CN110020742A - A kind of industrial user source lotus stores up demand response optimization method and equipment - Google Patents
A kind of industrial user source lotus stores up demand response optimization method and equipment Download PDFInfo
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- CN110020742A CN110020742A CN201811592877.9A CN201811592877A CN110020742A CN 110020742 A CN110020742 A CN 110020742A CN 201811592877 A CN201811592877 A CN 201811592877A CN 110020742 A CN110020742 A CN 110020742A
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- 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
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
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- 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
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- G06Q10/067—Enterprise or organisation modelling
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- G—PHYSICS
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
The application provides a kind of industrial user source lotus storage demand response optimization method and equipment, wherein method includes: and establishes industrial user to cooperate with optimal operation model based on the multi-source of more tariff period, the moving model is constrained to constraint condition using industrial user's electric cost as objective function, with power plant for self-supply's constraint, the constraint of transferable part throttle characteristics, energy storage device operation；Electric power data is inputted into moving model and solves, obtain and exports response results of the industrial user under Peak-valley TOU power price.The application is by the multi-source collaboration optimization operation based on more tariff period, so that industrial user's peak load shifting effect is obvious, peak period load decreases, and low-valley interval load increased.Itself load curve is more original more gentle, reduces a possibility that itself load brings impulse to power grid, more friendly to power grid.Industrial user can not only save the electric cost of itself, improve its load curve, can also effectively responsive electricity grid demand, demand response potentiality are larger.
Description
Technical field
This application involves Operation of Electric Systems optimisation technique fields more particularly to a kind of industrial user source lotus storage demand to ring
Answer optimization method and equipment.
Background technique
Electric energy is the essential energy of high energy-consuming enterprises's production process, as the large electricity consumer of location, highly energy-consuming
Business electrical can have an important influence on area power grid.In order to make full use of the resource for being located at Demand-side, to improve electric system
Economy and safety, power grid studies and implements many demand response projects.Under normal circumstances due to industrial processes
It can not be interrupted, the demand response project based on price is commonly used for industrial user, and most common of them is peak and valley time electricity
Valence guides the spontaneous carry out power consumption management of user giving different periods electricity consumption in a manner of different electricity prices.Industrial user couple
There is demand elasticity there are different degrees of response in different prices, in the research about user oriented Peak-valley TOU power price
In, establish the incidence relation between different periods electricity rates and user power utilization demand more.Since the electricity consumption of industrial user is special
Property, this incidence relation generally can not be modeled simply, but be analyzed by the part throttle characteristics to industrial user, with
Peak-valley TOU power price is input, right according to constraint conditions such as its part throttle characteristics using industrial user's electric cost as objective function
The power consumption management optimization of industrial user is modeled and is solved, and finally exports response of the industrial user under Peak-valley TOU power price
As a result.
To improve comprehensive utilization rate of energy source and reducing electric cost, the industrial user of highly energy-consuming generally has installed capacity
With the comparable power plant for self-supply of itself load level.And electric energy needed for having the production process of the industrial user of power plant for self-supply is by providing for oneself
Power plant and power grid supply simultaneously, so as to form dual power supply mode, impart high energy-consuming enterprises and flexibly respond electricity price variation
Ability, and the electric cost and peak demand of enterprise can be significantly reduced.In addition, some industrial users provide for oneself in outfit
While power plant, in order to flexibly arrange power generation dispatching, it can also consider to configure energy storage device.Energy storage device can generate electricity
Electric energy is stored when cost is relatively low and electricity price is lower, electric energy is discharged to fast and flexible in peak of power consumption, is realized to peak valley
The response of tou power price.Under the tou power price that power grid gives, the purpose of high energy-consuming enterprises's electric energy management is to reduce electricity consumption
Cost.Self power generation scheduling, load transfer and energy storage response are the measures of common response electricity price signal.
In existing industrial user's demand response technical solution, power generation dispatching is mutually separated with electricity consumption scheduling, and does not consider energy storage
The responding ability and response policy of device.
Summary of the invention
This application provides a kind of industrial user source lotus storage demand response optimization method and equipment, can be according to industrial user
Load characteristic optimizes power generation, storage, electricity consumption strategy, and total electric cost of industrial user is reduced according to optimization algorithm.
In view of this, the application first aspect provides a kind of industrial user source lotus storage demand response optimization method, packet
It includes:
It establishes industrial user and optimal operation model is cooperateed with based on the multi-source of more tariff period, the moving model is with industry
User power utilization cost is objective function, is constrained to power plant for self-supply's constraint, the constraint of transferable part throttle characteristics, energy storage device operation
Constraint condition；
Electric power data is inputted into moving model and solves, obtain and exports sound of the industrial user under Peak-valley TOU power price
Answer result.
Preferably, the objective function of the moving model are as follows:
min Ctotal
Wherein, PbkIt is the purchase of electricity of period k；PskThe electricity sales amount of period k；PgkIt is the generated energy of period k；For electricity
Electricity price of the net in block of purchase electricity k；For the rate for incorporation into the power network of sale of electricity period k；For the unit cost of electricity-generating of period k；It is
The load cost of transfer of task m；smAt the beginning of being task m.
Preferably, power plant for self-supply's constraint of the moving model are as follows:
Wherein, PbkIt is the purchase of electricity of period k；PskThe electricity sales amount of period k；PgkIt is the generated energy of period k, PbminFor purchase
Electricity lower limit value, PbmaxFor purchase of electricity upper limit value, PsminFor electricity sales amount lower limit value, PsmaxFor electricity sales amount upper limit value, PgminFor hair
Electricity lower limit value, PgmaxFor generated energy upper limit value.
Preferably, the transferable part throttle characteristics constraint of the moving model are as follows:
Wherein,It is the start periods mark of task m；It is the processing completion time used for them mark of task m；TmIt is m-th
The continuous working period of business；WithThe respectively maximum and minimum value of task m time started；smIt is the beginning of task m
Time.
Preferably, the energy storage device of the moving model runs constraint are as follows:
Wherein, PbkIt is the purchase of electricity of period k；PskThe electricity sales amount of period k；PgkIt is the generated energy of period k；For power grid
In the electricity price of block of purchase electricity k；For the rate for incorporation into the power network of sale of electricity period k；For the unit cost of electricity-generating of period k；It is to appoint
The load cost of transfer of business m；smAt the beginning of being task m；For the base load of period k；For turning for period k
Move load；It is the start periods mark of task m；It is the processing completion time used for them mark of task m；It is task m (k+
1) mark of period；It is charge power of the energy storage device in period k；It is electric discharge function of the energy storage device in period k
Rate； CmaxIt is the maximum capacity of energy-storage system；It is energy-storage system maximum charge power；It is the electric discharge of energy-storage system maximum
Power；nchIt is the charge efficiency of energy storage device；ndchIt is the discharging efficiency of energy storage device.
Preferably, it is described establish industrial user based on more tariff period multi-source collaboration optimal operation model before also wrap
It includes:
Determine the auxiliary variable in industrial user's demand response model: storage capacity when energy storage starts mounted in period k
Ck, the start periods mark of task mWith processing completion time used for them markFor 0-1 variable；
Wherein,Expression task m start in period k or period k in front of have begun,Expression task
M in period k or in period k before do not start, and the latter period mark be more than or equal to the previous period mark, andExpression task m terminate in period k or period k in front of be over,Expression task m in period k or
It is also not finished before in period k, and the mark of latter period is less than or equal to the mark of previous period, thenIntermediate value
The period that expression task m is carried out can be corresponded to by 1 column.
Preferably, it is described establish industrial user based on more tariff period multi-source collaboration optimal operation model before also wrap
It includes:
Determine the main decision variables in industrial user's demand response model: the purchase of electricity Pb of period kk, generated energy PgkWith
Electricity sales amount Psk, the charge power of energy storage device day partAnd discharge powerS at the beginning of task mm。
The application second aspect provides a kind of industrial user source lotus storage demand response optimization equipment, and the equipment includes place
Manage device and memory:
Said program code is transferred to the processor for storing program code by the memory；
The processor is used to store up need according to the industrial user source lotus of the instruction execution first aspect in said program code
Seek response optimization method.
The application third aspect provides a kind of computer readable storage medium, and the computer readable storage medium is used for
Program code is stored, said program code is used to execute the industrial user source lotus storage demand response optimization method of first aspect.
The application fourth aspect provides a kind of computer program product including instruction, when run on a computer,
So that the industrial user source lotus that the computer executes first aspect stores up demand response optimization method.
As can be seen from the above technical solutions, the application has the following advantages:
The application provides a kind of industrial user source lotus storage demand response optimization method and equipment, and wherein method includes: to establish
Industrial user cooperates with optimal operation model based on the multi-source of more tariff period, and the moving model is with industrial user's electric cost
For objective function, constraint condition is constrained to power plant for self-supply's constraint, the constraint of transferable part throttle characteristics, energy storage device operation；It will be electric
Force data input moving model simultaneously solves, obtain and exports response results of the industrial user under Peak-valley TOU power price.The application
By the multi-source collaboration optimization operation based on more tariff period, so that industrial user's peak load shifting effect is obvious, peak period is negative
Lotus decreases, and low-valley interval load increased.Itself load curve is more original more gentle, reduce itself load to
Power grid brings a possibility that impulse, more friendly to power grid.Industrial user can make full use of low ebb electricity price to produce, can be with
Commercial power and residential electricity consumption carry out complementation in this feature on daytime mostly, keep power grid integral load curve gentler.Industry
User can not only save the electric cost of itself, improve its load curve, can also effectively responsive electricity grid demand, demand
It is larger to respond potentiality.
Detailed description of the invention
In ord to more clearly illustrate embodiments of the present application, will make below to required in embodiment or description of the prior art
Attached drawing is briefly described, it should be apparent that, the drawings in the following description are only some examples of the present application, right
For those of ordinary skill in the art, without any creative labor, it can also be obtained according to these attached drawings
Other attached drawings.
Fig. 1 is showing for one embodiment that a kind of industrial user source lotus provided by the present application stores up demand response optimization method
It is intended to.
Fig. 2 is that a kind of industrial user source lotus provided by the present application stores up industrial user source Chu He in demand response optimization method
System construction drawing.
Specific embodiment
This application provides a kind of industrial user source lotus storage demand response optimization method and equipment, can be according to industrial user
Load characteristic optimizes power generation, storage, electricity consumption strategy, and total electric cost of industrial user is reduced according to optimization algorithm.
To enable present invention purpose, feature, advantage more obvious and understandable, below in conjunction with this Shen
Please attached drawing in embodiment, the technical scheme in the embodiment of the application is clearly and completely described, it is clear that is retouched below
The embodiment stated is only some embodiments of the present application, and not all embodiment.Based on the embodiment in the application, originally
Field those of ordinary skill all other embodiment obtained without making creative work, belongs to this Shen
The range that please be protect.
Referring to Fig. 1, an a kind of implementation of industrial user source lotus storage demand response optimization method provided by the present application
Example, comprising:
101, it establishes industrial user and optimal operation model is cooperateed with based on the multi-source of more tariff period, moving model is with industry
User power utilization cost is objective function, is constrained to power plant for self-supply's constraint, the constraint of transferable part throttle characteristics, energy storage device operation
Constraint condition；
102, electric power data is inputted into moving model and solves, obtain and exports industrial user under Peak-valley TOU power price
Response results.
It should be noted that electric power data, which is inputted moving model and solved, can pass through the Optimization Solutions such as particle swarm algorithm
Algorithm, details are not described herein again.Response results of the industrial user under Peak-valley TOU power price are the solution of objective function independent variable.Mesh
Scalar functions seek its extreme value with the minimum target of industrial user's electric cost under constraint condition, obtain industry by solving model
Response results of the user under Peak-valley TOU power price.
The operation principle of the present invention is that: industrial user source lotus storage optimization response method is based on Peak-valley TOU power price, leads to
It crosses and the part throttle characteristics of industrial user is analyzed, consider power plant for self-supply, transferable load (containing adjustable load), energy storage dress
Common participation demand response is set, using industrial user's electric cost as objective function, is constrained according to its power plant for self-supply, is transferable negative
The constraint conditions such as the constraint of lotus characteristic, energy storage device operation constraint are modeled and are asked to the power consumption management optimization of industrial user
Solution finally exports response results of the industrial user under Peak-valley TOU power price.
Compared with prior art, the invention has the benefit that industrial user source storage lotus optimizes response method for three
Kind demand response resource, which is uniformly set up, has the industrial of power plant for self-supply, transferable load and energy storage based on electricity price signal
Family demand response model, and optimization operation is cooperateed with based on the multi-source of more tariff period, so that industrial user's peak load shifting effect is bright
Aobvious, peak period load decreases, and low-valley interval load increased.Itself load curve is more original more gentle, reduces
A possibility that itself load brings impulse to power grid, it is more friendly to power grid.Industrial user can make full use of low ebb electricity price into
Row production, can be mostly complementary in this feature progress on daytime with commercial power and residential electricity consumption, makes power grid integral load curve more
Add gentle.Industrial user can not only save the electric cost of itself, improve its load curve, can also effectively responsive electricity grid
Demand, demand response potentiality are larger.
It should be noted that the application can be applied to industrial user source storage G system.Store up G system structure in industrial user source
As shown in Fig. 2, system includes self-supply power plant, transferable load, base load, energy-storage system, factory and interconnecting ties.
Power plant for self-supply is connected to the grid by transformer, and energy storage is connect by inverter with power grid, power plant for self-supply, transferable load and storage
It can the achievable response to Peak-valley TOU power price of system.
Further, modeled using discrete-time system, will be divided within one day n period, when each period a length of h, if work
Industry user shares m task, with the minimum target of total electric cost of user, the objective function of moving model are as follows:
min Ctotal
Wherein, PbkIt is the purchase of electricity of period k；PskThe electricity sales amount of period k；PgkIt is the generated energy of period k；For power grid
In the electricity price of block of purchase electricity k；For the rate for incorporation into the power network of sale of electricity period k；For the unit cost of electricity-generating of period k；It is to appoint
The load cost of transfer of business m；smAt the beginning of being task m.
According to objective function it is found that response results of the industrial user under Peak-valley TOU power price are PbkIt is the purchase of period k
Electricity；PskThe electricity sales amount of period k；PgkIt is the generated energy of period k.
Further, (the power autonomous power generation of user purchases the decision variable of sale of electricity about for power plant for self-supply's constraint of moving model
Beam condition) are as follows:
Wherein, PbkIt is the purchase of electricity of period k；PskThe electricity sales amount of period k；PgkIt is the generated energy of period k, PbminFor purchase
Electricity lower limit value, PbmaxFor purchase of electricity upper limit value, PsminFor electricity sales amount lower limit value, PsmaxFor electricity sales amount upper limit value, PgminFor hair
Electricity lower limit value, PgmaxFor generated energy upper limit value.
Each decision variable should meet the constraint condition of corresponding own physical characteristic；
Further, the transferable part throttle characteristics constraint (decision variable of transferable flexible load response of moving model
Constraint condition) are as follows:
Wherein,It is the start periods mark of task m；It is the processing completion time used for them mark of task m；TmIt is m-th
The continuous working period of business；WithThe respectively maximum and minimum value of task m time started；smIt is the beginning of task m
Time.
Further, the demand response process of energy storage device need to meet following stored energy capacitance limitation, charge power limits,
The constraint conditions such as discharge power limitation, energy balance limitation.Therefore energy storage device operation constraint (the energy storage response of moving model
The decision variable constraint condition of model) are as follows:
Wherein, PbkIt is the purchase of electricity of period k；PskThe electricity sales amount of period k；PgkIt is the generated energy of period k；For electricity
Electricity price of the net in block of purchase electricity k；For the rate for incorporation into the power network of sale of electricity period k；For the unit cost of electricity-generating of period k；It is
The load cost of transfer of task m；smAt the beginning of being task m；For the base load of period k；For period k can
Transfer load；It is the start periods mark of task m；It is the processing completion time used for them mark of task m；It is task m (k
+ 1) mark of period；It is charge power of the energy storage device in period k；It is electric discharge of the energy storage device in period k
Power； CmaxIt is the maximum capacity of energy-storage system；It is energy-storage system maximum charge power；It is that energy-storage system maximum is put
Electrical power；nchIt is the charge efficiency of energy storage device；ndchIt is the discharging efficiency of energy storage device.
Further, before establishing industrial user based on the multi-source collaboration optimal operation model of more tariff period further include:
Determine the auxiliary variable in industrial user's demand response model: storage capacity when energy storage starts mounted in period k
Ck, the start periods mark of task mWith processing completion time used for them markFor 0-1 variable；
Wherein,Expression task m start in period k or period k in front of have begun,Expression task
M in period k or in period k before do not start, and the latter period mark be more than or equal to the previous period mark, andExpression task m terminate in period k or period k in front of be over,Expression task m in period k or
It is also not finished before in period k, and the mark of latter period is less than or equal to the mark of previous period, thenIntermediate value
The period that expression task m is carried out can be corresponded to by 1 column.
Further, before establishing industrial user based on the multi-source collaboration optimal operation model of more tariff period further include:
Determine the main decision variables in industrial user's demand response model: the purchase of electricity Pb of period kk, generated energy PgkWith
Electricity sales amount Psk, the charge power of energy storage device day partAnd discharge powerS at the beginning of task mm。
It should be noted that calculating the response cost c of user side energy storage devicedr, including industrial user's configuration energy storage device
One-time fix cost of investment cin, energy storage device operation expense cop, energy caused by energy storage device efficiency for charge-discharge
Lose bring cost cη。
Energy storage device efficiency for charge-discharge is η, responds electricity W to day part energy storage deviceiWith corresponding period electricity price piMultiply
Product summation, multiplied by coefficientObtain energy loss bring cost c caused by energy storage device efficiency for charge-dischargeη。
To sum up, the response cost of user side energy storage device is
Energy storage device response model is indicated with storage capacity, charge power and discharge power.If one day is divided into N number of
Period, when each period a length of h, stored energy capacitance C when being started according to period kk, charge power of the energy storage device in period kAnd discharge powerThe charge efficiency n of energy storage devicechWith discharging efficiency ndch, obtain subsequent period, i.e. the k+1 period
Stored energy capacitance Ck+1, then the intraday response model of energy storage device
And power plant for self-supply's response model, transferable load responding model can use P=f (Pgk, Pbk, Psk) form indicate,
Details are not described herein again.
Be above to a kind of industrial user source lotus provided by the present application storage demand response optimization method one embodiment into
It is detailed will to provide the application a kind of storage demand response optimization equipment progress of industrial user source lotus below for the detailed description of row
Description.
The application provides a kind of industrial user source lotus storage demand response optimization equipment, and equipment includes processor and storage
Device:
Program code is transferred to processor for storing program code by memory；
Processor is used to store up demand response according to the industrial user source lotus of instruction execution above-described embodiment in program code
Optimization method.
The application provides a kind of computer readable storage medium, and computer readable storage medium is used to store program code,
Program code is used to execute the industrial user source lotus storage demand response optimization method of above-described embodiment.
The application provides a kind of computer program product including instruction, when run on a computer, so that calculating
Machine executes the industrial user source lotus storage demand response optimization method of above-described embodiment.
The above, above embodiments are only to illustrate the technical solution of the application, rather than its limitations；Although reference
The application is described in detail in previous embodiment, those skilled in the art should understand that: it still can be right
Technical solution documented by foregoing embodiments is modified or equivalent replacement of some of the technical features；And this
It modifies or replaces, the spirit and model of each embodiment technical solution of the application that it does not separate the essence of the corresponding technical solution
It encloses.
Claims (10)
1. a kind of industrial user source lotus stores up demand response optimization method characterized by comprising
It establishes industrial user and optimal operation model is cooperateed with based on the multi-source of more tariff period, the moving model is used with industrial user
Electric cost is objective function, is constrained to constraint item with power plant for self-supply's constraint, the constraint of transferable part throttle characteristics, energy storage device operation
Part；
Electric power data is inputted into moving model and solves, obtain and exports response knot of the industrial user under Peak-valley TOU power price
Fruit.
2. a kind of industrial user source lotus according to claim 1 stores up demand response optimization method, which is characterized in that the fortune
The objective function of row model are as follows:
min Ctotal
Wherein, PbkIt is the purchase of electricity of period k；PskThe electricity sales amount of period k；PgkIt is the generated energy of period k；It is being purchased for power grid
The electricity price of electric period k；For the rate for incorporation into the power network of sale of electricity period k；For the unit cost of electricity-generating of period k；It is task m
Load cost of transfer；smAt the beginning of being task m.
3. a kind of industrial user source lotus according to claim 1 stores up demand response optimization method, which is characterized in that the fortune
The power plant for self-supply of row model constrains are as follows:
Wherein, PbkIt is the purchase of electricity of period k；PskThe electricity sales amount of period k；PgkIt is the generated energy of period k, PbminFor under purchase of electricity
Limit value, PbmaxFor purchase of electricity upper limit value, PsminFor electricity sales amount lower limit value, PsmaxFor electricity sales amount upper limit value, PgminFor under generated energy
Limit value, PgmaxFor generated energy upper limit value.
4. a kind of industrial user source lotus according to claim 1 stores up demand response optimization method, which is characterized in that the fortune
The transferable part throttle characteristics of row model constrains are as follows:
Wherein,It is the start periods mark of task m；It is the processing completion time used for them mark of task m；TmIt is holding for m-th of task
The continuous working time；WithThe respectively maximum and minimum value of task m time started；smAt the beginning of being task m.
5. a kind of industrial user source lotus according to claim 1 stores up demand response optimization method, which is characterized in that the fortune
The energy storage device of row model runs constraint are as follows:
Wherein, PbkIt is the purchase of electricity of period k；PskThe electricity sales amount of period k；PgkIt is the generated energy of period k；It is being purchased for power grid
The electricity price of electric period k；For the rate for incorporation into the power network of sale of electricity period k；For the unit cost of electricity-generating of period k；It is task m
Load cost of transfer；smAt the beginning of being task m；For the base load of period k；For the transferable negative of period k
Lotus；It is the start periods mark of task m；It is the processing completion time used for them mark of task m；It is task m (k+1) period
Mark；It is charge power of the energy storage device in period k；It is discharge power of the energy storage device in period k；Cmax
It is the maximum capacity of energy-storage system；It is energy-storage system maximum charge power；It is energy-storage system maximum discharge power；nch
It is the charge efficiency of energy storage device；ndchIt is the discharging efficiency of energy storage device.
6. a kind of industrial user source lotus according to claim 1 stores up demand response optimization method, which is characterized in that described to build
Vertical industrial user is cooperateed with based on the multi-source of more tariff period before optimal operation model further include:
Determine the auxiliary variable in industrial user's demand response model: storage capacity C when energy storage starts mounted in period kk, task m
Start periods markWith processing completion time used for them markFor 0-1 variable；
Wherein,Expression task m start in period k or period k in front of have begun,Expression task m exists
Do not start before in period k or in period k, and the mark of latter period is more than or equal to the mark of previous period, andTable
Show task m terminate in period k or period k in front of be over,Expression task m in period k or in period k it
It is preceding to be also not finished, and the mark of latter period is less than or equal to the mark of previous period, thenThe column that intermediate value is 1 can
The period that corresponding expression task m is carried out.
7. a kind of industrial user source lotus according to claim 1 stores up demand response optimization method, which is characterized in that described to build
Vertical industrial user is cooperateed with based on the multi-source of more tariff period before optimal operation model further include:
Determine the main decision variables in industrial user's demand response model: the purchase of electricity Pb of period kk, generated energy PgkAnd sale of electricity
Measure Psk, the charge power of energy storage device day partAnd discharge powerS at the beginning of task mm。
8. a kind of industrial user source lotus, which stores up demand response, optimizes equipment, which is characterized in that the equipment includes processor and deposits
Reservoir:
Said program code is transferred to the processor for storing program code by the memory；
The processor is used for according to the described in any item industrial users of instruction execution claim 1-7 in said program code
Source lotus stores up demand response optimization method.
9. a kind of computer readable storage medium, which is characterized in that the computer readable storage medium is for storing program generation
Code, said program code require the described in any item industrial user source lotuses of 1-7 to store up demand response optimization method for perform claim.
10. a kind of computer program product including instruction, which is characterized in that when run on a computer, so that described
Computer perform claim requires the described in any item industrial user source lotuses of 1-7 to store up demand response optimization method.
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