Method, device and equipment for generating dispatching optimization information of sending-end power grid and storage medium

Abstract

The embodiment of the invention provides a sending-end power grid dispatching optimization information generation method and device, equipment and a storage medium, and the method comprises the steps: determining the power dispatching data of a sending-end power grid; determining a power dispatching index of the sending-end power grid based on the power dispatching data; predicting a dispatching optimization index of the sending-end power grid according to the power dispatching index; and determining scheduling optimization information of the sending-end power grid according to the scheduling optimization index. And determining a high-dimensional power dispatching index according to the power dispatching data of the sending-end power grid, and determining a dispatching optimization index for representing the next state of the sending-end power grid according to the high-latitude power dispatching index. And finally, preset scheduling optimization information is determined according to scheduling optimization so as to provide reference for decision makers of the sending-end power grid, and workers of the sending-end power grid are prompted to take necessary prevention measures in time according to upcoming power consumption defects of power distribution of the power grid.

Description

Technical Field

[0001] The embodiments of this specification relate to the field of power grid distribution dispatching, and in particular to a method, device, equipment and storage medium for generating dispatch optimization information of a sending-end power grid. Background Art

[0002] With the continuous growth of grid load and the massive access of renewable energy, the operating environment of distribution networks has become increasingly complex. Grids are facing challenges such as increased volatility and widening peak-to-valley differences. At the same time, frequent extreme weather events have put forward higher requirements for the stability and resilience of power supply. In order to meet these challenges, mobile energy storage devices (such as mobile energy storage vehicles) are applied to the power grid to form a sending-end power grid to regulate the complex power demand in the power grid.

[0003] However, when the traditional dispatching method for optimizing the path of mobile energy storage equipment in the sending-end power grid is used for the distribution and dispatching of mobile energy storage equipment in the sending-end power grid, it will be affected by factors such as the uncertainty of renewable energy sources such as wind power and photovoltaic power generation and power load in the sending-end power grid, which will affect the optimal dispatching of mobile energy storage equipment. In addition, the traditional dispatching method lacks the ability to respond immediately and dynamically adapt to mobile energy storage equipment, which makes it difficult to dispatch mobile energy storage equipment to meet the needs of the power grid in emergency situations. Therefore, the corresponding mobile energy storage equipment can only be dispatched to make up for it after the sending-end power grid alarms and power problems occur. Otherwise, only some areas can be selectively powered.

[0004] Therefore, an effective method is urgently needed to deal with the above problems. Summary of the invention

[0005] In view of this, the embodiments of this specification provide a method for generating dispatch optimization information of a power grid at the sending end. One or more embodiments of this specification also involve a device for generating dispatch optimization information of a power grid at the sending end, a computing device, a computer-readable storage medium and a computer program to solve the technical defects existing in the prior art.

[0006] According to a first aspect of an embodiment of this specification, a method for generating dispatch optimization information of a sending-end power grid is provided, comprising:

[0007] Determine the power dispatching data of the sending-end power grid;

[0008] Determine the power dispatching index of the sending-end power grid based on the power dispatching data;

[0009] Predict dispatch optimization indicators of the sending-end power grid based on power dispatch indicators;

[0010] The dispatch optimization information of the sending-end power grid is determined according to the dispatch optimization index.

[0011] In some embodiments of this specification, determining the power dispatching data of the sending-end power grid further includes:

[0012] Determine the power dispatch data at multiple historical moments;

[0013] Determine the impact factor at each historical moment based on the power dispatch data at each historical moment;

[0014] According to the power dispatching data corresponding to the plurality of historical moments and the influencing factors corresponding to the plurality of historical moments, first power dispatching data for the first scheduled time is determined.

[0015] In some embodiments of the present specification, determining the power dispatch index in the sending-end power grid based on the power dispatch data includes:

[0016] The power dispatching index in the sending-end power grid is determined according to the first power dispatching data and / or the influencing factors corresponding to a plurality of historical moments.

[0017] In some embodiments of this specification, the power dispatch data includes the total load of the mobile energy storage device and the grid load of the grid where the mobile energy storage device is located;

[0018] Determining first power dispatch data for a first scheduled time according to the power dispatch data corresponding to the plurality of historical moments and the influencing factors corresponding to the plurality of historical moments includes:

[0019] Determine a predicted value of the total load of the mobile energy storage device at a first predetermined moment according to the total load of the mobile energy storage device at multiple historical moments and the influencing factors corresponding to the multiple historical moments;

[0020] Determine a predicted value of the grid load of the grid where the mobile energy storage device is located at a first predetermined moment according to the grid load of the grid where the mobile energy storage device is located at multiple historical moments and the influencing factors corresponding to the multiple historical moments;

[0021] Determining a power dispatching index in a sending-end power grid according to the first power dispatching data and / or the influencing factors corresponding to a plurality of historical moments includes:

[0022] Determine the power supply load index based on the total load forecast value and the grid load forecast value;

[0023] According to the power dispatching indicators, the dispatching optimization indicators of the sending-end power grid are predicted, including:

[0024] Predict dispatch optimization indicators of the sending-end power grid based on power supply load indicators;

[0025] The dispatch optimization information of the sending-end power grid is determined according to the dispatch optimization index, including:

[0026] If the dispatch optimization index meets the first preset condition, dispatch optimization information for increasing the total load of the mobile energy storage device is generated.

[0027] In some embodiments of this specification, the power dispatch data includes dispatch cost and discharge efficiency of mobile energy storage equipment;

[0028] Determining first power dispatch data for a first scheduled time according to the power dispatch data corresponding to the plurality of historical moments and the influencing factors corresponding to the plurality of historical moments includes:

[0029] Determine a predicted dispatch cost value of the mobile energy storage device at a first predetermined time according to the dispatch costs of the mobile energy storage device at multiple historical times and the influencing factors corresponding to the multiple historical times; and

[0030] Determine a predicted value of the discharge efficiency of the mobile energy storage device at a first predetermined moment according to the discharge efficiency of the mobile energy storage device at multiple historical moments and the influencing factors corresponding to the mobile energy storage device at multiple historical moments;

[0031] Determining a power dispatching index in a sending-end power grid according to the first power dispatching data and / or the influencing factors corresponding to a plurality of historical moments includes:

[0032] Determine the power supply efficiency index based on the dispatch cost forecast value and the discharge efficiency forecast value;

[0033] According to the power dispatching indicators, the dispatching optimization indicators of the sending-end power grid are predicted, including:

[0034] Predict dispatch optimization indicators of the sending-end power grid based on power supply efficiency indicators;

[0035] The dispatch optimization information of the sending-end power grid is determined according to the dispatch optimization index, including:

[0036] If the scheduling optimization index meets the second preset condition, scheduling optimization information for improving the discharge efficiency of the mobile energy storage device is generated.

[0037] In some embodiments of this specification, the power dispatch data includes the displacement distance of the mobile energy storage device;

[0038] Determining first power dispatch data for a first scheduled time according to the power dispatch data corresponding to the plurality of historical moments and the influencing factors corresponding to the plurality of historical moments includes:

[0039] Determine a predicted displacement distance of the mobile energy storage device at a first predetermined moment according to the displacement distances of the mobile energy storage device at multiple historical moments and the influencing factors corresponding to the multiple historical moments;

[0040] Determining a power dispatching index in a sending-end power grid according to the first power dispatching data and / or the influencing factors corresponding to a plurality of historical moments includes:

[0041] determining a second influencing factor at a second predetermined time;

[0042] Determine the path index according to the predicted value of the displacement distance and the second influencing factor;

[0043] According to the power dispatching indicators, the dispatching optimization indicators of the sending-end power grid are predicted, including:

[0044] Predict dispatch optimization indicators of the sending-end power grid based on path indicators;

[0045] The dispatch optimization information of the sending-end power grid is determined according to the dispatch optimization index, including:

[0046] If the scheduling optimization index meets the third preset condition, scheduling optimization information for increasing the displacement distance of the mobile energy storage device is generated.

[0047] In some embodiments of the present specification, predicting the dispatch optimization index of the sending-end power grid according to the power dispatch index also includes:

[0048] Determine the dispatch optimization index of the sending-end power grid according to the power supply load index, power supply efficiency index and path index;

[0049] The dispatch optimization information of the sending-end power grid is determined according to the dispatch optimization index, including:

[0050] If the scheduling optimization index meets the fourth preset condition, scheduling optimization information is generated to improve the total load, displacement distance and power supply efficiency of the mobile energy storage device.

[0051] According to a second aspect of an embodiment of this specification, a device for generating dispatch optimization information of a sending-end power grid is provided, comprising:

[0052] A data acquisition module is used to determine the power dispatching data of the sending-end power grid;

[0053] A data processing module, used to determine the power dispatch index in the sending-end power grid based on the power dispatch data;

[0054] A data prediction module is used to predict the dispatch optimization index of the sending-end power grid based on the power dispatch index;

[0055] The optimization information generation module 4 is used to determine the dispatch optimization information of the sending-end power grid according to the dispatch optimization index.

[0056] According to a third aspect of an embodiment of this specification, a computing device is provided, including:

[0057] Memory and processor;

[0058] The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the above-mentioned method for generating the dispatch optimization information of the sending-end power grid are realized.

[0059] According to a fourth aspect of the embodiments of this specification, a computer-readable storage medium is provided, which stores computer-executable instructions, and when the instructions are executed by a processor, the steps of the above-mentioned method for generating the dispatch optimization information of the sending-end power grid are implemented.

[0060] According to a fifth aspect of the embodiments of this specification, a computer program is provided, wherein when the computer program is executed in a computer, the computer is caused to execute the steps of the above-mentioned method for generating the dispatch optimization information of the sending-end power grid.

[0061] An embodiment of the present specification implements a method for generating dispatch optimization information of a sending-end power grid, determines a high-dimensional power dispatch index based on the power dispatch data of the sending-end power grid, and determines a dispatch optimization index used to represent the next state of the sending-end power grid based on the high-dimensional power dispatch index. Finally, the pre-set dispatch optimization information is determined based on the dispatch optimization to provide it to the decision-makers of the sending-end power grid for reference, so as to prompt the staff of the sending-end power grid to take necessary preventive measures in a timely manner according to the upcoming power consumption defects of the power grid distribution. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 This is a flow chart of generating dispatch optimization information of a sending-end power grid provided by an embodiment of this specification;

[0063] Figure 3 It is a structural schematic diagram of a sending-end power grid dispatch optimization information generation device provided by an embodiment of this specification;

[0064] Figure 2 It is a structural block diagram of a computing device provided by an embodiment of this specification. DETAILED DESCRIPTION

[0065] Many specific details are described in the following description to facilitate a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the connotation of this specification, so this specification is not limited to the specific implementation disclosed below.

[0066] The terms used in one or more embodiments of this specification are only for the purpose of describing specific embodiments, and are not intended to limit one or more embodiments of this specification. The singular forms of "a" and "the" used in one or more embodiments of this specification and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0067] It should be understood that although the terms first, second, etc. may be used to describe various information in one or more embodiments of this specification, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of one or more embodiments of this specification, the first may also be referred to as the second, and similarly, the second may also be referred to as the first. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0068] The present invention aims to solve the problem of optimizing the scheduling of mobile energy storage vehicles affected by the uncertainty of renewable energy sources such as wind power and photovoltaic power and power load in traditional sending-end power grids.

[0069] In order to solve the above problems, a first aspect of an embodiment of this specification provides a method for generating dispatch optimization information of a sending-end power grid, comprising:

[0070] Step S1, determining the power dispatching data of the sending-end power grid;

[0071] Step S2: determining the power dispatch index of the sending-end power grid based on the power dispatch data;

[0072] Step S3, predicting the dispatch optimization index of the sending-end power grid according to the power dispatch index;

[0073] Step S4: Determine the dispatch optimization information of the sending-end power grid according to the dispatch optimization index.

[0074] In this embodiment, the sending-end power grid in the embodiment of this specification refers to a power system with a mobile energy storage device;

[0075] The power dispatching data includes: the power data that the sending-end power grid needs to supply to the main power grid to realize regional power supply, and the relevant data corresponding to the mobilization of mobile energy storage equipment in physical space; the power data includes: power load, discharge efficiency of mobile energy storage equipment and other related power consumption data;

[0076] The power dispatch index refers to the characteristic data processed based on the power dispatch data, which is used to predict the corresponding state of the power grid at the next moment;

[0077] The power dispatch optimization index refers to the data obtained through a series of data calculations based on the power dispatch data, which is used to represent the dispatch status of the sending-end power grid at the next moment;

[0078] The dispatch optimization information refers to information displayed to the staff of the corresponding sending-end power grid as a reference or used by the corresponding dispatch system for better planning the dispatch of mobile energy storage equipment in the sending-end power grid.

[0079] In step S1, the power dispatching data of the sending power grid is first collected. The power dispatching data includes the real-time data of the sending power grid, and also includes the previous power dispatching data of the sending power grid within a certain period of time. The specific time range is set according to the situation. The power dispatching data includes different data dimensions according to the data type, for example, the total load of the mobile energy storage device, the power grid load of the mobile energy storage vehicle, the discharge efficiency of the mobile energy storage vehicle, etc.

[0080] In step S2, based on the power dispatch data obtained in step S1, the power data of different dimensions are combined and calculated according to a preset combination method to determine the corresponding power dispatch index. The number and type of power dispatch indexes vary depending on the power dispatch data obtained.

[0081] In step S3, the dispatch optimization index corresponding to the sending-end power grid is calculated according to the index obtained in step S2 according to a predetermined algorithm. In some embodiments of this specification, different power dispatch data are obtained, corresponding power dispatch indexes are different, and corresponding algorithms for predicting the state of the sending-end power grid are also different.

[0082] In step S4, according to the dispatch optimization index obtained in step S3, it is determined to generate power dispatch data associated with the dispatch optimization index. According to the preset optimization logic, dispatch optimization information for optimizing the power dispatch data associated with the optimization index is generated. For example, if the corresponding dispatch optimization index is generated with a corresponding discharge efficiency, if the value of the dispatch optimization index satisfies the predetermined logic, dispatch optimization information for optimizing the discharge efficiency is generated, such as increasing the corresponding discharge efficiency or reducing the discharge efficiency.

[0083] In some embodiments of this specification, determining the power dispatching data of the sending-end power grid further includes:

[0084] Determine the power dispatch data at multiple historical moments;

[0085] Determine the impact factor at each historical moment based on the power dispatch data at each historical moment;

[0086] According to the power dispatching data corresponding to the plurality of historical moments and the influencing factors corresponding to the plurality of historical moments, first power dispatching data for the first scheduled time is determined.

[0087] In this embodiment, the first predetermined moment is the next moment after a plurality of historical moments, and the first power dispatching data is the power dispatching data corresponding to the next moment, that is, the corresponding predicted value.

[0088] First, what are the types of power dispatch data? Then, for each type of dispatch data, obtain the historical data corresponding to several previous historical moments.

[0089] Furthermore, for each historical moment, the impact factor of the corresponding moment is determined according to the moment value of the corresponding type of power dispatch data at that moment, and the maximum and minimum values ​​of each type of power dispatch data in the data corresponding to multiple historical moments. For example, suppose there is type A power dispatch data and type B power dispatch data. And there are dispatch data at 15 historical moments. To determine the impact factor of the 15th historical moment, that is, the last historical moment, it is necessary to determine the maximum and minimum values ​​of type A power dispatch data and the maximum and minimum values ​​of type B power dispatch data in these 15 historical moments respectively. Then, based on the moment value of type A power dispatch data and the moment value of type B power dispatch data at the 15th historical moment, determine the impact factor corresponding to the 15th historical moment.

[0090] After determining the corresponding impact factor at each historical moment, for each type of power dispatching data, the predicted value of each type of power dispatching data at the next moment is determined according to its corresponding data at multiple historical moments and the corresponding impact factors at multiple historical moments.

[0091] In some embodiments of the present specification, determining the power dispatch index in the sending-end power grid based on the power dispatch data includes:

[0092] The power dispatching index in the sending-end power grid is determined according to the first power dispatching data and / or the influencing factors corresponding to a plurality of historical moments.

[0093] In this embodiment, after determining the first power dispatch data corresponding to the power grid at the next moment based on the power dispatch data at multiple historical moments, the first power dispatch data of the corresponding type is combined according to the relationship between the power data of the corresponding types to generate the corresponding power dispatch index. For example, in some embodiments of this specification, the total load of the mobile energy storage device and the first power dispatch data corresponding to the load of the mobile energy storage device power grid are combined as a set of power dispatch indicators.

[0094] In some embodiments of this specification, the power dispatch data includes the total load of the mobile energy storage device and the grid load of the grid where the mobile energy storage device is located;

[0095] Determining first power dispatch data for a first scheduled time according to the power dispatch data corresponding to the plurality of historical moments and the influencing factors corresponding to the plurality of historical moments includes:

[0096] Determine a predicted value of the total load of the mobile energy storage device at a first predetermined moment according to the total load of the mobile energy storage device at multiple historical moments and the influencing factors corresponding to the multiple historical moments;

[0097] Determine a predicted value of the grid load of the grid where the mobile energy storage device is located at a first predetermined moment according to the grid load of the grid where the mobile energy storage device is located at multiple historical moments and the influencing factors corresponding to the multiple historical moments;

[0098] Determining a power dispatching index in a sending-end power grid according to the first power dispatching data and / or the influencing factors corresponding to a plurality of historical moments includes:

[0099] Determine the power supply load index based on the total load forecast value and the grid load forecast value;

[0100] According to the power dispatching indicators, the dispatching optimization indicators of the sending-end power grid are predicted, including:

[0101] Predict dispatch optimization indicators of the sending-end power grid based on power supply load indicators;

[0102] The dispatch optimization information of the sending-end power grid is determined according to the dispatch optimization index, including:

[0103] If the dispatch optimization index meets the first preset condition, dispatch optimization information for increasing the total load of the mobile energy storage device is generated.

[0104] In this embodiment, the power dispatching data includes the total load of the mobile energy storage device and the grid load of the grid where the mobile energy storage device is located, so as to determine the dispatching optimization information of the sending-end grid.

[0105] Specifically, in this embodiment, as described above, firstly, the impact factors corresponding to multiple historical moments are determined based on the total load of the mobile energy storage device and the grid load data of the grid where the mobile energy storage device is located at multiple moments.

[0106] Assume that the total load of the mobile energy storage device and the historical data of the grid load of the power grid where the mobile energy storage device is located at multiple times are expressed as follows:

[0107]

[0108] in, t s The total load of the mobile energy storage vehicle of the new sending-end power system at any moment; t s The grid load of the new sending-end power system mobile energy storage vehicle at each moment.

[0109] Furthermore, based on the total load at multiple historical moments and the corresponding grid load, the corresponding influencing factors of the total load at each historical moment and the grid load are determined. The calculation is as follows:

[0110]

[0111] Among them, H YDCN,max , H YDCN,min t 1 ,t 2 ,...,t s ,...,t n The maximum and minimum values ​​of the total load of the mobile energy storage vehicle of the new sending-end power system at the moment; DW FH,max , D.W. FH,min t 1 ,t 2 ,...,t s ,...,t n The maximum and minimum values ​​of the discharge efficiency of the mobile energy storage vehicle of the new sending-end power system at the moment, Indicates that at t s The corresponding influencing factors of the total load at each moment and the grid load.

[0112] Further, according to the total load at multiple historical moments and the power dispatching data of the power grid load, the normalized value of the total load at multiple moments and the power dispatching data of the power grid load is determined, t s The moment normalized value is calculated as follows:

[0113]

[0114] Among them, H YDCN,max , H YDCN,min t 1 ,t 2 ,...,t s ,...,t n The maximum and minimum values ​​of the total load of the mobile energy storage vehicle of the new sending-end power system at the moment; DW FH,max , D.W. FH,min t 1 ,t 2 ,...,t s ,...,t n The maximum and minimum values ​​of the discharge efficiency of the mobile energy storage vehicle of the new sending-end power system at the moment.

[0115] Based on the above calculation method, the normalized values ​​of the total load and power grid load at multiple times are obtained:

[0116]

[0117] After determining the corresponding influencing factors of the total load and grid load at each historical moment, based on the influencing factors and the corresponding power dispatching data of the total load and grid load at multiple moments, the predicted values ​​of the power dispatching data of the total load and grid load at the next moment are obtained respectively, and the calculation method is as follows:

[0118]

[0119] In the formula, t s+1 The predicted value of the total load of mobile energy storage equipment in the power grid at the sending end at any moment; t s+1 The predicted value of the grid load of the mobile energy storage device at the sending end of the grid at this moment.

[0120] Further, after obtaining t s+1 After the predicted value of the total load at the moment and the predicted value of the grid load are calculated, the corresponding power supply load index is determined based on the two:

[0121] Furthermore, the scheduling optimization index is determined based on the optimization index The calculation is as follows:

[0122] if When the first preset condition is met, dispatch optimization information for increasing the total load of the mobile energy storage device is generated.

[0123] In some embodiments of this specification, the power dispatch data includes dispatch cost and discharge efficiency of mobile energy storage equipment;

[0124] Determining first power dispatch data for a first scheduled time according to the power dispatch data corresponding to the plurality of historical moments and the influencing factors corresponding to the plurality of historical moments includes:

[0125] Determine a predicted dispatch cost value of the mobile energy storage device at a first predetermined time according to the dispatch costs of the mobile energy storage device at multiple historical times and the influencing factors corresponding to the multiple historical times; and

[0126] Determine a predicted value of the discharge efficiency of the mobile energy storage device at a first predetermined moment according to the discharge efficiency of the mobile energy storage device at multiple historical moments and the influencing factors corresponding to the mobile energy storage device at multiple historical moments;

[0127] Determining a power dispatching index in a sending-end power grid according to the first power dispatching data and / or the influencing factors corresponding to a plurality of historical moments includes:

[0128] Determine the power supply efficiency index based on the dispatch cost forecast value and the discharge efficiency forecast value;

[0129] According to the power dispatching indicators, the dispatching optimization indicators of the sending-end power grid are predicted, including:

[0130] Predict dispatch optimization indicators of the sending-end power grid based on power supply efficiency indicators;

[0131] The dispatch optimization information of the sending-end power grid is determined according to the dispatch optimization index, including:

[0132] If the scheduling optimization index meets the second preset condition, scheduling optimization information for improving the discharge efficiency of the mobile energy storage device is generated.

[0133] In this embodiment, similarly, if the power dispatching data is the dispatching cost and discharge efficiency of the mobile energy storage device, the power dispatching data of the dispatching cost and discharge efficiency of the mobile energy storage device at multiple historical moments are first determined:

[0134] Assume that the power dispatching data of the dispatching cost and discharge efficiency of mobile energy storage equipment at multiple historical moments are as follows:

[0135]

[0136] in, t s Traffic dispatching costs of mobile energy storage equipment at all times; t s The discharge efficiency of mobile energy storage devices at all times.

[0137] Furthermore, based on the dispatch costs and corresponding discharge efficiencies at multiple historical moments, the corresponding influencing factors of the dispatch costs and discharge efficiencies at each historical moment are determined. The calculation is as follows:

[0138]

[0139] Among them, C JTDQ,max , C JTDQ,min t 1 ,t 2 ,...,t s ,...,t n The maximum and minimum dispatching costs of mobile energy storage equipment at the moment; δ FDXL,max , δ FDXL,min t 1 ,t 2 ,...,t s ,...,t n The maximum and minimum values ​​of the discharge efficiency of the mobile energy storage device at the moment.

[0140] Further, according to the dispatching costs at multiple historical moments and the corresponding power dispatching data of the discharge efficiency, the normalized values ​​of the dispatching costs at multiple moments and the corresponding power dispatching data of the discharge efficiency are determined, t s The moment normalized value is calculated as follows:

[0141]

[0142] Furthermore, the normalized values ​​of the power dispatching data corresponding to the dispatching costs and the corresponding discharge efficiencies at multiple historical moments are obtained as follows:

[0143]

[0144] Furthermore, the scheduling cost and the corresponding discharge efficiency are calculated as follows:

[0145]

[0146] t s+1 The scheduling cost forecast value at time, t s+1 The predicted value of discharge efficiency at the moment.

[0147] Further, after obtaining t s+1 After calculating the predicted value of the dispatching cost and the predicted value of the discharge efficiency, the power supply efficiency is determined by the two:

[0148] Furthermore, based on the power supply efficiency index, the scheduling optimization index is determined, and the corresponding calculation method is as follows:

[0149]

[0150] Further, if When the second preset condition is met, scheduling optimization information for improving the discharge efficiency of the mobile energy storage device is generated.

[0151] In some embodiments of this specification, the power dispatch data includes the displacement distance of the mobile energy storage device;

[0152] Determining first power dispatch data for a first scheduled time according to the power dispatch data corresponding to the plurality of historical moments and the influencing factors corresponding to the plurality of historical moments includes:

[0153] Determine a predicted displacement distance of the mobile energy storage device at a first predetermined moment according to the displacement distances of the mobile energy storage device at multiple historical moments and the influencing factors corresponding to the multiple historical moments;

[0154] Determining a power dispatching index in a sending-end power grid according to the first power dispatching data and / or the influencing factors corresponding to a plurality of historical moments includes:

[0155] determining a second influencing factor at a second predetermined time;

[0156] Determine the path index according to the predicted value of the displacement distance and the second influencing factor;

[0157] According to the power dispatching indicators, the dispatching optimization indicators of the sending-end power grid are predicted, including:

[0158] Predict dispatch optimization indicators of the sending-end power grid based on path indicators;

[0159] The dispatch optimization information of the sending-end power grid is determined according to the dispatch optimization index, including:

[0160] If the scheduling optimization index meets the third preset condition, scheduling optimization information for increasing the displacement distance of the mobile energy storage device is generated.

[0161] In this embodiment, if the power dispatching data includes the displacement distance of the mobile energy storage device, the data corresponding to the displacement distance of the mobile energy storage device at multiple historical moments are determined:

[0162] Furthermore, based on the displacement distances of multiple historical moments, the impact factor of each historical moment is determined. The calculation is as follows:

[0163]

[0164] Among them, FL LX,max , F.L. LX,min t 1 ,t 2 ,...,t s ,...,t n The maximum and minimum displacement distances of the mobile energy storage device at the moment.

[0165] Further, according to the power dispatching data of displacement distances at multiple historical moments, the normalized values ​​of the power dispatching data of displacement distances at multiple moments are determined, t s The moment normalized value is calculated as follows:

[0166]

[0167] To obtain the normalized values ​​of the power dispatching data corresponding to the displacement distances at multiple historical moments, as follows:

[0168]

[0169] Furthermore, the predicted value of the displacement distance at the next moment is calculated as follows:

[0170]

[0171] That is t s+1 The displacement distance at the moment corresponds to the predicted value.

[0172] Further, after obtaining t s+1 After the displacement distance prediction value at time, determine the corresponding t s The impact factor of time, and according to t s The impact factor of time and t s+1 The displacement distance at the moment corresponds to the predicted value, and the path index is determined, namely:

[0173]

[0174] Furthermore, the scheduling optimization index is determined according to the path index

[0175]

[0176] If, if The third preset condition is met to generate scheduling optimization information for improving the displacement distance of the mobile energy storage device.

[0177] In some embodiments of the present specification, predicting the dispatch optimization index of the sending-end power grid according to the power dispatch index also includes:

[0178] Determine the dispatch optimization index of the sending-end power grid according to the power supply load index, power supply efficiency index and path index;

[0179] The dispatch optimization information of the sending-end power grid is determined according to the dispatch optimization index, including:

[0180] If the scheduling optimization index meets the fourth preset condition, scheduling optimization information is generated to improve the total load, displacement distance and power supply efficiency of the mobile energy storage device.

[0181] In this embodiment, if the power dispatching data includes the total load of the mobile energy storage device, the grid load of the grid where the mobile energy storage device is located, the dispatching cost of the mobile energy storage device, the discharge efficiency and the displacement distance of the mobile energy storage device.

[0182] Combining the above example, the power dispatch data corresponding to multiple historical moments are as follows:

[0183]

[0184] Furthermore, based on the power dispatch data at multiple historical moments, the corresponding impact factor at each moment is determined, and the calculation method is as follows:

[0185]

[0186] Furthermore, according to the power dispatching data at multiple historical moments, the normalized values ​​of the power dispatching data at multiple moments are determined, and the calculation method is as follows:

[0187]

[0188] In the formula, t s Normalized value of the total load of mobile energy storage equipment in the power grid at the sending end at the moment; t s The normalized value of the displacement distance of the mobile energy storage device in the power grid at the sending end at the moment; t s The normalized value of the traffic dispatch cost of the mobile energy storage equipment in the power grid at the power transmission end at the moment; t s The normalized value of the discharge efficiency of the mobile energy storage device in the power grid at the sending end at that moment; t s The normalized value of the power grid efficiency of the mobile energy storage device at the sending end at the moment; H YDCN,max , H YDCN,min t 1 ,t 2 ,...,t s ,...,t n The maximum and minimum values ​​of the total load of mobile energy storage equipment in the power grid at the sending end at the moment; FL LX,max , F.L. LX,min t 1 ,t 2 ,...,t s ,...,t n The maximum and minimum displacement distances of the mobile energy storage equipment in the power grid at the sending end at the moment C JTDQ,max , C JTDQ,min t 1 ,t 2 ,...,t s ,...,t n The maximum and minimum dispatching costs of mobile energy storage equipment in the power grid at the sending end at time δ FDXL,max , δ FDXL,min t 1 ,t 2 ,...,t s ,...,t n The maximum and minimum values ​​of the discharge efficiency of the mobile energy storage equipment in the sending-end power grid at the moment.

[0189] Furthermore, the predicted value of the above power dispatching data at the next moment is calculated as follows:

[0190]

[0191] In the formula, t s+1 The predicted value of the total load of mobile energy storage equipment in the power grid at the sending end at the moment, t s+1 The predicted value of the displacement distance of the mobile energy storage device in the power grid at the sending end at the moment, t s+1 The predicted value of the traffic dispatch cost of mobile energy storage equipment in the power grid at the sending end at each moment, t s+1 The predicted value of the discharge efficiency of the mobile energy storage device at the sending end of the power grid at this moment, t s+1 The predicted value of the grid load of the mobile energy storage device at the sending end of the grid at this moment.

[0192] Furthermore, after obtaining the predicted value of the power dispatching data corresponding to the next moment, referring to the above example, the power load index, power supply efficiency index and path index are determined according to the corresponding predicted value.

[0193] Furthermore, the dispatch optimization index of the sending-end power grid is determined based on the power load index, power supply efficiency index and path index. The calculation is as follows:

[0194]

[0195] Furthermore, if the dispatch optimization index of the sending-end power grid is obtained If it is greater than or equal to 0.7, it is considered that the optimal dispatching of the power grid path at the next moment meets the current load demand, ensuring the high dispatching flexibility of the mobile energy storage equipment during power grid dispatching, achieving peak load shaving and valley filling and improving the operating profit of the power system. At this time, the total load and displacement distance of the mobile energy storage equipment can be kept unchanged;

[0196] If the dispatch optimization index of the sending power grid is obtained If it is less than 0.7, it is considered that the optimal dispatching of the mobile energy storage equipment path of the sending-end power grid at the next moment does not meet the current load-side demand. At this time, the total load, displacement distance and discharge efficiency of the multi-energy mobile energy storage equipment can be increased, the traffic dispatching cost of the mobile energy storage vehicle can be reduced, and the stability of the power grid can be improved.

[0197] One embodiment of the present specification implements a method for generating dispatch optimization information of a sending-end power grid, determines a high-dimensional power dispatch index based on the power dispatch data of the sending-end power grid, and determines a dispatch optimization index used to represent the next state of the sending-end power grid based on the high-dimensional power dispatch index. Finally, the pre-set dispatch optimization information is determined based on the dispatch optimization to provide it to the decision-makers of the sending-end power grid for reference, so as to prompt the staff of the sending-end power grid to take necessary preventive measures in a timely manner according to the upcoming power consumption defects of the power grid distribution.

[0198] like Figure 2 As shown, according to the second aspect of the embodiment of this specification, a sending-end power grid dispatch optimization information generating device is provided, comprising:

[0199] Data acquisition module 1, used to determine the power dispatching data of the sending-end power grid;

[0200] Data processing module 2, used to determine the power dispatch index in the sending-end power grid based on the power dispatch data;

[0201] The data prediction module 3 is used to predict the dispatch optimization index of the sending-end power grid according to the power dispatch index;

[0202] The optimization information generation module 4 is used to determine the dispatch optimization information of the sending-end power grid according to the dispatch optimization index.

[0203] The above is a schematic scheme of a sending-end power grid dispatch optimization information generation device of this embodiment. It should be noted that the technical scheme of the sending-end power grid dispatch optimization information generation device and the technical scheme of the sending-end power grid dispatch optimization information generation method mentioned above belong to the same concept, and the details not described in detail in the technical scheme of the sending-end power grid dispatch optimization information generation device can be found in the description of the technical scheme of the sending-end power grid dispatch optimization information generation method mentioned above.

[0204] Figure 3 The structure block diagram of a computing device 300 provided according to an embodiment of the present specification is shown. The components of the computing device 300 include but are not limited to a memory 310 and a processor 320. The processor 320 is connected to the memory 310 via a bus 330, and the database 350 is used to store data.

[0205] The computing device 300 also includes an access device 340 that enables the computing device 300 to communicate via one or more networks 360. Examples of these networks include a public switched telephone network (PSTN), a local area network (LAN), a wide area network (WAN), a personal area network (PAN), or a combination of communication networks such as the Internet. The access device 340 may include one or more of any type of network interface (e.g., a network interface card (NIC)) that is wired or wireless, such as an IEEE 802.11 wireless local area network (WLAN) wireless interface, a world-wide interoperability for microwave access (Wi-MAX) interface, an Ethernet interface, a universal serial bus (USB) interface, a cellular network interface, a Bluetooth interface, and a near field communication (NFC).

[0206] In one embodiment of the present specification, the above components of the computing device 300 and Figure 3 Other components not shown in the figure may also be connected to each other, for example, via a bus. It should be understood that Figure 3 The computing device structure block diagram shown is only for the purpose of illustration, and is not intended to limit the scope of this specification. Those skilled in the art can add or replace other components as needed.

[0207] The computing device 300 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., a tablet computer, a personal digital assistant, a laptop computer, a notebook computer, a netbook, etc.), a mobile phone (e.g., a smart phone), a wearable computing device (e.g., a smart watch, smart glasses, etc.), or other types of mobile devices, or a stationary computing device such as a desktop computer or a personal computer (PC). The computing device 300 may also be a mobile or stationary server.

[0208] Among them, the processor 320 is used to execute the following computer executable instructions, which, when executed by the processor, implement the steps of generating the above-mentioned dispatch optimization information of the sending-end power grid. The above is a schematic scheme of a computing device of this embodiment. It should be noted that the technical scheme of the computing device and the above-mentioned technical scheme for generating dispatch optimization information of the sending-end power grid belong to the same concept. For the details not described in detail in the technical scheme of the computing device, please refer to the description of the technical scheme for generating dispatch optimization information of the sending-end power grid.

[0209] An embodiment of the present specification further provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-mentioned steps of generating the dispatch optimization information of the sending-end power grid.

[0210] The above is a schematic scheme of a computer-readable storage medium of this embodiment. It should be noted that the technical scheme of the storage medium and the technical scheme of generating the dispatch optimization information of the sending-end power grid belong to the same concept, and the details not described in detail in the technical scheme of the storage medium can be referred to the description of the technical scheme of generating the dispatch optimization information of the sending-end power grid.

[0211] An embodiment of the present specification further provides a computer program, wherein when the computer program is executed in a computer, the computer is instructed to execute the above-mentioned steps of generating the dispatch optimization information of the sending-end power grid.

[0212] The above is a schematic scheme of a computer program of this embodiment. It should be noted that the technical scheme of the computer program and the technical scheme of generating the dispatch optimization information of the sending-end power grid belong to the same concept, and the details not described in detail in the technical scheme of the computer program can be referred to the description of the technical scheme of generating the dispatch optimization information of the sending-end power grid.

[0213] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0214] Computer instructions include computer program codes, which may be in source code form, object code form, executable files or some intermediate form, etc. Computer readable media may include: any entity or device capable of carrying computer program codes, recording media, USB flash drives, mobile hard disks, magnetic disks, optical disks, computer memories, read-only memories (ROM), random access memories (RAM), electric carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content contained in computer readable media may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer readable media do not include electric carrier signals and telecommunication signals.

[0215] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the embodiments of this specification are not limited by the order of the actions described, because according to the embodiments of this specification, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the embodiments of this specification.

[0216] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0217] The preferred embodiments of this specification disclosed above are only used to help explain this specification. The optional embodiments do not describe all the details in detail, nor do they limit the invention to specific implementation methods. Obviously, many modifications and changes can be made according to the content of the embodiments of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the embodiments of this specification, so that those skilled in the art can understand and use this specification well. This specification is limited only by the claims and their full scope and equivalents.

Claims

1. A method for generating dispatch optimization information of a sending-end power grid, characterized in that: include: Determining power dispatching data of the sending-end power grid; Determining a power dispatching index of the sending-end power grid based on the power dispatching data; Predicting a dispatch optimization index of the sending-end power grid according to the power dispatch index; The dispatch optimization information of the sending-end power grid is determined according to the dispatch optimization index.

2. The method according to claim 1, characterized in that The determining of the power dispatching data of the sending-end power grid also includes: Determine the power dispatch data at multiple historical moments; Determine the impact factor at each historical moment based on the power dispatch data at each historical moment; According to the power dispatching data corresponding to the plurality of historical moments and the influencing factors corresponding to the plurality of historical moments, first power dispatching data for a first scheduled time is determined.

3. The method according to claim 2, characterized in that The determining of the power dispatch index in the sending-end power grid based on the power dispatch data includes: The power dispatching index in the sending-end power grid is determined according to the first power dispatching data and / or the influencing factors corresponding to the multiple historical moments.

4. The method according to claim 3, characterized in that The power dispatching data includes the total load of the mobile energy storage device and the grid load of the grid where the mobile energy storage device is located; The determining of first power dispatching data for a first predetermined time according to the power dispatching data corresponding to the plurality of historical moments and the influencing factors corresponding to the plurality of historical moments comprises: Determine a predicted value of the total load of the mobile energy storage device at a first predetermined moment according to the total load of the mobile energy storage device at multiple historical moments and the influencing factors corresponding to the multiple historical moments; Determine a predicted value of the grid load of the grid where the mobile energy storage device is located at a first predetermined moment according to the grid load of the grid where the mobile energy storage device is located at the multiple historical moments and the influencing factors corresponding to the multiple historical moments; The determining of the power dispatching index in the sending-end power grid according to the first power dispatching data and / or the influencing factors corresponding to the plurality of historical moments includes: Determine the power supply load index according to the total load forecast value and the power grid load forecast value; The predicting of the dispatch optimization index of the sending-end power grid according to the power dispatch index includes: Predicting a dispatch optimization index of the sending-end power grid according to the power supply load index; The step of determining the dispatch optimization information of the sending-end power grid according to the dispatch optimization index includes: If the scheduling optimization index meets the first preset condition, scheduling optimization information for increasing the total load of the mobile energy storage device is generated.

5. The method according to claim 3, characterized in that: The power dispatching data includes dispatching cost and discharge efficiency of mobile energy storage equipment; The determining of first power dispatching data for a first predetermined time according to the power dispatching data corresponding to the plurality of historical moments and the influencing factors corresponding to the plurality of historical moments comprises: Determine a predicted value of the dispatch cost of the mobile energy storage device at a first predetermined moment according to the dispatch costs of the mobile energy storage device at the plurality of historical moments and the influencing factors corresponding to the plurality of historical moments; and Determine a predicted value of the discharge efficiency of the mobile energy storage device at a first predetermined moment according to the discharge efficiency of the mobile energy storage device at the plurality of historical moments and the influencing factors corresponding to the mobile energy storage device at the plurality of historical moments; The determining of the power dispatching index in the sending-end power grid according to the first power dispatching data and / or the influencing factors corresponding to the plurality of historical moments includes: Determine a power supply efficiency index according to the scheduling cost prediction value and the discharge efficiency prediction value; The predicting of the dispatch optimization index of the sending-end power grid according to the power dispatch index includes: Predicting a dispatch optimization index of the sending-end power grid according to the power supply efficiency index; The step of determining the dispatch optimization information of the sending-end power grid according to the dispatch optimization index includes: If the scheduling optimization index meets the second preset condition, scheduling optimization information for improving the discharge efficiency of the mobile energy storage device is generated.

6. The method according to claim 3, characterized in that The power dispatching data includes the displacement distance of the mobile energy storage device; The determining of first power dispatching data for a first predetermined time according to the power dispatching data corresponding to the plurality of historical moments and the influencing factors corresponding to the plurality of historical moments comprises: Determine a predicted displacement distance of the mobile energy storage device at a first predetermined moment according to the displacement distances of the mobile energy storage device at multiple historical moments and the influencing factors corresponding to the multiple historical moments; The determining of the power dispatching index in the sending-end power grid according to the first power dispatching data and / or the influencing factors corresponding to the plurality of historical moments includes: determining a second influencing factor at a second predetermined time; Determine a path index according to the displacement distance prediction value and the second influencing factor; The predicting of the dispatch optimization index of the sending-end power grid according to the power dispatch index includes: Predicting a dispatch optimization index of the sending-end power grid according to the path index; The step of determining the dispatch optimization information of the sending-end power grid according to the dispatch optimization index includes: If the scheduling optimization index satisfies a third preset condition, scheduling optimization information for increasing the displacement distance of the mobile energy storage device is generated.

7. The method according to any one of claims 4 to 6, characterized in that: The predicting of the dispatch optimization index of the sending-end power grid according to the power dispatch index further includes: Determining the dispatch optimization index of the sending-end power grid according to the electric load index, the power supply efficiency index and the path index; The step of determining the dispatch optimization information of the sending-end power grid according to the dispatch optimization index includes: If the scheduling optimization index meets the fourth preset condition, scheduling optimization information for improving the total load, displacement distance and power supply efficiency of the mobile energy storage device is generated.

8. A device for generating dispatch optimization information of a sending-end power grid, characterized in that: include: A data acquisition module is used to determine the power dispatching data of the sending-end power grid; A data processing module, used to determine the power dispatch index in the sending-end power grid based on the power dispatch data; A data prediction module, used to predict the dispatch optimization index of the sending-end power grid according to the power dispatch index; The dispatch optimization information of the sending-end power grid is determined according to the dispatch optimization index.

9. A computing device, characterized in that include: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the method for generating sending-end power grid dispatch optimization information as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the method for generating dispatch optimization information of a sending-end power grid as described in any one of claims 1 to 7.

Images