CN116029518A - Carbon emission planning method for park comprehensive energy system considering generalized energy storage - Google Patents
Carbon emission planning method for park comprehensive energy system considering generalized energy storage Download PDFInfo
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Abstract
The invention discloses a carbon emission planning method of a park comprehensive energy system considering generalized energy storage, which comprises the following steps: collecting historical photovoltaic output data of a park comprehensive energy system and unit investment cost mainly comprising photovoltaic and storage battery equipment; constructing a multi-energy load increase long-term uncertainty and a photovoltaic output short-term uncertainty scene; establishing an energy hub model taking park hub as a core and park generalized energy storage resource equipment as a main body; establishing a generalized energy storage model; and calculating the operational cost and the extension cost of 365 days of planning years of the park, and outputting the optimal planning and operational strategy. According to the invention, the long-term uncertainty of load increase and the short-term uncertainty of photovoltaic output are fully considered, the time transfer characteristic is utilized to realize the multi-energy cross-period high-efficiency utilization, the generalized energy storage resources taking the data center and the building as main bodies in the park are excavated, the new energy consumption is effectively promoted, and the economical efficiency and the environmental protection performance of the comprehensive energy system planning and scheduling scheme are ensured.
Description
Technical Field
The invention relates to a carbon emission planning method of a park comprehensive energy system considering generalized energy storage, and belongs to the field of comprehensive energy system planning and extension.
Background
The comprehensive energy system of the park is reasonably planned, and the comprehensive energy system has an important supporting effect on improving the energy utilization structure of the park and promoting the low-carbonization transformation of industry. The comprehensive energy system planning around the park has a plurality of defects, such as the research on the planning level focuses on the energy balance for medium and long periods, ignores the problem of the flexibility balance of short-term operation, and does not fully excavate the flexible scheduling potential of various energy resources of the park. The generalized energy storage resource can fully utilize the time transfer characteristic of energy of each energy utilization main body in the park, can store heat in the valley period, release energy in the peak period, and realize the cross period and high value utilization of various energies.
Disclosure of Invention
The invention provides a park comprehensive energy system planning method utilizing a generalized energy storage effect.
The invention adopts the following technical scheme:
a carbon emission planning method of a park comprehensive energy system considering generalized energy storage comprises the following steps:
step 1: collecting historical photovoltaic output data of a park comprehensive energy system and unit investment cost mainly comprising photovoltaic and storage battery equipment;
step 2: according to known park parameters, constructing a scene of long-term uncertainty of multi-energy load growth and short-term uncertainty of photovoltaic output by taking the sum of extension cost and operation cost of a park comprehensive energy system as an objective function; the known park parameters refer to the operating parameters of each plant of the park, such as the efficiency of the units of CCHP, CHP, etc.
Step 3: establishing an energy hub model taking park hub as a core and park generalized energy storage resource equipment as a main body;
step 4: establishing a generalized energy storage model according to the energy storage of the storage battery, the thermal characteristics of the data center and the thermal characteristics of the building;
step 5: and calculating the operational cost and the extension cost of 365 days of planning years of the park, and outputting the optimal planning and operational strategy.
Specifically, the scenario of the long-term uncertainty of the multi-energy load increase in step 2 specifically includes: generating three kinds of upper layer multipotency load long-term uncertainty scenes according to seasonal differences, namely transitional seasons, summer and winter respectively;
the short-term uncertainty scene of the photovoltaic output specifically comprises: based on the photovoltaic historical output data, a k-means clustering method is utilized to generate four types of short-term uncertainty scenes of the lower photovoltaic output.
