CN109301820A - A kind of enterprise's electrical control method and system - Google Patents
A kind of enterprise's electrical control method and system Download PDFInfo
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- CN109301820A CN109301820A CN201811231288.8A CN201811231288A CN109301820A CN 109301820 A CN109301820 A CN 109301820A CN 201811231288 A CN201811231288 A CN 201811231288A CN 109301820 A CN109301820 A CN 109301820A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- 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]
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Abstract
The embodiment of the present application discloses a kind of enterprise's electrical control method and system, optimizes and revises for realizing to flexible load.The embodiment of the present application method includes: the historical record of rigid load in acquisition system；The rigid load prediction data of preset time period is generated according to the historical record of the rigid load；Obtain history electricity price record；The Research on electricity price prediction data of the preset time period are calculated according to history electricity price record；Using flexible load as variable, the objective function of total electricity price is generated according to the rigid load prediction data and the Research on electricity price prediction data；The minimum optimizing of total electricity price is carried out to the objective function by intelligent algorithm to solve, and obtains the first prediction data of the flexible load；The first prediction data in the preset time period according to the flexible load runs the flexible load in the system.To which according to the flexible load in the first prediction data operating system of flexible load, flexible load is optimized and revised in realization within a preset period of time.
Description
Technical field
This application involves power industry field more particularly to a kind of enterprise's electrical control method and systems.
Background technique
Electric power is the basic resource of the national economic development, and enterprise's production is closely related with electric power.Enterprise's electricity charge are by electric degree electricity
Take and basic charge as per installed capacity two parts form.Wherein, power cost is equal to the multiplying with power consumption and institute's electricity consumption real time price of enterprise
Product, basic charge as per installed capacity are then calculated by the product for declaring maximum demand definite value and local requirement price.
Maximum demand refer to enterprise a middle of the month, (China now executes 15 minutes) electricity consumption average load per unit time
Power peak needs to declare definite value in advance.If power peak is no more than declared maximum demand definite value, basic charge as per installed capacity is by fixed
Value calculates；If power peak is more than declared maximum demand definite value, exceed the double payment in part.
Therefore, the maximum demand control of enterprise directly reflects that enterprise's electrical management is horizontal, simul relation to production cost
Expenditure, maximum demand control method become urgent problem to be solved.
Apply for content
The embodiment of the present application provides a kind of enterprise's electrical control method and system, for realizing for the excellent of flexible load
Change adjustment.
The embodiment of the present application first aspect provides a kind of enterprise's electrical control method, comprising:
The historical record of rigid load in acquisition system；
The rigid load prediction data of preset time period is generated according to the historical record of the rigid load；
Obtain history electricity price record；
The Research on electricity price prediction data of the preset time period are calculated according to history electricity price record；
Using flexible load as variable, total electricity price is generated according to the rigid load prediction data and the Research on electricity price prediction data
Objective function；
The minimum optimizing of total electricity price is carried out to the objective function by intelligent algorithm to solve, and obtains the flexible load
First prediction data；
The first prediction data in the preset time period according to the flexible load runs the flexibility in the system
Load.
Optionally, the flexible load is run according to the prediction data of the flexible load in the preset time period
When, the method also includes:
The rigid load and flexible load of system described in real-time monitoring；
When the sum of rigid load and flexible load for determining object time is greater than threshold value, by the rigidity of the object time
Load substitutes into the objective function, obtains the second objective function, obtains the second prediction data of the flexible load；
The flexible load in the system is run according to the second prediction data of the flexible load.
Optionally, total amount of the flexible load in the preset time period is definite value.
Optionally, the objective function are as follows:
In formula, y is total electricity price of power cost and basic charge as per installed capacity, piFor the Spot Price of the i-th period, mi was the i-th period
Rigid load, niFor the flexible load of the i-th period, p0For local demand tariff, d0For enterprise's maximum demand setting value, if going out
Existing max (mi+ni)>d0, then d is updated0=max (mi+ni)；
The constraint of objective function is as follows:
In formula, dsoftFor the total amount of flexible load in preset time period.
