Main and distribution cooperative power grid operation optimization method and system considering extreme high temperature weather

Abstract

The invention provides a main and distribution cooperative power grid operation optimization method and system considering extreme high temperature weather, and the method comprises the steps: dividing a typical load into a temperature control type conventional load and a non-temperature-sensitive type conventional load at a distribution network side, and dividing the temperature control load into a high-energy-efficiency load and a low-energy-efficiency load; non-temperature sensitive loads are divided into time-space translational loads, time sequence flexible loads and fixed loads, a virtual power plant is adopted to perform joint regulation and control on various loads, user satisfaction and load importance weights are considered at the same time, and power supply of important loads is maintained on the premise of ensuring safe and stable operation of a power distribution network; the steam extraction energy storage system is adopted on the power generation side, the influence of the environment temperature on the heat storage effect of the molten salt tank is considered, the climbing margin and the start-stop margin of the generator set in the extreme scene are improved, and the operation strategy of the generator set in the extreme weather is optimized in cooperation with the virtual power plant on the distribution network side and the power supply network. And the loss load of the system is minimized on the premise of ensuring the safe and stable operation of the main and distribution cooperative system.

Description

Technical Field

[0001] This invention relates to the field of power system engineering, and in particular to a method and system for optimizing the coordinated operation of the main and distribution power grids considering extreme high-temperature weather. Background Technology

[0002] Driven by the ongoing global warming, the frequency, intensity, and duration of extreme heat events are all showing a significant upward trend, posing a comprehensive and profound challenge to the stable operation of the power system. Extreme heat impacts the power system primarily through a dual pathway on both the supply and demand sides: sustained heat leads to a sharp increase in cooling loads such as air conditioning and refrigeration, causing a significant "peaking" characteristic in the electricity demand curve; simultaneously, high temperatures and drought reduce water resources needed for hydropower generation and even affect the cooling efficiency and output stability of thermal power units. This simultaneous pressure on both the supply and demand sides severely tests the heat resistance limits of power equipment and the reliability of the power grid.

[0003] To effectively address the severe challenges posed by extreme high temperatures, strengthening a single link is no longer sufficient to ensure the overall resilience of the power system. It is urgent to simultaneously and collaboratively enhance the flexibility resources of both the generation and consumption sides. Summary of the Invention

[0004] The purpose of this invention is to overcome the aforementioned problems in the prior art and to provide a method and system for optimizing the operation of the main and distribution power grids in consideration of extreme high-temperature weather.

[0005] To achieve the above objectives, the technical solution of the present invention is:

[0006] In a first aspect, this invention proposes a method for optimizing the operation of a main and distribution power grid considering extreme high-temperature weather, comprising:

[0007] S1. Construct a power grid operation optimization model with the goal of minimizing losses from temperature-controlled loads and non-temperature-sensitive conventional loads. This model considers extreme high-temperature weather. On the distribution network side, temperature-controlled loads are divided into high-efficiency loads and low-efficiency loads according to their energy efficiency levels, and non-temperature-sensitive loads are divided into spatiotemporally movable loads, time-series flexible loads, and fixed loads according to their flexibility. A virtual power plant is used for joint regulation of various types of loads. On the generation side, an extraction steam storage system is used, and boiler-turbine decoupling is achieved through molten salt tank thermal storage. The influence of ambient temperature on the thermal storage effect of the molten salt tank is considered, and it is coordinated with the virtual power plant and power supply network on the distribution network side.

[0008] S2. Solve the power grid operation optimization model to obtain power grid operation optimization schemes under various weather scenarios, including temperature-controlled loads, non-temperature-sensitive conventional loads, and generator unit operation strategies.

[0009] The objective function of the power grid operation optimization model includes:

[0010] ;

[0011] ;

[0012] ;

[0013] In the above formula, , These are respectively temperature-controlled load losses and non-temperature-sensitive conventional load losses. , These are the energy efficiency ratios for high-efficiency temperature control loads and low-efficiency temperature control loads, respectively. , Weather scenarios Down Time period nodes The cooling capacity requirements of high-efficiency and low-efficiency temperature-controlled loads are considered, with weather scenarios including normal weather and extreme high-temperature weather. , Weather scenarios Down Time period nodes The electricity load demand of high-efficiency temperature-controlled loads and low-efficiency temperature-controlled loads at the location. For a unit of time, Weather scene within a time period The number of consecutive days, For weather scenes Down During a specific time period, a typical intraday node The proportion of non-temperature-sensitive load demand met. For nodes The rated non-temperature-sensitive load at the location;

[0014] The constraints include power generation side operation constraints and power consumption side operation constraints.

[0015] The power grid operation optimization model also considers the impact of high temperatures on pumped storage systems, and the power grid operation optimization scheme also includes a combined energy storage-ecological water control strategy under extreme high temperatures.

[0016] The power generation-side operational constraints include the operational constraints of pumped storage power stations:

[0017] ;

[0018] ;

[0019] ;

[0020] ;

[0021] ;

[0022] ;

[0023] In the above formula, The density of water, It is the acceleration due to gravity. The height difference of the reservoir of the pumped storage power station. This represents the maximum change in water volume per unit time at a pumped storage power station. For weather scenes Down Output power of pumped storage power stations during specific periods , These are the lower and upper limits of the water storage capacity of a pumped storage power station reservoir, respectively. The capacity of the pumped storage power station reservoir. For weather scenes The ecological water required below. For weather scenes Down The external ambient temperature during the period, The evaporation coefficient is the coefficient of water vapor. , Weather scenarios Down Output and input power of pumped storage power stations during specific time periods For weather scenes Down Operating state variables of pumped storage power stations during specific time periods. For the large M constant, This is the upper limit of the operating power of pumped storage power station units.

[0024] The power generation side operating constraints also include thermal power plant operating constraints:

[0025] ;

[0026] ;

[0027] ;

[0028] ;

[0029] ;

[0030] ;

[0031] ;

[0032] ;

[0033] ;

[0034] In the above formula, , Weather scenarios Down Start-up operation variables and state variables of thermal power generating units during the time period. For weather scenes The next typical daily limit for the number of start-up and shutdown operations of a thermal power generating unit. This refers to the minimum operating time of a thermal power generating unit. For weather scenes Down Power generation capacity of thermal power generating units during certain periods , Weather scenarios Minimum and maximum output of thermal power generating units For weather scenes The maximum power generation of a thermal power generating unit in a typical day. For weather scenes The maximum ramp rate of the thermal power generating unit. For weather scenes Down Total output power of the thermal power plant during the period For weather scenes Down The output power of the extraction steam storage system configured in the thermal power plant during certain periods. The energy storage capacity of the extraction steam storage system. , These are the lower and upper limits of the energy state of the extraction steam storage system, respectively. This refers to the internal temperature of the extraction steam storage system. The energy loss coefficient of the temperature difference and extraction steam storage system. This is the last period of the day.

[0035] The power grid operation optimization model also considers the impact of extreme high temperature weather, high ambient temperature, and high load rate on power supply lines and transformers;

[0036] The power consumption-side operating constraints include power supply line and transformer operating constraints:

[0037] ;

[0038] ;

[0039] ;

[0040] ;

[0041] ;

[0042] ;

[0043] In the above formula, For weather scenes Down The external ambient temperature during the period, For reference temperature, , These are the ambient temperature rise coefficients for power supply lines and transformers, respectively. , These are the load rate temperature rise coefficients for power supply lines and transformers, respectively. , These are the upper limits of operating temperature for power supply lines and transformers, respectively. , Weather scenarios Down Time-of-use power supply lines and transformer load rate, For weather scenes Down Time-of-use power supply lines Power transmitted For power supply lines The upper limit of transmission power, For transformer The upper limit of operating power, , These are the lower and upper limits of the line load rate, respectively. , These are the lower and upper limits of the transformer load rate, respectively.

[0044] The power consumption-side operation constraints also include virtual power plant constraints and power balance constraints;

[0045] The virtual power plant constraints include:

[0046] ;

[0047] ;

[0048] ;

[0049] ;

[0050] ;

[0051] ;

[0052] ;

[0053] ;

[0054] ;

[0055] ;

[0056] ;

[0057] In the above formula, This is the coefficient relating temperature and cooling demand. , Each is a reference weather scenario Time period nodes The cooling capacity requirements of high-efficiency temperature control loads and low-efficiency temperature control loads at the location. To meet the minimum proportion of cooling load, For weather scenes The next typical intraday node The overall cooling demand is met to a certain extent. For nodes Temperature control satisfaction index variable, This serves as a reference ratio for meeting cooling capacity requirements. , , Weather scenarios Down Time period nodes Fixed loads, spatially and temporally movable loads, and time-sequential flexible loads. For weather scenes Total electricity load demand for space-time transferable loads For weather scenes Next node Total electricity load demand for time-series flexible loads , These are the minimum satisfaction ratios for spatiotemporally movable loads and time-sequential flexible loads, respectively. For nodes Non-temperature-sensitive load satisfaction index variable, This is a reference satisfaction ratio for non-temperature-sensitive loads. The lowest overall satisfaction index;

[0058] The power balance constraints include:

[0059] ;

[0060] ;

[0061] ;

[0062] In the above formula, For weather scenes Down Time-of-use power supply lines Power transmitted For power supply lines With nodes Relationship constants, For weather scenes Down Time-of-use transformer Operating power For transformer With nodes The correlation constant, For weather scenes Down Power generation capacity of thermal power generating units during certain periods For weather scenes Down The output power of the extraction steam storage system configured in the thermal power plant during certain periods. For weather scenes Down Output power of pumped storage power stations during certain periods.

[0063] Secondly, this invention proposes a main and distribution coordinated power grid operation optimization system that takes into account extreme high temperature weather, including a model building module and a model solving module;

[0064] The model building module is used to construct a power grid operation optimization model with the goal of minimizing the losses of temperature-controlled loads and non-temperature-sensitive conventional loads. This model considers extreme high-temperature weather. On the distribution network side, temperature-controlled loads are divided into high-efficiency loads and low-efficiency loads according to their energy efficiency levels, and non-temperature-sensitive loads are divided into spatiotemporally movable loads, time-series flexible loads, and fixed loads according to their flexibility. A virtual power plant is used for joint control of various types of loads. On the generation side, an extraction steam storage system is used, and boiler-turbine decoupling is achieved through molten salt tank thermal storage. The influence of ambient temperature on the thermal storage effect of the molten salt tank is considered, and it is coordinated with the virtual power plant and power supply network on the distribution network side.

[0065] The model solving module is used to solve the power grid operation optimization model to obtain power grid operation optimization schemes under various weather scenarios, including temperature-controlled loads, non-temperature-sensitive conventional loads, and generator unit operation strategies.

[0066] The model building module includes an objective function building unit and a constraint condition building unit. The objective function building unit is used to build the following objective function:

[0067] ;

[0068] ;

[0069] ;

[0070] In the above formula, , These are respectively temperature-controlled load losses and non-temperature-sensitive conventional load losses. , These are the energy efficiency ratios for high-efficiency temperature control loads and low-efficiency temperature control loads, respectively. , Weather scenarios Down Time period nodes The cooling capacity requirements of high-efficiency and low-efficiency temperature-controlled loads are considered, with weather scenarios including normal weather and extreme high-temperature weather. , Weather scenarios Down Time period nodes The electricity load demand of high-efficiency temperature-controlled loads and low-efficiency temperature-controlled loads at the location. For a unit of time, Weather scene within a time period The number of consecutive days, For weather scenes Down During a specific time period, a typical intraday node The proportion of non-temperature-sensitive load demand met. For nodes The rated non-temperature-sensitive load at the location;

[0071] The constraint construction unit is used to construct the power generation side operation constraints and the power consumption side operation constraints.

[0072] The power grid operation optimization model also considers the impact of high temperatures on pumped storage systems, and the power grid operation optimization scheme also includes a combined energy storage-ecological water control strategy under extreme high temperatures.

[0073] The power generation side operation constraints include pumped storage power station operation constraints and thermal power plant operation constraints.

[0074] The operational constraints of the pumped storage power station include:

[0075] ;

[0076] ;

[0077] ;

[0078] ;

[0079] ;

[0080] ;

[0081] In the above formula, The density of water, It is the acceleration due to gravity. The height difference of the reservoir of the pumped storage power station. This represents the maximum change in water volume per unit time at a pumped storage power station. For weather scenes Down Output power of pumped storage power stations during specific periods , These are the lower and upper limits of the water storage capacity of a pumped storage power station reservoir, respectively. The capacity of the pumped storage power station reservoir. For weather scenes The ecological water required below. For weather scenes Down The external ambient temperature during the period, The evaporation coefficient is the coefficient of water vapor. , Weather scenarios Down Output and input power of pumped storage power stations during specific time periods For weather scenes Down Operating state variables of pumped storage power stations during specific time periods. For the large M constant, This is the upper limit of the operating power of pumped storage power station units;

[0082] The operating constraints of the thermal power plant include:

[0083] ;

[0084] ;

[0085] ;

[0086] ;

[0087] ;

[0088] ;

[0089] ;

[0090] ;

[0091] ;

[0092] In the above formula, , Weather scenarios Down Start-up operation variables and state variables of thermal power generating units during the time period. For weather scenes The next typical daily limit for the number of start-up and shutdown operations of a thermal power generating unit. This refers to the minimum operating time of a thermal power generating unit. For weather scenes Down Power generation capacity of thermal power generating units during certain periods , Weather scenarios Minimum and maximum output of thermal power generating units For weather scenes The maximum power generation of a thermal power generating unit in a typical day. For weather scenes The maximum ramp rate of the thermal power generating unit. For weather scenes Down Total output power of the thermal power plant during the period For weather scenes Down The output power of the extraction steam storage system configured in the thermal power plant during certain periods. The energy storage capacity of the extraction steam storage system. , These are the lower and upper limits of the energy state of the extraction steam storage system, respectively. This refers to the internal temperature of the extraction steam storage system. The energy loss coefficient of the temperature difference and extraction steam storage system. This is the last period of the day.

[0093] The power grid operation optimization model also considers the impact of extreme high temperature weather, high ambient temperature, and high load rate on power supply lines and transformers;

[0094] The power consumption-side operation constraints include power supply line and transformer operation constraints, virtual power plant constraints, and power balance constraints.

[0095] The operational constraints of the power supply lines and transformers include:

[0096] ;

[0097] ;

[0098] ;

[0099] ;

[0100] ;

[0101] ;

[0102] In the above formula, For weather scenes Down The external ambient temperature during the period, For reference temperature, , These are the ambient temperature rise coefficients for power supply lines and transformers, respectively. , These are the load rate temperature rise coefficients for power supply lines and transformers, respectively. , These are the upper limits of operating temperature for power supply lines and transformers, respectively. , Weather scenarios Down Time-of-use power supply lines and transformer load rate, For weather scenes Down Time-of-use power supply lines Power transmitted For power supply lines The upper limit of transmission power, For transformer The upper limit of operating power, , These are the lower and upper limits of the line load rate, respectively. , These are the lower and upper limits of the transformer load rate, respectively.

[0103] The virtual power plant constraints include:

[0104] ;

[0105] ;

[0106] ;

[0107] ;

[0108] ;

[0109] ;

[0110] ;

[0111] ;

[0112] ;

[0113] ;

[0114] ;

[0115] In the above formula, This is the coefficient relating temperature and cooling demand. , Each is a reference weather scenario Time period nodes The cooling capacity requirements of high-efficiency temperature control loads and low-efficiency temperature control loads at the location. To meet the minimum proportion of cooling load, For weather scenes The next typical intraday node The overall cooling demand is met to a certain extent. For nodes Temperature control satisfaction index variable, This serves as a reference ratio for meeting cooling capacity requirements. , , Weather scenarios Down Time period nodes Fixed loads, spatially and temporally movable loads, and time-sequential flexible loads. For weather scenes Total electricity load demand for space-time transferable loads For weather scenes Next node Total electricity load demand for time-series flexible loads , These are the minimum satisfaction ratios for spatiotemporally movable loads and time-sequential flexible loads, respectively. For nodes Non-temperature-sensitive load satisfaction index variable, This is a reference satisfaction ratio for non-temperature-sensitive loads. The lowest overall satisfaction index;

[0116] The power balance constraints include:

[0117] ;

[0118] ;

[0119] ;

[0120] In the above formula, For weather scenes Down Time-of-use power supply lines Power transmitted For power supply lines With nodes Relationship constants, For weather scenes Down Time-of-use transformer Operating power For transformer With nodes The correlation constant, For weather scenes Down Power generation capacity of thermal power generating units during certain periods For weather scenes Down The output power of the extraction steam storage system configured in the thermal power plant during certain periods. For weather scenes Down Output power of pumped storage power stations during certain periods.

[0121] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0122] 1. The present invention proposes a power grid operation optimization model that considers extreme high-temperature weather and constructs a main distribution coordinated power grid operation optimization method. This model considers extreme high-temperature weather and aims to minimize the losses of temperature-controlled loads and non-temperature-sensitive conventional loads. Specifically, on the distribution network side, typical loads are divided into temperature-controlled loads and non-temperature-sensitive conventional loads. Temperature-controlled loads are further divided into high-efficiency and low-efficiency loads based on energy efficiency levels. Non-temperature-sensitive loads are divided into spatiotemporally movable loads, time-series flexible loads, and fixed loads based on flexibility. A virtual power plant is used for joint control of various load types, while also considering user satisfaction and load importance weights to maintain power supply to important loads under the premise of ensuring the safe and stable operation of the distribution network. On the generation side, an extraction steam storage system is used, and boiler-generator decoupling is achieved through molten salt tank thermal storage. The impact of ambient temperature on the thermal storage effect of the molten salt tank is considered, improving the ramp-up and start-stop margins of generator units in extreme scenarios. Furthermore, in conjunction with the virtual power plant on the distribution network side and the power supply network, the operating strategy of generator units under extreme weather conditions is jointly optimized to minimize system load loss while ensuring the safe and stable operation of the main distribution coordinated system.

[0123] 2. The present invention proposes a main distribution coordinated power grid operation optimization method considering extreme high temperature weather. This method addresses the issue that the evaporation rate of pumped storage power station reservoirs will increase under high temperature weather, while also balancing the ecological water demand of the location. It takes into account the impact of high temperature weather on pumped storage systems and optimizes the energy storage-ecological joint water control strategy under extreme high temperature weather.

[0124] 3. The main distribution coordinated power grid operation optimization method proposed in this invention takes into account the impact of high temperature, high ambient temperature and high load rate on power supply lines and transformers under extreme high temperature weather. It designs limit load rate constraints for lines and transformers for extreme high temperature weather to avoid increased line losses, decreased power quality and increased transformer failure rate caused by excessive temperature. Attached Figure Description

[0125] Figure 1 This is a schematic diagram of the main distribution coordinated power grid.

[0126] Figure 2 This is a schematic diagram of the 12 power consumption node architecture in Example 1.

[0127] Figure 3 This is a temperature characteristic diagram under normal weather conditions in Example 1.

[0128] Figure 4 This is a temperature characteristic diagram under extreme high-temperature weather conditions in Example 1.

[0129] Figure 5 This is a schematic diagram of the system described in Example 2. Detailed Implementation

[0130] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0131] This invention proposes an optimization method for the coordinated operation of the main and distribution power grids considering extreme high-temperature weather. This method addresses issues such as... Figure 1 The main and distribution coordinated power grid shown constructs a diversified and integrated flexible supply system on the power generation side, promoting the flexible transformation of thermal power plants to enhance their ramp-up and regulation capabilities; on the power consumption side, it fully activates and mobilizes massive flexible load resources, and aggregates dispersed flexible and adjustable loads by developing new business models such as virtual power plants, breaking the traditional passive situation of "source follows load".

[0132] Example 1:

[0133] This embodiment uses Figure 2 The 12-node power consumption architecture shown is used as the object. An optimization method for main and distribution network operation considering extreme high-temperature weather is implemented. The specific steps are as follows:

[0134] 1. Considering temperature-controlled load losses and non-temperature-sensitive conventional load losses, a power grid operation optimization model is constructed with the objective of minimizing both temperature-controlled and non-temperature-sensitive conventional load losses. The objective function of this model includes:

[0135] (1)

[0136] (2)

[0137] (3)

[0138] In the above formula, , These are respectively temperature-controlled load losses and non-temperature-sensitive conventional load losses. , These are the energy efficiency ratios for high-efficiency temperature control loads and low-efficiency temperature control loads, respectively. , Weather scenarios Down Time period nodes The cooling demand of high-efficiency and low-efficiency temperature-controlled loads, under weather scenarios including normal weather and extreme high-temperature weather, with typical intraday temperatures under normal and extreme high-temperature weather scenarios as follows: Figure 3 , 4 As shown, , Weather scenarios Down Time period nodes The electricity load demand of high-efficiency temperature-controlled loads and low-efficiency temperature-controlled loads at the location. For a unit of time, Weather scene within a time period The number of consecutive days, For weather scenes Down During a specific time period, a typical intraday node The proportion of non-temperature-sensitive load demand met. For nodes The rated non-temperature-sensitive load at the location.

[0139] The constraints include power generation side operation constraints and power consumption side operation constraints, including thermal power plant operation constraints and pumped storage power station operation constraints. The power consumption side operation constraints include power supply line and transformer operation constraints, virtual power plant constraints, and power balance constraints.

[0140] Operating constraints of thermal power plants:

[0141] (4)

[0142] (5)

[0143] (6)

[0144] (7)

[0145] (8)

[0146] (9)

[0147] (10)

[0148] (11)

[0149] (12)

[0150] In the above formula, , Weather scenarios Down Start-up operation variables and state variables (binary) of thermal power generating units during a given time period. A value of 1 indicates that the thermal power generating unit is started, and a value of 0 indicates that it is not started. A value of 1 indicates that the thermal power generating unit is in operation, while a value of 0 indicates that it is in shutdown mode. For weather scenes The next typical daily limit for the number of start-up and shutdown operations of a thermal power generating unit. This refers to the minimum operating time of a thermal power generating unit. For weather scenes Down Power generation capacity of thermal power generating units during certain periods , Weather scenarios Minimum and maximum output of thermal power generating units For weather scenes The maximum power generation of a thermal power generating unit in a typical day. For weather scenes The maximum ramp rate of the thermal power generating unit. For weather scenes Down Total output power of the thermal power plant during the period For weather scenes Down The output power of the extraction steam storage system configured in the thermal power plant during a certain period is such that when it is greater than 0, the extraction steam storage system is in the state of outputting electrical energy; when it is less than 0, the extraction steam storage system is in the state of storing electrical energy. The energy storage capacity of the extraction steam storage system. , These are the lower and upper limits of the energy state of the extraction steam storage system, respectively. This refers to the internal temperature of the extraction steam storage system. The energy loss coefficient of the temperature difference and extraction steam storage system. This is the last period of the day.

[0151] Equations (4)-(5) are constraints on the number of times a thermal power generator unit can start; Equation (6) is constraints on the minimum operating time of a thermal power generator unit; Equation (7) is constraints on the upper and lower limits of the power generation of a thermal power generator unit; Equation (8) is constraints on the maximum daily power generation of a thermal power generator unit; Equation (9) is constraints on the ramping of a thermal power generator unit; Equation (10) is constraints on the power balance of a thermal power plant; Equations (11)-(12) are constraints on the operation of the extraction steam storage system in a thermal power plant.

[0152] Operational constraints of pumped storage power stations:

[0153] (13)

[0154] (14)

[0155] (15)

[0156] (16)

[0157] (17)

[0158] (18)

[0159] In the above formula, The density of water, It is the acceleration due to gravity. The height difference of the reservoir of the pumped storage power station. This represents the maximum change in water volume per unit time at a pumped storage power station. For weather scenes Down The output power of a pumped-storage hydroelectric power station during a given period is defined as follows: when the value is greater than 0, the power station is releasing water and outputting electrical energy; when the value is less than 0, the power station is pumping water and storing electrical energy. , These are the lower and upper limits of the water storage capacity of a pumped storage power station reservoir, respectively. The capacity of the pumped storage power station reservoir. For weather scenes The ecological water required below. For weather scenes Down The external ambient temperature during the period, The evaporation coefficient is positively correlated with the ambient temperature. , Weather scenarios Down Output and input power of pumped storage power stations during specific time periods For weather scenes Down The operating state variable (binary) of the pumped storage power station during a given time period: when it is 1, the pumped storage power station is in the state of releasing water and outputting electrical energy; when it is 0, the pumped storage power station is in the state of pumping water and storing electrical energy. For the large M constant, This is the upper limit of the operating power of pumped storage power station units.

[0160] Equation (13) is the operating power constraint of the pumped storage power station; Equation (14) is the energy storage state constraint of the pumped storage power station; Equations (15)-(17) are the operating state constraints of the pumped storage power station, which can only operate in one operating state at the same time; Equation (18) is the shutdown constraint of the pumped storage power station unit. The bidirectional unit of the pumped storage power station needs to ensure a certain working load. The unit may enter the vibration zone and cause failure when operating at low load.

[0161] Operating constraints of power supply lines and transformers:

[0162] (19)

[0163] (20)

[0164] (twenty one)

[0165] (twenty two)

[0166] (twenty three)

[0167] (twenty four)

[0168] In the above formula, For weather scenes Down The external ambient temperature during the period, For reference temperature, , These are the ambient temperature rise coefficients for power supply lines and transformers, respectively. , These are the load rate temperature rise coefficients for power supply lines and transformers, respectively. , These are the upper limits of operating temperature for power supply lines and transformers, respectively. , Weather scenarios Down Time-of-use power supply lines and transformer load rate, For weather scenes Down Time-of-use power supply lines Power transmitted For power supply lines The upper limit of transmission power, For transformer The upper limit of operating power, , These are the lower and upper limits of the line load rate, respectively. , These are the lower and upper limits of the transformer load rate, respectively.

