CN109980684A - A kind of distributed optimization dispatching method based on flexible interconnection micro-capacitance sensor - Google Patents
A kind of distributed optimization dispatching method based on flexible interconnection micro-capacitance sensor Download PDFInfo
- Publication number
- CN109980684A CN109980684A CN201910259596.XA CN201910259596A CN109980684A CN 109980684 A CN109980684 A CN 109980684A CN 201910259596 A CN201910259596 A CN 201910259596A CN 109980684 A CN109980684 A CN 109980684A
- Authority
- CN
- China
- Prior art keywords
- node
- capacitance sensor
- power
- micro
- flexible interconnection
- 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
- 238000005457 optimization Methods 0.000 title claims abstract description 43
- 238000000034 method Methods 0.000 title claims abstract description 35
- 238000004146 energy storage Methods 0.000 claims description 68
- 238000005520 cutting process Methods 0.000 claims description 20
- 230000005540 biological transmission Effects 0.000 claims description 10
- 238000004364 calculation method Methods 0.000 claims description 6
- 238000007599 discharging Methods 0.000 claims description 5
- 230000001105 regulatory effect Effects 0.000 claims description 5
- 239000002283 diesel fuel Substances 0.000 claims description 3
- 230000002452 interceptive effect Effects 0.000 claims description 3
- 238000011144 upstream manufacturing Methods 0.000 claims description 3
- 102000020897 Formins Human genes 0.000 claims 1
- 108091022623 Formins Proteins 0.000 claims 1
- 230000003993 interaction Effects 0.000 abstract description 9
- 238000004891 communication Methods 0.000 abstract description 7
- 230000008569 process Effects 0.000 description 6
- 230000005611 electricity Effects 0.000 description 4
- 238000011160 research Methods 0.000 description 4
- 238000006243 chemical reaction Methods 0.000 description 3
- 238000009826 distribution Methods 0.000 description 3
- 238000005265 energy consumption Methods 0.000 description 3
- 230000009467 reduction Effects 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012546 transfer Methods 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000003190 augmentative effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000000295 complement effect Effects 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000012804 iterative process Methods 0.000 description 1
- 238000010248 power generation Methods 0.000 description 1
- 230000006641 stabilisation Effects 0.000 description 1
- 238000011105 stabilization Methods 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
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
- G06Q10/06312—Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
-
- 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—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- 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
- H02J3/38—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
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/48—Controlling the sharing of the in-phase component
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/50—Controlling the sharing of the out-of-phase component
-
- 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]
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Power Engineering (AREA)
- Entrepreneurship & Innovation (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Educational Administration (AREA)
- Development Economics (AREA)
- Health & Medical Sciences (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Primary Health Care (AREA)
- General Health & Medical Sciences (AREA)
- Water Supply & Treatment (AREA)
- Public Health (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The embodiment of the present application shows a kind of distributed optimization dispatching method based on flexible interconnection micro-capacitance sensor, with two-way DC/AC current transformer replace ordinary tap by independent exchange micro-capacitance sensor carry out decoupling interconnection " soft " connection can in range of capacity two-way accurate continuous control trend, control speed and scheduling " flexibility " are improved, flexible apparatus can quickly adjust two sides power according to operating condition.Distributed optimization dispatching method shown in the application is not necessarily to central controller, and each micro-capacitance sensor only needs to carry out data interaction with the micro-capacitance sensor that is connected, and communications burden is lighter, and reliability is stronger.
Description
Technical field
The present invention relates to interconnection micro-capacitance sensor technical field, especially a kind of distributed optimizations based on flexible interconnection micro-capacitance sensor
Dispatching method.
Background technique
The micro-capacitance sensor (Microgrid, MG) of distribution type renewable energy containing high proportion and energy-storage system has become remotely
One of the important way of area's power supply.Due to the randomness of renewable energy power output and the fluctuation of customer charge, single independence is micro-
Power grid power supply reliability is lower and power supply cost is higher.If the independent micro-capacitance sensor interconnected operation that will be closer, may be implemented
Resource complementation between different micro-capacitance sensors guarantees renewable energy consumption in micro-capacitance sensor, while increasing micro-capacitance sensor spare capacity, mentions
The safety and reliability of high bulk supply system operation.
Optimized Operation is the key that interconnection micro-capacitance sensor economical operation.There is the optimization of literature research interconnection micro-capacitance sensor centralization
Scheduling problem, but system communication amount and the calculation amount of central controller are larger, need to share all inside each micro-capacitance sensor
Information.There is document to start with from distributed optimization scheduling, proposes a kind of micro-capacitance sensor group bilayer distributed optimization dispatching method, upper layer is not
Exchanged with coordinating power between micro-capacitance sensor group, lower layer's micro-capacitance sensor internal control controllable resources, between two layers transmit output power and
Cost coefficient.There is document to access the economic operation problem of power distribution network around micro-capacitance sensor group, proposes a kind of with second order convergence speed
With the complete distributed Newton optimization algorithm of lower communications burden, but this method model is limited it is more, can not handle network loss and
Complicated coupling constraint etc., applicability is poor.There is document to be directed to the optimization problem of extensive micro-capacitance sensor cluster interconnection, proposes a kind of base
In the distributed optimization frame of Model Predictive Control and more converse consistency1s, the plug and play of micro-capacitance sensor cluster is realized.But it is above-mentioned
Research is mostly the management and running problem between grid type micro-capacitance sensor group under hard connecting mode, is lacked at present flexible to independent micro-capacitance sensor
The distributed optimization of interconnection is studied.
In the prior art, it has the following disadvantages and insufficient:
(1) research at present is mostly the management and running problem between different micro-capacitance sensors under " hard " connection, and Hard link makes independence
There are direct electrical link between micro-capacitance sensor, once to involve range wider for generating system failure.Hard link can only connect identical
The exchange micro-capacitance sensor of voltage class.Meanwhile with the raising of renewable energy installed capacity and energy storage system capacity, more are needed
Current transformer interconnection, and more current transformer interconnections face there are circulation and flow difficult problem.In order to guarantee between different micro-capacitance sensors
Dominant eigenvalues balance needs the accurate voltage and generator rotor angle for adjusting unit in real time, actual motion difficulty.
(2) centralization optimization has the disadvantage that: dimension disaster caused by the central controller traffic and calculation amount are larger；It is logical
Believe that cost investment is big；Communication system Single Point of Faliure scarce capacity is coped with, the weak robustness of physical message system, reliability are shown as
It is poor.
Summary of the invention
The purpose of the present invention is to provide a kind of distributed optimization dispatching methods based on flexible interconnection micro-capacitance sensor, existing to solve
The technical issues of with the presence of scheme shown in technology.
The embodiment of the present application shows a kind of distributed optimization dispatching method based on flexible interconnection micro-capacitance sensor, the distribution
Optimization Scheduling includes:
Step S1: global variable initial value P is obtainedlink(0), enable initial Lagrange multiplier λP(0)=0, enable the number of iterations k
=0；
S2: two flexible interconnection micro-capacitance sensor devices of step solve respective Optimized model respectively, obtain decision variable and friendship
Mutual variable, first area tuning controller is by virtual burden with powerWithIt is sent to second area coordinated control
Device, first area tuning controller receive the area transmissions active power that second area tuning controller is sentWith
Step S3: first area tuning controller and second area tuning controller difference update area transmit wattful power
Rate global variable, first area tuning controller and second area tuning controller update Lagrange multiplier respectively；
Step S4: the raw residual of two flexible interconnection micro-capacitance sensor devices is calculated separatelyWith antithesis residual error First flexible interconnection micro-capacitance sensor device is by raw residualWith antithesis residual errorIt is sent to second area coordination
Controller, the second flexible interconnection micro-capacitance sensor device is by raw residualWith antithesis residual errorIt is sent to first area and coordinates control
Device processed；
Step S5: judging whether to terminate iteration, if the Infinite Norm of global residual error is less than given convergence threshold, stops
Iteration obtains optimal solution, otherwise, enables the number of iterations k=k+1, two flexible interconnection micro-capacitance sensor devices continue to obtain respective decision
Variable and interaction variable.
It is selectable, the global variable initial value Plink(0)For the reality of flexible interconnection micro-capacitance sensor device both ends active power
Measured data.
Selectable, the objective function of the Optimized model is min fMG=f1+f2+f3+f4+f5；
Wherein, fMGFor the operating cost of flexible interconnection micro-capacitance sensor device, f1For Web-based exercise, f2For diesel generating set fortune
Row cost, f3For energy storage device charge and discharge cost, f4Cost, f are cut down for photovoltaic cells5For cutting load cost；
The Web-based exercise function is
Wherein, clossFor loss factor,It is lost for flexible interconnection micro-capacitance sensor device internal network,It is flexible mutual
Join the loss of micro-capacitance sensor device；
The diesel generating set operating cost function is
Wherein, N is total node number, PDEGjFor the active power of node j diesel generating set output, a, b and c are expressed as
This coefficient；
The energy storage device charge and discharge cost function is f3=cbat(Pch+Pdis)；
Wherein, PchFor the charge power of energy storage device, PdisFor the discharge power of energy storage device, cbatFor charge and discharge cost system
Number；
The photovoltaic cells cut down cost function
Wherein, PctljFor the active power that node j photovoltaic cells are cut down, cctlTo cut down cost coefficient；
The cutting load cost function is
Wherein, PdecjFor node j cutting load active power, cdecFor cutting load unit power cost.
Selectable, the constraint condition that the objective function solves includes: trend constraint, node voltage constraint, photovoltaic list
Member operation constraint, energy storage constraint, diesel generating set operation constraint, the constraint of flexible interconnection micro-capacitance sensor device.
Selectable, the trend constraint is
Wherein, i → j is upstream node of the node i to node j；IijFor the electric current flowed out from node i to node j, UiAnd Uj
For the voltage magnitude of node i and node j, PijFor the active power flowed out from node i to node j, QijFor from node i to node j
The reactive power of outflow, PjThe active power of node j net load, QjFor the reactive power of node j net load, RijFor node i and
The resistance value of route, X between node jijThe reactance value of route, P between node i and node jLjFor the active power of node j load,
QLjFor the reactive power of node j load,For the maximum power point value of node j photovoltaic cells active power, QPVjFor node j
The idle output power of photovoltaic, QdecjFor node j cutting load reactive power, QDEGjFor the idle output of node j diesel generating set
Power；
The node voltage is constrained to U1=Uref, (1- ε) Uref≤Uj≤(1+ε)Uref；
Wherein, U1For region first node voltage magnitude, UrefFor Area Node voltage reference value, ε is the maximum of node voltage
Tolerance；
The photovoltaic cells operation is constrained to
Wherein, θ=cos-1PFminCorresponding minimum power factor PFminWhen angle；
The energy storage is constrained to
Wherein,For the charge power maximum value of root node energy storage device,For the electric discharge function of root node energy storage device
Rate maximum value, ηchFor energy storage device charge efficiency, ηdisFor energy storage device discharging efficiency, μchFor the charging of root node energy storage device
Mark, μdisFor the electric discharge mark of root node energy storage device；
The diesel generating set operation is constrained to
Wherein,For diesel generating set active power power output the upper limit,For diesel generating set active power
The lower limit of power output, UDEGjThe maximum power regulated quantity of power output, D are improved for diesel generating setDEGjFor diesel generating set drop
The maximum power regulated quantity of low-power output, SRFor operation reserve capacity；
The flexible interconnection micro-capacitance sensor device constraint includes: the constraint of flexible interconnection micro-capacitance sensor device active power, flexible mutual
Join the constraint of micro-capacitance sensor device reactive power, the constraint of flexible interconnection micro-capacitance sensor installed capacity；
The flexible interconnection micro-capacitance sensor device active power is constrained to
Wherein,For flexible interconnection micro-capacitance sensor device node m output active power,For flexible interconnection micro-capacitance sensor dress
The reactive power of node m output is set,For flexible interconnection micro-capacitance sensor device node n output active power,It is flexible mutual
Join the reactive power of micro-capacitance sensor device node n output,For the corresponding network loss of node m,For the corresponding net of node n
Damage, AlinkFor loss factor；
The flexible interconnection micro-capacitance sensor device reactive power is constrained to
Wherein,For the lower limit of flexible interconnection micro-capacitance sensor device node m output reactive power,It is micro- for flexible interconnection
The lower limit of electric net device node m output reactive power,For under flexible interconnection micro-capacitance sensor device node n output reactive power
Limit,For the lower limit of flexible interconnection micro-capacitance sensor device node n output reactive power；
The flexible interconnection micro-capacitance sensor installed capacity is constrained to
Wherein,For the capacity of current transformer at flexible interconnection micro-capacitance sensor device node m,For flexible interconnection micro-capacitance sensor
The capacity of current transformer at device node n.
Selectable, the decision variable includes: diesel generating set active-power PDEGj, energy storage device charge power
Pch, energy storage device discharge power Pdis, photovoltaic cells reduction active-power Pctlj, cutting load active-power Pdecj；
The interactive variable includes: two end node m active power of flexible interconnection micro-capacitance sensor deviceThe micro- electricity of flexible interconnection
Two end node n active power of net device
Selectable, the solving model of the update area transmitting active power global variable is
It is described update Lagrange multiplier solving model be
Selectable, the calculation formula of the raw residual of the flexible interconnection micro-capacitance sensor device is
The antithesis residual error of the flexible interconnection micro-capacitance sensor deviceCalculation formula be
The embodiment of the present application shows a kind of distributed optimization dispatching method based on flexible interconnection micro-capacitance sensor, with two-way DC/
AC (DC/AC) current transformer replaces ordinary tap that can hold " soft " connection that independent exchange micro-capacitance sensor carries out decoupling interconnection
Two-way accurate continuous control trend in range is measured, improves control speed and scheduling " flexibility ", flexible apparatus can be according to operating condition
Quickly adjust two sides power.Distributed optimization dispatching method shown in the application is not necessarily to central controller, and each micro-capacitance sensor only needs
Micro-capacitance sensor carries out data interaction with being connected, and communications burden is lighter, and reliability is stronger.
Detailed description of the invention
Fig. 1 is that a kind of distributed optimization dispatching method based on flexible interconnection micro-capacitance sensor exemplified is preferably implemented according to one
Flow chart；
Fig. 2 is the structural schematic diagram that a kind of flexible interconnection micro-capacitance sensor device exemplified is preferably implemented according to one；
Fig. 3 is that 33 meshed network of IEEE that a kind of flexible interconnection micro-capacitance sensor device exemplified is preferably implemented according to one shows
It is intended to；
Fig. 4 is that a kind of typical daily load demand exemplified and photovoltaic power curve are preferably implemented according to one；
Fig. 5 is the transimission power curve that a kind of flexible interconnection micro-capacitance sensor device exemplified is preferably implemented according to one；
Fig. 6 is that active/idle power curve of a kind of each equipment exemplified is preferably implemented according to one；
Fig. 7 is that a kind of residual error convergence process example exemplified is preferably implemented according to one.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Whole description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
The prior art lays particular emphasis on the bottom control architectural studies of flexible interconnection micro-capacitance sensor, to self micro-capacitance sensor flexible interconnection
The research of energy-optimised scheduling level also rarely have and be related to.Therefore, the present invention overcomes the deficiencies in the prior art, propose a kind of base
In the independent micro-capacitance sensor Optimization Scheduling of flexible interconnection.Each micro-capacitance sensor is separately formed a control area, inside micro-capacitance sensor
Network optimizes the power of the equipment such as photovoltaic cells, energy storage device and diesel generating set in each optimal load flow calculating process.
The information such as interface boundary active power between adjacent micro-capacitance sensor are realized in different micro-capacitance sensors based on alternating direction multipliers method (ADMM)
The coordination of resource, the final reliable and economic operation for realizing global optimization scheduling and system.
Firstly, establishing flexible interconnection micro-capacitance sensor device (MG), the structure for being illustrated in figure 2 flexible interconnection micro-capacitance sensor device is shown
It is intended to, the flexible interconnection micro-capacitance sensor device includes: diesel generating set (DEG), photovoltaic cells (PV), energy storage device (ESS),
Customer charge unit (LD), area coordination control model device, photovoltaic cells current transformer, energy storage device current transformer, micro-capacitance sensor current transformer.
Wherein, the diesel generating set is used to be insufficient for using in the sum of photovoltaic cells power output and energy storage device exoergic
It is energized when the load cell demand of family for flexible interconnection micro-capacitance sensor device；The photovoltaic cells are used to be flexible interconnection micro-capacitance sensor device
Energy supply；The energy storage device is used to store energy when photovoltaic cells power output is greater than customer charge unit demand, in photovoltaic cells
Power output releases energy when being less than customer charge unit demand；The customer charge unit is used in flexible interconnection micro-capacitance sensor device
Energy consumption；The area coordination control model device for the control variable inside optimal control flexible interconnection micro-capacitance sensor device, and be connected
The area coordination control model device of flexible interconnection micro-capacitance sensor device carries out data interaction, realizes distributed optimization scheduling；The photovoltaic list
The DC conversion that first current transformer is used to issue photovoltaic cells is the alternating current of flexible interconnection micro-capacitance sensor device；The energy storage dress
Set the alternating current that DC conversion of the current transformer for issuing energy storage device is flexible interconnection micro-capacitance sensor device；The micro-capacitance sensor
Current transformer is used to carry out in independent flexible interconnection micro-capacitance sensor device " soft " connection of decoupling interconnection, the two-way essence in range of capacity
True continuous control trend, improves control speed and scheduling " flexibility ", and flexible apparatus can quickly adjust two sides function according to operating condition
Rate.
In each micro-capacitance sensor, photovoltaic cells and energy storage device are directly output as DC output end, (straight by DC/AC
Stream/exchange) current transformer inversion is ac output end, with the output end of diesel generating set and customer charge unit by route company
It is connected in micro-capacitance sensor AC network.Some node in the exchange side connection micro-capacitance sensor AC network of DC/AC current transformer, first is micro-
The DC/AC current transformer DC side of power grid (MG1) is connect with the DC/AC current transformer DC side of the second micro-capacitance sensor (MG2).Wherein, micro-
Using energy storage device as root node main power source in power grid, voltage and frequency stabilization in micro-capacitance sensor are maintained；Diesel generating set and photovoltaic
Unit is power source.Under normal operating conditions, in order to keep power-balance, flexible interconnection micro-capacitance sensor device takes PQ-VdcQ
Control model, i.e. a current transformer determine active power and reactive power, another current transformer determines DC voltage and reactive power.It is logical
The coordinated control of this flexible interconnection and current transformer is crossed, it can be achieved that the power between adjacent micro-capacitance sensor supports.The micro- electricity of flexible interconnection
Net Optimized Operation includes: the coordinated control between the control of micro-capacitance sensor home rule, micro-capacitance sensor.Area coordination control model device is responsible for micro- electricity
Net internal autonomous control, optimize the power of photovoltaic cells, energy storage device and diesel generating set etc., at the same with the micro-capacitance sensor that is connected
Regional coordination is realized by boundary information.
Referring to Fig. 1, the embodiment of the present application shows a kind of distributed optimization dispatching method based on flexible interconnection micro-capacitance sensor,
The distributed coordination optimization process of flexible interconnection micro-capacitance sensor is a kind of distributed optimization algorithm answering in interconnection micro-capacitance sensor scheduling
With, including initialization, iteration and output, detailed process be as follows:
Step S1: initialization obtains the initial value P of global variable flexible interconnection micro-capacitance sensor device both ends active powerlink (0), enable initial Lagrange multiplier λP(0)=0, enable the number of iterations k=0；
The initialization procedure of distributed coordination optimization, initial value are iteration starting point, and initial Lagrange multiplier indicates initial
The direction of search.When micro-capacitance sensor independent operating, measured data be scheduling starting point, so using micro-capacitance sensor operation measured data as
Global variable initial value.Connected micro-capacitance sensor does not carry out data interaction also, can't determine iterative search direction, so enabling initial draw
Ge Lang multiplier λP(0)=0, enable the number of iterations k=0.
