Method and device for improving resilience of electric-gas integrated energy system based on compressor scheduling

Abstract

A method and device for improving resilience of an electric-gas integrated energy system based on compressor scheduling, the method constructs an operation model of the mobile compressor by analyzing the working characteristics and connection characteristics of the mobile compressor according to the actual working process of the mobile compressor; constructs a scheduling model of the mobile compressor by analyzing the role of the mobile compressor in the fault recovery process of the electric-gas integrated energy system after its introduction; constructs an operation model of the electric-gas integrated energy system according to the set constraints; and comprehensively solves all fault scenarios with the goal of minimizing the weighted load removal amount in the system after the fault, and obtains the prevention strategy of the electric-gas integrated energy system in the full fault scenario and the fault recovery strategy in the set scenario. According to the present invention, after an extreme weather event strikes, the mobile compressor will be used as a temporary branch to connect the gas grid island with the gas source, minimize the weighted load removal amount, and improve the resilience level of the system.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system operation and optimization, and specifically relates to a method and device for improving the resilience of an electric-gas integrated energy system based on compressor scheduling. Background Art

[0002] With the widespread use of gas turbines (GT) and electric-driven gas compressors, the coupling between the power distribution system (PDS) and the natural gas system (NGS) has become increasingly tight, forming an integrated electric-gas energy system (IEGS). On the one hand, IEGS can provide customers with efficient, clean and sustainable energy. On the other hand, the tight coupling between PDS and NGS also poses great challenges to the reliable and safe operation of IEGS under extreme weather events, such as hurricanes, which usually cause severe damage to critical infrastructure and lead to long power outages. At present, considerable progress has been made in improving the disaster resilience of IEGS, and potential measures can be categorized as network reinforcement measures and smart operation strategies. Network reinforcement measures are usually adopted several days before extreme weather events to strengthen weak links in IEGS, such as transmission lines and gas pipelines. Smart operation strategies are implemented from a few hours before the event until the end of the event, with the aim of facilitating emergency response and rapid recovery of the integrated energy system. These strategies include the dispatch of maintenance personnel, the opening and closing operation of remote switches or remote valves, active islanding, etc.

[0003] A mobile compressor is a flexible and mobile device in the natural gas system. It is usually deployed at the fault location before maintenance personnel repair the faulty gas pipeline to recover natural gas from the faulty pipeline. At the same time, the mobile compressor can also serve as a flexible and resilient resource for the natural gas system. After an extreme weather event hits the IEGS, it can quickly respond in the area affected by the system fault, reduce the scope of the natural gas system fault, and improve the resilience of the system. Usually, the mobile compressor includes two ports, a suction port and a venting port, and both ports can be quickly connected to the reserved exhaust port of the gas pipeline. In addition, the mobile compressor is installed on a trailer, has strong mobility, and can be flexibly mobilized between different locations in the system. When working, the suction end and the venting end of the mobile compressor are respectively connected to different pipelines or nodes, and the air pressure of the suction port and the venting port is set to remain unchanged. If the gas pressure of the target pipeline or node is higher than the gas pressure of the extraction port or lower than the gas pressure of the venting port, the mobile compressor can operate normally, continuously extract natural gas from a gas pipeline or a gas network node, and after consuming part of it to maintain the normal operation of the mobile compressor, the remaining natural gas is transported to the adjacent pipeline or node. When an extreme weather event hits IEGS, quickly dispatching the mobile compressor to the faulty gas pipeline or the gas network island formed by the fault can reduce the natural gas load shedding caused by the interruption of natural gas supply and accelerate the system failure recovery.

[0004] Therefore, it is necessary to consider the flexible scheduling process of mobile compressors within the integrated energy system to improve the resilience level of IEGS. Summary of the invention

[0005] To this end, the present invention provides a method and device for improving the resilience of an electric-gas integrated energy system based on compressor scheduling, which can ensure that the electric-gas integrated energy system determines the initial position of the mobile compressor before a failure, and prepares for the upcoming extreme weather events. After an extreme weather event strikes, the mobile compressor will serve as a temporary branch to connect the gas grid island with the gas source, minimize the weighted load removal, and improve the system resilience level.

[0006] In order to achieve the above object, the present invention provides the following technical solution: a chemical synthesis route ranking analysis method, comprising:

[0007] According to the actual working process of the mobile compressor, by analyzing the working characteristics and connection characteristics of the mobile compressor, an operation model of the mobile compressor is constructed;

[0008] By analyzing the role of the mobile compressor in the fault recovery process of the electric-gas integrated energy system after its introduction, a scheduling model of the mobile compressor is constructed;

[0009] According to the set constraints, an operation model of the electricity-gas integrated energy system is constructed; the constraints of the operation model of the electricity-gas integrated energy system include power flow constraints of the distribution network, node voltage constraints, upper and lower limit constraints of unit output, power flow constraints of the natural gas network, node gas pressure constraints, upper and lower limit constraints of gas well output, and gas network pipe storage and utilization constraints;

[0010] Taking minimizing the weighted load removal in the system after a fault as the objective function, a comprehensive solution is given to all fault scenarios to obtain the prevention strategy of the electric-gas integrated energy system in all fault scenarios and the fault recovery strategy in the set scenario.

[0011] As a preferred solution of the method for improving the resilience of the electric-gas integrated energy system based on compressor scheduling, constructing the operation model of the mobile compressor includes constructing a connection model of the mobile compressor and constructing a working model of the mobile compressor;

[0012] The connection model of the mobile compressor is constructed by formulas (1)-(7):

[0013]

[0014] In the formula, is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the pipeline mn under the fault scenario s at time t. If so, it is 1;

[0015] is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1;

[0016] is a 0-1 variable, indicating whether the discharge end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1;

[0017] V mn,s,t is the internal pipe inventory of the natural gas system pipeline mn under the fault scenario s at time t; f mn,s is a 0-1 constant, indicating whether the pipeline mn is faulty in fault scenario s, if so, it is 1;

[0018] D is the square of the maximum connection distance of the mobile compressor; MC is the total number of mobile compressors in the system; M is an infinite positive number; x mn ,y mn is the horizontal coordinate / vertical coordinate of the system pipeline mn; x m ,y m is the horizontal coordinate / vertical coordinate of the system node m; N is the set of all gas network nodes in the system; L is the set of all gas pipelines in the system; Ω mc is the set of all mobile compressors in the system; s is the index of different fault scenarios; t is the index of each time period in the post-fault stage;

[0019] The working model of the mobile compressor is constructed by formulas (8)-(15):

[0020]

[0021] In the formula, is the air flow rate extracted from pipeline mn by the extraction end of mobile compressor c under fault scenario s at time t; is the air flow rate of the mobile compressor c pumping end from node n under fault scenario s at time t; is the natural gas consumption of mobile compressor c under fault scenario s at time t; is the air flow rate from the air discharge end of mobile compressor c to node n under fault scenario s at time t;

