CN114865630A - Modeling method and device for thermoelectric unit - Google Patents

Modeling method and device for thermoelectric unit Download PDF

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CN114865630A
CN114865630A CN202210782942.4A CN202210782942A CN114865630A CN 114865630 A CN114865630 A CN 114865630A CN 202210782942 A CN202210782942 A CN 202210782942A CN 114865630 A CN114865630 A CN 114865630A
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thermoelectric
convex feasible
convex
feasible region
model
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陈新宇
金天昱
文劲宇
任正
曹阳
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Huazhong University of Science and Technology
Electric Power Research Institute of State Grid Eastern Inner Mongolia Power Co Ltd
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Electric Power Research Institute of State Grid Eastern Inner Mongolia Power Co Ltd
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Abstract

The invention discloses a modeling method and a device of a thermoelectric unit, belonging to the field of electrical engineering; the method includes the steps that based on vertex parameter values of non-convex feasible regions of the thermoelectric generating set, virtual boundaries are introduced to reconstruct the non-convex feasible regions, and a plurality of convex feasible regions formed by original boundaries and the virtual boundaries are formed; aiming at each convex feasible region, establishing a mathematical model strongly related to the vertex parameter of the convex feasible region; establishing a thermoelectric unit model of a non-convex feasible region by introducing a state judgment variable aiming at each convex feasible region and combining mathematical models of all convex feasible regions; and finally, introducing the thermoelectric generator set model of the non-convex feasible region into an optimized scheduling model of the power system, and realizing scheduling control on the thermoelectric generator set of the non-convex feasible region. The operation constraint of the thermoelectric generating set in the non-convex feasible region can be accurately reflected, and the scheduling mechanism is favorable for accurately controlling the operation state of the thermoelectric generating set in the non-convex feasible region; the capacity of the power system for absorbing wind power and photovoltaic is improved, and the overall operation cost of the system is reduced.

Description

Modeling method and device for thermoelectric unit
Technical Field
The invention belongs to the field of electrical engineering, and particularly relates to a modeling method and an optimized scheduling method of a thermoelectric unit in a non-convex feasible region.
Background
The thermoelectric unit is an indispensable position in the field of power supply and heat supply in China as a unit capable of simultaneously generating electric power and heat, particularly in northern areas in China, the installation of the thermoelectric unit exceeds more than half of the installation of all the thermoelectric units in the area, so that the power supply and heat supply output power of the thermoelectric unit is coordinated by optimizing and scheduling the thermoelectric unit, and great economic benefit is brought to the whole power system. And the optimal scheduling adopts a mathematical model of the thermoelectric unit, so that the accuracy of modeling of the thermoelectric unit directly influences the accuracy of a scheduling result.
Modeling for thermoelectric power plants generally starts from its feasible domain. The feasible regions of the thermoelectric unit can be divided into convex feasible regions and non-convex feasible regions, wherein a thermoelectric unit model with the convex feasible regions is mature, the modeling of the non-convex feasible region thermoelectric unit is rough, the modeling is generally simplified into a convex feasible region thermoelectric unit for approximate modeling, but the physical structure constraint of the non-convex feasible region thermoelectric unit is ignored, and the position of an operating point is often judged by adopting an iterative operation and alternate solution mode aiming at the optimal scheduling mode of the non-convex feasible region thermoelectric unit, so that the solving rate of the optimal scheduling of the power system is greatly reduced, and the scheduling efficiency of the system is seriously influenced.
Disclosure of Invention
Aiming at the defects or improvement requirements of the prior art, the invention provides a modeling method and an optimized scheduling method for a thermoelectric generating set in a non-convex feasible region, and aims to solve the technical problem that the thermoelectric generating set in the non-convex feasible region is difficult to perform mathematical modeling and participate in optimized scheduling of a power system.
In order to achieve the above object, the present invention provides a modeling method for a thermoelectric power unit in a non-convex feasible region, including:
s1, introducing a virtual boundary in a non-convex feasible region, and reconstructing the non-convex feasible region to form a plurality of convex feasible regions consisting of original boundaries and virtual boundaries;
s2, establishing a mathematical model strongly related to the vertex parameter of each convex feasible region obtained by reconstruction, and establishing a convex feasible region vertex parameter coefficient constraint model;
and S3, establishing a correlation model of the operation states of all convex feasible regions and the operation state of the whole thermoelectric unit, and combining the mathematical model and the constraint model corresponding to each convex feasible region obtained in the step S2 to obtain the mathematical model of the operation state of the thermoelectric unit in the whole non-convex feasible region.
Further, the mathematical model is specifically an electrical output model, a thermal output model or a cost model.
Further, the convex feasible domain vertex parameter coefficient constraint model is as follows:
Figure 677020DEST_PATH_IMAGE001
in the formula (I), the compound is shown in the specification,
Figure 509846DEST_PATH_IMAGE002
is shown as
Figure 667158DEST_PATH_IMAGE003
The thermoelectric unit is on
Figure 319856DEST_PATH_IMAGE004
The operating state of each convex feasible region when
Figure 219153DEST_PATH_IMAGE005
When is at
Figure 906486DEST_PATH_IMAGE003
The thermoelectric unit operates on
Figure 969120DEST_PATH_IMAGE004
A convex feasible domain; when in use
Figure 843535DEST_PATH_IMAGE006
When is at
Figure 282607DEST_PATH_IMAGE003
The thermoelectric generator set does not operate at the first time
Figure 824447DEST_PATH_IMAGE004
A convex feasible domain.
Further, the correlation model of the operation states of all convex feasible regions and the operation state of the whole thermoelectric unit is as follows:
Figure 808715DEST_PATH_IMAGE007
in the formula (I), the compound is shown in the specification,
Figure 170426DEST_PATH_IMAGE008
to represent
Figure 882030DEST_PATH_IMAGE003
The operating state of the thermoelectric power plant is constantly
Figure 543955DEST_PATH_IMAGE009
When is at
Figure 948392DEST_PATH_IMAGE003
The thermoelectric power unit is in operation state at any time
Figure 797399DEST_PATH_IMAGE010
When is at
Figure 312694DEST_PATH_IMAGE003
The thermoelectric unit is in a shutdown state at any moment.
Further, the mathematical model of the operation state of the thermoelectric unit in the whole non-convex feasible region is as follows:
Figure 812814DEST_PATH_IMAGE011
in the formula (I), the compound is shown in the specification,
Figure 388152DEST_PATH_IMAGE012
representing the number of convex feasible regions obtained by introducing virtual boundaries to reconstruct the non-convex feasible regions, and
Figure 990035DEST_PATH_IMAGE013
，
Figure 309021DEST_PATH_IMAGE014
is shown as
Figure 414380DEST_PATH_IMAGE016
A vertex in a convex feasible domain, an
Figure 426198DEST_PATH_IMAGE018
，
Figure 734951DEST_PATH_IMAGE019
Is shown as
Figure 857628DEST_PATH_IMAGE020
The number of vertices in the convex feasible domain,
Figure 83073DEST_PATH_IMAGE021
to represent
Figure 213DEST_PATH_IMAGE022
At the first moment
Figure 311109DEST_PATH_IMAGE020
The vertex parameter coefficient values of the convex-rowable domain,
Figure 971897DEST_PATH_IMAGE023
is shown as
Figure 786270DEST_PATH_IMAGE020
The vertex parameter value of each convex feasible region is taken as an electric power output value, a thermal power output value or a cost value according to the requirement,
Figure 657667DEST_PATH_IMAGE024
to represent
Figure 190280DEST_PATH_IMAGE022
Parameter values of thermoelectric power units at all times, corresponding
Figure 389180DEST_PATH_IMAGE023
The value of (a) is selected,
Figure 323638DEST_PATH_IMAGE025
to represent
Figure 848160DEST_PATH_IMAGE022
The power output value, the heat output value or the cost value of the thermoelectric unit at the moment.
Further, comprising: the thermoelectric unit model of the non-convex feasible region is applied to an electric power system optimization scheduling model, and Gurobi and Cplex solvers are adopted to carry out rapid solution to obtain an optimization scheduling result
In general, the above technical solutions contemplated by the present invention can achieve the following advantageous effects compared to the prior art.
The method is characterized in that a virtual boundary is introduced to reconstruct a non-convex feasible region based on a vertex parameter value of the non-convex feasible region of the thermoelectric generator set to form a plurality of convex feasible regions consisting of original boundaries and the virtual boundary, and all the convex feasible regions can form the original non-convex feasible region through splicing and combination; aiming at each convex feasible region formed by the original boundary and the virtual boundary, a mathematical model which is strongly related to the vertex parameter of the convex feasible region is established; establishing a thermoelectric unit model of a non-convex feasible region by introducing a state judgment variable aiming at each convex feasible region and combining mathematical models of all convex feasible regions; and finally, introducing the thermoelectric generator set model of the non-convex feasible region into an optimized scheduling model of the power system, and realizing scheduling control on the thermoelectric generator set of the non-convex feasible region.
The thermoelectric generating set model of the non-convex feasible region established by the technical scheme can accurately reflect the operation constraint of the thermoelectric generating set of the non-convex feasible region, and is beneficial to a scheduling mechanism to accurately control the operation state of the thermoelectric generating set of the non-convex feasible region; meanwhile, the thermoelectric generator set model of the non-convex feasible region can perfectly fit with the current mainstream power system optimization scheduling model, and the optimization scheduling result can be obtained by directly and quickly solving by adopting solvers such as Gurobi and Cplex; the thermoelectric generating set in the non-convex feasible region is optimally scheduled, so that the wind power and photovoltaic absorption capacity of the power system is improved, and the overall operation cost of the system is reduced.
Drawings
Fig. 1 is a diagram of a typical operating area of a non-convex-feasible-area thermoelectric power generation unit provided by the invention.
FIG. 2 is a diagram of an operating area of a thermoelectric power plant with non-convex feasible regions formed by combining a plurality of convex feasible regions after virtual boundaries are introduced.
Fig. 3 is a comparison graph of the amount of the wind curtailment provided by the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
The invention provides a modeling method of a thermoelectric unit in a non-convex feasible region, which comprises the following specific contents:
the thermoelectric unit can provide power and heat simultaneously, the feasible region of most thermoelectric units is convex, and the feasible region of a small part is non-convex, so that the operation interval of the thermoelectric unit with the non-convex feasible region cannot be represented by linear combination of vertexes of the feasible region, the typical operation interval of the thermoelectric unit with the non-convex feasible region is shown in FIG. 1, and the feasible region boundary is composed of AB, BC, CD, DE, EF, FG, GH and HA.
By introducing a virtual boundary, it is possible to,and reconstructing the non-convex feasible region to form a plurality of convex feasible regions consisting of the original boundary and the virtual boundary, and combining and splicing all the convex feasible regions to restore the original non-convex feasible region. As shown in fig. 2, introducing virtual boundaries BG and CF and reconstructing an original non-convex feasible region ABCDEFGH can obtain
Figure 868069DEST_PATH_IMAGE026
Three convex regions of which
Figure 886971DEST_PATH_IMAGE027
Is composed of original boundaries AB, GH and HA and a virtual boundary BG,
Figure 675936DEST_PATH_IMAGE028
is composed of original boundaries BC and FG and virtual boundaries BG and CF,
Figure 105780DEST_PATH_IMAGE029
is formed by the original boundaries CD, DE and EF and the virtual boundary CF. Thus, the number of the first and second electrodes,
Figure 878564DEST_PATH_IMAGE027
the operating state within the operating interval can be represented by a linear combination strongly correlated with the parameters of A, B, G and the four vertices of H, which, as such,
Figure 684846DEST_PATH_IMAGE028
the operating state within the operating interval can be represented by a linear combination strongly correlated with the parameters of B, C, F and the four vertices of G,
Figure 328317DEST_PATH_IMAGE029
the operating state within the operating interval may be represented by a linear combination strongly correlated with the parameters of C, D, E and the four vertices of F.
Is provided with
Figure 194642DEST_PATH_IMAGE030
Are respectively an operating region
Figure 438410DEST_PATH_IMAGE026
The values of the vertex parameters of (a),
Figure 48383DEST_PATH_IMAGE031
which is indicative of the value of the power output,
Figure 811940DEST_PATH_IMAGE032
、
Figure 583587DEST_PATH_IMAGE033
thermoelectric units with non-convex feasible regions for representing thermal output values
Figure 65383DEST_PATH_IMAGE022
Power output at a time
Figure 495359DEST_PATH_IMAGE034
And thermal output
Figure 113422DEST_PATH_IMAGE035
Can be respectively expressed as:
Figure 321550DEST_PATH_IMAGE036
（1）
Figure 25063DEST_PATH_IMAGE037
（2）
in the formula (I), the compound is shown in the specification,
Figure 976839DEST_PATH_IMAGE038
is that
Figure 449408DEST_PATH_IMAGE039
The coefficient value of the region vertex parameter satisfies the following equation:
Figure 828437DEST_PATH_IMAGE040
（3）
Figure 271444DEST_PATH_IMAGE041
（4）
Figure 26911DEST_PATH_IMAGE042
（5）
in the formula (I), the compound is shown in the specification,
Figure 619566DEST_PATH_IMAGE043
respectively showing the operation states of the thermoelectric power unit in different operation areas. If it is
Figure 169496DEST_PATH_IMAGE044
When it is, it means that the thermoelectric power unit is operated in the region
Figure 582023DEST_PATH_IMAGE045
In (1),
Figure 141180DEST_PATH_IMAGE046
indicating operation of thermoelectric power units in zones
Figure 339075DEST_PATH_IMAGE028
In (1),
Figure 59906DEST_PATH_IMAGE047
indicating operation of thermoelectric power units in zones
Figure 225308DEST_PATH_IMAGE048
In (1).
Since the thermoelectric power plant has only one operating point, the following constraints need to be satisfied:
Figure 322577DEST_PATH_IMAGE049
（6）
Figure 624245DEST_PATH_IMAGE050
（7）
in the formula (I), the compound is shown in the specification,
Figure 515978DEST_PATH_IMAGE051
indicating the operating state of the thermoelectric power plant when
Figure 417944DEST_PATH_IMAGE052
When the thermoelectric power unit is in operation, the thermoelectric power unit is in operation
Figure 53324DEST_PATH_IMAGE053
And when the thermoelectric generator set is in a shutdown state.
Correspondingly, thermoelectric units with non-convex operable zones are provided
Figure 475079DEST_PATH_IMAGE054
Running cost of time of day
Figure 537712DEST_PATH_IMAGE055
Or can be made of
Figure 412128DEST_PATH_IMAGE056
Figure 851199DEST_PATH_IMAGE057
The vertex running cost of a region is linearly expressed:
Figure 127460DEST_PATH_IMAGE058
（8）
in the formula (I), the compound is shown in the specification,
Figure 111727DEST_PATH_IMAGE059
respectively representing regions
Figure 473439DEST_PATH_IMAGE060
To middle
Figure 716201DEST_PATH_IMAGE061
The cost of running the individual vertices.
In the electric power system, there are multiple power supply, heating equipment, and power supply equipment includes thermal power generating set, thermoelectric generator set, wind-powered electricity generation, photovoltaic etc. and heating equipment includes thermoelectric generator set, coal-fired heat supply boiler, electric boiler etc. and the system will be with the minimizing cost, carries out the optimal scheduling to above-mentioned power supply, heating equipment, and its objective function is:
Figure 112547DEST_PATH_IMAGE062
（9）
in the formula (I), the compound is shown in the specification,
Figure 516984DEST_PATH_IMAGE063
respectively represent
Figure 100412DEST_PATH_IMAGE054
The cost of the thermal power generating unit and the coal-fired heat supply boiler at the moment, which meet the following equation constraints:
Figure 399063DEST_PATH_IMAGE064
（10）
Figure 649915DEST_PATH_IMAGE065
（11）
in the formula (I), the compound is shown in the specification,
Figure 225253DEST_PATH_IMAGE066
represents the electric output power of the thermal power generating unit at the moment,
Figure 561557DEST_PATH_IMAGE067
represents a transfer function between the power output and the cost of the thermal power generating unit,
Figure 880543DEST_PATH_IMAGE068
to represent
Figure 985902DEST_PATH_IMAGE054
The thermal output power of the coal-fired heat supply boiler is constantly,
Figure 732141DEST_PATH_IMAGE069
representing the transfer function between the thermal output power and the cost of the coal-fired heating boiler.
The system needs to satisfy the electric power balance constraint and the thermal power balance constraint:
Figure 572052DEST_PATH_IMAGE070
（12）
Figure 429150DEST_PATH_IMAGE071
（13）
in the formula (I), the compound is shown in the specification,
Figure 654595DEST_PATH_IMAGE072
respectively represent
Figure 837314DEST_PATH_IMAGE054
The power output of photovoltaic and wind power at the moment,
Figure 882631DEST_PATH_IMAGE073
to represent
Figure 543419DEST_PATH_IMAGE054
The power consumption of the electric boiler is controlled at any moment,
Figure 872638DEST_PATH_IMAGE074
to represent
Figure 960680DEST_PATH_IMAGE054
The power demanded by the electricity of the system at the time,
Figure 758872DEST_PATH_IMAGE075
to represent
Figure 223351DEST_PATH_IMAGE054
The thermal output power of the electric boiler at the moment,
Figure 157809DEST_PATH_IMAGE076
to represent
Figure 682331DEST_PATH_IMAGE054
The thermal demand power of the system at that moment.
The operation of the electric boiler needs to satisfy the following constraints:
Figure 452972DEST_PATH_IMAGE077
（14）
in the formula (I), the compound is shown in the specification,
Figure 721143DEST_PATH_IMAGE078
indicating the efficiency of the conversion of electrical boiler consumption power into thermal output power.
In the modeling process, the virtual boundary is introduced to reconstruct the non-convex feasible region, so that the original non-convex feasible region is changed into a plurality of convex feasible regions formed by the original boundary and the virtual boundary.
In addition, the models (6) and (7) can meet the physical constraint of the unique operating point of the thermoelectric unit when the thermoelectric unit in the non-convex feasible region is scheduled, and meanwhile, compared with other technical schemes which adopt an alternate iterative algorithm to judge the operating condition of the thermoelectric unit in the non-convex feasible region, the technical scheme enables the scheduling system to directly judge the operating state of the thermoelectric unit in the non-convex feasible region through integral optimization, and the solving speed is increased.
The thermoelectric generator set model of the non-convex feasible region provided by the technical scheme can fully fit with the current mainstream power system optimization scheduling model, and after the thermoelectric generator set model of the non-convex feasible region provided by the technical scheme is added, the optimization scheduling model can still adopt solvers such as Gurobi and Cplex to carry out rapid solution.
Examples
Based on an IEEE-6 node system, example analysis is carried out, and the wind abandoning level and the light abandoning level of the system and the overall operation cost of the system are compared before and after a thermoelectric unit with non-convex feasible region characteristics participates in the optimal scheduling of the power system.
The 6-node system comprises 3 traditional thermal power generating units (
Figure 510107DEST_PATH_IMAGE079
) Two thermoelectric units with non-convex operable domain characteristics (
Figure 939951DEST_PATH_IMAGE080
) A wind farm (
Figure 712735DEST_PATH_IMAGE081
) And a photovoltaic field (
Figure 519017DEST_PATH_IMAGE082
). The power demand of the system is set to be evenly distributed by the nodes 3 and 6, and two heating areas are arranged in the system and are respectively positioned after the nodes 3 (the heating areas 1) and the nodes 6 (the heating areas 2). The combined heat and power generation unit 1 is used for supplying heat for the area 1 independently, the combined heat and power generation unit 2 is used for supplying heat for the area 2 independently, a 120MW coal-fired heat supply boiler is arranged in the area 1, a 50MW electric boiler is arranged in the area 2, and the coal-fired heat supply boiler and the 50MW electric boiler are matched with the combined heat and power generation unit to operate, so that the heat balance of each heat supply area is realized.
In order to compare the effects before and after the thermoelectric generating set with the non-convex feasible region characteristic participates in the optimized dispatching of the power system, a control variable method is adopted, and two simulation scenes are set. In the first scenario, the ratio of the thermal output value of the thermoelectric unit No. 1 to the thermal load of the heat supply area 1 is fixed to be 0.7, and the thermoelectric unit No. 2 participates in the optimized scheduling of the power system; in the second scenario, both the two thermoelectric units always participate in the optimized scheduling of the power system.
The load, wind-solar output and other constraints are the same in scenario one and scenario two.
The wind curtailment and light curtailment of the scene one and the scene two are obtained through simulation analysis, and a comparison graph is shown in fig. 3.
In the two scenes, no wind curtailment is generated in the time periods 1-4 and 13-24, and in all other time periods, the wind curtailment quantity of the scene one is larger than that of the scene two. In the 5 th to 6 th time periods, the wind abandoning and light abandoning phenomena are avoided in the second scene, and the wind abandoning and light abandoning quantity of the first scene reaches 9.3MWh and 49.1 MWh; in the 7 th to 10 th time periods, the wind curtailment quantity of the scene two is reduced by more than 50% compared with the scene one, and the reduction degree is maximum to 65.4% in the 7 th time period. The total wind curtailment in scenario one is 695.9MWh, while the total wind curtailment in scenario two is 318.8MWh, which is 54.2% less.
The total operating cost of the system for scenario one and scenario two is shown in table 1,
Figure 162488DEST_PATH_IMAGE083
it can be seen from table 1 that after the two thermoelectric power units all participate in the optimal scheduling of the power system, the total system cost is reduced from 55.67 ten thousand yuan to 54.80 ten thousand yuan, which is reduced by 1.6%, and the operation cost of the system is reduced by performing the optimal scheduling on the thermoelectric power unit having the non-convex feasible region characteristic.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (7)

1. A modeling method for a thermoelectric unit with a non-convex feasible region is characterized by comprising the following steps:
s1, introducing a virtual boundary in a non-convex feasible region, and reconstructing the non-convex feasible region to form a plurality of convex feasible regions consisting of original boundaries and virtual boundaries;
s2, establishing a mathematical model strongly related to the vertex parameter of each convex feasible region obtained by reconstruction, and establishing a convex feasible region vertex parameter coefficient constraint model;
and S3, establishing a correlation model of the operation states of all convex feasible regions and the operation state of the whole thermoelectric unit, and combining the mathematical model and the constraint model corresponding to each convex feasible region obtained in the step S2 to obtain the mathematical model of the operation state of the thermoelectric unit in the whole non-convex feasible region.
2. The modeling method for the thermoelectric generating set of the non-convex feasible region as claimed in claim 1, wherein the mathematical model is specifically an electric power output model, a thermal power output model or a cost model.
3. The modeling method for the thermoelectric generating set of the non-convex feasible region as claimed in claim 2, wherein the convex feasible region vertex parameter coefficient constraint model is:
Figure 182530DEST_PATH_IMAGE001
in the formula (I), the compound is shown in the specification,
Figure 177031DEST_PATH_IMAGE002
is shown as
Figure 52583DEST_PATH_IMAGE003
The thermoelectric unit is on
Figure 550560DEST_PATH_IMAGE004
The operating state of each convex feasible region when
Figure 338519DEST_PATH_IMAGE005
When is at
Figure 554737DEST_PATH_IMAGE003
The thermoelectric unit operates on
Figure 702821DEST_PATH_IMAGE004
A convex feasible domain; when in use
Figure 586464DEST_PATH_IMAGE006
When is at
Figure 60170DEST_PATH_IMAGE003
The thermoelectric generator set does not operate at the first time
Figure 763684DEST_PATH_IMAGE004
A convex feasible domain.
4. The modeling method for the thermoelectric generating set with the non-convex feasible region as claimed in claim 3, wherein the correlation model of the operation states of all convex feasible regions and the operation state of the whole thermoelectric generating set is as follows:
Figure 967657DEST_PATH_IMAGE007
Figure 440226DEST_PATH_IMAGE008
in the formula (I), the compound is shown in the specification,
Figure 819255DEST_PATH_IMAGE009
to represent
Figure 275644DEST_PATH_IMAGE003
The operating state of the thermoelectric power plant is constantly
Figure 765532DEST_PATH_IMAGE010
When is at
Figure 623766DEST_PATH_IMAGE003
The thermoelectric power unit is in operation state at any time
Figure 658849DEST_PATH_IMAGE011
When is at
Figure 336955DEST_PATH_IMAGE003
The thermoelectric unit is in a shutdown state at any moment.
5. The modeling method for the thermoelectric generating set in the non-convex feasible region as claimed in claim 4, wherein the mathematical model of the operating state of the thermoelectric generating set in the whole non-convex feasible region is as follows:
Figure 630533DEST_PATH_IMAGE013
in the formula (I), the compound is shown in the specification,
Figure 343275DEST_PATH_IMAGE014
representing the number of convex feasible regions obtained by introducing virtual boundaries to reconstruct the non-convex feasible regions, and
Figure 64106DEST_PATH_IMAGE015
，
Figure 963929DEST_PATH_IMAGE017
is shown as
Figure 795619DEST_PATH_IMAGE019
A vertex in a convex feasible domain, an
Figure 877713DEST_PATH_IMAGE021
，
Figure 769446DEST_PATH_IMAGE022
Is shown as
Figure 156565DEST_PATH_IMAGE023
The number of vertices in the convex feasible domain,
Figure DEST_PATH_IMAGE024
to represent
Figure DEST_PATH_IMAGE025
At the first moment
Figure 588683DEST_PATH_IMAGE023
The vertex parameter coefficient values of the convex-rowable domain,
Figure DEST_PATH_IMAGE026
is shown as
Figure 292328DEST_PATH_IMAGE023
The vertex parameter value of each convex feasible region is taken as an electric power output value, a thermal power output value or a cost value according to the requirement,
Figure DEST_PATH_IMAGE027
to represent
Figure 620541DEST_PATH_IMAGE025
Parameter values of thermoelectric power units at all times, corresponding
Figure 494956DEST_PATH_IMAGE026
The value of (a) is selected,
Figure DEST_PATH_IMAGE028
to represent
Figure 934028DEST_PATH_IMAGE025
The power output value, the heat output value or the cost value of the thermoelectric unit at the moment.
6. An optimized scheduling method based on the modeling method of any one of claims 1-5, comprising: and applying the thermoelectric unit model of the non-convex feasible region to an optimized scheduling model of the power system, and quickly solving by adopting Gurobi and Cplex solvers to obtain an optimized scheduling result.
7. A modeling device for a thermoelectric power unit with a non-convex feasible region is characterized by comprising: a computer-readable storage medium and a processor; the computer-readable storage medium is used for storing executable instructions; the processor is used for reading executable instructions stored in the computer readable storage medium and executing the modeling method of the non-convex feasible domain thermoelectric power generating unit as claimed in any one of claims 1 to 5.
CN202210782942.4A 2022-07-05 2022-07-05 Modeling method and device for thermoelectric unit Pending CN114865630A (en)

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