Post-disaster self-healing recovery method for regional electricity-heat-gas comprehensive energy system

Abstract

The invention discloses a post-disaster self-healing recovery method for a regional electric-thermal-gas integrated energy system, and the method comprises the steps: firstly constructing a post-disaster self-healing recovery model which comprises a multi-objective optimization function and constraint conditions; the power distribution network operation model, the thermal power network operation model, the gas network operation model and the energy storage equipment operation model are used for representing the operation characteristics of the integrated energy system; then determining a function weight in the multi-objective optimization function according to historical data; after a disaster occurs, dividing the integrated energy system into a plurality of to-be-recovered areas; and finally, solving the post-disaster self-healing recovery model, and controlling the operation of the integrated energy system by using the obtained self-healing recovery model. According to the method, reconstruction of the network topology of the post-disaster power distribution network system is realized, the post-disaster self-healing recovery model is established based on the to-be-recovered area, effective recovery of all nodes is ensured, energy loss in the recovery process is reduced, and the energy utilization efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric power dispatching, and in particular relates to a post-disaster self-recovery method for an energy system. Background Art

[0002] In recent years, in order to promote the transformation of energy production and consumption and build a low-carbon, safe, reliable and efficient modern energy system, my country has significantly increased the development and utilization of the Integrated Electricity-Heat-Gas System (IEHGS) to achieve complementarity among multiple energy systems. Ensuring the safe and reliable operation of IEHGS is the key to the development of the integrated energy system. However, frequent and large-scale power outages, heat outages, gas outages and other failures caused by extreme disasters have brought unprecedented challenges to the operation of the integrated energy system.

[0003] At present, with the increase in the number of renewable energy grid-connected, the network topology at the distribution network system level has changed significantly. The existing self-healing recovery methods have the following problems: First, they fail to effectively rebuild the system network after the disaster, resulting in some nodes not being restored, or high losses during the recovery process, and failure to effectively utilize energy. Secondly, the existing methods only focus on the recovery of electrical loads, and fail to take into account the complementarity and substitutability of various energy sources in the integrated energy system, resulting in high power consumption, difficulty in recovery, slow recovery speed, low utilization of heat and gas energy, and poor recovery effect. Summary of the invention

[0004] The present invention proposes a post-disaster self-recovery method for a regional electric-heat-gas integrated energy system, the purpose of which is: 1. To solve the problem of network topology reconstruction of the distribution network system after a disaster, ensure the effective recovery of all nodes, reduce energy loss during the recovery process, and improve energy utilization efficiency; 2. To fully consider the complementarity and substitutability between various energy sources, optimize the energy consumption structure, improve the utilization rate of heat and gas energy, and enhance the overall recovery effect.

[0005] The technical solution of the present invention is as follows:

[0006] A post-disaster self-recovery method for a regional electric-heat-gas integrated energy system, comprising:

[0007] Step 1: construct a post-disaster self-recovery model, which includes a multi-objective optimization function and constraints, and also includes a distribution network operation model, a thermal network operation model, a gas network operation model, and an energy storage device operation model for representing the operation characteristics of the integrated energy system;

[0008] The multi-objective optimization function is constructed by weighting the first objective function and the second objective function by function weights. The first objective function includes the power consumption of the electric boiler during the recovery process, and the second objective function includes the heat load recovery amount and the gas load recovery amount.

[0009] The constraint conditions include safe operation constraints and balance relationship constraints within the area to be restored;

[0010] Step 2: Determine the function weights in the multi-objective optimization function based on historical data;

[0011] Step 3: After the disaster occurs, a connectivity analysis is performed based on the network topology of the integrated energy system after the disaster, the switch information of the distribution network, and the valve information of the pipelines in the heat network and the gas network. The integrated energy system is divided into multiple areas to be restored based on the principle of the shortest energy restoration path;

[0012] Step 4: Solve the post-disaster self-recovery model to obtain the output of each device in the integrated energy system in each time period, the charging and discharging power of each energy storage device in each time period, and the recovery amount of heat load and gas load; the output of each device in each time period and the charging and discharging power of each energy storage device in each time period constitute a self-recovery plan and issue it as an operation configuration to control the operation of the integrated energy system.

[0013] As a further improvement of the post-disaster self-recovery method of the regional electricity-heat-gas integrated energy system, the distribution network operation model includes:

[0014] Distributed photovoltaic power generation equipment model:

[0015]

[0016] Where: is the output power of distributed photovoltaic power generation equipment in period t, in kW; Y PV is the rated capacity of distributed photovoltaic power generation equipment, I S I is the rated solar radiation that the photovoltaic surface can withstand and is related to the photovoltaic manufacturing materials. t is the total solar radiation on the photovoltaic surface during period t, f PV is the attenuation factor;

[0017] Distributed wind power generation equipment model:

[0018]

[0019] Where: w t is the speed of the distributed wind power generation equipment during period t; is the output power of the distributed wind power generation equipment during period t, w1, w cutout and wr are the cut-in speed, cut-out speed and rated speed of distributed wind power generation equipment respectively; P nom is the rated output power of the distributed wind power generation equipment, k1 and k2 are the linear coefficients of the distributed wind power generation installed power;

[0020] Cogeneration plant power model:

[0021]

[0022] Where: is the output power of the cogeneration equipment during period t; is the fuel consumption of the cogeneration equipment in period t, in m 3 ; is the start / stop status of the cogeneration equipment in period t, which takes the value of 1 or 0, 1 means start, and 0 means shutdown; is the electricity conversion efficiency of the cogeneration equipment; LHV is the lower heating value of natural gas; is the output thermal power of the waste heat boiler in the cogeneration equipment during period t;

[0023] Gas Turbine Model:

[0024]

[0025] Where: is the output power of the gas turbine during period t; is the start / stop state of the gas turbine during period t, which takes the value of 1 or 0, 1 represents start, and 0 represents shutdown; is the fuel consumption of the gas turbine during period t; is the gas turbine electricity conversion efficiency.

[0026] As a further improvement of the post-disaster self-recovery method of the regional electricity-heat-gas integrated energy system, the thermal network operation model includes:

[0027] Thermal model of cogeneration equipment:

[0028]

[0029] Where: is the output power of the cogeneration equipment during period t; is the start / stop status of the cogeneration equipment in period t, which takes the value of 1 or 0, 1 means start, and 0 means shutdown; The heat conversion efficiency of the cogeneration equipment; is the output thermal power of the waste heat boiler in the cogeneration equipment during period t;

[0030] Gas boiler model:

[0031]

[0032] Where: is the output thermal power of the gas boiler during period t; The start / stop status of the gas boiler in period t, which can be 1 or 0, 1 means start, and 0 means shutdown; is the fuel consumption of the gas boiler during period t; is the heat conversion efficiency of the gas boiler; LHV is the lower heating value of natural gas;

[0033] Electric boiler model:

[0034]

[0035] Where: is the output thermal power of the electric boiler during period t, is the electric-to-heat conversion efficiency, is the input power of the electric boiler during period t; It is the start / stop status of the electric boiler during period t, and takes the value 1 or 0, 1 means on, and 0 means off.

[0036] As a further improvement of the post-disaster self-recovery method of the regional electricity-heat-gas integrated energy system, the thermal network operation model also includes a heating pipe network model;

[0037] The heating network consists of several nodes and pipes connected between the nodes. The heating network model includes:

[0038] Nodal thermal power and temperature balance equation:

[0039]

[0040] Where: H p is the thermal power at node h; C p is the specific heat capacity of water; m h is the flow rate of the medium at node h; is the heating temperature at node h; is the regenerative temperature at node h;

[0041] Node traffic balance equation:

[0042]

[0043] Where: They are respectively a pipeline set with node h as the first head end and a pipeline set with node h as the first end end; are the flow rates of the heating part and the heat recovery part of pipeline k respectively;

[0044] Nodal temperature mixing equation:

[0045]

[0046] Where: They are respectively a pipeline set with node h as the first head end and a pipeline set with node h as the first end end; They are respectively represented as the outlet temperature of the heat supply part and the outlet temperature of the heat recovery part of pipe k; are the heating temperature and reheating temperature of node h respectively; are the flow rates of the heating part and the heat recovery part of pipeline k respectively;

[0047] If hot swapping does not exist for the node:

[0048]

[0049] Where: are the inlet temperature of the heat supply part and the inlet temperature of the heat recovery part of pipe k respectively;

[0050] Node pipe temperature loss equation:

[0051]

[0052] β k =λ k L k ;

[0053] Where: β k is the thermal distance of pipeline k, which is determined by the thermal conductivity and length of pipeline k; T a , k , L k are the ambient temperature, the thermal conductivity of pipe k and the length of pipe k respectively; C p is the specific heat capacity of water; are the inlet temperature and outlet temperature of the same part of pipeline k, respectively. Both the heat supply part and the heat recovery part are applicable to the above node pipeline temperature loss equation;

[0054] Node temperature constraints:

[0055]

[0056] Where: are the minimum and maximum values ​​of node temperature respectively;

[0057] Pipe temperature constraints:

[0058]

[0059] Where: are the minimum and maximum values ​​of the pipeline temperature, respectively, indicating that the temperature of each pipeline should be within a reasonable range; are the inlet temperature and outlet temperature of any part of pipe k respectively. Both the heat supply part and the heat recovery part are subject to the above pipe temperature constraints.

[0060] As a further improvement of the post-disaster self-recovery method of the regional electricity-heat-gas integrated energy system, in the gas network, there are two types of pipelines, namely, pipelines with compressors and pipelines without compressors. The gas network operation model includes:

[0061] Node traffic balance equation:

[0062]

[0063] Where: G s，m , G d,m are the natural gas supply and gas load of node m respectively; N m is the set of nodes directly connected to node m; G mn is the natural gas flow in the pipeline between nodes m and n; M m is the set of compressor nodes connected to node m; G c,k is the natural gas flow rate through compressor k; τ c,k is the natural gas flow consumed by compressor k; when node m is the inlet of compressor k, sgn k (m)=1, otherwise it is the exit, sgn k (m) = -1;

[0064] Pipeline transmission constraints:

[0065]

[0066] in:

[0067]

[0068] Where: G mn is the natural gas flow rate of pipeline mn from node m to node n; is the maximum flow rate that can pass through the pipe mn; π m , π n are the pressures at nodes m and n respectively; s mn is a function of the pipeline flow direction. When the pressure at node m is greater than the pressure at node n, s mn =1, otherwise -1; k mn is a coefficient related to pipeline length, inner diameter, compression coefficient, gas specific gravity, and temperature; η mn is the pipeline transmission efficiency; f mn is the friction coefficient of the pipe mn; L gp,mn is the length of the pipe mn; d mn is the inner diameter of the pipe mn; T is the average ambient temperature; Sg is the specific gravity of natural gas in the pipeline; Z is the natural gas compression coefficient;

[0069] Pipeline transport constraints with compressors:

[0070] G c,k =G out =G in -τ c,k ;

[0071] in:

[0072]

[0073] Where: G in , G out are the natural gas flow rates at the upper and lower ends of the pipeline from node m to node n and passing through compressor k; mi , k jn are the pipeline correlation coefficients between node m and compressor k inlet node i, and between node n and compressor k outlet node j; π m , π n are the pressures at nodes m and n respectively; π i , π j are the pressures of compressor inlet node i and compressor outlet node j respectively; G c,k is the natural gas flow rate through compressor k; τ c,k is the natural gas flow consumed by compressor k; LHV is the lower heating value of natural gas; T g is the natural gas temperature; a is the compressor variability index; k cp is the pressure ratio of compressor k;

[0074] Nodal pressure constraints:

[0075] π min ≤π m , π n ≤π max ;

[0076] Where: π min , π max are the minimum and maximum values ​​of node pressure within a reasonable range, respectively;

[0077] Gas source constraints:

[0078]

[0079] Where: They are respectively the minimum and maximum values ​​of the gas source output flow rate within a reasonable range.

[0080] As a further improvement of the post-disaster self-recovery method of the regional electric-heat-gas integrated energy system: the energy storage device includes an electric storage device, a heat storage device and a gas storage device, and the operation model of the energy storage device is:

[0081]

[0082] Where: λ∈{ESS,HES,GES}, ESS,HES,GES represent the three energy types of electricity, heat and gas respectively; is the energy stored by the λ type energy storage device in time period t, where the unit for the distribution network and thermal network is kW·h, and the unit for the gas network is m 3 ; are the charging power and discharging power of the energy storage device in time period t, respectively. The corresponding charging power and discharging power in the distribution network and thermal network are in kW, and the corresponding charging power and discharging power in the gas network are in m 3 / s; σ λ is the self-consumption rate of the energy storage device of type λ; η λ,cha , η λ,dis are the charging efficiency and discharging efficiency of the energy storage equipment respectively; Δt is a scheduling period;

[0083] Energy storage equipment also has the following constraints:

[0084]

[0085] Where: β λ，cha , β λ，dis are the maximum charging rate and discharging rate of the λ type energy storage device; SOC λ，min , SOC λ，max are the minimum load state and the maximum load state of the energy storage of the λ type energy storage device, respectively; Eλ is the rated storage capacity of the λ type energy storage device; They are the storage amounts of the energy storage of type λ at the start and end of the scheduling period.

[0086] As a further improvement of the post-disaster self-recovery method of the regional electricity-heat-gas integrated energy system, the safe operation constraints include:

[0087] Equipment output constraints:

[0088]

[0089] Where: P n，t is the actual output of the nth device in the integrated energy system during period t; are the maximum output value and minimum output value of the nth device respectively;

[0090] Distributed generation output constraints:

[0091]

[0092] Where: is the output power of distributed photovoltaic power generation equipment in period t, is the output power of the distributed wind power generation equipment in period t, and They are the maximum outputs of distributed photovoltaic power generation equipment and distributed wind power generation equipment respectively;

[0093] The balance relationship constraints within the area to be restored include:

[0094] Balance relationship within the distribution network area:

[0095]

[0096] Where: K PV , K WT , K CHP , K GT , K ESS , K EB They are the number of distributed photovoltaic power generation equipment, distributed wind power generation equipment, cogeneration equipment, gas turbines, power storage equipment, and electric boilers in a certain area to be restored; are the output powers of the kth distributed photovoltaic power generation equipment, the kth distributed wind power generation equipment, the kth cogeneration equipment, and the kth gas turbine in a certain area to be restored during the t period, which are decision variables; is the input power of the kth electric boiler in a certain area to be restored during period t; is the charging power and discharging power of the kth power storage device in a certain area to be restored during period t, which is the decision variable; is the post-disaster power load demand in a certain area to be restored, which is the decision variable;

[0097] Balance relationship within the thermal network area:

[0098]

[0099] Where: K GB , K HES They are the number of gas boilers and heat storage equipment in the area to be restored; are the output thermal powers of the kth cogeneration equipment, the kth gas boiler, and the kth electric boiler in the area to be restored during period t, which are decision variables; are the heat storage power and heat release power of the kth heat storage device in the area to be restored in period t, respectively, which are decision variables; is the post-disaster heat load demand in the area to be restored, which is the decision variable;

[0100] Balance relationship within the gas network area:

[0101]

[0102] Where: K GES is the number of gas storage facilities in the area to be restored; are the fuel consumption of the kth cogeneration equipment, the kth gas turbine, and the kth gas boiler in the area to be restored; is the post-disaster gas load demand in the area to be restored, which is the decision variable; are the inflation and deflation volumes of the kth gas storage device in the area to be restored during period t, respectively, and are decision variables.

[0103] As a further improvement of the post-disaster self-recovery method of the regional electricity-heat-gas integrated energy system, the multi-objective optimization function is:

[0104]

[0105] Where: F1 and F2 are the first objective function and the second objective function respectively; λ1 and λ2 are the function weights of the first objective function and the second objective function respectively, λ1 and λ2 are both greater than 0, and λ1+λ2=1; F 1，max 、F 1，min are the maximum and minimum values ​​of F1 calculated based on historical data, which are known variables; F 1，max 、F 2，min are the maximum and minimum values ​​of F2 calculated based on historical data, which are known variables;

[0106] The first objective function is:

[0107]

[0108] Where: N is the number of areas to be restored after the disaster; T is the number of time periods in a scheduling cycle; K EB is the number of electric boilers in the corresponding number of areas to be restored; is the input power of k electric boilers in the i-th area to be restored during period t;

[0109] The second objective function is:

[0110]

[0111]

[0112] Where: are the heat load recovery ratio and gas load recovery ratio in the i-th area to be restored respectively; ω h，i ,ω g,i are weight parameters representing the recovery ratio of heat load and the importance of gas load in the i-th area to be restored, respectively; are the post-disaster load recovery amounts of the heat network and gas network in the i-th area to be restored during period t; They are respectively the heat network load demand and gas network load demand in the i-th area to be restored during period t predicted before the disaster;

[0113] The weight parameters of heat load recovery ratio and gas load importance are calculated as follows:

[0114]

[0115] Where: θ h,q is the load weight of node q in the thermal network of the area to be restored; θ g，p is the load weight of node p in the regional gas network to be restored; N h and N g They are the number of heating network nodes and the number of gas network nodes in the area to be restored respectively.

[0116] As a further improvement of the post-disaster self-recovery method of the regional electricity-heat-gas integrated energy system, step 2 specifically includes:

[0117] Step 2-1, assign initial values ​​to weight values ​​λ1 and λ2, and set the number of iterations to 0;

[0118] Step 2-2, construct the objective function obj:

[0119]

[0120] Step 2-3: Select N groups of historical data on post-disaster recovery and substitute them into the calculation formulas of the first objective function and the second objective function to obtain F 1，history and F 2,history , then calculate obj, and record the function value of the objective function obj corresponding to the historical data of the nth group of post-disaster recovery as obj n , and then calculate the average value And increase the number of iterations by 1;

[0121] Step 2-4: Determine whether the number of iterations reaches a preset threshold. If so, use the current values ​​of weights λ1 and λ2 as their respective optimal values. Otherwise, continue to step 2-5.

[0122] Step 2-5: Average value The maximum is the goal, and the values ​​of weights λ1 and λ2 are updated through the gradient descent method, and then jump to step 2-3.

[0123] As a further improvement of the post-disaster self-recovery method of the regional electricity-heat-gas integrated energy system, step 3 specifically includes:

[0124] Step 3-1: After the disaster occurs, the original integrated energy system is divided into multiple areas based on the damaged lines in the distribution network and the damaged pipelines in the heat network and gas network;

[0125] Step 3-2: Identify the isolated nodes that have lost their energy supply source in the integrated energy system;

[0126] Step 3-3: Establish a recovery energy supply path according to the energy type required by the isolated node, the recovery energy supply path includes a power supply recovery path, a heat supply recovery path, and a gas supply recovery path;

[0127] For an island node that cannot be powered: find all the distribution network lines connected to the island node that are in the off state and not damaged by the disaster, calculate the electrical distance of each line, where the electrical distance refers to the self-impedance of the line, select the line with the shortest electrical distance as the power restoration path, and close the switch in the power restoration path;

[0128] For isolated island nodes that cannot provide heat: find all the thermal network pipelines connected to the isolated island node that are in the valve-closed state and not damaged by the disaster, and calculate the thermal distance of each pipeline. The thermal distance calculation method is: β k =λ k L k ; Among them, β k is the thermal distance of pipeline k, λ k , L k are the thermal conductivity of pipeline k and the length of pipeline k respectively; then the pipeline with the shortest thermal distance is selected as the path for restoring the heat supply, and the valve in the path for restoring the heat supply is opened;

[0129] For isolated nodes that cannot supply natural gas: find all gas network pipelines connected to the isolated node that are in valve-closed state and not damaged by the disaster, and calculate the natural gas distance of each pipeline. The natural gas distance calculation method is: α mn =(1.3305×10 5 )Tη mn ; Among them, α mn is the natural gas distance of pipeline mn between node m and node n in the gas network, T is the average ambient temperature, is the transmission efficiency of pipeline mn, f mn is the friction coefficient of the pipe mn; L gp,mn is the length of the pipe mn; dmn is the inner diameter of the pipeline mn; then the pipeline with the shortest natural gas distance is selected as the gas supply recovery path, and the valve in the gas supply recovery path is opened;

[0130] Step 3-4: according to the established energy restoration path, add the isolated island node to the area where the node on the opposite side of the energy restoration path is located, and the multiple areas finally formed are the areas to be restored.

[0131] Compared with the prior art, the present invention has the following beneficial effects:

[0132] 1. Based on the principle of the shortest energy recovery path, the present invention divides the integrated energy system into multiple areas to be restored, realizes the reconstruction of the network topology of the distribution network system after the disaster, and establishes a post-disaster self-healing recovery model based on the areas to be restored to ensure the effective recovery of all nodes, reduce energy loss during the recovery process, and improve energy utilization efficiency.

[0133] 2. The post-disaster self-recovery model in the present invention fully considers the complementarity and substitutability between different energy sources, optimizes the energy consumption structure through multi-objective optimization functions, constraints and different types of energy models, minimizes electricity consumption, improves the utilization efficiency of heat and gas resources, and accelerates the regional self-recovery speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0134] Figure 1 It is a schematic diagram of the topological structure of the regional electricity-heat-gas integrated energy system in a specific implementation method. DETAILED DESCRIPTION

[0135] The technical solution of the present invention is described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments.

[0136] A post-disaster self-recovery method for a regional electric-heat-gas integrated energy system, comprising:

[0137] Step 1: Construct a post-disaster self-recovery model, which includes a multi-objective optimization function and constraints, and also includes a distribution network operation model, a thermal network operation model, a gas network operation model and an energy storage device operation model for representing the operating characteristics of the integrated energy system.

[0138] Among them, the multi-objective optimization function is constructed by weighting the first objective function and the second objective function through function weights. The first objective function includes the power consumption of the electric boiler during the recovery process, and the second objective function includes the heat load recovery amount and the gas load recovery amount.

[0139] The constraint conditions include safe operation constraints and balance relationship constraints within the area to be restored.

[0140] The regional integrated energy system is a comprehensive system composed of multiple energy forms such as electricity, heat and gas. Its energy subnet includes distribution network, heat network and gas network, and the networks are connected through coupling devices. The power generation equipment in the distribution network of the regional integrated energy system includes a high proportion of distributed renewable energy generators (such as solar photovoltaic power generation, wind power generation, etc.), combined heat and power (CHP) units, gas turbines, etc. As an important energy conversion equipment in the integrated energy system, coupling equipment can tightly couple energy of different grades and is the key to achieving multi-energy synergy. The regional integrated energy system mainly includes CHP units, gas turbines, gas boilers, electric boilers and other types of coupling equipment.

[0141] In a regional integrated energy system, different loads are supplied and can be traced back to different types of energy. These loads can be supported interchangeably. If one energy source is missing, they can be powered by another energy source through multi-energy coordination. For example, the heat load supplied by an electric boiler can be supported by a gas boiler during a period of insufficient power supply in the distribution network, thereby reducing the electrical load. Here, this type of load transformation is called "load substitution".

[0142] (1) Distribution network operation model.

[0143] The distribution network receives electricity from the external power grid, as well as distributed energy sources within the system, such as photovoltaic power generation, wind power generation, CHP units, and gas turbines.

[0144] The distribution network operation model includes:

[0145] (1.1) Distributed photovoltaic power generation equipment model:

[0146]

[0147] Where: is the output power of distributed photovoltaic power generation equipment in period t, in kW; Y PV is the rated capacity of distributed photovoltaic power generation equipment, I S I is the rated solar radiation that the photovoltaic surface can withstand and is related to the photovoltaic manufacturing materials. t is the total solar radiation on the photovoltaic surface during period t, f PV is the attenuation factor.

[0148] (1.2) Distributed wind power generation equipment model:

[0149]

[0150] Where: w tis the speed of the distributed wind power generation equipment during period t; is the output power of the distributed wind power generation equipment during period t, w1, w cutout and w r are the cut-in speed, cut-out speed and rated speed of distributed wind power generation equipment respectively; P nom is the rated output power of the distributed wind power generation equipment, k1 and k2 are the linear coefficients of the distributed wind power generation installed power.

[0151] (1.3) Power model of cogeneration equipment:

[0152] Combined heat and power equipment (CHP units) is the core energy flow coupling equipment in the regional integrated energy system. It is an efficient energy conversion equipment that can generate electricity and heat energy at the same time. CHP units usually use clean fuels such as natural gas as power sources to produce high-temperature and high-pressure gases through combustion. These gases not only generate heat energy, but also drive the turbine to rotate and convert heat energy into mechanical energy. The turbine is closely connected to the generator, which further converts mechanical energy into electrical energy, realizing efficient conversion and utilization of energy. The model is as follows:

[0153]

[0154] Where: is the output power of the cogeneration equipment during period t; is the fuel consumption of the cogeneration equipment in period t, in m 3 ; is the start / stop status of the cogeneration equipment in period t, which takes the value of 1 or 0, 1 means start, and 0 means shutdown; is the electricity conversion efficiency of the cogeneration equipment; LHV is the lower heating value of natural gas; It is the output thermal power of the waste heat boiler in the cogeneration equipment during period t.

[0155] (1.4) Gas turbine model:

[0156]

[0157] Where: is the output power of the gas turbine during period t; is the start / stop state of the gas turbine during period t, which takes the value of 1 or 0, 1 represents start, and 0 represents shutdown; is the fuel consumption of the gas turbine during period t; is the gas turbine electricity conversion efficiency.

[0158] (2) Thermal network operation model.

[0159] The thermal network is mainly composed of three parts: heat source, heating network, and heat load. The heat source includes cogeneration equipment, gas boilers, and electric boilers. The heating network transmits the energy generated by the heat source to each heat load through a heat transfer medium. Assume that the heat transfer medium in the heating network is hot water.

[0160] (2.1) Thermal model of cogeneration equipment:

[0161] In industrial production, cogeneration equipment will generate a large amount of high-temperature wastewater and waste gas. The waste heat boiler collects this waste heat through a specific device to achieve energy reuse. The model is as follows:

[0162]

[0163] Where: is the output power of the cogeneration equipment during period t; is the start / stop status of the cogeneration equipment in period t, which takes the value of 1 or 0, 1 means start, and 0 means shutdown; The heat conversion efficiency of the cogeneration equipment; It is the output thermal power of the waste heat boiler in the cogeneration equipment during period t.

[0164] (2.2) Gas boiler model:

[0165]

[0166] Where: is the output thermal power of the gas boiler during period t; The start / stop status of the gas boiler in period t, which can be 1 or 0, 1 means start, and 0 means shutdown; is the fuel consumption of the gas boiler during period t; is the heat conversion efficiency of the gas boiler; LHV is the lower heating value of natural gas.

[0167] (2.3) Electric boiler model:

[0168]

[0169] Where: is the output thermal power of the electric boiler during period t, is the electric-to-heat conversion efficiency, is the input power of the electric boiler during period t; It is the start / stop status of the electric boiler during period t, and takes the value 1 or 0, 1 means on, and 0 means off.

[0170] (2.4) Heating network model.

[0171] The static operation constraints of the heating network include node thermal power and temperature balance equations, node flow balance equations, node temperature and pipeline start temperature balance equations, pipeline temperature loss equations, node temperature constraints and pipeline temperature constraints.

[0172] The heating network includes several nodes and pipes connecting the nodes.

[0173] (2.4.1) Node thermal power and temperature balance equation:

[0174]

[0175] Where: H p is the thermal power at node h; C p is the specific heat capacity of water; m h is the flow rate of the medium at node h; is the heating temperature at node h; is the reheating temperature at node h.

[0176] (2.4.2) Node flow balance equation:

[0177] At node h, the flow of hot water should reach equilibrium:

[0178]

[0179] Where: They are respectively a pipeline set with node h as the first head end and a pipeline set with node h as the first end end; They are the flow rates of the heating part and the heat recovery part of pipe k respectively.

[0180] (2.4.3) Nodal temperature mixing equation:

[0181]

[0182] Where: They are respectively a pipeline set with node h as the first head end and a pipeline set with node h as the first end end; They are respectively represented as the outlet temperature of the heat supply part and the outlet temperature of the heat recovery part of pipe k; are the heating temperature and reheating temperature of node h respectively; They are the flow rates of the heating part and the heat recovery part of pipe k respectively.

[0183] If there is no heat exchange at the node, whether it is heat supply or heat recovery, the outlet temperature of node h should be equal to the inlet temperature:

[0184]

[0185] Where: They are the inlet temperature of the heat supply part and the inlet temperature of the heat recovery part of pipe k respectively.

[0186] (2.4.4) Node pipe temperature loss equation:

[0187]

[0188] β k =λ k L k ;

[0189] Where: β k is the thermal distance of pipeline k, which is determined by the thermal conductivity and length of pipeline k; T a , k , L k are the ambient temperature, the thermal conductivity of pipe k and the length of pipe k respectively; C p is the specific heat capacity of water; are the inlet temperature and outlet temperature of the same part in pipeline k respectively. Both the heating part and the heat recovery part are applicable to the above node pipeline temperature loss equation.

[0190] For the thermal distance of the pipelines in the same regional heating network, the specific material of the pipeline is determined, and the thermal conductivity is determined. Then the pipeline length L k is the only variable parameter.

[0191] (2.4.5)Node temperature constraint:

[0192]

[0193] Where: are the minimum and maximum values ​​of the node temperature, respectively, indicating that the temperature of each node should be within a reasonable range.

[0194] (2.4.6) Pipeline temperature constraints:

[0195]

[0196] Where: are the minimum and maximum values ​​of the pipeline temperature, respectively, indicating that the temperature of each pipeline should be within a reasonable range; are the inlet temperature and outlet temperature of any part of pipe k respectively. Both the heat supply part and the heat recovery part are subject to the above pipe temperature constraints.

[0197] (3) Gas network operation model.

[0198] The gas network is mainly composed of three parts: gas source, gas network, and gas load. The gas source is supplied by an external gas source. The static safety constraints of the gas network include node flow balance equations, pipeline transmission constraints, node pressure constraints, and gas source constraints. In the gas network, there are two types of pipelines, with compressors and without compressors.

[0199] (3.1) Node flow balance equation:

[0200]

[0201] Where: G s，m , G d,m are the natural gas supply and gas load of node m respectively; N m is the set of nodes directly connected to node m; G mn is the natural gas flow in the pipeline between nodes m and n; M m is the set of compressor nodes connected to node m; G c,k is the natural gas flow rate through compressor k; τ c,k is the natural gas flow consumed by compressor k; when node m is the inlet of compressor k, sgn k (m)=1, otherwise it is the exit, sgn k (m) = -1.

[0202] (3.2) Pipeline transmission constraints:

[0203] Without a compressor, the flow rate is only related to the pressure at both ends of the pipeline and the relevant parameters of the pipeline, and flows from the high-pressure node to the low-pressure node. Pipeline transmission constraints without a compressor:

[0204]

[0205] in:

[0206]

[0207] Where: G mn is the natural gas flow rate of pipeline mn from node m to node n; is the maximum flow rate that can pass through the pipe mn; π m , π n are the pressures at nodes m and n respectively; s mn is a function of the pipeline flow direction. When the pressure at node m is greater than the pressure at node n, s mn =1, otherwise -1; k mn is a coefficient related to pipeline length, inner diameter, compression coefficient, gas specific gravity, and temperature; ηη mn is the pipeline transmission efficiency; f mn is the friction coefficient of the pipe mn; Lgp,mn is the length of the pipe mn; d mn is the inner diameter of the pipe mn; T is the average ambient temperature; S g is the specific gravity of natural gas in the pipeline; Z is the natural gas compression coefficient.

[0208] Pipeline transport constraints with compressors:

[0209] When gas is transported in a gas pipeline, friction resistance will cause pressure loss. In order to ensure the gas supply pressure, a compressor is needed to increase the pipeline pressure. The natural gas pipeline with a compressor is modeled as follows:

[0210] G c,k =G out =G in -τ c,k ;

[0211] in:

[0212]

[0213] Where: G in , G out are the natural gas flow rates at the upper and lower ends of the pipeline from node m to node n and passing through compressor k; mi , k jn are the pipeline correlation coefficients between node m and compressor k inlet node i, and between node n and compressor k outlet node j; π m , π n are the pressures at nodes m and n respectively; π i , π j are the pressures of compressor inlet node i and compressor outlet node j respectively; G c，k is the natural gas flow rate through compressor k; τ c，k is the natural gas flow consumed by compressor k; LHV is the lower heating value of natural gas; T g is the natural gas temperature; a is the compressor variability index; k cp is the pressure ratio of compressor k.

[0214] (3.3) Nodal pressure constraint:

[0215] π min ≤π m , ,π n ≤π max ;

[0216] Where: π min , π max are the minimum and maximum values ​​of node pressure within a reasonable range, respectively.

[0217] (3.4) Gas source constraints:

[0218]

[0219] Where: They are respectively the minimum and maximum values ​​of the gas source output flow rate within a reasonable range.

[0220] (4) Energy storage equipment operation model.

[0221] Energy storage plays a vital role in balancing energy supply and demand, alleviating fluctuations, and improving the reliability of energy systems. In the post-disaster self-recovery phase, energy storage systems can provide backup power and ensure uninterrupted power supply to loads. Energy storage equipment includes electricity storage equipment, heat storage equipment, and gas storage equipment.

[0222]

[0223] Where: λ∈{ESS,HES,GES}, ESS,HES,GES represent the three energy types of electricity, heat and gas respectively; is the energy stored by the λ type energy storage device in time period t, where the unit for the distribution network and thermal network is kW·h, and the unit for the gas network is m 3 ; are the charging power and discharging power of the energy storage device in time period t, respectively. The corresponding charging power and discharging power in the distribution network and thermal network are in kW, and the corresponding charging power and discharging power in the gas network are in m 3 / s; σ λ is the self-consumption rate of the energy storage device of type λ; η λ,cha , η λ,dis are the charging efficiency and discharging efficiency of the energy storage equipment respectively; Δt is a scheduling period.

[0224] Energy storage devices have the following constraints:

[0225]

[0226] Where: β λ，cha , β λ，dis are the maximum charging rate and discharging rate of the λ type energy storage device; SOC λ，min , SOC λ，max They are the minimum load state and maximum load state of the energy storage of the λ type energy storage device; E λ is the rated storage capacity of the λ type energy storage device; They are the storage amounts of the energy storage of type λ at the start and end of the scheduling period.

[0227] (5)Safe operation constraints.

[0228] (5.1) Equipment output constraints:

[0229]

[0230] Where: P n，t is the actual output of the nth device in the integrated energy system during period t; They are the maximum output value and minimum output value of the nth device respectively.

[0231] (5.2) Distributed generation output constraints:

[0232]

[0233] Where: is the output power of distributed photovoltaic power generation equipment in period t, is the output power of the distributed wind power generation equipment in period t, and They are the maximum outputs of distributed photovoltaic power generation equipment and distributed wind power generation equipment respectively.

[0234] (6) Constraints on the equilibrium relationship within the area to be restored.

[0235] After a disaster occurs, the integrated energy system will be divided into multiple areas to be restored. Each area to be restored should meet the following balance constraints:

[0236] (6.1) Balance relationship within the distribution network area:

[0237]

[0238] Where: K PV , K WT , K CHP , K GT , K ESS , K EB They are the number of distributed photovoltaic power generation equipment, distributed wind power generation equipment, cogeneration equipment, gas turbines, power storage equipment, and electric boilers in a certain area to be restored; are the output powers of the kth distributed photovoltaic power generation equipment, the kth distributed wind power generation equipment, the kth cogeneration equipment, and the kth gas turbine in a certain area to be restored during the t period, which are decision variables; is the input power of the kth electric boiler in a certain area to be restored during period t; is the charging power and discharging power of the kth power storage device in a certain area to be restored during period t, which is the decision variable; is the post-disaster power load demand in a certain area to be restored and is the decision variable.

[0239] (6.2) Balance relationship within the thermal network area:

[0240]

[0241] Where: K GB , K HES They are the number of gas boilers and heat storage equipment in the area to be restored; are the output thermal powers of the kth cogeneration equipment, the kth gas boiler, and the kth electric boiler in the area to be restored during period t, which are decision variables; are the heat storage power and heat release power of the kth heat storage device in the area to be restored in period t, respectively, which are decision variables; is the post-disaster heat load demand in the area to be restored and is the decision variable.

[0242] (6.3) Balance relationship within the gas network area:

[0243]

[0244] Where: K GES is the number of gas storage facilities in the area to be restored; are the fuel consumption of the kth cogeneration equipment, the kth gas turbine, and the kth gas boiler in the area to be restored; is the post-disaster gas load demand in the area to be restored, which is the decision variable; are the inflation and deflation volumes of the kth gas storage device in the area to be restored during period t, respectively, and are decision variables.

[0245] (7) Multi-objective optimization function.

[0246] The multi-objective optimization function is expressed as:

[0247]

[0248] Where: F1 and F2 are the first objective function and the second objective function respectively; λ1 and λ2 are the function weights of the first objective function and the second objective function respectively, λ1 and λ2 are both greater than 0, and λ1+λ2=1; F 1，max 、F 1，min are the maximum and minimum values ​​of F1 calculated based on historical data, which are known variables; F 2，max 、F 2，min They are the maximum and minimum values ​​of F2 calculated based on historical data, which are known variables.

[0249] The multi-objective optimization function uses fuzzy theory to weight the two objective results and transforms the original multi-objective optimization problem into a single-objective optimization problem for solution.

[0250] (7.1) The first objective function.

[0251] For the distribution network, since the output of distributed photovoltaic and wind turbines is intermittent and uncertain, load substitution is considered to reduce the pressure of electric load during the restoration process. The purpose of the first objective function is to minimize power consumption by changing the form of variable energy. In this model, electric boilers are the only equipment that is powered by electricity and can provide other forms of energy. Therefore, it is necessary to minimize the power consumption of electric boilers in the area to be restored. The first objective function is:

[0252]

[0253] Where: N is the number of areas to be restored after the disaster; T is the number of time periods in a scheduling cycle; K EB is the number of electric boilers in the corresponding number of areas to be restored; is the input electric power of k electric boilers in the i-th area to be restored during period t.

[0254] (7.2) The second objective function.

[0255] For the thermal network and gas network, the utilization efficiency of heat and gas energy is improved through multi-energy complementarity, with the objective function of maximizing the recovery of heat and gas loads in the area to be restored.

[0256]

[0257]

[0258] Where: are the heat load recovery ratio and gas load recovery ratio in the i-th area to be restored respectively; ω h，i ,ω g，i are weight parameters representing the recovery ratio of heat load and the importance of gas load in the i-th area to be restored, respectively; are the post-disaster load recovery amounts of the heat network and gas network in the i-th area to be restored during period t; They are respectively the heat network load demand and gas network load demand predicted before the disaster in the i-th area to be restored during period t.

[0259] The weight parameters of the heat load restoration ratio and gas load importance are determined based on the load weight of each node in the heat network and gas network. The load weight represents the priority of the node load, which is determined based on the node's energy consumption, estimated interruption cost, and load type. High priority is for critical loads that need to be restored quickly after a failure, such as hospitals, banks, chemicals, etc. Residential loads are considered low priority loads due to their general consumption and low interruption cost. The weight parameters of the heat load restoration ratio and gas load importance are calculated as follows:

[0260]

[0261] Where: θ h，q is the load weight of node q in the thermal network of the area to be restored; θ g，p is the load weight of node p in the regional gas network to be restored; N h and N g They are the number of heating network nodes and the number of gas network nodes in the area to be restored respectively.

[0262] Step 2: Determine the function weights in the multi-objective optimization function based on historical data.

[0263] The specific steps are:

[0264] Step 2-1, assign initial values ​​to weight values ​​λ1 and λ2, and set the number of iterations to 0.

[0265] Step 2-2, construct the objective function obj:

[0266]

[0267] Step 2-3: Select N groups of historical data on post-disaster recovery and substitute them into the calculation formulas of the first objective function and the second objective function to obtain F 1，history and F 2,history , then calculate obj, and record the function value of the objective function obj corresponding to the historical data of the nth group of post-disaster recovery as obj n , and then calculate the average value And increase the number of iterations by 1.

[0268] Step 2-4: Determine whether the number of iterations reaches a preset threshold. If so, use the current values ​​of weights λ1 and λ2 as their respective optimal values. Otherwise, continue with step 2-5.

[0269] Step 2-5: Average value The maximum is the goal, and the values ​​of weights λ1 and λ2 are updated through the gradient descent method, and then jump to step 2-3.

[0270] At this point, the optimal values ​​of weights λ1 and λ2 can be determined.

[0271] Step 3: After a disaster occurs, a connectivity analysis is performed based on the network topology of the integrated energy system after the disaster, the switch information of the distribution network, and the valve information of the pipelines in the thermal network and the gas network, and the integrated energy system is divided into multiple areas to be restored.

[0272] The specific steps are:

[0273] Step 3-1: After the disaster occurs, the original integrated energy system is divided into multiple areas based on the damaged lines in the distribution network and the damaged pipelines in the heat network and gas network.

[0274] Step 3-2: Identify the isolated nodes in the integrated energy system that have lost their energy supply source.

[0275] In actual situations, some island nodes cannot supply power due to the disconnection of distribution network lines, while others cannot supply heat or natural gas due to the disconnection of heat network or gas network pipelines.

[0276] Step 3-3: Establish a recovery energy supply path based on the energy type required by the isolated node. The recovery energy supply path includes a power supply recovery path, a heat supply recovery path, and a gas supply recovery path.

[0277] For isolated island nodes that cannot supply power: find all the distribution network lines connected to the isolated island node that are in the off state and not damaged by the disaster, calculate the electrical distance of each line, where the electrical distance refers to the self-impedance of the line, and select the line with the shortest electrical distance as the power restoration path, and close the switches in the power restoration path.

[0278] For example Figure 1 Node n in e5 , the selectable line is L e35 , L e45 , if L e45 If the electrical distance is shorter, select L e45 As a power restoration path.

[0279] For isolated island nodes that cannot provide heat: find all the thermal network pipelines connected to the isolated island node that are in the valve-closed state and not damaged by the disaster, and calculate the thermal distance of each pipeline. The thermal distance calculation method is: β k =λ k L k ; Among them, β k is the thermal distance of pipeline k, λ k , L k are the thermal conductivity of pipeline k and the length of pipeline k respectively; then the pipeline with the shortest thermal distance is selected as the heat recovery path, and the valve in the heat recovery path is opened.

[0280] For example Figure 1 Node n in h4 , the selectable line is L h34 , L h24 , if L h34 The thermal distance is shorter, then select L h34 To restore the heating path.

[0281] For isolated nodes that cannot supply natural gas: find all gas network pipelines connected to the isolated node that are in valve-closed state and not damaged by the disaster, and calculate the natural gas distance of each pipeline. The natural gas distance calculation method is: α mn =(1.3305×10 5 )Tη mn ; Among them, α mn is the natural gas distance of pipeline mn between node m and node n in the gas network, T is the average ambient temperature, is the transmission efficiency of pipeline mn, f mn is the friction coefficient of the pipe mn; L gp,mn is the length of the pipe mn; d mn is the inner diameter of the pipeline mn; then the pipeline with the shortest natural gas distance is selected as the gas supply recovery path, and the valve in the gas supply recovery path is opened.

[0282] For example Figure 1 Node n in g5 , the selectable line is L g45 , L g35 , if L g45 If the natural gas distance is shorter, select L g45 To restore the gas supply path.

[0283] Step 3-4: according to the established energy restoration path, add the isolated island node to the area where the node on the opposite side of the energy restoration path is located, and the multiple areas finally formed are the areas to be restored.

[0284] Step 4: Solve the post-disaster self-recovery model to obtain the output of each device in the integrated energy system at each time period, the charging and discharging power of each energy storage device at each time period, and the recovery amount of heat load and gas load. The output of each device at each time period and the charging and discharging power of each energy storage device at each time period constitute a self-recovery plan and issue it as an operation configuration to control the operation of the integrated energy system.

[0285] In this embodiment, the self-healing and recovery operation optimization scheduling of the regional electricity-heat-gas integrated energy system within 24 hours after the disaster is performed, and the scheduling is performed hourly. The solution uses Cplex optimization software.

[0286] It should be noted that it is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential features of the present invention. The scope of the present invention is defined by the claims rather than the above description.

Claims

1. A post-disaster self-recovery method for a regional electricity-heat-gas integrated energy system, characterized in that: include: Step 1: construct a post-disaster self-recovery model, which includes a multi-objective optimization function and constraints, and also includes a distribution network operation model, a thermal network operation model, a gas network operation model, and an energy storage device operation model for representing the operation characteristics of the integrated energy system; The multi-objective optimization function is constructed by weighting the first objective function and the second objective function by function weights. The first objective function includes the power consumption of the electric boiler during the recovery process, and the second objective function includes the heat load recovery amount and the gas load recovery amount. The constraint conditions include safe operation constraints and balance relationship constraints within the area to be restored; Step 2: Determine the function weights in the multi-objective optimization function based on historical data; Step 3: After the disaster occurs, a connectivity analysis is performed based on the network topology of the integrated energy system after the disaster, the switch information of the distribution network, and the valve information of the pipelines in the heat network and the gas network. The integrated energy system is divided into multiple areas to be restored based on the principle of the shortest energy restoration path; Step 4: Solve the post-disaster self-recovery model to obtain the output of each device in the integrated energy system in each time period, the charging and discharging power of each energy storage device in each time period, and the recovery amount of heat load and gas load; the output of each device in each time period and the charging and discharging power of each energy storage device in each time period constitute a self-recovery plan and issue it as an operation configuration to control the operation of the integrated energy system.

2. The post-disaster self-recovery method for a regional electricity-heat-gas integrated energy system according to claim 1, characterized in that: The distribution network operation model includes: Distributed photovoltaic power generation equipment model: Where: is the output power of distributed photovoltaic power generation equipment in period t, in kW; Y PV is the rated capacity of distributed photovoltaic power generation equipment, I S I is the rated solar radiation that the photovoltaic surface can withstand and is related to the photovoltaic manufacturing materials. t is the total solar radiation on the photovoltaic surface during period t, f PV is the attenuation factor; Distributed wind power generation equipment model: Where: w t is the speed of the distributed wind power generation equipment during period t; is the output power of the distributed wind power generation equipment during period t, w1, w cutout and w r are the cut-in speed, cut-out speed and rated speed of distributed wind power generation equipment respectively; P nom is the rated output power of the distributed wind power generation equipment, l1 and k2 are the linear coefficients of the distributed wind power generation installed power; Cogeneration plant power model: Where: is the output power of the cogeneration equipment during period t; is the fuel consumption of the cogeneration equipment in period t, in m 3 ; The start / stop status of the cogeneration equipment in period t, which takes the value of 1 or 0, 1 means start, and 0 means shutdown; is the electricity conversion efficiency of the cogeneration equipment; LHV is the lower heating value of natural gas; is the output thermal power of the waste heat boiler in the cogeneration equipment during period t; Gas Turbine Model: Where: is the output power of the gas turbine during period t; is the start / stop state of the gas turbine during period t, which takes the value of 1 or 0, 1 represents start, and 0 represents shutdown; is the fuel consumption of the gas turbine during period t; is the gas turbine electricity conversion efficiency.

3. The post-disaster self-recovery method for a regional electricity-heat-gas integrated energy system according to claim 1, characterized in that: The thermal network operation model includes: Thermal model of cogeneration equipment: Where: is the output power of the cogeneration equipment during period t; The start / stop status of the cogeneration equipment in period t, which takes the value of 1 or 0, 1 means start, and 0 means shutdown; The heat conversion efficiency of the cogeneration equipment; is the output thermal power of the waste heat boiler in the cogeneration equipment during period t; Gas boiler model: Where: is the output thermal power of the gas boiler during period t; The start / stop status of the gas boiler in period t, which can be 1 or 0, 1 means start, and 0 means shutdown; is the fuel consumption of the gas boiler during period t; is the heat conversion efficiency of the gas boiler; LHV is the lower calorific value of natural gas; electric boiler model: Where: is the output thermal power of the electric boiler during period t, is the electric-to-heat conversion efficiency, is the input power of the electric boiler during period t; It is the start / stop status of the electric boiler during period t, and takes the value 1 or 0, 1 means on, and 0 means off.

4. The post-disaster self-recovery method for a regional electricity-heat-gas integrated energy system according to claim 3, characterized in that: The thermal network operation model also includes a heating pipe network model; The heating network includes several nodes and pipes connected between the nodes. The heating network model includes: node thermal power and temperature balance equations: Where: H p is the thermal power at node h; C p is the specific heat capacity of water; m h is the flow rate of the medium at node h; is the heating temperature at node h; is the regenerative temperature at node h; Node traffic balance equation: Where: They are respectively a pipeline set with node h as the first head end and a pipeline set with node h as the first end end; are the flow rates of the heating part and the heat recovery part of pipeline k respectively; Nodal temperature mixing equation: Where: They are respectively a pipeline set with node h as the first head end and a pipeline set with node h as the first end end; They are respectively represented as the outlet temperature of the heat supply part and the outlet temperature of the heat recovery part of pipe k; are the heating temperature and reheating temperature of node h respectively; are the flow rates of the heating part and the heat recovery part of pipeline k respectively; If hot swapping does not exist for the node: Where: are the inlet temperature of the heat supply part and the inlet temperature of the heat recovery part of pipe k respectively; Node pipe temperature loss equation: b k =λ k L k ; Where: β k is the thermal distance of pipeline k, which is determined by the thermal conductivity and length of pipeline k; T a , k , L k are the ambient temperature, the thermal conductivity of pipe k and the length of pipe k respectively; C p is the specific heat capacity of water; are the inlet temperature and outlet temperature of the same part of pipeline k, respectively. Both the heat supply part and the heat recovery part are applicable to the above node pipeline temperature loss equation; Node temperature constraints: Where: are the minimum and maximum values ​​of node temperature respectively; Pipe temperature constraints: Where: are the minimum and maximum values ​​of the pipeline temperature, respectively, indicating that the temperature of each pipeline should be within a reasonable range; are the inlet temperature and outlet temperature of any part of pipe k respectively. Both the heat supply part and the heat recovery part are subject to the above pipe temperature constraints.

5. The post-disaster self-recovery method for a regional electricity-heat-gas integrated energy system according to claim 1, characterized in that: In the gas network, there are two types of pipelines, pipelines with compressors and pipelines without compressors. The gas network operation model includes: Node traffic balance equation: Where: G s,m , G d,m are the natural gas supply and gas load of node m respectively; N m is the set of nodes directly connected to node m; G mn is the natural gas flow in the pipeline between nodes m and n; M m is the set of compressor nodes connected to node m; G c,k is the natural gas flow rate through compressor k; τ c,k is the natural gas flow consumed by compressor k; when node m is the inlet of compressor k, sgn k (m)=1, otherwise it is the exit, sgn k (m) = -1; Pipeline transmission constraints: in: Where: G mn is the natural gas flow rate of pipeline mn from node m to node n; is the maximum flow rate that can pass through the pipe mn; π m , π n are the pressures at nodes m and n respectively; s mn is a function of the pipeline flow direction. When the pressure at node m is greater than the pressure at node n, s mn =1, otherwise -1; k mn is a coefficient related to pipeline length, inner diameter, compression coefficient, gas specific gravity, and temperature; η mn is the pipeline transmission efficiency; f mn is the friction coefficient of the pipe mn; L gp,mn is the length of the pipe mn; d mn is the inner diameter of the pipe mn; T is the average ambient temperature; S g is the specific gravity of natural gas in the pipeline; Z is the natural gas compression coefficient; Pipeline transport constraints with compressors: G c,k =G out =G in -t c,k ; in: Where: G in , G out are the natural gas flow rates at the upper and lower ends of the pipeline from node m to node n and passing through compressor k; mi , k jn are the pipeline correlation coefficients between node m and compressor k inlet node i, and between node n and compressor k outlet node j; π m , π n are the pressures at nodes m and n respectively; π i , π j are the pressures of compressor inlet node i and compressor outlet node j respectively; G c,k is the natural gas flow rate through compressor k; τ c,k is the natural gas flow consumed by compressor k; LHV is the lower heating value of natural gas; T g is the natural gas temperature; a is the compressor variability index; k cp is the pressure ratio of compressor k; Nodal pressure constraints: π min ≤π m ,π n ≤π max ； Where: π min , π max are the minimum and maximum node pressures within a reasonable range; gas source constraints: Where: They are respectively the minimum and maximum values ​​of the gas source output flow rate within a reasonable range.

6. The post-disaster self-recovery method for a regional electric-heat-gas integrated energy system according to claim 1, characterized in that: Energy storage equipment includes electricity storage equipment, heat storage equipment and gas storage equipment. The operation model of energy storage equipment is: Where: λ∈{ESS,HES,GES}, ESS,HES,GES represent the three energy types of electricity, heat and gas respectively; is the energy stored by the λ type energy storage device in time period t, where the unit for the distribution network and thermal network is kW·h, and the unit for the gas network is m 3 ; are the charging power and discharging power of the energy storage device in time period t, respectively. The corresponding charging power and discharging power in the distribution network and thermal network are in kW, and the corresponding charging power and discharging power in the gas network are in m 3 / s; σ λ is the self-consumption rate of the energy storage device of type λ; η λ,cha , η λ,dis are the charging efficiency and discharging efficiency of the energy storage device respectively; Δt is a scheduling period; the energy storage device also has the following constraints: Where: β λ,cha , β λ,dis are the maximum charging rate and discharging rate of the λ type energy storage device; SOC λ,min , SOC λ,max They are the minimum load state and maximum load state of the energy storage of the λ type energy storage device; E λ is the rated storage capacity of the λ type energy storage device; They are the storage amounts of the energy storage of type λ at the start and end of the scheduling period.

7. The post-disaster self-recovery method for a regional electricity-heat-gas integrated energy system according to claim 1, characterized in that: The safe operation constraints include: Equipment output constraints: Where: P n,t is the actual output of the nth device in the integrated energy system during period t; are the maximum output value and minimum output value of the nth device respectively; Distributed generation output constraints: Where: is the output power of distributed photovoltaic power generation equipment in period t, is the output power of the distributed wind power generation equipment in period t, and They are the maximum outputs of distributed photovoltaic power generation equipment and distributed wind power generation equipment respectively; The balance relationship constraints within the area to be restored include: Balance relationship within the distribution network area: Where: K PV , K WT , K CHP , K GT , K ESS , K EB They are the number of distributed photovoltaic power generation equipment, distributed wind power generation equipment, cogeneration equipment, gas turbines, power storage equipment, and electric boilers in a certain area to be restored; are the output powers of the kth distributed photovoltaic power generation equipment, the kth distributed wind power generation equipment, the kth cogeneration equipment, and the kth gas turbine in a certain area to be restored during the t period, which are decision variables; is the input power of the kth electric boiler in a certain area to be restored during period t; is the charging power and discharging power of the kth power storage device in a certain area to be restored during period t, which is the decision variable; is the post-disaster power load demand in a certain area to be restored, which is the decision variable; Balance relationship within the thermal network area: Where: K GB , K HES They are the number of gas boilers and heat storage equipment in the area to be restored; are the output thermal powers of the kth cogeneration equipment, the kth gas boiler, and the kth electric boiler in the area to be restored during period t, which are decision variables; are the heat storage power and heat release power of the kth heat storage device in the area to be restored in period t, respectively, which are decision variables; is the post-disaster heat load demand in the area to be restored, is the decision variable; the balance relationship in the gas network area: Where: K GES is the number of gas storage facilities in the area to be restored; are the fuel consumption of the kth cogeneration equipment, the kth gas turbine, and the kth gas boiler in the area to be restored; is the post-disaster gas load demand in the area to be restored, which is the decision variable; are the inflation and deflation volumes of the kth gas storage device in the area to be restored during period t, respectively, and are decision variables.

8. The post-disaster self-recovery method for a regional electricity-heat-gas integrated energy system according to claim 1, characterized in that: The multi-objective optimization function is: Where: F1 and F2 are the first objective function and the second objective function respectively; λ1 and λ2 are the function weights of the first objective function and the second objective function respectively, λ1 and λ2 are both greater than 0, and λ1+λ2=1; F 1,max 、F 1,min are the maximum and minimum values ​​of F1 calculated based on historical data, which are known variables; F 2,max 、F 2,min are the maximum and minimum values ​​of F2 calculated based on historical data, which are known variables; The first objective function is: Where: N is the number of areas to be restored after the disaster; T is the number of time periods in a scheduling cycle; K EB is the number of electric boilers in the corresponding number of areas to be restored; is the input power of k electric boilers in the i-th area to be restored during period t; The second objective function is: Where: are the heat load recovery ratio and gas load recovery ratio in the i-th area to be restored respectively; ω h,i ,ω g,i are weight parameters representing the recovery ratio of heat load and the importance of gas load in the i-th area to be restored, respectively; are the post-disaster load recovery amounts of the heat network and gas network in the i-th area to be restored during period t; They are respectively the heat network load demand and gas network load demand in the i-th area to be restored during period t predicted before the disaster; The weight parameters of heat load recovery ratio and gas load importance are calculated as follows: Where: θ h,q is the load weight of node q in the thermal network of the area to be restored; θ g,p is the load weight of node p in the regional gas network to be restored; N h and N g They are the number of heating network nodes and the number of gas network nodes in the area to be restored respectively.

9. The post-disaster self-recovery method for a regional electricity-heat-gas integrated energy system according to claim 1, characterized in that: Step 2 specifically includes: Step 2-1, assign initial values ​​to weight values ​​λ1 and λ2, and set the number of iterations to 0; Step 2-2, construct the objective function obj: Step 2-3: Select N groups of historical data on post-disaster recovery and substitute them into the calculation formulas of the first objective function and the second objective function to obtain F 1,history and F 2,history , then calculate obj, and record the function value of the objective function obj corresponding to the historical data of the nth group of post-disaster recovery as obj n , and then calculate the average value And increase the number of iterations by 1; Step 2-4: Determine whether the number of iterations reaches a preset threshold. If so, use the current values ​​of weights λ1 and λ2 as their respective optimal values. Otherwise, continue to step 2-5. Step 2-5: Average value The maximum is the goal, and the values ​​of weights λ1 and λ2 are updated through the gradient descent method, and then jump to step 2-3.

10. The post-disaster self-recovery method for a regional electricity-heat-gas integrated energy system according to any one of claims 1 to 9, characterized in that: Step 3 specifically includes: Step 3-1: After the disaster occurs, the original integrated energy system is divided into multiple areas based on the damaged lines in the distribution network and the damaged pipelines in the heat network and gas network; Step 3-2: Identify the isolated nodes in the integrated energy system that have lost their energy supply sources; Step 3-3: Establish a recovery energy supply path according to the energy type required by the isolated node, the recovery energy supply path includes a power supply recovery path, a heat supply recovery path, and a gas supply recovery path; For an island node that cannot be powered: find all the distribution network lines connected to the island node that are in the off state and not damaged by the disaster, calculate the electrical distance of each line, where the electrical distance refers to the self-impedance of the line, select the line with the shortest electrical distance as the power restoration path, and close the switch in the power restoration path; For isolated island nodes that cannot provide heat: find all the thermal network pipelines connected to the isolated island node that are in the valve-closed state and not damaged by the disaster, and calculate the thermal distance of each pipeline. The thermal distance calculation method is: β k =λ k L k ; Among them, β k is the thermal distance of pipeline k, λ k , L k are the thermal conductivity of pipeline k and the length of pipeline k respectively; then the pipeline with the shortest thermal distance is selected as the path for restoring the heat supply, and the valve in the path for restoring the heat supply is opened; For isolated nodes that cannot supply natural gas: find all gas network pipelines connected to the isolated node that are in valve-closed state and not damaged by the disaster, and calculate the natural gas distance of each pipeline. The natural gas distance calculation method is: α mn =(1.3305×10 5 )Tη mn ; Among them, α mn is the natural gas distance of pipeline mn between node m and node n in the gas network, T is the average ambient temperature, is the transmission efficiency of pipeline mn, f mn is the friction coefficient of the pipe mn; L gp,mn is the length of the pipe mn; d mn is the inner diameter of the pipeline mn; then the pipeline with the shortest natural gas distance is selected as the gas supply recovery path, and the valve in the gas supply recovery path is opened; Step 3-4: according to the established energy restoration path, add the isolated island node to the area where the node on the opposite side of the energy restoration path is located, and the multiple areas finally formed are the areas to be restored.

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