CN106384207A - Distributed power supply and demand side response resource combined optimization operation method - Google Patents
Distributed power supply and demand side response resource combined optimization operation method Download PDFInfo
- Publication number
- CN106384207A CN106384207A CN201610884689.8A CN201610884689A CN106384207A CN 106384207 A CN106384207 A CN 106384207A CN 201610884689 A CN201610884689 A CN 201610884689A CN 106384207 A CN106384207 A CN 106384207A
- Authority
- CN
- China
- Prior art keywords
- optimization
- demand side
- distributed power
- side response
- response resource
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06315—Needs-based resource requirements planning or analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
Abstract
The invention discloses a distributed power supply and demand side response resource combined optimization operation method. The optimal planning cavity and position of distributed power supplies are determined by adopting a two-level optimization algorithm with the investment cost and the operation cost acting as optimization targets; the upper optimization is nonlinear planning, and the decision content is the capacity and the position of the distributed power supplies and the capacity of demand side response resources; lower optimization is linear planning, and the decision content is the output of the demand side response resources and calling of the demand side response resources; and upper optimization is solved by adopting a genetic algorithm, and lower optimization is solved by adopting optimization software. The problem of distributed power supply planning is enabled to be more complete and comprehensive, and solving speed is accelerated so that calculation time is greatly saved, and the method is suitable for multimode distribution network planning.
Description
Technical field
The present invention relates to a kind of distributed power source operation method, more particularly, to a kind of distributed power source and Demand Side Response money
The method that source combined optimization runs.
Background technology
The operation method of traditional power distribution network distributed power source is confined to investment and the operation of distributed power source, does not account for
With the allocation problem of combining of Demand Side Response resource, operation method is not comprehensive.And, traditional operation method adopts large-scale
Nonlinear Programming Algorithm, calculates the time long.
Content of the invention
Goal of the invention：For problem above, the present invention proposes a kind of more rapid more fully distributed power source and Demand-side
The method that resource response combined optimization runs.
Technical scheme：For realizing the purpose of the present invention, the technical solution adopted in the present invention is：A kind of distributed power source with
The method that Demand Side Response resource joint optimization runs, determines optimized operation scheme using dual-layer optimization, comprises the following steps：
(1) system initialization, obtains the network parameter of system；
(2) decision content that upper strata is optimized encodes, and randomly generates several initial individuals；
(3) initial individuals randomly generating are substituted into lower floor's optimization to be solved, obtain the optimized operation solution of typical day, and
Calculate the optimized operation cost of typical day；The node load of optimized operation is substituted into Load flow calculation, judges whether voltage electricity
Stream is out-of-limit, in the event of out-of-limit, reject this individuality, otherwise then calculates this individual Web-based exercise；
(4) calculate the target function value that upper strata optimizes, and be ranked up according to individual adaptation degree, retain elite；
(5) carry out selecting, intersect, make a variation according to individual adaptation degree, generate new population；
(6) judge whether to reach the condition of convergence, if so, then calculate and terminate, output distributed power source and Demand Side Response provide
The optimal case of source cooperation；Otherwise, return to step (3).
Upper strata optimization in step (4) adopts genetic algorithm for solving, and the lower floor's optimization in step (3) is asked using optimization software
Solution.Upper strata is optimized for Non-Linear Programming, and decision content is the capacity of the capacity, position and Demand Side Response resource of distributed power source；
Lower floor is optimized for linear programming, and decision content is exerting oneself and whether calling Demand Side Response resource of Demand Side Response resource.
Beneficial effect：The operation method of the present invention combines omnibearing Demand Side Response priority scheduling of resource fortune in distribution
OK, make distributed power source planning problem more complete and comprehensive；Large-scale nonlinear programming problem is converted into upper strata non-thread simultaneously
Property, the problem of lower floor's linear programming, accelerate solving speed, greatly save the calculating time it is adaptable to multinode distribution planning.
Brief description
Fig. 1 is operation method schematic diagram of the present invention；
Fig. 2 is the schematic diagram of distribution system；
Fig. 3 is the flow chart of the operation method realization of the present invention.
Specific embodiment
With reference to the accompanying drawings and examples technical scheme is further described.
The method that distributed power source of the present invention and Demand Side Response resource joint optimization run, with cost of investment and
Operating cost is optimization aim, according to daily load and distributed power source typical case's sunrise force curve, to Demand Side Response resource optimization
Scheduling, determines the optimum planned capacity of power distribution network distributed power source and position.As shown in figure 1, this method adopts dual-layer optimization to calculate
Method, upper strata optimizes the investment planning solving the problems, such as distributed power source, and lower floor is optimized solution distributed power source and provided with Demand Side Response
The optimization operation problem in source.Upper strata is optimized for Non-Linear Programming, and decision content is that capacity, position and the Demand-side of distributed power source ring
Answer the capacity of resource, using the genetic algorithm for solving retaining elitism strategy；Lower floor is optimized for linear programming, and decision content is Demand-side
Exerting oneself and whether calling Demand Side Response resource of resource response, is solved using optimization software cplex.Upper strata optimizes with distribution
Company's totle drilling cost is optimum to be target, including cost of investment and operating cost；Lower floor optimizes with the typical case's day distribution operation of certain wind-powered electricity generation
Optimum cost is target.
