CN109960874A - A kind of cold accumulation system operation method based on performance driving economy - Google Patents
A kind of cold accumulation system operation method based on performance driving economy Download PDFInfo
- Publication number
- CN109960874A CN109960874A CN201910226497.1A CN201910226497A CN109960874A CN 109960874 A CN109960874 A CN 109960874A CN 201910226497 A CN201910226497 A CN 201910226497A CN 109960874 A CN109960874 A CN 109960874A
- Authority
- CN
- China
- Prior art keywords
- cold
- storage
- cooling
- model
- refrigeration
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/89—Arrangement or mounting of control or safety devices
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/08—Thermal analysis or thermal optimisation
Landscapes
- Engineering & Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Physics & Mathematics (AREA)
- Air Conditioning Control Device (AREA)
Abstract
A kind of cold accumulation system operation method based on performance driving economy disclosed by the invention, comprising the following steps: establish cold-storage model: include refrigeration and cold-storage apparatus modeling;Establish user's air conditioner load model: comprising the modeling of user's air conditioner load and Modifying model;It establishes control strategy: according to cold-storage model and time-of-use tariffs, the lowest coursing cost in cold cycle being released using a cold-storage and establishes control strategy as target, for controlling each assembly operating of cold accumulation system and power output situation;Modifying model: model is modified for user's actual motion load and time-of-use tariffs variation.Cold accumulation system of the invention, which is unable to reach, utmostly reduces operating cost, and the operation reserve coupling of cold accumulation system cold accumulation system is strong, and response is timely, and equipment is relatively easy, and later maintenance cost is low.
Description
Technical field
The present invention relates to cold-storage field, in particular to a kind of cold accumulation system operation method based on performance driving economy.
Background technique
Cold accumulation system is as a kind of sky for effectively cutting down air conditioning system installed capacity and distribution capacity, lifting means utilization rate
Adjusting system, in conjunction with time-of-use tariffs, using night paddy electricity refrigeration and cold accumulation, daytime, peak electricity released cold cooling supply, promoted user's economy
Meanwhile also with the energy-conserving action to power grid " peak load shifting ".It, can also be with region except in addition to conventional center air-conditioning system combines
Cold supply system combines, and gives full play to scale effect.
In existing cold-storage project, frequently with simply releasing cold preferential, chiller priority, ratio when some projects control strategy is formulated
The simple strategies such as example control, or only consider not consider part load conditions under design conditions, and due to automatic control system in operational process
System can not match user's actual load situation, often rely on the practical operating experience accumulated of staff, thus cause cold-storage system
System is unable to reach the purpose for utmostly reducing operating cost, or even because system cold-storage releases cold additional energy in the process and causes to transport
The case where row expense increases.
Time-of-use tariffs are the economical premises of cold-storage project, since time-of-use tariffs more consider city in formulation process
City's electricity consumption factor, and customer charge is only related with user's industry situation and weather condition etc., cause electricity price peak Pinggu Time segments division and
There is the not exclusively identical even appearance of period and duration not overlapping period etc. in duration and customer charge peak Pinggu, and final result causes
Original peak electricity ice-melt, the general policies of paddy electricity ice-reserving are unable to reach its due economy.According to finding and domestic correlation
Patent family situation, service work strategy without judging load curve and time-of-use tariffs curvilinear trend and matching degree, are still pressed
The conventional operation strategy of " peak electricity ice-melt, flat Duan Kaiji, paddy electricity ice-reserving ", cold accumulation system economy are difficult to ensure.
In addition, cold accumulation system has, hysteresis quality, non-linear, coupling is not strong, and equipment is more, system complex, thus optimizes
Cold accumulation system operation reserve and automatic control are one of the critical issues of systematic economy operation.
Summary of the invention
The purpose of the present invention is to overcome the shortcomings of the existing technology and deficiency, provides a kind of cold-storage based on performance driving economy
System operation method.
The purpose of the present invention is realized by the following technical solution:
A kind of cold accumulation system operation method based on performance driving economy, comprising the following steps:
S1, cold-storage model is established: comprising refrigeration and cold-storage apparatus modeling;
S2, user's air conditioner load model is established: comprising the modeling of user's air conditioner load and Modifying model;
S3, it establishes control strategy: according to cold-storage model and time-of-use tariffs, operating cost being released in cold cycle most with a cold-storage
Low is target, establishes control strategy, for controlling each assembly operating of cold accumulation system and power output situation;
S4, Modifying model: model is modified for user's actual motion load and time-of-use tariffs variation, promotes operation
Tactful accuracy.
