CN110783917A - Configuration method of multi-energy hub containing new energy consumption - Google Patents

Configuration method of multi-energy hub containing new energy consumption Download PDF

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Publication number
CN110783917A
CN110783917A CN201911069527.9A CN201911069527A CN110783917A CN 110783917 A CN110783917 A CN 110783917A CN 201911069527 A CN201911069527 A CN 201911069527A CN 110783917 A CN110783917 A CN 110783917A
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energy
hub
power
electricity
energy hub
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方美芳
张聂鹏
王满商
雷一
杨利荣
白少锋
胡航
李海波
熊宇威
葛路明
于若英
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Jiangsu Xin Zhi He Electric Power Technology Co Ltd
State Grid Jiangsu Electric Power Co Ltd Zhenjiang Power Supply Branch
China Electric Power Research Institute Co Ltd CEPRI
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Jiangsu Xin Zhi He Electric Power Technology Co Ltd
State Grid Jiangsu Electric Power Co Ltd Zhenjiang Power Supply Branch
China Electric Power Research Institute Co Ltd CEPRI
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
    • H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
    • 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
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
    • Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
    • Y02B70/3225—Demand response systems, e.g. load shedding, peak shaving
    • 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
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
    • Y04S20/20—End-user application control systems
    • Y04S20/222—Demand response systems, e.g. load shedding, peak shaving

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Abstract

The invention discloses a configuration method of a multi-energy hub containing new energy consumption, which comprises the following steps: s1, collecting parameters for establishing an energy hub; s2, establishing an optimization objective function based on the acquired parameters; m in C ATC＝C IN+C OM+C ES(ii) a Wherein, C INFor initial installation costs of equipment in an energy hub, C OMFor operating and maintenance costs of the energy hub, C ESCost of energy consumption for energy hub, C ATCIs the total cost of the energy hub; s3, adjusting parameters of the energy hub to enable the optimization objective function to obtain an optimal solution, and configuring the capacity parameters of each device of the energy hub under the current optimal solution of the objective function; based on the optimal solution of the objective function, the capacity of each device is configured, and therefore the energy model is setAnd optimizing, so that the energy hub model can be ensured to be in the optimal operation, the stability of the whole energy system can be ensured, the analysis process is simple, the implementation is easy, and the operation and operation cost of the energy hub can be ensured to be low.

Description

Configuration method of multi-energy hub containing new energy consumption
Technical Field
The invention relates to a power analysis method, in particular to a configuration method of a multi-energy hub containing new energy consumption, and belongs to the technical field of power analysis.
Background
A multi-energy hub comprises an energy system formed by coupling a plurality of energy sources of electricity, heat and gas, and can be described by using the energy hub no matter the size of the system as long as the energy system can be reasonably modeled, such as a single residential user, a commercial building (such as an airport and a hospital), a factory (such as a steel mill and a paper mill), a conventional generator set (such as a hydropower station with pumped storage, a CHP (chemical vapor deposition) and the like), an energy system of a region (such as a business district and an industrial park) and even a country and the like, which can be called as energy hubs, wherein the multi-energy hub comprises: the energy conduction equipment does not carry out any energy conversion and can realize the direct transmission of energy, such as a cable, a heat supply network pipeline and an air network pipeline; energy conversion equipment for converting and coupling different energy forms, such as fuel cells, motors, steam and gas turbines, internal combustion engines, electrolyzers, etc.; an energy storage device: batteries, extraction and storage power station, heat-retaining device etc. energy hub all generally adopts foretell three aspect to describe, and when energy hub consumes the new forms of energy in the operation process, for example: the consumption of heat energy and gas energy needs to be optimally configured for the capacity of the equipment in the energy hub so as to ensure the stability of the energy system, but no effective method for optimally configuring the capacity of the energy hub exists at present.
Disclosure of Invention
The invention aims to provide a configuration method of a multi-energy hub containing new energy consumption, which can optimize and configure the capacity of the energy hub.
The purpose of the invention is realized by the following technical scheme:
a configuration method of a multi-energy hub containing new energy consumption comprises the following steps:
s1, collecting parameters for establishing an energy hub, wherein the parameters comprise unit capacity cost, fuel price cost and operation and maintenance cost in the service life cycle of various devices;
s2, establishing an optimization objective function based on the acquired parameters;
min C ATC＝C IN+C OM+C ES(ii) a Wherein, C INFor initial installation costs of equipment in an energy hub, C OMFor operating and maintenance costs of the energy hub, C ESCost of energy consumption for energy hub, C ATCIs the total cost of the energy hub;
and S3, adjusting parameters of the energy hub to enable the optimization objective function to obtain an optimal solution, configuring capacity parameters of each device of the energy hub under the current optimal solution of the objective function, determining a time curve of load energy supply under three seasonal scenes of spring, autumn, summer and winter in one year, and analyzing the sensitivity of the energy hub.
Preferably, in step S2, the initial installation cost C of the devices in the energy hub INIs determined by the following method:
Figure BDA0002260508350000021
wherein, C SIs the installation capacity of the device S,
Figure BDA0002260508350000022
the installation cost per unit volume of the equipment S, r is the reference discount rate of the equipment S, l sIs the average life of the device S.
Preferably, in step S2, the operation and maintenance cost C of the energy hub OMIs determined by the following method:
C OM＝C INand x a, a is the operation and maintenance cost coefficient of the equipment and is the ratio of the annual maintenance cost of the equipment to the initial installation cost.
Preferably, in step S1, the energy consumption cost C of the energy hub ESIs determined by the following method:
Figure BDA0002260508350000023
Figure BDA0002260508350000024
and
Figure BDA0002260508350000025
respectively the gas purchase price, the electricity purchase price and the electricity sale price at the moment t; and the electricity purchasing power and the electricity selling power at the moment t are respectively; f. of s.tIs the gas consumption rate of the equipment s at the moment t, n is the number of scenes of the energy hub operation, d nThe number of days the energy hub lasts in different scenes.
Preferably, the energy consumption cost C of the energy hub ESWith the following constraints:
Figure BDA0002260508350000029
Figure BDA00022605083500000210
Figure BDA00022605083500000211
respectively the electric load, the heat load and the cold load of the system at the moment t;
Figure BDA00022605083500000212
and
Figure BDA00022605083500000213
electric power consumed and electric power output by the device s at the time t, respectively;
Figure BDA00022605083500000214
and
Figure BDA00022605083500000215
respectively representing the thermal power consumed and the thermal power output by the device s at the moment t; representing the cold power output by the device s at time t.
Preferably, the method further comprises the following steps of:
Figure BDA00022605083500000217
Figure BDA0002260508350000031
Figure BDA0002260508350000032
p buy.maxpurchasing electric power upper limit, p, from the distribution system for the energy hub sell.maxAn upper limit of power sold to the distribution system;
Figure BDA0002260508350000033
Figure BDA0002260508350000034
respectively 0-1 state variables of the energy hub at the time t for purchasing and selling electricity,
Figure BDA0002260508350000035
it is indicated that the electricity is purchased,
Figure BDA0002260508350000036
indicating the sale of electricity.
Preferably, the method further comprises the following installation capacity constraint conditions:
Figure BDA0002260508350000037
γ sis a 0-1 state variable, gamma s0 and γ s1 denotes no installation and installation equipment, respectively;
Figure BDA0002260508350000038
and
Figure BDA0002260508350000039
respectively, a lower limit and an upper limit of the installation capacity of the device s.
Preferably, the following constraints are also included:
Figure BDA00022605083500000310
Figure BDA00022605083500000311
Figure BDA00022605083500000313
wherein the content of the first and second substances,
Figure BDA00022605083500000314
and
Figure BDA00022605083500000315
minimum and maximum load rates of an energy hub unit (including various energy conduction, conversion and storage devices) s, respectively, with the subscript s denoting the s-th energy hub unit; psi s.tIs a 0-1 state variable, # s.t0 and psi s.t1 denotes that the energy terminal unit is not switched on and is switched on at time t, respectively, and for the energy conversion unit, w s.tRepresenting the output power of the device s at the instant t,
Figure BDA00022605083500000316
and
Figure BDA00022605083500000317
respectively, a minimum stored energy requirement and a maximum stored energy requirement, W, of the energy storage unit s.tThe stored energy that the energy storage unit has at time t; and
Figure BDA00022605083500000319
respectively charging energy power and discharging energy power for the energy storage unit at the moment t;
Figure BDA00022605083500000320
and the charging and discharging multiplying power of the energy storage unit is respectively set;
Figure BDA00022605083500000322
and representing the energy storage unit in a 0-1 state variable charged and discharged respectively at time t,
Figure BDA00022605083500000324
the indication is that the energy is being charged,
Figure BDA00022605083500000325
indicating the discharge energy.
