A dynamic response method of flexible resources in distribution network based on priority data model

Abstract

The present invention proposes a method for dynamic response of flexible resources in a distribution network based on a priority data model, which belongs to the technical field of smart grids and comprises the following steps: S1: constructing a dynamic response model of flexible resources based on the operating characteristics of flexible resources; S2: considering the controlled priority of flexible resources, establishing a priority controlled model based on state margin and time margin; S3: establishing an optimization control objective function with the goal of minimizing the deviation between the response power of flexible resources and the target power and optimizing the controlled balance of the response; S4: determining the constraint conditions of the flexible resources, solving the model constructed in S1-S3, thereby determining a reasonable method for adjusting the demand of flexible resources, and issuing it to the flexible resources for execution. The present invention can uniformly exert the elastic regulation potential of multiple power loads and meet the response requirements of actual multiple heterogeneous flexible resources.

Description

Technical Field

[0001] The present invention belongs to the technical field of smart grids, and in particular relates to a distribution network flexible resource dynamic response method based on a priority data model. Background Art

[0002] In order to cope with the problems of system volatility, intermittency, randomness, low flexibility and economic benefits brought about by the access of renewable energy generation to modern power systems, system operators have researched and developed a variety of operating modes and new participating units to maintain the economy and reliability of power system operation. Among them, flexible resources on the load side, such as HVAC loads and electric vehicle loads, account for a large proportion of daily power consumption. They have good energy storage characteristics and can be directly controlled by load control means under the demand response mechanism. On the one hand, during the peak period of renewable energy output, electrical energy can be converted into thermal energy and stored in temperature-controlled loads or directly in electric vehicle batteries. On the other hand, during the trough period of renewable energy output, the inertial characteristics of slowly changing thermal energy in temperature-controlled loads and the energy storage characteristics of electric vehicle batteries are utilized to adjust power consumption within the user's energy comfort range to respond to power fluctuations caused by renewable energy output fluctuations or load activities, thereby providing the power grid with various types of auxiliary services to promote the optimized operation of modern power systems. They are regarded as important interactive participating resources in future energy systems.

[0003] Although certain progress has been made in the participation of flexible resources in the optimal operation of distribution networks, the types of flexible resources considered in the existing optimal operation models and methods of distribution networks with the participation of flexible resources are single, making it difficult to uniformly exert the regulatory potential of multiple power load elasticity and unable to meet the actual response needs of multiple heterogeneous flexible resources. In addition, the existing optimal operation of distribution networks with multiple flexible resources lacks consideration of the balanced response of flexible resources. Most of them are designed from the perspective of minimum regulation deviation, ignoring the tendency of the flexible resource response state and the balanced nature of the response control. Summary of the invention

[0004] In order to solve the above problems existing in the prior art, a method for dynamic response of flexible resources in a distribution network based on a priority data model is provided.

[0005] The technical solution adopted by the present invention to solve its technical problem is:

[0006] The present invention proposes a distribution network flexible resource dynamic response method based on a priority data model, which is characterized by comprising the following steps:

[0007] S1: Building a dynamic response model of flexible resources based on the operational characteristics of flexible resources;

[0008] S2: Considering the controlled priority of flexible resources, a priority controlled model based on state margin and time margin is established;

[0009] S3: Establish an optimization control objective function with the goal of minimizing the deviation between the response power of flexible resources and the target power and optimizing the response controlled balance;

[0010] S4: Determine the constraints of flexible resources and solve the model constructed in S1-S3 to determine the reasonable method of adjusting the demand of flexible resources and send it to the flexible resources for execution.

[0011] Furthermore, in S1, the flexible resources include heat pumps, electric water heaters, and electric vehicles.

[0012] Furthermore, in S1, the modeling of the heat pump model includes the following steps:

[0013] Calculate the equivalent thermal parameters of the heat pump model using the following formula:

[0014] ;

[0015] In the formula, Respectively represent the room number of the room. represents the equivalent heat capacity of the building walls and room air, represents the difference time step, Indicates the indoor temperature for the next counting period. Indicates the indoor temperature of the current period. Indicates the outdoor temperature, represents the equivalent thermal resistance of the building wall and air, represents the heat pump thermal power, represents the radiant heat power of the room, is the heat generated in the room;

[0016] Calculate the operating power of the heat pump model. Considering the different power regulation methods, the heat pump model is divided into two types: fixed-frequency heat pump and variable-frequency heat pump. The operating power calculation formula of the fixed-frequency heat pump is as follows:

[0017] (2);

[0018] ;

[0019] In the formula, Indicates the device serial number. Indicates the electrical power of the fixed-frequency heat pump, Indicates the rated electrical power of the fixed-frequency heat pump. Indicates the operating status of the fixed-frequency heat pump in the current period. It is a binary variable. 1 indicates that the compressor is started, and 0 indicates that the compressor is stopped. Indicates the operating status of the fixed-frequency heat pump in the next counting period. is the permissible temperature deviation, Indicates the current ambient temperature. is the set temperature;

[0020] The variable frequency heat pump relies on the inverter. Considering that its operating power can be continuously adjusted, the operating power constraint equation of the variable frequency heat pump is as follows:

[0021] (4);

[0022] In the formula, Indicates the electrical power of the variable frequency heat pump, Indicates the power upper limit of the variable frequency heat pump. Indicates the lower power limit of the variable frequency heat pump.

[0023] Furthermore, for a fixed-frequency heat pump, the heat pump thermal power The calculation formula is as follows:

[0024] (5);

[0025] In the formula, represents the heat pump thermal power, Indicates the operating power of the fixed frequency heat pump. Indicates the operating efficiency coefficient of the fixed-frequency heat pump in the room;

[0026] For variable frequency heat pumps, heat pump thermal power The calculation formula is as follows:

[0027] (6);

[0028] In the formula, represents the heat pump thermal power, Indicates the operating power of the variable frequency heat pump. Indicates the operating efficiency coefficient of the variable frequency heat pump in the room.

[0029] Furthermore, in S1, the modeling process of the electric water heater model includes the following steps:

[0030] Considering the thermodynamic equilibrium law and the equivalent thermal parameter equation, the hot water temperature dynamic equation of the electric water heater is established, and the formula is as follows:

[0031] ;

[0032] In the formula, Indicates the heat capacity of the electric water heater. Indicates the water temperature of the electric water heater in the current period. Indicates the water temperature of the electric water heater in the next counting period. represents the difference time step, Indicates the electrical power of the electric water heater. Indicates the operating efficiency of the electric water heater. represents the thermal disturbance power caused by hot water use, Represents the conduction heat loss of the electric water heater, where: Indicates the indoor temperature. Indicates the equivalent thermal resistance of the electric water heater;

[0033] In order to meet the hot water demand of the user during the specified period, a water temperature constraint equation is established, and the formula is as follows:

[0034] (8);

[0035] (9);

[0036] In the formula, Indicates the inlet water temperature. The water temperature of the electric water heater, Indicates that the user sets the concentrated use time of hot water, and the electric water heater needs to provide hot water that reaches the required temperature before this time. Indicates the upper limit of hot water temperature allowed by the electric water heater. Indicates the desired hot water temperature set by the user;

[0037] Establish the operating power equation of the electric water heater, the formula is as follows:

[0038] (10);

[0039] In the formula, Indicates the lower limit of the operating power adjustment of the electric water heater. Indicates the electrical power of the electric water heater. Indicates the upper limit of the operating power adjustment of the electric water heater.

[0040] Furthermore, in S1, the modeling process of the electric vehicle model includes the following steps:

[0041] Considering the flexible charging and discharging of electric vehicles, the SOC value of the electric vehicle in the next period is calculated as follows:

[0042] (11);

[0043] In the formula, Indicates the serial number of the electric vehicle. Indicates the SOC state of the electric vehicle in the next period, Indicates the SOC state of the electric vehicle in the current period. represents the charging power of the electric vehicle, represents the charging efficiency of electric vehicles, represents the discharge power of the electric vehicle, represents the discharge efficiency of electric vehicles, represents the difference time step, Indicates the battery capacity of an electric vehicle battery;

[0044] The SOC constraint equation of electric vehicles is established as follows:

[0045] (12);

[0046] In the formula, Indicates the SOC state of the electric vehicle in the current period. It is a binary variable that reflects the availability of electric vehicles. A value of 1 indicates that the electric vehicle is charged at the charging station, and a value of 0 indicates that the electric vehicle is not charged. represents the lower limit of SOC of electric vehicles, Indicates the upper limit of SOC of electric vehicles;

[0047] Establish the charging power constraint equation of electric vehicles and determine the value range of charging power. The formula is as follows:

[0048] (13);

[0049] In the formula, represents the charging power of the electric vehicle, It is a binary variable that reflects the availability of electric vehicles. A value of 1 indicates that the electric vehicle is charged at the charging station, and a value of 0 indicates that the electric vehicle is not charged. It is a binary variable, indicating the charging and discharging status of the electric vehicle, where 1 indicates that the electric vehicle is charging, and 0 indicates that the electric vehicle is discharging. Indicates the upper limit of charging power for electric vehicles;

[0050] Establish the discharge power constraint equation of electric vehicles and determine the range of discharge power. The formula is as follows:

[0051] (14);

[0052] In the formula, represents the discharge power of the electric vehicle, It is a binary variable that reflects the availability of electric vehicles. A value of 1 indicates that the electric vehicle is charged at the charging station, and a value of 0 indicates that the electric vehicle is not charged. It is a binary variable, indicating the charging and discharging status of the electric vehicle, where 1 indicates that the electric vehicle is charging, and 0 indicates that the electric vehicle is discharging. Indicates the upper limit of the discharge power of the electric vehicle;

[0053] Determine the initial state of charge of the electric vehicle, the formula is as follows:

[0054] (15);

[0055] In the formula, represents the initial state of charge of the electric vehicle, is the arrival time of the electric vehicle;

[0056] Determine the expected state of charge of the electric vehicle when it drives away, the formula is as follows:

[0057] (16);

[0058] In the formula, represents the expected state of charge of the electric vehicle when it drives away, is the departure time of the electric vehicle;

[0059] Sure The value of is as follows:

[0060] (17);

[0061] In the formula, is the arrival time of the electric vehicle, is the departure time of the electric vehicle.

[0062] Furthermore, in S2, the priority controlled model modeling process based on the state margin and the time margin includes the following steps:

[0063] Considering the operating status indicators of flexible resources, the controlled priority equation of flexible resources is established from the status perspective. The formula is as follows:

[0064] (18);

[0065] In the formula, represents various flexible resources, including heat pumps, electric water heaters, electric vehicles, Indicators of flexible resource control priority from a status perspective, Indicates the current controlled state of flexible resources. represents the lower limit of the controlled state of the flexible resource, Indicates the upper limit of the controlled state of flexible resources;

[0066] The controlled priority equation of flexible resources is established from the perspective of time. The formula is as follows:

[0067] (19);

[0068] In the formula, Indicator representing the priority of flexible resources controlled from a time perspective, represents the planned end time at which the flexible resource response is controlled, Represents the initial moment when the flexible resource response is controlled.

[0069] Furthermore, in S3, the optimization control objective function construction process includes the following steps:

[0070] Calculate the deviation target in the optimization control, the formula is as follows:

[0071] (20);

[0072] In the formula, represents the deviation target of the optimization control, represents the total control period, represents the response aggregate control deviation of the fixed-frequency heat pump cluster, represents the response aggregate control deviation of the variable frequency heat pump, represents the response aggregate control deviation of the electric water heater cluster, represents the response aggregate control deviation of the EV cluster;

[0073] Calculate the response priority target in the optimization control, the formula is as follows:

[0074] (twenty one);

[0075] In the formula, represents the response priority target of the optimization control, represents the total control period, represents various flexible resources, including heat pumps, electric water heaters, electric vehicles, Indicates the scale of various flexible resources (fixed frequency heat pumps, variable frequency heat pumps, electric water heaters, electric vehicles), Indicates the response power of various flexible resources (fixed frequency heat pump, variable frequency heat pump, electric water heater, electric vehicle), Indicates the priority index of various flexible resources (fixed frequency heat pump, variable frequency heat pump, electric water heater, electric vehicle) from the perspective of status, Indicators indicating the priority of various flexible resources (fixed-frequency heat pumps, variable-frequency heat pumps, electric water heaters, electric vehicles) from a time perspective;

[0076] With the goal of minimizing the deviation between the response power of flexible resources and the target power and optimizing the response controlled balance, the optimization control objective function is established, and the formula is as follows:

[0077] (twenty two);

[0078] In the formula, represents the optimization scheduling target item, represents the deviation target of the optimization control, Represents the response priority target for optimization control.

[0079] Furthermore, in S4, the constraints of the flexible resources include:

[0080] Fixed frequency heat pump: (twenty three);

[0081] Inverter heat pump: (twenty four);

[0082] Electric water heater: (25);

[0083] Electric Vehicles:

[0084] (26);

[0085] Where: represents various flexible resources, including heat pumps, electric water heaters, electric vehicles, Indicates the scale of various flexible resources (fixed frequency heat pumps, variable frequency heat pumps, electric water heaters, electric vehicles), represents the response power of various flexible resources, represents the deviation penalty weight, Indicates the actual operating power of various flexible resources (fixed frequency heat pump, variable frequency heat pump, electric water heater, electric vehicle), represents the charging power of the electric vehicle, Indicates the discharge power of an electric vehicle.

[0086] Furthermore, the deviation penalty weight The value range is .

[0087] Compared with the prior art, the present invention has the following advantages:

[0088] The present application discloses a method for dynamic response of flexible resources in a distribution network based on a priority data model. Flexible resources include fixed-frequency heat pumps, variable-frequency heat pumps, electric water heaters, and electric vehicles. Various types of flexible resources are considered, so that the elastic regulation potential of multiple power loads can be uniformly exerted to meet the response needs of actual multiple heterogeneous flexible resources.

[0089] This application conducts targeted quantitative modeling of flexible resources according to specific participating objects and forms, and considers the control priority of flexible resources, establishes a priority controlled model based on state margin and time margin, takes the minimum deviation between the response power of flexible resources and the target power and the optimal response controlled balance as the goal, establishes an optimization control objective function, determines the constraints of flexible resources, obtains the adjustment demand of flexible resources based on state margin and time margin, distributes the adjustment demand to each flexible resource single response action, fully considers the tendency of flexible resource response state and the balance of response control, conforms to the tendency of flexible resource cluster response adjustment, and realizes the balanced control of flexible resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0090] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0091] Figure 1 It is the overall flow chart of the present invention;

[0092] Figure 2 It is a parameter setting diagram when the present invention is implemented;

[0093] Figure 3 is the response curve of the HPss cluster when the present invention is implemented;

[0094] Figure 4 is the response curve of the HPiv cluster when the present invention is implemented;

[0095] Figure 5 is the response curve of the EWH cluster when the present invention is implemented;

[0096] Figure 6 is the response curve of the EVc cluster when the present invention is implemented;

[0097] Figure 7 It is the response curve of the EVr cluster when the present invention is implemented. DETAILED DESCRIPTION

[0098] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0099] like Figure 1 As shown, this embodiment proposes a distribution network flexible resource dynamic response method based on a priority data model, wherein:

[0100] The flexible resources of the power system are distributed on the power generation side, the grid side and the load side. The flexible resources on the load side are a highly potential demand response resource with good virtual energy storage characteristics. By regulating large-scale flexible resources on the load side and realizing flexible interaction with the grid side, responding to power fluctuations caused by load activities and the volatility, intermittency and uncertainty of renewable energy generation, it can promote the consumption of renewable energy, which is an inevitable requirement for the development of the future power system. Therefore, it is an inevitable requirement for the development of the future power system to establish an optimized control strategy for the flexible resource cluster on the distribution network side and fully tap the dispatch flexibility and dispatch potential of flexible resources, which has important theoretical value and practical significance for promoting the optimized operation of the power grid and the consumption of renewable energy.

[0101] In this embodiment, the flexible resources specifically include fixed-frequency heat pumps, variable-frequency heat pumps, electric water heaters, and electric vehicles.

[0102] The following steps are involved:

[0103] S1: Building a dynamic response model of flexible resources based on the operational characteristics of flexible resources;

[0104] S2: Considering the controlled priority of flexible resources, a priority controlled model based on state margin and time margin is established;

[0105] S3: Establish an optimization control objective function with the goal of minimizing the deviation between the response power of flexible resources and the target power and optimizing the response controlled balance;

[0106] S4: Determine the constraints of flexible resources and solve the model constructed in S1-S3 to determine the reasonable method of adjusting the demand of flexible resources and send it to the flexible resources for execution.

[0107] In S1, flexible resources include heat pumps, electric water heaters, and electric vehicles, among which heat pumps are divided into fixed-frequency heat pumps and variable-frequency heat pumps.

[0108] Heat pump (HP) load elastic resources can adjust their operating power according to the current temperature state of the thermal zone to provide adjustment flexibility for system operation. According to different power adjustment methods, HP can be divided into two types: heat pump driven by singlespeed (HPss) and heat pump driven by inverter (HPiv).

[0109] Specifically, in S1, the modeling of the heat pump model includes the following steps:

[0110] HP modeling includes two parts: regional thermal dynamics and power operation status. For HPss and HPiv, regional thermal dynamics can be characterized by equivalent thermal parameter models.

[0111] Calculate the equivalent thermal parameters of the heat pump model using the following formula:

[0112] ;

[0113] In the formula, Respectively represent the room number of the room. represents the equivalent heat capacity of the building walls and room air, represents the difference time step, Indicates the indoor temperature for the next counting period. Indicates the indoor temperature of the current period. Indicates the outdoor temperature, represents the equivalent thermal resistance of the building wall and air, represents the heat pump thermal power, represents the radiant heat power of the room, is the heat generated in the room;

[0114] HPss maintains the indoor temperature within the set temperature range by adjusting the start and stop of the compressor. Its operating power cannot be adjusted continuously. Taking the cooling background as an example, the operating power calculation formula of the fixed-frequency heat pump is as follows:

[0115] (2);

[0116] ;

[0117] In the formula, Indicates the device serial number. Indicates the electrical power of the fixed-frequency heat pump, Indicates the rated electrical power of the fixed-frequency heat pump. Indicates the operating status of the fixed-frequency heat pump in the current period. It is a binary variable. 1 indicates that the compressor is started, and 0 indicates that the compressor is stopped. Indicates the operating status of the fixed-frequency heat pump in the next counting period. is the permissible temperature deviation, Indicates the current ambient temperature. is the set temperature;

[0118] The variable frequency heat pump relies on the inverter. Considering that its operating power can be continuously adjusted, the operating power constraint equation of the variable frequency heat pump is as follows:

[0119] (4);

[0120] In the formula, Indicates the electrical power of the variable frequency heat pump, Indicates the power upper limit of the variable frequency heat pump. Indicates the lower power limit of the variable frequency heat pump.

[0121] For fixed frequency heat pumps, The calculation formula is as follows:

[0122] (5);

[0123] In the formula, represents the heat pump thermal power, Indicates the operating power of the fixed frequency heat pump. Indicates the operating efficiency coefficient of the fixed-frequency heat pump in the room;

[0124] For variable frequency heat pumps, The calculation formula is as follows:

[0125] (6);

[0126] In the formula, represents the heat pump thermal power, Indicates the operating power of the variable frequency heat pump. Indicates the operating efficiency coefficient of the variable frequency heat pump in the room;

[0127] Under the condition of meeting the expected hot water demand at the time set by the user, the electric water heater (EWH) can adjust its operating power according to the current hot water temperature state to provide adjustment flexibility for system operation without causing significant impact on the user. EWH modeling includes two parts: hot water dynamics and operating power.

[0128] In S1, the modeling process of the electric water heater model includes the following steps:

[0129] Considering the thermodynamic equilibrium law and the equivalent thermal parameter equation, the hot water temperature dynamic equation of the electric water heater is established, and the formula is as follows:

[0130] ;

[0131] In the formula, Indicates the heat capacity of the electric water heater. Indicates the water temperature of the electric water heater in the current period. Indicates the water temperature of the electric water heater in the next counting period. represents the difference time step, Indicates the electrical power of the electric water heater. Indicates the operating efficiency of the electric water heater. represents the thermal disturbance power caused by hot water use, Represents the conduction heat loss of the electric water heater, where: Indicates the indoor temperature. Indicates the equivalent thermal resistance of the electric water heater;

[0132] It should be noted that for ,Considering that EWH operates in an indoor environment, the ,effects of heat convection and heat radiation are small and ,can be ignored in practical applications.

[0133] In the process of providing flexible regulation and response control, in order to meet the hot water demand of users in the specified period, EWH needs to heat the hot water to the desired temperature before the user's concentrated use time. Therefore, the water temperature constraint should also be met, and the water temperature constraint equation is established. The formula is as follows:

[0134] (8);

[0135] (9);

[0136] In the formula, Indicates the inlet water temperature. The water temperature of the electric water heater, Indicates that the user sets the concentrated use time of hot water, and the electric water heater needs to provide hot water that reaches the required temperature before this time. Indicates the upper limit of hot water temperature allowed by the electric water heater. Indicates the desired hot water temperature set by the user;

[0137] Establish the operating power equation of the electric water heater, the formula is as follows:

[0138] (10);

[0139] In the formula, Indicates the lower limit of the operating power adjustment of the electric water heater. Indicates the upper limit of the operating power adjustment of the electric water heater.

[0140] In S1, the modeling process of the electric vehicle model includes the following steps:

[0141] Considering flexible charging and discharging, a mathematical model of the battery state of charge of electric vehicles is established, and the formula is as follows:

[0142] (11);

[0143] In the formula, Indicates the serial number of the electric vehicle. Indicates the SOC state of the electric vehicle in the next period, Indicates the SOC state of the electric vehicle in the current period. represents the charging power of the electric vehicle, represents the charging efficiency of electric vehicles, represents the discharge power of the electric vehicle, represents the discharge efficiency of electric vehicles, represents the difference time step, Indicates the battery capacity of an electric vehicle battery;

[0144] The SOC constraint equation of electric vehicles is established as follows:

[0145] (12);

[0146] In the formula, Indicates the SOC state of the electric vehicle in the current period. It is a binary variable that reflects the availability of electric vehicles. A value of 1 indicates that the electric vehicle is charged at the charging station, and a value of 0 indicates that the electric vehicle is not charged. represents the lower limit of SOC of electric vehicles, Indicates the upper limit of SOC of electric vehicles;

[0147] Establish the charging power constraint equation of electric vehicles and determine the value range of charging power. The formula is as follows:

[0148] (13);

[0149] In the formula, represents the charging power of the electric vehicle, It is a binary variable that reflects the availability of electric vehicles. A value of 1 indicates that the electric vehicle is charged at the charging station, and a value of 0 indicates that the electric vehicle is not charged. It is a binary variable, indicating the charging and discharging status of the electric vehicle, where 1 indicates that the electric vehicle is charging, and 0 indicates that the electric vehicle is discharging. Indicates the upper limit of charging power for electric vehicles;

[0150] Establish the discharge power constraint equation of electric vehicles and determine the range of discharge power. The formula is as follows:

[0151] (14);

[0152] In the formula, represents the discharge power of the electric vehicle, It is a binary variable that reflects the availability of electric vehicles. A value of 1 indicates that the electric vehicle is charged at the charging station, and a value of 0 indicates that the electric vehicle is not charged. It is a binary variable, indicating the charging and discharging status of the electric vehicle, where 1 indicates that the electric vehicle is charging, and 0 indicates that the electric vehicle is discharging. Indicates the upper limit of the discharge power of the electric vehicle;

[0153] Determine the initial state of charge of the electric vehicle, the formula is as follows:

[0154] (15);

[0155] In the formula, represents the initial state of charge of the electric vehicle, is the arrival time of the electric vehicle;

[0156] Determine the expected state of charge of the electric vehicle when it drives away, the formula is as follows:

[0157] (16);

[0158] In the formula, represents the expected state of charge of the electric vehicle when it drives away, is the departure time of the electric vehicle;

[0159] (17);

[0160] In the formula, is the arrival time of the electric vehicle, is the departure time of the electric vehicle.

[0161] The priority of flexible resource control reflects the response control order of resources or the distribution of response adjustment amount. In the control process, flexible resources with high control priority are made to respond as much as possible and respond first, which can improve the balance of flexible resource response control and conform to the control state tendency of flexible resources.

[0162] The operating status indicators of flexible resources, such as the hot zone temperature status of HP flexible resources, the SOC status of EV flexible resources, and the water temperature status of EWH flexible resources, reflect the margin of the power load elasticity of load elastic resources. In S2, the modeling process of the priority controlled model based on the state margin and time margin includes the following steps:

[0163] First, considering the operating status indicators of flexible resources, a unified calculation equation for the controlled priority of various flexible resources is designed from the perspective of status. The formula is as follows:

[0164] (18);

[0165] In the formula, represents various flexible resources, including heat pumps, electric water heaters, electric vehicles, Indicators of flexible resource control priority from a status perspective, Indicates the current controlled state of flexible resources. represents the lower limit of the controlled state of the flexible resource, Indicates the upper limit of the controlled state of flexible resources;

[0166] In addition to the state factors, the response priority of some flexible resources such as EV and EWH is also related to the time margin. Therefore, the control priority equation of flexible resources is established from the time perspective. The formula is as follows:

[0167] (19);

[0168] In the formula, Indicator representing the priority of flexible resources controlled from a time perspective, represents the planned end time at which the flexible resource response is controlled, Represents the initial moment when the flexible resource response is controlled.

[0169] It should be noted that in the controlled priority equation of flexible resources from the time perspective shown above, for EV, Corresponding to the time of driving into charging, Corresponding to the planned departure time. For EWH, Corresponding to the initial controlled moment, Corresponding to the desired temperature setting time.

[0170] In S3, the process of constructing the optimization control objective function includes the following steps:

[0171] Calculate the deviation target in the optimization control, the formula is as follows:

[0172] (20);

[0173] In the formula, represents the deviation target of the optimization control, represents the total control period, represents the response aggregate control deviation of the fixed-frequency heat pump cluster, represents the response aggregate control deviation of the variable frequency heat pump, represents the response aggregate control deviation of the electric water heater cluster, represents the response aggregate control deviation of the EV cluster;

[0174] Calculate the response priority target in the optimization control, the formula is as follows:

[0175] (twenty one);

[0176] In the formula, represents the response priority target for optimization control, represents the total control period, represents various flexible resources, including heat pumps, electric water heaters, electric vehicles, Indicates the scale of various flexible resources (fixed frequency heat pumps, variable frequency heat pumps, electric water heaters, electric vehicles), Indicates the response power of various flexible resources (fixed frequency heat pump, variable frequency heat pump, electric water heater, electric vehicle), Indicates the priority index of various flexible resources (fixed frequency heat pump, variable frequency heat pump, electric water heater, electric vehicle) from the perspective of status, Indicators indicating the priority of various flexible resources (fixed-frequency heat pumps, variable-frequency heat pumps, electric water heaters, electric vehicles) from a time perspective;

[0177] With the goal of minimizing the deviation between the response power of flexible resources and the target power and optimizing the response controlled balance, the optimization control objective function is established, and the formula is as follows:

[0178] (twenty two);

[0179] In the formula, represents the optimization scheduling target item, represents the deviation target of the optimization control, Represents the response priority target for optimization control.

[0180] It should be noted that , as well as The data is calculated periodically and updated in real time. , as well as The data will be saved in sequence to form a set of optimization scheduling targets to be selected. When the optimization scheduling target needs to be determined, the smallest one is selected from the currently saved optimization scheduling target set. The value is used as the final optimization dispatch target and sent to the resource entities under the distribution network for execution.

[0181] In order to achieve the goal of optimizing control deviation Respond to priority targets with optimized control To make the two more compatible, design the deviation penalty weight , ensuring that the optimization control equation takes into account the balance of flexible resource response control while minimizing the control deviation, where the deviation penalty weight It is obtained through empirical analysis and historical data verification, and updated dynamically.

[0182] In S4, the constraints on flexible resources include:

[0183] Fixed frequency heat pump: (twenty three);

[0184] Inverter heat pump: (twenty four);

[0185] Electric water heater: (25);

[0186] Electric Vehicles:

[0187] (26);

[0188] Specifically, in S4, the absolute value constraints shown in the constraints of the flexible resources are linearized to include:

[0189] Fixed frequency heat pump: ;

[0190] ;

[0191] Inverter heat pump:

[0192] ;

[0193] ;

[0194] Electric water heater:

[0195] ;

[0196] ;

[0197] Electric Vehicles:

[0198] ;

[0199] ;

[0200] Where: Represents various flexible resources, including heat pumps, electric water heaters, and electric vehicles. Heat pumps specifically include fixed-frequency heat pumps and variable-frequency heat pumps. Indicates the scale of various flexible resources (fixed frequency heat pumps, variable frequency heat pumps, electric water heaters, electric vehicles), represents the response power of various flexible resources, represents the deviation penalty weight, Indicates the actual operating power of various flexible resources, represents the charging power of the electric vehicle, Indicates the discharge power of an electric vehicle.

[0201] It should be noted that in this embodiment, the deviation penalty weight The value range is .

[0202] The present invention also provides a system for dynamic response of flexible resources based on a priority data model, the system implements a method for dynamic response of flexible resources based on a priority data model, the whole system includes an operation module, a control module and a flexible resource module, specifically, the operation module is a distribution network operator, the distribution network operator, as a market entity, proposes a regulation quantity demand, the control module is a resource management platform, the resource management platform is a software system, which includes the flexible resource dynamic response model proposed in the present invention, the priority controlled model based on state margin and time margin, and can obtain a reasonable method for flexible resource regulation demand by solving and calculating the above models, the flexible resource module is various types of flexible resources managed under the resource management platform, including heat pumps, electric water heaters and electric vehicles.

[0203] Please refer to the attached Figure 2 To Attachment Figure 7 In the specific implementation, an example is constructed and analyzed by taking the IEEE 33-node power distribution system as an example. Considering that the corresponding operating indicators of the load elastic resources such as the occupancy rate, operation rate, entry rate and exit rate determine its flexible response characteristics, the present invention designs five types of small-capacity load elastic resources: residential HPss, residential EWH, commercial HPiv, commercial EV charged at commercial locations (EVc) and residential EV charged at residential locations (EVr). EVc and EVr have the same parameters, but their entry rate and exit rate characteristics are different. The charging power of electric vehicles in commercial areas is designed to be 30kW, corresponding to fast charging. The residential area is designed to be 10kW, corresponding to slow charging. The thermal parameters of HPss, HPiv and EWH all obey normal distribution. The parameter mean and scale settings of each type of small-capacity load elastic resources are shown in the attached figure. Figure 2 The standard deviation is set to 20% of the mean. The temperature deadband of HP is set to , the allowable water temperature of EWH is ,The load elastic resource response cost is set to 40% of the grid electricity price, EVr and EVc are distributed at 23rd and 24th nodes, EWH is distributed at 7th nodes, and HPss and HPiv are distributed at 30th and 31st nodes.

[0204] Please refer to the attached Figure 3 , attached Figure 3 The response aggregate power and corresponding temperature status of the HPss cluster are shown. Before simulation, refer to the attached Figure 2 , the number of individuals in the HPss cluster is set to 200. During the simulation, it can be seen that Figure 3The temperature state image in is an envelope composed of many graphs, each of which represents an individual in the HPss cluster, reflecting that the HPss cluster can adjust the operation of the HPss cluster according to the response power, so that the HPss cluster can maintain the temperature of the hot area where it is located within the set range while providing the required power. At the same time, under the control priority, the temperature state of the HPss cluster will alternately rise or fall during the control process to maintain the balance and fairness of the regulation.

[0205] Please refer to the attached Figure 4 , attached Figure 4 The response aggregate power and corresponding temperature status of the HPiv cluster are shown. Before simulation, refer to the attached Figure 2 , the number of individuals in the HPiv cluster is set to 100. During the simulation, it can be seen that Figure 4 The temperature state image in is an envelope composed of many graphs, each of which represents an individual in the HPiv cluster, reflecting that the HPiv cluster can adjust the operation of the HPiv cluster according to the response power, so that the HPiv cluster can maintain the temperature of the thermal area where it is located within the set range while providing the required power. At the same time, under the control priority, the temperature state of the HPiv cluster will alternately rise or fall during the control process to maintain the balance and fairness of the regulation.

[0206] Please refer to the attached Figure 5 , attached Figure 5 The response aggregate power and corresponding temperature status of the EWH cluster are shown. Before simulation, refer to the attached Figure 2 ,The number of individuals in the EWH cluster is set to 200. During the simulation, it can be seen that Figure 5 The temperature state image in the figure is an envelope composed of many graphs, each of which represents an individual in the EWH cluster, reflecting that under the controlled priority of the EWH cluster, the EWH monomers with different hot water demands will be allocated corresponding response power so that their temperatures will respond in an orderly manner. The hot water temperature of the EWH is moderate within the allowable setting range.

[0207] Please refer to the attached Figure 6-7 , attached Figure 6 The EVc response optimization is shown in Figure 2. Figure 7 The optimized response of EVr is shown. The entry and exit characteristics of EVc and EVr are different, which provides different degrees of adjustment flexibility for the optimal operation of the distribution network. Figure 2 The number of individuals in the EVc cluster is set to 50, and the number of individuals in the EVr cluster is set to 80. During the simulation, it can be seen that the attached Figure 6The SOC image in the figure is an envelope composed of many lines, each of which represents an individual in the EVc cluster. Figure 7 The SOC image in is also an envelope composed of many graphs, each of which represents an individual in the EVc cluster, reflecting that the EVc cluster and the EVr cluster can adjust the operation of the corresponding EV monomer according to the response power, so that the EV cluster can meet the SOC requirements set by the user while providing the required power. At the same time, under the effect of controlled priority, the control method will reasonably control the response power of different EV monomers according to the EV's SOC and departure time, and improve the system's optimized operation level.

[0208] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

Claims

1. A distribution network flexible resource dynamic response method based on a priority data model, characterized in that: The following steps are involved: S1: Building a dynamic response model of flexible resources based on the operational characteristics of flexible resources; S2: Considering the controlled priority of flexible resources, a priority controlled model based on state margin and time margin is established; S3: Establish an optimization control objective function with the goal of minimizing the deviation between the response power of flexible resources and the target power and optimizing the response controlled balance; S4: Determine the constraints of flexible resources, solve the model constructed in S1-S3, and thus determine the reasonable method of adjusting the demand of flexible resources, and send it to the flexible resources for execution; In S1, flexible resources include heat pumps, electric water heaters, and electric vehicles; In S1, the modeling of the heat pump model includes the following steps: Calculate the equivalent thermal parameters of the heat pump model using the following formula: ； In the formula, Respectively represent the room number of the room. represents the equivalent heat capacity of the building walls and room air, represents the difference time step, Indicates the indoor temperature for the next counting period. Indicates the indoor temperature of the current period. Indicates the outdoor temperature, represents the equivalent thermal resistance of the building wall and air, represents the heat pump thermal power, represents the radiant heat power of the room, is the heat generated in the room; Calculate the operating power of the heat pump model. Considering the different power regulation methods, the heat pump model is divided into two types: fixed-frequency heat pump and variable-frequency heat pump. The operating power calculation formula of the fixed-frequency heat pump is as follows: （2）； ； In the formula, Indicates the device serial number. Indicates the electrical power of the fixed-frequency heat pump, Indicates the rated electrical power of the fixed-frequency heat pump. Indicates the operating status of the fixed-frequency heat pump in the current period. It is a binary variable. 1 indicates that the compressor is started, and 0 indicates that the compressor is stopped. Indicates the operating status of the fixed-frequency heat pump in the next counting period. is the permissible temperature deviation, Indicates the current ambient temperature. is the set temperature; The variable frequency heat pump relies on the inverter. Considering that its operating power can be continuously adjusted, the operating power constraint equation of the variable frequency heat pump is as follows: （4）； In the formula, Indicates the electrical power of the variable frequency heat pump, Indicates the power upper limit of the variable frequency heat pump. Indicates the lower power limit of the variable frequency heat pump; For a fixed frequency heat pump, the heat pump thermal power The calculation formula is as follows: （5）； In the formula, represents the heat pump thermal power, Indicates the operating power of the fixed frequency heat pump. Indicates the operating efficiency coefficient of the fixed-frequency heat pump in the room; For variable frequency heat pumps, heat pump thermal power The calculation formula is as follows: （6）； In the formula, represents the heat pump thermal power, Indicates the operating power of the variable frequency heat pump. Indicates the operating efficiency coefficient of the variable frequency heat pump in the room; In S1, the modeling process of the electric water heater model includes the following steps: Considering the thermodynamic equilibrium law and the equivalent thermal parameter equation, the hot water temperature dynamic equation of the electric water heater is established, and the formula is as follows: ； In the formula, Indicates the heat capacity of the electric water heater. Indicates the water temperature of the electric water heater in the current period. Indicates the water temperature of the electric water heater in the next counting period. represents the difference time step, Indicates the electrical power of the electric water heater. Indicates the operating efficiency of the electric water heater. represents the thermal disturbance power caused by hot water use, Represents the conduction heat loss of the electric water heater, where: Indicates the indoor temperature. Indicates the equivalent thermal resistance of the electric water heater; In order to meet the hot water demand of the user during the specified period, a water temperature constraint equation is established, and the formula is as follows: （8）； （9）； In the formula, Indicates the inlet water temperature. The water temperature of the electric water heater, Indicates that the user sets the concentrated use time of hot water, and the electric water heater needs to provide hot water that reaches the required temperature before this time. Indicates the upper limit of hot water temperature allowed by the electric water heater. Indicates the desired hot water temperature set by the user; Establish the operating power equation of the electric water heater, the formula is as follows: （10）； In the formula, Indicates the lower limit of the operating power adjustment of the electric water heater. Indicates the electrical power of the electric water heater. Indicates the upper limit of the operating power adjustment of the electric water heater; In S1, the modeling process of the electric vehicle model includes the following steps: Considering the flexible charging and discharging of electric vehicles, the SOC value of the electric vehicle in the next period is calculated as follows: （11）； In the formula, Indicates the serial number of the electric vehicle. Indicates the SOC state of the electric vehicle in the next period, Indicates the SOC state of the electric vehicle in the current period. represents the charging power of the electric vehicle, represents the charging efficiency of electric vehicles, represents the discharge power of the electric vehicle, represents the discharge efficiency of electric vehicles, represents the difference time step, Indicates the battery capacity of an electric vehicle battery; The SOC constraint equation of electric vehicles is established as follows: （12）； In the formula, Indicates the SOC state of the electric vehicle in the current period. It is a binary variable that reflects the availability of electric vehicles. A value of 1 indicates that the electric vehicle is charged at the charging station, and a value of 0 indicates that the electric vehicle is not charged. represents the lower limit of SOC of electric vehicles, Indicates the upper limit of SOC of electric vehicles; Establish the charging power constraint equation of electric vehicles and determine the value range of charging power. The formula is as follows: （13）； In the formula, represents the charging power of the electric vehicle, It is a binary variable that reflects the availability of electric vehicles. A value of 1 indicates that the electric vehicle is charged at the charging station, and a value of 0 indicates that the electric vehicle is not charged. It is a binary variable, indicating the charging and discharging status of the electric vehicle, where 1 indicates that the electric vehicle is charging, and 0 indicates that the electric vehicle is discharging. Indicates the upper limit of charging power for electric vehicles; Establish the discharge power constraint equation of electric vehicles and determine the range of discharge power. The formula is as follows: （14）； In the formula, represents the discharge power of the electric vehicle, It is a binary variable that reflects the availability of electric vehicles. A value of 1 indicates that the electric vehicle is charged at the charging station, and a value of 0 indicates that the electric vehicle is not charged. It is a binary variable, indicating the charging and discharging status of the electric vehicle, where 1 indicates that the electric vehicle is charging, and 0 indicates that the electric vehicle is discharging. Indicates the upper limit of the discharge power of the electric vehicle; Determine the initial state of charge of the electric vehicle, the formula is as follows: （15）； In the formula, represents the initial state of charge of the electric vehicle, is the arrival time of the electric vehicle; Determine the expected state of charge of the electric vehicle when it drives away, the formula is as follows: （16）； In the formula, represents the expected state of charge of the electric vehicle when it drives away, is the departure time of the electric vehicle; Sure The value of is as follows: （17）； In the formula, is the arrival time of the electric vehicle, is the departure time of the electric vehicle; 2. A method for dynamic response of distribution network flexible resources based on priority data model according to claim 1, characterized in that: In S2, the priority controlled model modeling process based on the state margin and the time margin includes the following steps: Considering the operating status indicators of flexible resources, the controlled priority equation of flexible resources is established from the status perspective. The formula is as follows: （18）； In the formula, represents various flexible resources, including heat pumps, electric water heaters, electric vehicles, Indicators of flexible resource control priority from a status perspective, Indicates the current controlled state of flexible resources. represents the lower limit of the controlled state of the flexible resource, Indicates the upper limit of the controlled state of flexible resources; The controlled priority equation of flexible resources is established from the perspective of time. The formula is as follows: （19）； In the formula, Indicator representing the priority of flexible resources controlled from a time perspective, represents the planned end time at which the flexible resource response is controlled, Represents the initial moment when the flexible resource response is controlled.

3. A method for dynamic response of distribution network flexible resources based on priority data model according to claim 1, characterized in that: In S3, the optimization control objective function construction process includes the following steps: Calculate the deviation target in the optimization control, the formula is as follows: （20）； In the formula, represents the deviation target of the optimization control, represents the total control period, represents the response aggregate control deviation of the fixed-frequency heat pump cluster, represents the response aggregate control deviation of the variable frequency heat pump, represents the response aggregate control deviation of the electric water heater cluster, represents the response aggregate control deviation of the EV cluster; Calculate the response priority target in the optimization control, the formula is as follows: （21）； In the formula, represents the response priority target of the optimization control, represents the total control period, represents various flexible resources, including heat pumps, electric water heaters, electric vehicles, Indicates the scale of various flexible resources (fixed frequency heat pumps, variable frequency heat pumps, electric water heaters, electric vehicles), Indicates the response power of various flexible resources (fixed frequency heat pump, variable frequency heat pump, electric water heater, electric vehicle), Indicates the priority index of various flexible resources (fixed frequency heat pump, variable frequency heat pump, electric water heater, electric vehicle) from the perspective of status, Indicators indicating the priority of various flexible resources (fixed-frequency heat pumps, variable-frequency heat pumps, electric water heaters, electric vehicles) from a time perspective; With the goal of minimizing the deviation between the response power of flexible resources and the target power and optimizing the response controlled balance, the optimization control objective function is established, and the formula is as follows: （22）； In the formula, represents the optimization scheduling target item, represents the deviation target of the optimization control, Represents the response priority target for optimization control.

4. A distribution network flexible resource dynamic response method based on a priority data model according to claim 1, characterized in that: In S4, the constraints of the flexible resources include: Fixed frequency heat pump: (twenty three); Inverter heat pump: (twenty four); Electric water heater: (25); Electric Vehicles: （26）； Where: represents various flexible resources, including heat pumps, electric water heaters, electric vehicles, Indicates the scale of various flexible resources (fixed frequency heat pumps, variable frequency heat pumps, electric water heaters, electric vehicles), represents the response power of various flexible resources, represents the deviation penalty weight, Indicates the actual operating power of various flexible resources (fixed frequency heat pump, variable frequency heat pump, electric water heater, electric vehicle), represents the charging power of the electric vehicle, Indicates the discharge power of an electric vehicle.

5. A method for dynamic response of distribution network flexible resources based on priority data model according to claim 4, characterized in that: The deviation penalty weight The value range is .

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