CN111555282B - Elastic power distribution network post-disaster emergency response operation control system and method - Google Patents
Elastic power distribution network post-disaster emergency response operation control system and method Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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- H—ELECTRICITY
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- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
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Abstract
The invention discloses a system and a method for controlling the emergency response operation of an elastic power distribution network after a disaster, which comprises the following steps: judging whether the power distribution network after the disaster has partial power networks which do not meet the condition of normal operation or have no power supply according to the fault condition of the power distribution network after the disaster, and transferring the nearest movable energy storage system in the power distribution network to provide electric energy for the part of the power distribution network without the power supply; meanwhile, electric energy is provided for the power distribution network through the gas turbine based on the electricity-gas comprehensive energy network joint optimization, and the load recovery power supply amount is increased through the movable energy storage system and the gas turbine joint emergency response. On the basis of guaranteeing the normal operation of the natural gas network, the interconnection of the network is utilized, the power distribution network load loss is saved to the maximum degree in the first time, and the safe and stable operation of the post-disaster power distribution network is guaranteed.
Description
Technical Field
The disclosure belongs to the technical field of elastic power distribution network system optimization, and particularly relates to a system and a method for controlling emergency response operation of an elastic power distribution network after a disaster.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The electric power system and the natural gas system are closely related in all links such as transmission and use, the mutual blending of the two energy systems forms a basic framework of a modern comprehensive energy system, and ideas such as multi-energy complementation, pursuit of efficient utilization of energy and the like are paid more and more attention.
For a power distribution network system, the access of a natural gas system not only improves the diversity of energy supply system selection, but also correspondingly improves the flexibility of the operation of a power system. Simultaneously, the multi-energy system jointly optimizes the factor and the available resource that consider more comprehensively in whole operation, not only can realize the high-efficient utilization of the energy, improves the low carbon benefit, also can resume the power supply through gas turbine to electric power system's safe and reliable operation moreover, saves the lost load. Therefore, the emergency response operation control system and method for the elastic power distribution network for deploying the electricity-gas comprehensive energy source have important significance.
At present, the research ideas of the emergency response of the electricity-gas comprehensive energy source are various, and the adopted models and methods are different. Two modeling methods are commonly used, one is a simplified mathematical model based on physical description of a power grid and a natural gas network, and the other is a modeling method based on an energy hub. In the problem construction, one type of research is calculated by selecting a typical fault scene, and the other type of research adopts a random fault scene, an uncertain fault disconnection set and a decision variable optimization method to comprehensively consider the fault scene condition, but most research objects of the research only aim at the power distribution network. In terms of post-disaster recovery measures, most of research is only directed at post-disaster recovery, and rapidity is related to whether subsequent post-disaster recovery can be normally and rapidly operated, but few documents can independently consider the time period of emergency response.
In the aspect of optimization methods, one type of research adopts a Column-and-Constraint Generation algorithm (C & CG) or a Benders algorithm and other multilayer iterative algorithms, the other type of research adopts a modeling solver solution method, and a small number of research adopts ant colony algorithms and other intelligent algorithms. The core problem with the above scheme is that the maximum power supply cannot be quickly restored.
Disclosure of Invention
In order to overcome the defects of the prior art, the emergency response operation control method for the elastic power distribution network after the disaster is provided, the rapidness and timeliness of emergency repair are mainly considered, and a recovery strategy for the elastic power distribution network of the electricity-gas comprehensive energy after the disaster is laid.
In order to achieve the above object, one or more embodiments of the present disclosure provide the following technical solutions:
the emergency response operation control method after the elastic power distribution network disaster comprises the following steps:
judging whether the power distribution network after the disaster has partial power networks which do not meet the condition of normal operation or have no power supply according to the fault condition of the power distribution network after the disaster, and transferring the nearest movable energy storage system in the power distribution network to provide electric energy for the part of the power distribution network without the power supply;
meanwhile, electric energy is provided for the power distribution network through the gas turbine based on the electricity-gas comprehensive energy network joint optimization, and the load recovery power supply amount is increased through the movable energy storage system and the gas turbine joint emergency response.
Further technical scheme shifts the nearest movable energy storage system in the distribution network and provides electric energy for the distribution network part losing power supply, specifically:
establishing a gridding power distribution network traffic model;
establishing a transportation model of a mobile energy storage system MESS;
the moving route of the MESS is optimized by taking the shortest time as an optimization target.
According to the further technical scheme, a grid distribution network traffic model is established: firstly, the power distribution network structure is divided into grids, and the actual distance between each node can be represented by the distance on the graph between two nodes shown in the table.
According to the further technical scheme, a transportation model of the MESS of the movable energy storage system is established:
the MESS can only run on the grid line, and the time consumed in the recovery process after the MESS disaster is as follows:
tij,m＝nijΔL/vm
in the formula: i, j respectively denote the starting node of the line, tij,mRepresents the time required for the mth MESS to travel between nodes i and j; n isijThe number of the side lengths of the small grids between the nodes i and j is set; delta L is the side length of the small grid; v. ofmIndicating the average speed of the mth MESS traveling during the t period.
The further technical scheme is that the electric-gas comprehensive energy network-based combined optimization provides electric energy for the power distribution network through the gas turbine, and specifically comprises the following steps:
determining an optimized objective function of the emergency response after the disaster to restore the maximum power supply load of the power distribution network;
according to the fault condition, a power distribution network and natural gas network power flow model is established, and a network constraint condition, a constraint condition of energy conversion element P2G equipment, a constraint condition of each element in the network and an operation constraint and a path constraint of MESS are established;
solving the constraint to obtain the optimal charging and discharging operation condition of the energy storage power station, feeding the obtained optimization result back to the power distribution network, tracking the change of the node voltage of the power distribution network in real time, and realizing the safe operation of the power distribution network.
In a further technical scheme, the optimization objective function for determining the emergency response after the disaster is as follows:
in the formula:
power is restored for node e at time t.
On the other hand, the utility model discloses elastic distribution network emergency response operation control system after calamity, includes: the control server judges whether the power distribution network after the disaster has partial power networks which do not meet the normal operation condition or have no power supply according to the post-disaster fault condition of the power distribution network, and transfers the nearest movable energy storage system in the power distribution network to provide electric energy for the part of the power distribution network without the power supply;
meanwhile, electric energy is provided for the power distribution network through the gas turbine based on the electricity-gas comprehensive energy network joint optimization, and the load recovery power supply amount is increased through the gas turbine joint emergency response in the movable energy storage system and the natural gas system.
According to a further technical scheme, the movable energy storage system comprises a power vehicle and a container energy storage system, and the container energy storage system comprises an energy storage battery system, a monitoring system, a battery management system, a battery monitoring and displaying system, a container battery special air conditioner, an energy storage converter and an isolation transformer.
The above one or more technical solutions have the following beneficial effects:
according to the emergency response operation control method of the elastic power distribution network based on the electricity-gas comprehensive energy, the characteristic of interconnection of comprehensive energy networks is utilized to realize that after a disaster, energy support is provided for loads in the network mutually, the natural gas network provides energy support for the power distribution network through a gas turbine, the purpose of rapidly and maximally recovering power supply from lost loads is achieved, and by utilizing the mobility of the MESS, the purpose of rapidly recovering the loads is realized by providing energy support for a part without a power supply formed after the disaster.
According to the emergency response operation control method for the elastic power distribution network, on the basis of ensuring normal operation of a natural gas network, the interconnection of the network is utilized, so that the lost load can be saved to the maximum extent in the first time, and safe and stable operation of the power distribution network after a disaster is ensured; through the mobility of the MESS, the energy support for the disaster part is realized, and the rapidity and the effectiveness of the recovery after the disaster are improved; the two measures are jointly involved in the emergency response of the electricity-gas comprehensive energy after disaster, and the elasticity of the power distribution network is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure and are not to limit the disclosure.
FIG. 1 is a flow chart of a post-disaster response provided by a method of an embodiment of the present disclosure;
fig. 2 is a flowchart of an emergency response method of an electric-gas integrated energy-based flexible power distribution network provided by an embodiment method of the disclosure;
FIG. 3 is a schematic diagram of a meshing distribution network according to an embodiment of the present disclosure;
FIG. 4 is a modified IEEE33 node grid and Belgian 20 node natural gas network, one suitable system provided by the present method of transportable energy storage embodying the present disclosure.
Detailed Description
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present disclosure. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.
The invention provides an electric-gas integrated energy system-based emergency response control system and method for an elastic power distribution network after disaster, which aim to quickly recover the power supply of affected loads within a short time after a disaster, ensure that the disaster situation in the power distribution network is minimized, and maintain the safe and reliable operation of the power distribution network. The invention realizes the rapid and reliable recovery of load power supply after the power distribution network disaster and ensures the safe and reliable operation of the power distribution network.
The elastic lifting method of the power distribution network is divided into four stages as shown in figure 1 according to the time sequence, and elastic planning, preventive response, emergency response and recovery after disasters are carried out. The elastic planning mainly improves the disaster resistance of the power distribution network by configuring resources and planning network lines in the normal operation stage; the prevention response mainly aims at improving the disaster resistance capability of the power distribution network by taking certain measures before the forecast of the disaster; the emergency response mainly aims at how to readjust and restore the normal operation state of the power distribution network in a short time after a disaster occurs; the post-disaster recovery is mainly the last stage of the elastic improvement of the power distribution network, so that the economical efficiency of the post-disaster recovery of the power distribution network is improved and the means of elastic improvement measures are optimized while the situation that the power supply of the post-disaster load is almost completely recovered is ensured. Distribution network the present disclosure is directed to an elasticity boosting method that is primarily the third stage-emergency response shown in fig. 1.
Example one
The embodiment discloses a method for controlling the operation of an elastic power distribution network after-disaster emergency response, which is characterized in that a specific implementation flow of the elastic power distribution network after-disaster emergency response method based on an electricity-gas integrated energy system is shown in fig. 2, firstly, movable energy storage is preferentially moved to supply power to a network without a power supply part according to a fault condition and an established grid traffic model after the fault occurs, and a movable energy storage moving path is optimized by taking the shortest used time as an optimization target; meanwhile, the air network provides energy support for the power grid, the output of the adjustable equipment is optimized, and the maximum recovery of load power supply is ensured; the two measures respond together, the effect of quickly and reliably saving lost load to the maximum is achieved, and the safe and reliable operation of the power distribution network after disaster is quickly recovered is guaranteed.
The time period of interest in the present disclosure is only a short time after a disaster and belongs to the post-disaster emergency response phase. The scheme is adopted, the movable energy storage supplies power for the power-off part, the gas network supplies power for most of the power-off load of the power grid through the gas turbine, and the two measures simultaneously and emergently respond to quickly and effectively maintain the safe and reliable operation of the power distribution network.
According to the mesh traffic model, the MESS selects the path with the shortest time to move the MESS according to the fault condition, and supplies power to the distribution network of the power-off part in the network.
Wherein, the optimization goal of mobile movable energy storage is that the used time is shortest; and the maximum optimization target for recovering the maximum power supply capacity of the power distribution network is the optimization target of the emergency response of the electricity-gas comprehensive energy network after the disaster.
The constraint of mobile energy storage mainly considers a gridding power distribution network structure and an MESS traffic transportation model.
The constraint conditions in the electricity-gas comprehensive energy emergency response comprise constraint conditions of a power distribution network system, photovoltaic constraint, energy conversion equipment constraint, movable energy storage operation constraint, transportation constraint, load loss constraint, natural gas network constraint and the like.
In this embodiment, referring to fig. 2, the method for emergency response of the elastic power distribution network after disaster based on the electricity-gas integrated energy system specifically includes: and establishing an emergency response model of the electric-gas integrated energy system, wherein the model comprises MESS mobile response and combined optimization recovery power supply of the integrated energy network. The MESS response is carried out, and an optimal moving route is worked out by taking the shortest MESS moving time as an optimization target according to disaster conditions; the combined optimization of the comprehensive energy network takes the maximum recovered power supply load as an optimization target, considers power distribution network power flow constraint, system constraint, natural gas network constraint, energy conversion equipment constraint, constraint of installation elements in the system, recovered load constraint and the like as constraint conditions, and then adopts a Gurobi solver to solve.
Specifically, the emergency response comprises power flow constraints of the power distribution network and the natural gas network, and the emergency response model is a general model framework.
Specifically, a power flow model of the power distribution network is established, and a Distflow power flow model is adopted. And in order to solve by adopting a solver, a second-order cone relaxation mode is adopted to process the power flow model.
In addition, when the natural gas network model is established, a dynamic natural gas transmission equation comprising a momentum equation, a material balance equation and a state equation is adopted. Converting partial differential equations into differential forms of differential equations by adopting a solver to solve;
and establishing mathematical models of natural gas network constraint, MESS operation constraint, gas turbine constraint, photovoltaic constraint, P2G equipment constraint and the like.
Key problem explanation:
with regard to: MESS mobility response
The MESS mainly comprises two parts, namely a power vehicle and a container energy storage system. The container energy storage system generally comprises an energy storage battery system, a monitoring system, a battery management system, a battery monitoring and displaying system, a container battery special air conditioner, an energy storage converter, an isolation transformer and the like. Compared with a fixed battery energy storage system, the MESS is more flexible, convenient and easy to produce, assemble and maintain, and easy to realize accident isolation, and is widely applied to the scenes of peak regulation, frequency modulation, post-disaster recovery and the like under the normal operation condition of a power system.
And planning the position of the movable energy storage in time according to the fault condition after the disaster, and moving the MESS to the passive power distribution network part losing the power supply.
And establishing a gridding traffic model.
And establishing a transportation model of the MESS.
The traffic model is a meshed road model in a traffic network.
The transportation model is a MESS movement model introduced in (2) below.
The moving route of the MESS is optimized by taking the shortest time as an optimization target.
(1) Operational model for MESS
The operation model represents that the MESS participates in the charge and discharge power of the operation of the power distribution network and an operation constraint of the SOC state, and participates in the recovery of power supply of the power distribution network, and the traffic model represents that the MESS can reach a designated power distribution network node to participate in power supply through what path in the traffic network.
The MESS operation model considered in the present disclosure is the same as the fixed operation model, and is different only in the access node, and the MESS operation model is shown in formulas (1) to (8).
In the formula: m is a node set for installing the MESS; t is a set of recovery time after disaster;
and
respectively is the charging and discharging active power of the MESS at the node m in the time period t;
and
respectively charging and discharging reactive power of the MESS at the node m in the time period t; sPCS,max,mThe maximum apparent power of the energy storage converter of the mth MESS is obtained;
and
respectively the charge and discharge flag bits of the MESS at the node m during the period t,
indicating that if the MESS is in a charging state
Otherwise, the value is 0; pchmaxAnd PdismaxMaximum charging power and discharging power of MESS respectively; etach,mAnd ηdis,mCharge efficiency and discharge efficiency of the MESS at node m, respectively;
representing the SOC state of the MESS at the node m in the time period t; SOCminAnd SOCmaxRespectively, the lowest and highest limits of the SOC.
(2) MESS traffic model
According to the method, the traffic condition of the MESS in the post-disaster mobile transportation process is considered, a grid-divided power distribution network structure model is established, the power distribution network structure is firstly divided into grids by the model, and the actual distance between each node can be represented by the distance on the graph between the two nodes shown in the table. The MESS is required to travel only on the grid lines. The schematic diagram of the elastic distribution network divided by the grid method is shown in fig. 3. Assuming that the side length of the small grid on the graph is 1km, the MESS must travel on the grid line, and if the MESS is transferred from node 1 to node 6, the travel distance is 4 km. The time consumed in the recovery process after the MESS disaster is shown as a formula (9).
tij,m＝nijΔL/vm (9)
In the formula: i, j respectively denote the starting node of the line, tij,mRepresents the time required for the mth MESS to travel between nodes i and j; n isijThe number of the side lengths of the small grids between the nodes i and j is set; delta L is the side length of the small grid; v. ofmIndicating the average speed of the mth MESS traveling during the t period.
2. Joint optimization of integrated energy networks
And determining the optimal objective function of the emergency response after the disaster as the minimum load loss of the power distribution network.
According to the fault condition, a Power distribution network and natural Gas network Power flow model is established, and a network constraint condition, a constraint condition of Power to Gas (P2G) equipment, a constraint condition of each element in the network, and an operation constraint and a path constraint of the MESS are established.
Solving the constraint problem by using a Gurobi solver.
(1) Objective function
The objective function of the strategy proposed herein aims to restore the maximum available power load of the distribution network.
In the formula:
power is restored for node e at time t.
(2) Power flow constraint of power distribution network
The distribution network adopts a DistFlow power flow model and adopts second-order cone relaxation treatment:
wherein subscript k represents a branch; subscript i, j represents the start and end points of line k, respectively, and subscript e represents the node; the subscript t represents time; k (e,: indicates the branch k with the e point as the head, and k (e,: indicates the branch k with the e point as the tail, omegaALRepresenting an AC line set; pk,tAnd Qk,tRespectively representing active power and reactive power on a line k at the moment t; pInj e,tAnd QInj e,tRespectively representing the injected active power and reactive power of a node e at the moment t; rkAnd XkRespectively representing the resistance and reactance on line k; i is2,k,tAnd U2,i,tRepresenting variables in a newly defined second-order cone model, namely the square of the k current of the original line and the square of the voltage of the node i; pWT e,tRepresenting the active power of the fan flowing into the node e; pVSC e,tRepresenting the active power of the VSC flowing into node e; pch e,tAnd Pdis e,tRespectively representing the charge and discharge power of an energy storage power station installed at a node e; pLoad e,tAnd QLoad e,tRespectively representing the active load and the reactive load of the node e; psub e,tAnd Qsub e,tThe active power and the reactive power transmitted to the power distribution network by the transformer substation are respectively represented.
(3) Natural gas network model constraints
Using dynamic natural gas transport equations
P＝c2ρ (7)
Wherein A isij、Lij、dijRespectively, the sectional area, length, diameter of the pipeline, Mj，t+1Mass flow of the jth observation node at time t + 1, Mi，t+1Mass flow of the ith observation node at time t + 1, Mj,tMass flow for the jth observation node at time t, Mi，tFor the ith observation node mass flow at time t, pj，t+1Pressure of j observation node at time t + 1, pi，t+1Pressure of the ith observation node at time t + 1, pj，tFor the j-th observation node pressure at time t, pi，tPressure intensity of an ith observation node at the moment t, lambda is a friction coefficient of the pipeline,
for average flow velocity, Δ t is the time step, ρj，t+1Gas density, rho, at the jth observation node at time t +1i，t+1Gas density, rho, at the ith observation node at time t +1i，tGas density, rho, for the ith observation node at time tj，tAnd the gas density of the jth observation node at the moment t, c is the sound velocity, p is the gas pressure and rho is the gas density.
Natural gas networks also have some boundary constraints. The pipes connected with each other have the same gas density at the connecting point, and the mass flow of the same node needs to be balanced.
ρi,t＝ρi+1,t＝ρi+2,t... (10)
Mi/Ai+Mi+1/Ai+1+Mi+2/Ai+2...＝0 (11)
(4) Gas turbine constraints
Pgt＝ηgtMgt (12)
Pgt，min≤Pgt≤Pgt，max (13)
Pgt(t+Δt)-Pgt(t)≤rgtΔt (14)
Wherein P isatActive power, η, generated for gas turbinesgtFor the efficiency of the gas turbine power generation, MatMass flow of natural gas, P, for consumption by gas turbinesgt，minIs the lower limit of the active power output, P, of the gas turbinegt，maxIs the upper limit of the active power output, P, of the gas turbinegt(t + Deltat) is the active power of the gas turbine at time t + Deltat, Pgt(t) the active power of the gas turbine at time t, rgtFor gas turbine ramp rate, Δ t is the time step.
(5) Electric to gas restraint
MP2G＝ηP2GPP2G (15)
MP2G，min≤MP2G≤MP2G，max (16)
Wherein M isP2GFor injecting mass flow of electric gas-converting apparatus, etaP2GFor the operating efficiency of electric gas-converting apparatus, PP2GElectric power consumed for electric gas-converting apparatus, MP2G，minLower limit of mass flow, M, for injecting natural gas into electric gas-converting apparatusP2G，maxAnd injecting the upper limit of the mass flow of the natural gas for the electric gas conversion equipment.
(6) Photovoltaic confinement
The photovoltaic output is limited by environmental factors.
In the formula:
and
respectively representing the active power and the reactive power of the photovoltaic system absorbed by the power distribution network at the moment t;
representing the maximum photovoltaic output active power; tan θ represents the power factor of the photovoltaic.
A typical system for the present disclosure is shown in fig. 4, and comprises a 33-node distribution network power system and a 20-node natural gas system, wherein the distribution system comprises 3 photovoltaic devices and 2 MESS devices. The electric-gas system is coupled with 1 electric gas conversion device through 2 gas turbines.
An elastic power distribution network after-disaster emergency response operation control system based on an electricity-gas comprehensive energy system comprises the following control methods:
the target function construction module is set as an optimization target for saving the maximum load loss;
the constraint condition setting module is used for setting constraint conditions to be constraints of photovoltaic power, an energy storage system and system safe operation in the power distribution network, natural gas network constraint, mobile energy storage operation constraint, transportation constraint and the like;
the measuring module is configured to determine network measurement values required for realizing the objective function according to the objective function and the constraint conditions, and specifically comprises nodes which are not recovered to supply power in the power distribution network, nodes corresponding to the geographic positions of the nodes in the traffic network and the load loss amount of the nodes;
the control module is configured to obtain a calculation result through optimization calculation according to measured network parameters of the alternating current-direct current power distribution network through the algorithm, the optimal real-time charging and discharging power of the energy storage power station is obtained, the obtained optimization result is fed back to the power distribution network, the change of the network node voltage of the power distribution network is tracked in real time, and safe and economical operation of the power distribution network is achieved.
In other embodiments, a terminal device is disclosed that includes a processor and a computer-readable storage medium, the processor to implement instructions; the computer-readable storage medium is used for storing a plurality of instructions, and the instructions are suitable for being loaded by a processor and executing the method for planning and operating the joint optimization based on the distributed multi-scenario electric-gas hybrid system in the first embodiment.
In other embodiments, a computer-readable storage medium is disclosed, having stored thereon a plurality of instructions adapted to be loaded by a processor of a terminal device and to perform a method for emergency response after disaster of an electric-gas integrated energy system-based flexible power distribution network as described in the examples.
In the embodiment of the disclosure, whether a power distribution network subjected to disaster has a partial power network which does not meet the condition of normal operation or has no power supply is analyzed according to the fault condition, a nearest Mobile Energy Storage System (MESSs) in the power distribution network is transferred to provide electric energy for the power distribution network part losing the power supply, meanwhile, the electric-gas comprehensive energy network is optimized in a combined manner to rapidly provide electric energy through a gas turbine, and the two measures are combined to perform emergency response to improve the recovery load. According to the comprehensive energy emergency response strategy provided by the disclosure, the load power restoration amount is increased through the emergency response measure combining the two measures, the requirement on rapidity is met, and the maximum power restoration is realized rapidly.
Those skilled in the art will appreciate that the modules or steps of the present disclosure described above can be implemented using general purpose computer means, or alternatively, they can be implemented using program code executable by computing means, whereby the modules or steps may be stored in memory means for execution by the computing means, or separately fabricated into individual integrated circuit modules, or multiple modules or steps thereof may be fabricated into a single integrated circuit module. The present disclosure is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure, and various modifications and changes may be made to the present disclosure by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.
Although the present disclosure has been described with reference to specific embodiments, it should be understood that the scope of the present disclosure is not limited thereto, and those skilled in the art will appreciate that various modifications and changes can be made without departing from the spirit and scope of the present disclosure.
Claims (8)
1. The emergency response operation control method after the elastic power distribution network disaster is characterized by comprising the following steps of:
judging whether the power distribution network after the disaster has partial power networks which do not meet the condition of normal operation or have no power supply according to the fault condition of the power distribution network after the disaster, and transferring the nearest movable energy storage system in the power distribution network to provide electric energy for the part of the power distribution network without the power supply;
meanwhile, electric energy is provided for the power distribution network through the gas turbine based on the electricity-gas comprehensive energy network joint optimization, and the movable energy storage system and the gas turbine are combined to perform emergency response to increase the recovery load power supply quantity;
the combined optimization based on the electricity-gas comprehensive energy network provides electric energy for the power distribution network through the gas turbine, and specifically comprises the following steps:
determining an optimized objective function of the emergency response after the disaster to be the minimum load loss of the power distribution network; the optimization objective function for determining the emergency response after the disaster is as follows:
in the formula:
restoring the power supply amount for the node e at the time t;
according to the fault condition, a power distribution network and natural gas network power flow model is established, and a network constraint condition, a constraint condition of an energy conversion element electric-to-gas device, a constraint condition of each element in the network and an operation constraint and a path constraint of a movable energy storage system are established;
solving the constraint to obtain the optimal charging and discharging operation condition of the energy storage power station, feeding the obtained optimization result back to the power distribution network, tracking the change of the node voltage of the power distribution network in real time, and realizing the operation of the power distribution network.
2. The method for controlling the emergency response operation of the elastic power distribution network after the disaster, according to claim 1, is characterized in that a nearest movable energy storage system in the power distribution network is transferred to provide electric energy for the power distribution network part losing a power supply, and specifically comprises the following steps:
establishing a gridding power distribution network traffic model;
establishing a traffic transportation model of the movable energy storage system;
and optimizing the moving route of the movable energy storage system by taking the shortest time as an optimization target.
3. The elastic power distribution network post-disaster emergency response operation control method as claimed in claim 2, wherein a gridded power distribution network traffic model is established: firstly, the power distribution network structure is divided into grids, and the actual distance between each node can be represented by the distance on the graph between two nodes shown in the table.
4. The elastic power distribution network post-disaster emergency response operation control method as claimed in claim 2, wherein a traffic transportation model of the movable energy storage system is established:
the movable energy storage system can only run on the grid line, and the movable energy storage system consumes time in the recovery process after disaster:
tij,m＝nijΔL/vm
in the formula: i, j respectively denote the starting node of the line, tij,mRepresenting the time required by the mth movable energy storage system to travel between the nodes i and j; n isijThe number of the side lengths of the small grids between the nodes i and j is set; delta L is the side length of the small grid; v. ofmRepresenting the average speed of travel of the mth mobile energy storage system over the period of time t.
5. Elastic distribution network emergency response operation control system after calamity, characterized by includes: the control server judges whether the power distribution network after the disaster has partial power networks which do not meet the normal operation condition or have no power supply according to the post-disaster fault condition of the power distribution network, and transfers the nearest movable energy storage system in the power distribution network to provide electric energy for the part of the power distribution network without the power supply;
meanwhile, electric energy is provided for the power distribution network through the gas turbine based on the electricity-gas comprehensive energy network joint optimization, and the gas turbine joint emergency response in the movable energy storage system and the natural gas system increases the recovery load power supply quantity;
the combined optimization based on the electricity-gas comprehensive energy network provides electric energy for the power distribution network through the gas turbine, and specifically comprises the following steps:
determining an optimized objective function of the emergency response after the disaster to be the minimum load loss of the power distribution network; the optimization objective function for determining the emergency response after the disaster is as follows:
in the formula:
restoring power supply for node e at time tAn amount;
according to the fault condition, a power distribution network and natural gas network power flow model is established, and a network constraint condition, a constraint condition of an energy conversion element electric-to-gas device, a constraint condition of each element in the network and an operation constraint and a path constraint of a movable energy storage system are established;
solving the constraint to obtain the optimal charging and discharging operation condition of the energy storage power station, feeding the obtained optimization result back to the power distribution network, tracking the change of the node voltage of the power distribution network in real time, and realizing the operation of the power distribution network.
6. The system for controlling emergency response operation of the elastic power distribution network after disaster as claimed in claim 5, wherein the movable energy storage system comprises a power vehicle and a container energy storage system, and the container energy storage system comprises an energy storage battery system, a monitoring system, a battery management system, a battery monitoring and displaying system, a container battery special air conditioner, an energy storage converter and an isolation transformer.
7. A terminal device comprising a processor and a computer-readable storage medium, the processor being configured to implement instructions; a computer readable storage medium for storing a plurality of instructions, wherein the instructions are adapted to be loaded by a processor and to perform the steps of the method for controlling operation of a resilient power distribution network in emergency response after a disaster as claimed in any one of claims 1 to 4.
8. A computer readable storage medium having stored thereon a plurality of instructions, wherein the instructions are adapted to be loaded by a processor of a terminal device and to perform the steps of the method for controlling operation of a resilient power distribution network in emergency response after disaster according to any of claims 1-4.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106877397A (en) * | 2017-03-22 | 2017-06-20 | 燕山大学 | A kind of active distribution network isolated island restoration methods based on game theory for considering Demand Side Response |
| WO2019236193A1 (en) * | 2018-06-04 | 2019-12-12 | Wellhead Power Solutions, Llc | Hybrid energy system and method |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2019236193A1 (en) * | 2018-06-04 | 2019-12-12 | Wellhead Power Solutions, Llc | Hybrid energy system and method |
Non-Patent Citations (1)
| Title |
|---|
| 考虑可移动式储能与网络重构的弹性配电网灾后恢复策略;任郡枝 等;《电力建设》;20200331;第41卷(第3期);第86-92页 * |
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