CN104794541B - A kind of power distribution network running optimizatin method based on simulated annealing and cone optimization - Google Patents
A kind of power distribution network running optimizatin method based on simulated annealing and cone optimization Download PDFInfo
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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
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
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- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
A kind of power distribution network running optimizatin method based on simulated annealing and cone optimization：According to selected distribution system input basic parameter and information；Interconnection switch and intelligent Sofe Switch are established according to basic parameter and information and the mathematical model of power distribution network running optimizatin problem deposited and is constrained according to network structure and scale setting rotating cone, so as to form interconnection switch and intelligent Sofe Switch and the cone Optimized model of power distribution network running optimizatin problem deposited；Basic principle and network topology according to simulated annealing constrain, and randomly generate feasible Switch State Combination in Power Systems, are solved to the interconnection switch and intelligent Sofe Switch and the cone Optimized model of power distribution network running optimizatin problem deposited using cone optimization tool；It exports solving result and utilizes simulated annealing principle analysis optimal solution situation.The economy point that the present invention is run from distribution system considers the state of interconnection switch and the transimission power of SNOP in distribution system, determines the optimal transmission power of the optimized switch combination and SNOP of interconnection switch in power distribution network.
Description
Technical field
The present invention relates to a kind of power distribution network running optimizatin algorithms.More particularly to a kind of based on simulated annealing and cone optimization
Power distribution network running optimizatin method.
Background technology
With the extensive use of the technologies such as distributed power generation, energy storage, Demand Side Response, electric vehicle, power distribution network has turned
Become the novel energy system for integrating the various rolls such as production, transmission, storage and the distribution of electric energy, and the following intelligence electricity
The core of network technology development.Intelligent distribution network will initiatively to distributed generation resource, energy storage, Demand Side Response resource, electric vehicle,
The operation of reactive-load compensation equipment, intelligent switch etc. is optimized and is controlled, and will thoroughly be changed the planning of conventional electrical distribution net, be set
Meter and the method for operation, form new operational mode.Main means of the network reconfiguration as change conventional electrical distribution network operation mode,
Under conditions of the radial operation of guarantee power distribution network, network is realized by interconnection switch (Tie Switch, TS) grid switching operation
The conversion of topological structure.But network reconfiguration mathematically belongs to large-scale nonlinear integer optimization problem, numerous researchs are endeavoured
In improving the calculating speed solved and optimizing ability, but the still effective method of neither one solves this np hard problem.
In actual application, the problems such as also relating to grid switching operation, Alloy White Iron impact, switch motion loss, network reconfiguration is asked
The computational efficiency of topic is difficult to meet the needs of real-time optimization.
With the development of power electronic technique, various power electronic equipments are widely used in distribution system.Intelligence is soft to be opened
It closes (Soft Normally Open Point, SNOP) and is mounted to the power electronic equipment at traditional interconnection switch, it can
Accurately control the active and reactive power of its connected both sides feeder line.The introducing of SNOP revolutionizes conventional electrical distribution net closed loop and sets
The advantages of power supply mode of meter, open loop operation, the hybrid network of formation combines radial and looped network shape power supply mode, gives distribution
The operation of net brings many benefits.In view of the investment operating cost of SNOP is higher, SNOP can not possibly replace completely at this stage
All interconnection switches in system, thus cause the running optimizatin problem of distribution system need overall thinking interconnection switch and
SNOP and the case where deposit.
Substantially from mathematics, which belongs to mixed integer nonlinear optimization problem, and is also difficult to find one kind at present
Fast and effectively method for solving.The solution of the problem has been proposed at present and has developed a variety of optimization methods, mainly have with
Lower three aspects：1) traditional mathematics optimisation technique, including analytic method, successive elimination method etc.；2) heuritic approach, wherein wrapping
Include Sensitivity Analysis Method, expert system etc.；3) randomized optimization process, including genetic algorithm, particle cluster algorithm etc..
Although the above method or technology have certain Application effect, also all there is clearly disadvantageous, such as traditional numbers
Although global optimizing can theoretically be carried out by learning optimization method, " dimension calamity " problem is inevitably present in practical application,
Explosive surge is often presented in the calculating time；Heuristic value is required in terms of time complexity there are one polynomial time
Boundary, calculating speed is fast, but obtained optimal solution either lacks optimality in mathematical meaning or only locally optimal solution；Although
The last solution that randomized optimization process is searched is unrelated with initial solution, but the power distribution network of different scales is needed to reset its control
Parameter processed, population quantity, iterations etc., to ensure to find globally optimal solution with larger probability.It is heuristic and random
Method is suitable for solving integer programming problem more, but for interconnection switch and SNOP and the power distribution network running optimizatin problem deposited, number
Substantially be mixed integer nonlinear optimization problem, so traditional mathematics optimization method, heuritic approach are this kind of for solving
In problem, speed or precision cannot mostly be met the requirements simultaneously.
Invention content
The technical problem to be solved by the invention is to provide one kind improved on calculating time and precision it is non-to MIXED INTEGER
The solution ability of linear optimization problem can quickly and accurately seek to prioritization scheme based on simulated annealing and cone optimization
Power distribution network running optimizatin method.
The technical solution adopted in the present invention is：A kind of power distribution network running optimizatin side based on simulated annealing and cone optimization
Method includes the following steps：
1) according to selected distribution system input basic parameter and information, including system component parameter, load level, network
Topological connection relation, intelligent Sofe Switch on-position and capacity, the initial value of reference voltage and reference power；
2) the distribution network operation established interconnection switch and intelligent Sofe Switch according to the basic parameter of step 1) and information and deposited
The mathematical model of optimization problem, including：Selection root node is balance nodes, and network topology constraint, system load flow is set separately about
Beam, operation voltage level constraint, branch current constraint, intelligent Sofe Switch operation constraint and capacity-constrained distribution network operation about
Beam；
3) it is constrained according to network structure and scale setting rotating cone
2RiRj≥Sij 2+Tij 2, i=1 ..., n, j ∈ N (i)
The power distribution network running optimizatin problem that step 2) and step 3) together form interconnection switch and intelligent Sofe Switch and deposit
Cone Optimized model；
4) it is constrained according to the basic principle of simulated annealing and network topology, randomly generates feasible Switch State Combination in Power Systems,
Mould is optimized to the interconnection switch and intelligent Sofe Switch and the cone of power distribution network running optimizatin problem deposited using cone optimization tool
Type is solved；
5) solving result of step 4), including on off state, intelligent Sofe Switch optimal transmission performance number, network trend are exported
As a result and target function value is analyzed at Current Temperatures and all temperature using simulated annealing principle analysis optimal solution situation
The optimality of solution, if not optimal solution, then return to step 4), if it is optimal solution, then terminate, and export result.
Network topology constraint representation described in step 2) is：
In formula, L is system branch number；AlFor the on off state of initial network branch l, alIt is opened for branch l after network reconfiguration
Off status, is 0 when switch disconnects, and is 1 when switch is closed；WmaxFor the maximum value of network reconfiguration branch.
Intelligent Sofe Switch operation constraint described in step 2) is expressed as with capacity-constrained：
PSNOPi+PSNOPj=0
In formula, PSNOPi、QSNOPi、PSNOPj、QSNOPjRespectively intelligence Sofe Switch connecting node i and connecting node j current transformers
Active power and reactive power, and provide positive direction of the power direction as power transmission to inject intelligent Sofe Switch；SSNOPi、
SSNOPjThe respectively access capacity of intelligence Sofe Switch connecting node i and connecting node j current transformers.
A kind of power distribution network running optimizatin method based on simulated annealing and cone optimization of the present invention, runs from distribution system
Economy point considers the state of interconnection switch and the transimission power of SNOP in distribution system, establishes entire to minimize
Network active loss is object function, with network topology constraint, system load flow constraint, operation voltage level constraint, branch current
Constraint, SNOP operations constraint, SNOP capacity-constraineds etc. are the power distribution network optimal operation model of constraints, pass through simulated annealing
The optimal transmission power of the optimized switch combination and SNOP of interconnection switch in power distribution network is determined with cone optimization algorithm.It is solving
When, it is first the integer optimization problem for optimizing on off state and the Filled function for optimizing SNOP transimission powers by PROBLEM DECOMPOSITION to be asked
Problem.Integer optimization problem is solved using simulated annealing, and it is a kind of according to probability that simulated annealing assigns search process
Jumping characteristic, efficiently avoid search process and be absorbed in locally optimal solution, be conducive to find globally optimal solution.Continuous optimization problems are adopted
It is solved with cone optimization algorithm, by the linearisation of variable replacement problem of implementation, then introduces nonlinear rotating cone constraint
Condition converts the problem to a cone optimization problem.
In terms of computational efficiency, simulated annealing of the present invention is solving integer optimization problem, that is, interconnection switch shape
In state, program is realized simply, has good convergence property, and can as much as possible find approximate optimal solution.It is continuous solving
In optimization problem, cone optimization algorithm can carry out Unify legislation to Load flow calculation problem and SNOP transimission power optimization problems, real
It is solved while existing two problems, avoids cumbersome iteration and a large amount of test, have in calculating speed and significantly promoted；Separately
On the one hand, because graceful geometry and special processing mode possessed by cone, can ensure solved optimality,
It applies it in SNOP running optimizatin problems, the allocation plan after being optimized.
Description of the drawings
Fig. 1 is 33 node example structure charts of IEEE；
Fig. 2 is a kind of power distribution network running optimizatin method flow diagram based on simulated annealing and cone optimization of the present invention；
Fig. 3 is that 33 node examples of IEEE carry out the structure chart after network reconfiguration and SNOP optimizations；
Fig. 4 is the front and back node voltage comparison diagram of 33 node examples of IEEE optimization.
Specific implementation mode
It is excellent to a kind of distribution network operation based on simulated annealing and cone optimization of the present invention with reference to embodiment and attached drawing
Change method is described in detail.
A kind of power distribution network running optimizatin method based on simulated annealing and cone optimization of the present invention, runs for distribution system
In optimizing research, the software realizations such as MOSEK, LINGO, CPLEX may be used in cone optimization algorithm.The present invention uses MOSEK softwares,
Using 33 bus test systems of IEEE shown in FIG. 1 as embodiment.
A kind of power distribution network running optimizatin method based on simulated annealing and cone optimization of the present invention, as shown in Fig. 2, including such as
Lower step：
1) according to selected distribution system input basic parameter and information, including system component parameter, load level, network
The initial values such as topological connection relation, the on-positions SNOP and capacity, reference voltage, reference power.
For the present embodiment, input the impedance value of circuit element in 33 node systems of IEEE first, load cell it is active
Power, reactive power, network topology connection relation；Then two SNOP are set and access power distribution network, replace corresponding interconnection switch；
Finally setting system reference voltage be 12.66kV, reference power 100MVA.
2) according to step 1) basic parameter and information establishes interconnection switch and SNOP and the power distribution network running optimizatin deposited is asked
The mathematical model of topic, including：Selection root node is balance nodes, and the present embodiment is that the node 1 chosen in Fig. 1 is balance nodes,
Network topology constraint, system load flow constraint, operation voltage level constraint, branch current constraint, SNOP operation constraints is set separately
It is constrained with the distribution network operation of capacity-constrained, the mathematical model of the optimization problem is established based on cone optimization algorithm.Tool
Body is as follows：
(1) it sets first and minimizes the whole network active loss as object function, be represented by：
In formula, n is system node number；PiFor the sum of the active power of node i injection, effective power flow in formula (3) can be used
Equality constraint indicates；
(2) the network topology constraint representation described in is：
(3) the system load flow constraint representation described in is：
(4) the operation voltage level constraint representation described in is：
(5) the branch current constraint representation described in is：
I=1 ..., n, j ∈ N (i)
(6) SNOP described in runs constraint representation：
PSNOPi+PSNOPj=0 (6)
(7) the SNOP capacity-constraineds described in are expressed as：
3) it is constrained according to network structure and scale setting rotating cone：
2RiRj≥Sij 2+Tij 2, i=1 ..., n, j ∈ N (i) (8)
In formula, n is system node number；N (i) is the set of the adjacent node of node i.
Above-mentioned steps 2) and step 3) together form interconnection switch and SNOP and the power distribution network running optimizatin problem deposited
Bore Optimized model.
4) it is constrained according to the basic principle of simulated annealing and network topology, randomly generates feasible Switch State Combination in Power Systems,
Using cone optimization algorithm, using cone optimization tool (MOSEK softwares) to the interconnection switch and SNOP and the power distribution network deposited
The cone Optimized model of running optimizatin problem is solved.
The present invention is based on being solved while cone optimization algorithm realizes SNOP optimal transmissions power and trend, not only ensure solution
Computational accuracy can also be effectively reduced calculate the time.
5) export step 4) solving result, including on off state, SNOP optimal transmissions performance number, network power flow solutions with
And target function value is solved using simulated annealing principle analysis optimal solution situation under analysis Current Temperatures and all temperature
Optimality, if not optimal solution, then return to step 4), if it is optimal solution, then terminate, and export result.
For the present embodiment, choose two SNOP here and access power distribution networks, replace interconnection switch TS1 and TS2 in Fig. 1 into
Row analysis, Fig. 1 are 33 node example structure charts of IEEE, and network loss of whole system when without optimization is 202.67kW.Implement
Example optimizes interconnection switch and SNOP and the power distribution network deposited.
It is Intel (R) Xeon (R) CPU E5-1620v2 to execute the computer hardware environment that optimization calculates, and dominant frequency is
3.70GHz inside saves as 32GB；Software environment is 7 operating systems of Windows.
Prioritization scheme changes system topology by network reconfiguration, as shown in Figure 3.Prioritization scheme is simultaneously by network weight
The active power and reactive power of structure and SNOP optimize, and system losses are 84.76kW after optimization, significantly reduce network
Loss.On the other hand, network reconfiguration and SNOP running optimizatins can improve the operation voltage level of system to a certain extent, such as
Shown in Fig. 4, further improves power quality, improves power supply reliability.In order to verify the validity of optimization algorithm of the present invention, it incite somebody to action this
Invention is compared for the obtained result of embodiment and solution time with the result that other methods obtain.BONMIN right and wrong
Linear mixed-integer optimization algorithm packet, pattern search method are one kind of intelligent algorithm, by calling Load Flow Calculation Software OPENDSS
Calculating target function value searches for optimal solution, and specific data refer to table 1.By comparing, the on off state of three kinds of methods is consistent
, SNOP is active and idle work optimization result is essentially identical, due to the difference of implementation method and computational accuracy, final solving result
And real optimal solution can all have slightly deviation, but error is all in allowed limits.Meanwhile method proposed by the present invention exists
It solves on the time compared with other methods, there is prodigious advantage.
1 optimum results of the present invention of table obtain Comparative result with other optimization methods
Claims (2)
1. a kind of power distribution network running optimizatin method based on simulated annealing and cone optimization, which is characterized in that include the following steps：
1) according to selected distribution system input basic parameter and information, including system component parameter, load level, network topology
Connection relation, intelligent Sofe Switch on-position and capacity, the initial value of reference voltage and reference power；
2) the power distribution network running optimizatin established interconnection switch and intelligent Sofe Switch according to the basic parameter of step 1) and information and deposited
The mathematical model of problem, including：Selection root node is balance nodes, and network topology constraint, system load flow constraint, fortune is set separately
Row voltage level restraint, branch current constraint, intelligent Sofe Switch operation constrains and the constraint of the distribution network operation of capacity-constrained, described
Network topology constraint representation be：
In formula, L is system branch number；AlFor the on off state of initial network branch l, alFor the switch shape of branch l after network reconfiguration
State, is 0 when switch disconnects, and is 1 when switch is closed；WmaxFor the maximum value of network reconfiguration branch；
3) it is constrained according to network structure and scale setting rotating cone
2RiRj≥Sij 2+Tij 2, i=1 ..., n, j ∈ N (i)
In formula, n is system node number；N (i) is the set of the adjacent node of node i；Ri、Sij、TijRespectively node voltage amplitude
Ui、UjAnd phase angle thetaijFunction,
The cone of power distribution network running optimizatin problem that step 2) and step 3) together form interconnection switch and intelligent Sofe Switch and deposit
Optimized model；
4) it is constrained according to the basic principle of simulated annealing and network topology, randomly generates feasible Switch State Combination in Power Systems, used
Cone optimization tool to the interconnection switch and intelligent Sofe Switch and the cone Optimized model of power distribution network running optimizatin problem deposited into
Row solves；
5) solving result of step 4), including on off state, intelligent Sofe Switch optimal transmission performance number, network power flow solutions are exported
And target function value is solved using simulated annealing principle analysis optimal solution situation under analysis Current Temperatures and all temperature
Optimality, if not optimal solution, then return to step 4), if it is optimal solution, then terminate, and export result.
2. a kind of power distribution network running optimizatin method based on simulated annealing and cone optimization according to claim 1, feature
It is, the intelligent Sofe Switch operation constraint described in step 2) is expressed as with capacity-constrained：
PSNOPi+PSNOPj=0
In formula, PSNOPi、QSNOPi、PSNOPj、QSNOPjRespectively intelligence Sofe Switch connecting node i and connecting node j current transformers it is active
Power and reactive power, and provide positive direction of the power direction as power transmission to inject intelligent Sofe Switch；SSNOPi、SSNOPj
The respectively access capacity of intelligence Sofe Switch connecting node i and connecting node j current transformers.
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| CN105449713B (en) * | 2015-12-11 | 2017-11-03 | 天津大学 | Consider the intelligent Sofe Switch planing method of active power distribution network of distributed power source characteristic |
| CN105740973B (en) * | 2016-01-25 | 2020-06-09 | 天津大学 | Intelligent power distribution network comprehensive voltage reactive power optimization method based on mixed integer cone programming |
| CN105896537B (en) * | 2016-06-21 | 2018-05-01 | 中国南方电网有限责任公司电网技术研究中心 | A kind of power distribution network service restoration method based on intelligent Sofe Switch |
| CN107591804B (en) * | 2017-09-22 | 2020-11-10 | 广东电网有限责任公司电力科学研究院 | Power quality evaluation method and device based on OPENDS |
| CN108306298B (en) * | 2018-01-17 | 2020-06-12 | 中国科学院电工研究所 | Design method for flexible multi-state switch to be connected to power distribution network |
| CN108695875B (en) * | 2018-06-28 | 2021-08-20 | 华北电力大学（保定） | Power distribution network operation optimization method based on joint access of intelligent soft switch and energy storage device |
| CN108923418A (en) * | 2018-07-10 | 2018-11-30 | 华北电力大学（保定） | A kind of Poewr control method of three ends intelligence Sofe Switch |
| CN109447369B (en) * | 2018-11-09 | 2022-05-17 | 浙江大学 | Multi-factor considering capacity end power distribution method based on simulated annealing algorithm |
| CN113949108B (en) * | 2021-10-14 | 2022-12-06 | 合肥工业大学 | Power distribution network power regulation and control method with intelligent soft switch based on two-person zero-sum game |
| CN114421470B (en) * | 2022-01-18 | 2023-03-24 | 国网上海市电力公司 | Intelligent real-time operation control method for flexible diamond type power distribution system |
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