CN112508730A - Wind power consumption strategy of comprehensive energy virtual power plant - Google Patents

Wind power consumption strategy of comprehensive energy virtual power plant Download PDF

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CN112508730A
CN112508730A CN202011208508.2A CN202011208508A CN112508730A CN 112508730 A CN112508730 A CN 112508730A CN 202011208508 A CN202011208508 A CN 202011208508A CN 112508730 A CN112508730 A CN 112508730A
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heat
supply network
tau
formula
pipeline
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杨剑峰
沈鉴
张建浩
吴佩莹
任核权
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Shaoxing Daming Electric Power Design Institute Co ltd
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Shaoxing Daming Electric Power Design Institute Co ltd
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    • G06Q50/06—Electricity, gas or water supply
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00—Details relating to CAD techniques
    • G06F2111/04—Constraint-based CAD
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2113/00—Details relating to the application field
    • G06F2113/06—Wind turbines or wind farms
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/08—Thermal analysis or thermal optimisation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
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    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

The invention discloses a method for acquiring a wind power consumption strategy of a comprehensive energy virtual power plant, which comprises the following steps: step S1, constructing an electric heating coupling type virtual power plant structure containing a cogeneration unit and a ground source heat pump; step S2, analyzing thermal delay, transmission loss and heat storage characteristics of the internal thermal energy transmission process of the electrothermal coupling type virtual power plant, and performing dynamic modeling; step S3, constructing a wind power consumption model of the electric-heat coupling type virtual power plant by combining the running characteristics of the cogeneration unit and the heat pump; and step S4, solving the wind power absorption model to obtain the output scheme of each energy device in the electric heating coupling type virtual power plant, and adjusting in real time. By implementing the method, the wind power consumption level of the system can be improved, and the total cost of the energy consumption of the system in one day can be reduced.

Description

Wind power consumption strategy of comprehensive energy virtual power plant
Technical Field
The invention relates to the technical field of power dispatching, in particular to a wind power consumption strategy of a comprehensive energy virtual power plant.
Background
In recent years, the installed scale of renewable energy represented by wind power has been rapidly developed. According to the statistics of the world wind energy society, the annual growth rate of the global wind power installed capacity is kept above 10% from 2000 to the present, thereby bringing about a serious wind power consumption problem. In Jilin province, a cogeneration unit supplies more than 70% of heat load, the operation of the cogeneration unit is often restricted by using heat to fix power, the regulation capacity is limited, the cogeneration unit cannot complement wind power generation, and the wind power receiving capacity is seriously influenced. With the further increase of future wind power development, the problem of wind power consumption is more prominent, and how to effectively consume wind power and reduce the wind abandoning rate is widely concerned.
The existing method mostly operates by combining the hot-electricity cogeneration unit with the electric boiler, the heat storage device and other equipment, so as to achieve the effects of consuming wind power and improving the system economy, but the schemes need larger additional investment and equipment construction land. Considering that the heat supply network has thermal inertia, the heat supply network can be regarded as a natural heat storage device, so that the heat storage capacity of the heat supply network of the thermoelectric coupling virtual power plant can be utilized to remove part of thermoelectric coupling constraint of cogeneration so as to improve the wind power consumption capacity. A significant advantage of this solution is that the heat network is already present in the urban district heating system without major additional investments.
In some occasions, for example, places which simultaneously adopt wind power for power supply, such as an electrothermal coupling type virtual power plant, due to uncertainty of power load, situations such as wind power and wind power often occur, so that the total cost of power consumption in a system is high, and how to effectively improve the wind power consumption level of the system and reduce the wind abandoning cost is a problem to be solved.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a method for acquiring a wind power consumption strategy of an electrothermal coupling type virtual power plant, which can adjust the self output of cogeneration according to the predicted output of the wind power and the electric load demand of a system, realize the transfer of the heat load of the system across time periods, and finally achieve the purposes of improving the wind power consumption level of the system and reducing the total cost of energy consumption of the system in one day.
In order to solve the technical problem, the technical scheme adopted by the invention is to provide a method for acquiring a wind power consumption strategy of an electrothermal coupling type virtual power plant, which comprises the following steps:
step S1, constructing an electric heating coupling type virtual power plant structure containing a cogeneration unit and a ground source heat pump; the electric-heating coupling type virtual power plant structure comprises an electric power system and a thermodynamic system which are connected through a coupling device, wherein the coupling device comprises a cogeneration unit and a heat pump;
step S2, analyzing heat delay, transmission loss and heat storage characteristics of the internal heat energy transmission process of the electrothermal coupling type virtual power plant, performing dynamic modeling, and determining the regulation potential of the heat storage of the heat supply network participating in the wind power consumption of the power system;
step S3, combining the running characteristics of the cogeneration unit and the heat pump, and constructing a wind power consumption model of the electric-heat coupling type virtual power plant according to the adjusting potential;
and step S4, solving the wind power absorption model to obtain the output scheme of each energy device in the electric heating coupling type virtual power plant, and adjusting the output of each energy device in real time.
Preferably, the thermodynamic system comprises at least: the heat supply network comprises a heat source, a heat supply network and a heat load, wherein the heat supply network is divided into a primary heat supply network and a secondary heat supply network, and a heat exchange primary station and a heat exchange station are respectively built at the head end and the tail end of the primary heat supply network; the physical networks of the primary heat supply network and the secondary heat supply network realize heat exchange through the heat exchange station, and the primary heat supply network has heat energy transmission delay and heat storage characteristics.
Preferably, the step S2 further includes:
step S20, establishing a heat supply network heat energy transmission dynamic model; determining the dynamic characteristics of heat energy transmission in a heat supply pipeline of a primary heat supply network, wherein the heat energy transmission comprises three aspects of heat delay, transmission loss and heat storage;
and step S21, establishing a heat exchange station model and a heat exchange network node in the primary heat supply network.
Preferably, the step S20 further includes:
s200, determining the transmission delay transmission time delay tau of the temperature change at two ends of the heat supply pipeline according to the following formula (1)j：
Figure BDA0002757841620000021
In the formula: tau isjThe unit is h for the transmission delay of the pipeline j; ljIs the length of the pipe j in m; v. ofjThe flow velocity of the working medium in the pipeline j is unit m/s;
s201, obtaining a coupling relation of the inlet temperature and the outlet temperature of the working medium in the same pipeline on time, and determining that no heat loss exists from the inlet to the outlet of the working medium according to a formula (2):
Figure BDA0002757841620000022
in the formula: τ is a period number within one cycle, τ is 1,2, …, N;
Figure BDA0002757841620000023
in order to not consider the water outlet temperature of the pipeline j in the period tau when the heat loss of the pipeline is consumed, the unit is;
Figure BDA0002757841620000024
for the pipe j at (tau-tau)j) Inlet temperature in time periods in units of;
s202, obtaining the transmission loss (temperature reduction) of the working medium in the pipe network according to the following formula (3):
Figure BDA0002757841620000031
a＝kj/(qjcw) (4)
in the formula:
Figure BDA0002757841620000032
in order to consider the water outlet temperature of the pipeline j in the period tau when the pipeline heat loss is consumed, the unit is; k is a radical ofjThe heat leakage loss coefficient of the pipeline is represented by the unit W/(m DEG C); c. CwIs the specific heat capacity of water, and the unit is kJ/(kg DEG C); ljIs the length of the pipeline, and has the unit of m; t isamIs the ambient temperature around the pipe in degrees celsius.
Preferably, the step S21 further includes:
step S210, obtaining a heat supply network node temperature mixed constraint condition according to the following formula (5):
Figure BDA0002757841620000033
in the formula:
Figure BDA0002757841620000034
and
Figure BDA0002757841620000035
respectively, a set of pipes connected to and ending from node n and starting from node n; q. q.sτ,jAnd q isτ,kThe flow rates of the pipelines j and k in the period tau respectively;
Figure BDA0002757841620000036
the water outlet temperature of the pipeline j is tau period;
Figure BDA0002757841620000037
the water inlet temperature of the pipeline k is tau period;
step S211, obtaining a heat supply network node continuity constraint condition according to the following formula (6):
Figure BDA0002757841620000038
establishing a heat exchange station model of heat exchange stations in the primary heat supply network according to the following formula (7):
Figure BDA0002757841620000039
in the formula: qτ,iThe heat exchange amount of a heat exchange station at a load i in a period tau, kJ; m isτ,iThe mass of hot water flowing through the heat exchange station at the load i in the period of tau is kg;
Figure BDA00027578416200000310
and
Figure BDA00027578416200000311
the water supply temperature and the water return temperature of the heat exchange station at the load i in the tau time period are respectively DEG C;
step S212, determining the relationship between the heat exchange amount and the heat load of the heat exchange station according to the following formula (8) as shown in the formula (8):
Figure BDA00027578416200000312
in the formula:
Figure BDA00027578416200000313
the calculated heat load of the heat exchange station at time period τ load i, kW.
Step S213, determining the relationship between the heat exchange amount of the first heat exchange station and the water temperature of the primary heat supply network according to the following formula (9):
Figure BDA00027578416200000314
Figure BDA00027578416200000315
in the formula:
Figure BDA00027578416200000316
and
Figure BDA00027578416200000317
for combined heat and power generation and heat pump respectivelyThermal power at time τ, kW; m isτ,wThe mass of hot water flowing through the heat exchange primary station is kg for a period tau; t isτ supplyAnd Tτ returnThe water supply temperature and the water return temperature of the heat exchange initial station at the tau time interval are respectively DEG C; subscripts min and max represent upper and lower temperature limits, respectively;
step S214, determining a pipeline temperature constraint condition according to the following equation (11):
Tj≤Tmax (11)
in the formula: t ismaxThe highest temperature of the pipeline working medium is specified.
Preferably, the step S3 further includes:
step S30, determining a wind power consumption target according to equation (12):
minC＝Cgas+Cwind (12)
Figure BDA0002757841620000041
Figure BDA0002757841620000042
in the formula: c is the total operation cost of the system, and the unit is element; cgasThe unit is Yuan for the cost of purchasing natural gas; cwindThe unit is Yuan for the cost of wind abandonment; kgas is the price of natural gas in unit volume, and the unit is Yuan/m 3;
Figure BDA0002757841620000043
the volume of natural gas purchased by the cogeneration unit from the upstream natural gas grid for period τ is m 3; kcut is the cost coefficient of the abandoned wind, and the unit is Yuan/kWh;
Figure BDA0002757841620000044
predicting the power of the wind power in kW for the tau time period; pτ windWind power absorption power is generated in a unit of kW for a period of tau;
step S31, determining constraint conditions of the electric-heat coupling type virtual power plant wind power consumption model based on heat storage characteristics of the heat supply network, comprising the following steps:
the electric power balance constraint is determined by the following equation (15):
Figure BDA0002757841620000045
in the formula: pτ CHPThe electric power of the cogeneration in the tau time period is kW;
the cogeneration model constraints are determined by the following equations (16) and (17):
Figure BDA0002757841620000046
Figure BDA0002757841620000047
in the formula: eta is the gas-heat conversion efficiency;
the heat pump model constraints are determined by the following equation (18):
Figure BDA0002757841620000048
in the formula: COP is the energy efficiency coefficient; pτ HPThe electric power of the heat pump in the unit of kW is in the period of tau;
determining the output limit value and the climbing constraint condition of the energy equipment according to the following formulas (19) to (21):
Figure BDA0002757841620000049
Figure BDA00027578416200000410
Figure BDA00027578416200000411
in the formula: subscripts min and max represent the upper and lower limits of the force, respectively;
Figure BDA00027578416200000412
and
Figure BDA00027578416200000413
respectively setting the upward and downward climbing speed limits of the output of the cogeneration unit;
determining heat supply network transmission characteristic constraint conditions according to the formulas (3) to (4);
heat supply network node constraints in equations (5) - (6);
the heat exchange station constraints are determined in equations (7) - (11).
Preferably, the step S4 further includes:
and solving the wind power absorption model by adopting a nonlinear programming optimization algorithm, and solving the output scheme of each energy device in the electric heating coupling type virtual power plant.
The embodiment of the invention has the following beneficial effects:
according to the method for acquiring the wind power absorption strategy of the electric heating coupling type virtual power plant, the dynamic process of heat energy transmission is modeled by analyzing the heat storage characteristics of a heat supply network, and the heat delay, the transmission loss and the heat storage property of the heat energy transmission process can be reflected;
meanwhile, after heat storage of a heat supply network is considered, the invention can enable the thermoelectric cogeneration unit equipment in the electric heating coupling type virtual power plant to adjust self output according to the predicted output of the system wind power and the demand of the electric load, realize the transfer of the system heat load across time periods, and finally achieve the aims of improving the wind power consumption level of the system and reducing the total energy consumption cost of the system in one day.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is within the scope of the present invention for those skilled in the art to obtain other drawings based on the drawings without inventive exercise.
Fig. 1 is a schematic main flow diagram of an embodiment of a method for acquiring a wind power consumption strategy of an electrothermal coupling type virtual power plant according to the present invention;
FIG. 2 is a schematic diagram of the thermally coupled virtual power plant of FIG. 1;
FIG. 3 is a schematic diagram of the thermodynamic system involved in FIG. 2;
FIG. 4 is a heating network configuration involved in one embodiment of the present invention;
FIG. 5 is a schematic diagram of load conditions and wind power predicted output curves involved in one embodiment of the present invention;
FIG. 6 is a schematic diagram of the wind power consumption rate of the system under two scenarios involved in an embodiment of the present invention;
FIG. 7 is a graphical representation of the total thermal output of the system under two scenarios involved in one embodiment of the present invention;
FIG. 8 is a schematic illustration of combined heat and power and heat pump thermal output in scenario 1, as contemplated by an embodiment of the present invention;
FIG. 9 is a schematic illustration of combined heat and power and heat pump thermal output in scenario 2, as contemplated by an embodiment of the present invention;
FIG. 10 is a schematic illustration of cogeneration and fan power in scenario 1 as contemplated by an embodiment of the present invention;
fig. 11 is a schematic diagram of cogeneration and fan power in scenario 2, as contemplated by an embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, but rather should be construed as broadly as the present invention is capable of modification in various respects, all without departing from the spirit and scope of the present invention.
In the description of the present invention, it is to be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention.
As shown in fig. 1, a main flow diagram of an embodiment of a method for acquiring a wind power consumption strategy of an electrothermal coupling virtual power plant according to the present invention is shown, and is shown in fig. 2 to 3, in this embodiment, the method includes the following steps:
step S1, constructing an electric heating coupling type virtual power plant structure containing a cogeneration unit and a ground source heat pump; the electric-heating coupling type virtual power plant structure comprises an electric power system and a thermodynamic system which are connected through a coupling device, wherein the coupling device comprises a cogeneration unit and a heat pump; the electric heating coupling type virtual power plant structure can be shown by referring to FIG. 2; the heat pump removes the electric heat coupling of the heat and power cogeneration unit part through the electric heat load conversion. In the system, complementary characteristics of electric power and heat can be fully utilized to realize wind power consumption and energy economic utilization. For example, the dynamic process of electric energy transmission is described by the time scale from nanosecond to millisecond, while the dynamic state of heat energy transmission is described by the time scale of second, minute or even hour, the electric energy is easy to transmit and difficult to store, the heat energy is easy to store and difficult to transmit, and the heat supply network has natural heat storage characteristics due to the time delay from a heat source to a user;
step S2, analyzing heat delay, transmission loss and heat storage characteristics of the internal heat energy transmission process of the electrothermal coupling type virtual power plant, performing dynamic modeling, and determining the regulation potential of the heat storage of the heat supply network participating in the wind power consumption of the power system;
step S3, combining the running characteristics of the cogeneration unit and the heat pump, and constructing a wind power consumption model of the electric-heat coupling type virtual power plant according to the adjusting potential;
and step S4, solving the wind power absorption model to obtain the output scheme of each energy device in the electric heating coupling type virtual power plant, and adjusting the output of each energy device in real time.
In a specific example, as shown in fig. 3, the thermodynamic system includes at least: the heat supply network comprises a heat source, a heat supply network and a heat load, wherein the heat supply network is divided into a primary heat supply network and a secondary heat supply network, and a heat exchange primary station and a heat exchange station are respectively built at the head end and the tail end of the primary heat supply network; the physical networks of the primary heat supply network and the secondary heat supply network realize heat exchange through the heat exchange station, and the primary heat supply network has the characteristics of heat energy transmission delay and heat storage, in other words, the characteristics of heat energy transmission delay, heat storage and the like are mainly reflected in the primary heat supply network.
In a specific example, the step S2 further includes:
step S20, establishing a heat supply network heat energy transmission dynamic model; determining the dynamic characteristics of heat energy transmission in a heat supply pipeline of a primary heat supply network, wherein the heat energy transmission comprises three aspects of heat delay, transmission loss and heat storage; it will be appreciated that in a heating pipeline, the temperature change at the inlet will slowly spread to the outlet, the heat of the hot water entering and exiting the pipeline at the same time period is not necessarily equal, and the heat supply network can play the roles of buffering energy and delaying response. The dynamic characteristic of heat energy transmission has direct influence on the temperature of a working medium in a heat supply network;
and step S21, establishing a heat exchange station model and a heat exchange network node in the primary heat supply network.
In a specific example, the step S20 further includes:
s200, after absorbing heat from a heat source and increasing the temperature, the working medium enters a primary heat supply network water supply pipeline and moves to a heat load at a certain speed. Thus, the temperature change of the working medium at the heat load lags behind the temperature change at the heat source. Transmission delay transmission time delay tau of temperature change at two ends of heat supply pipelinejThe transmission delay tau of the temperature change at the two ends of the heat supply pipeline can be determined according to the following formula (1) in accordance with the time that hot water flows through the pipelinej：
Figure BDA0002757841620000071
In the formula: tau isjThe unit is h for the transmission delay of the pipeline j; ljIs the length of the pipe j in m; v. ofjThe flow velocity of the working medium in the pipeline j is unit m/s;
s201, obtaining a coupling relation of the inlet temperature and the outlet temperature of the working medium in the same pipeline on time, and determining that no heat loss exists from the inlet to the outlet of the working medium according to a formula (2):
Figure BDA0002757841620000072
in the formula: τ is a period number within one cycle, τ is 1,2, …, N;
Figure BDA0002757841620000081
in order to not consider the water outlet temperature of the pipeline j in the period tau when the heat loss of the pipeline is consumed, the unit is;
Figure BDA0002757841620000082
for the pipe j at (tau-tau)j) Inlet temperature in time periods in units of;
it can be understood that the coupling relation of the inlet temperature and the outlet temperature of the working medium in the same pipeline in time is the key for describing the dynamic characteristics of the heat supply network;
s202, because of the difference between the temperature of the working medium in the heat supply network and the ambient temperature, heat loss occurs in the transmission process, which is specifically expressed as the reduction of the temperature of the working medium in the pipe network, and the transmission loss (temperature reduction) of the working medium in the pipe network is obtained according to the Suhoff temperature reduction formula of the following formula (3) in combination with the formula (2):
Figure BDA0002757841620000083
a＝kj/(qjcw) (4)
in the formula:
Figure BDA0002757841620000084
in order to consider the water outlet temperature of the pipeline j in the period tau when the pipeline heat loss is consumed, the unit is; k is a radical ofjThe heat leakage loss coefficient of the pipeline is represented by the unit W/(m DEG C); c. CwIs the specific heat capacity of water, and the unit is kJ/(kg DEG C); ljIs the length of the pipeline, and has the unit of m; t isamIs the ambient temperature around the pipe in degrees celsius.
It can be understood that, because the dynamic process of heat energy transmission has a large time scale, the change of the heat quantity of the hot water at the inlet of the pipeline can be reflected to the outlet after a certain delay time, and the heat supply network can play the roles of buffering energy and delaying response, thereby externally showing the heat storage property. During a scheduling period, the total heat stored in the hot water in the pipeline is increased (or decreased), corresponding to the heat storage (or release) condition, through the change of the temperature of the hot water. After the heat storage of the heat supply network is considered, the heat energy can be transferred in different time periods, the flexibility of the cogeneration unit is improved, and the wind power can be favorably absorbed.
In the invention, the primary heat supply network adopts a mass regulation mode, namely the mass flow rate of hot water in the heat supply network is not changed, and only the water temperature is regulated.
In a specific example, the step S21 further includes:
step S210, hot water in different pipelines flows into the same node and then is mixed in temperature, the temperature of the hot water flowing out of the node after mixing is the same, and a heat supply network node temperature mixing constraint condition is obtained according to the following formula (5):
Figure BDA0002757841620000085
in the formula:
Figure BDA0002757841620000086
and
Figure BDA0002757841620000087
are respectively connected with the node n and the slave noden sets of ending and starting pipes; q. q.sτ,jAnd q isτ,kThe flow rates of the pipelines j and k in the period tau respectively;
Figure BDA0002757841620000088
the water outlet temperature of the pipeline j is tau period;
Figure BDA0002757841620000089
the water inlet temperature of the pipeline k is tau period;
step S211, the working medium in the heat supply network should meet a node continuity equation, that is, the sum of the mass flow rates flowing through the node n in any time period tau is zero, and the heat supply network node continuity constraint condition can be obtained according to the following formula (6):
Figure BDA0002757841620000091
for the heat exchange station in the primary heat supply network, the concept of calculating load in the analysis of the power system can be imitated, the load and the loss are bound together to form the calculating load of the heat exchange station, and the user load and the heat loss of the heat exchanger and the secondary heat supply network are replaced in the model. Establishing a heat exchange station model of heat exchange stations in the primary heat supply network according to the following formula (7):
Figure BDA0002757841620000092
in the formula: qτ,iThe heat exchange amount of a heat exchange station at a load i in a period tau, kJ; m isτ,iThe mass of hot water flowing through the heat exchange station at the load i in the period of tau is kg;
Figure BDA0002757841620000093
and
Figure BDA0002757841620000094
the water supply temperature and the water return temperature of the heat exchange station at the load i in the tau time period are respectively DEG C;
step S212, the heat exchange station specifically meets the requirement of the heat load of the user by adjusting the flow in the secondary heat supply network pipeline, and the relationship between the heat exchange amount and the heat load of the heat exchange station is determined as shown in the formula (8) in the following formula (8):
Figure BDA0002757841620000095
in the formula:
Figure BDA0002757841620000096
the calculated heat load of the heat exchange station at time period τ load i, kW.
Step S213, the heat exchange primary station is connected with a heat source and a primary heat supply network, and the relationship between the heat exchange amount of the heat exchange primary station and the water temperature of the primary heat supply network is determined by the following formula (9):
Figure BDA0002757841620000097
Figure BDA0002757841620000098
in the formula:
Figure BDA0002757841620000099
and
Figure BDA00027578416200000910
thermal power, kW, of cogeneration and heat pump in the period tau; m isτ,wThe mass of hot water flowing through the heat exchange primary station is kg for a period tau; t isτ supplyAnd Tτ returnThe water supply temperature and the water return temperature of the heat exchange initial station at the tau time interval are respectively DEG C; subscripts min and max represent upper and lower temperature limits, respectively;
step S214, in order to ensure the operation safety, the temperature of the working medium in the pipeline can not exceed the engineering standard, and the following formula (11) determines the constraint condition of the temperature of the pipeline:
Tj≤Tmax (11)
in the formula: t ismaxThe highest temperature of the pipeline working medium is specified.
In a specific example, the step S3 further includes:
and step S30, the objective of the wind power consumption strategy of the electric heating coupling type virtual power plant based on the heat storage characteristics of the heat supply network is to minimize the total operation cost of the system by reasonably arranging the output of each energy device under the condition of meeting the electric and heat loads and operation constraints. In order to promote wind power consumption, the abandoned wind cost is added into the total running cost of the system, and a wind power consumption target is determined according to the formula (12):
minC＝Cgas+Cwind (12)
Figure BDA0002757841620000101
Figure BDA0002757841620000102
in the formula: c is the total operation cost of the system, and the unit is element; cgasThe unit is Yuan for the cost of purchasing natural gas; cwindThe unit is Yuan for the cost of wind abandonment; kgas is the price of natural gas in unit volume, and the unit is Yuan/m 3;
Figure BDA0002757841620000103
the volume of natural gas purchased by the cogeneration unit from the upstream natural gas grid for period τ is m 3; kcut is the cost coefficient of the abandoned wind, and the unit is Yuan/kWh;
Figure BDA0002757841620000104
predicting the power of the wind power in kW for the tau time period; pτ windWind power absorption power is generated in a unit of kW for a period of tau;
step S31, determining constraint conditions of the electric-heat coupling type virtual power plant wind power consumption model based on heat storage characteristics of the heat supply network, comprising the following steps:
the electric power balance constraint is determined by the following equation (15):
Figure BDA0002757841620000105
in the formula: pτ CHPThe electric power of the cogeneration in the tau time period is kW;
the cogeneration model constraints are determined by the following equations (16) and (17):
Figure BDA0002757841620000106
Figure BDA0002757841620000107
in the formula: eta is the gas-heat conversion efficiency;
the heat pump model constraints are determined by the following equation (18):
Figure BDA0002757841620000108
in the formula: COP is the energy efficiency coefficient; pτ HPThe electric power of the heat pump in the unit of kW is in the period of tau;
determining the output limit value and the climbing constraint condition of the energy equipment according to the following formulas (19) to (21):
Figure BDA0002757841620000109
Figure BDA00027578416200001010
Figure BDA00027578416200001011
in the formula: subscripts min and max represent the upper and lower limits of the force, respectively;
Figure BDA00027578416200001012
and
Figure BDA00027578416200001013
respectively setting the upward and downward climbing speed limits of the output of the cogeneration unit;
determining heat supply network transmission characteristic constraint conditions according to the formulas (3) to (4);
heat supply network node constraints in equations (5) - (6);
the heat exchange station constraints are determined in equations (7) - (11).
In a specific example, the step S4 further includes:
and solving the wind power absorption model by adopting a nonlinear programming optimization algorithm, and solving the output scheme of each energy device in the electric heating coupling type virtual power plant.
In order to further understand the present invention, the following description will be made with reference to specific examples, and the embodiments of the present invention will be described with reference to fig. 4 to 11.
In one specific example of the present invention, a 10-node heating network is selected, and the structure thereof is shown in fig. 4. A heat exchange initial station is built at Nd1, and heat exchange stations are built at Nd 5-Nd 10. The load situation and the wind power predicted output are shown in fig. 5. The heat supply network parameters are shown in table 1, and the other data are shown in table 2.
Table 110 node heating network parameters
Figure BDA0002757841620000111
TABLE 2 electrothermal coupling type virtual power plant-related parameters
Parameter(s) Numerical value Parameter(s) Numerical value
kj 2W/(m·℃) η 3.59
cw 4.2kJ/(kg·℃) COP 2.5
T am 0℃ Kgas 1.72 yuan/m3
ε 1.11 vj 1m/s
Kcut 0.2 yuan/kWh
Two typical scenes were then constructed for comparison:
scene 1: a wind power consumption strategy considering the heat storage characteristic of the heat supply network;
scene 2: and wind power consumption strategies without considering heat storage and time delay of a heat supply network.
The objective function in scenario 1 is shown as equation (12). The scheduling period is 24h, and the scheduling interval Δ t is 0.5 h.
The system operating costs for both scenarios are shown in table 3.
TABLE 3 System running cost under two scenarios
Running cost (Yuan) Abandon wind cost (Yuan) Total cost (Yuan)
Scene 1 33395.42 3292.064 36687.48
Scene 2 35806.70 6093.377 41900.08
From the above table it can be seen that: the system operation cost, the wind curtailment cost and the total cost in the scene 1 are all reduced compared with those in the scene 2. Wherein, the operation cost can be saved by 6.7 percent, the wind-abandoning cost can be saved by 46.0 percent, and the total cost can be saved by 12.4 percent. The method provided by the invention has the advantages that the air abandoning rate is reduced, and the economy is good.
The wind power consumption rates under the two scenarios are shown in fig. 6. It can be seen that: at a temperature of 0: 00-3: 00, the wind power consumption rate of the system in the scene 2 is generally lower than 0.6, and the wind abandoning condition is serious. And the wind power consumption rate of the scene 1 system in the period is obviously higher than that of the scene 2, and the most obvious period is 1: at 00 hours, the wind power consumption rate of scene 1 is increased by about 76.2% compared with scene 2. At 21: 00-24: 00 and the next day 3: 00-5: and in the 30-time period, the wind power consumption rate of the scene 1 is higher than that of the scene 2. The method can effectively improve the wind power consumption level of the system.
The total thermal output of the system for both scenarios is shown in fig. 7. Comparing fig. 5 with fig. 7, it can be seen that: in scenario 2, the total thermal output of the system is relatively stable during a day, and the change of thermal load during the day is basically tracked. While the total thermal output of the system in scenario 1 is 23: 00-day 5: the time interval is 30, the time interval is smaller than scene 2, the predicted wind power output of the system in the time interval is large, the electric load demand is small, and the combined heat and power generation is not suitable to operate with large output; at 16: 30-20: in a period of 30, the total thermal output of the system in the scene 1 is greater than that in the scene 2, the predicted wind power output of the system in the period is smaller, the electric load demand is large, and the cogeneration is required to be operated with larger output. This indicates that the system can achieve a transfer of thermal load across time periods after taking into account thermal storage characteristics of the thermal network.
The changes of the cogeneration and the heat pump thermal output of the system in one day under the two scenarios are shown in fig. 8 and 9. At 21: 00-day 5: 30, the heat output of the thermoelectric coupling in the scene 1 is smaller than that in the scene 2; at 16: 30-20: 30, the thermoelectric combined heat output in the scene 1 is larger than that in the scene 2, and the phenomenon is consistent with the conclusion of the graph 7. This indicates that: in the operation strategy of the invention, because the heat storage characteristic of the heat supply network is considered, the cogeneration can adjust the self output according to the predicted output of the wind power and the electric load demand of the system, and the output is reduced in the time period of large predicted output of the wind power and small electric load demand; and the output is improved in the time period when the predicted output of the wind power is small and the electric load demand is large. The above-mentioned operating characteristics of cogeneration are inherent reasons for the system to achieve a transfer of heat load across time periods after taking into account the heat storage characteristics of the heat network.
The changes of the cogeneration of the system and the electric power of the wind turbine in one day under the two scenarios are shown in fig. 10 and 11. Comparing the two figures, it can be seen that: at a temperature of 0: 00-3: 00, the wind power consumed by the system in the scene 1 is obviously higher than that in the scene 2, and the total electric power (the sum of cogeneration and fan electric power) of the system in the two scenes is equal. In combination with the above analysis, the wind abandoning situation of the scene 2 in this period is severe, and is mainly limited by the maximum output of the heat pump. The scene 1 system realizes the transfer of heat load across time intervals, the cogeneration output in the time intervals is greatly reduced, more power demands of the system are provided by wind power, and the purpose of wind power consumption is achieved.
Further, at 16: 30-20: 30, although the output is improved by the cogeneration in the scene 1, the wind power consumption rate is not reduced. As can be seen from fig. 7 and 8, the output of the heat pump in the scene 1 is greater than that in the scene 2 in the time period, and the scene 1 consumes the redundant electric energy of the system by using the heat storage characteristics of the heat pump and the heat supply network, so that the high wind power consumption rate in the time period is ensured.
The method provided by the invention can effectively improve the wind power consumption level of the system and reduce the wind abandoning cost by integrating the condition of one day. Because the wind power with low operation cost occupies a larger proportion in the energy consumption of the system in one day, the operation cost of the system is also reduced, and finally the total cost of the power consumption of the system in one day is reduced.
The embodiment of the invention has the following beneficial effects:
according to the method for acquiring the wind power absorption strategy of the electric heating coupling type virtual power plant, the dynamic process of heat energy transmission is modeled by analyzing the heat storage characteristics of a heat supply network, and the heat delay, the transmission loss and the heat storage property of the heat energy transmission process can be reflected;
meanwhile, after heat storage of a heat supply network is considered, the invention can enable the thermoelectric cogeneration unit equipment in the electric heating coupling type virtual power plant to adjust self output according to the predicted output of the system wind power and the demand of the electric load, realize the transfer of the system heat load across time periods, and finally achieve the aims of improving the wind power consumption level of the system and reducing the total energy consumption cost of the system in one day.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.

Claims (7)

1. A method for acquiring a wind power consumption strategy of an electrothermal coupling type virtual power plant is characterized by comprising the following steps:
step S1, constructing an electric heating coupling type virtual power plant structure containing a cogeneration unit and a ground source heat pump; the electric-heating coupling type virtual power plant structure comprises an electric power system and a thermodynamic system which are connected through a coupling device, wherein the coupling device comprises a cogeneration unit and a heat pump;
step S2, analyzing heat delay, transmission loss and heat storage characteristics of the internal heat energy transmission process of the electrothermal coupling type virtual power plant, performing dynamic modeling, and determining the regulation potential of the heat storage of the heat supply network participating in the wind power consumption of the power system;
step S3, combining the running characteristics of the cogeneration unit and the heat pump, and constructing a wind power consumption model of the electric-heat coupling type virtual power plant according to the adjusting potential;
and step S4, solving the wind power absorption model to obtain the output scheme of each energy device in the electric heating coupling type virtual power plant, and adjusting the output of each energy device in real time.
2. The method according to claim 1, characterized in that the thermodynamic system comprises at least: the heat supply network comprises a heat source, a heat supply network and a heat load, wherein the heat supply network is divided into a primary heat supply network and a secondary heat supply network, and a heat exchange primary station and a heat exchange station are respectively built at the head end and the tail end of the primary heat supply network; the physical networks of the primary heat supply network and the secondary heat supply network realize heat exchange through the heat exchange station, and the primary heat supply network has heat energy transmission delay and heat storage characteristics.
3. The method according to claim 2, wherein the step S2 further comprises:
step S20, establishing a heat supply network heat energy transmission dynamic model; determining the dynamic characteristics of heat energy transmission in a heat supply pipeline of a primary heat supply network, wherein the heat energy transmission comprises three aspects of heat delay, transmission loss and heat storage;
and step S21, establishing a heat exchange station model and a heat exchange network node in the primary heat supply network.
4. The method of claim 3, wherein the step S20 further comprises:
s200, determining the transmission delay transmission time delay tau of the temperature change at two ends of the heat supply pipeline according to the following formula (1)j：
Figure FDA0002757841610000011
In the formula: tau isjThe unit is h for the transmission delay of the pipeline j; ljIs the length of the pipe j in m; v. ofjThe flow velocity of the working medium in the pipeline j is unit m/s;
s201, obtaining a coupling relation of the inlet temperature and the outlet temperature of the working medium in the same pipeline on time, and determining that no heat loss exists from the inlet to the outlet of the working medium in the pipeline according to a formula (2):
Figure FDA0002757841610000021
in the formula: τ is a period number within one cycle, τ is 1,2, …, N;
Figure FDA0002757841610000022
in order to not consider the water outlet temperature of the pipeline j in the period tau when the heat loss of the pipeline is consumed, the unit is;
Figure FDA0002757841610000023
for the pipe j at (tau-tau)j) Inlet temperature in time periods in units of;
s202, obtaining the transmission loss (temperature reduction) of the working medium in the pipe network according to the following formula (3):
Figure FDA0002757841610000024
a＝kj/(qjcw) (4)
in the formula:
Figure FDA0002757841610000025
in order to consider the water outlet temperature of the pipeline j in the period tau when the pipeline heat loss is consumed, the unit is; k is a radical ofjThe heat leakage loss coefficient of the pipeline is represented by the unit W/(m DEG C); c. CwIs the specific heat capacity of water, and the unit is kJ/(kg DEG C); ljIs the length of the pipeline, and has the unit of m; t isamIs the ambient temperature around the pipe in degrees celsius.
5. The method of claim 4, wherein the step S21 further comprises:
step S210, obtaining a heat supply network node temperature mixed constraint condition according to the following formula (5):
Figure FDA0002757841610000026
in the formula:
Figure FDA0002757841610000027
and
Figure FDA0002757841610000028
respectively, a set of pipes connected to and ending from node n and starting from node n; q. q.sτ,jAnd q isτ,kAre respectively provided withThe flow of the pipelines j and k is tau period;
Figure FDA0002757841610000029
the water outlet temperature of the pipeline j is tau period;
Figure FDA00027578416100000210
the water inlet temperature of the pipeline k is tau period;
step S211, obtaining a heat supply network node continuity constraint condition according to the following formula (6):
Figure FDA00027578416100000211
establishing a heat exchange station model of heat exchange stations in the primary heat supply network according to the following formula (7):
Figure FDA00027578416100000212
in the formula: qτ,iThe heat exchange amount of a heat exchange station at a load i in a period tau, kJ; m isτ,iThe mass of hot water flowing through the heat exchange station at the load i in the period of tau is kg;
Figure FDA00027578416100000213
and
Figure FDA00027578416100000214
the water supply temperature and the water return temperature of the heat exchange station at the load i in the tau time period are respectively DEG C;
step S212, determining the relationship between the heat exchange amount and the heat load of the heat exchange station according to the following formula (8) as shown in the formula (8):
Figure FDA00027578416100000215
in the formula:
Figure FDA00027578416100000216
the calculated heat load of the heat exchange station at time period τ load i, kW.
Step S213, determining the relationship between the heat exchange amount of the first heat exchange station and the water temperature of the primary heat supply network according to the following formula (9):
Figure FDA00027578416100000217
Figure FDA00027578416100000218
in the formula:
Figure FDA00027578416100000219
and
Figure FDA00027578416100000220
thermal power, kW, of cogeneration and heat pump in the period tau; m isτ,wThe mass of hot water flowing through the heat exchange primary station is kg for a period tau;
Figure FDA0002757841610000031
and
Figure FDA0002757841610000032
the water supply temperature and the water return temperature of the heat exchange initial station at the tau time interval are respectively DEG C; subscripts min and max represent upper and lower temperature limits, respectively;
step S214, determining a pipeline temperature constraint condition according to the following equation (11):
Tj≤Tmax (11)
in the formula: t ismaxThe highest temperature of the pipeline working medium is specified.
6. The method of claim 5, wherein the step S3 further comprises:
step S30, determining a wind power consumption target according to equation (12):
minC＝Cgas+Cwind (12)
Figure FDA0002757841610000033
Figure FDA0002757841610000034
in the formula: c is the total operation cost of the system, and the unit is element; cgasThe unit is Yuan for the cost of purchasing natural gas; cwindThe unit is Yuan for the cost of wind abandonment; kgasIs the price of natural gas per unit volume, unit is yuan/m3；
Figure FDA0002757841610000035
Volume of natural gas purchased from an upstream natural gas grid for a tau period cogeneration unit in m3；KcutThe unit is yuan/kWh;
Figure FDA0002757841610000036
predicting the power of the wind power in kW for the tau time period; pτ windWind power absorption power is generated in a unit of kW for a period of tau;
step S31, determining constraint conditions of the electric-heat coupling type virtual power plant wind power consumption model based on heat storage characteristics of the heat supply network, comprising the following steps:
the electric power balance constraint is determined by the following equation (15):
Figure FDA0002757841610000037
in the formula: pτ CHPThe electric power of the cogeneration in the tau time period is kW;
the cogeneration model constraints are determined by the following equations (16) and (17):
Figure FDA0002757841610000038
Figure FDA0002757841610000039
in the formula: eta is the gas-heat conversion efficiency;
the heat pump model constraints are determined by the following equation (18):
Figure FDA00027578416100000310
in the formula: COP is the energy efficiency coefficient;
Figure FDA00027578416100000311
the electric power of the heat pump in the unit of kW is in the period of tau;
determining the output limit value and the climbing constraint condition of the energy equipment according to the following formulas (19) to (21):
Figure FDA00027578416100000312
Figure FDA0002757841610000041
Figure FDA0002757841610000042
in the formula: subscripts min and max represent the upper and lower limits of the force, respectively;
Figure FDA0002757841610000043
and
Figure FDA0002757841610000044
respectively setting the upward and downward climbing speed limits of the output of the cogeneration unit;
determining heat supply network transmission characteristic constraint conditions according to the formulas (3) to (4);
heat supply network node constraints in equations (5) - (6);
the heat exchange station constraints are determined in equations (7) - (11).
7. The method according to claim 6, wherein the step S4 further comprises:
and solving the wind power absorption model by adopting a nonlinear programming optimization algorithm, and solving the output scheme of each energy device in the electric heating coupling type virtual power plant.
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Publication number Priority date Publication date Assignee Title
CN113610305A (en) * 2021-08-11 2021-11-05 东南大学 Optimized scheduling method of comprehensive energy system
CN113610305B (en) * 2021-08-11 2024-01-30 东南大学 Optimized scheduling method of comprehensive energy system

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