Method, device and system for improving toughness of electric water system and storage medium

Abstract

The invention discloses a method, a device and a system for improving the toughness of an electricity, gas and water system, and a storage medium. The method comprises the following steps: S1, calculating an economic influence evaluation index IE to describe the influence of a disaster on a system physical domain; s2, calculating a personal influence evaluation index IP to describe the influence of the disaster on the social domain; s3, according to the influence of the disasters on the physical domain of the system and the influence of the disasters on the social domain, constructing a mixed integer nonlinear programming model by taking the minimum comprehensive evaluation index as a target and taking the power, gas and water system operation equation and the element operation equation as constraint conditions; and formulating a post-disaster optimal emergency recovery strategy of the electricity-gas-water coupling system based on the load comprehensive importance degree. According to the technical scheme, the public psychological risk perception change process caused by power-gas-water energy loss after disasters is considered, toughness improvement of physical domain and social domain coupled power-gas-water network post-disaster joint scheduling is achieved, and the method is used for guiding formulation of a coupled system post-disaster emergency recovery strategy.

Description

Technical Field

[0001] The present invention belongs to the technical field of electrical water systems, and in particular relates to a method and device, a system, and a storage medium for improving the toughness of an electrical water system. Background Art

[0002] In response to the impact of extreme events on the power grid, academia and industry have jointly proposed the concept of power grid resilience, which characterizes the power grid's resistance and recovery capabilities to low-probability, high-impact disturbance events. When urban infrastructure networks are damaged by extreme weather, restoring power to the power grid as soon as possible can not only create conditions for the functional recovery of other infrastructure networks, but is also a key factor in ensuring urban social order. Existing research has conducted a lot of research on improving the resilience of electrical and water systems from the perspective of post-disaster recovery processes. The research methods can be divided into two aspects: one-way and two-way fault propagation according to the coupling relationship between networks.

[0003] When evaluating the impact of extreme disasters on the electrical and water coupled system, the existing studies have established resilience improvement indicators that only focus on the physical domain. That is, first, the load importance is divided into primary, secondary and tertiary levels according to relevant criteria, and each load is assigned a corresponding weight coefficient, and the economic loss of the undersupplied load is used to describe the economic loss situation. The use of such conventional resilience indicator systems can indeed ensure that the more important power grid loads within the criteria, such as electronic manufacturing, military production, and data centers, are given priority in restoring power supply; however, such methods ignore the impact of extreme disasters on other fields such as the social field. Existing research has not yet conducted how to quantify the relationship between residents' perception of extreme weather disasters and the shortage of electricity, water, and gas, which is of great significance for ensuring urban functions, normal social operations, and people's life and health safety after disasters. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a method and device, system, and storage medium for improving the resilience of electrical and water systems, taking into account the changes in public psychological risk perception caused by the loss of electricity, gas, and water energy after a disaster, to achieve resilience improvement in the post-disaster joint scheduling of electricity, gas, and water networks coupled in the physical and social domains, and to guide the formulation of post-disaster emergency recovery strategies for coupled systems.

[0005] To achieve the above object, the present invention adopts the following technical solution:

[0006] A method for improving the toughness of an electrical water system, comprising:

[0007] Step S1: Calculate economic impact assessment index I E To describe the impact of disasters on the physical domain of the system;

[0008] Step S2: Calculate the personal impact evaluation index I P To describe the impact of disasters on the social domain;

[0009] Step S3: Based on the impact of disasters on the physical domain of the system and the impact of disasters on the social domain, with the goal of minimizing the comprehensive evaluation index and the operating equations of the electricity, gas and water systems and the component operating equations as constraints, a mixed integer nonlinear programming model is constructed to formulate the optimal post-disaster emergency recovery strategy for the electricity-gas-water coupling system based on the comprehensive importance of loads.

[0010] As a preferred method, in step S1, the economic impact evaluation index I is calculated based on the unit price data of residents' electricity, gas and water purchases. E To describe the impact of disasters on the physical domain of the system.

[0011] As a preferred method, in step S1, according to the location distribution and number of users of different age groups in the three network nodes, the prospect theory is used to calculate the personal impact evaluation index I P To describe the impact of disasters on the social domain.

[0012] The present invention also provides an electrical water system toughness improvement device, comprising:

[0013] The first calculation module is used to calculate the economic impact evaluation index I E To describe the impact of disasters on the physical domain of the system;

[0014] The second calculation module is used to calculate the personal impact evaluation index I P To describe the impact of disasters on the social domain;

[0015] The improvement module is used to construct a mixed integer nonlinear programming model based on the impact of disasters on the physical domain of the system and the impact of disasters on the social domain, with the goal of minimizing the comprehensive evaluation index, and with the operating equations of the electricity, gas and water systems and the component operating equations as constraints, to formulate the optimal post-disaster emergency recovery strategy for the electricity-gas-water coupling system based on the comprehensive importance of loads.

[0016] As a preferred embodiment, the first calculation module calculates the economic impact evaluation index I according to the unit price data of residents' electricity, gas and water purchases. E To describe the impact of disasters on the physical domain of the system.

[0017] As a preferred method, the second calculation module uses prospect theory to calculate the personal impact evaluation index I according to the location distribution and number of users of different age groups in the three network nodes. P To describe the impact of disasters on the social domain.

[0018] The present invention also provides an electrical water system resilience improvement system, comprising: a memory and a processor, wherein the memory stores a computer program run by the processor, and the computer program executes an electrical water system resilience improvement method when run by the processor.

[0019] The present invention also provides a storage medium, on which a computer program is stored, and the computer program executes the method for improving the resilience of an electrical water system when running.

[0020] The invention has the following technical effects:

[0021] 1) In view of the problem that the existing resilience improvement index only focuses on the impact of extreme disasters on the physical domain, this paper divides the impact of extreme disasters into two aspects: the physical domain and the social domain. For the physical domain, the power generation ratio and energy loss are used to construct the economic impact evaluation index; for the social domain, considering the differences in the tolerance of different individuals to the loss of electricity, gas and water energy and the changes in risk perception, the prospect theory is used to fit the psychological risk perception curve and the risk-taking willingness curve to construct the personal impact evaluation index.

[0022] 2) In response to the problem of formulating post-disaster recovery strategies, the present invention has established a mixed integer nonlinear programming model based on the coupling characteristics of the electricity, gas and water networks, with the goal of minimizing the impact of disasters on the physical and social domains of the system, and with the operating equations of the electricity, gas, and water systems and components as constraints. It analyzes the propagation process of power failure in the gas and water networks, and formulates the optimal emergency recovery strategy for multi-source coordination after disasters. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0024] Figure 1 This is a flow chart of a method for synthesizing a metal organic framework electrode having a multi-level structure of conductive polymer interlaced according to an embodiment of the present invention;

[0025] Figure 2 It is a schematic diagram of the value function curve;

[0026] Figure 3 It is a schematic diagram of the weight function curve;

[0027] Figure 4 Schematic diagram of the psychological risk perception curve for power, gas and water supply failure. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0030] Embodiment 1:

[0031] like Figure 1 As shown, an embodiment of the present invention provides a method for improving the toughness of an electrical water system, comprising:

[0032] Step S1: Calculate the economic impact evaluation index I based on the unit price data of residents' electricity, gas and water purchases E To describe the impact of disasters on the physical domain of the system;

[0033] Step S2: Based on the location distribution and quantity of users of different age groups in the three network nodes, the prospect theory is used to calculate the personal impact evaluation index I P To describe the impact of disasters on the social domain;

[0034] Step S3: Based on the impact of disasters on the physical domain of the system and the impact of disasters on the social domain, with the goal of minimizing the comprehensive evaluation index and the operating equations of the electricity, gas and water systems and the component operating equations as constraints, a mixed integer nonlinear programming model is constructed to formulate the optimal post-disaster emergency recovery strategy for the electricity-gas-water coupling system.

[0035] As an implementation method of an embodiment of the present invention, in step S1, an economic impact evaluation index is established to describe the impact of the disaster on the physical domain of the system. Specifically, the power grid load shortage is multiplied by the load-to-power generation ratio (that is, the economic benefits that can be created by unit electricity in a certain area within a year, which can be used to measure the value of electricity currency) to describe the economic impact of the disaster on the power grid load; in addition, the gas grid and water grid load shortages are multiplied by the unit price of residents purchasing gas and water, respectively, to describe the economic impact of the disaster on the gas grid and water grid load. The specific mathematical model of the economic impact evaluation index (influence of economy, IE) is shown in formulas (1)-(2).

