A distributed photovoltaic heat-generating power storage control system for residential areas

Abstract

The application discloses a kind of distributed photovoltaic heat collecting power generation energy storage control systems for residential area, photovoltaic equipment adjustment module is dynamically adjusted photovoltaic panel angle according to season and environmental change, to maximize light energy absorption efficiency, and formulate operation scheme;Photovoltaic equipment evaluation module monitors the power generation performance of each device, and identifies the abnormal device with poor performance;Charging and discharging decision module then according to time and the efficiency of energy storage device, intelligent planning charging and discharging strategy, balance power supply and demand;Heat collecting equipment adjustment module optimizes heat collecting efficiency through comprehensive coefficient, and heat collecting equipment evaluation module evaluates heat conversion efficiency and cleanliness, and selects abnormal equipment;Comprehensive feedback module real-time transmission all monitoring data and generated optimization scheme to control terminal, so that management personnel can respond in time and take necessary maintenance measures.Precision regulation of photovoltaic power generation equipment and heat collecting equipment is realized, and abnormal photovoltaic power generation equipment and heat collecting equipment are accurately identified, to ensure the safety of energy storage system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of photovoltaic heat collection power generation and energy storage integration control, more particularly to a distributed photovoltaic heat collection power generation and energy storage control system for residential areas. BACKGROUND

[0002] With the increasing demand for clean energy and the gradual depletion of traditional energy sources, solar energy as a clean and renewable energy source has received widespread attention. In the field of residential areas, distributed photovoltaic (PV) heat collection power generation and energy storage control systems have become an important solution, which not only effectively utilizes solar energy resources, but also solves the intermittency and instability of photovoltaic power generation through energy storage technology, improving the quality and reliability of power supply.

[0003] Although the distributed photovoltaic heat collection power generation and energy storage control system has shown great potential in clean energy utilization, the existing technology still faces some problems to be solved: lack of effective abnormality detection mechanism, the existing method pays more attention to static indicators, and ignores potential risk points in dynamic operation process, for example, when encountering extreme weather events or equipment aging, simple performance coefficient calculation may not fully reflect the true state of the equipment; the energy storage strategy of most current systems is relatively single, which may cause overcharging or underutilization of the energy storage device, thereby affecting the battery life; the existing method focuses on obtaining heat collection and related parameters to evaluate the performance of heat collection equipment, but in actual operation, the performance of heat collection equipment is affected by many factors, such as surface cleanliness, heat conversion efficiency, etc., so the existing method cannot accurately evaluate the performance of heat collection equipment.

[0004] Therefore, how to accurately adjust photovoltaic power generation equipment and heat collection equipment, accurately identify abnormal photovoltaic power generation equipment and heat collection equipment, and ensure the safety of the energy storage system are problems that need to be solved by those skilled in the art. SUMMARY

[0005] Therefore, the present application provides a distributed photovoltaic heat collection power generation and energy storage control system for residential areas, which realizes accurate adjustment of photovoltaic power generation equipment and heat collection equipment, accurate identification of abnormal photovoltaic power generation equipment and heat 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 purpose, the technical scheme adopted by the present application is as follows:

[0007] A distributed photovoltaic heat collection power generation and energy storage control system for residential areas comprises:

[0008] Photovoltaic equipment adjustment module: used to obtain the angle of the photovoltaic panels 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 factors;

[0009] Photovoltaic equipment evaluation module: used to obtain 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 identify photovoltaic power generation devices that do not meet the performance standards as abnormal photovoltaic devices;

[0010] Charge / discharge decision module: used to obtain a charging execution coefficient based on the current time period and the charging / discharging efficiency of the energy storage device, to obtain a charging scheme for the energy storage device based on the charging execution coefficient, and to obtain a discharging scheme based on the power demand.

[0011] The solar collector adjustment module is used to obtain the heat collection capacity and related parameters of each solar collector to obtain a comprehensive coefficient, and to determine a second adjustment scheme for the operation of each solar collector based on the comprehensive coefficient.

[0012] The solar collector evaluation module is used to obtain the heat conversion efficiency and cleanliness factor of each solar collector, derive a second performance coefficient, and further identify solar collectors that fail to meet performance standards as abnormal solar collectors; and,

[0013] Integrated feedback module: used to feed back the abnormal photovoltaic equipment, the abnormal thermal collector, the first adjustment scheme, the charging scheme, the discharging scheme and the second adjustment scheme to the control terminal.

[0014] Preferably, the process of implementing the photovoltaic equipment adjustment module includes:

[0015] Obtain 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) was obtained based on the seasonal effects.

[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 The environmental impact factor E of the i-th photovoltaic power generation device is obtained. 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 The adjustment coefficient K of each photovoltaic power generation device is obtained.θi :

[0019]

[0020] Where W represents the weighting factor, and Δθ represents the photovoltaic panel angle deviation threshold;

[0021] Based on the adjustment coefficient, the photovoltaic power generation equipment whose photovoltaic panel angle needs to be adjusted is determined as the first adjustment equipment;

[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 t represents the amplitude adjustment factor. d t represents the current date. s It indicates the date of the winter solstice or the summer solstice.

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

[0027]

[0028] Where α and β represent empirical constants, I r T represents the light intensity under standard test conditions. r This indicates the temperature under standard test conditions.

[0029] Preferably, the process of implementing the photovoltaic equipment evaluation module includes:

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

[0031] Obtain the surface temperature T of the photovoltaic panel of each photovoltaic power generation device. pi (t) and optimal operating temperature T oi ;

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

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

[0034]

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

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

[0037] Preferably, the function implementation process of the charge / discharge decision module includes:

[0038] Determine whether the current time period is a low price period; if not, do not perform charging operation.

[0039] 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 ;

[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 Energy consumption cost of auxiliary equipment C au The charging execution coefficient R is obtained as follows:

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

[0043] Among them, C peak C represents the peak electricity price. valley This indicates the electricity price during off-peak periods.

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

[0045] based on the actual electricity demand, to obtain the discharging scheme.

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

[0047] When the charging scheme is executed, the optimal charging amount is obtained based on the charging execution coefficient R and the related constraint conditions

[0048]

[0049] The constraint conditions are:

[0050] E in ≤S max -S current ;

[0051] 0.2S max ≤Sa(t)≤0.8S max ;

[0052]

[0053] wherein, S max represents the maximum rated capacity of the energy storage device, S current represents the current energy storage amount of the energy storage device, Sa(t) represents the actual state of charge of the energy storage device at time point t, E total represents the total amount of available energy of the energy storage system from t start to t end , t start and t end represent the charging start time and the charging end time respectively, and P PV,forecasted(t) represents the future photovoltaic power prediction value calculated based on the weather forecast.

[0054] Preferably, the function implementation process of the heat collecting device adjustment module comprises:

[0055] obtaining the actual heat collection amount Q aj (t) and the expected heat collection amount Q cj (t) of each heat collecting device at time t, wherein j represents the number of the jth heat collecting device;

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

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

[0058]

[0059] wherein, η j (t) represents the thermal energy conversion efficiency of the jth thermal collector at time t, a1, a2 and a3 represent the weight coefficients of each index respectively, ΔT n represents the maximum allowable deviation of the collector, I tk represents the real-time measured light intensity of each thermal collector, I x represents the light intensity of each thermal collector under standard test conditions; F b (t) represents the performance attenuation factor of each thermal collector;

[0060] selecting the thermal collector with the comprehensive coefficient less than the target threshold as the second adjustment device;

[0061] determining the angle adjustment amount of the second adjustment device based on the comprehensive coefficient of the second adjustment device and the target threshold, as the second adjustment scheme and executing.

[0062] Preferably, the function implementation process of the thermal collector adjustment module further comprises:

[0063] determining the performance deviation e(t) based on the comprehensive coefficient P evj (t) of the second adjustment device and the target threshold P tar .

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

[0065] obtaining the angle adjustment amount Δθ adj (t) based on the performance deviation e(t) using a PID controller.

[0066]

[0067] wherein, Kp, Ki and Kd represent the 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 with time.

[0068] Preferably, the function implementation process of the thermal collector evaluation module comprises:

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

[0070] obtaining the current pollution degree δ j and the maximum allowable pollution degree δ jmax of each thermal collector.

[0071] based on the current pollution degree δ j and the maximum allowed pollution degree δ jmax obtain a cleanliness factor Cj clean (t):

[0072]

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

[0074]

[0075] wherein c1, c2, c3, c4 and c5 represent the weight coefficients of each index respectively;

[0076] select the heat collecting device with the second performance coefficient less than the preset value as the abnormal heat collecting device.

[0077] Via the above technical solution, compared with the prior art, the present disclosure provides a distributed photovoltaic heat collecting and power generating and energy storage control system for residential areas, which has the following beneficial effects:

[0078] 1. Optimize photovoltaic power generation performance: through the photovoltaic device adjustment module, the system can automatically adjust the angle of the photovoltaic panel according to seasonal changes and environmental conditions, ensuring 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 component, abnormal photovoltaic devices can be identified in time for maintenance or replacement, ensuring the efficient and stable operation of the entire photovoltaic system.

