CN107069791B - A kind of integration requirement response method for considering industrial park and being interacted with factory - Google Patents
A kind of integration requirement response method for considering industrial park and being interacted with factory Download PDFInfo
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- CN107069791B CN107069791B CN201710461438.3A CN201710461438A CN107069791B CN 107069791 B CN107069791 B CN 107069791B CN 201710461438 A CN201710461438 A CN 201710461438A CN 107069791 B CN107069791 B CN 107069791B
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- 230000010354 integration Effects 0.000 title claims abstract description 17
- 238000000034 method Methods 0.000 title claims abstract description 15
- 230000003993 interaction Effects 0.000 claims abstract description 9
- 240000002853 Nelumbo nucifera Species 0.000 claims abstract description 3
- 235000006508 Nelumbo nucifera Nutrition 0.000 claims abstract description 3
- 235000006510 Nelumbo pentapetala Nutrition 0.000 claims abstract description 3
- 230000005611 electricity Effects 0.000 claims description 23
- 238000004146 energy storage Methods 0.000 claims description 22
- 238000005057 refrigeration Methods 0.000 claims description 18
- 210000000582 semen Anatomy 0.000 claims description 13
- 238000001816 cooling Methods 0.000 claims description 12
- 238000007599 discharging Methods 0.000 claims description 7
- 238000009825 accumulation Methods 0.000 claims description 3
- 238000000048 melt cooling Methods 0.000 claims description 3
- 230000015572 biosynthetic process Effects 0.000 claims 1
- 238000003786 synthesis reaction Methods 0.000 claims 1
- 241000196324 Embryophyta Species 0.000 abstract description 3
- 230000002457 bidirectional effect Effects 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 230000002595 cold damage Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000005265 energy consumption Methods 0.000 description 2
- 238000010248 power generation Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
Classifications
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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
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
-
- 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
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P80/00—Climate change mitigation technologies for sector-wide applications
- Y02P80/10—Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier
Abstract
The invention discloses a kind of integration requirement response methods that consideration industrial park is interacted with factory.This method builds the integrated energy system model of factory first, under conditions of considering that user power utilization satisfaction and system loading fluctuate, using user power utilization cost minimization as target, building considers factory from the IDR model for becoming excellent, the excellent scheduling that becomes certainly for realizing factory, as the basis for participating in interaction.Secondly, industrial park scheduling and plant control system information interaction, entire garden level further excavate with using garden Nei Ge factory source, storage, lotus distributed resource controllable ability, with garden critical point power is not out-of-limit and user is with can cost is minimum establishes the IDR model for considering that industrial park is interacted with factory, response higher level's power grid demand.
Description
Technical field
The present invention relates to a kind of integration requirement responses that consideration industrial park is interacted with factory, belong to comprehensive energy and electric power
Demand response field.
Background technique
Under energy Background of Internet, decentralized energy market and energy network structure ring traditional electricity needs
Answer (demand response, DR) will be gradually to integration requirement response (integrated demand response, IDR)
Direction is developed.And industrial park is constantly increased with its energy demand, variety of energy sources is more, energy resource structure is unreasonable, conventional energy resource storage
The features such as standby amount reduces, energy utilization rate is universal relatively low, peak valley electric power load difference volume is big, becomes the good platform of IDR implementation.And
If only considering the excellent operation that becomes certainly of factory in industrial park, it is likely to occur new load peak, is unsatisfactory for higher level's power grid
Peak regulation demand.Therefore, research considers the integration requirement response policy that industrial park is interacted with factory, is guaranteeing higher level's peak load regulation network
The optimized operation that inside plants are realized on the basis of demand, it is comprehensive to the interaction and future of realizing polynary user in industrial park
Popularization of the energy resource system in industrial user field has important directive significance.
Summary of the invention
In order to overcome the above-mentioned deficiencies of the prior art, the present invention provides a kind of consideration industrial park interacted with factory it is comprehensive
Close demand response method.This method builds the integrated energy system model of factory first, is considering user power utilization satisfaction and is being
It unites under conditions of load fluctuation, using user power utilization cost minimization as target, building considers that factory from the IDR model for becoming excellent, realizes
The excellent scheduling that becomes certainly of factory, as the basis for participating in interaction.Secondly, information is handed between industrial park scheduling and plant control system
Mutually, entire garden level further excavate with using garden Nei Ge factory source, storage, lotus distributed resource controllable energy
Power, with garden critical point power is not out-of-limit and user with can cost is minimum establishes the IDR model for considering that industrial park is interacted with factory,
Respond higher level's power grid demand.This method can be applied in different types of industrial park integrated energy system.
The purpose of the present invention is achieved through the following technical solutions: a kind of consideration industrial park interacts comprehensive with factory
Demand response method is closed, method includes the following steps:
Step 1: building the integrated energy system model of factory, building considers that factory from the IDR model for becoming excellent, realizes factory
The economic optimum operation of itself；
Step 2: factory uploads from the critical point power curve of Qu Youhou factory to garden Energy Management System, by garden energy
Management system carries out the out-of-limit assessment of power, determines whether peak clipping demand；
Step 3: if the out-of-limit risk of inactivity, by becoming certainly, excellent result is run；Industry park is carried out if emergent power is out-of-limit
The integration requirement response that area is interacted with factory, realizes good interaction with higher level's power grid；It is comprehensive to consider that industrial park is interacted with factory
The objective function for closing demand response model is to maximize to meet peak clipping demand, while minimizing electric cost as far as possible:
In formula, t0-t1For peak clipping period, P0(t) the peak clipping object reference power of entire garden, P0(t)=P (t)-Δ P0
(t), P (t) is factory's critical point power after becoming excellent certainly for the first time, Δ P0(t) peak clipping is needed for the garden that entire garden issues
Power；It P'(t is) factory's critical point power of period t after update, C'ATCFor the overall running cost of factory after update, λ1,λ2For target
The weight coefficient of peak clipping target and economy objectives in function, wherein λ1> > λ2；
Constraint condition: compared to the IDR for considering that factory becomes excellent certainly, when newly increasing critical point power constraint of non-peak clipping period and peak clipping
Section peak clipping upper limit of the power constraint, corestriction are identical；
A) critical point power constraint of non-peak clipping period:
P'(t)≤P1(t)
Wherein P1It (t) is the critical point power constraint of the non-peak clipping period issued from garden, t is the non-peak clipping period；
B) the peak clipping period peak clipping upper limit of the power constrains:
P(t)-P'(t)≤ΔP0(t)
The constraint of the peak clipping upper limit of the power refers to that user provides peak clipping amount and is no more than garden requirement peak clipping amount.
Further, consider in the step 1 factory from the objective function of the IDR model that becomes excellent be whole day total electricity bill about
Beam:
In formula, t be period serial number, n be the whole day period sum, C (t) be period t tou power price, P (t) be period t from
The output power that major network obtains, T are unit Period Length；
Constraint condition are as follows:
A) DC power supply and AC power source
General power Constraints of Equilibrium:
P (t)=PAC-load(t)+PAC-DC(t)+Pi(t)-P'i(t)+PCT(t)
PAC-load(t) AC load for being period t, PAC-DCIt (t) is the power of AC/DC changeover switch；PiIt (t) is Ice Storage Tank
Power consumption, P'i(t) cooling load, ∑ P' are undertaken for Ice Storage Tanki(t)=∑ Pi(t) * η, η are cooling efficiency (since there are cold damages
Lose), the P when Ice Storage Tank cold storage of ice makingi(t) > 0, the P' when Ice Storage Tank ice-melt cooling supplyi(t)>0；PCTIt (t) is cooling tower power consumption,
PCT(t)=0.025* (Qk(t)+Pk(t)), wherein QkIt (t) is refrigeration machine semen donors, PkIt (t) is refrigeration machine power consumption, Qk(t)=
Pk(t)*EER；EER is refrigeration machine Energy Efficiency Ratio, can be fitted to obtain by refrigeration unit operating parameter；
AC/DC changeover switch efficiency constraints:
In formula: ηA/DTo exchange the transfer efficiency for being converted to direct current, ηD/AThe transfer efficiency of exchange, P are converted into for direct currentDC
(t) the DC bus total load for being period t；
The constraint of DC bus total load:
PDC(t)+PPV(t)=PDC-load(t)+PB(t)
PPVIt (t) is photovoltaic generation power, PDC-loadIt (t) is DC load, PBIt (t) is power of the energy-storage battery in period t,
P when chargingB(t) > 0, P when electric dischargeB(t)<0；
Load fluctuation constraint:
In order to limit the fluctuation of system loading after integration requirement responds, does not increase the difficulty of electric system side scheduling, introduce
Load fluctuation constraint:
λ is the geometric mean of load active power, proportionality coefficient k1And k2It is provided according to specific actual conditions and experience, and
Using load fluctuation rate l as the standard for judging load fluctuation；Wherein:
L=σ/λ
L is defined as the ratio between the standard deviation sigma of load active power and the geometric mean λ of load active power；
B) constraint of equipment and Energy Sources Equilibrium
Discharging efficiency constraint:
For maximum charge efficiency,For maximum discharging efficiency；
The constraint of energy-storage battery state of charge:
Emin≤EB(t)≤Emax
Emin=SOCminR
Emax=SOCmaxR
EmaxFor energy-storage battery maximum electricity, EminFor the minimum electricity of energy-storage battery, EB(t) the battery energy storage shape for being period t
State；SOCminAnd SOCmaxFor minimum and maximum state-of-charge, R is battery capacity；
At any time, the gross energy of energy storage is the summation of energy storage primary power and cumlative energy:
E (0) is battery initial quantity of electricity, and E (t) is the accumulation electricity of period t, and i is the when number of segment of whole day charging；
Daily electricity giant ties:
Cold-storage device constraint:
Wherein, QkmaxFor refrigeration unit maximum semen donors, QiIt (t) is Ice Storage Tank semen donors, QimaxFor Ice Storage Tank maximum cooling supply
Amount, Qsys(t) system needs semen donors, and QI is ice-reserving tankage.
Compared with prior art, the beneficial effects of the present invention are: on the one hand, various energy resources cooperative compensating guides user's system
Fixed reasonable comprehensive energy Utilization plan, improves the energy consumption efficiency of user side, and reducing using for user can cost；On the other hand,
By the collaboration of entire garden level distributed resource and controllable burden, the ancillary services such as peak clipping are provided for higher level's power grid, can be shown
It writes and promotes power grid asset utilization rate.The present invention is suitable for different types of industrial park integrated energy system.
Detailed description of the invention
Fig. 1 is typical factory integration energy resource system schematic diagram；
The IDR strategy that the industrial park Tu2Wei is interacted with factory.
Specific embodiment
The following further describes the present invention with reference to the drawings.
Typical factory integration energy resource system schematic diagram is as shown in Figure 1, by m group photovoltaic generating system, battery and/or directly
Stream load is respectively coupled on m DC bus, is connected by bidirectional converter with public ac bus, is matched on ac bus
Cold-storage device.Power distribution network is accessed by transformer by ac bus again.The system can both meet DC load demand, can also meet
AC load demand.Whole system is divided into DC power supply, DC load and AC power source, AC load.Local
DC bus is used to be connected with DC energy source equipment, and is connect by a bidirectional transducer with AC system.This structure makes
Obtain the energy that battery and DC load can be exported before AC and DC conversion using photovoltaic.When by eliminating AC-DC conversion
Unnecessary energy loss, users can save the electricity charge using tou power price, may also participate in Demand Side Response to mitigate
Power grid pressure.
First with common user's alternating current-direct current load, refrigeration duty and photovoltaic power generation prediction technique, load to next day and
Photovoltaic and wind-power electricity generation are predicted.
Prediction result and electricity price information based on alternating current-direct current load, refrigeration duty and photovoltaic power generation, it is minimum with total electricity bill
Target, charging and discharging state and refrigeration machine, the distribution of Ice Storage Tank refrigeration duty to electric energy storage establish Optimized model.The target of Optimized model
Function is the constraint of whole day total electricity bill.
In formula, t is period serial number, and n is whole day period sum, n desirable 96.C (t) is the tou power price of period t.P (t) is
The output power that period t is obtained from major network, T is unit Period Length, when n takes 96, T=0.25h.
Constraint condition are as follows:
A) DC power supply and AC power source
General power Constraints of Equilibrium:
P (t)=PAC-load(t)+PAC-DC(t)+Pi(t)-P'i(t)+PCT(t)
PAC-load(t) AC load for being period t, PAC-DCIt (t) is the power of AC/DC changeover switch.PiIt (t) is Ice Storage Tank
Power consumption, P'i(t) cooling load, ∑ P' are undertaken for Ice Storage Tanki(t)=∑ Pi(t) * η, η are cooling efficiency (since there are cold damages
It loses).When Ice Storage Tank cold storage of ice making, Pi(t)>0；When Ice Storage Tank ice-melt cooling supply, P'i(t)>0。PCTIt (t) is cooling tower power consumption
Amount often uses empirical equation since shared ratio is little in systems for the energy consumption of cooling tower in practical applications:
PCT(t)=0.025* (Qk(t)+Pk(t))
Wherein QkIt (t) is refrigeration machine semen donors, PkIt (t) is refrigeration machine power consumption, Qk(t)=Pk(t)*EER.EER is refrigeration
Machine Energy Efficiency Ratio can be fitted to obtain by refrigeration unit operating parameter.
AC/DC changeover switch efficiency constraints:
In formula: ηA/DTo exchange the transfer efficiency for being converted to direct current, ηD/AThe transfer efficiency of exchange, P are converted into for direct currentDC
(t) the DC bus total load for being period t.
The constraint of DC bus total load:
PDC(t)+PPV(t)=PDC-load(t)+PB(t)
PPVIt (t) is photovoltaic generation power, PDC-loadIt (t) is DC load, PBIt (t) is power of the energy-storage battery in period t,
P when chargingB(t) > 0, P when electric dischargeB(t)<0。
Load fluctuation constraint:
In order to limit the fluctuation of system loading after integration requirement responds, does not increase the difficulty of electric system side scheduling, introduce
Load fluctuation constraint:
λ is the geometric mean of load active power, proportionality coefficient k1And k2It is provided according to specific actual conditions and experience, it can
Take k1=0.1, k2=0.15, and using load fluctuation rate l as the standard for judging load fluctuation；Wherein:
L=σ/λ
Load fluctuation rate l is defined as the ratio between the standard deviation sigma of load active power and the geometric mean λ of load active power.
B) constraint of equipment and Energy Sources Equilibrium
Discharging efficiency constraint:
For maximum charge efficiency,For maximum discharging efficiency.
The constraint of energy-storage battery state of charge:
Emin≤EB(t)≤Emax
Emin=SOCminR
Emax=SOCmaxR
EmaxFor energy-storage battery maximum electricity, EminFor the minimum electricity of energy-storage battery, EB(t) the battery energy storage shape for being period t
State.SOCminAnd SOCmaxFor minimum and maximum state-of-charge, R is battery capacity.
At any time, the gross energy of energy storage is the summation of energy storage primary power and cumlative energy:
E (0) is battery initial quantity of electricity, and E (t) is the accumulation electricity of period t, and i is the when number of segment of whole day charging.
Daily electricity giant ties:
Cold-storage device constraint:
Wherein, QkmaxFor refrigeration unit maximum semen donors, QiIt (t) is Ice Storage Tank semen donors, QimaxFor Ice Storage Tank maximum cooling supply
Amount, Qsys(t) system needs semen donors, and QI is ice-reserving tankage.
Factory formulates from after the excellent scheduling strategy that becomes, and will become excellent certainly and be uploaded to garden Energy Management System with energy curve, by garden
Area's Energy Management System carries out the out-of-limit assessment of power, determines whether peak clipping demand.If the out-of-limit risk of inactivity, by the excellent knot that becomes certainly
Fruit operation；The integration requirement response that industrial park is interacted with factory is carried out if emergent power is out-of-limit, is realized with higher level's power grid good
Property interaction.
Consider that the objective function for the integration requirement response model that industrial park is interacted with factory meets peak clipping need to maximize
It asks, while minimizing electric cost as far as possible.
In formula, t0-t1For peak clipping period, P0(t) the peak clipping object reference power of entire garden, P0(t)=P (t)-Δ P0
(t), P (t) is factory's critical point power after becoming excellent certainly for the first time, Δ P0(t) peak clipping is needed for the garden that entire garden issues
Power；It P'(t is) factory's critical point power of period t after update, C'ATCFor the overall running cost of factory after update, λ1,λ2For target
The weight coefficient of peak clipping target and economy objectives in function, wherein λ1λ2；
Constraint condition: compared to the IDR for considering that factory becomes excellent certainly, when newly increasing critical point power constraint of non-peak clipping period and peak clipping
Section peak clipping upper limit of the power constraint, corestriction are identical；
A) critical point power constraint of non-peak clipping period:
P'(t)≤P1(t)
Wherein P1It (t) is the critical point power constraint of the non-peak clipping period issued from garden, t is the non-peak clipping period；
B) the peak clipping period peak clipping upper limit of the power constrains:
P(t)-P'(t)≤ΔP0(t)
The constraint of the peak clipping upper limit of the power refers to that user provides peak clipping amount and is no more than garden requirement peak clipping amount.
Consider that the advantage for the integration requirement response method that industrial park is interacted with factory is: constructing and only consider factory certainly
Become the IDR model of excellent operation, makes switching and cascade utilization of the energy in different levels energy resource system, preferably realizes power grid
Peak load shifting, alleviate power grid pressure.And user is made to possess " the virtual energy unit " of larger capacity, optimize and uses energy behavior, from
And the use for reducing itself can cost.The IDR model for considering that industrial park is interacted with factory is constructed on this basis, and proposes to examine
The IDR for considering user satisfaction compensates quotation form, and while meeting higher level's power grid peak clipping demand, reasonable compensation is to industrial
The influence of family economy and satisfaction promotes the good interaction of higher level's power grid and industrial user.
Claims (2)
1. a kind of integration requirement response method for considering industrial park and being interacted with factory, it is characterised in that: this method includes following
Step:
Step 1: building the integrated energy system model of factory, building considers that factory from the IDR model for becoming excellent, realizes factory itself
Economic optimum operation；
Step 2: factory uploads from the critical point power curve of Qu Youhou factory to garden Energy Management System, by garden energy management
System carries out the out-of-limit assessment of power, determines whether peak clipping demand；
Step 3: if the out-of-limit risk of inactivity, by becoming certainly, excellent result is run；Carried out if emergent power is out-of-limit industrial park with
The integration requirement response of factory's interaction, realizes good interaction with higher level's power grid；The synthesis for considering that industrial park is interacted with factory needs
It asks the objective function of response model to meet peak clipping demand to maximize, while minimizing electric cost as far as possible:
In formula, t0-t1For peak clipping period, P0(t) the peak clipping object reference power of entire garden, P0(t)=P (t)-Δ P0(t), P
It (t) is factory's critical point power for the first time from after becoming excellent, Δ P0(t) power of peak clipping is needed for the garden that entire garden issues；
It P'(t is) factory's critical point power of period t after update, C'ATCFor the overall running cost of factory after update, λ1,λ2For objective function
The weight coefficient of middle peak clipping target and economy objectives, wherein λ1> > λ2；
Constraint condition: it compared to the IDR for considering that factory becomes excellent certainly, newly increases critical point power constraint of non-peak clipping period and the peak clipping period cuts
The constraint of the peak upper limit of the power；
A) critical point power constraint of non-peak clipping period:
P'(t)≤P1(t)
Wherein P1It (t) is the critical point power constraint of the non-peak clipping period issued from garden, t is the non-peak clipping period；
B) the peak clipping period peak clipping upper limit of the power constrains:
P(t)-P'(t)≤ΔP0(t)
The constraint of the peak clipping upper limit of the power refers to that user provides peak clipping amount and is no more than garden requirement peak clipping amount.
