CN109347139A - A kind of Distributed Generation in Distribution System maximum penetration level Optimal Configuration Method - Google Patents

A kind of Distributed Generation in Distribution System maximum penetration level Optimal Configuration Method Download PDF

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Publication number
CN109347139A
CN109347139A CN201811141556.7A CN201811141556A CN109347139A CN 109347139 A CN109347139 A CN 109347139A CN 201811141556 A CN201811141556 A CN 201811141556A CN 109347139 A CN109347139 A CN 109347139A
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power
formula
maximum
particle
network
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Inventor
顾皓亮
阎鼎
郝珈玮
孙志恒
邓孟华
刘议华
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State Grid Shanghai Electric Power Co Ltd
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State Grid Shanghai Electric Power Co Ltd
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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
    • H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
    • H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
    • 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
    • H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
    • 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]

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

Abstract

The invention discloses a kind of Distributed Generation in Distribution System maximum penetration level Optimal Configuration Methods, it establishes and target is up to DG access capacity, fully consider that power distribution network is safe and reliable, DG Optimal Allocation Model of stable operation, enable DG at high proportion, large capacity access power distribution network.

Description

A kind of Distributed Generation in Distribution System maximum penetration level Optimal Configuration Method
Technical field
The present invention relates to a kind of Distributed Generation in Distribution System maximum penetration level optimizations for distributed power grid field Configuration method.
Background technique
Currently, generally acknowledged bulk power grid interconnection can be solved effectively with the grid-connected electric system combined of distributed generation resource in the world The certainly inconsistent problem in resource, load position increases grid stability, improves power supply reliability, and power transmission and distribution economy is sent out in optimization, The problems such as improving electric system flexibility.Distributed generation resource (Distributed Generation, DG), which refers to, to be directly arranged at Power distribution network or the power generating equipment being distributed near load, general capacity is at thousands of watts between 50MW.Distributed power generation unit root According to the difference for using technology, can be divided into thermoelectric cold cogeneration power generation, miniature gas turbine power generation, miniature hydro-power generation, wind-power electricity generation, Solar energy power generating, fuel cell, energy storage device etc..
Because DG power supply ratio increase can reduce the pollutant discharge amount of conventional rack, DG and network capacity in power distribution network Amount maximizes the optimization for being also equivalent to environmental benefit.But when DG permeability is higher in network, if unreasonable optimization DG's connects Enter position, quantity and capacity, then can seriously threaten the safe and stable operation of system.It is target to distribution using DG maximum penetration level Net DG distribute rationally be technical staff main target.
Summary of the invention
It is maximum quasi- the purpose of the invention is to overcome the deficiencies of the prior art and provide a kind of Distributed Generation in Distribution System Entering capacity configuration optimizing method, it enables to power distribution network DG grid connection capacity higher, and ensure that power distribution network safe and stable operation, Network voltage distribution is optimized, node voltage level is improved, reduces active power loss when distribution system operation.
Realizing a kind of technical solution of above-mentioned purpose is: a kind of 1. Distributed Generation in Distribution System maximum penetration level optimizations Configuration method, including for describing the grid-connected maximum objective function of DG capacity in plot to be planned
N in formulaDGFor DG access node to be selected, PDGiActive power is accessed for the DG of i-th of access point, which uses The total active maximum allocation plan of access of DG in searching power distribution network,
It is characterised in that it includes following several constraint steps:
Step 1, power flow equation constrains step, in the case where power network safety operation, the wattful power of the power distribution network containing DG Shown in rate equation, reactive power equation and nodal voltage equation such as formula (2)-(4), using 3 power flow equations as (1) formula mesh The equality constraint of scalar functions:
P in formulai、QiThe active and reactive power of respectively i-th branch road, Ri、XiFor i-th branch road resistance with Reactance, UiFor the node voltage of i-th of node, PLi、QLiFor the load active and reactive power of i-th of node, PDGi、QDGiIt is i-th The DG active and reactive power of a node；
Step 2, node voltage constrains step, and formula (5) is the node voltage constraint equation of this paper；