The constraints that upper strata optimizes includes Network Security Constraints, balance nodes power constraint, distributed power source capacity about
Bundle, the constraint of Demand Side Response resource capacity etc.；The constraints that lower floor optimizes is power-balance constraint, Demand Side Response resource
Bound of exerting oneself constraint, minimum start/close down time-constrain, call number constraint, call price constraints etc..
The idiographic flow of this method realization is described below by the example of a distribution system.Power distribution system as shown in Figure 2
System, totally 34 nodes, wherein 29 load buses, 4 T-shaped connecting nodes, 1 power supply node and 5 frontier nodes.Power supply section
The numbering of point is 0, and head end voltage is 10.5kV, and initial phase is 0, and capacity reference value is 100MVA.This system is distributed
Formula power source planning, distributed power source configuration node 26,29,33 to be selected.Each node maximum configured capacity is 500kW.Can join
User node with Demand Side Response is 23,28,32, and the maximum capacity of buying of each node is this node peak load
30%.
As shown in figure 3, the concretely comprising the following steps of flow process realized using this method：
(1) algorithm initialization, obtains the network parameter of system；
(2) to upper strata, the capacity of distributed power source (DG) optimizing and the capacity of position, Demand Side Response resource (DR) enter
Row coding, randomly generates several initial individuals；
(3) initial individuals randomly generating are substituted into lower floor to optimize, the optimization obtaining typical day runs solution, and calculates optimum
Operating cost；The node load that running optimizatin obtains substitutes into Load flow calculation, judges whether to occur voltage, electric current out-of-limit, if sent out
Life is out-of-limit, rejects this individuality, otherwise then calculates Web-based exercise；
(4) calculate upper strata target function value, and be ranked up according to individual adaptation degree, retain elite；
(5) carry out selecting, intersect, make a variation according to individual adaptation degree, generate new population；
(6) judge whether to reach the condition of convergence, if so, then calculate and terminate, export optimum distributed power source and Demand-side
Resource response optimizes operating scheme；Otherwise, return to step (3).
It may be determined that the optimal operation scheme of this system after iteration 20 times convergence.Optimal operation scheme is No. 26 node configurations
The distributed power source of 450kW, 23,28, No. 32 nodes are each buy 30% Demand Side Response resource.
Claims (3)
1. a kind of method that distributed power source is run with Demand Side Response resource joint optimization, determines optimum fortune using dual-layer optimization
Row scheme it is characterised in that：Comprise the following steps：
(1) system initialization, obtains the network parameter of system；
(2) decision content that upper strata is optimized encodes, and randomly generates several initial individuals；
(3) initial individuals randomly generating are substituted into lower floor's optimization to be solved, obtain the optimized operation solution of typical day, and calculate
The optimized operation cost of typical day；The node load of optimized operation is substituted into Load flow calculation, judges whether to occur voltage x current to get over
Limit, in the event of out-of-limit, reject this individuality, otherwise then calculates this individual Web-based exercise；
(4) calculate the target function value that upper strata optimizes, and be ranked up according to individual adaptation degree, retain elite；
(5) carry out selecting, intersect, make a variation according to individual adaptation degree, generate new population；
(6) judge whether to reach the condition of convergence, if so, then calculate and terminate, output distributed power source and Demand Side Response resource join
Close the optimal case running；Otherwise, return to step (3).
2. the method that distributed power source according to claim 1 is run with Demand Side Response resource joint optimization, its feature
It is：Upper strata is optimized for Non-Linear Programming, and decision content is the appearance of the capacity, position and Demand Side Response resource of distributed power source
Amount；Lower floor is optimized for linear programming, and decision content is exerting oneself and whether calling Demand Side Response resource of Demand Side Response resource.
