:
Objective function:
Constraint condition:
xk+1=g (xk,uk) (25)
cKE(xk,uk)=0, cNE(xN)=0 (26)
ck1(xk,uk)≤0,cN1(xN)≤0 (27)
In formula, cKE、cNEIndicate equality constraint, generation refers to that power-balance constraint and the SOC of electric energy storage, hot energy storage balance about Beam；ck1、cN1Indicate inequality constraints, generation refers to that unit operation constraint, energy storage charge and discharge constraint and tie-line power transmission hold Amount constraint.
The invention adopts the above technical scheme compared with prior art, have following technical effect that the present invention establish with System runs the multiple-energy-source microgrid Optimal Operation Model of the minimum target of comprehensive cost, is carried out based on dynamic programming to model It solves, timesharing or Spot Price are conducive to guide and motivate energy storage low price, load paddy period power purchase, and the high price load peak period sells Electricity plays a significant role in terms of the peak load shifting of power grid.
The present invention implements the control of energy combined optimization to various energy resources, and energy-intensive Regional Energy can be effectively relieved The contradiction of supply and demand promotes renewable energy on-site elimination, reaches by applying the technologies such as energy storage, heat pump, distributed power supply management To the purpose of low-carbon energy-saving optimization operation, and then construct the various energy resources low-carbon environment-friendly based on electric power energy, energy conservation warp Ji, the comprehensive utilization of seamless and efficient and energy services system.
The present invention, both can be with by developing distributed energy, the various energy resources storage conversion such as heat accumulation boiler and dispatching technique The complementary coordination advantage of diversification power supply is played, the waste heat during electrical energy production is efficiently used, realizes Regional Energy using effect The promotion of rate, while the carbon emission value that unit source utilizes can be reduced.Study the operation control of micro-grid multi-energy combined optimization Strategy study, the coordination optimization to reach lifting region distributed energy realize region energy supply system using horizontal and comprehensive energy efficiency The operational objectives such as low-carbon, economization, safe, high-qualityization of system.
Detailed description of the invention
Fig. 1 is dispatching method flow chart of the invention.
Fig. 2 is microgrid multi-energy system optimizing control models of the invention.
Fig. 3 is of the invention based on dynamic programming model solution flow chart.
Specific embodiment
The present embodiment provides a kind of micro-grid multi-energy joint optimal operation methods, as shown in Figure 1, include the following steps,
Step 1, contributed based on powering device under different scenes situation and energy storage device operating status, build multiple-energy-source system The physical model of system.
Wherein, the physical model of multi-energy system is as shown in Fig. 2, comprising distribution type renewable energy, cogeneration of heat and power list First, hot energy storage, electric energy storage and other controllability distributed generation resources, the system can provide hot, electric various energy resources simultaneously for load Supply, and intercoupled between electric power networks and ther mal network based on cogeneration units.For the confession for guaranteeing heat, electric flux simultaneously It needs to balance, when electric energy surplus in system, can be received by batteries to store energy or be transported to low-voltage network outward, electricity Starting backup power source is supported when can be insufficient.In terms of thermic load, miniature gas turbine (abbreviation micro turbine, MT) can utilize it The advantage of cogeneration synthesis high efficiency, meets the needs of thermic load as far as possible, power output should according to system day part thermoelectricity The price of load ratio and the various energy carrys out integrated decision-making, when micro turbine heat supply surplus, can be received by hot energy storage, avoid providing The waste in source；When micro turbine heat supply deficiency, supplemented simultaneously by external additional combustion boiler and hot energy storage.
Step 2 establishes micro-grid multi-energy system each unit mathematical model, including wind-driven generator model, photovoltaic power generation Model, micro turbine model, fuel cell mode and energy storage model.
Wherein, wind-driven generator model, photovoltaic power generation model, micro turbine model, fuel cell mode, storage are established respectively It can model.
(1) wind-driven generator model:
The probability density function expression formula of the wind speed statistics description of wind-driven generator are as follows:
In formula, v is wind speed；K and c is two important parameters of Weibull distribution, and k is form parameter, k > 0；C is known as Scale parameter, c > 1；
The output power P of wind-driven generatorWTFollowing piecewise function relationship approximate representation can be used in relationship between wind speed v:
In formula, vin、vn、voutIt respectively cuts wind speed, limit wind speed, cut-out wind speed；PrFor blower rated power； aWT、 bWT、cWTThree u can be fitted to obtain according to wind-driven generator wind speed-power characteristic；
(2) photovoltaic power generation model,
The factors such as photovoltaic power generation output power and sunlight exposure intensity, environment temperature are closely related, according to statistics, 1~ In 10h Intensity of the sunlight can approximation regard Beta distribution as, probability density function can be expressed as follows:
In formula, Γ is Gamma function, G and GmaxPractical intensity of illumination and maximum illumination respectively in this period of time Intensity；α and β is the form parameter of Be-ta distribution, and the μ value that can be averaged by the intensity of illumination in this period of time and standard deviation sigma obtain It arrives；
The output power of photovoltaic cell can be equal to real by the output under its standard test condition, intensity of illumination, environment temperature Intensity of illumination under the operating condition of border is obtained by formula (4) comparison estimation:
In formula, the physical quantity of the STC containing subscript is the operating parameter under standard test condition；GSTCFor under standard test condition Intensity of the sunlight, be taken as 1000W/m2；TSTCFor standard reference temperature；T is the surface Working Temperature of solar cell.
The probability density distribution of the output power of photovoltaic generating system can be obtained by formula (3) and formula (4) synthesis are as follows:
(3) micro turbine model:
When miniature gas turbine work in cogeneration of heat and power mode, the related mathematical modulo of coupled thermomechanics relationship and burnup Type may be expressed as:
In formula, QMTFor combustion turbine exhaustion excess heat；PeFor the electrical power of miniature gas turbine output；ηeFor combustion gas hair Electrical efficiency；η1For miniature gas turbine radiation loss coefficient；QHEThe heating capacity provided for gas turbine flue gas waste heat；KHEFor bromine The heating efficiency of cold；VMTFor the amount of natural gas of gas turbine consumption；LHVfFor natural gas underground heat calorific value, it is taken as 9.7KWh/ m3；△ t is the time interval between scheduling twice；
According to formula (6), Thermal Synthetic, Electricity Federation produce total benefit, the operation gross efficiency η of miniature gas turbineMTIt can be counted by formula (7) It calculates:
In formula, mfFor the flow of natural gas；
After the total operational efficiency for determining miniature gas turbine, the operating cost C of miniature gas turbineMTIt can state are as follows:
In formula, cgasFor the price of natural gas；
(4) fuel cell mode:
Fuel cell can be obtained by the power-efficient curve matching of its factory, acquire the operational efficiency of fuel cell Afterwards, burnup cost CFCIt approximate can be calculated by formula (9):
In formula, PFCIt (t) is the output power of fuel cell；ηFCFor the generating efficiency of fuel cell；
(5) energy storage model:
Energy-storage system is the important component in microgrid, in energy storage charge and discharge process, charged shape of the energy storage in the t period The discharge and recharge and electricity attenuation hourly of the state-of-charge, [t-1, t] period battery of state (SOC) and t-1 period It is related.When energy storage is charged, the SOC of t period be may be expressed as:
When energy storage is discharged, the SOC of t period be may be expressed as:
In formula, SocIt (t) is state-of-charge of the energy storage in t moment；σ is the self-discharge rate of energy storage；ηcAnd ηdRespectively energy storage Charging and discharging efficiency；Pch,tFor the energy storage charge power of t period；Pch,tFor the energy storage discharge power of t period；EbatFor storage It can capacity.
Step 3, the minimum target of comprehensive cost run with system comprehensively consider operation constraint, the system safety of each DG Coupled characteristic between constraint and multiple-energy-source, establishes micro-grid multi-energy Optimal Operation Model.
It comprises the following specific steps that:
(1) objective function
Burnup expense, maintenance cost, the amortization charge, the rejection penalty of pollutant effulent, boiler of each DG are comprehensively considered Power trade situation between afterburning expense and microgrid and bulk power grid, with the minimum target of system integrated operation expense, simultaneously The operation restrict of consideration system security constraint and each equipment establishes Optimized Operation mathematical model, the objective function table of model It states as follows:
In formula, NTFor traffic control it is total when number of segment；NDCFor the number of distributed generation resource； Cf(·)、COM(·)、Cdp (·)、Ceav() is respectively burnup cost, maintenance cost, depreciable cost and disposal of pollutants cost that DG is run；PGi,tIt is Electrical power of the i distributed generation resource in the t period；NBFor the quantity of additional combustion boiler；ηBjFor j-th of boiler efficiency；HBj,tIt is Thermal power of the j boiler in t live shell；Pgrid,tPower is exchanged in the t period between microgrid and major network；Cpp(·)、Isp(·) Respectively microgrid is in cost from the t period to bulk power grid power purchase and sale of electricity income.
(2) constraint condition
System meets following constraint condition when running:
1. electrical power Constraints of Equilibrium:
In formula, PL,tFor the electric load power of t period.
2. heating power balance constrains:
3. distributed generation resource goes out the constraint of activity of force bound:
In formula,WithThe minimum and maximum output power of respectively i-th distributed generation resource；
The Climing constant 4. distributed generation resource is contributed:
In formula, RD and RU are respectively schedulable distributed generation resource climbing rate Lower Limit Amplitude hourly and the climbing rate upper limit Amplitude；
5. tie-line power transmission limits:
In formula,WithThe minimum and maximum function for allowing to transmit as agreed respectively between microgrid and bulk power grid Rate；
6. the state-of-charge of energy storage constrains:
In formula,WithThe respectively state-of-charge lower limit and upper limit value of energy storage；
7. the SOC of traffic control end period should be equal to the SOC of start periods to guarantee that energy storage meets operation in next day:
SOc, t=0=SOc, t=T (19)
8. energy storage charge-discharge electric power is limited range and energy-storage battery itself technology by its state-of-charge in traffic control The influence of limitation, maximum charge-discharge electric power can state are as follows:
In formula,WithThe respectively maximum charge and discharge power of energy storage permission；WithRespectively energy storage The maximum charge and discharge current of permission；VbatFor energy storage end voltage；PinvFor energy-storage system inverter capacity；
9. the quantity of heat storage of hot energy storage constrains:
10. in formula,WithThe lower limit and upper limit value of the quantity of heat storage of respectively hot energy storage；
The quantity of heat storage that hot storage energy operation dispatches the last period should be equal to the quantity of heat storage of start periods:
EHSS, t=0=EHss, t=T (22)
The constraint of hot energy storage output power:
In formula,WithThe lower limit and the upper limit of respectively hot energy storage output power.
Step 4 solves micro-grid multi-energy Optimized model based on backward Dynamic Programming, obtains microgrid multiple-energy-source Combined optimization operation reserve.
(1) Optimized Operation process is divided into 24 stage decision processes, when carrying out each stage decision, be considered as from Amount of storage of this stage up to the last stage.
(2) Dynamic Programming Equation for listing microgrid Optimal Operation Model coordinates inequality constraints and improvement using interior point method Equality constraint, and solved using sequential quadratic programming.Enable xkFor state variable, the power output of unit can be dispatched；uk For decision variable, the power output adjustment amount of unit can be dispatched；Function vk(xk,uk) it is stage indicial equation, i.e., in traffic control Comprehensive cost；Function xk+1=g (xk,uk) it is state transition equation, the i.e. iterative equation of adjacent time interval unit output and energy storage The iterative equation of SOC, then the solution equation of microgrid Optimized Operation are as follows:
Objective function:
Constraint condition:
xk+1=g (xk,uk) (25)
cKE(xk,uk)=0, cNE(xN)=0 (26)
ck1(xk,uk)≤0,cN1(xN)≤0 (27)
In formula, cKE、cNEIndicate equality constraint, generation refers to that power-balance constraint and the SOC of electric energy storage, hot energy storage balance about Beam；ck1、cN1Indicate inequality constraints, generation refers to that unit operation constraint, energy storage charge and discharge constraint and tie-line power transmission hold Amount constraint.
The basic principles, main features and advantages of the invention have been shown and described above.Those skilled in the art should Understand, the present invention do not limited by above-mentioned specific embodiment, the description in above-mentioned specific embodiment and specification be intended merely into One step illustrates the principle of the present invention, and under the premise of not departing from spirit of that invention range, the present invention also has various change and changes Into these changes and improvements all fall within the protetion scope of the claimed invention.The scope of protection of present invention is by claim Book and its equivalent thereof.

Claims (6)

1. a kind of micro-grid multi-energy joint optimal operation method, it is characterised in that: include the following steps,
Step 1, contributed based on powering device under different scenes situation and energy storage device operating status, build the object of multi-energy system Manage model；
Step 2 establishes micro-grid multi-energy system each unit mathematical model, including wind-driven generator model, photovoltaic power generation model, Micro turbine model, fuel cell mode and energy storage model；
Step 3, the minimum comprehensive cost run using system comprehensively consider operation constraint, the system security constraint of each DG as target And the coupled characteristic between multiple-energy-source, establish micro-grid multi-energy Optimal Operation Model；Wherein, DG is distributed generation resource, packet Include photovoltaic, wind-force, fuel cell, micro turbine；
Step 4: micro-grid multi-energy Optimized model being solved based on backward Dynamic Programming, it is excellent to obtain microgrid multiple-energy-source joint Change operation reserve.
2. micro-grid multi-energy joint optimal operation method according to claim 1, it is characterised in that: in the step 1 The physical model of multi-energy system includes distribution type renewable energy, cogeneration unit, hot energy storage, electric energy storage and other are controllable Property distributed generation resource, the multi-energy system is that load at least provides the supply of heat, electric energy, and electric power networks and heat supply network simultaneously It is intercoupled between network based on cogeneration units；To guarantee heat, the equilibrium of supply and demand of electric flux simultaneously, in terms of electric load, when being In system when electric energy surplus, low-voltage network is received by batteries to store energy or is transported to outward, when electric energy deficiency starts standby It is supported with power supply；In terms of thermic load, miniature gas turbine utilizes the advantage of its cogeneration synthesis high efficiency, to meet heat The demand of load, power output should according to system in the thermoelectricity load ratio of day part and the price of the various energy come integrated decision-making, It when miniature gas turbine heat supply surplus, is received by hot energy storage, avoids the waste of resource；When miniature gas turbine heat supply is insufficient When, it is supplemented simultaneously by external additional combustion boiler and hot energy storage.
3. micro-grid multi-energy joint optimal operation method according to claim 1, it is characterised in that: the step 2 Specific steps are as follows: establish wind-driven generator model, photovoltaic power generation model, micro turbine model, fuel cell mode, energy storage mould respectively Type；
Step 2.1, the wind-driven generator model,
The probability density function expression formula of the wind speed statistics description of wind-driven generator are as follows:
In formula, v is wind speed；K and c is two important parameters of Weibull distribution, and k is form parameter, k > 0；
C is known as scale parameter, c > 1；
The output power P of wind-driven generatorWTFollowing piecewise function relationship approximate representation can be used in relationship between wind speed v:
In formula, vin、vn、voutIt respectively cuts wind speed, limit wind speed, cut-out wind speed；PrFor blower rated power；aWT、bWT、cWT Three u can be fitted to obtain according to wind-driven generator wind speed-power characteristic；
Step 2.2, the photovoltaic power generation model,
The factors such as photovoltaic power generation output power and sunlight exposure intensity, environment temperature are closely related, according to statistics, in 1~10h Intensity of the sunlight can approximation regard Beta distribution as, probability density function can be expressed as follows:
In formula, Γ is Gamma function, G and GmaxPractical intensity of illumination and maximum intensity of illumination respectively in this period of time；α It is the form parameter of Be-ta distribution with β, the μ value that can be averaged by the intensity of illumination in this period of time and standard deviation sigma obtain；
The output power of photovoltaic cell can be equal to practical work by the output under its standard test condition, intensity of illumination, environment temperature Intensity of illumination under the conditions of work is obtained by formula (4) comparison estimation:
In formula, the physical quantity of the STC containing subscript is the operating parameter under standard test condition；GSTCFor under standard test condition too Positive intensity of illumination, is taken as 1000W/m2；TSTCFor standard reference temperature；T is the surface Working Temperature of solar cell.
The probability density distribution of the output power of photovoltaic generating system can be obtained by formula (3) and formula (4) synthesis are as follows:
Step 2.3, the micro turbine model:
When miniature gas turbine work is in cogeneration of heat and power mode, the Related Mathematical Models of coupled thermomechanics relationship and burnup can table It is shown as:
In formula, QMTFor combustion turbine exhaustion excess heat；PeFor the electrical power of miniature gas turbine output；ηeFor fuel gas generation efficiency； η1For miniature gas turbine radiation loss coefficient；QHEThe heating capacity provided for gas turbine flue gas waste heat；KHEFor the system of bromine cooling machine Hot coefficient；VMTFor the amount of natural gas of gas turbine consumption；LHVfFor natural gas underground heat calorific value, it is taken as 9.7KWh/m3；△ t is Time interval between scheduling twice；
According to formula (6), Thermal Synthetic, Electricity Federation produce total benefit, the operation gross efficiency η of miniature gas turbineMTIt can be calculated by formula (7):
In formula, mfFor the flow of natural gas；
After the total operational efficiency for determining miniature gas turbine, the operating cost C of miniature gas turbineMTIt can state are as follows:
In formula, cgasFor the price of natural gas；
Step 2.4, the fuel cell mode:
Fuel cell can be obtained by the power-efficient curve matching of its factory, after the operational efficiency for acquiring fuel cell, combustion Consume cost CFCIt approximate can be calculated by formula (9):
In formula, PFCIt (t) is the output power of fuel cell；ηFCFor the generating efficiency of fuel cell；
Step 2.5, the energy storage model:
Energy-storage system is the important component in microgrid, in energy storage charge and discharge process, state-of-charge of the energy storage in the t period (SOC) have with the state-of-charge of t-1 period, the discharge and recharge of [t-1, t] period battery and electricity attenuation hourly It closes.When energy storage is charged, the SOC of t period be may be expressed as:
When energy storage is discharged, the SOC of t period be may be expressed as:
In formula, SocIt (t) is state-of-charge of the energy storage in t moment；σ is the self-discharge rate of energy storage；ηcAnd ηdThe respectively charging of energy storage And discharging efficiency；Pch,tFor the energy storage charge power of t period；Pch,tFor the energy storage discharge power of t period；EbatFor stored energy capacitance.
4. micro-grid multi-energy joint optimal operation method according to claim 1, it is characterised in that: the step 3 Specific steps are as follows:
Step 3.1 establishes objective function,
Burnup expense, maintenance cost, the amortization charge, the rejection penalty of pollutant effulent, boiler afterburning of each DG are comprehensively considered Power trade situation between expense and microgrid and bulk power grid is considered simultaneously with the minimum target of system integrated operation expense The operation restrict of system security constraint and each equipment establishes Optimized Operation mathematical model, and the objective function statement of model is such as Under:
In formula, NTFor traffic control it is total when number of segment；NDCFor the number of distributed generation resource；Cf(·)、COM(·)、Cdp(·)、Ceav () is respectively burnup cost, maintenance cost, depreciable cost and disposal of pollutants cost that DG is run；PGi,tFor i-th of distribution Electrical power of the power supply in the t period；NBFor the quantity of additional combustion boiler；ηBjFor j-th of boiler efficiency；HBj,tIt is j-th of boiler in t The thermal power of live shell；Pgrid,tPower is exchanged in the t period between microgrid and major network；Cpp(·)、Isp() is respectively microgrid In cost from the t period to bulk power grid power purchase and sale of electricity income；
Step 3.2, constraint condition
System meets following constraint condition when running:
1. electrical power Constraints of Equilibrium:
In formula, PL,tFor the electric load power of t period.
2. heating power balance constrains:
3. distributed generation resource goes out the constraint of activity of force bound:
In formula,WithThe minimum and maximum output power of respectively i-th distributed generation resource；
The Climing constant 4. distributed generation resource is contributed:
In formula, RD and RU are respectively schedulable distributed generation resource climbing rate Lower Limit Amplitude hourly and climbing rate upper limit magnitude；
5. tie-line power transmission limits:
In formula,WithThe minimum and maximum power for allowing to transmit as agreed respectively between microgrid and bulk power grid；
6. the state-of-charge of energy storage constrains:
In formula,WithThe respectively state-of-charge lower limit and upper limit value of energy storage；
7. the SOC of traffic control end period should be equal to the SOC of start periods to guarantee that energy storage meets operation in next day:
SOc, t=0=SOc, t=T (19)
8. energy storage charge-discharge electric power is limited range and energy-storage battery itself technical restriction by its state-of-charge in traffic control It influences, maximum charge-discharge electric power can state are as follows:
In formula,WithThe respectively maximum charge and discharge power of energy storage permission；WithRespectively energy storage allows Maximum charge and discharge current；VbatFor energy storage end voltage；PinvFor energy-storage system inverter capacity；
9. the quantity of heat storage of hot energy storage constrains:
10. in formula,WithThe lower limit and upper limit value of the quantity of heat storage of respectively hot energy storage；
The quantity of heat storage that hot storage energy operation dispatches the last period should be equal to the quantity of heat storage of start periods:
EHSS, t=0=EHss, t=T (22)
The constraint of hot energy storage output power:
In formula,WithThe lower limit and the upper limit of respectively hot energy storage output power.
5. micro-grid multi-energy joint optimal operation method according to claim 1, it is characterised in that: the step 4 Specific steps are as follows:
Optimized Operation process is divided into 24 stage decision processes by step 4.1, when carrying out each stage decision, be considered as from Amount of storage of this stage up to the last stage；
Step 4.2, the Dynamic Programming Equation for listing microgrid Optimal Operation Model coordinate inequality constraints and improvement using interior point method Equality constraint, and solved using sequential quadratic programming.
6. micro-grid multi-energy joint optimal operation method according to claim 5, it is characterised in that: the step 4.2 Method particularly includes:
Enable xkFor state variable, the power output of unit can be dispatched；ukFor decision variable, the power output adjustment of unit can be dispatched Amount；Function vk(xk,uk) it is stage indicial equation, i.e. comprehensive cost in traffic control；Function xk+1=g (xk,uk) turn for state Equation, the i.e. iterative equation of the iterative equation of adjacent time interval unit output and energy storage SOC are moved, then the solution side of microgrid Optimized Operation Journey are as follows:
Objective function:
Constraint condition:
xk+1=g (xk,uk) (25)
cKE(xk,uk)=0, cNE(xN)=0 (26)
ck1(xk,uk)≤0,cN1(xN)≤0 (27)
In formula, cKE、cNEIndicate equality constraint, generation refers to the SOC Constraints of Equilibrium of power-balance constraint and electric energy storage, hot energy storage；ck1、 cN1Indicate inequality constraints, generation refers to unit operation constraint, energy storage charge and discharge constraint and tie-line power transmission capacity-constrained.
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