CN107844053A - A kind of building level cooling heating and power generation system active energy supply method - Google Patents
A kind of building level cooling heating and power generation system active energy supply method Download PDFInfo
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Abstract
The present invention discloses a kind of building level cooling heating and power generation system active energy supply method, utilize air themperature, air humidity, solar radiation, the relevant historical data such as wind speed and system hot/cold load is trained to neutral net, the real time temperature gathered using sensor, humidity, solar radiation, the real time datas such as wind speed, by the hot/cold load of the neural network prediction building trained, neutral net is predicted every some cycles (cycle time is adjustable) to the hot/cold load of subsequent period, the hot/cold workload demand obtained according to prediction, and in cooling heating and power generation system source pump performance parameter, automatically determine the energy supply amount required for system.This method can will be traditional according to the passive energy resource supply mode of user's request in cooling heating and power generation system, it is converted into and carries perspective, more active energy resource supply mode, especially for the cooling heating and power generation system that northern heating demands are larger, can solve heating delay issue well.
Description
Technical field
The invention belongs to active energy supply technical field, more particularly to a kind of building level cooling heating and power generation system active energy
Source Supply Method, this method are remarkably improved the initiative of system, and the promptness to user's energy supply, have shown intelligent micro- electricity
The theory of net.
Background technology
Building level cooling heating and power generation system is one of important form of distributed energy, is a kind of establish in energy cascade profit
With on conceptual foundation, in units of mansion, school or a cell, collect refrigeration, heat supply (heating and domestic hot-water) and generated electricity
The multiple-supplying supply system that journey is integrated.The characteristics of its is maximum be adapted in, small-scale terminal user, provide a user simultaneously
Three kinds of products of cool and thermal power.The Effec-tive Function of building level cooling heating and power generation system, not only form and hold with co-feeding system structure, equipment
It is relevant to measure size, it is also relevant with many factors such as cold and hot electric load, operation reserve.
Found by being retrieved to the open source literature of prior art, Publication No. CN1945472 Chinese patent gives one
The centralized optimization control method of kind cold, heat and electricity three-way energy supply system, the optimization method is using expense and energy consumption as object function
Optimize, and the running status of terminal device or the operational factor of adjusting device are controlled with this；Publication No.
CN101667013A Chinese patent discloses a kind of miniature gas turbine combined cooling and power distributed energy supply system optimized operation control
Method processed, the optimization method is only for miniature gas turbine cooling heating and power generation system, based on load prediction results, with most economical
The method of operation is that the optimal power generation of co-feeding system is optimized target；Publication No. CN101813941A Chinese patent is public
A kind of energy efficiency optimizing and dispatching system for cold, heat and electricity triple supply equipment is opened, the system is predicted by load system energy requirement and correlation
Optimization calculates, and completes the Optimized Operation of energy conversion plant capacity output, realizes that the dynamic between cool and thermal power supply and demand is put down
Weighing apparatus.The technical scheme for comparing three documents can be seen that the Optimization Design of cooling heating and power generation system and be typically based on
The objective optimization of primary energy ratio and (or) financial cost index, although the above method or technology have certain be applied to
Effect, but also all exist clearly disadvantageous：
1) do not change traditional energy supply model, be user terminal to after supply side proposition demand, supply side is again to it
Convey the mode of the energy；
2) the associated loadings Forecasting Methodology being directed to is relative complex, and most load forecasting methods are built to specified building
Build effectively, without good generality and portability；
3) in-advance almost refer to for the promptness of intelligent energy resource supply mode, satisfaction property and not.
The content of the invention
Lack initiative, load forecasting model for the control method that existing cooling heating and power generation system is mentioned in above-mentioned background
The deficiencies of complicated, the present invention propose a kind of building level cooling heating and power generation system active energy supply method.Realize cold and hot Electricity Federation
For the active function of system, solve the problems, such as that building heating has time delay, embody the theory of intelligent micro-grid.
The technical solution adopted in the present invention is：A kind of building level cooling heating and power generation system active energy supply method, its
It is characterised by, future load is predicted using neutral net, in advance to energy supply end feedback user demand, realizes cold and hot Electricity Federation
For the active function of system, methods described comprises the following steps：
(1) output is used as by the use of relevant historical data as input, and the hot/cold load of corresponding period, to nerve net
Network is trained；
(2) using the real time data of sensor collection, by the neural network prediction subsequent period system that trains
Hot/cold load；
(3) neutral net is once predicted the hot/cold load of subsequent period every some cycles, and pre- by what is obtained
Measured value, according to the performance parameter of heat reclamation device and donkey boiler, determine the demand for energy required for system；
(4) demand for energy determined by, energy resource supply in advance is carried out by co-feeding system, to meet to use to user
On the basis of the heat demand of family, for the electric power energy conveyed to user, compared to the electric demand of user, at most carried out to bulk power grid defeated
Send；Asked at least to bulk power grid, supply the electricity supply lacked.
Further, relevant historical data described in step (1) includes air themperature, air humidity, solar radiation, wind
Speed.
Further, real time data described in step (2) includes air themperature, air humidity, solar radiation, wind speed.
Further, predict that the hot/cold load realization principle in subsequent period system is described in step (2)：
From cooling heating and power generation system workflow and structure, thermic load Qh, refrigeration duty QcMeet following equation
Qr=Qhrh (3)
Euser=Epgu-Ep-Eec (6)
Wherein ηhFor the unit efficiency that heats, COPecFor electric refrigerating plant efficiency, ηpguFor generating set efficiency, ηhrsReturned for heat
Receiving apparatus efficiency.
From formula (5), (6), the hot/cold load gone out according to neural network prediction, it can be derived that what generating set was sent
Electric energy total amount Epgu, and the electric energy total amount E that user can finally receiveuser, it is achieved that " electricity determining by heat ".
The beneficial effects of the invention are as follows：The present invention has the following advantages that compared with prior art：
(1) present invention is predicted using neutral net to the hot/cold load of building level cooling heating and power generation system, its model
Fitting degree height simple, to data are established, as long as and have substantial amounts of historical data as training sample, can be to arbitrarily building
Build or system loading is accurately predicted, therefore there is fine simplicity and transplantability.
(2) present invention is predicted using the load to subsequent period in system, true in advance using the method for electricity determining by heat
The energy stream in system is determined, on the premise of heat demand is met, can accomplish to accomplish user heat supply in advance.Due to heat
Transmission is slower relative to electric energy, there is certain retardance, and this method is supplied in advance for user's heat demand of subsequent period
Heat solves this problem well.
(3) present invention embody to power grid user energy supply initiative with it is in-advance, agree with the intelligentized hair of current power network
Open up direction.
Brief description of the drawings
Fig. 1 is the basic structure block diagram of cooling heating and power generation system in the present invention.
Fig. 2 is the neural network structure figure for being used for load prediction in the present invention.
In Fig. 1：Fm is the consumption of the total fuel of cooling heating and power generation system；Fpgu is the fuel consumption of generating set；Supplemented by Fb
Help the fuel consumption of boiler；Epgu is the electric energy that generating set is sent；Egrid is the electric energy that power network is supplemented system；Ep is defeated
The electric energy that dead resistance consumes in electric line；Eec is the consumed electric energy of electricity refrigeration；Euser is the electric energy needed for user；Qr is
Heat energy caused by heat reclamation device；Qb is heat energy caused by donkey boiler；Qhrh is the recovery heat for producing heat energy；Qc user
Refrigeration duty；Qh system heat loads.
In Fig. 2：WijWith WjkThe connection weight of input layer and hidden layer, hidden layer and output layer respectively in network.
Embodiment
Form is described in further detail again to the above of the present invention by the following examples, but should not manage this
The scope solved as the above-mentioned theme of the present invention is only limitted to following embodiment, and all technologies for being realized based on the above of the present invention are equal
Belong to the scope of the present invention.
A kind of building level cooling heating and power generation system active energy supply method proposed by the present invention, using neutral net to not
Carry out load to be predicted, in advance to energy supply end feedback user demand, realize the active function of cooling heating and power generation system, solve building
Space heating has the problem of time delay.Specific method is：
(1) neutral net is trained using relevant historical data.
