Intelligent Control Method for Building Photovoltaic Curtain Walls Based on the Linkage of Light Transmittance and Energy Storage Status

Abstract

This invention discloses an intelligent control method for building photovoltaic (PV) curtain walls based on the linkage between light transmittance and energy storage status. This invention relates to the field of PV curtain wall control technology. By real-time monitoring of PV array power generation, energy storage system state of charge (SOC), and building load data, a SOC change curve is constructed to divide the power into high, medium, and low energy zones. A global control mode is automatically matched, maximizing economic benefits, self-balancing, or ensuring energy security. Based on this, an objective function is established with grid purchase cost, temperature deviation penalty, and battery loss as comprehensive objectives. A rolling optimization strategy is used to solve for the optimal light transmittance, energy storage charging and discharging power, and load adjustment under constraints, forming a collaborative control instruction set and issuing it for execution. This achieves deep coupling control of the PV curtain wall's light transmittance characteristics and the energy storage system, balancing building energy efficiency, economic benefits, and energy security, and improving the overall operational performance and intelligence level of the building PV system.

Description

Technical Field

[0001] This invention belongs to the field of photovoltaic curtain wall control technology, specifically, it relates to an intelligent control method for building photovoltaic curtain walls based on the linkage between light transmittance and energy storage status. Background Technology

[0002] As an organic integration of building envelope and distributed energy carrier, building-integrated photovoltaics (BIPV) technology has become a key path to reduce carbon emissions from building operations.

[0003] Existing technologies for intelligent control of building photovoltaic (PV) curtain walls typically suffer from numerous drawbacks and shortcomings. These primarily manifest as a lack of systematic coordination and adaptive optimization mechanisms. Traditional methods often treat PV curtain walls, energy storage systems, and building loads as independent units for control. The transmittance adjustment of PV curtain walls often relies on fixed strategies or single illumination parameters, failing to link with the real-time state of charge of the energy storage system, leading to low energy utilization efficiency. For example, when energy storage capacity is sufficient, the curtain wall may maintain high transmittance to maximize power generation, but excess energy cannot be effectively stored or utilized, resulting in wasted solar power. Conversely, when energy storage capacity is insufficient, curtain wall control fails to prioritize charging needs, affecting system power supply reliability. Furthermore, control modes are usually fixed or manually set, unable to dynamically switch according to energy storage status. For instance, there is a lack of overcharge prevention strategies during high charge periods, and a failure to switch to energy-saving mode in a timely manner during low charge periods, increasing system operational risks. Secondly, in terms of economics, the minimization of the building's overall operating costs is ignored. Factors such as real-time electricity prices, indoor temperature comfort, and battery wear are not integrated, resulting in higher electricity costs, inaccurate temperature control, and shortened energy storage life. Control commands are mostly based on static or offline planning, lacking rolling optimization and real-time feedback mechanisms, making it difficult to cope with dynamic changes in dynamic parameters, causing control lags or deviations. For example, if the light transmittance is not adjusted in time when there are sudden weather changes, it will affect the balance between power generation and indoor lighting, thus leading to power imbalance and system instability.

[0004] To address the aforementioned issues, this invention proposes an intelligent control method for building photovoltaic curtain walls based on the linkage between light transmittance and energy storage status. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides an intelligent control method for building photovoltaic curtain walls based on the linkage between light transmittance and energy storage status, which solves the problems of high operating costs and low energy efficiency caused by insufficient coordination between photovoltaic curtain walls, energy storage and load in existing technologies.

[0006] The objective of this invention can be achieved through the following technical solutions: A smart control method for building photovoltaic curtain walls based on the linkage between light transmittance and energy storage status, the method comprising: Step 1: Determine the power generation of the photovoltaic array, the state of charge of the energy storage system, and the building load, all aligned with the time frame. Step 2: Perform power zoning based on the state of charge aligned with the time, and automatically match the current operating state of the photovoltaic curtain wall to the pre-built global control mode based on the power zoning. Step 3: Construct an objective function with the goal of minimizing the overall building operating cost, perform rolling optimization in combination with the corresponding global control mode, and generate control instructions for photovoltaic curtain walls, energy storage systems, and building loads, which are then combined into the optimal set of control instructions. Step four: Issue the optimal control command set to the photovoltaic curtain wall actuator, energy storage system converter, and building load controller to achieve coordinated control of the curtain wall, energy storage, and load.

[0007] As a further aspect of the present invention, the specific method for determining the power generation of the photovoltaic array aligned with the time, the state of charge of the energy storage system, the building load, and the solar irradiance in step one is as follows: Determine the current time, denoted as t1, and obtain the total number of times within the monitoring period T, denoted as j, where the monitoring period T is the time period preset by the operator; Taking time t1 as the start time of the monitoring period T, the power generation of the photovoltaic array, the state of charge of the energy storage system, and the building load are continuously monitored for one monitoring period T, and the end time is recorded as tj. Determine the power generation, state of charge, and building load corresponding to j time points, and construct data sequences respectively, denoted as power generation sequence F1, F2, ..., Fj, state of charge sequence H1, H2, ..., Hj, and building load sequence G1, G2, ..., Gj.

[0008] As a further aspect of the present invention, the specific method for performing charge partitioning based on time-aligned state of charge in step two is as follows: Extract the charged state sequence H1, H2, ..., Hj; Construct a two-dimensional coordinate system with time as the horizontal axis and state of charge as the vertical axis. Plot the state of charge sequence H1, H2, ..., Hj with time points in the two-dimensional coordinate system to generate a state of charge change curve, denoted as W_H. Determine the scales for 75% and 25% charge state on the vertical axis, and construct straight lines parallel to the horizontal axis and perpendicular to the vertical axis through the two scales respectively, denoted as the high charge scale line L1 and the low charge scale line L2. When the state of charge change curve W_H is higher than the high charge scale line L1, the charge zone is determined to be a high charge zone. When the state of charge change curve W_H is lower than or equal to the high charge scale line L1 and higher than the low charge scale line L2, the charge zone is determined to be the medium charge zone. When the state of charge change curve W_H is lower than the low charge scale line L2, the charge zone is determined to be a low charge zone.

[0009] As a further aspect of the present invention, the specific method for automatically matching the current operating state of the photovoltaic curtain wall to the pre-constructed global control mode based on power zoning in step two is as follows: When the power zone is a high-charge zone, the current operating state of the photovoltaic curtain wall is adjusted to the mode of maximizing economic benefits, so as to transmit power to the grid with the maximum discharge power of the energy storage system. When the power distribution zone is a medium-Dutch power distribution zone, the power generation of the photovoltaic array of the current photovoltaic curtain wall and the building load are extracted based on the power generation sequence F1,F2,...,Fj and the building load sequence G1,G2,...,Gj. If the power generation is greater than the building load, the mode is adjusted to maximize economic benefits. Conversely, the system will switch to a self-balancing mode, supplying power to the building at the maximum discharge power of the energy storage system. When the power zone is a low-charge zone, the regulation is set to energy security mode, using the photovoltaic array's power generation to charge the energy storage system.

[0010] As a further aspect of the present invention, the objective function in step three, which aims to minimize the overall operating cost of the building, is specifically expressed as follows: MJ=C_grid×P_grid+α×|T_room-T_set|+β×Wear_batt; Wherein, C_grid is the real-time electricity price, obtained from the power grid; P_grid is the power exchanged between the photovoltaic curtain wall and the power grid, which is considered a known value; α is the temperature deviation penalty coefficient preset by the operator; T_room is the indoor temperature; T_set is the set temperature; β is the battery loss cost coefficient, which is considered a known value; and Wear_batt is the battery cycle loss cost, which is considered a known value.

[0011] As a further aspect of the present invention, in step three, the specific method for generating photovoltaic curtain wall control instructions, energy storage system control instructions, and building load control instructions by performing rolling optimization in conjunction with the corresponding global control mode is as follows: Obtain a preset rolling optimization time domain window, wherein the duration of the rolling optimization time domain window is less than the monitoring period T. Perform the following operations within each rolling optimization time domain window within the monitoring period T: The global control mode of the photovoltaic curtain wall, the power generation sequence F1, F2, ..., Fj, the building load sequence G1, G2, ..., Gj, the state of charge sequence H1, H2, ..., Hj, and the real-time electricity price C_grid obtained from the grid are used as inputs for rolling optimization. An optimization problem is constructed with the objective function MJ as the goal. The decision variables are set as the target light transmittance τ of the photovoltaic curtain wall, the adjustment amount of the building load P_load, and the charging and discharging power P_batt of the energy storage system. The charging and discharging power P_batt is positive for discharging and negative for charging. Based on the global control mode and physical limitations, optimization constraints are set, including the energy storage system charging and discharging power constraints: P_batt_min≤P_batt≤P_batt_max, where P_batt_min and P_batt_max are the minimum and maximum allowable power; Energy storage system state of charge constraint: H_min≤H≤H_max, where H_min and H_max are preset safe state of charge ranges; Photovoltaic curtain wall transmittance adjustment constraint: τ_min≤τ≤τ_max, where τ_min and τ_max are the minimum and maximum transmittance allowed by the physical structure of the photovoltaic curtain wall; Power balance constraint: P_pv(τ) + P_batt + P_grid = G - P_load, where P_pv(τ) is the real-time power generation of the photovoltaic array at the corresponding transmittance τ, and G is the building load; Based on a multi-objective optimization solver, and in combination with the above optimization constraints, the objective function MJ is iteratively solved within the rolling optimization time window. Output the optimal decision variable values ​​that minimize the objective function MJ, including the target transmittance τ*, the optimal charging and discharging power of the energy storage system P_batt*, and the optimal adjustment amount of the building load P_load*.

[0012] As a further aspect of the present invention, in step three, the combined target transmittance τ*, the optimal charging and discharging power P_batt* of the energy storage system, and the optimal adjustment amount P_load* of the building load are denoted as the set of optimal control instructions R={τ*,P_batt*,P_load*} associated within the corresponding rolling optimization time-domain window.

[0013] As a further aspect of the present invention, in step four, the specific method for issuing the optimal control command set to the photovoltaic curtain wall actuator, the energy storage system converter, and the building load controller to achieve coordinated control of the curtain wall, energy storage, and load is as follows: Receive the optimal set of control instructions R; The target transmittance τ* is converted into a drive signal that can be recognized by the photovoltaic curtain wall actuator, and sent to the photovoltaic curtain wall actuator to adjust the light-transmitting unit of the curtain wall to the specified transmittance; The optimal charging and discharging power P_batt* of the energy storage system is converted into a power setting command for the energy storage system converter and sent to the energy storage system converter to control the energy storage system to charge and discharge at the specified power. The optimal adjustment amount of building load P_load* is converted into an adjustment command for the building load controller and sent to the building load controller to execute the building load adjustment; Real-time monitoring of the light transmittance of the photovoltaic curtain wall, the actual charging and discharging power and state of charge of the energy storage system, and the feedback signals of the actual power of the building load are compared with the issued instructions; If the actual state is detected to deviate from the command by more than a preset threshold, the process of recalculating and issuing the control command is triggered, and the current moment is used as the start moment of the rolling optimization time domain window to perform a rolling optimization.

[0014] The beneficial effects of this invention are: This invention achieves integrated intelligent control of energy production, storage, and consumption by linking and coordinating photovoltaic curtain walls, energy storage systems, and building loads through real-time data and collaborative optimization. Its advantages lie in the introduction of a zone matching mechanism based on energy storage status, which can adaptively switch global control modes and generate the optimal instruction set in real time through rolling optimization. This enhances the self-balancing ability and operational economy of building energy, effectively mitigates fluctuations in photovoltaic power generation, maximizes the self-consumption ratio, reduces dependence on the external power grid and electricity costs, and extends the lifespan of energy storage through linkage control, thereby enhancing the overall resilience and sustainability of the building energy system. This invention establishes a clear starting point for the monitoring cycle and a data recording method to construct a time-aligned sequence of power generation, state of charge, and building load. Its core advantage lies in ensuring the synchronization and integrity of data in the time dimension. Based on a standardized data acquisition framework, it effectively avoids data analysis deviations caused by time misalignment or monitoring interruptions, facilitating subsequent accurate assessment of system operating status and analysis of energy supply and demand. Through the synchronous acquisition of multi-parameter sequences within the complete cycle, it comprehensively reflects the dynamic correlation between photovoltaic systems, energy storage, and loads. This invention monitors the battery's state of charge in real time and precisely divides it into high, medium, and low charge ranges. By combining real-time comparison of power generation and building load, it constructs an adaptive, multi-level intelligent control strategy. The advantage lies in achieving dynamic matching between the photovoltaic curtain wall's operating mode and the actual battery storage state. This ensures that when the battery has ample charge, economic benefits are prioritized; when the charge is moderate, the mode is flexibly switched according to power generation and load conditions; and when the charge is insufficient, energy supply security is automatically guaranteed. This enhances the system's autonomous control capability and operating efficiency, balancing economic benefits and power supply reliability while extending battery life and optimizing energy utilization efficiency. This invention constructs a comprehensive cost objective function with real-time electricity price, temperature comfort, and battery loss as the core, and adopts a rolling optimization mechanism to dynamically coordinate the light transmittance of photovoltaic curtain walls, energy storage charging and discharging, and building load adjustment. This achieves a multi-objective balance of economy, comfort, and equipment durability. The advantages are that it makes full use of real-time data and constraints to ensure the feasibility and safety of the solution, significantly reduces the long-term operating cost of buildings through multi-variable collaborative optimization, and gives the system the ability to respond quickly to dynamic environments through rolling optimization, thereby improving energy utilization efficiency and overall control flexibility. This invention achieves efficient coordinated control of photovoltaic curtain walls, energy storage systems, and building loads by receiving the optimal set of control commands and automatically converting them into identifiable drive signals for each actuator. Its advantages lie in ensuring reliable execution by monitoring feedback signals in real time and comparing them with commands. Once the deviation exceeds the threshold, a recalculation and reissue process is triggered. Furthermore, the rolling optimization and dynamic adjustment strategy enhances the system's adaptability and robustness, thereby optimizing energy dispatch efficiency, ensuring the stable operation of the building energy system, effectively responding to real-time changes, and reducing the need for human intervention. Attached Figure Description

[0015] The invention will now be further described with reference to the accompanying drawings.

[0016] Figure 1 This is a flowchart illustrating the method described in this invention; Figure 2 This is a schematic diagram of the process structure of the method described in Embodiment 1 of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] like Figure 1 , Figure 2 As shown, this application provides a smart control method for building photovoltaic curtain walls based on the linkage between light transmittance and energy storage status; As an embodiment 1 of this application, it specifically includes: Step 1: Determine the power generation of the photovoltaic array, the state of charge of the energy storage system, and the building load, all aligned with the time frame. Step 2: Perform power zoning based on the state of charge aligned with the time, and automatically match the current operating state of the photovoltaic curtain wall to the pre-built global control mode based on the power zoning. Step 3: Construct an objective function with the goal of minimizing the overall building operating cost, perform rolling optimization in combination with the corresponding global control mode, and generate control instructions for photovoltaic curtain walls, energy storage systems, and building loads, which are then combined into the optimal set of control instructions. Step four: Issue the optimal control command set to the photovoltaic curtain wall actuator, energy storage system converter, and building load controller to achieve coordinated control of the curtain wall, energy storage, and load.

[0019] Example 2 This embodiment, based on Embodiment 1, further discloses a method for determining the power generation of a photovoltaic array aligned with time, the state of charge of the energy storage system, the building load, and the solar irradiance, and for determining a global control mode based on the energy storage system's power zoning, specifically including the following: Based on the content described in Example 1, firstly, the photovoltaic array, energy storage system, and building electrical equipment are determined; Among them, the photovoltaic array is integrated with the photovoltaic curtain wall, the energy storage system is a device that receives the power generated by the photovoltaic array and performs energy storage, and the building electrical equipment is a facility that generates building load; Photovoltaic arrays, energy storage systems, and building electrical equipment are heterogeneous data sources with different sampling frequencies and communication delays. Therefore, hard synchronization of time series of multiple physical quantities is achieved by establishing a unified monitoring period T and discrete time series. Extract the current time, denoted as t1, and obtain the total number of times within a monitoring period T preset by the operator, denoted as j; Take the current time t1 as the start time of a monitoring period T. Starting from the current time t1, monitor the photovoltaic system, energy storage system and building electrical equipment. Extract the power generation of the photovoltaic array, the state of charge of the energy storage system and the building load of the building electrical equipment (the total load of all electrical equipment in the building) according to the time. From start time t1 to end time tj, the power generation, state of charge (SOC), and building load at each time point are determined and arranged in chronological order to obtain the power generation sequence F1, F2, ..., Fj, the SOC sequence H1, H2, ..., Hj, and the building load sequence G1, G2, ..., Gj. This ensures that the power generation, SOC, and building load are causally correlated at the same timestamp. It is important to note that in actual implementation, the power generation sequence F1, F2, ..., Fj, the SOC sequence H1, H2, ..., Hj, and the building load sequence G1, G2, ..., Gj within a monitoring period T are not generated all at once, but are gradually improved over time. This embodiment operates in this way for ease of understanding and subsequent calculations.

[0020] Next, charge partitioning is performed based on the time-aligned state of charge; Extract the charge state sequence H1, H2, ..., Hj determined above; A two-dimensional coordinate system is constructed with the time line as the horizontal axis and the state of charge as the vertical axis. Then, the j states of charge in the state of charge sequence H1, H2, ..., Hj are used as data points and plotted in the two-dimensional coordinate system at the corresponding time points to obtain the j data points corresponding to the j states of charge. Then, curve fitting is used to fit the j data points to generate a curve, which is denoted as the state of charge change curve W_H. Next, determine the scales for 75% and 25% charge state on the vertical axis of the two-dimensional coordinate system. Then, construct straight lines parallel to the horizontal axis and perpendicular to the vertical axis through the two scales respectively. The straight line corresponding to the 75% charge state is denoted as the high charge scale line L1, and the straight line corresponding to the 25% charge state is denoted as the low charge scale line L2. It should be noted that the 75% and 25% state of charge values ​​in this embodiment are example values ​​set in conjunction with the physical characteristics of the energy storage system. Operators can modify them according to the actual situation and can also set buffer values ​​to ensure that system oscillations caused by frequent switching of control modes are avoided.

[0021] Next, monitor the state of charge change curve W_H in real time. If the state of charge change curve W_H is higher than the high charge scale line L1, the charge zone is determined to be a high charge zone, close to the full charge state. If the state of charge change curve W_H is lower than or equal to the high charge scale line L1 and simultaneously higher than the low charge scale line L2, the charge zone is determined to be the medium charge zone. When the state of charge change curve W_H is lower than the low charge scale line L2, the charge zone is determined to be a low charge zone.

[0022] When the power distribution zone is a high-load zone, the current operating state of the photovoltaic curtain wall is adjusted to the mode of maximizing economic benefits. The power is delivered to the grid at the maximum discharge power of the energy storage system, and the electricity price benefits are obtained first through peak shaving and valley filling, so as to avoid curtailment of solar power. The specific process is as follows: the photovoltaic array is charged to the energy storage system, and the energy storage system supplies power to the building while discharging to the grid. When the power distribution zone is a medium-Dutch power distribution zone, the power generation of the photovoltaic array of the current photovoltaic curtain wall and the building load are first extracted based on the power generation sequence F1,F2,...,Fj and the building load sequence G1,G2,...,Gj. If the power generation exceeds the building load, it indicates a power generation surplus. In this case, the photovoltaic output not only meets the building self-sufficiency requirement but also has a surplus available for sale. Furthermore, the batteries do not require deep discharge and are ready to transmit power to the grid. Therefore, the regulation mode is the one that maximizes economic benefits. If the power generation is less than or equal to the building load, it means that the power generation is insufficient and the photovoltaic output is not enough to meet the building self-sufficiency. In addition, the electricity stored in the energy storage system needs to be used. At this time, the building load self-sufficiency is given priority, and the energy storage system discharges to the building function at its maximum discharge power. At this time, the energy storage system stops transmitting power to the grid. When the power distribution zone is a low-charge zone, the regulation is in energy security mode, using the power generated by the photovoltaic array to charge the energy storage system. In other words, all the power generated by the photovoltaic array is used to supply power to the building. When the power generated by the photovoltaic array is insufficient to meet the building's self-sufficiency, the missing building load is supplemented by the grid (that is, the energy storage system will not continue to reduce its state of charge).

[0023] Example 3 This embodiment further discloses a method for generating an optimal set of control instructions based on embodiment 2, specifically including the following: First, we construct an objective function that aims to minimize the overall operating cost of the building, which will facilitate subsequent rolling optimization with the goal of minimizing the objective function. The specific objective function is as follows: MJ=C_grid×P_grid+α×|T_room-T_set|+β×Wear_batt; It should be noted that C_grid×P_grid represents the grid purchase cost of electricity, corresponding to the low-load zone. For other zones, C_grid×P_grid=0. C_grid is the real-time electricity price, which is obtained from the grid and is considered a known value. α×|T_room-T_set| is the thermal comfort penalty, where α is the temperature deviation penalty coefficient preset by the operator, used to convert temperature deviation into economic cost and avoid blindly saving energy at the expense of the actual experience of users in the building (corresponding to the light transmittance of the photovoltaic curtain wall), T_room is the indoor temperature, and T_set is the set temperature (generally based on a constant temperature of 26 degrees Celsius). β×Wear_batt represents the battery cycle depreciation cost, β is the battery loss cost coefficient (considered a known value), and Wear_batt represents the battery cycle loss cost (considered a known value).

[0024] Next, rolling optimization is performed by combining the objective function MJ and the global control mode to generate photovoltaic curtain wall control instructions, energy storage system control instructions and building load control instructions; First, obtain the operator's preset rolling optimization time domain window, where the duration of the rolling optimization time domain window is less than the monitoring period T. Within each rolling optimization time domain window within the monitoring period T, perform the following operations: The global control mode of the photovoltaic curtain wall, the power generation sequence F1, F2, ..., Fj, the building load sequence G1, G2, ..., Gj, the state of charge sequence H1, H2, ..., Hj, and the real-time electricity price C_grid obtained from the grid are used as inputs for rolling optimization. Then, an optimization problem is constructed with the objective function MJ as the goal. The decision variables are set as the target light transmittance τ of the photovoltaic curtain wall, the adjustment amount of the building load P_load, and the charging and discharging power P_batt of the energy storage system. It should be noted that the charging and discharging power P_batt is positive for discharging and negative for charging. Before iteratively solving the objective function MJ, it is also necessary to determine the optimization constraints, including: energy storage system charging and discharging power constraints, energy storage system state of charge constraints, photovoltaic curtain wall transmittance adjustment constraints, and power balance constraints. The charging and discharging power constraint of the energy storage system is expressed as: P_batt_min≤P_batt≤P_batt_max, where P_batt_min and P_batt_max are the minimum and maximum allowable power of the energy storage system (including charging and current power, positive and negative values ​​are not considered here). The state of charge constraint of the energy storage system is expressed as: H_min≤H≤H_max, where H_min and H_max are preset safe state of charge ranges; The light transmittance adjustment constraint of the photovoltaic curtain wall is expressed as: τ_min≤τ≤τ_max, where τ_min and τ_max are the minimum and maximum light transmittance allowed by the physical structure of the photovoltaic curtain wall; The power balance constraint is expressed as: P_pv(τ) + P_batt + P_grid = G - P_load, where P_pv(τ) is the real-time power generation of the photovoltaic array under the corresponding transmittance τ, G is the building load, and P_pv(τ) also needs to be determined in conjunction with the light intensity. This is covered by existing technology and will not be elaborated on in this solution. Next, based on the multi-objective optimization solver, and in conjunction with the above optimization constraints, the objective function MJ is iteratively solved within the rolling optimization time window; The multi-objective optimization solver outputs the optimal decision variable values ​​based on minimizing the objective function MJ, specifically the light transmittance τ*, the optimal charging and discharging power P_batt* of the energy storage system, and the optimal adjustment amount P_load* of the building load; Finally, the target transmittance τ*, the optimal charging and discharging power P_batt* of the energy storage system, and the optimal adjustment amount P_load* of the building load are combined, and the combination result is recorded as the set of optimal control instructions R={τ*,P_batt*,P_load*} associated within the corresponding rolling optimization time domain window.

[0025] Example 4 This embodiment, based on embodiment 3, further discloses a method for achieving coordinated control of curtain walls, energy storage, and load, specifically including the following: Based on the content described in Example 3, obtain the optimal set of control instructions R; By analyzing the optimal control command set R, the target light transmittance τ*, the optimal charging and discharging power P_batt* of the energy storage system, and the optimal adjustment amount P_load* of the building load are obtained; Next, the target transmittance τ* is converted into a drive signal that the photovoltaic curtain wall actuator can recognize and sent to the actuator of the photovoltaic curtain wall. Finally, the actuator of the photovoltaic curtain wall adjusts the light-transmitting unit of the curtain wall to the specified transmittance, that is, the target transmittance τ*. The following steps are performed simultaneously with transmittance adjustment: The optimal charging and discharging power P_batt* of the energy storage system is converted into a power setting command for the energy storage system converter and sent to the energy storage system converter to control the energy storage system to perform charging and discharging operations at the specified power. The optimal adjustment amount P_load* of the building load is then converted into an adjustment command for the building load controller and sent to the building load controller to perform building load adjustment. For example, based on a predefined uninterruptible load whitelist, uninterruptible electrical equipment is identified, and then other interruptible electrical equipment is regulated. Then, the system monitors the real-time light transmittance of the photovoltaic curtain wall, the actual charging and discharging power and state of charge of the energy storage system, and the feedback signals of the actual power of the building load, and compares them with the issued instructions. The feedback signals specifically include the actual light transmittance of the photovoltaic curtain wall, the actual charging and discharging power of the energy storage system, and the actual total load of the building. If, during monitoring, the actual state of the feedback signal deviates from the command beyond the operator's preset threshold, a recalculation and issuance process for the control command is triggered. The current moment is then used as the start of the rolling optimization time window, and a rolling optimization is performed. If multiple consecutive rolling optimizations (which can be determined by the operator) fail to return to normal, an early warning command is triggered to notify the operator to perform maintenance. The target of the maintenance is a photovoltaic curtain wall, energy storage system, or building electrical equipment whose actual state deviates from the command beyond the operator's preset threshold.

[0026] All data in the formulas described above have been calculated with dimensions removed. Furthermore, any content not described in detail in this specification is existing technology known to those skilled in the art.

[0027] The above description is merely an example and illustration of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the invention or exceed the scope defined in the claims, all of which should fall within the protection scope of the present invention.

[0028] It should be stated that all user data collected in this application was collected with the user's consent and authorization. Furthermore, the uses of user data are legal and compliant, and the use and processing of user data comply with the relevant laws, regulations, and standards of the relevant regions.

Claims

1. A smart control method for building-integrated photovoltaic (BIPV) curtain walls based on the linkage between light transmittance and energy storage status, characterized in that, The method includes: Step 1: Determine the power generation of the photovoltaic array, the state of charge of the energy storage system, and the building load, all aligned with the time frame. Step 2: Perform power zoning based on the state of charge aligned with the time, and automatically match the current operating state of the photovoltaic curtain wall to the pre-built global control mode based on the power zoning. Step 3: Construct an objective function with the goal of minimizing the overall building operating cost, perform rolling optimization in combination with the corresponding global control mode, and generate control instructions for photovoltaic curtain walls, energy storage systems, and building loads, which are then combined into the optimal set of control instructions. Step four: Issue the optimal control command set to the photovoltaic curtain wall actuator, energy storage system converter, and building load controller to achieve coordinated control of the curtain wall, energy storage, and load.

2. The method according to claim 1, characterized in that, In step one, the specific method for determining the power generation of the photovoltaic array aligned with the time, the state of charge of the energy storage system, the building load, and the solar irradiance is as follows: Determine the current time, denoted as t1, and obtain the total number of times within the monitoring period T, denoted as j, where the monitoring period T is the time period preset by the operator; Taking time t1 as the start time of the monitoring period T, the power generation of the photovoltaic array, the state of charge of the energy storage system, and the building load are continuously monitored for one monitoring period T, and the end time is recorded as tj. Determine the power generation, state of charge, and building load corresponding to j time points, and construct data sequences respectively, denoted as power generation sequence F1, F2, ..., Fj, state of charge sequence H1, H2, ..., Hj, and building load sequence G1, G2, ..., Gj.

3. The method according to claim 2, characterized in that, In step two, the specific method for performing charge partitioning based on time-aligned state of charge is as follows: Extract the charged state sequence H1, H2, ..., Hj; Construct a two-dimensional coordinate system with time as the horizontal axis and state of charge as the vertical axis. Plot the state of charge sequence H1, H2, ..., Hj with time points in the two-dimensional coordinate system to generate a state of charge change curve, denoted as W_H. Determine the scales for 75% and 25% charge state on the vertical axis, and construct straight lines parallel to the horizontal axis and perpendicular to the vertical axis through the two scales respectively, denoted as the high charge scale line L1 and the low charge scale line L2. When the state of charge change curve W_H is higher than the high charge scale line L1, the charge zone is determined to be a high charge zone. When the state of charge change curve W_H is lower than or equal to the high charge scale line L1 and higher than the low charge scale line L2, the charge zone is determined to be the medium charge zone. When the state of charge change curve W_H is lower than the low charge scale line L2, the charge zone is determined to be a low charge zone.

4. The method according to claim 3, characterized in that, In step two, the specific method for automatically matching the current operating state of the photovoltaic curtain wall to the pre-built global control mode based on power zoning is as follows: When the power zone is a high-charge zone, the current operating state of the photovoltaic curtain wall is adjusted to the mode of maximizing economic benefits, so as to transmit power to the grid with the maximum discharge power of the energy storage system. When the power distribution zone is a medium-Dutch power distribution zone, the power generation of the photovoltaic array of the current photovoltaic curtain wall and the building load are extracted based on the power generation sequence F1,F2,...,Fj and the building load sequence G1,G2,...,Gj. If the power generation is greater than the building load, the mode is adjusted to maximize economic benefits. Conversely, the system will switch to a self-balancing mode, supplying power to the building at the maximum discharge power of the energy storage system. When the power zone is a low-charge zone, the regulation is set to energy security mode, using the photovoltaic array's power generation to charge the energy storage system.

5. The method according to claim 4, characterized in that, In step three, the objective function aimed at minimizing the overall building operating cost is specifically expressed as follows: MJ=C_grid×P_grid+α×|T_room-T_set|+β×Wear_batt; Wherein, C_grid is the real-time electricity price, obtained from the power grid; P_grid is the power exchanged between the photovoltaic curtain wall and the power grid, which is considered a known value; α is the temperature deviation penalty coefficient preset by the operator; T_room is the indoor temperature; T_set is the set temperature; β is the battery loss cost coefficient, which is considered a known value; and Wear_batt is the battery cycle loss cost, which is considered a known value.

6. The method according to claim 5, characterized in that, In step three, the specific method for generating photovoltaic curtain wall control commands, energy storage system control commands, and building load control commands by performing rolling optimization in conjunction with the corresponding global control mode is as follows: Obtain a preset rolling optimization time domain window, wherein the duration of the rolling optimization time domain window is less than the monitoring period T. Perform the following operations within each rolling optimization time domain window within the monitoring period T: The global control mode of the photovoltaic curtain wall, the power generation sequence F1, F2, ..., Fj, the building load sequence G1, G2, ..., Gj, the state of charge sequence H1, H2, ..., Hj, and the real-time electricity price C_grid obtained from the grid are used as inputs for rolling optimization. An optimization problem is constructed with the objective function MJ as the goal. The decision variables are set as the target light transmittance τ of the photovoltaic curtain wall, the adjustment amount of the building load P_load, and the charging and discharging power P_batt of the energy storage system. The charging and discharging power P_batt is positive for discharging and negative for charging. Based on the global control mode and physical limitations, optimization constraints are set, including the energy storage system charging and discharging power constraints: P_batt_min≤P_batt≤P_batt_max, where P_batt_min and P_batt_max are the minimum and maximum allowable power; Energy storage system state of charge constraint: H_min≤H≤H_max, where H_min and H_max are preset safe state of charge ranges; Photovoltaic curtain wall transmittance adjustment constraint: τ_min≤τ≤τ_max, where τ_min and τ_max are the minimum and maximum transmittance allowed by the physical structure of the photovoltaic curtain wall; Power balance constraint: P_pv(τ) + P_batt + P_grid = G - P_load, where P_pv(τ) is the real-time power generation of the photovoltaic array at the corresponding transmittance τ, and G is the building load; Based on a multi-objective optimization solver, and in combination with the above optimization constraints, the objective function MJ is iteratively solved within the rolling optimization time window; The output is the optimal decision variable value that minimizes the objective function MJ, including the target light transmittance τ*, the optimal charging and discharging power of the energy storage system P_batt*, and the optimal adjustment amount of the building load P_load*.

7. The method according to claim 6, characterized in that, In step three, the combined target transmittance τ*, the optimal charging and discharging power P_batt* of the energy storage system, and the optimal adjustment amount P_load* of the building load are denoted as the set of optimal control instructions R={τ*,P_batt*,P_load*} associated within the corresponding rolling optimization time-domain window.

8. The method according to claim 7, characterized in that, In step four, the optimal control command set is issued to the photovoltaic curtain wall actuator, the energy storage system converter, and the building load controller. The specific method for achieving coordinated control of the curtain wall, energy storage, and load is as follows: Receive the optimal set of control instructions R; The target transmittance τ* is converted into a drive signal that the photovoltaic curtain wall actuator can recognize and sent to the photovoltaic curtain wall actuator to adjust the light-transmitting unit of the curtain wall to the specified transmittance; The optimal charging and discharging power P_batt* of the energy storage system is converted into a power setting command for the energy storage system converter and sent to the energy storage system converter to control the energy storage system to charge and discharge at the specified power. The optimal adjustment amount of building load P_load* is converted into an adjustment command for the building load controller and sent to the building load controller to execute the building load adjustment; Real-time monitoring of the light transmittance of the photovoltaic curtain wall, the actual charging and discharging power and state of charge of the energy storage system, and the feedback signals of the actual power of the building load are compared with the issued instructions; If the actual state is detected to deviate from the command by more than a preset threshold, the process of recalculating and issuing the control command is triggered, and the current moment is used as the start moment of the rolling optimization time domain window to perform a rolling optimization.

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