Specifically, the objective function in step 2 is:
in the formula (A-1), a subscript t represents a scheduling time;
capacity expansion for photovoltaic units, +.>
Capacity expansion for a battery pack>
Capacity expansion for ground source heat pump unit +.>
The expansion capacity of the combined cooling heating power unit is provided; />
Cost for unit expansion of photovoltaic unit, +.>
Cost for unit expansion of storage battery unit, < >>
The unit expansion cost of the ground source heat pump unit is +.>
The unit extension cost of the combined cooling heating power unit is set; omega shape g Omega as a typical day collection g Weighting for each typical day; omega shape PV Omega for the photovoltaic output scene set PV The method comprises the steps of weighing a photovoltaic output scene; p (P) t E For the upper power grid electricity purchasing quantity of t time period, < >>
The upper-level gas online shopping amount is t time period; />
For the electricity price of the t period, < > for>
Gas price for period t; i E Carbon emission cost per unit electricity purchase amount, I G Carbon emission costs per unit amount of purchased gas;
in the formula (A-1), the first four items are annual extension costs of each extension unit, namely a photovoltaic unit, a storage battery unit, a ground source heat pump unit and a combined cooling, heating and power unit, and the fifth item is annual operation costs, wherein carbon emission costs of electricity purchase and gas purchase are taken into account;
each planning variable constraint is:
in the formula (A-2),
extend the upper capacity limit for the photovoltaic unit, < >>
Extend the upper limit of capacity for the battery unit, +.>
Expansion capacity upper limit for ground source heat pump unit, < ->
The expansion capacity upper limit of the combined cooling heating and power unit is +.>
For the original photovoltaic installation capacity, < > a->
For the original battery capacity>
The capacity of the original cold-heat-electricity triple supply unit is +.>
The capacity of the original ground source heat pump unit; the first four items are investment upper limit constraints of the extension unit, and the last four items are operation upper limit constraints of the extension unit.
Specifically, the energy hub model in step 3 is specifically:
the energy level constraint of the park is as follows:
wherein P is t LC For the period t of the cold load demand,
industrial cooling capacity of GSHP unit in t period>
The cooling capacity of the CCHP unit is supplied for the period t; p (P) t LH For t-period heat load demand, < > and->
Heat is supplied to the t-period CCHP unit; />
Heat is supplied to the GSHP unit in the t period; />
Heat supply of the air boiler in the t period of time, +.>
Heat is supplied to the electric boiler in the period t; p (P) t PV For the t period of photovoltaic output, P t dis For t period of battery charge, P t LE For t-period electrical load demand, P t GSHP For t-period industrial GSHP unit power consumption, P t EB For t-period electric boiler power consumption, P t ch For the discharge quantity of the storage battery set in the t period, P t BD For the power consumption of the GSHP unit of the building at the period of t, P t DC Power consumption of the data center is t time periods; />
The electric quantity provided for the t-period CCHP unit; p (P) t CCHP For the consumption of the CCHP unit in t period, P t GB And the air consumption of the air boiler is t time periods. Constraint (A-2) is a cold bus, a hot bus, an electric bus and an air bus balance equation from top to bottom in sequence;
the operational constraints of conventional multi-energy conversion equipment in a park are as follows:
in the method, in the process of the invention,
for CCHP unit cold conversion efficiency, P t CCHP，C Natural gas quantity for cold transfer is input into the CCHP unit;
for the thermal conversion efficiency of the CCHP unit, P t CCHP，H Natural gas quantity for transferring heat is input into the CCHP unit; />
For the electric conversion efficiency of the CCHP unit, P t CCHP,E Natural gas quantity for inputting CCHP units for power conversion; p (P) t TF To input the electric quantity of the transformer, eta TF The electric conversion efficiency of the transformer; η (eta) EB For the heat conversion efficiency of the electric boiler, eta GB The heat conversion efficiency of the gas boiler is; the first three terms are CCHP unit operation equations, and the last three terms are respectively transformer, electric boiler and gas boiler operation equations;
equipment operating constraints related to campus generalized energy storage resources include storage batteries, ground source heat pumps, and data centers, where:
the operation constraint of the storage battery unit is as follows:
wherein P is t ch For t period of energy storage charging power, P t dis Energy storage and discharge power is t time period;
for the t period of the energy-storing charge state variable, +.>
The energy storage and discharge state variable is t time period; e (E) t Energy storage electric quantity is carried out for a period t; lambda (lambda) E For t period of energy storage self-discharge coefficient, eta ch For the energy storage and charging efficiency of t period, eta dis Energy storage and discharge efficiency is t time period; e (E) min For storing energy, E is the lower limit of the electric quantity max Is the upper limit of the energy storage electric quantity;
the operation constraint of the ground source heat pump unit is as follows:
wherein P is t BD，C Electric energy for converting heat for t-period building GSHP unit, P t BD，H The GSHP unit is used for converting cold electric energy for the building at the time of t;
and->
The heat energy and the cold energy which are respectively transmitted to the building by GSHP in t time period; />
And->
Heating and cooling operation state variables are respectively;
the operation constraint of the data center is as follows;
wherein P is t IT For a period t data center IT device power consumption,
for each k-shaped suit in t time periodServer power; />
For a fixed power consumption of a t-period k-class server, < >>
CPU power consumption is t time period; c (C) 1 D 'is the power consumption coefficient of the server' k，t The data load quantity required to be processed for the k-type server of the data center in the t period; a, a k，s，t The working frequency zone bit is s-gear of a k-type server CPU of the data center in the t period; f (f) k,s And the working frequency is s-gear for the CPU of the k-type server of the data center.
According to the storage battery energy storage, the thermal characteristics of a data center and the thermal characteristics of a building, a generalized energy storage model is established, and the method comprises the following steps:
generalized energy storage capacity of storage battery in t period is E t ；
The thermal characteristics and generalized energy storage constraints of the data center are:
in the method, in the process of the invention,
generalized energy storage for data center t period, H DC Specific heat capacity of data center, T t dc，in Temperature in data center T time period room, T t dc,in,max An upper limit of the indoor temperature in the t period; η (eta) c Data center refrigeration unit efficiency, Q t Refrigeration T produced by refrigeration equipment of data center T-section t dc,out For t period of external environment temperature, U C The heat transfer coefficient of the data center to the outside;
lower limit of temperature change rate of data center, +.>
An upper limit for the temperature change rate of the data center; />
Is the indoor temperature lower limit of the data center, +.>
An upper temperature limit in the data center room;
the thermal characteristics and generalized energy storage constraints of the park building are as follows:
in the method, in the process of the invention,
generalized energy storage for data center t period, H BD Specific heat capacity of data center, T t BD Indoor temperature in t time period of data center,/o>
For the upper limit of the indoor temperature in the t period, < >>
The lower limit of the indoor temperature is t time period; />
Phi for the solar radiation quantity passing through the glazing of a building t The solar radiation heat is in a t period, and sigma is the solar radiation loss rate; />
For building to radiate heat outwards, T t E Building wall temperature for the park at time t; t (T) t The indoor temperature of the park at the period t; u (U) A The heat transfer coefficient is the direct heat transfer coefficient of the outer vertical surface of the building; u (U) E Heat transfer coefficients for indoor to wall; t (T) t a Is the external environment temperature in the t period. Wherein T is t E Building for t periodOuter wall temperature->
For the temperature of the building outer wall in t-1 time period, H PE Is the specific heat capacity of the building wall, T t a Is the external environment temperature in the t period.
The generalized energy storage total amount of the park is as follows:
calculating the operational cost and the extension cost of 365 days of the planning year of the park, and outputting the optimal planning and the operational strategy, wherein the method comprises the following steps:
in the actual solving process, the objective function is the sum of annual investment cost and planning annual operation cost, wherein the annual investment cost is the total extension cost divided by the planning age, and when the planning annual operation cost is calculated, all loads and photovoltaic output conditions during the planning period need to be met by each equipment operation constraint.
The invention has the beneficial effects that:
according to the invention, the long-term uncertainty of load increase and the short-term uncertainty of photovoltaic output are fully considered, the time transfer characteristic is utilized to realize the multi-energy cross-period high-efficiency utilization, the generalized energy storage resources taking the data center and the building as main bodies in the park are excavated, the new energy consumption is effectively promoted, and the economical efficiency and the environmental protection performance of the comprehensive energy system planning and scheduling scheme are ensured.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Figure 2 is a block diagram of a campus energy hub.
Figure 3 is a graph of typical daily energy load conditions for each campus.
Fig. 4 is a diagram of a campus planning year summer generalized energy storage situation that accounts for generalized energy storage.
Fig. 5 is a short term uncertainty scenario for photovoltaic output.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention and are not intended to limit the scope of the present invention, and based on the embodiments of the present invention, all other embodiments obtained by a person skilled in the art without making any creative effort belong to the protection scope of the present invention.
As shown in fig. 1, the invention provides a carbon emission planning method of a park comprehensive energy system considering generalized energy storage, and the method for planning the park comprehensive energy system in the embodiment of the invention comprises the following steps:
step 1: and collecting park operation parameters such as historical photovoltaic output data of a park comprehensive energy system and unit investment cost mainly comprising photovoltaic equipment, storage batteries and the like.
Step 2: generating a scene of long-term uncertainty of multi-energy load growth and short-term uncertainty of photovoltaic output, and taking the sum of annual extension cost and operation cost of system planning as an objective function.
Generating a multi-energy load increase long-term uncertainty and a photovoltaic output short-term uncertainty scene:
generating three kinds of upper layer multipotency load long-term uncertainty scenes according to seasonal differences, namely transitional seasons, summer and winter respectively, as shown in figure 3; based on the photovoltaic historical output data, a k-means clustering method is utilized to generate four types of short-term uncertainty scenes of the lower photovoltaic output, as shown in figure 5.
Based on the uncertainty scene, constructing an objective function with the sum of the extension cost and the running cost as an objective function, wherein the objective function is as follows:
in the formula, a subscript t represents a scheduling time;
capacity expansion for photovoltaic units, +.>
The capacity of the accumulator unit is extended,
capacity expansion for ground source heat pump unit +.>
The expansion capacity of the combined cooling heating power unit is provided; />
Cost for unit expansion of photovoltaic unit, +.>
Cost for unit expansion of storage battery unit, < >>
The unit expansion cost of the ground source heat pump unit is +.>
The unit extension cost of the combined cooling heating power unit is set; omega shape g Omega as a typical day collection g Weighting for each typical day; omega shape PV Omega for the photovoltaic output scene set PV The method comprises the steps of weighing a photovoltaic output scene; p (P) t E For the upper power grid electricity purchasing quantity of t time period, < >>
The upper-level gas online shopping amount is t time period; />
For the electricity price of the t period, < > for>
Gas price for period t; i E Carbon emission cost per unit electricity purchase amount, I G Carbon emission costs per unit amount of purchased gas.
In the formula (A-1), the first four items are annual extension costs of each extension unit respectively, and the annual extension costs comprise a photovoltaic unit, a storage battery unit, a ground source heat pump unit and a combined cooling, heating and power unit, and the fifth item is annual operation costs, wherein carbon emission costs of electricity purchase and gas purchase are taken into account.
Each planning variable constraint is:
in the formula (A-2),
extend the upper capacity limit for the photovoltaic unit, < >>
Extend the upper limit of capacity for the battery unit, +.>
Extend the upper capacity limit for GSHP units, < > for>
And (5) expanding the upper limit of capacity for the CCHP unit. />
For the original photovoltaic installation capacity, < > a->
For the original battery capacity>
For the original CCHP unit capacity, < > and->
Is the original GSHP unit capacity. The first four items are investment upper limit constraints of the extension unit, and the last four items are operation upper limit constraints of the extension unit.
Step 3: building an energy hub model with a park hub as a core:
the energy level constraint of the park is as follows:
wherein P is t LC For the period t of the cold load demand,
for industrial cold supply of GSHP unit in t period, GSHP unit is ground source heat pump unit, and ∈>
The cooling capacity is supplied to a t-period CCHP unit, namely a cold-heat-power cogeneration unit; p (P) t LH For t-period heat load demand, < > and->
Heat is supplied to the t-period CCHP unit; />
Heat is supplied to the GSHP unit in the t period; />
Heat supply of the air boiler in the t period of time, +.>
Heat is supplied to the electric boiler in the period t; p (P) t PV For the t period of photovoltaic output, P t dis For t period of battery charge, P t LE For t-period electrical load demand, P t GSHP For t-period industrial GSHP unit power consumption, P t EB For t-period electric boiler power consumption, P t ch For the discharge quantity of the storage battery set in the t period, P t BD For the power consumption of the GSHP unit of the building at the period of t, P t DC Power consumption of the data center is t time periods; />
For period tThe electric quantity provided by the CCHP unit; p (P) t CCHP For the consumption of the CCHP unit in t period, P t GB And the air consumption of the air boiler is t time periods. The constraint (A-2) is a cold bus, a hot bus, an electric bus and an air bus balance equation in sequence from top to bottom.
The operational constraints of conventional multi-energy conversion equipment in a park are as follows:
in the method, in the process of the invention,
for CCHP unit cold conversion efficiency, P t CCHP，C Natural gas quantity for cold transfer is input into the CCHP unit;
for the thermal conversion efficiency of the CCHP unit, P t CCHP，H Natural gas quantity for transferring heat is input into the CCHP unit; />
For the electric conversion efficiency of the CCHP unit, P t CCHP，E Natural gas quantity for inputting CCHP units for power conversion; p (P) t TF To input the electric quantity of the transformer, eta TF The electric conversion efficiency of the transformer; η (eta) EB For the heat conversion efficiency of the electric boiler, eta GB The heat conversion efficiency of the gas boiler is achieved. The first three terms are CCHP unit operation equations, and the last three terms are respectively transformer, electric boiler and gas boiler operation equations.
Equipment operating constraints related to campus generalized energy storage resources include storage batteries, ground source heat pumps, and data centers, where:
the operation constraint of the storage battery unit is as follows:
wherein P is t ch For t period of energy storage charging power, P t dis Energy storage and discharge power is t time period;
for the t period of the energy-storing charge state variable, +.>
The energy storage and discharge state variable is t time period; e (E) t Energy storage electric quantity is carried out for a period t; lambda (lambda) E For t period of energy storage self-discharge coefficient, eta ch For the energy storage and charging efficiency of t period, eta dis Energy storage and discharge efficiency is t time period; e (E) min For storing energy, E is the lower limit of the electric quantity max Is the upper limit of the stored energy.
The operation constraint of the ground source heat pump unit is as follows:
wherein P is t BD，C Electric energy for converting heat for t-period building GSHP unit, P t BD，H The GSHP unit is used for converting cold electric energy for the building at the time of t;
and->
The heat energy and the cold energy which are respectively transmitted to the building by GSHP in t time period; />
And->
And the operation state variables are respectively heating and cooling operation state variables. The operating constraints of the industrial GSHP unit are the same as those of the industrial GSHP unit, and therefore the operation constraints are not repeated.
The operation constraint of the data center is as follows;
wherein P is t IT For a period t data center IT device power consumption,
power for each k-type server for a period t; />
For a fixed power consumption of a t-period k-class server, < >>
CPU power consumption is t time period; c (C) 1 D 'is the power consumption coefficient of the server' k，t The data load quantity required to be processed for the k-type server of the data center in the t period; a, a k，s，t The working frequency zone bit is s-gear of a k-type server CPU of the data center in the t period; f (f) k，s And the working frequency is s-gear for the CPU of the k-type server of the data center.
Step 4: and building a generalized energy storage model according to the energy storage of the storage battery, the thermal characteristics of the data center and the thermal characteristics of the buildings in the park.
Generalized energy storage capacity of storage battery in t period is E t 。
The thermal characteristics and generalized energy storage constraints of the data center are:
in the method, in the process of the invention,
generalized energy storage for data center t period, H DC Specific heat capacity of data center, T t dc，in Temperature in data center T time period room, T t dc，in，max An upper limit of the indoor temperature in the t period; η (eta) c Data center refrigeration unit efficiency, Q t Refrigeration T produced by refrigeration equipment of data center T-section t dc,out At tOutside environmental temperature of the section, U C The heat transfer coefficient of the data center to the outside; />
Lower limit of temperature change rate of data center, +.>
An upper limit for the temperature change rate of the data center; />
Is the indoor temperature lower limit of the data center, +.>
An upper temperature limit within the data center room.
The thermal characteristics and generalized energy storage constraints of the park building are as follows:
in the method, in the process of the invention,
generalized energy storage for data center t period, H BD Specific heat capacity of data center, T t BD Indoor temperature in t time period of data center,/o>
For the upper limit of the indoor temperature in the t period, < >>
The lower limit of the indoor temperature is t time period; />
Phi for the solar radiation quantity passing through the glazing of a building t The solar radiation heat is in a t period, and sigma is the solar radiation loss rate; />
For building to radiate heat outwards, T t E Building wall temperature for the park at time t; t (T) t The indoor temperature of the park at the period t; u (U) A The heat transfer coefficient is the direct heat transfer coefficient of the outer vertical surface of the building; u (U) E Heat transfer coefficients for indoor to wall; t (T) t a Is the external environment temperature in the t period. Wherein T is t E For the temperature of the building outer wall in t time period,/for the building outer wall temperature>
For the temperature of the building outer wall in t-1 time period, H PE Is the specific heat capacity of the building wall, T t a Is the external environment temperature in the t period.
The generalized energy storage total amount of the park is as follows:
step 5: and calculating the operational cost and the extension cost of 365 days of planning years of the park, and outputting the optimal planning and operational strategy.
In the actual solving process, the objective function is the sum of annual investment cost and planning annual operation cost, wherein the annual investment cost is the total extension cost divided by the planning age, and when the planning annual operation cost is calculated, all loads and photovoltaic output conditions during the planning period need to be met by each equipment operation constraint.
Example analysis
And selecting each typical daily energy load of an industrial park in Jiangsu province as a test load, wherein the photovoltaic input data is derived from a database of solar forecast and intelligent power grid projects in the Netherlands. Typical daily selection is shown in table 1, and time-sharing energy prices are shown in table 2.
Table 1 typical day selection
TABLE 2 price of time-sharing electricity and gas purchase [ this/kWh ]
In this example we compared the proposed method with respect to investment cost, total cost and carbon emissions with a campus planning method that does not take into account generalized energy storage, where the building and data center temperatures are controlled to a constant value without peak clipping and valley filling capabilities, as shown in table 3. The investment cost of the planning method for the park comprehensive energy system considering the flexible operation mode of the generalized energy storage resources is slightly higher than that of the conventional method, but the total annual planning cost is reduced by 170.7 ten thousand yuan, the annual carbon emission is reduced by 0.15 kiloton, and the temperature of a building and a data center can be changed in a specific comfort zone to realize energy cross-period transfer, so that the planning method considering the flexible operation of the park generalized energy storage main body improves the operation economy and environmental protection of the park comprehensive energy system.
Table 3 investment costs and carbon emissions comparisons with and without park generalized energy storage resources
In this example, a campus planning year summer generalized energy storage scenario that accounts for generalized energy storage is shown in fig. 4. As can be seen from fig. 4, in a typical day in summer, electricity prices are lower in 2-7 and 15-18 periods, the generalized energy storage preferentially stores energy, that is, the energy storage histogram has a "double-peak" characteristic, wherein the storage battery purchases electric energy in the flat valley period and discharges electric energy in 12-14 and 19-22 periods, so as to meet the load demand at peak time. The data center and the building perform thermal energy storage in the peak period and the valley period of new energy output, and release part of energy storage in the 18-23 period. From the above results, the generalized energy storage utilizes the flexible charge/discharge characteristics thereof to realize peak clipping and valley filling of energy loads for park diversification.
Claims (6)
1. A carbon emission planning method of a park comprehensive energy system considering generalized energy storage is characterized by comprising the following steps:
step 1: collecting historical photovoltaic output data of a park comprehensive energy system and unit investment cost mainly comprising photovoltaic and storage battery equipment;
step 2: according to known park parameters, constructing a scene of long-term uncertainty of multi-energy load growth and short-term uncertainty of photovoltaic output by taking the sum of extension cost and operation cost of a park comprehensive energy system as an objective function;
step 3: establishing an energy hub model taking park hub as a core and park generalized energy storage resource equipment as a main body;
step 4: establishing a generalized energy storage model according to the energy storage of the storage battery, the thermal characteristics of the data center and the thermal characteristics of the building;
step 5: and calculating the operational cost and the extension cost of 365 days of planning years of the park, and outputting the optimal planning and operational strategy.
2. The method for planning carbon emissions in a campus integrated energy system involving generalized energy storage according to claim 1, wherein constructing a scenario of long-term uncertainty of multi-energy load increase in step 2 specifically comprises: generating three kinds of upper layer multipotency load long-term uncertainty scenes according to seasonal differences, namely transitional seasons, summer and winter respectively;
the short-term uncertainty scene of the photovoltaic output specifically comprises: based on the photovoltaic historical output data, a k-means clustering method is utilized to generate four types of short-term uncertainty scenes of the lower photovoltaic output.
3. A method for planning carbon emissions in a campus integrated energy system involving generalized energy storage according to claim 2, wherein the objective function in step 2 is:
in the formula (A-1), a subscript t represents a scheduling time;
capacity expansion for photovoltaic units, +.>
The capacity of the accumulator unit is extended,
capacity expansion for ground source heat pump unit +.>
The expansion capacity of the combined cooling heating power unit is provided; />
Cost for unit expansion of photovoltaic unit, +.>
Cost for unit expansion of storage battery unit, < >>
The unit expansion cost of the ground source heat pump unit is +.>
The unit extension cost of the combined cooling heating power unit is set; omega shape g Omega as a typical day collection g Weighting for each typical day; omega shape PV Omega for the photovoltaic output scene set PV The method comprises the steps of weighing a photovoltaic output scene; p (P) t E For the upper power grid electricity purchasing quantity of t time period, < >>
The upper-level gas online shopping amount is t time period; />
For the electricity price of the t period, < > for>
Gas price for period t; i E Carbon emission cost per unit electricity purchase amount, I G Carbon emission costs per unit amount of purchased gas;
in the formula (A-1), the first four items are annual extension costs of each extension unit, namely a photovoltaic unit, a storage battery unit, a ground source heat pump unit and a combined cooling, heating and power unit, and the fifth item is annual operation costs, wherein carbon emission costs of electricity purchase and gas purchase are taken into account;
each planning variable constraint is:
in the formula (A-2),
extend the upper capacity limit for the photovoltaic unit, < >>
Extend the upper limit of capacity for the battery unit, +.>
Expansion capacity upper limit for ground source heat pump unit, < ->
The expansion capacity upper limit of the combined cooling heating and power unit is +.>
For the original photovoltaic installation capacity, < > a->
For the original battery capacity>
The capacity of the original cold-heat-electricity triple supply unit is +.>
The capacity of the original ground source heat pump unit; the first four items are investment upper limit constraints of the extension unit, and the last four items are operation upper limit constraints of the extension unit.
4. The method for planning carbon emissions in a campus integrated energy system involving generalized energy storage according to claim 1, wherein step 3 specifically comprises:
the energy level constraint of the park is as follows:
wherein P is t LC For the period t of the cold load demand,
industrial cooling capacity of GSHP unit in t period>
The cooling capacity of the CCHP unit is supplied for the period t; p (P) t LH For t-period heat load demand, < > and->
Heat is supplied to the t-period CCHP unit; />
Heat is supplied to the GSHP unit in the t period; />
Heat supply of the air boiler in the t period of time, +.>
Heat is supplied to the electric boiler in the period t; p (P) t PV For the t period of photovoltaic output, P t dis For t period of battery charge, P t LE For t-period electrical load demand, P t GSHP For t-period industrial GSHP unit power consumption, P t EB For t-period electric boiler power consumption, P t ch For the discharge quantity of the storage battery set in the t period, P t BD For the power consumption of the GSHP unit of the building at the period of t, P t DC Power consumption of the data center is t time periods; />
The electric quantity provided for the t-period CCHP unit; p (P) t CCHP For the consumption of the CCHP unit in t period, P t GB And the air consumption of the air boiler is t time periods. Constraint (A-2) is a cold bus, a hot bus, an electric bus and an air bus balance equation from top to bottom in sequence;
the operational constraints of conventional multi-energy conversion equipment in a park are as follows:
in the method, in the process of the invention,
for CCHP unit cold conversion efficiency, P t CCHP，C Natural gas quantity for cold transfer is input into the CCHP unit;
for the thermal conversion efficiency of the CCHP unit, P t CCHP，H Natural gas quantity for transferring heat is input into the CCHP unit; />
For the electric conversion efficiency of the CCHP unit, P t CCHP,E Natural gas quantity for inputting CCHP units for power conversion;P t TF to input the electric quantity of the transformer, eta TF The electric conversion efficiency of the transformer; η (eta) EB For the heat conversion efficiency of the electric boiler, eta GB The heat conversion efficiency of the gas boiler is; the first three terms are CCHP unit operation equations, and the last three terms are respectively transformer, electric boiler and gas boiler operation equations;
equipment operating constraints related to campus generalized energy storage resources include storage batteries, ground source heat pumps, and data centers, where:
the operation constraint of the storage battery unit is as follows:
wherein P is t ch For t period of energy storage charging power, P t dis Energy storage and discharge power is t time period;
for the t period of the energy-storing charge state variable, +.>
The energy storage and discharge state variable is t time period; e (E) t Energy storage electric quantity is carried out for a period t; lambda (lambda) E For t period of energy storage self-discharge coefficient, eta ch For the energy storage and charging efficiency of t period, eta dis Energy storage and discharge efficiency is t time period; e (E) min For storing energy, E is the lower limit of the electric quantity max Is the upper limit of the energy storage electric quantity;
the operation constraint of the ground source heat pump unit is as follows:
wherein P is t BD，C Electric energy for converting heat for t-period building GSHP unit, P t BD，H The GSHP unit is used for converting cold electric energy for the building at the time of t;
and->
The heat energy and the cold energy which are respectively transmitted to the building by GSHP in t time period; />
And->
Heating and cooling operation state variables are respectively;
the operation constraint of the data center is as follows;
wherein P is t IT For a period t data center IT device power consumption,
power for each k-type server for a period t; />
For a fixed power consumption of a t-period k-class server, < >>
CPU power consumption is t time period; c (C) 1 D 'is the power consumption coefficient of the server' k，t The data load quantity required to be processed for the k-type server of the data center in the t period; a, a k，s，t The working frequency zone bit is s-gear of a k-type server CPU of the data center in the t period; f (f) k，s And the working frequency is s-gear for the CPU of the k-type server of the data center.
5. The method for planning carbon emissions of a campus integrated energy system with generalized energy storage according to claim 1, wherein the building thermal characteristics and thermal characteristics of the data center are used to build the generalized energy storage model according to the energy storage of the storage battery, comprising:
generalized energy storage capacity of storage battery in t period is E t ；
The thermal characteristics and generalized energy storage constraints of the data center are:
in the method, in the process of the invention,
generalized energy storage for data center t period, H DC Specific heat capacity of data center, T t dc,in Temperature in data center T time period room, T t dc,in,max An upper limit of the indoor temperature in the t period; η (eta) c Data center refrigeration unit efficiency, Q t Refrigeration T produced by refrigeration equipment of data center T-section t dc,out For t period of external environment temperature, U C The heat transfer coefficient of the data center to the outside; />
Lower limit of temperature change rate of data center, +.>
An upper limit for the temperature change rate of the data center; />
Is the indoor temperature lower limit of the data center, +.>
An upper temperature limit in the data center room;
the thermal characteristics and generalized energy storage constraints of the park building are as follows:
in the method, in the process of the invention,
generalized energy storage for data center t period, H BD Specific heat capacity of data center, T t BD Indoor temperature in t time period of data center,/o>
For the upper limit of the indoor temperature in the t period, < >>
The lower limit of the indoor temperature is t time period; />
Phi for the solar radiation quantity passing through the glazing of a building t The solar radiation heat is in a t period, and sigma is the solar radiation loss rate; />
For building to radiate heat outwards, T t E Building wall temperature for the park at time t; t (T) t The indoor temperature of the park at the period t; u (U) A The heat transfer coefficient is the direct heat transfer coefficient of the outer vertical surface of the building; u (U) E Heat transfer coefficients for indoor to wall; t (T) t a Is the external environment temperature in the t period. Wherein T is t E For the temperature of the building outer wall in t time period,/for the building outer wall temperature>
For the temperature of the building outer wall in t-1 time period, H PE Is the specific heat capacity of the building wall, T t a Is the external environment temperature in the t period.
The generalized energy storage total amount of the park is as follows:
6. the method for planning carbon emissions in a campus integrated energy system with generalized energy storage according to claim 1, wherein calculating the operational cost and the extension cost for 365 days of the campus planning, outputting the optimal planning and the operational strategy comprises:
in the actual solving process, the objective function is the sum of annual investment cost and planning annual operation cost, wherein the annual investment cost is the total extension cost divided by the planning age, and when the planning annual operation cost is calculated, all loads and photovoltaic output conditions during the planning period need to be met by each equipment operation constraint.
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