Reliability evaluation method of electrical-thermal integrated energy system considering icing modeling of wind turbine under freezing weather

Abstract

The application discloses an electrical-thermal integrated energy system reliability evaluation method considering fan icing modeling under frozen weather, and steps include: 1) calculating the icing amount on the fan blade; 2) establishing an electrical-thermal integrated energy system energy flow model and an optimal load shedding model; 3) obtaining energy system state parameters; 4) inputting the energy system state parameters into the electrical-thermal integrated energy system energy flow model, and obtaining the system energy flow by solving; analyzing the system energy flow, if the system energy flow is not evaluable, then entering step 5), otherwise jumping to step 6); 5) optimizing the load parameters in the energy system state parameters by using the optimal load shedding model, and then returning to step 4); 6) based on the system energy flow, calculating the energy system reliability index, and completing the energy system reliability evaluation. The fan icing stop model provided by the application makes the integrated energy system reliability evaluation more accurate.

Description

Technical Field

[0001] This invention relates to the field of reliability assessment of integrated energy systems under extreme freezing weather, specifically a reliability assessment method for integrated electrical and thermal energy systems considering wind turbine icing modeling under freezing weather. Background Technology

[0002] With rapid socio-economic development, the demand for and scale of electricity are constantly expanding, and the power grid is continuously increasing its investment in and use of renewable energy. However, with the intensification of climate change, the frequency and density of natural disasters and extreme weather events are increasing. Wind and solar power are extremely vulnerable to the impact of extreme weather, leading to large-scale outages and power losses. Especially in winter, freezing weather can cause wind turbines in high-altitude areas to become icy and stop operating. For example, in Guangxi, more than 70 wind farms experience short-term outages annually due to freezing weather, severely impacting the reliable operation of the power grid. Furthermore, because the integrated energy system combines electricity, gas, and heat, insufficient power supply will increase the load on gas and heat networks, placing a burden on them.

[0003] Against this backdrop, establishing an icing-induced shutdown model for wind turbines under freezing weather conditions, considering factors such as temperature, pressure, and wind speed, helps the power system adjust its power generation strategy in a timely manner based on wind power supply, thereby improving the reliability of the integrated energy system. Existing research has documented the impact of extreme freezing weather on power system reliability assessments. Some scholars have proposed an image-based ice detection method to study the capacitance effect of the icing process. The feasibility of icing based on conductor capacitance measurement monitoring has been empirically studied through air icing experiments under certain climatic conditions. The relationship between ice capacitance and conductor and ice thickness is a power function. This method explores the functional relationship of ice thickness but cannot determine the relationship between ice thickness and wind turbine shutdown, limiting its application to specific experimental environments. Some scholars, addressing the cascading fault risk caused by transmission line icing, have established a piecewise linear model of transmission line fault probability considering ice accumulation thickness, based on a transmission line ice accumulation model. This model often relies on prediction and observation of line sag, making it unsuitable for assessing the icing situation of wind turbines. Some scholars have also established real-time fault probability prediction models for transmission lines and towers under ice storm disasters based on extreme learning machines and Copula functions. This prediction method requires a large amount of data; in reality, there is limited data on wind turbine icing, making it difficult to accurately predict wind turbine shutdown due to icing. Grid connection of wind power has a positive impact on improving low-voltage and transmission loads, alleviating the power system's electricity consumption burden to some extent. However, current research has not addressed the icing situation of wind turbines under extreme freezing weather, posing a serious challenge to wind power reliability under such conditions. It is essential to accurately and effectively determine whether wind turbines will stop due to icing and to conduct a comprehensive energy reliability assessment under freezing weather conditions. This will enable timely adjustments to power generation strategies to improve system reliability. Summary of the Invention

[0004] The purpose of this invention is to provide a reliability assessment method for an integrated electrical and thermal energy system that considers wind turbine icing modeling under freezing weather conditions, comprising the following steps:

[0005] 1) Calculate the amount of ice accumulation on the wind turbine blades and determine the wind turbine failure rate;

[0006] 2) Establish an energy flow model and an optimal load shedding model for the integrated electricity-gas-heat energy system;

[0007] 3) Based on the failure rate of the wind turbine, the integrated electrical and thermal energy system is sampled to obtain the energy system status parameters;

[0008] 4) Input the energy system state parameters into the energy flow model of the integrated electric-gas-heat energy system and calculate the system energy flow; analyze the system energy flow. If the system energy flow cannot be evaluated, proceed to step 5); otherwise, proceed to step 6.

[0009] 5) Optimize the load parameters in the energy system state parameters using the optimal load shedding model, and then return to step 4);

[0010] 6) Based on the system energy flow, calculate the energy system reliability index and complete the energy system reliability assessment.

[0011] Furthermore, the steps for calculating the amount of ice accumulation on the wind turbine blades include:

[0012] 1.1) Calculate the flow field distribution on the surface of the wind turbine blades using the Navier-Stokes equations;

[0013] 1.2) Calculate the trajectory of water droplets in the air;

[0014] 1.3) Calculate the amount of ice on the wind turbine blades based on the flow field distribution on the surface of the wind turbine blades and the trajectory of water droplets in the air.

[0015] Furthermore, the Navier-Stokes equations are as follows:

[0016]

[0017]

[0018]

[0019] In the formula, P is the pressure on the fluid element; For generalized source terms; F x F y F z Let F be the volume force on the infinitesimal element. If the only volume force is gravity, and the z-axis is vertically upward, then F x =0,F y =0,F z =-ρg;u x u y u z , , and z represent the velocities along the x, y, and z axes, respectively; μ is the dynamic viscosity of the fluid; ρ is the second molecular viscosity of the fluid; U represents the velocity vector of the difference between the blade velocity and the fluid velocity; ρ is the fluid density.

[0020] Furthermore, the trajectories of water droplets in the air are shown below:

[0021]

[0022] Where: M d For the mass of the water droplet, M d =V d *ρ a V d ρ is the volume of the water droplet; aρ d These are the densities of air and water droplets, respectively; A d The surface area of ​​the water droplet facing the wind; These are the air motion vector and the water droplet motion vector, respectively; C d This is the drag coefficient. It is the acceleration due to gravity;

[0023] Furthermore, the amount of ice accretion on the wind turbine blades was calculated using the Messier model;

[0024] The Messinger model is shown below:

[0025]

[0026]

[0027] In the formula: This refers to convective heat transfer between the airflow and the surface of a certain controlled area. The surface of the controlled area is heated by air friction; The heat absorbed by the evaporation of water droplets or ice surfaces within the controlled area; The heat energy generated by the water droplets impacting the surface of that area; The heat generated by the kinetic energy of water droplets impacting the surface of that area. This refers to the heat released during the freezing process of water droplets into ice in the controlled area; The mass of the water droplet impacting a certain controlled area; The mass of water droplets overflowing from the surface of the wind turbine blades and flowing into the control area; This refers to the amount of water droplet evaporation or the mass of ice sublimation in the controlled area. The mass of water droplets overflowing from the surface of the wind turbine blades and flowing out of the control area; This refers to the mass of water droplets that freeze into ice in this area.

[0028] Furthermore, the failure rate of the wind turbine is characterized by the icing coefficient;

[0029] The icing coefficient f is shown below:

[0030]

[0031] In the formula: The mass of the water droplet impacting the control area; The mass of water droplets overflowing from the surface of the wind turbine blades and flowing into the control area; The mass of water droplets frozen into ice in this area. The icing coefficient obtained by formula (7) is compared with the actual situation. By comparison, the critical value of the fan icing failure is obtained, and thus the fan failure rate is obtained.

[0032] Furthermore, the energy system status parameters include system component status parameters, electrical-gas-heat load, illumination, and wind speed; the system component parameters include generators, lines, transformers, gas sources, gas pipelines, and heat sources.

[0033] Furthermore, the energy flow model of the integrated electric-gas-heat energy system is shown below:

[0034]

[0035]

[0036]

[0037]

[0038] In the formula: P W,i P represents the active power output of the i-th wind farm. PV,i P represents the active power output of the i-th photovoltaic electric field. G,i Q G,i P represents the active power and reactive power output of the i-th non-gas conventional generator set; GAS,i Q GAS,i P represents the active power and reactive power output of the i-th gas generator set; CHP,i Q CHP,i Let Q be the active power and reactive power output of the i-th gas-fired combined heat and power generator unit; W,i Q represents the reactive power output of the i-th wind farm. PV,i Q represents the reactive power output of the i-th photovoltaic field. C,i P represents the reactive power output of the i-th reactive power compensation device. D,i Q D,i F represents the active and reactive power of the load at the i-th node. GAS,m F CHP,m F P2G,m These are the gas-fired generator sets, gas-fired combined heat and power units, and the injection gas flow of the P2G unit at node m of the natural gas system; F G,m F D,m F m These represent the injection gas flow, gas load, and node injection gas flow at node m of the natural gas system, respectively; Φ G,i Φ represents the thermal power output of the i-th heat source station. D,i N represents the thermal power of the heat load at the i-th node; e N m N h These represent the number of nodes in the power system, natural gas system, and heating system, respectively; P P2G,i The active power output of the P2G device; Φ CHP,iP represents the thermal power of a gas-fired combined heat and power unit. EB,i Φ represents the active power output of the i-th gas-fired boiler. EB,i Let i be the output thermal power of the i-th gas-fired boiler;

[0039] Among them, the active power P injected by node i of the power system i Reactive power Q i Natural gas node m injection gas flow F m Thermal power Φ at node i of the thermal system i As shown below:

[0040]

[0041]

[0042]

[0043]

[0044] In the formula, V i V j θ represents the voltage amplitude at the i-th and j-th power system nodes; ij It is the voltage phase angle difference between nodes i and j in the power system; G ij and B ij Let N be the real and imaginary parts of the element in the i-th row and j-th column of the nodal admittance matrix, respectively; e F represents the total number of nodes in the power system. m Inject gas flow into the natural gas node; B mr E mr and T mr These are the elements in the m-th row and r-th column of the node-pipe association matrix B, the node-compressor association matrix E, and the node-compressor inlet node association matrix T, respectively; N m Φ represents the total number of nodes in the natural gas system. i For the injected thermal power at node i; C p D is the specific heat capacity of water. ih The element in the i-th row and h-th column of the node-heating pipeline association matrix of the thermal system; T s,i ,T r,i These represent the heating and regeneration temperatures at node i of the thermal system, respectively; N h m is the number of nodes in the thermal system. h N represents the heat flow rate of the h-th heating pipe. p N r Total number of gas transmission pipelines and compressor branches respectively; L r C r τ rThese represent the flow rates through the gas transmission pipeline r and the compressor branch r in the natural gas system, respectively, and the flow rates consumed by the compressor branch r.

[0045] The electrical power P generated by the i-th unit CHP,i The natural gas flow rate F consumed by the i-th unit CHP,i As shown below:

[0046]

[0047]

[0048] In the formula, P CHP,i and H CHP,i F represents the electrical power and thermal power generated by the i-th unit, respectively; CHP,i v represents the natural gas flow rate consumed by the i-th unit; CHP,i and η CHP,i These represent the heat-to-power ratio and conversion efficiency of the i-th unit, respectively; GHV represents the higher calorific value of natural gas; N b This represents the total number of gas-fired combined heat and power (CHP) units.

[0049] The power consumption F of P2G device i P2G,i As shown below:

[0050]

[0051] In the formula: F P2G,i P P2G,i η P2G,i These represent the power consumption, injection gas flow, and conversion efficiency of P2G unit i, respectively; GHV represents the higher calorific value of natural gas; N w N c These represent the total number of wind farms and P2G transpositions, respectively; ΔP W,k Let k be the wind curtailment power of wind farm k;

[0052] The amount of natural gas consumed by the i-th gas-fired boiler, F GB,i As shown below:

[0053]

[0054] In the formula, F GB,i Φ represents the amount of natural gas consumed by the i-th gas-fired boiler; GB,i η is the output thermal power of the i-th gas-fired boiler; GB,i Let N be the conversion efficiency of the i-th gas-fired boiler; gb This refers to the number of gas-fired boilers.

[0055] Furthermore, the objective function min f of the optimal load reduction model is as follows:

[0056]

[0057] In the formula: C e,i C g,m C h,k These represent the load reduction amounts at electrical load node i, gas load node m, and gas-fired cogeneration unit k, respectively; ΔP W,i Let ΔP be the curtailment power of wind farm i; S,i Let N be the power of the discarded light in the photoelectric field i; d N g These represent the total number of electrical load nodes and gas load nodes, respectively; λ e,i , λ g,m , λ h,k , λ w,i , λ s,i Weighting factors representing the severity of wind and solar curtailment for each electrical load, gas load, heat load, and wind / solar farm; N s This represents the total number of natural gas sources.

[0058] Furthermore, the constraints of the optimal load shedding model include equality constraints and inequality constraints;

[0059] The equality constraints are as follows:

[0060]

[0061]

[0062]

[0063]

[0064] The inequality constraints are as follows:

[0065]

[0066]

[0067]

[0068]

[0069]

[0070]

[0071]

[0072]

[0073]

[0074]

[0075]

[0076]

[0077]

[0078]

[0079]

[0080]

[0081]

[0082]

[0083]

[0084]

[0085]

[0086]

[0087] Where: N e_load N represents the number of electrical loads. g_load For gas load quantity; N h_load P represents the amount of heat load. W,i The active power of the wind farm; and These are the upper and lower limits of the active power output of the i-th gas-fired combined heat and power unit with thermal storage, respectively. and These are the upper and lower limits of the reactive power output of the i-th gas-fired cogeneration unit with thermal storage, respectively. This represents the maximum storage capacity of the i-th thermal storage device; and These are the upper and lower limits of the active power output of the i-th gas generator set, respectively; and These are the upper and lower limits of the reactive power output of the i-th gas generator set, respectively; and Let m be the upper and lower limits of the electrical power consumption of the i-th electric boiler, respectively; h The heat flow rate of the h-th heating pipe; and These are the upper and lower limits of the active power output of the i-th non-gas conventional generator set, respectively; and N represents the upper and lower limits of the reactive power output of the i-th non-gas conventional generator set; u This represents the total number of non-gas-fired conventional generating units. and N represents the upper and lower limits of the gas injection volume for the m-th natural gas system node; s This represents the total number of natural gas sources. and These are the upper and lower limits of the heat power of the heat source station at the i-th node of the thermal system, respectively; N z The number of heat source stations; R r Let r be the compression ratio of the compressor branch. and These are the upper and lower limits of the compression ratio for compressor branch r, respectively; and These are the upper and lower limits of the voltage amplitude at the i-th power system node, respectively; and These are the upper and lower limits of the transmission power of the l-th transmission line; and These are the upper and lower limits of the gas pressure at the m-th natural gas system node, respectively; and Let these be the upper and lower limits of the heating temperature supplied to the i-th node of the thermal system; and Let be the upper and lower limits of the regeneration temperature of the i-th thermal system node; and These are the upper and lower limits of the heat flow rate for the h-th heating pipe, respectively. hp This refers to the number of heating pipes.

[0088] Furthermore, the energy system reliability indicators include the expected value of insufficient power (EEDNS), the expected value of insufficient gas (EGDNS), the expected value of insufficient heat (EHDNS), the expected value of curtailed wind power (EWC), and the expected value of curtailed solar power (ESC).

[0089] The expected values ​​for system power shortage (EEDNS), gas shortage (EGDNS), heat shortage (EHDNS), wind power curtailment (EWC), and solar power curtailment (ESC) are as follows:

[0090]

[0091]

[0092]

[0093]

[0094]

[0095] In the formula: G1, G2, and G3 represent the sets of states where electricity, gas, and heat loads are reduced, respectively; P(x) is the probability that the system is in state x; G4 and G5 represent the sets where wind curtailment and solar curtailment occur, respectively.

[0096] Wherein, under state x, the system electrical load reduction C e (x) System gas load reduction C g (x) System heat load reduction C h (x) Wind curtailment ΔP W (x), Photoelectric field abandoned light amount ΔP S (x) are shown below:

[0097]

[0098]

[0099]

[0100]

[0101]

[0102] In the formula, ΔP S,i (x) represents the amount of light discarded by the i-th photoelectric field.

[0103] Furthermore, the inability to assess system energy flow refers to situations where voltage or gas pressure exceeds limits, or where system energy flow does not converge.

