CN120016953B - Distributed photovoltaic heat collection power generation energy storage control system for residential area - Google Patents

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

Info

Publication number
CN120016953B
CN120016953B CN202510181635.4A CN202510181635A CN120016953B CN 120016953 B CN120016953 B CN 120016953B CN 202510181635 A CN202510181635 A CN 202510181635A CN 120016953 B CN120016953 B CN 120016953B
Authority
CN
China
Prior art keywords
power generation
photovoltaic
sub
energy storage
adjustment
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202510181635.4A
Other languages
Chinese (zh)
Other versions
CN120016953A (en
Inventor
张绪伟
丰百峰
刘璟
石风刚
盛飞龙
谭黎
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shandong Huake Planning Architectural Design Co ltd
Original Assignee
Shandong Huake Planning Architectural Design Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shandong Huake Planning Architectural Design Co ltd filed Critical Shandong Huake Planning Architectural Design Co ltd
Priority to CN202510181635.4A priority Critical patent/CN120016953B/en
Publication of CN120016953A publication Critical patent/CN120016953A/en
Application granted granted Critical
Publication of CN120016953B publication Critical patent/CN120016953B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24S—SOLAR HEAT COLLECTORS; SOLAR HEAT SYSTEMS
    • F24S20/00—Solar heat collectors specially adapted for particular uses or environments
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24S—SOLAR HEAT COLLECTORS; SOLAR HEAT SYSTEMS
    • F24S50/00—Arrangements for controlling solar heat collectors
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for AC mains or AC distribution networks
    • H02J3/001—Arrangements for handling faults or abnormalities, e.g. emergencies or contingencies
    • H02J3/0014—Arrangements for handling faults or abnormalities, e.g. emergencies or contingencies for preventing or reducing power oscillations in networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for AC mains or AC distribution networks
    • H02J3/007—Arrangements for selectively connecting one or more loads to one or more power sources or power lines
    • H02J3/0075—Arrangements for selectively connecting one or more loads to one or more power sources or power lines for providing alternative feeding paths between load and source according to economic or energy efficiency considerations, e.g. economic dispatch
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for AC mains or AC distribution networks
    • H02J3/28—Arrangements for balancing of the load in networks by storage of energy
    • H02J3/32—Arrangements for balancing of the load in networks by storage of energy using batteries or super capacitors with converting means
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries
    • H02J7/02—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries for charging batteries from AC mains by converters
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries
    • H02J7/60—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries including safety or protection arrangements
    • H02J7/61—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries including safety or protection arrangements against overcharge
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries
    • H02J7/60—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries including safety or protection arrangements
    • H02J7/63—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries including safety or protection arrangements against overdischarge
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries
    • H02J7/865—Battery or charger load switching, e.g. concurrent charging and load supply
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00—Circuit arrangements for charging or discharging batteries or for supplying loads from batteries
    • H02J7/90—Regulation of charging or discharging current or voltage
    • H02J7/933—Regulation of charging or discharging current or voltage the cycle being controlled or terminated in response to electric parameters
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02S—GENERATION OF ELECTRIC POWER BY CONVERSION OF INFRARED RADIATION, VISIBLE LIGHT OR ULTRAVIOLET LIGHT, e.g. USING PHOTOVOLTAIC [PV] MODULES
    • H02S20/00—Supporting structures for PV modules
    • H02S20/30—Supporting structures being movable or adjustable, e.g. for angle adjustment
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02S—GENERATION OF ELECTRIC POWER BY CONVERSION OF INFRARED RADIATION, VISIBLE LIGHT OR ULTRAVIOLET LIGHT, e.g. USING PHOTOVOLTAIC [PV] MODULES
    • H02S40/00—Components or accessories in combination with PV modules, not provided for in groups H02S10/00 - H02S30/00
    • H02S40/40—Thermal components
    • H02S40/44—Means to utilise heat energy, e.g. hybrid systems producing warm water and electricity at the same time
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24S—SOLAR HEAT COLLECTORS; SOLAR HEAT SYSTEMS
    • F24S20/00—Solar heat collectors specially adapted for particular uses or environments
    • F24S2020/10—Solar modules layout; Modular arrangements
    • F24S2020/17—Arrangements of solar thermal modules combined with solar PV modules
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2101/00—Supply or distribution of decentralised, dispersed or local electric power generation
    • H02J2101/20—Dispersed power generation using renewable energy sources
    • H02J2101/22—Solar energy
    • H02J2101/24—Photovoltaics
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2105/00—Networks for supplying or distributing electric power characterised by their spatial reach or by the load
    • H02J2105/10—Local stationary networks having a local or delimited stationary reach
    • H02J2105/12—Local stationary networks having a local or delimited stationary reach supplying households or buildings
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers

Landscapes

  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Sustainable Development (AREA)
  • Sustainable Energy (AREA)
  • Thermal Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Photovoltaic Devices (AREA)

Abstract

The invention discloses a distributed photovoltaic heat collection power generation and energy storage control system for a residential area, which is characterized in that a photovoltaic device adjusting module dynamically adjusts angles of photovoltaic panels according to seasons and environmental changes to maximize light energy absorption efficiency and formulate an operation scheme, a photovoltaic device evaluation module monitors power generation performance of each device to identify abnormal devices with poor performance, a charge and discharge decision module intelligently plans a charge and discharge strategy according to the efficiency of a time and an energy storage device to balance power supply and demand, a heat collection device adjusting module optimizes heat collection efficiency through comprehensive coefficients, a heat collection device evaluation module evaluates heat conversion efficiency and cleanliness to screen out abnormal devices, and a comprehensive feedback module transmits all monitoring data and generated optimization schemes to a control terminal in real time so that management personnel can respond timely and take necessary maintenance measures. The accurate adjustment of photovoltaic power generation equipment and heat collecting equipment is realized, abnormal photovoltaic power generation equipment and heat collecting equipment are accurately identified, and the safety of an energy storage system is ensured.

Description

Distributed photovoltaic heat collection power generation energy storage control system for residential area
Technical Field
The invention relates to the technical field of integrated control of photovoltaic heat collection, power generation and energy storage, in particular to a distributed photovoltaic heat collection, power generation and energy storage control system for residential areas.
Background
With the increasing global demand for clean energy and the progressive exhaustion of traditional energy, solar energy has received widespread attention as a form of clean, renewable energy. In the residential area field, a distributed Photovoltaic (PV) heat collection, power generation and energy storage control system becomes an important solution, not only can solar energy resources be effectively utilized, but also the intermittent and unstable problems of Photovoltaic power generation can be solved through an energy storage technology, and the quality and reliability of power supply are improved.
Although the distributed photovoltaic heat collection power generation energy storage control system has great potential in terms of clean energy utilization, the prior art still faces some problems to be solved, namely, the lack of an effective abnormality detection mechanism, the existing method focuses more on static indexes, and potential risk points in the dynamic operation process are ignored, for example, when extreme climate events or equipment aging are encountered, simple performance coefficient calculation may not be enough to comprehensively reflect the real state of the equipment, the situation that an energy storage device is excessively charged and discharged or the utilization rate is insufficient may occur in the existing energy storage strategy of most systems, so that the service life of a battery is influenced, the existing method focuses on acquiring heat collection quantity and related parameters to evaluate the performance of the heat collection equipment, and in actual operation, the performance of the heat collection equipment is influenced by various factors, such as surface cleanliness, heat conversion efficiency and the like, so that the existing method cannot accurately evaluate the performance of the heat collection equipment.
Therefore, how to accurately realize the adjustment of the photovoltaic power generation device and the heat collection device, accurately identify the abnormal photovoltaic power generation device and the heat collection device, and ensure the safety of the energy storage system is a problem which needs to be solved by those skilled in the art.
Disclosure of Invention
In view of the above, the invention provides a distributed photovoltaic heat collection power generation energy storage control system for residential areas, which realizes the accurate adjustment of photovoltaic power generation equipment and heat collection equipment, accurately identifies abnormal photovoltaic power generation equipment and heat collection equipment, ensures the safety and economy of an energy storage system, greatly improves the application efficiency and service quality of clean energy, and provides powerful support for promoting the development of green residential areas.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
a distributed photovoltaic thermal-arrest power generation energy storage control system for a residential area, comprising:
The photovoltaic equipment adjusting module is used for acquiring the angles of photovoltaic panels of all photovoltaic power generation equipment in the residential area and determining a first adjusting scheme for the operation of all the photovoltaic power generation equipment by combining the seasonal and environmental influences;
The photovoltaic equipment evaluation module is used for acquiring the generated energy and the environmental information of each photovoltaic power generation equipment, obtaining a first performance coefficient of each photovoltaic power generation equipment, and further determining the photovoltaic power generation equipment with the performance not reaching the standard as abnormal photovoltaic equipment;
The charging and discharging decision module is used for obtaining a charging execution coefficient based on the time period and the charging and discharging efficiency of the 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 electricity demand;
the heat collecting equipment adjusting module is used for acquiring the heat collecting quantity and related parameters of each heat collecting equipment to obtain a comprehensive coefficient, and determining a second adjusting scheme for the operation of each heat collecting equipment based on the comprehensive coefficient;
The heat collecting equipment evaluation module is used for acquiring the heat conversion efficiency and the cleanliness factor of each heat collecting equipment to obtain a second performance coefficient and further determining the heat collecting equipment with the performance not reaching the standard as abnormal heat collecting equipment, and the heat collecting equipment evaluation module is used for acquiring the heat conversion efficiency and the cleanliness factor of each heat collecting equipment to obtain a second performance coefficient
And the comprehensive feedback module is used for feeding the abnormal photovoltaic equipment, the abnormal heat collection equipment, the first adjustment scheme, the charging scheme, the discharging scheme and the second adjustment scheme back to the control terminal.
Preferably, the photovoltaic device adjustment module function implementation process includes:
acquiring a photovoltaic panel angle theta i of each photovoltaic power generation device and a proper panel angle theta 0i (t) at the current time t;
Obtaining a seasonal adjustment factor S (t) based on the seasonal influence;
Obtaining an environmental impact factor E i(I,Ti of the ith photovoltaic power generation equipment based on the real-time measured illumination intensity I and the real-time temperature T i of the surface of the photovoltaic panel of the ith photovoltaic power generation equipment;
Obtaining an adjustment coefficient K θi of each photovoltaic power generation apparatus 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,Ti):
Wherein W represents a weight factor, and delta theta represents a photovoltaic panel angle deviation threshold;
determining a photovoltaic power generation device needing to adjust the angle of the photovoltaic panel as the first adjusting device based on the adjusting coefficient;
and obtaining the adjusting direction and the adjusting amount of the angle of the photovoltaic panel of the first adjusting device based on the angle deviation of the photovoltaic panel of the first adjusting device as the first adjusting scheme and executing the first adjusting scheme.
Preferably, the seasonal adjustment factor S (t) is specifically:
Where a s denotes an amplitude adjustment coefficient, t d denotes a current date, and t s denotes a date of winter or summer.
Preferably, the environmental impact factor E i(I,Ti) is specifically:
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.
Preferably, the photovoltaic device evaluation module function implementation process includes:
Acquiring an actual power generation amount P ai (t) and a reference power generation amount P ri (t) of each photovoltaic power generation device;
Acquiring the surface temperature T pi (T) and the optimal working temperature T oi of the photovoltaic panels of each photovoltaic power generation device;
Acquiring an ambient temperature T e (T) of the current time T;
Obtaining the first performance coefficient of each photovoltaic power generation device 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 environment temperature T e (T):
Wherein DeltaT represents the allowable maximum temperature deviation, I ti represents the illumination intensity measured by each photovoltaic power generation device in real time, I r represents the illumination intensity under the standard test condition of each photovoltaic power generation device, gamma represents the empirical constant of the influence of temperature on efficiency, T v (T) represents the environmental temperature at the current moment T, w1, w2, w3, w4, w5 and w6 respectively represent the weight coefficients of each index, and F a (T) represents the performance attenuation factor of each photovoltaic power generation device;
and selecting the photovoltaic power generation equipment with the first performance coefficient smaller than a set value as the abnormal photovoltaic equipment.
Preferably, the function implementation process of the charge-discharge decision module includes:
Judging whether the current period is in the valley price period or not based on the current period, and if not, not performing charging operation;
If yes, correspondingly obtaining charging input energy E in and discharging output energy E out based on the charging and discharging efficiency of the energy storage system;
Acquiring the energy consumption cost C au of auxiliary equipment of the energy storage system;
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:
R=Eout×Cpeak-Ein×Cvalley-Cau;
wherein, C peak represents the peak price period electricity price, and C valley represents the valley price period electricity price;
when the charging execution coefficient R is larger than an execution threshold value, the energy storage system executes charging operation to obtain the charging scheme;
And preferentially releasing the electric energy in the energy storage system based on the actual electricity demand to obtain the discharging scheme.
Preferably, the function implementation process of the charge-discharge decision module further includes:
When the charging scheme is executed, an optimal charge amount is obtained based on the charging execution coefficient R and related constraint conditions
The constraint conditions are as follows:
Ein≤Smax-Scurrent;
0.2Smax≤Sa(t)≤0.8Smax;
Wherein S max represents the maximum rated capacity of the energy storage device, S current represents the currently existing energy storage capacity 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 available energy amount of the energy storage system in the period 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 predicted value calculated based on weather forecast.
Preferably, the function implementation process of the heat collecting device adjusting module includes:
Acquiring the actual heat collection quantity Q aj (t) and the expected heat collection quantity Q cj (t) of each heat collection device at the moment t, wherein j represents the number of the jth heat collection device;
acquiring the surface temperature T 1 (T) and the optimal working temperature T 2 of each heat collecting device at the time T;
Obtaining the comprehensive coefficient P evj (t) of each heat collecting device based on the actual heat collecting amount, the desired heat collecting amount, the surface temperature, and the optimal operation temperature:
Wherein η j (T) represents the heat energy conversion efficiency of the jth heat collecting device at time T, a1, a2 and a3 respectively represent the weight coefficients of each index, deltaT n represents the maximum allowable deviation of the heat collector, I tk represents the illumination intensity measured by each heat collecting device in real time, I x represents the illumination intensity under the standard test condition of each heat collecting device, F b (T) represents the performance attenuation factor of each heat collecting device;
selecting heat collection equipment with the comprehensive coefficient smaller than a target threshold value as the second adjusting equipment;
And determining an angle adjustment amount of the second adjustment device based on the comprehensive coefficient of the second adjustment device and the target threshold value, and executing the angle adjustment amount as the second adjustment scheme.
Preferably, the function implementation process of the heat collecting device adjusting module further includes:
Obtaining a performance deviation e (t) based on the integrated coefficient P evj (t) of the second adjustment device and the target threshold P tar:
e(t)=Ptar-Pevj(t);
obtaining an angle adjustment quantity delta theta adj (t) by adopting a PID controller based on the performance deviation e (t):
wherein Kp, ki and Kd represent a proportional gain, an integral gain and a differential gain, respectively, Represents the cumulative sum of all errors from the start time to the current time t,Indicating the rate of change of the error over time.
Preferably, the function implementation process of the heat collecting device evaluation module includes:
Obtaining the heat energy conversion efficiency eta j (t) of each heat collecting device at the time t;
Acquiring the current pollution degree delta j and the maximum allowable pollution degree delta jmax of each heat collecting device;
Obtaining a cleanliness factor Cj clean (t) based on the current contamination level δ j and the maximum allowable contamination level δ jmax:
Obtaining the second comprehensive performance coefficient P 2j (t) based on the thermal energy conversion efficiency η j (t) and the cleanliness factor Cj clean (t):
wherein c1, c2, c3, c4 and c5 respectively represent the weight coefficients of each index;
And selecting the heat collecting equipment with the second coefficient of performance smaller than a preset value as the abnormal heat collecting equipment.
Compared with the prior art, the distributed photovoltaic heat collection, power generation and energy storage control system for residential areas has the following beneficial effects:
1. The photovoltaic power generation performance is optimized, namely, through the photovoltaic equipment adjusting module, the system can automatically adjust the angle of the photovoltaic panel according to seasonal changes and environmental conditions, and the photovoltaic panel is ensured to be always in an optimal illumination receiving state, so that the generated energy is maximized. In addition, the performance of each photovoltaic module is evaluated by calculating the first performance coefficient, and the abnormal photovoltaic equipment is timely identified for maintenance or replacement, so that the high-efficiency and stable operation of the whole photovoltaic system is ensured.
2. The heat energy utilization rate is improved, namely the heat collecting equipment adjusting module is combined with the evaluation module, so that the working parameters, such as angles and the like, of each heat collecting device can be accurately controlled to match actual demands and maintain high-efficiency heat conversion rate. Meanwhile, the cleaning condition of the heat collector is checked regularly, so that the efficiency is prevented from being reduced due to dust accumulation, and a good heat absorption effect is maintained.
3. The intelligent charge-discharge decision-making module selects to charge the energy storage battery when the electricity price is low by taking the peak-valley electricity price difference of the electricity market into consideration, and releases the stored energy for a user to use or sell to a power grid in a peak period, so that the cost is reduced and the income is increased. The state of health (e.g., state of charge) of the energy storage system is also considered, avoiding over-charge and over-discharge from compromising battery life.
4. The system stability and safety are enhanced, namely the comprehensive feedback module gathers all detected information to the control terminal, so that an operator can monitor the system state in real time and can respond to possible problems quickly. This helps to prevent the occurrence of potential faults, ensuring long-term stable operation of the system.
5. The development of green low carbon is promoted, and the increasing power consumption demands of residents can be met by adopting a distributed energy solution on the premise of not increasing carbon emission. The application of such techniques is of great importance for reducing greenhouse gas emissions.
6. The control system of the invention has the characteristics of high integration and intellectualization, improves the energy conversion efficiency and makes positive contribution to realizing energy conservation and emission reduction. The energy-saving system is not only suitable for a newly built residential area, but also can be used as a part of energy-saving reconstruction of the existing residential area, and has wide application prospect and development potential.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic structural diagram of a distributed photovoltaic heat collection, power generation and energy storage control system for a residential area.
Fig. 2 is a flow chart of a distributed photovoltaic heat collection, power generation and energy storage control method for a residential area.
Fig. 3 is a block diagram of a computer device according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
As shown in fig. 1, an embodiment of the present invention discloses a distributed photovoltaic heat collection, power generation and energy storage control system for a residential area, including:
The photovoltaic equipment adjusting module is used for acquiring the angles of photovoltaic panels of all photovoltaic power generation equipment in the residential area and determining a first adjusting scheme for the operation of all the photovoltaic power generation equipment by combining the seasonal and environmental influences;
the photovoltaic equipment evaluation module is used for acquiring the generated energy and the environmental information of each photovoltaic power generation equipment, obtaining a first performance coefficient of each photovoltaic power generation equipment, and further determining the photovoltaic power generation equipment with the performance not reaching the standard as abnormal photovoltaic equipment;
the charging and discharging decision module is used for obtaining a charging execution coefficient based on the time period and the charging and discharging efficiency of the 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 electricity demand;
The heat collecting equipment adjusting module is used for acquiring the heat collecting quantity and related parameters of each heat collecting equipment to obtain a comprehensive coefficient, and determining a second adjusting scheme for the operation of each heat collecting equipment based on the comprehensive coefficient;
The heat collecting equipment evaluation module is used for acquiring the heat conversion efficiency and the cleanliness factor of each heat collecting equipment to obtain a second performance coefficient and further determining the heat collecting equipment with the performance not reaching the standard as abnormal heat collecting equipment, and the heat collecting equipment evaluation module is used for acquiring the heat conversion efficiency and the cleanliness factor of each heat collecting equipment to obtain a second performance coefficient
The comprehensive feedback module is used for feeding back the abnormal photovoltaic equipment, the abnormal heat collection equipment, the first adjustment scheme, the charging scheme, the discharging scheme and the second adjustment scheme to the control terminal.
Example 2
As shown in fig. 1, an embodiment of the present invention discloses a distributed photovoltaic heat collection, power generation and energy storage control system for a residential area, including:
And the photovoltaic equipment adjusting module is used for acquiring the angles of photovoltaic panels of all the photovoltaic power generation equipment in the residential area and determining a first adjusting scheme for the operation of all the photovoltaic power generation equipment by combining the seasonal and environmental influences.
Preferably, the photovoltaic device adjustment module function implementation process includes:
Acquiring a photovoltaic panel angle theta i of each photovoltaic power generation device and a proper panel angle theta 0i (t) at the current time t;
Obtaining a seasonal adjustment factor S (t) based on the seasonal influence;
and obtaining an environmental impact factor E i(I,Ti of the ith photovoltaic power generation equipment based on the real-time measured illumination intensity I and the real-time temperature T i of the photovoltaic panel surface of the ith photovoltaic power generation equipment.
Preferably, the seasonal adjustment factor S (t) is specifically:
Wherein a s represents an amplitude adjustment coefficient, calibration is performed according to the geographical position and the history data, t d represents the current date (represented by days in the year), and t s represents the date of winter or summer;
The environmental impact factor E i(I,Ti) is specifically:
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.
Preferably, t s depends on which is chosen as the reference point. For example, in the northern hemisphere, the summer solstice occurs on about day 172 (around 21 days of 6 months) and the winter solstice on about 355 (around 22 days of 12 months).
Preferably, the seasonal adjustment factor S (t) mainly considers the influence of the change in the solar altitude with the change in season, and the change in the sunlight time. The specific solar altitude of a certain day is calculated based on an astronomical algorithm, and the angle of the photovoltaic panel is adjusted accordingly.
Preferably, the exponential function in the environmental impact factor E i(I,Ti) is used to describe the effect of temperature on photovoltaic efficiency, the efficiency decays exponentially as the temperature increases, and meanwhile, the efficiency is multiplied by the proportion of illumination intensity, so that the change of the efficiency can be correctly reflected under different illumination conditions.
Preferably, the illumination intensity I r under the standard test conditions in this example is set to 1000W/m 2, and the temperature T r under the standard test conditions is set to 25 ℃.
Preferably, the photovoltaic device adjustment module function implementation process further includes:
The adjustment coefficient K θi of each photovoltaic power generation device is obtained based on the photovoltaic panel angle theta i, the proper panel angle theta 0i (t), the seasonal adjustment factor S (t) and the environmental impact factor E i(I,Ti:
wherein W represents a weight factor for emphasizing the importance of the photovoltaic panel angle in system performance evaluation, and delta theta represents a photovoltaic panel angle deviation threshold;
determining photovoltaic power generation equipment needing to adjust the angle of the photovoltaic panel based on the adjustment coefficient as first adjustment equipment;
and obtaining the adjusting direction and the adjusting amount of the angle of the photovoltaic panel of the first adjusting device based on the angle deviation of the photovoltaic panel of the first adjusting device as a first adjusting scheme and executing the first adjusting scheme.
Preferably, by combining the seasonal adjustment factor S (t) and the environmental impact factor E i(I,Ti, the obtained adjustment coefficient 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.
The photovoltaic equipment evaluation module is used for acquiring the generated energy and the environmental information of each photovoltaic power generation equipment, obtaining the first performance coefficient of each photovoltaic power generation equipment, and further determining the photovoltaic power generation equipment with the performance not reaching the standard as abnormal photovoltaic equipment.
Preferably, the photovoltaic device evaluation module function implementation process includes:
Acquiring an actual power generation amount P ai (t) and a reference power generation amount P ri (t) of each photovoltaic power generation device;
Acquiring the surface temperature T pi (T) and the optimal working temperature T oi of the photovoltaic panels of each photovoltaic power generation device;
Acquiring an ambient temperature T e (T) of the current time T;
Obtaining a first performance coefficient of each photovoltaic power generation device 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 environment temperature T e (T):
Wherein, deltaT represents the maximum temperature deviation allowed, I ti represents the illumination intensity measured by each photovoltaic power generation device in real time, I r represents the illumination intensity under the standard test condition of each photovoltaic power generation device, gamma represents the empirical constant of the temperature effect on the efficiency, T v (T) represents the environmental temperature at the current moment T, w1, w2, w3, w4, w5 and w6 respectively represent the weight coefficients of each index, the weight coefficients can be adjusted according to the actual situation to reflect the importance of different factors, and F a (T) represents the performance attenuation factors of each photovoltaic power generation device;
and selecting the photovoltaic power generation equipment with the first performance coefficient smaller than the set value as abnormal photovoltaic equipment.
Preferably, the performance attenuation factor F a (t) of each photovoltaic power generation apparatus is specifically:
f a(t)＝e-Ω×LV, wherein Ω represents the decay rate, LV represents the age of each photovoltaic power plant.
Preferably, in this embodiment, by using a Statistical Process Control (SPC) method, upper and lower control limits are set as the set values, and when LCL is less than or equal to p 1i (t) is less than or equal to UCL, LCL represents the lower control limit, and UCL represents the upper control limit, then the device is considered to have a potential problem as an abnormal photovoltaic device, and further inspection is required.
Preferably, the weight coefficient wi is set according to the specific application scenario and importance. For example, if the power generation is the most critical indicator, a higher value for w1 may be given, and if temperature management is critical, the weights for w2 and w4 should be appropriately increased. The sum of all weight coefficients should be equal to 1, ensuring that the balance between the factors is maintained.
Preferably, the performance of the photovoltaic power generation equipment can be more comprehensively evaluated through the first coefficient of performance formula, the photovoltaic power generation equipment is not only limited to the generated energy, but also comprises multiple aspects of temperature management, illumination conditions, equipment aging and the like, so that equipment with unqualified performance can be more accurately identified, and targeted maintenance suggestions can be provided.
And the charge-discharge decision module is used for obtaining a charge execution coefficient based on the time period and the charge-discharge efficiency of the energy storage device, obtaining a charge scheme of the energy storage device based on the charge execution coefficient and obtaining a discharge scheme based on electricity demand.
Preferably, the function implementation process of the charge-discharge decision module includes:
Judging whether the current period is in the valley price period or not based on the current period, and if not, not performing charging operation;
If yes, correspondingly obtaining charging input energy E in and discharging output energy E out based on the charging and discharging efficiency of the energy storage system;
acquiring the energy consumption cost C au of auxiliary equipment of the energy storage system;
Based on the charging input energy E in, the discharging output energy E out and the auxiliary equipment energy consumption cost C au, the charging execution coefficient R is obtained:
R=Eout×Cpeak-Ein×Cvalley-Cau;
wherein, C peak represents the peak price period electricity price, and C valley represents the valley price period electricity price;
when the charging execution coefficient R is larger than the execution threshold, the energy storage system executes charging operation to obtain a charging scheme, otherwise, the current situation is maintained or only part of electric quantity is supplemented to maintain the lowest running level;
and preferentially releasing the electric energy in the energy storage system based on the actual electricity demand to obtain a discharging scheme.
Preferably, E in＝Eusable/ηcharge,Eusable represents the actual available energy, η charge represents the charging efficiency, E out＝Ein×ηcharge×ηdischarge, where η discharge represents the discharging efficiency.
Preferably, the auxiliary equipment energy consumption cost C au is specifically:
Cau＝Pauxiliary×(tcharge+tdischarge)×Caverage;
Wherein P auxiliary represents the average power consumption (kW) of auxiliary equipment such as an air conditioning system, t charge represents the charging duration (hours), t discharge represents the discharging duration (hours), C average represents the average electricity price over the whole charging and discharging period, and the value of this embodiment is a weighted average of C peak and C valley.
Preferably, the function implementation process of the charge-discharge decision module further includes:
when the charging scheme is executed, the optimal charge amount is obtained based on the charging execution coefficient R and related constraint conditions
The constraint conditions are as follows:
Ein≤Smax-Scurrent;
0.2Smax≤Sa(t)≤0.8Smax;
Wherein S max represents the maximum rated capacity of the energy storage device, S current represents the currently existing energy storage capacity 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 available energy of the energy storage system in the period from t start to t end, the total available energy comprises the existing energy storage capacity and the photovoltaic power generation contribution expected to be newly increased, 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 predicted value calculated based on weather forecast.
Preferably E in≤Smax-Scurrent is used for energy storage capacity limitation, the new charge cannot exceed the remaining available capacity.
Preferably, 0.2S max≤Sa(t)≤0.8Smax is used to limit the state of charge (SOC) range, where 0.2S max represents the lower limit of the safe operating range of the energy storage device, i.e., the lowest allowable state of charge, and by setting the lowest allowable state of charge so that the energy storage device maintains a minimum energy reserve, it can help cope with sudden peak demand or grid faults, ensuring the stability and reliability of the power supply, and ensuring that the energy storage device is not damaged by overdischarge during daily operation. 0.8S max represents the upper limit of the safe operating range of the energy storage system, i.e. the highest allowable state of charge, by setting the highest allowable state of charge, it is ensured that the energy storage device is not damaged by overcharging in daily operation, and its storage capacity can be effectively utilized to optimize energy management.
By limiting the state of charge (SOC) range, overcharging or overdischarging can be avoided, safe operating boundaries are maintained, battery life can be extended and system reliability can be ensured in this interval.
Preferably, the method comprises the steps of,For taking into account the effect of future photovoltaic power predictions on total energy.
Preferably, other limitations are included including, but not limited to, a single maximum charge-discharge power, a minimum charge period, etc., depending on the characteristics and application scenario of the energy storage system.
Preferably, weather forecast information is crucial for predicting photovoltaic power generation, and particularly on sunny and cloudless days, the power output of a photovoltaic system is high, and in overcast and rainy days, the power output is possibly reduced greatly. In order to more accurately estimate future photovoltaic power generation potential, the invention combines short-term weather forecast data (such as cloud cover, temperature and the like) to adjust the expected power generation amount of the photovoltaic array to obtain a future photovoltaic power predicted value P PV,forecasted(t) calculated based on weather forecast.
Preferably, the optimal charge amountThe formula not only considers direct economic benefits, but also considers the technical feasibility and the influence of environmental factors. The method is helpful for a decision maker to manage the energy storage more scientifically and reasonably, thereby realizing win-win situation of economic benefit and social responsibility.
And the heat collecting equipment adjusting module is used for acquiring the heat collecting quantity and related parameters of each heat collecting equipment to obtain a comprehensive coefficient, and determining a second adjusting scheme for the operation of each heat collecting equipment based on the comprehensive coefficient.
Preferably, the function implementation process of the heat collecting device adjusting module includes:
Acquiring the actual heat collection quantity Q aj (t) and the expected heat collection quantity Q cj (t) of each heat collection device at the moment t, wherein j represents the number of the jth heat collection device;
Acquiring the surface temperature T 1 (T) and the optimal working temperature T 2 of each heat collecting device at the time T;
The comprehensive coefficient P evj (t) of each heat collecting device is obtained based on the actual heat collecting quantity, the expected heat collecting quantity, the surface temperature and the optimal working temperature:
Wherein η j (T) represents the heat energy conversion efficiency of the jth heat collecting device at time T, a1, a2 and a3 respectively represent the weight coefficients of each index, deltaT n represents the maximum allowable deviation of the heat collector, I tk represents the illumination intensity measured by each heat collecting device in real time, I x represents the illumination intensity under the standard test condition of each heat collecting device, F b (T) represents the performance attenuation factor of each heat collecting device;
selecting heat collection equipment with the comprehensive coefficient smaller than a target threshold value as second adjusting equipment;
And determining an angle adjustment amount of the second adjustment device based on the comprehensive coefficient of the second adjustment device and the target threshold value, and executing the angle adjustment amount as a second adjustment scheme.
Preferably, the expected heat collection quantity Q cj (t) is calculated based on the current illumination condition and a theoretical model, and the illumination intensity I x of each heat collection device under the standard test condition is set to 1000W/m 2.
Preferably byDirectly reflects the actual performance of the heat collecting device,Indicating the deviation between the surface temperature of the collector and the optimal operating temperature, ensuring that the device operates within the optimal temperature range,The method reflects the influence of illumination conditions on heat collection efficiency, and a3.F b (t) considers the aging condition of equipment along with time, is favorable for long-term performance evaluation, can evaluate the performance of the heat collection equipment more comprehensively through the comprehensive coefficient, is not only limited to heat energy conversion efficiency, but also comprises multiple aspects of temperature management, illumination conditions and equipment aging, so that the equipment with substandard performance can be identified more accurately, and a targeted maintenance suggestion is provided.
Preferably, F b(t)＝e-U×LZ, where U represents the decay rate and LZ represents the age of each heat collecting device.
Preferably, the sum of all weighting coefficients a1, a2 and a3 is equal to 1, ensuring that a balance is maintained between the factors.
Preferably, the historical data is analyzed by a machine learning algorithm (such as reinforcement learning and genetic algorithm), and the weight coefficients a1, a2 and a3 are continuously optimized, so that the system can better adapt to different environmental conditions and operation requirements.
Preferably, the function implementation process of the heat collecting device adjusting module further includes:
the performance deviation e (t) is obtained based on the integrated coefficient P evj (t) of the second adjustment device and the target threshold P tar:
e(t)=Ptar-Pevj(t);
Obtaining an angle adjustment quantity delta theta adj (t) by adopting a PID controller based on the performance deviation e (t):
wherein Kp, ki and Kd represent a proportional gain, an integral gain and a differential gain, respectively, Represents the cumulative sum of all errors from the start time to the current time t,Indicating the rate of change of the error over time.
Preferably, the present embodiment determines an initial optimal collector panel angle θ base (t) based on the seasonal adjustment factor S (t) and the sun position information α (t):
θbase(t)＝θfixed+Δθ·S(t)+f(α(t))
Where θ fixed denotes a base installation angle, Δ θ denotes an angle increment adjusted according to a seasonal variation, and f (α (t)) denotes an angle adjustment amount calculated according to a real-time solar position.
Preferably, the adjusted final collector panel angle θ opt (t) is based on the sum of the optimal collector panel angle θ base (t) and the angle adjustment Δθ adj (t):
θopt(t)＝θbase(t)+Δθadj(t)。
and the heat collecting equipment evaluation module is used for acquiring the heat conversion efficiency and the cleanliness factor of each heat collecting equipment to obtain a second performance coefficient and further determining the heat collecting equipment with the performance not reaching the standard as abnormal heat collecting equipment.
Preferably, the function implementation process of the heat collecting device evaluation module includes:
Obtaining the heat energy conversion efficiency eta j (t) of each heat collecting device at the time t;
Acquiring the current pollution degree delta j and the maximum allowable pollution degree delta jmax of each heat collecting device;
The cleanliness factor Cj clean (t) is derived based on the current contamination level δ j and the maximum allowable contamination level δ jmax:
Obtaining a second comprehensive performance coefficient P 2j (t) based on the heat energy conversion efficiency eta j (t) and the cleanliness factor Cj clean (t):
wherein c1, c2, c3, c4 and c5 respectively represent the weight coefficients of each index;
And selecting the heat collecting equipment with the second coefficient of performance smaller than a preset value as abnormal heat collecting equipment.
Preferably, the thermal energy conversion efficiency η j (t) is:
Wherein E solar (t) represents the total solar irradiation (W/m 2),Acollector represents the heat collection area (m 2).
And the comprehensive feedback module is used for feeding back the abnormal photovoltaic equipment, the abnormal heat collection equipment and all generated schemes to the control terminal.
Preferably, the integrated feedback module is configured to feed back the abnormal photovoltaic device, the abnormal heat collecting device, the first adjustment scheme, the charging scheme, the discharging scheme and the second adjustment scheme to the control terminal.
Preferably, the comprehensive feedback module gathers all detected information to the control terminal, so that an operator can conveniently monitor the system state in real time and can quickly respond to possible problems. This helps to prevent the occurrence of potential faults, ensuring long-term stable operation of the system.
Example 3
As shown in fig. 2, the embodiment of the invention discloses a distributed photovoltaic heat collection, power generation and energy storage control method for a residential area, which comprises the following steps:
Acquiring the angles of photovoltaic panels of all photovoltaic power generation equipment in a residential area, and determining a first adjustment scheme for the operation of all the photovoltaic power generation equipment by combining the seasonal and environmental influences;
Acquiring the generated energy and the environmental information of each photovoltaic power generation device, obtaining a first performance coefficient of each photovoltaic power generation device, and further determining the photovoltaic power generation devices with the performance not reaching the standard as abnormal photovoltaic devices;
Obtaining a charging execution coefficient based on the time period and the charging and discharging efficiency of the 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 electricity demand;
acquiring heat collection quantity and related parameters of each heat collection device to obtain a comprehensive coefficient, and determining a second adjustment scheme for operation of each heat collection device based on the comprehensive coefficient;
Acquiring heat conversion efficiency and cleanliness factors of each heat collecting device to obtain a second performance coefficient, and further determining heat collecting devices with performance not reaching standards as abnormal heat collecting devices;
and feeding back the abnormal photovoltaic equipment, the abnormal heat collection equipment and all generated schemes to the control terminal.
Preferably, the implementation process of each step in this embodiment corresponds to the implementation process of the function module, which is not described herein.
Example 4
Based on the same inventive concept, the invention also provides a computer device, which comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete communication with each other through the communication bus;
a memory for storing a computer program;
the processor, when executing the program stored on the memory, can implement a distributed photovoltaic heat collection, power generation and energy storage control method for residential areas as in embodiment 3.
As shown in fig. 3, the electronic device may include a processor (processor) 31, a communication interface (Communications Interface) 32, a memory (memory) 33, and a communication bus 34, where the processor 31, the communication interface 32, and the memory 33 communicate with each other via the communication bus 34. The processor 31 may invoke logic instructions in the memory 33 to execute one of the distributed photovoltaic thermal-arrest power generation and storage control methods for residential areas of embodiment 3.
Further, the logic instructions in the memory 33 described above may be implemented in the form of software functional units and may be stored in a computer readable storage medium when sold or used as a stand alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method of the embodiments of the present invention. The storage medium includes a U disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, an optical disk, or other various media capable of storing program codes.
According to the technical scheme, the invention discloses a distributed photovoltaic heat collection, power generation and energy storage control system for a residential area, which has the following beneficial effects:
1. The photovoltaic power generation performance is optimized, namely, through the photovoltaic equipment adjusting module, the system can automatically adjust the angle of the photovoltaic panel according to seasonal changes and environmental conditions, and the photovoltaic panel is ensured to be always in an optimal illumination receiving state, so that the generated energy is maximized. In addition, the performance of each photovoltaic module is evaluated by calculating the first performance coefficient, and the abnormal photovoltaic equipment is timely identified for maintenance or replacement, so that the high-efficiency and stable operation of the whole photovoltaic system is ensured.
2. The heat energy utilization rate is improved, namely the heat collecting equipment adjusting module is combined with the evaluation module, so that the working parameters, such as angles and the like, of each heat collecting device can be accurately controlled to match actual demands and maintain high-efficiency heat conversion rate. Meanwhile, the cleaning condition of the heat collector is checked regularly, so that the efficiency is prevented from being reduced due to dust accumulation, and a good heat absorption effect is maintained.
3. The intelligent charge-discharge decision-making module selects to charge the energy storage battery when the electricity price is low by taking the peak-valley electricity price difference of the electricity market into consideration, and releases the stored energy for a user to use or sell to a power grid in a peak period, so that the cost is reduced and the income is increased. The state of health (e.g., state of charge) of the energy storage system is also considered, avoiding over-charge and over-discharge from compromising battery life.
4. The system stability and safety are enhanced, namely the comprehensive feedback module gathers all detected information to the control terminal, so that an operator can monitor the system state in real time and can respond to possible problems quickly. This helps to prevent the occurrence of potential faults, ensuring long-term stable operation of the system.
5. The development of green low carbon is promoted, and the increasing power consumption demands of residents can be met by adopting a distributed energy solution on the premise of not increasing carbon emission. The application of such techniques is of great importance for reducing greenhouse gas emissions.
6. The control system of the invention has the characteristics of high integration and intellectualization, improves the energy conversion efficiency and makes positive contribution to realizing energy conservation and emission reduction. The energy-saving system is not only suitable for a newly built residential area, but also can be used as a part of energy-saving reconstruction of the existing residential area, and has wide application prospect and development potential.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer 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 points refer to the description of the method section.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (8)

1.一种用于住宅区的分布式光伏集热发电储能控制系统，其特征在于，包括：1. A distributed photovoltaic thermal power generation and energy storage control system for residential areas, characterized in that it comprises: 光伏设备调整模块：用于获取住宅区中各光伏发电设备的光伏面板角度，结合季节和环境影响确定各光伏发电设备运行的第一调整方案；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; 光伏设备评价模块：用于获取所述各光伏发电设备的发电量和环境信息，得到所述各光伏发电设备的第一性能系数，进一步确定性能不达标的光伏发电设备作为异常光伏设备；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; 充放电决策模块：用于基于所处时段和储能装置的充放电效率得到充电执行系数，基于所述充电执行系数得到所述储能装置的充电方案，基于用电需求得到放电方案；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. 所述充放电决策模块功能实现过程包括：The function implementation process of the charging/discharging decision module includes: 基于当前时段判断是否处于谷价期，若否，则不进行充电操作；Determine whether the current time period is a low price period; if not, do not perform charging operation. 若是，则基于储能系统的充放电效率对应得到充电输入能量Ein和放电输出能量Eout；If so, the charging input energy Ein and discharging output energy Eout are obtained based on the charging and discharging efficiency of the energy storage system. 获取所述储能系统的辅助设备能耗成本Cau；Obtain the energy consumption cost C au of the auxiliary equipment of the energy storage system; 基于所述充电输入能量Ein、放电输出能量Eout和辅助设备能耗成本Cau得到充电执行系数R：Based on the charging input energy Ein , the discharging output energy Eout , and the auxiliary equipment energy consumption cost Cau, the charging execution coefficient R is obtained: R＝Eout×Cpeak-Ein×Cvalley-Cau；R＝E out ×C peak -E in ×C valley -C au ; 其中，Cpeak表示峰价期电价，Cvalley表示谷价期的电价；Where C peak represents the electricity price during peak season, and C valley represents the electricity price during off-peak season; 辅助设备能耗成本Cau具体为：The energy cost of auxiliary equipment, Cau , is as follows: Cau＝Pauxiliary×(tcharge+tdischarge)×Caverage；C au =P auxiliary ×(t charge +t discharge )×C average ; 其中，Pauxiliary表示辅助设备的平均功率消耗，tcharge表示充电持续时间，tdischarge表示放电持续时间，Caverage表示整个充放电周期内平均电价；Where P auxiliary represents the average power consumption of the auxiliary equipment, t charge represents the charging duration, t discharge represents the discharging duration, and C average represents the average electricity price over the entire charging and discharging cycle. 当所述充电执行系数R大于执行阈值时所述储能系统执行充电操作，得到所述充电方案；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; 基于实际用电需求优先释放所述储能系统中的电能，得到所述放电方案；The discharge scheme is obtained by prioritizing the release of electrical energy from the energy storage system based on actual electricity demand. 执行所述充电方案时，基于所述充电执行系数R及相关约束条件得到最优充电量 When executing the charging scheme, the optimal charging amount is obtained based on the charging execution coefficient R and related constraints. 约束条件为：The constraints are: Ein≤Smax-Scurrent；E in ≤S max -S current ; 0.2Smax≤Sa(t)≤0.8Smax；0.2S max ≤Sa(t)≤0.8S max ; 其中，Smax表示储能装置的最大额定容量，Scurrent表示储能装置当前已有的储能量，Sa(t)表示储能装置在时间点t时的实际荷电状态,Etotal表示从tstart到tend这段时间内储能系统总的可用能量总量，tstart和tend分别表示充电开始时间和结束时间，PPV,forecasted(t)表示基于天气预报计算得出的未来光伏功率预测值；Where Smax represents the maximum rated capacity of the energy storage device, Scurrent represents the current stored energy of the energy storage device, Sa(t) represents the actual state of charge of the energy storage device at time t, Etotal represents the total available energy of the energy storage system from tstart to tend , tstart and tend represent the start and end times of charging, respectively, and PPV,forecasted(t) represents the predicted value of future photovoltaic power calculated based on weather forecasts. 结合短期气象预报数据调整光伏阵列的预期发电量得到基于天气预报计算得出的未来光伏功率预测值PPV,forecasted(t)；By combining short-term weather forecast data to adjust the expected power generation of the photovoltaic array, we obtain the future photovoltaic power forecast value P PV,forecasted(t) calculated based on the weather forecast. 集热设备调整模块：用于获取各集热设备的集热量和相关参数得到综合系数，基于所述综合系数确定所述各集热设备运行的第二调整方案；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. 集热设备评价模块：用于获取所述各集热设备热量转换效率和清洁度因子，得到第二性能系数，进一步确定性能不达标的集热设备作为异常集热设备；以及，The solar collector evaluation module is used to obtain the heat conversion efficiency and cleanliness factor of each solar collector, obtain a second performance coefficient, and further identify solar collectors that fail to meet performance standards as abnormal solar collectors; and, 综合反馈模块：用于将所述异常光伏设备、所述异常集热设备、所述第一调整方案、所述充电方案、所述放电方案和所述第二调整方案反馈至控制终端。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. 2.根据权利要求1所述的一种用于住宅区的分布式光伏集热发电储能控制系统，其特征在于，所述光伏设备调整模块功能实现过程包括：2. The distributed photovoltaic thermal power generation and energy storage control system for residential areas according to claim 1, characterized in that the function implementation process of the photovoltaic equipment adjustment module includes: 获取所述各光伏发电设备的光伏面板角度θi和在当前时间t的适宜面板角度θ0i(t)；Obtain the photovoltaic panel angle θi and the suitable panel angle θ0i (t) at the current time t for each photovoltaic power generation device; 基于季节性影响获取得到季节性调整因子S(t)；The seasonal adjustment factor S(t) was obtained based on the seasonal effects. 基于实时测量到的光照强度I和第i个光伏发电设备光伏面板表面的实时温度Ti得到第i个光伏发电设备的环境影响因子Ei(I,Ti)；The environmental impact factor E <sub>i</sub> (I, Ti ) of the i-th photovoltaic power generation device is obtained based on the real-time measured light intensity I and the real-time temperature Ti on the surface of the photovoltaic panel of the i-th photovoltaic power generation device. 基于所述光伏面板角度θi、所述适宜面板角度θ0i(t)、所述季节性调整因子S(t)和所述环境影响因子Ei(I,Ti)得到所述各光伏发电设备的调整系数Kθi：Based on the photovoltaic panel angle θi , the suitable panel angle θ0i (t), the seasonal adjustment factor S(t), and the environmental impact factor Ei (I, Ti ), the adjustment coefficient Kθi for each photovoltaic power generation device is obtained: 其中，W表示权重因子，Δθ表示光伏面板角度偏差阈值；Where W represents the weighting factor, and Δθ represents the photovoltaic panel angle deviation threshold; 基于所述调整系数确定需要调节光伏面板角度的光伏发电设备作为第一调整设备；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; 基于所述第一调整设备的光伏面板角度偏差得到所述第一调整设备的光伏面板角度的调节方向及调整量作为所述第一调整方案并执行。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.根据权利要求2所述的一种用于住宅区的分布式光伏集热发电储能控制系统，其特征在于，所述季节性调整因子S(t)具体为：3. The 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: 其中，As表示幅度调整系数，td表示当前日期，ts表示冬至日或夏至日的日期。Where As represents the amplitude adjustment coefficient, td represents the current date, and ts represents the date of the winter solstice or summer solstice. 4.根据权利要求3所述的一种用于住宅区的分布式光伏集热发电储能控制系统，其特征在于，所述环境影响因子Ei(I,Ti)具体为：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 <sub>i</sub> (I,T<sub>i</sub> ) is specifically: 其中，α和β表示经验常数，Ir表示标准测试条件下的光照强度，Tr表示标准测试条件下的温度。Where α and β represent empirical constants, I <sub>r</sub> represents the light intensity under standard test conditions, and T <sub>r</sub> represents the temperature under standard test conditions. 5.根据权利要求4所述的一种用于住宅区的分布式光伏集热发电储能控制系统，其特征在于，所述光伏设备评价模块功能实现过程包括：5. A distributed photovoltaic thermal power generation and energy storage control system for residential areas according to claim 4, characterized in that the function implementation process of the photovoltaic equipment evaluation module includes: 获取所述各光伏发电设备的实际发电量Pai(t)和参考发电量Pri(t)；Obtain the actual power generation Pai (t) and reference power generation Pri (t) of each photovoltaic power generation device; 获取所述各光伏发电设备光伏面板的表面温度Tpi(t)和最佳工作温度Toi；Obtain the surface temperature Tpi (t) and optimal operating temperature Tooi of the photovoltaic panels of each photovoltaic power generation device; 获取当前时间t的环境温度Te(t)；Get the ambient temperature Te (t) at the current time t; 基于实际发电量Pai(t)、参考发电量Pri(t)、表面温度Tpi(t)、最佳工作温度Toi和环境温度Te(t)得到各光伏发电设备的所述第一性能系数：The first performance coefficient of each photovoltaic power generation device is obtained based on the actual power generation Pai (t), the reference power generation Pri(t), the surface temperature Tpi (t), the optimal operating temperature Toi , and the ambient temperature Te (t): 其中，ΔT表示允许的最大温度偏差，Iti表示各光伏发电设备实时测量到的光照强度，Ir表示各光伏发电设备标准测试条件下的光照强度，γ表示温度对效率影响的经验常数，Tv(t)表示当前时刻t的环境温度，w1、w2、w3、w4、w5和w6分别表示各项指标的权重系数，Fa(t)表示各光伏发电设备的性能衰减因子；Where ΔT represents the maximum allowable temperature deviation, I <sub>ti</sub> represents the real-time measured light intensity of each photovoltaic power generation device, I <sub>r</sub> represents the light intensity of each photovoltaic power generation device under standard test conditions, γ represents the empirical constant of the effect of temperature on efficiency, T <sub>v</sub> (t) represents the ambient temperature at the current time t, w<sub>1</sub>, w<sub>2</sub>, w<sub>3</sub>, w<sub>4</sub>, w<sub>5</sub> and w<sub>6</sub> represent the weighting coefficients of each index, and Fa (t) represents the performance degradation factor of each photovoltaic power generation device; 选取所述第一性能系数小于设定值的光伏发电设备作为所述异常光伏设备。Photovoltaic power generation equipment with a first performance coefficient less than a set value is selected as the abnormal photovoltaic equipment. 6.根据权利要求1所述的一种用于住宅区的分布式光伏集热发电储能控制系统，其特征在于，所述集热设备调整模块功能实现过程包括：6. A distributed photovoltaic thermal power generation and energy storage control system for residential areas according to claim 1, characterized in that the function implementation process of the thermal collector adjustment module includes: 获取所述各集热设备在t时刻的实际集热量Qaj(t)和期望集热量Qcj(t)，j表示第j个集热设备的编号；Obtain the actual heat collection Q <sub>aj</sub> (t) and the expected heat collection Q <sub>cj</sub> (t) of each heat collection device at time t, where j represents the number of the j-th heat collection device; 获取所述各集热设备在t时刻的表面温度T1(t)和最佳工作温度T2；Obtain the surface temperature T1 (t) and optimal operating temperature T2 of each of the solar collectors at time t; 基于所述实际集热量、所述期望集热量、所述表面温度和所述最佳工作温度得到各集热设备的所述综合系数Pevj(t)：Based on the actual heat collection, the expected heat collection, the surface temperature, and the optimal operating temperature, the comprehensive coefficient Pevj (t) of each heat collection device is obtained: 其中，ηj(t)表示第j个集热设备在时间t的热能转换效率，a1、a2和a3分别表示各项指标的权重系数，ΔTn表示集热器最大允许偏差，Itk表示各集热设备实时测量到的光照强度，Ix表示各集热设备标准测试条件下的光照强度；Fb(t)表示各集热设备的性能衰减因子；Where ηj (t) represents the thermal energy conversion efficiency of the j-th solar collector at time t, a1, a2 and a3 represent the weighting coefficients of each index, ΔTn represents the maximum permissible deviation of the solar collector, Itk represents the real-time measured light intensity of each solar collector, Ix represents the light intensity of each solar collector under standard test conditions, and Fb (t) represents the performance degradation factor of each solar collector. 选取所述综合系数小于目标阈值的集热设备作为第二调整设备；The heat collection device with a comprehensive coefficient less than the target threshold is selected as the second adjustment device; 基于所述第二调整设备的综合系数和所述目标阈值确定所述第二调整设备的角度调整量，作为所述第二调整方案并执行。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, and is used as the second adjustment scheme and executed. 7.根据权利要求6所述的一种用于住宅区的分布式光伏集热发电储能控制系统，其特征在于，所述集热设备调整模块功能实现过程还包括：7. A distributed photovoltaic thermal power generation and energy storage control system for residential areas according to claim 6, characterized in that the function implementation process of the thermal collector adjustment module further includes: 基于所述第二调整设备的综合系数Pevj(t)和所述目标阈值Ptar得到性能偏差e(t)：Based on the comprehensive coefficient P <sub>evj</sub> (t) of the second adjustment device and the target threshold P<sub>tar</sub> , the performance deviation e(t) is obtained: e(t)＝Ptar-Pevj(t)；e(t) = P tar - P evj (t); 基于所述性能偏差e(t)采用PID控制器得到角度调整量Δθadj(t)：Based on the performance deviation e(t), the angle adjustment Δθ adj (t) is obtained using a PID controller: 其中，Kp、Ki和Kd分别表示比例增益、积分增益和微分增益，表示从开始时刻到当前时刻t的所有误差的累积总和，表示误差随时间的变化率。Where Kp, Ki, and Kd represent the proportional gain, integral gain, and derivative gain, respectively. This represents the cumulative sum of all errors from the start time to the current time t. This represents the rate of change of error over time. 8.根据权利要求3或6所述的一种用于住宅区的分布式光伏集热发电储能控制系统，其特征在于，所述集热设备评价模块功能实现过程包括：8. A distributed photovoltaic thermal power generation and energy storage control system for residential areas according to claim 3 or 6, characterized in that the function implementation process of the thermal collector evaluation module includes: 获取各集热设备在时间t的热能转换效率ηj(t)；Obtain the thermal energy conversion efficiency ηj (t) of each heat collection device at time t; 获取各集热设备的当前污染程度δj及最大允许污染程度δjmax；Obtain the current pollution level δj and the maximum allowable pollution level δjmax for each solar collector; 基于所述当前污染程度δj和所述最大允许污染程度δjmax得到清洁度因子Cjclean(t)：Based on the current pollution level δj and the maximum permissible pollution level δjmax, the cleanliness factor Cj clean (t) is obtained: 基于所述热能转换效率ηj(t)和清洁度因子Cjclean(t)得到所述第二性能系数P2j(t)：Based on the aforementioned thermal energy conversion efficiency ηj (t) and cleanliness factor Cjcle (t), the second performance coefficient P2j (t) is obtained: 其中，c1、c2、c3、c4和c5分别表示各项指标的权重系数；Where c1, c2, c3, c4 and c5 represent the weight coefficients of each indicator; 选取所述第二性能系数小于预设值的集热设备作为所述异常集热设备。The heat collection device whose second performance coefficient is less than the preset value is selected as the abnormal heat collection device.
CN202510181635.4A 2025-02-19 2025-02-19 Distributed photovoltaic heat collection power generation energy storage control system for residential area Active CN120016953B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202510181635.4A CN120016953B (en) 2025-02-19 2025-02-19 Distributed photovoltaic heat collection power generation energy storage control system for residential area

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202510181635.4A CN120016953B (en) 2025-02-19 2025-02-19 Distributed photovoltaic heat collection power generation energy storage control system for residential area

Publications (2)

Publication Number Publication Date
CN120016953A CN120016953A (en) 2025-05-16
CN120016953B true CN120016953B (en) 2026-02-06

Family

ID=95663943

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202510181635.4A Active CN120016953B (en) 2025-02-19 2025-02-19 Distributed photovoltaic heat collection power generation energy storage control system for residential area

Country Status (1)

Country Link
CN (1) CN120016953B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN120262483B (en) * 2025-06-05 2025-08-22 国网上海市电力公司 Distribution network side configuration optimization method based on photovoltaic output characteristics

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117170417A (en) * 2023-11-02 2023-12-05 吉林建筑大学 An integrated control system for distributed photovoltaic heat collection, power generation and energy storage for buildings and residential buildings

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2018166577A1 (en) * 2017-03-13 2018-09-20 Siemens Aktiengesellschaft Method for operating a photovoltaic installation, photovoltaic installation and method of manufacture therefor
AU2019301575C1 (en) * 2018-07-11 2025-10-02 Raygen Resources Pty Ltd Low cost dispatchable solar power
CN115954903A (en) * 2022-10-28 2023-04-11 国网四川省电力公司经济技术研究院 A method and system for controlling charging and discharging of distributed energy storage equipment
CN117060475A (en) * 2023-08-22 2023-11-14 阳光电源(南京)有限公司 A control method and related equipment for new energy charging stations
CN118739276B (en) * 2024-06-14 2025-04-04 江苏新杰智科技有限责任公司 A control method and system based on distributed photovoltaic energy storage

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117170417A (en) * 2023-11-02 2023-12-05 吉林建筑大学 An integrated control system for distributed photovoltaic heat collection, power generation and energy storage for buildings and residential buildings

Also Published As

Publication number Publication date
CN120016953A (en) 2025-05-16

Similar Documents

Publication Publication Date Title
CN117879018B (en) Configuration operation method of energy storage system for new energy consumption
CN116454951A (en) Light energy storage control system and method
CN107039975B (en) Energy management method for distributed energy system
CN118282017A (en) A photovoltaic energy storage management and regulation system based on artificial intelligence
CN118971099A (en) A power coordination control method for a photovoltaic power station
CN118054451A (en) Wind farm group optimized energy storage management method and device, microgrid system
CN114036451A (en) Energy storage control method and system of grid-connected optical storage and charging device
CN117663503B (en) Method and system for intelligently adjusting molten salt heat storage rate
CN119543421B (en) An energy management system and method based on cloud-edge integrated photovoltaic storage system
CN118409549B (en) Equipment control method and system based on green energy-saving building
CN107425541B (en) A kind of active distribution network wind storage combined scheduling method
CN120016953B (en) Distributed photovoltaic heat collection power generation energy storage control system for residential area
CN119726879B (en) Self-adaptive regulation and control method for light storage straight-flexible system of low-carbon transformer substation
CN119315700A (en) Photovoltaic power generation energy storage intelligent control method and system
CN118920523A (en) Energy storage configuration method and system based on optical storage, charging and replacement integrated power station
CN118842095A (en) Regulation and control method for low-voltage distributed photovoltaic grid-connected point
CN117458543A (en) A method and system for power optimization of microgrid group energy storage devices
CN119401518A (en) A photovoltaic energy storage dispatching and management system
CN117639050B (en) Distributed multi-energy nanogrid monitoring method and system
CN118868176A (en) An optimization scheduling method and system for energy storage system
CN117748509A (en) Renewable energy system grid-connected scheduling control method based on liquid cooling energy storage system
CN117691653A (en) Optimal operation method of distributed energy storage power stations based on model predictive control algorithm
CN120517246B (en) A control method and system for intelligent photovoltaic charging piles
CN116505591A (en) A method and device for a virtual power plant to participate in the coordinated optimal dispatch of a distribution network
CN114825400A (en) Energy storage optimization configuration method for wind-solar-energy-storage combined operation

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant