CN109217352A - Active distribution network source net lotus collaborative planning method based on DG initialization addressing - Google Patents
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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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Abstract
Disclosed herein is a kind of active distribution network source net lotus collaborative planning methods based on DG initialization addressing, the following steps are included: first, dual uncertain and Demand-side resource the response characteristic for considering renewable energy power output, establishes the timing power flow algorithm of polymorphic type distributed generation resource and flexible load.On this basis, consider active control and management measure, establish the double-deck coordinated planning model of active distribution network " source-net-lotus ", and solve to plan model using a kind of improvement particle swarm algorithm and the hybrid algorithm for predicting that correction interior point combines.The algorithm uses the fuzzy control method based on node voltage and the power loss sensitivity factor, initializes to the on-position DG, can effectively improve the global optimizing ability of algorithm.
Description
Technical field
The present invention relates to active distribution network planning field, more specifically to a kind of active based on DG initialization addressing
Power distribution network source net lotus collaborative planning method.
Background technique
It is contributed and is had as the renewable distributed generation resource (distributed generator, DG) of representative using wind-powered electricity generation and photovoltaic
There is apparent uncertainty, this characteristic brings new huge challenge to distribution network planning work.Conventional electrical distribution net follows " peace
Dress i.e. forget " passive control mode, limit the infiltration capacity of DG, be unable to give full play DG reduce network loss, improvement system
Voltage and trend distribution etc. positive effect.Active distribution network (active distribution network, ADN) is adopted
With flexible active control and management measure, the compatibility of renewable energy can be significantly improved, is the hair of the following smart grid
Open up direction.How on the basis of using active control and management measure, the coordination and interaction between power supply, power grid and load are considered
Global resource collaborative planning is carried out, is of great significance for guaranteeing ADN safe and stable operation, improving its economic benefit.
It is drawn relative to conventional electrical distribution network planning, active distribution network project study is also in the starting stage, but also achieves one
Fixed achievement.Current active distribution network project study is using the candidate installation node of artificial setting in terms of the addressing of DG
Set, this method are influenced by designer's subjective experience, are easy to cause the solution space of optimization process limited, algorithmic statement is in office
Portion's optimal solution can not obtain the programme of global optimum.
Summary of the invention
It is an object of the present invention to be directed to active distribution network unified plan problem, active control and management measure are being used
On the basis of, consider that the coordination and interaction between power supply, power grid and load carry out global resource collaborative planning, for guaranteeing ADN peace
Full stable operation improves its economic benefit.
To achieve the above object, the technical solution adopted by the present invention is that:
1) dual uncertain and Demand-side resource the response characteristic for considering renewable energy power output, establishes polymorphic type
The timing power flow algorithm of distributed generation resource and flexible load；
2) on this basis, consider active control and management measure, establish the double-deck coordination of active distribution network " source-net-lotus "
Plan model；
3) using a kind of improvement particle swarm algorithm and predict the hybrid algorithm that combines of correction interior point to plan model into
Row solves.
Technical solution of the present invention has the advantages that
Technical solution of the present invention is directed to active distribution network unified plan problem, using active control and management measure
On the basis of, consider that the coordination and interaction between power supply, power grid and load carry out global resource collaborative planning, for guaranteeing ADN safety
Stable operation improves its economic benefit.
Below by drawings and examples, technical scheme of the present invention will be described in further detail.
Detailed description of the invention
Fig. 1 is wind power supply power curve
Fig. 2 is photo-voltaic power supply power curve
Fig. 3 is active distribution network " source-net-lotus " collaborative planning frame
Fig. 4 is IEEE-33 Node power distribution system structure chart
Fig. 5 is dual layer resist flow chart
Specific embodiment
Below in conjunction with the drawings and specific embodiments, the present invention will be described in further detail.
This example is calculated by taking IEEE-33 Node power distribution system as an example, and structure is as shown in Figure 4.The benchmark of system holds
100MVA is measured, reference voltage is voltage rating 12.66kV, and network total load is (3715+j2300) kVA.Node voltage value
Range is 0.95~1.05p.u., and blower, photo-voltaic power supply, miniature gas turbine installation number of nodes are 2, energy storage and reactive compensation
Equipment node to be selected is 15,33.The rated capacity of separate unit DG is 10kW, and each node to be selected allows the DG number of units upper limit installed
It is 10；Separate unit capacity of energy storing device is 10kWh, and maximum charge-discharge electric power is 2kW, and each node to be selected allows the storage installed
Energy device the upper limit of the number is 5；OLTC tapping range is 0.95~1.05 (8 × 0.0125)；Group switching capacitor is most
Big installation group number is 10 groups, and every group of reactive compensation amount is 1kvar；Interruptible load node is 5,17, and unit demand interruption amount is
10kW.If rate of return on investment is that 0.08, DG duration of service is 20 years.
1) active distribution network " source-net-lotus " collaborative planning model is established.
A, upper layer plan model is established.
A1, objective function.
Civ=C1+CEENS+Cpp
In formula, Civ--- comprehensive method of investment operating cost；C1--- DG, energy storage, reactive compensation, Demand-side various kinds of equipment year
Convert cost of investment；CEENS--- power distribution network lacks power supply volume cost；Cop--- active distribution network annual operating and maintenance cost.
A2, constraint condition.
In formula, SI, g--- the installed capacity of i-node g class equipment；--- the maximum installation of i-node g class equipment
Capacity；Zg--- g class equipment installation node set to be selected；--- total installed capacity upper limit of power distribution network g class equipment.
B, lower layer's plan model is established.
B1, objective function.
Cop=Cs+CMT+CDR+Closs
In formula, Cs--- higher level's power grid purchases strategies；CMT--- miniature gas turbine operating cost；CDR--- it can interrupt negative
Carrying capacity cost；Closs--- distribution network loss cost.
B2, constraint condition.
In formula, PS, t、QS, t--- the active and reactive power of t moment higher level's power grid input ADN；NL--- it is negative in ADN
Lotus point sum；PL I, t、QL I, t--- the active and load or burden without work of i-th of load point of t moment；N --- system line sum；
PI, t loss、QI, t loss--- the active and reactive loss of i-th branch road of t moment；VB, t--- the voltage amplitude at t moment node b
Value；Vb min、Vb max--- the bound of voltage magnitude at node b；ΩB--- the set of ADN network node；IL, t--- t moment
Load on branch ij；Il max--- the maximum load of branch ij；PS, min--- higher level's power grid power output minimum value；Pt Ess, b——t
The charge/discharge power of energy storage device at moment b node；--- it the specified charging of energy storage device and is put at b node
Electrical power；ηc、ηd--- the charge and discharge efficiency of energy storage device；SOCt b--- the state-of-charge of t moment b node energy storage；SOCb max、
SOCb min--- the upper lower limit value of b node energy storage charge state；--- the position of t moment OLTC tap；--- the minimum and maximum position of OLTC tap；--- the reactive compensation amount at t moment b node；--- the bound of b node reactive compensation amount.
2) fuzzy control method based on the power loss sensitivity factor and node voltage is used, herein to use priority method
Obtained load point priority generates initial distributed generation resource addressing as guidance, is not only able to satisfy diversity, but also have one
Fixed reasonability.
Power loss sensitivity factor calculation formula is as follows:
In formula: Pij-lossFor node i, active power loss between j on route, PjFor the injection active power of node j, UjFor section
The voltage of point j, RijFor node i, the resistance value of route between j.LSF (j) is bigger, indicates after load point j installs distributed generation resource,
Active loss reduction amount is bigger on route i-j, more to the improvement of system active power loss.Using following formula to power loss sensitivity
The factor is normalized:
In formula: LSFmax、LSFminRespectively indicate the bound of LSF (j) value.
Fuzzy decision is carried out according to obscurity specialist rule shown in fuzzy decision matrix (such as table 1), then passes through gravity model appoach solution
Blurring, obtains the fitness value of each optimal addressing of load point distributed generation resource.It is sorted according to fitness size to each load point,
Obtain the priority sequence table of the optimal addressing of distributed generation resource.When carrying out initialization addressing to distributed generation resource, preferential choose is adapted to
Spend initial position of the big load point as distributed generation resource.
The obscurity specialist rule of 1 distributed generation resource fitness of table
3) using a kind of improvement particle swarm algorithm and predict the hybrid algorithm that combines of correction interior point to plan model into
Row solves.
In Bi-level Programming Models, upper layer plans to form " source-net-lotus " equipment investment programme, and lower layer's planning then exists
Optimal load flow calculating is carried out to the dry run operating condition of annual ADN on the basis of upper layered scheme, then returns to calculated result
Layer calculates final target function value by upper layer planning；For the non-linear Bilevel Programming Problem of MIXED INTEGER of above-mentioned complexity,
It is solved herein using a kind of improvement particle swarm algorithm-prediction correction interior point hybrid algorithm；Wherein, particle swarm algorithm is improved
It is distributed rationally for each equipment in the planning of upper layer, prediction correction interior point is then used for the optimization operation of each equipment in lower layer's planning
Control.
4) investment and operation for comprehensively considering " source-net-lotus " each side apparatus, show that optimum programming scheme is as shown in table 2.
2 active distribution network of table " source-net-lotus " collaborative planning scheme
The foregoing is only a preferred embodiment of the present invention, is not intended to restrict the invention, although referring to aforementioned reality
Applying example, invention is explained in detail, for those skilled in the art, still can be to aforementioned each implementation
Technical solution documented by example is modified or equivalent replacement of some of the technical features.It is all in essence of the invention
Within mind and principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (5)
1. the active distribution network source net lotus collaborative planning method based on DG initialization addressing comprising the steps of:
1) dual uncertain and Demand-side resource the response characteristic for considering renewable energy power output, establishes polymorphic type distribution
The timing power flow algorithm of formula power supply and flexible load；
2) on this basis, consider active control and management measure, establish the double-deck coordinated planning of active distribution network " source-net-lotus "
Model；
3) plan model is asked using a kind of improvement particle swarm algorithm and the hybrid algorithm for predicting that correction interior point combines
Solution.
2. the active distribution network source net lotus collaborative planning method according to claim 1 based on DG initialization addressing, special
Sign is, the objective function that step 1) is planned at the middle and upper levels are as follows:
Civ=C1+CEENS+Cop
In formula, Civ--- comprehensive method of investment operating cost；C1--- DG, energy storage, reactive compensation, the year conversion of Demand-side various kinds of equipment
Cost of investment；CEENS--- power distribution network lacks power supply volume cost；Cop--- active distribution network annual operating and maintenance cost；
Constraint condition are as follows:
In formula, SI, g--- the installed capacity of i-node g class equipment；--- the maximum installed capacity of i-node g class equipment；
Zg--- g class equipment installation node set to be selected；--- total installed capacity upper limit of power distribution network g class equipment.
3. the active distribution network source net lotus collaborative planning method according to claim 1 based on DG initialization addressing, special
Sign is, the objective function that lower layer plans in step 1) are as follows:
Cop=Cs+CMT+CDR+Closs
In formula, Cs--- higher level's power grid purchases strategies；CMT--- miniature gas turbine operating cost；CDR--- interruptible load electricity
Measure cost；Closs--- distribution network loss cost；
Constraint condition are as follows:
In formula, PS, t、QS, t--- the active and reactive power of t moment higher level's power grid input ADN；NL--- the load point in ADN is total
Number；--- the active and load or burden without work of i-th of load point of t moment；N --- system line sum；PI, t loss、
QI, t loss--- the active and reactive loss of i-th branch road of t moment；VB, t--- the voltage magnitude at t moment node b；--- the bound of voltage magnitude at node b；ΩB--- the set of ADN network node；I1, t--- t moment branch
Load on the ij of road；--- the maximum load of branch ij；PS, min--- higher level's power grid power output minimum value；Pt Ess, b--- when t
Carve the charge/discharge power of energy storage device at b node；--- the specified charging and discharging of energy storage device at b node
Power；ηc、ηd--- the charge and discharge efficiency of energy storage device；SOCb--- the state-of-charge of t moment b node energy storage； --- the upper lower limit value of b node energy storage charge state；--- the position of t moment OLTC tap；--- the minimum and maximum position of OLTC tap；--- the reactive compensation amount at t moment b node；--- the bound of b node reactive compensation amount.
4. the active distribution network source net lotus collaborative planning method according to claim 1 based on DG initialization addressing, special
Sign is that power loss sensitivity factor calculation formula is as follows in step 2):
In formula: Pij-lossFor node i, active power loss between j on route, PjFor the injection active power of node j, UjFor node j's
Voltage, RijFor node i, the resistance value of route between j.LSF (j) is bigger, indicates after load point j installs distributed generation resource, route
The upper active loss reduction amount of i-j is bigger, more to the improvement of system active power loss；Using following formula to the power loss sensitivity factor
It is normalized:
In formula: LSFmax、LSFminRespectively indicate the bound of LSF (j) value；
Using the normalized power loss sensitivity factor and node voltage as Indistinct Input, the in a distributed manner adaptation of the optimal addressing of power supply
Angle value is as fuzzy output；It is sorted according to fitness size to each load point, obtains the preferential suitable of the optimal addressing of distributed generation resource
Sequence table；When carrying out initialization addressing to distributed generation resource, the preferential big load point of fitness of choosing is as the first of distributed generation resource
Beginning position.
5. the active distribution network source net lotus collaborative planning method according to claim 1 based on DG initialization addressing, special
Sign is that step 3) in Bi-level Programming Models, plan to form " source-net-lotus " equipment investment programme by upper layer, lower layer's planning
Optimal load flow calculating then is carried out to the dry run operating condition of annual ADN on the basis of upper layered scheme, then returns calculated result
Upper layer is gone back to, final target function value is calculated by upper layer planning；For the non-linear dual layer resist of MIXED INTEGER of above-mentioned complexity
Problem is solved using a kind of improvement particle swarm algorithm-prediction correction interior point hybrid algorithm herein；Wherein, particle is improved
Group's algorithm is distributed rationally for each equipment in the planning of upper layer, and prediction correction interior point is then used for the excellent of each equipment in lower layer's planning
Change operation control.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109871989A (en) * | 2019-01-29 | 2019-06-11 | 国网山西省电力公司吕梁供电公司 | A kind of power distribution network hierarchical reconfiguration planning method containing distributed generation resource |
| CN110032828A (en) * | 2019-05-10 | 2019-07-19 | 四川大学 | It is a kind of meter and demand response soft readjustment power distribution network two stages distribution robust D G distribute linear method rationally |
| CN110048407A (en) * | 2019-04-12 | 2019-07-23 | 浙江浙能技术研究院有限公司 | Distributed energy power generation plan feasible zone method for optimization analysis |
| CN110570327A (en) * | 2019-08-07 | 2019-12-13 | 广东电网有限责任公司 | active power distribution network double-layer planning method considering source-load interactive response |
| CN112070351A (en) * | 2020-08-04 | 2020-12-11 | 国家电网有限公司 | Transformer substation optimal site selection method based on gravity center regression and particle swarm hybrid algorithm |
| CN112234621A (en) * | 2020-11-09 | 2021-01-15 | 金华电力设计院有限公司 | Power distribution network flexibility resource optimization site selection method based on three-phase power flow model |
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| CN109871989A (en) * | 2019-01-29 | 2019-06-11 | 国网山西省电力公司吕梁供电公司 | A kind of power distribution network hierarchical reconfiguration planning method containing distributed generation resource |
| CN110048407A (en) * | 2019-04-12 | 2019-07-23 | 浙江浙能技术研究院有限公司 | Distributed energy power generation plan feasible zone method for optimization analysis |
| CN110048407B (en) * | 2019-04-12 | 2021-04-27 | 浙江浙能技术研究院有限公司 | Distributed energy power generation plan feasible region optimization analysis method |
| CN110032828A (en) * | 2019-05-10 | 2019-07-19 | 四川大学 | It is a kind of meter and demand response soft readjustment power distribution network two stages distribution robust D G distribute linear method rationally |
| CN110570327A (en) * | 2019-08-07 | 2019-12-13 | 广东电网有限责任公司 | active power distribution network double-layer planning method considering source-load interactive response |
| CN110570327B (en) * | 2019-08-07 | 2022-05-10 | 广东电网有限责任公司 | Active power distribution network double-layer planning method considering source-load interactive response |
| CN112070351A (en) * | 2020-08-04 | 2020-12-11 | 国家电网有限公司 | Transformer substation optimal site selection method based on gravity center regression and particle swarm hybrid algorithm |
| CN112234621A (en) * | 2020-11-09 | 2021-01-15 | 金华电力设计院有限公司 | Power distribution network flexibility resource optimization site selection method based on three-phase power flow model |
| CN112234621B (en) * | 2020-11-09 | 2022-06-14 | 金华电力设计院有限公司 | Power distribution network flexibility resource optimization site selection method based on three-phase power flow model |
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