CN112560221A - Capacity distribution method and device for facility agriculture energy network containing enhanced geothermal system - Google Patents

Capacity distribution method and device for facility agriculture energy network containing enhanced geothermal system Download PDF

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CN112560221A
CN112560221A CN202011273098.XA CN202011273098A CN112560221A CN 112560221 A CN112560221 A CN 112560221A CN 202011273098 A CN202011273098 A CN 202011273098A CN 112560221 A CN112560221 A CN 112560221A
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梅生伟
司杨
陈晓弢
张雪敏
陈来军
薛小代
郭岩
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Qinghai University
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Abstract

The embodiment of the invention provides a capacity distribution method and a capacity distribution device for a facility agriculture energy network containing an enhanced geothermal system, wherein the method comprises the following steps: determining a CHP-EGS model, a wind power generation model and a photovoltaic power generation model; based on all models, the system electric power balance and the cold and hot network power balance are used as constraint conditions, the minimum system annual average cost is used as an objective function, and the corresponding installed capacity distribution results of the heat storage device, the heat generation device, the wind power generation device and the photovoltaic power generation device are obtained through optimized solving and used for capacity distribution of the energy network. According to the method, optimization solution is carried out on the limiting conditions according to the CHP-EGS model, the wind power generation model and the photovoltaic power generation model, the installed capacity distribution results of the heat storage device, the heat generation device, the wind power generation and the photovoltaic power generation which minimize the annual average cost of the system are obtained, and the cost expenditure of the system is effectively reduced on the premise that the energy network operates stably.

Description

Capacity distribution method and device for facility agriculture energy network containing enhanced geothermal system
Technical Field
The invention relates to the technical field of new energy, in particular to a capacity distribution method and device for a facility agriculture energy network containing an enhanced geothermal system.
Background
Facility agriculture becomes a main form of future agricultural modernization development, and with the diversified development of the demand of social economy on energy, a comprehensive energy network constructed by using a micro gas turbine or a compressed air energy storage system as a Combined Heat and Power (CHP) unit becomes a hot spot of research in the field of comprehensive utilization of energy. At present, research aiming at the agricultural scene of facilities mainly focuses on the aspects of responding to cold, heat and electric load demands of the agricultural facilities by combining renewable energy sources such as wind, light and the like with a micro gas turbine. The volatility of renewable energy and the environmental protection constraint of a gas turbine become key factors restricting the green development of the facility agriculture comprehensive energy network.
With the discovery of high-quality Hot Dry Rock (HDR) resources, some scholars aim at comprehensive development and utilization of hot dry rock thermal energy. However, the hot dry rock resource enrichment area is usually far away from a load center, the cost of building a power transmission line is high, and in addition, strict regional ecological environment protection requirements are met, so that the method is very suitable for building a comprehensive energy network taking an enhanced geothermal system (enhanced geothermal system EGS) as a CHP unit so as to meet the energy requirements of multiple types and multiple grades of facility agriculture.
However, there is relatively little research on the facility agriculture integrated energy network, and the research is limited to the optimization of source, load and storage scheduling, so that the installed capacity allocation result is not reasonable, resulting in relatively high cost.
Disclosure of Invention
The embodiment of the invention provides a facility agriculture energy network capacity distribution method and device with an enhanced geothermal system, which are used for solving the problems in the prior art.
The embodiment of the invention provides a capacity distribution method of a facility agriculture energy network containing an enhanced geothermal system, which comprises the following steps: determining a CHP-EGS model, a wind power generation model and a photovoltaic power generation model; based on all models, taking system electric power balance and cold and hot network power balance as constraint conditions, taking minimized system annual average cost as an objective function, and optimally solving to obtain corresponding installed capacity distribution results of the heat storage device, the heat generation device, the wind power generation and the photovoltaic power generation for capacity distribution of the energy network; the CHP-EGS model is a heat conversion model among a heat extraction unit, a power generation unit, a high-temperature heat supply unit, a medium-temperature heat supply unit and a refrigeration system in a facility agriculture energy network; the wind power generation model and the photovoltaic power generation model are respectively a relation model between the output power of wind power generation and photovoltaic power generation and the installed capacity of the wind power generation model and the photovoltaic power generation model.
According to the capacity distribution method of the facility agriculture energy network containing the enhanced geothermal system, the system annual average cost is determined according to the system annual average investment cost and the annual average operation cost under different scenes; the annual average running cost under different scenes is determined according to the probability of each scene and the system running cost expectation of the corresponding scene; the different scenes are generated according to the historical data of the wind speed and solar irradiance of the whole year and corresponding probability.
According to the facility agriculture energy network capacity distribution method with the reinforced geothermal system, the annual average investment cost is determined as follows:
Cinv＝cPVPPV+cWindPWind+cQS(SHS+SMS)+cEQ(PHEQ+PMEQ)；
wherein, PPVInstalled capacity, P, for photovoltaic power generation systemsWindInstalled capacity for wind power systems, SH/SMRespectively high/medium temperature heat storage system capacity, PHEQ/PMEQRespectively the power of the high/medium temperature electric heating system; c. CPV、cWind、cQS、cEQRespectively, the unit investment cost coefficients of the corresponding systems.
According to the facility agriculture energy network capacity distribution method with the enhanced geothermal system, the system operation cost expectation of each scene is determined as follows:
Figure BDA0002778270360000031
wherein tau represents the whole scheduling time period, and delta tau is the length of each time interval divided at equal intervals in the whole scheduling period;
Figure BDA0002778270360000032
respectively representing the medium-temperature heat power loss, the high-temperature heat power loss and the power loss of the power generation system at the moment t under the scene s; c. Cm、cH、ceRespectively corresponding loss cost coefficients;
Figure BDA0002778270360000033
abandoning load thermal power from medium temperature
Figure BDA0002778270360000034
Heat dissipation loss of medium temperature heat storage system
Figure BDA0002778270360000035
Forming;
Figure BDA0002778270360000036
in order that the system cannot meet the power shortage generated when the medium-temperature heat supply load is carried out,
Figure BDA0002778270360000037
power loss for heat storage system to dissipate heat to the environment;
Figure BDA0002778270360000038
thermal power from high temperature to waste load
Figure BDA0002778270360000039
And heat dissipation loss of high-temperature heat storage system
Figure BDA00027782703600000310
Forming;
Figure BDA00027782703600000311
power of electric load by abandoning
Figure BDA00027782703600000312
Optical power of waste
Figure BDA00027782703600000313
Wind power curtailment
Figure BDA00027782703600000314
And electric heating power loss
Figure BDA00027782703600000315
Forming;
Figure BDA00027782703600000316
the power of the equipment in the process of electric heating and heat storage is lost.
According to one embodiment of the invention, the method for capacity allocation of the facility agricultural energy network with the enhanced geothermal system comprises the following steps:
Figure BDA00027782703600000317
Figure BDA00027782703600000318
Figure BDA00027782703600000319
Figure BDA00027782703600000320
wherein s and t represent t moments in an s scene;
Figure BDA00027782703600000321
is the output power of the geothermal power generation unit,
Figure BDA00027782703600000322
is the output power of the photovoltaic power generation system,
Figure BDA00027782703600000323
is the output power of the wind power system, PHDRInstalled capacity, P, for geothermal power systemsPVInstalled capacity, P, for photovoltaic power generation systemsWindFor the installed capacity of the wind power generation system,
Figure BDA00027782703600000324
the electric load required for the agriculture of the facility,
Figure BDA00027782703600000325
in order to electrically cool the load,
Figure BDA00027782703600000326
for the self-powered load of the hot dry rock heat extraction system,
Figure BDA00027782703600000327
is used for high-temperature electric heating power,
Figure BDA00027782703600000328
the medium temperature electric heating power.
According to one embodiment of the invention, the method for allocating capacity of the facility agriculture energy network with the enhanced geothermal system comprises the following steps:
Figure BDA0002778270360000041
Figure BDA0002778270360000042
Figure BDA0002778270360000043
wherein s and t represent t moments in an s scene;
Figure BDA0002778270360000044
and
Figure BDA0002778270360000045
respectively adopts high-temperature and medium-temperature heat supply power,
Figure BDA0002778270360000046
and
Figure BDA0002778270360000047
respectively the heat release power of the high-temperature heat storage system and the medium-temperature heat storage system,
Figure BDA0002778270360000048
and
Figure BDA0002778270360000049
respectively the heat storage power of the high-temperature heat storage system and the medium-temperature heat storage system,
Figure BDA00027782703600000410
and
Figure BDA00027782703600000411
respectively adopts high-temperature and medium-temperature waste heat power,
Figure BDA00027782703600000412
in order to provide the thermal cooling power,
Figure BDA00027782703600000413
respectively for high temperature and medium temperature thermal loads,
Figure BDA00027782703600000414
for cold load, λeIs the electric refrigeration coefficient, λqCoefficient of thermal cooling.
According to one embodiment of the invention, the CHP-EGS model comprises the following components:
Figure BDA00027782703600000427
Figure BDA00027782703600000415
Figure BDA00027782703600000416
Figure BDA00027782703600000417
Figure BDA00027782703600000418
Figure BDA00027782703600000419
Figure BDA00027782703600000420
Figure BDA00027782703600000421
wherein t represents the tth scheduling time in the whole scheduling period tau, and t +1 represents the next scheduling time after the tth scheduling time; alpha is alphatIs the geothermal energy coefficient for power generation; beta is atIs the geothermal energy coefficient for supplying heat;
Figure BDA00027782703600000422
the residual temperatures of the geothermal working media after passing through the high-temperature heat supply unit and the geothermal power generation unit are respectively;
Figure BDA00027782703600000423
the heat source temperature of the heat exchanger of the medium temperature heat supply unit;
Figure BDA00027782703600000424
the output power of the geothermal power generation unit at the present moment,
Figure BDA00027782703600000425
for the efficiency of electricity generation, cpHDRIs the specific heat capacity of the geothermal working medium,
Figure BDA00027782703600000426
for the mass flow of the power generating unit, the value is determined from the total mass flow of the geothermal working medium and alphatObtaining the product of; t isHDRInputting the temperature of geothermal working medium of the geothermal power generation unit; m isHDRIs the total mass flow of the geothermal working medium,
Figure BDA0002778270360000051
cpOilrespectively providing mass flow and specific heat capacity, T, of high-temperature heat supply working mediumHProviding a temperature, T, for a high temperature loadOilThe initial temperature of the high-temperature heat supply working medium is determined by the ambient temperature;
Figure BDA0002778270360000052
represents the input thermal power of the high-temperature heat exchanger,
Figure BDA0002778270360000053
the output thermal power of the high-temperature heat exchanger is shown,
Figure BDA0002778270360000054
the input thermal power of the medium-temperature heat exchanger is shown,
Figure BDA0002778270360000055
the output thermal power of the medium-temperature heat exchanger is represented;
Figure BDA0002778270360000056
the high-temperature heat storage quantity at the time t,
Figure BDA0002778270360000057
storing the heat quantity for the high temperature at the next scheduling moment;
Figure BDA0002778270360000058
and
Figure BDA0002778270360000059
respectively obtaining high-temperature heat accumulation/release power and electric heating power at the moment t; etaHIs a heat dissipation coefficient, ηEQIs the electric heat transfer coefficient, muHc、μHdcThe variable is 0-1, so that the heat storage and release processes can not be carried out simultaneously;
Figure BDA00027782703600000510
the temperature is the reinjection temperature of the geothermal working medium;
Figure BDA00027782703600000511
cpwaterrespectively providing medium temperature heat supply working medium mass flow and specific heat capacity; t isMProviding temperature, T, for medium temperature loadswaterInitial temperature of medium temperature heat supply working medium;
Figure BDA00027782703600000512
and
Figure BDA00027782703600000513
the medium-temperature heat storage quantity, the heat storage/release power and the electric heating power at the moment t are respectively; etaMIs a heat dissipation coefficient, ηEQIs the electrical heat transfer coefficient; mu.sMc、μMdcThe variable is 0-1, so that the heat accumulation and heat release processes can not be carried out simultaneously.
The embodiment of the invention also provides a facility agriculture energy network capacity distribution device with the enhanced geothermal system, which comprises: the input module is used for determining a CHP-system EGS model, a wind power generation model and a photovoltaic power generation model; the analysis module is used for optimizing, solving and obtaining the installed capacity distribution results of the corresponding heat storage device, the heat production device, the wind power generation and the photovoltaic power generation based on all models by taking the system electric power balance and the cold and hot network power balance as constraint conditions and the minimized system annual average cost as an objective function, and is used for capacity distribution of the energy network; the CHP-EGS model is a heat conversion model among a heat extraction unit, a power generation unit, a high-temperature heat supply unit, a medium-temperature heat supply unit and a refrigeration system in a facility agriculture energy network; the wind power generation model and the photovoltaic power generation model are respectively a relation model between the output power of wind power generation and photovoltaic power generation and the installed capacity of the wind power generation model and the photovoltaic power generation model.
The embodiment of the invention also provides electronic equipment, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the steps of the method for distributing the capacity of the facility agriculture energy network containing the enhanced geothermal system.
Embodiments of the present invention also provide a non-transitory computer readable storage medium having stored thereon a computer program that, when executed by a processor, performs the steps of the method for capacity allocation of a facility agricultural energy grid including an enhanced geothermal system as described in any one of the above.
According to the facility agriculture energy network capacity distribution method and device with the enhanced geothermal system, provided by the embodiment of the invention, optimization solution is carried out according to the CHP-EGS model, the wind power generation model and the photovoltaic power generation model as limiting conditions, so that the installed capacity distribution results of the heat storage device, the heat production device, the wind power generation and the photovoltaic power generation which minimize the annual average cost of the system are obtained, and the cost overhead of the system is effectively reduced under the precondition that the energy network stably operates.
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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 described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for allocating capacity of a facility agricultural energy grid including an enhanced geothermal system according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a facility agricultural energy grid capacity distribution device with an enhanced geothermal system according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The method and the device for allocating the capacity of the facility agriculture energy network containing the enhanced geothermal system according to the embodiment of the invention are described below with reference to fig. 1 to 3. Fig. 1 is a schematic flow chart of a capacity allocation method for a facility agricultural energy grid including an enhanced geothermal system according to an embodiment of the present invention, and as shown in fig. 1, the capacity allocation method for the facility agricultural energy grid including the enhanced geothermal system according to the embodiment of the present invention includes:
101. and determining a CHP-EGS model, a wind power generation model and a photovoltaic power generation model.
The CHP-EGS independent facility agriculture comprehensive energy network architecture comprises a cold network, a heat network and a power network. The cold net is composed of an absorption refrigerator and an electric refrigerating device, and supplies cold for the cold load in the independent facility agriculture. When the geothermal energy is abundant, the absorption refrigerator is driven by the geothermal energy to supply cold, and when the power supply such as wind and light is excessive, the electric refrigeration equipment supplies cold. The heat supply network consists of a high-temperature heat supply network and a medium-temperature heat supply network, and supplies heat for high-temperature load and medium-temperature load in independent facility agriculture respectively.
The power grid is composed of a wind-solar renewable energy power generation system and a geothermal power generation system. The fluctuation of the wind-solar power generation renewable energy power system is stabilized through the geothermal power generation system so as to meet the power demand of independent facility agriculture.
The CHP-EGS model comprises a heat extraction unit, a power generation unit, a high-temperature heat supply unit, a medium-temperature heat supply unit and a refrigeration system. The high/medium temperature heat supply unit consists of a high/medium temperature heat exchanger and a heat storage system. The model of the wind and light power generation system comprises an output power model of the wind power generation system and an output power model of the photovoltaic power generation system which are convenient to analyze in a CHP-EGS-containing facility agricultural integrated energy network.
The output power model of the wind power generation system is shown in the following formula. Wherein v ist、
Figure BDA0002778270360000071
vrated、
Figure BDA0002778270360000072
Respectively actual wind speed, cut-in wind speed, rated wind speed and cut-out wind speed, the values of which are obtained by actual measured wind speed and wind generating set parameters, PWindAnd the installed capacity of the wind power generation system is obtained.
Figure BDA0002778270360000073
The output power model of the photovoltaic power generation system is shown as the following formula:
Figure BDA0002778270360000081
wherein St, SrActual solar irradiance and nominal solar irradiance, respectively, obtained from measurements, PPVThe installed capacity of the photovoltaic power generation system.
102. Based on all models, the system electric power balance and the cold and hot network power balance are used as constraint conditions, the minimum system annual average cost is used as an objective function, and the corresponding installed capacity distribution results of the heat storage device, the heat generation device, the wind power generation device and the photovoltaic power generation device are obtained through optimized solving and used for capacity distribution of the energy network.
Under the agricultural comprehensive energy network architecture with the CHP-EGS independent facilities provided by the embodiment of the invention, the wind and light power generation capacity, the heat generation device and the heat storage capacity of the CHP-EGS independent agricultural comprehensive energy network are required, and the investment cost for meeting the load requirement is considered. Meanwhile, the operating cost generated by energy interconversion and adjustment due to uncertainty of wind and light output power can be considered.
For system electric power balance, when capacity optimization analysis and calculation of a photovoltaic power station, a wind power plant, a heat storage device and an electric heating device are carried out, CHP-EGS-containing facility agriculture comprehensive energy network model parameters are restricted by actual physical and environmental factors. Therefore, the constraint model operating conditions which must be met when the capacity configuration optimization analysis is calculated are formed. Similarly, when the heat of the cold and hot network is converted, the power balance condition needs to be met. And carrying out iterative solution on the model analysis target by means of nonlinear optimization solution software, and obtaining the installed capacity distribution results of the corresponding heat storage device, heat production device, wind power generation and photovoltaic power generation through optimization solution.
According to the capacity distribution method of the facility agriculture energy network containing the enhanced geothermal system, which is disclosed by the embodiment of the invention, optimization solution is carried out on the limiting conditions according to the CHP-EGS model, the wind power generation model and the photovoltaic power generation model, so that the installed capacity distribution results of the heat storage device, the heat generation device, the wind power generation and the photovoltaic power generation which minimize the annual average cost of the system are obtained, and the cost expenditure of the system is effectively reduced under the precondition that the energy network stably operates.
Based on the content of the above embodiment, as an optional embodiment, the system annual average cost is determined according to the system annual average investment cost and the annual average operation cost in different scenes; the annual average running cost under different scenes is determined according to the probability of each scene and the system running cost expectation of the corresponding scene; the different scenes are generated according to the historical data of the wind speed and solar irradiance of the whole year and corresponding probability.
Because wind and photovoltaic power systems are both fluctuating and intermittent energy sources, the output power has certain randomness, and in order to deeply analyze the configuration requirements of wind and light capacity in winter and summer of the agricultural integrated energy network containing the CHP-EGS independent facilities, the uncertainty difference of the wind and the light in winter and summer needs to be fully described.
The invention adopts a random optimization method to carve the uncertainty and the intermittent characteristics of wind and light output power. By utilizing a scene production method, the mean value and the variance of prediction errors in different seasons are determined through wind speed and solar irradiance prediction data, for example, spring-autumn divided days, summer solstice and winter solstice are respectively used as typical seasonal scenes, a plurality of scenes of wind speed and solar irradiance are randomly generated according to historical data to realize wind and light uncertainty, then the scenes are reduced to a specified number of typical scenes through a scene reduction method, and the probabilities of different scenes are given.
The system annual average cost analysis target can be as follows:
Figure BDA0002778270360000091
wherein, CallThe annual average cost of the system is calculated by an optimization model, and S is the total number of typical scenes, pisThe probability for each scene is obtained by a random scene generation system, CinvAnd
Figure BDA0002778270360000092
respectively the annual average investment cost of the system and the annual average running cost under different scenes, and the system are respectively passed through the modelAnd calculating an optimization model. Wherein C isinvThe method comprises the steps of photovoltaic system installation investment, wind power system installation investment and heat storage subsystem investment cost;
Figure BDA0002778270360000093
the expectations for system operating costs resulting from the use of a stochastic optimization approach include high/medium temperature heating unit operating costs and power generation system operating costs.
Based on the content of the above embodiment, as an alternative embodiment, the annual average investment cost is determined as follows:
Cinv＝cPVPPV+cWindPWind+cQS(SHS+SMS)+cEQ(PHEQ+PMEQ)；
wherein, PPVInstalled capacity, P, for photovoltaic power generation systemsWindInstalled capacity for wind power systems, SH/SMRespectively high/medium temperature heat storage system capacity, PHEQ/PMEQRespectively the power of the high/medium temperature electric heating system; c. CPV、cWind、cQS、cEQThe cost coefficients are the unit investment cost coefficients of the corresponding system, and the cost coefficients are all selected according to actual price data.
Based on the contents of the above embodiments, as an alternative embodiment, the system operation cost expectation of each scene is determined as follows:
Figure BDA0002778270360000101
wherein τ represents the whole scheduling time period, and Δ τ is the length of each time interval divided at equal intervals in the whole scheduling period (generally τ is 24 hours, Δ τ is 1 hour);
Figure BDA0002778270360000102
Figure BDA0002778270360000103
respectively, the medium temperature loss at time t in the s sceneThermal power, high-temperature heat loss power and power loss power of a power generation system (subsequent s and t have the same meaning and are t moments under the scene of s); c. Cm、cH、ceRespectively corresponding loss cost coefficients;
Figure BDA0002778270360000104
abandoning load thermal power from medium temperature
Figure BDA0002778270360000105
Heat dissipation loss of medium temperature heat storage system
Figure BDA0002778270360000106
Forming;
Figure BDA0002778270360000107
in order that the system cannot meet the power shortage generated when the medium-temperature heat supply load is carried out,
Figure BDA0002778270360000108
the power loss generated by the heat dissipation of the medium-temperature heat storage system to the environment;
Figure BDA0002778270360000109
thermal power from high temperature to waste load
Figure BDA00027782703600001010
And heat dissipation loss of high-temperature heat storage system
Figure BDA00027782703600001011
The structure of the utility model is that the material,
Figure BDA00027782703600001012
in order that the system cannot meet the power shortage generated when the high-temperature heat supply load is carried out,
Figure BDA00027782703600001013
power loss for the high temperature heat storage system to dissipate heat to the environment;
Figure BDA00027782703600001014
by abandoningElectric load power
Figure BDA00027782703600001015
(the system can not meet the power shortage generated by the medium-temperature heat supply load), and the light-abandoning power
Figure BDA00027782703600001016
Wind power curtailment
Figure BDA00027782703600001017
(parts which cannot be connected with the network due to photovoltaic power and wind power excess generation respectively) and electric heating power loss
Figure BDA00027782703600001018
Forming;
Figure BDA00027782703600001019
the power loss of the equipment in the process of electric heating and heat storage is determined by the following formula.
Figure BDA00027782703600001020
Wherein eta isEQAnd taking values according to actual equipment for the electric heating efficiency.
Based on the content of the above embodiments, as an alternative embodiment, the system electric power balancing includes:
Figure BDA00027782703600001021
Figure BDA0002778270360000111
Figure BDA0002778270360000112
Figure BDA0002778270360000113
wherein the content of the first and second substances,
Figure BDA0002778270360000114
the output power of the geothermal power generation unit at the present moment,
Figure BDA0002778270360000115
for the output power of the photovoltaic power generation system at the current moment,
Figure BDA0002778270360000116
is the output power, P, of the wind power system at the present momentHDRInstalled capacity, P, for geothermal power systemsPVInstalled capacity, P, for photovoltaic power generation systemsWindAnd the installed capacity of the wind power generation system is obtained.
Figure BDA0002778270360000117
The electric load required by facility agriculture is determined by actual facility agriculture electric equipment;
Figure BDA0002778270360000118
the load is the electric refrigeration load and is determined by the parameters of the refrigerator of the refrigeration house;
Figure BDA0002778270360000119
the self-electricity load of the hot dry rock heat extraction system is determined by the power of the hot dry rock circulating pump. And the method also comprises the output constraint of a power generation system, and the wind, light and geothermal power generation power is not more than the planned capacity at any moment.
Based on the content of the foregoing embodiments, as an alternative embodiment, the power balancing of the cooling and heating network includes:
Figure BDA00027782703600001110
Figure BDA00027782703600001111
Figure BDA00027782703600001112
wherein the content of the first and second substances,
Figure BDA00027782703600001113
and
Figure BDA00027782703600001114
respectively adopts high-temperature and medium-temperature heat supply power,
Figure BDA00027782703600001115
and
Figure BDA00027782703600001116
respectively the heat release power of the high-temperature heat storage system and the medium-temperature heat storage system,
Figure BDA00027782703600001117
and
Figure BDA00027782703600001118
respectively the heat storage power of the high-temperature heat storage system and the medium-temperature heat storage system,
Figure BDA00027782703600001119
and
Figure BDA00027782703600001120
respectively adopts high-temperature and medium-temperature waste heat power,
Figure BDA00027782703600001121
in order to provide the thermal cooling power,
Figure BDA00027782703600001122
respectively for high temperature and medium temperature thermal loads,
Figure BDA00027782703600001123
for cold load, λeTo the electric refrigeration coefficient lambdaqCoefficient of thermal cooling.
The first formula is a high-temperature heat supply power balance constraint, the second formula is a medium-temperature heat supply power balance constraint,
Figure BDA00027782703600001124
the high temperature and medium temperature thermal loads are determined by actual needs of facility agriculture. The second formula is the balance of the cooling capacity,
Figure BDA00027782703600001125
lambda is the cooling load, determined by the actual operating requirements of the cold storeeFor the electric refrigeration coefficient, selected according to the actual refrigeration equipment, lambdaqAnd the thermal refrigeration coefficient is selected according to the performance of the actual absorption refrigerator.
Based on the content of the above embodiments, as an alternative embodiment, the CHP-EGS model includes:
Figure BDA0002778270360000121
Figure BDA0002778270360000122
Figure BDA0002778270360000123
Figure BDA0002778270360000124
Figure BDA0002778270360000125
Figure BDA0002778270360000126
QtMO＝mtMcpwater(TM-Twater)；
Figure BDA0002778270360000127
the above formula gives the basic operation model of CHP-EGS. Wherein the first formula sum is a heat extraction cycle model. Wherein t represents the tth scheduling time in the whole scheduling period tau, and t +1 represents the next scheduling time after the tth scheduling time; alpha is alphatThe value of the geothermal energy coefficient for power generation is between 0.1 and 1 according to the output power required by an actual system; beta is atThe geothermal energy coefficient for supplying heat is 1-alphat；
Figure BDA0002778270360000128
The residual temperatures of the geothermal working media after passing through the high-temperature heat supply unit and the geothermal power generation unit are respectively, and the value is not less than 75 ℃ for ensuring the medium-temperature heat supply quality.
Figure BDA0002778270360000129
The heat source temperature of the heat exchanger of the medium-temperature heat supply unit is taken into consideration of the actual heating demand, and the value is 75 ℃. The second formula is a simplified model of the geothermal power unit,
Figure BDA00027782703600001210
the output power of the geothermal power generation unit at the present moment,
Figure BDA00027782703600001211
for generating efficiency, cp is determined according to the actually selected low-temperature generatorHDRIs the specific heat capacity of geothermal working medium, the value of the specific heat capacity is the specific heat capacity of circulating water,
Figure BDA00027782703600001212
for the mass flow of the power generating unit, the value is determined from the total mass flow of the geothermal working medium and alphatThe product of (a) and (b). T isHDRThe value of the temperature of the geothermal working medium input into the geothermal power generation unit is selected according to the actual geothermal reservoir temperature. Third stepThe heat supply and storage models of the high-temperature heat exchange system are given by the fifth formula, wherein the third formula is a heat model of geothermal energy input into the high-temperature heat supply system, mHDRThe total mass flow of the geothermal working medium is 50-150kg/s according to the limitation of drilling technical conditions. The fourth formula is a heat model of the high temperature heat supply system providing high temperature heat load through the heat storage medium,
Figure BDA0002778270360000131
cpOilrespectively mass flow and specific heat capacity of high-temperature heat supply working medium, the values of which are respectively determined by the heat power required by heat supply and the physical properties of the adopted heat supply working medium, THProviding temperature for high temperature load, the value of which is geothermal reservoir temperature, TOilThe initial temperature of the high-temperature heat supply working medium is determined by the ambient temperature.
Figure BDA0002778270360000132
Represents the input thermal power of the high-temperature heat exchanger,
Figure BDA0002778270360000133
the output thermal power of the high-temperature heat exchanger is represented; the fifth formula is the equation of state of the high temperature heat storage tank,
Figure BDA0002778270360000134
the input thermal power of the medium-temperature heat exchanger is shown,
Figure BDA0002778270360000135
the output thermal power of the medium-temperature heat exchanger is shown,
Figure BDA0002778270360000136
the high-temperature heat storage quantity at the time t,
Figure BDA0002778270360000137
storing the heat quantity for the high temperature at the next scheduling moment;
Figure BDA0002778270360000138
and
Figure BDA0002778270360000139
the high-temperature heat accumulation/release power and the electric heating power at the time t are calculated by the model according to input conditions and are provided for the agricultural comprehensive energy network capacity configuration model containing the CHP-EGS independent facility for optimization. EtaHTaking 1%/24 h eta as heat dissipation coefficientEQTaking 95% as electric heat exchange coefficientHc、μHdcThe variable is 0-1, so that the heat accumulation and heat release processes can not be carried out simultaneously. The medium temperature heating system model (M in the parameter represents medium temperature) includes sixth to eighth formulas, wherein the sixth formula is a heat model of geothermal energy input to the medium temperature heating system,
Figure BDA00027782703600001310
the temperature of geothermal working medium reinjection. The seventh formula is a heat model of the medium-temperature heat supply system providing the medium-temperature heat load through the heat storage medium,
Figure BDA00027782703600001311
cpwaterrespectively medium-temperature heat supply working medium mass flow and specific heat capacity, the values of which are respectively determined by heat power required by heat supply and physical properties of adopted heat supply working medium, TMProviding temperature for the medium temperature load, the value of which is generally determined according to the local heating demand, TwaterThe initial temperature of the medium-temperature heat supply working medium is determined by the ambient temperature. The eighth formula is the equation of state of the medium temperature heat storage tank,
Figure BDA00027782703600001312
and
Figure BDA00027782703600001313
the values of the medium-temperature heat storage quantity, the heat storage/release power and the electric heating power at the moment t are calculated by the model according to input conditions and are provided for the CHP-EGS-containing independent facility agriculture comprehensive energy network capacity configuration model for optimization. EtaMTaking 1%/24 h eta as heat dissipation coefficientEQTaking 95% as electric heat exchange coefficientMc、μMdcThe variable is 0-1, so that the heat accumulation and heat release processes can not be simultaneously carried outThe process is carried out.
The operation conditions of the agricultural comprehensive energy network planning optimization model containing CHP-EGS contain decision variables
Figure BDA00027782703600001314
The product term is subjected to iterative solution on an analysis target by means of nonlinear optimization solution software, so that analysis is carried out on the scale of each energy configuration in agricultural comprehensive energy network planning.
The capacity allocation device for a facility agriculture energy network with an enhanced geothermal system according to an embodiment of the present invention is described below, and the capacity allocation device for a facility agriculture energy network with an enhanced geothermal system described below and the capacity allocation method for a facility agriculture energy network with an enhanced geothermal system described above may be referred to in correspondence.
Fig. 2 is a schematic structural diagram of a facility agricultural energy grid capacity distribution device with an enhanced geothermal system according to an embodiment of the present invention, and as shown in fig. 2, the facility agricultural energy grid capacity distribution device with an enhanced geothermal system includes: an input module 201 and an analysis module 202. The input module 201 is used for determining a CHP-EGS model, a wind power generation model and a photovoltaic power generation model; the analysis module 202 is used for optimizing, solving and obtaining installed capacity allocation results of the corresponding heat storage device, heat generation device, wind power generation and photovoltaic power generation based on all models by taking system electric power balance and cold and hot network power balance as constraint conditions and minimum system annual average cost as an objective function, and is used for capacity allocation of the energy network; the CHP-EGS model is a heat conversion model among a heat extraction unit, a power generation unit, a high-temperature heat supply unit, a medium-temperature heat supply unit and a refrigeration system in a facility agriculture energy network; the wind power generation model and the photovoltaic power generation model are respectively a relation model between the output power of wind power generation and photovoltaic power generation and the installed capacity of the wind power generation model and the photovoltaic power generation model.
The device embodiment provided in the embodiments of the present invention is for implementing the above method embodiments, and for details of the process and the details, reference is made to the above method embodiments, which are not described herein again.
The capacity distribution device for the facility agriculture energy network containing the enhanced geothermal system provided by the embodiment of the invention performs optimization solution on the limiting conditions according to the CHP-EGS model, the wind power generation model and the photovoltaic power generation model to obtain the installed capacity distribution result of the heat storage device, the heat generation device, the wind power generation and the photovoltaic power generation which minimizes the annual average cost of the system, and is beneficial to effectively reducing the cost of the system under the precondition of stable operation of the energy network.
Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, and as shown in fig. 3, the electronic device may include: a processor (processor)301, a communication Interface (communication Interface)302, a memory (memory)303 and a communication bus 304, wherein the processor 301, the communication Interface 302 and the memory 303 complete communication with each other through the communication bus 304. The processor 301 may invoke logic instructions in the memory 303 to perform a facility agricultural energy grid capacity allocation method including an enhanced geothermal system, the method comprising: determining a CHP-EGS model, a wind power generation model and a photovoltaic power generation model; based on all models, taking system electric power balance and cold and hot network power balance as constraint conditions, taking minimized system annual average cost as an objective function, and optimally solving to obtain corresponding installed capacity distribution results of the heat storage device, the heat generation device, the wind power generation and the photovoltaic power generation for capacity distribution of the energy network; the CHP-EGS model is a heat conversion model among a heat extraction unit, a power generation unit, a high-temperature heat supply unit, a medium-temperature heat supply unit and a refrigeration system in a facility agriculture energy network; the wind power generation model and the photovoltaic power generation model are respectively a relation model between the output power of wind power generation and photovoltaic power generation and the installed capacity of the wind power generation model and the photovoltaic power generation model.
In addition, the logic instructions in the memory 303 may be implemented in the form of software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, an embodiment of the present invention further provides a computer program product, the computer program product includes a computer program stored on a non-transitory computer-readable storage medium, the computer program includes program instructions, when the program instructions are executed by a computer, the computer can execute the method for allocating capacity of a facility agricultural energy grid including an enhanced geothermal system, the method includes: determining a CHP-EGS model, a wind power generation model and a photovoltaic power generation model; based on all models, taking system electric power balance and cold and hot network power balance as constraint conditions, taking minimized system annual average cost as an objective function, and optimally solving to obtain corresponding installed capacity distribution results of the heat storage device, the heat generation device, the wind power generation and the photovoltaic power generation for capacity distribution of the energy network; the CHP-EGS model is a heat conversion model among a heat extraction unit, a power generation unit, a high-temperature heat supply unit, a medium-temperature heat supply unit and a refrigeration system in a facility agriculture energy network; the wind power generation model and the photovoltaic power generation model are respectively a relation model between the output power of wind power generation and photovoltaic power generation and the installed capacity of the wind power generation model and the photovoltaic power generation model.
In yet another aspect, an embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program is implemented by a processor to perform the method for allocating capacity of a facility agricultural energy grid including an enhanced geothermal system according to the embodiments, where the method includes: determining a CHP-EGS model, a wind power generation model and a photovoltaic power generation model; based on all models, taking system electric power balance and cold and hot network power balance as constraint conditions, taking minimized system annual average cost as an objective function, and optimally solving to obtain corresponding installed capacity distribution results of the heat storage device, the heat generation device, the wind power generation and the photovoltaic power generation for capacity distribution of the energy network; the CHP-EGS model is a heat conversion model among a heat extraction unit, a power generation unit, a high-temperature heat supply unit, a medium-temperature heat supply unit and a refrigeration system in a facility agriculture energy network; the wind power generation model and the photovoltaic power generation model are respectively a relation model between the output power of wind power generation and photovoltaic power generation and the installed capacity of the wind power generation model and the photovoltaic power generation model.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus necessary general hardware devices, and certainly, can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (10)

1. A method for allocating capacity of a facility agricultural energy grid including an enhanced geothermal system, comprising:
determining an EGS model, a wind power generation model and a photovoltaic power generation model of a combined heat and power CHP-enhanced geothermal system;
based on all models, taking system electric power balance and cold and hot network power balance as constraint conditions, taking minimized system annual average cost as an objective function, and optimally solving to obtain corresponding installed capacity distribution results of the heat storage device, the heat generation device, the wind power generation and the photovoltaic power generation for capacity distribution of the energy network;
the CHP-EGS model is a heat conversion model among a heat extraction unit, a power generation unit, a high-temperature heat supply unit, a medium-temperature heat supply unit and a refrigeration system in a facility agriculture energy network; the wind power generation model and the photovoltaic power generation model are respectively a relation model between the output power of wind power generation and photovoltaic power generation and the installed capacity of the wind power generation model and the photovoltaic power generation model.
2. The method for allocating capacity of a facility agricultural energy grid including an enhanced geothermal system according to claim 1, wherein the system annual average cost is determined according to the system annual average investment cost and annual average operating cost in different scenarios;
the annual average running cost under different scenes is determined according to the probability of each scene and the system running cost expectation of the corresponding scene;
the different scenes are generated according to the historical data of the wind speed and solar irradiance of the whole year and corresponding probability.
3. The method for allocating capacity of a facility agricultural energy grid containing an enhanced geothermal system according to claim 2, wherein the annual average investment cost is determined as follows:
Cinv＝cPVPPV+cWindPWind+cQS(SHS+SMS)+cEQ(PHEQ+PMEQ)；
wherein, PPVInstalled capacity, P, for photovoltaic power generation systemsWindInstalled capacity for wind power systems, SH/SMRespectively high/medium temperature heat storage system capacity, PHEQ/PMEQRespectively the power of the high/medium temperature electric heating system; c. CPV、cWind、cQS、cEQRespectively, the unit investment cost coefficients of the corresponding systems.
4. The method for allocating capacity to a facility agricultural energy grid including an enhanced geothermal system according to claim 2, wherein the system operating cost expectation for each scenario is determined as follows:
Figure FDA0002778270350000021
wherein tau represents the whole scheduling time period, and delta tau is the length of each time interval divided at equal intervals in the whole scheduling period;
Figure FDA0002778270350000022
respectively representing the medium-temperature heat power loss, the high-temperature heat power loss and the power loss of the power generation system at the moment t under the scene s; c. Cm、cH、ceRespectively corresponding loss cost coefficients;
Figure FDA0002778270350000023
abandoning load thermal power from medium temperature
Figure FDA0002778270350000024
Heat dissipation loss of medium temperature heat storage system
Figure FDA0002778270350000025
Forming;
Figure FDA0002778270350000026
produced when the system cannot meet the medium-temperature heat supply loadThe shortage of power is set up,
Figure FDA0002778270350000027
power loss for heat storage system to dissipate heat to the environment;
Figure FDA0002778270350000028
thermal power from high temperature to waste load
Figure FDA0002778270350000029
And heat dissipation loss of high-temperature heat storage system
Figure FDA00027782703500000210
Forming;
Figure FDA00027782703500000211
power of electric load by abandoning
Figure FDA00027782703500000212
Optical power of waste
Figure FDA00027782703500000213
Wind power curtailment
Figure FDA00027782703500000214
And electric heating power loss
Figure FDA00027782703500000215
Forming;
Figure FDA00027782703500000216
the power loss of the equipment in the process of electric heating and heat storage is realized.
5. The method for utility agricultural energy grid capacity allocation with an enhanced geothermal system according to claim 2, wherein the system electrical power balancing comprises:
Figure FDA00027782703500000217
Figure FDA00027782703500000218
Figure FDA00027782703500000219
Figure FDA00027782703500000220
wherein s and t represent t moments in an s scene;
Figure FDA00027782703500000221
is the output power of the geothermal power generation unit,
Figure FDA00027782703500000222
is the output power of the photovoltaic power generation system,
Figure FDA00027782703500000223
is the output power of the wind power system, PHDRInstalled capacity, P, for geothermal power systemsPVInstalled capacity, P, for photovoltaic power generation systemsWindFor the installed capacity of the wind power generation system,
Figure FDA00027782703500000224
the electric load required for the agriculture of the facility,
Figure FDA00027782703500000225
in order to electrically cool the load,
Figure FDA00027782703500000226
for the hot dry rock heat extraction systemThe load of the electricity is used and the load,
Figure FDA00027782703500000227
is used for high-temperature electric heating power,
Figure FDA00027782703500000228
the medium temperature electric heating power.
6. The method for allocating capacity of a facility agricultural energy grid including an enhanced geothermal system according to claim 2, wherein the cold and hot grid power balancing comprises:
Figure FDA0002778270350000031
Figure FDA0002778270350000032
Figure FDA0002778270350000033
wherein s and t represent t moments in an s scene;
Figure FDA0002778270350000034
and
Figure FDA0002778270350000035
respectively adopts high-temperature and medium-temperature heat supply power,
Figure FDA0002778270350000036
and
Figure FDA0002778270350000037
respectively the heat release power of the high-temperature heat storage system and the medium-temperature heat storage system,
Figure FDA0002778270350000038
and
Figure FDA0002778270350000039
respectively the heat storage power of the high-temperature heat storage system and the medium-temperature heat storage system,
Figure FDA00027782703500000310
and
Figure FDA00027782703500000311
respectively adopts high-temperature and medium-temperature waste heat power,
Figure FDA00027782703500000312
in order to provide the thermal cooling power,
Figure FDA00027782703500000313
respectively for high temperature and medium temperature thermal loads,
Figure FDA00027782703500000314
for cold load, λeIs the electric refrigeration coefficient, λqCoefficient of thermal cooling.
7. The method for enhanced geothermal system-containing facility agricultural energy grid capacity allocation according to claim 1, wherein the CHP-EGS model comprises:
Figure FDA00027782703500000315
Figure FDA00027782703500000316
Figure FDA00027782703500000317
Figure FDA00027782703500000318
Figure FDA00027782703500000319
Figure FDA00027782703500000320
Figure FDA00027782703500000321
Figure FDA00027782703500000322
wherein t represents the tth scheduling time in the whole scheduling period tau, and t +1 represents the next scheduling time after the tth scheduling time; alpha is alphatIs the geothermal energy coefficient for power generation; beta is atIs the geothermal energy coefficient for supplying heat;
Figure FDA00027782703500000323
the residual temperatures of the geothermal working media after passing through the high-temperature heat supply unit and the geothermal power generation unit are respectively;
Figure FDA00027782703500000324
the heat source temperature of the heat exchanger of the medium temperature heat supply unit;
Figure FDA00027782703500000325
the output power of the geothermal power generation unit at the present moment,
Figure FDA00027782703500000326
to generate electricityEfficiency, cpHDRIs the specific heat capacity of the geothermal working medium,
Figure FDA0002778270350000041
for the mass flow of the power generating unit, the value is determined from the total mass flow of the geothermal working medium and alphatObtaining the product of; t isHDRInputting the temperature of geothermal working medium of the geothermal power generation unit; m isHDRIs the total mass flow of the geothermal working medium,
Figure FDA0002778270350000042
cpOilrespectively providing mass flow and specific heat capacity, T, of high-temperature heat supply working mediumHProviding a temperature, T, for a high temperature loadOilThe initial temperature of the high-temperature heat supply working medium is determined by the ambient temperature;
Figure FDA0002778270350000043
represents the input thermal power of the high-temperature heat exchanger,
Figure FDA0002778270350000044
the output thermal power of the high-temperature heat exchanger is shown,
Figure FDA0002778270350000045
the input thermal power of the medium-temperature heat exchanger is shown,
Figure FDA0002778270350000046
the output thermal power of the medium-temperature heat exchanger is represented;
Figure FDA0002778270350000047
the high-temperature heat storage quantity at the time t,
Figure FDA0002778270350000048
storing the heat quantity for the high temperature at the next scheduling moment;
Figure FDA0002778270350000049
and
Figure FDA00027782703500000410
respectively obtaining high-temperature heat accumulation/release power and electric heating power at the moment t; etaHIs a heat dissipation coefficient, ηEQIs the electric heat transfer coefficient, muHc、μHdcThe variable is 0-1, so that the heat storage and release processes can not be carried out simultaneously;
Figure FDA00027782703500000411
the temperature is the reinjection temperature of the geothermal working medium;
Figure FDA00027782703500000412
cpwaterrespectively providing medium temperature heat supply working medium mass flow and specific heat capacity; t isMProviding temperature, T, for medium temperature loadswaterInitial temperature of medium temperature heat supply working medium;
Figure FDA00027782703500000413
and
Figure FDA00027782703500000414
the medium-temperature heat storage quantity, the heat storage/release power and the electric heating power at the moment t are respectively; etaMIs a heat dissipation coefficient, ηEQIs the electrical heat transfer coefficient; mu.sMc、μMdcThe variable is 0-1, so that the heat accumulation and heat release processes can not be carried out simultaneously.
8. A facility agriculture energy grid capacity distribution device including an enhanced geothermal system, comprising:
the input module is used for determining an EGS model, a wind power generation model and a photovoltaic power generation model of the combined heat and power CHP-enhanced geothermal system;
the analysis module is used for optimizing, solving and obtaining the installed capacity distribution results of the corresponding heat storage device, the heat production device, the wind power generation and the photovoltaic power generation based on all models by taking the system electric power balance and the cold and hot network power balance as constraint conditions and the minimized system annual average cost as an objective function, and is used for capacity distribution of the energy network;
the CHP-EGS model is a heat conversion model among a heat extraction unit, a power generation unit, a high-temperature heat supply unit, a medium-temperature heat supply unit and a refrigeration system in a facility agriculture energy network; the wind power generation model and the photovoltaic power generation model are respectively a relation model between the output power of wind power generation and photovoltaic power generation and the installed capacity of the wind power generation model and the photovoltaic power generation model.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program performs the steps of the method for enhancing the capacity allocation of a facility agricultural energy grid including an geothermal enhancement system according to any one of claims 1 to 7.
10. A non-transitory computer readable storage medium having a computer program stored thereon, wherein the computer program when executed by a processor implements the steps of the method for allocating capacity to a facility agricultural energy grid including an augmented geothermal system according to any one of claims 1 to 7.
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