CN116760097A - A photovoltaic grid-connected flexible control system - Google Patents
A photovoltaic grid-connected flexible control system Download PDFInfo
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- 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
- H02J3/38—Arrangements for feeding a single network from two or more generators or sources in parallel; Arrangements for feeding already energised networks from additional generators or sources in parallel
- H02J3/381—Dispersed generators
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- 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
- H02J3/004—Generation forecast, e.g. methods or systems for forecasting future energy generation
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- 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
- H02J3/38—Arrangements for feeding a single network from two or more generators or sources in parallel; Arrangements for feeding already energised networks from additional generators or sources in parallel
- H02J3/46—Controlling the sharing of generated power between the generators, sources or networks
- H02J3/466—Scheduling or selectively controlling the operation of the generators or sources, e.g. connecting or disconnecting generators to meet a demand
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- 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
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- 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
- H02J2103/00—Details of circuit arrangements for mains or AC distribution networks
- H02J2103/30—Simulating, planning, modelling, reliability check or computer assisted design [CAD] of electric power networks
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- 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
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Abstract
本发明提供一种光伏并网柔性控制系统，包括电量预测模块、负荷计算模块、柔性计算模块、策略配置模块以及策略分配模块，可以根据光伏并网节点的实际负荷值以及用户的柔性响应值对供电需求进行柔性分析，最大化光伏电能的利用，提高了资源利用的合理性以及利用率；另一方面，由于所有控制信息通过数据中台的方式进行分析和生成，虽然可以集中算力，但是通讯负荷较高，也需要一定的传输和响应时间，本发明用于解决现有的光伏并网控制系统在对光伏并网进行分析控制时存在分析不够全面以及控制不够及时的问题。
The invention provides a photovoltaic grid-connected flexible control system, which includes a power prediction module, a load calculation module, a flexible calculation module, a strategy configuration module and a strategy distribution module. It can control the system according to the actual load value of the photovoltaic grid-connected node and the user's flexible response value. Flexible analysis of power supply demand maximizes the utilization of photovoltaic energy and improves the rationality and utilization rate of resource utilization. On the other hand, since all control information is analyzed and generated through the data center, although computing power can be concentrated, The communication load is high and a certain amount of transmission and response time is required. The present invention is used to solve the problems of insufficient analysis and insufficient timely control in existing photovoltaic grid-connected control systems when analyzing and controlling photovoltaic grid-connected systems.
Description
Technical Field
The invention relates to the field of grid-connected control, in particular to a photovoltaic grid-connected flexible control technology.
Background
Grid connection control, namely monitoring and analyzing various types of electric energy in a grid connection system, analyzing the requirements of users for electric energy quality, and controlling and adjusting the transmission proportion of various types of electric energy in the grid connection system according to the requirements of the users for the electric energy quality;
in the existing photovoltaic grid-connected control system, existing power data are monitored and analyzed, the current photovoltaic grid-connected state is controlled and regulated, and prediction of the photovoltaic grid-connected operation state is lacking, so that predictive control on the photovoltaic grid-connected state cannot be performed, and whether a photovoltaic module has faults or not is difficult to judge; and at present, on the power grid dispatching level, only large-scale power plants, load aggregators and participation demand response users can be dispatched, dispatching on distributed photovoltaic resident users is omitted, as the photovoltaic power generation system is influenced by power generation influence values corresponding to illumination and temperature, the output has the characteristics of randomness, volatility and intermittence, the existing photovoltaic grid-connected control system is difficult to control the photovoltaic users in real time, and the problems of incomplete analysis and untimely control exist in the existing photovoltaic grid-connected control system when the photovoltaic grid-connected control is analyzed and controlled.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a photovoltaic grid-connected flexible control system, which can predict the generated energy of a photovoltaic module and analyze the generated energy by combining with the actual value of the generated energy, judge whether the photovoltaic module has faults, analyze various information of the power load of a user and the user side, configure corresponding output strategies in the system, and select the output strategies in a table look-up mode of analysis results so as to solve the problems of incomplete analysis and untimely control when the existing photovoltaic grid-connected control system performs analysis control on the photovoltaic grid connection.
In order to achieve the above object, the present invention is realized by the following technical scheme: a photovoltaic grid-connected flexible control system, which comprises an electric quantity prediction module, a load calculation module, a flexible calculation module, a strategy configuration module and a strategy distribution module,
the electric quantity prediction module is used for calculating the predicted value of the generated energy of each user photovoltaic module;
the load calculation module is configured with a load calculation model, the load calculation model comprises photovoltaic grid-connected power supply topologies, nodes of each photovoltaic grid-connected power supply topology correspond to user photovoltaic modules, the load calculation model corresponds to each user photovoltaic module and is configured with a load calculation algorithm, and the power generation predicted value is brought into the load calculation algorithm to obtain a power generation load value of each user photovoltaic module;
the flexible calculation module is used for calculating a flexible response value according to the characteristic information of the photovoltaic module of the user;
the strategy configuration module is configured with a plurality of strategy index tables, the strategy index tables are configured with a plurality of output strategies, the output strategies take the power generation load value and the flexible response value as indexes, and the strategy configuration module obtains the output strategy of each user photovoltaic module according to the power generation load value and the flexible response value;
the strategy distribution module updates the output strategy every first preset time, and configures the output strategy to the user photovoltaic module;
the output strategy comprises a plurality of trigger conditions and corresponding output instructions, and when the generated energy information generated by the corresponding user photovoltaic module meets the trigger conditions, the corresponding output instructions are executed.
Further, the electric quantity prediction module is configured with an electric quantity prediction algorithm for calculating an electric quantity predicted value, and the electric quantity prediction algorithm is configured to:wherein G is a predicted value of generating capacity, W is a power generation influence value corresponding to weather information, li is a power generation influence value corresponding to illumination intensity, T is a power generation influence value corresponding to temperature, K1 is a preset first weight, K2 is a preset second weight, K3 is a preset third weight, A1 is a first conversion value, A2 is a second conversion value, A3 is a third conversion value, and alpha is a preset generating capacity prediction coefficient.
Further, in the grid-connected power supply topology, transmission paths among nodes are marked with a transmission electric quantity loss ratio and a transmission quality loss ratio.
Further, the load calculation algorithm is thatWherein E is a To generate load value beta 1 As the load weight of the generated energy, deltaP is the historical power generation efficiency in the historical power generation information, beta 2 For a preset topology loss weight, there is beta 1 +β 2 ＝1，h i For the loss of the transmission electric quantity corresponding to the ith transmission path in the user photovoltaic module, g i And n is the total number of power supply transmission paths of the user photovoltaic module for the transmission quality loss ratio corresponding to the ith transmission path in the user photovoltaic module.
Further, the historical power generation efficiency is calculated by the following formula:wherein χ is p Is a preset power generation efficiency parameter, t 0 T is the current time, t j T is the start time of the j-th power generation waveform with the same time sequence characteristic a For the first preset time, f j (x) For the j-th power generation waveform having the same timing characteristic, m is the total number of power generation waveforms having the same timing characteristic.
Further, the flexible computing module is configured with a flexible response algorithm, wherein the flexible response algorithm is b=k4×ec+k5×eq/a4+k6×qf; wherein, B is a flexible response value, ec is energy storage of a user, eq is power generation quality, qf is floating power consumption, K4 is a preset fourth weight, K5 is a preset fifth weight, K6 is a preset sixth weight, and A4 is a preset fourth conversion value.
Further, the user photovoltaic module is correspondingly configured with an indoor power supply branch and a community power supply branch, an indoor power supply task is arranged corresponding to the indoor power supply branch, a community power supply task is arranged corresponding to the community power supply branch, and the calculation formula of the floating electricity consumption is as follows:wherein ε is 1 For the preset indoor power supply weight epsilon 2 Power supply weight q for preset communities la To supply power for the la houseTask-corresponding floating electron value, q lb And (3) providing floating power supply values corresponding to the power supply tasks of the lbth community, wherein ka is the total number of indoor power supply tasks, and kb is the total number of power supply tasks of the community.
Further, the device also comprises a feedback correction module, wherein the feedback correction module is configured with a first error threshold and a first fault threshold, calculates the difference between the actual generated energy and the generated energy predicted value to obtain a generated energy difference, and outputs a calculation normal signal if the generated energy difference is smaller than or equal to the first error threshold; outputting a parameter calibration signal if the generated energy difference value is larger than the first error threshold value and smaller than or equal to the first fault threshold value; if the generated energy difference value is larger than the first fault threshold value, outputting a photovoltaic module fault signal;
if the parameter calibration signal is output, it passes through the formula alpha 1 ＝r a α 0 [(Gs-G)/G+1]Wherein alpha is 1 Alpha is the prediction coefficient of the modified power generation amount 0 R is the power generation amount prediction coefficient before correction a And Gs is the actual power generation amount and is a preset correction proportion value.
Further, each triggering condition comprises a different power generation quality reference and a power generation amount reference, the user photovoltaic module acquires power generation amount information in real time, and when the power generation quality in the power generation amount information meets the power generation quality reference and the power generation amount in the power generation amount information meets the power generation amount reference, the corresponding triggering condition is considered to be met.
The invention has the beneficial effects that: according to the invention, the generated energy of the photovoltaic module is predicted, and then the actual generated energy of the photovoltaic module is analyzed, so that the states of a plurality of photovoltaic modules on the photovoltaic grid can be judged, whether the photovoltaic module fails or not can be timely judged, and if the photovoltaic module does not fail, the calculation parameters of the generated energy prediction model are adjusted;
according to the invention, the actual load value of the corresponding photovoltaic grid-connected node and the uploading electric quantity of the user are obtained by analyzing the electric load of the photovoltaic grid-connected node, the flexible response value of the user is analyzed, the power supply capacity of the corresponding user is reflected through the flexible response value, and whether the photovoltaic grid-connected node can be additionally powered, and the method has the advantages that the power supply requirement can be flexibly analyzed according to the actual load value of the photovoltaic grid-connected node and the flexible response value of the user, the utilization of the photovoltaic electric energy is maximized, and the rationality and the utilization rate of the resource utilization are improved;
according to the method, the corresponding output strategy is found by establishing the strategy reference table and carrying out the table lookup on the actual load value of the photovoltaic grid-connected node and the flexible response value of the user, so that the problem of data caused by overlarge load during centralized data processing can be avoided, and the safety of system operation, the timeliness and the accuracy of data processing are improved.
Additional aspects of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
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Other features, objects and advantages of the present invention will become more apparent upon reading of the detailed description of non-limiting embodiments, given with reference to the accompanying drawings in which:
FIG. 1 is a schematic diagram of the architecture of the system of the present invention.
Detailed Description
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present invention.
Embodiments of the invention and features of the embodiments may be combined with each other without conflict.
Referring to fig. 1, a photovoltaic grid-connected flexible control system includes an electric quantity prediction module, a load calculation module, a flexible calculation module, a strategy configuration module and a strategy distribution module,
the electric quantity prediction module is used for calculating the predicted value of the generated energy of each user photovoltaic module; the electric quantity prediction module is configured with an electric quantity prediction algorithm for calculating an electric quantity predicted value, and the electric quantity prediction algorithm is configured to:wherein G is a predicted value of generating capacity, W is a power generation influence value corresponding to weather information, li is a power generation influence value corresponding to illumination intensity, T is a power generation influence value corresponding to temperature, K1 is a preset first weight, K2 is a preset second weight, K3 is a preset third weight, A1 is a first conversion value, A2 is a second conversion value, A3 is a third conversion value, and alpha is a preset generating capacity prediction coefficient. In a specific application, the first prediction time is set to 1 hour, K1 is set to 0.3, K2 is set to 0.5, K3 is set to 0.2, A1 is set to 0.003, A2 is set to 1000, A3 is set to 10, α is set to 0.99, and when weather is sunny, the power generation influence value corresponding to weather information is 3; when the weather is negative, the power generation influence value corresponding to the weather information is 2; when the weather is rain, the power generation influence value corresponding to the weather information is 1; when the weather is snow, the power generation influence value corresponding to the weather information is 1; and if weather in the future first prediction time is sunny, weather information W is 3, a power generation influence value Li corresponding to illumination intensity is 67824lx, a power generation influence value T corresponding to temperature is 30 ℃, the power generation amount of the photovoltaic module of the user 1 is predicted, a power generation amount predicted value G is calculated to be 1054.55kw, and a calculation result is reserved in two decimal places. The prediction data acquisition unit is used for accessing a network weather forecast and acquiring weather information, a power generation influence value corresponding to illumination intensity and a power generation influence value corresponding to temperature in a first future prediction time in the weather forecast; the influence of different weather on the photovoltaic power generation information can be generated by calculating a numerical value through the relation between actual weather and photovoltaic power generation efficiency in the region. This makes it possible to generate a relationship between weather, temperature, lighting conditions, and power generation amount corresponding to the next period of the user.
The load calculation module is configured withThe load calculation model comprises photovoltaic grid-connected power supply topologies, wherein nodes of each photovoltaic grid-connected power supply topology correspond to a user photovoltaic module, and transmission paths among the nodes in the photovoltaic grid-connected power supply topologies are marked with transmission electric quantity loss ratios and transmission quality loss ratios. The load calculation model is configured with a load calculation algorithm corresponding to each user photovoltaic module, and the generated energy predicted value is brought into the load calculation algorithm to obtain a generated load value of each user photovoltaic module; the load calculation algorithm is thatWherein E is a To generate load value beta 1 As the load weight of the generated energy, deltaP is the historical power generation efficiency in the historical power generation information, beta 2 For a preset topology loss weight, there is beta 1 +β 2 ＝1，h i For the loss of the transmission electric quantity corresponding to the ith transmission path in the user photovoltaic module, g i And n is the total number of power supply transmission paths of the user photovoltaic module for the transmission quality loss ratio corresponding to the ith transmission path in the user photovoltaic module. The historical power generation efficiency is calculated by the following formula:Wherein χ is p Is a preset power generation efficiency parameter, t 0 T is the current time, t j T is the start time of the j-th power generation waveform with the same time sequence characteristic a For the first preset time, f j (x) For the j-th power generation waveform having the same timing characteristic, m is the total number of power generation waveforms having the same timing characteristic. The load of each node under different power supply amounts is calculated, and the load of the uploading redundant power consumption to the whole system is calculated, so that a judgment basis is made for whether the power consumption is used as local energy storage or not and whether the community is close to a direct power supply selection mode, on one hand, the historical power generation condition is acquired, and on the other hand, the historical power generation efficiency is calculated, so that the change of the actual power generation value caused by different positions or equipment is obtained, and a more accurate result is obtained, and on the other hand, the power is transmitted according to the power supplyThe actual loss condition is judged, and the method is more reliable and accurate.
The flexible calculation module is used for calculating a flexible response value according to the characteristic information of the photovoltaic module of the user; the flexible computing module is configured with a flexible response algorithm, wherein the flexible response algorithm is B=K4+K5+Eq/A4+K6 Qf; wherein, B is a flexible response value, ec is energy storage of a user, eq is power generation quality, qf is floating power consumption, K4 is a preset fourth weight, K5 is a preset fifth weight, K6 is a preset sixth weight, and A4 is a preset fourth conversion value. In a specific application, K4 is set to 0.3, K5 is set to 0.4, K6 is set to 0.1, A4 is set to 0.5, the energy storage Ec of a user is obtained to be 800kw, the Eq power generation quality is 200, the floating power consumption Qf is 2000kw, and the flexible response value B of the user 1 is obtained through calculation to be 600. The user photovoltaic module is correspondingly provided with an indoor power supply branch and a community power supply branch, an indoor power supply task is arranged corresponding to the indoor power supply branch, a community power supply task is arranged corresponding to the community power supply branch, and the floating electricity consumption calculation formula is as follows:wherein ε is 1 For the preset indoor power supply weight epsilon 2 Power supply weight q for preset communities la A floating power supply value corresponding to the la-th indoor power supply task, q lb And (3) providing floating power supply values corresponding to the power supply tasks of the lbth community, wherein ka is the total number of indoor power supply tasks, and kb is the total number of power supply tasks of the community. The user data acquisition unit acquires the power consumption required by the dynamic power consumption task in a user uploading mode, and marks the power consumption as floating power consumption; the dynamic electricity utilization task is an electricity utilization activity which does not belong to the daily electricity utilization range; for example, the dynamic electricity task is an electricity task that a user needs to maintain a power generation influence value corresponding to indoor temperature or heat hot water, and the floating electricity consumption corresponding to the dynamic electricity task is obtained through interaction with an intelligent platform at the user side, so that when the electricity consumption required to be output to a power grid at the photovoltaic side is small, the electricity can be used for the floating tasks. The user can also directly supply power to the nearby community devices to serve as a floating task, such as the charging system of the communityAnd the system, the community cleaning equipment, the filtering equipment and the like make full use of the advantages of the transmission distance, calculate floating tasks and have different weights of different floating power supply tasks. Then, the optimal output strategy in the hour is found according to the actual load value and the flexible response value in a table look-up mode, so that the influence of data centralized processing caused by randomness can be avoided, and then the middle station adjusts the parameters for calculating the actual load value according to the actual expected power transmission quantity and the actual power transmission quantity of each node, so that the actual load value and the theoretical load value in the next time are more approximate. The user data acquisition unit is a mobile phone APP installed on a user side of the photovoltaic grid-connected flexible control system, and a user can input a predicted value of the electricity consumption of the special electricity consumption requirement through the APP when the user has the special electricity consumption requirement. Because the power supply end on the photovoltaic parallel network consists of a power plant and distributed photovoltaic resident users, the power distribution and the power consumption of each area are difficult to accurately analyze, and data support can be provided for the selection of the power supply end by analyzing the actual load value of the photovoltaic grid-connected node.
The strategy configuration module is configured with a plurality of strategy index tables, the strategy index tables are configured with a plurality of output strategies, the output strategies take the power generation load value and the flexible response value as indexes, and the strategy configuration module obtains the output strategy of each user photovoltaic module according to the power generation load value and the flexible response value; the strategy distribution module updates the output strategy every first preset time, and configures the output strategy to the user photovoltaic module; the photovoltaic module can be adjusted directly according to the actual situation according to the output strategy.
The output strategy comprises a plurality of trigger conditions and corresponding output instructions, and when the generated energy information generated by the corresponding user photovoltaic module meets the trigger conditions, the corresponding output instructions are executed. Each triggering condition comprises different power generation quality references and power generation amount references, the user photovoltaic module acquires power generation amount information in real time, and when the power generation quality in the power generation amount information meets the power generation quality references and the power generation amount in the power generation amount information meets the power generation amount references, the corresponding triggering conditions are considered to be met. Establishing a power generation quality evaluation table, recording the power generation quality corresponding to each uploading harmonic frequency, and comparing and searching the uploading harmonic frequency with the power generation quality evaluation table to obtain the corresponding power generation quality; the calculation of the generated energy can be obtained through the electric energy meter.
The power generation quality evaluation table is shown in the following table:
acquiring uploading harmonic frequency of a user, and comparing the uploading harmonic frequency with a power generation quality evaluation table to obtain power generation quality corresponding to the user;
in the specific application, the uploading harmonic frequency of the user 1 is obtained to be 4 through a power analyzer, and the power generation quality Eq of the user 1 is obtained to be 3 through comparison with a power generation quality evaluation table; the output instruction can supply power to a power grid, or supply power to a user or a setting, and different output instructions can be generated according to different power supply quality and power supply quantity to realize power supply.
The device comprises a power generation module, a feedback correction module and a control module, wherein the power generation module is provided with a first error threshold value and a first fault threshold value, the feedback correction module calculates the difference value between the actual power generation amount and a power generation amount predicted value to obtain a power generation amount difference value, and if the power generation amount difference value is smaller than or equal to the first error threshold value, a calculation normal signal is output; outputting a parameter calibration signal if the generated energy difference value is larger than the first error threshold value and smaller than or equal to the first fault threshold value; if the generated energy difference value is larger than the first fault threshold value, outputting a photovoltaic module fault signal;
if the parameter calibration signal is output, it passes through the formula alpha 1 ＝r a α 0 [(Gs-G)/G+1]Wherein alpha is 1 Alpha is the prediction coefficient of the modified power generation amount 0 R is the power generation amount prediction coefficient before correction a And Gs is the actual power generation amount and is a preset correction proportion value.
The invention provides a photovoltaic grid-connected flexible control system, which is used for judging whether a photovoltaic module has faults or not by predicting the generated energy of the photovoltaic module and analyzing the generated energy by combining with the actual value of the generated energy, analyzing various information of a user power load and a user side, configuring a corresponding output strategy in the system, and selecting the output strategy in a table look-up mode of an analysis result so as to solve the problems that the existing photovoltaic grid-connected control system is not comprehensive in analysis and not timely in control when the photovoltaic grid-connected control is performed.
Working principle: firstly, acquiring corresponding information through a prediction data acquisition unit, predicting the generated energy of a photovoltaic module through a generated energy prediction unit, acquiring the power load and the uploading electric quantity of a photovoltaic grid-connected node in a photovoltaic grid-connected database through a system data acquisition unit, and analyzing the power load and uploading electric quantity through a load analysis unit to obtain an actual load value of the corresponding photovoltaic grid-connected node;
the method comprises the steps that energy storage capacity, floating electricity consumption and uploading harmonic frequency of a user are obtained through a user data obtaining unit, the energy storage capacity, floating electricity consumption and uploading harmonic frequency of the user are analyzed through a flexible response analysis unit to obtain a flexible response value of the corresponding user, an actual load value of a photovoltaic grid-connected node and the flexible response value of the user are analyzed through a table look-up mode, corresponding output strategies are judged to be configured to corresponding user photovoltaic modules, the user photovoltaic modules can configure local power generation conditions according to the output strategies, and a request middle platform does not need to conduct data analysis and processing;
and analyzing the power generation predicted value and the actual power generation of the photovoltaic module through power generation analysis to obtain whether the photovoltaic module fails or whether parameter calibration is required to be carried out on a power generation prediction model.
The above examples are only specific embodiments of the present invention, and are not intended to limit the scope of the present invention, but it should be understood by those skilled in the art that the present invention is not limited thereto, and that the present invention is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (9)
1. A photovoltaic grid-connected flexible control system is characterized by comprising an electric quantity prediction module, a load calculation module, a flexible calculation module, a strategy configuration module and a strategy distribution module,
the electric quantity prediction module is used for calculating the predicted value of the generated energy of each user photovoltaic module;
the load calculation module is configured with a load calculation model, the load calculation model comprises photovoltaic grid-connected power supply topologies, nodes of each photovoltaic grid-connected power supply topology correspond to user photovoltaic modules, the load calculation model corresponds to each user photovoltaic module and is configured with a load calculation algorithm, and the power generation predicted value is brought into the load calculation algorithm to obtain a power generation load value of each user photovoltaic module;
the flexible calculation module is used for calculating a flexible response value according to the characteristic information of the photovoltaic module of the user;
the strategy configuration module is configured with a plurality of strategy index tables, the strategy index tables are configured with a plurality of output strategies, the output strategies take the power generation load value and the flexible response value as indexes, and the strategy configuration module obtains the output strategy of each user photovoltaic module according to the power generation load value and the flexible response value;
the strategy distribution module updates the output strategy every first preset time, and configures the output strategy to the user photovoltaic module;
the output strategy comprises a plurality of trigger conditions and corresponding output instructions, and when the generated energy information generated by the corresponding user photovoltaic module meets the trigger conditions, the corresponding output instructions are executed.
2. The photovoltaic grid-connected flexible control system of claim 1, wherein the power prediction module is configured with power predictionThe algorithm is used for calculating a power generation amount predicted value, and the power generation amount predicted algorithm is configured to:wherein G is a predicted value of generating capacity, W is a power generation influence value corresponding to weather information, li is a power generation influence value corresponding to illumination intensity, T is a power generation influence value corresponding to temperature, K1 is a preset first weight, K2 is a preset second weight, K3 is a preset third weight, A1 is a first conversion value, A2 is a second conversion value, A3 is a third conversion value, and alpha is a preset generating capacity prediction coefficient.
3. The photovoltaic grid-connected flexible control system of claim 2, wherein transmission paths between nodes in the photovoltaic grid-connected power supply topology are marked with a transmission power loss ratio and a transmission quality loss ratio.
4. A photovoltaic grid-connected flexible control system according to claim 3, wherein the load calculation algorithm isWherein E is a To generate load value beta 1 As the load weight of the generated energy, deltaP is the historical power generation efficiency in the historical power generation information, beta 2 For a preset topology loss weight, there is beta 1 +β 2 ＝1，h i For the loss of the transmission electric quantity corresponding to the ith transmission path in the user photovoltaic module, g i And n is the total number of power supply transmission paths of the user photovoltaic module for the transmission quality loss ratio corresponding to the ith transmission path in the user photovoltaic module.
5. The photovoltaic grid-connected flexible control system of claim 4, wherein the historical power generation efficiency is calculated by the formula:wherein χ is p Is a preset power generation efficiency parameter, t 0 T is the current time, t j T is the start time of the j-th power generation waveform with the same time sequence characteristic a For the first preset time, f j (x) For the j-th power generation waveform having the same timing characteristic, m is the total number of power generation waveforms having the same timing characteristic.
6. The photovoltaic grid-connected flexible control system according to claim 1, wherein the flexible computing module is configured with a flexible response algorithm, the flexible response algorithm being b=k4+k5×eq/a4+k6×qf; wherein, B is a flexible response value, ec is energy storage of a user, eq is power generation quality, qf is floating power consumption, K4 is a preset fourth weight, K5 is a preset fifth weight, K6 is a preset sixth weight, and A4 is a preset fourth conversion value.
7. The photovoltaic grid-connected flexible control system according to claim 6, wherein the user photovoltaic module is correspondingly configured with an indoor power supply branch and a community power supply branch, an indoor power supply task is set corresponding to the indoor power supply branch, a community power supply task is set corresponding to the community power supply branch, and the floating electricity consumption calculation formula is as follows:wherein ε is 1 For the preset indoor power supply weight epsilon 2 Power supply weight q for preset communities la A floating power supply value corresponding to the la-th indoor power supply task, q lb And (3) providing floating power supply values corresponding to the power supply tasks of the lbth community, wherein ka is the total number of indoor power supply tasks, and kb is the total number of power supply tasks of the community.
8. The photovoltaic grid-connected flexible control system according to claim 1, further comprising a feedback correction module configured with a first error threshold and a first fault threshold, wherein the feedback correction module calculates a difference between an actual power generation amount and a predicted power generation amount to obtain a power generation amount difference, and outputs a calculation normal signal if the power generation amount difference is less than or equal to the first error threshold; outputting a parameter calibration signal if the generated energy difference value is larger than the first error threshold value and smaller than or equal to the first fault threshold value; if the generated energy difference value is larger than the first fault threshold value, outputting a photovoltaic module fault signal;
if the parameter calibration signal is output, it passes through the formula alpha 1 ＝r a α 0 [(Gs-G)/G+1]Wherein alpha is 1 Alpha is the prediction coefficient of the modified power generation amount 0 R is the power generation amount prediction coefficient before correction a And Gs is the actual power generation amount and is a preset correction proportion value.
9. The photovoltaic grid-connected flexible control system of claim 1, wherein: each triggering condition comprises different power generation quality references and power generation amount references, the user photovoltaic module acquires power generation amount information in real time, and when the power generation quality in the power generation amount information meets the power generation quality references and the power generation amount in the power generation amount information meets the power generation amount references, the corresponding triggering conditions are considered to be met.
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| CN118659426A (en) * | 2024-06-03 | 2024-09-17 | 国网安徽省电力有限公司淮北供电公司 | Distributed photovoltaic energy storage energy management system based on artificial intelligence |
| CN119171526A (en) * | 2024-11-25 | 2024-12-20 | 南京飞腾电子科技有限公司 | An intelligent control method and system based on photovoltaic grid-connected switches |
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| CN118659426A (en) * | 2024-06-03 | 2024-09-17 | 国网安徽省电力有限公司淮北供电公司 | Distributed photovoltaic energy storage energy management system based on artificial intelligence |
| CN119171526A (en) * | 2024-11-25 | 2024-12-20 | 南京飞腾电子科技有限公司 | An intelligent control method and system based on photovoltaic grid-connected switches |
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