[0169] Equations (19) and (20) are the temperature constraints of the power supply line and the transformer, respectively. Under extreme weather conditions, the ambient temperature and high load rate will cause the temperature to rise. Equations (21)-(24) are the load rate constraints of the power supply line and the transformer.

[0170] Virtual power plant constraints:

[0171] (25)

[0172] (26)

[0173] (27)

[0174] (28)

[0175] (29)

[0176] (30)

[0177] (31)

[0178] (32)

[0179] (33)

[0180] (34)

[0181] (35)

[0182] In the above formula, This is the coefficient relating temperature and cooling demand. , These are reference weather scenarios (temperature is a reference temperature). Time period nodes The cooling capacity requirements of high-efficiency temperature control loads and low-efficiency temperature control loads at the location. To meet the minimum proportion of cooling load, For weather scenes The next typical intraday node The overall cooling demand is met to a certain extent. For nodes The temperature control satisfaction index variable (binary) is defined as follows: a value of 1 indicates user satisfaction, and a value of 0 indicates dissatisfaction. This serves as a reference ratio for meeting cooling capacity requirements. , , Weather scenarios Down Time period nodes Fixed loads, spatially and temporally movable loads, and time-sequential flexible loads. For weather scenes Total electricity load demand for space-time transferable loads For weather scenes Next node Total electricity load demand for time-series flexible loads , These are the minimum satisfaction ratios for spatiotemporally movable loads and time-sequential flexible loads, respectively. For nodes The non-temperature-sensitive load satisfaction index variable (binary) is defined as follows: a value of 1 indicates user satisfaction, and a value of 0 indicates dissatisfaction. This is a reference satisfaction ratio for non-temperature-sensitive loads. The lowest overall satisfaction index.

[0183] Equations (25)-(28) are the cooling demand constraints for high-efficiency temperature-controlled loads and low-efficiency temperature-controlled loads; Equations (25)-(28) are the electricity load constraints for high-efficiency temperature-controlled loads and low-efficiency temperature-controlled loads; Equations (29)-(30) are the user satisfaction constraints for temperature control; Equations (31)-(32) are the flexible load dispatch constraints, which take into account the virtual power plant's dispatch capability for time-space transferable loads and time-series flexible loads; Equations (33)-(34) are the user satisfaction constraints for non-temperature-sensitive loads; Equation (35) is the overall satisfaction constraint for the electricity consumption side.

[0184] Power balance constraints:

[0185] (36)

[0186] (37)

[0187] (38)

[0188] In the above formula, For weather scenes Down Time-of-use power supply lines Power transmitted For power supply lines With nodes A relational constant (binary), when it is 1, indicates a power supply line. With nodes Connected, a value of 0 indicates a power supply line. With nodes Not connected For weather scenes Down Time-of-use transformer Operating power For transformer With nodes The correlation constant (binary), when it is 1, indicates the transformer At the node At this point, a value of 0 indicates a transformer. Not in node Place, For weather scenes Down Power generation capacity of thermal power generating units during certain periods For weather scenes Down The output power of the extraction steam storage system configured in the thermal power plant during certain periods. For weather scenes Down Output power of pumped storage power stations during certain periods.

[0189] In this embodiment, the parameters of the model are set as follows:

[0190] The minimum operating time of the thermal power generating unit is 2 hours; the unit time is 1 hour; the energy storage capacity of the extraction steam storage system is 300 MWh; the internal temperature of the extraction steam storage system is 300 degrees Celsius; the energy loss coefficient of the temperature difference and extraction steam storage system is 0.05; the lower limit and upper limit of the energy state of the extraction steam storage system are 0.2 and 0.9 respectively; the maximum water volume change per unit time of the pumped storage power station is... cubic meters; the evaporation coefficient of the reservoir in a pumped storage power station is cubic meters; the lower and upper limits of the water storage ratio of the pumped storage power station reservoir are 0.15 and 0.85 respectively; the initial water storage capacity of the pumped storage power station reservoir is cubic meters; the density of water is kilograms per cubic meter; gravitational acceleration is 9.8 meters per second. 2 The height difference of the pumped storage power station reservoir is 200 meters; the lower limit of the operating power of the pumped storage power station unit is 40 MW; the reference temperature is 20 degrees Celsius; the ambient temperature rise coefficients of power lines and transformers are 0.02 degrees Celsius and 0.5 degrees Celsius, respectively; the load rate temperature rise coefficients of power lines and transformers are 1 degree Celsius and 2 degrees Celsius, respectively; the lower and upper limits of line load rate are 0.1 and 0.8, respectively; the lower and upper limits of transformer load rate are 0.1 and 0.8, respectively; the relationship coefficient between temperature and cooling demand is 0.15; the energy efficiency ratios of high-efficiency temperature-controlled loads and low-efficiency temperature-controlled loads are 4 and 2, respectively; the reference satisfaction ratio of cooling demand is 0.8; the minimum satisfaction ratios of time-space-transferable loads and time-flexible loads are both 0.8; the reference satisfaction ratio of non-temperature-sensitive loads is 0.8.

[0191] 2. Based on the MATLAB / CPLEX platform (hardware parameters: Intel Core i7-9750H, 32G RAM, 2.6GHz), solve the power grid operation optimization model to obtain power grid operation optimization schemes under various weather scenarios, including temperature-controlled load loss, non-temperature-sensitive conventional loads and generator unit operation strategies, and energy storage-ecological joint water control strategies under extreme high temperature weather.

[0192] To verify the effectiveness of the method proposed in this invention (Method 1), its results were compared with those obtained using the traditional independent operation method (Method 2), and the load losses for each method were calculated. The results are shown in Table 1.

[0193] Table 1 Comparison of load loss between the two methods

[0194] .

[0195] The comparison shows that Method 1 reduces the temperature-controlled load loss by 16.12%, the non-temperature-sensitive conventional load loss by 14.59%, and the overall load loss by 14.86% compared to Method 2. This means that the present invention achieves the effect of minimizing system load loss while ensuring the safe and stable operation of the main and auxiliary coordinated system.

[0196] Example 2:

[0197] like Figure 5 As shown, a main distribution coordinated power grid operation optimization system considering extreme high temperature weather includes a model building module and a model solving module.

[0198] The model building module is used to construct a power grid operation optimization model with the objective of minimizing temperature-controlled load loss and non-temperature-sensitive conventional load loss. It includes an objective function construction unit and a constraint condition construction unit. The objective function construction unit is used to construct the following objective function:

[0199] ;

[0200] ;

[0201] ;

[0202] In the above formula, , These are respectively temperature-controlled load losses and non-temperature-sensitive conventional load losses. , These are the energy efficiency ratios for high-efficiency temperature control loads and low-efficiency temperature control loads, respectively. , Weather scenarios Down Time period nodes The cooling capacity requirements of high-efficiency and low-efficiency temperature-controlled loads are considered, with weather scenarios including normal weather and extreme high-temperature weather. , Weather scenarios Down Time period nodes The electricity load demand of high-efficiency temperature-controlled loads and low-efficiency temperature-controlled loads at the location. For a unit of time, Weather scene within a time period The number of consecutive days, For weather scenes Down During a specific time period, a typical intraday node The proportion of non-temperature-sensitive load demand met. For nodes The rated non-temperature-sensitive load at the location.

[0203] The constraint construction unit is used to construct power generation side operation constraints and power consumption side operation constraints. The power generation side operation constraints include pumped storage power station operation constraints and thermal power plant operation constraints. The power consumption side operation constraints include power line and transformer operation constraints, virtual power plant constraints, and power balance constraints.

[0204] The operating constraints of the thermal power plant include:

[0205] ;

[0206] ;

[0207] ;

[0208] ;

[0209] ;

[0210] ;

[0211] ;

[0212] ;

[0213] ;

[0214] In the above formula, , Weather scenarios Down Start-up operation variables and state variables of thermal power generating units during the time period. For weather scenes The next typical daily limit for the number of start-up and shutdown operations of a thermal power generating unit. This refers to the minimum operating time of a thermal power generating unit. For weather scenes Down Power generation capacity of thermal power generating units during certain periods , Weather scenarios Minimum and maximum output of thermal power generating units For weather scenes The maximum power generation of a thermal power generating unit in a typical day. For weather scenes The maximum ramp rate of the thermal power generating unit. For weather scenes Down Total output power of the thermal power plant during the period For weather scenes Down The output power of the extraction steam storage system configured in the thermal power plant during certain periods. The energy storage capacity of the extraction steam storage system. , These are the lower and upper limits of the energy state of the extraction steam storage system, respectively. This refers to the internal temperature of the extraction steam storage system. The energy loss coefficient of the temperature difference and extraction steam storage system. This is the last period of the day.

[0215] The operational constraints of the pumped storage power station include:

[0216] ;

[0217] ;

[0218] ;

[0219] ;

[0220] ;

[0221] ;

[0222] In the above formula, The density of water, It is the acceleration due to gravity. The height difference of the reservoir of the pumped storage power station. This represents the maximum change in water volume per unit time at a pumped storage power station. For weather scenes Down Output power of pumped storage power stations during specific periods , These are the lower and upper limits of the water storage capacity of a pumped storage power station reservoir, respectively. The capacity of the pumped storage power station reservoir. For weather scenes The ecological water required below. For weather scenes Down The external ambient temperature during the period, The evaporation coefficient is the coefficient of water vapor. , Weather scenarios Down Output and input power of pumped storage power stations during specific time periods For weather scenes Down Operating state variables of pumped storage power stations during specific time periods. For the large M constant, This is the upper limit of the operating power of pumped storage power station units.

[0223] The operational constraints of the power supply lines and transformers include:

[0224] ;

[0225] ;

[0226] ;

[0227] ;

[0228] ;

[0229] ;

[0230] In the above formula, For weather scenes Down The external ambient temperature during the period, For reference temperature, , These are the ambient temperature rise coefficients for power supply lines and transformers, respectively. , These are the load rate temperature rise coefficients for power supply lines and transformers, respectively. , These are the upper limits of operating temperature for power supply lines and transformers, respectively. , Weather scenarios Down Time-of-use power supply lines and transformer load rate, For weather scenes Down Time-of-use power supply lines Power transmitted For power supply lines The upper limit of transmission power, For transformer The upper limit of operating power, , These are the lower and upper limits of the line load rate, respectively. , These are the lower and upper limits of the transformer load rate, respectively.

[0231] The virtual power plant constraints include:

[0232] ;

[0233] ;

[0234] ;

[0235] ;

[0236] ;

[0237] ;

[0238] ;

[0239] ;

[0240] ;

[0241] ;

[0242] ;

[0243] In the above formula, This is the coefficient relating temperature and cooling demand. , Each is a reference weather scenario Time period nodes The cooling capacity requirements of high-efficiency temperature control loads and low-efficiency temperature control loads at the location. To meet the minimum proportion of cooling load, For weather scenes The next typical intraday node The overall cooling demand is met to a certain extent. For nodes Temperature control satisfaction index variable, This serves as a reference ratio for meeting cooling capacity requirements. , , Weather scenarios Down Time period nodes Fixed loads, spatially and temporally movable loads, and time-sequential flexible loads. For weather scenes Total electricity load demand for space-time transferable loads For weather scenes Next node Total electricity load demand for time-series flexible loads , These are the minimum satisfaction ratios for spatiotemporally movable loads and time-sequential flexible loads, respectively. For nodes Non-temperature-sensitive load satisfaction index variable, This is a reference satisfaction ratio for non-temperature-sensitive loads. The lowest overall satisfaction index.

[0244] The power balance constraints include:

[0245] ;

[0246] ;

[0247] ;

[0248] In the above formula, For weather scenes Down Time-of-use power supply lines Power transmitted For power supply lines With nodes Relationship constants, For weather scenes Down Time-of-use transformer Operating power For transformer With nodes The correlation constant, For weather scenes Down Power generation capacity of thermal power generating units during certain periods For weather scenes Down The output power of the extraction steam storage system configured in the thermal power plant during certain periods. For weather scenes Down Output power of pumped storage power stations during certain periods.

[0249] The model solving module is used to solve the power grid operation optimization model and obtain power grid operation optimization schemes under various weather scenarios, including the operation strategies of temperature-controlled loads, non-temperature-sensitive conventional loads and generator sets, and the energy storage-ecological joint water control strategy under extreme high temperature weather.

Claims

1. A method for optimizing the coordinated operation of the main and distribution power grids considering extreme high-temperature weather, characterized in that: The method includes: S1. Construct a power grid operation optimization model with the goal of minimizing losses from temperature-controlled loads and non-temperature-sensitive conventional loads. This model considers extreme high-temperature weather. On the distribution network side, temperature-controlled loads are divided into high-efficiency loads and low-efficiency loads according to their energy efficiency levels, and non-temperature-sensitive loads are divided into spatiotemporally movable loads, time-series flexible loads, and fixed loads according to their flexibility. A virtual power plant is used for joint regulation of various types of loads. On the generation side, an extraction steam storage system is used, and boiler-turbine decoupling is achieved through molten salt tank thermal storage. The influence of ambient temperature on the thermal storage effect of the molten salt tank is considered, and it is coordinated with the virtual power plant and power supply network on the distribution network side. S2. Solve the power grid operation optimization model to obtain power grid operation optimization schemes under various weather scenarios, including temperature-controlled loads, non-temperature-sensitive conventional loads, and generator unit operation strategies.

2. The method for optimizing the operation of the main and distribution power grids considering extreme high-temperature weather as described in claim 1, characterized in that, The objective function of the power grid operation optimization model includes: ； ； ； In the above formula, , These are respectively temperature-controlled load losses and non-temperature-sensitive conventional load losses. , These are the energy efficiency ratios for high-efficiency temperature control loads and low-efficiency temperature control loads, respectively. , Weather scenarios Down Time period nodes The cooling capacity requirements of high-efficiency and low-efficiency temperature-controlled loads are considered, with weather scenarios including normal weather and extreme high-temperature weather. , Weather scenarios Down Time period nodes The electricity load demand of high-efficiency temperature-controlled loads and low-efficiency temperature-controlled loads at the location. For a unit of time, Weather scene within a time period The number of consecutive days, For weather scenes Down During a specific time period, a typical intraday node The proportion of non-temperature-sensitive load demand met. For nodes The rated non-temperature-sensitive load at the location; The constraints include power generation side operation constraints and power consumption side operation constraints.

3. The method for optimizing the coordinated operation of the main and distribution power grids considering extreme high-temperature weather as described in claim 2, characterized in that, The power grid operation optimization model also considers the impact of high temperatures on pumped storage systems, and the power grid operation optimization scheme also includes a combined energy storage-ecological water control strategy under extreme high temperatures. The power generation-side operational constraints include the operational constraints of pumped storage power stations: ； ； ； ； ； ； In the above formula, The density of water, It is the acceleration due to gravity. The height difference of the reservoir of the pumped storage power station. This represents the maximum change in water volume per unit time at a pumped storage power station. For weather scenes Down Output power of pumped storage power stations during specific periods , These are the lower and upper limits of the water storage capacity of a pumped storage power station reservoir, respectively. The capacity of the pumped storage power station reservoir. For weather scenes The ecological water required below For weather scenes Down The external ambient temperature during the period, The evaporation coefficient is the coefficient of water vapor. , Weather scenarios Down Output and input power of pumped storage power stations during specific time periods For weather scenes Down Operating state variables of pumped storage power stations during specific time periods. For the large M constant, This is the upper limit of the operating power of pumped storage power station units.

4. The method for optimizing the coordinated operation of the main and distribution power grids considering extreme high-temperature weather as described in claim 3, characterized in that, The power generation side operating constraints also include thermal power plant operating constraints: ； ； ； ； ； ； ； ； ； In the above formula, , Weather scenarios Down Start-up operation variables and state variables of thermal power generating units during the time period. For weather scenes The next typical daily limit for the number of start-up and shutdown operations of a thermal power generating unit. This refers to the minimum operating time of a thermal power generating unit. For weather scenes Down Power generation capacity of thermal power generating units during certain periods , Weather scenarios The minimum and maximum output of the thermal power generating unit. For weather scenes The maximum power generation of a thermal power generating unit in a typical day. For weather scenes The maximum ramp rate of the thermal power generating unit. For weather scenes Down Total output power of the thermal power plant during the period For weather scenes Down The output power of the extraction steam storage system configured in the thermal power plant during a certain period. The energy storage capacity of the extraction steam storage system. , These are the lower and upper limits of the energy state of the extraction steam storage system, respectively. This refers to the internal temperature of the extraction steam storage system. The energy loss coefficient of the temperature difference and extraction steam storage system. This is the last period of the day.

5. The method for optimizing the operation of the main and distribution power grids considering extreme high-temperature weather as described in claim 2, characterized in that, The power grid operation optimization model also considers the impact of extreme high temperature weather, high ambient temperature, and high load rate on power supply lines and transformers; The power consumption-side operating constraints include power supply line and transformer operating constraints: ； ； ； ； ； ； In the above formula, For weather scenes Down The external ambient temperature during the period, For reference temperature, , These are the ambient temperature rise coefficients for power supply lines and transformers, respectively. , These are the load rate temperature rise coefficients for power supply lines and transformers, respectively. , These are the upper limits of operating temperature for power supply lines and transformers, respectively. , Weather scenarios Down Time-of-use power supply lines and transformer load rate, For weather scenes Down Time-of-use power supply lines Power transmitted For power supply lines The upper limit of transmission power, For transformer The upper limit of operating power, , These are the lower and upper limits of the line load rate, respectively. , These are the lower and upper limits of the transformer load rate, respectively.

6. The method for optimizing the operation of a main and distribution power grid considering extreme high-temperature weather as described in claim 5, characterized in that, The power consumption-side operation constraints also include virtual power plant constraints and power balance constraints; The virtual power plant constraints include: ； ； ； ； ； ； ； ； ； ； ； In the above formula, This is the coefficient relating temperature and cooling demand. , Each is a reference weather scenario Time period nodes The cooling capacity requirements of high-efficiency temperature control loads and low-efficiency temperature control loads at the location. To meet the minimum proportion of cooling load, For weather scenes The next typical intraday node The overall cooling demand is met to a certain extent. For nodes Temperature control satisfaction index variable, This serves as a reference ratio for meeting cooling capacity requirements. , , Weather scenarios Down Time period nodes Fixed loads, spatially and temporally movable loads, and time-sequential flexible loads. For weather scenes Total electricity load demand for space-time transferable loads For weather scenes Next node Total electricity load demand for time-series flexible loads , These are the minimum satisfaction ratios for spatiotemporally movable loads and time-sequential flexible loads, respectively. For nodes Non-temperature-sensitive load satisfaction index variable, This is a reference satisfaction ratio for non-temperature-sensitive loads. The lowest overall satisfaction index; The power balance constraints include: ； ； ； In the above formula, For weather scenes Down Time-of-use power supply lines Power transmitted For power supply lines With nodes Relationship constants, For weather scenes Down Time-of-use transformer Operating power For transformer With nodes The correlation constant, For weather scenes Down Power generation capacity of thermal power generating units during certain periods For weather scenes Down The output power of the extraction steam storage system configured in the thermal power plant during a certain period. For weather scenes Down Output power of pumped storage power stations during certain periods.

