CN110390432A - Energy dynamically optimized scheduling method, apparatus and electronic equipment for comprehensive energy - Google Patents
Energy dynamically optimized scheduling method, apparatus and electronic equipment for comprehensive energy Download PDFInfo
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Abstract
The present invention provides a kind of energy dynamically optimized scheduling methods for comprehensive energy, which comprises obtains the current active power output and gas production of integrated energy system；Gas production based on the current active power output establishes prediction model, and the prediction model is used to predict the active processing and gas production of the integrated energy system of default expected time；The prediction model is solved, to obtain the active power output increment and gas production increment in multiple prediction step times；According to the multiple prediction not for a long time in the first prediction step time in the active power output increment and gas production increment determine the Optimized Operation strategy of comprehensive energy；Send the Optimized Operation strategy of the comprehensive energy.With active power output increment and gas increment is produced as control variable, and by feedback compensation, while guaranteeing economy as far as possible, so that each unit active power output and gas source gas production change according to load fluctuation, thus scheduling result is more smooth.
Description
Technical field
The present invention relates to comprehensive energy technical field, in particular for comprehensive energy energy dynamically optimized scheduling method,
Device and electronic equipment.
Background technique
Main department one of of the power industry as energy consumption, the power source in China are mainly traditional thermoelectricity, however
Natural gas power is more cleaned, efficiently.China Gas power generation ratio is expected to increase year by year, and on the other hand, gas turbine group is fast
The response characteristic of speed can be used for stabilizing the fluctuation of intermittent new energy, to effectively support the grid-connected of extensive intermittent new energy
With consumption.Natural gas system can be deposited by pipe and gas storage facility Mass storage natural gas, provides for Operation of Electric Systems scheduling
It is spare.For the high-efficiency and economic operation for guaranteeing IPGES, on the one hand considers the temporal and spatial correlations characteristic of natural gas storage, electricity need to be studied
Multibreak face coordination optimization between Force system and natural gas system；On the other hand, (such as day on different runing time scales
Preceding scheduling in a few days dispatch), due to the difference of net load precision of prediction, demand of the IPGES to natural gas storage amount is completely not yet
Together, thus it is necessary to study the IPGES traffic controls under Multiple Time Scales.
Current IPGES Optimization Scheduling is mostly open loop Optimization Scheduling, i.e. Mr. Yu's a period of time discontinuity surface or more times
Section optimizes scheduling controlling, still falls within static optimization.And net load prediction inevitably there is a certain error, and predict error with
The increase of time scale and increase.It, can be by the time to reduce the poor influence to Optimal Decision-making of net load precision of prediction
The division of scale improves load prediction precision, but this method has ignored real system and runs influence to optimal control process,
It is non-critical optimal to easily lead to Optimal Decision-making result.
Summary of the invention
In view of this, the purpose of the present invention is to provide:
In a first aspect, the embodiment of the invention provides a kind of energy dynamically optimized scheduling method for comprehensive energy,
It is characterized in that, which comprises
Obtain the current active power output and gas production of integrated energy system；Gas production based on the current active power output is built
Vertical prediction model, the prediction model are used to predict the active processing of the integrated energy system of default expected time and produce gas
Amount；The prediction model is solved, to obtain the active power output increment and gas production increment in multiple prediction step times；According to institute
State it is multiple prediction not for a long time in the first prediction step time in the active power output increment and gas production increment determine it is comprehensive
Close the Optimized Operation strategy of the energy；Send the Optimized Operation strategy of the comprehensive energy.
Preferably,
The method also includes:
Judge whether the prediction model meets pre-set level；If the not up to described pre-set level optimizes described pre-
Survey model.
Preferably,
The gas production based on the current active power output establishes prediction model, and the prediction model is for predicting to preset
The active processing of the integrated energy system of expected time and gas production include:
Based on the gas production of the current active power output, with goal-selling function, it is minimised as optimizing according to operating cost
Target establishes the prediction model:
The goal-selling function are as follows:
Wherein, T is the Optimized Operation period a few days ago；U is generating set set；W is natural gas set；S is gas storage facility collection
It closes；CP(u) cost of electricity-generating for being generating set u；CG(w) Gas Prices for being natural air-air source w；CSIt (s) is gas storage facility s
Extract the cost of natural gas；Punit (u, t) is the active power output of t moment generating set u；Gwell(w, t) is t moment natural gas
The gas production of gas source w；Sout(s, t) is the amount of natural gas that t moment is extracted from gas storage facility s.
Preferably,
It is described to solve the prediction model, to obtain the active power output increment and gas production increasing in multiple prediction step times
Amount includes:
Control variable, which is solved, by rolling optimization solves the prediction model, it is any in multiple prediction step times to obtain
Active power output increment and gas production increment in a moment.
Preferably,
The active power output increment and production in the multiple prediction step time in any one moment are obtained by following formula
Tolerance increment:
Wherein, ((w, k+n Δ t) are respectively having for the following k+n time Δt unit u predicted at the k moment to u, k+n Δ t) to P with G
The gas production of function power output and gas source w；P0(u, k) and G0(w, k) is respectively the initial value of k moment unit u and gas source w；Δup(u, k
+ t) and Δ uw(w, k+t) is respectively the active power output increment and production gas increment of unit u and gas source w at the k+t moment；Δ t is in a few days
Scheduling time inter；N is prediction step.
Preferably,
The active power output increment and gas production increment are as follows:
Wherein, P (u, k+t) and G (w, k+t) is respectively the active power output and gas production reference value at k+t moment；HGIt is natural
Gas calorific value.
Preferably,
If the not up to described pre-set level, optimizing the prediction model includes:
Determine the corresponding active power output of current time corresponding subsequent time and gas production using as excellent according to the following formula
Change initial value:
Wherein, P0(u, k+ Δ t) and G0(w, k+ Δ t) are respectively the active power output and production of k+ time Δt unit u and gas source w
Tolerance initial value；Preal(u, k+ Δ t) and Greal(w, k+ Δ t) are respectively the active of k+ time Δt unit u and natural air-air source w
Power output and the practical measuring value of gas production；
According to the optimized initial value, the prediction model is optimized by rolling optimal dispatching.
Second aspect, the embodiment of the invention provides a kind of energy dynamically optimized scheduling device for comprehensive energy, institutes
Stating device includes:
Module is obtained, for obtaining the current active power output and gas production of integrated energy system；
Model building module establishes prediction model, the prediction mould for the gas production based on the current active power output
Type is used to predict the active processing and gas production of the integrated energy system of default expected time；
Module is solved, for solving the prediction model, to obtain the active power output increment in multiple prediction step times
With gas production increment；
Tactful determining module, for according to it is the multiple prediction not for a long time in the first prediction step time in described in
Active power output increment and gas production increment determine the Optimized Operation strategy of comprehensive energy；
Sending module, for sending the Optimized Operation strategy of the comprehensive energy.
Preferably,
Described device further include:
Judgment module, judges whether the prediction model meets pre-set level；Optimization module, if not up to described default
Index then optimizes the prediction model.
The third aspect, provides a kind of electronic equipment, and the electronic equipment includes: electronic equipment, which is characterized in that packet
It includes: memory；Processor；And it is stored in the energy for comprehensive energy that can be run on the memory and on the processor
Source dynamically optimized scheduling program, it is real when the energy dynamically optimized scheduling program for comprehensive energy is executed by the processor
The step of showing the above-mentioned energy dynamically optimized scheduling method for comprehensive energy.
The embodiment of the invention provides a kind of energy dynamically optimized scheduling method, apparatus and electronics for comprehensive energy to set
It is standby, based on dynamically optimized scheduling control under each unit active power output and gas source gas production on the whole with dispatch active power output a few days ago
Value is identical with gas production, but in a few days rolling optimal dispatching considers running situation, with active power output increment and produces gas
Increment is control variable, by feedback compensation, while guaranteeing economy as far as possible, so that each unit active power output and gas source
Gas production changes according to load fluctuation, thus scheduling result is more smooth.
Other features and advantages of the present invention will illustrate in the following description, also, partly become from specification
It obtains it is clear that understand through the implementation of the invention.The objectives and other advantages of the invention are in specification, claims
And specifically noted structure is achieved and obtained in attached drawing.
To enable the above objects, features and advantages of the present invention to be clearer and more comprehensible, preferred embodiment is cited below particularly, and cooperate
Appended attached drawing, is described in detail below.
Detailed description of the invention
It, below will be to specific in order to illustrate more clearly of the specific embodiment of the invention or technical solution in the prior art
Embodiment or attached drawing needed to be used in the description of the prior art be briefly described, it should be apparent that, it is described below
Attached drawing is some embodiments of the present invention, for those of ordinary skill in the art, before not making the creative labor
It puts, is also possible to obtain other drawings based on these drawings.
Fig. 1 is a kind of signal stream of the energy dynamically optimized scheduling method for comprehensive energy provided in an embodiment of the present invention
Cheng Tu.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with attached drawing to the present invention
Technical solution be clearly and completely described, it is clear that described embodiments are some of the embodiments of the present invention, rather than
Whole embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art are not making creative work premise
Under every other embodiment obtained, shall fall within the protection scope of the present invention.
Main department one of of the power industry as energy consumption, the power source in China are mainly traditional thermoelectricity, however
Natural gas power is more cleaned, efficiently.China Gas power generation ratio is expected to increase year by year, and on the other hand, gas turbine group is fast
The response characteristic of speed can be used for stabilizing the fluctuation of intermittent new energy, to effectively support the grid-connected of extensive intermittent new energy
With consumption.Thus in the case where electric system couples the trend gradually deepened with natural gas system, thermal power generation-natural gas interconnection is comprehensive
Energy resource system (IPGES) is closed to be expected to promote the building of low-carbon sustainable energy system.
Natural gas system can be deposited by pipe and gas storage facility Mass storage natural gas, provides for Operation of Electric Systems scheduling
It is spare.For the high-efficiency and economic operation for guaranteeing IPGES, on the one hand considers the temporal and spatial correlations characteristic of natural gas storage, electricity need to be studied
Multibreak face coordination optimization between Force system and natural gas system；On the other hand, (such as day on different runing time scales
Preceding scheduling in a few days dispatch), due to the difference of net load precision of prediction, demand of the IPGES to natural gas storage amount is completely not yet
Together, thus it is necessary to study the IPGES traffic controls under Multiple Time Scales.
Current IPGES Optimization Scheduling is mostly open loop Optimization Scheduling, i.e. Mr. Yu's a period of time discontinuity surface or more times
Section optimizes scheduling controlling, still falls within static optimization.And net load prediction inevitably there is a certain error, and predict error with
The increase of time scale and increase.It, can be by the time to reduce the poor influence to Optimal Decision-making of net load precision of prediction
The division of scale improves load prediction precision, but this method has ignored real system and runs influence to optimal control process,
It is non-critical optimal to easily lead to Optimal Decision-making result；In comparison, Model Predictive Control (MPC) is used as a kind of system optimization controlling party
Method, it is different from refinement time scale Optimization Scheduling, quantity of state feedback compensation link is introduced, is missed so as to correct prediction
Optimized Operation deviation caused by the factors such as difference.This patent passes through the Spatial-temporal Properties of natural gas system transient state tide model, mentions
The IPGES dynamic operation optimization method based on Multiple Time Scales and MPC is gone out.On the basis of scheduling strategy a few days ago, with it is active go out
Power and production gas increment are that control variable carries out in a few days rolling optimal dispatching.
The embodiment of the present invention is described in detail below in conjunction with attached drawing so that those skilled in the art can understand,
Accurately understand technical solution of the present invention.
Fig. 1 is a kind of signal stream of the energy dynamically optimized scheduling method for comprehensive energy provided in an embodiment of the present invention
Cheng Tu.
As shown in Figure 1, a kind of energy dynamically optimized scheduling method for comprehensive energy may include steps of:
Step 110, the current active power output and gas production of integrated energy system are obtained.
Step 120, the gas production based on the current active power output establishes prediction model, and the prediction model is for predicting
The active processing and gas production of the integrated energy system of default expected time.
In some embodiments, the present invention may be implemented are as follows: the gas production based on the current active power output, to preset mesh
Scalar functions are minimised as optimization aim according to operating cost and establish the prediction model, wherein the goal-selling function are as follows:
Wherein, T is the Optimized Operation period a few days ago；U is generating set set；W is natural gas set；S is gas storage facility collection
It closes；CP(u) cost of electricity-generating for being generating set u；CG(w) Gas Prices for being natural air-air source w；CSIt (s) is gas storage facility s
Extract the cost of natural gas；Punit (u, t) is the active power output of t moment generating set u；Gwell(w, t) is t moment natural gas
The gas production of gas source w；Sout(s, t) is the amount of natural gas that t moment is extracted from gas storage facility s.
Step 130, the prediction model is solved, to obtain the active power output increment in multiple prediction step times and produce gas
Measure increment.
In some embodiments, control variable can be solved by rolling optimization solve the prediction model, it is more to obtain
Active power output increment and gas production increment in a prediction step time in any one moment.
It is active in any one moment in the multiple prediction step time it is possible to further be obtained by following formula
Power output increment and gas production increment:
Wherein, ((w, k+n Δ t) are respectively having for the following k+n time Δt unit u predicted at the k moment to u, k+n Δ t) to P with G
The gas production of function power output and gas source w；P0(u, k) and G0(w, k) is respectively the initial value of k moment unit u and gas source w；Δup(u, k
+ t) and Δ uw(w, k+t) is respectively the active power output increment and production gas increment of unit u and gas source w at the k+t moment；Δ t is in a few days
Scheduling time inter；N is prediction step.
And active power output increment and gas production increment can indicate are as follows:
Wherein, P (u, k+t) and G (w, k+t) is respectively the active power output and gas production reference value at k+t moment；HGIt is natural
Gas calorific value.
Step 140, according to it is the multiple prediction not for a long time in the first prediction step time in the active power output
Increment and gas production increment determine the Optimized Operation strategy of comprehensive energy.
Step 150, the Optimized Operation strategy of the comprehensive energy is sent.
In further embodiments, method provided by the invention can also include the following steps (not shown): judgement
Whether the prediction model meets pre-set level；If the not up to described pre-set level, optimizes the prediction model.Further
Ground can determine the corresponding active power output of current time corresponding subsequent time and gas production using as optimization according to the following formula
Initial value:
Wherein, P0(u, k+ Δ t) and G0(w, k+ Δ t) are respectively the active power output and production of k+ time Δt unit u and gas source w
Tolerance initial value；Preal(u, k+ Δ t) and Greal(w, k+ Δ t) are respectively the active of k+ time Δt unit u and natural air-air source w
Power output and the practical measuring value of gas production；According to the optimized initial value, the prediction model is carried out by rolling optimal dispatching
Optimization.
Continue with that the present invention will be described, so that those skilled in the art can clearly and accurately understand this hair
Bright technical solution.
One, IPGES Optimal Operation Model:
It is dispatched a few days ago using the cost that runs minimized as target making hour service capacity plan in lower day and is issued.And in a few days
Rolling optimal dispatching is then using operation plan a few days ago as reference value, using running power output as initial value rolling optimization, a few days ago
Scheduling is optimized by target of economic optimum, regulation goal function is as follows a few days ago:
Wherein, T is the Optimized Operation period a few days ago, illustratively can be for for 24 hours；U is generating set set；W is natural gas
Source set；S is gas storage facility set；Cp(u) cost of electricity-generating for being generating set u；Cg (w) is the Gas Prices of gas source w；Cs
(s) cost of natural gas is extracted for gas storage facility s；Punit(u, t) is the active power output of t moment generating set u；Gwell(w, t) is
The gas production of t moment gas source w；Sout(s, t) is the amount of natural gas that t moment is extracted from gas storage facility s.
Two, in a few days rolling optimal dispatching
Traditional IP GES optimal dispatch control is mostly open-loop control method, i.e., disposably seeks from the initial stage following a certain
Long period Optimized Operation strategy simultaneously issues.This method is suitable for net load precision of prediction height, scheduling strategy meets system reality
The case where operation.But with the growth of predicted time scale, the decline of net load precision of prediction leads to Optimized Operation strategy and system
There is relatively large deviation in actual motion, is unable to satisfy system actual schedule demand.
MPC is mainly made of model prediction, rolling optimization and feedback compensation three parts, using system mode at that time as initially
State is based on prediction model, by solving the following optimal control problem for having limit, obtains the controlling behavior sheet at current time
Using active power output and gas production rolling forecast value as input variable, the practical measuring value with initial time power supply and gas source is text
Initial value carries out rolling optimization solution to predict active power output increment in time domain and produce gas increment as control variable.
Control variable is solved by rolling optimization, predicts that generating set active power output and gas source produce gas in the following finite time-domain
Amount.K moment prediction model is as follows:
Wherein, ((w, k+n Δ t) are respectively having for the following k+n time Δt unit u predicted at the k moment to u, k+n Δ t) to P with G
The gas production of function power output and gas source w；P0(u, k) and G0(w, k) is respectively the initial value of k moment unit u and gas source w；Δup(u, k
+ t) and Δ uw(w, k+t) is respectively the active power output increment and production gas increment of unit u and gas source w at the k+t moment；Δ t is in a few days
Scheduling time inter；N is prediction step.
Compared to dispatching a few days ago, in a few days scheduling net load precision of prediction is higher, leads to Optimized Operation under different time scales
It is tactful different.In a few days regulation goal function minimizes the active power output increment in a few days dispatched using scheduling decision a few days ago as reference value
It is as follows with production gas increment:
In formula, P (u, k+t) and G (w, k+t) are respectively the active power output and gas production reference value at k+t moment；HG is natural
Gas calorific value.
In formula, P0(u, k+ Δ t) and G0(w, k+ Δ t) are respectively the active power output and production of k+ time Δt unit u and gas source w
Tolerance initial value；Preal(u, k+ Δ t) and Greal(w, k+ Δ t) be respectively k+ time Δt unit u and gas source w active power output and
The practical measuring value of gas production.
Three, network constraint
In embodiments of the present invention, the steady-state model also based on electric system constructs IPGES transient Model.
The present invention is when constructing IPGES transient Model, it is contemplated that electromagnetic wave is in power grid with light velocity propagation, transient state time
Constant is smaller than gas net, therefore uses electric power system stability states model.For natural gas line, gas net is described slow under IPGES transient Model
The partial differential equation expression formula of dynamic characteristic is as follows:
Influenced by factors such as load prediction precision and environment, as prediction model calculate obtained by predicted value may be
There are deviations for actual motion active power output of uniting and gas production, it is therefore desirable to which feedback compensation link is corrected, i.e., with current system
State measuring value carries out the rolling optimal dispatching of subsequent time as original state, is constituted closed-loop control with this.Then subsequent time
Initial value are as follows:
In formula: fl,tAnd Πl,tRespectively t moment length is the pipeline flow and pressure at l；D is internal diameter of the pipeline；R is gas
Body constant；T is gas temperature；Z is Gas Compression Factor；ρ0For natural gas density under standard state；F is coefficient of pipe friction.