[0022] α mn,s,t It is a 0-1 variable, indicating whether the gas pressure of the natural gas system pipeline mn under the fault scenario s at time t meets the pumping requirements of the mobile compressor. If yes, it is 1;

[0023] κ n,s,t is a 0-1 variable, indicating whether the gas pressure at node n of the natural gas system under fault scenario s at time t meets the pumping requirements of the mobile compressor. If yes, it is 1;

[0024] β n,s,t is a 0-1 variable, indicating whether the gas pressure at node n of the natural gas system under fault scenario s at time t meets the requirements for the mobile compressor to bleed gas. If yes, it is 1;

[0025] Π mn,s,t is the gas pressure of the natural gas system pipeline mn under fault scenario s at time t; n,s,t is the gas pressure of node n in the natural gas system under fault scenario s at time t; cha / Π dis They are respectively the minimum suction pressure / maximum discharge pressure of the mobile compressor; are the minimum / maximum values ​​of the natural gas flow through the mobile compressor; θ is the natural gas consumption coefficient of the mobile compressor; M is an infinite positive number; mn is the index of each gas pipeline; n is the index of each gas network node; c is the index of each mobile compressor, s is the index of each fault scenario; and t is the index of each time period in the post-fault stage.

[0026] As a preferred solution of the method for improving the resilience of the electric-gas integrated energy system based on compressor scheduling, constructing the scheduling model of the mobile compressor includes constructing the pre-fault stage pre-configuration constraints of the mobile compressor and constructing the post-fault stage scheduling constraints of the mobile compressor;

[0027] Through formulas (16)-(18), the pre-fault stage mobile compressor pre-configuration constraints are constructed:

[0028]

[0029] In the formula, is the square of the maximum connection distance of the mobile compressor; M is an infinite positive number; N is the set of all gas network nodes in the system; x m ,y m is the abscissa / ordinate of the system node m; c is the index of each mobile compressor;

[0030] Through formulas (19)-(21), the mobile compressor scheduling constraints in the post-fault stage are constructed:

[0031]

[0032] In the formula, is the time required for the mobile compressor to move from pipeline mn to pipeline op; is the time required for the mobile compressor to move from pipeline mn to node o;

[0033] is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the pipeline mn under the fault scenario s at time t. If so, it is 1;

[0034] is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1;

[0035] is a 0-1 variable, indicating whether the discharge end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1;

[0036] t R is the total number of time periods in the post-fault stage; M is an infinite positive number; N is the set of all gas network nodes in the system; L is the set of all gas pipelines in the system; c is the index of each mobile compressor; s is the index of each fault scenario; t is the index of each time period in the post-fault stage.

[0037] As the optimal solution for improving the resilience of the electric-gas integrated energy system based on compressor scheduling, the objective function expression for comprehensive solution of all fault scenarios is:

[0038]

[0039] Where Δt is the duration of each period in the post-fault stage; ω j ,ω n are the weights of the grid nodes and gas grid nodes respectively; are the amount of power load removal on grid node j and the amount of natural gas load removal on gas grid node n in the post-fault stage under fault scenario s at time t, respectively; s is the occurrence probability of scene s; W s For penalty items.

[0040] As a preferred solution for improving the resilience of the electric-gas integrated energy system based on compressor scheduling, the penalty term in the objective function is constructed through formulas (23)-(26):

[0041]

[0042] In the formula, ω a ,ω b ,ω0 are the penalty terms W a,s ,W b,s ,W 0,s The coefficient of c,s,t , is a 0-1 vector, reflecting the connection relationship between the mobile compressor c and all nodes in the system under the fault scenario s at time t; c,s,t is a 0-1 vector, reflecting the connection relationship between the mobile compressor c and all pipelines in the system under the fault scenario s at time t; X P is the distance matrix between any two pipelines in the natural gas system; X N is the distance matrix between any two nodes in the natural gas system; L is the set of all gas pipelines in the system; Ω mc is the collection of all mobile compressors in the system; Ω T is the set of all time periods in the post-fault phase; s is the index of different fault scenarios.

[0043] The present invention also provides a device for improving the resilience of an electric-gas integrated energy system based on compressor scheduling, which adopts the above-mentioned method for improving the resilience of an electric-gas integrated energy system based on compressor scheduling, comprising:

[0044] A mobile compressor operation model building module, used to build an operation model of the mobile compressor by analyzing the working characteristics and connection characteristics of the mobile compressor according to the actual working process of the mobile compressor;

[0045] A scheduling model building module for a mobile compressor, used to build a scheduling model for the mobile compressor by analyzing the role of the mobile compressor in the fault recovery process of the electric-gas integrated energy system after its introduction;

[0046] An electricity-gas integrated energy system operation model construction module is used to construct an electricity-gas integrated energy system operation model according to set constraints; the constraints of the electricity-gas integrated energy system operation model include distribution network flow constraints, node voltage constraints, unit output upper and lower limit constraints, natural gas network flow constraints, node gas pressure constraints, gas well output upper and lower limit constraints and gas network pipe storage and utilization constraints;

[0047] The prevention strategy and recovery strategy acquisition module is used to comprehensively solve the full fault scenario with the goal of minimizing the weighted load removal in the system after the fault, and obtain the prevention strategy of the electric-gas integrated energy system in the full fault scenario and the fault recovery strategy in the set scenario.

[0048] As a preferred solution for the resilience enhancement device of the electric-gas integrated energy system based on compressor scheduling, in the operation model construction module of the mobile compressor, constructing the operation model of the mobile compressor includes constructing a connection model of the mobile compressor and constructing a working model of the mobile compressor;

[0049] The connection model of the mobile compressor is constructed by formulas (1)-(7):

[0050]

[0051]

[0052] In the formula, is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the pipeline mn under the fault scenario s at time t. If so, it is 1;

[0053] is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1;

[0054] is a 0-1 variable, indicating whether the discharge end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1;

[0055] V mn,s,t is the internal pipe inventory of the natural gas system pipeline mn under the fault scenario s at time t; f mn,s is a 0-1 constant, indicating whether the pipeline mn is faulty in fault scenario s, if so, it is 1;

[0056] D is the square of the maximum connection distance of the mobile compressor; MC is the total number of mobile compressors in the system; M is an infinite positive number; x mn ,y mn is the horizontal coordinate / vertical coordinate of the system pipeline mn; x m ,y mis the horizontal coordinate / vertical coordinate of the system node m; N is the set of all gas network nodes in the system; L is the set of all gas pipelines in the system; Ω mc is the set of all mobile compressors in the system; s is the index of different fault scenarios; t is the index of each time period in the post-fault stage;

[0057] The working model of the mobile compressor is constructed by formulas (8)-(15):

[0058]

[0059]

[0060] In the formula, is the air flow rate extracted from pipeline mn by the extraction end of mobile compressor c under fault scenario s at time t; is the air flow rate of the mobile compressor c pumping end from node n under fault scenario s at time t; is the natural gas consumption of mobile compressor c under fault scenario s at time t; is the air flow rate from the air discharge end of mobile compressor c to node n under fault scenario s at time t;

[0061] α mn,s,t It is a 0-1 variable, indicating whether the gas pressure of the natural gas system pipeline mn under the fault scenario s at time t meets the pumping requirements of the mobile compressor. If yes, it is 1;

[0062] κ n,s,t is a 0-1 variable, indicating whether the gas pressure at node n of the natural gas system under fault scenario s at time t meets the pumping requirements of the mobile compressor. If yes, it is 1;

[0063] β n,s,t is a 0-1 variable, indicating whether the gas pressure at node n of the natural gas system under fault scenario s at time t meets the requirements for the mobile compressor to bleed gas. If yes, it is 1;

[0064] Π mn,s,t is the gas pressure of the natural gas system pipeline mn under fault scenario s at time t; n,s,t is the gas pressure of node n in the natural gas system under fault scenario s at time t; cha / Π dis They are respectively the minimum suction pressure / maximum discharge pressure of the mobile compressor; are the minimum / maximum values ​​of the natural gas flow through the mobile compressor; θ is the natural gas consumption coefficient of the mobile compressor; M is an infinite positive number; mn is the index of each gas pipeline; n is the index of each gas network node; c is the index of each mobile compressor, s is the index of each fault scenario; and t is the index of each time period in the post-fault stage.

[0065] As a preferred solution for the resilience improvement device of the electric-gas integrated energy system based on compressor scheduling, in the scheduling model construction module of the mobile compressor, constructing the scheduling model of the mobile compressor includes constructing the pre-fault stage pre-configuration constraints of the mobile compressor and constructing the post-fault stage scheduling constraints of the mobile compressor;

[0066] Through formulas (16)-(18), the pre-fault stage mobile compressor pre-configuration constraints are constructed:

[0067]

[0068] In the formula, is the square of the maximum connection distance of the mobile compressor; M is an infinite positive number; N is the set of all gas network nodes in the system; x m ,y m is the abscissa / ordinate of the system node m; c is the index of each mobile compressor;

[0069] Through formulas (19)-(21), the mobile compressor scheduling constraints in the post-fault stage are constructed:

[0070]

[0071] In the formula, is the time required for the mobile compressor to move from pipeline mn to pipeline op; is the time required for the mobile compressor to move from pipeline mn to node o;

[0072] is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the pipeline mn under the fault scenario s at time t. If so, it is 1;

[0073] is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1;

[0074] is a 0-1 variable, indicating whether the discharge end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1;

[0075] t R is the total number of time periods in the post-fault stage; M is an infinite positive number; N is the set of all gas network nodes in the system; L is the set of all gas pipelines in the system; c is the index of each mobile compressor; s is the index of each fault scenario; t is the index of each time period in the post-fault stage.

[0076] As a preferred solution for the resilience improvement device of the electric-gas integrated energy system based on compressor scheduling, the objective function expression for comprehensive solution of all fault scenarios in the prevention strategy and recovery strategy acquisition module is:

[0077]

[0078] Where Δt is the duration of each period in the post-fault stage; ω j ,ω n are the weights of the grid nodes and gas grid nodes respectively; are the amount of power load removal on grid node j and the amount of natural gas load removal on gas grid node n in the post-fault stage under fault scenario s at time t, respectively; s is the occurrence probability of scene s; W s For penalty items.

[0079] As a preferred solution for the resilience improvement device of the electric-gas integrated energy system based on compressor scheduling, in the prevention strategy and recovery strategy acquisition module, the penalty term in the objective function is constructed through formulas (23)-(26):

[0080]

[0081] In the formula, ω a ,ω b ,ω0 are the penalty terms W a,s ,W b,s ,W 0,s The coefficient of c,s,t , is a 0-1 vector, reflecting the connection relationship between the mobile compressor c and all nodes in the system under the fault scenario s at time t; c,s,t is a 0-1 vector, reflecting the connection relationship between the mobile compressor c and all pipelines in the system under the fault scenario s at time t; X P is the distance matrix between any two pipelines in the natural gas system; X N is the distance matrix between any two nodes in the natural gas system; L is the set of all gas pipelines in the system; Ω mc is the collection of all mobile compressors in the system; Ω T is the set of all time periods in the post-fault phase; s is the index of different fault scenarios.

[0082] The present invention has the following advantages: according to the actual working process of the mobile compressor, by analyzing the working characteristics and connection characteristics of the mobile compressor, an operation model of the mobile compressor is constructed; by analyzing the role of the mobile compressor in the fault recovery process of the electric-gas integrated energy system after its introduction, a scheduling model of the mobile compressor is constructed; according to the set constraints, an operation model of the electric-gas integrated energy system is constructed; the constraints of the operation model of the electric-gas integrated energy system include distribution network flow constraints, node voltage constraints, upper and lower limit constraints of unit output, natural gas network flow constraints, node gas pressure constraints, upper and lower limit constraints of gas well gas output and gas network pipe storage utilization constraints; with minimizing the weighted load removal amount in the system after the fault as the objective function, a comprehensive solution is performed on the full fault scenario to obtain the prevention strategy of the electric-gas integrated energy system in the full fault scenario and the fault recovery strategy in the set scenario. The present invention establishes a multi-stage defense and response model for the electric-gas integrated energy system under extreme weather events, comprehensively considers the role of mobile compressors in the fault recovery process of the electric-gas integrated energy system, including the pre-fault pre-configuration of mobile compressors and the scheduling process after the fault, establishes the working model and scheduling model of mobile compressors, and focuses on the role of mobile compressors in improving the resilience level of the electric-gas integrated energy system and reducing the impact of extreme weather events. The mobile compressor is pre-configured in the natural gas system before the fault occurs, and after the fault occurs, it serves as a temporary branch to connect the gas grid island and the gas source, thereby improving the resilience level of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings in the following description are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.

[0084] Figure 1 This is a flow chart of a method for improving resilience of an electric-gas integrated energy system based on compressor scheduling provided in Example 1 of the present invention;

[0085] Figure 2 A topological diagram of an electric-gas integrated energy system in a possible embodiment provided in Embodiment 1 of the present invention;

[0086] Figure 3 A topology diagram of a system prevention phase in a full scenario in a possible embodiment provided in Embodiment 1 of the present invention;

[0087] Figure 4 A post-fault topology of a system in a possible embodiment provided in Embodiment 1 of the present invention under a fault scenario 5;

[0088] Figure 5 A post-fault scheduling process of a mobile compressor in a possible embodiment provided in Embodiment 1 of the present invention under a fault scenario 5;

[0089] Figure 6 This is an architecture diagram of the device for improving the resilience of an electric-gas integrated energy system based on compressor scheduling provided in Example 2 of the present invention. DETAILED DESCRIPTION

[0090] The following is a description of the implementation of the present invention by specific embodiments. People familiar with the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0091] Example 1

[0092] See also Figure 1 Embodiment 1 of the present invention provides a method for improving the resilience of an electric-gas integrated energy system based on compressor scheduling, comprising the following steps:

[0093] S1. According to the actual working process of the mobile compressor, by analyzing the working characteristics and connection characteristics of the mobile compressor, an operation model of the mobile compressor is constructed;

[0094] S2. By analyzing the role of the mobile compressor in the fault recovery process of the electric-gas integrated energy system after its introduction, a scheduling model of the mobile compressor is constructed;

[0095] S3. Construct an operation model of an integrated electricity-gas energy system according to set constraints; the constraints of the operation model of the integrated electricity-gas energy system include power flow constraints of distribution network, node voltage constraints, upper and lower limit constraints of unit output, power flow constraints of natural gas network, node gas pressure constraints, upper and lower limit constraints of gas well output, and gas network pipe storage and utilization constraints;

[0096] S4. With the goal of minimizing the weighted load removal in the system after a fault, a comprehensive solution is obtained for all fault scenarios to obtain the prevention strategy of the electric-gas integrated energy system under all fault scenarios and the fault recovery strategy within the set scenario.

[0097] In this embodiment, in step S1, the mobile compressor can extract natural gas or release natural gas from the target pipeline or node only when the gas pressure value of the target pipeline or node is higher than the minimum extraction pressure or lower than the maximum deflation pressure, and the mobile compressor can only connect to pipelines or nodes that are geographically adjacent.

[0098] Constructing the operation model of the mobile compressor includes constructing a connection model of the mobile compressor and constructing a working model of the mobile compressor;

[0099] The connection model of the mobile compressor is constructed by formulas (1)-(7):

[0100]

[0101] Mobile compressors are limited to connecting to geographically nearby gas grid pipelines or nodes;

[0102] In the formula, is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the pipeline mn under the fault scenario s at time t. If so, it is 1;

[0103] is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1;

[0104] is a 0-1 variable, indicating whether the discharge end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1;

[0105] V mn,s,t is the internal pipe inventory of the natural gas system pipeline mn under the fault scenario s at time t; f mn,s is a 0-1 constant, indicating whether the pipeline mn is faulty in fault scenario s, if so, it is 1;

[0106] D is the square of the maximum connection distance of the mobile compressor; MC is the total number of mobile compressors in the system; M is an infinite positive number; x mn ,y mn is the horizontal coordinate / vertical coordinate of the system pipeline mn; x m ,y m is the horizontal coordinate / vertical coordinate of the system node m; N is the set of all gas network nodes in the system; L is the set of all gas pipelines in the system; Ω mc is the set of all mobile compressors in the system; s is the index of different fault scenarios; t is the index of each time period in the post-fault stage;

[0107] The working model of the mobile compressor is constructed by formulas (8)-(15):

[0108]

[0109] The natural gas extracted from the suction end is partially consumed by the compressor itself to maintain its normal operation, and the rest will be released through the venting end, and the amount of natural gas consumed is proportional to the amount of natural gas extracted from the suction end. At the same time, the mobile compressor can only extract or release natural gas from the target pipeline or node when the gas pressure of the target pipeline or node is higher than the minimum suction pressure or lower than the maximum venting pressure;

[0110] In the formula, is the air flow rate extracted from pipeline mn by the extraction end of mobile compressor c under fault scenario s at time t; is the air flow rate of the mobile compressor c pumping end from node n under fault scenario s at time t; is the natural gas consumption of mobile compressor c under fault scenario s at time t; is the air flow rate from the air discharge end of mobile compressor c to node n under fault scenario s at time t;

[0111] α mn,s,t It is a 0-1 variable, indicating whether the gas pressure of the natural gas system pipeline mn under the fault scenario s at time t meets the pumping requirements of the mobile compressor. If yes, it is 1;

[0112] κ n,s,t is a 0-1 variable, indicating whether the gas pressure at node n of the natural gas system under fault scenario s at time t meets the pumping requirements of the mobile compressor. If yes, it is 1;

[0113] β n,s,t is a 0-1 variable, indicating whether the gas pressure at node n of the natural gas system under fault scenario s at time t meets the requirements for the mobile compressor to bleed gas. If yes, it is 1;

[0114] Π mn,s,t is the gas pressure of the natural gas system pipeline mn under fault scenario s at time t; n,s,t is the gas pressure of node n in the natural gas system under fault scenario s at time t; cha / Π dis They are respectively the minimum suction pressure / maximum discharge pressure of the mobile compressor; are the minimum / maximum values ​​of the natural gas flow through the mobile compressor; θ is the natural gas consumption coefficient of the mobile compressor; M is an infinite positive number; mn is the index of each gas pipeline; n is the index of each gas network node; c is the index of each mobile compressor, s is the index of each fault scenario; and t is the index of each time period in the post-fault stage.

[0115] In this embodiment, in step S2, the mobile compressor will be pre-configured at a node in the natural gas system before the failure; then, after the failure, the mobile compressor will serve as a temporary branch to connect the gas network island with the gas source to restore the gas supply of the gas network island.

[0116] Constructing the scheduling model of the mobile compressor includes constructing the pre-configuration constraints of the mobile compressor in the pre-fault stage and constructing the scheduling constraints of the mobile compressor in the post-fault stage;

[0117] Through formulas (16)-(18), the pre-fault stage mobile compressor pre-configuration constraints are constructed:

[0118]

[0119] Before a fault occurs, the mobile compressor will be pre-configured somewhere in the system so that the total dispatch distance of the mobile compressor in all scenarios after the fault is the shortest.

[0120] In the formula, is the square of the maximum connection distance of the mobile compressor; M is an infinite positive number; N is the set of all gas network nodes in the system; x m ,y m is the abscissa / ordinate of the system node m; c is the index of each mobile compressor;

[0121] Through formulas (19)-(21), the mobile compressor scheduling constraints in the post-fault stage are constructed:

[0122]

[0123] In the formula, is the time required for the mobile compressor to move from pipeline mn to pipeline op; is the time required for the mobile compressor to move from pipeline mn to node o;

[0124] is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the pipeline mn under the fault scenario s at time t. If so, it is 1;

[0125] is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1;

[0126] is a 0-1 variable, indicating whether the discharge end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1;

[0127] t R is the total number of time periods in the post-fault stage; M is an infinite positive number; N is the set of all gas network nodes in the system; L is the set of all gas pipelines in the system; c is the index of each mobile compressor; s is the index of each fault scenario; t is the index of each time period in the post-fault stage.

[0128] In this embodiment, in step S3, the set constraints include distribution network flow constraints, node voltage constraints, unit output upper and lower limit constraints, natural gas network flow constraints, node gas pressure constraints, gas well output upper and lower limit constraints, gas network pipeline storage utilization constraints, etc.

[0129] In this embodiment, in step S4, the objective function expression for comprehensively solving the full fault scenario is:

[0130]

[0131] Where Δt is the duration of each period in the post-fault stage; ω j ,ω n are the weights of the grid nodes and gas grid nodes respectively; are the amount of power load removal on grid node j and the amount of natural gas load removal on gas grid node n in the post-fault stage under fault scenario s at time t, respectively; s is the occurrence probability of scene s; W s For penalty items.

[0132] The penalty term in the objective function is constructed by formulas (23)-(26):

[0133]

[0134] Penalty term W s It consists of three parts, among which the penalty term W a,s is the penalty term of the second-order cone relaxation of the Weymouth equation, which is used to improve the accuracy of the linear constraints obtained after the second-order cone relaxation of the original Weymouth equation; the penalty term W b,s is the system storage level penalty item, which is used to limit the system to maximize the use of the storage in the faulty pipeline under the premise of minimizing the load shedding during the fault recovery process; the penalty item W 0,s The penalty term for the moving distance of the mobile compressor is used to restrict the scheduling process of the mobile compressor after a failure, so as to minimize unnecessary movement of the mobile compressor;

[0135] In the formula, ω a ,ω b ,ω0 are the penalty terms W a,s ,W b,s ,W 0,s The coefficient of c,s,t , is a 0-1 vector, reflecting the connection relationship between the mobile compressor c and all nodes in the system under the fault scenario s at time t; c,s,t is a 0-1 vector, reflecting the connection relationship between the mobile compressor c and all pipelines in the system under the fault scenario s at time t; X P is the distance matrix between any two pipelines in the natural gas system; XN is the distance matrix between any two nodes in the natural gas system; L is the set of all gas pipelines in the system; Ω mc is the collection of all mobile compressors in the system; Ω T is the set of all time periods in the post-fault phase; s is the index of different fault scenarios.

[0136] In a possible embodiment, an example of improving toughness is provided as follows:

[0137] T1, select the improved 33-node power distribution system and the improved 20-node natural gas system for coupling for the example verification part, such as Figure 2 As shown. The improved 33-node power distribution system consists of 1 substation, 32 load nodes, 37 transmission lines and 3 GTs. The solid line indicates that the power line is closed, the dotted line indicates that it is disconnected, and the red line indicates that the power line is equipped with a remote control switch. Node 1 is a substation node. There are 37 transmission lines in the system, and 3 GTs are installed on nodes 14, 25 and 26 respectively, with the maximum output set to 0.9MVA. The total power demand of the system is 3.715MW+2.3MVar, and the voltage amplitude fluctuation range of all nodes is set to [0.95,1.05]. The improved 20-node natural gas system includes 2 gas well nodes, 12 gas load nodes, and 19 gas pipelines. The total gas demand of the system is 1.8224MSm3, and there is a mobile compressor in the system. In addition, two gas compressors are installed on pipelines 9-10 and 17-18 respectively. Ten fault scenarios were randomly generated. In each scenario, four power transmission lines and two gas pipelines failed, and the probability was set to 0.1. The failure forms of the gas pipelines in the natural gas system were all considered to be freezing failures.

[0138] T2. Establish a mathematical model of the fault defense and response process of the electric-gas integrated energy system. The objective function is to minimize the weighted load removal in the system during the whole process. The constraints include fault transmission constraints, system operation constraints, network topology change constraints, pipeline storage utilization constraints, coupling equipment operation constraints, mobile compressor operation constraints, mobile compressor scheduling constraints, etc.

[0139] T3, using GUROBI commercial solver to solve efficiently and ensure the global optimality of the solution, we get Figure 3 The preventive measures of the system before the failure occurs and the failure recovery process of the system under different failures are shown. Among them, in the system preventive measures, the mobile compressor is pre-configured at the gas network node 8. Figure 4 The following is the post-fault topology of the system under fault scenario 5. Figure 5 The figure shows the post-fault dispatching process of the mobile compressor under fault scenario 5.

[0140] In summary, the present invention constructs an operation model of the mobile compressor according to the actual working process of the mobile compressor by analyzing the working characteristics and connection characteristics of the mobile compressor; constructs a scheduling model of the mobile compressor by analyzing the role of the mobile compressor in the fault recovery process of the electric-gas integrated energy system after its introduction; constructs an operation model of the electric-gas integrated energy system according to the set constraints; the constraints of the operation model of the electric-gas integrated energy system include distribution network flow constraints, node voltage constraints, upper and lower limit constraints of unit output, natural gas network flow constraints, node gas pressure constraints, upper and lower limit constraints of gas well gas output, and gas network pipeline storage utilization constraints; with the goal of minimizing the weighted load removal amount in the system after the fault, a comprehensive solution is performed on the full fault scenario to obtain the prevention strategy of the electric-gas integrated energy system in the full fault scenario and the fault recovery strategy in the set scenario. The present invention establishes a multi-stage defense and response model for the electric-gas integrated energy system under extreme weather events, comprehensively considers the role of mobile compressors in the fault recovery process of the electric-gas integrated energy system, including the pre-fault pre-configuration of mobile compressors and the scheduling process after the fault, establishes the working model and scheduling model of mobile compressors, and focuses on the role of mobile compressors in improving the resilience level of the electric-gas integrated energy system and reducing the impact of extreme weather events. The mobile compressor is pre-configured in the natural gas system before the fault occurs, and after the fault occurs, it serves as a temporary branch to connect the gas grid island and the gas source, thereby improving the resilience level of the system.

[0141] It should be noted that the method of the embodiment of the present disclosure can be performed by a single device, such as a computer or a server. The method of the present embodiment can also be applied in a distributed scenario and completed by multiple devices cooperating with each other. In the case of such a distributed scenario, one of the multiple devices can only perform one or more steps in the method of the embodiment of the present disclosure, and the multiple devices will interact with each other to complete the described method.

[0142] It should be noted that the above describes some embodiments of the present disclosure. 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 above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying 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.

[0143] Example 2

[0144] See also Figure 6Embodiment 2 of the present invention further provides a device for improving resilience of an electric-gas integrated energy system based on compressor scheduling, which adopts the method for improving resilience of an electric-gas integrated energy system based on compressor scheduling of the above embodiment 1, including:

[0145] The mobile compressor operation model building module 001 is used to build the operation model of the mobile compressor by analyzing the working characteristics and connection characteristics of the mobile compressor according to the actual working process of the mobile compressor;

[0146] The scheduling model building module 002 of the mobile compressor is used to build the scheduling model of the mobile compressor by analyzing the role of the mobile compressor in the fault recovery process of the electric-gas integrated energy system after its introduction;

[0147] The electricity-gas integrated energy system operation model construction module 003 is used to construct the electricity-gas integrated energy system operation model according to the set constraints; the constraints of the electricity-gas integrated energy system operation model include distribution network flow constraints, node voltage constraints, unit output upper and lower limit constraints, natural gas network flow constraints, node gas pressure constraints, gas well output upper and lower limit constraints and gas network pipe storage and utilization constraints;

[0148] The prevention strategy and recovery strategy acquisition module 004 is used to comprehensively solve the full fault scenario with the goal of minimizing the weighted load removal in the system after the fault, and obtain the prevention strategy of the electric-gas integrated energy system in the full fault scenario and the fault recovery strategy in the set scenario.

[0149] In this embodiment, in the operation model construction module 001 of the mobile compressor, constructing the operation model of the mobile compressor includes constructing a connection model of the mobile compressor and constructing a working model of the mobile compressor;

[0150] The connection model of the mobile compressor is constructed by formulas (1)-(7):

[0151]

[0152] In the formula, is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the pipeline mn under the fault scenario s at time t. If so, it is 1;

[0153] is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1;

[0154] is a 0-1 variable, indicating whether the discharge end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1;

[0155] V mn,s,t is the internal pipe inventory of the natural gas system pipeline mn under the fault scenario s at time t; f mn,s is a 0-1 constant, indicating whether the pipeline mn is faulty in fault scenario s, if so, it is 1;

[0156] D is the square of the maximum connection distance of the mobile compressor; MC is the total number of mobile compressors in the system; M is an infinite positive number; x mn ,y mn is the horizontal coordinate / vertical coordinate of the system pipeline mn; x m ,y m is the horizontal coordinate / vertical coordinate of the system node m; N is the set of all gas network nodes in the system; L is the set of all gas pipelines in the system; Ω mc is the set of all mobile compressors in the system; s is the index of different fault scenarios; t is the index of each time period in the post-fault stage;

[0157] The working model of the mobile compressor is constructed by formulas (8)-(15):

[0158]

[0159] In the formula, is the air flow rate extracted from pipeline mn by the extraction end of mobile compressor c under fault scenario s at time t; is the air flow rate of the mobile compressor c pumping end from node n under fault scenario s at time t; is the natural gas consumption of mobile compressor c under fault scenario s at time t; is the air flow rate from the air discharge end of mobile compressor c to node n under fault scenario s at time t;

[0160] α mn,s,t It is a 0-1 variable, indicating whether the gas pressure of the natural gas system pipeline mn under the fault scenario s at time t meets the pumping requirements of the mobile compressor. If yes, it is 1;

[0161] κ n,s,t is a 0-1 variable, indicating whether the gas pressure at node n of the natural gas system under fault scenario s at time t meets the pumping requirements of the mobile compressor. If yes, it is 1;

[0162] β n,s,t is a 0-1 variable, indicating whether the gas pressure at node n of the natural gas system under fault scenario s at time t meets the requirements for the mobile compressor to bleed gas. If yes, it is 1;

[0163] Π mn,s,t is the gas pressure of the natural gas system pipeline mn under fault scenario s at time t; n,s,t is the gas pressure of node n in the natural gas system under fault scenario s at time t; cha / Π disThey are respectively the minimum suction pressure / maximum discharge pressure of the mobile compressor; are the minimum / maximum values ​​of the natural gas flow through the mobile compressor; θ is the natural gas consumption coefficient of the mobile compressor; M is an infinite positive number; mn is the index of each gas pipeline; n is the index of each gas network node; c is the index of each mobile compressor, s is the index of each fault scenario; and t is the index of each time period in the post-fault stage.

[0164] In this embodiment, in the scheduling model building module 002 of the mobile compressor, building the scheduling model of the mobile compressor includes building the pre-fault stage pre-configuration constraints of the mobile compressor and building the post-fault stage scheduling constraints of the mobile compressor;

[0165] Through formulas (16)-(18), the pre-fault stage mobile compressor pre-configuration constraints are constructed:

[0166]

[0167] In the formula, is the square of the maximum connection distance of the mobile compressor; M is an infinite positive number; N is the set of all gas network nodes in the system; x m ,y m is the abscissa / ordinate of the system node m; c is the index of each mobile compressor;

[0168] Through formulas (19)-(21), the mobile compressor scheduling constraints in the post-fault stage are constructed:

[0169]

[0170]

[0171] In the formula, is the time required for the mobile compressor to move from pipeline mn to pipeline op; is the time required for the mobile compressor to move from pipeline mn to node o;

[0172] is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the pipeline mn under the fault scenario s at time t. If so, it is 1;

[0173] is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1;

[0174] is a 0-1 variable, indicating whether the discharge end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1;

[0175] t R is the total number of time periods in the post-fault stage; M is an infinite positive number; N is the set of all gas network nodes in the system; L is the set of all gas pipelines in the system; c is the index of each mobile compressor; s is the index of each fault scenario; t is the index of each time period in the post-fault stage.

[0176] In this embodiment, in the prevention strategy and recovery strategy acquisition module 004, the objective function expression for comprehensively solving all fault scenarios is:

[0177]

[0178] Where Δt is the duration of each period in the post-fault stage; ω j ,ω n are the weights of the grid nodes and gas grid nodes respectively; are the amount of power load removal on grid node j and the amount of natural gas load removal on gas grid node n in the post-fault stage under fault scenario s at time t, respectively; s is the occurrence probability of scene s; W s For penalty items.

[0179] In this embodiment, in the prevention strategy and recovery strategy acquisition module, the penalty term in the objective function is constructed by formulas (23)-(26):

[0180]

[0181]

[0182] In the formula, ω a ,ω b ,ω0 are the penalty terms W a,s ,W b,s ,W 0,s The coefficient of c,s,t , is a 0-1 vector, reflecting the connection relationship between the mobile compressor c and all nodes in the system under the fault scenario s at time t; c,s,t is a 0-1 vector, reflecting the connection relationship between the mobile compressor c and all pipelines in the system under the fault scenario s at time t; X P is the distance matrix between any two pipelines in the natural gas system; X N is the distance matrix between any two nodes in the natural gas system; L is the set of all gas pipelines in the system; Ω mc is the collection of all mobile compressors in the system; Ω T is the set of all time periods in the post-fault phase; s is the index of different fault scenarios.

[0183] It should be noted that the information interaction, execution process and other contents between the modules of the above-mentioned device are based on the same concept as the method embodiment in Example 1 of the present application, and the technical effects they bring are the same as those of the method embodiment of the present application. For specific contents, please refer to the description in the method embodiment shown in the previous part of the present application, and will not be repeated here.

[0184] Example 3

[0185] Embodiment 3 of the present invention provides a non-transitory computer-readable storage medium, in which a program code for a method for improving the resilience of an electric-gas integrated energy system based on compressor scheduling is stored. The program code includes instructions for executing embodiment 1 or any possible implementation method of the method for improving the resilience of an electric-gas integrated energy system based on compressor scheduling.

[0186] The computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more available media. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0187] Example 4

[0188] Embodiment 4 of the present invention provides an electronic device, including: a memory and a processor;

[0189] The processor and the memory communicate with each other via a bus; the memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute the method for improving the resilience of an electric-gas integrated energy system based on compressor scheduling of Example 1 or any possible implementation thereof.

[0190] Specifically, the processor can be implemented by hardware or by software. When implemented by hardware, the processor can be a logic circuit, an integrated circuit, etc.; when implemented by software, the processor can be a general-purpose processor implemented by reading software codes stored in a memory. The memory can be integrated in the processor or can be located outside the processor and exist independently.

[0191] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center.

[0192] Obviously, those skilled in the art should understand that the above modules or steps of the present invention can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0193] Although the present invention has been described in detail above by general description and specific embodiments, it is obvious to those skilled in the art that some modifications or improvements can be made to the present invention. Therefore, these modifications or improvements made without departing from the spirit of the present invention all belong to the scope of protection claimed by the present invention.

Claims

1. A method for improving the resilience of an electric-gas integrated energy system based on compressor scheduling, characterized in that: include: According to the actual working process of the mobile compressor, by analyzing the working characteristics and connection characteristics of the mobile compressor, an operation model of the mobile compressor is constructed; By analyzing the role of the mobile compressor in the fault recovery process of the electric-gas integrated energy system after its introduction, a scheduling model of the mobile compressor is constructed; According to the set constraints, an operation model of the electricity-gas integrated energy system is constructed; the constraints of the operation model of the electricity-gas integrated energy system include power flow constraints of the distribution network, node voltage constraints, upper and lower limit constraints of unit output, power flow constraints of the natural gas network, node gas pressure constraints, upper and lower limit constraints of gas well output, and gas network pipe storage and utilization constraints; Taking minimizing the weighted load removal in the system after a fault as the objective function, a comprehensive solution is obtained for all fault scenarios to obtain the prevention strategy of the electric-gas integrated energy system in all fault scenarios and the fault recovery strategy in the set scenario; Constructing the operation model of the mobile compressor includes constructing a connection model of the mobile compressor and constructing a working model of the mobile compressor; The connection model of the mobile compressor is constructed by formulas (1)-(7): In the formula, is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the pipeline mn under the fault scenario s at time t. If so, it is 1; is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1; is a 0-1 variable, indicating whether the discharge end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1; V mn,s,t is the internal pipe inventory of the natural gas system pipeline mn under the fault scenario s at time t; f mn,s is a 0-1 constant, indicating whether the pipeline mn is faulty in fault scenario s, if so, it is 1; D is the square of the maximum connection distance of the mobile compressor; MC is the total number of mobile compressors in the system; M is an infinite positive number; x mn ,y mn is the horizontal / vertical coordinate of the system pipeline mn; x m ,y m is the horizontal coordinate / vertical coordinate of the system node m; N is the set of all gas network nodes in the system; L is the set of all gas pipelines in the system; Ω mc is the set of all mobile compressors in the system; s is the index of different fault scenarios; t is the index of each time period in the post-fault stage; The working model of the mobile compressor is constructed by formulas (8)-(15): In the formula, is the air flow rate extracted from pipeline mn by the extraction end of mobile compressor c under fault scenario s at time t; is the air flow rate of the mobile compressor c pumping end from node n under fault scenario s at time t; is the natural gas consumption of mobile compressor c under fault scenario s at time t; is the air flow rate from the air discharge end of mobile compressor c to node n under fault scenario s at time t; α mn,s,t It is a 0-1 variable, indicating whether the gas pressure of the natural gas system pipeline mn under the fault scenario s at time t meets the pumping requirements of the mobile compressor. If yes, it is 1; κ n,s,t is a 0-1 variable, indicating whether the gas pressure at node n of the natural gas system under fault scenario s at time t meets the pumping requirements of the mobile compressor. If yes, it is 1; β n,s,t is a 0-1 variable, indicating whether the gas pressure at node n of the natural gas system under fault scenario s at time t meets the requirements for the mobile compressor to bleed gas. If yes, it is 1; Π mn,s,t is the gas pressure of the natural gas system pipeline mn under fault scenario s at time t; n,s,t is the gas pressure of node n in the natural gas system under fault scenario s at time t; cha / Π dis They are respectively the minimum suction pressure / maximum discharge pressure of the mobile compressor; are the minimum / maximum values ​​of the natural gas flow through the mobile compressor; θ is the natural gas consumption coefficient of the mobile compressor; M is an infinite positive number; mn is the index of each gas pipeline; n is the index of each gas network node; c is the index of each mobile compressor, s is the index of each fault scenario; t is the index of each time period in the post-fault stage; Constructing the scheduling model of the mobile compressor includes constructing the pre-configuration constraints of the mobile compressor in the pre-fault stage and constructing the scheduling constraints of the mobile compressor in the post-fault stage; Through formulas (16)-(18), the pre-fault stage mobile compressor pre-configuration constraints are constructed: Where D is the square of the maximum connection distance of the mobile compressor; M is an infinite positive number; N is the set of all gas network nodes in the system; x m ,y m is the abscissa / ordinate of the system node m; c is the index of each mobile compressor; Through formulas (19)-(21), the mobile compressor scheduling constraints in the post-fault stage are constructed: In the formula, is the time required for the mobile compressor to move from pipeline mn to pipeline op; is the time required for the mobile compressor to move from pipeline mn to node o; is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the pipeline mn under the fault scenario s at time t. If so, it is 1; is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1; is a 0-1 variable, indicating whether the discharge end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1; t R is the total number of time periods in the post-fault stage; M is an infinite positive number; N is the set of all gas network nodes in the system; L is the set of all gas pipelines in the system; c is the index of each mobile compressor; s is the index of each fault scenario; t is the index of each time period in the post-fault stage.

2. The method for improving resilience of an electric-gas integrated energy system based on compressor scheduling according to claim 1 is characterized in that: The objective function expression for comprehensive solution of all fault scenarios is: Where △t is the duration of each period in the post-fault stage; ω j ,ω n are the weights of the grid nodes and gas grid nodes respectively; are the amount of power load removal on grid node j and the amount of natural gas load removal on gas grid node n in the post-fault stage under fault scenario s at time t, respectively; s is the occurrence probability of scene s; W s For penalty items.

3. The method for improving resilience of an electric-gas integrated energy system based on compressor scheduling according to claim 2 is characterized in that: The penalty term in the objective function is constructed by formulas (23)-(26): In the formula, ω a ,ω b ,ω0 are the penalty terms W a,s ,W b,s ,W 0,s The coefficient of is a 0-1 vector, reflecting the connection relationship between the mobile compressor c and all nodes in the system under the fault scenario s at time t; is a 0-1 vector, reflecting the connection relationship between the mobile compressor c and all pipelines in the system under the fault scenario s at time t; X P is the distance matrix between any two pipelines in the natural gas system; X N is the distance matrix between any two nodes in the natural gas system; L is the set of all gas pipelines in the system; Ω mc is the collection of all mobile compressors in the system; Ω T is the set of all time periods in the post-fault phase; s is the index of different fault scenarios.

4. A device for improving the resilience of an electric-gas integrated energy system based on compressor scheduling, adopting a method for improving the resilience of an electric-gas integrated energy system based on compressor scheduling as described in any one of claims 1 to 3, characterized in that: include: A mobile compressor operation model building module, used to build an operation model of the mobile compressor by analyzing the working characteristics and connection characteristics of the mobile compressor according to the actual working process of the mobile compressor; A scheduling model building module for a mobile compressor, used to build a scheduling model for the mobile compressor by analyzing the role of the mobile compressor in the fault recovery process of the electric-gas integrated energy system after its introduction; An electricity-gas integrated energy system operation model construction module is used to construct an electricity-gas integrated energy system operation model according to set constraints; the constraints of the electricity-gas integrated energy system operation model include distribution network flow constraints, node voltage constraints, unit output upper and lower limit constraints, natural gas network flow constraints, node gas pressure constraints, gas well output upper and lower limit constraints and gas network pipe storage and utilization constraints; The prevention strategy and recovery strategy acquisition module is used to comprehensively solve the full fault scenario with the goal of minimizing the weighted load removal in the system after the fault, and obtain the prevention strategy of the electric-gas integrated energy system in the full fault scenario and the fault recovery strategy in the set scenario; In the operation model construction module of the mobile compressor, constructing the operation model of the mobile compressor includes constructing a connection model of the mobile compressor and constructing a working model of the mobile compressor; The connection model of the mobile compressor is constructed by formulas (1)-(7): In the formula, is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the pipeline mn under the fault scenario s at time t. If so, it is 1; is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1; is a 0-1 variable, indicating whether the discharge end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1; V mn,s,t is the internal pipe inventory of the natural gas system pipeline mn under the fault scenario s at time t; f mn,s is a 0-1 constant, indicating whether the pipeline mn is faulty in fault scenario s, if so, it is 1; D is the square of the maximum connection distance of the mobile compressor; MC is the total number of mobile compressors in the system; M is an infinite positive number; x mn ,y mn is the horizontal / vertical coordinate of the system pipeline mn; x m ,y m is the horizontal coordinate / vertical coordinate of the system node m; N is the set of all gas network nodes in the system; L is the set of all gas pipelines in the system; Ω mc is the set of all mobile compressors in the system; s is the index of different fault scenarios; t is the index of each time period in the post-fault stage; The working model of the mobile compressor is constructed by formulas (8)-(15): In the formula, is the air flow rate extracted from pipeline mn by the extraction end of mobile compressor c under fault scenario s at time t; is the air flow rate of the mobile compressor c pumping end from node n under fault scenario s at time t; is the natural gas consumption of mobile compressor c under fault scenario s at time t; is the air flow rate from the air discharge end of mobile compressor c to node n under fault scenario s at time t; α mn,s,t It is a 0-1 variable, indicating whether the gas pressure of the natural gas system pipeline mn under the fault scenario s at time t meets the pumping requirements of the mobile compressor. If yes, it is 1; κ n,s,t is a 0-1 variable, indicating whether the gas pressure at node n of the natural gas system under fault scenario s at time t meets the pumping requirements of the mobile compressor. If yes, it is 1; β n,s,t is a 0-1 variable, indicating whether the gas pressure at node n of the natural gas system under fault scenario s at time t meets the requirements for the mobile compressor to bleed gas. If yes, it is 1; Π mn,s,t is the gas pressure of the natural gas system pipeline mn under fault scenario s at time t; n,s,t is the gas pressure of node n in the natural gas system under fault scenario s at time t; cha / Π dis They are respectively the minimum suction pressure / maximum discharge pressure of the mobile compressor; are the minimum / maximum values ​​of the natural gas flow through the mobile compressor; θ is the natural gas consumption coefficient of the mobile compressor; M is an infinite positive number; mn is the index of each gas pipeline; n is the index of each gas network node; c is the index of each mobile compressor, s is the index of each fault scenario; t is the index of each time period in the post-fault stage; In the scheduling model building module of the mobile compressor, building the scheduling model of the mobile compressor includes building the pre-fault stage pre-configuration constraints of the mobile compressor and building the scheduling constraints of the mobile compressor in the post-fault stage; Through formulas (16)-(18), the pre-fault stage mobile compressor pre-configuration constraints are constructed: Where D is the square of the maximum connection distance of the mobile compressor; M is an infinite positive number; N is the set of all gas network nodes in the system; x m ,y m is the abscissa / ordinate of the system node m; c is the index of each mobile compressor; Through formulas (19)-(21), the mobile compressor scheduling constraints in the post-fault stage are constructed: In the formula, is the time required for the mobile compressor to move from pipeline mn to pipeline op; is the time required for the mobile compressor to move from pipeline mn to node o; is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the pipeline mn under the fault scenario s at time t. If so, it is 1; is a 0-1 variable, indicating whether the suction end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1; is a 0-1 variable, indicating whether the discharge end of the mobile compressor c is connected to the node n in the fault scenario s at time t. If so, it is 1; t R is the total number of time periods in the post-fault stage; M is an infinite positive number; N is the set of all gas network nodes in the system; L is the set of all gas pipelines in the system; c is the index of each mobile compressor; s is the index of each fault scenario; t is the index of each time period in the post-fault stage.

5. The device for improving the resilience of an electric-gas integrated energy system based on compressor scheduling according to claim 4 is characterized in that: In the prevention strategy and recovery strategy acquisition module, the objective function expression for comprehensive solution of all fault scenarios is: Where △t is the duration of each period in the post-fault stage; ω j ,ω n are the weights of the grid nodes and gas grid nodes respectively; are the amount of power load removal on grid node j and the amount of natural gas load removal on gas grid node n in the post-fault stage under fault scenario s at time t, respectively; s is the occurrence probability of scene s; W s For penalty items.

6. The device for improving the resilience of an electric-gas integrated energy system based on compressor scheduling according to claim 5 is characterized in that: In the prevention strategy and recovery strategy acquisition module, the penalty term in the objective function is constructed by formulas (23)-(26): In the formula, ω a ,ω b ,ω0 are the penalty terms W a,s ,W b,s ,W 0,s The coefficient of is a 0-1 vector, reflecting the connection relationship between the mobile compressor c and all nodes in the system under the fault scenario s at time t; is a 0-1 vector, reflecting the connection relationship between the mobile compressor c and all pipelines in the system under the fault scenario s at time t; X P is the distance matrix between any two pipelines in the natural gas system; X N is the distance matrix between any two nodes in the natural gas system; L is the set of all gas pipelines in the system; Ω mc is the collection of all mobile compressors in the system; Ω T is the set of all time periods in the post-fault phase; s is the index of different fault scenarios.

Images