[0036]

[0037] Among them, I E is the economic impact evaluation index; T is the time collection; is a set of power grid nodes; is the power generation ratio of the grid load at node j; and P j,t is the normal value and actual value of the power of the grid load on node j at time t; and are the annual gross product value and annual electricity consumption of the power grid load at node j respectively; is the set of gas network nodes; is the unit price of gas purchased by residents at node j; and g j,t is the normal value and actual value of the power of the gas grid load at node j at time t; is a collection of water network nodes; is the unit price of water purchased by residents at node j; and m j,t are the normal and actual values ​​of the water grid load power at node j at time t.

[0038] As an implementation method of an embodiment of the present invention, in step S2, a personal impact evaluation index is established to describe the degree of impact of disasters on the social domain of the system. Specifically, in order to characterize the differences in tolerance characteristics and risk-taking levels of people of different ages to energy outages, the prospect theory is first briefly introduced from four aspects: definition, properties, value function, and weight function; secondly, considering the differences in the psychological change trends of residential users, a questionnaire is used to evaluate the tolerance threshold of energy outages for different individuals, and the corresponding psychological risk perception curve and risk-taking willingness curve are fitted; finally, a personal impact evaluation index reflecting the impact of extreme disasters on the social domain is constructed.

[0039] 1. Basic concepts of prospect theory

[0040] Definition of Prospect Theory:

[0041] Prospect theory believes that decision makers are not completely rational and is a risk decision theory that takes decision makers’ cognition into account. The theory believes that decision makers have unequal attitudes when facing the same gains and losses, and the attributes of gains or losses are defined based on the decision maker’s psychological expectations as a reference point. The specific description of the equation is shown in formula (3).

[0042] V=π + (p)v + (x)+π - (p)v - (x) (3)

[0043] Where V is the prospect value of the decision object; π + (·) and π - (·) are the weight functions when the decision maker perceives it as gain and loss respectively; v + (·) and v- (·) are the value functions when the decision maker perceives them as gains and losses respectively; π(·) is the weight function, with π(0)=0, π(1=1; v(·) is the value function, with v(0)=0.

[0044] Properties of Prospect Theory:

[0045] (1) When the attribute is benefit relative to the reference point, the decision maker is risk-averse and the value function is convex;

[0046] (2) When the attribute is a loss relative to the reference point, the decision maker exhibits risk preference and the value function is a concave function;

[0047] (3) Equal amounts of losses and gains bring more pain to the decision maker than pleasure;

[0048] (4) Both marginal benefits and marginal losses are decreasing, that is, the farther away from the reference point, the smaller the benefit gap (loss gap). At this time, the value brought (lost) by adding one unit of benefit (loss) will be lower than the value brought (lost) by the previous unit, but decision makers are more sensitive to marginal losses than marginal benefits;

[0049] (5) The specific values ​​of the reference points vary from person to person, and their selection will directly affect the decision maker’s views on the gains and losses of the prospective behavior outcomes, thereby affecting the value function.

[0050] Value function curve and equation:

[0051] The value function curve is shown in the figure, and its specific mathematical equation is shown in formula (4).

[0052]

[0053] Among them, x0 is the reference point, which is subjectively confirmed by the decision maker; α and β are the marginal benefit sensitivity coefficient and the marginal loss sensitivity coefficient, respectively, which indicate the degree of concavity of the value function in the benefit range and the loss range, generally 0≤α≤1, 0≤β≤1, indicating that both marginal benefits and marginal losses are decreasing; λ is the loss aversion coefficient, indicating that the decision maker is more sensitive to marginal losses than marginal benefits, that is, λ≥1.

[0054] Weight function curve and equation:

[0055] The weight function curve is shown in the figure, and its specific mathematical equation is shown in formula (5).

[0056]

[0057] Among them, γ and δ are the risk attitude coefficients of the decision maker when facing unit profit or unit loss.

[0058] 2. Application of Prospect Theory

[0059] The application of prospect theory in assessing the impact of extreme disasters on people can include two parts: psychological risk perception (PRP) and risk taking willingness (RTW). The former shows the psychological changes of different residents after a disaster occurs, which can be transformed through the value curve; the latter depicts the subjective willingness of different residents to take risks after a disaster occurs, which can be transformed through the weight function curve. The combination of the two can reflect the impact of energy supply failure on people.

[0060] Psychological risk perception curve and equation:

[0061] Since residential users have different tolerance time and subjective willingness to bear risks for different energy supply failures, this paper assumes that the user’s tolerance time for power supply failure is T TTPO (Tolerance time of power outrage, TTPO), the tolerance time to gas energy outage is T TTGO (Tolerance time of gas outrage, TTGO), the tolerance time to water energy outage is T TTWO The modeling methods of the psychological risk perception curves of the three types of energy supply failure are similar. Taking the power supply failure as an example, this paper takes time t as the horizontal axis and the psychological risk perception value R of the power supply failure as the horizontal axis. PO (t) is the vertical axis, with the start time t0 of power failure as the origin and the power tolerance time T TTPO As a reference point, As the psychological risk perception mutation value, the value curve is transformed into a power failure psychological risk perception curve, as shown in the schematic diagram;

[0062] The psychological risk perception curves of gas energy and water energy failure are shown in the figure;

[0063] As shown by dashed and dotted lines. Through the schematic diagram;

[0064] The figure shows that

[0065] (1) When the actual time to restore energy supply is shorter than the expected time, residents remain psychologically optimistic about the impact of the extreme disaster, that is, the psychological risk perception curve corresponds to the "benefit interval" of the original value curve on the left side of the reference point, and the marginal benefit is decreasing (the slope of the curve gradually decreases from the reference point to the left);

[0066] (2) When the actual time to restore energy supply is equal to the expected time, the psychological risk perception of residents will reach a certain level and will suddenly change at the next moment.

[0067] (3) When the actual time to restore energy supply is longer than the expected time, residential users will think that the impact of the extreme disaster is great and will be in a negative psychological state. That is, the psychological risk perception curve on the right side of the time reference point corresponds to the "loss interval" of the original value curve, which is also a decreasing marginal loss (the slope of the curve gradually decreases from the reference point to the right);

[0068] (4) By comparing the blue line in Figure 1 and Figure 2, we can find that the psychological risk perception curve of power outage R PO (t) is actually the value curve v(t) transformed symmetrically about the reference point and then moved up Then the corresponding mathematical model can be established as shown in formula (6).

[0069]

[0070] (5) similar, schematic diagram;

[0071] The mathematical models of the psychological risk perception curves of gas and water energy failure corresponding to the yellow and green lines in the figure are shown in equations (7) and (8).

[0072]

[0073]

[0074] Risk-taking willingness curve and equation:

[0075] The risk willingness curve W(p) for the three types of energy supply failure is similar to the weight function curve π(p). Since the probability p of the residents' psychological risk perception relative to the reference point being a "benefit interval" (psychological optimism) or a "loss interval" (psychological pessimism) for a certain extreme disaster is determined to be 1 or 0, the corresponding risk willingness function should also be 1 or 0. Specifically, the risk willingness functions of residents for the three types of energy supply failures of electricity, gas, and water are shown in equations (9), (10), and (11), respectively.

[0076]

[0077] 3. Personal impact evaluation indicators

[0078] Calculation of the prospect value of energy supply failure

[0079] Substituting equations (6)-(8) and equations (9), (10), and (11) into equation (3), we can calculate the prospect values ​​of power failure, gas failure, and water failure, as shown in equations (12), (13), and (14), respectively. The specific mathematical model of the total personal impact index (IP) of disasters on residential users is shown in equation (15).

[0080] I P(PO) (t) = W PO+ (p)R PO+ (t)+W PO- (p)R PO- (t) (12)

[0081] I P(GO) (t) = W GO+ (p)R GO+ (t)+W GO- (p)R GO- (t) (13)

[0082] I P(WO) (t) = W WO+ (p)R WO+ (t)+W WO- (p)R WO- (t) (14)

[0083] I P =N user (I P(PO) (t PR )+I P(GO) (t GR )+I P(WO) (t WR )) (15)

[0084] Among them, I P(PO) ,I P(GO) ,I P(WO) I are the personal impact of power, gas and water failure at time t; P As the personal impact evaluation index; N user is the number of residential users; t PR ,t GR and t WR They are the moments when electricity, gas and water energy are restored.

[0085] Individual Difference Analysis

[0086] in I P The parameters to be determined mainly include two aspects, one of which is the reference point T TTPO , T TTGO , T TTWOThe second is the selection of the degree of concavity of the psychological risk perception curve, namely the parameters α, β and λ.

[0087] Since there are large individual differences in the values ​​of the two types of parameters, that is, they are related to the tolerance of different users to energy supply failures and the subjective willingness to take risks, residential users are divided into three categories according to their age: teenagers, middle-aged people, and elderly people. Specifically, a questionnaire survey was used to evaluate the tolerance of the three groups of people to the three types of energy supply failures and the subjective willingness to take risks. The evaluation results are shown in Tables 1 and 2, respectively. Among them, Table 1 is the result obtained by conducting a questionnaire survey on 500 residents in a community and screening the data. In Table 2, data from the literature are used as various coefficients for middle-aged people to risks and losses, and considering that young people are less sensitive and less averse to marginal gains / losses than middle-aged people, but they are more willing to take risks for small probability events, at this time there is α TE <α MA , β TE <β MA ,λ TE <λ MA ; The elderly are more sensitive and avoidant of marginal gains / losses than middle-aged people, and are less willing to take risks for low-probability events. EL >α MA , β EL >β MA ,λ EL >λ MA .

[0088] Table 1

[0089] <![CDATA[Power outage tolerance time T TTPO > <![CDATA[Gas energy loss supply tolerance time T TTGO > <![CDATA[Water energy loss supply tolerance time T TTWO > young people 5(h) 8(h) 5(h) Middle-aged people 4(h) 4(h) 2(h) Elderly 2(h) 4(h) 2(h)

[0090] Table 2

[0091]

[0092]

[0093] As an implementation method of an embodiment of the present invention, in step S3, through the modeling of steps S1 and S2, the prerequisite for evaluating the impact of disasters on the physical domain and social domain has been met. However, in actual disaster scenarios, the actual energy supply outage time of each residential user is difficult to obtain. Therefore, an innovative emergency recovery strategy is proposed, which can not only coordinate distributed power sources and repair teams to participate in system recovery after the disaster, but also accurately evaluate the user's power outage time. Specifically, this strategy aims to minimize the impact of disasters on the physical domain and social domain of the system, and uses the operating equations of the three systems of electricity, gas, and water as constraints to establish an innovative mixed integer programming model.

[0094] In order to evaluate and effectively reduce the impact of extreme disasters on the physical and social domains of the system, a mixed integer nonlinear programming model was established with the goal of minimizing the comprehensive evaluation index and the operating equations of the electricity, gas and water systems and the components as constraints. The propagation process of power failure between the gas and water networks was analyzed, and the optimal emergency recovery strategy for multi-source coordination after the disaster was formulated.

[0095] 1. Objective function:

[0096] minε1I E +ε2I P +ε3χ extra (16)

[0097]

[0098] Among them, ε1, ε2 and ε3 are weight coefficients respectively, among which ε3 is much smaller than ε1 and ε2, while the values ​​of ε1 and ε2 depend on the degree of attention paid by decision makers to the physical domain impact and social domain impact caused by the disaster; c ES The cost of charging a unit of electricity into the energy storage; is the electric power absorbed by the energy storage at node j at time t; is the electric power generated by the diesel generator on node j at time t; c DG It is the output cost of diesel generator per unit power generation.

[0099] The objective function (16) is mainly composed of three parts. The first two items are the main parts, representing the impact of disasters on the physical domain and social domain. The third item is the dispatch cost of emergency recovery resources of the power system, including energy storage charging costs and diesel generator output costs. The reason for taking the third item into account is to avoid unnecessary work processes of emergency resources when the system function returns to normal. Since the order of magnitude of the third item is generally smaller than the first two items, the main part of the objective function is still to minimize the impact of disasters on the physical domain and social domain of the system.

[0100] 2. Power system model

[0101] System operation equation

[0102] The power system operation equations include node active and reactive power balance (18)-(19); node power reduction (20)-(21); linear Distflow describing branch power flow constraints (22). When w ij,t= 0, that is, when the switch of branch (i, j) is disconnected, the relationship between the branch flow and the node voltage is relaxed; linearized branch capacity constraints (23)-(24); node voltage constraints (25); repair team scheduling constraints (26)-(29), branch switch state constraints (30); grid dynamic reconstruction constraints described by a single commodity flow (31)-(34).

[0103]

[0104]

[0105] in, is the set of grid nodes, A collection of power grid lines; and are the sets of nodes downstream and upstream of node j respectively; P jk,t is the active power flow of branch (j, k) at time t; Q jk,t is the reactive power flow of branch (j, k) at time t; P j,t and Q j,t are the active power and reactive power of the load at node j at time t respectively; is the electric power discharged by the energy storage on node j at time t; is the electric power generated by the distributed photovoltaic on node j at time t; is the electrical power consumed by the compressor on node j at time t; is the electric power consumed by the water pump at node j at time t; and are the normal values ​​of active power and reactive power of the load at node j at time t; p ij,t is a 0-1 variable that determines whether the fault line (i, j) is being repaired at time t. If it is being repaired, then p ij,t =1, otherwise p ij,t =0;q ij,t is a 0-1 variable indicating whether the fault state of the fault line (i, j) has changed at time t. If the fault state has changed, then q ij,t =1, otherwise q ij,t =0; r ij,t is the repair status of the fault line (i, j) at time t. If the repair is complete, then r ij,t =1, otherwise r ij,t =0; is the set of fault lines; M is a very large constant; T ij is the repair time of the faulty line (i, j); N RC is the number of repair teams; w ij,t is the switch state of line (i, j) at time t. When the switch is closed, wij,t =1, otherwise w ij,t =0; R ij and X ij are the resistance and reactance of branch (i, j) respectively; S ij is the capacity of branch (i, j); V j,t is the voltage of node j at time t; and are the maximum and minimum values ​​of the voltage at node j, respectively; is the number of grid nodes; is a set of potential root nodes, including substation nodes, distributed power generation nodes, and the first and last nodes of the fault line; I j,t A 0-1 variable to determine whether node j can be the root node of an island. When node j can be the root node, I j,t =1, otherwise I j,t =0; F ij,t is the power flow of branch (i, j) in the virtual network at time t.

[0106] Component operation equation

[0107] The operating equations of the power system components include energy storage charging and discharging constraints (35)-(39), diesel generator discharge constraints (40), and distributed photovoltaic output constraints (41).

[0108]

[0109] in, and are the charging and discharging states of the energy storage on node j at time t respectively. If it is in the charging state, then If it is in the discharge state, there is and are the maximum electric power that the energy storage at node j can absorb or release within unit time Δt; is the capacity of energy storage on node j at time t; and are the charging and discharging efficiencies of energy storage at node i, respectively; is the maximum capacity of energy storage at node j; and are the minimum and maximum values ​​of the energy storage charge state at node i, respectively; and are the minimum and maximum electric power that the diesel generator at node j can generate respectively; is the maximum value of distributed photovoltaic output at node j; h t is the per-unit value of the distributed photovoltaic output at time t.

[0110] 3. Natural gas system model

[0111] System operation equation

[0112] This patent does not consider the dynamic change process of natural gas, that is, it adopts the system steady-state operation equation, including node flow balance (42), node flow reduction (43), the relationship between pipeline flow and node pressure of low-pressure gas network (gas pressure less than 750pa) (Lacey equation) (44)-(46), pipeline flow limitation (47), and node pressure limitation (48).

[0113]

[0114] in, is the set of gas network nodes; For the gas network pipeline collection, this paper divides the natural gas pipeline into pipelines with compressors (active pipelines) and pipelines without compressors (inactive pipelines), which are set as collections and G ij,t is the natural gas flow in the gas network pipeline (i, j) at time t, g i,t is the natural gas flow rate injected into or out of the gas grid node i at time t, with outflow taking positive values ​​and injection taking negative values; and are the sets of nodes downstream and upstream of natural gas grid node j respectively; is the normal value of natural gas load at gas grid node i at time t; s ij,t is a 0-1 variable that determines the natural gas flow direction in pipeline (i, j) at time t; p i,t is the pressure at the gas network node i at time t; and are the diameter, friction coefficient and length of the natural gas pipeline (i, j) respectively; ρ G is the relative density of gas; and are the minimum and maximum flow rates allowed to flow through the natural gas pipeline (i, j) respectively; and are the minimum and maximum allowable pressures at natural gas node j, respectively.

[0115] Component operation equation

[0116] (1) Gas source (GS)

[0117] This patent assumes that the gas storage capacity at the gas source is large enough, that is, the flow balance equation corresponding to the gas source node in formula (42) is relaxed; at the same time, it is assumed that the gas source can always maintain a constant air pressure in each time period after the occurrence of an extreme disaster, as shown in formula (49).

[0118]

[0119] in, A collection of nodes connected to the gas source.

[0120] (2) Compressor (CP)

[0121] The compressor used in this patent is driven by a motor. When the compressor input power is greater than the minimum rated value, the electric energy consumed by the compressor is related to the flow rate and compression ratio of the connected pipeline; when the compressor input power is less than the minimum rated value, the compressor does not work, the flow rate of the connected pipeline is 0, and the component operation equation is shown in formula (50).

[0122]

[0123] in, is the input electrical power of the compressor connected to the natural gas pipeline (i, j) at time t; is the power consumption coefficient of the compressor; It is the minimum rated electrical power of the compressor connected to the natural gas pipeline (i, j) when it is working normally.

[0124] 4. Hydraulic system model

[0125] System operation equation

[0126] The operating equations of the water network system include node flow balance (51), node flow reduction (52), pipeline head loss (53), Darey-Weisbach equation (54), pipeline flow limitation (55), and node head limitation (56).

[0127]

[0128] in, is a collection of water network nodes; is a water network pipeline set. In this paper, the water network pipeline is divided into pipelines with water pumps (active pipeline) and pipelines without water pumps (inactive pipeline), which are set as sets and are the sets of nodes downstream and upstream of water network node j respectively; is the normal value of water load at water network node j at time t; H i is the altitude of node i (residential user on the first floor); and are the friction coefficient, length and diameter of the water network pipe (i, j) respectively; g is the acceleration due to gravity; and are the minimum and maximum flow rates allowed to flow through the water network pipe (i, j) respectively; and are the minimum and maximum allowable water head at water network node j, respectively.

[0129] Component operation equation

[0130] (1) Water supply plant (WSP)

[0131] This patent assumes that the water capacity of the water supply plant is large enough, that is, the flow balance equation corresponding to the water supply plant node in formula (51) is relaxed; at the same time, it is assumed that the water supply plant can always keep the water head unchanged in each time period after the occurrence of extreme disasters, as shown in formula (57).

[0132]

[0133] in, A collection of nodes connected to the water plant.

[0134] (2) Water pump (WP)

[0135] This patent assumes that the water pump is a constant speed machine. According to the flow-power performance curve of the water pump, it can be found that when the input power of the water pump is greater than the minimum rated value, the power consumed by the water pump will be positively correlated with the flow of the connected water pipe, and the head of the node that the water pump can lift and the flow of the connected water pipe can be approximated as a linear function; when the input power of the water pump is less than the minimum rated value, that is, the water pump is not working, although there can still be a certain amount of water flow through the water pump, long-term non-powered operation will cause damage to the water pump, so in real life, measures are usually taken to close the valve, that is, the flow of the pipe connected to the water pump is 0. The specific mathematical model is shown in equations (58)-(59).

[0136]

[0137] in, is the input power of the water pump connected to the water network pipeline (i, j) at time t; ρ is the water density; η WP is the efficiency of the water pump; A and B are the linear term and constant term coefficients of the linear function between the water head that the water pump can lift and the flow rate of the connected water pipe; It is the minimum rated electrical power of the water pump connected to the water network pipe (i, j) when it is working normally.

[0138] Embodiment 2:

[0139] The embodiment of the present invention further provides a device for improving the toughness of an electrical water system, comprising:

[0140] The first calculation module is used to calculate the economic impact evaluation index I E To describe the impact of disasters on the physical domain of the system;

[0141] The second calculation module is used to calculate the personal impact evaluation index I P To describe the impact of disasters on the social domain;

[0142] The improvement module is used to construct a mixed integer nonlinear programming model based on the impact of disasters on the physical domain of the system and the impact of disasters on the social domain, with the goal of minimizing the comprehensive evaluation index, and with the operating equations of the electricity, gas and water systems and the component operating equations as constraints, to formulate the optimal post-disaster emergency recovery strategy for the electricity-gas-water coupling system based on the comprehensive importance of loads.

[0143] As an implementation method of an embodiment of the present invention, the first calculation module calculates the economic impact evaluation index I according to the unit price data of residents' electricity, gas and water purchases. E To describe the impact of disasters on the physical domain of the system.

[0144] As an implementation method of an embodiment of the present invention, the second calculation module uses prospect theory to calculate the personal impact evaluation index I according to the location distribution and number of users of different age groups in the three network nodes. P To describe the impact of disasters on the social domain.

[0145] Embodiment 3:

[0146] An embodiment of the present invention also provides an electrical water system resilience improvement system, characterized in that it includes: a memory and a processor, wherein the memory stores a computer program run by the processor, and the computer program executes an electrical water system resilience improvement method when run by the processor.

[0147] Embodiment 4:

[0148] An embodiment of the present invention further provides a storage medium, on which a computer program is stored, and the computer program executes the method for improving the resilience of an electrical water system when running.

[0149] The embodiments described above are only descriptions of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for improving the toughness of an electrical water system, characterized in that: include: Step S1: Calculate economic impact assessment index I E To describe the impact of disasters on the physical domain of the system; Step S2: Calculate the personal impact evaluation index I P To describe the impact of disasters on the social domain; Step S3: Based on the impact of disasters on the physical domain of the system and the impact of disasters on the social domain, with the goal of minimizing the comprehensive evaluation index and the operating equations of the electricity, gas and water systems and the component operating equations as constraints, a mixed integer nonlinear programming model is constructed to formulate the optimal post-disaster emergency recovery strategy for the electricity-gas-water coupling system based on the comprehensive importance of loads.

2. The method for improving the toughness of an electrical water system according to claim 1, characterized in that: In step S1, the economic impact evaluation index I is calculated based on the unit price data of residents' electricity, gas and water purchases. E To describe the impact of disasters on the physical domain of the system.

3. The method for improving the toughness of an electrical water system according to claim 2, characterized in that: In step S1, according to the location distribution and number of users of different age groups in the three network nodes, the prospect theory is used to calculate the personal impact evaluation index I P To describe the impact of disasters on the social domain.

4. An electrical water system toughness improvement device, characterized in that: include: The first calculation module is used to calculate the economic impact evaluation index I E To describe the impact of disasters on the physical domain of the system; The second calculation module is used to calculate the personal impact evaluation index I P To describe the impact of disasters on the social domain; The improvement module is used to construct a mixed integer nonlinear programming model based on the impact of disasters on the physical domain of the system and the impact of disasters on the social domain, with the goal of minimizing the comprehensive evaluation index, and with the operating equations of the electricity, gas and water systems and the component operating equations as constraints, to formulate the optimal post-disaster emergency recovery strategy for the electricity-gas-water coupling system based on the comprehensive importance of loads.

5. The electrical water system toughness improvement device according to claim 4, characterized in that: The first calculation module calculates the economic impact evaluation index I based on the unit price data of residents' electricity, gas and water purchases. E To describe the impact of disasters on the physical domain of the system.

6. The electrical water system toughness improvement device according to claim 5, characterized in that: The second calculation module uses prospect theory to calculate the personal impact evaluation index I according to the location distribution and number of users of different age groups in the three network nodes. P To describe the impact of disasters on the social domain.

7. An electrical water system toughness improvement system, characterized in that: include: A memory and a processor, wherein the memory stores a computer program executed by the processor, and when the computer program is executed by the processor, the method for improving the resilience of an electrical water system as described in any one of claims 1 to 3 is executed.

8. A storage medium, characterized in that: The storage medium stores a computer program, which, when running, executes the method for improving the resilience of an electrical water system as described in any one of claims 1 to 3.

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