CN105226652B - A kind of smart power grid user side energy-saving control method - Google Patents
A kind of smart power grid user side energy-saving control method Download PDFInfo
- Publication number
- CN105226652B CN105226652B CN201510723991.0A CN201510723991A CN105226652B CN 105226652 B CN105226652 B CN 105226652B CN 201510723991 A CN201510723991 A CN 201510723991A CN 105226652 B CN105226652 B CN 105226652B
- Authority
- CN
- China
- Prior art keywords
- time
- equipment
- mrow
- time interval
- transferred
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 12
- 238000012546 transfer Methods 0.000 claims abstract description 13
- 230000002068 genetic effect Effects 0.000 claims abstract description 9
- 210000000349 chromosome Anatomy 0.000 claims abstract description 6
- 238000011161 development Methods 0.000 description 3
- 230000005611 electricity Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000007726 management method Methods 0.000 description 3
- 230000004075 alteration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 239000006185 dispersion Substances 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000013519 translation Methods 0.000 description 1
Abstract
The present invention relates to a kind of smart power grid user side energy-saving control method, choose a period of time and by it according to certain time interval discretization, target consumption curve P of the equipment under sometime interval kT is obtained respectively0And actual consumption curve P (kT)L(kT).Because equipment may postpone during connection power network, the transfer equipment maximum number in a time step is calculated according to device type number and maximum delay time.Using genetic algorithm by setting chromosome length and fitness function, the optimal solution that the time step of power network is connected in equipment is tried to achieve, and then the optimal solution is transferred to intelligent controller, transfer of the equipment in the time step is completed.
Description
Technical field
The present invention relates to a kind of smart power grid user side energy-saving control method, it is related to the skill of the dsm of intelligent grid
Art field.
Background technology
With continuing to develop for economic society, the raising at full speed of scientific and technological level, the operation and management of modern power network are
Through ripe day by day, and more and more it is inclined to the development of intelligent grid.Intelligent grid is led to by advanced sensing measurement, information
Electric network reconstruction is intelligent, information-based, the interactive power network of new generation of height by the technologies such as letter, Automated condtrol, new material, right
Whole power system has the important meaning such as safe and reliable, economical and efficient, energy-saving and emission-reduction, environment-friendly, for improving electric energy
Important breakthrough is achieved in terms of quality, good service and the sustainable development of socio-economy.
Wherein, side demand management is the important component of intelligent grid, refers to the side of electricity consumption one is implemented to manage, by arranging
Used less a little when applying guiding user peak, Multifunctional electric during low ebb, so as to improve power supplying efficiency.User can be according to Spot Price and oneself
Body situation optimizes the energy and used to greatest extent, saves electric power spending.And dispatching of power netwoks institutional capacity is analyzed, plans, counted in real time
Draw, power network is optimized operating cost.The algorithm used in the prior art in DSM is that system is special mostly
Fixed strategy, the utility system of some of which polytype autonomous device.Most of technological development uses dynamic programming and line
Property planning, and these technologies can not be handled with several computation schemas and didactic polytype sum purpose is controllable sets
It is standby.
The content of the invention
That invents aims to overcome that the deficiencies in the prior art, it is proposed that a kind of smart power grid user side Energy Saving Control side
Method, a large amount of and polytype equipment can not be handled for solving the dsm of intelligent grid.
The present invention is achieved by following scheme：
A kind of smart power grid user side energy-saving control method, step is as follows：
Step 1), choose a period of time and by it according to certain time interval discretization, equipment is obtained respectively a certain
Target consumption curve P under time interval kT0And actual consumption curve P (kT)L(kT), described actual consumption curve PL(kT)
Including：Forecast consumption P of the target load under time interval kTF(kT), and target load connected under time interval kT and
Consumption during disconnection, i.e. PCAnd P (kT)D(kT)；
Step 2), the optimal solution that the time step of power network is connected in equipment is tried to achieve using genetic algorithm, wherein, it will dye
The length of body and sets restrictive condition as the quantity of all devices of transfer needed in time step, finally utilizes target
Consumption curve P0And actual consumption curve P (kT)L(kT) fitness function that the difference between is set up, obtains equipment and is connected to electricity
The optimal solution of the time step of net；
Step 3), described optimal solution is transferred to intelligent controller, transfer of the equipment in the time step is completed.
Further, step 1) described in PC(kT) it is made up of two parts：Equipment is transferred to the connection in time interval kT
Load increment and equipment produced by time are transferred to the load increment produced in the Connection Time predetermined before time interval kT；
The PD(kT) it is also to be made up of two parts：1) because the equipment Connection Time postpones, target load is transferred in time interval kT
The not connected time in produced by load decrement；2) because the equipment Connection Time postpones, expect between equipment is transferred to the time
Every connection in the time step before kT, and the fact is not connected with produced load decrement.
Further, step 2) described in time step in needed for transfer all devices quantity, expression formula is as follows：
Wherein, m is equipment maximum delay time；N is time step；K represents the number of types of equipment.
Further, step 2) described in setting restrictive condition for be transferred to number of devices in a time step can not be big
In the controllable device quantity in current time step.
Further, step 2) described in fitness function expression formula it is as follows：
Wherein, d is a period of time chosen；S is the time interval of setting.
Present invention beneficial effect compared to the prior art is：
It is main in the prior art that side demand management is carried out to electric power system by formulating system specific strategy, but it is this
Mode can not be met when connection device type and increased amount of situation in power supply network.The present invention will be carried out at discretization the time
Reason, obtains target consumption curve and actual consumption curve of the equipment within certain interval time, equipment is in connection power network process respectively
In may postpone, transfer equipment in a time step is calculated most according to device type number and maximum delay time
Big figure, the load transfer for setting up super proxima luce (prox. luc) minimizes mathematical modeling.Then, equipment access is finally tried to achieve using genetic algorithm
The optimal solution of the time step of power network.Even if the present invention can realize that power supply network accesses substantial amounts of polymorphic type target load, equally
It can meet and both allow user oneself to formulate planned high efficient energy sources consumption, and can assist power company reduction peak load demand
With reconstruct part throttle characteristics, and user can by the load of high priority reasonable time step-length access power network, add intelligence
Sustainability and flexibility that energy power network is powered.
Brief description of the drawings
Fig. 1 is the schematic flow sheet of the embodiment of the present invention；
Fig. 2 is the intelligent grid structural model figure of the embodiment of the present invention.
Embodiment
The present invention will be further described in detail with reference to the accompanying drawings and examples.
Step (1), choose the time and by it according to the time interval discretization of one hour, equipment is obtained respectively and is existed
Sometime it is spaced the target consumption curve P under kT0And actual consumption curve P (kT)L(kT)；Wherein, the actual consumption curve
PL(kT) include：Equipment forecast consumption P under time interval kTF(kT), and when equipment is connected and disconnected under time interval kT
Consumption, i.e. PCAnd P (kT)D(kT)。PC(kT) by two parts group：(1) equipment was transferred in the Connection Time in time interval kT
Produced load increment；(2) equipment is transferred to the load increment produced in the Connection Time predetermined before time interval kT.PD
(kT) it is also to be made up of two parts：(1) because the equipment Connection Time postpones, when equipment is transferred to not connected in time interval kT
Load decrement produced by interior；(2) because the equipment Connection Time postpones, expect when equipment is transferred to before time interval kT
Between step-length connect, and true be not connected with produced load decrement.
What step (2), the quantity shifted under time interval kT due to target load can not be more than current time interval can
Target load is controlled, equipment may postpone during connection power network, according to device type number and maximum delay time
The transfer equipment maximum number N in a time step is calculated, expression formula is as follows：
Wherein, m is target load maximum delay time, and n is time step, and k represents the number of types of equipment.
Step (3), the optimal time interval that target load accesses power network is obtained using genetic algorithm：
(1) initialization value of population is set, using binary coded system and chromosome length is set, the length of chromosome
Degree and N are directly related, i.e. the quantity and fitness function for all devices that the length of chromosome is shifted for needed in time step,
Try to achieve the optimal value of the transfer equipment quantity under time interval kT.
(2) suitable crossing-over rate and aberration rate are selected, and ensures that evolutionary generation reaches that specified quantity or fitness value become
Change amplitude is no more than permissible value.
(3) choosing one makes final load curve as close as the fitness function of target load curve, passes through institute
The fitness function of foundation asks for the optimal solution of chromosome, and as user equipment accesses the time step of power network, and by its time
Step-length is input to intelligent controller, and then completes load transfer of the equipment in the time step.Fitness function expression formula is as follows：
Wherein, d is a period of time chosen；S is the time interval of setting.
The time chosen in the present embodiment be 24 hours, using each hour as time interval the time of selection is carried out from
Dispersion, as other embodiment, situation about can also be shifted according to the quantity and physical device of equipment is chosen to be consistent therewith
Time and time interval.
Dsm genetic algorithm control device is set in the present embodiment, and intelligence is set on each user equipment (user)
Energy controller is connected with Demand-side genetic algorithm control device (host computer).The working voltage of whole network is 220V, is carried out
12 hours of simulation maximum delay.Due to the number increase of load bearing load transfer, so time delay is longer, Demand-side
The performance for managing genetic algorithm is better, so as to improve the accuracy of result.Among one day, the low ebb energy consuming curve of load will go out
Before rush hour now.If the peak load shifting time is 0 to 24 hours, peak load can not be transferred to the valley time.
In order to avoid such case, controlling cycle from the 8 of the previous day when to next day 8 when.The every kind of equipment chosen in the present embodiment
Power consumption pattern be different from, the optimal time that equipment is connected to power network is found according to the power consumption pattern of equipment by genetic algorithm
Step-length, makes final load curve close to target load curve, saves the user side electricity charge, realize the saving of the energy, reduce
The workload demand of intelligent grid peak period.
Under the thinking that the present invention is provided, to above-mentioned implementation by the way of being readily apparent that to those skilled in the art
Technological means in example enters line translation, replacement, modification, and plays a part of and the basic phase of relevant art means in the present invention
Goal of the invention that is same, realizing is also essentially identical, and the technical scheme so formed is finely adjusted to be formed to above-described embodiment, this
Technical scheme is planted to still fall within protection scope of the present invention.
Claims (5)
1. a kind of smart power grid user side energy-saving control method, it is characterised in that step is as follows：
Step 1), choose a period of time and by it according to certain time interval discretization, equipment is obtained respectively sometime
It is spaced the target consumption curve P under kT0And actual consumption curve P (kT)L(kT), described actual consumption curve PL(kT) include：
Target load forecast consumption P under time interval kTF(kT), and when target load is connected and disconnected under time interval kT
Consumption, respectively PCAnd P (kT)D(kT)；
Step 2), the optimal solution that the time step of power network is connected in equipment is tried to achieve using genetic algorithm, wherein, by chromosome
The quantity for all devices that length is shifted for needed in time step, and restrictive condition is set, finally consume bent using target
Line P0And actual consumption curve P (kT)L(kT) fitness function that difference between is set up, obtain equipment be connected to power network when
Between step-length optimal solution；
Step 3), described optimal solution is transferred to intelligent controller, transfer of the equipment in the time step is completed.
2. a kind of smart power grid user side energy-saving control method according to claim 1, it is characterised in that step 1) it is described
PC(kT) it is made up of two parts：Equipment be transferred in the Connection Time in time interval kT produced by load increment and equipment
It is transferred to the load increment produced in the Connection Time predetermined before time interval kT；The PD(kT) it is also to be made up of two parts：
Due to the delay of equipment Connection Time, the load produced by target load was transferred in the not connected time in time interval kT subtracts
Amount, and due to the delay of equipment Connection Time, expect to connect in the time step before equipment is transferred to time interval kT, and thing
It is real to be not connected with produced load decrement.
3. a kind of smart power grid user side energy-saving control method according to claim 1, it is characterised in that step 2) in institute
The quantity of all devices of transfer needed in the time step stated, expression formula is as follows：
<mrow>
<mi>N</mi>
<mo>=</mo>
<mi>k</mi>
<mo>&times;</mo>
<munderover>
<mi>&Sigma;</mi>
<mrow>
<mi>n</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>m</mi>
</munderover>
<mi>n</mi>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>1</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein, m is equipment maximum delay time, and n is time step, and k represents the number of types of equipment.
4. a kind of smart power grid user side energy-saving control method according to claim 1, it is characterised in that step 2) in institute
The setting restrictive condition stated is to be transferred to the controllable device that number of devices can not be more than in current time step in a time step
Quantity.
5. a kind of smart power grid user side energy-saving control method according to claim 1, it is characterised in that step 2) in institute
The fitness function expression formula stated is as follows：
<mrow>
<mi>f</mi>
<mo>=</mo>
<mfrac>
<mn>1</mn>
<mrow>
<mn>1</mn>
<mo>+</mo>
<munderover>
<mi>&Sigma;</mi>
<mrow>
<mi>k</mi>
<mi>T</mi>
<mo>=</mo>
<mi>s</mi>
</mrow>
<mi>d</mi>
</munderover>
<msup>
<mrow>
<mo>(</mo>
<msub>
<mi>P</mi>
<mi>L</mi>
</msub>
<mo>(</mo>
<mrow>
<mi>k</mi>
<mi>T</mi>
</mrow>
<mo>)</mo>
<mo>-</mo>
<msub>
<mi>P</mi>
<mi>O</mi>
</msub>
<mo>(</mo>
<mrow>
<mi>k</mi>
<mi>T</mi>
</mrow>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
</mrow>
</mfrac>
</mrow>
Wherein, d is a period of time chosen；S is the time interval of setting.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510723991.0A CN105226652B (en) | 2015-10-30 | 2015-10-30 | A kind of smart power grid user side energy-saving control method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510723991.0A CN105226652B (en) | 2015-10-30 | 2015-10-30 | A kind of smart power grid user side energy-saving control method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105226652A CN105226652A (en) | 2016-01-06 |
| CN105226652B true CN105226652B (en) | 2017-11-03 |
Family
ID=54995444
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510723991.0A Active CN105226652B (en) | 2015-10-30 | 2015-10-30 | A kind of smart power grid user side energy-saving control method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105226652B (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103761587A (en) * | 2014-02-13 | 2014-04-30 | 国家电网公司 | Power demand side resource planning method based on intelligent power utilization technology |
| EP2927644A1 (en) * | 2014-03-31 | 2015-10-07 | Alcatel Lucent | System and method for performing problem-solving in smart grid networks |
-
2015
- 2015-10-30 CN CN201510723991.0A patent/CN105226652B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103761587A (en) * | 2014-02-13 | 2014-04-30 | 国家电网公司 | Power demand side resource planning method based on intelligent power utilization technology |
| EP2927644A1 (en) * | 2014-03-31 | 2015-10-07 | Alcatel Lucent | System and method for performing problem-solving in smart grid networks |
Non-Patent Citations (1)
| Title |
|---|
| 智能电网框架下的DSM成本效益分析模型;苏浩益;《电力系统保护与控制》;20120716;第40卷(第14期);第69-73、80页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105226652A (en) | 2016-01-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Yang et al. | Optimal energy flow control strategy for a residential energy local network combined with demand-side management and real-time pricing | |
| CN101752903B (en) | Time sequence progressive power dispatching method | |
| CN105515110B (en) | A kind of electric automobile charges real-time control system in order | |
| CN106532751B (en) | A kind of distributed generation resource efficiency optimization method and system | |
| CN109193812A (en) | A kind of garden light storage lotus micro-capacitance sensor economic load dispatching implementation method | |
| CN109103912A (en) | Consider the industrial park active distribution system method for optimizing scheduling of peaking demand of power grid | |
| CN103426032A (en) | Method for economically and optimally dispatching cogeneration units | |
| CN105279578A (en) | Power supply optimization configuration bilevel programming method in active distribution network region | |
| CN105140958A (en) | Method for planning power distribution network comprising photovoltaic power supply | |
| CN112952805A (en) | Electric hydrogen energy system scheduling method considering flexible hydrogen demand | |
| CN104915725B (en) | Meter and the microgrid user group electric energy optimizing of Spot Price mutually help method of commerce | |
| CN104268697A (en) | Energy-saving risk probability considered provincial power grid electricity purchasing decision making system and method | |
| CN105337310A (en) | Series-structure light-storing-type multi-micro-grid economical operation system and method | |
| Maffei et al. | Optimal Power Flow model with energy storage, an extension towards large integration of renewable energy sources. | |
| CN106487035B (en) | A kind of flexible load dispatching method for improving power distribution network renewable energy and receiving ability | |
| CN103617455A (en) | Power network and plant two-stage optimal load scheduling method based on virtual machine set subgroup | |
| JP2020524325A (en) | A method of constructing a displaceable load model considering both environmental costs and rear-time electricity bill | |
| CN114662319A (en) | Construction method of active power distribution network planning model considering data center | |
| CN105320999A (en) | Combination method for demand response based time-of-use power price strategy suitable for smart grid development | |
| CN101989743B (en) | Energy-saving power generation dispatching optimization method based on direct current power flow | |
| CN104868506B (en) | A kind of active power output dispatching method of centralized energy-accumulating power station | |
| CN104778507B (en) | A kind of building intelligent electricity consumption strategy acquisition methods based on APSO algorithm | |
| CN111799793B (en) | Source-grid-load cooperative power transmission network planning method and system | |
| CN104239960A (en) | Electricity generating schedule optimizing method considering pump storage unit | |
| CN114154790A (en) | Industrial park light storage capacity configuration method based on demand management and flexible load |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C41 | Transfer of patent application or patent right or utility model | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20160922 Address after: No. 1298 Xuchang City, Henan province 461000 XJ Avenue Applicant after: Xuji Group Co., Ltd. Applicant after: Xuchang Xuji Software Technology Co., Ltd. Applicant after: State Grid Corporation of China Applicant after: STATE GRID HUBEI ELECTRIC POWER COMPANY Address before: No. 1298 Xuchang City, Henan province 461000 XJ Avenue Applicant before: Xuji Group Co., Ltd. Applicant before: State Grid Corporation of China Applicant before: Xuchang Xuji Software Technology Co., Ltd. |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |