Power equipment control method and device, storage medium and electronic equipment
By determining the status transfer information and status correlation information in the power equipment control and performing intelligent control, the problem of poor coordinated control of power equipment in the prior art is solved, and higher system stability and reliability are achieved.
Patent Information
- Application Number
- CN202510044006.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-01-10
- Publication Date
- 2025-05-27
AI Technical Summary
The existing power equipment control methods are difficult to effectively consider the complex correlation between power equipment, resulting in poor coordinated control effects, frequent failures, and insufficient system stability and reliability.
By determining the status transfer information of the target power equipment and the status correlation information with the associated power equipment, intelligent control is carried out based on this information to ensure that the control strategy takes into account the status of the target device itself and other equipment status and avoids adverse effects.
It realizes more effective coordinated control of the power system, reduces the occurrence of faults, and improves the stability and reliability of the system.
Smart Images
Figure CN120044837A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the technical field of power equipment control, and in particular, to a power equipment control method, device, storage medium, and electronic device. Background Art
[0002] In the field of power equipment control, traditional methods mainly rely on the physical characteristics of equipment and the experience of engineers to formulate static control strategies. With the development of power equipment, there are more and more power equipment in the power system, and the association and dependency relationships between different equipment are becoming more and more complex. Therefore, it is becoming more and more important to consider the complex relationships of power equipment to achieve coordinated control of the power system. Summary of the Invention
[0003] The purpose of the present disclosure is to provide a power equipment control method, device, storage medium, and electronic device.
[0004] To achieve the above purpose, according to the first aspect of the present disclosure, a power equipment control method is provided, and the method includes: Determine the state transition information of the target power equipment, where the state transition information is used to represent the state transition probability of the target power equipment changing from one equipment state to another; Determine the state association information between the target power equipment and the associated power equipment, where the state association information is used to represent the equipment states of the target power equipment and the associated power equipment that have an association relationship; Control the target power equipment according to the state transition information and the state association information.
[0005] Optionally, the determining the state transition information of the target power equipment includes: Obtain the equipment operation information and operation environment information of the target power equipment during the first operation process; Determine the equipment state of the target power equipment at each operation period during the first operation process according to the equipment operation information and the operation environment information; Determine the state transition information according to the change situation of the equipment states of the target power equipment at different operation periods during the first operation process.
[0006] Optionally, the determining the equipment state of the target power equipment at each operation period during the first operation process according to the equipment operation information and the operation environment information includes: For each operation period during the first operation process, according to the first information corresponding to the operation period in the device operation information and the operation environment information, determine the preset performance state corresponding to the target power device among multiple preset performance states as the device state of the target power device during the operation period.
[0007] Optionally, the determining the preset performance state corresponding to the target power device among multiple preset performance states according to the first information corresponding to the operation period in the device operation information and the operation environment information includes: For each of the preset performance states, according to the second information associated with the preset performance state in the first information, determine the performance prediction value of the target power device corresponding to the preset performance state, and when the performance prediction value is within the threshold range corresponding to the preset performance state, determine the preset performance state as the preset performance state corresponding to the target power device.
[0008] Optionally, the state transition information includes multiple state transition probabilities; The state transition probability of changing from the first state to the second state is determined by the following method: Determine the number of times the target power device changes from the first state to the second state during the first operation process as the first quantity; Determine the total number of operation periods included in the first operation process as the second quantity; Determine the ratio of the first quantity to the second quantity as the state transition probability of changing from the first state to the second state; Wherein, the first state and the second state are respectively taken from the device states of the target power device during the first operation process.
[0009] Optionally, determining the state association information between the target power device and the associated power device includes: Determine the device states of the target power device in each operation period during the second operation process; Determine the device states of the associated power device in each operation period during the second operation process; According to the device states of the target power device and the associated power device that exist simultaneously in the same operation period, determine the state association information.
[0010] Optionally, the determining the state association information according to the device states of the target power device and the associated power device that exist simultaneously in the same operation period includes: According to the device states of the target power device and the associated power device that exist simultaneously in the same operation period, determine the frequent item set with a support degree higher than the first threshold; For each of the frequent item sets, generate association rules between the device states of different power devices according to the device state of the target power device and the device state of the associated power device included in the frequent item set; In the association rules, determine target association rules with a support degree higher than a second threshold and a confidence degree higher than a third threshold, and use the target association rules as the state association information.
[0011] Optionally, the controlling the target power device according to the state transition information and the state association information includes: Determine the device state of the target power device at a target moment as the target device state; According to the target state transition probability corresponding to the target device state in the state transition information, determine the device state that the target power device changes to after the target moment as the predicted device state; According to the state association information, determine the device state of the associated power device having an association relationship with the predicted device state as the associated device state; If the predicted device state or the associated device state is an abnormal device state, determine a target control strategy capable of preventing the target power device from changing from the target device state to the predicted device state; Control the target power device according to the target control strategy at the target moment.
[0012] Optionally, the determining a target control strategy capable of preventing the target power device from changing from the target device state to the predicted device state includes: Generate an initial control strategy; Determine the predicted control effect corresponding to the initial control strategy; If the predicted control effect can prevent the target power device from changing from the target device state to the predicted device state, determine the initial control strategy as the target control strategy; If the predicted control effect cannot prevent the target power device from changing from the target device state to the predicted device state, return to the step of generating the initial control strategy to generate a new initial control strategy.
[0013] Optionally, the method further includes: Determine the control error corresponding to the target power device; According to the control error, determine target control parameters for a control system, where the control system is a system for controlling the target power device; Control the control system by using the target control parameters.
[0014] According to a second aspect of the present disclosure, there is provided a power equipment control device, the device comprising: A first determination module, configured to determine state transition information of a target power equipment, the state transition information being used to characterize the state transition probability of the target power equipment changing from one equipment state to another equipment state; A second determination module, configured to determine state association information between the target power equipment and associated power equipment, the state association information being used to characterize the equipment state of the target power equipment and the equipment state of the associated power equipment having an association relationship; A first control module, configured to control the target power equipment according to the state transition information and the state association information.
[0015] According to a third aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method described in the first aspect of the present disclosure are implemented.
[0016] According to a fourth aspect of the present disclosure, there is provided an electronic device, comprising: A memory, on which a computer program is stored; A processor, configured to execute the computer program in the memory to implement the steps of the method described in the first aspect of the present disclosure.
[0017] Through the above technical solutions, the state transition information of the target power equipment and the state association information between the target power equipment and the associated power equipment are determined, and the target power equipment is controlled according to the state transition information and the state association information, wherein the state transition Sydney is used to characterize the state transition probability of the target power equipment changing from one equipment state to another equipment state, and the state association information is used to characterize the equipment state of the target power equipment and the equipment state of the associated power equipment having an association relationship. Thus, based on the state transition information, the equipment state change trend of the target power equipment itself can be known, and based on the state association information, the correlation of the equipment states of different power equipment can be known. In this way, the control of the target power equipment according to the state transition information and the state association information fully considers both the equipment state of the target power equipment itself and the equipment states of other power equipment, effectively avoiding adverse effects on other power equipment caused by the control of the target power equipment, improving the overall cooperative control effect of the power system, reducing the occurrence of faults, and enhancing the stability and reliability of the power system.
[0018] Other features and advantages of the present disclosure will be described in detail in the subsequent specific implementation part. BRIEF DESCRIPTION OF THE DRAWINGS
[0019] The accompanying drawings are used to provide a further understanding of the present disclosure, and constitute a part of the specification. Together with the following detailed description, they are used to explain the present disclosure, but do not constitute a limitation to the present disclosure. In the drawings: Figure 1 is a flowchart of a power equipment control method provided according to an embodiment of the present disclosure; Figure 2 is a block diagram of a power equipment control device provided according to an embodiment of the present disclosure; Figure 3 is a block diagram of an electronic device shown according to an exemplary embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS
[0020] The following provides a detailed description of the specific embodiments of the present disclosure with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only used to illustrate and explain the present disclosure, and are not used to limit the present disclosure.
[0021] It should be noted that all actions of obtaining signals, information or data in the present disclosure are carried out on the premise of complying with the corresponding data protection regulations and policies of the country where it is located and obtaining authorization from the owner of the corresponding device.
[0022] As described in the background art, with the increase in the number of power equipment and the increase in the complexity of relationships in the power system, it is very important to achieve coordinated control of the power system. In recent years, the development of the Internet of Things and big data technologies has provided new possibilities for data-driven control methods. By collecting and analyzing the operation data of power equipment in real time, not only can we more accurately understand and predict the operation status and performance of the equipment, but also we can formulate more accurate and efficient control strategies by applying intelligent algorithms (such as machine learning and optimization algorithms). Although the automation control technology of power equipment has been widely applied, how to combine advanced data analysis and intelligent algorithm technologies with the existing automation control system to achieve intelligent control of power equipment is still a technical problem that needs to be solved.
[0023] To solve the above technical problems, the present disclosure provides a power equipment control method, device, storage medium and electronic device.
[0024] Figure 1 is a flowchart of a power equipment control method provided according to an embodiment of the present disclosure. The method provided by the present disclosure can be applied to a control system, and the control system can control power equipment. Exemplarily, the method provided by the present disclosure can be applied to an electronic device on which the above control system runs. As Figure 1 shown, the power equipment control method provided by the present disclosure may include steps 11 to 13.
[0025] In step 11, determine the state transition information of the target power device.
[0026] Among them, the state transition information is used to characterize the state transition probability of the target power device changing from one device state to another. By way of example, the state transition information may be a state transition matrix, and each element in the matrix is a state transition probability.
[0027] In a possible implementation manner, step 11 may include the following steps: Obtain the device operation information and operation environment information of the target power device during the first operation process; According to the device operation information and operation environment information, determine the device state of each operation period of the target power device during the first operation process; According to the change situation of the device states of the target power device in different operation periods during the first operation process, determine the state transition information.
[0028] The following explains the device operation information and operation environment information.
[0029] The device operation information is the information generated by the power device during operation. Optionally, the device operation information may include, but is not limited to, at least one of the following: voltage data, current data, power data, frequency data, power quality, device state, device temperature, device load.
[0030] By way of example, the voltage data may include, but is not limited to, the input / output voltage, phase voltage, etc. of the device.
[0031] By way of example, the current data may include, but is not limited to, the input / output current, phase current, etc. of the device.
[0032] By way of example, the power data may include, but is not limited to, active power, reactive power, apparent power, etc.
[0033] By way of example, the frequency data may include, but is not limited to, the operating frequency of the power grid.
[0034] By way of example, the power quality may include, but is not limited to, power factor, harmonic content, etc.
[0035] By way of example, the device state may include, but is not limited to, the running / stopping state of the device, fault information, etc.
[0036] By way of example, the device temperature may include, but is not limited to, the operating temperature of the device or the state of the cooling system.
[0037] By way of example, the device load may include, but is not limited to, the load rate or load current of the device.
[0038] The operating environment information refers to the operating environment in which the power equipment is located during operation. Optionally, the operating environment information may include, but is not limited to, at least one of the following: ambient temperature, ambient humidity, air pressure, dust and pollutants, noise, vibration, gas components.
[0039] Exemplarily, the ambient temperature may include, but is not limited to, the temperature of the environment where the power equipment is located.
[0040] Exemplarily, the ambient humidity may include, but is not limited to, the humidity of the environment where the power equipment is located.
[0041] Exemplarily, the air pressure may include, but is not limited to, the air pressure of the environment where the power equipment is located.
[0042] Exemplarily, the dust and pollutants may include, but is not limited to, the concentration of dust and pollutants in the air.
[0043] Exemplarily, the noise may include, but is not limited to, the ambient noise level.
[0044] Exemplarily, the vibration may include, but is not limited to, the vibration level of the equipment or the vibration of the surrounding environment.
[0045] Exemplarily, the gas components may include, but is not limited to, oxygen, carbon dioxide, etc.
[0046] By setting corresponding sensors or detection devices, the above-mentioned equipment operation information and operating environment information of the power equipment during operation can be collected in real time.
[0047] After collecting the equipment operation information and operating environment information, before using them for subsequent data processing (such as determining the equipment status, etc.), a certain degree of preprocessing can also be performed to facilitate the simplicity of subsequent data processing. Optionally, the preprocessing may include, but is not limited to, data cleaning, data conversion, etc. Among them, data cleaning can be, for example, the processing of missing values, outliers, and duplicate values, and data conversion can be, for example, the processing of data such as standardization, normalization, and discretization.
[0048] Based on this, the equipment operation information and operating environment information of the target power equipment during the first operation process can be collected through sensors, detection devices, etc. Among them, the first operation process can be the historical operation process of the target power equipment.
[0049] After obtaining the equipment operation information and operating environment information of the target power equipment during the first operation process, the equipment status of each operation period of the target power equipment during the first operation process can be determined according to the obtained equipment operation information and operating environment information.
[0050] Optionally, the equipment status of each operation period of the target power equipment during the first operation process can be determined in the following ways: For each operation period in the first operation process, according to the first information corresponding to the operation period in the device operation information and the operation environment information, determine the preset performance state corresponding to the target power device among multiple preset performance states, and use it as the device state of the target power device in the operation period.
[0051] Among them, the preset performance state is the device state concerned in the process of controlling the power device. It can be determined based on the main factors considered when controlling the power device and can be predefined and set according to actual needs. For example, if in the process of controlling the power device, it is necessary to consider the operation efficiency, load level, fault condition, etc. of the device for control, then the corresponding preset performance states that can be set include: high-efficiency operation, low-efficiency operation, maintenance mode, and fault state.
[0052] The first operation process may include multiple operation periods. The device operation information and operation environment information collected at the collection moment within an operation period are the device operation information and operation environment of this operation period, that is, the first information. Therefore, for each operation period, the first information belonging to this operation period can be extracted from the device operation information and operation environment information in the first operation process.
[0053] For an operation period, determining the preset performance state corresponding to the target power device among multiple preset performance states is to determine which one or more of the preset performance states (that is, the device states that are expected to be concerned) the target power device appears in during this operation period. The following mainly describes the determination method of the device state of the target power device in an operation period, and the determination method for each operation period is the same by analogy.
[0054] Optionally, the preset performance state corresponding to the target power device can be determined by the following method: For each preset performance state, according to the second information associated with this preset performance state in the first information, determine the performance prediction value of the target power device corresponding to this preset performance state, and when the performance prediction value is within the threshold range corresponding to this preset performance state, determine this preset performance state as the preset performance state corresponding to the target power device.
