Optimization design method for light-storage direct-flexible low-carbon cold supply system of public building

Abstract

The invention provides an optimal design method for a light-storage direct-flexible low-carbon cold supply system of a public building. The invention follows the principle of'design based on control ', and provides an optimal design method for a light-storage direct-flexible low-carbon cold supply system of a public building, which comprehensively considers economy and low carbon. Establishing a building cold supply energy consumption simulation model, a building centralized cold station energy efficiency model, a distributed photovoltaic system power generation model and a building optical storage direct flexible low-carbon cold supply system optimization design model, and determining distributed photovoltaic system installation boundary conditions and related boundary conditions of external power grid input power; the building optical storage direct flexible low-carbon cooling system optimization design model comprehensively considers the influence of a power trading market and a carbon trading market on system optimization design, and the minimum system total equiannual value cost of the optical storage direct flexible low-carbon cooling system is taken as a target, and the optimal design model of the building optical storage direct flexible low-carbon cooling system is obtained by solving the optimal design model of the building optical storage direct flexible low-carbon cooling system. And the optimal configuration scheme of the light storage direct flexible low-carbon cold supply system of the public building is obtained.

Description

Technical Field

[0001] The present invention relates to the technical field related to photovoltaic, storage, direct and flexible cooling, and in particular to an optimization design method for a photovoltaic, storage, direct and flexible low-carbon cooling system for a public building. Background Art

[0002] In the traditional design of building centralized cooling systems, the cooling index per square meter is often used as the basis for the capacity configuration of the building centralized cooling system. In actual projects, it is very common to have excessive initial investment, redundant system configuration, and idle equipment. In the few more sophisticated design methods, a building energy consumption simulation analysis model is often established to obtain the delayed load curve of the building's terminal demand cooling power as a design reference to guide the configuration and selection of the building's centralized cooling system.

[0003] Applying the photovoltaic storage direct flexible technology to the field of public building cooling is of great significance for reducing the operating costs of public building cooling and achieving low-carbon or even zero-carbon cooling in public buildings. In the optimization design of the photovoltaic storage direct flexible low-carbon cooling system for public buildings, the capacity configuration results between its distributed photovoltaic system, distributed power storage system, cold storage system and centralized cooling system affect each other, and the traditional design method is no longer applicable. How to comprehensively consider the two factors of economic factors and low carbon and sort out a set of scientific and reasonable optimization design methods is of great significance for highlighting the economic superiority of the photovoltaic storage direct flexible low-carbon cooling solution for public buildings and helping the implementation and promotion of the photovoltaic storage direct flexible low-carbon cooling system for public buildings. Summary of the invention

[0004] In order to solve the above technical difficulties, the present invention provides an optimization design method for a solar-storage direct-flexible low-carbon cooling system for public buildings, which provides a solid foundation for the implementation and promotion of solar-storage direct-flexible low-carbon cooling systems for public buildings.

[0005] In order to solve the above technical difficulties, the technical solution adopted by the present invention is: an optimization design method for a public building photovoltaic storage direct flexible low-carbon cooling system, which comprehensively considers the two factors of economy and low carbon, and optimizes the rated cooling capacity of the variable frequency chiller that can be driven by DC in the centralized cooling station system of the public building, the capacity of the distributed photovoltaic system, the capacity of the distributed power storage system, the capacity of the cold storage system, and the capacity of the bidirectional AC / DC converter. Following the principle of "design based on control", it specifically includes the following steps:

[0006] Step 1: Establish a building energy consumption simulation analysis model, calculate the hourly cooling demand of the building in a typical year, and then determine the peak cooling load;

[0007] Step 2: Obtain the hourly total radiation intensity per unit horizontal area in a typical year in the area where the building is located, and establish a distributed photovoltaic system power generation model to calculate the hourly power generation per unit photovoltaic module area in a typical year;

[0008] Step 3: Define the boundary conditions for the installation of distributed photovoltaic systems: determine the available area of ​​the building roof and the available area of ​​the open space around the building;

[0009] Step 4: Clarify the boundary conditions of the external power grid: obtain the time-of-use electricity price list of the building area, the dynamic carbon emission responsibility factor in a typical year, and the carbon price in the carbon trading market;

[0010] Step 5: Establish an energy efficiency model for building centralized cooling stations;

[0011] Step 6: Establish an optimization design model for the building photovoltaic storage direct flexible low-carbon cooling system, and determine the optimization objectives, optimization variables and related constraints in the optimization model;

[0012] Step 7: Solve the optimization design model of the building photovoltaic storage direct flexible low-carbon cooling system to obtain the optimal solution to guide the optimization design of the building photovoltaic storage direct flexible low-carbon cooling system.

[0013] In step 1, a building energy consumption simulation analysis model is established. It is recommended to use professional building energy consumption simulation software, including but not limited to DEST, EnergyPlus, etc., to clarify the building physical model parameters, internal disturbance setting parameters, and external disturbance setting parameters to build the building energy consumption simulation analysis model.

[0014] The peak cooling load in step 1 is used as a reference upper limit value of the rated cooling capacity of the variable frequency chiller capable of direct current drive.

[0015] The available area of ​​the building roof and the available area of ​​the open space around the building in step 3 are used as reference upper limits of the capacity of the distributed photovoltaic system.

[0016] The dynamic carbon emission responsibility factor in step 4 is the carbon emission responsibility that the public building's photovoltaic storage direct flexible low-carbon cooling system needs to bear for every 1kWhe of electricity input by the municipal power grid to the public building's photovoltaic storage direct flexible low-carbon cooling system, and the unit is kgCO2 / kWhe.

[0017] The energy efficiency model of the building centralized cooling station in step five includes the chiller energy efficiency model, the cooling water system transmission and distribution energy efficiency model, the chilled water system transmission and distribution energy efficiency model and the cold storage system transmission and distribution energy efficiency model.

[0018] The optimization goal in step six is ​​to minimize the total equivalent annual cost of the building's photovoltaic storage direct flexible low-carbon cooling system. The total equivalent annual cost of the system includes four parts: the system's equivalent annual initial investment cost, the system's equivalent annual replacement cost, the system's annual operation and maintenance cost, and the system's annual operating cost. The system's annual operating cost includes the system's annual electricity purchase cost, the system's annual power return income, and the system's annual carbon reduction income.

[0019] The optimization variables in step six include time-independent optimization variables and time-dependent optimization variables: the time-independent optimization variables include the rated cooling capacity of the DC-driven variable frequency chiller, distributed photovoltaic capacity, distributed power storage capacity, cold storage capacity, and bidirectional AC / DC converter capacity; the time-dependent optimization variables include the hourly cooling power of the DC-driven variable frequency chiller, the hourly power consumption of distributed photovoltaics, the hourly operating power of the distributed power storage system, and the hourly operating power of the cold storage system.

[0020] The relevant constraints in step six include power balance-related constraints, power limit-related constraints, energy balance-related constraints, and energy limit-related constraints. The power balance-related constraints include electric power balance constraints and cooling power balance constraints; the power limit-related constraints include distributed photovoltaic power consumption constraints, DC-driven variable frequency refrigeration power constraints, AC / DC bidirectional converter operating power constraints, distributed power storage system operating power constraints, and cooling system operating power constraints; the energy balance-related constraints include distributed power storage system energy balance constraints and cooling system energy balance constraints; the energy limit-related constraints include distributed power storage system energy limit constraints and cooling system energy limit constraints.

[0021] The optimal solution in step seven includes the optimal rated cooling configuration capacity of the DC-driven variable frequency chiller, the optimal configuration capacity of the distributed photovoltaic system, the optimal configuration capacity of the distributed power storage system, the optimal configuration capacity of the cold storage system and the optimal configuration capacity of the bidirectional AC / DC converter.

[0022] The present invention proposes an optimization design method for a public building photovoltaic storage direct flexible low-carbon cooling system. The present invention follows the principle of "design based on control" and proposes an optimization design method for a public building photovoltaic storage direct flexible low-carbon cooling system that comprehensively considers economy and low carbon. It establishes a building cooling energy consumption simulation model, a building centralized cooling station energy efficiency model, a distributed photovoltaic system power generation model, and a building photovoltaic storage direct flexible low-carbon cooling system optimization design model, and clarifies the distributed photovoltaic system installation boundary conditions and the relevant boundary conditions of the external power grid input power; the building photovoltaic storage direct flexible low-carbon cooling system optimization design model comprehensively considers the impact of the electricity trading market and the carbon trading market on the system optimization design, and takes the lowest system total equivalent annual cost of the photovoltaic storage direct flexible low-carbon cooling system as the goal. By solving the building photovoltaic storage direct flexible low-carbon cooling system optimization design model, the optimal configuration scheme of the public building photovoltaic storage direct flexible low-carbon cooling system is obtained. The present invention proposes an optimization design method for a direct and flexible low-carbon cooling system for solar energy storage in public buildings, which can achieve the system configuration with the lowest investment cost, the lowest carbon emission and the highest efficiency. It is of great significance to promote the implementation and promotion of the direct and flexible low-carbon cooling system for solar energy storage in public buildings and to assist the deep low-carbon transformation of the construction sector. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 Optimize the design flow chart of the solar-storage direct-flexible low-carbon cooling system for public buildings. DETAILED DESCRIPTION

[0024] The technical solutions in the embodiments of the present invention will be described in more detail below in conjunction with the accompanying drawings. Although the exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. These embodiments are provided to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art. All other embodiments obtained by those of ordinary skill in the art without making creative efforts are within the scope of protection of the present invention.

[0025] Example 1

[0026] Figure 1 Optimize the design flow chart of the solar-storage direct-flexible low-carbon cooling system for public buildings. Figure 1 As shown, the optimization design method of a public building solar energy storage direct flexible low-carbon cooling system in this embodiment follows the principle of "design based on control" and specifically includes the following steps:

[0027] Step 1: Establish a building energy consumption simulation analysis model, calculate the hourly cooling demand of the building in a typical year, and then determine the peak cooling load;

[0028] In the step 1, a building energy consumption simulation analysis model is established. It is recommended to use professional building energy consumption simulation software, including but not limited to DEST, EnergyPlus, DOE, etc., to clarify the building physical model parameters, internal disturbance setting parameters, and external disturbance setting parameters to build the building energy consumption simulation analysis model.

[0029] The peak cooling load in step 1 is used as a reference upper limit value of the rated cooling capacity of the variable frequency chiller capable of direct current drive.

[0030] Step 2: Obtain the hourly total radiation intensity per unit horizontal area in a typical year in the area where the building is located, and establish a distributed photovoltaic system power generation model to calculate the hourly power generation per unit photovoltaic module area in a typical year.

[0031] In view of the limited spatial resources of public buildings, it is recommended that the distributed photovoltaic system of public buildings adopt a horizontal laying method to maximize the use of spatial resources. Without considering complex shading, the expression shown in Formula 1 can be used to establish the power generation model of the distributed photovoltaic system:

[0032] P pv (t) = S pv,system ×I solar(t)×IPCE×η pv，system (Formula 1)

[0033] Where P pv (t) is the power generation of the distributed photovoltaic system at the tth moment, in kWe; S pv，system is the total area of ​​components of the distributed photovoltaic system, in square meters; I solar (t) is the total hourly radiation intensity per unit module area at the tth moment in the area where the building is located, in W / ㎡. For a horizontally laid distributed photovoltaic system, the total hourly radiation intensity per unit module area is the total hourly radiation intensity per unit horizontal area; IPCE is the photoelectric conversion efficiency of the photovoltaic module, in %; η pv，system It is the comprehensive efficiency of distributed photovoltaic system, unit is %.

[0034] For non-horizontally laid distributed photovoltaic systems, the hourly total radiation intensity per unit component area in the power generation model of the distributed photovoltaic system is not equal to the hourly total radiation intensity per unit horizontal area. The hourly total radiation intensity per unit component area on the inclined surface includes three parts: direct solar radiation intensity, sky scattered radiation intensity and ground reflected radiation intensity. The mathematical calculation models of each part are relatively complex. In addition, for distributed photovoltaic systems with complex shading conditions, it is more difficult to establish the mathematical expression of their power generation model. It is recommended to establish an accurate physical model in professional photovoltaic system design software, and obtain the hourly power generation power per unit photovoltaic component area of ​​the distributed photovoltaic system in a typical year through simulation calculation.

[0035] Step 3: Clarify the boundary conditions for the installation of the distributed photovoltaic system: determine the available area of ​​the building roof and the available area of ​​the open space around the building.

[0036] The usable area of ​​the building roof and the usable area of ​​the open space around the building in step three can be obtained through design drawings, on-site surveys or satellite map surveys, and the specific values ​​will serve as the reference upper limit of the capacity of the distributed photovoltaic system.

[0037] Step 4: Clarify the boundary conditions of the external power grid: obtain the time-of-use electricity price list of the building area, the carbon price of the carbon trading market, and the hourly reference curve of the dynamic carbon emission responsibility factor in a typical year.

[0038] The dynamic carbon emission responsibility factor in step 4 is the carbon emission responsibility that the public building solar-storage direct-flexible low-carbon cooling system needs to bear for every 1 kWhe of electricity input by the municipal power grid to the public building solar-storage direct-flexible low-carbon cooling system, and the unit is kgCO2 / kWhe.

[0039] Step 5: Establish an energy efficiency model for the building's centralized cooling station.

[0040] The energy efficiency model of the building centralized cooling station in step 5 includes a chiller energy efficiency model, a cooling water system transmission and distribution energy efficiency model, a chilled water system transmission and distribution energy efficiency model, and a cold storage system transmission and distribution energy efficiency model.

[0041] The energy efficiency model of the chiller is recommended to be expressed as shown in Formula 2:

[0042] COP=f(PLR,T chws , T out ) (Formula 2)

[0043] Wherein PLR is the load rate of the variable frequency chiller capable of direct current drive, in %; T chws T is the chilled water supply temperature setting value of the DC-driven variable frequency chiller, in °C; out is the outdoor temperature of the building location, in °C; f(PLR, T chws , T out ) indicates that the independent variables are PLR, T chws , T out The function expression of is recommended to be a ternary quadratic polynomial expression, as shown in Formula 3:

[0044]

[0045] where a 0 is the zero-order coefficient, a 1 、a 2 、a 3 is the degree of the first term, a 4 、a 5 、a 6 、a 7 、a 8 、a 9 is the coefficient of the quadratic term.

[0046] The recommended definition expression of the cooling water system distribution energy efficiency model is shown in Formula 4: Where, WTF cw Pc is the cooling water system distribution coefficient, unit kWc / kWe; cw is the heat rejection power of the cooling water system, in kWc; Pe cw The power consumption of the variable frequency cooling water system distribution equipment that can be driven by direct current is in kWe. During the design stage, it is recommended that the energy efficiency of the cooling water distribution system be taken as a fixed value.

[0047]

[0048] Optionally, the building centralized cooling station is a primary pump system, and the recommended definition expression of the chilled water system distribution energy efficiency model is shown in Formula 5: Wherein, WTF chw Pc is the chilled water system distribution coefficient, unit: kWc / kWe;load is the cooling demand power at the end of the building, that is, the cooling power of the chilled water system, in kWc; Pe chw The power consumption of the variable frequency chilled water system distribution equipment that can be driven by direct current is in kWe. During the design stage, it is recommended that the energy efficiency of the chilled water distribution system be taken as a fixed value.

[0049]

[0050] Optionally, the building centralized cooling station is a secondary pump system, and the chilled water system distribution energy efficiency model includes a primary chilled water system distribution energy efficiency model and a secondary chilled water system distribution energy efficiency model: the secondary chilled water system distribution energy efficiency model is the same as Formula 5, expressed as the ratio of the cooling demand power at the end of the building to the power consumption of the secondary chilled water system distribution equipment; the recommended definition expression of the primary chilled water system distribution energy efficiency model is shown in Formula 6:

[0051]

[0052] Among them, WTF pchw Pc is the primary chilled water system distribution coefficient, unit: kWc / kWe; ch is the cooling power of the variable frequency chiller capable of direct current drive, in kWc; Pe pchw It is the power consumption of the distribution equipment of the primary chilled water system, in kWe. During the design phase, it is recommended that the distribution energy efficiency of the chilled water system be taken as a constant value.

[0053] The recommended definition expression of the transmission and distribution energy efficiency model of the cold storage system is shown in Formula 7: Where, WTF TES Pc is the transmission coefficient of the cold storage system, in kWc / kWe; TES is the operating power of the cold storage system, in kWc; Pe TES The power consumption of the DC-driven variable frequency cold storage system distribution equipment is in kWe. During the design phase, it is recommended that the energy efficiency of the cold storage system distribution system be taken as a constant value.

[0054]

[0055] Step 6. Establish an optimization design model for the building photovoltaic storage direct flexible low-carbon cooling system, and determine the optimization objectives, optimization variables and related constraints in the optimization model.

[0056] The optimization goal of the optimization design model of the building photovoltaic storage direct flexible low-carbon cooling system is to minimize the total annual cost of the system, as shown in Formula 8: where F is the objective function of the optimization model, Cost eav It is the system total equal annual cost function of the building solar energy storage direct flexible low-carbon cooling system.

[0057] min F=Cost eav (Formula 8)

[0058] As shown in Formula 9, the total annual cost of the system includes: the initial investment cost of the annual cost of the system init，eav , system and other annual replacement costs Cost rep，eav 、System annual operation and maintenance cost Cost om 、System annual operating cost Cost operation , the unit is Yuan / year.

[0059] Cost eav =Cost init,eav +Cost rep，eav +Cost om +Cost operation (Formula 9)

[0060] As shown in formula 10, the initial investment cost of the system is equal to the annual value Cost init，eav Including: Distributed photovoltaic system and other annual initial investment costs pv，init，eav , building centralized cooling station system, etc. Annual initial investment cost hvac，init，eav , distributed power storage system, etc. Annual initial investment cost BES，init，eav , cold storage system, etc. Annual initial investment cost TES,init.eav Cost of initial investment of bidirectional AC / DC converter Con，init.eav , unit is Yuan / year.

[0061]

[0062] As shown in Formula 11, the system equivalent annual replacement cost Cost rep，eav Including: Distributed photovoltaic system and other annual replacement costs Cost pv，rep，eav , Annual replacement cost of building centralized cooling station system, etc. hvac，rep，eav , Distributed power storage system, etc. Annual replacement cost Cost BES，rep，eav , annual replacement cost of cold storage system, etc. TES，rep，eav Cost of replacement of bidirectional AC / DC converters Con，rep.eav , unit is Yuan / year.

[0063]

[0064] The annual cost of each of the above parts can be calculated based on the net present value cost. dev And the capital recovery coefficient A is calculated as shown in Formula 12: where i is the discount rate, unit %; l is the expected value of the system life, unit year.

[0065]

[0066] As shown in formula 13, the annual operation and maintenance cost of the system is Cost om Includes: Annual operation and maintenance cost of distributed photovoltaic system pv，om , Annual operation and maintenance cost of building centralized cooling station system hvac，on , Annual operation and maintenance cost of distributed power storage system BES，om , Annual operation and maintenance cost of cold storage system TES，om and the annual operation and maintenance cost of the bidirectional AC / DC converter Con，om , unit is Yuan / year.

[0067]

[0068] As shown in Formula 14, the annual operating cost of the system is operation Includes: System annual electricity purchase cost Cost grid 、System annual electricity return income grid and the system's annual carbon reduction income carbon , unit is Yuan / year.

[0069] Cost operation =Cost grid -Income grid -Income carbon (Formula 14)

[0070] The annual electricity purchase cost of the system is grid The calculation formula is shown in Formula 15: Where N is the number of hours in the cooling season; Peg rid+ The power drawn by the DC bus of the building centralized cooling station from the building AC bus, that is, the rectified power of the bidirectional AC / DC converter, in kWe; Fee electricity (t) is the electricity price of the municipal power grid during the period from time t to time t+1, in units of RMB / kWhe.

[0071]

[0072] The annual return of electricity income of the system grid The calculation formula is shown in Formula 16: Where N is the number of hours in the cooling season; Pe grid- is the power returned from the DC bus of the building centralized cooling station to the AC bus of the building, that is, the inverter power of the bidirectional AC / DC converter, in kWe; α is the proportion of the returned power consumed by the AC load on the building AC bus, in %; Fee electricity (t) is the electricity price of the municipal power grid from time t to time t+1, in units of RMB / kWhe; Feesale (t) is the electricity price sold from the building AC bus to the municipal power grid during the period from time t to time t+1, in units of RMB / kWhe.

[0073]

[0074] Annual carbon reduction income of the system carbon The calculation formula is shown in Formula 17: Where N is the number of hours in the cooling season; Pc load is the power required for building cooling, in kWc; EER is the energy efficiency value of a conventional high-efficiency cooling station in a building without a cold storage system, in kWc / kWe; Pe grid is the operating power of the bidirectional AC / DC converter between the DC bus of the building centralized cooling station and the AC bus of the building, in kWe; C grid is the dynamic carbon emission responsibility factor of the municipal power grid from time t to time t+1, in kgCO2 / kWhe; Fee carbon It is the carbon price in the carbon trading market where the building is located, in Yuan / kgCO2.

[0075]

[0076] Furthermore, the optimization variables of the optimization design model of the building photovoltaic storage direct flexible low-carbon cooling system include time-independent optimization variables and time-dependent optimization variables: the time-independent optimization variables include the rated cooling capacity of the DC-driven variable frequency chiller, distributed photovoltaic capacity, distributed power storage capacity, cold storage capacity, and bidirectional AC / DC converter capacity; the time-dependent optimization variables include the hourly cooling power of the DC-driven variable frequency chiller, the hourly power consumption of distributed photovoltaics, the hourly operating power of the distributed power storage system, and the hourly operating power of the cold storage system.

[0077] Furthermore, the relevant constraints of the optimization design model of the building photovoltaic storage direct flexible low-carbon cooling system include power balance related constraints, power limitation related constraints, energy balance related constraints, and energy limitation related constraints.

[0078] The power balance related constraints include electric power balance constraints and cooling power balance constraints. The variable signs are specified as follows: taking electricity from the grid is negative, discharging to the grid is positive; taking cooling from the cooling grid is negative, discharging cooling to the cooling grid is positive.

[0079] ① The power balance constraint is shown in formula 18:

[0080] P grid (t)+Pe pv,use (t)+Pe BES (t)+Pe hvac(t) = 0 (Formula 18)

[0081] Among them, Pe grid (t) is the operating power of the bidirectional AC / DC converter at time t; Pe pv，use (t) is the distributed photovoltaic power consumption at time t; Pe BES (t) is the operating power of the distributed power storage system at time t; Pe hvac (t) is the power consumption of the building centralized cooling station, and its calculation formula is shown in Formula 19:

[0082] P hvac (t) = Pe ch (t)+Pe cw (t)+Pe chw (t)+Pe TES (t) (Formula 19)

[0083] Among them, Pe ch (t) is the power consumption of the variable frequency refrigerator capable of direct current drive at time t, which can be calculated based on the cooling power and energy efficiency of the variable frequency refrigerator capable of direct current drive; Pe cw (t) is the power consumption of the DC-driven variable frequency cooling water system distribution equipment at time t, which can be calculated based on the heat rejection power and distribution energy efficiency; Pe chw (t) is the power consumption of the DC-driven variable frequency chilled water system distribution equipment at time t, which can be calculated based on the cooling demand power and distribution energy efficiency at the end of the building; Pe TES (t) is the power consumption of the DC-driven variable frequency cold storage system transmission and distribution equipment at time t, which can be calculated based on the operating power and transmission and distribution energy efficiency of the cold storage system; the units of the above electric power are all kWe.

[0084] ②The power balance constraint condition is shown in formula 20: Pc ch (t) is the cooling power of the DC-driven variable frequency chiller at time t; Pc TES (t) is the operating power of the cold storage system at time t; Pc load is the cooling power demand at the end of the building at time t; the above cooling power units are all kWc.

[0085] Pc ch (t)+Pc TES (t)+Pc load (t) = 0 (Formula 20)

[0086] Furthermore, the power limitation related constraints include distributed photovoltaic absorption power constraints, chiller cooling power constraints, AC / DC bidirectional converter operating power constraints, distributed power storage system operating power constraints, and cold storage system operating power constraints.

[0087] ① The distributed photovoltaic power consumption constraint is shown in formula 21: where Pe pv，mppt (t) is the maximum power generation of the distributed photovoltaic system at time t, in kWe.

[0088] 0≤Pe pv,use (t)≤Pe pv，mppt (t) (Formula 21)

[0089] ② When the chiller is turned off, the chiller refrigeration power constraint is as shown in formula 22:

[0090] Pc ch (t) = 0 (Formula 22)

[0091] When the chiller is turned on, the chiller cooling power constraint is as shown in Formula 23: ch PLR is the rated cooling capacity of the DC-driven variable frequency chiller, in kWc; min is the minimum load rate of the DC-driven variable frequency chiller, in %.

[0092] PLR min ×Cap ch ≤Pc ch (t)≤Cap ch (Formula 23)

[0093] ③ When the AC / DC bidirectional converter is in the rectifying working state, the operating power constraint of the AC / DC bidirectional converter is as shown in Formula 24: Where, Pe rec，max is the maximum rectified power of the AC / DC bidirectional converter, in kVA.

[0094] 0≤Pe grid (t)≤Pe rec,max (Formula 24)

[0095] When the AC / DC bidirectional converter is in the inverter working state, the operating power constraint of the AC / DC bidirectional converter is as shown in Formula 25: Where, Pe inv，max is the maximum inverter power of the AC / DC bidirectional converter, in kVA.

[0096] P inv,max ≤Pe grid (t)≤0 (Formula 25)

[0097] ④ When the distributed power storage system is in a charging state, the operating power constraint of the distributed power storage system is as shown in Formula 26: Where, Pe BES，ch (t) is the charging power of the distributed power storage system at time t; Pe BES，ch，maxis the maximum charging power of the distributed power storage system; Pe BES，ch，min is the minimum charging power of the distributed power storage system; the above units are all kWe.

[0098] P BES,ch,min ≤Pe BES，ch (t)≤Pe BES，ch,max (Formula 26)

[0099] When the distributed power storage system is in a discharging state, the operating power constraint of the distributed power storage system is as shown in Formula 27: Where, Pe BES，disch (t) is the discharge power of the distributed power storage system at time t; Pe BES，disch，max is the maximum discharge power of the distributed power storage system; Pe BES，disch，min is the minimum discharge power of the distributed power storage system; the above units are all kWe.

[0100] P BES,disch,min ≤Pe BES，disch (t)≤Pe BES，disch,max (Formula 27)

[0101] The charging state and discharging state of the distributed power storage system cannot appear at the same time, and must satisfy the constraint relationship shown in Formula 28:

[0102] P BES,ch (t)×Pe BES,disch (t) = 0 (Formula 28)

[0103] ⑤ When the cold storage system is in the cold storage state, the operating power constraint of the cold storage system is as shown in Formula 29: Where, Pe BES，ch (t) is the cold storage power of the cold storage system at time t; Pe BES，ch，max is the maximum cold storage power of the cold storage system; Pe BES，ch，min is the minimum cold storage power of the cold storage system; the above units are all kWc.

[0104] P TES,ch,min ≤Pe TES,ch (t)≤Pe TES,ch,max (Formula 29)

[0105] When the cold storage system is in a cooling state, the operating power constraint of the cold storage system is as shown in Formula 30: Where, Pe BES，disch (t) is the discharge power of the cold storage system at time t; Pe BES，disch，max is the maximum discharge power of the cold storage system; Pe BES，disch，min is the minimum discharge power of the cold storage system; the above units are all kWc.

[0106] P TES,disch,min≤Pe TES,disch (t)≤Pe TES,disch,max (Formula 30)

[0107] The cold storage state and the cold release state of the cold storage system cannot appear at the same time, and the constraint relationship shown in formula 31 must be satisfied:

[0108] P TES,ch (t)×Pe TES,disch (t) = 0 (Formula 31)

[0109] Furthermore, the energy balance related constraints include distributed power storage system energy balance constraints and cold storage system energy balance constraints.

[0110] ① The energy balance constraint of the distributed power storage system is shown in formula 32: where, is the initial charge state of the distributed power storage system, unit: %; is the charge state of the distributed power storage system at the end of the nth energy balance cycle, in %; T is the duration of the cooling season, in min; N1 is the duration of the distributed power storage system's power balance cycle, in min.

[0111]

[0112] ② The energy balance constraint of the cold storage system is shown in formula 33, which defines the equivalent state of charge of the cold storage system as the ratio of the actual cold storage capacity to the rated cold storage capacity: is the equivalent initial state of charge of the cold storage system, unit: %; is the equivalent charge state of the cold storage system at the end of the nth energy balance cycle, in %; T is the duration of the cooling season, in min; N2 is the duration of the heat balance cycle of the cold storage system, in min.

[0113]

[0114] Furthermore, the energy limitation related constraints include distributed power storage system energy limitation constraints and cold storage system energy limitation constraints.

[0115] ① The energy limit constraint of the distributed power storage system includes the SOC threshold constraint and the adjacent moment SOC limit constraint. The SOC threshold constraint is shown in Formula 34: BES (t) is the state of charge of the distributed power storage system at time t; SOC BES，max SOC is the maximum allowable state of charge of the distributed power storage system; BES，min is the minimum allowable state of charge of the distributed power storage system; the unit is %.

[0116] SOC BES,min≤SOC BES (t)≤SOC BES,max (Formula 34)

[0117] The adjacent time SOC limit constraint is shown in Formula 35: BES (t+1) is the state of charge of the distributed power storage system at time (t+1), in %; Cap BES is the rated storage capacity of the distributed power storage system, in kWhe; ε c is the charging efficiency of the distributed power storage system, in %; ε dc is the discharge efficiency of the distributed power storage system, unit: %

[0118]

[0119] ② The energy restriction constraint of the cold storage system includes an equivalent SOC threshold constraint and an equivalent SOC restriction constraint at adjacent moments. The SOC threshold constraint is shown in Formula 36: TES (t) is the equivalent state of charge of the cold storage system at time t; SOC TES，max SOC is the maximum allowable equivalent state of charge of the cold storage system; TES，min It is the minimum allowable equivalent state of charge of the cold storage system; the unit is %.

[0120] SOC TES,min ≤SOC TES (t)≤SOC TES,max (Formula 36)

[0121] The equivalent SOC limit constraint at adjacent moments is shown in Formula 37: TES (t+1) is the equivalent state of charge of the cold storage system at time (t+1), unit: %; Cap TES is the rated cold storage capacity of the cold storage system, in kWhc; η c is the cold storage efficiency of the cold storage system, unit: %; η dc The cooling efficiency of the cold storage system, unit: %

[0122]

[0123] Step 7. Solve the optimization design model of the building photovoltaic storage direct flexible low-carbon cooling system to obtain the specific values ​​of the optimized variables, which are used to guide the optimization design of the building photovoltaic storage direct flexible low-carbon cooling system.

[0124] The optimal solution in step seven includes the optimal rated cooling configuration capacity of the DC-driven variable frequency chiller, the optimal configuration capacity of the distributed photovoltaic system, the optimal configuration capacity of the distributed power storage system, the optimal configuration capacity of the cold storage system and the optimal configuration capacity of the bidirectional AC / DC converter.

[0125] By solving the optimization design model of the building photovoltaic storage direct flexible low-carbon cooling system, the most economical and lowest-cost optimal configuration plan of the building photovoltaic storage direct flexible low-carbon cooling system is obtained.

[0126] The above implementation modes are not limitations of the present invention, and the present invention is not limited to the above examples. Changes, modifications, additions or substitutions made by technicians in this technical field within the scope of the technical solution of the present invention also belong to the protection scope of the present invention.

Claims

1. An optimization design method for a public building solar energy storage direct flexible low-carbon cooling system, characterized in that: Taking into account both economic and low-carbon factors, the rated cooling capacity of the variable frequency chiller that can be driven by DC, the capacity of the distributed photovoltaic system, the capacity of the distributed power storage system, the capacity of the cold storage system, and the capacity of the bidirectional AC / DC converter in the centralized cooling station system of public buildings are optimized. Following the principle of "design based on control", the following steps are specifically included: Step 1: Establish a building energy consumption simulation analysis model, calculate the hourly cooling demand of the building in a typical year, and then determine the peak cooling load; Step 2: Obtain the hourly total radiation intensity per unit horizontal area in a typical year in the area where the building is located, and establish a distributed photovoltaic system power generation model to calculate the hourly power generation per unit photovoltaic module area in a typical year; Step 3: Define the boundary conditions for the installation of distributed photovoltaic systems: determine the available area of ​​the building roof and the available area of ​​the open space around the building; Step 4: Clarify the boundary conditions of the external power grid: obtain the time-of-use electricity price list of the building area, the dynamic carbon emission responsibility factor in a typical year, and the carbon price in the carbon trading market; Step 5: Establish an energy efficiency model for building centralized cooling stations; Step 6: Establish an optimization design model for the building photovoltaic storage direct flexible low-carbon cooling system, and determine the optimization objectives, optimization variables and related constraints in the optimization model; Step 7: Solve the optimization design model of the building photovoltaic storage direct flexible low-carbon cooling system to obtain the optimal solution to guide the optimization design of the building photovoltaic storage direct flexible low-carbon cooling system.

2. The optimization design method of a solar-storage direct-flexible low-carbon cooling system for public buildings as claimed in claim 1, characterized in that: In the step 1, a building energy consumption simulation analysis model is established. It is recommended to use professional building energy consumption simulation software, including but not limited to DEST, EnergyPlus, DOE, etc., to clarify the building physical model parameters, internal disturbance setting parameters, and external disturbance setting parameters to build the building energy consumption simulation analysis model.

3. The optimization design method of a solar-storage direct-flexible low-carbon cooling system for public buildings as claimed in claim 2 is characterized in that: The peak cooling load in step 1 is used as a reference upper limit value of the rated cooling capacity of the variable frequency chiller capable of direct current drive.

4. The optimization design method of a solar-storage direct-flexible low-carbon cooling system for public buildings as claimed in claim 3 is characterized in that: The available area of ​​the building roof and the available area of ​​the open space around the building in step three are used as reference upper limits of the capacity of the distributed photovoltaic system.

5. The optimization design method of a solar-storage direct-flexible low-carbon cooling system for public buildings as claimed in claim 4 is characterized in that: The dynamic carbon emission responsibility factor in step 4 is the carbon emission responsibility that the public building solar-storage direct-flexible low-carbon cooling system needs to bear for every 1 kWhe of electricity input by the municipal power grid to the public building solar-storage direct-flexible low-carbon cooling system, and the unit is kgCO2 / kWhe.

6. The optimization design method of a solar-storage direct-flexible low-carbon cooling system for public buildings as claimed in claim 5 is characterized in that: The energy efficiency model of the building centralized cooling station in step 5 includes a chiller energy efficiency model, a cooling water system transmission and distribution energy efficiency model, a chilled water system transmission and distribution energy efficiency model, and a cold storage system transmission and distribution energy efficiency model.

7. The optimization design method of a solar-storage direct-flexible low-carbon cooling system for public buildings as claimed in claim 6 is characterized in that: The optimization goal in step six is ​​to minimize the total equivalent annual cost of the building's photovoltaic storage direct flexible low-carbon cooling system. The total equivalent annual cost of the system includes four parts: the system's equivalent annual initial investment cost, the system's equivalent annual replacement cost, the system's annual operation and maintenance cost, and the system's annual operating cost. The system's annual operating cost includes the system's annual electricity purchase cost, the system's annual power return income, and the system's annual carbon reduction income.

8. The optimization design method of a solar-storage direct-flexible low-carbon cooling system for public buildings as claimed in claim 7 is characterized in that: The optimization variables in step six include time-independent optimization variables and time-dependent optimization variables: the time-independent optimization variables include the rated cooling capacity of the DC-driven variable frequency chiller, distributed photovoltaic capacity, distributed power storage capacity, cold storage capacity, and bidirectional AC / DC converter capacity; the time-dependent optimization variables include the hourly cooling power of the DC-driven variable frequency chiller, the hourly power consumption of distributed photovoltaics, the hourly operating power of the distributed power storage system, and the hourly operating power of the cold storage system.

9. The optimization design method of a solar-storage direct-flexible low-carbon cooling system for public buildings as claimed in claim 8, characterized in that: The relevant constraints in step six include power balance-related constraints, power limit-related constraints, energy balance-related constraints, and energy limit-related constraints. The power balance-related constraints include electric power balance constraints and cooling power balance constraints; the power limit-related constraints include distributed photovoltaic power consumption constraints, the DC-driven variable frequency refrigeration machine cooling power constraints, AC / DC bidirectional converter operating power constraints, distributed power storage system operating power constraints, and cooling system operating power constraints; the energy balance-related constraints include distributed power storage system energy balance constraints and cooling system energy balance constraints; the energy limit-related constraints include distributed power storage system energy limit constraints and cooling system energy limit constraints.

10. The optimization design method of a solar-storage direct-flexible low-carbon cooling system for public buildings as claimed in claim 9, characterized in that: The optimal solution in step seven includes the optimal rated cooling configuration capacity of the DC-driven variable frequency chiller, the optimal configuration capacity of the distributed photovoltaic system, the optimal configuration capacity of the distributed power storage system, the optimal configuration capacity of the cold storage system and the optimal configuration capacity of the bidirectional AC / DC converter.

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