CN113393123A - Power supply vehicle rescue scheduling optimization method with few vehicles and multiple accident points - Google Patents
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Abstract
The invention discloses a power supply vehicle rescue scheduling optimization method with few vehicles and multiple accident points, which comprises the following steps: the method comprises the steps of obtaining the number of available power vehicles, obtaining the position coordinates of accident points, calculating the residual fuel reserves of the power vehicles, calculating the power shortage of the accident points, setting the constraint conditions of scheduling optimization problems by taking the minimum loss value of the accident points as an optimization target, and searching and solving the optimization problems based on a genetic algorithm.
Description
Technical Field
The invention relates to the technical field of power supply vehicle rescue, in particular to a power supply vehicle rescue scheduling optimization method with few vehicles and multiple accident points.
Background
Since the electric age, the use of electricity has become something that we cannot lose in life; in the current society, a lot of equipment needs to be kept running by electricity, however, in recent years, a series of major power failure accidents occurring at home and abroad not only cause serious economic loss, but also cause great influence on the society and even cause casualties, so that the occurrence of the mobile power supply vehicle effectively relieves the situation, and the accompanying optimization of power supply vehicle dispatching correspondingly becomes a key problem of improving rescue efficiency and reducing economic loss; although various technical methods are used for power supply vehicle rescue scheduling, most of the technical methods are dedicated to distribution scheduling under the condition of sufficient quantity of power supply vehicles, and the condition that the quantity of the power supply vehicles of a power supply station is insufficient is ignored. That is, when there are many accident points and the number of power source vehicles available for emergency rescue is small, how to efficiently perform rescue and reduce economic loss as much as possible becomes a problem to be solved.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention aims to provide a power supply vehicle rescue scheduling optimization method with few vehicles and multiple accident points.
The invention is realized by adopting the following technical method:
a power supply vehicle rescue scheduling optimization method with few vehicles and multiple accident points comprises the following steps:
step 1: obtaining: the method comprises the steps of obtaining the number of remaining available power supply vehicles of a power supply station, classifying the power supply vehicles according to the capacity of an oil tank of the power supply vehicles, then obtaining corresponding position coordinates of each accident point, calculating a position distance matrix between the accident points and a time matrix consumed by the power supply vehicles between every two accident points, and finally recording and analyzing the power shortage of each accident point and the generated energy meeting the normal power supply requirement of the accident point within unit time of the accident point to conjecture the oil consumption required by the power supply vehicles at the accident point;
step 2: and (3) calculating: after the initial data is obtained, a model of power supply vehicle dispatching is established by taking the minimum value of the accident point loss as a target, because the dispatching of the power supply vehicle is different from the dispatching of vehicles in terms of logistics, for the power failure accident belongs to the emergency, therefore, the emergency degree formula (2) of the accident place is introduced, because one power failure accident can cause great influence, the design formulates reasonable weight and numerical value from three aspects of life safety influence, economic influence and special influence in combination with practical situation, then calculates the power failure loss of unit power in unit time according to the basic power failure loss of unit power in unit time of the accident point, and can cause far accident point because the distance is different because the position of the accident point is different, the emergency degree is high, the emergency degree is close to the accident point, and the emergency degree is low, so the design comprehensively considers the time of reaching each accident point and the emergency degree of each accident point;
and step 3: and (3) constraint: performing basic assumption and adding corresponding constraint conditions on the model according to the actual situation, wherein each vehicle starts from a power supply station and finally returns to the garage after passing through an accident point, the back-and-forth distance between every two accident places is unchanged, and one accident point is only rescued once; the oil consumption required by power supply of each accident point is kept to be smaller than the capacity of an oil tank of the power supply vehicle; the number of the required power supply vehicles is less than that of the power supply vehicles which can be normally used;
and 4, step 4: and (3) analysis: the method comprises the steps of carrying out example analysis, selecting a proper optimization algorithm to carry out optimization solution on the model, and selecting the genetic algorithm to carry out power supply vehicle scheduling planning in consideration of the characteristics of wide application range, strong group search performance, good expandability and the like of the genetic algorithm.
The beneficial technical effects of the invention are as follows: the method can compare the capacity of the oil tank required by the normal power supply of the power shortage power in the power failure time according to the capacity of the oil tank of the power supply vehicle and the capacity of the oil tank required by the maintenance of the accident point, plan out a corresponding accident point path and the number and the types of the power supply vehicles required to be dispatched, and solve out an optimal rescue path and a minimum loss value caused by the power failure accident at the accident point by utilizing the genetic algorithm.
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FIG. 1 is a flow process diagram of the present invention;
FIG. 2 is a flow chart of a genetic algorithm processing the model.
Detailed Description
The following description of the embodiments is intended to better explain the present invention and should not be taken as limiting the invention, and any changes in the definition of the process or the technical features and/or in the form of a whole framework rather than in the nature of a whole framework should be considered as the protection scope defined by the technical method of the present invention.
Fig. 1 shows a power supply vehicle rescue scheduling method based on different fuel tank storage margins of a genetic algorithm, which includes the following steps:
step 1: the method comprises the steps of obtaining the number of remaining available power supply vehicles of a power supply station, classifying the power supply vehicles according to the capacity of an oil tank of the power supply vehicles, then obtaining corresponding position coordinates of each accident point, calculating a position distance matrix between the accident points and a time matrix consumed by the power supply vehicles between every two accident points, and finally recording and analyzing the power shortage of each accident point and the generated energy meeting the normal power supply requirement of the accident point within unit time of the accident point to conjecture the oil consumption required by the power supply vehicles at the accident point;
step 2: after initial data is obtained, a power supply vehicle dispatching model is established by taking the minimum value of the loss of the accident point as a target, because the dispatching of the power supply vehicle is different from the dispatching of vehicles in the aspect of logistics, and the power failure accident belongs to an emergency, an emergency degree formula (2) of the accident point is introduced, because a power failure accident can cause great influence, the design makes reasonable weight and numerical value by combining the three aspects of life safety influence, economic influence and special influence and the practical situation, and then the power failure loss of unit power in unit time is calculated according to the basic power failure loss of unit power in unit time of the accident point, and because the positions of the accident point are different, the distance is different, the situations of far accident point, high emergency degree, near accident point and low emergency degree can be caused, so the design comprehensively considers the time reaching each accident point and the emergency degree of each accident point, an objective function is established as follows (1):
Sj＝Ij(wααj+wββj+wrrj)，(2)
wα+wβ+wr＝1(3)
wherein: j-represents the accident point number; n represents the total number of accident points;
-representing the cumulative time from the garage departure to the point of accident; alpha is alphajRepresenting the degree of impact on life safety after loss of power at the accident site, betajRepresenting the degree of impact on the regional economy after loss of power at the accident site, rj-indicating the degree of specific influence upon loss of power at the accident site; sj-loss of blackout per unit of power per unit of time representing the point of accident;
pj-the power shortage at the accident point j; i isj-a loss of a basic outage per unit of power per unit of time at the point of accident j; w is aα-a life safety impact weight; w is aβ-an economic impact weight; w is ar-a specificity impact weight; formula (3) is that the sum of the weighted values is one;
and step 3: and (3) constraint: performing basic assumption and adding corresponding constraint conditions on the model according to the actual situation, wherein each vehicle starts from a power supply station and finally returns to the garage after passing through an accident point, the back-and-forth distance between every two accident places is unchanged, and one accident point is only rescued once; the oil consumption required by power supply of each accident point is kept to be smaller than the capacity of an oil tank of the power supply vehicle; the number of the required power supply vehicles is less than that of the power supply vehicles which can be normally used;
and 4, step 4: the method comprises the steps of carrying out example analysis, obtaining required parameter values, carrying out initial processing on the parameter values, selecting a proper algorithm to carry out optimization solution on the examples, and considering the characteristics of wide application range, strong group search performance, good expandability and the like of the genetic algorithm, therefore, the genetic algorithm is selected to carry out continuous iteration optimization on the obtained path population, the optimal path and the minimum loss value are continuously updated, and the power supply vehicle scheduling planning is displayed until traversal is finished or the optimal solution is found.
As shown in fig. 2, the flow of simulation solution of the problem by using a genetic algorithm is implemented, after comparing the capacity of an oil tank of a power supply vehicle with the oil tank maintenance power generation amount required by an accident point on a path, determining the types and the number of vehicles which need to be dispatched for rescue in the rescue, and performing operations such as encoding, decoding, selecting, crossing, and mutating on a generated path population, and continuously iterating until an iteration termination condition is met, and calculating the minimum loss value of the accident point and an optimal path.
In the embodiment, the capacity of an oil tank of the power supply vehicle is compared with the quantity of a power supply oil tank required by an accident point on a path, if the quantity of the oil tank required to maintain power generation is larger than the maximum oil tank reserve quantity of the power supply vehicle, no new accident point is added on the path, and a new power supply vehicle is generated to continuously optimize the rest accident point; if the quantity of the oil tanks required to maintain power generation is smaller than the maximum oil tank reserve quantity of the power supply vehicle, accident points need to be added to the path, path population is continuously and iteratively optimized through a genetic algorithm, and finally an optimal scheduling method and path planning of the emergency power supply vehicle are obtained.
The present invention is capable of other embodiments, and various changes and modifications may be made by one skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (1)
1. A power supply vehicle rescue scheduling optimization method with few vehicle accident points is characterized by comprising the following steps:
step 1: obtaining: the method comprises the steps of obtaining the number of remaining available power supply vehicles of a power supply station, classifying the power supply vehicles according to the capacity of an oil tank of the power supply vehicles, then obtaining corresponding position coordinates of each accident point, calculating a position distance matrix between the accident points and a time matrix consumed by the power supply vehicles between every two accident points, and finally recording and analyzing the power shortage of each accident point and the generated energy meeting the normal power supply requirement of the accident point within unit time of the accident point to conjecture the oil consumption required by the power supply vehicles at the accident point;
step 2: and (3) calculating: after the initial data is obtained, a model of power supply vehicle dispatching is established by taking the minimum value of the accident point loss as a target, because the dispatching of the power supply vehicle is different from the dispatching of vehicles in terms of logistics, for the power failure accident, which belongs to the emergency, the emergency degree formula of the accident place is introduced, because one power failure accident can cause great influence, the design formulates reasonable weight and numerical value from three aspects of life safety influence, economic influence and special influence in combination with practical situation, then calculates the power failure loss of unit power in unit time according to the basic power failure loss of unit power in unit time of the accident point, and can cause far accident point because the distance is different because the position of the accident point is different, the emergency degree is high, the emergency degree is close to the accident point, and the emergency degree is low, so the design comprehensively considers the time of reaching each accident point and the emergency degree of each accident point;
and step 3: and (3) constraint: performing basic assumption and adding corresponding constraint conditions on the model according to the actual situation, wherein each vehicle starts from a power supply station and finally returns to the garage after passing through an accident point, the back-and-forth distance between every two accident places is unchanged, and one accident point is only rescued once; the oil consumption required by power supply of each accident point is kept to be smaller than the capacity of an oil tank of the power supply vehicle; the number of the required power supply vehicles is less than that of the power supply vehicles which can be normally used;
and 4, step 4: and (3) analysis: the method comprises the steps of carrying out example analysis, selecting a proper optimization algorithm to carry out optimization solution on the model, and selecting the genetic algorithm to carry out power supply vehicle scheduling planning in consideration of the characteristics of wide application range, strong group search performance, good expandability and the like of the genetic algorithm.
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| CN114243901A (en) * | 2021-11-12 | 2022-03-25 | 国网浙江省电力有限公司杭州供电公司 | Urban power grid fault rapid response system and method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114243901A (en) * | 2021-11-12 | 2022-03-25 | 国网浙江省电力有限公司杭州供电公司 | Urban power grid fault rapid response system and method |
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