CN106295900A - A kind of city intelligent energy management system - Google Patents
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Abstract
The invention discloses a kind of city intelligent energy management system, under the air-conditioning comfort premise of the urban energy management system of present invention terminal temperature difference in ensureing energy feed region, realize the hydraulic equilibrium of whole energy transmission lines system, the loss that minimizing system is unnecessary, and assist to improve Architectural Equipment operation level, reduce maintenance management personnel and overspending.The method that the present invention uses is by arranging a set of analog systems, load prediction to terminal temperature difference in advance, set the running status that whole system is optimum, then carrying out real-time optimizing and revising by real-time feedback control system, it is achieved optimization, the most energy-conservation operation purpose.
Description
Technical field
The present invention relates to a kind of energy management system.
Background technology
Urban energy supply includes power supply, cooling, heat supply, confession combustion gas, supplying hot water etc., and this is for the cooling in city, confession
Hot systems, proposes a kind of novel city intelligent energy conservation way.The cooling in city, heat supply refer to a certain specific region
Interior buildings, by special energy centre centralized system for cold water or hot water, are supplied to region building concentration by region pipe network
Cold heat supply.
City cold and heat supply system also exists characteristic complicated and changeable, and system is in the running of every day, by external rings
Border condition and the impact of the condition of use, running status all the time is all ceaselessly changing.For this change, conventional city
Energy supply system is to reach energy-conservation purpose, uses variable flow system more, and each branch service supplies water according to self needing regulation
The frequency of circulating pump.But the change of a branch service flow, certainly will affect the change of supervisor's net flow system flow, and supervisor's net is
The change of system certainly will cause again the change of other branch service flows, and the hydraulic regime between branch system influences each other so that
Whole air conditioning system is run in the environment of being constantly in a disorderly change, and the imbalance of pipe network system is at city multiple-energy-source
Show particularly evident in the system of associating energy supply.On this basis, a lot of designing units can consider in each pipe-line system
Increase some self-balancing valves to regulate.The result ultimately resulted in is exactly: the energy consumption of system variable-flow operation saving is wasted again
Overcoming on the resistance of balanced valve, the most stable of operation of the system that do not realizes and truly energy-conservation.
Usual whole urban energy supply system be divided into hot and cold water prepare, hot and cold water conveying and hot and cold water use three portions
Point, form loop, secondary loop and load side loop.Loop by Cooling and Heat Source (boiler, heat pump, handpiece Water Chilling Units etc.),
Primary pump, confession return pipe and balance pipe composition, be responsible for the preparation of hot and cold water；Secondary loop by communicating pipe, outdoor transmission pipeline network, two
Level pump, plate change primary side for water return pipeline, plate type heat exchanger composition, responsible hot and cold water conveying；Load side loop is by plate-type heat-exchange
Device, end water circulating pump, end supply backwater pipe network, tail end air conditioner equipment form, and are responsible for the use of hot and cold water.As shown in Figure 1.
The control mode of traditional energy management system is simple feedback control, i.e. according to temperature, pressure transducer
Line is monitored, and signal is fed back to corresponding water pump and electrically operated valve regulates accordingly.
(1) the index circuit pressure reduction that first load side end water circulating pump is typically according to detecting carries out frequency conversion control
System, this control be wind dish based on terminal temperature difference, coil pipe or packaged air conditioner etc. be mounted with electric two-way valve or electric adjustable
Joint valve.When end-equipment starts, electric two-way valve or electric control valve are opened or regulation, when end-equipment quits work, and electricity
Dynamic two-port valve or electric control valve are also accordingly turned off.Along with electric two-way valve or electric control valve are opened, closed or regulate, supply back
Pressure reduction between water pipe can change therewith.Now, pressure difference signal is fed back to load side water pump by differential pressure controller, utilizes and becomes
Frequency modulation speed meets the basic pressure difference of least favorable user.
The problem existed: the change of outdoor climate etc. and the change of indoor temperature and humidity, if not affecting opening of electric two-way valve
Closing or the aperture of electric control valve, water circulating pump will not carry out variable-flow operation, often result in the waste of energy；More have
The switch of user's end of profit or regulation affect the pressure reduction of index circuit the most hardly, and water circulating pump is the same will not frequency modulation fortune
OK.
(2) secondly the change of the temperature that two stage pump typically changes secondary side water main according to the plate detected carries out frequency conversion
Control, when plate change secondary side supply water temperature change time, the frequency of regulation two stage pump, ensure that plate changes secondary side supply water temperature permanent
Fixed.
The problem existed: the temperature signal on secondary side water main has certain time delay, it is impossible to feed back end in time
The most real service condition of user；The change of one of them user's two stage pump flow can affect the change of supervisor's net flow system flow,
The change of supervisor's net flow system flow can affect again the change of other branch service flows, influences each other, mutually between branch system
Interference, causes system to be constantly in unbalanced running status.
(3) primary pump often sets according to the metered flow of Cooling and Heat Source equipment, and constant flow runs.
The problem existed: the reality such as equipment such as heat pump main frame, can run under 50% ~ 150% state of metered flow, and not
Must be that the device efficiency under metered flow is the highest, cause system operationally, the flow between a two stage pump has difference in flow, and one
Directly it is being balanced by balance pipe, is causing the waste of energy.
(4) additionally, system often arranges such as static balancing valve or dynamic balance valve, according to design conditions or debugging working condition
Set initial opening, according to the resistance of branch path is increased or decreased, realize the balance of pipe network.
Existing problems: design conditions or debugging working condition are often widely different with actual operating mode, and the effect of balanced valve is past
Toward widely different with expected effect；The regulation of balanced valve is a kind of regulation increasing resistance of pipe system loss, setting the most, energy
Amount waste is the most serious.
Summary of the invention
It is an object of the invention to provide a kind of city intelligent energy management system, it is achieved the water of whole energy transmission lines system
Dynamic balance, reduces the loss that system is unnecessary.
The present invention solves the concrete scheme of its technical problem:
A kind of city intelligent energy management system, comprises the steps:
The first step: set up the simulation management model of whole urban energy supply；
Energy preparation system, pipe network conveying system and user are used the system integration in unification by urban energy supply phantom
In one big system, simulation management model establishment step is as follows:
(1) set up the cooling and heating load computation model of energy supply user: as much as possible will be for all buildings of energy range according to difference
Building industry situation, different set up corresponding BUILDINGS MODELS towards, different building height, the meteorologic parameter outdoor by input calculates
The cooling and heating load of all buildings in the range of going out energy supply；
(2) all of for system distributing system is set up model: include pipe network blood circulation, secondary pipe network blood circulation, an end
End subscriber blood circulation；
(3) performance parameter of all devices in gathering system, including load performance parameter and the pump operating characteristic of heat pump main frame
Curve；
(4) by said system, model, device performance parameters all being combined, a whole set of simulation management mould is formed
Type；
Second step: set up the customer charge prediction management system in the range of energy supply；
Customer charge prediction management system is premise based on cooling and heating load computation model, can be by the meteorological money of following a period of time
Material parameter input, to cooling and heating load computation model, calculates the cooling and heating load numerical value of following a period of time, in conjunction with history run number
According to, automatically generate future customer load data；This customer charge prediction management system mainly includes load Analysis prediction, load pipe
Reason；
(1) load Analysis prediction is based on carry calculation model, the phantom of the building by setting up, and inputs location
Typical meteorological parameter or following meteorologic parameter, can to Building Indoor Environment parameter, architectural environment control system operation conditions and
Building energy consumption carries out annual hourly load simulation and forecast and calculates；
(2) load management is to be analyzed by the load data of load Analysis prediction data with actual motion, by big number
According to management, optimize correcting load computation model, and accurate can analyze future load situation；
3rd step: set up real-time energy supply data collecting system；
The collection of real time data mainly includes the collection of Outdoor Air Parameters, the collection of end-equipment service condition, energy supplying system
The collection of actual operating data,
(1) collection of Outdoor Air Parameters: Real-time Collection outdoor temperature humidity, atmospheric pressure parameter；
(2) collection of end-equipment service condition: include the unlatching of end-equipment, close, regulate change；
(3) collection of energy supplying system actual operating data: refer to monitor energy supplying system practical operation situation, gathers real-time confession backwater
Temperature, pressure, flow actual operating data；
4th step: predicted load inputs simulation management model, finds out the initial launch operating point of optimum；
Load prediction is managed the predicted load that systematic analysis goes out, is input in the load model assembly of simulation management model,
Run the phantom of urban energy supply, calculate optimum according to pipe network distributing system model and equipment performance characteristics analysis meter
Initial launch operating point；
5th step: according to simulation results, initialization system runs optimal initial launch operating point；
The optimal operating condition point 4th step simulation run obtained, by control system, is input in actual energy supplying system, makees
Run optimal initial launch operating point for system, energy supplying system is regulated for the first time；
6th step: the service data that timing acquiring is real-time, inputs simulation management model, calculates real-time optimal operating condition；
According to the data of energy supply data collecting system Real-time Collection, timing input simulation management model, analysis meter calculates real-time
Optimal operating condition point；
7th step: according to simulation results, initialization system runs optimal real time execution operating point；
By the 6th step calculated optimal operating condition point data, by control system, it is input in actual energy supplying system, right
Energy supplying system regulates again, has both ensured the air-conditioning using effect of terminal temperature difference in energy feed region, can realize again whole
The secondary hydraulic equilibrium of individual energy transmission lines system, the optimal operating condition point that the system that reaches is real-time；
8th step: set up large database concept, periodically optimizes load prediction management system and simulation management model so that it is at utmost connect
Nearly practical situation；Set up the large database concept of whole urban energy supply, periodically optimize load prediction management system and simulation management
Model so that it is at utmost close to practical situation, runs to provide for system optimization and supplies essentially according to, it is achieved whole urban energy
The wisdomization answering system manages.
The air-conditioning of the urban energy management system of present invention terminal temperature difference in ensureing energy feed region uses comfortable
Under degree premise, it is achieved the hydraulic equilibrium of whole energy transmission lines system, reduce the loss that system is unnecessary, and assist raising building to set
Standby operation level, reduces maintenance management personnel and overspending.The method that the present invention uses is by arranging a set of analog systems,
Load prediction to terminal temperature difference in advance, is set the running status that whole system is optimum, then is existed by real-time feedback control system
Carry out real-time optimizing and revising, it is achieved optimization, the most energy-conservation operation purpose.
Accompanying drawing explanation
Fig. 1 is traditional cities energy supply system control principle simplification figure.
Fig. 2 is the urban energy supply system management method system flow chart of the present invention.
Detailed description of the invention
Below in conjunction with the accompanying drawings the present invention is described in further detail, but protection scope of the present invention is not limited to
Described embodiment.
Urban energy supply system management method system flow chart is as in figure 2 it is shown, specifically comprise the following steps that
The first step: set up the simulation management model of whole urban energy supply；
Energy preparation system, pipe network conveying system and user are used the system integration in unification by urban energy supply phantom
In one big system.Phantom is the nearest with the degree of closeness of real system, and whole system is controlled the most favourable by simulation result, because of
The most crucial content of this present invention is exactly to must be set up the phantom most like with reality.Building of Simulation Model step is as follows:
(1) set up the cooling and heating load computation model of energy supply user: as much as possible will be for all buildings of energy range according to difference
Building industry situation, different set up corresponding BUILDINGS MODELS, by ginsengs such as the meteorological datas that input is outdoor towards, different building height
Number is the cooling and heating load of all buildings in the range of can calculating energy supply；
(2) all of for system distributing system is set up model: include pipe network blood circulation, secondary pipe network blood circulation, an end
End subscriber blood circulation.
(3) performance of all devices in gathering system: such as part load performance parameter, the pump operating characteristic of heat pump main frame
Curve etc..
(4) by said system, model, device performance parameters all being combined, a whole set of simulation management is formed
Model.
Second step: set up the customer charge prediction management system in the range of energy supply；
Customer charge prediction management system is premise based on cooling and heating load computation model, except can be by the gas of following a period of time
As the parameter inputs such as data to cooling and heating load computation model, calculate outside the cooling and heating load numerical value of following a period of time, it is also possible to
In conjunction with history data, automatically generate future customer load data.This management system mainly includes load Analysis prediction, load
Management.
(1) load Analysis prediction is based on carry calculation model, the phantom of the building by setting up, and inputs place
The data such as area typical meteorological parameter or following meteorologic parameter, can be to ambient parameter, architectural environments such as the architecture indoor wet light of heat
Control system operation conditions and building energy consumption etc. carry out annual 8760 hours hourly load simulation and forecasts and calculate.
(2) load management is to be analyzed by the load data of load Analysis prediction data with actual motion, passes through
Big data management, optimizes correcting load computation model, and accurate can analyze future load situation.
3rd step: set up real-time energy supply data collecting system；
The collection of real time data mainly includes the collection of Outdoor Air Parameters, the collection of end-equipment service condition, energy supplying system
The collection of actual operating data.
(1) collection of Outdoor Air Parameters: the change of outdoor microenvironment can affect the accuracy of prediction load equally, passes through
The parameters such as Real-time Collection outdoor temperature humidity, atmospheric pressure, provide reliable analytical data for load prediction management system.
(2) collection of end-equipment service condition: the start and stop of end-user equipment can enter along with personnel or leave and send out
Changing, actually used load can along with the unlatching of end-equipment, close, there is the change of artificial property in regulation etc..Only by negative
Lotus prediction management system is cannot really to grasp the change of end actual load, the most also needs to gather end-equipment and uses feelings
Condition data use the correction of load in real time.
(3) collection of energy supplying system actual operating data: refer to monitor energy supplying system practical operation situation, gather real-time confession
The actual operating data such as return water temperature, pressure, flow.
4th step: predicted load inputs simulation management model, finds out the initial launch operating point of optimum；
Load prediction is managed the predicted load that systematic analysis goes out, is input in the load model assembly of simulation management model.
Run the phantom of urban energy supply, analyze according to pipe network distributing system model and equipment performance characteristics etc. and calculate optimum
Initial launch operating point.
5th step: according to simulation results, initialization system runs optimal initial launch operating point；
The optimal operating condition point 4th step simulation run obtained, by control system, is input in actual energy supplying system, makees
Run optimal initial launch operating point for system, energy supplying system is regulated for the first time.
6th step: the service data that timing acquiring is real-time, inputs simulation management model, calculates real-time optimum operation work
Condition；
According to the data of energy supply data collecting system Real-time Collection, input simulation management model regularly (can be set), analyze
Calculate real-time optimal operating condition point.
7th step: according to simulation results, initialization system runs optimal real time execution operating point；
By the 6th step calculated optimal operating condition point data, by control system, it is input in actual energy supplying system, right
Energy supplying system regulates again.Both ensured the air-conditioning using effect of terminal temperature difference in energy feed region, and can realize again whole
The secondary hydraulic equilibrium of individual energy transmission lines system, the optimal operating condition point that the system that reaches is real-time.
8th step: set up large database concept, periodically optimizes load prediction management system and simulation management model so that it is maximum journey
Degree is close to practical situation.
Set up the large database concept of whole urban energy supply, the energy supply pipe including house, business, hotel, office etc.
Reason data.Periodically optimize load prediction management system and simulation management model so that it is at utmost close to practical situation, for system
Optimized running provides the wisdomization management essentially according to, it is achieved whole urban energy supply system.
(1) set up urban energy data base, city difference can be carried out, with diagnosing, providing for policymaker at different levels by object
Multidimensional, directly perceived, comprehensive, deep load prediction and simulation management model data, lay good for urban energy planning next time
Good basis.
(2) setting up urban energy data base, setting up can be to the energy resource consumption carrying out Intelligent Support with energy and emission reduction work
Information network.By energy resource consumption information network, can consult at any time each time with can situation and energy-conservation with energy equipment
Situation, scrap build situation.Can be to the power consumption behavior of city difference energy object and energy market segmentation, it is each right to automatically analyze
The use energy index of elephant, gives warning in advance to energy consumption trend, exercises supervision energy-saving and emission-reduction work.
Claims (1)
1. a city intelligent energy management system, it is characterised in that comprise the steps:
The first step: set up the simulation management model of whole urban energy supply；
Energy preparation system, pipe network conveying system and user are used the system integration in unification by urban energy supply phantom
In one big system, simulation management model establishment step is as follows:
Set up the cooling and heating load computation model of energy supply user: all buildings by confession energy range as much as possible are built according to different
Building industry situation, different set up corresponding BUILDINGS MODELS towards, different building height, the meteorologic parameter outdoor by input can calculate
The cooling and heating load of all buildings in the range of going out energy supply；
All of for system distributing system is set up model: include that pipe network blood circulation, secondary pipe network blood circulation, an end are used
Family blood circulation；
The performance parameter of all devices in gathering system, load performance parameter and pump operating characteristic including heat pump main frame are bent
Line；
By said system, model, device performance parameters all being combined, form a whole set of simulation management model；
Second step: set up the customer charge prediction management system in the range of energy supply；
Customer charge prediction management system is premise based on cooling and heating load computation model, can be by the meteorological money of following a period of time
Material parameter input, to cooling and heating load computation model, calculates the cooling and heating load numerical value of following a period of time, in conjunction with history run number
According to, automatically generate future customer load data；This customer charge prediction management system mainly includes load Analysis prediction, load pipe
Reason；
(1) load Analysis prediction is based on carry calculation model, the phantom of the building by setting up, and inputs location
Typical meteorological parameter or following meteorologic parameter, can to Building Indoor Environment parameter, architectural environment control system operation conditions and
Building energy consumption carries out annual hourly load simulation and forecast and calculates；
(2) load management is to be analyzed by the load data of load Analysis prediction data with actual motion, by big number
According to management, optimize correcting load computation model, and accurate can analyze future load situation；
3rd step: set up real-time energy supply data collecting system；
The collection of real time data mainly includes the collection of Outdoor Air Parameters, the collection of end-equipment service condition, energy supplying system
The collection of actual operating data,
(1) collection of Outdoor Air Parameters: Real-time Collection outdoor temperature humidity, atmospheric pressure parameter；
(2) collection of end-equipment service condition: include the unlatching of end-equipment, close, regulate change；
(3) collection of energy supplying system actual operating data: refer to monitor energy supplying system practical operation situation, gathers real-time confession backwater
Temperature, pressure, flow actual operating data；
4th step: predicted load inputs simulation management model, finds out the initial launch operating point of optimum；
Load prediction is managed the predicted load that systematic analysis goes out, is input in the load model assembly of simulation management model,
Run the phantom of urban energy supply, calculate optimum according to pipe network distributing system model and equipment performance characteristics analysis meter
Initial launch operating point；
5th step: according to simulation results, initialization system runs optimal initial launch operating point；
The optimal operating condition point 4th step simulation run obtained, by control system, is input in actual energy supplying system, makees
Run optimal initial launch operating point for system, energy supplying system is regulated for the first time；
6th step: the service data that timing acquiring is real-time, inputs simulation management model, calculates real-time optimal operating condition；
According to the data of energy supply data collecting system Real-time Collection, timing input simulation management model, analysis meter calculates reality
Time optimal operating condition point；
7th step: according to simulation results, initialization system runs optimal real time execution operating point；
By the 6th step calculated optimal operating condition point data, by control system, it is input in actual energy supplying system, right
Energy supplying system regulates again, has both ensured the air-conditioning using effect of terminal temperature difference in energy feed region, can realize again whole
The secondary hydraulic equilibrium of individual energy transmission lines system, the optimal operating condition point that the system that reaches is real-time；
8th step: set up large database concept, periodically optimizes load prediction management system and simulation management model so that it is at utmost connect
Nearly practical situation；Set up the large database concept of whole urban energy supply, periodically optimize load prediction management system and simulation management
Model so that it is at utmost close to practical situation, runs to provide for system optimization and supplies essentially according to, it is achieved whole urban energy
The wisdomization answering system manages.
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| CN108921412A (en) * | 2018-06-22 | 2018-11-30 | 中船第九设计研究院工程有限公司 | A kind of project feasibility assessment system based on simulation intelligence |
| CN109373438A (en) * | 2018-09-11 | 2019-02-22 | 太原理工大学 | Heating energy-saving control method and system based on transfer learning algorithm |
| CN109740888A (en) * | 2018-12-24 | 2019-05-10 | 新奥数能科技有限公司 | The calculation method and device of energy loss, storage medium, electronic device |
| CN110175785A (en) * | 2019-05-30 | 2019-08-27 | 杭州安脉盛智能技术有限公司 | Extending type energy lean supply method and system |
| CN110244576A (en) * | 2019-05-31 | 2019-09-17 | 大连海心信息工程有限公司 | A kind of two net balance methods adjusted based on Computer Simulation |
| CN111025895A (en) * | 2019-04-21 | 2020-04-17 | 贾继刚 | Building energy-saving control system based on artificial intelligence |
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| CN111442478A (en) * | 2020-03-10 | 2020-07-24 | 珠海派诺科技股份有限公司 | Air conditioning system optimization control method, intelligent terminal and storage device |
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| CN113671830A (en) * | 2021-08-10 | 2021-11-19 | 浙江浙能技术研究院有限公司 | Thermal power generating unit cold end optimization closed-loop control method based on intelligent scoring |
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| CN108921412A (en) * | 2018-06-22 | 2018-11-30 | 中船第九设计研究院工程有限公司 | A kind of project feasibility assessment system based on simulation intelligence |
| CN109373438A (en) * | 2018-09-11 | 2019-02-22 | 太原理工大学 | Heating energy-saving control method and system based on transfer learning algorithm |
| CN111090241A (en) * | 2018-10-24 | 2020-05-01 | 中国电力科学研究院有限公司 | Energy system visualization method |
| CN109740888A (en) * | 2018-12-24 | 2019-05-10 | 新奥数能科技有限公司 | The calculation method and device of energy loss, storage medium, electronic device |
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| CN114930375A (en) * | 2020-01-08 | 2022-08-19 | Lg电子株式会社 | Energy management control system and control method for building equipment |
| CN111626453A (en) * | 2020-02-20 | 2020-09-04 | 南京绿慧能源科技有限公司 | Positive feedback energy station group control system, method, storage medium and electronic equipment |
| CN111626453B (en) * | 2020-02-20 | 2024-08-20 | 南京绿慧能源科技有限公司 | Positive feedback energy station group control system, method, storage medium and electronic equipment |
| CN111442478A (en) * | 2020-03-10 | 2020-07-24 | 珠海派诺科技股份有限公司 | Air conditioning system optimization control method, intelligent terminal and storage device |
| CN113836785B (en) * | 2021-07-28 | 2024-02-13 | 南京尔顺科技发展有限公司 | Municipal area intelligent water supply system and artificial intelligent control optimization method thereof |
| CN113836785A (en) * | 2021-07-28 | 2021-12-24 | 南京尔顺科技发展有限公司 | Municipal regional intelligent water supply system and artificial intelligent control optimization method thereof |
| WO2023004809A1 (en) * | 2021-07-30 | 2023-02-02 | 西门子（中国）有限公司 | Modeling method and apparatus for smart energy management system, and storage medium |
| CN113671830A (en) * | 2021-08-10 | 2021-11-19 | 浙江浙能技术研究院有限公司 | Thermal power generating unit cold end optimization closed-loop control method based on intelligent scoring |
| CN113776143A (en) * | 2021-09-17 | 2021-12-10 | 江苏图创建筑工程有限公司 | Energy-saving pipeline combined structure and method for reducing fluid resistance of efficient cold and heat supply system |
| CN113819513A (en) * | 2021-10-19 | 2021-12-21 | 吉林建筑大学 | Urban clean heat supply control method and system based on artificial intelligence |
| CN114440419B (en) * | 2021-12-31 | 2023-10-27 | 博锐尚格科技股份有限公司 | Control method, device, equipment and storage medium of cold station secondary pump system |
| CN114440419A (en) * | 2021-12-31 | 2022-05-06 | 博锐尚格科技股份有限公司 | Control method, device and equipment for secondary pump system of cold station and storage medium |
| CN118278028A (en) * | 2024-04-10 | 2024-07-02 | 江苏鼎集智能科技股份有限公司 | Smart city energy management system and method |
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