CN110783917A - Configuration method of multi-energy hub containing new energy consumption - Google Patents
Configuration method of multi-energy hub containing new energy consumption Download PDFInfo
- 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
- Authority
- CN
- China
- Prior art keywords
- energy
- hub
- power
- electricity
- energy hub
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 40
- 238000005265 energy consumption Methods 0.000 title claims abstract description 22
- 238000009434 installation Methods 0.000 claims abstract description 25
- 238000012423 maintenance Methods 0.000 claims abstract description 14
- 238000005457 optimization Methods 0.000 claims abstract description 11
- 230000005611 electricity Effects 0.000 claims description 104
- 238000004146 energy storage Methods 0.000 claims description 35
- 238000006243 chemical reaction Methods 0.000 claims description 12
- 238000007599 discharging Methods 0.000 claims description 7
- 238000009826 distribution Methods 0.000 claims description 6
- 238000002330 electrospray ionisation mass spectrometry Methods 0.000 claims description 3
- 239000000446 fuel Substances 0.000 claims description 3
- 101150067055 minC gene Proteins 0.000 claims 1
- 238000004458 analytical method Methods 0.000 abstract description 11
- 230000008569 process Effects 0.000 abstract description 6
- 239000007789 gas Substances 0.000 description 69
- 239000002918 waste heat Substances 0.000 description 10
- 238000003860 storage Methods 0.000 description 8
- 230000007423 decrease Effects 0.000 description 4
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 description 4
- 230000035945 sensitivity Effects 0.000 description 4
- 238000010521 absorption reaction Methods 0.000 description 3
- 230000008859 change Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000020169 heat generation Effects 0.000 description 3
- 238000010248 power generation Methods 0.000 description 3
- 238000001816 cooling Methods 0.000 description 2
- 230000008878 coupling Effects 0.000 description 2
- 238000010168 coupling process Methods 0.000 description 2
- 238000005859 coupling reaction Methods 0.000 description 2
- 238000010438 heat treatment Methods 0.000 description 2
- 239000003345 natural gas Substances 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 229910000831 Steel Inorganic materials 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000005229 chemical vapour deposition Methods 0.000 description 1
- 238000002485 combustion reaction Methods 0.000 description 1
- 230000009365 direct transmission Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000000630 rising effect Effects 0.000 description 1
- 230000001932 seasonal effect Effects 0.000 description 1
- 239000010959 steel Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 238000000844 transformation Methods 0.000 description 1
Images
Classifications
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
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
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:
wherein, C
SIs the installation capacity of the device S,
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:
and
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:
respectively the electric load, the heat load and the cold load of the system at the moment t;
and
electric power consumed and electric power output by the device s at the time t, respectively;
and
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:
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;
respectively 0-1 state variables of the energy hub at the time t for purchasing and selling electricity,
it is indicated that the electricity is purchased,
indicating the sale of electricity.
Preferably, the method further comprises the following installation capacity constraint conditions:
γ
sis a 0-1 state variable, gamma
s0 and γ
s1 denotes no installation and installation equipment, respectively;
and
respectively, a lower limit and an upper limit of the installation capacity of the device s.
Preferably, the following constraints are also included:
wherein,
and
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,
and
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
respectively charging energy power and discharging energy power for the energy storage unit at the moment t;
and
the charging and discharging multiplying power of the energy storage unit is respectively set;
and
representing the energy storage unit in a 0-1 state variable charged and discharged respectively at time t,
the indication is that the energy is being charged,
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:
wherein, C
SIs the installation capacity of the device S,
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:
and
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 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:
respectively the electric, heat and cold loads of the system at the moment t;
and
electric power consumed and electric power output by the device s at the time t, respectively;
and
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:
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,
it is indicated that the electricity is purchased,
indicating the sale of electricity.
The configuration method further comprises installing capacity constraints:
γ
sis a 0-1 state variable, gamma
s0 and γ
s1 denotes no installation and installation equipment, respectively;
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:
wherein,
and
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,
and
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
respectively charging energy power and discharging energy power for the energy storage unit at the moment t;
and
the charging and discharging multiplying power of the energy storage unit is respectively set;
and
representing the energy storage unit in a 0-1 state variable charged and discharged respectively at time t,
the indication is that the energy is being charged,
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:
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:
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:
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:
wherein, C
SIs the installation capacity of the device S,
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:
and
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.
5. The method of claim 4, wherein the energy cost C of the energy hub is
ESWith the following constraints:
respectively, the electricity of the system at time tLoad, thermal load, cold load;
and
electric power consumed and electric power output by the device s at the time t, respectively;
and
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.
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:
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;
respectively 0-1 state variables of the energy hub at the time t for purchasing and selling electricity,
it is indicated that the electricity is purchased,
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:
8. The method of deployment of a multi-energy hub with new energy consumption of claim 5, further comprising the following constraints:
wherein,
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,
and
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
respectively charging energy power and discharging energy power for the energy storage unit at the moment t;
and
the charging and discharging multiplying power of the energy storage unit is respectively set;
and
representing the energy storage unit in a 0-1 state variable charged and discharged respectively at time t,
the indication is that the energy is being charged,
indicating the discharge energy.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201911069527.9A CN110783917A (en) | 2019-11-05 | 2019-11-05 | Configuration method of multi-energy hub containing new energy consumption |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201911069527.9A CN110783917A (en) | 2019-11-05 | 2019-11-05 | Configuration method of multi-energy hub containing new energy consumption |
Publications (1)
Publication Number | Publication Date |
---|---|
CN110783917A true CN110783917A (en) | 2020-02-11 |
Family
ID=69388964
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201911069527.9A Pending CN110783917A (en) | 2019-11-05 | 2019-11-05 | Configuration method of multi-energy hub containing new energy consumption |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN110783917A (en) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111369064A (en) * | 2020-03-09 | 2020-07-03 | 华北电力大学 | Method for relieving power distribution network blockage based on energy hub optimal operation |
CN113327044A (en) * | 2021-06-10 | 2021-08-31 | 国家电网有限公司 | Collaborative operation quality analysis system of energy hub |
Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2002252926A (en) * | 2001-02-26 | 2002-09-06 | Toshiba Corp | Cogeneration apparatus operating system and energy supply method for the same |
US7130832B2 (en) * | 2000-07-14 | 2006-10-31 | Hitachi, Ltd. | Energy service business method and system |
CN104778635A (en) * | 2015-04-24 | 2015-07-15 | 西安交通大学 | Replacing method for distribution transformer under whole life cycle frame |
CN107565605A (en) * | 2017-08-24 | 2018-01-09 | 浙江万克新能源科技有限公司 | A kind of shop equipment based on micro-capacitance sensor tends to the method for optimization automatically |
CN107767074A (en) * | 2017-11-09 | 2018-03-06 | 东南大学 | A kind of energy projects collocated method of meter and integration requirement resource response |
CN107832979A (en) * | 2017-12-06 | 2018-03-23 | 浙江大学 | A kind of factory integration energy resource system economic optimization dispatching method for considering cascaded utilization of energy |
CN110210992A (en) * | 2019-04-25 | 2019-09-06 | 国网天津市电力公司电力科学研究院 | Cooling heating and power generation system and optimized operation containing sea water desalination and clean energy resource |
CN110322051A (en) * | 2019-06-06 | 2019-10-11 | 国网浙江省电力有限公司经济技术研究院 | Consider the integrated energy system Optimal Configuration Method of N-1 security constraint |
-
2019
- 2019-11-05 CN CN201911069527.9A patent/CN110783917A/en active Pending
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7130832B2 (en) * | 2000-07-14 | 2006-10-31 | Hitachi, Ltd. | Energy service business method and system |
JP2002252926A (en) * | 2001-02-26 | 2002-09-06 | Toshiba Corp | Cogeneration apparatus operating system and energy supply method for the same |
CN104778635A (en) * | 2015-04-24 | 2015-07-15 | 西安交通大学 | Replacing method for distribution transformer under whole life cycle frame |
CN107565605A (en) * | 2017-08-24 | 2018-01-09 | 浙江万克新能源科技有限公司 | A kind of shop equipment based on micro-capacitance sensor tends to the method for optimization automatically |
CN107767074A (en) * | 2017-11-09 | 2018-03-06 | 东南大学 | A kind of energy projects collocated method of meter and integration requirement resource response |
CN107832979A (en) * | 2017-12-06 | 2018-03-23 | 浙江大学 | A kind of factory integration energy resource system economic optimization dispatching method for considering cascaded utilization of energy |
CN110210992A (en) * | 2019-04-25 | 2019-09-06 | 国网天津市电力公司电力科学研究院 | Cooling heating and power generation system and optimized operation containing sea water desalination and clean energy resource |
CN110322051A (en) * | 2019-06-06 | 2019-10-11 | 国网浙江省电力有限公司经济技术研究院 | Consider the integrated energy system Optimal Configuration Method of N-1 security constraint |
Non-Patent Citations (2)
Title |
---|
崔鹏程: ""计及综合需求侧响应的能量枢纽优化配置"", 《电力自动化设备》 * |
李国军: ""风电-氢储能与煤化工多能耦合***全寿命周期经济性评估"", 《电工技术学报》 * |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111369064A (en) * | 2020-03-09 | 2020-07-03 | 华北电力大学 | Method for relieving power distribution network blockage based on energy hub optimal operation |
CN111369064B (en) * | 2020-03-09 | 2023-10-27 | 华北电力大学 | Method for relieving power distribution network blocking based on optimal operation of energy hub |
CN113327044A (en) * | 2021-06-10 | 2021-08-31 | 国家电网有限公司 | Collaborative operation quality analysis system of energy hub |
CN113327044B (en) * | 2021-06-10 | 2023-11-21 | 国家电网有限公司 | Collaborative operation quality analysis system of energy hub |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN108717594B (en) | Economic optimization scheduling method for combined cooling heating and power type multi-microgrid system | |
CN109523052B (en) | Virtual power plant optimal scheduling method considering demand response and carbon transaction | |
CN109193626B (en) | Unified solving method for model selection and constant volume optimization planning of distributed energy station | |
CN110826815B (en) | Regional comprehensive energy system operation optimization method considering comprehensive demand response | |
CN108154309B (en) | Energy internet economic dispatching method considering multi-load dynamic response of cold, heat and electricity | |
CN112464477A (en) | Multi-energy coupling comprehensive energy operation simulation method considering demand response | |
CN110807588B (en) | Optimized scheduling method of multi-energy coupling comprehensive energy system | |
CN110138004A (en) | One kind is provided multiple forms of energy to complement each other system optimized operation method | |
Liu et al. | Impacts of distributed renewable energy generations on smart grid operation and dispatch | |
Tasdighi et al. | Energy management in a smart residential building | |
CN109919399A (en) | A kind of integrated energy system economic load dispatching method and system a few days ago | |
CN109543889A (en) | A kind of regional complex energy resource system cooperates with optimizing operation method a few days ago | |
CN107276080A (en) | A kind of computational methods of energy-saving and emission-reduction developing goal contribution rate | |
CN114844124B (en) | Operation control method of comprehensive energy system based on target optimization | |
CN113627011A (en) | Comprehensive energy operation simulation method based on multi-objective optimization | |
CN114065530A (en) | Energy station operation optimization and comprehensive evaluation method | |
CN110783917A (en) | Configuration method of multi-energy hub containing new energy consumption | |
Zhang et al. | Economic and Optimal Dispatch Model of Electricity, Heat and Gas for Virtual Power Plants in Parks Considering Low Carbon Targets. | |
CN113240205A (en) | Regional energy utilization system substitution optimization method based on multi-energy comprehensive utilization | |
CN110571868B (en) | Optimal configuration method of micro-grid | |
CN113313329B (en) | Optimal scheduling method for power distribution network containing comprehensive energy system | |
CN112446616B (en) | Modeling method for optimal operation strategy and load characteristic of park type comprehensive energy system | |
CN114757469A (en) | Regional comprehensive energy system day-ahead optimization scheduling method considering multi-energy flow equipment | |
Ma et al. | Optimization of Integrated Energy System Scheduling Considering Stepped Carbon Emission Trading Mechanism and Electricity Heat Demand Response | |
CN115378002A (en) | Optimal scheduling model of regional comprehensive energy system based on hybrid energy storage |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
RJ01 | Rejection of invention patent application after publication | ||
RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200211 |