Utilize the relevant historical datas pair such as air themperature, air humidity, solar radiation, wind speed and system hot/cold load
Neutral net is trained.What time relevant historical data should include but are not limited to the above, can increase number according to actual conditions
According to type, such as：The data stronger with payload correlation to be predicted such as previous, two days same future positions load condition.
Under normal circumstances, more to the training data of neutral net input, the training effect of network is also better, and load is predicted
The degree of accuracy it is also higher.
(2) using the real time data of sensor collection, by the hot/cold load of the neural network prediction building trained.
(3) neutral net is carried out once pre- every the fixed cycle (cycle time is adjustable) to the hot/cold load of subsequent period
Survey, and the predicted value by obtaining, according to the performance parameter of heat reclamation device and donkey boiler, the energy required for determining system supplies
Ying Liang.
(4) demand for energy determined by, energy resource supply in advance is carried out by co-feeding system, to meet to use to user
On the basis of the heat demand of family, for the electric power energy conveyed to user, compared to the electric demand of user, at most carried out to bulk power grid defeated
Send；Asked at least to bulk power grid, supply the electricity supply lacked.
As shown in figure 1, the workflow of cooling heating and power generation system is：The total fuel of system is distributed to generating set and auxiliary
Help boiler；Generating set is consumed the electric energy sent by the dead resistance of circuit, electric refrigerating plant and user；Produce simultaneously
Waste heat by the processing of thermal reduction device, the heat energy of output is conveyed to absorption refrigeration jointly with the heat energy that donkey boiler is produced
Device and heating unit；The heat energy that absorption refrigerator comes with heating unit to higher level's conveying, is allocated according to demand, right
Energy is processed, and meets the thermic load and refrigeration duty of user respectively.
In cooling heating and power generation system, traditional control method mainly has " electricity determining by heat " and two kinds of " with the fixed heat of electricity ", this
The building level cooling heating and power generation system active energy supply method proposed is invented, key step is as follows：
(1) a large amount of historical datas are utilized, such as air themperature, air humidity, solar radiation, wind speed are used as input, and
The hot/cold load of corresponding period is trained as output to neutral net.
(2) input such as the real-time air themperature that is collected by sensor in system, air humidity, solar radiation, wind speed
Amount, Q is obtained by thermic load in neural network prediction subsequent period system and refrigeration dutyh、Qc。
From working-flow and structure, Qh、QcMeet following equation
Qr=Qhrh (3)
Euser=Epgu-Ep-Eec (6)
Wherein ηh、COPec、ηpgu、ηhrsRespectively heat unit efficiency, electric refrigerating plant efficiency, generating set efficiency, heat
Retracting device efficiency.From formula (5), (6), the hot/cold load gone out according to neural network prediction, it can be deduced that generating set is sent out
The electric energy total amount E gone outpgu, and the electric energy total amount E that user can finally receiveuser.It is achieved that " electricity determining by heat ".Certainly,
The electric energy E that user can finally receivepgu, can just not necessarily meet user's request, when electric energy deficiency, the part lacked can
Supplied with being supplemented by bulk power grid；When electric energy is excessive, the part of spilling can convey to power network, can also be deposited using energy storage device
Storage is got up, and the research of this respect needs further to be deployed.
Claims (4)
- A kind of 1. building level cooling heating and power generation system active energy supply method, it is characterised in that using neutral net to future Load is predicted, and in advance to energy supply end feedback user demand, realizes the active function of cooling heating and power generation system, methods described bag Include following steps：(1) output is used as by the use of relevant historical data as input, and the hot/cold load of corresponding period, neutral net is entered Row training；(2) using the real time data of sensor collection, the hot/cold in the neural network prediction subsequent period system that trains is passed through Load；(3) neutral net is once predicted the hot/cold load of subsequent period every some cycles, and the prediction by obtaining Value, according to the performance parameter of heat reclamation device and donkey boiler, determines the demand for energy required for system；(4) demand for energy determined by, energy resource supply in advance is carried out by co-feeding system to user, to meet user's heat On the basis of demand, for the electric power energy conveyed to user, compared to the electric demand of user, at most conveyed to bulk power grid； Asked at least to bulk power grid, supply the electricity supply lacked.