The invention has the beneficial effects that: according to the method, an analysis model with cost as a target function is established, relevant parameters of the energy hub model are obtained, the optimal solution of the target function is used as a reference when the target function reaches the optimal solution, and then the capacity of each device is configured, so that the energy model is set and optimized, the energy hub model can be ensured to be in the optimal operation, the stability of the whole energy system can be ensured, the analysis process is simple, the implementation is easy, and the operation cost of the energy hub can be ensured to be low.
Drawings
FIG. 1 is a schematic diagram of an energy hub according to the present invention;
FIG. 2 is a diagram of the cooling, heating and power load curves of the embodiment of the present invention;
FIG. 3 is a graph of electricity prices for an embodiment of the present invention;
FIG. 4 is a comparison graph of thermal and electrical balance curves of the embodiment of the present invention in spring and autumn;
FIG. 5 is a comparison graph of thermal and electrical balance curves for an embodiment of the present invention during summer operation;
fig. 6 is a comparison graph of thermal balance and electrical balance curves of the embodiment of the invention in a winter running state.
Detailed Description
The present invention is explained in further detail below with reference to the drawings attached to the specification, and it should be noted that the detailed description of the present invention is only for the preferred embodiments, and any modifications and equivalents of the technical solutions of the present invention by those skilled in the art are included in the scope of the technical solutions of the present application.
The topology of the energy hub model provided by the invention is shown in fig. 1, for an energy-using carrier (such as a building or a factory), the required energy forms comprise electric energy (for lighting, converting into mechanical energy such as an elevator, supplying energy for IT equipment and the like), heat energy (for heating air, generating hot water or for some processing processes requiring heat) and cold (for cooling air and refrigerating), and the injected energy forms comprise purchasing electricity from a power grid, purchasing gas from a gas grid, building photovoltaic by using a roof and building discrete fans by using a building vertex angle. The obtained energy form (wind, light and electricity) needs to be subjected to a series of conduction, conversion and storage to match the requirements of cold, heat and electricity loads, and the conversion (an electric refrigerator converts electric energy into cold and gas and converts gas into electricity and heat, an absorption refrigerator converts heat into cold and photovoltaic converts light into electricity, a fan converts wind into electricity, a heat pump converts electricity into heat, a gas boiler converts gas into heat, and a waste heat boiler converts waste heat of a gas engine into heat energy), the storage (electric energy storage and heat energy storage) and the conduction equipment (pipelines) are configured differently, so that the cost is different. The patent aims to solve the problems that the energy conversion, storage and conduction equipment is configured, the configuration capacity is the most economical, and the load requirement can be met. In fig. 1, a schematic diagram of a thermally, electrically and electrically coupled topology is shown, and a detailed analysis is performed based on the topology according to an embodiment of the present invention.
The invention provides a configuration method of a multi-energy hub containing new energy consumption, which comprises the following steps:
s1, collecting parameters for establishing an energy hub;
s2, establishing an optimization objective function based on the acquired parameters;
min C ATC＝C IN+C OM+C ES(ii) a Wherein, C INFor initial installation costs of equipment in an energy hub, C OMFor operating and maintenance costs of the energy hub, C ESCost of energy consumption for energy hub, C ATCIs the total cost of the energy hub;
s3, adjusting parameters of the energy hub to enable the optimization objective function to obtain an optimal solution, and configuring the capacity parameters of each device of the energy hub under the current optimal solution of the objective function; for the capacity configuration of each device, the capacity of each energy device in the energy hub is changed through the energy price, load and the like of the season, and the specific configuration process is described by the following specific examples; according to the method, the cost is used as an analysis model of the objective function, the relevant parameters of the energy hub model are obtained, the optimal solution of the objective function is used as a reference when the objective function reaches the optimal solution, and the capacity of each device is configured, so that the energy model is set and optimized, the energy hub model can be ensured to be in the optimal operation, the stability of the whole energy system can be ensured, the analysis process is simple, the implementation is easy, and the running cost of the energy hub can be ensured to be low.
In step S2, the initial installation cost C of the devices in the energy hub INIs determined by the following method:
Figure BDA0002260508350000051
wherein, C SIs the installation capacity of the device S,
Figure BDA0002260508350000052
the installation cost per unit volume of the equipment S, r is the reference discount rate of the equipment S, l sOf apparatus SAverage life.
In step S2, the operation maintenance cost C of the energy hub OMIs determined by the following method:
C OM＝C INand x a, a is the coefficient of the running and maintenance cost of the equipment.
In step S1, energy consumption cost C of energy hub ESIs determined by the following method:
Figure BDA0002260508350000053
Figure BDA0002260508350000054
and
Figure BDA0002260508350000055
respectively the gas purchase price, the electricity purchase price and the electricity sale price at the moment t; and
Figure BDA0002260508350000057
the electricity purchasing power and the electricity selling power at the moment t are respectively; f. of s.tIs the gas consumption rate of the equipment s at the moment t, n is the number of scenes of the energy hub operation, d nThe duration days of the energy hub under different scenes are shown, wherein the scenes refer to three scenes of spring and autumn, winter and summer in one year.
Energy cost of an energy hub C ESWith the following constraints:
Figure BDA0002260508350000058
Figure BDA0002260508350000061
Figure BDA0002260508350000062
Figure BDA0002260508350000063
respectively the electric, heat and cold loads of the system at the moment t;
Figure BDA0002260508350000064
and electric power consumed and electric power output by the device s at the time t, respectively;
Figure BDA0002260508350000066
and
Figure BDA0002260508350000067
respectively representing the thermal power consumed and the thermal power output by the device s at the moment t; representing the cold power output by the device s at time t.
The configuration method further comprises the following steps of:
Figure BDA0002260508350000069
Figure BDA00022605083500000610
p buy.max、p sell.maxpurchasing power from a power distribution system and selling power to the power distribution system for the energy hub; respectively 0-1 state variables of the energy hub at the time t for purchasing and selling electricity,
Figure BDA00022605083500000613
it is indicated that the electricity is purchased, indicating the sale of electricity.
The configuration method further comprises installing capacity constraints:
Figure BDA00022605083500000615
γ sis a 0-1 state variable, gamma s0 and γ s1 denotes no installation and installation equipment, respectively;
Figure BDA00022605083500000616
and respectively, a lower limit and an upper limit of the installation capacity of the device s.
The configuration method further comprises the following constraint conditions:
Figure BDA00022605083500000618
Figure BDA00022605083500000619
Figure BDA00022605083500000620
Figure BDA00022605083500000621
wherein the content of the first and second substances, and
Figure BDA00022605083500000623
minimum and maximum load rates of an energy hub unit (including various energy conduction, conversion and storage devices) s, respectively, with the subscript s denoting the s-th energy hub unit; psi s.tIs a 0-1 state variable, # s.t0 and psi s.t1 denotes that the energy terminal unit is not switched on and is switched on at time t, respectively, and for the energy conversion unit, w s.tRepresenting the output power of the device s at the instant t,
Figure BDA0002260508350000071
and
Figure BDA0002260508350000072
respectively, a minimum stored energy requirement and a maximum stored energy requirement, W, of the energy storage unit s.tThe stored energy that the energy storage unit has at time t;
Figure BDA0002260508350000073
and
Figure BDA0002260508350000074
respectively charging energy power and discharging energy power for the energy storage unit at the moment t;
Figure BDA0002260508350000075
and
Figure BDA0002260508350000076
the charging and discharging multiplying power of the energy storage unit is respectively set; and
Figure BDA0002260508350000078
representing the energy storage unit in a 0-1 state variable charged and discharged respectively at time t,
Figure BDA0002260508350000079
the indication is that the energy is being charged,
Figure BDA00022605083500000710
indicating the discharge energy. Through the constraint conditions, the optimal solution can be accurately solved for the cost model, and the analysis of the energy hub model is guided.
The following is a specific embodiment, a 6 square kilometer area comprehensive energy source is configured as an object to develop planning, one existing and newly-built 110 kv substation in the area mainly uses energy loads including two commercial building air conditioners and 5 industrial enterprises needing hot water, and the area planning builds 1 ten thousand kilowatt solar photovoltaic and 1 ten thousand kilowatt discrete wind power. The cold, heat and electricity loads of the region are shown in figure 2, and the given natural gas price is 2.6 yuan/m in spring and autumn 3And 2.7 yuan/m in summer 32.8 yuan/m in winter 3。
The time-of-use electricity price is shown in fig. 3, the peak value of the electricity purchasing price is 0.96 yuan/kWh, the average value of the electricity purchasing price is 0.66 yuan/kWh, and the valley value of the electricity purchasing price is 0.36 yuan/kWh; the peak value of the electricity selling price is 0.585 yuan/kWh, the average price is 0.39 yuan/kWh, and the valley price is 0.195 yuan/kWh. In this example, the capacity configuration is shown in graph 1 in kW:
Figure BDA00022605083500000711
TABLE 1
The thermoelectric power balance situation of a typical day in spring and autumn is shown in fig. 4. In the period 23-7, the electricity price is low, the gas turbine does not work, the heat load is provided by the heat pump, and the electricity is purchased from the power grid to meet the electricity consumption power of the heat pump and the electricity load; in the period 7-23, the electricity price is higher, the gas turbine works, the heat load is provided by triple supply, and the electricity load is supplied by the gas turbine and the power grid. Through capacity optimization configuration, the heat pump and the triple co-generation output heat power can better meet the heat load requirement, and almost no heat energy storage equipment is needed.
The energy hub purchases electricity from the grid during off-peak electricity prices without using more gas turbines because the heat load is satisfied at this time, using more gas turbines to satisfy the electricity load will result in excess heat production, requiring more thermal energy storage devices, and it is more economical to purchase electricity from the grid when the electricity shortage is small.
The thermoelectric power balance situation in the summer on a typical day is shown in fig. 5. In the period 23-7, the electricity price is low, the gas turbine does not work, the heat load is provided by the heat pump, and the electricity is purchased from the power grid to meet the electricity consumption power of the heat pump and the electricity load; in time period 7-23, the electricity price is higher, the gas turbine works, the heat load is provided by the triple co-generation and heat pump, and the electricity load is supplied by the gas turbine and the power grid. Through capacity optimization configuration, the heat pump and the triple co-generation output heat power can better meet the heat load requirement, and almost no heat energy storage equipment is needed.
The energy hub increases cold load in typical summer days compared with typical spring and autumn days, and the cold load can not be met even when the energy hub is in full-load operation in a triple-generation mode during off-peak electricity price. At the critical point, compared with the expansion of triple supply capacity, even if the electricity price is higher at the moment, the heat generation by using an idle heat pump is more economical.
The thermoelectric power balance situation of a typical day in winter is shown in fig. 6. In the period 23-7, the electricity price is low, the gas turbine does not work, the heat load is provided by the heat pump, and the electricity is purchased from the power grid to meet the electricity consumption power of the heat pump and the electricity load; in periods 7-11 and 19-23, the electricity prices are higher, the gas turbine is working, the heat load is provided by the triple feed and the heat pump, and the electricity load is mainly supplied by the gas turbine. In the time interval 11-19, the electricity price is the flat value electricity price, the gas turbine does not work, the heat load is provided by the heat pump, and the electricity purchasing from the power grid meets the electricity load and the power consumption power of the heat pump. Through capacity optimization configuration, the heat pump and the triple co-generation output heat power can better meet the heat load requirement, and almost no heat energy storage equipment is needed.
The energy hub does not use a gas turbine to supply the thermoelectric load at the average electricity price on a typical day in winter, because the gas price is expensive on a typical day in winter, and the purchase of electricity from the power grid to supply the thermoelectric load is more economical than the use of triple co-generation.
In the above example, the capacity configuration after the wind power and the photovoltaic new energy with different proportions are added for power generation is shown in table 2, the unit KW:
Figure BDA0002260508350000081
TABLE 2
The larger the installed capacity of the new energy is, the less the capacity configuration of the gas turbine and the waste heat boiler is, and the capacity configuration of the heat pump is basically unchanged. When the installed capacity of the new energy exceeds one time, the thermal energy storage equipment is not configured any more.
The thermoelectric ratio is changed by adding new energy, the more new energy is added, the larger the thermoelectric ratio is, and the less triple co-generation is. At the moment, the power generation of the gas turbine only needs to just meet the electric load, and the heat load shortage is provided by the heat pump, so the heat pump is not changed greatly. If the gas turbine is operated to meet the heat load at a gas price of 2.6 to 2.8, the surplus electric power is sold to the grid.
The method includes the steps that electric energy supplied by new energy is subtracted from an electric load to form an equivalent electric load, after the new energy is added, the relation of 4.5 times between output thermal power and input electric power of a heat pump is met, when the electric load is at a non-valley electricity price, the electric load is mainly purchased and supplied from a power grid through a gas turbine and an energy hub, when the new energy is added by 1 time, the equivalent electric load is reduced, the power of the gas turbine is almost unchanged, the electricity purchasing power is greatly reduced, the typical daily gas price is low in spring and autumn, the electricity price is relatively expensive, compared with the reduction of the power of the gas turbine, the reduction of electricity purchasing from the power grid can enable the energy consumption cost to be greatly reduced, and therefore the output power of the gas turbine is not large compared. The heat balance shows that the heat load is not changed, the output heat power of the gas turbine is not changed, and the heat pump power is not changed. The equivalent electric load is further reduced along with the increase of the installed capacity of the new energy, and when the new energy is added by 1 time, the energy hub hardly purchases electricity from the power grid, so that the output power of the gas turbine is reduced, and the output power of the heat pump is increased according to the heat balance.
The charging and discharging power of the thermal energy storage device is negligible compared with other devices; when the electricity price is not valley value (7-23 points), the gas turbine works, the heat load and the equivalent electric load are mainly supplied by the gas turbine at the time, and the heat pump is used for supplying the heat load in an auxiliary way; when the electricity price is at the valley value (23-7 points), the gas turbine does not work, the equivalent electric load is completely supplied by the energy hub from the power grid, and the heat load is completely supplied by the heat pump; the energy hub purchases the most electricity at the valley price.
According to the electric balance equation, after new energy is added, equivalent electric load is correspondingly reduced, and thermal load is unchanged, so that the output electric power of the gas turbine and the purchased electric power of the energy hub are reduced, the upper limit of the output electric power of the gas turbine is reduced, and the capacity configuration is reduced. In this example, the capacity allocation of the gas turbine and the waste heat boiler is 0.4286 times, so that the capacity allocation of the gas turbine is reduced to reduce the capacity allocation of the waste heat boiler.
In this example, the heat generation and power generation of the gas turbine satisfy a relationship of 1.87 times, and a decrease in the output electric power of the gas turbine leads to a decrease in the heat generation power thereof, but the heat load does not change, leading to an increase in the output power of the heat pump during the operation of the gas turbine (at off-peak electricity prices), but still does not exceed the maximum output power at off-peak electricity prices; and when the electricity price is at the valley value, the heat load is completely provided by the heat pump, no matter how the installed capacity of the new energy is changed, the heat load is unchanged, the maximum output power of the heat pump is unchanged when the electricity price is at the valley value, the upper limit of the heat pump power is basically unchanged, and the capacity configuration is basically unchanged.
When the new energy is added by 3 times, at points 13, 14, 16 and 19, the equivalent electric load is less than the rated power of the gas turbine at the moment, so that the energy hub does not need to purchase electricity from the power grid, and the electricity purchasing power is zero.
The winter plant operating conditions are more similar to summer, since there is more cold load in summer and more heat load in winter in heat balance. The output power of the gas turbine is reduced to zero when the electricity price is flat, and the electricity is more economical to purchase from the power grid because the gas price in winter is higher, so the electricity purchasing power is greatly increased when the electricity price is flat compared with the typical day in summer. From the heat balance, it can be known that, when the electricity price is flat, the output power of the gas turbine is greatly reduced, and the output power of the heat pump is greatly increased.
For the analysis of sensitivity: when new energy is added by 1 time, the energy hub is only provided with a gas turbine, a waste heat boiler, a heat pump and heat energy storage equipment. The four devices were therefore analyzed for sensitivity at a cost per unit volume. The unit capacity cost is shown in table 3:
Figure BDA0002260508350000091
the capacity configuration conditions obtained after the unit capacity cost of the four devices fluctuates by 50% up and down are as follows: as the cost per unit capacity of the gas turbine increases, the capacity configuration of the gas turbine decreases, and the capacity configuration of other equipment is basically unchanged. The energy hub capacity configuration is hardly affected by the cost change of the unit capacity of the waste heat boiler and the heat pump. The capacity configuration of the thermal energy storage equipment is in a trend of descending in steps along with the increase of the unit capacity cost, and when the unit capacity cost of the thermal energy storage equipment is 280 yuan/kW.h, the thermal energy storage equipment is not configured in the energy hub. The change in the cost per unit capacity of the thermal energy storage device does not substantially affect the configuration of the capacity of the device other than the thermal energy storage device.
The capacity allocation obtained after the simultaneous 50% fluctuation of the typical daily electricity and gas prices is:
when the electricity price is lower than 0.8 time of the original price, the energy hub is not provided with triple co-generation, and the electricity price is low, so that electricity is more economical to purchase directly from a power grid than to generate electricity by using a gas turbine; and when the price is lower than 0.9 times of the original price, the energy hub is not provided with a thermal energy storage device. Along with the increase of the electricity price, the capacity configuration of a gas turbine, a waste heat boiler and heat energy storage equipment is increased, the configuration of an absorption refrigerator is unchanged, the capacity configuration of a heat pump is slightly reduced, and the electricity price is expensive, so that the heat pump is not more economical for converting electric energy into heat energy than using triple heat supply.
When the gas price is 1.3 times higher than the original price, the energy hub is not provided with triple co-generation, because the gas price is expensive, the electricity purchasing from the power grid is more economical than the electricity generation of the gas turbine; when the price is 1.1 times higher than the original price, the energy hub is not provided with a thermal energy storage device, because the gas price is expensive, and the conversion of natural gas into heat energy for storage is not as economical as the conversion of electric energy into heat energy by a heat pump. Along with the increase of gas price, the capacity configuration of a gas turbine, a waste heat boiler and heat energy storage equipment is reduced, the capacity configuration of a heat pump is slightly increased, and the configuration of an absorption refrigerator is unchanged.
The influence of the rising of the electricity price on the capacity allocation of each device of the energy hub is the same as the influence of the same proportional falling of the gas price.
Since the model is a linear programming, if the thermoelectric load increases in the same proportion, the capacity configuration of each device also increases in the same proportion, so that the influence of different thermoelectric ratio loads on the capacity configuration of the device is researched.
The capacity configuration obtained after the electric load is unchanged and the thermoelectric ratio of each typical day is floated by 50% up and down simultaneously is as follows: as the thermoelectric ratio increases, the triple co-generation and heat pump capacity configurations increase and the thermal energy storage devices decrease.
According to the method, the configuration result can be accurately predicted and analyzed by the cost optimal model based on different season scenes in the energy hub, and the analysis result of the example shows that the capacity configuration of the gas turbine and the waste heat boiler is reduced and the capacity configuration of the heat pump is basically unchanged due to the increase of the installed capacity of the new energy. When the electricity price is off-valley in spring and autumn typical days, the power of the gas turbine is reduced and the power of the heat pump is increased due to the addition of new energy; and when the electricity price is at the valley value, the addition of the new energy reduces the electricity purchasing power. When the electricity price is off-valley in typical days in summer, the addition of new energy reduces the power of the gas turbine and the power of electricity purchase, and the power of the heat pump is increased; and when the electricity price is at the valley value, the addition of the new energy reduces the electricity purchasing power. The influence of the addition of new energy on the running state of the equipment in the typical winter day is similar to that in the typical summer day; the energy hub can continuously and stably provide required energy for the load, the running cost is low, and on the basis of the invention, the sensitivity of the energy hub model can be analyzed, so that the running stability and the running cost of the energy hub are further ensured.
In addition to the above embodiments, the present invention may have other embodiments, and any technical solutions formed by equivalent substitutions or equivalent transformations fall within the scope of the claims of the present invention.

Claims (8)

1. A configuration method of a multi-energy hub containing new energy consumption is characterized by comprising the following steps:
s1, collecting parameters for establishing an energy hub, wherein the parameters comprise unit capacity cost, fuel price cost and operation and maintenance cost in the service life cycle of various devices;
s2, establishing an optimization objective function based on the acquired parameters;
minC ATC＝C IN+C OM+C ES(ii) a Wherein, C INFor initial installation costs of equipment in an energy hub, C OMFor operating and maintenance costs of the energy hub, C ESCost of energy consumption for energy hub, C ATCIs the total cost of the energy hub;
and S3, adjusting parameters of the energy hub to enable the optimization objective function to obtain an optimal solution, and configuring the capacity parameters of each device of the energy hub under the current optimal solution of the objective function.
2. The method of deploying a multi-energy hub with new energy consumption of claim 1, wherein in step S2, the initial installation cost C of the devices in the energy hub INIs determined by the following method:
Figure FDA0002260508340000011
wherein, C SIs the installation capacity of the device S,
Figure FDA0002260508340000012
the installation cost per unit volume of the equipment S, r is the reference discount rate of the equipment S, l sIs the average life of the device S.
3. The method of claim 2, wherein the step S2 is performed according to the operation and maintenance cost C of the energy hub OMIs determined by the following method:
C OM＝C INand x a, a is the operation and maintenance cost coefficient of the equipment and is the ratio of the annual maintenance cost of the equipment to the initial installation cost.
4. The method of deploying a multi-energy hub with new energy consumption according to claim 1, wherein in step S1, the energy consumption cost C of the energy hub ESIs determined by the following method:
Figure FDA0002260508340000014
and
Figure FDA0002260508340000015
respectively the gas purchase price, the electricity purchase price and the electricity sale price at the moment t;
Figure FDA0002260508340000016
and the electricity purchasing power and the electricity selling power at the moment t are respectively; f. of s.tIs the gas consumption rate of the equipment s at the moment t, n is the number of scenes of the energy hub operation, d nThe number of days the energy hub lasts in different scenes.
5. The method of claim 4, wherein the energy cost C of the energy hub is ESWith the following constraints:
Figure FDA0002260508340000021
Figure FDA0002260508340000022
Figure FDA0002260508340000023
Figure FDA0002260508340000024
respectively, the electricity of the system at time tLoad, thermal load, cold load;
Figure FDA0002260508340000025
and
Figure FDA0002260508340000026
electric power consumed and electric power output by the device s at the time t, respectively;
Figure FDA0002260508340000027
and
Figure FDA0002260508340000028
respectively representing the thermal power consumed and the thermal power output by the device s at the moment t;
Figure FDA0002260508340000029
representing the cold power output by the device s at time t.
6. The method of deploying a multi-energy hub with new energy consumption of claim 5, further comprising the tie-line power constraint and the power purchase state constraint:
Figure FDA00022605083400000211
Figure FDA00022605083400000212
p buy.maxpurchasing electric power upper limit, p, from the distribution system for the energy hub sell.maxAn upper limit of power sold to the distribution system;
Figure FDA00022605083400000213
Figure FDA00022605083400000214
respectively 0-1 state variables of the energy hub at the time t for purchasing and selling electricity,
Figure FDA00022605083400000215
it is indicated that the electricity is purchased,
Figure FDA00022605083400000216
indicating the sale of electricity.
7. The method of deployment of a multi-energy hub with new energy consumption of claim 5, further comprising installing capacity constraints:
Figure FDA00022605083400000217
γ sis a 0-1 state variable, gamma s0 and γ s1 denotes no installation and installation equipment, respectively;
Figure FDA00022605083400000218
and
Figure FDA00022605083400000219
respectively, a lower limit and an upper limit of the installation capacity of the device s.
8. The method of deployment of a multi-energy hub with new energy consumption of claim 5, further comprising the following constraints:
Figure FDA0002260508340000031
Figure FDA0002260508340000033
Figure FDA0002260508340000034
wherein the content of the first and second substances,
Figure FDA0002260508340000035
and respectively, the minimum load rate and the maximum load rate of the energy hub unit s, and the subscript s represents the s-th energy hub unit; psi s.tIs a 0-1 state variable, # s.t0 and psi s.t1 denotes that the energy terminal unit is not switched on and is switched on at time t, respectively, and for the energy conversion unit, w s.tRepresenting the output power of the device s at the instant t,
Figure FDA0002260508340000037
and
Figure FDA0002260508340000038
respectively, a minimum stored energy requirement and a maximum stored energy requirement, W, of the energy storage unit s.tThe stored energy that the energy storage unit has at time t;
Figure FDA0002260508340000039
and
Figure FDA00022605083400000310
respectively charging energy power and discharging energy power for the energy storage unit at the moment t; and
Figure FDA00022605083400000312
the charging and discharging multiplying power of the energy storage unit is respectively set;
Figure FDA00022605083400000313
and
Figure FDA00022605083400000314
representing the energy storage unit in a 0-1 state variable charged and discharged respectively at time t,
Figure FDA00022605083400000315
the indication is that the energy is being charged,
Figure FDA00022605083400000316
indicating the discharge energy.
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