[0079] 2. Improve thermal energy utilization rate: the heat collecting device adjustment module combined with the evaluation module can accurately control the working parameters of each heat collecting device, such as angle, to match actual needs and maintain high thermal conversion efficiency. At the same time, the cleaning condition of the heat collector is checked regularly to prevent efficiency decline due to dust accumulation and maintain good heat absorption effect.

[0080] 3. Intelligent charging and discharging decision: the charging and discharging decision module takes into account the peak and valley price difference of the electricity market, choosing to charge the energy storage battery when the electricity price is low and release the stored energy for user use or sell to the grid during peak periods, thereby reducing costs and increasing revenue. It also takes into account the state of health of the energy storage system (such as state of charge) to avoid excessive charging and discharging damage to battery life.

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

[0082] 5. Promoting green and low-carbon development: The use of distributed energy solutions can meet the growing demand for residential power consumption without increasing carbon emissions. The application of such technologies is of great significance in reducing greenhouse gas emissions.

[0083] 6. The control system of the present application, with its high integration and intelligence, not only improves energy conversion efficiency, but also makes a positive contribution to energy saving and emission reduction. It is not only suitable for newly built residential areas, but also can be used as part of the energy saving reconstruction of existing residential areas, showing broad application prospects and development potential. BRIEF DESCRIPTION OF DRAWINGS

[0084] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only a part of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of the provided drawings.

[0085] Figure 1 A structural diagram of a distributed photovoltaic heat collection and power generation energy storage control system for residential areas is provided.

[0086] Figure 2 A flow chart of a distributed photovoltaic heat collection and power generation energy storage control method for residential areas is provided.

[0087] Figure 3 A structural diagram of a computer device is provided. DETAILED DESCRIPTION

[0088] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0089] Embodiment 1

[0090] As shown in Figure 1 , the present application discloses a distributed photovoltaic heat collection and power generation energy storage control system for residential areas, comprising:

[0091] Photovoltaic equipment adjustment module: used to obtain the angle of the photovoltaic panels 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 factors;

[0092] Photovoltaic equipment evaluation module: used to obtain 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 identify photovoltaic power generation devices that do not meet the performance standards as abnormal photovoltaic devices;

[0093] Charge / discharge decision module: used to obtain the charging execution coefficient based on the current time period and the charging / discharging efficiency of the energy storage device, obtain the charging scheme of the energy storage device based on the charging execution coefficient, and obtain the discharging scheme based on the power demand;

[0094] The solar collector adjustment module is used to obtain the heat collection capacity and related parameters of each solar collector to obtain a comprehensive coefficient, and to determine a second adjustment scheme for the operation of each solar collector based on the comprehensive coefficient.

[0095] The solar collector evaluation module is used to obtain the heat conversion efficiency and cleanliness factor of each solar collector, derive a second performance coefficient, and further identify substandard solar collectors as abnormal solar collectors; and,

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

[0097] Example 2

[0098] like Figure 1 As shown, this embodiment of the 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 angle of the photovoltaic panels 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 factors.

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

[0101] Obtain 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) was obtained based on the seasonal effects.

[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 The environmental impact factor E of the i-th photovoltaic power generation device is obtained.i (I,T i )。

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

[0105]

[0106] where A s represents the amplitude adjustment coefficient, calibrated according to geographical location and historical data, t d represents the current date (in days within a year), t s represents the date of the winter solstice or the summer solstice.

[0107] The environmental impact factor E i (I,T i ) is specifically:

[0108]

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

[0110] Preferably, t s depends on which point is chosen as the reference point. For example, in the northern hemisphere, the summer solstice occurs around day 172 of the year (around June 21), while the winter solstice occurs around day 355 (around December 22).

[0111] Preferably, the seasonal adjustment factor S(t) mainly considers the influence of the change of the solar elevation angle with the seasons, as well as the change of the sunshine duration. The specific solar elevation angle of a day is calculated based on astronomical algorithms, and the angle of the photovoltaic panel is adjusted accordingly.

[0112] Preferably, the exponential function in the environmental impact factor E i (I,T i ) is used to describe the influence of temperature on photovoltaic efficiency, which decays exponentially with the increase of temperature; at the same time, it is multiplied by the proportion of light intensity to ensure that the change of efficiency can be correctly reflected under different light conditions.

