Short-term combined heat and power storage photovoltaic photo-thermal integrated energy system and control method

Abstract

The invention provides a short-term combined heat and power storage photovoltaic and photo-thermal integrated energy system and a control method. The method comprises the steps that the heating and power generation capacity of a photovoltaic and photo-thermal assembly and the heat and power utilization demand of a heat and power supply area in a future target short term are predicted respectively; a combined heat and power storage scheme is decided based on the heating and power generation capacity and the heat and power utilization requirements; and based on the combined heat and power storage scheme, the heating power generation energy of the photovoltaic photo-thermal assembly is jointly stored to the photoelectric energy storage assembly in a target short period. According to the method, the heating and power generation capacity of the photovoltaic photo-thermal assembly and the heat and power utilization demand of the thermoelectric supply area in the future target short period are predicted respectively, the combined heat and power storage scheme is decided based on the heating and power generation capacity and the heat and power utilization demand, and the power generation capacity of the photovoltaic photo-thermal assembly is determined based on the combined heat and power storage scheme. The heating and power generation energy of the photovoltaic and photo-thermal assembly is jointly stored to the photoelectric energy storage assembly in the target short period, management personnel do not need to carry out energy storage decision control purely manually, the labor cost is reduced, and the reasonability of energy storage decision control is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic and thermal energy, and in particular to a short-term combined heat and power photovoltaic and thermal integrated energy system and a control method. Background Art

[0002] With the development of photovoltaic technology and solar thermal technology, the power supply and heating needs in many regions have been solved in a green and environmentally friendly way.

[0003] The amount of thermoelectric energy generated by photovoltaic and solar thermal technologies basically depends on the amount of solar energy collected. However, the amount of solar energy collected in some areas is greatly affected by factors such as weather. In order to avoid the inability to provide electricity and heat to the area in the short term in the future, it is necessary to combine the thermoelectric energy obtained by photovoltaic and solar thermal technologies in advance. However, the storage capacity of photovoltaic energy storage components is limited, and the storage cost of full storage is also high. How to reasonably combine the thermoelectric energy obtained by photovoltaic and solar thermal technologies in advance has become an urgent problem to be solved.

[0004] Generally, in order to reasonably carry out combined energy storage of thermal power obtained by photovoltaic technology and solar thermal technology in advance, managers usually carry out energy storage decision-making and control manually. This has a high labor cost and the rationality of energy storage decision-making and control may be insufficient.

[0005] Therefore, a solution is urgently needed. Summary of the invention

[0006] One of the purposes of the present invention is to provide a short-term combined heat and power photovoltaic and solar thermal integrated energy system, which predicts the heating and power generation capacity of photovoltaic and solar thermal components and the heat and electricity demand of the thermal power supply area in the future target short term, and decides on the combined heat and power storage plan based on the heating and power generation capacity and the heat and electricity demand. Based on the combined heat and power storage plan, the heating and power generation energy of the photovoltaic and solar thermal components is combined and stored in the photovoltaic energy storage components in the target short term, and the thermal power energy obtained by photovoltaic technology and solar thermal technology is reasonably combined and stored in advance. There is no need for management personnel to perform storage decision-making control manually, which reduces labor costs and improves the rationality of energy storage decision-making control.

[0007] An embodiment of the present invention provides a short-term photovoltaic and thermal integrated energy system with combined heat and power storage, comprising:

[0008] A prediction module is used to predict the heating and power generation capacity of photovoltaic thermal components and the heat and power demand of the thermal power supply area in the future target short term;

[0009] A decision-making module is used to decide on a combined heat and power storage solution based on the heating and power generation capacity and the demand for heat and electricity;

[0010] The energy storage module is used to store the heating and power generation energy of the photovoltaic thermal component into the photovoltaic energy storage component within a target short period of time based on the cogeneration solution.

[0011] Preferably, the decision module decides on a combined heat and power storage solution based on the heating and power generation capacity and the heat and power demand, including:

[0012] Extract features of heating and power generation capacity and heat and electricity demand to obtain a descriptive feature set;

[0013] Try to determine the first decision knowledge corresponding to the description feature set from the decision knowledge base;

[0014] When the attempt is made to determine the time, a combined heat and power storage scheme is decided based on the first decision knowledge;

[0015] Otherwise, try to determine the idle expert group corresponding to the description feature set from the idle expert group library;

[0016] When the attempt is determined, assist the idle expert group to decide on the combined heat and power storage scheme;

[0017] Otherwise, the second decision knowledge is obtained online based on the descriptive feature set;

[0018] Based on the second decision knowledge, a combined heat and power storage scheme is decided.

[0019] Preferably, the decision module assists the idle expert group in deciding the combined heat and power storage scheme, including:

[0020] Generate a visual model based on heating and power generation capacity and heat and electricity demand;

[0021] Based on the discussion records generated by each idle expert in the idle expert group within a recent first preset time period, determining the recommended viewing perspective of each idle expert in the visualization model;

[0022] Guide each idle expert to view the visualization model from their recommended viewing perspective;

[0023] When at least one idle expert inputs a plan input request, the combined heat and power storage plans input by the idle experts are received.

[0024] Preferably, the decision module determines the recommended viewing perspectives of each idle expert in the visualization model based on the discussion records generated by each idle expert in the idle expert group within the latest first preset time period, including:

[0025] Performing timeline representation processing on the discussion record to obtain a record timeline;

[0026] Vectorizing the keywords in each first record item on the record time axis, the time sequence of each first record item, and the time distance between two adjacent first record items to obtain a situation representation vector;

[0027] Determine the first perspective determination knowledge corresponding to the situation representation vector from the perspective determination knowledge base;

[0028] Based on the knowledge determined from the first perspective, the recommended viewing perspectives of each idle expert are determined in the visualization model;

[0029] and / or,

[0030] When at least a preset number of threshold second record items generated by the same idle expert on the record time axis meet the standard record item conditions, semantic analysis is performed on each second record item to obtain a discussion semantic set;

[0031] Determine the second perspective-determined knowledge corresponding to the discussion semantic set from the perspective-determined knowledge base;

[0032] Based on the knowledge determined from the second perspective, the recommended viewing perspectives of each idle expert are determined in the visualization model;

[0033] Among them, standard record item conditions include:

[0034] The second record item contains at least one standard keyword;

[0035] and / or,

[0036] There is no third record item generated by other idle experts within a preset time range before or after the second record item on the record time axis;

[0037] and / or,

[0038] The time distance between the generation time of the last generated second record item and the end time of the most recent first preset time period is greater than or equal to the distance threshold.

[0039] Preferably, the decision module acquires the second decision knowledge online based on the descriptive feature set, including:

[0040] Determine the conditional generation knowledge corresponding to the description feature set from the conditional generation knowledge base;

[0041] Based on the conditional knowledge generation, multiple knowledge acquisition conditions are generated according to the heating and power generation capacity and the demand for heat and electricity, and the corresponding condition weights are determined;

[0042] Generate an acquisition indication graph based on each knowledge acquisition condition, the condition weight corresponding to each knowledge acquisition condition, and the condition association relationship between each knowledge acquisition condition;

[0043] Access knowledge acquisition scenarios;

[0044] Determine the indication acquisition operation rule and the indication value based on the acquisition indication map and the information interaction information between the knowledge acquisition scenario at every preset second time period;

[0045] When the indication value is greater than or equal to the indication threshold, the indication acquisition operation rule is executed on the knowledge acquisition scenario to obtain sub-knowledge;

[0046] Otherwise, stop accessing the knowledge acquisition scenario;

[0047] Integrate sub-knowledge to obtain the second decision-making knowledge.

[0048] The control method of a short-term combined heat and power photovoltaic and thermal integrated energy system provided in an embodiment of the present invention is characterized by comprising:

[0049] Predict the heating and power generation capacity of photovoltaic thermal modules and the heat and electricity demand in the thermal power supply area in the future target short term;

[0050] Decisions on combined heat and power storage solutions are made based on heating and power generation capacity and heat and power demand;

[0051] Based on the cogeneration scheme, the heating and power generation energy of the photovoltaic thermal components is combined and stored in the photovoltaic energy storage components within a target short period of time.

[0052] Preferably, the decision on the combined heat and power storage scheme based on the heating and power generation capacity and the heat and power demand includes:

[0053] Extract features of heating and power generation capacity and heat and electricity demand to obtain a descriptive feature set;

[0054] Try to determine the first decision knowledge corresponding to the description feature set from the decision knowledge base;

[0055] When the attempt is made to determine the time, a combined heat and power storage scheme is decided based on the first decision knowledge;

[0056] Otherwise, try to determine the idle expert group corresponding to the description feature set from the idle expert group library;

[0057] When the attempt is determined, assist the idle expert group to decide on the combined heat and power storage scheme;

[0058] Otherwise, the second decision knowledge is obtained online based on the descriptive feature set;

[0059] Based on the second decision knowledge, a combined heat and power storage scheme is decided.

[0060] Preferably, the auxiliary idle expert group decides on the combined heat and power storage scheme, including:

[0061] Generate a visual model based on heating and power generation capacity and heat and electricity demand;

[0062] Based on the discussion records generated by each idle expert in the idle expert group within a recent first preset time period, determining the recommended viewing perspective of each idle expert in the visualization model;

[0063] Guide each idle expert to view the visualization model from their recommended viewing perspective;

[0064] When at least one idle expert inputs a plan input request, the combined heat and power storage plans input by the idle experts are received.

[0065] Preferably, the step of determining the recommended viewing perspectives of the idle experts in the idle expert group in the latest first preset time period in the visualization model includes:

[0066] Performing timeline representation processing on the discussion record to obtain a record timeline;

[0067] Vectorizing the keywords in each first record item on the record time axis, the time sequence of each first record item, and the time distance between two adjacent first record items to obtain a situation representation vector;

[0068] Determine the first perspective determination knowledge corresponding to the situation representation vector from the perspective determination knowledge base;

[0069] Based on the knowledge determined from the first perspective, the recommended viewing perspectives of each idle expert are determined in the visualization model;

[0070] and / or,

[0071] When at least a preset number of threshold second record items generated by the same idle expert on the record time axis meet the standard record item conditions, semantic analysis is performed on each second record item to obtain a discussion semantic set;

[0072] Determine the second perspective-determined knowledge corresponding to the discussion semantic set from the perspective-determined knowledge base;

[0073] Based on the knowledge determined from the second perspective, the recommended viewing perspectives of each idle expert are determined in the visualization model;

[0074] Among them, standard record item conditions include:

[0075] The second record item contains at least one standard keyword;

[0076] and / or,

[0077] There is no third record item generated by other idle experts within a preset time range before or after the second record item on the record time axis;

[0078] and / or,

[0079] The time distance between the generation time of the last generated second record item and the end time of the most recent first preset time period is greater than or equal to the distance threshold.

[0080] Preferably, the online acquisition of the second decision knowledge based on the descriptive feature set includes:

[0081] Determine the conditional generation knowledge corresponding to the description feature set from the conditional generation knowledge base;

[0082] Based on the conditional knowledge generation, multiple knowledge acquisition conditions are generated according to the heating and power generation capacity and the demand for heat and electricity, and the corresponding condition weights are determined;

[0083] Generate an acquisition indication graph based on each knowledge acquisition condition, the condition weight corresponding to each knowledge acquisition condition, and the condition association relationship between each knowledge acquisition condition;

[0084] Access knowledge acquisition scenarios;

[0085] Determine the indication acquisition operation rule and the indication value based on the acquisition indication map and the information interaction information between the knowledge acquisition scenario at every preset second time period;

[0086] When the indication value is greater than or equal to the indication threshold, the indication acquisition operation rule is executed on the knowledge acquisition scenario to obtain sub-knowledge;

[0087] Otherwise, stop accessing the knowledge acquisition scenario;

[0088] Integrate sub-knowledge to obtain the second decision-making knowledge.

[0089] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0090] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0091] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0092] Figure 1 A schematic diagram of a short-term combined heat and power photovoltaic and thermal integrated energy system in an embodiment of the present invention;

[0093] Figure 2The present invention is a flowchart of a control method for a short-term photovoltaic-thermal integrated energy system with combined heat and power storage in an embodiment of the present invention. DETAILED DESCRIPTION

[0094] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0095] The embodiment of the present invention provides a short-term photovoltaic and thermal integrated energy system with combined heat and power storage, such as Figure 1 As shown, including:

[0096] Prediction module 1 is used to predict the heating and power generation capacity of photovoltaic thermal components and the heat and power demand of the thermal power supply area in the future target short term;

[0097] Decision module 2, used to decide on the combined heat and power storage solution based on the heating and power generation capacity and the heat and power demand;

[0098] The energy storage module 3 is used to store the heating and power generation energy of the photovoltaic thermal component into the photovoltaic energy storage component within a target short period of time based on the cogeneration solution.

[0099] In the above technical scheme, the future short-term target can be within the next 48 hours; photovoltaic thermal components are devices that use photovoltaic technology to generate electricity and use thermal technology to generate heat; the heating and power generation capacity can be the estimated heating and power generation of photovoltaic thermal components in the target short term. When predicting, it can be predicted based on the weather conditions in the area, solar radiation, historical heating and power generation of photovoltaic thermal components, etc.; the thermal power supply area is the urban area where photovoltaic photovoltaic components supply thermal power, etc.; the demand for heat and electricity is the thermal power required to be used in the thermal power supply area in the target short term; the system decides on the combined heat and power storage scheme based on the heating and power generation capacity and the demand for heat and electricity; the combined heat and power storage scheme is a scheme for jointly storing the heating and power generation energy of photovoltaic thermal components in the target short term in advance to photovoltaic energy storage components; photovoltaic energy storage components are devices for jointly storing thermal energy and electricity.

[0100] This application predicts the heating and power generation capacity of photovoltaic thermal components and the heat and electricity demand in the thermal power supply area in the future target short term, and decides on a cogeneration scheme based on the heating and power generation capacity and the heat and electricity demand. Based on the cogeneration scheme, the heating and power generation energy of the photovoltaic thermal components is combined and stored in the photovoltaic energy storage components in the target short term. The thermal power energy obtained by photovoltaic technology and thermal technology is reasonably combined and stored in advance, and there is no need for management personnel to manually perform energy storage decision-making and control, which reduces labor costs and improves the rationality of energy storage decision-making and control.

[0101] In one embodiment, the decision module decides on a combined heat and power storage solution based on the heating and power generation capacity and the heat and power demand, including:

[0102] Extract features of heating and power generation capacity and heat and electricity demand to obtain a descriptive feature set;

[0103] Try to determine the first decision knowledge corresponding to the description feature set from the decision knowledge base;

[0104] When the attempt is made to determine the time, a combined heat and power storage scheme is decided based on the first decision knowledge;

[0105] Otherwise, try to determine the idle expert group corresponding to the description feature set from the idle expert group library;

[0106] When the attempt is determined, assist the idle expert group to decide on the combined heat and power storage scheme;

[0107] Otherwise, the second decision knowledge is obtained online based on the descriptive feature set;

[0108] Based on the second decision knowledge, a combined heat and power storage scheme is decided.