When natural gas network failure or fluctuation, gas storage facility can be used as stable gas source and provide natural gas.
In embodiments of the present invention, consider its time adjacent segments Coupled Dynamic process, constrain as follows:
In formula: Sm,tFor the gas-storing capacity of gas storage facility on t moment node m；WithOn respectively t moment node m
Flow is extracted in the injection of gas storage facility；And SmGas storage facility gas-storing capacity upper and lower limit on respectively node m；WithPoint
Not Wei gas storage facility injection on node m, extract the upper limit of flow.
The embodiment of the present invention based on MPC dynamically optimized scheduling control under each unit active power output and gas source gas production it is whole
It is identical as scheduling active power output value and gas production a few days ago on body, but in a few days rolling optimal dispatching considers running feelings
Condition is control variable with active power output increment and production gas increment, by MPC feedback compensation, while guaranteeing economy as far as possible,
So that each unit active power output and gas source gas production change according to load fluctuation, thus scheduling result is more smooth.
The present invention also provides a kind of device corresponding with the above method, the apparatus may include:
Module is obtained, for obtaining the current active power output and gas production of integrated energy system；Model building module is used for
Gas production based on the current active power output establishes prediction model, and the prediction model is used to predict the institute of default expected time
State the active processing and gas production of integrated energy system；Module is solved, for solving the prediction model, to obtain multiple predictions
Active power output increment and gas production increment in the step-length time；Tactful determining module, when being used for not long according to the multiple prediction
Between in the first prediction step time in the active power output increment and gas production increment determine the Optimized Operation of comprehensive energy
Strategy；Sending module, for sending the Optimized Operation strategy of the comprehensive energy.
The device can also include: judgment module, judge whether the prediction model meets pre-set level；Optimization module,
If the not up to described pre-set level, optimizes the prediction model.
The embodiment of the present invention also provides a kind of electronic equipment, including memory, processor, and being stored in memory can locate
The computer program run on reason device, processor are realized provided by the above embodiment for comprehensive energy when executing computer program
The energy dynamically optimized scheduling the step of.
The embodiment of the present invention also provides a kind of computer readable storage medium, and meter is stored on computer readable storage medium
Calculation machine program executes the energy dynamic optimization tune for comprehensive energy of above-described embodiment when computer program is run by processor
The step of spending.
In addition, in the description of the embodiment of the present invention unless specifically defined or limited otherwise, term " installation ", " phase
Even ", " connection " shall be understood in a broad sense, for example, it may be being fixedly connected, may be a detachable connection, or be integrally connected；It can
To be mechanical connection, it is also possible to be electrically connected；It can be directly connected, can also can be indirectly connected through an intermediary
Connection inside two elements.For the ordinary skill in the art, above-mentioned term can be understood at this with concrete condition
Concrete meaning in invention.
In the description of the present invention, it should be noted that term " center ", "upper", "lower", "left", "right", "vertical",
The orientation or positional relationship of the instructions such as "horizontal", "inner", "outside" be based on the orientation or positional relationship shown in the drawings, merely to
Convenient for description the present invention and simplify description, rather than the device or element of indication or suggestion meaning must have a particular orientation,
It is constructed and operated in a specific orientation, therefore is not considered as limiting the invention.In addition, term " first ", " second ",
" third " is used for descriptive purposes only and cannot be understood as indicating or suggesting relative importance.
The computer program that the energy dynamically optimized scheduling for comprehensive energy is carried out provided by the embodiment of the present invention produces
Product, the computer readable storage medium including storing the executable non-volatile program code of processor, said program code
Including instruction can be used for executing previous methods method as described in the examples, specific implementation can be found in embodiment of the method, herein
It repeats no more.