2. a kind of integration requirement response method for considering industrial park and being interacted with factory according to claim 1, feature
Be: the objective function that the IDR model that factory becomes excellent certainly is considered in the step 1 is the constraint of whole day total electricity bill:
In formula, t is period serial number, and n is whole day period sum, and C (t) is the tou power price of period t, and P (t) is period t from major network
Obtained output power, T are unit Period Length；
Constraint condition are as follows:
A) DC power supply and AC power source
General power Constraints of Equilibrium:
P (t)=PAC-load(t)+PAC-DC(t)+Pi(t)-P'i(t)+PCT(t)
PAC-load(t) AC load for being period t, PAC-DCIt (t) is the power of AC/DC changeover switch；PiIt (t) is Ice Storage Tank power consumption
Amount, P'i(t) cooling load, ∑ P' are undertaken for Ice Storage Tanki(t)=∑ Pi(t) * η, η are cooling efficiency, when Ice Storage Tank cold storage of ice making
When Pi(t) 0 >, the P' when Ice Storage Tank ice-melt cooling supplyi(t) 0 >；PCTIt (t) is cooling tower power consumption, PCT(t)=0.025* (Qk
(t)+Pk(t)), wherein QkIt (t) is refrigeration machine semen donors, PkIt (t) is refrigeration machine power consumption, Qk(t)=Pk(t)*EER；EER is system
Cold Energy Efficiency Ratio can be fitted to obtain by refrigeration unit operating parameter；
AC/DC changeover switch efficiency constraints:
In formula: ηA/DTo exchange the transfer efficiency for being converted to direct current, ηD/AThe transfer efficiency of exchange, P are converted into for direct currentDC(t) it is
The DC bus total load of period t；
The constraint of DC bus total load:
PDC(t)+PPV(t)=PDC-load(t)+PB(t)
PPVIt (t) is photovoltaic generation power, PDC-loadIt (t) is DC load, PB(t) power for energy-storage battery in period t, charging
When PB(t) 0 >, P when electric dischargeB(t) 0 <；
Load fluctuation constraint:
λ is the geometric mean of load active power, proportionality coefficient k1And k2It is provided according to specific actual conditions and experience, and with negative
Lotus stability bandwidth l is as the standard for judging load fluctuation；Wherein:
L=σ/λ
L is defined as the ratio between the standard deviation sigma of load active power and the geometric mean λ of load active power；
B) constraint of equipment and Energy Sources Equilibrium
Discharging efficiency constraint:
For maximum charge efficiency,For maximum discharging efficiency；
The constraint of energy-storage battery state of charge:
Emin≤EB(t)≤Emax
Emin=SOCminR
Emax=SOCmaxR
EmaxFor energy-storage battery maximum electricity, EminFor the minimum electricity of energy-storage battery, EB(t) the battery energy storage state for being period t；
SOCminAnd SOCmaxFor minimum and maximum state-of-charge, R is battery capacity；
At any time, the gross energy of energy storage is the summation of energy storage primary power and cumlative energy:
E (0) is battery initial quantity of electricity, and E (t) is the accumulation electricity of period t, and i is the when number of segment of whole day charging；
Daily electricity giant ties:
Cold-storage device constraint:
Wherein, QkmaxFor refrigeration unit maximum semen donors, QiIt (t) is Ice Storage Tank semen donors, QimaxFor Ice Storage Tank maximum semen donors,
Qsys(t) system needs semen donors, and QI is ice-reserving tankage.
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| CN109002910A (en) * | 2018-06-29 | 2018-12-14 | 合肥工业大学 | Industrial load Optimization Scheduling and system |
| CN111553544B (en) * | 2020-05-19 | 2023-08-25 | 国网浙江省电力有限公司杭州供电公司 | Industrial park distributed comprehensive demand response method based on consistency algorithm |
| CN113673739B (en) * | 2021-02-22 | 2023-04-18 | 华北电力大学（保定） | Multi-time-space scale collaborative optimization operation method of distributed comprehensive energy system |
| CN115018668B (en) * | 2022-08-09 | 2022-11-22 | 东方电子股份有限公司 | Controllable capacity modeling system for park |
| CN115046246B (en) * | 2022-08-15 | 2022-11-15 | 东方电子股份有限公司 | Self-optimization-seeking control system for comprehensive energy |
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| CN106230007A (en) * | 2016-07-25 | 2016-12-14 | 中能建江苏能源科技有限公司 | A kind of micro-capacitance sensor energy storage Optimization Scheduling |
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