CN111146819B - Electric heating combined system auxiliary service scheduling method considering heat supply network characteristics - Google Patents

Electric heating combined system auxiliary service scheduling method considering heat supply network characteristics Download PDF

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CN111146819B
CN111146819B CN201911367823.7A CN201911367823A CN111146819B CN 111146819 B CN111146819 B CN 111146819B CN 201911367823 A CN201911367823 A CN 201911367823A CN 111146819 B CN111146819 B CN 111146819B
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边晓燕
邹黎明
史越奇
赵健
王小宇
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Shanghai Electric Power University
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Abstract

The invention relates to an auxiliary service scheduling method of an electric heating combined system considering heat supply network characteristics, which comprises the following steps: 1) obtaining a feasible operation interval for mutual coordination of the thermoelectric generating set and the electric boiler according to the adjusting characteristics of the thermoelectric generating set and the electric boiler; 2) constructing an optimized scheduling model of the electric-heating combined system considering the characteristics of the heat supply network, taking a profit and cost model of the thermoelectric unit participating in the auxiliary peak shaving service as an objective function, and solving under a constraint condition to obtain an optimized scheduling scheme of the electric-heating combined system; 3) and executing electric heating combined system optimized dispatching participating in the auxiliary service market. Compared with the prior art, the method has the advantages of effectively excavating peak shaving capacity of the thermoelectric generator set, improving the problem of abandoned wind in the power system, having remarkable economic benefit in the aspects of peak shaving of the generator set and wind power consumption and the like.

Description

Electric heating combined system auxiliary service scheduling method considering heat supply network characteristics
Technical Field
The invention relates to the technical field of scheduling of an electric heating combined system, in particular to an auxiliary service scheduling method of the electric heating combined system considering the characteristics of a heat supply network.
Background
The power generation mode of cogeneration can effectively utilize the waste heat generated by the generator set, and the efficiency and the economy of the generator set are improved. However, the traditional cogeneration operation mode is limited by the operation of fixing electricity by heat in the heat supply period, the adjustment range of the electric output is small due to the thermal constraint of the unit, so that the peak regulation capacity is insufficient, and the high operation electric output occupies the wind power on-line space, so that the serious wind abandon phenomenon is caused.
In recent years, researchers have proposed various schemes for improving the peak shaving capability of the unit and alleviating the problem of wind curtailment, such as configuring a large-capacity heat storage device in the system, configuring an electric boiler in a thermoelectric system, and the like. Compared with the traditional thermoelectric unit, although a part of peak regulation space is obtained in advance, the real-time operation process is not considered, the huge heat storage potential existing in the heat supply system can not be fully utilized, and in addition, the traditional method for improving the peak regulation capacity of the thermoelectric unit is researched on the side of a thermodynamic system and does not consider the effect of the heat supply network characteristic on the peak regulation market.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide an auxiliary service scheduling method of an electric heating combined system considering the characteristics of a heat supply network.
The purpose of the invention can be realized by the following technical scheme:
an electric heating combined system auxiliary service scheduling method considering heat supply network characteristics comprises the following steps:
1) obtaining a feasible operation interval for mutual coordination of the thermoelectric generating set and the electric boiler according to the adjusting characteristics of the thermoelectric generating set and the electric boiler;
2) constructing an optimized scheduling model of the electric-heating combined system considering the characteristics of the heat supply network, taking a profit and cost model of the thermoelectric unit participating in the auxiliary peak shaving service as an objective function, and solving under a constraint condition to obtain an optimized scheduling scheme of the electric-heating combined system;
3) and executing electric heating combined system optimized dispatching participating in the auxiliary service market.
In the step 1), the feasible operation interval of the mutual coordination of the thermoelectric unit and the electric boiler is described as follows by a convex inequality:
Pi,t≥max{Pi min-Cv,iQi,t，Pco+Cm,iQi,t}
Pi,t≤Pi max-Cv,iQi,t
0≤Qi,t≤Qi max
wherein, Pi maxAnd Pi minMaximum and minimum electrical output, P, of the thermoelectric power unit ii,tThe electric output at the time t of the thermoelectric unit, PcoIs the intercept of the maximum steam admission working condition curve of the thermoelectric unit on the vertical axis, Cv,iThe slope of the pure condensing condition curve of the thermoelectric unit, Qi,tThe thermal output of the thermoelectric power plant i, Cm,iIs the slope of the minimum condensate condition curve, Q, of the thermoelectric uniti maxThe maximum thermal output of the thermoelectric unit.
In the step 2), the objective function of the optimal scheduling model of the electric heating combined system considering the heat supply network characteristics is as follows:
Figure BDA0002338900120000021
Figure BDA0002338900120000022
C2＝rn(SN*Rn-PN)Tp
C3＝λ1+λ2*(Pi,t)+λ3*(mi,t)+λ4*(Pi,t)2+λ5*(mi,t)2+λ6*(Pi,t)*(mi,t)
wherein theta is the coal price, C1For the amount of the unit peak shaving income, EnFor the clearing price of the nth gear, PnCompensated peak shaving power for nth gear, C2Compensating the electric quantity loss in the deep peak regulation time period after the thermoelectric generator set participating in the auxiliary service market reaches the deep peak regulation, rnCompensation standard for nth gear of peak regulation of thermoelectric generator set, PNThe average output of the unit in the scheduling time is SNAs unit capacity, RnFor compensating prices in nth gear, TpFor a deep peak shaving period within a scheduling period, C3For the increased running coal consumption cost, lambda, of the thermoelectric unit during deep peak shaving1、λ2、λ3、λ4、λ5、λ6Are all fitting coefficients, mi,tQuality of steam extraction for heat supply of thermoelectric units, Pi,tThe electric output, delta P, at time t of the thermoelectric unitt,iAnd the difference value between the compensated peak regulation electric quantity and the required peak regulation electric quantity at the moment T of the thermoelectric unit is represented, and T is a set formed by all scheduling time periods.
The constraint conditions of the optimal scheduling model of the electric-heating combined system considering the heat supply network characteristics comprise power supply balance constraint of a power system, unit output constraint, unit climbing constraint and thermodynamic system constraint.
The power supply balance constraint of the power system is as follows:
Figure BDA0002338900120000031
wherein the content of the first and second substances,
Figure BDA0002338900120000032
for the power output of the j thermal power generating unit at the moment t,
Figure BDA0002338900120000033
for the power output of the ith thermoelectric unit at the moment t,
Figure BDA0002338900120000034
is the electric output of the kth wind turbine at the moment t,
Figure BDA0002338900120000035
the power of the electrical load/at time t.
The unit output constraint comprises the thermal power unit and the wind power unit operation output constraint, and the method comprises the following steps:
Figure BDA0002338900120000036
Figure BDA0002338900120000037
wherein the content of the first and second substances,
Figure BDA0002338900120000038
respectively the minimum limit and the maximum limit of the electric power output of the jth thermal power generating unit at the moment t,
Figure BDA0002338900120000039
and the maximum limit of the electric output of the kth wind turbine at the moment t is obtained.
The unit climbing constraint is as follows:
Figure BDA00023389001200000310
Figure BDA00023389001200000311
wherein the content of the first and second substances,
Figure BDA00023389001200000312
respectively the electric power output of the jth thermal power generating unit at the time t and the time t +1,
Figure BDA00023389001200000313
the power output of the ith thermoelectric unit at the time t and the time t +1 respectively,
Figure BDA00023389001200000314
respectively the maximum electric output of the jth thermal power generating unit allowed to be reduced or increased from the moment t to the moment t +1,
Figure BDA00023389001200000315
the maximum electric output of the ith thermoelectric unit allowed to be lowered or raised from the moment t to the moment t + 1.
The thermodynamic system constraints include:
and (3) restraining the heat exchange process inside the heat exchanger:
Figure BDA00023389001200000316
wherein Q is the heat exchange power of the heat exchanger, k is the heat exchange coefficient of the heat exchanger, A is the heat exchange area of the heat exchanger, and T ishot,in、Thot,outIs the inlet and outlet temperature, T, of the high temperature side of the heat exchangercold,in、Tcold,outThe inlet and outlet temperature of the low temperature side of the heat exchanger;
heat pipe network constraint:
Figure BDA00023389001200000317
Figure BDA0002338900120000041
wherein, Tt in、
Figure BDA0002338900120000042
TsoilRespectively the temperature of the pipeline inlet at the time t, the temperature of the pipeline outlet at the time t + lambda and the ambient soil environment, lambda is a value obtained by discretizing the delay time delta tau of the pipeline according to a scheduling interval delta t and then integrating cw、ρwIs the specific heat capacity and density of water, mu is the heat loss coefficient, L, R is the length and radius of the pipe, mpipeThe heat flow circulation flow in the pipeline is adopted;
building heat storage property constraint:
Figure BDA0002338900120000043
Qr＝ηcwmpipe(tr-te)
Ql＝vS(Tin-Tout)
wherein c is the total indoor heat capacity of the building, TinIs the indoor temperature, eta is the heat dissipation efficiency of the radiator, trTemperature of water supply to radiator inlet, teIs the average indoor temperature, Q, of a buildingrHeat dissipating capacity of the radiator, v is indoor heat loss per unit area per unit temperature difference, S is heat supply area, ToutIs the outdoor temperature, QlIs a loss of heat within the building.
Compared with the prior art, the invention has the following advantages:
the auxiliary service scheduling method of the electric heating combined system analyzes and models the flexible adjustment capacity of the thermoelectric generator set which can participate in the auxiliary service, considers the auxiliary service peak regulation excitation in the peak regulation cost objective function, increases the influence of the heat supply network characteristic in the constraint condition, effectively excavates the peak regulation capacity of the thermoelectric generator set, improves the wind abandoning problem in the power system and has obvious economic benefits in the aspects of peak regulation of the generator set and wind power consumption by adjusting the characteristic parameters of the heat supply network and performing the auxiliary service peak regulation excitation on the thermoelectric generator set.
Drawings
Fig. 1 is a schematic diagram of an operable interval of the steam extraction type thermoelectric power unit.
Fig. 2 is a diagram of a thermodynamic system architecture.
Fig. 3 is a heat exchange schematic diagram of a counter-flow heat exchanger.
Fig. 4 is a model of a heat supply network pipeline structure.
FIG. 5 is a diagram of a building load model.
Fig. 6 is a schematic diagram of the thermoelectric power unit with compensation peak regulation.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments.
Example (b):
the invention provides an auxiliary service scheduling method of an electric-heat combined system considering heat supply network characteristics, which comprises the following steps:
and step 1, analyzing the flexibility of the thermoelectric unit. Meanwhile, the adjustment characteristics of the thermoelectric unit and the electric boiler are considered, and the feasible operation interval of the thermoelectric unit and the electric boiler which are mutually coordinated is described in the form of a convex inequality.
And 2, establishing a mathematical model of the heat supply network characteristics. Mathematical models are established for the heat exchanger, the heat pipe network and the thermal load, respectively. The heat exchanger model considers the internal heat exchange characteristics of the heat exchanger model; the heat pipe network model considers the loss and time delay existing at the inlet and the outlet of the heat pipe network model; the heat load model takes a heating building as a reference, and respectively considers three parts of a radiator, indoor air and a building maintenance structure.
And 3, establishing a profit and cost model of the thermoelectric unit participating in the auxiliary peak shaving service. The profit of the peak shaving service of the thermoelectric generator set, which is paid by other generator sets purchasing this part of capacity; after the thermoelectric generator set reaches deep peak shaving, the current policy in China can compensate the electric quantity loss in the deep peak shaving time period; the unit participates in deep peak regulation, so that the operation efficiency of the unit is reduced, and the operation coal consumption cost is increased.
And 4, establishing an optimized scheduling model of the electric heating combined system. The optimized scheduling model comprises an objective function and a constraint condition. The objective function is the profit and cost model established in step 3; the constraint conditions comprise power supply balance constraint of the power system, unit output constraint, unit climbing constraint and thermodynamic system constraint. Wherein, the thermodynamic system constraint is the heat supply network characteristic model established in the step 2.
And 5, executing electric heating combined system optimized dispatching participating in the auxiliary service market. In the day-ahead stage, the power plant reports the day-deep peak shaving service quotation and the active output adjustable interval of the operating unit to the governed scheduling mechanism before 10 hours a day; in the in-day stage, the power grid operation dispatcher preferentially calls the gratuitous peak regulation service of each power plant, and after the gratuitous peak regulation service is completely called, the low-price peak regulation service is preferentially called according to the quotation sequence of each power plant; and calculating the income and cost of the power plant at a later stage.
Step 1, analyzing the flexibility of the thermoelectric unit
The thermoelectric unit is usually a steam extraction and condensation type thermoelectric unit, the operation feasible region of which is shown as a polygon ABCD in figure 1, AB and CD respectively represent the maximum steam inlet working condition and the minimum steam inlet working condition of the unit, BC and DA represent the minimum condensation working condition of the unit (the slope is C)m) And pure condensing working condition, the inclined parallel line represents the relationship of electric and thermal output under different steam admission quantities, and the slope is Cv,i。. In the heat supply period, the air temperature is low, and the unitHeat output Qi,tThe operation is always close to the maximum value, the adjustable power interval is close to the point B, such as a section E1F1 in the figure, the peak shaving capacity is limited, and the flexibility is low.
The feasible operation interval of the thermoelectric unit can be described by a group of convex inequalities:
Pi,t≥max{Pi min-Cv,iQi,t，Pco+Cm,iQi,t} (1)
Pi,t≤Pi max-Cv,iQi,t (2)
0≤Qi,t≤Qi max (3)
in the formula: pi maxAnd Pi minThe maximum and minimum electric output of the thermoelectric unit are respectively; pcoIs the intercept of BA on the vertical axis.
As shown in figure 1, under the traditional 'heating and power-fixing' operation mode of the thermoelectric power unit, the heat output of the unit is Qi,tThe electric power of the thermoelectric generator set can be adjusted in E1F1, the adjustable range of the electric power of the thermoelectric generator set is small, the thermoelectric generator set also has a large downward adjusting space, and when the proportion of the thermoelectric generator set is high, the thermoelectric generator set occupies the space of wind power on-line, and the wind power absorption and the flexibility of a system are seriously influenced.
In order to increase the regulating capacity of the thermoelectric unit, the thermoelectric unit can be operated in cooperation with other thermal equipment such as an electric boiler and heat storage, and the thermal equipment shares part of heat supply output, so that the thermoelectric unit can reduce the output of the thermoelectric unit under the condition of constant heat supply load, such as operating in a graph Q1At this time, the electric output range of the thermoelectric generator set is increased to E2F2, and compared with the traditional method of 'fixing the electricity with heat', a part of scheduling space is increased.
In the real-time operation stage, after the thermal characteristics of a thermodynamic system such as a heat pipe network, a heat exchanger and a heat load are considered, the thermal output of the thermoelectric unit does not need to correspond to the heat load in real time, heat can be stored in a building and the heat network in advance, the thermal output can be released in a heat load peak, and the output of the thermoelectric unit to Q in the graph is reduced2Where the adjustment range of the electrical output is increased to that in the figureE3F3 section, through the cooperation of thermoelectric generator group and thermodynamic system, further promoted thermoelectric generator group's regulation space, promote wind-powered electricity generation to surf the net.
Step 2, establishing a mathematical model of the thermodynamic system
The thermodynamic system is constructed as shown in fig. 2, and mainly comprises a heat source, a heat exchanger, a heat pipe network and a heat load. The heat source is a steam extraction type thermoelectric unit, the heat load is a building, and the heat pipe network consists of a water supply pipe network and a water return pipe network. After steam is pumped out from the intermediate pressure cylinder section of the steam turbine, the steam flows through the heat exchanger to exchange heat with the cold water pipeline, and finally the heat energy requirement of a centralized heat supply user is met.
The structure of the heat exchanger is shown in fig. 3. Under the condition of a certain heat load, the heat output of the thermoelectric unit is influenced by the self properties such as the heat exchange area of the heat exchanger and the internal heat exchange characteristics of the heat exchanger. The internal heat exchange process of the heat exchanger can be described as follows:
Figure BDA0002338900120000071
in the formula: q is the heat exchange power of the heat exchanger; k is the heat exchange coefficient of the heat exchanger; a is the heat exchange area of the heat exchanger; t ishot,in、Thot,outThe inlet and outlet temperature of the high temperature side of the heat exchanger; t iscold,in、Tcold,outIs the inlet and outlet temperature of the low temperature side of the heat exchanger.
The hot water flows in the pipe in heat exchange with the external environment, and there are certain losses and time delays at the inlet and outlet of the pipe due to the limitation of the hot water flow rate. A single conduit is shown in figure 4. For a particular pipe, the relationship between outlet and inlet hot water temperature is:
Figure BDA0002338900120000072
the pipeline delay time is:
Figure BDA0002338900120000073
in the formula:
Figure BDA0002338900120000074
Tt out、
Figure BDA0002338900120000075
the temperature of the pipeline inlet, the pipeline outlet and the ambient soil environment at the moment t are respectively set; lambda is obtained by discretizing the pipeline delay time according to a scheduling interval delta t and then rounding; c. Cw、ρwIs the specific heat capacity and density of water; l, R is the length and radius of the pipe; m ispipeThe heat flow circulation flow in the pipeline is adopted; mu is the coefficient of heat loss.
Hot water power Q at inlet and outlet of pipelinet inAnd Qt outThe relationship with temperature is:
Figure BDA0002338900120000076
Figure BDA0002338900120000077
the building thermal load model is shown in fig. 5. The radiator obtains the inside heat source as the building after the heat in the water supply pipe network, gives indoor air with heat transfer for the building temperature rises, stores heat in indoor air and outer wall, and the mathematical model description of radiator is:
Qr＝ηcwmpipe(tr-te) (9)
in the formula: eta is the heat dissipation efficiency of the radiator; t is trSupplying water temperature to the inlet of the radiator; t is teIs the building indoor average temperature; qrThe heat sink dissipates heat.
The heat loss from the building load can be expressed as:
Ql＝vS(Tin-Tout) (10)
in the formula: qlHeat loss in the building; v is the indoor heat loss per unit area per unit temperature difference, and is related to the properties of the building; s is the heat supply area; t isinIs the indoor temperature; t isoutIs the outdoor temperature.
Without considering the indoor internal disturbance heat, in conjunction with (9), (10), the thermodynamic model describing the thermal storage characteristics of the building can be described as:
Figure BDA0002338900120000081
in the formula: and c is the total indoor heat capacity of the building.
Step 3, peak shaving auxiliary service income and cost
The revenue of the thermoelectric units participating in the auxiliary service market is mainly the profit of providing the peak shaving service for compensation, and the income is paid by other units purchasing the capacity, and the sum of the peak shaving electric quantity of each gear and the product of the clearing price of the gear is the total cost. The method specifically comprises the following steps:
Figure BDA0002338900120000082
in the formula: c1Adjusting peak income amount for the unit; piThe compensated peak regulation electric quantity of the ith gear; eiThe clearing price of the ith grade.
After the unit participating in the auxiliary service market reaches the deep peak shaving, the unit will be compensated for power loss in the deep peak shaving time period:
C2＝rn(SN*Rn-PN)Tp (13)
in the formula, rnCompensation criterion for the nth gear of a unit peak regulation, RnThe compensation price for the nth gear; pNThe average output of the unit in the scheduling time is obtained; sNThe capacity of the unit; t ispIs a deep peak shaver period within a schedule period.
The unit participates in deep peak regulation to reduce the unit operation efficiency, and the operation coal consumption cost is increased:
Figure BDA0002338900120000083
in the formula: lambda [ alpha ]1、λ2、λ3、λ4、λ5、λ6Is a fitting coefficient; m isi,tThe steam extraction quality is supplied to the thermoelectric unit; pi,tThe power is the electric power of the thermoelectric unit.
Step 4, optimizing and scheduling model of electric heating combined system
For thermoelectric power generation units, the essence of participating in the auxiliary service market is how to respond to the peak shaving needs of the grid with the lowest operating costs or the highest market revenue. As shown in fig. 6, the lower oblique line part is the peak shaving demand condition of the system, the upper oblique line part is the peak shaving demand of the thermoelectric system responding to the power grid after considering the heat supply network characteristics, and the dotted line is the peak shaving demand period. In FIG. 6, pbIs the peak shaver reference capacity; p is a radical oft,rPeak shaving capacity required by the power grid at the moment t; Δ pt,iAnd the difference value between the compensated peak regulation electric quantity of the unit and the required peak regulation electric quantity is obtained. Wherein each time interval compensated peak regulation capacity P of thermoelectric unittfComprises the following steps:
Figure BDA0002338900120000091
establishing a thermoelectric system scheduling model considering auxiliary services:
Figure BDA0002338900120000092
in the formula: theta is coal price, Delta Pt,iAnd the difference value between the compensated peak regulation electric quantity and the required peak regulation electric quantity at the moment T of the thermoelectric unit is represented, and T is a set formed by all scheduling time periods.
The constraint conditions comprise power supply balance constraint, unit output constraint, unit climbing constraint and thermodynamic system constraint.
The supply balance constraints are as follows:
Figure BDA0002338900120000093
in the formula:
Figure BDA0002338900120000094
for the power output of the j thermal power generating unit at the moment t,
Figure BDA0002338900120000095
for the power output of the ith thermoelectric unit at the moment t,
Figure BDA0002338900120000096
is the electric output of the kth wind turbine at the moment t,
Figure BDA0002338900120000097
the power of the electrical load/at time t.
And (3) restraining the operating output of the thermal power generating unit and the wind power generating unit:
Figure BDA0002338900120000098
in the formula:
Figure BDA0002338900120000099
and
Figure BDA00023389001200000910
the minimum and maximum output limits are set for the operation of the thermal power generating unit; pk,t wp,maxThe method is the maximum limit of the running output of the wind turbine generator.
Unit climbing restraint:
Figure BDA00023389001200000911
in the formula:
Figure BDA00023389001200000912
are respectively the jth thermal power generatorThe electrical outputs at time t and time t +1,
Figure BDA00023389001200000913
the power output of the ith thermoelectric unit at the time t and the time t +1 respectively,
Figure BDA00023389001200000914
respectively the maximum electric output of the jth thermal power generating unit allowed to be reduced or increased from the moment t to the moment t +1,
Figure BDA00023389001200000915
the maximum electric output of the ith thermoelectric unit allowed to be lowered or raised from the moment t to the moment t + 1.
Constraints of thermodynamic systems include equations (4) - (11).
The invention analyzes and models the flexible regulation capacity of the thermoelectric unit which can participate in the auxiliary service, takes the auxiliary service peak regulation excitation mechanism into account in the peak regulation cost target function, considers the influence of the heat supply network characteristic in the constraint condition, and can excavate the peak regulation capacity of the thermoelectric unit by regulating the heat supply network characteristic parameter and carrying out the auxiliary service peak regulation excitation on the thermoelectric unit, thereby effectively improving the problem of wind abandon in the power system and having remarkable economic benefits in the aspects of peak regulation of the unit and wind power absorption. The simulation result verifies the effectiveness and feasibility of the method.

Claims (7)

1. An electric heating combined system auxiliary service scheduling method considering heat supply network characteristics is characterized by comprising the following steps:
1) obtaining a feasible operation interval for mutual coordination of the thermoelectric generating set and the electric boiler according to the adjusting characteristics of the thermoelectric generating set and the electric boiler;
2) an optimized scheduling model of the electric heating combined system considering the heat supply network characteristics is constructed, a profit and cost model of the thermoelectric generator set participating in the auxiliary peak shaving service is used as an objective function, and a solution is carried out under a constraint condition to obtain an optimized scheduling scheme of the electric heating combined system, wherein the objective function of the optimized scheduling model of the electric heating combined system considering the heat supply network characteristics is as follows:
Figure FDA0002889833600000011
Figure FDA0002889833600000012
C2＝rn(SN*Rn-PN)Tp
C3＝λ1+λ2*(Pi,t)+λ3*(mi,t)+λ4*(Pi,t)2+λ5*(mi,t)2+λ6*(Pi,t)*(mi,t)
wherein theta is the coal price, C1For the amount of the unit peak shaving income, EnFor the clearing price of the nth gear, PnCompensated peak shaving power for nth gear, C2Compensating the electric quantity loss in the deep peak regulation time period after the thermoelectric generator set participating in the auxiliary service market reaches the deep peak regulation, rnCompensation standard for nth gear of peak regulation of thermoelectric generator set, PNThe average output of the unit in the scheduling time is SNAs unit capacity, RnFor compensating prices in nth gear, TpFor a deep peak shaving period within a scheduling period, C3For the increased running coal consumption cost, lambda, of the thermoelectric unit during deep peak shaving1、λ2、λ3、λ4、λ5、λ6Are all fitting coefficients, mi,tQuality of steam extraction for heat supply of thermoelectric units, Pi,tThe electric output, delta P, at time t of the thermoelectric unitt,iThe difference value between the compensated peak regulation electric quantity and the required peak regulation electric quantity at the moment T of the thermoelectric unit is set, wherein T is a set formed by all scheduling time periods;
3) and executing electric heating combined system optimized dispatching participating in the auxiliary service market.
2. The auxiliary service scheduling method of an electric-heating combined system considering characteristics of a heat supply network according to claim 1, wherein in the step 1), the feasible operation interval of the mutual coordination of the thermoelectric power unit and the electric boiler is described by a convex inequality as follows:
Pi,t≥max{Pi min-Cv,iQi,t，Pco+Cm,iQi,t}
Pi,t≤Pi max-Cv,iQi,t
0≤Qi,t≤Qi max
wherein, Pi maxAnd Pi minMaximum and minimum electrical output, P, of the thermoelectric power unit ii,tThe electric output at the time t of the thermoelectric unit, PcoIs the intercept of the maximum steam admission working condition curve of the thermoelectric unit on the vertical axis, Cv,iThe slope of the pure condensing condition curve of the thermoelectric unit, Qi,tThe thermal output of the thermoelectric power plant i, Cm,iIs the slope of the minimum condensate condition curve, Q, of the thermoelectric uniti maxThe maximum thermal output of the thermoelectric unit.
3. The electric-heating combined system auxiliary service scheduling method considering the heat supply network characteristics as claimed in claim 1, wherein the constraints of the optimized scheduling model of the electric-heating combined system considering the heat supply network characteristics include a power supply balance constraint of an electric power system, a unit output constraint, a unit climbing constraint and a thermodynamic system constraint.
4. The electric-heat combined system auxiliary service scheduling method considering heat supply network characteristics according to claim 3, wherein the power supply balance constraint of the power system is as follows:
Figure FDA0002889833600000021
wherein the content of the first and second substances,
Figure FDA0002889833600000022
for the power output of the j thermal power generating unit at the moment t,
Figure FDA0002889833600000023
for the power output of the ith thermoelectric unit at the moment t,
Figure FDA0002889833600000024
is the electric output of the kth wind turbine at the moment t,
Figure FDA0002889833600000025
the power of the electrical load/at time t.
5. The method of claim 3, wherein the plant output constraints comprise thermal power plant and wind power plant operational output constraints, and further comprising:
Figure FDA0002889833600000026
Figure FDA0002889833600000027
wherein the content of the first and second substances,
Figure FDA0002889833600000028
respectively the minimum limit and the maximum limit of the electric power output of the jth thermal power generating unit at the moment t,
Figure FDA0002889833600000029
and the maximum limit of the electric output of the kth wind turbine at the moment t is obtained.
6. The electric-heat combined system auxiliary service scheduling method considering heat supply network characteristics according to claim 3, wherein the unit climbing constraint is as follows:
Figure FDA00028898336000000210
Figure FDA00028898336000000211
wherein the content of the first and second substances,
Figure FDA0002889833600000031
respectively the electric power output of the jth thermal power generating unit at the time t and the time t +1,
Figure FDA0002889833600000032
the power output of the ith thermoelectric unit at the time t and the time t +1 respectively,
Figure FDA0002889833600000033
respectively the maximum electric output of the jth thermal power generating unit allowed to be reduced or increased from the moment t to the moment t +1,
Figure FDA0002889833600000034
the maximum electric output of the ith thermoelectric unit allowed to be lowered or raised from the moment t to the moment t + 1.
7. A method as claimed in claim 3, wherein the thermodynamic system constraints include:
and (3) restraining the heat exchange process inside the heat exchanger:
Figure FDA0002889833600000035
wherein Q is the heat exchange power of the heat exchanger, k is the heat exchange coefficient of the heat exchanger, A is the heat exchange area of the heat exchanger, and T ishot,in、Thot,outIs the inlet and outlet temperature, T, of the high temperature side of the heat exchangercold,in、Tcold,outThe inlet and outlet temperature of the low temperature side of the heat exchanger;
heat pipe network constraint:
Figure FDA0002889833600000036
Figure FDA0002889833600000037
wherein, Tt in、
Figure FDA0002889833600000038
TsoilRespectively the temperature of the pipeline inlet at the time t, the temperature of the pipeline outlet at the time t + lambda and the ambient soil environment, lambda is a value obtained by discretizing the delay time delta tau of the pipeline according to a scheduling interval delta t and then integrating cw、ρwIs the specific heat capacity and density of water, mu is the heat loss coefficient, L, R is the length and radius of the pipe, mpipeThe heat flow circulation flow in the pipeline is adopted;
building heat storage property constraint:
Figure FDA0002889833600000039
Qr＝ηcwmpipe(tr-te)
Ql＝vS(Tin-Tout)
wherein c is the total indoor heat capacity of the building, TinIs the indoor temperature, eta is the heat dissipation efficiency of the radiator, trTemperature of water supply to radiator inlet, teIs the average indoor temperature, Q, of a buildingrHeat dissipating capacity of the radiator, v is indoor heat loss per unit area per unit temperature difference, S is heat supply area, ToutIs the outdoor temperature, QlIs a loss of heat within the building.
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CN113627033A (en) * 2021-08-27 2021-11-09 西安热工研究院有限公司 Heat preservation and power regulation capacity improvement method and system for heating cogeneration unit
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106992555A (en) * 2017-04-25 2017-07-28 国网吉林省电力有限公司 A kind of CHP system distributed scheduling method under assisted hatching environment
CN108155644A (en) * 2017-12-26 2018-06-12 清华大学 Meter and the dynamic heating system of ancillary service and electric system coupled scheduler method
CN108964128A (en) * 2018-08-07 2018-12-07 燕山大学 The low-carbon economy for coordinating heat supply based on electric boiler and heat-storing device dispatches method for solving
CN109687532A (en) * 2019-03-08 2019-04-26 燕山大学 A kind of combined heat and power dispatching method improving wind electricity digestion based on cooperative game

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
SK288722B6 (en) * 2007-10-04 2020-01-07 Auxilien A S Method of extension control range of electric power supplied by electricity supply system and energy system with advanced control range

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106992555A (en) * 2017-04-25 2017-07-28 国网吉林省电力有限公司 A kind of CHP system distributed scheduling method under assisted hatching environment
CN108155644A (en) * 2017-12-26 2018-06-12 清华大学 Meter and the dynamic heating system of ancillary service and electric system coupled scheduler method
CN108964128A (en) * 2018-08-07 2018-12-07 燕山大学 The low-carbon economy for coordinating heat supply based on electric boiler and heat-storing device dispatches method for solving
CN109687532A (en) * 2019-03-08 2019-04-26 燕山大学 A kind of combined heat and power dispatching method improving wind electricity digestion based on cooperative game

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
互联电力系统二次调频协调技术与调频资源挖掘方法研究;张磊;《中国博士学位论文全文数据库 工程科技Ⅱ辑》;20180715;第61-62页 *
周一凡等.考虑热电联产调峰主动性的电热协调调度.《电力系统自动化》.2019,第43卷(第19期), *
考虑热电联产调峰主动性的电热协调调度;周一凡等;《电力系统自动化》;20191010;第43卷(第19期);第43-46页 *
考虑集中供热系统热动态特性的风电消纳研究;李平;《中国博士学位论文全文数据库 工程科技Ⅱ辑》;20190215;全文 *
计及热网特性的电热联合系统调度方法;邵世圻等;《电力系统保护与控制》;20180516;第46卷(第10期);全文 *

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