[0113] Preferably, the light intensity I r under standard test conditions in this embodiment is set to 1000 W / m 2 ; and the temperature T r under standard test conditions is set to 25℃.

[0114] Preferably, the function implementation process of the photovoltaic device adjustment module also includes:

[0115] Based on the 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 device θi :

[0116]

[0117] wherein W represents a weight factor to emphasize the importance of the photovoltaic panel angle in system performance evaluation, and Δθ represents a photovoltaic panel angle deviation threshold value;

[0118] Based on the adjustment coefficient, the photovoltaic power generation device that needs to adjust the photovoltaic panel angle is determined as the first adjustment device;

[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 the 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 adjustment coefficient obtained more accurately evaluates whether the angle of the photovoltaic panel is suitable, and can be dynamically adjusted according to the actual situation, thereby improving the overall performance of the system.

[0121] Photovoltaic device evaluation module: used to obtain the power generation amount and environmental information of each photovoltaic power generation device, to obtain the first performance coefficient of each photovoltaic power generation device, and further to determine the photovoltaic power generation device whose performance does not meet the standard as an abnormal photovoltaic device.

[0122] Preferably, the function implementation process of the photovoltaic device evaluation module includes:

[0123] obtaining the actual power generation amount P ai (t) and the reference power generation amount P ri (t) of each photovoltaic power generation device;

[0124] obtaining the surface temperature T pi (t) and the optimal working temperature T oi of the photovoltaic panel of each photovoltaic power generation device;

[0125] obtaining the environmental temperature T e (t) at the current time t;

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

[0127]

[0128] wherein, ΔT represents the maximum allowable temperature deviation, I ti represents the real-time measured light intensity of each photovoltaic power generation device, I r represents the light intensity under standard test conditions of each photovoltaic power generation device, γ represents the empirical constant of the temperature effect 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, which can be adjusted according to actual conditions to reflect the importance of different factors, F a (t) represents the performance attenuation factor of each photovoltaic power generation device.

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

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

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

[0132] Preferably, the present embodiment sets the upper and lower control limits as the set value through 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, it is considered that the device has potential problems as an abnormal photovoltaic device, which needs to be further checked.

[0133] Preferably, the weight coefficients wi are set according to specific application scenarios and importance. For example, if the power generation capacity is the most critical index, w1 can be given a higher value; if temperature management is crucial, the weights of w2 and w4 should be appropriately increased. The sum of all weight coefficients should be equal to 1, ensuring that each factor remains balanced.

[0134] Preferably, the present application can more comprehensively evaluate the performance of photovoltaic power generation devices through the first performance coefficient formula, not limited to power generation capacity, but also including temperature management, light conditions, device aging and other aspects, so as to more accurately identify devices with substandard performance and provide targeted maintenance recommendations.

[0135] The charge-discharge decision module is configured to obtain a charging execution coefficient based on the time period and the charge-discharge efficiency of the energy storage device, obtain a charging scheme of the energy storage device based on the charging execution coefficient, and obtain a discharging scheme based on the electricity demand.

[0136] Preferably, the function implementation process of the charge-discharge decision module comprises:

[0137] determining whether the current time period is a valley price period, and if not, not performing the charging operation;

[0138] if yes, obtaining a charging input energy E in and a discharging output energy E out based on the charge-discharge efficiency of the energy storage system;

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

[0140] obtaining a charging execution coefficient R based on the charging input energy E in , the discharging output energy E out , and the auxiliary equipment energy consumption cost C au :

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

[0142] wherein C peak represents the peak price period electricity price, and C valley represents the valley price period electricity price;

[0143] when the charging execution coefficient R is greater than an execution threshold value, the energy storage system performs the charging operation to obtain a charging scheme, otherwise, maintaining the status or only supplementing part of the electricity to maintain the minimum operating level;

[0144] obtaining a discharging scheme based on the actual electricity demand to preferentially release the electricity in the energy storage system.

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

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

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

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

[0149] Preferably, the function implementation process of the charging and discharging decision module further comprises:

[0150] When the charging scheme is executed, the optimal charging amount is obtained based on the charging execution coefficient R and the related constraint conditions

[0151]

[0152] The constraint conditions are:

[0153] E in ≤ S max - S current ;

[0154] 0.2S max ≤ Sa(t) ≤ 0.8S max ;

[0155]

[0156] where S max represents the maximum rated capacity of the energy storage device, S current represents the existing energy storage amount of the energy storage device, Sa(t) represents the actual state of charge of the energy storage device at time point t, E total represents the total amount of energy available to the energy storage system from t start to t end , including the existing energy storage amount and the expected additional photovoltaic power generation contribution, t start and t end represent the charging start time and the charging end time respectively, and P PV,forecasted(t) represents the future photovoltaic power prediction value calculated based on the weather forecast.

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

[0158] Preferably, 0.2S max ≤Sa(t)≤0.8S max For limiting the state of charge (SOC) range, wherein, 0.2S max represents 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 can maintain a minimum energy reserve to help deal with sudden demand peaks or power grid failures, ensuring the stability and reliability of power supply; ensure that the energy storage device will not be damaged by over-discharge in daily operation. 0.8S max represents 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 ensures that the energy storage device will not be damaged by overcharging in daily operation, and can effectively utilize its storage capacity to optimize energy management.

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

[0160] Preferably, For considering the impact of future photovoltaic power prediction on total energy.

[0161] Preferably, it also includes other restrictions: including but not limited to single maximum charging and discharging power, minimum charging period, etc., depending on the characteristics of the energy storage system and the application scenario.

[0162] Preferably, weather forecast information is crucial for predicting photovoltaic power generation, especially on sunny and cloudless days, when photovoltaic systems have a larger output; while in rainy weather, it may be significantly reduced. In order to more accurately estimate the future photovoltaic power generation potential, the present application adjusts the expected power generation of the photovoltaic array based on short-term weather forecast data (such as cloud cover, temperature, etc.) to obtain the future photovoltaic power prediction value P PV,forecasted(t) .

[0163] Preferably, the above optimal charging amount formula, not only considers the direct economic benefits, but also takes into account the influence of technical feasibility and environmental factors. It helps decision-makers to more scientifically and reasonably manage energy storage, so as to realize the win-win situation of economic benefits and social responsibility.

[0164] Heat collection equipment adjustment module: for obtaining the heat collection amount and related parameters of each heat collection equipment to obtain a comprehensive coefficient, and determining a second adjustment scheme for the operation of each heat collection equipment based on the comprehensive coefficient.

[0165] Preferably, the function implementation process of the heat collection device adjustment module comprises:

[0166] acquiring the actual heat collection amount Q aj (t) of each heat collection device at time t; cj (t), j representing the number of the jth heat collection device;

[0167] acquiring the surface temperature T1(t) and the optimal working temperature T2 of each heat collection device at time t;

[0168] obtaining the comprehensive coefficient P evj (t) of each heat collection device based on the actual heat collection amount, the expected heat collection amount, the surface temperature and the optimal working temperature;

[0169]

[0170] wherein, η j (t) represents the thermal energy conversion efficiency of the jth heat collection device at time t, a1, a2 and a3 represent the weight coefficients of each index respectively, ΔT n represents the maximum allowable deviation of the heat collector, I tk represents the light intensity measured in real time by each heat collection device, I x represents the light intensity under standard test conditions of each heat collection device; F b (t) represents the performance attenuation factor of each heat collection device;

[0171] selecting the heat collection device with a comprehensive coefficient less than a target threshold value as a second adjustment device;

[0172] determining the angle adjustment amount of the second adjustment device based on the comprehensive coefficient of the second adjustment device and the target threshold value, taking the second adjustment amount as a second adjustment scheme and executing the second adjustment scheme.

[0173] Preferably, the expected heat collection amount Q cj (t) is calculated based on the current light condition and a theoretical model; the light intensity I x under standard test conditions of each heat collection device is set to 1000 W / m 2 .

[0174] Preferably, the comprehensive coefficient P directly reflects the actual performance of the heat collection device, the deviation between the surface temperature of the heat collector and the optimal working temperature ensures that the device operates within the optimal temperature range, a3·F reflects the influence of the light condition on the heat collection efficiency; a3·F b(t) is considered, which helps long-term performance evaluation. Through the above comprehensive coefficient, the performance of the heat collection device can be evaluated more comprehensively, not limited to heat conversion efficiency, but also including temperature management, light conditions and device aging, so as to more accurately identify the performance of the device that does not meet the standard 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 heat collection device.

[0176] Preferably, the sum of all weight coefficients a1, a2 and a3 is equal to 1, which ensures the balance between each factor.

[0177] Preferably, machine learning algorithms such as reinforcement learning and genetic algorithms are 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 operation requirements.

[0178] Preferably, the heat collection device adjustment module function implementation process further includes:

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

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

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

[0182]

[0183] Where Kp, Ki and Kd represent proportional gain, integral gain and differential gain, 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, the present embodiment determines an initial optimal heat collector panel angle θ base (t) based on the seasonal adjustment factor S(t) and the sun position information α(t):

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

[0186] Where θ fixedIndicates the basic installation angle, Δ θ The angle increment is represented by f(α(t)), which is calculated based on the real-time position of the sun.

[0187] Preferably, based on the optimal collector panel angle θ base (t) and angle adjustment Δθ adj (t) Sum to obtain the final adjusted collector panel angle θ opt (t):

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

[0189] The solar collector evaluation module is used to obtain the heat conversion efficiency and cleanliness factor of each solar collector, obtain the second performance coefficient, and further identify the solar collectors that do not meet the performance standards as abnormal solar collectors.

[0190] Preferably, the implementation process of the solar collector evaluation module includes:

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

[0192] Obtain the current pollution level δ of each solar collector. j and the maximum permissible pollution level δ jmax ;

[0193] Based on the current pollution level δ j and maximum permissible pollution level δ jmax The cleanliness factor Cj was obtained. clean (t):

[0194]

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

[0196]

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

[0198] The heat collection device with a second performance coefficient less than the preset value is selected as the abnormal heat collection device.

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

[0200]

[0201] Among them, E solar (t) represents the total solar irradiance (W / m²) 2 ), A collector Represents the heat collection area (m²) 2 ).

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

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

[0204] Preferably, the integrated feedback module aggregates all detected information to the control terminal, facilitating real-time monitoring of the system status by operators and enabling rapid response to potential problems. This helps prevent potential failures and ensures the long-term stable operation of the system.

[0205] Example 3

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

[0207] Obtain the angle of the photovoltaic panels 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 factors;

[0208] The power generation and environmental information of each photovoltaic power generation device are obtained, the first performance coefficient of each photovoltaic power generation device is obtained, and the photovoltaic power generation devices that do not meet the performance standards are further identified as abnormal photovoltaic devices.

[0209] The charging execution coefficient is obtained based on the time period and the charging and discharging efficiency of the energy storage device. The charging scheme of the energy storage device is obtained based on the charging execution coefficient. The discharging scheme is obtained based on the electricity demand.

[0210] A comprehensive coefficient is obtained by acquiring the heat collection capacity and related parameters of each heat collection device, and a second adjustment scheme for the operation of each heat collection device is determined based on the comprehensive coefficient.

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

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

[0213] Preferably, each step in the embodiment realizes the process corresponding to the function of the above-mentioned functional module, which will not be described one by one.

[0214] Embodiment 4

[0215] Based on the same inventive concept, the present application also provides a computer device comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete the communication among each other through the communication bus;

[0216] The memory is used for storing a computer program.

[0217] The processor is used for executing the program stored on the memory, and can realize the distributed photovoltaic heat collecting power generation and energy storage control method for residential areas in embodiment 3.

[0218] As shown in Figure 3 the electronic device can include: a processor 31, a communication interface 32, a memory 33 and a communication bus 34, wherein the processor 31, the communication interface 32, the memory 33 complete the communication among each other through the communication bus 34. The processor 31 can call the logical instructions in the memory 33 to execute the distributed photovoltaic heat collecting power generation and energy storage control method for residential areas in embodiment 3.

[0219] In addition, the logical instructions in the memory 33 described above can be realized in the form of a software functional unit and sold or used as an independent product, which can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or part of the technical solutions can be embodied in the form of a software product, and the computer software product stored in a storage medium includes a plurality of instructions for making a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk and various program code storage media.

[0220] Through the above technical solutions, the present application provides a distributed photovoltaic heat collecting 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 device adjustment module, the system can automatically adjust the angle of the photovoltaic panel according to seasonal changes and environmental conditions, ensuring 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 component, abnormal photovoltaic devices can be identified in time for maintenance or replacement, ensuring the efficient and stable operation of the entire photovoltaic system.

[0222] 2. Improve heat utilization rate: The heat collection device adjustment module combined with the evaluation module can accurately control the working parameters of each heat collection device, such as angle, to match actual needs and maintain high heat conversion efficiency. At the same time, regular checks are made on the cleanliness of the collector to prevent efficiency decline due to dust accumulation and maintain good heat absorption effect.

[0223] 3. Intelligent charging and discharging decision: The charging and discharging decision module takes into account the peak and valley price differences in the electricity market, choosing to charge the energy storage battery when the price is low and release the stored energy for user use or sell to the grid during peak periods, thereby reducing costs and increasing revenue. It also takes into account the state of health of the energy storage system (such as state of charge) to avoid excessive charging and discharging damage to 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 system status in real time and respond quickly to potential problems. This helps prevent potential failures and ensures long-term stable operation of the system.

[0225] 5. Promote green and low-carbon development: The use of distributed energy solutions can meet the growing demand for residential power consumption without increasing carbon emissions. The application of such technology is of great significance in reducing greenhouse gas emissions.

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

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

[0228] The foregoing description of the disclosed embodiments enables a person skilled in the art to make or use the application. Modifications of these embodiments will occur to persons of skill in the art, and that the appended claims are intended to cover all such modifications that do not depart from the true spirit and scope of the application. Therefore, the application is not limited to the embodiments shown but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A distributed photovoltaic heat-generating power storage control system for residential areas, characterized in that, The application relates to a photovoltaic device adjustment module, a photovoltaic device evaluation module, a charging and discharging decision module, a heat collection device adjustment module, a heat collection device evaluation module and a comprehensive feedback module. The photovoltaic device adjustment module is used for acquiring photovoltaic panel angles of photovoltaic power generation devices in a residential area, combining seasonal and environmental influences to determine a first adjustment scheme for operation of the photovoltaic power generation devices. The photovoltaic device evaluation module is used for acquiring power generation amounts and environmental information of the photovoltaic power generation devices, obtaining first performance coefficients of the photovoltaic power generation devices, and further determining photovoltaic power generation devices with substandard performance as abnormal photovoltaic devices. The charging and discharging decision module is used for obtaining a charging execution coefficient based on a time period and charging and discharging efficiency of an energy storage device, obtaining a charging scheme of the energy storage device based on the charging execution coefficient, and obtaining a discharging scheme based on power consumption demand. The charging and discharging decision module function implementation process comprises the following steps: If the current time period is not a valley price period, no charging operation is performed. If yes, the charging input energy E is obtained based on the charging and discharging efficiency of the energy storage system in and the discharging output energy E out ; obtaining an auxiliary equipment energy consumption cost C of the energy storage system au ; based on the charging input energy E in , the discharge output energy E out and the auxiliary equipment energy consumption cost C au to obtain a charging execution coefficient R: R = E out x C peak -E in x C valley -C au ; wherein C peak represents the peak price period electricity price, C valley represents the valley price period electricity price; The auxiliary device energy consumption cost C au Specifically: C au = P auxiliary × (t charge + t discharge ) × C average ; where P auxiliary represents the average power consumption of the auxiliary device, t charge represents the charging duration, t discharge represents the discharging duration, C average represents the average electricity price over the entire charging and discharging cycle; When the charging execution coefficient R is greater than an execution threshold value, the energy storage system performs a charging operation to obtain the charging scheme. Based on actual power consumption demand, the energy in the energy storage system is preferentially released to obtain the discharging scheme. When the charging scheme is executed, an optimal charging amount is obtained based on the charging execution coefficient R and related constraint conditions The heat collection device adjustment module is used for acquiring heat collection amounts and related parameters of heat collection devices to obtain comprehensive coefficients, and determining a second adjustment scheme for operation of the heat collection devices based on the comprehensive coefficients. E in ≤S max -S current ; 0.2S max ≤ Sa(t) ≤ 0.8S max ; where S max denotes the maximum rated capacity of the energy storage device, S current denotes the currently available energy storage capacity of the energy storage device, Sa(t) denotes the actual state of charge of the energy storage device at time point t, E total denotes the total amount of energy available to the energy storage system from t start to t end , t start and t end denote the start and end times of the charging period, P PV,forecasted(t) denotes the future photovoltaic power prediction calculated based on the weather forecast; Adjusting the expected power production of a photovoltaic array in conjunction with short-term weather forecast data results in a future photovoltaic power prediction value P calculated based on weather forecasts PV,forecasted(t) ; The heat collection device evaluation module is used for acquiring heat conversion efficiency and cleanliness factors of the heat collection devices to obtain second performance coefficients, and further determining heat collection devices with substandard performance as abnormal heat collection devices. The comprehensive feedback module is used for feeding back the abnormal photovoltaic devices, the abnormal heat collection devices, the first adjustment scheme, the charging scheme, the discharging scheme and the second adjustment scheme to a control terminal. The photovoltaic device adjustment module function implementation process comprises the following steps:

2. The distributed photovoltaic heat-generating power storage control system for residential areas according to claim 1, characterized in that, A seasonal adjustment factor S(t) is obtained based on seasonal influences. acquiring a photovoltaic panel angle θ of each photovoltaic power generation device i and a suitable panel angle θ at the current time t 0i (t); Wherein, W represents a weight factor, and Delta theta represents a photovoltaic panel angle deviation threshold value. based on the real-time measured light intensity I and the real-time temperature T of the surface of the photovoltaic panel of the i-th photovoltaic power generation device i obtaining the environmental influence factor E of the i-th photovoltaic power generation device 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 θi for each photovoltaic power plant. Based on the adjustment coefficient, a photovoltaic power generation device needing to adjust the photovoltaic panel angle is determined as a 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 are executed. The seasonal adjustment factor S(t) is specifically as follows:

3. The distributed photovoltaic heat-generating power storage control system for residential areas according to claim 2, characterized in that, The photovoltaic device evaluation module function implementation process comprises the following steps: where A s represents an amplitude adjustment coefficient, t d represents the current date, t s represents the date of the winter or summer solstice.

4. The 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 ) is in particular: wherein a and β represent empirical constants, I r represents the light intensity under standard test conditions, T r represents the temperature under standard test conditions.

5. The distributed photovoltaic thermal power generation and energy storage control system for residential areas according to claim 4, wherein, The photovoltaic power generation device with the first performance coefficient less than a set value is selected as the abnormal photovoltaic device. acquiring actual power generation amount P of each photovoltaic power generation device ai (t) and reference power generation amount P ri (t); acquiring the surface temperature T of the photovoltaic panel of each photovoltaic power plant pi (t) and the optimal operating temperature T oi ; Obtaining an ambient temperature T at a current time t e (t); based on the actual power generation P ai (t), the reference power generation P ri (t), the surface temperature T pi (t), the optimal operating temperature T oi and the ambient temperature T e (t) to obtain the first performance coefficient of each photovoltaic power generation device: wherein ΔT represents the maximum allowable temperature deviation, I ti represents the light intensity measured in real time by each photovoltaic power generation device, I r represents the light intensity under standard test conditions of each photovoltaic power generation device, γ represents an 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 heat collection device adjustment module function implementation process comprises the following steps:

6. The distributed photovoltaic thermal power generation and energy storage control system for residential areas according to claim 1, wherein, The surface temperature T1(t) and the optimal working temperature T2 of the heat collection devices at t time are acquired. acquire the actual heat collection amount Q of each heat collection device at time t aj (t) and the expected heat collection amount Q cj (t), j represents the number of the jth heat collection device The heat collection device with the comprehensive coefficient less than a target threshold value is selected as a second adjustment device. 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): wherein 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 each index respectively, ΔT n represents the maximum allowable deviation of the collector, I tk represents the real-time measured light intensity of each collector, I x represents the light intensity under standard test conditions of each collector; F b (t) represents the performance attenuation factor of each collector; Based on the comprehensive coefficient of the second adjustment device and the target threshold value, the angle adjustment amount of the second adjustment device is determined as the second adjustment scheme and is executed. The heat collection device adjustment module function implementation process further comprises the following steps:

7. The distributed photovoltaic thermal power generation and energy storage control system for residential areas according to claim 6, wherein, The heat collection device evaluation module function implementation process comprises the following steps: based on the overall coefficient P of the second adjusting device evj (t) and the target threshold value P tar a performance deviation e(t) is obtained e(t) = P tar - P evj (t); obtaining an angle adjustment amount Δθ based on the performance deviation e(t) using a PID controller adj (t): where Kp, Ki, and Kd represent a proportional gain, an integral gain, and a differential gain, respectively, denotes a cumulative sum of all errors from a start time to a current time t, denotes a rate of change of the error with respect to time.

8. The distributed photovoltaic heat-generating power storage control system for residential areas according to claim 3 or 6, characterized in that, Wherein, c1, c2, c3, c4 and c5 respectively represent weight coefficients of the indexes. acquiring the thermal energy conversion efficiency η of each heat collecting device at time t j (t); acquiring the current pollution degree δ of each heat collecting device j and the maximum allowed pollution degree δ jmax ; based on the current pollution level δ j and the maximum allowed pollution level δ jmax a cleanliness factor Cj clean (t): based on said thermal energy conversion efficiency η j (t) and a cleanliness factor Cj clean (t) to obtain said second performance coefficient P 2j (t): The heat collection device with the second performance coefficient less than a preset value is selected as the abnormal heat collection device. ​

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