It is apparent to those skilled in the art that for convenience and simplicity of description, the system of foregoing description,
The specific work process of device and unit, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
In several embodiments provided herein, it should be understood that disclosed systems, devices and methods, it can be with
It realizes by another way.The apparatus embodiments described above are merely exemplary, for example, the division of the unit,
Only a kind of logical function partition, there may be another division manner in actual implementation, in another example, multiple units or components can
To combine or be desirably integrated into another system, or some features can be ignored or not executed.Another point, it is shown or beg for
The mutual coupling, direct-coupling or communication connection of opinion can be through some communication interfaces, device or unit it is indirect
Coupling or communication connection can be electrical property, mechanical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.
It, can be with if the function is realized in the form of SFU software functional unit and when sold or used as an independent product
It is stored in the executable non-volatile computer-readable storage medium of a processor.Based on this understanding, of the invention
Technical solution substantially the part of the part that contributes to existing technology or the technical solution can be with software in other words
The form of product embodies, which is stored in a storage medium, including some instructions use so that
One computer equipment (can be personal computer, server or the network equipment etc.) executes each embodiment institute of the present invention
State all or part of the steps of method.And storage medium above-mentioned includes: USB flash disk, mobile hard disk, read-only memory (ROM, Read-
Only Memory), random access memory (RAM, Random Access Memory), magnetic or disk etc. are various can be with
Store the medium of program code.
Finally, it should be noted that embodiment described above, only a specific embodiment of the invention, to illustrate the present invention
Technical solution, rather than its limitations, scope of protection of the present invention is not limited thereto, although with reference to the foregoing embodiments to this hair
It is bright to be described in detail, those skilled in the art should understand that: anyone skilled in the art
In the technical scope disclosed by the present invention, it can still modify to technical solution documented by previous embodiment or can be light
It is readily conceivable that variation or equivalent replacement of some of the technical features；And these modifications, variation or replacement, do not make
The essence of corresponding technical solution is detached from the spirit and scope of technical solution of the embodiment of the present invention, should all cover in protection of the invention
Within the scope of.Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. a kind of energy dynamically optimized scheduling method for comprehensive energy, which is characterized in that the described method includes:
Obtain the current active power output and gas production of integrated energy system；
Gas production based on the current active power output establishes prediction model, and the prediction model is for predicting the default expected time
The integrated energy system active processing and gas production；
The prediction model is solved, to obtain the active power output increment and gas production increment in multiple prediction step times；
According to it is the multiple prediction not for a long time in the first prediction step time in the active power output increment and gas production
Increment determines the Optimized Operation strategy of comprehensive energy；
Send the Optimized Operation strategy of the comprehensive energy.
2. the method according to claim 1, wherein the method also includes:
Judge whether the prediction model meets pre-set level；
If the not up to described pre-set level, optimizes the prediction model.
3. according to the method described in claim 1, which is characterized in that the gas production based on the current active power output
Prediction model is established, the prediction model is used to predict the active processing and production of the integrated energy system of default expected time
Tolerance includes:
Based on the gas production of the current active power output, with goal-selling function, optimization aim is minimised as according to operating cost
Establish the prediction model:
The goal-selling function are as follows:
Wherein, T is the Optimized Operation period a few days ago；U is generating set set；W is natural gas set；S is gas storage facility set；CP
(u) cost of electricity-generating for being generating set u；CG(w) Gas Prices for being natural air-air source w；CS(s) day is extracted for gas storage facility s
The cost of right gas；Punit (u, t) is the active power output of t moment generating set u；Gwell(w, t) is t moment natural air-air source w's
Gas production；Sout(s, t) is the amount of natural gas that t moment is extracted from gas storage facility s.
4. the method according to claim 1, wherein described solve the prediction model, to obtain multiple predictions
Active power output increment and gas production increment in the step-length time include:
Control variable is solved by rolling optimization and solves the prediction model, when obtaining in multiple prediction step times any one
Active power output increment and gas production increment in quarter.