[0104] It is worth noting that this invention accurately models the icing situation of wind turbines under freezing weather conditions and assesses the impact of wind turbine icing on the reliability of the integrated energy system. This invention first considers factors such as temperature, pressure, and wind speed, and establishes an icing model of wind turbines under extreme freezing weather based on the Navier-Stokes equations and the Messier model. The icing conditions of the wind turbines are determined through mathematical modeling, and then the reliability of the integrated energy system is assessed using an optimal load shedding model based on Newton's method.

[0105] The technical effectiveness of this invention is undeniable. The wind turbine icing shutdown model proposed in this invention makes the reliability assessment of integrated energy systems more accurate. The power grid can adjust its power generation strategy based on the assessment results, ensuring the reliable operation of the integrated energy system. Reliability assessments of the electricity-gas-heat integrated energy system under extreme freezing weather conditions show that, considering wind turbine icing, all reliability indicators decrease, more closely reflecting actual conditions. Attached Figure Description

[0106] Figure 1This is a system architecture diagram of IEEE 9-NGS6-DHN7;

[0107] Figure 2 To take into account the comparison of various data before and after the wind turbine is covered with ice. Detailed Implementation

[0108] The present invention will be further described below with reference to embodiments, but it should not be construed that the scope of the present invention is limited to the following embodiments. Various substitutions and modifications made based on ordinary technical knowledge and common practices in the art without departing from the above-described technical concept of the present invention should be included within the scope of protection of the present invention.

[0109] Example 1:

[0110] See Figures 1 to 2 A reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions includes the following steps:

[0111] 1) Calculate the amount of ice accumulation on the wind turbine blades and determine the wind turbine failure rate;

[0112] 2) Establish an energy flow model and an optimal load shedding model for the integrated electricity-gas-heat energy system;

[0113] 3) Based on the failure rate of the wind turbine, the integrated electrical and thermal energy system is sampled to obtain the energy system status parameters;

[0114] When conducting reliability assessments, it is necessary to sample various parts of the system. If the fan failure rate is not considered, the sampling is a random process, and the assessment results are not accurate enough. The role of the fan failure rate is to ensure that the fan is judged as faulty when the system status is sampled, based on the probability of the fan failure.

[0115] 4) Input the energy system state parameters into the energy flow model of the integrated electric-gas-heat energy system and calculate the system energy flow; analyze the system energy flow. If the system energy flow cannot be evaluated, proceed to step 5); otherwise, proceed to step 6.

[0116] 5) Optimize the load parameters in the energy system state parameters using the optimal load shedding model, and then return to step 4);

[0117] 6) Based on the system energy flow, calculate the energy system reliability index and complete the energy system reliability assessment.

[0118] Example 2:

[0119] The reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions is the same as in Example 1. Further, the steps for calculating the amount of ice accretion on the wind turbine blades include:

[0120] 1.1) Calculate the flow field distribution on the surface of the wind turbine blades using the Navier-Stokes equations;

[0121] 1.2) Calculate the trajectory of water droplets in the air;

[0122] 1.3) Calculate the amount of ice on the wind turbine blades based on the flow field distribution on the surface of the wind turbine blades and the trajectory of water droplets in the air.

[0123] Example 3:

[0124] A reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions is provided. The technical content is the same as any one of Examples 1-2. Furthermore, the Navier-Stokes equations are as follows:

[0125]

[0126]

[0127]

[0128] In the formula, P is the pressure on the fluid element; For generalized source terms; F x F y F z Let F be the volume force on the infinitesimal element. If the only volume force is gravity, and the z-axis is vertically upward, then F x =0,F y =0,F z =-ρg;u x u y u z , , and z represent the velocities along the x, y, and z axes, respectively; μ is the dynamic viscosity of the fluid; ρ is the second molecular viscosity of the fluid; U represents the velocity vector of the difference between the blade velocity and the fluid velocity; ρ is the fluid density.

[0129] Example 4:

[0130] A reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions is provided, with technical content identical to any one of Examples 1-3. Furthermore, the trajectory of water droplets in the air is shown below:

[0131]

[0132] Where: M d For the mass of the water droplet, Md =V d *ρ a V d ρ is the volume of the water droplet; a ρ d These are the densities of air and water droplets, respectively; A d The surface area of ​​the water droplet facing the wind; These are the air motion vector and the water droplet motion vector, respectively; C d This is the drag coefficient. It is the acceleration due to gravity;

[0133] Example 5:

[0134] A reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions, with technical content the same as any one of Examples 1-2. Furthermore, the amount of icing on the wind turbine blades is calculated using the Messier model.

[0135] Example 6:

[0136] A reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions is provided. The technical content is the same as any one of Examples 1-5. Furthermore, the Messinger model is shown below:

[0137]

[0138]

[0139]

[0140] In the formula: This refers to convective heat transfer between airflow and the surface of a certain control area; the control area is a field selected according to the size of the fan blades. In this embodiment, two sets of surfaces with a radius of 44m are selected, and the area between the two surfaces constitutes the field with a width of 1m. The surface of the controlled area is heated by air friction; The heat absorbed by the evaporation of water droplets or ice surfaces within the controlled area; The heat energy generated by the water droplets impacting the surface of that area; The heat generated by the kinetic energy of water droplets impacting the surface of that area. This refers to the heat released during the freezing process of water droplets into ice in the controlled area; The mass of the water droplet impacting a certain controlled area; The mass of water droplets overflowing from the surface of the wind turbine blades and flowing into the control area; This refers to the amount of water droplet evaporation or the mass of ice sublimation in the controlled area. The mass of water droplets overflowing from the surface of the wind turbine blades and flowing out of the control area; This refers to the mass of water droplets that freeze into ice in this area.

[0141] Example 7:

[0142] A reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions is provided. The technical content is the same as any one of Examples 1-6. Furthermore, the energy system state parameters include system component state parameters, electrical-gas-heat load, illumination, and wind speed; the system component parameters include generators, lines, transformers, gas sources, gas pipelines, and heat sources.

[0143] Example 8:

[0144] A reliability assessment method for an integrated electrical-thermal energy system considering wind turbine icing modeling under freezing weather conditions is provided, with technical content identical to any one of Examples 1-7. Furthermore, the energy flow model of the integrated electrical-gas-thermal energy system is as follows:

[0145]

[0146]

[0147]

[0148]

[0149] In the formula: P W,i P represents the active power output of the i-th wind farm. PV,i P represents the active power output of the i-th photovoltaic electric field. G,i Q G,i P represents the active power and reactive power output of the i-th non-gas conventional generator set; GAS,i Q GAS,i P represents the active power and reactive power output of the i-th gas generator set; CHP,i Q CHP,i Let Q be the active power and reactive power output of the i-th gas-fired combined heat and power generator unit; W,i Q represents the reactive power output of the i-th wind farm. PV,i Q represents the reactive power output of the i-th photovoltaic field. C,i P represents the reactive power output of the i-th reactive power compensation device. D,i Q D,i F represents the active and reactive power of the load at the i-th node. GAS,m F CHP,m F P2G,m These are the gas-fired generator sets, gas-fired combined heat and power units, and the injection gas flow of the P2G unit at node m of the natural gas system; F G,m F D,m F mThese represent the gas source injection gas flow, gas load, and node injection gas flow at node m of the natural gas system; the node injection gas flow is the normal inflow of natural gas; Φ G,i Φ represents the thermal power output of the i-th heat source station. D,i N represents the thermal power of the heat load at the i-th node; e N m N h These represent the number of nodes in the power system, natural gas system, and heating system, respectively; P P2G,i The active power output of the P2G device; Φ CHP,i P represents the thermal power of a gas-fired combined heat and power unit. EB,i Φ represents the active power output of the i-th gas-fired boiler. EB,i Let i be the output thermal power of the i-th gas-fired boiler;

[0150] Example 9:

[0151] A reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions, with technical content identical to any one of Examples 1-8, further comprising the active power P injected into power system node i. i Reactive power Q i Natural gas node m injection gas flow F m Thermal power Φ at node i of the thermal system i As shown below:

[0152]

[0153]

[0154]

[0155]

[0156] In the formula, V i V j θ represents the voltage amplitude at the i-th and j-th power system nodes; ij It is the voltage phase angle difference between nodes i and j in the power system; G ij and B ij Let N be the real and imaginary parts of the element in the i-th row and j-th column of the nodal admittance matrix, respectively; e F represents the total number of nodes in the power system. m Inject gas flow into the natural gas node; B mr E mr and T mr These are the elements in the m-th row and r-th column of the node-pipe association matrix B, the node-compressor association matrix E, and the node-compressor inlet node association matrix T, respectively; N m Φ represents the total number of nodes in the natural gas system. iFor the injected thermal power of node i; C p D is the specific heat capacity of water. ih The element in the i-th row and h-th column of the node-heating pipeline association matrix of the thermal system; T s,i ,T r,i These represent the heating and regeneration temperatures at node i of the thermal system, respectively; N h m is the number of nodes in the thermal system. h N represents the heat flow rate of the h-th heating pipe. p N r Total number of gas transmission pipelines and compressor branches respectively; L r C r τ r These represent the flow rates through the gas transmission pipeline r and the compressor branch r in the natural gas system, respectively, and the flow rates consumed by the compressor branch r.