7. A power grid operation optimization system considering extreme high-temperature weather, characterized in that: The system includes a model building module and a model solving module; The model building module is used to construct a power grid operation optimization model with the goal of minimizing the losses of temperature-controlled loads and non-temperature-sensitive conventional loads. This model considers extreme high-temperature weather. On the distribution network side, temperature-controlled loads are divided into high-efficiency loads and low-efficiency loads according to their energy efficiency levels, and non-temperature-sensitive loads are divided into spatiotemporally movable loads, time-series flexible loads, and fixed loads according to their flexibility. A virtual power plant is used for joint control of various types of loads. On the generation side, an extraction steam storage system is used, and boiler-turbine decoupling is achieved through molten salt tank thermal storage. The influence of ambient temperature on the thermal storage effect of the molten salt tank is considered, and it is coordinated with the virtual power plant and power supply network on the distribution network side. The model solving module is used to solve the power grid operation optimization model to obtain power grid operation optimization schemes under various weather scenarios, including temperature-controlled loads, non-temperature-sensitive conventional loads, and generator unit operation strategies.

8. The main distribution coordinated power grid operation optimization system considering extreme high-temperature weather as described in claim 7, characterized in that, The model building module includes an objective function building unit and a constraint condition building unit. The objective function building unit is used to build the following objective function: ； ； ； In the above formula, , These are respectively temperature-controlled load losses and non-temperature-sensitive conventional load losses. , These are the energy efficiency ratios for high-efficiency temperature control loads and low-efficiency temperature control loads, respectively. , Weather scenarios Down Time period nodes The cooling capacity requirements of high-efficiency and low-efficiency temperature-controlled loads are considered, with weather scenarios including normal weather and extreme high-temperature weather. , Weather scenarios Down Time period nodes The electricity load demand of high-efficiency temperature-controlled loads and low-efficiency temperature-controlled loads at the location. For a unit of time, Weather scene within a time period The number of consecutive days, For weather scenes Down During a specific time period, a typical intraday node The proportion of non-temperature-sensitive load demand met. For nodes The rated non-temperature-sensitive load at the location; The constraint construction unit is used to construct the power generation side operation constraints and the power consumption side operation constraints.

9. The main distribution coordinated power grid operation optimization system considering extreme high-temperature weather as described in claim 8, characterized in that, The power grid operation optimization model also considers the impact of high temperatures on pumped storage systems, and the power grid operation optimization scheme also includes a combined energy storage-ecological water control strategy under extreme high temperatures. The power generation side operation constraints include pumped storage power station operation constraints and thermal power plant operation constraints. The operational constraints of the pumped storage power station include: ； ； ； ； ； ； In the above formula, The density of water, It is the acceleration due to gravity. The height difference of the reservoir of the pumped storage power station. This represents the maximum change in water volume per unit time at a pumped storage power station. For weather scenes Down Output power of pumped storage power stations during specific periods , These are the lower and upper limits of the water storage capacity of a pumped storage power station reservoir, respectively. The capacity of the pumped storage power station reservoir. For weather scenes The ecological water required below For weather scenes Down The external ambient temperature during the period, The evaporation coefficient is the coefficient of water vapor. , Weather scenarios Down Output and input power of pumped storage power stations during specific time periods For weather scenes Down Operating state variables of pumped storage power stations during specific time periods. For the large M constant, This is the upper limit of the operating power of pumped storage power station units; The operating constraints of the thermal power plant include: ； ； ； ； ； ； ； ； ； In the above formula, , Weather scenarios Down Start-up operation variables and state variables of thermal power generating units during the time period. For weather scenes The next typical daily limit for the number of start-up and shutdown operations of a thermal power generating unit. This refers to the minimum operating time of a thermal power generating unit. For weather scenes Down Power generation capacity of thermal power generating units during certain periods , Weather scenarios The minimum and maximum output of the thermal power generating unit. For weather scenes The maximum power generation of a thermal power generating unit in a typical day. For weather scenes The maximum ramp rate of the thermal power generating unit. For weather scenes Down Total output power of the thermal power plant during the period For weather scenes Down The output power of the extraction steam storage system configured in the thermal power plant during a certain period. The energy storage capacity of the extraction steam storage system. , These are the lower and upper limits of the energy state of the extraction steam storage system, respectively. This refers to the internal temperature of the extraction steam storage system. The energy loss coefficient of the temperature difference and extraction steam storage system. This is the last period of the day.

10. The main distribution coordinated power grid operation optimization system considering extreme high-temperature weather as described in claim 8, characterized in that, The power grid operation optimization model also considers the impact of extreme high temperature weather, high ambient temperature, and high load rate on power supply lines and transformers; The power consumption-side operation constraints include power supply line and transformer operation constraints, virtual power plant constraints, and power balance constraints. The operational constraints of the power supply lines and transformers include: ； ； ； ； ； ； In the above formula, For weather scenes Down The external ambient temperature during the period, For reference temperature, , These are the ambient temperature rise coefficients for power supply lines and transformers, respectively. , These are the load rate temperature rise coefficients for power supply lines and transformers, respectively. , These are the upper limits of operating temperature for power supply lines and transformers, respectively. , Weather scenarios Down Time-of-use power supply lines and transformer load rate, For weather scenes Down Time-of-use power supply lines Power transmitted For power supply lines The upper limit of transmission power, For transformer The upper limit of operating power, , These are the lower and upper limits of the line load rate, respectively. , These are the lower and upper limits of the transformer load rate, respectively. The virtual power plant constraints include: ； ； ； ； ； ； ； ； ； ； ； In the above formula, This is the coefficient relating temperature and cooling demand. , Each is a reference weather scenario Time period nodes The cooling capacity requirements of high-efficiency temperature control loads and low-efficiency temperature control loads at the location. To meet the minimum proportion of cooling load, For weather scenes The next typical intraday node The overall cooling demand is met to a certain extent. For nodes Temperature control satisfaction index variable, This serves as a reference ratio for meeting cooling capacity requirements. , , Weather scenarios Down Time period nodes Fixed loads, spatially and temporally movable loads, and time-sequential flexible loads. For weather scenes Total electricity load demand for space-time transferable loads For weather scenes Next node Total electricity load demand for time-series flexible loads , These are the minimum satisfaction ratios for spatiotemporally movable loads and time-sequential flexible loads, respectively. For nodes Non-temperature-sensitive load satisfaction index variable, This is a reference satisfaction ratio for non-temperature-sensitive loads. The lowest overall satisfaction index; The power balance constraints include: ； ； ； In the above formula, For weather scenes Down Time-of-use power supply lines Power transmitted For power supply lines With nodes Relationship constants, For weather scenes Down Time-of-use transformer Operating power For transformer With nodes The correlation constant, For weather scenes Down Power generation capacity of thermal power generating units during certain periods For weather scenes Down The output power of the extraction steam storage system configured in the thermal power plant during a certain period. For weather scenes Down Output power of pumped storage power stations during certain periods.

Images