5. according to the method described in claim 4, it is characterized in that, obtaining the multiple prediction step time by following formula
Active power output increment and gas production increment in any one interior moment:
Wherein, P (u, k+n Δ t) and G (and w, k+n Δ t) be respectively following k+n time Δt unit u predict at the k moment it is active out
The gas production of power and gas source w；P0(u, k) and G0(w, k) is respectively the initial value of k moment unit u and gas source w；Δup(u, k+t)
With Δ uw(w, k+t) is respectively the active power output increment and production gas increment of unit u and gas source w at the k+t moment；Δ t is in a few days to adjust
Spend time interval；N is prediction step.
6. method according to claim 1 or 5, which is characterized in that the active power output increment and gas production increment are as follows:
Wherein, P (u, k+t) and G (w, k+t) is respectively the active power output and gas production reference value at k+t moment；HGFor natural gas heat
Value.
7. according to the method described in claim 2, it is characterized in that, if the not up to described pre-set level, optimizes institute
Stating prediction model includes:
Determine according to the following formula the corresponding active power output of current time corresponding subsequent time and gas production using as optimization just
Initial value:
Wherein, P0(u, k+ Δ t) and G0(w, k+ Δ t) are respectively the active power output and gas production of k+ time Δt unit u and gas source w
Initial value；Preal(u, k+ Δ t) and Greal(w, k+ Δ t) are respectively the active power output of k+ time Δt unit u and natural air-air source w
With the practical measuring value of gas production；
According to the optimized initial value, the prediction model is optimized by rolling optimal dispatching.
8. a kind of energy dynamically optimized scheduling device for comprehensive energy, which is characterized in that described device includes:
Module is obtained, for obtaining the current active power output and gas production of integrated energy system；
Model building module establishes prediction model for the gas production based on the current active power output, and the prediction model is used
In the active processing and gas production of the integrated energy system for predicting the default expected time；
Module is solved, for solving the prediction model, to obtain the active power output increment and production in multiple prediction step times
Tolerance increment；
Tactful determining module, for according to it is the multiple prediction not for a long time in the first prediction step time in it is described active
Power output increment and gas production increment determine the Optimized Operation strategy of comprehensive energy；
Sending module, for sending the Optimized Operation strategy of the comprehensive energy.
9. device according to claim 8, which is characterized in that described device further include:
Judgment module, judges whether the prediction model meets pre-set level；
Optimization module, if the not up to described pre-set level, optimizes the prediction model.
10. a kind of electronic equipment characterized by comprising
Memory；
Processor；
And the energy dynamic optimization tune for comprehensive energy that is stored on the memory and can run on the processor
Program is spent, such as claim is realized when the energy dynamically optimized scheduling program for comprehensive energy is executed by the processor
The step of energy dynamically optimized scheduling method of comprehensive energy is used for described in any one of 1 to 7.
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| CN107732982A (en) * | 2017-10-20 | 2018-02-23 | 河海大学 | Consider the integrated energy system Multiple Time Scales dispatching method of Model Predictive Control |
| CN109031952A (en) * | 2018-07-18 | 2018-12-18 | 河海大学 | A kind of electric-gas interconnection integrated energy system mixing control method |
| CN109861305A (en) * | 2019-01-31 | 2019-06-07 | 东南大学 | A kind of transmission & distribution collaboration economic load dispatching method of binding model PREDICTIVE CONTROL |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107732982A (en) * | 2017-10-20 | 2018-02-23 | 河海大学 | Consider the integrated energy system Multiple Time Scales dispatching method of Model Predictive Control |
| CN109031952A (en) * | 2018-07-18 | 2018-12-18 | 河海大学 | A kind of electric-gas interconnection integrated energy system mixing control method |
| CN109861305A (en) * | 2019-01-31 | 2019-06-07 | 东南大学 | A kind of transmission & distribution collaboration economic load dispatching method of binding model PREDICTIVE CONTROL |
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