[0109] In the above technical solution, the descriptive feature set can reflect the pending decision situations that require the decision of the cogeneration scheme. The descriptive feature set contains multiple descriptive features, including: the estimated total heating power generation of photovoltaic thermal components in the target short term, the estimated heating power generation and failure probability of different heating power generation sub-components in the photovoltaic thermal components in the target short term, the estimated total thermal energy demand and the estimated total electric energy demand in the thermal power supply area in the target short term, the estimated thermal energy demand and the estimated electric energy demand of different electricity users in the thermal power supply area in the target short term, etc.; the system presets a decision knowledge base, and when the first decision knowledge corresponding to the descriptive feature set is tried to be determined from the decision knowledge base, it means that the decision knowledge base can respond and make a scheme decision. Based on the first decision knowledge, a decision is made on the cogeneration scheme, where the first decision knowledge may be in the form of expert decision experience, etc.; when it is impossible to determine the first decision knowledge from the decision knowledge base, an attempt is made to determine an idle expert group corresponding to the descriptive feature set from the idle expert group library preset by the system, where there are idle online experts in the idle expert group who are good at making scheme decisions on the situations to be decided reflected by the descriptive feature set, and the idle expert group is assisted in making decisions on the cogeneration scheme; when it is impossible to determine an idle expert group from the idle expert group library, it means that there are no online experts to make a decision at this time, and based on the descriptive feature set, a second decision knowledge is obtained online, where the second decision knowledge is expert experience obtained online that can be used for making decisions on the cogeneration scheme, etc., and based on the second decision knowledge, a decision is made on the cogeneration scheme.

[0110] When deciding on a cogeneration scheme based on the heating and power generation capacity and the heat and electricity demand, the embodiment of the present invention first determines whether the system can use the decision knowledge base to respond on its own. If so, it responds on its own. If not, it determines whether it can connect with a suitable idle expert group. If so, it assists the idle expert group in making a decision. If not, second decision knowledge is obtained online, and a decision is made based on the second decision knowledge. The layered arrangement ensures the comprehensiveness and rationality of the decision on the cogeneration scheme, and greatly improves the applicability of the system and the decision-making ability of the cogeneration scheme.

[0111] In one embodiment, the decision module assists the idle expert group in deciding the combined heat and power storage scheme, including:

[0112] Generate a visualization model based on the heating and power generation capacity and the demand for heat and electricity; when generating the visualization model, the three-dimensional urban map of the thermal power supply area can be used as the basic model, and the estimated total heating and power generation of photovoltaic thermal components in the heating and power generation capacity and the demand for heat and electricity in the target short term, the estimated heating and power generation and failure probability of different heating and power generation sub-components in the photovoltaic thermal components in the target short term, the estimated total demand for heat energy and the estimated total demand for electricity in the thermal power supply area in the target short term, and the estimated heat energy demand and the estimated electricity demand of different electricity users in the thermal power supply area in the target short term are set on the basic model, and then the basic model is used as a visualization model;

[0113] Based on the discussion records generated by each idle expert in the idle expert group within the most recent first preset time period, the recommended viewing perspective of each idle expert is determined in the visualization model; the most recent first preset time period may be the most recent 100 seconds; each idle expert will discuss how to decide on the cogeneration scheme, thereby generating a discussion record; the discussion records generated by each idle expert within the most recent first preset time period reflect the discussion topics, discussion progress, etc. of each idle expert. When each idle expert views the visualization model from their own recommended viewing perspective, they can view the model content that matches the discussion topic and discussion progress in the visualization model, thereby improving the discussion and decision-making efficiency of each idle expert. There is no need for each idle expert to adjust how to view the visualization model according to the discussion content, which is more humane and more intelligent.

[0114] Guide each idle expert to view the visualization model from their recommended viewing perspective;

[0115] When at least one idle expert inputs a scheme input request, the heat and power combined storage scheme input by each idle expert is received. When an idle expert inputs a scheme input request, it means that the idle expert has decided on the heat and power combined storage scheme and needs to input it at this time, so the heat and power combined storage scheme input by each idle expert is received.

[0116] In one embodiment, the decision module determines the recommended viewing perspectives of each idle expert in the visualization model based on the discussion records generated by each idle expert in the idle expert group within the latest first preset time period, including:

[0117] Performing timeline representation processing on the discussion record to obtain a record timeline; when performing timeline representation processing on the discussion record, based on the generation time of each first record item in the discussion record, each first record item is set on the timeline, and finally, the timeline on which each first record item is set is used as the record timeline;

[0118] The keywords in each first record item on the recording time axis, the time sequence of each first record item, and the time distance between each adjacent first record item are vectorized to obtain a situation representation vector; the first record item is the discussion content generated by a speech of an idle expert; the keywords in each first record item on the recording time axis, the time sequence of each first record item, and the time distance between each adjacent first record item are vectorized and converted into vector form to obtain a situation representation vector;

[0119] Determine the first perspective determination knowledge corresponding to the situation representation vector from the perspective determination knowledge base; there is first perspective determination knowledge corresponding to different situation representation vectors in the perspective determination knowledge base, the situation representation vector reflects a first determination situation that requires determination of a recommended viewing perspective, and the first perspective determination knowledge indicates how to determine the recommended viewing perspective in the first determination situation, for example: the keywords in each first record item are "check the electricity demand of Building A in the urban area", "good", "OK", etc., the time sequence of each first record item is first record item B, first record item C, first record item D, the time sequence of each first record item and the time distance between each adjacent first record item are 2 seconds and 1 second respectively, which means that the determination situation reflected by the constructed situation representation vector is that a free expert wants other free experts to check the electricity demand of Building A in the urban area, and the corresponding first perspective determination knowledge is to indicate that the area showing the electricity demand of Building A in the urban area in the visualization model is used as the visual content of the recommended viewing perspective, then based on the first perspective determination knowledge, the recommended viewing perspective of each free expert can be determined in the visualization model;

[0120] Based on the knowledge determined from the first perspective, the recommended viewing perspectives of each idle expert are determined in the visualization model;

[0121] and / or,

[0122] When at least a preset number threshold of second record items generated by the same idle expert on the record time axis meet the standard record item conditions, semantic analysis is performed on each second record item to obtain a discussion semantic set; the preset number threshold may be 2;

[0123] Determine the second perspective determination knowledge corresponding to the discussion semantic set from the perspective determination knowledge base; when at least a preset number of threshold second record items generated by the same idle expert on the recording timeline meet the standard record item conditions, it means that the semantics of each second record item can directly reflect a second determination situation that requires a recommended viewing perspective determination, and perform semantic analysis on each second record item to obtain a discussion semantic set; the perspective determination knowledge base has second perspective determination knowledge corresponding to different discussion semantic sets, and the second perspective determination knowledge indicates how to determine the recommended viewing perspective in this determination situation. For example: the discussion semantics in the discussion semantic set are "first look at the total electricity demand of area E", "then look at the electricity demand of different buildings in area E", etc., which means that a certain idle expert wants other idle experts to look at the total electricity demand of area E first, and then look at the electricity demand of different buildings in area E. After forming the discussion semantic set, the corresponding second perspective determination knowledge is to determine that the recommended viewing perspective is first the perspective of the total electricity demand of the visible area E, and then the perspective of the electricity demand of different buildings in the visible area E;

[0124] Based on the knowledge determined from the second perspective, the recommended viewing perspectives of each idle expert are determined in the visualization model;

[0125] Among them, standard record item conditions include:

[0126] The second record item includes at least one standard keyword; when the second record item includes the standard keyword, it means that the semantics of each second record item can directly reflect a second determination situation that requires determination of a recommended viewing perspective, for example, if the standard keyword is "first", "later", etc., it means that all the second record items reflect the wishes of a certain idle expert on how other idle experts view the visualization model, which can directly reflect a second determination situation that requires determination of a recommended viewing perspective;

[0127] and / or,

[0128] There is no third record item generated by other idle experts within a preset time range before or after the second record item on the recording timeline; the preset time range can be 5 seconds; when the second record item meets this standard record item condition, it means that no other idle experts spoke in a short period of time before and after the second record item was generated, and it is a continuous speech of the same idle expert, which means that all the second record items reflect the wishes of a certain idle expert on how other idle experts view the visualization model, which can directly reflect a second determination situation that requires a recommended viewing perspective determination;

[0129] and / or,

[0130] The time distance between the generation time of the last generated second record item and the end time of the most recent first preset time period is greater than or equal to the distance threshold. The distance threshold can be 30 seconds; when this standard record item condition is met, it means that a certain idle expert has not spoken since his last speech, and may be waiting for others' opinions after expressing his wishes, which means that all second record items reflect the wishes of a certain idle expert on how other idle experts view the visualization model, which can directly reflect a second determination situation that requires a recommended viewing perspective to be determined;

[0131] The embodiment of the present invention introduces two methods when determining the recommended viewing perspective based on the discussion record, which greatly improves the comprehensiveness, rationality and accuracy of the determination of the recommended viewing perspective, and greatly improves the applicability of the system.

[0132] In one embodiment, the decision module acquires the second decision knowledge online based on the descriptive feature set, including:

[0133] Determine the conditional generation knowledge corresponding to the description feature set from the conditional generation knowledge base; there are conditional generation knowledge corresponding to different description feature sets in the conditional generation knowledge base, and the conditional generation knowledge indicates how to generate knowledge acquisition conditions and determine the corresponding condition weights in the pending decision situation reflected by the description feature set that requires the decision on the cogeneration scheme. For example: the description feature set has the estimated total power generation of photovoltaic thermal components in the target short term of 950 kWh, then the conditional generation knowledge indicates that the generated knowledge acquisition condition is that the acquired sub-knowledge must be applicable to the situation that the estimated total power generation of photovoltaic thermal components in the target short term is 950 kW, and the corresponding condition weight is 8. The larger the condition weight, the greater the degree to which the acquired sub-time must meet the corresponding knowledge acquisition condition. The technicians can set the condition weights of different types of knowledge acquisition conditions in advance according to actual needs;

[0134] Based on the conditional knowledge generation, multiple knowledge acquisition conditions are generated according to the heating and power generation capacity and the demand for heat and electricity, and the corresponding condition weights are determined;

[0135] Based on each knowledge acquisition condition, each corresponding condition weight of each knowledge acquisition condition and the condition association relationship between each knowledge acquisition condition, an acquisition indication map is generated; the condition association relationship between each knowledge acquisition condition can be an AND logical relationship, an OR logical relationship, etc.; when generating the acquisition indication map, different knowledge acquisition conditions, their respective condition weights and the condition association relationship between each knowledge acquisition condition can be tabulated according to a preset tabulation template, and the table obtained by tabulation is used as the acquisition indication map;

[0136] Visit the knowledge acquisition scenario; the knowledge acquisition scenario is a scenario for acquiring the second decision-making knowledge, which can be a forum for sharing experience in decision-making of combined heat and power storage solutions, etc.

[0137] At every preset second time period, based on the acquisition of the indication map, according to the information interaction information between the knowledge acquisition scenario, the indication acquisition operation rule and the indication value are determined; the second time period can be 10 seconds; the information interaction information is the newly generated content in the knowledge acquisition scenario, etc.; based on the acquisition of the indication map, the indication acquisition operation rule and the indication value are determined according to the information interaction information, and the indication acquisition operation rule is the next acquisition operation indicated by the acquisition indication map, for example: the information interaction content is the decision-making experience of a certain cogeneration scheme, then the indication acquisition operation is to verify whether the decision-making experience of the cogeneration scheme is applicable to the situation where the total power generation of the photovoltaic thermal component in the target short term is expected to be 950 kilowatts; the indication value represents the credibility of the indication acquisition operation rule indicated by the acquisition indication map, and the larger the indication value, the greater the credibility represented;

[0138] When the indication value is greater than or equal to the indication threshold, the indication acquisition operation rule is executed on the knowledge acquisition scenario to obtain sub-knowledge; the indication threshold can be 5; when the indication value is greater than or equal to the indication threshold, the indication acquisition operation rule is executed on the knowledge acquisition scenario to obtain sub-knowledge;

[0139] Otherwise, stop accessing the knowledge acquisition scenario; when the indication value is less than the indication threshold, it means that the credibility is low, and stop accessing the knowledge acquisition scenario;

[0140] Integrate the sub-knowledge to obtain the second decision-making knowledge. Finally, integrate the sub-knowledge obtained by executing the instruction acquisition operation rule for each knowledge acquisition scenario to obtain the second decision-making knowledge.

[0141] The embodiment of the present invention acquires the second decision knowledge online, introduces conditional generation knowledge, generates multiple knowledge acquisition conditions based on the conditional generation knowledge and determines the corresponding condition weights, then introduces an acquisition indication map, determines indication acquisition operation rules and indication values ​​based on the acquisition indication map, acquires sub-knowledge based on the indication acquisition operation rules and indication values, and determines whether to continue to access the knowledge acquisition scenario. This greatly improves the credibility of the second decision knowledge acquisition and the applicability of the system.

[0142] The embodiment of the present invention provides a control method for the photovoltaic-thermal integrated energy system of short-term heat and power cogeneration, such as Figure 2 As shown, including:

[0143] S1. Forecast the heating and power generation capacity of photovoltaic thermal modules and the heat and electricity demand of the thermal power supply area in the future target short term;

[0144] S2. Decision on the combined heat and power storage solution based on the heating and power generation capacity and the demand for heat and electricity;

[0145] S3. Based on the cogeneration scheme, the heating and power generation energy of the photovoltaic thermal components is combined and stored in the photovoltaic energy storage components within the target short term.

[0146] The decision on the combined heat and power storage solution based on the heating and power generation capacity and the heat and power demand includes:

[0147] Extract features of heating and power generation capacity and heat and electricity demand to obtain a descriptive feature set;

[0148] Try to determine the first decision knowledge corresponding to the description feature set from the decision knowledge base;

[0149] When the attempt is made to determine the time, a combined heat and power storage scheme is decided based on the first decision knowledge;

[0150] Otherwise, try to determine the idle expert group corresponding to the description feature set from the idle expert group library;

[0151] When the attempt is determined, assist the idle expert group to decide on the combined heat and power storage scheme;

[0152] Otherwise, the second decision knowledge is obtained online based on the descriptive feature set;

[0153] Based on the second decision knowledge, a combined heat and power storage scheme is decided.

[0154] The auxiliary idle expert group decides on the combined heat and power storage scheme, including:

[0155] Generate a visual model based on heating and power generation capacity and heat and electricity demand;

[0156] Based on the discussion records generated by each idle expert in the idle expert group within a recent first preset time period, determining the recommended viewing perspective of each idle expert in the visualization model;

[0157] Guide each idle expert to view the visualization model from their recommended viewing perspective;

[0158] When at least one idle expert inputs a plan input request, the combined heat and power storage plans input by the idle experts are received.