The embodiment of the present application second aspect provides a kind of enterprise's electric control system, the system comprises:
First acquisition unit, the historical record for load rigid in acquisition system；
First generation unit, the rigid load for generating preset time period according to the historical record of the rigid load are pre-
Measured data；
Second acquisition unit, for obtaining history electricity price record；
Computing unit, for the Research on electricity price prediction number of the preset time period to be calculated according to history electricity price record
According to；
Second generation unit is used for using flexible load as variable, according to the rigid load prediction data and the electricity price
Prediction data generates the objective function of total electricity price；
Unit is solved, solves, obtains for carrying out the minimum optimizing of total electricity price to the objective function by intelligent algorithm
First prediction data of the flexible load；
First running unit, for being run in the preset time period according to the first prediction data of the flexible load
Flexible load in the system.
Optionally, the system also includes:
Monitoring unit, rigid load and flexible load for system described in real-time monitoring；
Unit is substituted into, it, will be described for when the sum of rigid load and flexible load for determining object time is greater than threshold value
The rigid load of object time substitutes into the objective function, obtains the second prediction data of the flexible load；
Second running unit runs the flexibility in the system for second prediction data according to the flexible load
Load.
Optionally, total amount of the flexible load in the preset time period is definite value.
Optionally, the objective function are as follows:
In formula, y is total electricity price of power cost and basic charge as per installed capacity, piFor the Spot Price of the i-th period, mi was the i-th period
Rigid load, niFor the flexible load of the i-th period, p0For local demand tariff, d0For enterprise's maximum demand setting value, if going out
Existing max (mi+ni)>d0, then d is updated0=max (mi+ni)；
The constraint of objective function is as follows:
In formula, dsoftFor the total amount of flexible load in preset time period.
The embodiment of the present application third aspect provides a kind of computer installation, comprising:
Processor, memory, input-output equipment and bus；
The processor, memory, input-output equipment are connected with the bus respectively；
The processor is used to execute method as in the preceding embodiment.
The embodiment of the present application fourth aspect provides a kind of computer readable storage medium, is stored thereon with computer journey
Sequence, it is characterised in that: the step of method as in the preceding embodiment is realized when the computer program is executed by processor.
As can be seen from the above technical solutions, the embodiment of the present application has the advantage that rigid load in acquisition system
Historical record；The rigid load prediction data of preset time period is generated according to the historical record of the rigid load；Obtain history
Electricity price record；The Research on electricity price prediction data of the preset time period are calculated according to history electricity price record；With flexible load
For variable, the objective function of total electricity price is generated according to the rigid load prediction data and the Research on electricity price prediction data；Pass through intelligence
Energy algorithm carries out the minimum optimizing of total electricity price to the objective function and solves, and obtains the first prediction data of the flexible load；
The first prediction data in the preset time period according to the flexible load runs the flexible load in the system.Its
In, rigid load includes fixed production plan load and/or the load for supporting enterprise's normal operation, and flexible load includes can be real-time
The load of its run the period is adjusted, which not only considers the cost payout of the maximum demand electricity charge, in combination with electric power city
The real-time power cost of field carries out minimum optimizing to total electricity price and solves, according to described flexible negative in the preset time period
The first prediction data of lotus runs the flexible load in the system, realizes optimizing and revising for flexible load.
Detailed description of the invention
Fig. 1 is an a kind of schematic diagram of enterprise's electrical control method embodiment in the embodiment of the present application；
Fig. 2 is a kind of another schematic diagram of enterprise's electrical control method embodiment in the embodiment of the present application；
Fig. 3 is an a kind of schematic diagram of enterprise's electric control system embodiment in the embodiment of the present application；
Fig. 4 is a kind of another schematic diagram of enterprise's electric control system embodiment in the embodiment of the present application；
Fig. 5 is a schematic diagram of computer Installation practice in the embodiment of the present application.
Specific embodiment
The embodiment of the present application provides a kind of enterprise's electrical control method and system, for realizing for the excellent of flexible load
Change adjustment.
In order to make those skilled in the art more fully understand application scheme, below in conjunction in the embodiment of the present application
Attached drawing, the technical scheme in the embodiment of the application is clearly and completely described, it is clear that described embodiment is only
The embodiment of the application a part, instead of all the embodiments.Based on the embodiment in the application, ordinary skill people
Member's every other embodiment obtained without making creative work, all should belong to the model of the application protection
It encloses.
The description and claims of this application and term " first ", " second ", " third ", " in above-mentioned attached drawing
Four " etc. be to be used to distinguish similar objects, without being used to describe a particular order or precedence order.It should be understood that using in this way
Data be interchangeable under appropriate circumstances, so that the embodiments described herein can be in addition to illustrating herein or describing
Sequence other than appearance is implemented.In addition, term " includes " and " having " and their any deformation, it is intended that covering is non-exclusive
Include, for example, the process, method, system, product or equipment for containing a series of steps or units are not necessarily limited to clearly arrange
Those of out step or unit, but may include be not clearly listed or it is solid for these process, methods, product or equipment
The other step or units having.
In order to make it easy to understand, the detailed process in the embodiment of the present application is described below, referring to Fig. 1, the application
A kind of one embodiment of enterprise's electrical control method includes: in embodiment
101, in acquisition system rigid load historical record；
The historical record of rigid load, which can be directly read in system, in the present embodiment, in specific acquisition system stores
The historical record of rigid load is also possible to receive the historical record for the rigid load that storage equipment is sent, not do herein specifically
It limits.Wherein, which includes fixed production plan load and/or the load for supporting enterprise's normal operation, is different from soft
Property load, flexible load includes the load that can adjust its run the period in real time.
102, the rigid load prediction data of preset time period is generated according to the historical record of the rigid load；
It is negative according to the rigidity after the historical record for getting rigid load according to normal process in the present embodiment
The historical record of lotus generates the rigid load prediction data of preset time period.
The specific rigidity load prediction data can be presented by a variety of mathematical expression modes such as curve, ordered series of numbers, equation, be had
Body is herein without limitation.In addition, the preset time period can be 12 hours, 24 hours, 48 hours, or it is other default when
Between section, specific enterprise can be regulated and controled according to itself actual traffic-operating period.
103, history electricity price record is obtained；
In the present embodiment, system obtain history electricity price record, herein electricity price be recorded as electric degree record, power cost be according to
Active energy meter reading is what radix calculated in the charge electric energy metering device of electric power enterprise installation, not by the shadow of maximum demand
It rings.
104, the Research on electricity price prediction data of the preset time period are calculated according to history electricity price record；
In the present embodiment, recorded after getting history electricity price record according to the history electricity price according to normal process
Generate the Research on electricity price prediction data of preset time period.
105, it using flexible load as variable, is generated according to the rigid load prediction data and the Research on electricity price prediction data total
The objective function of electricity price；
In the present embodiment, using flexible load as variable, according to the rigid load prediction data and the Research on electricity price prediction number
According to the objective function for generating total electricity price, the specific objective function are as follows:
In formula, y is total electricity price of power cost and basic charge as per installed capacity, piFor the Spot Price of the i-th period, mi was the i-th period
Rigid load, niFor the flexible load of the i-th period, p0For local demand tariff, d0For enterprise's maximum demand setting value, if going out
Existing max (mi+ni)>d0, then d is updated0=max (mi+ni)；
The constraint of objective function is as follows:
In formula, dsoftFor the total amount of flexible load in preset time period.
106, the minimum optimizing of total electricity price is carried out to the objective function by intelligent algorithm to solve, obtain described flexible negative
The first prediction data of lotus；
In the present embodiment, system carries out the minimum optimizing of total electricity price to the objective function by intelligent algorithm and solves, and obtains
To the first prediction data of the flexible load.The specific intelligent algorithm can be particle swarm algorithm, neural network algorithm, ant colony
Algorithm etc., or other intelligent algorithms, herein without limitation.
The solution procedure in the present embodiment is illustrated by taking particle swarm algorithm as an example below:
Step 1: the population of n (n is natural number) a particle is generated at random, to each particle localization by the way of coding,
Wherein, particle represents the performance number of flexible load；
Step 2: the friction speed obtained according to each particle and position solve objective function, and it is excessive to eliminate objective function
Particle, according to retain particle speed generate similar new particle group at random again with position；
Step 3: repeating step 2, continuous grey iterative generation new particle group obtains mesh until the value of objective function tends towards stability
The optimal solution of scalar functions, this generation population are optimal particle group；
Step 4: optimal particle group being decoded, obtains the flexible load power optimized setting value of each i period, in turn
Obtain the first prediction data of the flexible load in preset time period.
107, it is run in the system in the preset time period according to the first prediction data of the flexible load
Flexible load.
In the present embodiment, after the first prediction data for acquiring flexible load in step 106, when described default
Between flexible load in the system is run in section according to the first prediction data of the flexible load.
In the present embodiment, the historical record of rigid load in acquisition system；Historical record according to the rigid load is raw
At the rigid load prediction data of preset time period；Obtain history electricity price record；It is calculated according to history electricity price record
The Research on electricity price prediction data of the preset time period；Using flexible load as variable, according to the rigid load prediction data and described
Research on electricity price prediction data generate the objective function of total electricity price；Carry out that total electricity price is minimum to seek to the objective function by intelligent algorithm
Excellent solution obtains the first prediction data of the flexible load；According to the of the flexible load in the preset time period
One prediction data runs the flexible load in the system.Wherein, rigid load includes fixed production plan load and/or support
The load of enterprise's normal operation, flexible load include the load that can adjust its run the period in real time, which not only considers
The cost payout of the maximum demand electricity charge carries out minimum optimizing to total electricity price in combination with the real-time power cost of electricity market
It solves, it is negative that the first prediction data in the preset time period according to the flexible load runs the flexibility in the system
Lotus realizes optimizing and revising for flexible load.
In the embodiment of the present application, previous embodiment is for providing a predictive flexible load curve, in step 107
In, it is negative that first prediction data of the system in the preset time period according to the flexible load runs the flexibility in the system
When lotus, under normal circumstances, the first prediction data based on flexible load calculated is to be not in more than maximum demand
The case where, if but due to temporarily producing caused by responsible surge, it is necessary to again according to the objective function meter
The optimization operation curve for calculating the remaining period in preset time period kind presses this curve motion after the completion of calculating.
Below referring to Fig. 2, in the embodiment of the present application, being based on embodiment described in Fig. 1, during step 107 executes,
Another embodiment of one of the embodiment of the present application enterprise electrical control method includes:
201, the rigid load and flexible load of system described in real-time monitoring；
In the present embodiment, system real-time monitoring gets the rigid load and flexible load of system, wherein rigid load packet
It includes fixed production plan load and/or supports the load of enterprise's normal operation, flexible load includes when can adjust its operation in real time
The load of section.
202, the rigid load of the object time is substituted into the objective function, obtains the second objective function, obtains institute
State the second prediction data of flexible load；
In the present embodiment, when the sum of rigid load and flexible load for determining object time is greater than threshold value, by the mesh
The rigid load for marking the moment substitutes into the objective function, obtains the second objective function, obtains the second prediction of the flexible load
Data.
Specifically, if the load caused by due to temporarily producing or is other increases sharply, rigid load increases at this time
Add, then when system determines that the sum of rigid load and flexible load of object time is greater than threshold value, by the rigid of the object time
Property load substitute into the objective function, obtain the second objective function, obtain the second prediction data of the flexible load.
203, the flexible load in the system is run according to the second prediction data of the flexible load.
In the present embodiment, the second prediction data of the flexible load that system is acquired according to step 202 is when this is preset
Between flexible load in remaining time in section in the operation system.
In the present embodiment, on the basis of the embodiment described in Fig. 1, flexible load is completed according to real-time load operating region
Real-time maximum demand control, so as to preferably be applied to enterprise basic charge as per installed capacity management, to reduce enterprise's production cost,
It improves enterprise intelligent management and energy-saving and emission-reduction is of great significance.
Enterprise a kind of in the embodiment of the present application electrical control method is illustrated from method part above, below from void
The angle of quasi- device introduces enterprise's electric control system in the embodiment of the present application.Referring to Fig. 3, a kind of in the embodiment of the present application
One embodiment of enterprise's electric control system includes:
First acquisition unit 301, the historical record for load rigid in acquisition system；
First generation unit 302, the rigidity for generating preset time period according to the historical record of the rigid load are negative
Lotus prediction data；
Second acquisition unit 303, for obtaining history electricity price record；
Computing unit 304, for the Research on electricity price prediction of the preset time period to be calculated according to history electricity price record
Data；
Second generation unit 305 is used for using flexible load as variable, according to the rigid load prediction data and the electricity
Valence prediction data generates the objective function of total electricity price；
Unit 306 is solved, solves, obtains for carrying out the minimum optimizing of total electricity price to the objective function by intelligent algorithm
To the first prediction data of the flexible load；
First running unit 307, for the first prediction data in the preset time period according to the flexible load
Run the flexible load in the system.
In the present embodiment, first acquisition unit 301, the historical record for load rigid in acquisition system；First generates
Unit 302, for generating the rigid load prediction data of preset time period according to the historical record of the rigid load；Second obtains
Unit 303 is taken, for obtaining history electricity price record；Computing unit 304, for institute to be calculated according to history electricity price record
State the Research on electricity price prediction data of preset time period；Second generation unit 305 is used for using flexible load as variable, according to the rigidity
Load prediction data and the Research on electricity price prediction data generate the objective function of total electricity price；Unit 306 is solved, for calculating by intelligence
Method carries out the minimum optimizing of total electricity price to the objective function and solves, and obtains the first prediction data of the flexible load；First
Running unit 307, for running the system according to the first prediction data of the flexible load in the preset time period
Interior flexible load.Wherein, rigid load includes the load of fixed production plan load and/or support enterprise's normal operation, soft
Property load includes the load that can adjust its run the period in real time, which not only considers the cost branch of the maximum demand electricity charge
Out, in combination with the real-time power cost of electricity market, minimum optimizing is carried out to total electricity price and is solved, in the preset time period
Interior the first prediction data according to the flexible load runs the flexible load in the system, realizes for the excellent of flexible load
Change adjustment.
Referring to Fig. 4, being based on Fig. 3 the embodiment described, as a preferred embodiment, a kind of enterprise's electric control system
Can also include:
Monitoring unit 401, rigid load and flexible load for system described in real-time monitoring；
Substitute into unit 402, for when the sum of rigid load and flexible load for determining object time be greater than threshold value when, by institute
The rigid load for stating object time substitutes into the objective function, obtains the second prediction data of the flexible load；
Second running unit 403 is run in the system for this according to the second prediction data of the flexible load
Flexible load.
Referring to Fig. 5, a specific embodiment of computer installation includes: in the embodiment of the present application
The device 500 can generate bigger difference because configuration or performance are different, may include one or more
Central processing unit (central processing units, CPU) 501 (for example, one or more processors) and storage
Device 505 is stored with one or more application program or data in the memory 505.
Wherein, memory 505 can be volatile storage or persistent storage.The program for being stored in memory 505 can wrap
One or more modules are included, each module may include to the series of instructions operation in server.Further, in
Central processor 501 can be set to communicate with memory 505, and a series of fingers in memory 505 are executed on intelligent terminal 500
Enable operation.
The device 500 can also include one or more power supplys 502, one or more wired or wireless networks
Interface 503, one or more input/output interfaces 504, and/or, one or more operating systems, such as
Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM etc..
It is retouched in process performed by central processing unit 501 in the present embodiment in computer installation 500 and previous embodiment
The step of stating execution in method flow is similar, and details are not described herein again.It is apparent to those skilled in the art that being
Convenienct and succinct, the specific work process of the system, apparatus, and unit of foregoing description of description can be implemented with reference to preceding method
Corresponding process in example, details are not described herein.
It is understood that the size of the serial number of above steps is not meant in the various embodiments of the application
Execution sequence it is successive, the execution of each step sequence should be determined by its function and internal logic, without coping with the embodiment of the present application
Implementation process constitute any restriction.
It is apparent to those skilled in the art that for convenience and simplicity of description, the system of foregoing description,
The specific work process of device and unit, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
In several embodiments provided herein, it should be understood that disclosed system, device and method can be with
It realizes by another way.For example, the apparatus embodiments described above are merely exemplary, for example, the unit
It divides, only a kind of logical function partition, there may be another division manner in actual implementation, such as multiple units or components
It can be combined or can be integrated into another system, or some features can be ignored or not executed.Another point, it is shown or
The mutual coupling, direct-coupling or communication connection discussed can be through some interfaces, the indirect coupling of device or unit
It closes or communicates to connect, can be electrical property, mechanical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, each functional unit in each embodiment of the application can integrate in one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of software functional units.
If the integrated unit is realized in the form of SFU software functional unit and sells or use as independent product
When, it can store in a computer readable storage medium.Based on this understanding, the technical solution of the application is substantially
The all or part of the part that contributes to existing technology or the technical solution can be in the form of software products in other words
It embodies, which is stored in a storage medium, including some instructions are used so that a computer
Equipment (can be personal computer, server or the network equipment etc.) executes the complete of each embodiment the method for the application
Portion or part steps.And storage medium above-mentioned includes: USB flash disk, mobile hard disk, read-only memory (ROM, Read-Only
Memory), random access memory (RAM, Random Access Memory), magnetic or disk etc. are various can store journey
The medium of sequence code.
The above, above embodiments are only to illustrate the technical solution of the application, rather than its limitations；Although referring to before
Embodiment is stated the application is described in detail, those skilled in the art should understand that: it still can be to preceding
Technical solution documented by each embodiment is stated to modify or equivalent replacement of some of the technical features；And these
It modifies or replaces, the spirit and scope of each embodiment technical solution of the application that it does not separate the essence of the corresponding technical solution.
Claims (10)
1. a kind of enterprise's electrical control method is applied to enterprise's electric control system, which is characterized in that the described method includes:
The historical record of rigid load in acquisition system；
The rigid load prediction data of preset time period is generated according to the historical record of the rigid load；
Obtain history electricity price record；
The Research on electricity price prediction data of the preset time period are calculated according to history electricity price record；
Using flexible load as variable, the mesh of total electricity price is generated according to the rigid load prediction data and the Research on electricity price prediction data
Scalar functions；
The minimum optimizing of total electricity price is carried out to the objective function by intelligent algorithm to solve, and obtains the first of the flexible load
Prediction data；
The first prediction data in the preset time period according to the flexible load runs the flexible load in the system.
2. the method according to claim 1, wherein according to the flexible load in the preset time period
When prediction data runs the flexible load, the method also includes:
The rigid load and flexible load of system described in real-time monitoring；
When the sum of rigid load and flexible load for determining object time is greater than threshold value, by the rigid load of the object time
The objective function is substituted into, the second objective function is obtained, obtains the second prediction data of the flexible load；
The flexible load in the system is run according to the second prediction data of the flexible load.