[0055] For a preset performance state, there are usually reference factors used to assist in judging whether the power device is in this preset performance state. These reference factors can be regarded as being associated with the preset performance state. Therefore, for whether the target power device is in a preset performance state within an operation period, according to the first information corresponding to this operation period, screen the second information associated with this preset performance state from the first information, and use this second information to determine whether this preset performance state is the preset performance state corresponding to the target power device.
[0056] Therefore, according to the second information, the performance prediction value corresponding to the target power device for the preset performance state can be determined. Exemplarily, the performance prediction value Y of the preset performance state A can be determined according to the following formula A :
[0057] where X 1 , X 2 , …, X m are the second information associated with the preset performance state A, β 0 is the intercept term, β 1 , β 2 , …, β m are the regression coefficients, respectively representing the influence degrees of X 1 , X 2 , …, X m on the preset performance state A, is the error term.
[0058] Meanwhile, the preset performance state also corresponds to a threshold range, which represents the range where the performance prediction value should be when the power device is in the preset performance state. Therefore, after determining the performance prediction value corresponding to the target power device for the preset performance state, the performance prediction value can be compared with the threshold range corresponding to the preset performance state: if the performance prediction value is within the threshold range corresponding to the preset performance state, it can be determined that the preset performance state is the preset performance state corresponding to the target power device; if the performance prediction value is not within the threshold range corresponding to the preset performance state, it can also be determined that the target power device is not currently in the preset performance state.
[0059] Based on the above method, for each preset performance state, it can be determined whether the target power device is in the preset performance state. In this way, it can be determined which preset performance state the target power device is in during an operation period, and thus the device state of the target power device during an operation period is determined. In some cases, during the same operation period, the target power may also correspond to more than one device state, and the present disclosure does not limit this.
[0060] In this way, the state of the target power device in each operation period during the first operation process can be determined. Furthermore, according to the change of the device state in different operation periods, the state transition information can be determined.
[0061] The state transition information may include multiple state transition probabilities. In one possible implementation manner, the state transition probability from the first state to the second state can be determined through the following method: Determine the number of times the target power device changes from the first state to the second state during the first operation process as the first quantity; Determine the total number of operating periods included in the first operating process as the second quantity; Determine the ratio of the first quantity to the second quantity as the state transition probability of changing from the first state to the second state.
[0062] Wherein, the first state and the second state are respectively taken from the device states of the target power device in the first operating process.
[0063] For example, within a total of 100 operating periods in the first operating process, there are 20 operating periods during which the target power device changes from state B1 to state B2. State B1 can be taken as the first state, and state B2 can be taken as the second state. Then, the first quantity is determined to be 20, and the second quantity is 100. Correspondingly, the state transition probability of changing from state B1 to state B2 is 20 / 100, that is, 20%. It should be noted that the state transition probability of changing from state B1 to state B2 is not the same as the state transition probability of changing from state B2 to state B1, and the two need to be determined separately according to the above method.
[0064] According to the above method, the state transition probability between any two device states of the target power device can be determined. Based on the determined state transition probability, a state transition matrix can be generated. By way of example, the state transition matrix can be P:
[0065] Wherein, P ij is the state transition probability of the target power device changing from device state i to device state j , and n is the total number of types of device states that the target power device has appeared in the first operating process. For example, if the target power device has appeared in 4 types of device states, namely high-efficiency operation, low-efficiency operation, maintenance mode, and fault state, during the first operating process, then n is 4.
[0066] In another possible implementation manner, the state transition information of the target power device can be determined by obtaining the state transition information of other power devices similar to the operating mode and operating environment of the target power device. For example, the state transition information of other power devices similar to the operating mode and operating environment of the target power device can be used as the state transition information of the target power device. For another example, it can be generated by referring to the state transition information of other power devices similar to the operating mode and operating environment of the target power device and making certain modifications.
[0067] In step 12, determine the state association information between the target power device and the associated power device.
[0068] Among them, the status association information is used to characterize the device status of the target power device with an association relationship and the device status of the associated power device. Optionally, there may be one or more associated power devices.
[0069] In a possible implementation manner, it is possible to determine the device status that the target power device has had during a certain operation process, and at the same time determine the device status that the associated power device has had during this operation process, and take the operation period as a unit to determine the device status combination corresponding to each operation period. Among them, the device status combination corresponding to an operation period is composed of the device status of the target power device during this operation period and the device status of the associated power device during this operation period. Based on this, count the frequencies of different device status combinations that appear during this operation process, and determine the top K with the highest frequencies. Then, based on the device status combinations of the top K, generate K groups of the device status of the target power device with an association relationship and the device status of the associated power device, and thus determine the status association information.
[0070] Among them, the determination methods of the device status of the target power device and the device status of the associated power device can both refer to the method provided in the previous text for determining the device status of the target power device in each operation period during the first operation process. The principles are the same and will not be elaborated here.
[0071] In another possible implementation manner, step 12 may include the following steps: Determine the device status of the target power device in each operation period during the second operation process; Determine the device status of the associated power device in each operation period during the second operation process; Determine the status association information according to the device status of the target power device and the device status of the associated power device that exist simultaneously in the same operation period.
[0072] Among them, the second operation process may be a historical operation process. The methods for determining the device status of the target power device in each operation period during the second operation process and determining the device status of the associated power device in each operation period during the second operation process can both refer to the method provided in the previous text for determining the device status of the target power device in each operation period during the first operation process. The principles are the same and will not be elaborated here.
[0073] After determining the above device status, the status association information can be determined according to the device status of the target power device and the device status of the associated power device that exist simultaneously in the same operation period.
[0074] Optionally, the status association information can be determined by the following method: Determine the frequent item sets with support higher than the first threshold according to the device status of the target power equipment and the device status of the associated power equipment that coexist during the same operation period; For each frequent item set, generate the association rules between the device statuses of different power equipment according to the device status of the target power equipment and the device status of the associated power equipment included in the frequent item set; In the association rules, determine the target association rules with support higher than the second threshold and confidence higher than the third threshold, and use the target association rules as the status association information.
[0075] For a given global item set, the support of item C in this global item set is the percentage of the transactions containing item C in the whole set of item sets. Exemplarily, the Apriori algorithm can be used to determine the frequent item sets. The Apriori algorithm is a classical algorithm for discovering frequent item sets in data mining and can be used to learn association rules. It is based on the fact that if an item set is frequent, then all its non-empty subsets must also be frequent. This algorithm repeatedly finds all frequent item sets through the connection step and the pruning step. Among them, the connection step is used to generate candidate item sets of length (k + 1), and the pruning step is used to remove the infrequent candidate item sets.
[0076] After determining all the frequent item sets based on the device status, for each frequent item set, corresponding association rules can be generated based on the items included in the frequent item set, that is, the device status of the target power equipment and the device status of the associated power equipment, and the support and confidence of the association rules are calculated respectively.
[0077] Exemplarily, the confidence of the association rule A → B can be determined in the following way:
[0078]
[0079] where A and B are the device status of the target power equipment and the device status of the associated power equipment respectively, is the frequency of the occurrence of the association rule A → B, is the confidence of the association rule A → B.
[0080] Based on this, the target association rules in the association rules with support higher than the second threshold and confidence higher than the third threshold can be screened out, and the status association information is generated based on the target association rules.
[0081] If there is a target association rule associating the device status 2 of the target power equipment 1 and the device status 4 of the associated power equipment 3, it can be considered that if the target power equipment 1 is in the device status 1, the associated power equipment 3 is very likely to be in or become the device status 4.
[0082] Among them, the first threshold, the second threshold, and the third threshold can be set according to actual requirements.
[0083] In step 13, the target power device is controlled according to the state transition information and the state association information.
[0084] In a possible implementation manner, step 13 may include the following steps: Determine the device state of the target power device at the target moment as the target device state; According to the target state transition probability corresponding to the target device state in the state transition information, determine the device state that the target power device changes to after the target moment as the predicted device state; According to the state association information, determine the device state of the associated power device that has an association relationship with the predicted device state as the associated device state; If the predicted device state or the associated device state is an abnormal device state, determine the target control strategy that can prevent the target power device from changing from the target device state to the predicted device state; Control the target power device according to the target control strategy at the target moment.
[0085] If it is necessary to control the target power device at the target moment, the device state of the target power device at the target moment can be first determined as the target device state (the determination method has been given above and will not be elaborated here).
[0086] According to the target device state and in combination with the state transition information, all the state transition probabilities starting from the target device state as the state change starting point can be determined from the state transition information, and then the largest one can be determined from these state transition probabilities. Furthermore, the device state corresponding to the state change end point of the maximum state transition probability can be used as the predicted device state. The predicted device state represents the device state that the target device state is most likely to enter in the future.
[0087] According to the state association information, the device state of the associated power device that has an association relationship with the predicted device state can be determined as the associated device state. The associated device state represents the device state that the associated power device is most likely to be in in the future due to the influence of the device state change of the target power device.
[0088] Based on this, if the predicted device state or the associated device state is an abnormal device state, the target power device should be controlled to prevent the power device from entering the predicted device state, thereby avoiding the abnormal predicted device state or the abnormal associated device state.
[0089] Optionally, the target control strategy that can avoid the target power device from changing from the target device state to the predicted device state can be determined in the following manner: Generate an initial control strategy; Determine the predicted control effect corresponding to the initial control strategy; If the predicted control effect can avoid the target power device from changing from the target device state to the predicted device state, determine the initial control strategy as the target control strategy; If the predicted control effect cannot avoid the target power device from changing from the target device state to the predicted device state, return to the step of generating the initial control strategy to generate a new initial control strategy.
[0090] Optionally, the initial control strategy can be randomly generated, or a certain control strategy generation rule can be preset and generated according to this generation rule.
[0091] After generating the initial control strategy, based on the initial control strategy, the possible control effect generated by this initial control strategy can be predicted as the predicted control effect.
[0092] Exemplarily, the predicted control effect can be determined according to the following formula:
[0093] Where J is the performance index, which can be set according to actual requirements, Q and R are both weight matrices, x(t) is the state variable at the target time t (i.e., the device operation information and operation environment information described above), u(t) is the control input corresponding to the initial control strategy, and T is the considered time period.
[0094] Through the above formula, after substituting the control output u(t) corresponding to the initial control strategy into the formula, the result of the performance index J can be determined to determine the predicted control effect.
[0095] Furthermore, if the predicted control effect can avoid the target power device from changing from the target device state to the predicted device state, the initial control strategy can be determined as the final target control strategy.
[0096] If the predicted control effect cannot avoid the target power device from changing from the target device state to the predicted device state, return to the step of generating the initial control strategy to generate a new initial control strategy, and then conduct effect evaluation based on the new initial control strategy until the predicted control effect corresponding to the initial control strategy can avoid the target power device from changing from the target device state to the predicted device state.
[0097] Based on the above method, after determining the target control strategy, the target power equipment can be controlled according to the target control strategy at the target time. Thus, precise control of the target power equipment can be achieved, and problems caused during the control process of the target power equipment can be effectively avoided, realizing the optimized operation of the power system.
[0098] Optionally, based on the above solution provided by the present disclosure, the method provided by the present disclosure may further include the following steps: Determine the control error corresponding to the target power equipment; Determine the target control parameter for the control system according to the control error; Control the control system using the target control parameter.
[0099] Wherein, the control system is a system for controlling the target power equipment.
[0100] Exemplarily, the target control parameter can be determined according to the following formula:
[0101] Wherein, is the target control parameter at time t, is the adaptive gain, is the control error at time t (i.e., the error between the actual control and the desired control), is the state variable at the target time t (i.e., the equipment operation information and operation environment information described above).
[0102] Thus, by controlling the control parameters of the control system, the control parameters of the control system can be dynamically adjusted to timely adapt to the changes and uncertainties of the equipment.
[0103] Through the above technical solutions, the state transition information of the target power equipment and the state association information between the target power equipment and the associated power equipment are determined, and the target power equipment is controlled according to the state transition information and the state association information. Among them, the state transition probability is used to characterize the probability of the target power equipment changing from one equipment state to another equipment state, and the state association information is used to characterize the equipment states of the target power equipment and the associated power equipment with an association relationship. Thus, based on the state transition information, the equipment state change trend of the target power equipment itself can be obtained, and based on the state association information, the correlation of the equipment states of different power equipment can be obtained. In this way, the control of the target power equipment according to the state transition information and the state association information fully considers both the equipment state of the target power equipment itself and the equipment states of other power equipment, effectively avoiding adverse effects on other power equipment caused by the control of the target power equipment, improving the overall cooperative control effect of the power system, reducing the occurrence of faults, and enhancing the stability and reliability of the power system.
[0104] Figure 2 is a block diagram of a power equipment control device provided according to an embodiment of the present disclosure. As Figure 2 shown, the device 20 may include: A first determination module 21, configured to determine the state transition information of the target power equipment, where the state transition information is used to characterize the state transition probability of the target power equipment changing from one equipment state to another equipment state; A second determination module 22, configured to determine the state association information between the target power equipment and the associated power equipment, where the state association information is used to characterize the equipment states of the target power equipment and the associated power equipment with an association relationship; A first control module 23, configured to control the target power equipment according to the state transition information and the state association information.
[0105] Optionally, the first determination module 21 includes: An acquisition sub-module, configured to acquire the equipment operation information and the operation environment information of the target power equipment during a first operation process; A first determination sub-module, configured to determine the equipment state of each operation period of the target power equipment during the first operation process according to the equipment operation information and the operation environment information; A second determination sub-module, configured to determine the state transition information according to the change situation of the equipment states of the target power equipment in different operation periods during the first operation process.
[0106] Optionally, the first determination sub-module includes: A third determination sub-module, configured to, for each operation period in the first operation process, determine, according to the first information corresponding to the operation period in the device operation information and the operation environment information, a preset performance state corresponding to the target power device among a plurality of preset performance states as the device state of the target power device in the operation period.
[0107] Optionally, the third determination sub-module is configured to: for each of the preset performance states, determine a performance prediction value corresponding to the target power device for the preset performance state according to the second information associated with the preset performance state in the first information, and determine the preset performance state as the preset performance state corresponding to the target power device when the performance prediction value is within the threshold range corresponding to the preset performance state.
[0108] Optionally, the state transition information includes a plurality of state transition probabilities; The state transition probability from the first state to the second state is determined by the following method: Determine the number of times the target power device changes from the first state to the second state in the first operation process as the first quantity; Determine the total number of operation periods included in the first operation process as the second quantity; Determine the ratio of the first quantity to the second quantity as the state transition probability from the first state to the second state; Wherein, the first state and the second state are respectively taken from the device states of the target power device in the first operation process.
[0109] Optionally, the second determination module 22 includes: A fourth determination sub-module, configured to determine the device states of the target power device in each operation period in the second operation process; A fifth determination sub-module, configured to determine the device states of the associated power device in each operation period in the second operation process; A sixth determination sub-module, configured to determine the state association information according to the device states of the target power device and the associated power device that exist simultaneously in the same operation period.
[0110] Optionally, the sixth determination sub-module includes: A seventh determination sub-module, configured to determine a frequent item set with a support degree higher than a first threshold according to the device states of the target power device and the associated power device that exist simultaneously in the same operation period; A first generation sub-module, configured to generate an association rule between device states of different power devices for each of the frequent item sets according to the device state of the target power device and the device state of the associated power device included in the frequent item set; An eighth determination sub-module, configured to determine, in the association rule, a target association rule whose support degree is higher than a second threshold and whose confidence degree is higher than a third threshold, and use the target association rule as the state association information.
[0111] Optionally, the first control module 23 includes: A ninth determination sub-module, configured to determine the device state of the target power device at a target moment as the target device state; A tenth determination sub-module, configured to determine, according to a target state transition probability corresponding to the target device state in the state transition information, the device state that the target power device changes to after the target moment as the predicted device state; An eleventh determination sub-module, configured to determine, according to the state association information, the device state of the associated power device having an association relationship with the predicted device state as the associated device state; A twelfth determination sub-module, configured to determine a target control strategy that can prevent the target power device from changing from the target device state to the predicted device state if the predicted device state or the associated device state is an abnormal device state; A control sub-module, configured to control the target power device according to the target control strategy at the target moment.
[0112] Optionally, the twelfth determination sub-module includes: A second generation sub-module, configured to generate an initial control strategy; A thirteenth determination sub-module, configured to determine the predicted control effect corresponding to the initial control strategy; A fourteenth determination sub-module, configured to determine the initial control strategy as the target control strategy if the predicted control effect can prevent the target power device from changing from the target device state to the predicted device state; The twelfth determination sub-module is configured to trigger the second generation sub-module to generate an initial control strategy to generate a new initial control strategy if the predicted control effect cannot prevent the target power device from changing from the target device state to the predicted device state.
[0113] Optionally, the apparatus 20 further includes: A third determination module, configured to determine the control error corresponding to the target power device; A fourth determination module, configured to determine a target control parameter for a control system according to the control error, where the control system is a system for controlling the target power device; A second control module, configured to control the control system by using the target control parameter.
[0114] Regarding the device in the above embodiments, the specific manners in which each module performs operations have been described in detail in the embodiments related to the method, and will not be elaborated herein.
[0115] Figure 3 is a block diagram of an electronic device 700 shown according to an exemplary embodiment. As Figure 3 shown, the electronic device 700 may include: a processor 701, a memory 702. The electronic device 700 may further include one or more of a multimedia component 703, an input / output (I / O) interface 704, and a communication component 705.
[0116] Among them, the processor 701 is used to control the overall operation of the electronic device 700 to complete all or part of the steps in the above-mentioned power device control method. The memory 702 is used to store various types of data to support the operation of the electronic device 700. These data may include, for example, instructions for any application or method operating on the electronic device 700, as well as application-related data, such as contact data, sent and received messages, pictures, audio, video, and so on. The memory 702 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic memory, flash memory, a magnetic disk, or an optical disc. The multimedia component 703 may include a screen and an audio component. Among them, the screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone, and the microphone is used to receive external audio signals. The received audio signals may be further stored in the memory 702 or sent through the communication component 705. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 704 provides an interface between the processor 701 and other interface modules, and the above-mentioned other interface modules may be a keyboard, a mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 705 is used for wired or wireless communication between the electronic device 700 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IOT, eMTC, or other 5G, etc., or a combination of one or more of them is not limited herein. Therefore, correspondingly, the communication component 705 may include: a Wi-Fi module, a Bluetooth module, an NFC module, and so on.
[0117] In an exemplary embodiment, the electronic device 700 can be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components, and is used to execute the above-mentioned power device control method.
[0118] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided. When the program instructions are executed by a processor, the steps of the above-mentioned power device control method are implemented. For example, the computer-readable storage medium can be the above-mentioned memory 702 including program instructions, and the above-mentioned program instructions can be executed by the processor 701 of the electronic device 700 to complete the above-mentioned power device control method.
[0119] In another exemplary embodiment, a computer program product is also provided. The computer program product includes a computer program that can be executed by a programmable device, and the computer program has a code portion for executing the above-mentioned power device control method when executed by the programmable device.
[0120] The preferred embodiments of the present disclosure have been described in detail above in conjunction with the accompanying drawings. However, the present disclosure is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present disclosure, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.
[0121] In addition, it should be noted that, in the above specific embodiments, the various specific technical features described can be combined in any suitable manner without conflict. To avoid unnecessary repetition, the present disclosure will not separately describe various possible combination methods.
[0122] In addition, any combination can be made between various different embodiments of the present disclosure as long as it does not violate the idea of the present disclosure, and it should also be regarded as the content disclosed by the present disclosure.