[0159] The step of determining the recommended viewing perspectives of the idle experts in the idle expert group based on the discussion records generated within the most recent first preset time period in the idle expert group includes:

[0160] Performing timeline representation processing on the discussion record to obtain a record timeline;

[0161] Vectorizing the keywords in each first record item on the record time axis, the time sequence of each first record item, and the time distance between two adjacent first record items to obtain a situation representation vector;

[0162] Determine the first perspective determination knowledge corresponding to the situation representation vector from the perspective determination knowledge base;

[0163] Based on the knowledge determined from the first perspective, the recommended viewing perspectives of each idle expert are determined in the visualization model;

[0164] and / or,

[0165] When at least a preset number of threshold second record items generated by the same idle expert on the record time axis meet the standard record item conditions, semantic analysis is performed on each second record item to obtain a discussion semantic set;

[0166] Determine the second perspective-determined knowledge corresponding to the discussion semantic set from the perspective-determined knowledge base;

[0167] Based on the knowledge determined from the second perspective, the recommended viewing perspectives of each idle expert are determined in the visualization model;

[0168] Among them, standard record item conditions include:

[0169] The second record item contains at least one standard keyword;

[0170] and / or,

[0171] There is no third record item generated by other idle experts within a preset time range before or after the second record item on the record time axis;

[0172] and / or,

[0173] The time distance between the generation time of the last generated second record item and the end time of the most recent first preset time period is greater than or equal to the distance threshold.

[0174] The method of acquiring the second decision knowledge online based on the description feature set includes:

[0175] Determine the conditional generation knowledge corresponding to the description feature set from the conditional generation knowledge base;

[0176] Based on the conditional knowledge generation, multiple knowledge acquisition conditions are generated according to the heating and power generation capacity and the demand for heat and electricity, and the corresponding condition weights are determined;

[0177] Generate an acquisition indication graph based on each knowledge acquisition condition, the condition weight corresponding to each knowledge acquisition condition, and the condition association relationship between each knowledge acquisition condition;

[0178] Access knowledge acquisition scenarios;

[0179] Determine the indication acquisition operation rule and the indication value based on the acquisition indication map and the information interaction information between the knowledge acquisition scenario at every preset second time period;

[0180] When the indication value is greater than or equal to the indication threshold, the indication acquisition operation rule is executed on the knowledge acquisition scenario to obtain sub-knowledge;

[0181] Otherwise, stop accessing the knowledge acquisition scenario;

[0182] Integrate sub-knowledge to obtain the second decision-making knowledge.

[0183] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A short-term photovoltaic and thermal integrated energy system with combined heat and power storage, characterized in that: include: A prediction module is used to predict the heating and power generation capacity of photovoltaic thermal components and the heat and power demand of the thermal power supply area in the future target short term; A decision-making module is used to decide on a combined heat and power storage solution based on the heating and power generation capacity and the demand for heat and electricity; The energy storage module is used to store the heating and power generation energy of the photovoltaic thermal component into the photovoltaic energy storage component within a target short period of time based on the cogeneration solution.

2. The short-term combined heat and power photovoltaic and thermal integrated energy system according to claim 1, characterized in that: The decision module decides on the combined heat and power storage solution based on the heating and power generation capacity and the heat and power demand, including: Extract features of heating and power generation capacity and heat and electricity demand to obtain a descriptive feature set; Try to determine the first decision knowledge corresponding to the description feature set from the decision knowledge base; When the attempt is made to determine the time, a combined heat and power storage scheme is decided based on the first decision knowledge; Otherwise, try to determine the idle expert group corresponding to the description feature set from the idle expert group library; When the attempt is determined, assist the idle expert group to decide on the combined heat and power storage scheme; Otherwise, the second decision knowledge is obtained online based on the descriptive feature set; Based on the second decision knowledge, a combined heat and power storage scheme is decided.

3. The short-term combined heat and power photovoltaic and thermal integrated energy system according to claim 2, characterized in that: The decision module assists the idle expert group in deciding the combined heat and power storage scheme, including: Generate a visual model based on heating and power generation capacity and heat and electricity demand; Based on the discussion records generated by each idle expert in the idle expert group within a recent first preset time period, determining the recommended viewing perspective of each idle expert in the visualization model; Guide each idle expert to view the visualization model from their recommended viewing perspective; When at least one idle expert inputs a plan input request, the combined heat and power storage plans input by the idle experts are received.

4. The short-term combined heat and power photovoltaic and thermal integrated energy system according to claim 3, characterized in that: The decision module determines the recommended viewing perspectives of each idle expert in the idle expert group in the visualization model based on the discussion records generated by each idle expert in the latest first preset time period, including: Performing timeline representation processing on the discussion record to obtain a record timeline; Vectorizing the keywords in each first record item on the record time axis, the time sequence of each first record item, and the time distance between two adjacent first record items to obtain a situation representation vector; Determine the first perspective determination knowledge corresponding to the situation representation vector from the perspective determination knowledge base; Based on the knowledge determined from the first perspective, the recommended viewing perspectives of each idle expert are determined in the visualization model; and / or, When at least a preset number of threshold second record items generated by the same idle expert on the record time axis meet the standard record item conditions, semantic analysis is performed on each second record item to obtain a discussion semantic set; Determine the second perspective-determined knowledge corresponding to the discussion semantic set from the perspective-determined knowledge base; Based on the knowledge determined from the second perspective, the recommended viewing perspectives of each idle expert are determined in the visualization model; Among them, standard record item conditions include: The second record item contains at least one standard keyword; and / or, There is no third record item generated by other idle experts within a preset time range before or after the second record item on the record time axis; and / or, The time distance between the generation time of the last generated second record item and the end time of the most recent first preset time period is greater than or equal to the distance threshold.

5. The short-term combined heat and power storage photovoltaic and thermal integrated energy system according to claim 3, characterized in that: The decision module acquires the second decision knowledge online based on the description feature set, including: Determine the conditional generation knowledge corresponding to the description feature set from the conditional generation knowledge base; Based on the conditional knowledge generation, multiple knowledge acquisition conditions are generated according to the heating and power generation capacity and the demand for heat and electricity, and the corresponding condition weights are determined; Generate an acquisition indication graph based on each knowledge acquisition condition, the condition weight corresponding to each knowledge acquisition condition, and the condition association relationship between each knowledge acquisition condition; Access knowledge acquisition scenarios; Determine the indication acquisition operation rule and the indication value based on the acquisition indication map and the information interaction information between the knowledge acquisition scenario at every preset second time period; When the indication value is greater than or equal to the indication threshold, the indication acquisition operation rule is executed on the knowledge acquisition scenario to obtain sub-knowledge; Otherwise, stop accessing the knowledge acquisition scenario; Integrate sub-knowledge to obtain the second decision-making knowledge.

6. A control method for a short-term combined heat and power photovoltaic and thermal integrated energy system according to any one of claims 1 to 5, characterized in that: include: Predict the heating and power generation capacity of photovoltaic thermal modules and the heat and electricity demand of the thermal power supply area in the future target short term; Decisions on combined heat and power storage solutions are made based on heating and power generation capacity and heat and power demand; Based on the cogeneration scheme, the heating and power generation energy of the photovoltaic thermal components is combined and stored in the photovoltaic energy storage components within a target short period of time.

7. The control method according to claim 6, characterized in that: The decision on the combined heat and power storage solution based on the heating and power generation capacity and the heat and power demand includes: Extract features of heating and power generation capacity and heat and electricity demand to obtain a descriptive feature set; Try to determine the first decision knowledge corresponding to the description feature set from the decision knowledge base; When the attempt is made to determine the time, a combined heat and power storage scheme is decided based on the first decision knowledge; Otherwise, try to determine the idle expert group corresponding to the description feature set from the idle expert group library; When the attempt is determined, assist the idle expert group to decide on the combined heat and power storage scheme; Otherwise, the second decision knowledge is obtained online based on the descriptive feature set; Based on the second decision knowledge, a combined heat and power storage scheme is decided.

8. The control method according to claim 7, characterized in that: The auxiliary idle expert group decides on the combined heat and power storage scheme, including: Generate a visual model based on heating and power generation capacity and heat and electricity demand; Based on the discussion records generated by each idle expert in the idle expert group within a recent first preset time period, determining the recommended viewing perspective of each idle expert in the visualization model; Guide each idle expert to view the visualization model from their recommended viewing perspective; When at least one idle expert inputs a plan input request, the combined heat and power storage plans input by the idle experts are received.

9. The control method according to claim 8, characterized in that: The step of determining the recommended viewing perspectives of the idle experts in the idle expert group based on the discussion records generated within the most recent first preset time period in the idle expert group includes: Performing timeline representation processing on the discussion record to obtain a record timeline; Vectorizing the keywords in each first record item on the record time axis, the time sequence of each first record item, and the time distance between two adjacent first record items to obtain a situation representation vector; Determine the first perspective determination knowledge corresponding to the situation representation vector from the perspective determination knowledge base; Based on the knowledge determined from the first perspective, the recommended viewing perspectives of each idle expert are determined in the visualization model; and / or, When at least a preset number of threshold second record items generated by the same idle expert on the record time axis meet the standard record item conditions, semantic analysis is performed on each second record item to obtain a discussion semantic set; Determine the second perspective-determined knowledge corresponding to the discussion semantic set from the perspective-determined knowledge base; Based on the knowledge determined from the second perspective, the recommended viewing perspectives of each idle expert are determined in the visualization model; Among them, standard record item conditions include: The second record item contains at least one standard keyword; and / or, There is no third record item generated by other idle experts within a preset time range before or after the second record item on the record time axis; and / or, The time distance between the generation time of the last generated second record item and the end time of the most recent first preset time period is greater than or equal to the distance threshold.

10. The control method according to claim 8, characterized in that: The method of acquiring the second decision knowledge online based on the description feature set includes: Determine the conditional generation knowledge corresponding to the description feature set from the conditional generation knowledge base; Based on the conditional knowledge generation, multiple knowledge acquisition conditions are generated according to the heating and power generation capacity and the demand for heat and electricity, and the corresponding condition weights are determined; Generate an acquisition indication graph based on each knowledge acquisition condition, the condition weight corresponding to each knowledge acquisition condition, and the condition association relationship between each knowledge acquisition condition; Access knowledge acquisition scenarios; Determine the indication acquisition operation rule and the indication value based on the acquisition indication map and the information interaction information between the knowledge acquisition scenario at every preset second time period; When the indication value is greater than or equal to the indication threshold, the indication acquisition operation rule is executed on the knowledge acquisition scenario to obtain sub-knowledge; Otherwise, stop accessing the knowledge acquisition scenario; Integrate sub-knowledge to obtain the second decision-making knowledge.

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