Island recovery method considering optimal scheduling of emergency mobile resources

Abstract

The invention provides an island recovery method considering the optimal scheduling of emergency mobile resources, belonging to the technical field of distribution network fault recovery; solves the problem that the existing emergency mobile resources participate in the load recovery of the power system and cannot be fully coordinated without considering the temporal and spatial volatility; comprises the following steps: a pre-disaster EPS pre-dispatching model which balances the mobile characteristics and the operating cost is proposed for the emergency mobile resources in the active distribution network; on the basis of the pre-disaster EPS pre-dispatching model, the volatility of the distributed photovoltaic output is considered, a primary and secondary dual objective function is established from the two aspects of load shedding and network loss, and the functions are normalized into a post-disaster island recovery scheduling model which comprehensively considers the coordinated application of EPS, fixed energy storage and distributed power source islands; the pre-disaster EPS pre-dispatching model is combined with the post-disaster island recovery scheduling model to obtain a pre-disaster-post-disaster two-stage load recovery model; the invention is applied to the active distribution network fault recovery.

Description

Technical Field

[0001] The invention provides an island recovery method considering the optimal scheduling of emergency mobile resources, belonging to the technical field of distribution network fault recovery. Background Art

[0002] In order to cope with large-scale power outages in the distribution network caused by extreme disasters, a large number of distributed resources need to be used to jointly restore important loads. In recent years, extreme weather events caused by climate change, such as ice storms, typhoons, earthquakes and other extreme disasters, have caused increasingly devastating damage to critical energy infrastructure. Emergency mobile resources can be used in conjunction with differentiated distributed power sources to ensure the supply of critical loads by applying active fault isolation and island reconstruction. However, due to the volatility of distributed power resources in both time and space, how to fully coordinate emergency mobile resources to participate in power system load restoration has become a key technical issue that needs to be solved urgently. Summary of the invention

[0003] In order to solve the above technical problems, the present invention proposes an island recovery method considering the optimal scheduling of emergency mobile resources. By constructing a pre-disaster and post-disaster two-stage load recovery model for the coordinated application of emergency mobile resources and distributed power supply islands, more power-lost loads can be restored.

[0004] The technical solution adopted by the present invention is: an island recovery method considering the optimal scheduling of emergency mobile resources, comprising the following steps:

[0005] Firstly, a pre-disaster EPS pre-dispatching model is proposed for emergency mobile resources in active distribution networks, which takes into account both mobility characteristics and operating costs.

[0006] The objective function expression of the pre-disaster EPS pre-dispatching model is as follows:

[0007] ;

[0008] Where: F t represents the comprehensive benefit objective function; Indicates the charging and discharging benefits based on real-time electricity prices and demand response; Represents the additional benefits under the sharing economy model; C op represents EPS mobile operating cost; C d represents the EPS battery loss cost; C m represents the EPS maintenance cost;

[0009] The constraints of the objective function of the pre-disaster EPS pre-scheduling model include:

[0010] ESS charging and discharging constraints;

[0011] EPS spatiotemporal constraints;

[0012] EPS configuration constraints;

[0013] Secondly, based on the pre-disaster EPS pre-dispatching model, considering the volatility of distributed photovoltaic output, a primary and secondary dual objective function is established from the two aspects of load shedding and network loss, and normalized into a post-disaster island recovery scheduling model that comprehensively considers the coordinated application of EPS, fixed energy storage and distributed power generation islands;

[0014] The main objective function expression of the post-disaster island recovery scheduling model is as follows:

[0015] ;

[0016] Where: F 1 is the main objective function; ω i Indicates the load importance of load node i; It represents the active load size of load node i in period t; y i =1 means that load node i is cut off, y i =0 means that the load node i is included in the island operation range; T is the scheduling time set; Ω b represents the set of load nodes; x ij , , z si , a is is the first-level decision variable, which determines the EPS distribution location. x ij is the recovery decision 0-1 variable of branch (i, j), Divide the branch (i, j) island into 0-1 variables, z si Configure 0-1 variables for EPS, a is Divide the load node i island into 0-1 variables; , , U i,t is the second-level decision variable, the purpose is to find the optimal load shedding minimum. is the active power of branch g during period t, is the reactive power of branch g during period t, U i,t is the voltage of load node i during period t;

[0017] The secondary objective function expression of the post-disaster island recovery scheduling model is as follows:

[0018] ;

[0019] ;

[0020] Where: P l is the network loss of the entire distribution network system during period t; F 2 is the secondary objective function, which represents the total network loss of the system during the fault period; is the active power of the kth DG in period t; is the active power of the kth EPS in period t; m is the total number of DGs and EPSs in the system; h is the total number of load nodes;

[0021] Using weight coefficient ω 0 Normalize the primary and secondary objective functions to obtain the total integrated objective function:

[0022] F 3 = F 1 + ω 0 F 2 ;

[0023] The constraints of the overall integrated objective function include:

[0024] ESS charging and discharging constraints;

[0025] Distributed power generation island division constraints;

[0026] Distributed generation island power flow balance constraints;

[0027] Finally, the pre-disaster EPS pre-disaster scheduling model and the post-disaster island recovery scheduling model were combined to obtain a two-stage load recovery model of pre-disaster and post-disaster.

[0028] The expression is as follows:

[0029] ;

[0030] Where: Δ t is the time step; T is the scheduling time set; θ it is the electricity price of load node i at time t; , are the charge and discharge power of load node i at time t respectively;

[0031] The expression is as follows:

[0032] ;

[0033] Where: R n The fee rate paid by user n based on usage; S n is the actual usage of user n in the time period; C sh is the additional maintenance cost under the sharing model, including user support and billing system maintenance; N is the total number of users;

[0034] C op The expression is as follows:

[0035] ;

[0036] Where: c op is the usage cost of EPS per unit time; Indicates whether EPS is dispatched from load node i to load node j at time t, 1 if it is being dispatched, otherwise 0;

[0037] C d The expression is as follows:

[0038] ;

[0039] Where: c d is the cost of unit battery capacity attenuation; s t is the fixed attenuation capacity of the battery per day;

[0040] C m The expression is as follows:

[0041] C m = K m N m ;

[0042] Where: K m is the average cost per maintenance action of EPS; N m The total number of maintenance actions planned by EPS during the scheduling period.

[0043] ESS charging and discharging constraints include:

[0044] ESS charging state constraint, its expression is as follows:

[0045] ;

[0046] The ESS power overcharge or overdischarge constraint is expressed as follows:

[0047] ;

[0048] Where: SOC k,t is the charging state of the energy storage system at the kth fixed energy storage at the tth period; Δ t is the time step; P k,t-1 is the charging and discharging power of the kth fixed energy storage in the t-1th period; E k is the total fixed energy storage capacity in the energy storage system; D It is the collection of fixed energy storage in the energy storage system; and The minimum and maximum values ​​of the state of charge of the energy storage system; and is the charging and discharging power of the energy storage system for the kth fixed energy storage in time period t; and is the maximum value of the charging and discharging power of the energy storage system of the kth fixed energy storage in the t period; and is a 0-1 variable. If the energy storage system is charged, =1, the energy storage system discharges =1.

[0049] The EPS spatiotemporal scheduling constraints include constraints for indicating the mobility characteristics of the EPS and the connection status of the EPS and the power line, and constraints for indicating the scheduling time, wherein the expressions for indicating the mobility characteristics of the EPS and the connection status of the EPS and the power line are as follows:

[0050] ;

[0051] ;

[0052] ;

[0053] ;

[0054] ;

[0055] Where: δ itIndicates whether the EPS leaves the load node i at time t, 1 if it is leaving, otherwise 0; ε it Indicates whether EPS reaches load node i at time t, which is 1 if it reaches load node i, otherwise 0; Indicates whether the EPS is docked at load node i at time t. If it is docked at load node i, it is 1, otherwise it is 0; Indicates whether EPS is dispatched from load node i to load node j at time t, 1 if it is being dispatched, otherwise 0; It is an auxiliary 0-1 variable and has no practical meaning; Ω b Represents a collection of load nodes;

[0056] The constraints used to indicate the scheduling time include:

[0057] The minimum time used to constrain the EPS scheduling process is expressed as follows:

[0058] T ijt = T D + T M + T C ;

[0059] Where: T ijt It represents the total dispatching time of EPS between two load nodes; T D represents the time required for EPS to disconnect at load node i; T M represents the transportation time of EPS between load nodes; T C represents the time required for EPS to connect at load node j;

[0060] It is used to constrain the running time of EPS between two load nodes. The expression is as follows:

[0061] ;

[0062] The rationality used to constrain the arrival and departure time of EPS is as follows:

[0063] .

[0064] The expression of EPS configuration constraint is as follows:

[0065] ;

[0066] Where: ais Divide the load node i into 0-1 variables, a is =1 means that load node i belongs to island s; a is =0 means that load node i does not belong to island s; z si Configure 0-1 variables for EPS, z si =1 means EPS is connected to load node i; z si =0 means that EPS is not connected to load node i; S is the set of all islands divided; Ω b is the set of all load nodes.

[0067] The distributed generation island partitioning constraint is used to ensure that each load node in the system can only belong to a certain island when performing island partitioning, that is, it satisfies:

[0068] ;

[0069] When the branch (i, j) belongs to the divided island range, then the load nodes i, j must belong to the divided island range, and the expression is as follows:

[0070] ;

[0071] Where: Divide the branch (i, j) island into 0-1 variables, =1 means branch (i, j) belongs to island s; =0 means that branch (i, j) does not belong to island s; Represents the set of all branches in the system; only when both ends of the branch are on the island s =1; a js Divide the load node j island into 0-1 variables;

[0072] make x ij represents the opening and closing state of branch (i, j), that is, the recovery decision 0-1 variable of branch (i, j), so:

[0073] ;

[0074] Where: x ij =1 means branch (i, j) resumes operation, x ij =0 means that branch (i, j) is removed from the system.

[0075] The distributed generation island power flow balance constraint uses the linearized DistFlow formula to establish the power flow equation of the active distribution network containing ESS, and its expression is as follows:

[0076] ;

[0077] ;

[0078] ;

[0079] Where: and They represent the set of branches where power flows into and out of load node i respectively; is the active power of load node i in period t; is the active power of the kth DG in period t; is the active power of the kth EPS in period t; r i is a 0-1 variable. When the kth EPS is transferred from any load node to the candidate access point on load node i to supply power to the island within the t period r i =1, otherwise r i =0; s i,t is the load connection state. If the i-th load is restored by DG or EPS within the t period, then s i,t =1, otherwise s i,t =0; is the reactive power of load node i in period t; and are the reactive powers of the kth ESS and EPS in period t respectively; is the reactive power demand of the i-th load in period t; Represents the binary variable of the branch. When the flow moves from load node i to load node j in period t, is 1, otherwise it is 0; r g and x g are the resistance and reactance of branch g respectively; U i,t is the voltage of load node i during period t; is the active power of branch g during period t; is the reactive power of branch g during period t; U jt is the voltage of load node j during period t; U 1 is the reference voltage;I g is the set of load nodes directly connected to branch g; M is an infinite constant; σ is the voltage deviation.

[0080] The pre-disaster and post-disaster two-stage load recovery model maximizes the comprehensive benefit objective function F t and minimize the total integrated objective function F 3 get.

[0081] The beneficial effects of the present invention compared with the prior art are as follows: the present invention is a two-stage load recovery method before and after disasters that takes into account the coordinated application of emergency mobile resources (Emergency Power Supply, EPS) and distributed power islands. First, a pre-disaster EPS pre-disaster scheduling model that balances the mobility characteristics and operating costs is proposed for emergency mobile resources in active distribution networks; secondly, on the basis of the pre-disaster EPS pre-dispatching model, the volatility of distributed photovoltaic output is considered, and the primary and secondary dual objective functions are established from the two aspects of load shedding and network loss, and normalized into a post-disaster island recovery scheduling model that comprehensively considers the coordinated application of EPS, fixed energy storage and distributed power islands; finally, the proposed pre-disaster-post-disaster two-stage load recovery model is applied to improve the N-5 fault under IEEE 33 nodes. The example shows that the proposed pre-disaster-post-disaster two-stage load recovery model can obtain the optimal EPS scheduling path and the optimal island division method, and compared with not considering pre-disaster pre-disaster scheduling, it can restore the interrupted load more quickly and effectively. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] The present invention will be further described below in conjunction with the accompanying drawings:

[0083] Figure 1 This is the architecture diagram of the active distribution network scenario;

[0084] Figure 2 is a flow chart of the method of the present invention;

[0085] Figure 3 To improve the IEEE 33-node distribution network topology diagram;

[0086] Figure 4 It is a curve diagram of traffic network congestion degree;

[0087] Figure 5 This is a graph showing the photovoltaic output prediction after a disaster occurs;

[0088] Figure 6 Provide a location map for EPS access at different times after a disaster;

[0089] Figure 7 It is the charging and discharging power diagram of EPS in each time period;

[0090] Figure 8 It is the charge state curve diagram of EPS in each time period;

[0091] Fig. 9 It is a total power curve of power supply load in each time period;

[0092] Fig.10 It is the load recovery ratio diagram for each time period;

[0093] Fig.11 This is the island recovery result diagram considering EPS scheduling from 4 to 6 o'clock;

[0094] Fig.12 This is the result diagram of island recovery from 8:00 to 10:00 considering EPS scheduling;

[0095] Fig.13 This is the result diagram of island recovery from 12:00 to 14:00 considering EPS scheduling;

[0096] Fig.14 This is the output power diagram of ESS during the post-disaster recovery phase. DETAILED DESCRIPTION

[0097] like Figures 1 to 14 As shown, the present invention provides an island recovery method considering the optimal scheduling of emergency mobile resources. First, a pre-disaster EPS pre-scheduling model that balances the mobility characteristics and operating costs of emergency mobile resources (Emergency Power Supply, EPS) in the active distribution network is proposed; secondly, on the basis of the pre-disaster EPS pre-scheduling model, the volatility of distributed photovoltaic output is considered, and a primary and secondary dual objective function is established from the two aspects of load shedding and network loss, and is normalized into a post-disaster island recovery scheduling model that comprehensively considers the coordinated application of EPS, fixed energy storage and distributed power source islands; finally, the pre-disaster EPS pre-scheduling model is combined with the post-disaster island recovery scheduling model to obtain a pre-disaster-post-disaster two-stage load recovery model.

[0098] The present invention is described in detail below.

[0099] 1. Active distribution network scenario framework

[0100] The large-scale access of distributed power resources has endowed active distribution networks with more flexible and effective fault recovery strategies, providing new methods and opportunities for enhancing the resilience of distribution networks. Figure 1As shown in the figure, the active distribution network is a small power generation and distribution system composed of fixed power system energy storage (ESS), photovoltaic power (PV), residential power load, AC and DC drive and protection devices. It is an autonomous system that can achieve self-control, protection and management. There are two types of distributed power sources in the active distribution network: one is uncontrollable distributed generation (DG), which refers to general wind power (WT) and photovoltaic (PV) power generation. Its characteristics are that the output has large fluctuations and is difficult to adjust; the other is controllable DG, which is typically represented by ESS, diesel engines and gas turbines. The output power of its power supply is stable, and it has the ability to adjust its output according to the changes of other power sources and loads in the network. Through comprehensive control strategies, it can maintain the stability of voltage and frequency in the island.

[0101] When an extreme disaster strikes, the load recovery resources in the active distribution network will work together to maintain the stability of the grid. ESS can release energy during grid failures to provide temporary power support for critical loads, helping to smooth grid supply and demand fluctuations and maintain grid stability; when a main grid failure occurs, PV will work with ESS to form an island to ensure the basic power supply needs of local critical loads; EPS can quickly isolate the fault area in the event of a fault to prevent the fault from spreading, and can quickly dispatch to provide continuous power supply to critical loads to ensure their normal operation.

[0102] 2. Active distribution network load restoration resource model

[0103] Aiming at the role of coordinated fault recovery among various systems in active distribution network fault scenarios, an active distribution network load recovery resource model is designed. The model mainly focuses on ESS, EPS and distributed generation islands.

[0104] 2.1 ESS model

[0105] ESS can realize load supply within a certain range through orderly charging and discharging. The charging and discharging model is represented by the state of charge (SOC), and its mathematical model can be expressed as:

[0106] (1);

[0107] In order to prevent the ESS from overcharging or overdischarging, it is necessary to constrain the SOC state and the charging and discharging power per unit time period, which can be expressed as:

[0108] (2);

[0109] Where: SOCk,t is the charging state of the energy storage system at the kth fixed energy storage at the tth period; Δ t is the time step; P k,t-1 is the charging and discharging power of the kth fixed energy storage in the t-1th period; E k is the total fixed energy storage capacity in the energy storage system; D It is the collection of fixed energy storage in the energy storage system; and The minimum and maximum values ​​of the state of charge of the energy storage system; and is the charging and discharging power of the energy storage system for the kth fixed energy storage in time period t; and is the maximum value of the charging and discharging power of the energy storage system of the kth fixed energy storage in the t period; and is a 0-1 variable. If the energy storage system is charged, =1, the energy storage system discharges =1.

[0110] 2.2 EPS Scheduling Model

[0111] EPS is a power guarantee device designed for critical loads to ensure rapid power support when the main power grid fails. The EPS system proposed in the present invention integrates a battery energy storage unit on a truck, thereby giving it the ability to charge and discharge flexibly across regions, hereinafter referred to as an emergency electric vehicle.

[0112] The EPS dispatch model ensures that emergency electric vehicles can achieve maximum efficiency in the power grid through precise calculations. The model first considers the responsiveness of the EPS system in time and space, and ensures that emergency electric vehicles can arrive at the charging and discharging stations on time by analyzing traffic conditions and estimated travel time. Secondly, the configuration of the EPS system when dividing the island is considered, so that it can efficiently and reliably serve as the main power source in the island.

[0113] 2.2.1 EPS spatiotemporal characteristics

[0114] The spatiotemporal characteristics of the EPS system need to clearly indicate the mobility characteristics of the EPS and its connection status with the power line. In order to fully express the spatiotemporal state of the EPS, the present invention introduces a 0-1 variable δ it , ε it , , , , and construct the following constraints;

[0115] (3);

[0116] (4);

[0117] (5);

[0118] (6);

[0119] (7);

[0120] Formula (3) indicates that the arrival and departure of EPS at the load node are consistent with the change of the specific location identification; Formula (4) indicates that an EPS can only appear on one load node, and will not appear on any load node during the scheduling process; Formula (5) indicates the state of EPS after leaving the load node; Formulas (6) and (7) are used to constrain the consistency of EPS arrival and departure to avoid confusion.

[0121] Where: δ it Indicates whether the EPS leaves the load node i at time t, 1 if it is leaving, otherwise 0; ε it Indicates whether EPS reaches load node i at time t, which is 1 if it reaches load node i, otherwise 0; Indicates whether the EPS is docked at load node i at time t. If it is docked at load node i, it is 1, otherwise it is 0; Indicates whether EPS is dispatched from load node i to load node j at time t, 1 if it is being dispatched, otherwise 0; It is an auxiliary 0-1 variable and has no practical meaning; Ω b Represents a collection of load nodes.

[0122] Among them, the minimum time in the EPS scheduling process consists of three parts, as shown in formula (8):

[0123] T ijt = T D + T M + T C (8);

[0124] Where: T ijt It represents the total dispatching time of EPS between two load nodes; T D represents the time required for EPS to disconnect at load node i; T M represents the transportation time of EPS between load nodes; TC It represents the time required for EPS to connect at load node j.

[0125] Formula (9) is used to constrain the running time of EPS between two load nodes; Formula (10) is used to constrain the rationality of EPS arrival and departure time;

[0126] (9);

[0127] (10).

[0128] 2.2.2 EPS Configuration Features

[0129] After a fault occurs, the emergency electric vehicle receives an order from the dispatch center and goes to a designated location to connect to the power grid to serve as a backup power source. Each emergency electric vehicle serves as the main power source in an isolated island, and its connection point should belong to a specific isolated island, as shown in the following formula (11):

[0130] (11);

[0131] Where: a is Divide the load node i into 0-1 variables, a is =1 means that load node i belongs to island s; a is =0 means that load node i does not belong to island s; z si Configure 0-1 variables for EPS, z si =1 means EPS is connected to load node i; z si =0 means that EPS is not connected to load node i; S is the set of all islands divided; Ω b is the set of all load nodes.

[0132] 2.3 Distributed Generation Island Model

[0133] Distributed power island refers to a local independently operated power system consisting of one or more distributed power sources (such as solar photovoltaic, wind power, fixed energy storage, etc.) and the loads they supply when the main power grid fails or is unavailable. This configuration can ensure the power supply of local critical loads when the main power grid fails, thereby improving the resilience and reliability of the power grid.

[0134] The distributed generation island model mainly considers two aspects: on the one hand, how to effectively divide the power grid into several islands to achieve fault isolation and load recovery, that is, the island division characteristic; on the other hand, how to effectively manage the power flow within the island to achieve reasonable power distribution and voltage stability, that is, the island power flow balance characteristic.

[0135] 2.3.1 Island Division Characteristics

[0136] When dividing islands, ensure that each load node in the system can only belong to one island, that is, satisfy the following conditions:

[0137] (12).

[0138] When the branch (i, j) belongs to the divided island range, then the load nodes i, j must belong to the divided island range, and the expression is as follows:

[0139] (13);

[0140] Where: Divide the branch (i, j) island into 0-1 variables, =1 means branch (i, j) belongs to island s; =0 means that branch (i, j) does not belong to island s; Represents the set of all branches in the system. Only when both ends of the branch are on the island s =1. a js Divide the load node j into 0-1 variables.

[0141] make x ij represents the opening and closing state of branch (i, j), that is, the recovery decision 0-1 variable of branch (i, j), so:

[0142] (14);

[0143] Where: x ij =1 means branch (i, j) resumes operation, x ij =0 means that branch (i, j) is removed from the system.

[0144] 2.3.2 Island current balance characteristics

[0145] Using the linearized DistFlow formula, the power flow equation of the active distribution network containing ESS is established, and its expression is as follows:

[0146] (15);

[0147] (16);

[0148] (17);

[0149] Where: and They represent the set of branches where power flows into and out of load node i respectively; is the active power of load node i in period t; is the active power of the kth DG in period t; is the active power of the kth EPS in period t; r i is a 0-1 variable. When the kth EPS is transferred from any load node to the candidate access point on load node i to supply power to the island within the t period r i =1, otherwise r i =0; s i,t is the load connection state. If the i-th load is restored by DG or EPS within the t period, then s i,t =1, otherwise s i,t =0; is the reactive power of load node i in period t; and are the reactive powers of the kth ESS and EPS in period t respectively; is the reactive power demand of the i-th load in period t; Represents the binary variable of the branch. When the flow moves from load node i to load node j in period t, is 1, otherwise it is 0; r g and x g are the resistance and reactance of branch g respectively; U i,t is the voltage of load node i during period t; is the active power of branch g during period t; is the reactive power of branch g during period t; U jt is the voltage of load node j during period t; U 1 is the reference voltage, which is taken as 1. I g is the set of load nodes directly connected to branch g; M is an infinite constant, and the voltage is decoupled using the BIG-M method; σ is the voltage deviation, which is 5% in this embodiment.

[0150] 3. Pre-disaster and post-disaster two-stage load recovery model

[0151] Based on the load recovery resource model of active distribution network, a two-stage load recovery model of pre-disaster and post-disaster is established considering the coordinated application of EPS and distributed generation islands.

[0152] 3.1 Pre-disaster EPS pre-configuration and optimization scheduling

[0153] Compared with fixed energy storage, EPS has higher mobility and can quickly isolate the fault area when a fault occurs to prevent the fault from spreading. At the same time, it can quickly dispatch to provide continuous power supply for critical loads to ensure their normal operation. Economy is the key to the spatiotemporal scheduling of emergency electric vehicles. Therefore, the present invention generates a pre-disaster EPS pre-dispatching model that balances mobility characteristics and operating costs for the EPS in the active distribution network, aiming to comprehensively consider the multi-dimensional operating costs of EPS in the pre-dispatching stage, thereby reducing the dispatching cost while reducing the load outage loss.

[0154] Based on the above requirements, the objective function of the pre-disaster EPS pre-dispatching model is established:

[0155] (18);

[0156] Where: F t represents the comprehensive benefit objective function; Indicates the charging and discharging benefits based on real-time electricity prices and demand response; Represents the additional benefits under the sharing economy model; C op represents EPS mobile operating cost; C d represents the EPS battery loss cost; C m Represents EPS maintenance cost.

[0157] in:

[0158] (19);

[0159] Where: θ it is the electricity price of load node i at time t, T is the scheduling time set;

[0160] (20);

[0161] Where: R n is the fee rate paid by user n based on usage, S nis the actual usage of user n during the time period. C sh is the additional maintenance cost in the shared model, including user support and billing system maintenance. N is the total number of users.

[0162] (twenty one);

[0163] Where: c op is the usage cost per unit time.

[0164] (twenty two);

[0165] Where: c d is the cost of unit battery capacity attenuation; s t is the fixed decay capacity of the battery per day (MWh).

[0166] C m = K m N m (twenty three);

[0167] Where: K m is the average cost per maintenance action of EPS; N m The total number of maintenance actions planned by EPS during the scheduling period.

[0168] 3.2 Post-disaster recovery of isolated islands

[0169] The post-disaster island recovery model is a response strategy for distribution networks in extreme situations such as large-scale power outages. The present invention assumes that the energy storage connected to the active distribution network includes PV, ESS and EPS. The present invention sets primary and secondary objective functions for optimization. The main objective function performs double-layer optimization. The first layer divides the island range according to the location of the emergency electric vehicle; the second layer finds the optimal load shedding strategy under a given topology and a given photovoltaic output scenario to minimize the load shedding amount. The secondary objective function is to minimize the sum of all losses in the network during the fault period.

[0170] The main objective function is shown in formula (24):

[0171] (twenty four);

[0172] Where: F 1 is the main objective function; ω iIndicates the load importance of load node i; It represents the active load size of load node i in period t; y i =1 means that load node i is cut off, y i =0 means that the load node i is included in the island operation range; T is the scheduling time set; Ω b represents the set of load nodes; x ij , , z si , a is is the first-level decision variable, which determines the EPS distribution location. x ij is the recovery decision 0-1 variable of branch (i, j), Divide the branch (i, j) island into 0-1 variables, z si Configure 0-1 variables for EPS, a is Divide the load node i island into 0-1 variables; , , U i,t is the second-level decision variable, the purpose is to find the optimal load shedding minimum. is the active power of branch g during period t, is the reactive power of branch g during period t, U i,t is the voltage of load node i during period t;

[0173] The secondary objective function is shown in equation (25) and equation (26):

[0174] (25);

[0175] (26);

[0176] Where: P l is the network loss of the entire distribution network system during period t; F 2 It is the secondary objective function, which represents the total network loss of the system during the fault period. is the active power of the kth DG in period t; is the active power of the kth EPS in period t; m is the total number of DGs and EPSs in the system; h is the total number of load nodes.

[0177] Using weight coefficient ω0 Normalize the primary and secondary objective functions, where the weight coefficient is defined by yourself and should not be too large; setting different weight coefficients will result in different recovery strategies; according to experience, the present invention sets the weight coefficient ω 0 Set to 0.2. The total integrated objective function is obtained:

[0178] F 3 = F 1 + ω 0 F 2 (27).

[0179] 3.3 Pre-disaster and post-disaster two-stage load recovery model

[0180] The two-stage load recovery model considering EPS optimal scheduling is as follows:

[0181] (28);

[0182] (29).

[0183] After obtaining the IEEE distribution network topology, based on the above-mentioned post-disaster island recovery model, the basic parameters of load, PV, ESS, and EPS are input; the fault branch, fault time, and fault duration are determined; finally, the pre-disaster and post-disaster two-stage load recovery model is brought in for solution. The specific solution process is as follows.

[0184] The present invention is further described below based on specific examples.

[0185] This embodiment will use the improved IEEE 33-node distribution network to perform simulation analysis in MATLAB. The improved IEEE 33-node distribution network topology diagram is as follows: Figure 3 As shown. It includes 38 branches, 1 power source head end reference voltage is 12.66kv, reference power is 10MVA, total network load is 2182+j1256kVA, total critical load is 1210+560kVA, and voltage deviation is 5%. This embodiment sets 2 EPS scheduling resources, 5 ESSs, and 5 photovoltaic power sources; the maximum active power of ESS1, ESS2, and ESS3 is 120kw, and the maximum active power of ESS4 and ESS5 is 100kw. The specific connection method is as follows Figure 3 As shown. The red dots in the figure are important loads, and their load importance is ω i Take 10; the green points are non-important loads, and their load importance is ω iTake 1. The specific parameters of EPS are shown in Table 1 and Table 3. The specific parameters of the photovoltaic power generation peak during normal operation and the output prediction curve after the disaster are shown in Table 2 and Table 3. Figure 5 As shown, for example, PV1 reaches 60% of its peak value, i.e. 72 kW, at 8 o'clock.

[0186]

[0187] Table 1 Basic parameters of EPS.

[0188]

[0189] Table 2 Peak photovoltaic power generation during normal operation.

[0190]

[0191] Table 3 EPS specific parameters.

[0192] This embodiment assumes that an extreme disaster such as full coverage of ice and snow occurs suddenly at 4 o'clock, causing the lines between the four load nodes 3-4, 7-8, 12-22, and 28-29 to fail. Figure 3 After the disaster, the traffic congestion in the 24-hour period is divided into different levels of severity. Figure 4 As shown, it is assumed that the actual road distance between the two load nodes is 3 km. It is estimated that the time from the completion of fault repair to the normal operation of the distribution network is 10 hours. It is also assumed that the EPS is fully charged; before the disaster occurs, the EPS has sufficient time to configure to the pre-arranged load nodes.

[0193] According to the system operation parameters and photovoltaic power generation parameters, the scheme for the pre-disaster EPS pre-deployment stage is shown in Table 4. The scheme is based on the same degree of failure at the same line before the disaster. The difference is that Scheme 1 does not consider the pre-disaster EPS through optimized scheduling, but fixes two EPS at load node 1 for energy supply; Scheme 2 considers the pre-distribution of EPS through optimized scheduling. The comprehensive benefits in Table 4 include charging and discharging benefits, battery maintenance costs, mobile resource scheduling costs, and system maintenance costs.

[0194]

[0195] Table 4 EPS pre-arrangement plan table.

[0196] The EPS scheduling resources in Scheme 1 are all fixed at the starting load node 1. Although this scheme can reduce the resource scheduling cost of EPS, the EPS fixed at load node 1 provides limited power to all fault locations, which reduces the charging and discharging benefits of restoring the fault. Therefore, the comprehensive benefit obtained by Scheme 1 is 3,156 yuan. The EPS in Scheme 2 is optimized and scheduled according to the node load power and its importance, and its distribution is pre-arranged to load nodes 12 and 24 respectively. Although the scheduling cost of EPS is increased, the benefits brought to the fault load are greatly improved compared with Scheme 1, and the final comprehensive benefit is increased by 38.4%.

[0197] Therefore, the pre-disaster EPS pre-dispatching strategy proposed in the present invention significantly increases the comprehensive benefits of dispatching EPS after a distribution network failure, verifying that the scheme is effective.

[0198] After a natural disaster occurs, multiple distributed power sources in the distribution network cooperate to supply energy to the load at the fault location. The relationship between the position and time of the load nodes connected to the two EPS is as follows: Figure 6 As shown by Figure 6 It can be seen that after the fault, EPS1 and EPS2 were at the pre-arranged load nodes 12 and 24 respectively before the disaster occurred. Due to the continuous change of light intensity, the photovoltaic output continues to change. Therefore, EPS continuously optimizes scheduling over time to meet the load power supply needs.

[0199] According to the load node location and load demand after EPS optimization scheduling, the relationship between the charging and discharging power and time of the two EPSs is as follows: Figure 7 As shown, Figure 7 The positive power represents the discharge state, and the negative power represents the charge state. It is not difficult to see that the two EPS are in the discharge state in most time periods, and are only in a stable or charge state when the light intensity is high and the photovoltaic output is large at noon. The relationship between the charge state and time of the two EPS is obtained from the charge and discharge power of the EPS in each period. Figure 8 As shown by Figure 8 It is not difficult to see that the charge state of EPS1 and EPS2 has generally been decreasing over time since the failure, with a stable or charging state only appearing at noon.

[0200] The power distribution network load power line chart for each period within 24 hours is as follows: Fig. 9 As shown by Fig. 9 It can be seen that after the fault occurred at 4 o'clock, the total load power of the distribution network was reduced to about 50% of the normal level. After the island recovery was carried out by the dispatch of EPS and the coordination of ESS and PV, it was restored to 82% of the normal level at 13:00 that afternoon. The recovery percentages of important loads and non-important loads were subdivided to obtain the following: Fig.10 The division result shown is given by Fig.10It can be seen that the recovery ratio of important loads is significantly higher than that of non-important loads, and the recovery rate is generally around 80%, or even up to 85%. This verifies that the recovery method proposed in the present invention maintains the normal operation of most important loads.

[0201] Depend on Figure 6 , Figure 11-13 It can be seen that at the moment of disaster occurrence and the post-disaster recovery stage, the two EPSs are connected to load nodes 12 and 24 according to scheme 2. At this time, the distribution network is divided into three isolated islands.

[0202] The ESS power generation during the post-disaster distribution network failure recovery period is as follows: Fig.14 As shown in the figure, the power generation capacity of ESS1, ESS2, and ESS3 is always 120kW, and the power generation capacity of ESS4 and ESS5 is always 100kW. It can be seen that after the disaster, the power supply output of all fixed energy storages during the fault time is peak value.

[0203] According to the above results, during the period of 4:00-6:00 after the fault occurs, the photovoltaic output is low due to less sunlight, so all ESSs supply energy according to the maximum active power. At the same time, EPS1 is transferred from the pre-configured load node 12 to the load node 31 for energy supply, and EPS2 goes to the load node 7 for energy supply after the pre-configured load node 24 supplies energy for 1 hour. Since ESS and EPS cooperate to supply important loads, the important loads are reduced less, and their recovery percentage reaches 82%, which verifies that the two-stage recovery strategy proposed in the present invention enables the distribution network to have better resistance after a fault occurs.

[0204] During the period of 8 to 10 o'clock after the fault occurred, the photovoltaic power generation power gradually increased due to the gradual increase in light, so that the power supply showed an overall growth trend, among which the percentage of important load recovery was about 85%. At this time, EPS1 was transferred from load node 31 to load node 12, and EPS2 reached load node 8. During the period of 10 to 12 o'clock after the fault occurred, the photovoltaic output gradually reached its peak, and EPS1 was transferred from load node 8 to load node 6, thereby supplying power to the island without photovoltaic power support. Except for the load node voltage at the connection of distributed power sources such as ESS, the voltage of other load nodes will produce large fluctuations; however, distributed power sources such as EPS and ESS provide part of the load power, so that the voltage at each load node has a certain support capacity, and its voltage drop is maintained within a reasonable fluctuation, thereby verifying that the strategy proposed in the present invention maintains the stability of the power grid.

[0205] During the period from 12:00 to 14:00 after the fault occurred, EPS2 had reached load node 27, and EPS1 stayed at load node 6. The photovoltaic power generation capacity decreased, but the power supply capacity of EPS1 and EPS2 for important loads was significantly improved, resulting in a slight increase in the overall power supply load power. The percentage of important load recovery in this period was as high as 85%, that is, the system's fault recovery capability reached a high level. The percentage of important load recovery at this time reached the highest.

[0206] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An island recovery method considering optimal scheduling of emergency mobile resources, characterized in that: The following steps are involved: Firstly, a pre-disaster EPS pre-dispatching model is proposed for emergency mobile resources in active distribution networks, which takes into account both mobility characteristics and operating costs. The objective function expression of the pre-disaster EPS pre-dispatching model is as follows: ； Where: F t represents the comprehensive benefit objective function; Indicates the charging and discharging benefits based on real-time electricity prices and demand response; Represents the additional benefits under the sharing economy model; C op represents EPS mobile operating cost; C d represents the EPS battery loss cost; C m represents the EPS maintenance cost; The constraints of the objective function of the pre-disaster EPS pre-scheduling model include: ESS charging and discharging constraints; EPS spatiotemporal constraints; EPS configuration constraints; Secondly, based on the pre-disaster EPS pre-dispatching model, considering the volatility of distributed photovoltaic output, a primary and secondary dual objective function is established from the two aspects of load shedding and network loss, and normalized into a post-disaster island recovery scheduling model that comprehensively considers the coordinated application of EPS, fixed energy storage and distributed power generation islands; The main objective function expression of the post-disaster island recovery scheduling model is as follows: ； Where: F 1 is the main objective function; ω i Indicates the load importance of load node i; It represents the active load size of load node i in period t; y i =1 means that load node i is cut off, y i =0 means that the load node i is included in the island operation range; T is the scheduling time set; Ω b represents the set of load nodes; x ij , , z si , a is is the first-level decision variable, which determines the EPS distribution location. x ij is the recovery decision 0-1 variable of branch (i, j), Divide the branch (i, j) island into 0-1 variables, z si Configure 0-1 variables for EPS, a is Divide the load node i island into 0-1 variables; , , U i,t is the second-level decision variable, the purpose is to find the optimal load shedding minimum. is the active power of branch g during period t, is the reactive power of branch g during period t, U i,t is the voltage of load node i during period t; The secondary objective function expression of the post-disaster island recovery scheduling model is as follows: ； ； Where: P l is the network loss of the entire distribution network system during period t; F 2 is the secondary objective function, which represents the total network loss of the system during the fault period; is the active power of the kth DG in period t; is the active power of the kth EPS in period t; m is the total number of DGs and EPSs in the system; h is the total number of load nodes; Using weight coefficient ω 0 Normalize the primary and secondary objective functions to obtain the total integrated objective function: F 3= F 1+ ω 0 F 2； The constraints of the overall integrated objective function include: ESS charging and discharging constraints; Distributed power generation islanding constraints; Distributed power generation island power flow balance constraints; Finally, the pre-disaster EPS pre-disaster scheduling model and the post-disaster island recovery scheduling model were combined to obtain a two-stage load recovery model of pre-disaster and post-disaster.

2. The island recovery method considering the optimal scheduling of emergency mobile resources according to claim 1 is characterized by: The expression is as follows: ； Where: Δ t is the time step; T is the scheduling time set; θ it is the electricity price of load node i at time t; , are the charge and discharge power of load node i at time t respectively; The expression is as follows: ； Where: R n The fee rate paid by user n according to usage; S n is the actual usage of user n in the time period; C sh is the additional maintenance cost under the sharing model, including user support and billing system maintenance; N is the total number of users; C op The expression is as follows: ； Where: c op is the usage cost of EPS per unit time; Indicates whether EPS is dispatched from load node i to load node j at time t, 1 if it is being dispatched, otherwise 0; C d The expression is as follows: ； Where: c d is the cost of unit battery capacity attenuation; s t is the fixed attenuation capacity of the battery per day; C m The expression is as follows: C m = K m N m ； Where: K m is the average cost per maintenance action of EPS; N m The total number of maintenance actions planned by EPS during the scheduling period.

3. The island recovery method considering the optimal scheduling of emergency mobile resources according to claim 2 is characterized by: ESS charging and discharging constraints include: ESS charging state constraint, its expression is as follows: ； The ESS power overcharge or overdischarge constraint is expressed as follows: ； Where: SOC k,t is the charging state of the energy storage system at the kth fixed energy storage at the tth period; Δ t is the time step; P k,t-1 is the charging and discharging power of the kth fixed energy storage in the t-1th period; E k is the total fixed energy storage capacity in the energy storage system; D It is the collection of fixed energy storage in the energy storage system; and The minimum and maximum values ​​of the state of charge of the energy storage system; and is the charging and discharging power of the energy storage system for the kth fixed energy storage in time period t; and is the maximum value of the charging and discharging power of the energy storage system of the kth fixed energy storage in the t period; and is a 0-1 variable. If the energy storage system is charged, =1, the energy storage system discharges =1.

4. The island recovery method considering the optimal scheduling of emergency mobile resources according to claim 2 is characterized in that: The EPS spatiotemporal scheduling constraints include constraints for indicating the mobility characteristics of the EPS and the connection status of the EPS and the power line, and constraints for indicating the scheduling time, wherein the expressions for indicating the mobility characteristics of the EPS and the connection status of the EPS and the power line are as follows: ； ； ； ； ； Where: δ it Indicates whether the EPS leaves the load node i at time t, 1 if it is leaving, otherwise 0; ε it Indicates whether EPS reaches load node i at time t, which is 1 if it reaches load node i, otherwise 0; Indicates whether the EPS is docked at load node i at time t. If it is docked at load node i, it is 1, otherwise it is 0; Indicates whether EPS is dispatched from load node i to load node j at time t, 1 if it is being dispatched, otherwise 0; It is an auxiliary 0-1 variable and has no practical meaning; Ω b represents a collection of load nodes; The constraints used to indicate the scheduling time include: The minimum time used to constrain the EPS scheduling process is expressed as follows: T ijt = T D + T M + T C ； Where: T ijt It represents the total dispatching time of EPS between two load nodes; T D represents the time required for EPS to disconnect at load node i; T M represents the transportation time of EPS between load nodes; T C represents the time required for EPS to connect at load node j; It is used to constrain the running time of EPS between two load nodes. The expression is as follows: ； The rationality used to constrain the arrival and departure time of EPS is as follows: 。 5. The island recovery method considering the optimal scheduling of emergency mobile resources according to claim 4 is characterized in that: The expression of EPS configuration constraint is as follows: ； Where: a is Divide the load node i into 0-1 variables, a is =1 means that load node i belongs to island s; a is =0 means that load node i does not belong to island s; z si Configure 0-1 variables for EPS, z si =1 means EPS is connected to load node i; z si =0 means that EPS is not connected to load node i; S is the set of all islands divided; Ω b is the set of all load nodes.

6. The island recovery method considering the optimal scheduling of emergency mobile resources according to claim 1 is characterized by: The distributed generation island partitioning constraint is used to ensure that each load node in the system can only belong to a certain island when performing island partitioning, that is, it satisfies: ； When the branch (i, j) belongs to the divided island range, then the load nodes i, j must belong to the divided island range, and the expression is as follows: ； Where: Divide the branch (i, j) island into 0-1 variables, =1 means branch (i, j) belongs to island s; =0 means that branch (i, j) does not belong to island s; Represents the set of all branches in the system; only when both ends of the branch are on the island s =1; a js Divide the load node j island into 0-1 variables; make x ij represents the opening and closing state of branch (i, j), that is, the recovery decision 0-1 variable of branch (i, j), so: ； Where: x ij =1 means branch (i, j) resumes operation, x ij =0 means that branch (i, j) is removed from the system.

7. The island recovery method considering the optimal scheduling of emergency mobile resources according to claim 1 is characterized by: The distributed generation island power flow balance constraint uses the linearized DistFlow formula to establish the power flow equation of the active distribution network containing ESS, and its expression is as follows: ； ； ； Where: and They represent the set of branches where power flows into and out of load node i respectively; is the active power of load node i in period t; is the active power of the kth DG in period t; is the active power of the kth EPS in period t; r i is a 0-1 variable. When the kth EPS is transferred from any load node to the candidate access point on load node i to supply power to the island within the t period r i =1, otherwise r i =0; s i,t is the load connection state. If the i-th load is restored by DG or EPS within the t period, then s i,t =1, otherwise s i,t =0; is the reactive power of load node i in period t; and are the reactive powers of the kth ESS and EPS in period t respectively; is the reactive power demand of the i-th load in period t; Represents the binary variable of the branch. When the flow moves from load node i to load node j in period t, is 1, otherwise it is 0; r g and x g are the resistance and reactance of branch g respectively; U i,t is the voltage of load node i during period t; is the active power of branch g during period t; is the reactive power of branch g during period t; U jt is the voltage of load node j during period t; U 1 is the reference voltage; I g is the set of load nodes directly connected to branch g; M is an infinite constant; σ is the voltage deviation.

8. The island recovery method considering the optimal scheduling of emergency mobile resources according to claim 1 is characterized by: The pre-disaster and post-disaster two-stage load recovery model maximizes the comprehensive benefit objective function F t and minimize the total integrated objective function F 3 get.

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