Claims
1. A method for controlling an electric power device, characterized in that: The method comprises: Determine state transition information of a target power device, wherein the state transition information is used to characterize a state transition probability of the target power device changing from one device state to another device state; Determine state association information between the target power device and the associated power device, wherein the state association information is used to characterize the device state of the target power device and the device state of the associated power device that have an associated relationship; The target electric device is controlled according to the state transfer information and the state association information.
2. The method according to claim 1, characterized in that The determining of the state transfer information of the target power equipment includes: Acquire equipment operation information and operation environment information of the target electric equipment during a first operation process; Determine, according to the device operation information and the operation environment information, the device status of each operation period of the target power device in the first operation process; The state transfer information is determined according to changes in the device state of the target power device in different operating time periods during the first operating process.
3. The method according to claim 2, characterized in that The determining, according to the device operation information and the operation environment information, the device status of each operation period of the target power device in the first operation process includes: For each operating period in the first operating process, based on the equipment operating information and the first information corresponding to the operating period in the operating environment information, the preset performance state corresponding to the target power equipment is determined from multiple preset performance states as the equipment state of the target power equipment in the operating period.
4. The method according to claim 3, characterized in that The determining, according to the device operation information and the first information corresponding to the operation period in the operation environment information, a preset performance state corresponding to the target power device from a plurality of preset performance states includes: For each of the preset performance states, a performance prediction value of the target power equipment corresponding to the preset performance state is determined based on second information in the first information that is associated with the preset performance state, and when the performance prediction value is within a threshold range corresponding to the preset performance state, the preset performance state is determined to be the preset performance state corresponding to the target power equipment.
5. The method according to claim 2, characterized in that: The state transition information includes a plurality of state transition probabilities; The state transition probability from the first state to the second state is determined by: determining, as a first quantity, a number of times that the target power device changes from a first state to a second state during the first operation; Determine a total number of running time periods included in the first running process as a second number; determining a ratio of the first quantity to the second quantity as a state transition probability of changing from the first state to the second state; The first state and the second state are respectively taken from the device states of the target power device during the first operation process.
6. The method according to claim 1, characterized in that The determining of the state association information between the target power device and the associated power device includes: Determine the equipment state of the target electric equipment in each operation period during the second operation process; Determining the device status of the associated power equipment in each operating time period during the second operating process; The state association information is determined according to the device state of the target electric device and the device state of the associated electric device that exist simultaneously in the same operation period.
7. The method according to claim 6, characterized in that The determining of the state association information according to the device state of the target power device and the device state of the associated power device simultaneously existing in the same operating period includes: Determining a frequent item set whose support is higher than a first threshold according to the device state of the target power device and the device state of the associated power device that exist simultaneously in the same operating period; For each of the frequent itemsets, generating association rules between the equipment states of different electric devices according to the equipment state of the target electric device and the equipment state of the associated electric devices included in the frequent itemsets; Among the association rules, a target association rule having a support higher than a second threshold and a confidence higher than a third threshold is determined, so as to use the target association rule as the state association information.
8. The method according to claim 1, characterized in that The controlling the target power device according to the state transfer information and the state association information includes: Determining a device state of the target power device at a target time as a target device state; Determine, according to the target state transition probability corresponding to the target device state in the state transition information, the device state to which the target power device changes after the target time as the predicted device state; Determine, according to the state association information, a device state of an associated power device that has an association relationship with the predicted device state as the associated device state; If the predicted device state or the associated device state is an abnormal device state, determining a target control strategy that can prevent the target power device from changing from the target device state to the predicted device state; The target power device is controlled according to the target control strategy at the target time.
9. The method according to claim 8, characterized in that The determining of a target control strategy capable of preventing the target power device from changing from the target device state to the predicted device state includes: Generate an initial control strategy; Determining a predictive control effect corresponding to the initial control strategy; If the predicted control effect can prevent the target power device from changing from the target device state to the predicted device state, determining the initial control strategy as the target control strategy; If the predicted control effect cannot prevent the target power device from changing from the target device state to the predicted device state, return to the step of generating the initial control strategy to generate a new initial control strategy.
10. The method according to any one of claims 1 to 9, characterized in that The method further comprises: Determining a control error corresponding to the target power equipment; Determining a target control parameter for a control system according to the control error, the control system being a system for controlling the target power device; The control system is controlled using the target control parameter.
11. A power equipment control device, characterized in that: The device comprises: A first determination module is used to determine state transition information of a target power device, wherein the state transition information is used to characterize a state transition probability of the target power device changing from one device state to another device state; A second determination module is used to determine the state association information between the target power device and the associated power device, wherein the state association information is used to characterize the device state of the target power device and the device state of the associated power device that have an associated relationship; The first control module is used to control the target power equipment according to the state transfer information and the state association information.
12. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 10 are implemented.
13. An electronic device, characterized in that: include: a memory having a computer program stored thereon; A processor, configured to execute the computer program in the memory to implement the steps of the method according to any one of claims 1 to 10.