CN111555280A - Elastic power distribution network post-disaster recovery control method based on electricity-gas comprehensive energy system - Google Patents
Elastic power distribution network post-disaster recovery control method based on electricity-gas comprehensive energy system Download PDFInfo
- Publication number
- CN111555280A CN111555280A CN202010474058.5A CN202010474058A CN111555280A CN 111555280 A CN111555280 A CN 111555280A CN 202010474058 A CN202010474058 A CN 202010474058A CN 111555280 A CN111555280 A CN 111555280A
- Authority
- CN
- China
- Prior art keywords
- distribution network
- power distribution
- post
- disaster recovery
- network
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- 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
- H02J3/001—Methods to deal with contingencies, e.g. abnormalities, faults or failures
-
- 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
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
-
- 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
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A30/00—Adapting or protecting infrastructure or their operation
- Y02A30/60—Planning or developing urban green infrastructure
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses an electric-gas comprehensive energy system-based elastic power distribution network post-disaster recovery control method, which comprises the following steps of: carrying out power flow modeling on the network according to the fault; the method comprises the steps that with the aim of minimizing the cost of all recovery loss load post-disaster recovery strategies, an optimal coordination scheme is obtained for three post-disaster recovery measure models, namely a network reconstruction model, a diesel generator model and a gas turbine model; and judging whether the formed micro-grid meets the reliable operation condition, if not, moving the MESS according to the optimal path scheme until the formed micro-grid meets the reliable operation condition. The elastic power distribution network after-disaster recovery control operation method based on the electricity-gas comprehensive energy improves the elasticity of the power distribution network by three optimization strategies of network reconstruction, energy supply of a diesel generator or a MESS and energy supply of a natural gas network through a gas turbine and taking the lowest cost of the after-disaster recovery strategy as an optimization target, and guarantees quick and effective maximum recovery of power supply load by taking rescue load as a load constraint condition.
Description
Technical Field
The disclosure belongs to the technical field of elastic power distribution network system optimization, and particularly relates to an elastic power distribution network post-disaster recovery control method based on an electricity-gas comprehensive energy system.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
In recent years, with global temperature rise and increasingly severe environmental pollution, extreme weather is frequent. According to statistics, the average typhoon logging in every year in China is as high as 9.09, and extreme events such as typhoons, earthquakes, snowstorms and the like not only cause economic loss, but also threaten the life safety of people, and further hinder the development of social economy. The utilization of electric energy has penetrated the aspect of life, and if the economic loss is wanted to be reduced, the post-disaster reconstruction is accelerated, the normal life state is quickly recovered, and the continuation of the electric energy is essential. The foundation of the important energy source of providing electric energy in the power distribution network must bear the task of continuously supplying power for reconstruction after disasters without being seriously affected by disasters. Therefore, how to provide rapidity, high efficiency and economy for the recovery of the power distribution network after disaster is a challenge to be developed at present.
At present, various research ideas for the recovery of the power distribution network in the comprehensive energy system after the disaster exist, and the adopted models and methods are different. In terms of modeling methods, two common methods are mainly 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 aspect of 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 the aspect of optimizing the target, most of researches are focused on saving the maximum load loss of the system, and the economic consideration of the recovery of the power distribution network after the disaster is less. In the aspect of research content, most researches only adopt one or two measures to optimize together to recover the power supply with lost load, and few researches provide optimized combinations of various recovery measures while ensuring safety and economy through various optimization measures. In the aspect of an optimization method, one type of research adopts a Column-and-Constraint generational algorithm (C & CG) or a Benders algorithm and other multilayer iterative algorithms, the other type of research adopts a method for solving by a modeling solver, and a small number of research adopts ant colony algorithms and other intelligent algorithms, the iterative algorithms generally have the problems of complex modeling and difficult convergence, and the intelligent algorithms have the defect of easy sinking into a local optimal solution.
Disclosure of Invention
In order to overcome the defects of the prior art, the disclosure provides an elastic power distribution network post-disaster recovery control method based on an electricity-gas integrated energy system, and various post-disaster recovery measures are optimized and adjusted on the basis of ensuring that most loads of a system of the power distribution network post-disaster recover power supply.
In order to achieve the above object, one or more embodiments of the present disclosure provide the following technical solutions:
an elastic power distribution network post-disaster recovery control method based on an electricity-gas comprehensive energy system comprises the following steps:
carrying out power flow modeling on the network according to the fault;
the method comprises the steps that with the aim that the cost of a post-disaster recovery strategy for recovering all lost loads is the lowest, an optimal coordination scheme is obtained on the basis of three post-disaster recovery measure models including network reconstruction, a diesel generator and a gas turbine;
and judging whether the formed micro-grid meets the reliable operation condition, if not, moving the MESS according to the optimal path scheme until the formed micro-grid meets the reliable operation condition.
The above one or more technical solutions have the following beneficial effects:
(1) the elastic power distribution network after-disaster recovery control operation method based on the electricity-gas comprehensive energy improves the elasticity of the power distribution network by using three optimization strategies of network reconstruction, energy support of a diesel generator or an MESS and a natural gas network through a gas turbine and using the lowest cost of the after-disaster recovery strategy as an optimization target, and ensures the quick and effective maximum recovery of the power supply load by using the rescue load as a load constraint condition.
(2) And an optimal coordination scheme of three post-disaster recovery measures is provided, so that the power distribution network is guided to minimize the post-disaster recovery cost of the power distribution network while ensuring that the power supply load is completely recovered, and the safety, reliability and economy of the post-disaster recovery operation of the power distribution network are ensured.
(3) Through the movement of the MESS, the requirement of safe and reliable operation for a long time can be met in the microgrid after the network is reconstructed.
(4) By carrying out gridding division on the power distribution network, the optimal moving path of the MESS is optimized, and the optimal moving cost and moving time of the MESS are ensured.
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 detailed flow chart of a post-disaster recovery strategy provided in a first embodiment of the present disclosure;
fig. 2 is a diagram of a distributed computing framework provided in a first embodiment of 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 method aims to reduce the cost of recovery measures for the power distribution network after-disaster recovery, ensure that most of the power distribution network after-disaster recovers power supply, and improve the economy of the power distribution network after-disaster recovery. The disclosure provides an electric-gas comprehensive energy system-based elastic power distribution network post-disaster recovery control system and method. The method can meet the requirement of quickly and reliably recovering power supply after the power distribution network disaster, improve the economy of the power distribution network, and ensure the safety, reliability and economy of the power distribution network after the disaster.
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 elasticity-boosting method to which the present disclosure is directed is primarily the fourth stage-post-disaster recovery shown in fig. 1.
Example one
The embodiment discloses a post-disaster recovery control method for an elastic power distribution network based on an electricity-gas integrated energy system, which is specifically implemented by the following steps that (1) as shown in fig. 2, after a fault occurs and after emergency response of the elastic power distribution network is carried out, on the basis that most of loads in the elastic power distribution network can be guaranteed to recover power supply, firstly, power flow modeling is carried out on the existing state of the power distribution network, secondly, the lowest cost of a post-disaster recovery strategy is taken as an optimization target, three recovery strategies of network reconstruction, a diesel generator or MESS and a gas turbine are optimized and adjusted, model solution is carried out by taking the minimized cost as a target function, and finally, whether a formed micro-power distribution network meets the reliable operation condition is judged, and; and if not, moving the MESS according to the optimal path scheme.
In the embodiment, referring to fig. 2, the elastic distribution network post-disaster recovery control method based on the electricity-gas integrated energy system specifically includes firstly, performing power flow modeling on a network according to a fault position; secondly, on the basis of ensuring the power supply recovery of most loads, three post-disaster recovery measure models of network reconstruction, a gas turbine and a diesel generator or calling MESS are established, the lowest cost of the post-disaster recovery measures is taken as an optimization target, and the combination of post-disaster recovery strategies of three optimization measures is given by considering the network reconstruction constraint of a power distribution network, the natural gas network constraint, the energy conversion equipment constraint, the system installation element constraint, the recovery load constraint and the like; and finally, judging whether the formed micro-grid meets the condition of reliable operation or not according to the scheme result, moving the MESS by taking the shortest moving time as an optimization target according to the established power distribution network path model, and optimizing the scheme again until the micro-grid topological structure reconstructed by the network meets the condition of safe operation, thereby finishing the optimization. The optimization problem in the problem is solved by a Gurobi solver.
In the optimal coordination scheme for the optimal multiple measures, all recovered power supply loads are used as constraint conditions, network reconstruction is carried out through the installation site of a gas turbine and the photovoltaic installation site in a power distribution network, the power supply of the loads is guaranteed, the missing part is moved through a MESS or supplied by adding a diesel generator, the loads are all recovered, on the basis, the lowest cost of the various recovery measures is used as an optimization target, and an economic optimal post-disaster recovery strategy is provided.
And verifying whether the formed micro-grid can meet the conditions of normal safe and reliable operation.
If the condition is met, an economically optimal post-disaster recovery strategy is provided on the basis of meeting all the requirements of recovering the power supply load; if the optimal route of the MESS movement is not satisfied according to the optimal route scheme, the formed micro-grid can completely satisfy the scheme of normal and reliable operation.
If the microgrid formed after network reconstruction only contains photovoltaic or only contains energy storage, safe and reliable operation of the microgrid cannot be met, and therefore the route with the shortest time needs to be selected to move the MESS to provide the optimal moving route scheme of the MESS.
Key problem explanation:
1. power distribution network constraint and reconfiguration constraint
The power flow model of the power distribution network adopts a linearized DistFlow power flow model as shown below.
In the formula: k (i, j) represents a line k with the starting node and the ending node being i, j respectively, and e represents a node; omegaDLRepresenting a line set in the elastic distribution network;
and
respectively representing the active power and the reactive power flowing on the line k at the time t;
and
respectively representing active power and reactive power injected at a node e at the moment t;
representing the voltage magnitude at node i at time t αi,jIs a binary variable representing the on-off state of the line with i, j as the starting and stopping points, and α if the line is oni,j1, otherwise 0; ri,jAnd Xi,jRespectively representing the resistance and reactance of the line;
and
respectively representing the active power and the reactive power absorbed by the power distribution network at the moment t by the photovoltaic arranged at the node e; respectively representing active power and reactive power released by the stored energy installed at the node e at the moment t;
and
respectively representing the recovery load quantity of the node e at the time t;
and
respectively representing active power and reactive power charged by the stored energy installed at the node e at the moment t; pmaxAnd QmaxRespectively representing the maximum active and reactive power allowed to pass by the line; sk,maxRepresenting the maximum ampacity of the line k; u shapeminAnd UmaxRespectively representing the minimum value and the allowable voltage during normal operationA maximum value;
representing the load capacity of the point e at the time t; e and B respectively represent the number of nodes in the power distribution network and the number of formed islands planned after the fault; m is the number selected when the line voltage is processed by the large M method.
2. Natural gas flow restraint
Using dynamic natural gas transport equations
P＝c2ρ (15)
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 jth observation node at time t +1, Mj，tMass flow for the jth observation node at time t, Mi，tMass flow of the jth observation node 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 jth 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… (18)
Mi/Ai+Mi+1/Ai+1+Mi+2/Ai+2…＝0 (19)
3. Gas turbine constraints
Pgt＝ηgtMgt(20)
Pgt，min≤Pgt≤Pgt，max(21)
Pgt(t+Δt)-Pgt(t)≤rgtΔt (22)
Wherein P isgtFor active power generated by gas turbines, ηgtFor the efficiency of the gas turbine power generation, MgtMass 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.
4. Electric to gas restraint
MP2G＝ηP2GPP2G(23)
MP2G.min≤MP2G≤MP2G.max(24)
Wherein M isP2GInjection mass flow for electric gas-converting apparatus, ηP2GFor the operating efficiency of electric gas-converting apparatus, PP2GElectric power consumed for electric gas-converting apparatus, MP2G.minFor injecting into electric gas-converting apparatusLower limit of natural gas mass flow, MP2G.maxAnd injecting the upper limit of the mass flow of the natural gas for the electric gas conversion equipment.
5. 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.
6. Objective function
The objective function is that the cost of the post-disaster recovery measures is the lowest, and the cost of the post-disaster recovery measures comprises the cost of natural gas, the loss cost of energy conversion equipment, the switching cost of a network reconstruction remote control switch, the fuel cost of the MESS and the loss cost of lost load of consumed time.
min f＝min(f1+f2+f3+f4) (27)
f4＝CMESStload(31)
f5＝Cloadtload(32)
In the formula: f represents the total cost of the recovery measures after the disaster; f. of1Represents a natural gas cost; i, t respectively represent the ith gas turbine and the tth moment; f and T respectively represent the number of the gas turbines in the system and a planning time period; cnExpressing the unit natural gas price; mi，tRepresenting the node mass flow passed by the ith gas turbine at time t; f. of2Represents the energy conversion equipment loss cost; cpAnd CgRespectively representing the loss coefficients of a P2G device and a gas turbine device; f. of3Represents the loss cost of the remote control switch; ckA cost coefficient indicating one time of switching operation; k is a radical ofj,tThe switching state of the jth switch at the moment t is shown, the closed state is 1, and the open state is 0; f. of4Represents the fuel cost of the MESS; cMESSRepresenting the fuel cost factor per MESS unit time; t is tloadIndicating the MESS movement time; f. of5A total loss of load representing the time spent; cloadRepresenting the loss cost factor of the unpowered load when the MESS moves.
8. 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.
(1) MESS operating model
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, ηch,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 between two nodes shown in a table. The MESS is required to travel only on the grid lines. Assuming that the side length of the small grid 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(41)
In the formula: i, j are eachIndicating 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 time period concerned by the technical scheme is only a longer-term recovery stage after the disaster, and the economical efficiency of the power distribution network after recovery is optimized by optimizing various implementation schemes of recovery measures after the disaster on the premise of recovering important loads and most loads after the disaster, so that the power distribution network is operated safely, economically and reliably on the basis of ensuring that most loads are recovered after the disaster.
The objective function of the post-disaster recovery measure optimization is that the cost of the post-disaster recovery measure is the lowest, including the cost of natural gas, the loss cost of energy conversion equipment, the loss cost of a network reconstruction remote control switch, the fuel cost of the MESS and the loss cost of lost load of consumed time.
The constraint conditions comprise load constraint conditions in the power distribution network, power flow constraint conditions in the power distribution network, natural gas network power flow constraint, constraint conditions of installation elements in the power distribution network, and constraint conditions of operation and transportation of the energy storage power station.
According to the planned scheme, under the condition that the normal operation of the micro-grid is not met, the movable energy storage is selected to move, so that the micro-grid meets the condition of reliable operation for a long time, and then an economic recovery measure scheme for recovering the reliable operation of the power distribution network after a disaster is provided.
In other embodiments, a system for controlling operation of an electric-gas integrated energy system based resilient power distribution network after disaster recovery is disclosed, comprising:
and an objective function construction module in the post-disaster operation control system is set as an optimization objective for minimizing the cost of the post-disaster recovery strategy.
And the constraint condition setting module is used for setting the constraint conditions to be power distribution network system constraint conditions, power supply recovery load constraint conditions, natural gas network constraint conditions, energy conversion element conditions, photovoltaic constraint conditions, MESS operation constraint conditions and the like.
The measurement module is configured to determine network measurement values required for achieving the objective function according to the objective function and the constraint conditions, and specifically includes unrecovered power supply nodes 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 recovery scheme through optimization calculation of the algorithm according to the parameters measured by the measurement module, namely the optimal charging and discharging operation condition of the energy storage power station is obtained, the state of the power distribution network after network reconstruction and the output condition of the gas turbine feed back the obtained optimization result to the power distribution network, and at the recovery stage of the MESS, the control module shows that the MESS movement starting and receiving points in the power distribution network are given according to the load information of the power distribution network measured by the measurement module, so that the safe and economic operation of the power distribution network is realized.
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.
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 (10)
1. An elastic power distribution network post-disaster recovery control method based on an electricity-gas comprehensive energy system is characterized by comprising the following steps:
carrying out power flow modeling on the network according to the fault position;
establishing three post-disaster recovery measure models of network reconstruction, a gas turbine and a diesel generator or calling MESS based on power flow modeling, and obtaining an optimal coordination scheme by taking the lowest cost of the post-disaster recovery measures as an optimization target so as to obtain a micro-grid topological structure of the network reconstruction;
and judging whether the micro-grid topological structure reconstructed by the network meets the reliable operation condition, if not, moving the MESS by taking the shortest moving time as an optimization target until the micro-grid topological structure reconstructed by the network meets the reliable operation condition.
2. The elastic distribution network post-disaster recovery control method based on the electricity-gas comprehensive energy system as claimed in claim 1, wherein the optimal coordination scheme is obtained by: aiming at the three established post-disaster recovery measure models, the lowest cost of the post-disaster recovery measures is taken as an optimization target, and the post-disaster recovery strategy combination of the three optimization measures is obtained by considering power distribution network reconstruction constraint, natural gas network constraint, energy conversion equipment constraint, system installation element constraint and recovery load constraint.
3. The elastic power distribution network post-disaster recovery control method based on the electricity-gas comprehensive energy system as claimed in claim 1, characterized in that in the optimal coordination scheme, the network reconfiguration is performed through the installation site of a gas turbine and the installation site of a photovoltaic in the power distribution network by taking all the recovered power supply loads as constraint conditions, so as to ensure the power supply of the loads, the missing part is moved through the MESS or supplied by adding a diesel generator, so as to ensure that the loads are all recovered, and on the basis, the lowest cost of various recovery measures is taken as an optimization target, so that an economic optimal post-disaster recovery strategy is given.
4. The elastic distribution network post-disaster recovery control method based on the electricity-gas comprehensive energy system as claimed in claim 1, wherein if the microgrid formed after network reconstruction contains only photovoltaic or only stored energy and cannot meet safe and reliable operation of the microgrid, the route with the shortest time is selected to move the MESS to provide the optimal moving route scheme of the MESS.
5. The elastic power distribution network post-disaster recovery control method based on the electricity-gas comprehensive energy system as claimed in claim 1, wherein the power flow model of the power distribution network adopts a linearized DistFlow power flow model.
6. The electrical-pneumatic energy integration system-based elastic distribution network post-disaster recovery control method as claimed in claim 1, wherein the objective function is that the post-disaster recovery measure costs are the lowest, and the post-disaster recovery measure costs include a natural gas cost, a loss cost of an energy conversion device, a loss cost of a network reconfiguration remote control switch, a fuel cost of a MESS, and a loss-of-load cost of a consumed time.
7. The elastic power distribution network post-disaster recovery control method based on the electricity-gas comprehensive energy system as claimed in claim 1, wherein the MESS mainly comprises two parts, namely a power vehicle and a container energy storage system, wherein 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.
8. An elastic power distribution network after-disaster recovery control operation system based on an electricity-gas comprehensive energy system is characterized by comprising:
an objective function construction module in the post-disaster operation control system is set as an optimization objective with minimum post-disaster recovery strategy cost;
the constraint condition setting module is used for setting constraint conditions to be power distribution network system constraint conditions, power supply recovery load constraint conditions, natural gas network constraint conditions, energy conversion element conditions, photovoltaic constraint conditions and MESS operation constraint conditions;
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 recovery scheme through optimization calculation of the algorithm according to the parameters measured by the measurement module, namely the optimal charging and discharging operation condition of the energy storage power station is obtained, the state of the power distribution network after network reconstruction and the output condition of the gas turbine feed back the obtained optimization result to the power distribution network, and at the recovery stage of the MESS, the control module shows that the MESS movement starting and receiving points in the power distribution network are given according to the load information of the power distribution network measured by the measurement module, so that the safe and economic operation of the power distribution network is realized.
9. A terminal device comprising a processor and a computer-readable storage medium, the processor being configured to implement instructions; the computer-readable storage medium is used for storing a plurality of instructions, wherein the instructions are suitable for being loaded by a processor and executing the method for planning and operating the joint optimization of the distributed multi-scenario based electric-gas hybrid system according to any one of claims 1 to 7.
10. 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 execute a method for responding to an emergency after a disaster in an electric-gas integrated energy system-based distribution resilient network according to any of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010474058.5A CN111555280B (en) | 2020-05-29 | 2020-05-29 | Elastic power distribution network post-disaster recovery control method based on electricity-gas comprehensive energy system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010474058.5A CN111555280B (en) | 2020-05-29 | 2020-05-29 | Elastic power distribution network post-disaster recovery control method based on electricity-gas comprehensive energy system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111555280A true CN111555280A (en) | 2020-08-18 |
| CN111555280B CN111555280B (en) | 2022-04-29 |
Family
ID=72006796
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010474058.5A Active CN111555280B (en) | 2020-05-29 | 2020-05-29 | Elastic power distribution network post-disaster recovery control method based on electricity-gas comprehensive energy system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111555280B (en) |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112257944A (en) * | 2020-10-29 | 2021-01-22 | 山东大学 | Electric power emergency material optimal configuration method and system in elastic power distribution network |
| CN112260271A (en) * | 2020-10-10 | 2021-01-22 | 北京交通大学 | Method and device for generating power distribution network fault recovery strategy |
| CN112434442A (en) * | 2020-12-08 | 2021-03-02 | 湘潭大学 | Electric-gas region comprehensive energy system elasticity evaluation method based on heterogeneous dependency network |
| CN112751350A (en) * | 2020-12-28 | 2021-05-04 | 国网天津市电力公司电力科学研究院 | Method for making mobile energy storage space-time joint optimization scheduling strategy |
| CN112986731A (en) * | 2021-02-08 | 2021-06-18 | 天津大学 | Electrical interconnection system toughness assessment and improvement method considering seismic uncertainty |
| CN113010988A (en) * | 2021-04-13 | 2021-06-22 | 中国农业大学 | Post-disaster optimization recovery method and system for AC/DC hybrid power distribution network |
| CN113312761A (en) * | 2021-05-17 | 2021-08-27 | 广东电网有限责任公司广州供电局 | Method and system for improving toughness of power distribution network |
| CN114336749A (en) * | 2021-12-30 | 2022-04-12 | 国网北京市电力公司 | Power distribution network optimization method, system, device and storage medium |
| CN114678881A (en) * | 2022-04-06 | 2022-06-28 | 四川大学 | Method for quickly recovering power grid after earthquake disaster under V2G auxiliary support |
| CN115345391A (en) * | 2022-10-20 | 2022-11-15 | 广东电网有限责任公司 | Post-disaster recovery method and device for electric-gas energy system and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8988444B2 (en) * | 2011-12-16 | 2015-03-24 | Institute For Information Industry | System and method for configuring graphics register data and recording medium |
| CN106532684A (en) * | 2016-10-20 | 2017-03-22 | 燕山大学 | Active distribution network multi-fault repair method based on multi-agent system |
| CN109510196A (en) * | 2018-11-28 | 2019-03-22 | 燕山大学 | A kind of fault recovery betting model based on electric-gas coupled system |
| CN110222970A (en) * | 2019-05-30 | 2019-09-10 | 天津大学 | Consider that the spare gas-of energy storage is electrically coupled integrated energy system flexible scheduling method |
| CN111106622A (en) * | 2019-12-17 | 2020-05-05 | 南京理工大学 | Active power distribution network power supply recovery method based on RMPC |
-
2020
- 2020-05-29 CN CN202010474058.5A patent/CN111555280B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8988444B2 (en) * | 2011-12-16 | 2015-03-24 | Institute For Information Industry | System and method for configuring graphics register data and recording medium |
| CN106532684A (en) * | 2016-10-20 | 2017-03-22 | 燕山大学 | Active distribution network multi-fault repair method based on multi-agent system |
| CN109510196A (en) * | 2018-11-28 | 2019-03-22 | 燕山大学 | A kind of fault recovery betting model based on electric-gas coupled system |
| CN110222970A (en) * | 2019-05-30 | 2019-09-10 | 天津大学 | Consider that the spare gas-of energy storage is electrically coupled integrated energy system flexible scheduling method |
| CN111106622A (en) * | 2019-12-17 | 2020-05-05 | 南京理工大学 | Active power distribution network power supply recovery method based on RMPC |
Non-Patent Citations (2)
| Title |
|---|
| 任郡枝: "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", 《电力建设》 * |
| 齐世雄: "计及弹性恢复的区域综合能源***多目标优化调度", 《中国电力》 * |
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112260271A (en) * | 2020-10-10 | 2021-01-22 | 北京交通大学 | Method and device for generating power distribution network fault recovery strategy |
| CN112257944A (en) * | 2020-10-29 | 2021-01-22 | 山东大学 | Electric power emergency material optimal configuration method and system in elastic power distribution network |
| CN112434442B (en) * | 2020-12-08 | 2022-06-03 | 湘潭大学 | Elasticity evaluation method for electricity-gas region comprehensive energy system |
| CN112434442A (en) * | 2020-12-08 | 2021-03-02 | 湘潭大学 | Electric-gas region comprehensive energy system elasticity evaluation method based on heterogeneous dependency network |
| CN112751350A (en) * | 2020-12-28 | 2021-05-04 | 国网天津市电力公司电力科学研究院 | Method for making mobile energy storage space-time joint optimization scheduling strategy |
| CN112751350B (en) * | 2020-12-28 | 2024-03-19 | 国网天津市电力公司电力科学研究院 | Method for formulating mobile energy storage space-time combined optimization scheduling strategy |
| CN112986731A (en) * | 2021-02-08 | 2021-06-18 | 天津大学 | Electrical interconnection system toughness assessment and improvement method considering seismic uncertainty |
| CN112986731B (en) * | 2021-02-08 | 2022-12-02 | 天津大学 | Electrical interconnection system toughness assessment and improvement method considering seismic uncertainty |
| CN113010988B (en) * | 2021-04-13 | 2023-10-31 | 中国农业大学 | Post-disaster optimization recovery method and system for AC/DC hybrid power distribution network |
| CN113010988A (en) * | 2021-04-13 | 2021-06-22 | 中国农业大学 | Post-disaster optimization recovery method and system for AC/DC hybrid power distribution network |
| CN113312761A (en) * | 2021-05-17 | 2021-08-27 | 广东电网有限责任公司广州供电局 | Method and system for improving toughness of power distribution network |
| CN114336749A (en) * | 2021-12-30 | 2022-04-12 | 国网北京市电力公司 | Power distribution network optimization method, system, device and storage medium |
| CN114336749B (en) * | 2021-12-30 | 2023-10-27 | 国网北京市电力公司 | Power distribution network optimization method, system, device and storage medium |
| CN114678881A (en) * | 2022-04-06 | 2022-06-28 | 四川大学 | Method for quickly recovering power grid after earthquake disaster under V2G auxiliary support |
| CN114678881B (en) * | 2022-04-06 | 2023-03-07 | 四川大学 | Method for quickly recovering power grid after earthquake disaster under V2G auxiliary support |
| CN115345391A (en) * | 2022-10-20 | 2022-11-15 | 广东电网有限责任公司 | Post-disaster recovery method and device for electric-gas energy system and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111555280B (en) | 2022-04-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111555280B (en) | Elastic power distribution network post-disaster recovery control method based on electricity-gas comprehensive energy system | |
| CN105811409B (en) | A kind of microgrid multiple target traffic control method containing hybrid energy storage system of electric automobile | |
| Yang et al. | Resilience-oriented hierarchical service restoration in distribution system considering microgrids | |
| CN109919399B (en) | Day-ahead economic dispatching method and system for comprehensive energy system | |
| CN108233430B (en) | Alternating current-direct current hybrid micro-grid optimization method considering system energy volatility | |
| Zhang et al. | A coordinated restoration method of electric buses and network reconfiguration in distribution systems under extreme events | |
| Wang et al. | A hybrid transmission network in pelagic islands with submarine cables and all-electric vessel based energy transmission routes | |
| Li et al. | Optimized energy storage system configuration for voltage regulation of distribution network with PV access | |
| CN111563691A (en) | Performance evaluation method for AC/DC hybrid power distribution network accessed with new energy | |
| CN107622332A (en) | A kind of grid side stored energy capacitance Optimal Configuration Method based on static security constraint | |
| CN104868468A (en) | UPFC optimization configuration method based on life cycle cost | |
| CN109950928A (en) | A kind of active distribution network fault recovery method counted and charge and discharge storage is integrally stood | |
| Lu et al. | Clean generation mix transition: Large-scale displacement of fossil fuel-fired units to cut emissions | |
| CN111555282B (en) | Elastic power distribution network post-disaster emergency response operation control system and method | |
| CN104281984A (en) | Power supply method for microgrid economical operation | |
| Ma et al. | An overview on impacts of electric vehicles integration into distribution network | |
| CN104092209A (en) | Interactional micro-power-grid energy control processing method based on real-time feedback | |
| CN115719967A (en) | Active power distribution network energy storage device optimal configuration method for improving power supply reliability | |
| CN112736948A (en) | Power adjusting method and device for energy storage system in charging station | |
| Yang et al. | Multi-time scale collaborative scheduling strategy of distributed energy systems for energy Internet | |
| Sang et al. | The Power Planning of Interacted and Interconnected Microgrid in Pelagic Clustering Islands Based on Energy Storage Vessel Transport Route | |
| Liu et al. | Bi-level collaborative expansion planning for power grid and plants considering operational flexibility | |
| Li et al. | The rapid and coordinated charging strategy for private electric vehicles | |
| Cheng et al. | Research on optimal matching of renewable energy power generation system and ship power system | |
| CN110112778B (en) | Distributed energy networking power supply method and system for large-scale destruction of power grid |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |