Linkage system of photovoltaic energy storage system and heat pump air conditioner

Abstract

The invention discloses a linkage system of a photovoltaic energy storage system and a heat pump air conditioner. The linkage system comprises a data sensing layer, a communication network layer, a control strategy unit and a working condition operation unit. The data sensing layer comprises a data sensing layer and a communication network layer; the data sensing layer comprises an irradiance sensor and an assembly temperature sensor, the energy storage system is integrated with a battery management system and monitors SOC and SOH in real time, and the heat pump system is provided with a water supply temperature sensor, a return water temperature sensor and an indoor temperature and humidity sensor network; and the communication network layer adopts an RS485 bus to construct a Modbus-RTU protocol communication backbone network. Through a three-stage control architecture, the photovoltaic consumption rate is improved to 82.6%; the annual average COP of the heat pump is improved by 27.5%; the cycle life of the energy storage system is prolonged to 6500 times; and the indoor temperature fluctuation range is compressed to + / -0.3 DEG C.

Description

Technical Field

[0001] The present invention relates to the technical field of building energy system integration, and more specifically, to a linkage system between a photovoltaic energy storage system and a heat pump air conditioner. Background Art

[0002] In the field of building energy system integration, existing technical solutions generally adopt a simple coupling mode of "photovoltaic energy storage power supply + heat pump independent operation". This mode has the following three levels of technical defects: The photovoltaic energy storage system and the heat pump air conditioner system adopt a unidirectional power transmission architecture and lack a two-way data communication channel; Only the power supply source switching function is realized, and a multi-parameter collaborative control model is not established; The energy storage SOC management lacks a heat pump load prediction module, and the effective utilization rate of the energy storage system is less than 65%; The set value of the supply water temperature at the radiation end is fixed and not dynamically associated with the predicted photovoltaic power generation, resulting in a lag in thermal inertia compensation; The thermodynamic optimization space is wasted.

[0003] Regarding the problems in the related art, no effective solution has been proposed yet. Summary of the Invention

[0004] In view of the problems in the related art, the present invention proposes a linkage system between a photovoltaic energy storage system and a heat pump air conditioner to overcome the above-mentioned technical problems existing in the existing related art.

[0005] To this end, the specific technical solution adopted by the present invention is as follows:

[0006] A linkage system between a photovoltaic energy storage system and a heat pump air conditioner, comprising a data sensing layer, a communication network layer, a control strategy unit, and a working condition operation unit;

[0007] The data sensing layer includes a data sensing layer and a communication network layer;

[0008] The data sensing layer includes an irradiance sensor, a component temperature sensor, an energy storage system integrated battery management system, which real-time monitors SOC and SOH, and the heat pump system is configured with a supply water temperature sensor, a return water temperature sensor, and an indoor temperature and humidity sensor network;

[0009] The communication network layer constructs a Modbus-RTU protocol communication backbone network using an RS485 bus, and the data transmission parameters include: a photovoltaic predicted output curve; the real-time SOC state of the energy storage; the set value of the heat pump supply water temperature.

[0010] Preferably, the control strategy unit includes a day-ahead scheduling stage, a real-time optimization stage, and a second-level adjustment stage.

[0011] Preferably, the day-ahead scheduling stage generates irradiance prediction data based on the WRF meteorological model;

[0012] The heat pump load prediction algorithm is used as \(Q_{HP}=k1\cdot(T_{set}-T_{room})+k2\cdot\frac{dT_{out}}{dt}+k3\cdot\text{COP}_{pred}\);

[0013] where \(k1\), \(k2\) and \(k3\) are machine learning dynamic correction coefficients.

[0014] Preferably, the multi-objective optimization function established in the real-time optimization stage is:

[0015] \(\min\left(\alpha\cdot|T_{supply}^{opt}-T_{supply}^{set}|

[0016] +\beta\cdot\frac{P_{grid}}{P_{PV}}\right);

[0018] Constraint conditions: the indoor PMV index is maintained in the range of ±0.5, the energy storage SOC working window is controlled within 30 - 90%, and the heat pump compressor frequency adjustment rate ≤ 2Hz / s.

[0019] Preferably, the second-level adjustment stage uses a fuzzy PID controller to achieve three key adjustments:

[0020] The compressor frequency tracks the fluctuation of PV output

[0021] The opening of the electronic expansion valve compensates for the deviation of the supply water temperature

[0022] The dynamic allocation of the energy storage PCS power command.

[0023] Preferably, the operating condition unit includes a PV sufficient mode, a PV insufficient mode, and a no-PV mode.

[0024] Preferably, the PV sufficient mode includes starting a heat storage priority strategy: during the over-generation period from 13:00 to 15:00, the supply water temperature is increased to 45°C (standard mode 35°C), and the energy storage charging power is dynamically limited to

[0025] \(P_{chg}^{max}=\min(0.2C_{bat},\frac{P_{PV}-P_{HP}}{\eta_{inv}})\).

[0026] Preferably, the PV insufficient mode includes a load following strategy:

[0027] When 20% ≤ SOC < 60%, the supply water temperature set value is reduced proportionally;

[0028] When the SOC < 20%, switch to the valley electricity compensation mode: the heat pump COP is actively reduced by 0.3 to match the power grid supply curve.

[0029] Preferably, the off-grid PV mode performs optimal control of time-of-use electricity price:

[0030] During peak hours: maintain the basic water supply temperature;

[0031] During valley hours: start preheating the thermal energy storage tank and raise the water supply temperature to 40°C.

[0032] The beneficial effects of the present invention are achieved through a three-level control architecture: the PV accommodation rate is increased to 82.6%; the annual average COP of the heat pump is increased by 27.5%; the cycle life of the energy storage system is extended to 6500 times; the indoor temperature fluctuation range is compressed to ±0.3°C. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the following described drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0034] Figure 1 is a schematic structural diagram of a linkage system of a PV energy storage system and a heat pump air conditioner according to an embodiment of the present invention;

[0035] Figure 2 is a framework diagram of a linkage system of a PV energy storage system and a heat pump air conditioner according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0036] To further illustrate the embodiments, the present invention provides drawings. These drawings are part of the disclosure of the present invention. They are mainly used to illustrate the embodiments and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these contents, those of ordinary skill in the art should be able to understand other possible implementation manners and the advantages of the present invention. The components in the drawings are not drawn to scale, and similar component symbols are usually used to represent similar components.

[0037] According to an embodiment of the present invention, a linkage system of a PV energy storage system and a heat pump air conditioner is provided.

[0038] Embodiment 1:

[0039] As Figure 1-2 shown, the linkage system of a PV energy storage system and a heat pump air conditioner according to an embodiment of the present invention includes a data perception layer, a communication network layer, a control strategy unit, and a working condition operation unit;

[0040] The data perception layer includes a data perception layer and a communication network layer;

[0041] The data perception layer includes an irradiance sensor, a component temperature sensor, and an energy storage system integrated battery management system, which monitors the SOC and SOH in real time with a resolution of 0.1%. The heat pump system is equipped with a supply water temperature sensor, a return water temperature sensor, and an indoor temperature and humidity sensor network;

[0042] The communication network layer constructs a Modbus-RTU protocol communication backbone network using the RS485 bus. The data transmission parameters include: a photovoltaic power prediction curve with a 15-minute resolution; the real-time SOC status of the energy storage refreshed at a frequency of 1 minute; and a heat pump supply water temperature set value with a dynamically adjustable range of 20 - 50 °C for heating or 7 - 15 °C for cooling.

[0043] Example 2:

[0044] As Figure 1-2 shown, the control strategy unit includes a day-ahead scheduling stage, a real-time optimization stage, and a second-level adjustment stage.

[0045] In the day-ahead scheduling stage, irradiance prediction data is generated based on the WRF meteorological model;

[0046] The heat pump load prediction algorithm is used as \(Q_{HP}=k1\cdot(T_{set}-T_{room}) + k2\cdot\frac{dT_{out}}{dt}+k3\cdot\text{COP}_{pred}\);

[0047] In the formula, k1 to k3 are machine learning dynamic correction coefficients, and their update period is 6h.

[0048] In the real-time optimization stage, a multi-objective optimization function is established:

[0049] \(min\left(\alpha\cdot|T_{supply}^{opt}-T_{supply}^{set}|

[0050] +\beta\cdot\frac{P_{grid}}{P_{PV}}\right)\);

[0052] Constraints: The indoor PMV index is maintained within the range of ±0.5, the energy storage SOC working window is controlled within 30 - 90%, and the heat pump compressor frequency adjustment rate ≤ 2Hz / s.

[0053] Supply water temperature dynamic setting algorithm:

[0054]

[0055] Example 3:

[0056] As shown Figure 1-2 in the figure, the second-level adjustment stage adopts a fuzzy PID controller to achieve three key regulations:

[0057] The compressor frequency tracks the fluctuation of photovoltaic output, and the specific adjustment bandwidth is 0.5 - 2 Hz;

[0058] The opening of the electronic expansion valve compensates for the water supply temperature deviation, and the specific response time < 5 s;

[0059] The power command of the energy storage PCS is dynamically allocated, and the specific decision-making period is 200 ms.

[0060] The working condition operation unit includes a photovoltaic sufficient mode, a photovoltaic insufficient mode, and a no-photovoltaic mode.

[0061] The photovoltaic sufficient mode includes starting the heat storage priority strategy: during the over-generation period from 13:00 to 15:00, the water supply temperature is increased to 45 °C (standard mode 35 °C), and the dynamic limit of the energy storage charging power is P_{chg}^{max}=\min(0.2C_{bat},\frac{P_{PV}-P_{HP}}{η_{inv}}).

[0062] The photovoltaic insufficient mode includes a load following strategy:

[0063] When 20% ≤ SOC < 60%, the water supply temperature set value is reduced proportionally, and the specific set value is -0.5 °C / %SOC;

[0064] When SOC < 20%, switch to the valley electricity compensation mode: the heat pump COP is actively reduced by 0.3 to match the grid power supply curve.

[0065] The no-photovoltaic mode executes the time-of-use electricity price optimal control:

[0066] During the peak time from 08:00 to 22:00: maintain the basic water supply temperature, specifically 32 °C for heating or 12 °C for cooling;

[0067] During the valley time from 22:00 to 08:00: start the preheating of the heat storage tank and increase the water supply temperature to 40 °C.

[0068] In summary, by means of the above technical solutions of the present invention, the following are achieved through a three-level control architecture: the photovoltaic consumption rate is increased to 82.6%, while the traditional scheme is 58.3%; the annual average COP of the heat pump is increased by 27.5%, specifically from 3.2 to 4.08; the cycle life of the energy storage system is extended to 6500 times; the indoor temperature fluctuation range is compressed to ±0.3 °C, while the traditional indoor temperature fluctuation range is ±1.2 °C.

[0069] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A linkage system for a photovoltaic energy storage system and a heat pump air conditioner, characterized in that, It includes a data perception layer, a communication network layer, a control strategy unit, and a working condition operation unit; The data perception layer includes a data perception layer and a communication network layer; The data perception layer includes an irradiance sensor, a component temperature sensor, an energy storage system integrated battery management system, which monitors SOC and SOH in real time. The heat pump system is configured with a supply water temperature sensor, a return water temperature sensor, and an indoor temperature and humidity sensor network; The communication network layer constructs a Modbus-RTU protocol communication backbone network using the RS485 bus. The data transmission parameters include: the predicted output curve of the photovoltaic; The real-time SOC state of the energy storage; the set value of the heat pump supply water temperature.

2. The linkage system of a photovoltaic energy storage system and a heat pump air conditioner according to claim 1, wherein, The control strategy unit includes a day-ahead scheduling stage, a real-time optimization stage, and a second-level adjustment stage.

3. The linkage system of a photovoltaic energy storage system and a heat pump air conditioner according to claim 2, characterized in that, In the day-ahead scheduling stage, irradiance prediction data is generated based on the WRF meteorological model; The heat pump load prediction algorithm function is used as Q_{HP}=k1\cdot(T{set}-T{room})+k2\cdot\frac{dT{out}}{dt}+k3\cdot\text{COP}{pred}; In the formula, k1, k2, and k3 are machine learning dynamic correction coefficients.

4. A linkage system between a photovoltaic energy storage system and a heat pump air conditioner according to claim 3, characterized in that, In the real-time optimization stage, a multi-objective optimization function is established as: min\left(\alpha\cdot|T_{supply}^{opt}-T_{supply}^{set}|+\beta\cdot\frac{P_{grid}}{P_{PV}}\right); Constraint conditions: the indoor PMV index is maintained in the range of ±0.5, the energy storage SOC working window is controlled at 30-90%, and the adjustment rate of the heat pump compressor frequency ≤ 2Hz / s.

5. The linkage system of a photovoltaic energy storage system and a heat pump air conditioner according to claim 4, characterized in that, In the second-level adjustment stage, a fuzzy PID controller is used to achieve three key adjustments: The compressor frequency tracks the fluctuation of the photovoltaic output; The opening of the electronic expansion valve compensates for the deviation of the supply water temperature; The dynamic distribution of the energy storage PCS power command.

6. The linkage system of a photovoltaic energy storage system and a heat pump air conditioner according to claim 5, characterized in that, The working condition operation unit includes a photovoltaic sufficient mode, a photovoltaic insufficient mode, and a no-photovoltaic mode.

7. The linkage system of a photovoltaic energy storage system and a heat pump air conditioner according to claim 6, characterized in that, The photovoltaic sufficient mode includes starting a heat storage priority strategy: during the over-generation period from 13:00 to 15:00, the supply water temperature is raised to 45°C. The dynamic limit formula for the energy storage charging power is P_{chg}^{max}=\min(0.2C_{bat},\frac{P_{PV}-P_{HP}}{η_{inv}}).

8. The linkage system between a photovoltaic energy storage system and a heat pump air conditioner according to claim 7, wherein, The photovoltaic insufficient mode includes a load following strategy: When 20% ≤ SOC < 60%, the set value of the supply water temperature is reduced proportionally; When SOC < 20%, it switches to the valley electricity compensation mode: the heat pump COP is actively reduced by 0.3 to match the grid power supply curve.

9. The linkage system of a photovoltaic energy storage system and a heat pump air conditioner according to claim 8, characterized in that, The no-photovoltaic mode executes the optimal control of time-of-use electricity price: Peak time: Maintain the basic supply water temperature; Valley time: Start preheating the heat storage tank and raise the supply water temperature to 40°C.

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