In step S1, each component of the refrigeration and cold-storage apparatus modeling comprising participating in refrigeration and cold-storage, is 01 base in detail
Carry host, 02 conventional host, 03 cold-storage host (cooling condition) and 04 cold-storage apparatus, the 05 mating water for releasing cool equipment and each component
The equipment such as pump, cooling tower, heat exchanger, the model include monitoring modular, control module, monitoring modular real-time refrigerating capacity containing each equipment
Monitoring, power consumption monitoring, water consumption monitoring and cold storage capacity release cooling capacity monitoring, and monitoring modular should have data feedback function.
In step S1, the refrigeration and cold-storage apparatus modeling refer to and are grouped modeling by system, be divided into refrigeration system and
Cold-storage releases cooling system;Modeling purpose is to establish refrigeration and cold-storage input, output and regulation and control system, thus according to control plan
Slightly, each system energy consumption and refrigerating capacity output are adjusted;
The refrigeration system includes 01 base main chiller, 02 conventional host, 03 cold-storage host (cooling condition);Cold accumulation system packet
Cool equipment is released containing 04 cold-storage apparatus, 05;Refrigeration system includes that the refrigeration host computer operates normally a complete set of equipment, as host, water pump are (cold
Freeze water pump, cooling water pump, ethylene glycol water pump (if there is)), cooling tower, heat exchange equipment etc., the system have by when refrigerating capacity Q it is defeated
Out, power W is exported, and adds up refrigerating capacity QC and power consumption P statistics and output;
The cold-storage releases the equipment such as mating water pump, cooling tower, heat exchanger, cold-storage when cooling system includes cold-storage host and cold-storage
Unit etc., the system have by when cold storage capacity/release cooling capacity Q output, power W output, cold-storage/release cold refrigerating capacity QC and power consumption P system
Meter and output.
In step S2, user's air conditioner load modeling is containing annual 8760 hours hourly load prediction models and subsequent reality
Operating load carries out Modifying model;Load forecasting model includes more than one submodule, and the submodule includes history meteorology number
According to library and weather forecast comparing correction module, working day and nonworkdays monitoring modular, peak value and valley monitoring modular.
The history meteorogical phenomena database and weather forecast comparing correction module are for obtaining accurate user's gas
Image data, convenient for the order of accuarcy of increasing productivity prediction model;Its workflow is to establish annual meteorogical phenomena database and communication system
System carries out dynamic corrections using weather forecast data, main corrected parameter is temperature (dry bulb based on history meteorological data
Temperature, wet-bulb temperature), relative humidity, sunshine, outdoor wind speed.
The working day and nonworkdays monitoring modular are used to arrange Load adjustment prediction model according to user job plan
In influence factor about personnel activity;Its process is that user formulates flow process chart, and system is executed according to flow process chart, and
Have modification function (such as add, delete) and historgraphic data recording and calling function.
The peak value and valley monitoring modular are used for the monitoring of user's air conditioner load peak value and valley, according to Historical Monitoring number
According to, to refrigeration and cold accumulation system peak value and valley power, peak value and valley cold-discharged rate etc. be defined, avoid system from frequently moving
Make.
In step S3, the control strategy of establishing is decomposed into host cooling supply part and releases cold cooling supply part;
Host cooling supply part includes: 01 base main chiller, 02 conventional host, 03 cold-storage host (cooling condition);
It is described release cold cooling supply part include: 04 release cooling capacity (the ordinary telegram period releases cold) substantially, 05 peak value releases cooling capacity (peak potential period
It releases cold);Cooling equipment is combined between cool equipment with releasing, and each host power output and is released cooling capacity and can be controlled;Cooling capacity is released in control
With cold storage capacity balance under the premise of, calculating main frame cooling supply and release cold cooling supply each section by when operating cost, select operating cost most
Low combination is as control strategy.
Described 04 to release cooling capacity substantially be refrigeration duty is more than host installed capacity, but when electricity price is not belonging to peak electricity price must release it is cold
Cooling capacity is released with meet cooling needs;It is that electricity price releases cold semen donors when belonging to peak electricity price that 05 peak value, which releases cooling capacity, in Cool storage rate
In constant situation, peak value releases that cooling capacity accounting is higher, and performance driving economy is higher.