0.93UN≤U≤1.07UN(5)
U in formulaNFor node voltage rating；
Step 3, voltage level and network loss constrain step, formula (6), the network voltage that (7) are this paper level and active power loss Constraint equation,
LDG< ε1×Ldis(6)
Ploss.DG≤ε2×Ploss.dis(7)
L in formulaDG、LdisVoltage level index when DG, P are added and are added without for power distribution networkloss.DG、Ploss.disFor distribution Net is added and is added without active power loss when DG；
Step 4, DG investment operation total cost constraint, the upper limit C of setting DG investment operation total costDGmax；
CDG< CDGmax(8)
C in formulaDGTotal cost is run for the actual investment of DG in certain planning horizon；Y is the DG planning investment time limit；CZiFor The unit capacity equipment complex cost of i-th of DG, including prime mover cost, generator cost and other ancillary equipment costs；CAi For the installation cost as per machine capacity of i-th of DG；CWiFor the fixation year maintenance cost of DG；
Step 5, constraint condition aggregation step, each constraint condition summarize as shown in formula (10).
P in formulal、Pl.maxIt is limited for the practical active power and maximum active power of each branch of power distribution network；PsFor power distribution system The actual power united to transmission system purchase, Ps.maxThe maximum power bought for distribution system to transmission system；
Step 6, step is exported, DG maximum grid connection capacity and optimal on-position are exported by particle swarm algorithm.
Further, the step 6, output step are included the following steps: using random weight heavy particle group's algorithm
Step 6.1, network initial parameter and algorithm parameter are inputted, taking population scale herein is 80, μmin=0.5, μmax= 0.8, σ=0.2；
Step 6.2, the value and initial velocity for generating each particle at random calculate network trend with Newton-Raphson approach, Then objective function is solved, the maximum target functional value P in each particle is recordedbest(i.e. DG maximum grid connection capacity), each particle Target function value FPbestAnd the position Pos (i.e. each DG access point to be selected) of optimal particle；
Step 6.3, the number of iterations is updated, by formula
ω is calculated, the speed and location information of each particle are then updated, rand (0,1) indicates random between 0-1 in formula Number, N (0,1) indicate standardized normal distribution random number, the random weight of μ average out to, μminFor least random weighted mean, μmaxFor Largest random weighted mean, σ are the variance of random weight；
Step 6.4 calculates new trend and each particle target function value, and compared with previous iteration result, updates and record Maximum target functional value and particle position in each particle；
Step 6.5 judges whether to reach maximum number of iterations kmaxIf reaching, terminator, it is on the contrary then repeat step 5.3,5.4；
Step 6.6, output DG maximum grid connection capacity and optimal on-position.
A kind of Distributed Generation in Distribution System maximum penetration level Optimal Configuration Method of the invention, is established and is accessed with DG Capacity is up to target, fully considers that power distribution network is safe and reliable, DG Optimal Allocation Model of stable operation, enables DG high Ratio, large capacity access power distribution network.
Specific embodiment
In order to preferably understand technical solution of the present invention, carried out in detail below by specifically embodiment Illustrate:
A kind of Distributed Generation in Distribution System maximum penetration level Optimal Configuration Method of the invention, including for describe to Plan the grid-connected maximum objective function of DG capacity in plot:
N in formulaDGFor DG access node to be selected, PDGiActive power is accessed for the DG of i-th of access point, which uses The total active maximum allocation plan of access of DG in searching power distribution network,
Including following several constraint steps:
Step 1, power flow equation constrains step, in the case where power network safety operation, the wattful power of the power distribution network containing DG Shown in rate equation, reactive power equation and nodal voltage equation such as formula (2)-(4), using 3 power flow equations as (1) formula mesh The equality constraint of scalar functions:
P in formulai、QiThe active and reactive power of respectively i-th branch road, Ri、XiFor i-th branch road resistance with Reactance, UiFor the node voltage of i-th of node, PLi、QLiFor the load active and reactive power of i-th of node, PDGi、QDGiIt is i-th The DG active and reactive power of a node；
Step 2, node voltage constrains step, the grid-connected original operating status for changing distribution power flow of DG, to each section The voltage of point has lifting effect.According to China's standard GB/T/T's 12325-2008 " power quality-supply voltage deviation " Regulation, 20kV and following three phase supply voltage deviation are ± the 7% of nominal voltage.Since the object of this method adjustment is in 10kV It is press-fitted power grid, so taking ± 7% is the limit value of node voltage deviation.Formula (5) is the node voltage constraint equation of this method.
0.93UN≤U≤1.07UN(5)
U in formulaNFor node voltage rating.
Step 3, voltage level and network loss constrain step, improve distribution network voltage level and reduce the weight that network loss is DG investment One of economical, society, environmental benefit are wanted, so requiring the investment objective of DG herein is to improve power distribution system voltage level, net Damage reduces；
