An intelligent control system and method for new energy and power grid

Abstract

The present invention provides an intelligent control system and method for new energy and power grid, including: a monitoring and prediction module, which is used to monitor the power grid load and power grid status at multiple monitoring points in each cycle based on the monitoring cycle, and predict the stage power demand of the power grid based on the power grid load and power grid status; an energy optimization configuration module, which is used to integrate the energy storage parameters in multiple categories of new energy equipment based on the stage power demand, and perform mutual complementary discharge control on multiple categories of new energy equipment and power grid based on the integration result; a guarantee operation and maintenance module, which is used to perform real-time operation and maintenance monitoring on the mutual complementary discharge process based on the control result, and locate and respond to the fault when there is a fault. The stable operation between multiple categories of new energy equipment and the power grid is guaranteed, and the control effect of electric energy complementarity between multiple categories of new energy equipment and the power grid is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment control, and in particular to an intelligent control system and method for new energy and power grid. Background Art

[0002] At present, under the requirements of current energy transformation and intelligent development, new energy is particularly important. New energy includes wind energy and solar energy. At the same time, new energy has been widely used in many industries. Combining with the power grid is one of them. It can effectively integrate various new energy resources and realize intelligent monitoring, control and management of the power grid to ensure efficient, safe and reliable supply of electricity.

[0003] However, there are still some defects in the current control of renewable energy and power grids. For example, the uncertainty of renewable energy will bring uncertainty and volatility to the operation of the power grid, and the frequent switching of power supply demand between renewable energy and power grid leads to different effective responses to energy changes between the two, resulting in unstable system operation and greatly reducing the control effect of renewable energy and power grid.

[0004] Therefore, in order to overcome the above-mentioned defects, the present invention provides an intelligent control system and method for new energy and power grid. Summary of the invention

[0005] The present invention provides an intelligent control system and method for new energy and power grid, which is used to determine a monitoring cycle and multiple monitoring points within each monitoring cycle, so as to realize real-time and effective monitoring of the power grid load and power grid state of the power grid through the monitoring cycle and multiple monitoring points, thereby providing data support for the prediction of the stage power demand of the power grid. Secondly, the stage power demand of the power grid is predicted by the obtained power grid load and power grid state, and the energy storage parameters of various types of new energy equipment are integrated according to the prediction results, so as to realize mutual complementary discharge control of multiple types of new energy equipment and the power grid according to the integration results and the stage power demand, thereby ensuring the accuracy and reliability of the charge and discharge control. Finally, real-time operation and maintenance monitoring of the mutual complementary discharge process is carried out, so as to realize timely positioning and solving of the fault when there is a fault, thereby ensuring the stable operation between multiple types of new energy equipment and the power grid, and improving the control effect of electric energy complementarity between multiple types of new energy equipment and the power grid.

[0006] The present invention provides an intelligent control system for new energy and power grid, including:

[0007] A monitoring and prediction module is used to monitor the grid load and grid status at multiple monitoring points in each cycle based on the monitoring cycle, and predict the grid's stage power demand based on the grid load and grid status;

[0008] Energy optimization configuration module, which is used to integrate the energy storage parameters of multiple types of new energy equipment based on the stage power demand, and to control the mutual complementary discharge of multiple types of new energy equipment and the power grid based on the integration results;

[0009] The guarantee operation and maintenance module is used to perform real-time operation and maintenance monitoring of the complementary discharge process based on the control results, and locate and respond to faults when faults occur.

[0010] Preferably, an intelligent control system, monitoring and prediction module for new energy and power grid includes:

[0011] Cycle configuration unit, used to:

[0012] Based on the analysis of the monitoring needs of the power grid, the monitoring cycle is determined, and the monitoring cycle is divided into multiple frequency irregular monitoring points based on the time span of the monitoring cycle to obtain multiple monitoring points within the cycle;

[0013] Configure a multi-dimensional monitoring sensor for each multi-point monitoring point obtained by dividing the irregular monitoring points, and adapt the triggering conditions of the multi-dimensional monitoring sensor based on the time attributes of the multi-point monitoring points;

[0014] The monitoring unit is used to perform time-effect configuration on each irregular monitoring point division result based on the adaptation result, and control the multi-dimensional monitoring sensor to monitor the power grid load and power grid status in turn at multiple monitoring points based on the time-effect configuration result;

[0015] The management unit is used to add periodic labels to the monitoring results and build a sample database based on the added results.

[0016] Preferably, in an intelligent control system for new energy and power grid, the power grid status includes power grid voltage, power grid current, power grid frequency and power grid power.

[0017] Preferably, an intelligent control system, monitoring and prediction module for new energy and power grid includes:

[0018] A result acquisition unit is used to acquire the grid load and grid state at multiple monitoring points in each cycle, and generate a two-dimensional grid operation curve diagram based on the values ​​of the grid load and grid state;

[0019] An abnormal data determination unit is used to determine abnormal value mutation points under multiple monitoring points in each cycle based on the two-dimensional operation curve diagram of the power grid, and determine upper and lower value parameters of the abnormal value mutation points;

[0020] The data cleaning unit is used to adjust the target value of the abnormal value mutation point based on the upper and lower value parameters, and smooth the adjustment result.

[0021] Preferably, an intelligent control system, monitoring and prediction module for new energy and power grid includes:

[0022] A data group determination unit is used to bind the power grid load and power grid state at each monitoring point in each cycle to obtain an associated data group, and to construct a comparison data group between different associated data groups based on the time series of multiple monitoring points in each cycle;

[0023] Data parsing unit, used for:

[0024] Obtain multi-dimensional influencing factors at multiple monitoring points in each cycle, and construct auxiliary analysis data sets at each monitoring point in each cycle based on the multi-dimensional influencing factors;

[0025] Based on the neural network, the associated data group, the control data group and the auxiliary analysis data group corresponding to each monitoring point in each cycle are extracted to obtain the periodic change trend characteristics of the power grid in each cycle, and the periodic change trend characteristics of the power grid are corrected based on the characteristic differences between different cycles;

[0026] The power prediction unit is used to train the correction results, build a power prediction model, and analyze the real-time operating parameters of the power grid based on the power prediction model to obtain the stage power demand of the power grid.

[0027] Preferably, an intelligent control system for new energy and power grid, an energy optimization configuration module, comprises:

[0028] Energy integration units for:

[0029] Access multiple types of new energy equipment and determine the energy storage parameters of each new energy equipment based on the access results;

[0030] Determine the minimum power reserve based on the basic operation guarantee requirements of each new energy device, determine the effective energy supply of each new energy device based on the minimum power reserve and energy storage parameters, and integrate the effective energy supply of each new energy device;

[0031] The mutual complementary discharge relationship and energy determination unit is used for:

[0032] Performing data registration on the integration result and the stage power demand, and generating floating curves of the integration result and the stage power demand in the same coordinate system based on the registration result;

[0033] Determine the power supply subordination and the electric energy supply amount under the power supply subordination based on the floating curve;

[0034] The complementary discharge control unit is used to dynamically balance the charging and discharging between various types of new energy equipment and the power grid based on the power supply subordination relationship and the amount of electric energy replenishment.

[0035] Preferably, an intelligent control system for new energy and power grid, a complementary discharge control unit, comprises:

[0036] A direction determination subunit is used to:

[0037] Determine the hierarchical relationship between the integration result and the stage power based on the floating curve, and take the upper value as the power supplier and the lower value as the power recipient based on the hierarchical relationship;

[0038] A power supply affiliation relationship is obtained based on the power supplier and the power recipient;

[0039] The charge and discharge control subunit is used to:

[0040] When the power supply affiliation is that each new energy device is the power supply party:

[0041] Divide each new energy device into an independent power supply unit, and determine the power supply network topology between each independent power supply unit based on the energy storage parameters of each new energy device;

[0042] Determine the discharge priority and discharge balance point of each independent power supply unit based on the power supply network topology, and control each independent power supply unit to discharge to the power grid based on the discharge priority and discharge balance point;

[0043] When the power supply affiliation is that each new energy device is the party being powered:

[0044] Obtaining energy loss values ​​of each new energy device, and determining a power supply sequence for each new energy device based on the energy loss values;

[0045] At the same time, the triggering conditions of the coordinated power supply balance point among the new energy devices are determined, and the power grid is controlled to supply power to the new energy devices based on the power supply sequence and the triggering conditions of the coordinated power supply balance point.

[0046] Preferably, an intelligent control system for new energy and power grid, ensuring operation and maintenance module, includes:

[0047] A monitoring unit, configured to configure a monitoring thread for the mutual complementary discharge process, and perform real-time operation and maintenance monitoring on the mutual complementary discharge process based on the monitoring thread to obtain real-time operation parameters of the mutual complementary discharge process;

[0048] Status analysis unit for:

[0049] Retrieve status assessment indicators and build a status assessment system based on the status assessment indicators;

[0050] Based on the status assessment system, the real-time operating parameters are analyzed in multiple dimensions to obtain the multi-dimensional operating status of each new energy device and the power grid, and based on the status difference between the multi-dimensional operating status and the preset operating status, it is determined whether each new energy device and the power grid has a fault;

[0051] A fault response unit, used to determine the fault subject based on the state difference when a fault exists, and to lock the abnormal representation state based on the multi-dimensional operation state;

[0052] The faulty component in the fault subject is determined based on the abnormal characterization state. At the same time, a response strategy is retrieved from the operation and maintenance response strategy library based on the abnormal characterization state to perform operation and maintenance response.

[0053] Preferably, an intelligent control system for new energy and power grid, a state analysis unit, comprises:

[0054] A state evaluation subunit is used to obtain the multi-dimensional operation state of each new energy device and the power grid, and determine the mutual complementary discharge effect between each new energy device and the power grid based on the multi-dimensional operation state;

[0055] The optimization subunit is used to determine the optimization direction and optimization parameters of the mutual complementary discharge process based on the mutual complementary discharge effect and the preset effect threshold when the mutual complementary discharge effect does not meet the preset effect threshold, and iteratively optimize the mutual complementary discharge process based on the optimization direction and optimization parameters.

[0056] The present invention provides an intelligent control method for new energy and power grid, comprising:

[0057] Based on the monitoring cycle, the grid load and grid status at multiple monitoring points in each cycle are monitored, and the grid's stage power demand is predicted based on the grid load and grid status;

[0058] Integrate the energy storage parameters of multiple types of new energy equipment based on the stage power demand, and control the complementary discharge of multiple types of new energy equipment and the power grid based on the integration results;

[0059] Based on the control results, the complementary discharge process is monitored in real time, and when a fault occurs, the fault is located and an operation and maintenance response is performed.

[0060] Compared with the prior art, the present invention has the following beneficial effects:

[0061] 1. By determining the monitoring cycle and multiple monitoring points within each monitoring cycle, the grid load and grid status of the power grid can be monitored in real time and effectively through the monitoring cycle and multiple monitoring points, thereby providing data support for the grid's stage power demand forecast. Secondly, the grid's stage power demand is predicted through the obtained grid load and grid status, and the energy storage parameters of various types of new energy equipment are integrated according to the prediction results, so as to achieve mutual complementary discharge control of multiple types of new energy equipment and the power grid according to the integration results and stage power demand, ensuring the accuracy and reliability of charging and discharging control. Finally, real-time operation and maintenance monitoring of the mutual complementary discharge process is carried out to locate and solve the fault in time when there is a fault, ensuring the stable operation between multiple types of new energy equipment and the power grid, and improving the control effect of electric energy complementarity between multiple types of new energy equipment and the power grid.

[0062] 2. By binding the grid load and grid status of each monitoring point in each cycle, the associated data group can be accurately and effectively determined, and the associated data between different monitoring points in each cycle can be compared to achieve accurate and effective acquisition of the comparison data group. Secondly, by determining the multi-dimensional influencing factors under multiple monitoring points in each cycle, the auxiliary analysis data group can be accurately and effectively acquired according to the multi-dimensional influencing factors. Finally, the associated data group, comparison data group and auxiliary analysis data group corresponding to each monitoring point in each cycle are extracted through neural networks to achieve accurate and effective construction of the power forecasting model based on the feature extraction results, and the constructed power forecasting model can be used to accurately and reliably analyze the real-time operation data of the power grid, thereby ensuring the accurate and effective determination of the stage power demand of the power grid.

[0063] 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 specifically pointed out in this application document.

[0064] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] 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:

[0066] Figure 1 This is a structural diagram of an intelligent control system for new energy and power grid in an embodiment of the present invention;

[0067] Figure 2This is a structural diagram of a monitoring and prediction module in an intelligent control system for new energy and power grids in an embodiment of the present invention;

[0068] Figure 3 The figure is a flow chart of an intelligent control method for new energy and power grid in an embodiment of the present invention. DETAILED DESCRIPTION

[0069] 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.

[0070] Embodiment 1:

[0071] This embodiment provides an intelligent control system for new energy and power grid, such as Figure 1 As shown, including:

[0072] A monitoring and prediction module is used to monitor the grid load and grid status at multiple monitoring points in each cycle based on the monitoring cycle, and predict the grid's stage power demand based on the grid load and grid status;

[0073] Energy optimization configuration module, which is used to integrate the energy storage parameters of multiple types of new energy equipment based on the stage power demand, and to control the mutual complementary discharge of multiple types of new energy equipment and the power grid based on the integration results;

[0074] The guarantee operation and maintenance module is used to perform real-time operation and maintenance monitoring of the complementary discharge process based on the control results, and locate and respond to faults when faults occur.

[0075] In this embodiment, the monitoring cycle is determined according to the monitoring requirements and is used to represent the length of time for monitoring the operating status of the power grid. For example, one day may be a monitoring cycle.

[0076] In this embodiment, multiple monitoring points refer to multiple monitoring time periods divided in each cycle, for example, 10 am, 2 pm and 8 pm in a day.

[0077] In this embodiment, the grid load refers to the number of terminals carried by the grid and their demand for electric energy.

[0078] In this embodiment, the phase power demand refers to the amount of electric energy required by the power grid in each operation phase.

[0079] In this embodiment, the multiple categories of new energy equipment include various types of devices such as photovoltaic equipment and wind power generation equipment.

[0080] In this embodiment, the integration of energy storage parameters refers to summarizing the electric energy currently stored in different new energy devices, so as to facilitate mutual complementary discharge with the power grid.

[0081] In this embodiment, the mutual complementary discharge control of multiple categories of new energy equipment and the power grid means that when the power grid needs electric energy, the power grid is discharged by multiple categories of new energy equipment. At the same time, when the power grid has abundant electric energy, the excess electric energy is used to supply power to multiple categories of new energy equipment.

[0082] In this embodiment, the real-time operation and maintenance monitoring refers to real-time monitoring of the operation status of the complementary discharge process.

[0083] The working principle and beneficial effects of the above technical solution are: by determining the monitoring cycle and the multiple monitoring points within each monitoring cycle, the grid load and grid status of the power grid are monitored in real time and effectively through the monitoring cycle and the multiple monitoring points, thereby providing data support for the stage power demand forecast of the power grid. Secondly, the stage power demand of the power grid is predicted by the obtained grid load and grid status, and the energy storage parameters of various types of new energy equipment are integrated according to the prediction results, so as to realize the mutual complementary discharge control of multiple types of new energy equipment and the power grid according to the integration results and the stage power demand, thereby ensuring the accuracy and reliability of the charging and discharging control. Finally, the mutual complementary discharge process is monitored in real time for operation and maintenance, so that when a fault occurs, the fault can be located and resolved in time, thereby ensuring the stable operation between multiple types of new energy equipment and the power grid, and improving the control effect of electric energy complementarity between multiple types of new energy equipment and the power grid.

[0084] Embodiment 2:

[0085] Based on Example 1, this embodiment provides an intelligent control system for new energy and power grid, such as Figure 2 As shown, the monitoring and prediction module includes:

[0086] Cycle configuration unit, used to:

[0087] Based on the analysis of the monitoring needs of the power grid, the monitoring cycle is determined, and the monitoring cycle is divided into multiple frequency irregular monitoring points based on the time span of the monitoring cycle to obtain multiple monitoring points within the cycle;

[0088] Configure a multi-dimensional monitoring sensor for each multi-point monitoring point obtained by dividing the irregular monitoring points, and adapt the triggering conditions of the multi-dimensional monitoring sensor based on the time attributes of the multi-point monitoring points;

[0089] The monitoring unit is used to perform time-effect configuration on each irregular monitoring point division result based on the adaptation result, and control the multi-dimensional monitoring sensor to monitor the power grid load and power grid status in turn at multiple monitoring points based on the time-effect configuration result;

[0090] The management unit is used to add periodic labels to the monitoring results and build a sample database based on the added results.

[0091] In this embodiment, the monitoring requirements are known in advance and are used to characterize the period and standard for monitoring the power grid.

[0092] In this embodiment, the time span refers to the length of time each monitoring cycle lasts, for example, it can be one day or one week.

[0093] In this embodiment, the multi-frequency irregular monitoring point division refers to dividing the monitoring period into nodes, the purpose of which is to set up multiple monitoring points within the monitoring period, so as to achieve comprehensive and effective monitoring of the power grid, wherein the multi-point monitoring point is the result of dividing the monitoring period into multi-frequency irregular monitoring points.

[0094] In this embodiment, the multi-dimensional monitoring sensor refers to a plurality of different types of sensors, thereby achieving comprehensive monitoring of the power grid.

[0095] In this embodiment, the time attribute refers to the specific time corresponding to each monitoring point.

[0096] In this embodiment, the time configuration refers to configuring the effective time of each monitoring point division result.

[0097] In this embodiment, the period label refers to a label symbol that can distinguish different monitoring periods.

[0098] The working principle and beneficial effects of the above technical solution are: by analyzing the monitoring needs of the power grid, the monitoring period can be accurately and effectively determined, and the monitoring points are divided into the monitoring period, and each monitoring point is configured with a multi-dimensional monitoring sensor. Secondly, the triggering conditions and timeliness of the multi-dimensional monitoring sensor are configured to achieve real-time and effective monitoring of the power grid load and power grid status according to the configuration results. Finally, the data monitored in each monitoring period is periodically marked to achieve accurate and reliable construction of the sample database, which provides data support for the intelligent control of new energy and power grids.

[0099] Embodiment 3:

[0100] Based on Example 1, this embodiment provides an intelligent control system for new energy and power grid, and the power grid status includes power grid voltage, power grid current, power grid frequency and power grid power.

[0101] Embodiment 4:

[0102] Based on Example 1, this embodiment provides an intelligent control system for new energy and power grid, a monitoring and prediction module, including:

[0103] A result acquisition unit is used to acquire the grid load and grid state at multiple monitoring points in each cycle, and generate a two-dimensional grid operation curve diagram based on the values ​​of the grid load and grid state;

[0104] An abnormal data determination unit is used to determine abnormal value mutation points under multiple monitoring points in each cycle based on the two-dimensional operation curve diagram of the power grid, and determine upper and lower value parameters of the abnormal value mutation points;

[0105] The data cleaning unit is used to adjust the target value of the abnormal value mutation point based on the upper and lower value parameters, and smooth the adjustment result.

[0106] In this embodiment, the abnormal value mutation point refers to a numerical point where the values ​​of the grid load and grid state determined according to the two-dimensional grid operation curve diagram undergo abnormal changes, and specifically may be a numerical point where the value change threshold exceeds a preset threshold.

[0107] In this embodiment, the upper and lower value parameters refer to the specific values ​​corresponding to the upper and lower data of the abnormal value mutation point.

[0108] In this embodiment, the target value refers to the specific value corresponding to the abnormal mutation point.

[0109] The working principle and beneficial effect of the above technical solution are: by analyzing the values ​​of the power grid load and the power grid state at multiple monitoring points in each cycle, the abnormal value mutation points of the power grid load and the power grid state are accurately and effectively determined. Finally, the target value of the abnormal value mutation point is adjusted according to the upper and lower value parameters of the abnormal value mutation point, so as to achieve accurate and effective cleaning of the power grid load and the power grid state in each monitoring cycle, thereby ensuring the accuracy and reliability of the power grid load and the power grid state.

[0110] Embodiment 5:

[0111] Based on Example 1, this embodiment provides an intelligent control system for new energy and power grid, a monitoring and prediction module, including:

[0112] A data group determination unit is used to bind the power grid load and power grid state at each monitoring point in each cycle to obtain an associated data group, and to construct a comparison data group between different associated data groups based on the time series of multiple monitoring points in each cycle;

[0113] Data parsing unit, used for:

[0114] Obtain multi-dimensional influencing factors at multiple monitoring points in each cycle, and construct auxiliary analysis data sets at each monitoring point in each cycle based on the multi-dimensional influencing factors;

[0115] Based on the neural network, the associated data group, the control data group and the auxiliary analysis data group corresponding to each monitoring point in each cycle are extracted to obtain the periodic change trend characteristics of the power grid in each cycle, and the periodic change trend characteristics of the power grid are corrected based on the characteristic differences between different cycles;

[0116] The power prediction unit is used to train the correction results, build a power prediction model, and analyze the real-time operating parameters of the power grid based on the power prediction model to obtain the stage power demand of the power grid.

[0117] In this embodiment, the associated data group refers to a data pair obtained by binding the grid load and the grid state at each monitoring point in each cycle.

[0118] In this embodiment, the comparison data group refers to data obtained by comparing the associated data groups corresponding to different monitoring points.

[0119] In this embodiment, the multi-dimensional influencing factors refer to interference factors that affect the operating state of the power grid in each cycle.

[0120] In this embodiment, the auxiliary analysis data group refers to data parameters that can assist in analyzing the actual operation of the power grid after summarizing the multi-dimensional influencing factors at multiple monitoring points in each cycle.

[0121] In this embodiment, the characteristic difference refers to the difference between the periodic change trend characteristics between different monitoring periods.

[0122] The working principle and beneficial effects of the above technical solution are: by binding the power grid load and power grid status of each monitoring point in each cycle, the associated data group can be accurately and effectively determined, and the associated data between different monitoring points in each cycle can be compared to achieve accurate and effective acquisition of the comparison data group; secondly, by determining the multi-dimensional influencing factors under multiple monitoring points in each cycle, the auxiliary analysis data group can be accurately and effectively acquired according to the multi-dimensional influencing factors; finally, the associated data group, comparison data group and auxiliary analysis data group corresponding to each monitoring point in each cycle are feature extracted through a neural network, so that the power forecasting model can be accurately and effectively constructed according to the feature extraction results; and the real-time operation data of the power grid can be accurately and reliably analyzed through the constructed power forecasting model, thereby ensuring the accurate and effective determination of the stage power demand of the power grid.

[0123] Embodiment 6:

[0124] Based on Example 1, this embodiment provides an intelligent control system for new energy and power grid, an energy optimization configuration module, including:

[0125] Energy integration units for:

[0126] Access multiple types of new energy equipment and determine the energy storage parameters of each new energy equipment based on the access results;

[0127] Determine the minimum power reserve based on the basic operation guarantee requirements of each new energy device, determine the effective energy supply of each new energy device based on the minimum power reserve and energy storage parameters, and integrate the effective energy supply of each new energy device;

[0128] The mutual complementary discharge relationship and energy determination unit is used for:

[0129] Performing data registration on the integration result and the stage power demand, and generating floating curves of the integration result and the stage power demand in the same coordinate system based on the registration result;

[0130] Determine the power supply subordination and the electric energy supply amount under the power supply subordination based on the floating curve;

[0131] The complementary discharge control unit is used to dynamically balance the charging and discharging between various types of new energy equipment and the power grid based on the power supply subordination relationship and the amount of electric energy replenishment.

[0132] In this embodiment, the energy storage parameter refers to the amount of energy stored inside each new energy device.

[0133] In this embodiment, the basic operation guarantee requirements refer to the specific operation conditions of each new energy device, including the minimum amount of electricity that each new energy device needs to retain, wherein the minimum amount of electricity retained refers to the minimum amount of electricity required for the operation of each energy device itself.

[0134] In this embodiment, the effective functional energy refers to the effective amount of electricity that various energy devices can provide to the power grid.

[0135] In this embodiment, data alignment refers to matching the integration result of the effective energy supply with the stage power demand, so as to facilitate the determination of whether the effective energy supply can meet the power supply demand of the power grid.

[0136] In this embodiment, the floating curve is used to represent the changes between the integration result of the effective energy supply and the stage power demand.

[0137] In this embodiment, the power supply affiliation is used to characterize the power supply direction between each new energy device and the power grid, including each new energy device supplying power to the power grid and the power grid supplying power to each new energy device.

[0138] In this embodiment, the power supply refers to the amount of power that can be exchanged based on the power supply affiliation.

[0139] The working principle and beneficial effects of the above technical solution are: by accessing multiple categories of new energy equipment, the energy storage parameters of each new energy equipment can be accurately and effectively determined. At the same time, the minimum electric energy reserve is locked according to the basic operation guarantee requirements of each new energy equipment, and the effective energy supply of each new energy equipment is determined according to the minimum electric energy reserve. Secondly, the integrated results of the effective energy supply and the stage power demand are data aligned to achieve accurate and effective determination of the floating curve of the integrated results and the stage power demand. Finally, the power supply subordination and the electric energy replenishment are accurately and effectively determined according to the floating curve, and the dynamic balance control of charging and discharging between multiple categories of new energy equipment and the power grid is achieved according to the power supply subordination and the electric energy replenishment, thereby improving the accuracy and intelligence of the control between the new energy equipment and the power grid.

[0140] Embodiment 7:

[0141] Based on Example 6, this embodiment provides an intelligent control system for new energy and power grid, a complementary discharge control unit, including:

[0142] A direction determination subunit is used to:

[0143] Determine the hierarchical relationship between the integration result and the stage power based on the floating curve, and take the upper value as the power supplier and the lower value as the power recipient based on the hierarchical relationship;

[0144] A power supply affiliation relationship is obtained based on the power supplier and the power recipient;

[0145] The charge and discharge control subunit is used to:

[0146] When the power supply affiliation is that each new energy device is the power supply party:

[0147] Divide each new energy device into an independent power supply unit, and determine the power supply network topology between each independent power supply unit based on the energy storage parameters of each new energy device;

[0148] Determine the discharge priority and discharge balance point of each independent power supply unit based on the power supply network topology, and control each independent power supply unit to discharge to the power grid based on the discharge priority and discharge balance point;

[0149] When the power supply affiliation is that each new energy device is the party being powered:

[0150] Obtaining energy loss values ​​of each new energy device, and determining a power supply sequence for each new energy device based on the energy loss values;

[0151] At the same time, the triggering conditions of the coordinated power supply balance point among the new energy devices are determined, and the power grid is controlled to supply power to the new energy devices based on the power supply sequence and the triggering conditions of the coordinated power supply balance point.

