CN108964098A - A kind of independent micro-grid system capacity configuration optimizing method - Google Patents
A kind of independent micro-grid system capacity configuration optimizing method Download PDFInfo
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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
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
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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
- H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
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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
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
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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
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E70/00—Other energy conversion or management systems reducing GHG emissions
- Y02E70/30—Systems combining energy storage with energy generation of non-fossil origin
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- 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
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P80/00—Climate change mitigation technologies for sector-wide applications
- Y02P80/20—Climate change mitigation technologies for sector-wide applications using renewable energy
Abstract
The invention discloses a kind of independent micro-grid system capacity configuration optimizing methods, and flexible load is divided into industrial height and loads with 3 class of lotus, commercial polymerization load and resident's intelligent domestic load.Using flexible load as a kind of schedulable resource coordination energy-storage system to wind/optical functions leveling, with the preferential stabilizing system imbalance power of energy-storage system, flexible load coordinates battery to the principle of wind/optical functions balance, establishes the optimization energy management strategies for the flexible load containing polymorphic type that " source-storage-lotus " mutually coordinates.It establishes with micro-capacitance sensor infrastructure investment cost, flexible load dispatches cost and the comprehensive optimal multiple-objection optimization allocation models of renewable energy consumption rate.Capacity Optimal Allocation Model is solved using the particle swarm algorithm for introducing dynamic inertia weight.It is emulated using MATLAB 7.10, demonstrates the reasonability and validity of this method.The method of the present invention makes system in the case where guaranteeing operational reliability, can reduce system cost, improves renewable energy utilization rate.
Description
Technical field
The present invention relates to micro-capacitance sensor design planning field, especially a kind of independent micro-capacitance sensor that consideration source-storage-lotus is mutually coordinated
Power system capacity Optimal Configuration Method.
Background technique
The problems such as with energy shortage, environmental pollution, continues to bring out, containing renewable energy such as wind-force and photovoltaics
Distributed power generation have become the hot spot studied in world wide.Micro-capacitance sensor can by distributed generation unit, energy-storage units with
And load combines, and realizes integration operation, works in grid-connected or island mode, be the important set of the following smart grid
At part.Therefore, natural resources is rationally utilized, optimizing configuration to the capacity of wind/light micro battery and energy storage is micro-capacitance sensor rule
Draw the core topic in design field.
At present about in the research of capacity configuration, since solar energy and wind energy have randomness, fluctuation and intermittence etc.
Characteristic, generallys use the generation mode of booster battery to stabilize wind/optical functions, and group becomes a common practice/light/storage system.However as can
The extensive utilization of the renewable sources of energy does not only simply fail to solve local consumption difficulty, the utilization of resources not by the mode of booster battery
The problems such as abundant, causes renewable energy loss excessive, capacity configuration cost can also increased.
With the development of smart grid, realize that " interactivity " of both sides of supply and demand has become raising and optimization micro-capacitance sensor is renewable
One of the digestion capability of the energy and the effective ways of economy.Flexible load is the effective way for realizing both sides of supply and demand " interactivity "
One of diameter, balance of the tunable battery to regenerative resource power supply while realizing supply and demand interaction.It is rigid compared to traditional
Property load, flexible load flexibly and can be changed, can be actively engaged in micro-capacitance sensor operation control, by change itself electricity consumption time or bear
Lotus size cooperates the regulation demand of power grid, realizes " interactivity " of supply and demand side both sides, changes script load and unidirectionally, passively receives
The history of adjusting.As a kind of schedulable load side resource, flexible load tunable battery stabilizes load and renewable energy
The imbalance of power, effectively reduces capacity needed for battery between the power output of source.
Summary of the invention
It is an object of that present invention to provide a kind of consideration sources-that system economy and renewable energy consumption level can be improved
The independent micro-grid system capacity configuration optimizing method that storage-lotus is mutually coordinated.
To achieve the above object, use following technical scheme: the step of the method for the invention, is as follows:
Step 1, it determines the networking mode of micro-grid system, refines flexible load type；
Step 2, it determines micro-grid system energy scheduling strategy priority, proposes the system capacity for considering flexible load scheduling
Scheduling strategy；
Step 3, it establishes and considers polymorphic type flexible load Optimal Operation Model；
Step 4, objective function and constraint condition are determined, the double-goal optimal model for considering flexible load is established；
Step 5, it introduces dynamic inertia weight and improves particle swarm algorithm；
Step 6, example and its essential feature are determined, example is carried out using MATLAB software programming particle swarm algorithm program
Simulation analysis.
Further, detailed process is as follows for the step 1:
Step 1-1 determines the networking mode of micro-grid system
Wind-power electricity generation, photovoltaic power generation, energy-storage system, inverter and load (including firm demand and flexible load) are constituted
Typical independent wind/light/storage micro-grid system structure.The characteristics of networking modes various according to wind/light/storage micro-grid system,
Present invention selection has many advantages, such as the networking mode for the DC bus that control is simple, dilatation is convenient.
Step 1-2 refines flexible load type:
The flexible load dispatching of different regions is different, this is related with the load type in area, excellent using flexible load
Regional flexible load scheduling Potential Evaluation is carried out before changing energy scheduling, then flexible load is excited by cost of compensation mechanism
Initiative.Under the premise of this, schedulable flexible load is divided into industrial height and loads with lotus, commercial polymerization load and residence by the present invention
3 class of wisdom of the people energy household loads.
Further, detailed process is as follows for the step 2:
Step 2-1 determines micro-grid system energy scheduling strategy priority
Flexible load participates in the imbalance that scheduling tunable battery stabilizes power between load and renewable energy power output,
Effectively realize the synergistic effect between renewable energy, battery and load.Coordinative role based on flexible load, the present invention
Construct the optimization energy management strategies for the flexible load containing polymorphic type that " source-storage-lotus " mutually coordinates.
According to way to manage difference, flexible load, which is divided into, can motivate load and interruptible load.The present invention is based on contracts about
Fixed mode decreases or increases user's in any time that micro-capacitance sensor requires according to the agreement that micro-capacitance sensor and user sign
Power demand.And when user decreases or increases its power demand according to agreement, micro-capacitance sensor pays certain expense to user to mend
It repays its loss or reduces electricity price as reward, guidance user is actively engaged in microgrid operation, realizes the two-way interaction of supply and demand side.
When the unbalanced power between load and blower and photovoltaic power output, preferentially put down by battery by charge and discharge
Weighing apparatus；When the charge-discharge electric power of battery or remaining capacity exceed restriction range, arranged to coordinate storage as agreed by flexible load
Energy system stabilizes the imbalance power between load and micro battery.
Step 2-2 proposes the system capacity scheduling strategy for considering flexible load
When scene power output is sufficient, the power of system spare first charges to battery；When charge power or residue
Electricity is more than that the restriction range of battery still has residue later, then is dissolved by flexible load by increasing electricity consumption；
When honourable undercapacity, the power of system spare first discharges to battery；When discharge power and residue
Electricity is more than that the restriction range of battery still has vacancy later, reduces system power load by flexible load to balance.
Further, detailed process is as follows for the step 3:
Schedulable flexible load is divided into industrial height and loads with lotus, commercial polymerization load and resident's intelligent domestic by the present invention to be born
3 class of lotus.
The present invention sets the schedulable capacity amount of each period flexible load are as follows:
Δ P (t)=Pwt(t)+Ppv(t)-PL, 0(t)-Pbat(t)
In formula, Δ P (t) is the schedulable total capacity of flexible load；PL, 0It (t) is initial load demand, i.e. flexible load is joined
With the workload demand before scheduling；Pwt(t)、Ppv(t) and PbatIt (t) is respectively blower output power, photovoltaic output power and electric power storage
The charge/discharge power in pond.
The scheduling mode of each period actual schedule capacity of flexible load and all kinds of flexible loads, scheduling potentiality and each user
It reduces related with conditions such as the wishes of increase electricity consumption.Industrial high energy load has the characteristics that capacity is big, steady load, mainly with
It can interrupt, the form of load can be motivated to be applied to smooth extensive renewable energy power swing；Commercial polymerization load scheduling root
It is realized according to the demand response of the middle-size and small-size commercial user of Load aggregation quotient integration, and participates in micro- electricity in the form of interruptible load
Net scheduling；Resident's intelligent domestic load mainly realizes the small user of family and smart grid in the form of it can interrupt, can motivate load
Two-way interactive.
The mathematical model that all kinds of flexible loads participate in scheduling may be defined as:
In formula, i=1,2,3 be flexible load type, respectively refers to industrial height and loads with lotus, commercial polymerization load and resident's intelligence
Household loads；NiFor the number of users for participating in flexible load i scheduling；PfliIt (t) is flexible load i actual schedule total capacity；Pfli-n
It (t) is user n actual participation flexible load i scheduling capacity；PLi, 0-n(t) workload demand for being user n；WithRespectively load i's drive factor and can interrupt coefficient；WithDetermine that can load i for a pair
Participate in the decision-making coefficient group of flexible load scheduling.
The wish that electricity consumption was interrupted and increased to the scheduling potentiality of flexible load and each user affect can drive factor and can in
The value of disconnected coefficient, may be defined as:
In formula,WithRespectively flexible load i can motivate potentiality and can interrupt potentiality；WithRespectively user n increases and the willingness factor of interruptible load i.
Decision-making coefficient is related with the form that each flexible load participates in scheduling, may be expressed as:
In formula, as i=2, λ=0；When i ≠ 2, λ=1.
Further, detailed process is as follows for the step 4:
Step 4-1, determines objective function
For optimizing capacity allocation models, the present invention is established with micro-capacitance sensor infrastructure investment cost, and flexible load dispatches cost
With the comprehensive optimal Optimal Allocation Model of renewable energy consumption rate.
Integrated objective function may be expressed as:
For integrated objective function, the physics meaning as representated by each sub-goal is different, there is the difference in dimension,
Therefore often lack between each sub-goal comprehensive.To avoid this problem, the present invention is based on the concepts of per unit value, with each specific item
Equal weight is marked, each sub-goal independence optimal solution carries out nondimensionalization processing to integrated objective function as a reference value.
In formula,fflAnd fUREPRespectively system cost, flexible load scheduling cost and renewable energy discard rate,
That is each sub-goal of integrated objective function；WithThe independent optimal solution of respectively each sub-goal；ωACS、
ωflAnd ωUREPFor each sub-goal weight.
Step 4-1-1, system cost
The years value investment cost such as system ACS (Annualized Cost of System) can be used as evaluating independent wind
The index of light storage micro-grid system capacity configuration economy superiority and inferiority.The years value expense such as system mainly includes equipment investment cost, operation
With maintenance cost and displacement cost, expression formula are as follows:
In formula, CCI、COM、CRRespectively indicate a year equipment investment cost, year operation and maintenance cost and year displacement cost.
Wherein:
In formula:The respectively unit price of photovoltaic battery panel, blower, battery；
It is respectively the year operation and maintenance cost of unit photovoltaic battery panel, blower, battery；CRLTo be replaced as this summation in the time limit；
Npv、Nwt、NbatThe respectively installation number of photovoltaic battery panel, blower, battery；fcrFor coefficient of depreciation；R indicates allowance for depreciation；
Step 4-1-2, flexible load dispatch cost
By previous analysis it is found that flexible load scheduling cost includes the cost of compensation of interruptible load and can motivate load
Incentive cost.Flexible load participates in scheduling and shows as demand response, in the case where keeping both sides of supply and demand interests dynamic equalization, draws
Lead the behavior of power consumer.Therefore, flexible load scheduling cost had both shown as the operation cost of supply side or had shown as user side
Income.
For supply side micro-capacitance sensor, part sale of electricity income is dispatched cost recovery user by micro-capacitance sensor.
For ensure micro-capacitance sensor income, present invention provide that flexible load dispatch cost allow dispatch range in it is not out-of-limit, that is, work as flexibility
Load scheduling cost is not prescribed a time limit more, and the present invention will be flexible negative using being described based on the nonlinear model of marginal cost pricing strategy
Lotus dispatch cost, it is on the contrary then according to maximum allowable cost recovery user.Therefore, the flexible load i scheduling cost of user n can define
Are as follows:
Wherein:
In formula,For the incentive cost for motivating load of user n；For the interruptible load of user n
Cost of compensation；θmaxFor greatest flexibility load scheduling cost coefficient；ciFor load i unit price of power；Pli-n(t) it is dispatched for flexible load
The workload demand of user n afterwards；α1And α2For the drive factor that can motivate load；β1And β2For the penalty coefficient of interruptible load.
Micro-capacitance sensor year flexible load dispatches cost:
In formula,For the cost of compensation of year interruptible load；The incentive cost of load can be motivated for year.
Step 4-1-3, renewable energy discard rate
Renewable energy discards rate UREP (Unutilized Renewable Energy Probability) and can be used to make
The horizontal index of renewable energy consumption is configured to evaluate independent wind-light storage micro-grid system power supply capacity, definition can be described as:
In formula, fUREPRate is discarded for renewable energy；Pl(t) workload demand after scheduling is participated in for flexible load
Step 4-2, evaluation index,
Step 4-2-1, wind light mutual complementing
For luminous energy and the Variation Features of wind energy, the two has stronger complementarity in time.This characteristic can table
It is shown as:
In formula, DLFor wind light mutual complementing characteristic；For the mean power of initial load.And DLSmaller, wind light mutual complementing is got over
It is good.
Step 4-2-2, power supply reliability
Load short of electricity rate (the loss of power supply probability, LPSP) is represented by a period of time
Interior, system power output is less than the period of load power and the ratio of total period, can be used to indicate system power supply reliability.
Step 4-2-3, year electricity cost expenditure
User participates in micro-capacitance sensor operation in such a way that flexible load is dispatched, and realizes supply and demand interaction.Its year electricity cost by
Actual load electricity cost and flexible load scheduling cost composition.
In formula, CelFor year electricity cost expenditure.
Step 4-3, constraint condition
Step 4-3-1, power supply reliability constraint
To ensure user power utilization demand, it is desirable that load short of electricity rate is can be in tolerance range:
LPSP≤εLPSP
Wherein, εLPSPFor the reference value for loading short of electricity rate.
Step 4-3-2, system installed capacity constraint
Each generator unit installed capacity of micro-grid system is influenced to be limited in by the engineerings practical factor such as place occupied area
Within a certain range.
In formula, NPv, min、NWt, min、NBat, minThe respectively minimum installation number of photovoltaic battery panel, blower, battery；
NPv, max、NWt, max、NBat, maxRespectively its corresponding maximum installation number.
Step 4-3-3, power-balance constraint
At runtime, wind-powered electricity generation, photovoltaic, energy storage and load in system etc. require to meet active power balance micro-capacitance sensor,
That is:
In formula, PURE(t) power discarded for renewable energy；PlossIt (t) is system power vacancy.
Step 4-3-4, accumulator cell charging and discharging constraint
The service life for effectively extending battery, can avoid cost of investment caused by due to frequently replacing battery substantially
Degree increases.It can play the role of extending the battery-operated service life to the limitation of accumulator cell charging and discharging depth and charge-discharge electric power.
SOCmin≤SOC(t)≤SOCmax
Wherein, SOCmaxAnd SOCminThe respectively upper and lower bound of battery remaining capacity；
WithThe respectively upper and lower bound of accumulator cell charging and discharging power；
Step 4-3-5, flexible load schedule constraints
Scheduling potentiality be flexible load a kind of intrinsic physical attribute, for describing power when flexible load participates in scheduling
The ability increasedd or decreased.
In formula,WithRespectively all kinds of flexible load maximums can motivate potentiality and maximum that can interrupt
Potentiality.
Further, detailed process is as follows for the step 5:
Step 5-1 introduces dynamic inertia weight and improves particle swarm algorithm
Particle swarm optimization algorithm (PSO) is proposed by Kennedy and Eberhart 1995 for the first time, because its concept is simple, spirit
The features such as active strong and easy to accomplish and be widely used in the solution of engineering problem.PSO can be used for solving multi-target non-linear
Optimization problem, it is assumed that in a D dimension search space, population X is formed by m particle, wherein i-th of particle is expressed as a D
The X of dimensional vectori.For each particle i, all it is made of 3 D dimensional vectors, respectively current position (Xi), the optimal position of history
Set (pbesti) and speed (Vi).In each iterative process, particle will update the speed of itself by individual extreme value and group's extreme value
Degree and position, it may be assumed that
Wherein, ω is inertia weight；K is current iteration number；D=1,2 ..., D；I=1,2 ..., m；c1And c2To accelerate
The factor；r1And r2For the random number for being distributed in [0,1] section.
In solution procedure, ω plays the role of a balance local search ability and ability of searching optimum, value
Range effects the solving precision of algorithm.The value of ω may be set to changeless and dynamic change.Based on being ground to PSO
Study carefully, when compared to ω dynamic change, although PSO has faster convergence rate when ω immobilizes, solving precision is lower.
It is therefore of the invention by ω is defined as:
ω (k)=ωstart(ωstart-ωend)(K-k)/K
Wherein, ωstartFor initial inertia weight；ωendInertia weight when for the number of iterations maximum；K is greatest iteration time
Number.
Step 5-2, model solution
Model is solved using modified particle swarm optiziation.Specific step is as follows
(1) particle initializes, and the part of each particle is found out according to practical climatic environment, user data and component parameter
Optimal solution and globally optimal solution；
(2) fitness of each particle is calculated, and judges whether particle meets constraint；
(3) compare the individual optimal solution (pbest) of particle adaptive value and it, if being better than pbest, pbest is current
Particle position；Compare particle pbest and globally optimal solution (gbest), if being better than gbest, the pbest of this particle is
gbest；
(4) speed of more new particle and position；
(5) continue iteration until reaching maximum number of iterations, and export result.
Compared with prior art, the present invention has the advantage that
1, flexible load participates in " interactivity " that scheduling increases supply and demand side both sides, improves user and is actively engaged in microgrid fortune
Capable enthusiasm and electricity consumption satisfaction.
2, flexible load participates in scheduling tunable energy-storage system to wind/optical functions balance, improves the energy consumption of system
Rate and system economy realize micro-grid system source-storage-lotus coordination.
3, materialization classification is carried out to flexible load, and to dispatch cost not based on marginal cost nonlinear model and consideration
It is out-of-limit to dispatch cost to describe flexible load.
Detailed description of the invention
Fig. 1 is the independent micro-grid system structure chart of the method for the present invention.
Fig. 2 is the policy map of the method for the present invention.
Fig. 3 is the independent micro-grid system capacity configuration Optimization Solution flow chart of the method for the present invention.
Specific embodiment
The present invention will be further described with reference to the accompanying drawing:
In conjunction with Fig. 2 and Fig. 3, the step of the method for the invention, is as follows:
Step 1, it determines the networking mode of micro-grid system, refines flexible load type:
Step 1-1 determines the networking mode of micro-grid system
Wind-power electricity generation, photovoltaic power generation, energy-storage system, inverter and load (including firm demand and flexible load) are constituted
Typical independent wind/light/storage micro-grid system structure.The characteristics of networking modes various according to wind/light/storage micro-grid system,
Present invention selection has many advantages, such as the networking mode for the DC bus that control is simple, dilatation is convenient.Structure chart is as shown in Fig. 1.
Step 1-2 refines flexible load type
The flexible load dispatching of different regions is different, this is related with the load type in area, excellent using flexible load
Regional flexible load scheduling Potential Evaluation is carried out before changing energy scheduling, then flexible load is excited by cost of compensation mechanism
Initiative.Under the premise of this, schedulable flexible load is divided into industrial height and loads with lotus, commercial polymerization load and residence by the present invention
3 class of wisdom of the people energy household loads.
Step 2, it determines micro-grid system energy scheduling strategy priority, proposes the system capacity for considering flexible load scheduling
Scheduling strategy:
Step 2-1 determines micro-grid system energy scheduling strategy priority
Flexible load participates in the imbalance that scheduling tunable battery stabilizes power between load and renewable energy power output,
Effectively realize the synergistic effect between renewable energy, battery and load.Coordinative role based on flexible load, the present invention
Construct the optimization energy management strategies for the flexible load containing polymorphic type that " source-storage-lotus " mutually coordinates.
According to way to manage difference, flexible load, which is divided into, can motivate load and interruptible load.The present invention is based on contracts about
Fixed mode decreases or increases user's in any time that micro-capacitance sensor requires according to the agreement that micro-capacitance sensor and user sign
Power demand.And when user decreases or increases its power demand according to agreement, micro-capacitance sensor pays certain expense to user to mend
It repays its loss or reduces electricity price as reward, guidance user is actively engaged in microgrid operation, realizes the two-way interaction of supply and demand side.
When the unbalanced power between load and blower and photovoltaic power output, preferentially put down by battery by charge and discharge
Weighing apparatus；When the charge-discharge electric power of battery or remaining capacity exceed restriction range, arranged to coordinate storage as agreed by flexible load
Energy system stabilizes the imbalance power between load and micro battery.
Step 2-2 proposes the system capacity scheduling strategy for considering flexible load
When scene power output is sufficient, the power of system spare first charges to battery；When charge power or residue
Electricity is more than that the restriction range of battery still has residue later, then is dissolved by flexible load by increasing electricity consumption；
When honourable undercapacity, the power of system spare first discharges to battery；When discharge power and residue
Electricity is more than that the restriction range of battery still has vacancy later, reduces system power load by flexible load to balance.Optimization
Energy management strategies figure is as shown in Figure 2.
Step 3, it establishes and considers polymorphic type flexible load Optimal Operation Model:
Schedulable flexible load is divided into industrial height and loads with lotus, commercial polymerization load and resident's intelligent domestic by the present invention to be born
3 class of lotus.
The present invention sets the schedulable capacity amount of each period flexible load are as follows:
Δ P (t)=Pwt(t)+Ppv(t)-Pl,0(t)-Pbat(t)
In formula, Δ P (t) is the schedulable total capacity of flexible load；PL, 0It (t) is initial load demand, i.e. flexible load is joined
With the workload demand before scheduling；Pwt(t)、Ppv(t) and PbatIt (t) is respectively blower output power, photovoltaic output power and electric power storage
The charge/discharge power in pond.
The scheduling mode of each period actual schedule capacity of flexible load and all kinds of flexible loads, scheduling potentiality and each user
It reduces related with conditions such as the wishes of increase electricity consumption.Industrial high energy load has the characteristics that capacity is big, steady load, mainly with
It can interrupt, the form of load can be motivated to be applied to smooth extensive renewable energy power swing；Commercial polymerization load scheduling root
It is realized according to the demand response of the middle-size and small-size commercial user of Load aggregation quotient integration, and participates in micro- electricity in the form of interruptible load
Net scheduling；Resident's intelligent domestic load mainly realizes the small user of family and smart grid in the form of it can interrupt, can motivate load
Two-way interactive.
The mathematical model that all kinds of flexible loads participate in scheduling may be defined as:
In formula, i=1,2,3 be flexible load type, respectively refers to industrial height and loads with lotus, commercial polymerization load and resident's intelligence
Household loads；NiFor the number of users for participating in flexible load i scheduling；PfliIt (t) is flexible load i actual schedule total capacity；Pfli-n
It (t) is user n actual participation flexible load i scheduling capacity；PLi, 0-n(t) workload demand for being user n；WithRespectively load i's drive factor and can interrupt coefficient；WithDetermine that can load i for a pair
Participate in the decision-making coefficient group of flexible load scheduling.
The wish that electricity consumption was interrupted and increased to the scheduling potentiality of flexible load and each user affect can drive factor and can in
The value of disconnected coefficient, may be defined as:
In formula,WithRespectively flexible load i can motivate potentiality and can interrupt potentiality；WithRespectively user n increases and the willingness factor of interruptible load i.
Decision-making coefficient is related with the form that each flexible load participates in scheduling, may be expressed as:
In formula, as i=2, λ=0；When i ≠ 2, λ=1.
Step 4, objective function and constraint condition are determined, the double-goal optimal model for considering flexible load is established:
Step 4-1, determines objective function
For optimizing capacity allocation models, the present invention is established with micro-capacitance sensor infrastructure investment cost, and flexible load dispatches cost
With the comprehensive optimal Optimal Allocation Model of renewable energy consumption rate.
Integrated objective function may be expressed as:
For integrated objective function, the physics meaning as representated by each sub-goal is different, there is the difference in dimension,
Therefore often lack between each sub-goal comprehensive.To avoid this problem, the present invention is based on the concepts of per unit value, with each specific item
Equal weight is marked, each sub-goal independence optimal solution carries out nondimensionalization processing to integrated objective function as a reference value.
In formula,fflAnd fUREPRespectively system cost, flexible load scheduling cost and renewable energy discard rate,
That is each sub-goal of integrated objective function；WithThe independent optimal solution of respectively each sub-goal；ωACS、
ωflAnd ωUREPFor each sub-goal weight.
Step 4-1-1, system cost
The years value investment cost such as system ACS (Annualized Cost of System) can be used as evaluating independent wind
The index of light storage micro-grid system capacity configuration economy superiority and inferiority.The years value expense such as system mainly includes equipment investment cost, operation
With maintenance cost and displacement cost, expression formula are as follows:
In formula, CCI、COM、CRRespectively indicate a year equipment investment cost, year operation and maintenance cost and year displacement cost.
Wherein:
In formula:The respectively unit price of photovoltaic battery panel, blower, battery；
It is respectively the year operation and maintenance cost of unit photovoltaic battery panel, blower, battery；CRLTo be replaced as this summation in the time limit；
Npv、Nwt、NbatThe respectively installation number of photovoltaic battery panel, blower, battery；fcrFor coefficient of depreciation；R indicates allowance for depreciation；
Step 4-1-2, flexible load dispatch cost
By previous analysis it is found that flexible load scheduling cost includes the cost of compensation of interruptible load and can motivate load
Incentive cost.Flexible load participates in scheduling and shows as demand response, in the case where keeping both sides of supply and demand interests dynamic equalization, draws
Lead the behavior of power consumer.Therefore, flexible load scheduling cost had both shown as the operation cost of supply side or had shown as user side
Income.
For supply side micro-capacitance sensor, part sale of electricity income is dispatched cost recovery user by micro-capacitance sensor.
For ensure micro-capacitance sensor income, present invention provide that flexible load dispatch cost allow dispatch range in it is not out-of-limit, that is, work as flexibility
Load scheduling cost is not prescribed a time limit more, and the present invention will be flexible negative using being described based on the nonlinear model of marginal cost pricing strategy
Lotus dispatch cost, it is on the contrary then according to maximum allowable cost recovery user.Therefore, the flexible load i scheduling cost of user n can define
Are as follows:
Wherein:
In formula,For the incentive cost for motivating load of user n；For the interruptible load of user n
Cost of compensation；θmaxFor greatest flexibility load scheduling cost coefficient；ciFor load i unit price of power；Pli-n(t) it is dispatched for flexible load
The workload demand of user n afterwards；α1And α2For the drive factor that can motivate load；β1And β2For the penalty coefficient of interruptible load.
Micro-capacitance sensor year flexible load dispatches cost:
In formula,For the cost of compensation of year interruptible load；The incentive cost of load can be motivated for year.
Step 4-1-3, renewable energy discard rate
Renewable energy discards rate UREP (Unutilized Renewable Energy Probability) and can be used to make
The horizontal index of renewable energy consumption is configured to evaluate independent wind-light storage micro-grid system power supply capacity, definition can be described as:
In formula, fUREPRate is discarded for renewable energy；Pl(t) workload demand after scheduling is participated in for flexible load
Step 4-2, evaluation index,
Step 4-2-1, wind light mutual complementing
For luminous energy and the Variation Features of wind energy, the two has stronger complementarity in time.This characteristic can table
It is shown as:
In formula, DLFor wind light mutual complementing characteristic；For the mean power of initial load.And DLSmaller, wind light mutual complementing is got over
It is good.
Step 4-2-2, power supply reliability
Load short of electricity rate (the loss of power supply probability, LPSP) is represented by a period of time
Interior, system power output is less than the period of load power and the ratio of total period, can be used to indicate system power supply reliability.
Step 4-2-3, year electricity cost expenditure
User participates in micro-capacitance sensor operation in such a way that flexible load is dispatched, and realizes supply and demand interaction.Its year electricity cost by
Actual load electricity cost and flexible load scheduling cost composition.
In formula, CelFor year electricity cost expenditure.
Step 4-3, constraint condition
Step 4-3-1, power supply reliability constraint
To ensure user power utilization demand, it is desirable that load short of electricity rate is can be in tolerance range:
LPSP≤εLPSP
Wherein, εLPSPFor the reference value for loading short of electricity rate.
Step 4-3-2, system installed capacity constraint
Each generator unit installed capacity of micro-grid system is influenced to be limited in by the engineerings practical factor such as place occupied area
Within a certain range.
In formula, NPv, min、NWt, min、NBat, minThe respectively minimum installation number of photovoltaic battery panel, blower, battery；
NPv, max、NWt, max、NBat, maxRespectively its corresponding maximum installation number.
Step 4-3-3, power-balance constraint
At runtime, wind-powered electricity generation, photovoltaic, energy storage and load in system etc. require to meet active power balance micro-capacitance sensor,
That is:
In formula, PURE(t) power discarded for renewable energy；PlossIt (t) is system power vacancy.
Step 4-3-4, accumulator cell charging and discharging constraint
The service life for effectively extending battery, can avoid cost of investment caused by due to frequently replacing battery substantially
Degree increases.It can play the role of extending the battery-operated service life to the limitation of accumulator cell charging and discharging depth and charge-discharge electric power.
SOCmin≤SOC(t)≤SOCmax
Wherein, SOCmaxAnd SOCminThe respectively upper and lower bound of battery remaining capacity；
WithThe respectively upper and lower bound of accumulator cell charging and discharging power；
Step 4-3-5, flexible load schedule constraints
Scheduling potentiality be flexible load a kind of intrinsic physical attribute, for describing power when flexible load participates in scheduling
The ability increasedd or decreased.
In formula,WithRespectively all kinds of flexible load maximums can motivate potentiality and maximum that can interrupt
Potentiality.
Step 5, " taboo list " and " disturbance ", " restarting " operations improvement particle swarm algorithm are introduced:
Step 5-1 introduces dynamic inertia weight and improves particle swarm algorithm
Particle swarm optimization algorithm (PSO) is proposed by Kennedy and Eberhart 1995 for the first time, because its concept is simple, spirit
The features such as active strong and easy to accomplish and be widely used in the solution of engineering problem.PSO can be used for solving multi-target non-linear
Optimization problem, it is assumed that in a D dimension search space, population X is formed by m particle, wherein i-th of particle is expressed as a D
The X of dimensional vectori.For each particle i, all it is made of 3 D dimensional vectors, respectively current position (Xi), the optimal position of history
Set (pbesti) and speed (Vi).In each iterative process, particle will update the speed of itself by individual extreme value and group's extreme value
Degree and position, it may be assumed that
Wherein, ω is inertia weight；K is current iteration number；D=1,2 ..., D；I=1,2 ..., m；c1And c2To accelerate
The factor；r1And r2For the random number for being distributed in [0,1] section.
In solution procedure, ω plays the role of a balance local search ability and ability of searching optimum, value
Range effects the solving precision of algorithm.The value of ω may be set to changeless and dynamic change.Based on being ground to PSO
Study carefully, when compared to ω dynamic change, although PSO has faster convergence rate when ω immobilizes, solving precision is lower.
It is therefore of the invention by ω is defined as:
ω (k)=ωStart(ωStart-ωend)(K-k)/K
Wherein, ωstartFor initial inertia weight；ωendInertia weight when for the number of iterations maximum；K is greatest iteration time
Number.
Step 5-2, model solution
Model is solved using modified particle swarm optiziation, such as attached drawing 3.
Step 6, example and its essential feature are determined, using MATLAB software programming particle swarm algorithm program to example into
Row simulation analysis.
Step 6-1 determines example and its essential feature
By taking somewhere as an example, simulation analysis is carried out with MATLAB 7.10.Choose the meteorological data (packet of this area's Typical Year
Include wind speed, illumination and temperature) and power load；Choose rated power be 35kW Wind turbines, rated power be 100W light
Battery pack and rated capacity are lied prostrate as the battery of 300Wh；It is research section with annual 8760h as unit of hour.
Step 6-2 carries out simulation analysis to example using MATLAB software programming modified particle swarm optiziation program
By emulation it is found that the model can improve microgrid economical operation in the case where guaranteeing system operation reliability
Property and renewable energy consumption ability.
Embodiment described above only describe the preferred embodiments of the invention, not to model of the invention
It encloses and is defined, without departing from the spirit of the design of the present invention, those of ordinary skill in the art are to technical side of the invention
The various changes and improvements that case is made should all be fallen into the protection scope that claims of the present invention determines.
Claims (9)
1. a kind of independent micro-grid system capacity configuration optimizing method, which is characterized in that the step of the method is as follows:
Step 1, it determines the networking mode of micro-grid system, refines flexible load type；
Step 2, it determines micro-grid system energy scheduling strategy priority, proposes the system capacity scheduling for considering flexible load scheduling
Strategy；
Step 3, it establishes and considers polymorphic type flexible load Optimal Operation Model；
Step 4, objective function and constraint condition are determined, the double-goal optimal model for considering flexible load is established；
Step 5, it introduces dynamic inertia weight and improves particle swarm algorithm；
Step 6, example and its essential feature are determined, example is emulated using MATLAB software programming particle swarm algorithm program
Analysis.
2. a kind of independent micro-grid system capacity configuration optimizing method according to claim 1, which is characterized in that the step
Rapid 1 detailed process is as follows:
Step 1-1 determines the networking mode of micro-grid system
Select the networking mode of DC bus；
Step 1-2 refines flexible load type
Schedulable flexible load is divided into industrial height and loads with 3 class of lotus, commercial polymerization load and resident's intelligent domestic load.
3. a kind of independent micro-grid system capacity configuration optimizing method according to claim 1, which is characterized in that the step
Rapid 2 detailed process is as follows:
Step 2-1 determines micro-grid system energy scheduling strategy priority
The optimization energy management strategies for the flexible load containing polymorphic type that building " source-storage-lotus " is mutually coordinated；
According to way to manage difference, flexible load, which is divided into, can motivate load and interruptible load；Mode based on contract engagement, root
The power demand of user is decreased or increased in any time that micro-capacitance sensor requires according to the agreement that micro-capacitance sensor and user sign；And
When user decreases or increases its power demand according to agreement, micro-capacitance sensor pays certain expense to user to compensate its loss or drop
For low electricity price as reward, guidance user is actively engaged in microgrid operation, realizes the two-way interaction of supply and demand side；
When the unbalanced power between load and blower and photovoltaic power output, preferentially balanced by battery by charge and discharge；When
When the charge-discharge electric power or remaining capacity of battery exceed restriction range, arranged to coordinate energy-storage system as agreed by flexible load
Stabilize the imbalance power between load and micro battery；
Step 2-2 proposes the system capacity scheduling strategy for considering flexible load
When scene power output is sufficient, the power of system spare first charges to battery；When charge power or remaining capacity
More than still having residue after the restriction range of battery, then dissolved by flexible load by increasing electricity consumption；
When honourable undercapacity, the power of system spare first discharges to battery；When discharge power and remaining capacity
More than still having vacancy after the restriction range of battery, system power load is reduced by flexible load to balance.
4. a kind of independent micro-grid system capacity configuration optimizing method according to claim 1, which is characterized in that the step
Rapid 3 detailed process is as follows: schedulable flexible load being divided into industrial height and loads with lotus, commercial polymerization load and resident's intelligence man
With 3 class of load；
If each schedulable capacity amount of period flexible load are as follows:
Δ P (t)=Pwt(t)+Ppv(t)-PL, 0(t)-Pbat(t)
In formula, Δ P (t) is the schedulable total capacity of flexible load；PL, 0It (t) is initial load demand, i.e., flexible load participates in adjusting
Workload demand before degree；Pwt(t)、Ppv(t) and PbatIt (t) is respectively blower output power, photovoltaic output power and battery
Charge/discharge power；
The mathematical model that all kinds of flexible loads participate in scheduling may be defined as:
In formula, i=1,2,3 be flexible load type, respectively refers to industrial height and loads with lotus, commercial polymerization load and resident's intelligent domestic
Load；NiFor the number of users for participating in flexible load i scheduling；PfliIt (t) is flexible load i actual schedule total capacity；Pfli-n(t)
For user's n actual participation flexible load i scheduling capacity；PLi, 0-n(t) workload demand for being user n；WithRespectively load i's drive factor and can interrupt coefficient；WithDetermine that can load i for a pair
Participate in the decision-making coefficient group of flexible load scheduling；
The wish that electricity consumption was interrupted and increased to the scheduling potentiality of flexible load and each user, which affects, drive factor and can interrupt and be
Several values, may be defined as:
In formula,WithRespectively flexible load i can motivate potentiality and can interrupt potentiality；
WithRespectively user n increases and the willingness factor of interruptible load i；
Decision-making coefficient is related with the form that each flexible load participates in scheduling, may be expressed as:
In formula, as i=2, λ=0；When i ≠ 2, λ=1.
5. a kind of independent micro-grid system capacity configuration optimizing method according to claim 1, which is characterized in that the step
Rapid 4 detailed process is as follows:
Step 4-1, determines objective function
Establish Optimal Allocation Model；
Integrated objective function may be expressed as:
Concept based on per unit value, with each sub-goal equal weight, each sub-goal independence optimal solution is as a reference value to integration objective
Function carries out nondimensionalization processing；
In formula,fflAnd fUREPRespectively system cost, flexible load scheduling cost and renewable energy discard rate, i.e., comprehensive
Close each sub-goal of objective function；WithThe independent optimal solution of respectively each sub-goal；ωACS、ωflWith
ωUREPFor each sub-goal weight；
Step 4-2, evaluation index；
Step 4-3, constraint condition.
6. a kind of independent micro-grid system capacity configuration optimizing method according to claim 1, which is characterized in that the step
Rapid 5 detailed process is as follows:
Step 5-1 introduces dynamic inertia weight and improves particle swarm algorithm
For particle swarm optimization algorithm (PSO) in each iterative process, particle will update itself by individual extreme value and group's extreme value
Speed and position, it may be assumed that
Wherein, ω is inertia weight；K is current iteration number；D=1,2 ..., D；I=1,2 ..., m；c1And c2For accelerate because
Son；r1And r2For the random number for being distributed in [0,1] section；
By ω is defined as:
ω (k)=ωstart(ωstart-ωend)(K-k)/K
Wherein, ωstartFor initial inertia weight；ωendInertia weight when for the number of iterations maximum；K is maximum number of iterations；
Step 5-2, model solution
Model is solved using modified particle swarm optiziation, the specific steps are as follows:
(1) particle initializes, and the local optimum of each particle is found out according to practical climatic environment, user data and component parameter
Solution and globally optimal solution；
(2) fitness of each particle is calculated, and judges whether particle meets constraint；
(3) compare the individual optimal solution (pbest) of particle adaptive value and it, if being better than pbest, pbest is current particle
Position；Compare particle pbest and globally optimal solution (gbest), if being better than gbest, the pbest of this particle is gbest；
(4) speed of more new particle and position；
(5) continue iteration until reaching maximum number of iterations, and export result.
7. a kind of independent micro-grid system capacity configuration optimizing method according to claim 5, which is characterized in that step 4-
1 particular content is as follows:
Step 4-1-1, system cost
The years value expense such as system mainly includes equipment investment cost, operation and maintenance cost and displacement cost, expression formula are as follows:
In formula, CCI、COM、CRRespectively indicate a year equipment investment cost, year operation and maintenance cost and year displacement cost；
Wherein:
In formula:The respectively unit price of photovoltaic battery panel, blower, battery；Point
Not Wei unit photovoltaic battery panel, blower, battery year operation and maintenance cost；CRLTo be replaced as this summation in the time limit；Npv、
Nwt、NbatThe respectively installation number of photovoltaic battery panel, blower, battery；fcrFor coefficient of depreciation；R indicates allowance for depreciation；
Step 4-1-2, flexible load dispatch cost
Will using describing based on the nonlinear model of marginal cost pricing strategy flexible load scheduling cost, it is on the contrary then according to most
It is big to allow cost recovery user；Therefore, the flexible load i scheduling cost of user n may be defined as:
Wherein:
In formula,For the incentive cost for motivating load of user n；For the compensation of the interruptible load of user n
Cost；θmaxFor greatest flexibility load scheduling cost coefficient；ciFor load i unit price of power；Pli-n(t) it is used after being dispatched for flexible load
The workload demand of family n；α1And α2For the drive factor that can motivate load；β1And β2For the penalty coefficient of interruptible load；
Micro-capacitance sensor year flexible load dispatches cost:
In formula,For the cost of compensation of year interruptible load；The incentive cost of load can be motivated for year；
Step 4-1-3, renewable energy discard rate
Renewable energy discards rate UREP (Unutilized Renewable EnergyProbability) and can be used as commenting
Valence independence wind-light storage micro-grid system power supply capacity configures the horizontal index of renewable energy consumption, and definition can be described as:
In formula, fUREPRate is discarded for renewable energy；Pl(t) workload demand after scheduling is participated in for flexible load.
8. a kind of independent micro-grid system capacity configuration optimizing method according to claim 5, which is characterized in that step 4-
2 particular content is as follows:
Step 4-2-1, wind light mutual complementing
For luminous energy and the Variation Features of wind energy, the two has stronger complementarity in time, may be expressed as:
In formula, DLFor wind light mutual complementing characteristic；For the mean power of initial load；And DLSmaller, wind light mutual complementing is better；
Step 4-2-2, power supply reliability
Load short of electricity rate (the loss of power supply probability, LPSP) was represented by a period of time,
System power output is less than the period of load power and the ratio of total period, can be used to indicate system power supply reliability；
Step 4-2-3, year electricity cost expenditure
User participates in micro-capacitance sensor operation in such a way that flexible load is dispatched, and realizes supply and demand interaction；Electricity cost is by reality within its year
Load electricity cost and flexible load scheduling cost composition；
In formula, CelFor year electricity cost expenditure.
9. a kind of independent micro-grid system capacity configuration optimizing method according to claim 5, which is characterized in that step 4-
3 particular content is as follows:
Step 4-3-1, power supply reliability constraint
To ensure user power utilization demand, it is desirable that load short of electricity rate is can be in tolerance range:
LPSP≤εLPSP
Wherein, εLPSPFor the reference value for loading short of electricity rate；
Step 4-3-2, system installed capacity constraint
Each generator unit installed capacity of micro-grid system is influenced to be limited in certain by the engineerings practical factor such as place occupied area
Within the scope of；
In formula, NPv, min、NWt, min、NBat, minThe respectively minimum installation number of photovoltaic battery panel, blower, battery；NPv, max、
NWt, max、NBat, maxRespectively its corresponding maximum installation number；
Step 4-3-3, power-balance constraint
At runtime, wind-powered electricity generation, photovoltaic, energy storage and load in system etc. require to meet active power balance micro-capacitance sensor, it may be assumed that
In formula, PURE(t) power discarded for renewable energy；PlossIt (t) is system power vacancy；
Step 4-3-4, accumulator cell charging and discharging constraint
It can play the role of extending the battery-operated service life to the limitation of accumulator cell charging and discharging depth and charge-discharge electric power；
SOCmin≤SOC(t)≤SOCmax
Wherein, SOCmaxAnd SOCminThe respectively upper and lower bound of battery remaining capacity；WithThe respectively upper and lower bound of accumulator cell charging and discharging power；
Step 4-3-5, flexible load schedule constraints
Scheduling potentiality be flexible load a kind of intrinsic physical attribute, increase for describing power when flexible load participates in scheduling
Or reduced ability；
In formula,WithRespectively all kinds of flexible load maximums can motivate potentiality and maximum that can interrupt potentiality.
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