3. method according to claim 1 or 2, which is characterized in that the flexible load is in the preset time period
Total amount is definite value.
4. according to the method described in claim 3, it is characterized in that, the objective function are as follows:
In formula, y is total electricity price of power cost and basic charge as per installed capacity, piFor the Spot Price of the i-th period, mi is the rigidity of the i-th period
Load, niFor the flexible load of the i-th period, p0For local demand tariff, d0For enterprise's maximum demand setting value, if there is max
(mi+ni)>d0, then d is updated0=max (mi+ni)；
The constraint of objective function is as follows:
In formula, dsoftFor the total amount of flexible load in preset time period.
5. a kind of enterprise's electric control system, which is characterized in that the system comprises:
First acquisition unit, the historical record for load rigid in acquisition system；
First generation unit, for generating the rigid load prediction number of preset time period according to the historical record of the rigid load
According to；
Second acquisition unit, for obtaining history electricity price record；
Computing unit, for the Research on electricity price prediction data of the preset time period to be calculated according to history electricity price record；
Second generation unit is used for using flexible load as variable, according to the rigid load prediction data and the Research on electricity price prediction
Data generate the objective function of total electricity price；
Unit is solved, solves, obtains described for carrying out the minimum optimizing of total electricity price to the objective function by intelligent algorithm
First prediction data of flexible load；
First running unit, in the preset time period according to the first prediction data of the flexible load operation described in
Flexible load in system.
6. according to the method described in claim 5, it is characterized in that, the system also includes:
Monitoring unit, rigid load and flexible load for system described in real-time monitoring；
Substitute into unit, for when the sum of rigid load and flexible load for determining object time be greater than threshold value when, by the target
The rigid load at moment substitutes into the objective function, obtains the second prediction data of the flexible load；
It is negative to run the flexibility in the system for second prediction data according to the flexible load for second running unit
Lotus.
7. system according to claim 5 or 6, which is characterized in that the flexible load is in the preset time period
Total amount is definite value.
8. system according to claim 7, which is characterized in that the objective function are as follows:
In formula, y is total electricity price of power cost and basic charge as per installed capacity, piFor the Spot Price of the i-th period, mi is the rigidity of the i-th period
Load, niFor the flexible load of the i-th period, p0For local demand tariff, d0For enterprise's maximum demand setting value, if there is max
(mi+ni)>d0, then d is updated0=max (mi+ni)；
The constraint of objective function is as follows:
In formula, dsoftFor the total amount of flexible load in preset time period.
9. a kind of computer installation characterized by comprising
Processor, memory, input-output equipment and bus；
The processor, memory, input-output equipment are connected with the bus respectively；
The processor is for executing such as the described in any item methods of Claims 1-4.
10. a kind of computer readable storage medium, is stored thereon with computer program, it is characterised in that: the computer program
It is realized when being executed by processor such as the step of any one of Claims 1-4 the method.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811231288.8A CN109301820A (en) | 2018-10-22 | 2018-10-22 | A kind of enterprise's electrical control method and system |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110837936A (en) * | 2019-11-12 | 2020-02-25 | 哈尔滨学院 | Community adjustable load power utilization optimization method based on ant colony algorithm |
| CN112669055A (en) * | 2020-12-15 | 2021-04-16 | 山东鲁能软件技术有限公司 | Power transmission and transformation project exploitable estimation simulation group price method and device |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110837936A (en) * | 2019-11-12 | 2020-02-25 | 哈尔滨学院 | Community adjustable load power utilization optimization method based on ant colony algorithm |
| CN112669055A (en) * | 2020-12-15 | 2021-04-16 | 山东鲁能软件技术有限公司 | Power transmission and transformation project exploitable estimation simulation group price method and device |
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