Distributed photovoltaic heat collection power generation energy storage control system for residential area

Abstract

The invention discloses a distributed photovoltaic heat collection power generation energy storage control system for a residential area, and the system is characterized in that a photovoltaic equipment adjustment module dynamically adjusts the angle of a photovoltaic panel according to seasons and environment changes, so as to maximize the light energy absorption efficiency, and formulate an operation scheme; the photovoltaic equipment evaluation module monitors the power generation performance of each piece of equipment and identifies abnormal equipment with poor performance; the charging and discharging decision module intelligently plans a charging and discharging strategy and balances power supply and demand according to time and the efficiency of the energy storage device; the heat collection equipment adjusting module optimizes the heat collection efficiency through the comprehensive coefficient, and the heat collection equipment evaluation module evaluates the heat conversion efficiency and cleanliness and screens out abnormal equipment; and the comprehensive feedback module transmits all monitoring data and the generated optimization scheme to the control terminal in real time, so that management personnel can respond in time and take necessary maintenance measures. Accurate adjustment of the photovoltaic power generation equipment and the heat collection equipment is achieved, the abnormal photovoltaic power generation equipment and the abnormal heat collection equipment are accurately recognized, and the safety of the energy storage system is ensured.

Description

Technical Field

[0001] The present invention relates to the field of photovoltaic thermal power generation and energy storage integrated control technology, and more specifically to a distributed photovoltaic thermal power generation and energy storage control system for residential areas. Background Art

[0002] As the global demand for clean energy continues to increase and traditional energy is gradually exhausted, solar energy as a clean and renewable energy form has received widespread attention. In the residential area, distributed photovoltaic (PV) thermal power generation and energy storage control systems have become an important solution. It can not only effectively utilize solar energy resources, but also solve the intermittent and instability problems of photovoltaic power generation through energy storage technology, and improve the quality and reliability of power supply.

[0003] Although distributed photovoltaic thermal power generation and energy storage control systems have shown great potential in the utilization of clean energy, existing technologies still face some urgent problems: lack of effective anomaly detection mechanism, existing methods focus more on static indicators and ignore potential risk points in the dynamic operation process. For example, when encountering extreme climate events or equipment aging, simple performance coefficient calculation may not be sufficient to fully reflect the true status of the equipment; the energy storage strategy of most systems is relatively simple, and the energy storage device may be overcharged or underutilized, which in turn affects the battery life; the existing methods focus on obtaining the collected heat and related parameters to evaluate the performance of the thermal collector. In actual operation, the performance of the thermal collector is affected by many factors, such as surface cleanliness, thermal conversion efficiency, etc., so the existing methods cannot accurately evaluate the performance of the thermal collector.

[0004] Therefore, how to accurately adjust photovoltaic power generation equipment and thermal collection equipment, accurately identify abnormal photovoltaic power generation equipment and thermal collection equipment, and ensure the safety of energy storage systems are issues that technical personnel in this field urgently need to solve. Summary of the invention

[0005] In view of this, the present invention provides a distributed photovoltaic thermal power generation and energy storage control system for residential areas, which realizes the precise adjustment of photovoltaic power generation equipment and thermal collection equipment, and the accurate identification of abnormal photovoltaic power generation equipment and thermal collection equipment, ensures the safety and economy of the energy storage system, greatly improves the application efficiency and service quality of clean energy, and provides strong support for promoting the development of green residential areas.

[0006] In order to achieve the above object, the present invention adopts the following technical solution:

[0007] A distributed photovoltaic thermal power generation and energy storage control system for residential areas, comprising:

[0008] Photovoltaic equipment adjustment module: used to obtain the photovoltaic panel angle of each photovoltaic power generation equipment in the residential area, and determine the first adjustment plan for the operation of each photovoltaic power generation equipment in combination with seasonal and environmental influences;

[0009] Photovoltaic equipment evaluation module: used to obtain the power generation and environmental information of each photovoltaic power generation equipment, obtain the first performance coefficient of each photovoltaic power generation equipment, and further determine the photovoltaic power generation equipment with substandard performance as abnormal photovoltaic equipment;

[0010] A charging and discharging decision module: used to obtain a charging execution coefficient based on the time period and the charging and discharging efficiency of the energy storage device, obtain a charging plan for the energy storage device based on the charging execution coefficient, and obtain a discharging plan based on the power demand;

[0011] A heat collecting device adjustment module: used for obtaining the collected heat and related parameters of each heat collecting device to obtain a comprehensive coefficient, and determining a second adjustment scheme for the operation of each heat collecting device based on the comprehensive coefficient;

[0012] A heat collecting equipment evaluation module: used to obtain the heat conversion efficiency and cleanliness factor of each heat collecting equipment, obtain a second performance coefficient, and further determine the heat collecting equipment that does not meet the performance standard as an abnormal heat collecting equipment; and

[0013] Comprehensive feedback module: used for feeding back the abnormal photovoltaic device, the abnormal heat collection device, the first adjustment plan, the charging plan, the discharging plan and the second adjustment plan to the control terminal.

[0014] Preferably, the photovoltaic equipment adjustment module function realization process includes:

[0015] Get the photovoltaic panel angle θ of each photovoltaic power generation device i and the appropriate panel angle θ at the current time t 0i (t);

[0016] The seasonal adjustment factor S(t) is obtained based on the seasonal impact;

[0017] Based on the real-time measured light intensity I and the real-time temperature T of the photovoltaic panel surface of the i-th photovoltaic power generation device i Get the environmental impact factor E of the i-th photovoltaic power generation equipment i (I,T i );

[0018] Based on the photovoltaic panel angle θ i , the suitable panel angle θ 0i (t), the seasonal adjustment factor S(t) and the environmental impact factor E i (I,T i ) to obtain the adjustment coefficient K of each photovoltaic power generation deviceθi :

[0019]

[0020] Where W represents the weight factor, Δθ represents the PV panel angle deviation threshold;

[0021] Determine, based on the adjustment coefficient, a photovoltaic power generation device that needs to adjust the photovoltaic panel angle as the first adjustment device;

[0022] Based on the photovoltaic panel angle deviation of the first adjustment device, the adjustment direction and adjustment amount of the photovoltaic panel angle of the first adjustment device are obtained as the first adjustment scheme and executed.

[0023] Preferably, the seasonal adjustment factor S(t) is specifically:

[0024]

[0025] Among them, A s represents the amplitude adjustment coefficient, t d Indicates the current date, t s The date indicating the winter solstice or the summer solstice.

[0026] Preferably, the environmental impact factor E i (I,T i ) specifically:

[0027]

[0028] Among them, α and β represent empirical constants, I r Indicates the light intensity under standard test conditions, T r Indicates the temperature under standard test conditions.

[0029] Preferably, the photovoltaic equipment evaluation module function realization process includes:

[0030] Obtain the actual power generation P of each photovoltaic power generation device ai (t) and reference power generation P ri (t);

[0031] Get the surface temperature T of the photovoltaic panels of each photovoltaic power generation device pi (t) and the optimum operating temperature T oi ;

[0032] Get the ambient temperature T at the current time t e (t);

[0033] Based on the actual power generation P ai (t), reference power generation P ri (t), surface temperature Tpi (t), optimal working temperature T oi and ambient temperature T e (t) obtaining the first performance coefficient of each photovoltaic power generation device:

[0034]

[0035] Where ΔT represents the maximum allowable temperature deviation, I ti It represents the light intensity measured by each photovoltaic power generation device in real time, I r represents the light intensity under standard test conditions of each photovoltaic power generation equipment, γ represents the empirical constant of the effect of temperature on efficiency, T v (t) represents the ambient temperature at the current time t, w1, w2, w3, w4, w5 and w6 represent the weight coefficients of each index respectively, F a (t) represents the performance attenuation factor of each photovoltaic power generation device;

[0036] The photovoltaic power generation equipment whose first performance coefficient is less than a set value is selected as the abnormal photovoltaic equipment.

[0037] Preferably, the function implementation process of the charging and discharging decision module includes:

[0038] Determine whether the current time period is in the valley price period, if not, do not perform charging operation;

[0039] If so, then the charging input energy E is obtained based on the charging and discharging efficiency of the energy storage system. in and discharge output energy E out ;

[0040] Obtain the energy consumption cost C of the auxiliary equipment of the energy storage system au ;

[0041] Based on the charging input energy E in , discharge output energy E out and auxiliary equipment energy consumption cost C au Get the charging execution coefficient R:

[0042] R=E out ×C peak -E in ×C valley -C au ;

[0043] Among them, C peak represents the peak electricity price, C valley Indicates the electricity price during the valley period;

[0044] When the charging execution coefficient R is greater than an execution threshold, the energy storage system performs a charging operation to obtain the charging plan;

[0045] The electric energy in the energy storage system is released preferentially based on actual electricity demand to obtain the discharge plan.

[0046] Preferably, the function realization process of the charging and discharging decision module further includes:

[0047] When executing the charging scheme, the optimal charging capacity is obtained based on the charging execution coefficient R and related constraints.

[0048]

[0049] The constraints are:

[0050] E in ≤S max -S current ;

[0051] 0.2S max ≤Sa(t)≤0.8S max ;

[0052]

[0053] Among them, S max Indicates the maximum rated capacity of the energy storage device, S current represents the current storage energy of the energy storage device, Sa(t) represents the actual charge state of the energy storage device at time point t, and E total Indicates that from t start to end The total available energy of the energy storage system during this period, t start and t end Represent the charging start time and end time respectively, PV,forecasted(t) Represents the future photovoltaic power forecast value calculated based on weather forecast.

[0054] Preferably, the function realization process of the heat collection equipment adjustment module includes:

[0055] Get the actual heat collection Q of each heat collection device at time t aj (t) and expected heat collection Q cj (t), j represents the number of the jth solar collector;

[0056] Obtaining the surface temperature T1(t) and the optimal operating temperature T2 of each heat collecting device at time t;

[0057] The comprehensive coefficient P of each heat collecting device is obtained based on the actual heat collection amount, the expected heat collection amount, the surface temperature and the optimal working temperature evj (t):

[0058]

[0059] Among them, η j (t) represents the thermal energy conversion efficiency of the jth collector at time t, a1, a2 and a3 represent the weight coefficients of various indicators, ΔT n Indicates the maximum allowable deviation of the collector, I tk It represents the light intensity measured by each collector in real time, I x Indicates the light intensity under standard test conditions of each collector equipment; F b (t) represents the performance attenuation factor of each solar collector;

[0060] Selecting a heat collecting device whose comprehensive coefficient is less than a target threshold as the second adjustment device;

[0061] An angle adjustment amount of the second adjustment device is determined based on the comprehensive coefficient of the second adjustment device and the target threshold value, and is executed as the second adjustment scheme.

[0062] Preferably, the function realization process of the heat collection equipment adjustment module further includes:

[0063] Based on the comprehensive coefficient P of the second adjustment device evj (t) and the target threshold P tar Get the performance deviation e(t):

[0064] e(t)=P tar -P evj (t);

[0065] Based on the performance deviation e(t), a PID controller is used to obtain the angle adjustment value Δθ adj (t):

[0066]

[0067] Among them, Kp, Ki and Kd represent proportional gain, integral gain and differential gain respectively. represents the cumulative sum of all errors from the start time to the current time t, Represents the rate of change of error over time.

[0068] Preferably, the function realization process of the thermal collector equipment evaluation module includes:

[0069] Obtain the thermal energy conversion efficiency η of each collector at time t j (t);

[0070] Get the current pollution level of each collector device δ j and the maximum permissible pollution degree δ jmax ;

[0071] Based on the current pollution level δ j and the maximum permissible contamination degree δ jmax Get the cleanliness factor Cj clean (t):

[0072]

[0073] Based on the thermal energy conversion efficiency η j (t) and cleanliness factor Cj clean (t) Obtain the second comprehensive performance coefficient P 2j (t):

[0074]

[0075] Among them, c1, c2, c3, c4 and c5 represent the weight coefficients of each indicator respectively;

[0076] A heat collecting device whose second performance coefficient is less than a preset value is selected as the abnormal heat collecting device.

[0077] It can be seen from the above technical solutions that, compared with the prior art, the present invention discloses a distributed photovoltaic thermal power generation and energy storage control system for residential areas, which has the following beneficial effects:

[0078] 1. Optimize photovoltaic power generation performance: Through the photovoltaic equipment adjustment module, the system can automatically adjust the angle of the photovoltaic panel according to seasonal changes and environmental conditions to ensure that it is always in the best light receiving state, thereby maximizing power generation. In addition, by calculating the first performance coefficient to evaluate the performance of each photovoltaic module, and promptly identify abnormal photovoltaic equipment for maintenance or replacement, it ensures the efficient and stable operation of the entire photovoltaic system.

[0079] 2. Improve thermal energy utilization: The combination of the collector adjustment module and the evaluation module can accurately control the working parameters of each collector, such as angle, to match actual needs and maintain efficient heat conversion rate. At the same time, regularly check the cleanliness of the collector to prevent efficiency loss due to dust accumulation and maintain a good heat absorption effect.

[0080] 3. Intelligent charging and discharging decision-making: The charging and discharging decision-making module takes into account the difference in peak and valley electricity prices in the electricity market, chooses to charge the energy storage battery when the electricity price is low, and releases the stored energy for users to use or sell to the power grid during peak hours, thereby reducing costs and increasing profits. It also takes into account the health status of the energy storage system (such as the state of charge) to avoid excessive charging and discharging that damages the battery life.

[0081] 4. Enhance system stability and security: The comprehensive feedback module aggregates all detected information to the control terminal, allowing operators to monitor the system status in real time and respond quickly to possible problems. This helps prevent potential failures and ensures long-term stable operation of the system.

[0082] 5. Promote green and low-carbon development: Distributed energy solutions can meet the growing electricity consumption needs of residents without increasing carbon emissions. The application of such technology is of great significance for reducing greenhouse gas emissions.

[0083] 6. The control system of the present invention, with its highly integrated and intelligent characteristics, not only improves the energy conversion efficiency, but also makes a positive contribution to achieving energy conservation and emission reduction. It is not only suitable for newly built residential areas, but can also be used as a part of energy-saving renovation of existing residential areas, showing broad application prospects and development potential. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0085] Figure 1 A schematic structural diagram of a distributed photovoltaic thermal power generation and energy storage control system for residential areas provided by the present invention.

[0086] Figure 2 A flow chart of a distributed photovoltaic thermal power generation and energy storage control method for residential areas provided by the present invention.

[0087] Figure 3 This is a structural block diagram of the computer device provided by the present invention. DETAILED DESCRIPTION

[0088] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0089] Example 1

[0090] like Figure 1 As shown, the embodiment of the present invention discloses a distributed photovoltaic thermal power generation and energy storage control system for residential areas, comprising:

[0091] Photovoltaic equipment adjustment module: used to obtain the photovoltaic panel angle of each photovoltaic power generation equipment in the residential area, and determine the first adjustment plan for the operation of each photovoltaic power generation equipment in combination with seasonal and environmental influences;

[0092] Photovoltaic equipment evaluation module: used to obtain the power generation and environmental information of each photovoltaic power generation equipment, obtain the first performance coefficient of each photovoltaic power generation equipment, and further determine the photovoltaic power generation equipment that does not meet the performance standards as abnormal photovoltaic equipment;

[0093] Charging and discharging decision module: used to obtain a charging execution coefficient based on the time period and the charging and discharging efficiency of the energy storage device, obtain a charging plan for the energy storage device based on the charging execution coefficient, and obtain a discharging plan based on the power demand;

[0094] Heat collecting equipment adjustment module: used to obtain the collected amount and related parameters of each heat collecting equipment to obtain a comprehensive coefficient, and determine a second adjustment scheme for the operation of each heat collecting equipment based on the comprehensive coefficient;

[0095] Thermal collector equipment evaluation module: used to obtain the heat conversion efficiency and cleanliness factor of each thermal collector equipment, obtain the second performance coefficient, and further determine the thermal collector equipment that does not meet the performance standards as abnormal thermal collector equipment; and,

[0096] Comprehensive feedback module: used to feed back abnormal photovoltaic equipment, abnormal thermal collection equipment, the first adjustment plan, the charging plan, the discharging plan and the second adjustment plan to the control terminal.

[0097] Example 2

[0098] like Figure 1 As shown, the embodiment of the present invention discloses a distributed photovoltaic thermal power generation and energy storage control system for residential areas, comprising:

[0099] Photovoltaic equipment adjustment module: used to obtain the photovoltaic panel angle of each photovoltaic power generation equipment in the residential area, and determine the first adjustment plan for the operation of each photovoltaic power generation equipment in combination with seasonal and environmental influences.

[0100] Preferably, the photovoltaic equipment adjustment module function realization process includes:

[0101] Get the photovoltaic panel angle θ of each photovoltaic power generation device i and the appropriate panel angle θ at the current time t 0i (t);

[0102] The seasonal adjustment factor S(t) is obtained based on the seasonal impact;

[0103] Based on the real-time measured light intensity I and the real-time temperature T of the photovoltaic panel surface of the i-th photovoltaic power generation device i Get the environmental impact factor E of the i-th photovoltaic power generation equipmenti (I,T i ).

[0104] Preferably, the seasonal adjustment factor S(t) is specifically:

[0105]

[0106] Among them, A s represents the amplitude adjustment factor, which is calibrated according to the geographical location and historical data, t d Indicates the current date (expressed as the number of days in the year), t s The date of the winter or summer solstice;

[0107] Environmental impact factor E i (I,T i ) Specifically:

[0108]

[0109] Among them, α and β represent empirical constants, I r Indicates the light intensity under standard test conditions, T r Indicates the temperature under standard test conditions.

[0110] Preferably, t s Depends on which one is chosen as the reference point. For example, in the Northern Hemisphere, the summer solstice occurs on approximately the 172nd day of the year (around June 21st), while the winter solstice occurs on approximately the 355th day (around December 22nd).

[0111] Preferably, the seasonal adjustment factor S(t) mainly considers the influence of seasonal changes in the solar altitude angle and changes in sunshine time. The specific solar altitude angle of a certain day is calculated based on an astronomical algorithm, and the angle of the photovoltaic panel is adjusted accordingly.

[0112] Preferably, the environmental impact factor E i (I,T i ) is used to describe the effect of temperature on photovoltaic efficiency. As the temperature increases, the efficiency decays exponentially. At the same time, it is multiplied by the ratio of light intensity to ensure that the change in efficiency can be correctly reflected under different lighting conditions.

[0113] Preferably, the light intensity I under the standard test conditions in this embodiment is r Set to 1000W / m 2 ; Temperature T under standard test conditions r Set to 25°C.

[0114] Preferably, the photovoltaic equipment adjustment module function realization process also includes:

[0115] Based on the photovoltaic panel angle θi 、Suitable panel angle θ 0i (t), seasonal adjustment factor S(t) and environmental impact factor E i (I,T i ) to obtain the adjustment coefficient K of each photovoltaic power generation equipment θi :

[0116]

[0117] Where W represents the weight factor, which is used to emphasize the importance of the PV panel angle in the system performance evaluation, and Δθ represents the PV panel angle deviation threshold;

[0118] Determine, based on the adjustment coefficient, the photovoltaic power generation equipment that needs to adjust the photovoltaic panel angle as the first adjustment equipment;

[0119] Based on the photovoltaic panel angle deviation of the first adjustment device, the adjustment direction and adjustment amount of the photovoltaic panel angle of the first adjustment device are obtained as a first adjustment scheme and executed.

[0120] Preferably, by combining the seasonal adjustment factor S(t) and the environmental impact factor E i (I,T i ), the obtained adjustment coefficient can more accurately evaluate whether the angle of the photovoltaic panel is appropriate, and can be dynamically adjusted according to actual conditions, thereby improving the overall performance of the system.

[0121] Photovoltaic equipment evaluation module: used to obtain the power generation and environmental information of each photovoltaic power generation equipment, obtain the first performance coefficient of each photovoltaic power generation equipment, and further determine the photovoltaic power generation equipment that does not meet the performance standards as abnormal photovoltaic equipment.

[0122] Preferably, the photovoltaic equipment evaluation module function realization process includes:

[0123] Get the actual power generation P of each photovoltaic power generation equipment ai (t) and reference power generation P ri (t);

[0124] Get the surface temperature T of each photovoltaic panel of photovoltaic power generation equipment pi (t) and the optimum operating temperature T oi ;

[0125] Get the ambient temperature T at the current time t e (t);

[0126] Based on the actual power generation P ai (t), reference power generation P ri (t), surface temperature T pi (t), optimal working temperature T oi and ambient temperature Te (t) Obtain the first performance coefficient of each photovoltaic power generation device:

[0127]

[0128] Where ΔT represents the maximum allowable temperature deviation, I ti It represents the light intensity measured by each photovoltaic power generation device in real time, I r represents the light intensity under standard test conditions of each photovoltaic power generation equipment, γ represents the empirical constant of the effect of temperature on efficiency, T v (t) represents the ambient temperature at the current time t, w1, w2, w3, w4, w5 and w6 represent the weight coefficients of various indicators, which can be adjusted according to the actual situation to reflect the importance of different factors. a (t) represents the performance attenuation factor of each photovoltaic power generation device;

[0129] A photovoltaic power generation device whose first performance coefficient is less than a set value is selected as an abnormal photovoltaic device.

[0130] Preferably, the performance attenuation factor F of each photovoltaic power generation device is a (t) Specifically:

[0131] F a (t) = e -Ω×LV , where Ω represents the attenuation rate and LV represents the service life of each photovoltaic power generation equipment.

[0132] Preferably, in this embodiment, the upper and lower control limits are set as set values ​​by the statistical process control (SPC) method. When LCL≤p 1i (t)≤UCL, LCL represents the lower control limit, and UCL represents the upper control limit, then the equipment is considered to have potential problems as an abnormal photovoltaic equipment and requires further inspection.

[0133] Preferably, the weight coefficient wi is set according to the specific application scenario and importance. For example, if power generation is the most critical indicator, a higher value can be assigned to w1; if temperature management is critical, the weights of w2 and w4 should be appropriately increased. The sum of all weight coefficients should be equal to 1 to ensure a balance between factors.

[0134] Preferably, the present invention can more comprehensively evaluate the performance of photovoltaic power generation equipment through the first performance coefficient formula, which is not limited to power generation, but also includes temperature management, lighting conditions, equipment aging and other aspects, so as to more accurately identify equipment with substandard performance and provide targeted maintenance suggestions.

[0135] Charging and discharging decision module: used to obtain the charging execution coefficient based on the time period and the charging and discharging efficiency of the energy storage device, obtain the charging plan of the energy storage device based on the charging execution coefficient, and obtain the discharging plan based on the power demand.

[0136] Preferably, the function implementation process of the charge and discharge decision module includes:

[0137] Determine whether the current time period is in the valley price period, if not, do not perform charging operation;

[0138] If so, the charging input energy E is obtained based on the charging and discharging efficiency of the energy storage system. in and discharge output energy E out ;

[0139] Obtain the energy consumption cost C of the auxiliary equipment of the energy storage system au ;

[0140] Based on charging input energy E in , discharge output energy E out and auxiliary equipment energy consumption cost C au Get the charging execution coefficient R:

[0141] R=E out ×C peak -E in ×C valley -C au ;

[0142] Among them, C peak represents the peak electricity price, C valley Indicates the electricity price during the valley period;

[0143] When the charging execution coefficient R is greater than the execution threshold, the energy storage system performs the charging operation and obtains the charging plan. Otherwise, it maintains the status quo or only replenishes part of the power to maintain the minimum operating level.

[0144] Based on the actual electricity demand, the electric energy in the energy storage system is released first to obtain a discharge plan.

[0145] Preferably, E in =E usable / η charge , E usable represents the real available energy, η charge Indicates charging efficiency; E out＝ E in ×η charge ×η discharge , where η discharge Indicates the discharge efficiency.

[0146] Preferably, the auxiliary equipment energy consumption cost C au Specifically:

[0147] C au =P auxiliary ×(t charge +t discharge )×C average ;

[0148] Among them, P auxiliary Indicates the average power consumption (kW) of auxiliary equipment such as air conditioning system, t charge Indicates charging duration (hours), t discharge Indicates discharge duration (hours), C average Indicates the average electricity price during the entire charge and discharge cycle. In this embodiment, the value is C peak With C valley The weighted average of .

[0149] Preferably, the charging and discharging decision module function implementation process also includes:

[0150] When executing the charging plan, the optimal charging capacity is obtained based on the charging execution coefficient R and related constraints.

[0151]

[0152] The constraints are:

[0153] E in ≤S max -S current ;

[0154] 0.2S max ≤Sa(t)≤0.8S max ;

[0155]

[0156] Among them, S max Indicates the maximum rated capacity of the energy storage device, S current represents the current storage energy of the energy storage device, Sa(t) represents the actual charge state of the energy storage device at time point t, and E total Indicates that from t start to end The total available energy of the energy storage system during this period, including the existing storage energy and the expected contribution of additional photovoltaic power generation, t start and t end Represent the charging start time and end time respectively, PV,forecasted(t) Represents the future photovoltaic power forecast value calculated based on weather forecast.

[0157] Preferably, E in ≤S max -S currentUsed for energy storage capacity limitation: the new charge amount cannot exceed the remaining available capacity.

[0158] Preferably, 0.2S max ≤Sa(t)≤0.8S max Used to limit the state of charge (SOC) range, where 0.2S max Indicates the lower limit of the safe operating range of the energy storage device, that is, the minimum allowable state of charge. By setting the minimum allowable state of charge, the energy storage device maintains a minimum energy reserve, which can help cope with sudden demand peaks or grid failures, ensure the stability and reliability of power supply, and ensure that the energy storage device will not be damaged due to excessive discharge in daily operation. 0.8S max It indicates the upper limit of the safe operating range of the energy storage system, that is, the maximum allowable state of charge. By setting the maximum allowable state of charge, it is ensured that the energy storage device will not be damaged by overcharging in daily operation, and its storage capacity can be effectively used to optimize energy management.

[0159] By limiting the state of charge (SOC) range, overcharging or over-discharging can be avoided and a safe operating boundary can be maintained. Staying within this range can extend battery life and ensure system reliability.

[0160] Preferably, Used to consider the impact of future photovoltaic power forecasts on total energy.

[0161] Preferably, other restrictions are also included: including but not limited to the maximum single charge and discharge power, the minimum charging cycle, etc., depending on the characteristics and application scenarios of the energy storage system.

[0162] Preferably, weather forecast information is crucial for predicting photovoltaic power generation, especially on sunny and cloudless days, when the output of the photovoltaic system is relatively large; on rainy days, the output may be greatly reduced. In order to more accurately estimate the future photovoltaic power generation potential, the present invention adjusts the expected power generation of the photovoltaic array in combination with short-term meteorological forecast data (such as cloud cover, temperature, etc.) to obtain the future photovoltaic power prediction value P calculated based on the weather forecast. PV,forecasted(t) .

[0163] Preferably, the above optimal charging amount The formula not only takes into account direct economic benefits, but also takes into account the impact of technical feasibility and environmental factors. It helps decision makers to manage energy storage more scientifically and rationally, thus achieving a win-win situation of economic benefits and social responsibility.

[0164] The solar collector adjustment module is used to obtain the collected heat and related parameters of each solar collector to obtain a comprehensive coefficient, and determine the second adjustment plan for the operation of each solar collector based on the comprehensive coefficient.

[0165] Preferably, the function realization process of the heat collection equipment adjustment module includes:

[0166] Get the actual heat collection Q of each collector at time t aj (t) and expected heat collection Q cj (t), j represents the number of the jth solar collector;

[0167] Obtain the surface temperature T1(t) and the optimal operating temperature T2 of each solar collector at time t;

[0168] The comprehensive coefficient P of each collector is obtained based on the actual collected heat, expected collected heat, surface temperature and optimal working temperature. evj (t):

[0169]

[0170] Among them, η j (t) represents the thermal energy conversion efficiency of the jth collector at time t, a1, a2 and a3 represent the weight coefficients of various indicators, ΔT n Indicates the maximum allowable deviation of the collector, I tk It represents the light intensity measured by each collector in real time, I x Indicates the light intensity under standard test conditions of each collector equipment; F b (t) represents the performance attenuation factor of each solar collector;

[0171] Selecting a solar collector with a comprehensive coefficient less than a target threshold as the second adjustment device;

[0172] The angle adjustment amount of the second adjustment device is determined based on the comprehensive coefficient of the second adjustment device and the target threshold value, and is executed as a second adjustment scheme.

[0173] Preferably, the desired heat collection amount Q cj (t) Calculated based on current lighting conditions and theoretical models; the light intensity I under standard test conditions of each solar collector x Set to 1000W / m 2 .

[0174] Preferably, by Directly reflects the actual performance of the solar collector. Indicates the deviation between the collector surface temperature and the optimal operating temperature, ensuring that the equipment operates within the optimal temperature range. Reflects the effect of light conditions on heat collection efficiency; a3·F b(t) It takes into account the aging of the equipment over time, which helps to evaluate the long-term performance. Through the above-mentioned comprehensive coefficient, the performance of the solar collector equipment can be more comprehensively evaluated, not only limited to the thermal energy conversion efficiency, but also including temperature management, lighting conditions and equipment aging. It can more accurately identify equipment that does not meet the performance standards and provide targeted maintenance recommendations.

[0175] Preferably, F b (t) = e -U×LZ , where U represents the decay rate and LZ represents the service life of each collector equipment.

[0176] Preferably, the sum of all weight coefficients a1, a2 and a3 is equal to 1, ensuring a balance between the factors.

[0177] Preferably, a machine learning algorithm (such as reinforcement learning, genetic algorithm) is used to analyze historical data and continuously optimize weight coefficients a1, a2, and a3 so that the system can better adapt to different environmental conditions and operational requirements.

[0178] Preferably, the function realization process of the heat collection device adjustment module also includes:

[0179] Based on the comprehensive coefficient P of the second adjustment device evj (t) and target threshold P tar Get the performance deviation e(t):

[0180] e(t)=P tar -P evj (t);

[0181] Based on the performance deviation e(t), the PID controller is used to obtain the angle adjustment value Δθ adj (t):

[0182]

[0183] Among them, Kp, Ki and Kd represent proportional gain, integral gain and differential gain respectively. represents the cumulative sum of all errors from the start time to the current time t, Represents the rate of change of error over time.

[0184] Preferably, this embodiment determines an initial optimal collector panel angle θ based on the seasonal adjustment factor S(t) and the solar position information α(t). base (t):

[0185] θ base (t) = θ fixed +Δθ·S(t)+f(α(t))

[0186] Among them, θ fixedIndicates the foundation installation angle, Δ θ represents the angle increment adjusted according to seasonal changes, and f(α(t)) represents the angle adjustment calculated based on the real-time sun position.

[0187] Preferably, based on the optimal collector panel angle θ base (t) and angle adjustment Δθ adj (t) The final adjusted collector panel angle θ is obtained by summing opt (t):

[0188] θ opt (t) = θ base (t)+Δθ adj (t).

[0189] Solar collector equipment evaluation module: used to obtain the heat conversion efficiency and cleanliness factor of each solar collector equipment, obtain the second performance coefficient, and further determine the solar collector equipment that does not meet the performance standards as abnormal solar collector equipment.

[0190] Preferably, the function realization process of the thermal collector equipment evaluation module includes:

[0191] Obtain the thermal energy conversion efficiency η of each collector at time t j (t);

[0192] Get the current pollution level of each collector device δ j and the maximum permissible pollution degree δ jmax ;

[0193] Based on the current pollution level δ j and the maximum permissible contamination level δ jmax Get the cleanliness factor Cj clean (t):

[0194]

[0195] Based on the thermal energy conversion efficiency η j (t) and cleanliness factor Cj clean (t) Get the second comprehensive performance coefficient P 2j (t):

[0196]

[0197] Among them, c1, c2, c3, c4 and c5 represent the weight coefficients of each indicator respectively;

[0198] A heat collecting device whose second performance coefficient is less than a preset value is selected as an abnormal heat collecting device.

[0199] Preferably, the thermal energy conversion efficiency η j (t) is:

[0200]

[0201] Among them, E solar (t) represents the total solar radiation (W / m 2 ), A collector Indicates the heat collection area (m 2 ).

[0202] Comprehensive feedback module: used to feed back abnormal photovoltaic equipment, abnormal thermal collection equipment and all generated solutions to the control terminal.

[0203] Preferably, the comprehensive feedback module is used to feed back abnormal photovoltaic equipment, abnormal thermal collection equipment, the first adjustment plan, the charging plan, the discharging plan and the second adjustment plan to the control terminal.

[0204] Preferably, the integrated feedback module aggregates all detected information to the control terminal, so that the operator can monitor the system status in real time and respond quickly to possible problems. This helps prevent potential failures and ensure the long-term stable operation of the system.

[0205] Example 3

[0206] like Figure 2 As shown, the embodiment of the present invention discloses a distributed photovoltaic thermal power generation and energy storage control method for residential areas, comprising:

[0207] Obtain the photovoltaic panel angle of each photovoltaic power generation device in the residential area, and determine the first adjustment plan for the operation of each photovoltaic power generation device in combination with seasonal and environmental influences;

[0208] Acquire the power generation and environmental information of each photovoltaic power generation device, obtain the first performance coefficient of each photovoltaic power generation device, and further determine the photovoltaic power generation device that does not meet the performance standard as an abnormal photovoltaic device;

[0209] A charging execution coefficient is obtained based on the time period and the charging and discharging efficiency of the energy storage device, a charging plan of the energy storage device is obtained based on the charging execution coefficient, and a discharging plan is obtained based on the power demand;

[0210] The collected heat and related parameters of each heat collecting device are obtained to obtain a comprehensive coefficient, and a second adjustment scheme for the operation of each heat collecting device is determined based on the comprehensive coefficient;

[0211] The heat conversion efficiency and cleanliness factor of each heat collecting device are obtained to obtain a second performance coefficient, and the heat collecting devices that do not meet the performance standards are further determined as abnormal heat collecting devices;

[0212] Abnormal photovoltaic equipment, abnormal thermal collection equipment and all generated solutions are fed back to the control terminal.

[0213] Preferably, the implementation process of each step in this embodiment corresponds one-to-one to the implementation process of the function modules described above, and will not be described in detail here.

[0214] Example 4

[0215] Based on the same inventive concept, the present invention also provides a computer device, including a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

[0216] Memory, used to store computer programs;

[0217] The processor, when used to execute the program stored in the memory, can implement a distributed photovoltaic thermal power generation and energy storage control method for residential areas as described in Example 3.

[0218] like Figure 3 As shown, the electronic device may include: a processor 31, a communication interface 32, a memory 33 and a communication bus 34, wherein the processor 31, the communication interface 32 and the memory 33 communicate with each other through the communication bus 34. The processor 31 may call the logic instructions in the memory 33 to execute a distributed photovoltaic thermal power generation and energy storage control method for a residential area in Example 3.

[0219] In addition, the logic instructions in the above-mentioned memory 33 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0220] It can be seen from the above technical solutions that the present invention discloses a distributed photovoltaic thermal power generation and energy storage control system for residential areas, which has the following beneficial effects:

[0221] 1. Optimize photovoltaic power generation performance: Through the photovoltaic equipment adjustment module, the system can automatically adjust the angle of the photovoltaic panel according to seasonal changes and environmental conditions to ensure that it is always in the best light receiving state, thereby maximizing power generation. In addition, by calculating the first performance coefficient to evaluate the performance of each photovoltaic module, and promptly identify abnormal photovoltaic equipment for maintenance or replacement, it ensures the efficient and stable operation of the entire photovoltaic system.

[0222] 2. Improve thermal energy utilization: The combination of the collector adjustment module and the evaluation module can accurately control the working parameters of each collector, such as angle, to match actual needs and maintain efficient heat conversion rate. At the same time, regularly check the cleanliness of the collector to prevent efficiency loss due to dust accumulation and maintain a good heat absorption effect.

[0223] 3. Intelligent charging and discharging decision-making: The charging and discharging decision-making module takes into account the difference in peak and valley electricity prices in the electricity market, chooses to charge the energy storage battery when the electricity price is low, and releases the stored energy for users to use or sell to the power grid during peak hours, thereby reducing costs and increasing profits. It also takes into account the health status of the energy storage system (such as the state of charge) to avoid excessive charging and discharging that damages the battery life.

[0224] 4. Enhance system stability and security: The comprehensive feedback module aggregates all detected information to the control terminal, allowing operators to monitor the system status in real time and respond quickly to possible problems. This helps prevent potential failures and ensures long-term stable operation of the system.

[0225] 5. Promote green and low-carbon development: Distributed energy solutions can meet the growing electricity consumption needs of residents without increasing carbon emissions. The application of such technology is of great significance for reducing greenhouse gas emissions.

[0226] 6. The control system of the present invention, with its highly integrated and intelligent characteristics, not only improves the energy conversion efficiency, but also makes a positive contribution to achieving energy conservation and emission reduction. It is not only suitable for newly built residential areas, but can also be used as a part of energy-saving renovation of existing residential areas, showing broad application prospects and development potential.

[0227] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0228] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A distributed photovoltaic thermal power generation and energy storage control system for residential areas, characterized in that: include: Photovoltaic equipment adjustment module: used to obtain the photovoltaic panel angle of each photovoltaic power generation equipment in the residential area, and determine the first adjustment plan for the operation of each photovoltaic power generation equipment in combination with seasonal and environmental influences; Photovoltaic equipment evaluation module: used to obtain the power generation and environmental information of each photovoltaic power generation equipment, obtain the first performance coefficient of each photovoltaic power generation equipment, and further determine the photovoltaic power generation equipment with substandard performance as abnormal photovoltaic equipment; A charging and discharging decision module: used to obtain a charging execution coefficient based on the time period and the charging and discharging efficiency of the energy storage device, obtain a charging plan for the energy storage device based on the charging execution coefficient, and obtain a discharging plan based on the power demand; A heat collecting device adjustment module: used for obtaining the collected heat and related parameters of each heat collecting device to obtain a comprehensive coefficient, and determining a second adjustment scheme for the operation of each heat collecting device based on the comprehensive coefficient; A heat collecting equipment evaluation module: used to obtain the heat conversion efficiency and cleanliness factor of each heat collecting equipment, obtain a second performance coefficient, and further determine the heat collecting equipment with substandard performance as an abnormal heat collecting equipment; as well as, Comprehensive feedback module: used for feeding back the abnormal photovoltaic device, the abnormal heat collection device, the first adjustment plan, the charging plan, the discharging plan and the second adjustment plan to the control terminal.

2. A distributed photovoltaic thermal power generation and energy storage control system for residential areas according to claim 1, characterized in that: The photovoltaic equipment adjustment module function realization process includes: Get the photovoltaic panel angle θ of each photovoltaic power generation device i and the appropriate panel angle θ at the current time t 0i (t); The seasonal adjustment factor S(t) is obtained based on the seasonal impact; Based on the real-time measured light intensity I and the real-time temperature T of the photovoltaic panel surface of the i-th photovoltaic power generation device i Get the environmental impact factor E of the i-th photovoltaic power generation equipment i (I,T i ); Based on the photovoltaic panel angle θ i , the suitable panel angle θ 0i (t), the seasonal adjustment factor S(t) and the environmental impact factor E i (I,T i ) to obtain the adjustment coefficient K of each photovoltaic power generation device θi : Where W represents the weight factor, Δθ represents the PV panel angle deviation threshold; Determine, based on the adjustment coefficient, a photovoltaic power generation device that needs to adjust the photovoltaic panel angle as the first adjustment device; Based on the photovoltaic panel angle deviation of the first adjustment device, the adjustment direction and adjustment amount of the photovoltaic panel angle of the first adjustment device are obtained as the first adjustment scheme and executed.

3. A distributed photovoltaic thermal power generation and energy storage control system for residential areas according to claim 2, characterized in that: The seasonal adjustment factor S(t) is specifically: Among them, A s represents the amplitude adjustment coefficient, t d Indicates the current date, t s The date indicating the winter solstice or the summer solstice.

4. A distributed photovoltaic thermal power generation and energy storage control system for residential areas according to claim 3, characterized in that: The environmental impact factor E i (I,T i ) specifically: Among them, α and β represent empirical constants, I r Indicates the light intensity under standard test conditions, T r Indicates the temperature under standard test conditions.

5. A distributed photovoltaic thermal power generation and energy storage control system for residential areas according to claim 4, characterized in that: The photovoltaic equipment evaluation module function realization process includes: Obtain the actual power generation P of each photovoltaic power generation device ai (t) and reference power generation P ri (t); Get the surface temperature T of the photovoltaic panels of each photovoltaic power generation device pi (t) and the optimum operating temperature T oi ; Get the ambient temperature T at the current time t e (t); Based on the actual power generation P ai (t), reference power generation P ri (t), surface temperature T pi (t), optimal working temperature T oi and ambient temperature T e (t) obtaining the first performance coefficient of each photovoltaic power generation device: Where ΔT represents the maximum allowable temperature deviation, I ti It represents the light intensity measured by each photovoltaic power generation device in real time, I r represents the light intensity under standard test conditions of each photovoltaic power generation equipment, γ represents the empirical constant of the effect of temperature on efficiency, T v (t) represents the ambient temperature at the current time t, w1, w2, w3, w4, w5 and w6 represent the weight coefficients of each index respectively, F a (t) represents the performance attenuation factor of each photovoltaic power generation device; The photovoltaic power generation equipment whose first performance coefficient is less than a set value is selected as the abnormal photovoltaic equipment.

6. A distributed photovoltaic thermal power generation and energy storage control system for residential areas according to claim 1, characterized in that: The function realization process of the charging and discharging decision module includes: Determine whether the current time period is in the valley price period, if not, do not perform charging operation; If so, then the charging input energy E is obtained based on the charging and discharging efficiency of the energy storage system. in and discharge output energy E out ; Obtain the energy consumption cost C of the auxiliary equipment of the energy storage system au ; Based on the charging input energy E in , discharge output energy E out and auxiliary equipment energy consumption cost C au Get the charging execution coefficient R: R=E out ×C peak -E in ×C valley -C au ; Among them, C peak represents the peak electricity price, C valley Indicates the electricity price during the valley period; When the charging execution coefficient R is greater than an execution threshold, the energy storage system performs a charging operation to obtain the charging plan; The electric energy in the energy storage system is released preferentially based on actual electricity demand to obtain the discharge plan.

7. A distributed photovoltaic thermal power generation and energy storage control system for residential areas according to claim 6, characterized in that: The function realization process of the charging and discharging decision module also includes: When executing the charging scheme, the optimal charging capacity is obtained based on the charging execution coefficient R and related constraints. The constraints are: E in ≤S max -S current ; 0.2S max ≤Sa(t)≤0.8S max ; Among them, S max Indicates the maximum rated capacity of the energy storage device, S current represents the current storage energy of the energy storage device, Sa(t) represents the actual charge state of the energy storage device at time point t, and E total Indicates that from t start to end The total available energy of the energy storage system during this period, t start and t end Represent the charging start time and end time respectively, PV,forecasted(t) Represents the future photovoltaic power forecast value calculated based on weather forecast.

8. A distributed photovoltaic thermal power generation and energy storage control system for residential areas according to claim 1, characterized in that: The function realization process of the heat collecting equipment adjustment module includes: Get the actual heat collection Q of each heat collection device at time t aj (t) and expected heat collection Q cj (t), j represents the number of the jth solar collector; Obtaining the surface temperature T1(t) and the optimal operating temperature T2 of each heat collecting device at time t; The comprehensive coefficient P of each heat collecting device is obtained based on the actual heat collection amount, the expected heat collection amount, the surface temperature and the optimal working temperature evj (t): Among them, η j (t) represents the thermal energy conversion efficiency of the jth collector at time t, a1, a2 and a3 represent the weight coefficients of various indicators, ΔT n Indicates the maximum allowable deviation of the collector, I tk It represents the light intensity measured by each collector in real time, I x Indicates the light intensity under standard test conditions of each collector equipment; F b (t) represents the performance attenuation factor of each solar collector; Selecting a heat collecting device whose comprehensive coefficient is less than a target threshold as the second adjustment device; An angle adjustment amount of the second adjustment device is determined based on the comprehensive coefficient of the second adjustment device and the target threshold value, and is executed as the second adjustment scheme.

9. A distributed photovoltaic thermal power generation and energy storage control system for residential areas according to claim 8, characterized in that: The function realization process of the heat collecting equipment adjustment module also includes: Based on the comprehensive coefficient P of the second adjustment device evj (t) and the target threshold P tar Get the performance deviation e(t): e(t)=P tar -P evj (t); Based on the performance deviation e(t), a PID controller is used to obtain the angle adjustment value Δθ adj (t): Among them, Kp, Ki and Kd represent proportional gain, integral gain and differential gain respectively. represents the cumulative sum of all errors from the start time to the current time t, Represents the rate of change of error over time.

10. A distributed photovoltaic thermal power generation and energy storage control system for residential areas according to claim 3 or 8, characterized in that: The function realization process of the thermal collector equipment evaluation module includes: Obtain the thermal energy conversion efficiency η of each collector at time t j (t); Get the current pollution level of each collector device δ j and the maximum permissible pollution degree δ jmax ; Based on the current pollution level δ j and the maximum permissible contamination degree δ jmax Get the cleanliness factor Cj clean (t): Based on the thermal energy conversion efficiency η j (t) and cleanliness factor Cj clean (t) Obtain the second comprehensive performance coefficient P 2j (t): Among them, c1, c2, c3, c4 and c5 represent the weight coefficients of each indicator respectively; A heat collecting device whose second performance coefficient is less than a preset value is selected as the abnormal heat collecting device.

Images