Formula (6), the network voltage level and active power loss constraint equation that (7) are this paper,
LDG< ε1×Ldis(6)
Ploss.DG≤ε2×Ploss.dis(7)
L in formulaDG、LdisVoltage level index when DG, P are added and are added without for power distribution networkloss.DG、Ploss.disFor distribution Net is added and is added without active power loss when DG；ε1、ε2Between 0-1, according to physical planning scheme rear system electricity grid-connected to DG The requirement of voltage levels and network loss carries out value.
Step 4, DG investment operation total cost constraint, although the use scope recently as DG is increasing, is mounted to This is also reduced year by year, but the power system operation mode relative to the interconnection of traditional bulk power grid, and investment operating cost is still inclined It is high.So needing to invest it operation total cost makes certain limitation.Herein by reference to the engineering actual state of domestic DG, DG is taken Unit capacity equipment complex cost and installation cost are respectively 4,300,000 yuan/MW and 1,200,000 yuan/MW, and the maintenance operation expense of DG is 150000/(year * MW).To certain planning horizon, the upper of operation total cost can be invested according to above-mentioned economy data setting DG Limit CDGmax
CDG< CDGmax(8)
C in formulaDGTotal cost is run for the actual investment of DG in certain planning horizon；Y is the DG planning investment time limit；CZiFor The unit capacity equipment complex cost, including prime mover cost, generator cost and other ancillary equipment costs etc. of i-th of DG； CAiFor the installation cost as per machine capacity of i-th of DG； CWiFor the fixation year maintenance cost of DG；
Step 5, constraint condition aggregation step, each constraint condition summarize as shown in formula (10).
P in formulal、Pl.maxIt is limited for the practical active power and maximum active power of each branch of power distribution network；PsFor power distribution system The actual power united to transmission system purchase, Ps.maxThe maximum power bought for distribution system to transmission system；
Step 6, step is exported, DG maximum grid connection capacity and optimal on-position are exported by particle swarm algorithm.
Particle swarm algorithm is a kind of Swarm Intelligence Algorithm, it is a kind of EVOLUTIONARY COMPUTATION based on swarm intelligence method, it Advantage is that calculating effect is good, and precision is high, and simple, intuitive is easy to accomplish, versatile, and it is again especially suitable to be not only suitable for scientific research For engineering optimization problem.
The superiority and inferiority of all kinds of particle swarm algorithms depends on its ability of searching optimum and local search ability.Random weight heavy particle group Algorithm is generated because its weights omega is random in each iteration, therefore its overall situation and partial situation's search energy that can preferably take into account algorithm Power.Compared with linear weight particle swarm algorithm, it can overcome two o'clock shortcoming.One, if the initial position of particle with most Excellent to be closely located to, then algorithm makes particle be quickly found out optimal location there may be less ω；Two, if the initial stage without Method is quickly found out optimal location, then the ω of linear decrease, which will lead to algorithm, cannot find optimum point, and the random generation of ω is then The limitation can be overcome.Shown in the ω calculation formula such as formula (11) generated at random:
Rand (0,1) indicates the random number between 0-1 in formula, and N (0,1) indicates standardized normal distribution random number, μ average out to Random weight, μminFor least random weighted mean, μmaxFor largest random weighted mean, σ is the variance of random weight.
It includes following sub-step that DG based on random weight heavy particle group's algorithm, which distributes step rationally:
Step 6.1, network initial parameter and algorithm parameter are inputted, taking population scale herein is 80, μmin=0.5, μmax= 0.8, σ=0.2；
Step 6.2, the value and initial velocity for generating each particle at random calculate network trend with Newton-Raphson approach, Then objective function is solved, the maximum target functional value Pbest (i.e. DG maximum grid connection capacity) in each particle, each particle are recorded Target function value FPbest and optimal particle position Pos (i.e. each DG access point to be selected)；
Step 6.3, the number of iterations is updated, ω is calculated by formula (11), then updates the speed and location information of each particle；
Step 6.4 calculates new trend and each particle target function value, and compared with previous iteration result, updates and record Maximum target functional value and particle position in each particle；
Step 6.5 judges whether to reach maximum number of iterations kmaxIf reaching, termination process, it is on the contrary then repeat step 6.3、6.4。
Those of ordinary skill in the art it should be appreciated that more than embodiment be intended merely to illustrate the present invention, And be not used as limitation of the invention, as long as the change in spirit of the invention, to embodiment described above Change, modification will all be fallen within the scope of claims of the present invention.

Claims (2)

1. a kind of Distributed Generation in Distribution System maximum penetration level Optimal Configuration Method, including for describing plot to be planned simultaneously Net the maximum objective function of DG capacity:
N in formulaDGFor DG access node to be selected, PDGiActive power is accessed for the DG of i-th of access point, the objective function is for seeking The total active maximum allocation plan of access of DG in power distribution network is looked for,
It is characterised in that it includes following several constraint steps:
Step 1, power flow equation constrains step, in the case where power network safety operation, the active power side of the power distribution network containing DG Shown in journey, reactive power equation and nodal voltage equation such as formula (2)-(4), using 3 power flow equations as (1) formula target letter Several equality constraints:
P in formulai、QiThe active and reactive power of respectively i-th branch road, Ri、XiResistance and reactance for i-th branch road, Ui For the node voltage of i-th of node, PLi、QLiFor the load active and reactive power of i-th of node, PDGi、QDGiFor i-th of node DG active and reactive power；
Step 2, node voltage constrains step, and formula (5) is the node voltage constraint equation of this paper；
0.93UN≤U≤1.07UN (5)
U in formulaNFor node voltage rating；
Step 3, voltage level and network loss constrain step, and formula (6), the network voltage level that (7) are this paper and active power loss constrain Equation,
LDG< ε1×Ldis (6)
Ploss.DG≤ε2×Ploss.dis (7)
L in formulaDG、LdisVoltage level index when DG, P are added and are added without for power distribution networkloss.DG、Ploss.disFor power distribution network plus Active power loss when entering and being added without DG；
Step 4, DG investment operation total cost constraint, the upper limit C of setting DG investment operation total costDGmax；
CDG< CDGmax (8)
C in formulaDGTotal cost is run for the actual investment of DG in certain planning horizon；Y is the DG planning investment time limit；CZiIt is i-th The unit capacity equipment complex cost of DG, including prime mover cost, generator cost and other ancillary equipment costs；CAiIt is i-th The installation cost as per machine capacity of a DG；CWiFor the fixation year maintenance cost of DG；
Step 5, constraint condition aggregation step, each constraint condition summarize as shown in formula (10).
P in formulal、Pl.maxIt is limited for the practical active power and maximum active power of each branch of power distribution network；PsIt is distribution system to defeated The actual power of electric system purchase, Ps.maxThe maximum power bought for distribution system to transmission system；
Step 6, step is exported, DG maximum grid connection capacity and optimal on-position are exported by particle swarm algorithm.
2. a kind of Distributed Generation in Distribution System maximum penetration level Optimal Configuration Method according to claim 1, special Sign is that the step 5, output step is included the following steps: using random weight heavy particle group's algorithm
Step 6.1, network initial parameter and algorithm parameter are inputted, taking population scale herein is 80, μmin=0.5, μmax=0.8, σ =0.2；
Step 6.2, the value and initial velocity for generating each particle at random calculate network trend with Newton-Raphson approach, then Objective function is solved, the maximum target functional value P in each particle is recordedbest(i.e. DG maximum grid connection capacity), the target of each particle Functional value FPbestAnd the position Pos (i.e. each DG access point to be selected) of optimal particle；
Step 6.3, the number of iterations is updated, by formula
ω is calculated, the speed and location information of each particle are then updated, rand (0,1) indicates the random number between 0-1, N in formula (0,1) standardized normal distribution random number, the random weight of μ average out to, μ are indicatedminFor least random weighted mean, μmaxFor maximum Random weighted mean, σ are the variance of random weight；
Step 6.4 calculates new trend and each particle target function value, and compared with previous iteration result, updates and record each grain Maximum target functional value and particle position in son；
Step 6.5 judges whether to reach maximum number of iterations kmaxIf reaching, terminator, it is on the contrary then repeat step 6.3, 6.4；
Step 6.6, output DG maximum grid connection capacity and optimal on-position.
CN201811141556.7A 2018-09-28 2018-09-28 A kind of Distributed Generation in Distribution System maximum penetration level Optimal Configuration Method Pending CN109347139A (en)

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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110311422A (en) * 2019-07-23 2019-10-08 南方电网科学研究院有限责任公司 Control method, device and equipment for distributed power supply grid-connected power
CN110556881A (en) * 2019-10-25 2019-12-10 南方电网科学研究院有限责任公司 Method and device for quantizing flexibility margin of power compensation of power distribution network
CN110932308A (en) * 2019-07-23 2020-03-27 国网浙江省电力有限公司湖州供电公司 Distributed power supply grid-connected capacity management system and management method
CN112039122A (en) * 2020-09-24 2020-12-04 南方电网科学研究院有限责任公司 Planning method and device for designing distributed power supply grid connection based on power grid access capacity

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110311422A (en) * 2019-07-23 2019-10-08 南方电网科学研究院有限责任公司 Control method, device and equipment for distributed power supply grid-connected power
CN110932308A (en) * 2019-07-23 2020-03-27 国网浙江省电力有限公司湖州供电公司 Distributed power supply grid-connected capacity management system and management method
CN110556881A (en) * 2019-10-25 2019-12-10 南方电网科学研究院有限责任公司 Method and device for quantizing flexibility margin of power compensation of power distribution network
CN112039122A (en) * 2020-09-24 2020-12-04 南方电网科学研究院有限责任公司 Planning method and device for designing distributed power supply grid connection based on power grid access capacity

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