In step 3, the control strategy is as follows in the section operation of electricity price peak Pinggu:
4) peak electricity price: maximum cold-discharged rate is preferentially released cold, and insufficient section preferentially opens base main chiller, secondly electricity refrigeration master
Machine finally opens cold-storage host (operation cooling condition);
5) ordinary telegram valence: preferentially opening base main chiller, and insufficient section opens electric refrigeration host computer, finally opens cold-storage host (fortune
Row cooling condition);
6) paddy electricity valence: maximum ice storage cold-storage opens base main chiller refrigeration, and load fluctuation leads to the base load machine short time not
When sufficient, part electricity refrigeration host computer can be opened.
Step 4 Modifying model, it is therefore intended that according to user's actual operating data, modified load model, to be promoted
Load prediction accuracy;Run corresponding situation according to cold accumulation system, adjust system acting opportunity, thus dynamic adjustment cold storage capacity and
Control strategy.
Compared with the prior art, the invention has the following advantages and beneficial effects:
Cold accumulation system of the invention, which is unable to reach, utmostly reduces operating cost, the operation of cold accumulation system cold accumulation system
Tactful coupling is strong, and response is timely, and equipment is relatively easy, and later maintenance cost is low.
Detailed description of the invention
Fig. 1 is a kind of flow chart of the cold accumulation system operation method based on performance driving economy of the present invention.
Fig. 2-1,2-2,2-3,2-4 are respectively to transport under the specific embodiment of the invention 100%, 75%, 50% and 25% load
Row flow chart, embodiment design is at full capacity under operating condition, and Cool storage rate about 29%, load curve exists with time-of-use tariffs curve avoids the peak hour
Phenomenon.
Fig. 3-1,3-2,3-3,3-4 are respectively to transport under the specific embodiment of the invention 100%, 75%, 50% and 25% load
Row flow chart, the embodiment design under operating condition at full capacity, Cool storage rate about 29%, load curve and time-of-use tariffs curve co-insides.
Fig. 4 is structural block diagram corresponding to a kind of cold accumulation system operation method based on performance driving economy of the present invention;
Wherein, YG indicates that ethylene glycol supplies water, and YH indicates that ethylene glycol return water, L1 indicate that freezing is supplied water, and L2 indicates that freezing return water, LQ1 indicate
Cooling to supply water, LQ2 indicates cooling backwater.
Specific embodiment
Present invention will now be described in further detail with reference to the embodiments and the accompanying drawings, but embodiments of the present invention are unlimited
In this.
As shown in Figure 1, the cold accumulation system operation reserve based on performance driving economy of the present embodiment.The control strategy includes
Following process flow:
Process 1: load model carries out load prediction, and correction module is modified prediction result;
Process 2: revised load curve is compared with electricity price curve for control module, judges whether flat section electricity occur
When valence, there is refrigeration duty beyond refrigeration host computer refrigerating capacity situation;
Process 3: according to control module judging result, section electricity need to be put down respectively by, which taking, releases the cold cooling capacity strategy and normal released substantially
Peak Pinggu operation reserve;
Process 4: peak Pinggu operation reserve is executed.
The present invention use by when operation reserve, according to by when table run, table 1 respectively corresponds Fig. 2-1,2-2,2-
3,2-4 avoids the peak hour the operation reserve under phenomenon, the operation reserve in the case of table 2 respectively corresponds Fig. 3-1,3-2,3-3,3-4 are overlapped.
The operation reserve that 1 load curve of table and time-of-use tariffs curve are avoided the peak hour under phenomenon
Operation reserve in the case of 2 load curve of table and time-of-use tariffs curve co-insides
The above embodiment is a preferred embodiment of the present invention, but embodiments of the present invention are not by above-described embodiment
Limitation, other any changes, modifications, substitutions, combinations, simplifications made without departing from the spirit and principles of the present invention,
It should be equivalent substitute mode, be included within the scope of the present invention.
Claims (10)
1. a kind of cold accumulation system operation method based on performance driving economy, which comprises the following steps:
S1, cold-storage model is established: comprising refrigeration and cold-storage apparatus modeling;
S2, user's air conditioner load model is established: comprising the modeling of user's air conditioner load and Modifying model;
S3, establish control strategy: according to cold-storage model and time-of-use tariffs, releasing the lowest coursing cost in cold cycle with a cold-storage is
Target establishes control strategy, for controlling each assembly operating of cold accumulation system and power output situation;
S4, Modifying model: model is modified for user's actual motion load and time-of-use tariffs variation.
2. the cold accumulation system operation method based on performance driving economy according to claim 1, which is characterized in that in step S1,
The refrigeration and cold-storage apparatus modeling, which refer to, is grouped modeling by system, is divided into refrigeration system and cold-storage releases cooling system;Modeling
Purpose is to establish refrigeration and cold-storage input, output and regulation and control system, to adjust each system energy consumption according to control strategy
And refrigerating capacity output;
The refrigeration system includes base main chiller, conventional host, cold-storage host;Cold accumulation system includes cold-storage apparatus, releases cool equipment;
Refrigeration system include the refrigeration host computer operate normally a complete set of equipment, the system have by when refrigerating capacity Q output, power W output, tire out
Count refrigerating capacity QC and power consumption P statistics and output;
The cold-storage releases mating water pump, cooling tower when cooling system includes cold-storage host and cold-storage, and heat exchanger, cold-storage unit, this is
System have by when cold storage capacity/release cooling capacity Q output, power W output, cold-storage/release cold refrigerating capacity QC and power consumption P statistics and output.
3. the cold accumulation system operation method based on performance driving economy according to claim 1, which is characterized in that in step S2,
User's air conditioner load modeling carries out model containing annual 8760 hours hourly load prediction models and subsequent actual motion load
Amendment;Load forecasting model includes more than one submodule, and the submodule includes history meteorogical phenomena database and weather forecast number
According to comparison correction module, working day and nonworkdays monitoring modular, peak value and valley monitoring modular.
4. the cold accumulation system operation method based on performance driving economy according to claim 3, which is characterized in that the history gas
Image data library and weather forecast comparing correction module are convenient for increasing productivity for obtaining accurate user's meteorological data
The order of accuarcy of prediction model;Its workflow is to establish annual meteorogical phenomena database and communication system, is with history meteorological data
Basis carries out dynamic corrections using weather forecast data, and main corrected parameter is temperature, relative humidity, sunshine, outdoor wind speed.
5. the cold accumulation system operation method based on performance driving economy according to claim 3, which is characterized in that the working day
It is used to arrange the shadow in Load adjustment prediction model about personnel activity according to user job plan with nonworkdays monitoring modular
The factor of sound;Its process is that user formulates flow process chart, and system is executed according to flow process chart, and has modification function and history
Data record and calling function.
6. the cold accumulation system operation method based on performance driving economy according to claim 3, which is characterized in that the peak value with
Valley monitoring modular is used for the monitoring of user's air conditioner load peak value and valley, according to Historical Monitoring data, to refrigeration and cold-storage system
System peak value and valley power, peak value and valley cold-discharged rate etc. are defined, and avoid system frequent movement.
7. the cold accumulation system operation method based on performance driving economy according to claim 1, which is characterized in that in step S3,
The control strategy of establishing is decomposed into host cooling supply part and releases cold cooling supply part;
Host cooling supply part includes: base main chiller, conventional host, cold-storage host;
It is described release cold cooling supply part include: release cooling capacity substantially, peak value releases cooling capacity;Cooling equipment is combined between cool equipment with releasing, and
Each host contributes and releases cooling capacity and can control;Under the premise of control is released cooling capacity and cold storage capacity and is balanced, calculating main frame cooling supply with
Release cold cooling supply each section by when operating cost, select the combination of the lowest coursing cost as control strategy.
8. the cold accumulation system operation method based on performance driving economy according to claim 7, which is characterized in that described to release substantially
It is more than host installed capacity that cooling capacity, which is refrigeration duty, but when electricity price is not belonging to peak electricity price must release it is cold cold to meet releasing for cooling needs
Amount;It is that electricity price releases cold semen donors when belonging to peak electricity price that the peak value, which releases cooling capacity, and in the constant situation of Cool storage rate, peak value is released cooling capacity and accounted for
Than higher, performance driving economy is higher.
9. the cold accumulation system operation method based on performance driving economy according to claim 1, which is characterized in that in step 3, institute
Control strategy is stated, as follows in the section operation of electricity price peak Pinggu:
1) peak electricity price: maximum cold-discharged rate is preferentially released cold, and insufficient section preferentially opens base main chiller, secondly electric refrigeration host computer, most
Cold-storage host (operation cooling condition) is opened afterwards;
2) ordinary telegram valence: preferentially opening base main chiller, and insufficient section opens electric refrigeration host computer, finally opens cold-storage host (operation system
Cold operating condition);
3) paddy electricity valence: maximum ice storage cold-storage opens base main chiller refrigeration, and load fluctuation causes the base load machine short time insufficient
When, part electricity refrigeration host computer can be opened.
10. the cold accumulation system operation method based on performance driving economy according to claim 1, which is characterized in that the step 4
Modifying model, it is therefore intended that according to user's actual operating data, modified load model, to increasing productivity prediction accuracy;Root
Corresponding situation is run according to cold accumulation system, adjusts system acting opportunity, thus dynamic adjustment cold storage capacity and control strategy.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910226497.1A CN109960874A (en) | 2019-03-25 | 2019-03-25 | A kind of cold accumulation system operation method based on performance driving economy |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201910226497.1A CN109960874A (en) | 2019-03-25 | 2019-03-25 | A kind of cold accumulation system operation method based on performance driving economy |
Publications (1)
Publication Number | Publication Date |
---|---|
CN109960874A true CN109960874A (en) | 2019-07-02 |
Family
ID=67024902
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201910226497.1A Pending CN109960874A (en) | 2019-03-25 | 2019-03-25 | A kind of cold accumulation system operation method based on performance driving economy |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN109960874A (en) |
Cited By (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111159632A (en) * | 2020-01-10 | 2020-05-15 | 中国科学院广州能源研究所 | Method for calculating cooling energy efficiency and economy of data center |
CN112508372A (en) * | 2020-11-27 | 2021-03-16 | 上海发电设备成套设计研究院有限责任公司 | Method, device and equipment for determining operation strategy of energy storage water tank and storage medium |
CN112648787A (en) * | 2019-10-10 | 2021-04-13 | 中车石家庄车辆有限公司 | Method and device for determining cold accumulation residual service life and computer equipment |
CN112648784A (en) * | 2019-10-10 | 2021-04-13 | 中车石家庄车辆有限公司 | Method and device for determining cold accumulation residual service life and computer equipment |
CN112815473A (en) * | 2020-12-31 | 2021-05-18 | 珠海横琴能源发展有限公司 | Optimal control device and control method for cold accumulation air conditioning system |
CN113063189A (en) * | 2021-02-26 | 2021-07-02 | 广东申菱环境系统股份有限公司 | Air conditioner control method and control system based on load prediction |
CN115388530A (en) * | 2022-08-25 | 2022-11-25 | 重庆大学 | Intelligent control method of radiant heat and cold supply system based on peak-valley electricity price |
CN116379679A (en) * | 2023-03-15 | 2023-07-04 | 深圳市森若新材科技有限公司 | Cold accumulation and supply system and control method |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103574845A (en) * | 2013-11-04 | 2014-02-12 | 国家电网公司 | Cooling load prediction based optimal control method of ice-storage system |
CN104279724A (en) * | 2014-08-25 | 2015-01-14 | 广西申能达智能技术有限公司 | Heat pump control method and heat pump control system of energy-saving air conditioner |
CN106152343A (en) * | 2016-07-05 | 2016-11-23 | 西安建筑科技大学 | A kind of ice-chilling air conditioning system design optimization method based on Life cycle |
CN205980188U (en) * | 2016-08-05 | 2017-02-22 | 上海冰核时代科技中心(有限合伙) | Ice cold -storage optimal control system based on load forecast |
CN109376912A (en) * | 2018-09-29 | 2019-02-22 | 东南大学 | Cooling heating and power generation system running optimizatin method based on civil building thermal inertia |
-
2019
- 2019-03-25 CN CN201910226497.1A patent/CN109960874A/en active Pending
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103574845A (en) * | 2013-11-04 | 2014-02-12 | 国家电网公司 | Cooling load prediction based optimal control method of ice-storage system |
CN104279724A (en) * | 2014-08-25 | 2015-01-14 | 广西申能达智能技术有限公司 | Heat pump control method and heat pump control system of energy-saving air conditioner |
CN106152343A (en) * | 2016-07-05 | 2016-11-23 | 西安建筑科技大学 | A kind of ice-chilling air conditioning system design optimization method based on Life cycle |
CN205980188U (en) * | 2016-08-05 | 2017-02-22 | 上海冰核时代科技中心(有限合伙) | Ice cold -storage optimal control system based on load forecast |
CN109376912A (en) * | 2018-09-29 | 2019-02-22 | 东南大学 | Cooling heating and power generation system running optimizatin method based on civil building thermal inertia |
Cited By (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112648787A (en) * | 2019-10-10 | 2021-04-13 | 中车石家庄车辆有限公司 | Method and device for determining cold accumulation residual service life and computer equipment |
CN112648784A (en) * | 2019-10-10 | 2021-04-13 | 中车石家庄车辆有限公司 | Method and device for determining cold accumulation residual service life and computer equipment |
CN111159632A (en) * | 2020-01-10 | 2020-05-15 | 中国科学院广州能源研究所 | Method for calculating cooling energy efficiency and economy of data center |
CN111159632B (en) * | 2020-01-10 | 2023-04-25 | 中国科学院广州能源研究所 | Data center cooling energy efficiency and economical efficiency calculation method |
CN112508372A (en) * | 2020-11-27 | 2021-03-16 | 上海发电设备成套设计研究院有限责任公司 | Method, device and equipment for determining operation strategy of energy storage water tank and storage medium |
CN112815473A (en) * | 2020-12-31 | 2021-05-18 | 珠海横琴能源发展有限公司 | Optimal control device and control method for cold accumulation air conditioning system |
CN113063189A (en) * | 2021-02-26 | 2021-07-02 | 广东申菱环境系统股份有限公司 | Air conditioner control method and control system based on load prediction |
CN115388530A (en) * | 2022-08-25 | 2022-11-25 | 重庆大学 | Intelligent control method of radiant heat and cold supply system based on peak-valley electricity price |
CN116379679A (en) * | 2023-03-15 | 2023-07-04 | 深圳市森若新材科技有限公司 | Cold accumulation and supply system and control method |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN109960874A (en) | A kind of cold accumulation system operation method based on performance driving economy | |
CN102788005B (en) | Method for controlling the operation of the compressors in optimized VRV air conditioning system and device thereof | |
CN110460040B (en) | Micro-grid operation scheduling method considering intelligent building heat balance characteristic | |
CN106152343B (en) | A kind of ice-chilling air conditioning system design optimization method based on Life cycle | |
CN109059195B (en) | Control method and control system for central air conditioner for reducing load peak value of power grid | |
US5778683A (en) | Thermal storage system controller and method | |
Cole et al. | Use of model predictive control to enhance the flexibility of thermal energy storage cooling systems | |
CN106403102A (en) | Energy intelligent control method, device and system | |
CN102508474A (en) | Circulated cooling water operation optimization control system for industrial enterprise | |
CN109269021A (en) | Air conditioner system energy saving running optimizatin dispatching method | |
CN108426354A (en) | Air-conditioning Load Prediction system based on radiated time sequence method | |
CN109341010B (en) | Energy supply integrated control method and device for air conditioning system of electric refrigerator | |
CN104110782B (en) | A kind of water cold storage energy-saving management system of central air conditioner | |
CN114282729A (en) | Load prediction-based ice storage air conditioner optimal scheduling method | |
CN112032882B (en) | Scheduling method of ice storage air conditioning system | |
CN106765860A (en) | A kind of control system and method for nuclear power station central air-conditioning | |
CN110486896B (en) | Cascade air conditioning system optimization control method based on water chilling unit energy consumption model | |
CN111242361B (en) | Optimal scheduling method and device for park comprehensive energy system considering ground source heat pump | |
CN107732936A (en) | A kind of fast frequency based on temperature control load adjusts double-deck control system | |
CN112815473A (en) | Optimal control device and control method for cold accumulation air conditioning system | |
CN105631557B (en) | Consider ice storage air conditioner and there is the micro-capacitance sensor Optimization Scheduling of the cold coupling feature of electricity | |
CN105605733A (en) | Power grid responding method and device of air conditioner refrigerator | |
CN208567008U (en) | Air-conditioning Load Prediction system based on radiated time sequence method | |
CN116596148A (en) | Intelligent power plant two-stage optimal scheduling method and system based on combined cooling, heating and power | |
CN113054668B (en) | Rolling optimization scheduling method and device for cold storage air conditioning system |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination |