Multi-objective optimization operation control method of PV / T combined air source heat pump system

Abstract

The application discloses a kind of multi-objective optimization operation control methods of PV / T combined air source heat pump system, belong to solar energy utilization and heat pump heating technical field.The system includes PV / T collector array, heat storage water tank, air source heat pump, fan-coil unit, multiple water pumps, solenoid valve, three-way valve and photovoltaic grid-connected unit.The method includes: establishing system dynamic simulation model;With cost annual value and carbon emissions as evaluation index, construct weighted objective function;With collector installation inclination, azimuth, collector area, water tank volume and heat pump rated power as optimization variable, iteration optimization is carried out using Hooke-Jeeves algorithm;According to optimal parameter configuration system and execute collection temperature difference control, 45 ℃ threshold auxiliary heating control, 22±1 ℃ terminal temperature control and "self-generating self-use, surplus electricity on-grid" power allocation control.The application can make system initial investment, cost annual value and objective function respectively drop, carbon emission drop, realize the collaborative promotion of economy, environmental benefit and heating stability.

Description

Technical Field

[0001] This invention relates to the field of solar energy utilization and heat pump heating technology, specifically a multi-objective optimization operation control method for a PV / T combined air source heat pump system. Background Technology

[0002] Photovoltaic-thermal integration (PV / T) technology can output electrical and thermal energy simultaneously on the same collector. The photovoltaic cells convert only a portion of the solar energy into electrical energy, while the majority of the solar energy is lost as heat. The PV / T system removes this heat through a fluid, thus obtaining hot water and cooling the photovoltaic cells, thereby improving the photoelectric conversion efficiency and realizing "electricity-heat" cogeneration.

[0003] However, solar energy is intermittent and unstable, significantly affected by sunlight conditions, making it difficult for a single PV / T system to guarantee the continuity and stability of building heating. Air source heat pumps, based on the reverse Carnot cycle, extract heat from the ambient air and can operate continuously on cloudy days or at night; however, using an air source heat pump alone results in high power consumption and operating costs. Therefore, coupling a PV / T system with an air source heat pump to form a complementary "electricity-heat" combined heating system is an important way to achieve low-carbon building energy systems.

[0004] Existing PV / T combined air source heat pump systems are mostly designed based on recommended values ​​in design specifications or empirical values ​​in literature to determine key parameters such as collector area, water tank volume, and heat pump power. This makes it difficult to provide optimal design solutions for specific regional meteorological conditions and building conditions, resulting in high initial investment, high operating energy consumption, and high carbon emissions. Furthermore, the lack of coordinated control strategies among heat collection, auxiliary heating, terminal heating, and photovoltaic power generation during system operation hinders the improvement of overall system performance. Therefore, there is an urgent need for a multi-objective optimization operation control method for PV / T combined air source heat pump systems that balances economic and environmental benefits and enables coordinated control of system operation. Summary of the Invention

[0005] Therefore, in order to address the above shortcomings, this invention provides a multi-objective optimization operation control method for a PV / T combined air source heat pump system. This method constructs a multi-objective optimization objective function using annual cost and carbon emissions as evaluation indicators, optimizes key system design and operating parameters, and, in conjunction with a sub-mode operation control strategy, achieves a synergistic improvement in system economy, environmental benefits, and heating stability.

[0006] Specifically, a multi-objective optimization operation control method for a PV / T combined air source heat pump system is provided. The PV / T combined air source heat pump system includes a PV / T collector array, a hot water storage tank, an air source heat pump, a fan coil unit, a collector circulation pump, a heating circulation pump, a heating water pump, a first solenoid valve, a first three-way valve, a second three-way valve, a second solenoid valve, and a photovoltaic power generation grid-connected unit. The first solenoid valve is located on the collector circuit of the PV / T collector array. The outlet of the hot water storage tank is selectively connected to either the heating branch or the air source heat pump heating branch via the first three-way valve. The outlet of the air source heat pump heating branch is connected to the main circuit via the second three-way valve. The second solenoid valve is located in the heat exchange circuit of the air source heat pump. The multi-objective optimization operation control method includes the following steps: S1. Establish a simulation model: Obtain meteorological data for a typical meteorological year at the location of the target building, and establish a system dynamic simulation model including a PV / T collector model, a layered hot water storage tank model, an air source heat pump model, a water pump model, a fan model, and a building load model; S2. Determine the evaluation index: Use the annual cost Z as the economic evaluation index. ; In the formula, i Using the benchmark discount rate, n For system lifespan, L 0 For the initial investment in the system, C Annual operating costs; based on system carbon emissions Q CO2 As an indicator for evaluating environmental benefits Q CO2 = W p × f CO2 In the formula, W p Power consumption over the system's lifecycle f CO2 Carbon emission factor; S3. Construct a multi-objective optimization objective function: y = w 1 × Z + w 2 × Q CO2 In the formula, w 1 , w 2 These are the weighting coefficients for annual cost and carbon emissions, respectively. S4. Parameter optimization: Using the installation tilt angle, azimuth angle of the PV / T collector, collector area, hot water storage tank volume and rated power of the air source heat pump as optimization variables, and minimizing the objective function y as the objective, the Hooke-Jeeves direct search algorithm is used to call the system dynamic simulation model established in step S1 for iterative optimization to obtain the optimal parameter combination. S5. Configure and operate the PV / T combined air source heat pump system according to the optimal parameter combination, and perform the following controls during operation: (1) Heat collection control: The outlet water temperature of the PV / T collector array is compared with the water temperature of the hot water storage tank in real time. When the temperature difference between the two is greater than the first set temperature difference, the first solenoid valve is opened and the heat collection circulation pump is started, and the PV / T collector array starts to collect heat. When the temperature difference is less than the second set temperature difference, the heat collection circulation pump and the first solenoid valve are closed. (2) Auxiliary heating control: When the water temperature at the top of the hot water storage tank is not lower than the set water supply temperature, the first three-way valve and the second three-way valve are controlled to open the heating branch and close the air source heat pump heating branch, and the second solenoid valve is closed, so that the hot water in the hot water storage tank is directly heated by the heating water pump; when the water temperature in the hot water storage tank is lower than the set water supply temperature, the first three-way valve and the second three-way valve are controlled to close the heating branch and open the air source heat pump heating branch, and the second solenoid valve is opened, so that the heating circulation pump and the heating water pump are started, and the air source heat pump provides auxiliary heating to the water in the hot water storage tank; (3) Terminal temperature control: When the indoor temperature is lower than the first set room temperature, the heating water pump and the fan coil unit are started to heat the room; when the indoor temperature is higher than the second set room temperature, the fan coil unit and the heating water pump are turned off. (4) Power distribution and control: The photovoltaic power generation of the PV / T collector array is given priority to the use of the system's electrical equipment. The surplus power is output through the photovoltaic power generation grid-connected unit, and the insufficient power generation is supplemented by the mains power.

[0007] Optionally, in step S2, the benchmark discount rate i Take 5.5%, the system lifespan n Take 20 years; the carbon emission factor f CO2 Take 0.5 kg / kWh.

[0008] Optionally, in step S3, the weighting coefficient of the annual cost value w 1 The weighting factor for carbon emissions is set to 0.7. w 2 Take 0.3.

[0009] Optionally, in step S4, the optimization process of the Hooke-Jeeves direct search algorithm includes: first, performing a global search on each optimization variable with a set grid interval and iteration precision to obtain a global search point set; then, using a coordinate search matrix, performing a local search on the global search point set along each coordinate axis until the objective function converges to the optimal value.

[0010] Optionally, in step S4, the search range for each optimization variable is: installation tilt angle 10°~70°, azimuth angle -20°~20°, collector area 1~100m², hot water storage tank volume 0.01~0.3m³, and air source heat pump rated power 2~10kW.

[0011] Optionally, the first set temperature difference is 7°C, the second set temperature difference is 2°C, and the set water supply temperature is 45°C.

[0012] Optionally, the first room temperature setting is 21°C, and the second room temperature setting is 23°C, so as to maintain the indoor temperature at 22±1°C.

[0013] Optionally, the PV / T collector array consists of 30 photovoltaic-thermal integrated flat plate collectors. Every 15 collectors are connected in series to form an independent branch. The two branches are connected in parallel and arranged in the same direction to ensure hydraulic balance between the two branches.

[0014] Optionally, step S1 may also include a step of verifying the dynamic simulation model of the system using measured operating data: collecting measured data of the inlet water temperature, outlet water temperature and photovoltaic power generation of the PV / T collector array, and comparing them with the simulation results. When the trend of the simulated value and the experimental value are consistent, the dynamic simulation model of the system is confirmed to be effective.

[0015] The present invention has the following advantages: 1. A weighted objective function is constructed with annual cost and carbon emissions as dual objectives, taking into account both the system's economic efficiency and environmental benefits. This overcomes the one-sidedness of optimizing a single indicator and achieves a win-win situation for both the economy and the environment.

[0016] 2. The Hooke-Jeeves direct search algorithm is used to perform multi-dimensional continuous variable optimization of installation tilt angle, azimuth angle, collector area, water tank volume and heat pump power. It does not require the derivative information of the objective function and is suitable for unconstrained optimization scenarios such as thermal systems where the objective function is complex and difficult to differentiate. It has fewer parameters, is easy to implement, and has high local search efficiency.

[0017] 3. Significant optimization results: After optimization, the initial investment, annual cost and objective function of the system decreased by 17.78%, 33.71% and 38.95% respectively; annual carbon emissions decreased by 16.27%, net operating costs decreased by 19.40% and net electricity consumption decreased by 16.27%, and the system's dependence on external power was significantly reduced.

[0018] 4. The multi-mode operation control strategy realizes the synergy between solar thermal collection, air source heat pump auxiliary heating, terminal heating and photovoltaic power generation: during the day, solar thermal collection is fully utilized, at night or on cloudy or rainy days, air source heat pump ensures continuous heating, and photovoltaic power is used for self-consumption first, overcoming the limitation of solar energy relying on sunlight conditions and enhancing the stability of system operation.

[0019] 5. After optimization, the fluctuation range of the system's annual power generation efficiency is significantly reduced, and the power generation efficiency in most months is higher than before optimization, thus improving the system's seasonal adaptability. Attached Figure Description

[0020] Figure 1 This is a process flow diagram of the PV / T combined air source heat pump system of the present invention; Figure 2 Flowchart for multi-objective optimized operation control method; In the diagram: 100, PV / T collector array; 200, air source heat pump; 300, hot water storage tank; 400, collector circulation pump; 500, fan coil unit; 610, ultrasonic heat meter; 620, first three-way valve; 630, second three-way valve. Detailed Implementation

[0021] The technical solution of the present invention will be further described in detail below through specific embodiments and in conjunction with the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustrating and explaining the present invention and are not intended to limit the present invention in any way. The accompanying drawings in the present invention are only for describing the embodiments and for facilitating understanding and use, and are not intended to limit the present invention in any way.

[0022] As described in the background section, this embodiment addresses the problems of existing PV / T combined air source heat pump systems, such as design parameters relying on empirical values, lack of optimization methods for specific operating conditions, and lack of coordinated control among subsystems during operation. It provides a multi-objective optimization operation control method for PV / T combined air source heat pump systems.

[0023] This embodiment uses a classroom on the middle floor of a teaching building in a certain city as an example to build a PV / T combined air source heat pump system. The classroom is 11.25m long, 8m wide, and 3.3m high, with a south-facing window-to-wall ratio of 0.36 and a north-facing window-to-wall ratio of 0.48. The heating season is from December 1st to February 28th of the following year, with heating hours from 7:00 to 22:00, and a room design temperature of 22℃. According to building dynamic energy consumption simulation, the average heat load of this room during the heating season is 2.75kW, the maximum instantaneous heat load is 6.89kW, and the design thermal index is 76.52W / m².

[0024] The composition and main equipment parameters of the PV / T combined air source heat pump system are as follows: (1) PV / T collector array 100: It consists of 30 monocrystalline silicon photovoltaic-thermal integrated flat plate collectors, adopting a modular array structure of "series first, then parallel". Every 15 collectors are connected in series to form an independent branch, and the two branches are connected in parallel. The total flow channel length of a single branch is 15.75m. The two branches are arranged in the same direction to ensure hydraulic balance. The collectors are installed facing due south with an installation tilt angle of 38°. The anodized aluminum alloy integral load-bearing frame and laser-cut perforated metal truss are used to realize the distributed transfer of gravity load and wind load. The parameters of a single collector are: open circuit voltage 48.61V, short circuit current 10.30A, maximum power 375W, maximum power point voltage 38.89V, maximum power point current 9.65A, thermal power 1200W, working pressure 1.2MPa, flow channel volume 1.6L, weight 32kg, and dimensions 1.9m×0.9m×0.045m.

[0025] (2) Air source heat pump 200: including evaporator, compressor, condenser and throttle valve, extracts heat from ambient air and improves the heat energy quality based on reverse Carnot cycle, and ensures continuous operation of the system on cloudy days or at night.

[0026] (3) Hot water storage tank 300: volume 2m³, heat dissipation coefficient 0.4W / (m²·K), used to store hot water generated by solar thermal conversion, and balance the instability and intermittency of solar energy.

[0027] (4) Heat collection circulation pump 400: rated flow rate 13L / min, rated head 5m, start and stop controlled by temperature difference, and prevent pipeline freezing in cold working conditions.

[0028] (5) Fan coil unit 500: air volume 2000m³ / h, heat 15000W, input power 100W, using hot water provided by PV / T system or hot water heated by heat pump to output hot air for heating.

[0029] (6) Measurement and control components: Ultrasonic heat meter 610 (working pressure ≤1.6MPa, temperature difference range 3~75K) is used to measure the temperature and flow rate of circulating fluid; the first solenoid valve is located in the heat collection circuit, the outlet of the hot water storage tank is connected to the main circuit via the first three-way valve 620, the outlet of the air source heat pump heating branch is connected to the main circuit via the second three-way valve 630, and the second solenoid valve is located in the air source heat pump heat exchange circuit.

[0030] The multi-objective optimization operation control method includes the following steps: Step S1: Establish a simulation model.

[0031] Meteorological data (dry-bulb temperature, wet-bulb temperature, dew point temperature, solar radiation intensity, solar radiation angle, and relative humidity, etc.) for typical meteorological years in the region were acquired to establish a dynamic simulation model of the system. The PV / T collector model was established based on energy conservation: total solar radiation... G The energy transmitted through and reflected by the glass is absorbed by the photovoltaic cells. αG Equivalent to converting electrical energy E pv Absorbing and utilizing heat energy Q T Heat loss to the environment Q L The sum of these values, with glass transmittance taken as 0.95 and reflectivity as 0.05, photovoltaic cell heat absorption rate taken as 0.92 and reflectivity as 0.08; and the photovoltaic maximum power point efficiency. or m = or m,ref - m t ( T pv + T ref ),in, or m,ref This represents the maximum power point efficiency under standard operating conditions. m t The temperature decay coefficient is T pv This refers to the actual temperature of the battery. T ref This refers to the operating temperature under standard conditions. Temperature decay coefficient. m t Take 0.3% to 0.5%; heat loss Q L = U L ( T pv - T a ), U L It is the heat loss coefficient of photovoltaic cells.T a The ambient temperature is given; where the convective heat transfer coefficient is... h cv =5.7 + 3.8 v ( v (Wind speed, m / s), sky temperature T sky =0.0552 The energy balance equation for the solar collector is: ; in A C For the area of ​​light intake; F R For collector migration factor; c p Specific heat capacity of the fluid; For fluid mass; t out The fluid outlet temperature; t in This refers to the fluid inlet temperature.

[0032] The hot water storage tank adopts a layered model, and the energy conservation equations for each layer node are as follows: ; in m j For node quality; Q in,j The heat power flowing into the node; Q out,j The heat power flowing out of the node; Q loss,j This refers to the heat loss of the node to the environment. Q cond,j This is for heat conduction between adjacent layers.

[0033] Considering heat loss from the water tank wall Thermal conduction between adjacent layers, where UA j The heat loss coefficient at the nodes, T j For the first j The temperature of the water layer, T amb The ambient temperature outside the water tank is used. Pumps and fans are modeled using power-flow characteristic curves; building loads are calculated from the building model combined with personnel, equipment, lighting, and work / rest schedules. The simulation makes the following simplified assumptions: fluid friction and heat loss are not considered; fluid temperature and mass flow rate are the same at the same cross-section; equipment performance parameters are constant; fluid properties varying with temperature and the effects of dust obstruction are ignored; the collector array is considered a single unit.

[0034] Step S2: Determine the evaluation indicators.

[0035] Using the annual cost Z as an economic evaluation index, ; in L 0 The initial investment in the system (including the purchase cost of air source heat pumps, fan coil units, water pumps, water tanks, PV / T collectors, pipes, inverters, and exhaust heat recovery devices). i Using the benchmark discount rate, n For system lifespan, L 0 For the initial investment in the system, C Annual operating costs; based on system carbon emissions Q CO2 As an indicator for evaluating environmental benefits Q CO2 = W p × f CO2 In the formula, W p Power consumption over the system's lifecycle f CO2 It is a carbon emission factor.

[0036] Step S3: Construct a multi-objective optimization objective function.

[0037] Construct the objective function y = w 1 × Z + w 2 × Q CO2 In the formula, w 1 , w 2 These are the weighting coefficients for annual cost and carbon emissions, respectively. Annual cost reflects the economic cost of the system, while carbon emissions reflect the environmental impact of the system.

[0038] Step S4: Parameter optimization.

[0039] Using the installation tilt angle, azimuth angle, collector area, hot water storage tank volume, and rated power of the air source heat pump as optimization variables, the objective function is determined through the automatic coupling interface between the optimization software and the system dynamic simulation model. y With minimization as the objective, the Hooke-Jeeves direct search algorithm was used for iterative optimization to obtain the optimal parameter combination: installation tilt angle 16°, azimuth angle -1°, collector area 25m², hot water storage tank volume 0.04m³, and air source heat pump rated power 3.95kW.

[0040] Step S5: Mode-based operation control.

[0041] Configure and run the system according to the above optimal parameter combination, and execute the following controls during operation: ①Heat collection control: The outlet water temperature of the PV / T collector array is compared with the water temperature of the hot water storage tank in real time. When the temperature difference between the two is greater than the first set temperature difference of 7℃, the first solenoid valve is opened and the heat collection circulation pump is started, and the PV / T collector array starts heat collection operation; if the temperature difference drops to less than the second set temperature difference of 2℃ after operation, the heat collection circulation pump and the first solenoid valve are turned off.

[0042] ② Auxiliary heating control: When the water temperature at the top of the hot water storage tank is not lower than the set supply water temperature of 45℃, the first three-way valve and the second three-way valve are controlled to open the heating branch (i.e., outlet 2 of the first three-way valve and the second three-way valve are open, and outlet 3 is closed), and the second solenoid valve is closed. The heating circulation pump and the air source heat pump side water pump do not work, and the hot water in the hot water storage tank is driven by the heating water pump to directly heat the water. When the water temperature in the hot water storage tank is lower than 45℃, the first three-way valve and the second three-way valve are controlled to cut off the heating branch and open the air source heat pump heating branch (i.e., outlet 3 is open, and outlet 2 is closed), and the second solenoid valve is opened to start the heating circulation pump and the heating water pump. The air source heat pump provides auxiliary heating for the water in the hot water storage tank.

[0043] ③ Terminal temperature control: When the indoor temperature is lower than the first set room temperature of 21℃, the heating water pump and fan coil unit are started to heat the room; when the indoor temperature is higher than the second set room temperature of 23℃, the fan coil unit and heating water pump are turned off to maintain the indoor temperature at 22±1℃.

[0044] ④ Power distribution and control: The photovoltaic power generated by the PV / T collector array is given priority to the use of the system's electrical equipment. The surplus power is output to the grid through the photovoltaic power generation grid-connected unit, and the insufficient power generation is supplemented by the grid power.

[0045] In one embodiment, the parameter values ​​in steps S2 and S3 are further defined: the benchmark discount rate. i Take 5.5%, system lifespan n Take 20 years; carbon emission factor f CO2 Take 0.5 kg / kWh. Objective function. y =0.7×Z+0.3× Q CO2 That is, the weighting factor of the annual cost value. w 1 Take 0.7 as the weighting coefficient for carbon emissions. w 2Taking 0.3: Annual cost reflects the economic cost of the system and is the most important factor. Minimizing annual cost can reduce the system's operation and maintenance costs and improve economic efficiency. Carbon emissions reflect the system's environmental impact. Minimizing carbon emissions can reduce negative environmental impacts and achieve sustainable development. The initial investment price for the system is based on: air source heat pump 0.6 yuan / W heating capacity, fan coil unit 1000 yuan / unit, water pump 200 yuan / unit, water tank 1000 yuan / m³, PV / T collector 1200 yuan / m², pipe 10 yuan / m, inverter 2000 yuan / unit, exhaust heat recovery including fan 1600 yuan / unit.

[0046] In one embodiment, the optimization process of the Hooke-Jeeves direct search algorithm in step S4 is further explained. The optimization is performed in two steps: First, global search: input the initial values ​​of each optimization variable and the grid spacing Δ. k and iteration accuracy e The global search point set is obtained through grid search. G k The second step is local search: using a coordinate search matrix. (in s i Let the search step size be denoted by . e i Using the unit vectors of the coordinate axes, a local search is performed along each coordinate axis direction on the global search point set obtained in the first step until the optimal value of the objective function is found. The initial values ​​and search ranges of each optimization variable are shown in the table below:

[0047] The optimization process shows that the installation tilt angle decreases stepwise with the number of simulations, stabilizing at around 16° after approximately the 85th simulation; the azimuth angle stabilizes at around -1° after approximately the 80th simulation; the collector area stabilizes at around 25m² after approximately the 80th simulation; and the hot water storage tank volume and the rated power of the air source heat pump stabilize at 0.04m³ and 3.95kW, respectively, after approximately the 100th simulation. Since the optimization of this system is a multidimensional continuous variable optimization problem with a complex and difficult-to-differentiate objective function, the Hooke-Jeeves direct search algorithm is adopted. This algorithm requires no derivative information of the objective function, has fewer parameters, is easy to implement, and has high local search efficiency.

[0048] In one embodiment, the verification of the system dynamic simulation model in step S1 is further explained. Measured operating data of the PV / T system were collected for four consecutive days under similar weather conditions. Monitoring parameters included fluid inlet and outlet temperatures, solar radiation intensity, outdoor temperature, flow rate, and system power generation. The measured results showed that the flow rate remained relatively stable throughout the day, generally between 1360 and 1510 kg / h; the inlet water temperature gradually increased from approximately 30°C at 8:00 AM to 47.8°C at 3:00 PM, and then began to decrease; the outlet water temperature gradually increased from approximately 32°C at 8:00 AM to approximately 64°C around 1:30 PM, and then decreased, with the outlet water temperature consistently higher than the inlet water temperature, indicating effective heat collection by the system; and the power generation gradually increased from approximately 1.6 kW at 8:00 AM to approximately 7.5 kW around 12:30 PM, and then decreased. The measured water temperature and power generation were compared hourly with the simulation results. The daily variation trends of the two were consistent, both reaching their peak in the afternoon. The peak time was consistent with the daily distribution of solar radiation intensity. The simulated values ​​could reflect the variation trend of the experimental values ​​well. Based on this, it was confirmed that the dynamic simulation model of the system was effective and could be used for iterative optimization in step S4.

[0049] The system was configured according to the obtained optimal parameter combination, and dynamic simulations were conducted for the heating season and throughout the year. Before optimization (initial design parameters), the initial investment of the system was 52,748 yuan, the annual cost was 2,726.09 yuan, and the objective function was 1,467.86 yuan. After optimization, the initial investment of the system was 43,370 yuan, the annual cost was 1,807.05 yuan, and the objective function was 896.12 yuan, representing reductions of 17.78%, 33.71%, and 38.95%, respectively. After optimization, the system's electricity consumption during the heating season was 1,620.15 kWh; the cumulative photovoltaic power generation for the year was 4,167.02 kWh, and the municipal power supply was 1,188.24 kWh, resulting in a 16.27% decrease in net electricity consumption compared to before optimization; the annual carbon emissions decreased by 16.27% compared to before optimization, and the net operating cost decreased by 19.40%. After optimization, the PV / T power generation efficiency fluctuated significantly throughout the year, remaining stable between 17.6% and 18.1% from March to June, reaching a peak of nearly 18.8% in November, and exceeding the efficiency before optimization in most months. In comparison, the initial investment of a pure air source heat pump heating scheme (without PV / T) is RMB 14,548, the annual cost is RMB 2,008, and the objective function is RMB 1,702.78. Although the initial investment of the PV / T combined air source heat pump scheme of the present invention is higher, thanks to the photovoltaic power generation revenue and significant emission reduction, the objective function is 13.8% lower than that of the pure heat pump scheme, demonstrating the advantages of the present invention in terms of comprehensive economic and environmental benefits.

[0050] The above description is a detailed description of the preferred embodiments of the present invention. However, the embodiments are not intended to limit the scope of the patent application of the present invention. All equivalent changes or modifications made under the technical spirit of the present invention should fall within the patent scope covered by the present invention.

Claims

1. A multi-objective optimized operation control method for a PV / T combined air source heat pump system, characterized in that, The PV / T combined air source heat pump system includes a PV / T collector array, a hot water storage tank, an air source heat pump, a fan coil unit, a collector circulation pump, a heating circulation pump, a heating water pump, a first solenoid valve, a first three-way valve, a second three-way valve, a second solenoid valve, and a photovoltaic power generation grid-connected unit. The first solenoid valve is located on the collector circuit of the PV / T collector array. The outlet of the hot water storage tank is selectively connected to either the heating branch or the air source heat pump heating branch via the first three-way valve. The outlet of the air source heat pump heating branch is connected to the main circuit via the second three-way valve. The second solenoid valve is located in the heat exchange circuit of the air source heat pump. The multi-objective optimized operation control method includes the following steps: S1. Establish a simulation model: Obtain meteorological data for a typical meteorological year at the location of the target building, and establish a system dynamic simulation model including a PV / T collector model, a layered hot water storage tank model, an air source heat pump model, a water pump model, a fan model, and a building load model; S2. Determine the evaluation index: Use the annual cost Z as the economic evaluation index. ； In the formula, i Using the benchmark discount rate, n For system lifespan, L 0 For the initial investment in the system, C Annual operating costs; based on system carbon emissions Q CO2 As an indicator for evaluating environmental benefits Q CO2 = W p × f CO2 In the formula, W p Power consumption over the system's lifecycle f CO2 Carbon emission factor; S3. Construct a multi-objective optimization objective function: y = w 1 × Z + w 2 × Q CO2 In the formula, w 1 , w 2 These are the weighting coefficients for annual cost and carbon emissions, respectively. S4. Parameter optimization: Using the installation tilt angle, azimuth angle of the PV / T collector, collector area, hot water storage tank volume and rated power of the air source heat pump as optimization variables, and minimizing the objective function y as the objective, the Hooke-Jeeves direct search algorithm is used to call the system dynamic simulation model established in step S1 for iterative optimization to obtain the optimal parameter combination. S5. Configure and operate the PV / T combined air source heat pump system according to the optimal parameter combination. According to claim 1, the multi-objective optimization operation control method for a PV / T combined air source heat pump system is characterized in that step S5 executes the following control during operation: (1) Heat collection control: The outlet water temperature of the PV / T collector array is compared with the water temperature of the hot water storage tank in real time. When the temperature difference between the two is greater than the first set temperature difference, the first solenoid valve is opened and the heat collection circulation pump is started, and the PV / T collector array starts to collect heat. When the temperature difference is less than the second set temperature difference, the heat collection circulation pump and the first solenoid valve are closed. (2) Auxiliary heating control: When the water temperature at the top of the hot water storage tank is not lower than the set water supply temperature, the first three-way valve and the second three-way valve are controlled to open the heating branch and close the air source heat pump heating branch, and the second solenoid valve is closed, so that the hot water in the hot water storage tank is directly heated by the heating water pump; when the water temperature in the hot water storage tank is lower than the set water supply temperature, the first three-way valve and the second three-way valve are controlled to close the heating branch and open the air source heat pump heating branch, and the second solenoid valve is opened, so that the heating circulation pump and the heating water pump are started, and the air source heat pump provides auxiliary heating to the water in the hot water storage tank; (3) Terminal temperature control: When the indoor temperature is lower than the first set room temperature, the heating water pump and the fan coil unit are started to heat the room; when the indoor temperature is higher than the second set room temperature, the fan coil unit and the heating water pump are turned off. (4) Power distribution and control: The photovoltaic power generation of the PV / T collector array is given priority to the use of the system's electrical equipment. The surplus power is output through the photovoltaic power generation grid-connected unit, and the insufficient power generation is supplemented by the mains power.

2. The multi-objective optimization operation control method according to claim 1, characterized in that, In step S2, the benchmark discount rate i Take 5.5%, the system lifespan n Take 20 years; the carbon emission factor f CO2 Take 0.5 kg / kWh.

3. The multi-objective optimization operation control method according to claim 1, characterized in that, In step S3, the weighting coefficient of the annual cost value w 1 The weighting factor for carbon emissions is set to 0.

7. w 2 Take 0.

3.

4. The multi-objective optimization operation control method according to claim 1, characterized in that, In step S4, the optimization process of the Hooke-Jeeves direct search algorithm includes: first, performing a global search on each optimization variable with a set grid interval and iteration precision to obtain a global search point set; then, using a coordinate search matrix, performing a local search on the global search point set along each coordinate axis until the objective function converges to the optimal value.

5. The multi-objective optimization operation control method according to claim 1 or 5, characterized in that, In step S4, the search range for each optimization variable is: installation tilt angle 10°~70°, azimuth angle -20°~20°, collector area 1~100m², hot water storage tank volume 0.01~0.3m³, and air source heat pump rated power 2~10kW.

6. The multi-objective optimization operation control method according to claim 1, characterized in that, The first set temperature difference is 7°C, the second set temperature difference is 2°C, and the set water supply temperature is 45°C.

7. The multi-objective optimization operation control method according to claim 1, characterized in that, The first room temperature setting is 21°C, and the second room temperature setting is 23°C, so as to maintain the indoor temperature at 22±1°C.

8. The multi-objective optimization operation control method according to claim 1, characterized in that, The PV / T collector array consists of 30 photovoltaic-thermal integrated flat plate collectors. Every 15 collectors are connected in series to form an independent branch. The two branches are connected in parallel and are arranged in the same direction to ensure hydraulic balance.

9. The multi-objective optimization operation control method according to claim 1, characterized in that, Step S1 also includes a step of verifying the dynamic simulation model of the system using measured operating data: collecting measured data of the inlet water temperature, outlet water temperature and photovoltaic power generation of the PV / T collector array, and comparing them with the simulation results. When the trend of the simulated value and the experimental value are consistent, the dynamic simulation model of the system is confirmed to be effective.

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