3. the method that distributed power source according to claim 1 is run with Demand Side Response resource joint optimization, its feature
It is：Upper strata optimization in step (4) adopts genetic algorithm for solving, and the lower floor in step (3) optimizes using optimization software solution.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610884689.8A CN106384207A (en) | 2016-10-10 | 2016-10-10 | Distributed power supply and demand side response resource combined optimization operation method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610884689.8A CN106384207A (en) | 2016-10-10 | 2016-10-10 | Distributed power supply and demand side response resource combined optimization operation method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106384207A true CN106384207A (en) | 2017-02-08 |
Family
ID=57937197
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610884689.8A Pending CN106384207A (en) | 2016-10-10 | 2016-10-10 | Distributed power supply and demand side response resource combined optimization operation method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106384207A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106972483A (en) * | 2017-03-13 | 2017-07-21 | 东北电力大学 | A kind of power system Calculation of Available Transfer Capability method for considering Demand Side Response |
| CN108599237A (en) * | 2018-04-24 | 2018-09-28 | 南京理工大学 | A kind of active distribution network dual layer resist DG Optimal Configuration Methods |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102622488A (en) * | 2012-03-21 | 2012-08-01 | 江西省电力科学研究院 | Distributed power capacity planning method for distribution network |
| CN104505826A (en) * | 2014-12-22 | 2015-04-08 | 国家电网公司 | Coordinated optimization control method for active distribution network |
| CN105207205A (en) * | 2015-09-16 | 2015-12-30 | 国网天津市电力公司 | Distributed energy system energy optimization regulation and control method fusing demand side response |
| CN105279578A (en) * | 2015-10-27 | 2016-01-27 | 天津大学 | Power supply optimization configuration bilevel programming method in active distribution network region |
-
2016
- 2016-10-10 CN CN201610884689.8A patent/CN106384207A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102622488A (en) * | 2012-03-21 | 2012-08-01 | 江西省电力科学研究院 | Distributed power capacity planning method for distribution network |
| CN104505826A (en) * | 2014-12-22 | 2015-04-08 | 国家电网公司 | Coordinated optimization control method for active distribution network |
| CN105207205A (en) * | 2015-09-16 | 2015-12-30 | 国网天津市电力公司 | Distributed energy system energy optimization regulation and control method fusing demand side response |
| CN105279578A (en) * | 2015-10-27 | 2016-01-27 | 天津大学 | Power supply optimization configuration bilevel programming method in active distribution network region |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106972483A (en) * | 2017-03-13 | 2017-07-21 | 东北电力大学 | A kind of power system Calculation of Available Transfer Capability method for considering Demand Side Response |
| CN108599237A (en) * | 2018-04-24 | 2018-09-28 | 南京理工大学 | A kind of active distribution network dual layer resist DG Optimal Configuration Methods |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Kinhekar et al. | Utility oriented demand side management using smart AC and micro DC grid cooperative | |
| CN109103912A (en) | Consider the industrial park active distribution system method for optimizing scheduling of peaking demand of power grid | |
| CN104037765B (en) | The method of active power distribution network service restoration scheme is chosen based on improved adaptive GA-IAGA | |
| CN103426032A (en) | Method for economically and optimally dispatching cogeneration units | |
| CN109390932A (en) | A kind of security constraint Unit Combination calculation method considering DC link power optimization | |
| CN104079008B (en) | A kind of method of supplying power to based on micro-capacitance sensor and electric power system | |
| CN112651634B (en) | Active power distribution system source network load storage day-ahead active power scheduling method based on sequence operation | |
| JP2013544063A (en) | Method and system for facilitating control planning of an electronic power system interface of a distributed power supply | |
| CN109242217B (en) | Electricity-gas energy multi-target distributed transaction collaborative optimization method and device | |
| CN105071410A (en) | Power distribution network reactive power optimized dispatching method and system based on virtual power plant | |
| CN107767086A (en) | New energy station output lower limit rolling amendment method based on generated power forecasting | |
| Huang et al. | Distributed optimal energy management for microgrids in the presence of time-varying communication delays | |
| CN106384207A (en) | Distributed power supply and demand side response resource combined optimization operation method | |
| CN107294101A (en) | A kind of multiple target unit built-up pattern and method for solving based on security domain target and constraint | |
| CN105098839B (en) | A kind of wind-electricity integration coordination optimizing method based on the uncertain output of wind-powered electricity generation | |
| CN107528349A (en) | Thermal power generation unit load gearshift adjustment control method and system based on new energy load | |
| Jahromi et al. | The demand side management program considering AC/DC hybrid distribution system concept based on the energy hub | |
| CN106777521A (en) | Generating set based on double-chain quantum genetic algorithm relates to network parameters optimization method | |
| CN109213104B (en) | Scheduling method and scheduling system of energy storage system based on heuristic dynamic programming | |
| CN111064231A (en) | New energy graded interactive consumption method and system | |
| CN107887975A (en) | A kind of Demand-side resources regulation method and system | |
| CN106169770B (en) | A kind of electric power energy Optimal Configuration Method for water power enriching area | |
| CN109586278A (en) | A kind of alternating current-direct current mixing power distribution network evaluation of power supply capability method | |
| CN109038546A (en) | A kind of AC-DC hybrid power grid load restoration method and system based on VSC-HVDC system | |
| CN114971372A (en) | Multi-time-space scale optimization scheduling method of micro-energy network based on demand response |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170208 |
|
| RJ01 | Rejection of invention patent application after publication |