- 2. building level cooling heating and power generation system active energy supply method as claimed in claim 1, it is characterised in that：Step (1) relevant historical data described in includes air themperature, air humidity, solar radiation, wind speed.
- 3. building level cooling heating and power generation system active energy supply method as claimed in claim 1, it is characterised in that：Step (2) real time data described in includes air themperature, air humidity, solar radiation, wind speed.
- 4. building level cooling heating and power generation system active energy supply method as claimed in claim 3, it is characterised in that：Step (2) the hot/cold load realization principle in subsequent period system is predicted described in is：From cooling heating and power generation system workflow and structure, thermic load Qh, refrigeration duty QcMeet following equation<mrow> <msub> <mi>Q</mi> <mrow> <mi>h</mi> <mi>r</mi> <mi>h</mi> </mrow> </msub> <mo>=</mo> <mfrac> <msub> <mi>Q</mi> <mi>h</mi> </msub> <msub> <mi>&eta;</mi> <mi>h</mi> </msub> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow><mrow> <msub> <mi>E</mi> <mrow> <mi>e</mi> <mi>c</mi> </mrow> </msub> <mo>=</mo> <mfrac> <msub> <mi>Q</mi> <mi>c</mi> </msub> <mrow> <msub> <mi>COP</mi> <mrow> <mi>e</mi> <mi>c</mi> </mrow> </msub> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow>Qr=Qhrh (3)<mrow> <msub> <mi>F</mi> <mrow> <mi>p</mi> <mi>g</mi> <mi>u</mi> </mrow> </msub> <mo>=</mo> <mfrac> <msub> <mi>Q</mi> <mi>r</mi> </msub> <mrow> <mo>(</mo> <mn>1</mn> <mo>-</mo> <msub> <mi>&eta;</mi> <mrow> <mi>p</mi> <mi>g</mi> <mi>u</mi> </mrow> </msub> <mo>)</mo> <msub> <mi>&eta;</mi> <mrow> <mi>h</mi> <mi>r</mi> <mi>s</mi> </mrow> </msub> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>4</mn> <mo>)</mo> </mrow> </mrow><mrow> <msub> <mi>E</mi> <mrow> <mi>p</mi> <mi>g</mi> <mi>u</mi> </mrow> </msub> <mo>=</mo> <mfrac> <msub> <mi>Q</mi> <mi>r</mi> </msub> <mrow> <mo>(</mo> <mn>1</mn> <mo>-</mo> <msub> <mi>&eta;</mi> <mrow> <mi>p</mi> <mi>g</mi> <mi>u</mi> </mrow> </msub> <mo>)</mo> <msub> <mi>&eta;</mi> <mrow> <mi>h</mi> <mi>r</mi> <mi>s</mi> </mrow> </msub> </mrow> </mfrac> <msub> <mi>&eta;</mi> <mrow> <mi>p</mi> <mi>g</mi> <mi>u</mi> </mrow> </msub> <mo>=</mo> <mfrac> <mrow> <msub> <mi>Q</mi> <mi>h</mi> </msub> <mo>/</mo> <msub> <mi>&eta;</mi> <mi>h</mi> </msub> </mrow> <mrow> <mo>(</mo> <mn>1</mn> <mo>-</mo> <msub> <mi>&eta;</mi> <mrow> <mi>p</mi> <mi>g</mi> <mi>u</mi> </mrow> </msub> <mo>)</mo> <msub> <mi>&eta;</mi> <mrow> <mi>h</mi> <mi>r</mi> <mi>s</mi> </mrow> </msub> </mrow> </mfrac> <msub> <mi>&eta;</mi> <mrow> <mi>p</mi> <mi>g</mi> <mi>u</mi> </mrow> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>5</mn> <mo>)</mo> </mrow> </mrow>Euser=Epgu-Ep-Eec (6)Wherein ηhFor the unit efficiency that heats, COPecFor electric refrigerating plant efficiency, ηpguFor generating set efficiency, ηhrsFilled for recuperation of heat Put efficiency.From formula (5), (6), the hot/cold load gone out according to neural network prediction, the electric energy that generating set is sent can be derived that Total amount Epgu, and the electric energy total amount E that user can finally receiveuser, it is achieved that " electricity determining by heat ".
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Application publication date: 20180327 |