[0152] In this embodiment, the upper and lower relationship of the values ​​is used to characterize the relationship between the integration result and the value of the stage power.

[0153] In this embodiment, the upper value refers to the one with a larger value, and the lower value refers to the one with a smaller value.

[0154] In this embodiment, the independent power supply unit refers to dividing the new energy equipment, that is, each new energy equipment is a power supply unit.

[0155] In this embodiment, the power supply network topology is used to characterize the power supply structure of each new energy device when supplying power to the power grid, that is, the amount of energy supplied by each new energy device to the power grid.

[0156] In this embodiment, the discharge balance point refers to a node at which each independent power supply unit can effectively manage the discharge of each new energy device during discharge, that is, a node that can both effectively discharge and retain the minimum power demand.

[0157] In this embodiment, the energy loss value refers to the amount of power missing in each new energy device.

[0158] In this embodiment, the electric energy coordinated power supply balance point refers to a node that can effectively coordinate the power supply between the various new energy devices when supplying power to the various new energy devices, that is, it can effectively transmit energy to the various new energy devices.

[0159] The working principle and beneficial effects of the above technical solution are: by analyzing the integration results of the effective energy supply and the hierarchical relationship of the stage power values ​​according to the floating curve, the power supply subordination relationship between each new energy device and the power grid is accurately and effectively determined; secondly, the power supply mode between each new energy device and the power grid is discussed on a case-by-case basis according to the power supply subordination relationship, thereby realizing accurate and effective control of the charging and discharging between the power grid and various energy devices.

[0160] Embodiment 8:

[0161] Based on Example 1, this embodiment provides an intelligent control system for new energy and power grid, and a guarantee operation and maintenance module, including:

[0162] A monitoring unit, configured to configure a monitoring thread for the mutual complementary discharge process, and perform real-time operation and maintenance monitoring on the mutual complementary discharge process based on the monitoring thread to obtain real-time operation parameters of the mutual complementary discharge process;

[0163] Status analysis unit for:

[0164] Retrieve status assessment indicators and build a status assessment system based on the status assessment indicators;

[0165] Based on the status assessment system, the real-time operating parameters are analyzed in multiple dimensions to obtain the multi-dimensional operating status of each new energy device and the power grid, and based on the status difference between the multi-dimensional operating status and the preset operating status, it is determined whether each new energy device and the power grid has a fault;

[0166] A fault response unit, used to determine the fault subject based on the state difference when a fault exists, and to lock the abnormal representation state based on the multi-dimensional operation state;

[0167] The faulty component in the fault subject is determined based on the abnormal characterization state. At the same time, a response strategy is retrieved from the operation and maintenance response strategy library based on the abnormal characterization state to perform operation and maintenance response.

[0168] In this embodiment, the monitoring thread refers to a strategy for monitoring the mutual complementary discharge.

[0169] In this embodiment, the real-time operating parameters refer to monitoring data obtained after monitoring the mutual complementary discharge process.

[0170] In this embodiment, the state evaluation index is retrieved from the server and is used as a reference for evaluating the state of the complementary discharge process.

[0171] In this embodiment, the preset operating state is set in advance and is used to represent the corresponding state of each new energy device when it operates normally.

[0172] In this embodiment, the state difference refers to the difference between the multi-dimensional operating state and the preset operating state.

[0173] In this embodiment, the abnormal manifestation state refers to the abnormal phenomenon exhibited by the fault subject.

[0174] The working principle and beneficial effects of the above technical solution are: by configuring a monitoring thread for the mutually complementary discharge process, the mutual complementary discharge process can be effectively configured in real time according to the monitoring thread, thereby realizing real-time and effective acquisition of the real-time operating parameters of the mutually complementary discharge process; secondly, by retrieving state evaluation indicators, the real-time operating parameters can be effectively parsed according to the state evaluation indicators, and the multi-dimensional operating status of each new energy device and the power grid can be accurately and effectively determined; finally, according to the determined multi-dimensional operating status, the fault subject and the faulty components in the fault subject can be locked, thereby retrieving the response strategy from the operation and maintenance response strategy library for operation and maintenance response, ensuring the effective charging and discharging between the power grid and the new energy equipment.

[0175] Embodiment 9:

[0176] Based on Example 8, this embodiment provides an intelligent control system for new energy and power grid, and a state analysis unit, including:

[0177] A state evaluation subunit is used to obtain the multi-dimensional operation state of each new energy device and the power grid, and determine the mutual complementary discharge effect between each new energy device and the power grid based on the multi-dimensional operation state;

[0178] The optimization subunit is used to determine the optimization direction and optimization parameters of the mutual complementary discharge process based on the mutual complementary discharge effect and the preset effect threshold when the mutual complementary discharge effect does not meet the preset effect threshold, and iteratively optimize the mutual complementary discharge process based on the optimization direction and optimization parameters.

[0179] In this embodiment, the preset effect threshold is set in advance.

[0180] In this embodiment, the optimization direction and the optimization parameter refer to the specific steps of optimizing the mutual complementary discharge process when the mutual complementary discharge process does not meet the requirements and the specific degree of optimization of the specific steps.

[0181] The working principle and beneficial effects of the above technical solution are: by accurately and effectively determining the mutual complementary discharge effect between each new energy device and the power grid according to the multi-dimensional operating status of each new energy device and the power grid, secondly, comparing the mutual complementary discharge effect with a preset effect threshold, and realizing that when the preset effect threshold is not met, the optimization direction and optimization parameters of the mutual complementary discharge process are accurately and effectively determined, and finally, the mutual complementary discharge process is iteratively optimized through the determined optimization direction and optimization parameters, thereby ensuring the effective operation between the new energy device and the power grid.

[0182] Embodiment 10:

[0183] This embodiment provides an intelligent control method for new energy and power grid, such as Figure 3 As shown, including:

[0184] Step 1: Based on the monitoring cycle, the grid load and grid status at multiple monitoring points in each cycle are monitored, and the grid's stage power demand is predicted based on the grid load and grid status;

[0185] Step 2: Integrate the energy storage parameters of multiple types of new energy equipment based on the stage power demand, and perform complementary discharge control on multiple types of new energy equipment and the power grid based on the integration results;

[0186] Step 3: Based on the control results, the complementary discharge process is monitored in real time, and when a fault occurs, the fault is located and the operation and maintenance response is performed.

[0187] The working principle and beneficial effects of the above technical solution are: by determining the monitoring cycle and the multiple monitoring points within each monitoring cycle, the grid load and grid status of the power grid are monitored in real time and effectively through the monitoring cycle and the multiple monitoring points, thereby providing data support for the stage power demand forecast of the power grid. Secondly, the stage power demand of the power grid is predicted by the obtained grid load and grid status, and the energy storage parameters of various types of new energy equipment are integrated according to the prediction results, so as to realize the mutual complementary discharge control of multiple types of new energy equipment and the power grid according to the integration results and the stage power demand, thereby ensuring the accuracy and reliability of the charging and discharging control. Finally, the mutual complementary discharge process is monitored in real time for operation and maintenance, so that when a fault occurs, the fault can be located and resolved in time, thereby ensuring the stable operation between multiple types of new energy equipment and the power grid, and improving the control effect of electric energy complementarity between multiple types of new energy equipment and the power grid.

[0188] 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. An intelligent control system for new energy and power grid, characterized in that: include: A monitoring and prediction module is used to monitor the grid load and grid status at multiple monitoring points in each cycle based on the monitoring cycle, and predict the grid's stage power demand based on the grid load and grid status; Energy optimization configuration module, which is used to integrate the energy storage parameters of multiple types of new energy equipment based on the stage power demand, and to control the mutual complementary discharge of multiple types of new energy equipment and the power grid based on the integration results; The guarantee operation and maintenance module is used to perform real-time operation and maintenance monitoring of the complementary discharge process based on the control results, and locate and respond to faults when there are faults; Among them, the monitoring and prediction module includes: Cycle configuration unit, used to: Based on the analysis of the monitoring needs of the power grid, the monitoring cycle is determined, and the monitoring cycle is divided into multiple frequency irregular monitoring points based on the time span of the monitoring cycle to obtain multiple monitoring points within the cycle; Configure a multi-dimensional monitoring sensor for each multi-point monitoring point obtained by dividing the irregular monitoring points, and adapt the triggering conditions of the multi-dimensional monitoring sensor based on the time attributes of the multi-point monitoring points; The monitoring unit is used to perform time-effect configuration on each irregular monitoring point division result based on the adaptation result, and control the multi-dimensional monitoring sensor to monitor the power grid load and power grid status in turn at multiple monitoring points based on the time-effect configuration result; The management unit is used to add periodic labels to the monitoring results and build a sample database based on the added results.

2. According to claim 1, the intelligent control system for new energy and power grid is characterized in that: The grid status includes grid voltage, grid current, grid power frequency and grid power.

3. According to claim 1, the intelligent control system for new energy and power grid is characterized in that: Monitoring and prediction modules, including: A result acquisition unit is used to acquire the grid load and grid state at multiple monitoring points in each cycle, and generate a two-dimensional grid operation curve diagram based on the values ​​of the grid load and grid state; An abnormal data determination unit is used to determine abnormal value mutation points under multiple monitoring points in each cycle based on the two-dimensional operation curve diagram of the power grid, and determine upper and lower value parameters of the abnormal value mutation points; The data cleaning unit is used to adjust the target value of the abnormal value mutation point based on the upper and lower value parameters, and smooth the adjustment result.

4. The intelligent control system for new energy and power grid according to claim 1 is characterized in that: Monitoring and prediction modules, including: A data group determination unit is used to bind the power grid load and power grid state at each monitoring point in each cycle to obtain an associated data group, and to construct a comparison data group between different associated data groups based on the time series of multiple monitoring points in each cycle; Data parsing unit, used for: Obtain multi-dimensional influencing factors at multiple monitoring points in each cycle, and construct auxiliary analysis data sets at each monitoring point in each cycle based on the multi-dimensional influencing factors; Based on the neural network, the associated data group, the control data group and the auxiliary analysis data group corresponding to each monitoring point in each cycle are extracted to obtain the periodic change trend characteristics of the power grid in each cycle, and the periodic change trend characteristics of the power grid are corrected based on the characteristic differences between different cycles; The power prediction unit is used to train the correction results, build a power prediction model, and analyze the real-time operating parameters of the power grid based on the power prediction model to obtain the stage power demand of the power grid.

5. The intelligent control system for new energy and power grid according to claim 1 is characterized in that: Energy optimization configuration module, including: Energy integration units for: Access multiple types of new energy equipment and determine the energy storage parameters of each new energy equipment based on the access results; Determine the minimum power reserve based on the basic operation guarantee requirements of each new energy device, determine the effective energy supply of each new energy device based on the minimum power reserve and energy storage parameters, and integrate the effective energy supply of each new energy device; The mutual complementary discharge relationship and energy determination unit is used for: Performing data registration on the integration result and the stage power demand, and generating floating curves of the integration result and the stage power demand in the same coordinate system based on the registration result; Determine the power supply subordination and the electric energy supply amount under the power supply subordination based on the floating curve; The complementary discharge control unit is used to dynamically balance the charging and discharging between various types of new energy equipment and the power grid based on the power supply subordination relationship and the amount of electric energy replenishment.

6. The intelligent control system for new energy and power grid according to claim 5 is characterized in that: A complementary discharge control unit, comprising: A direction determination subunit is used to: Determine the hierarchical relationship between the integration result and the stage power based on the floating curve, and take the upper value as the power supplier and the lower value as the power recipient based on the hierarchical relationship; A power supply affiliation relationship is obtained based on the power supplier and the power recipient; The charge and discharge control subunit is used to: When the power supply affiliation is that each new energy device is the power supply party: Divide each new energy device into an independent power supply unit, and determine the power supply network topology between each independent power supply unit based on the energy storage parameters of each new energy device; Determine the discharge priority and discharge balance point of each independent power supply unit based on the power supply network topology, and control each independent power supply unit to discharge to the power grid based on the discharge priority and discharge balance point; When the power supply affiliation is that each new energy device is the party being powered: Obtaining energy loss values ​​of each new energy device, and determining a power supply sequence for each new energy device based on the energy loss values; At the same time, the triggering conditions of the coordinated power supply balance point among the new energy devices are determined, and the power grid is controlled to supply power to the new energy devices based on the power supply sequence and the triggering conditions of the coordinated power supply balance point.

7. The intelligent control system for new energy and power grid according to claim 1 is characterized in that: Ensure operation and maintenance modules, including: A monitoring unit, configured to configure a monitoring thread for the mutual complementary discharge process, and perform real-time operation and maintenance monitoring on the mutual complementary discharge process based on the monitoring thread to obtain real-time operation parameters of the mutual complementary discharge process; Status analysis unit for: Retrieve status assessment indicators and build a status assessment system based on the status assessment indicators; Based on the status assessment system, the real-time operating parameters are analyzed in multiple dimensions to obtain the multi-dimensional operating status of each new energy device and the power grid, and based on the status difference between the multi-dimensional operating status and the preset operating status, it is determined whether each new energy device and the power grid has a fault; A fault response unit, used to determine the fault subject based on the state difference when a fault exists, and to lock the abnormal representation state based on the multi-dimensional operation state; The faulty component in the fault subject is determined based on the abnormal characterization state. At the same time, a response strategy is retrieved from the operation and maintenance response strategy library based on the abnormal characterization state to perform operation and maintenance response.

8. The intelligent control system for new energy and power grid according to claim 7 is characterized in that: State analysis unit, including: A state evaluation subunit is used to obtain the multi-dimensional operation state of each new energy device and the power grid, and determine the mutual complementary discharge effect between each new energy device and the power grid based on the multi-dimensional operation state; The optimization subunit is used to determine the optimization direction and optimization parameters of the mutual complementary discharge process based on the mutual complementary discharge effect and the preset effect threshold when the mutual complementary discharge effect does not meet the preset effect threshold, and iteratively optimize the mutual complementary discharge process based on the optimization direction and optimization parameters.

9. An intelligent control method for new energy and power grid, characterized in that: include: Based on the monitoring cycle, the grid load and grid status at multiple monitoring points in each cycle are monitored, and the grid's stage power demand is predicted based on the grid load and grid status; Integrate the energy storage parameters of multiple types of new energy equipment based on the stage power demand, and control the complementary discharge of multiple types of new energy equipment and the power grid based on the integration results; Based on the control results, the complementary discharge process is monitored in real time, and when a fault occurs, the fault is located and the operation and maintenance response is carried out; Among them, based on the monitoring cycle, the grid load and grid status at multiple monitoring points in each cycle are monitored, including: Based on the analysis of the monitoring needs of the power grid, the monitoring cycle is determined, and the monitoring cycle is divided into multiple frequency irregular monitoring points based on the time span of the monitoring cycle to obtain multiple monitoring points within the cycle; Configure a multi-dimensional monitoring sensor for each multi-point monitoring point obtained by dividing the irregular monitoring points, and adapt the triggering conditions of the multi-dimensional monitoring sensor based on the time attributes of the multi-point monitoring points; Based on the adaptation results, the time-effectiveness configuration is performed for each irregular monitoring point division result, and based on the time-effectiveness configuration results, the multi-dimensional monitoring sensors are controlled to monitor the grid load and grid status in turn at multiple monitoring points; Add periodic labels to the monitoring results and build a sample database based on the added results.

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