[0157] Example 10:

[0158] A reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions, with technical content identical to any one of Examples 1-9, further comprising the following: the electrical power P generated by the i-th unit... CHP,i The natural gas flow rate F consumed by the i-th unit CHP,i As shown below:

[0159]

[0160]

[0161] In the formula, P CHP,i and H CHP,i F represents the electrical power and thermal power generated by the i-th unit, respectively; CHP,i v represents the natural gas flow rate consumed by the i-th unit; CHP,i and η CHP,i These represent the heat-to-power ratio and conversion efficiency of the i-th unit, respectively; GHV represents the higher calorific value of natural gas; N b This represents the total number of gas-fired combined heat and power (CHP) units.

[0162] Example 11:

[0163] A reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions, with technical content identical to any one of Examples 1-10, further specifying the power consumption F of P2G device i. P2G,i As shown below:

[0164]

[0165] In the formula: F P2G,i P P2G,i η P2G,iThese represent the power consumption, injection gas flow, and conversion efficiency of P2G unit i, respectively; GHV represents the higher calorific value of natural gas; N w N c These represent the total number of wind farms and P2G transpositions, respectively; ΔP W,k Let i be the curtailment power of wind farm k; i be the power system node; and m be the gas grid node.

[0166] Example 12:

[0167] A reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions, with technical content identical to any one of Examples 1-11, further specifying the natural gas consumption F of the i-th gas-fired boiler. GB,i As shown below:

[0168]

[0169] In the formula, F GB,i Φ represents the amount of natural gas consumed by the i-th gas-fired boiler; GB,i η is the output thermal power of the i-th gas-fired boiler; GB,i Let N be the conversion efficiency of the i-th gas-fired boiler; gb This refers to the number of gas-fired boilers.

[0170] Example 13:

[0171] The reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions is the same as any one of Examples 1-12. Furthermore, the objective function min f of the optimal load shedding model is as follows:

[0172]

[0173] In the formula: C e,i C g,m C h,k These represent the load reduction amounts at electrical load node i, gas load node m, and gas-fired cogeneration unit k, respectively; ΔP W,i Let ΔP be the curtailment power of wind farm i; S,i Let N be the power of the discarded light in the photoelectric field i; d N g The total number of electrical load nodes and gas load nodes, respectively; λ e,i , λ g,m , λ h,k , λ w,i , λ s,i Weighting factors representing the severity of wind and solar curtailment for each electrical load, gas load, heat load, and wind / solar farm; N s This represents the total number of natural gas sources.

[0174] Example 14:

[0175] A reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions, with technical content the same as any one of Examples 1-2. Furthermore, the constraints of the optimal load shedding model include equality constraints and inequality constraints.

[0176] Example 15:

[0177] A reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions is provided. The technical content is the same as any one of Examples 1-14. Furthermore, the equality constraints are as follows:

[0178]

[0179]

[0180]

[0181]

[0182] Example 16:

[0183] A reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions is provided. The technical content is the same as any one of Examples 1-15. Furthermore, the inequality constraints are as follows:

[0184]

[0185]

[0186]

[0187]

[0188]

[0189]

[0190]

[0191]

[0192]

[0193]

[0194]

[0195]

[0196]

[0197]

[0198]

[0199]

[0200]

[0201]

[0202]

[0203]

[0204]

[0205]

[0206] Where: N e_load N represents the number of electrical loads. g_load For gas load quantity; N h_load P represents the amount of heat load. W,i The active power of the wind farm; and These are the upper and lower limits of the active power output of the i-th gas-fired combined heat and power unit with thermal storage, respectively. and These are the upper and lower limits of the reactive power output of the i-th gas-fired cogeneration unit with thermal storage, respectively. This represents the maximum storage capacity of the i-th thermal storage device; and These are the upper and lower limits of the active power output of the i-th gas generator set, respectively; and These are the upper and lower limits of the reactive power output of the i-th gas generator set, respectively; and Let m be the upper and lower limits of the electrical power consumption of the i-th electric boiler, respectively; h The heat flow rate of the h-th heating pipe; and These are the upper and lower limits of the active power output of the i-th non-gas conventional generator set, respectively; and N represents the upper and lower limits of the reactive power output of the i-th non-gas conventional generator set; u This represents the total number of non-gas-fired conventional generating units. and N represents the upper and lower limits of the gas injection volume for the m-th natural gas system node; sThis represents the total number of natural gas sources. and These are the upper and lower limits of the heat power of the heat source station at the i-th node of the thermal system, respectively; N z The number of heat source stations; R r Let r be the compression ratio of the compressor branch. and These are the upper and lower limits of the compression ratio for compressor branch r, respectively; and These are the upper and lower limits of the voltage amplitude at the i-th power system node, respectively; and These are the upper and lower limits of the transmission power of the l-th transmission line; and These are the upper and lower limits of the gas pressure at the m-th natural gas system node, respectively; and Let these be the upper and lower limits of the heating temperature supplied to the i-th node of the thermal system; and Let be the upper and lower limits of the regeneration temperature of the i-th thermal system node; and These are the upper and lower limits of the heat flow rate for the h-th heating pipe, respectively. hp This refers to the number of heating pipes.

[0207] Example 17:

[0208] A reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions is provided. The technical content is the same as any one of Examples 1-16. Furthermore, the reliability indicators of the energy system include the expected power shortage value EEDNS, the expected gas shortage value EGDNS, the expected heat shortage value EHDNS, the expected wind power curtailment value EWC, and the expected solar power curtailment value ESC. These indicators are used to reflect the power supply, gas supply, and heat supply capabilities of the system under different external conditions.

[0209] Example 18:

[0210] The reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions is the same as any one of Examples 1-17. Further, the expected values ​​for system power shortage (EEDNS), gas shortage (EGDNS), heat shortage (EHDNS), wind power curtailment (EWC), and solar power curtailment (ESC) are as follows:

[0211]

[0212]

[0213]

[0214]

[0215]

[0216] In the formula: G1, G2, and G3 represent the sets of states where electricity, gas, and heat loads are reduced, respectively; P(x) is the probability that the system is in state x; G4 and G5 represent the sets where wind and solar power curtailment occurs, respectively; x represents the system state from the Monte Carlo sampling (more than 100,000 samples in this embodiment).

[0217] Wherein, under state x, the system electrical load reduction C e (x) System gas load reduction C g (x) System heat load reduction C h (x) Wind curtailment ΔP W (x), Photoelectric field abandoned light amount ΔP S (x) are shown below:

[0218]

[0219]

[0220]

[0221]

[0222]

[0223] In the formula, ΔP S,i (x) represents the amount of light discarded by the i-th photoelectric field.

[0224] Example 19:

[0225] The reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions is the same as any one of Examples 1-18. Furthermore, the system energy flow cannot be assessed because there are voltage or air pressure exceeding limits or the system energy flow does not converge.

[0226] Example 20:

[0227] A reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions, with technical content identical to any one of Examples 1-19, further wherein the wind turbine failure rate is characterized by the icing coefficient;

[0228] The icing coefficient f is shown below:

[0229]

[0230] In the formula: The mass of the water droplet impacting the control area; The mass of water droplets overflowing from the surface of the wind turbine blades and flowing into the control area; The mass of water droplets frozen into ice in this area. The icing coefficient obtained by formula (7) is compared with the actual situation. By comparison, the critical value of the fan icing failure is obtained, and thus the fan failure rate is obtained.

[0231] Example 21:

[0232] A reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions is presented below:

[0233] Wind turbine icing is primarily determined by calculating the flow field motion of water droplets around the wind turbine blades and their impacts on the surface, thus obtaining the droplet trajectory. The amount of ice forming on the wind turbine blade surface depends on the droplet trajectory and the amount of impact. The impact of water droplets on the surface depends on the flow field distribution on that surface. In summary, the calculation steps for the amount of ice on wind turbine blades are as follows:

[0234] a) Calculate the flow field distribution on the surface of the wind turbine blades; This paper uses the Navier-Stokes equations (NS equations) method for flow field calculation.

[0235] b) Calculate the trajectory of water droplets in the air; this paper uses the Lagrange method to calculate the trajectory of water droplets and the impact characteristics of water droplets.

[0236] c) Calculate the amount of icing on the wind turbine blades. The Messinger model is used for icing calculation. The Messinger model calculates the amount of icing within the control area by analyzing the conservation of mass and energy of the control volume.

[0237] In addition, the steps for integrated energy system reliability assessment are as follows:

[0238] Based on the energy flow model, load reduction optimization model, and reliability indicators established in this embodiment, a reliability assessment method for wind turbine freezing is proposed, and its specific assessment process is as follows:

[0239] 1) Wind Turbine Failure Assessment: Using actual weather data such as temperature, humidity, and pressure from the Guangxi Xiangtian Wind Farm, the failure rate of wind turbines stopping after freezing was calculated using the Navier-Stokes equations and the Messier model. The failure rate was obtained by comparing the theoretical icing value with the critical value under actual icing conditions. In this embodiment, the icing failure rate was 1.55%.

[0240] 2) Transitional sampling: Using the non-time-series Monte Carlo method, the system components (generators, lines, transformers, gas sources, gas pipelines, heat sources), electricity-gas-heat load, light intensity, wind speed and other variables are sampled to obtain the system state.

[0241] 3) Topology analysis: Identify the connectivity of the sampled system state and analyze how many subsystems are formed by the connections of each node, branch, and coupling element.

[0242] 4) Energy flow calculation: For the subsystem obtained after topology analysis, energy flow calculation is performed according to the energy flow model established in Section 2.3. Newton's method is used for effective solution. Analyze the energy flow results: If there are problems such as voltage or air pressure exceeding the limit and energy flow non-convergence, proceed to the next step; otherwise, proceed directly to step 6.

[0243] 5) Load reduction and curtailment calculation: Load reduction calculation is performed for system states with over-limit problems, and the interior point method is used for optimization solution.

[0244] 6) Reliability Index Calculation: Based on the optimization model calculation results and the indicators proposed in Section 2.5, calculate the expected power, gas, and heat shortages under different freezing conditions; and the expected wind and solar power curtailment. The specific steps are as follows:

[0245] 1. Modeling of wind turbines stopping due to icing

[0246] 1-1) Navier-Stokes Equation Model

[0247]

[0248]

[0249]

[0250] In equations (1)-(3), P is the pressure on the fluid element; S x S y S z For generalized source terms; F x F y F z Let F be the volume force on the infinitesimal element. If the only volume force is gravity, and the z-axis is vertically upward, then F x =0, F y =0,F z =-ρg;u x u y u z λ represents the velocity along the x, y, and z axes, respectively; μ is the dynamic viscosity of the fluid; and λ is the second molecular viscosity of the fluid, typically taken as -2 / 3 for gases.

[0251] 1-2) Calculate the trajectory of the water droplet

[0252] Before using the Lagrange method to solve for the trajectory and impact characteristics of water droplets, the following assumptions need to be made:

[0253] a) Assuming that the volume of the water droplet remains constant during the motion, the shape of the water droplet can change. At the same time, the concept of a rigid sphere with the same volume as the water droplet and a diameter of D is introduced.

[0254] b) Assume that the density, viscosity, temperature, etc. of the water droplets in the flow field remain constant;

[0255] c) Assume the initial velocity of the water droplet is equal to the free flow velocity, and neglect the interference of the water droplet on the flow field. The motion of the water droplet in the air is mainly affected by several forces, including viscous drag F, gravity and buoyancy G, and the pressure difference force P caused by the change in pressure before and after the droplet. Among these, P is small and can be ignored. Therefore, based on the above assumptions and Newton's second law, the equation of motion of the water droplet trajectory is:

[0256]

[0257] Where: M d For the mass of the water droplet, M d =V d *ρ a V d Let V be the volume of the water droplet. d =πD 3 / 6;ρ a ρ d ρ and ρ' represent the densities of air and water droplets, respectively; d Generally, 1000 kg / m 3 A d Let A be the windward surface area of ​​the water droplet. d =D 2 / 4; These are the air motion vector and the water droplet motion vector, respectively; C d This is the drag coefficient.

[0258] 1-3) Calculate the amount of icing on the fan

[0259] The Messier model is used to calculate the icing amount on wind turbine blades. The governing equations of this model include the mass conservation equation and the energy conservation equation. The mass conservation equation is as follows:

[0260]

[0261] In the formula: The mass of the water droplet impacting a certain controlled area; The mass of water droplets overflowing from the surface of the wind turbine blades and flowing into the control area; This refers to the amount of water droplet evaporation or the mass of ice sublimation in the controlled area. The mass of water droplets overflowing from the surface of the wind turbine blades and flowing out of the control area; This refers to the mass of water droplets that freeze into ice in this area.

[0262] The energy conservation equation is expressed as follows:

[0263]

[0264] In the formula: This refers to convective heat transfer between the airflow and the surface of a certain controlled area. The surface of the controlled area is heated by air friction; The heat absorbed by the evaporation of water droplets or ice surfaces within the controlled area; The heat energy generated by the water droplets impacting the surface of that area; The heat generated by the kinetic energy of water droplets impacting the surface of that area. This refers to the heat released during the freezing process of water droplets in the controlled area.

[0265] Because the fan is rotating rapidly before freezing, some water droplets overflow and some evaporate on the surface. Therefore, the amount of ice formed in the controlled area is less than the amount of water collected. Thus, an icing coefficient is defined, and its expression is as follows:

[0266]

[0267] 2. Energy Flow Model of Integrated Electric-Gas-Heat Energy System

[0268] 2-1) Nodal Injection Electrical Power, Airflow, and Thermal Power Model

[0269] The active and reactive power injected into node i of the power system; the gas flow injected into node m of the natural gas system; and the thermal power calculation formulas for node i of the thermal system are as follows:

[0270]

[0271]

[0272]

[0273]

[0274] In equations (8)-(9), V i θ is the voltage amplitude at the i-th power system node; ij It is the voltage phase angle difference between nodes i and j in the power system; G ij and B ij Let N be the real and imaginary parts of the element in the i-th row and j-th column of the nodal admittance matrix, respectively; e Let F be the total number of nodes in the power system. In equation (10), F m Inject gas flow into the natural gas node, B mr E mr and T mrThe elements N in the m-th row and r-th column of the node-pipe association matrix B, the node-compressor association matrix E, and the node-compressor inlet node association matrix T are respectively... m Φ represents the total number of nodes in the natural gas system. In equation (11), Φ i The injected thermal power at node i, in MW; C p D is the specific heat capacity of water, expressed in J / (kg·℃); ih The element in the i-th row and h-th column of the node-heating pipeline association matrix of the thermal system; T s,i ,T r,i N represents the supply and regeneration temperatures at node i of the thermal system, respectively, in °C; h This represents the number of nodes in the thermal system.

[0275] 2-2) Integrated Energy System Energy Flow Model

[0276] Based on the network models of the electrical, gas, and thermal subsystems, an energy flow model for the integrated energy system can be established:

[0277]

[0278]

[0279]

[0280]

[0281] Equation (12) is the active power balance equation of the power system; Equation (13) is the reactive power balance equation of the power system; Equation (14) is the flow balance equation of the natural gas system; Equation (15) is the heat power balance equation of the thermal system; where P W,i P represents the active power output of the i-th wind farm. PV,i Q represents the active power output of the i-th photovoltaic electric field. G,i Q represents the reactive power output of the i-th non-gas conventional generator set; GAS,i Q represents the reactive power output of the i-th gas generator set. CHP,i Q represents the reactive power output of the i-th gas-fired combined heat and power generator unit. W,i Q represents the reactive power output of the i-th wind farm. PV,i Q represents the reactive power output of the i-th photovoltaic field. C,i Q represents the reactive power output of the i-th reactive power compensation device. D,i F represents the reactive power of the load at the i-th node. GAS,m F CHP,m F P2G,m These are the gas-fired generator sets, gas-fired combined heat and power units, and the injection gas flow of the P2G unit at node m of the natural gas system; F G,m FD,m F ,m These represent the injection gas flow, gas load, and node injection gas flow at node m of the natural gas system, respectively; Φ G,i Φ represents the thermal power output of the i-th heat source station. D,i N represents the thermal power of the heat load at the i-th node; e N m N h These represent the number of nodes in the power system, natural gas system, and heating system, respectively.

[0282] 2-3) Coupled Element Model

[0283] Gas-fired combined heat and power (CHP) units can produce electricity and heat simultaneously, exhibiting strong coupling characteristics. The specific calculation formula is as follows:

[0284]

[0285]

[0286] In the formula, P CHP,i and H CHP,i F represents the electrical power and thermal power generated by the i-th unit, respectively; CHP,i v represents the natural gas flow rate consumed by the i-th unit; CHP,i and η CHP,i These represent the heat-to-power ratio and conversion efficiency of the i-th unit, respectively; GHV represents the higher calorific value of natural gas; N b This represents the total number of gas-fired combined heat and power (CHP) units.

[0287] When wind curtailment occurs in an integrated energy system, excess wind power can be converted into natural gas for storage using P2G (Power-to-Ground) devices. Therefore, the relationship between P2G power consumption and gas conversion efficiency needs to be established:

[0288]

[0289] In the formula: F P2G,i P P2G,i η P2G,i These represent the power consumption, injection gas flow, and conversion efficiency of P2G unit i, respectively; GHV represents the higher calorific value of natural gas; N w N c These represent the total number of wind farms and P2G transpositions, respectively.

[0290] A gas-fired boiler is a mechanical device that uses natural gas as input and heats hot water in the boiler by burning the gas, thereby outputting hot steam or high-temperature hot water. The specific expression is as follows:

[0291]

[0292] In the formula, F GB,iΦ represents the amount of natural gas consumed by the i-th gas-fired boiler, expressed in MMCFD. GB,i η represents the output thermal power of the i-th gas-fired boiler, in MW; GB,i Let N be the conversion efficiency of the i-th gas-fired boiler; gb This refers to the number of gas-fired boilers.

[0293] 3. Optimal load shedding model

[0294] 3-1) Objective Function

[0295] The optimization model established in this section aims to minimize the sum of the reductions in electrical load, gas load, and heat load, as well as the curtailment of wind and solar power.

[0296]

[0297] In the formula: C e,i C g,m C h,k These represent the load reduction amounts at electrical load node i, gas load node m, and gas-fired cogeneration unit k, respectively; ΔP W,i Let ΔP be the curtailment power of wind farm i; S,i Let N be the power of the discarded light in the photoelectric field i; d N g These represent the total number of electrical load nodes and gas load nodes, respectively; λ e,i , λ g,m , λ h,k , λ w,i , λ s,i Weighting factors that characterize the severity of wind and solar curtailment for each electrical load, gas load, heat load, and wind and solar power plant.

[0298] 3-2) Equality constraints

[0299] Based on the integrated energy flow model, variables for electricity load, gas load, heat load reduction, and wind and solar curtailment are introduced, forming the following equation constraints:

[0300]

[0301]

[0302]

[0303]

[0304] In the formula: the definitions of each variable are the same as those described above, and the corresponding coupling devices also satisfy the coupling constraints.

[0305] 3-3) Inequality constraints

[0306] The inequality constraints in the optimal load reduction model for wind / solar renewable energy consumption include the following four categories: First, adjustment constraints for correction measures of electricity / gas / heat load reduction variables and wind curtailment, solar curtailment, and solar-thermal curtailment variables; second, operational constraints of the four types of coupled equipment proposed in this paper; third, constraints of uncoupled equipment such as non-gas conventional units, conventional gas sources, conventional heat sources, and compressors; and fourth, network security constraints of subsystems such as node voltage, node gas pressure, node water supply, transmission line power, and heating pipeline flow. The specific expressions are as follows:

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[0308]

[0309]

[0310]

[0311]

[0312]

[0313]

[0314]

[0315]

[0316]

[0317]

[0318]

[0319]

[0320]

[0321]

[0322]

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[0328]

[0329] Equations (25)-(29) are the adjustment constraints for the correction measures, where N e_load N represents the number of electrical loads. g_load For gas load quantity; N h_load The heat load is the quantity; equations (30)-(35) represent the operating constraints of the coupling equipment, where and These are the upper and lower limits of the active power output of the i-th gas-fired combined heat and power unit with thermal storage, respectively. and These are the upper and lower limits of the reactive power output of the i-th gas-fired cogeneration unit with thermal storage, respectively. This represents the maximum storage capacity of the i-th thermal storage device; and These are the upper and lower limits of the active power output of the i-th gas generator set, respectively; and These are the upper and lower limits of the reactive power output of the i-th gas generator set, respectively; and Let be the upper and lower limits of the power consumption of the i-th electric boiler, respectively; Equations (36)-(40) are the operating constraints of the uncoupled equipment, where are given by equations. and These are the upper and lower limits of the active power output of the i-th non-gas conventional generator set, respectively; and N represents the upper and lower limits of the reactive power output of the i-th non-gas conventional generator set; u This represents the total number of non-gas-fired conventional generating units. and N represents the upper and lower limits of the gas injection volume for the m-th natural gas system node; s This represents the total number of natural gas sources. and These are the upper and lower limits of the heat power of the heat source station at the i-th node of the thermal system, respectively; N z The number of heat source stations; R r R is the compression ratio of compressor branch r. r =π n / π m ; and These are the upper and lower limits of the compression ratio of the compressor branch r, respectively. Equations (41)-(46) are network security constraints, where and These are the upper and lower limits of the voltage amplitude at the i-th power system node, respectively; and These are the upper and lower limits of the transmission power of the l-th transmission line; and These are the upper and lower limits of the gas pressure at the m-th natural gas system node, respectively; and Let these be the upper and lower limits of the heating temperature supplied to the i-th node of the thermal system; and Let be the upper and lower limits of the regeneration temperature of the i-th thermal system node; and These are the upper and lower limits of the heat flow rate of the h-th heating pipe, respectively.

[0330] 4. Reliability Indicators

[0331] The Expected Electric Demand Not Supplied (EEDNS, MW), Expected Gas Demand Not Supplied (EGDNS, MW), and Expected Heat Demand Not Supplied (EHDNS, MW) indices reflect the reliability levels of the system for electrical load, gas load, and heat load, respectively. Their expressions are as follows:

[0332]

[0333]

[0334]

[0335] In the formula: G1, G2, and G3 represent the sets of states where the electricity, gas, and heat loads are reduced, respectively; P(x) is the probability that the system is in state x; C e (x), C g (x), C h (x) represents the reduction in system electricity, gas, and heat loads under state x. These can be obtained from the reductions in electricity, gas, and heat loads at each node:

[0336]

[0337]

[0338]

[0339] The Expected Wind Curtailment (EWC, MW) and Expected Solar Curtailment (ESC, MW) indices are used to reflect the severity of wind and solar curtailment in the system, respectively, and their expressions are as follows:

[0340]

[0341]

[0342] In the formula: G4 and G5 represent the sets of wind curtailment and solar curtailment, respectively; ΔP W (x), ΔP S (x) represent the amount of wind and solar curtailment under state x, which can be calculated from the amount of wind and solar curtailment of each wind and solar power field under system state x:

[0343]

[0344]

[0345] Example 22:

[0346] The verification experiment for the reliability assessment method of the integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions is as follows:

[0347] To verify the effectiveness of the model and solution method established in this invention, this section takes the IEEE9-NGS6-DHN7 integrated electric-gas-thermal energy system as an example for simulation verification.

[0348] The IEEE9-NGS6-DHN7 integrated power-gas-heat energy system consists of the IEEE 9-node power system, the NGS6-node natural gas system, and the DHN7-node heat system. The system connection diagram is shown below. Figure 1 As shown, power system node 3 is connected to wind farm, photovoltaic power plant, solar thermal power plant and electric boiler. The heat converted by the electric boiler is injected into thermal system node 3. Natural gas system node 3 provides the gas demand of the gas-fired cogeneration unit with heat storage at power system node 3 and supplies its heat power to thermal system node 2. Node 6 provides the gas demand of the gas generator set at power system node 1 and the gas boiler at thermal system node 1.

[0349] In this invention, when sampling, it is assumed that the electrical load, gas load, and heat load in the IEEE9-NGS6-DHN7 system are all normally distributed, with a standard deviation of 5% of the expected load value of each node; and that the wind speed follows a two-parameter Weibull distribution.

[0350] To verify the necessity and accuracy of considering wind turbine icing, this invention sets up the following two case comparisons:

[0351] Case 1: Without considering wind turbine icing, conduct a reliability assessment of the system when the penetration rate of new energy sources is 10%, 15%, 20%, 25%, and 35%.

[0352] Case 2: Considering wind turbine icing, the system reliability was assessed under the conditions of renewable energy penetration rates of 10%, 15%, 20%, 25%, and 35%.

[0353] Test results

[0354] Figure 2 The study demonstrates the difference in load reduction before and after considering wind turbine icing when the penetration rate of new energy sources is 35%, with and without considering wind turbine icing.

[0355] from Figure 2 As can be seen from the data, the electrical load is most affected by wind turbine icing, with the overall difference being positive. This indicates that the reduction in renewable energy power supply due to wind turbine shutdown after freezing leads to a greater reduction in electrical load. The second largest impact is on the heat load, as the heat source is mainly provided by electricity, so the heat load also decreases when electricity is insufficient. For the gas load, since the gas source is mainly gas wells and the electricity-to-gas conversion is primarily used for storage, the impact on the gas grid load is not significant, showing a symmetrical distribution. Regarding the amount of wind curtailment, the overall impact is... Figure 1 In the lower half, the amount of wind energy converted is reduced, resulting in less wind curtailment after considering wind turbine icing; the overall amount of solar curtailment is in the upper half, indicating that the amount of solar curtailment is less after considering icing.

[0356] Tables 1 and 2 show the reliability indicators with and without considering wind turbine icing, respectively. A horizontal comparison shows that considering wind turbine icing, the expected power supply shortage is higher when renewable energy penetration is not less than 15%. When renewable energy penetration is less than 10%, wind power has little impact on the system's power supply due to the low penetration rate. For gas grid systems, only when renewable energy penetration is high, with a significant amount of natural gas supply converted from electricity, does wind power have a substantial impact on gas grid supply. When renewable energy penetration is low, the gas grid's dependence on the power grid is low, and wind turbine failures have a smaller impact on the gas grid. Heating networks depend on the power grid; if the power grid experiences a power shortage, the heating network will subsequently experience a power shortage. Therefore, the expected power shortage for heating networks is similar to that for the power grid.

[0357] Regarding the expected wind curtailment index, after the wind turbines freeze, the amount of wind energy converted into electrical energy will decrease, thus reducing the amount of wind curtailment. The correlation between solar energy and wind energy is relatively small. However, as the expectation of insufficient power supply increases, the amount of solar energy curtailment will decrease. Under the condition that the system's power supply expectation meets the requirements, there is no strong correlation between the expectation of solar energy curtailment and wind turbine icing.

[0358] Table1 Reliability indexes without considering wind turbine icing(MW)

[0359]

[0360] Table2 Reliability indexes considering wind turbine icing(MW)

[0361]

[0362] A horizontal comparison in Tables 1 and 2 shows that when the renewable energy penetration rate is below 15%, the differences in various indicators between considering and not considering wind turbine icing are not particularly significant. The lower the renewable energy penetration rate, the higher the reliability of the integrated electricity-gas-heat energy system. However, when the renewable energy penetration rate is above 15%, it becomes more apparent that considering wind turbine icing significantly increases the expected values ​​for insufficient power supply and insufficient gas supply. This indicates that wind turbine icing has a substantial impact on the reliability of the power and natural gas systems. For both wind and solar power curtailment expectations, considering wind turbine icing leads to varying degrees of reduction. This underscores the strong necessity of considering wind turbine icing factors in the reliability assessment of the integrated electricity-gas-heat energy system.

[0363] The experimental results show that:

[0364] Taking into account the impact of wind turbine icing, a reliability assessment of the integrated power-gas-heat energy system was conducted. The assessment results show that the expected values ​​for insufficient power supply and insufficient gas supply are significantly higher after considering wind turbine icing. This indicates that wind turbine icing has a significant impact on the reliability of the power system and the natural gas system. For the expected wind curtailment and solar curtailment, both decreased to varying degrees after considering wind turbine icing. Overall, while all reliability indicators decreased, the results are closer to actual conditions and provide guidance for developing power generation plans under real-world circumstances.

Claims

1. A reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions, characterized in that, Includes the following steps: Step 1) Calculate the amount of ice on the wind turbine blades and determine the wind turbine failure rate; Step 2) Establish the energy flow model and optimal load shedding model for the integrated electric-gas-heat energy system; Step 3) Based on the wind turbine failure rate, sample the integrated electrical and thermal energy system to obtain the energy system state parameters; Step 4) Input the energy system state parameters into the energy flow model of the integrated electric-gas-heat energy system, and calculate the system energy flow; Analyze the system energy flow. If the system energy flow cannot be evaluated, proceed to step 5; otherwise, proceed to step 6. Step 5) Optimize the load parameters in the energy system state parameters using the optimal load shedding model, and then return to step 4). Step 6) Based on the system energy flow, calculate the energy system reliability index and complete the energy system reliability assessment; The steps for calculating the amount of ice buildup on wind turbine blades include: Step 1.1) Calculate the flow field distribution on the surface of the wind turbine blades using the Navier-Stokes equations; The Navier-Stokes equations are shown below: （1） （2） （3） In the formula, P is the pressure on the fluid element; , , For generalized source terms; F x F y F z Let F be the volume force on the infinitesimal element. If the only volume force is gravity, and the z-axis is vertically upward, then F x =0, F y =0, F z = -ρg;u x u y u z , , and z represent the velocities along the x, y, and z axes, respectively; μ is the dynamic viscosity of the fluid; The second molecular viscosity of the fluid; The velocity vector representing the difference between the blade velocity and the fluid velocity. For fluid density; Step 1.2) Calculate the trajectory of the water droplets in the air; The trajectory of water droplets in the air is shown below: （4） Where: M d For the mass of the water droplet, V d Let the volume of the water droplet be denoted as 'Volume'. These are the densities of air and water droplets, respectively; A d The surface area of ​​the water droplet facing the wind; , These are the air motion vector and the water droplet motion vector, respectively; C d This is the drag coefficient; It is the acceleration due to gravity; Step 1.3) Calculate the amount of ice on the wind turbine blades based on the flow field distribution on the surface of the wind turbine blades and the trajectory of water droplets in the air.

2. The reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions, as described in claim 1, is characterized in that... The amount of ice accretion on the wind turbine blades was calculated using the Messier model; The Messinger model is shown below: （5） （6） In the formula: This is convective heat transfer between the airflow and the surface of the control area; The surface of the controlled area is heated by air friction; The heat absorbed by the evaporation of water droplets or ice surfaces within the controlled area; The heat energy generated by the water droplets impacting the surface of that area; The heat generated by the kinetic energy of water droplets impacting the surface of that area. This refers to the heat released during the freezing process of water droplets into ice in the controlled area; The mass of the water droplet impacting the control area; The mass of water droplets overflowing from the surface of the wind turbine blades and flowing into the control area; This refers to the amount of water droplet evaporation or the mass of ice sublimation in the controlled area. The mass of water droplets overflowing from the surface of the wind turbine blades and flowing out of the control area; This refers to the mass of water droplets that freeze into ice in this area.

3. The reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions, as described in claim 1, is characterized in that... The failure rate of the wind turbine is characterized by the icing coefficient. The icing coefficient f is shown below: （7） In the formula: The mass of the water droplet impacting the control area; The mass of water droplets overflowing from the surface of the wind turbine blades and flowing into the control area; This refers to the mass of water droplets that freeze into ice in this area.

4. The reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions, as described in claim 1, is characterized in that... The inability to assess system energy flow refers to situations where voltage or gas pressure exceeds limits, or where system energy flow does not converge.

5. The reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions, as described in claim 1, is characterized in that... The energy system status parameters include system component status parameters, electrical-gas-heat load, illumination, and wind speed; the system component parameters include generators, lines, transformers, gas sources, gas pipelines, and heat sources.

6. The reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions, as described in claim 1, is characterized in that... The energy flow model of the integrated electric-gas-heat energy system is shown below: （8） （9） （10） （11） In the formula: P W,i P represents the active power output of the i-th wind farm. PV,i Let be the active power output of the i-th photovoltaic electric field; Q G,i Let be the active power and reactive power output of the i-th non-gas conventional generator set; Q GAS,i Let i be the active power and reactive power output of the i-th gas generator set; Q CHP,i Q represents the active power and reactive power output of the i-th gas-fired combined heat and power generator unit. W,i Q represents the reactive power output of the i-th wind farm. PV,i Q represents the reactive power output of the i-th photovoltaic field. C,i Let i be the reactive power output of the i-th reactive power compensation device; Q D,i F represents the active and reactive power of the load at the i-th node. GAS,m F CHP,m F P2G,m These are the gas-fired power generation units, gas-fired combined heat and power units, and the injection gas flow of the P2G unit at node m of the natural gas system; F G,m F D,m F m These represent the gas source injection gas flow, gas load, and node injection gas flow at node m of the natural gas system. Let be the thermal power output of the i-th heat source station; N represents the thermal power of the heat load at the i-th node; e N m N h These represent the number of nodes in the power system, natural gas system, and heating system, respectively. The active power output by the P2G device; The thermal power of a gas-fired combined heat and power unit; Let be the active power output of the i-th gas-fired boiler; Let i be the output thermal power of the i-th gas-fired boiler; Among them, the active power P injected by node i of the power system i Reactive power Q i Natural gas node m injection gas flow F m Thermal power of node i in the thermal system As shown below: （12） （13） （14） （15） In the formula, V i V j θ represents the voltage amplitude at the i-th and j-th power system nodes; ij It is the voltage phase angle difference between nodes i and j in the power system; G ij and B ij Let N be the real and imaginary parts of the element in the i-th row and j-th column of the nodal admittance matrix, respectively; e F represents the total number of nodes in the power system. m Inject gas flow into the natural gas node; B mr E mr and T mr These are the elements in the m-th row and r-th column of the node-pipe association matrix B, the node-compressor association matrix E, and the node-compressor inlet node association matrix T, respectively; N m This represents the total number of nodes in the natural gas system. For the injected thermal power of node i; C p D is the specific heat capacity of water. ih The element in the i-th row and h-th column of the node-heating pipeline association matrix of the thermal system; T s,i , T r,i These represent the heating and regeneration temperatures at node i of the thermal system, respectively; N h This refers to the number of nodes in the thermal system. N represents the heat flow rate of the h-th heating pipe. p N r The total number of gas transmission pipelines and compressor branches, respectively; , , These represent the flow rates through the gas transmission pipeline r and the compressor branch r in the natural gas system, respectively, and the flow rates consumed by the compressor branch r. The electrical power P generated by the i-th unit CHP,i The natural gas flow rate F consumed by the i-th unit CHP,i As shown below: （16） （17） In the formula, P CHP,i and H CHP,i F represents the electrical power and thermal power generated by the i-th unit, respectively; CHP,i v represents the natural gas flow rate consumed by the i-th unit; CHP,i and η CHP,i These represent the heat-to-power ratio and conversion efficiency of the i-th unit, respectively; GHV represents the higher calorific value of natural gas; N b This represents the total number of gas-fired combined heat and power (CHP) units. P2G device Power consumption F P2G,i As shown below: （18） In the formula: These represent P2G devices. Power consumption, injection airflow, and device conversion efficiency; Indicates the high calorific value of natural gas; , These represent the total number of wind farms and P2G transposition, respectively. Let k be the wind curtailment power of wind farm k; The amount of natural gas consumed by the i-th gas boiler, F GB,i As shown below: （19） In the formula, F GB,i Let be the amount of natural gas consumed by the i-th gas-fired boiler; η is the output thermal power of the i-th gas-fired boiler; GB,i Let N be the conversion efficiency of the i-th gas-fired boiler; gb This refers to the number of gas-fired boilers.

7. The reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions, as described in claim 1, is characterized in that... The objective function of the optimal load reduction model As shown below: （20） In the formula: , , These represent the load reduction amounts for electrical load node i, gas load node m, and gas-fired cogeneration unit k, respectively. Let i be the curtailment power of wind farm i; Let N be the power of the discarded light in the photoelectric field i; d N g These represent the total number of electrical load nodes and gas load nodes, respectively. , , , , Weighting factors representing the severity of wind and solar curtailment for each electrical load, gas load, heat load, and wind / solar farm; N s This represents the total number of natural gas sources.

8. The reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions, as described in claim 1, is characterized in that... The constraints of the optimal load shedding model include equality constraints and inequality constraints. The equality constraints are as follows: （21） （22） （23） （24） The inequality constraints are as follows: （25） （26） （27） （28） （29） （30） （31） （32） （33） （34） （35） （36） （37） （38） （39） （40） （41） （42） （43） （44） （45） （46） Where: N e_load N represents the number of electrical loads. g_load For gas load quantity; N h_load This refers to the amount of heat load. The active power of the wind farm; and These are the upper and lower limits of the active power output of the i-th gas-fired combined heat and power unit with thermal storage, respectively. and These are the upper and lower limits of the reactive power output of the i-th gas-fired cogeneration unit with thermal storage, respectively; Smax i is the maximum storage capacity of the i-th thermal storage device; and These are the upper and lower limits of the active power output of the i-th gas generator set, respectively; and These are the upper and lower limits of the reactive power output of the i-th gas generator set, respectively; and These are the upper and lower limits of the electrical power consumption of the i-th electric boiler, respectively. The heat flow rate of the h-th heating pipe; and These are the upper and lower limits of the active power output of the i-th non-gas conventional generator set, respectively; and N represents the upper and lower limits of the reactive power output of the i-th non-gas conventional generator set; u This represents the total number of non-gas-fired conventional generating units. and N represents the upper and lower limits of the gas injection volume for the m-th natural gas system node; s This represents the total number of natural gas sources. and These are the upper and lower limits of the heat power of the heat source station at the i-th node of the thermal system, respectively; N z The number of heat source stations; R r Let r be the compression ratio of the compressor branch. and These are the upper and lower limits of the compression ratio for compressor branch r, respectively; and These are the upper and lower limits of the voltage amplitude at the i-th power system node, respectively; and These are the upper and lower limits of the transmission power of the l-th transmission line; and These are the upper and lower limits of the gas pressure at the m-th natural gas system node, respectively; and Let these be the upper and lower limits of the heating temperature supplied to the i-th node of the thermal system; and Let be the upper and lower limits of the regeneration temperature of the i-th thermal system node; and These are the upper and lower limits of the heat flow rate of the h-th heating pipe, respectively. This refers to the number of heating pipes.

9. The reliability assessment method for an integrated electrical and thermal energy system considering wind turbine icing modeling under freezing weather conditions, as described in claim 1, is characterized in that... The energy system reliability indicators include the expected value of insufficient power (EEDNS), the expected value of insufficient gas (EGDNS), the expected value of insufficient heat (EHDNS), the expected value of curtailed wind power (EWC), and the expected value of curtailed solar power (ESC). The expected values ​​for system power shortage (EEDNS), gas shortage (EGDNS), heat shortage (EHDNS), wind power curtailment (EWC), and solar power curtailment (ESC) are as follows: （47） （48） （49） （50） （51） In the formula: G1, G2, and G3 represent the sets of states where electricity, gas, and heat loads are reduced, respectively; P(x) is the probability that the system is in state x; G4 and G5 represent the sets where wind curtailment and solar curtailment occur, respectively. Wherein, under state x, the system electrical load reduction C e (x) System gas load reduction C g (x) System heat load reduction C h (x) Wind curtailment from wind farms Photovoltaic field waste They are shown below: （52） （53） （54） （55） （56） In the formula, Let be the amount of light discarded by the i-th photoelectric field.

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