Step S2: micro-capacitance sensor autonomy optimization, two flexible interconnection micro-capacitance sensor devices solve respective Optimized model respectively, obtain
Decision variable and interaction variable, first area tuning controller is by virtual burden with powerWithIt is sent to
Two area coordination control model devices, first area tuning controller receive the area transmissions wattful power that second area tuning controller is sent
RateWith
The micro-grid system of flexible interconnection contains multinomial operating cost, including route network loss and interconnect device Web-based exercise f1、
Diesel-driven generator cost of electricity-generating f2, energy-storage system charge and discharge cost f3, distributed photovoltaic unit cut down cost f4With cutting load cost
f5.It is minimum as the total operating cost for interconnecting micro-grid system to set objective function, the objective function of Optimal Operation Model such as formula (1)
It is shown.
min fMG=f1+f2+f3+f4+f5 (1)
Wherein, (a) Web-based exercise
In formula, clossIndicate loss factor, i.e. unit power Web-based exercise；WithIt respectively indicates inside micro-capacitance sensor
Via net loss and interconnect device loss.
(b) diesel generating set operating cost
In formula, N indicates total node number；PDEGjIndicate the active power of node j diesel generating set output；A, b and c is indicated
Cost coefficient.
(c) battery charging and discharging cost f3=cbat(Pch+Pdis) (4)
In formula, PchAnd PdisRespectively indicate the charge power and discharge power of energy-storage system；cbatIndicate charge and discharge cost system
Number, i.e. unit power charge and discharge cost.
(d) photovoltaic cuts down cost
In formula, PctljIndicate the active power that node j photovoltaic cells are cut down；cctlIt indicates to cut down cost coefficient, i.e. specific work
Rate cuts down cost.
(e) cutting load cost
In formula, PdecjIndicate node j cutting load active power；cdecIndicate cutting load unit power cost.
The constraint condition that the objective function solves includes: trend constraint, and node voltage constraint, photovoltaic cells operation is about
Beam, energy storage constraint, diesel generating set operation constraint, the constraint of flexible interconnection micro-capacitance sensor device.
Wherein, (a) trend constraint
Micro-capacitance sensor internal communication trend constraint is indicated using the Branch Power Flow model based on DistFlow.
In formula, i → j indicates that node i is the upstream node of node j；IijIndicate the electric current flowed out from node i to node j, Ui
And UjFor the voltage magnitude of node i and node j；Pij、QijIndicate the active and reactive power flowed out from node i to node j；PjWith
QjFor the active and reactive power of node j net load；RijAnd XijIndicate the resistance value and reactance value of route between node i and node j；
PLjAnd QLjFor the active and reactive power of node j load；Indicate the maximum power point of node j photovoltaic cells active power
Value；QPVjFor the idle output power of node j photovoltaic；QdecjIndicate node j cutting load reactive power；QDEGjFor node j diesel oil hair
The idle output power of motor group.
(b) node voltage constrains
For the independent micro-capacitance sensor of different voltages grade, voltage level should meet bound constraint.
U1=Uref (10)
(1-ε)Uref≤Uj≤(1+ε)Uref (11)
In formula, U1For region first node voltage magnitude, UrefFor Area Node voltage reference value；ε is the maximum of node voltage
Tolerance.
(c) photovoltaic cells operation constraint
In formula, θ=cos-1PFminCorresponding minimum power factor PFminWhen angle.
(d) energy storage constrains
μch+μdis≤1 (15)
In formula,WithRespectively indicate the charging and discharging power maximum value of root node energy storage device；ηchAnd ηdisPoint
It Biao Shi not energy storage device charging and discharging efficiency；Logical variable μchAnd μdisIt respectively indicates the charging of root node energy storage device and puts
Electrosemaphore indicates that energy storage device operates in corresponding state when taking 1, constraint (15) ensure that energy storage device is only transported in synchronization
Row is in a kind of working condition.
(e) generating set operation constraint
Diesel generating set needs to meet the constraint of power bound, Climing constant and Reserve Constraint:
In formula,WithIndicate the bound of diesel generating set active power power output；UDEGjAnd DDEGjIt respectively indicates
Diesel generating set improves and reduces the maximum power regulated quantity of power output；SRIndicate operation reserve capacity.
(f) flexible interconnection micro-capacitance sensor device constrains
The two sides of flexible interconnection micro-capacitance sensor device are exchange link, and connection exchange micro-capacitance sensor is converted into centre through current transformer
DC link.
The control variable of flexible interconnection micro-capacitance sensor device includes the active and reactive power of two current transformers.Operation constraint packet
Power constraint and capacity-constrained are included, is shown below:
1) flexible interconnection micro-capacitance sensor device active power constrains
In formula,WithIt is defeated to respectively indicate flexible interconnection micro-capacitance sensor device two side gusset m and node n
Active power and reactive power out,WithRespectively indicate corresponding network loss；AlinkIndicate loss factor.Due to becoming
It is different to flow the device method of operation, it is optimized variable that above-mentioned performance number, which only has side, and the other side only calculates variable.
2) flexible interconnection micro-capacitance sensor device reactive power constrains
In formula,WithIt is defeated to respectively indicate flexible interconnection micro-capacitance sensor device two side gusset m and node n
The bound of reactive power out.
3) flexible interconnection micro-capacitance sensor installed capacity constrains
In formula,WithRespectively indicate the appearance of current transformer at flexible interconnection micro-capacitance sensor device two side gusset m and node n
Amount.
The network loss constraint of flexible interconnection micro-capacitance sensor device and capacity-constrained can be rewritten as the second order taper being shown below
Formula:
Each region obtains local message from local, and two micro-capacitance sensors (MG1 and MG2) solve respectively according to formula (1)-(30)
Respective Optimized model obtains decision variable and interaction variable.
Step S3: global variable and Lagrange multiplier update, and first area tuning controller and second area are coordinated
Controller distinguishes update area transmitting active power global variable, first area tuning controller and second area coordinated control
Device updates Lagrange multiplier respectively；
Micro electric network coordination control based on flexible interconnection:
Only it need to guarantee the active balance consistency constraint as shown in formula (20) between different zones, so interregional
Exchange variable only has boundary active power.Formula (20) can be rewritten into following formula
In formula, PlinkFor flexible interconnection micro-capacitance sensor device both ends active power global value.
Interregional distributed coordination optimization is realized using ADMM herein, for the device of flexible interconnection micro-capacitance sensor shown in Fig. 2,
By taking MG1 as an example, λ is enabledPIndicate the Lagrange multiplier of zone boundary active power consistency constraint, ρ indicates penalty factor, then formula
(1) Augmented Lagrangian Functions are represented by as shown in following formula (32):
Each independent micro-capacitance sensor carries out independent parallel optimization according to micro-capacitance sensor internal resource, obtains energy storage device charge and discharge electric work
The optimal solution of rate and diesel engine unit output power etc. and the active power of zone boundary, and filled with through flexible interconnection micro-capacitance sensor
Connected adjacent micro-capacitance sensor exchange area boundary active power information is set, then according to the update area number of boundary as shown in formula (33)
According to global value；
Based on zone boundary active power information, each region according to formula (36) update area data boundary Suzanne Lenglen day
Multiplier.
Each region obtains information from adjacent area, by local information and adjacent area information update local message geometry,
I.e. each zone controller is according to formula (33) update area transmitting active power global variable.Later, by updated local message
Local iteration's point is updated, i.e., updates corresponding Lagrange multiplier according to formula (36).
Step S4: residual error updates, and calculates separately the raw residual of two flexible interconnection micro-capacitance sensor devicesWith
Antithesis residual errorFirst flexible interconnection micro-capacitance sensor device is by raw residualWith antithesis residual errorIt is sent to
Two area coordination control model devices, the second flexible interconnection micro-capacitance sensor device is by raw residualWith antithesis residual errorIt is sent to first
Area coordination control model device；
After obtaining flexible interconnection micro-capacitance sensor device two sides active power global value, the original residual of ADMM can be calculated
Difference and antithesis residual error, expression formula are as follows:
Wherein,WithRaw residual and antithesis residual error when respectively indicating MG1+1 iteration of kth, the number of iterations k
≥0。
It calculates separately to obtain the raw residual of MG1 and MG2 optimization problem according to formula (34), formula (35)And antithesis
Residual errorAnd respective residual error is sent to adjacent micro-capacitance sensor zone controller.
Step S5: iteration ends determine, judge whether to terminate iteration, if the Infinite Norm of global residual error is less than given receipts
Threshold value is held back, then stops iteration and obtains optimal solution, otherwise, enables the number of iterations k=k+1, two flexible interconnection micro-capacitance sensor devices continue
Obtain respective decision variable and interaction variable.
Residual error size checks whether to meet equation consistency constraint, i.e. whether Optimized Iterative problem restrains.If global residual error
Infinite Norm be less than given convergence threshold, then stop iteration, obtain optimal solution.Otherwise, k=k+1, return step S2 are enabled.
It is selectable, the global variable initial value Plink(0)For the reality of flexible interconnection micro-capacitance sensor device both ends active power
Measured data.
Selectable, the decision variable includes: diesel generating set active-power PDEGj, energy storage device charge power
Pch, energy storage device discharge power Pdis, photovoltaic cells reduction active-power Pctlj, cutting load active-power Pdecj。
Selectable, the interactive variable includes: two end node m active power of flexible interconnection micro-capacitance sensor deviceIt is soft
Property interconnection two end node n active power of micro-capacitance sensor device
In order to verify the validity of above-mentioned flexible interconnection micro-capacitance sensor installation optimization dispatching method, two independent micro-capacitance sensors are selected
Take 33 meshed network of IEEE as shown in Figure 3, respectively different node locations install photovoltaic cells, diesel generating set and
Energy storage device.Energy-storage system device access node, that is, node 1 is balance nodes.
Scheduling result is as shown in Fig. 4-7 and table 1-2.
It is illustrated in figure 5 the transimission power of flexible interconnection micro-capacitance sensor device, wherein Fig. 5 c is flexible interconnection micro-capacitance sensor device
The active power of transmission, Fig. 5 d are the reactive power of flexible interconnection micro-capacitance sensor device transmission.Active power is that timing is indicated by MG2
To MG1 output power, reactive power is that timing indicates that sending is idle.Due to transition loss etc., flexible interconnection micro-capacitance sensor device two
There are active difference powers for side.Device two sides are used as reactive source, provide reactive power support to system.
It is illustrated in figure 6 active/idle power curve of each equipment, wherein Fig. 6 e indicates that the diesel generating set in MG1 goes out
Power, Fig. 6 f indicate the diesel generating set power output in MG2, and Fig. 6 g indicates the idle power output of diesel generating set, and figure h indicates photovoltaic list
Power output that member is idle.As seen from Figure 6, diesel generating set power output is substantially complementary with photovoltaic cells power output, meets workload demand.
It is illustrated in figure 7 residual error convergence process example, wherein Fig. 7 i and 7j respectively indicate 16h and 19h Optimized Iterative process
In original residual sum antithesis residual error situation of change.From figure 7 it can be seen that ADMM algorithm coordinates convergence, region after iteration
The raw residual and antithesis residual error of boundary active power all level off to zero, the flexible interconnection micro-capacitance sensor device transmission after being balanced
Power.
Flexible interconnection micro-capacitance sensor appliance arrangement parameter setting is as shown in table 1.
1 flexible interconnection micro-capacitance sensor appliance arrangement parameter setting of table
The typical day total operating cost of flexible interconnection micro-capacitance sensor device is as shown in table 2.
The typical day total operating cost of 2 flexible interconnection micro-capacitance sensor device of table
The present invention is described in detail combined with specific embodiments below:
Embodiment one: when daytime is sunny, a micro-capacitance sensor photovoltaic power output is superfluous, another photovoltaic undercapacity.It is soft at this time
Property interconnection micro-capacitance sensor device can by the extra active power transfer of side micro-capacitance sensor to vacancy side, avoid starting diesel engine unit,
Such as 10h, 11h and 16h.
It is illustrated in figure 4 the typical daily load demand of MG1 (4a) and MG2 (4b) and photovoltaic power curve figure.In 16h, by Fig. 4
Know that MG1 photovoltaic power output is greater than workload demand, residue about 185.5kW, and MG2 photovoltaic power output is less than workload demand, vacancy is about
314.5kW.If micro-capacitance sensor independent operating, MG1 needs to store whole dump powers in this case, and MG2 exists
There is still a need for starting diesel generating sets to guarantee reliable power supply on the basis of energy storage electric discharge.Since photovoltaic power generation cost is sent out lower than diesel oil
Motor form sheet, by the coordination optimization of flexible interconnection micro-capacitance sensor device, MG1 is after meeting therein workload demand, by portion
Power transfer is divided to be delivered to MG2 energy supply, as shown in Figure 5.The power of MG1 conveying is about 176.6kW, and the received power of MG2 is about
158.7kW, extra energy consumption is in the alternating current-direct current conversion process inside flexible interconnection micro-capacitance sensor device.In addition, being stored up in MG2
Energy discharge power is about 205.5kW, supplements remaining power shortage.
Embodiment two: all micro-capacitance sensor photovoltaic power outputs are all superfluous when sunny daytime, load was smaller, energy storage device charging, if
Reach the stored energy capacitance upper limit or then to cut down photovoltaic more than the charge power upper limit active, such as 12h, 13h, 14h and 15h.
In 12h, the photovoltaic power output of MG1 and MG2 is all larger than workload demand as shown in Figure 4, and extra energy storage is in local
In energy-storage system, but energy storage still has energy residual after reaching maximum charge power inside MG1, and the energy storage charge power of MG2 is also not
Reach maximum value.Therefore, the remaining energy of MG1 conveys 200.5kW to MG2 by flexible interconnection micro-capacitance sensor device, is conveying
There is loss about 17kW in journey, as shown in Figure 5.
In Fig. 4, in 14h and 15h, MG2 photovoltaic power output be respectively 1700kW and 1600kW, load be 1077.4kW and
1003.1kW.At this point, energy storage device is with maximum charge power 300kW charging, MG2 to MG1 transimission power 84.4kW and 83.8kW,
But there are still photovoltaic power output residues, therefore the photovoltaic that there is about 209.6kW and 189.1kW is cut down.
Embodiment three: night is unglazed or photovoltaic undercapacity on daytime, the diesel generating set of certain micro-capacitance sensor can not because of failure
Operation, the diesel engine unit of another micro-capacitance sensor increase power output, and flexible interconnection micro-capacitance sensor device is use up maximum capacity transmission energy, reduced
Cutting load power, such as 19h.
Energy-storage system is with maximum discharge power 300kW operation in 19h, MG1 and MG2, but is still unable to satisfy user
Workload demand, it is therefore desirable to start diesel generating set and be powered.As shown in fig. 6, diesel engine unit in MG1 is moved back due to failure
It runs out, therefore the diesel engine unit in MG2 is run with larger power output, redundance is transported to by flexible interconnection micro-capacitance sensor device
MG2, about 173kW, as shown in Figure 5.It is supported by the power of interconnect device, MG1 cutting load is fallen to by original 814.5kW
662.1kW.Conveying active power is not up to the maximum capacity of flexible interconnection micro-capacitance sensor device, and reason is the micro- electricity of flexible interconnection
After failure of net device bavin in MG1 sending out exits, needs to compensate the load or burden without work in MG1, occupy total transmission capacity.
Example IV: night is unglazed or photovoltaic undercapacity on daytime, and energy storage device electric discharge, discharge power are small inside micro-capacitance sensor
Start diesel engine unit power supply when load, such as other moment.
In 17h, the photovoltaic power output of MG1 and MG2 is respectively less than load as shown in Figure 4, but power shortage is smaller, respectively
214.5kW and 154.5kW is less than energy storage device maximum discharge power, and energy storage device electric discharge at this time can meet demand；In 18h
~21h needs to start diesel engine unit and energy storage device is powered together since power shortage is larger；1h~9h and 22h~
For 24 hours, since energy storage device residual capacity is insufficient, system relies primarily on diesel engine unit power supply, as shown in table 2.
In conclusion the superfluous micro-capacitance sensor of photovoltaic power output is mutual by flexibility in flexible interconnection micro-capacitance sensor device in embodiment one
Join micro-capacitance sensor device transmission power, the micro-capacitance sensor for avoiding photovoltaic undercapacity enables diesel engine unit, reduces operating cost；It is real
The micro-capacitance sensor for applying photovoltaic power output surplus in flexible interconnection micro-capacitance sensor device in example two conveys function by flexible interconnection micro-capacitance sensor device
Rate avoids the reduction of photovoltaic active power, the energy of increased energy storage device storage can be in light although increasing cost depletions
Other lower moment of volt power output provide power support；The micro-capacitance sensor that diesel engine unit works normally in embodiment three passes through flexible mutual
Join micro-capacitance sensor device transmission power, support can be provided for the micro-capacitance sensor of diesel engine unit failure, ensure load power supply, realizes total operation
Cost reduces.
From the above technical scheme, the distributed optimization tune based on flexible interconnection micro-capacitance sensor shown in the embodiment of the present application
Degree method has the advantage that
(1) ordinary tap is replaced decouple mutually by independent exchange micro-capacitance sensor with two-way DC/AC (DC/AC) current transformer
Connection it is " soft " connection can in range of capacity two-way accurate continuous control trend, improve control speed and scheduling " flexibility ",
Flexible apparatus can quickly adjust two sides power according to operating condition；
(2) using distributed optimization dispatching method be not necessarily to central controller, each micro-capacitance sensor only need be connected micro-capacitance sensor into
Row data interaction, communications burden is lighter, and reliability is stronger.
Those skilled in the art after considering the specification and implementing the invention disclosed here, will readily occur to of the invention its
Its embodiment.This application is intended to cover any variations, uses, or adaptations of the invention, these modifications, purposes or
Person's adaptive change follows general principle of the invention and including the undocumented common knowledge in the art of the present invention
Or conventional techniques.The description and examples are only to be considered as illustrative, and true scope and spirit of the invention are by following
Claim is pointed out.
It should be understood that the present invention is not limited to the precise structure already described above and shown in the accompanying drawings, and
And various modifications and changes may be made without departing from the scope thereof.The scope of the present invention is limited only by the attached claims.
Claims (8)
1. a kind of distributed optimization dispatching method based on flexible interconnection micro-capacitance sensor, which is characterized in that the distributed optimization tune
Degree method includes:
Obtain global variable initial value Plink(0), enable initial Lagrange multiplier λP(0)=0, enable the number of iterations k=0；
Two flexible interconnection micro-capacitance sensor devices solve respective Optimized model respectively, obtain decision variable and interact variable, and first
Area coordination control model device is by virtual burden with powerWithIt is sent to second area tuning controller, first area
Tuning controller receives the area transmissions active power that second area tuning controller is sentWith
First area tuning controller and second area tuning controller distinguish update area transmitting active power global variable,
First area tuning controller and second area tuning controller update Lagrange multiplier respectively；
Calculate separately the raw residual r of two flexible interconnection micro-capacitance sensor devices1 k+1,With antithesis residual errorFirst
Flexible interconnection micro-capacitance sensor device is by raw residual r1 k+1With antithesis residual errorIt is sent to second area tuning controller, second is soft
Property interconnection micro-capacitance sensor device by raw residualWith antithesis residual errorIt is sent to first area tuning controller；
Judge whether to terminate iteration, if the Infinite Norm of global residual error is less than given convergence threshold, stops iteration and obtain most
Otherwise excellent solution enables the number of iterations k=k+1, two flexible interconnection micro-capacitance sensor devices continue to obtain respective decision variable and friendship
Mutual variable.
2. distributed optimization dispatching method according to claim 1, which is characterized in that the global variable initial value Plink (0)For the measured data of flexible interconnection micro-capacitance sensor device both ends active power.
3. distributed optimization dispatching method according to claim 2, which is characterized in that the objective function of the Optimized model
For min fMG=f1+f2+f3+f4+f5；
Wherein, fMGFor the operating cost of flexible interconnection micro-capacitance sensor device, f1For Web-based exercise, f2For diesel generating set operation at
This, f3For energy storage device charge and discharge cost, f4Cost, f are cut down for photovoltaic cells5For cutting load cost；
The Web-based exercise function is
Wherein, clossFor loss factor,It is lost for flexible interconnection micro-capacitance sensor device internal network,It is micro- for flexible interconnection
Electric net device loss；
The diesel generating set operating cost function is
Wherein, N is total node number, PDEGjFor the active power of node j diesel generating set output, a, b and c indicate cost system
Number；
The energy storage device charge and discharge cost function is f3=cbat(Pch+Pdis)；
Wherein, PchFor the charge power of energy storage device, PdisFor the discharge power of energy storage device, cbatFor charge and discharge cost coefficient；
The photovoltaic cells cut down cost function
Wherein, Pct l jFor the active power that node j photovoltaic cells are cut down, cctlTo cut down cost coefficient；
The cutting load cost function is
Wherein, PdecjFor node j cutting load active power, cdecFor cutting load unit power cost.
4. distributed optimization dispatching method according to claim 3, which is characterized in that the constraint that the objective function solves
Condition includes: trend constraint, and node voltage constraint, photovoltaic cells operation constraint, energy storage constraint, diesel generating set operation is about
Beam, the constraint of flexible interconnection micro-capacitance sensor device.
5. distributed optimization dispatching method according to claim 4, which is characterized in that the trend constraint is
Wherein, i → j is upstream node of the node i to node j；IijFor the electric current flowed out from node i to node j, UiAnd UjFor section
The voltage magnitude of point i and node j, PijFor the active power flowed out from node i to node j, QijTo be flowed out from node i to node j
Reactive power, PjThe active power of node j net load, QjFor the reactive power of node j net load, RijFor node i and node j
Between route resistance value, XijThe reactance value of route, P between node i and node jLjFor the active power of node j load, QLjFor section
The reactive power of point j load,For the maximum power point value of node j photovoltaic cells active power, QPVjFor the nothing of node j photovoltaic
Function output power, QdecjFor node j cutting load reactive power, QDEGjFor the idle output power of node j diesel generating set；
The node voltage is constrained to U1=Uref, (1- ε) Uref≤Uj≤(1+ε)Uref；
Wherein, U1For region first node voltage magnitude, UrefFor Area Node voltage reference value, ε is the maximum allowable of node voltage
Deviation；
The photovoltaic cells operation is constrained to
Wherein, θ=cos-1PFminCorresponding minimum power factor PFminWhen angle；
The energy storage is constrained toμch+μdis≤1；
Wherein,For the charge power maximum value of root node energy storage device,For root node energy storage device discharge power most
Big value, ηchFor energy storage device charge efficiency, ηdisFor energy storage device discharging efficiency, μchFor the charging mark of root node energy storage device
Will, μdisFor the electric discharge mark of root node energy storage device；
The diesel generating set operation is constrained to
Wherein,For diesel generating set active power power output the upper limit,For diesel generating set active power power output
Lower limit, UDEGjThe maximum power regulated quantity of power output, D are improved for diesel generating setDEGjFunction is reduced for diesel generating set
The maximum power regulated quantity of rate output, SRFor operation reserve capacity；
The flexible interconnection micro-capacitance sensor device constraint includes: the constraint of flexible interconnection micro-capacitance sensor device active power, and flexible interconnection is micro-
The constraint of electric net device reactive power, the constraint of flexible interconnection micro-capacitance sensor installed capacity；
The flexible interconnection micro-capacitance sensor device active power is constrained to
Wherein,For flexible interconnection micro-capacitance sensor device node m output active power,For flexible interconnection micro-capacitance sensor device section
The reactive power of point m output,For flexible interconnection micro-capacitance sensor device node n output active power,It is micro- for flexible interconnection
The reactive power of electric net device node n output,For the corresponding network loss of node m,For the corresponding network loss of node n,
AlinkFor loss factor；
The flexible interconnection micro-capacitance sensor device reactive power is constrained to
Wherein,For the lower limit of flexible interconnection micro-capacitance sensor device node m output reactive power,For flexible interconnection micro-capacitance sensor
The lower limit of device node m output reactive power,For the lower limit of flexible interconnection micro-capacitance sensor device node n output reactive power,For the lower limit of flexible interconnection micro-capacitance sensor device node n output reactive power；
The flexible interconnection micro-capacitance sensor installed capacity is constrained to
Wherein,For the capacity of current transformer at flexible interconnection micro-capacitance sensor device node m,For flexible interconnection micro-capacitance sensor device section
The capacity of current transformer at point n.
6. distributed optimization dispatching method according to claim 5, which is characterized in that the decision variable includes: diesel oil
Generating set active-power PDEGj, energy storage device charge power Pch, energy storage device discharge power Pdis, photovoltaic cells are cut down active
Power Pctlj, cutting load active-power Pdecj；
The interactive variable includes: two end node m active power of flexible interconnection micro-capacitance sensor deviceFlexible interconnection micro-capacitance sensor dress
Set two end node n active power
7. distributed optimization dispatching method according to claim 6, which is characterized in that the update area transmits wattful power
The solving model of rate global variable is
It is described update Lagrange multiplier solving model be
8. distributed optimization dispatching method according to claim 7, which is characterized in that the flexible interconnection micro-capacitance sensor device
The calculation formula of raw residual be
The antithesis residual error of the flexible interconnection micro-capacitance sensor deviceCalculation formula be
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910259596.XA CN109980684A (en) | 2019-04-02 | 2019-04-02 | A kind of distributed optimization dispatching method based on flexible interconnection micro-capacitance sensor |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910259596.XA CN109980684A (en) | 2019-04-02 | 2019-04-02 | A kind of distributed optimization dispatching method based on flexible interconnection micro-capacitance sensor |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109980684A true CN109980684A (en) | 2019-07-05 |
Family
ID=67082318
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910259596.XA Pending CN109980684A (en) | 2019-04-02 | 2019-04-02 | A kind of distributed optimization dispatching method based on flexible interconnection micro-capacitance sensor |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109980684A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110912137A (en) * | 2019-10-25 | 2020-03-24 | 国网天津市电力公司电力科学研究院 | Flexible power distribution network operation domain model construction method considering alternating current power flow |
| CN112290601A (en) * | 2020-10-27 | 2021-01-29 | 国网山东省电力公司电力科学研究院 | Optimized scheduling method and system for flexible interconnection alternating current-direct current power distribution system |
| CN112529276A (en) * | 2020-12-01 | 2021-03-19 | 国网湖北省电力有限公司电力科学研究院 | Interconnected micro-grid layered distributed optimization scheduling method |
| CN113762632A (en) * | 2021-09-10 | 2021-12-07 | 国网四川省电力公司经济技术研究院 | Collaborative optimization operation method and system of electrical comprehensive energy system |
| CN113890164A (en) * | 2021-09-30 | 2022-01-04 | 嘉兴学院 | Photovoltaic energy storage power supply control system |
| CN115800276A (en) * | 2023-02-09 | 2023-03-14 | 四川大学 | Power system emergency scheduling method considering unit climbing |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105140971A (en) * | 2015-09-17 | 2015-12-09 | 浙江工商大学 | AC-DC micro-grid distributed scheduling method based on reweighed acceleration Lagrangian |
| CN105186500A (en) * | 2015-09-17 | 2015-12-23 | 浙江工商大学 | Power distribution network energy dispersion coordination and optimization method based on reweighted acceleration Lagrangian |
| US20160064934A1 (en) * | 2013-03-27 | 2016-03-03 | Electric Power Research Institute Of State Grid Zhejiang Electric Power Company | Optimization method for independent micro-grid system |
-
2019
- 2019-04-02 CN CN201910259596.XA patent/CN109980684A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160064934A1 (en) * | 2013-03-27 | 2016-03-03 | Electric Power Research Institute Of State Grid Zhejiang Electric Power Company | Optimization method for independent micro-grid system |
| CN105140971A (en) * | 2015-09-17 | 2015-12-09 | 浙江工商大学 | AC-DC micro-grid distributed scheduling method based on reweighed acceleration Lagrangian |
| CN105186500A (en) * | 2015-09-17 | 2015-12-23 | 浙江工商大学 | Power distribution network energy dispersion coordination and optimization method based on reweighted acceleration Lagrangian |
Non-Patent Citations (2)
| Title |
|---|
| 罗天等: "基于拉格朗日对偶松弛的多区域柔性直流互联电网无功优化", 《电力系统自动化》 * |
| 路畅等: "基于柔性互联的独立微电网分布式优化调度方法", 《电网技术》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110912137A (en) * | 2019-10-25 | 2020-03-24 | 国网天津市电力公司电力科学研究院 | Flexible power distribution network operation domain model construction method considering alternating current power flow |
| CN110912137B (en) * | 2019-10-25 | 2023-05-23 | 国网天津市电力公司电力科学研究院 | Flexible power distribution network operation domain model construction method considering alternating current power flow |
| CN112290601A (en) * | 2020-10-27 | 2021-01-29 | 国网山东省电力公司电力科学研究院 | Optimized scheduling method and system for flexible interconnection alternating current-direct current power distribution system |
| CN112529276A (en) * | 2020-12-01 | 2021-03-19 | 国网湖北省电力有限公司电力科学研究院 | Interconnected micro-grid layered distributed optimization scheduling method |
| CN113762632A (en) * | 2021-09-10 | 2021-12-07 | 国网四川省电力公司经济技术研究院 | Collaborative optimization operation method and system of electrical comprehensive energy system |
| CN113890164A (en) * | 2021-09-30 | 2022-01-04 | 嘉兴学院 | Photovoltaic energy storage power supply control system |
| CN115800276A (en) * | 2023-02-09 | 2023-03-14 | 四川大学 | Power system emergency scheduling method considering unit climbing |
| CN115800276B (en) * | 2023-02-09 | 2023-05-30 | 四川大学 | Power system emergency scheduling method considering climbing of unit |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109980684A (en) | A kind of distributed optimization dispatching method based on flexible interconnection micro-capacitance sensor | |
| EP3872948B1 (en) | Edge computing-based multi-agent load regulation and control method | |
| CN109980685B (en) | Uncertainty-considered active power distribution network distributed optimization operation method | |
| CN102710013B (en) | Park energy-network energy optimizing management system based on microgrids and implementing method thereof | |
| US9778719B2 (en) | Ubiquitous energy network for achieving optimized utilization of energy and method for providing energy transaction and service | |
| US9690275B2 (en) | System energy efficiency controller, energy efficiency gain device and smart energy service system used for energy utilization | |
| CN104734168B (en) | Microgrid running optimization system and method based on power and heat combined dispatching | |
| CN103683272B (en) | A kind of independent direct current micro-grid system and energy equilibrium control method thereof | |
| CN107292449A (en) | One kind is containing the scattered collaboration economic load dispatching method of many microgrid active distribution systems | |
| CN108494015A (en) | The integrated energy system design method of one introduces a collection-lotus-storage coordination and interaction | |
| CN105552914B (en) | A kind of alternating current-direct current mixing micro-capacitance sensor hierarchical control method based on electricity price | |
| CN111049199B (en) | Distributed dynamic economic dispatching method for alternating current-direct current hybrid micro-grid | |
| CN107453381B (en) | Electric car cluster power regulating method and system based on two stages cross-over control | |
| CN108695868A (en) | Power distribution network energy storage addressing constant volume method based on electric power electric transformer | |
| CN107749642A (en) | A kind of household energy router | |
| CN103730908A (en) | Method for controlling energy storage converters in large-scale off-grid micro-grid | |
| CN103296754A (en) | Method for controlling distributed power resources of active power distribution networks | |
| CN105071389A (en) | Hybrid AC/DC microgrid optimization operation method and device considering source-grid-load interaction | |
| CN105140971B (en) | A kind of alternating current-direct current micro-capacitance sensor distributed scheduling method based on weighting acceleration Lagrangian again | |
| CN105244912B (en) | Active power distribution network isolated island restores electricity and black-start method | |
| CN109245091A (en) | A kind of two_layer strategies dispatching method towards sale of electricity company | |
| CN110867897A (en) | Coordination control strategy under multi-mode of multi-port energy router | |
| CN109245134A (en) | Adaptively regulate and control the hybrid energy-storing dispatching method and system of algorithm based on Virtual Fuzzy | |
| CN112380681A (en) | Distributed optimization-based comprehensive energy system parameter determination method and related device | |
| CN110829503B (en) | Wind, light, water and fire storage multi-energy complementary micro-grid joint optimization scheduling method and system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190705 |