CN111509716A

CN111509716A - Power grid flexible load control method and device, computer equipment and storage medium

Info

Publication number: CN111509716A
Application number: CN202010441146.5A
Authority: CN
Inventors: 梁哲恒; 陈晓江; 温柏坚; 张金波; 陈敏
Original assignee: Guangdong Power Grid Co Ltd
Current assignee: Guangdong Power Grid Co Ltd
Priority date: 2020-05-22
Filing date: 2020-05-22
Publication date: 2020-08-07

Abstract

The application relates to a power grid flexible load control method, a power grid flexible load control device, computer equipment and a storage medium. The method comprises the following steps: acquiring control parameters of a power grid on flexible load equipment; the flexible load equipment comprises charge and discharge equipment and power consumption equipment; obtaining an original load fluctuation value of the power grid according to the control parameters; updating the original load fluctuation value according to the constraint condition of the power grid to obtain a target load fluctuation value; the target load fluctuation value meets the preset fluctuation value convergence condition; the constraint condition comprises at least one of a charge and discharge electric quantity constraint condition, a charge demand constraint condition and an electricity utilization constraint condition; and determining a target control parameter of the power grid according to the target load fluctuation value, and performing charge and discharge control on charge and discharge equipment and/or performing power utilization control on power consumption equipment by the power supply network according to the target control parameter. By adopting the method, various flexible loads in the power grid can be optimally controlled, the power grid load fluctuation is ensured to be small, and the safe operation of the power grid is ensured.

Description

Power grid flexible load control method and device, computer equipment and storage medium

Technical Field

The application relates to the technical field of power grid regulation and control, in particular to a power grid flexible load control method, a power grid flexible load control device, computer equipment and a storage medium.

Background

With the development of new energy technology, a large amount of solar energy, biomass energy, wind energy, geothermal energy, wave energy, ocean current energy, tidal energy and the like are connected into a power system, so that the dependence of the power system on traditional energy can be reduced, and the problems of resource shortage, climate change and the like in the current energy development can be relieved. In the process of generating power by using new energy, a traditional power grid control method can be adopted, and the load change is tracked through the power generation side for control, so that the rotation standby is provided.

However, due to randomness and fluctuation of new energy power generation, the controlled capability of a power generation side of a power system is easily weakened, especially with the rise of a smart grid, a large number of flexible loads are connected to a user side of the smart grid, the regulation and control of the power grid are greatly influenced, and representatively the system comprises an air conditioner and an electric vehicle, wherein the air conditioner is a high-power consumption device, the electric vehicle is a high-power charging and discharging device, at the moment, a traditional power grid control method is continuously used, the optimal control of the flexible loads such as the air conditioner and the electric vehicle in the power grid is difficult to ensure, the fluctuation of the power grid load is easily caused to be large.

Therefore, the existing power grid control method has the problems that various flexible loads in a power grid are difficult to optimally control, and the power grid load fluctuation is easy to cause.

Disclosure of Invention

In view of the above, it is necessary to provide a power grid flexible load control method, apparatus, computer device and storage medium capable of optimally controlling a flexible load.

A method of grid flexible load control, the method comprising:

acquiring control parameters of the power grid on flexible load equipment; the flexible load equipment comprises charge and discharge equipment and power consumption equipment;

obtaining an original load fluctuation value of the power grid according to the control parameter;

updating the original load fluctuation value according to the constraint condition of the power grid to obtain a target load fluctuation value; the target load fluctuation value meets the preset fluctuation value convergence condition; the constraint condition comprises at least one of a power error constraint condition, a user satisfaction constraint condition, a power balance constraint condition, a voltage constraint condition, a capacity constraint condition, a charging and discharging electric quantity constraint condition, a charging demand constraint condition and a power utilization constraint condition;

and determining a target control parameter of the power grid according to the target load fluctuation value, so that the power grid can perform charge and discharge control on the charge and discharge equipment and/or perform power utilization control on the power consumption equipment according to the target control parameter.

A power grid flexible load control method comprises the steps that flexible load equipment comprises an air conditioner and an electric automobile; the method comprises the following steps:

acquiring control parameters of the power grid on the air conditioner and the electric vehicle;

updating the original load fluctuation value according to the constraint condition of the power grid to obtain a target load fluctuation value; the target load fluctuation value meets the preset fluctuation value convergence condition; the constraint condition comprises at least one of a power error constraint condition, a user satisfaction constraint condition, a power balance constraint condition, a voltage constraint condition, a capacity constraint condition, an electric vehicle charging and discharging constraint condition, a charging demand constraint condition and an air conditioner temperature constraint condition;

and determining a target control parameter of the power grid according to the target load fluctuation value, so that the power grid can perform charge and discharge control on the electric automobile and/or perform power utilization control on the air conditioner according to the target control parameter.

A power grid flexible load control device, the device comprising:

the acquisition module is used for acquiring control parameters of the power grid on the flexible load equipment; the flexible load equipment comprises charge and discharge equipment and power consumption equipment;

the calculation module is used for obtaining an original load fluctuation value of the power grid according to the control parameters;

the iteration updating module is used for updating the original load fluctuation value according to the constraint condition of the power grid to obtain a target load fluctuation value; the target load fluctuation value meets the preset fluctuation value convergence condition; the constraint condition comprises at least one of a power error constraint condition, a user satisfaction constraint condition, a power balance constraint condition, a voltage constraint condition, a capacity constraint condition, a charging and discharging electric quantity constraint condition, a charging demand constraint condition and a power utilization constraint condition;

and the output module is used for determining a target control parameter of the power grid according to the target load fluctuation value, so that the power grid can perform charge and discharge control on the charge and discharge equipment and/or perform power utilization control on the power consumption equipment according to the target control parameter.

A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:

A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:

According to the power grid flexible load control method, the power grid flexible load control device, the computer equipment and the storage medium, the control parameter of the power grid to the flexible load equipment is obtained, the original load fluctuation value of the power grid is obtained according to the control parameter, and the initial value of the power grid flexible load optimization control can be obtained; updating the original load fluctuation value according to the constraint conditions of the power grid to obtain a target load fluctuation value, wherein the updated target load fluctuation value can meet the constraint conditions of power grid charging and discharging electric quantity, charging demand, power utilization and the like, and the obtained target load fluctuation value is an optimal value; and determining target control parameters of the power grid according to the target load fluctuation value, obtaining the optimal target control parameters according to the optimal target load fluctuation value, optimally controlling various flexible loads in the power grid, ensuring that the power grid load fluctuation is small, and ensuring the safe operation of the power grid.

Drawings

FIG. 1 is a diagram of an application scenario of a method for controlling a grid flexible load according to an embodiment;

FIG. 2 is a schematic flow chart of a method for controlling a grid flexible load according to an embodiment;

FIG. 3 is a schematic flow chart of a power grid flexible load control method in another embodiment;

FIG. 4 is a schematic diagram of information interaction of a combined control method for flexible loads of an air conditioner and an electric vehicle in one embodiment;

FIG. 5 is a state transition diagram of a fixed frequency air conditioner in one embodiment;

FIG. 6 is a block diagram of a power grid flexible load control device according to an embodiment;

FIG. 7 is a diagram illustrating an internal structure of a computer device according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

The power grid flexible load control method provided by the application can be applied to the application environment shown in fig. 1. Wherein the power distribution device 102 communicates with the load aggregator device 104 and/or the flexible load device 106 over a network. The power distribution device 102 may be, but is not limited to, various terminals or servers of a power grid regulation center, and the load aggregator device 104 may be, but is not limited to, various terminals or servers of a load aggregator, where the terminals may be a personal computer, a notebook computer, a smart phone, a tablet computer, and a portable wearable device, and the server may be implemented by an independent server or a server cluster formed by a plurality of servers. The flexible load device 106 may be, but is not limited to, various charging and discharging devices (e.g., an electric vehicle), and power consuming devices (e.g., an air conditioner).

In one embodiment, as shown in fig. 2, a method for controlling a grid flexible load is provided, which is illustrated by applying the method to the power distribution equipment 102 in fig. 1, and includes the following steps:

step S210, acquiring control parameters of a power grid for flexible load equipment; the flexible load device comprises a charging and discharging device and a power consumption device.

The control parameters are data of starting and stopping, charging and discharging, power and the like of the flexible load equipment controlled by the power grid.

The charging and discharging device is a device capable of charging or discharging, such as an electric vehicle capable of temporarily storing energy, and the power consuming device is a device consuming power, such as an air conditioner consuming a large amount of power in summer.

In a specific implementation, the power distribution device 102 may record historical load data of a power grid, generate an operation control instruction for the flexible load device according to the historical load data, and send the operation control instruction to the flexible load device, and after receiving the instruction, the flexible load device may perform operation or charging and discharging according to the instruction, and return initial load data, including actual start and stop, actual power consumption, a charging and discharging state, a charging and discharging power, and the like of the flexible load device, to the power distribution device 102.

For example, the historical load data may be a load curve of the past 24 hours, the power distribution equipment 102 may generate an operation control command of an air conditioner and a charge and discharge control command of an electric vehicle according to load data of the same time of yesterday, for example, the air conditioner load in the power grid is 500W and the electric vehicle load is 100W at 22 yesterday, and since the electric vehicle has a temporary energy storage function, the power distribution equipment 102 may transmit a discharge control command to a part of the electric vehicles at 22 days to instruct the electric vehicles to discharge, or transmit an energy-saving operation control command to a part of the air conditioners to instruct the air conditioners to switch to an energy-saving mode to reduce the power supply pressure of the power grid.

And step S220, obtaining the original load fluctuation value of the power grid according to the control parameters.

The original load fluctuation value is an initial value of the load fluctuation of a root node of the feeder line of the power distribution network, and can be a load fluctuation standard deviation.

In specific implementation, a power grid flexible load control optimization model can be established to perform joint optimization control on various flexible load devices in a power grid, and the optimization model comprises an objective function and constraint conditions. Wherein the objective function formula can be

F＝min F₁， (1)

Wherein, F₁Is the standard deviation of the load fluctuation of the root node of the feeder line, and F is the value of the standard deviation of the load fluctuation of the root node of the feeder line, wherein,

wherein J is the total time interval number of research, and J is a time interval index value; p_{con_load,j}Normal load for period j; p_{felx_load,j}The actual value of the flexible load is the j time period;

the average value of the loads of the root nodes of the power distribution network in all time periods is obtained; p_loss,jThe loss of the whole power distribution network layer in the period j.

Wherein, P_{felx_load,j}Can be calculated as

Wherein N is_ev，N_airThe total number of the electric automobile and the total number of the air conditioners are respectively; i, i₂Respectively indexing values of the quantity of the electric automobile and the quantity of the air conditioner; p_chaFor charging electric vehicles, the electric vehicles can be charged with constant power, i.e. charging power P_chaIndependent of time period; u. of_i,jFor the charging state of the electric vehicle, a non-charging state can be represented by 0, and a charging state can be represented by 1; p_{dis_cha}Discharging power for the electric vehicle; v. of_i,jThe electric vehicle is in a discharging state, a non-discharging state can be represented by 0, and a discharging state can be represented by 1; n is a radical of_airThe total number of air conditioners;

for air conditioner i₂The power consumed during time period j. P_loss,jCan be calculated as

Wherein S is_LIs the set of all branches; m and n are respectively the segment head and the segment end of the time interval; p_loss,(m,n),jFor the network loss of m, n branches, the calculation formula can be

Wherein, V_m,j，V_n,jVoltage amplitudes at the first end and the last end of a node m and n branch time interval j are respectively;_m,j，_n,jvoltage phase angles of a node m and a node n at the moment j and the tail end are respectively;_mn,j＝_m,j-_n,jthe difference between the voltage phase angles at the first end and the last end of the branch in the period j; g_m,nIs the real part of the transadmittance between nodes m, n.

Can be calculated as

Obtaining control parameters of air conditioner

And control parameter P of electric vehicle_cha，P_{dis_cha}，v_i,j，u_i,jThen, the control parameters can be input into the formula (3), and the actual value P of the flexible load can be obtained through calculation_{felx_load,j}And is calculated according to the formula (4)

Then calculating a standard deviation F of the load fluctuation of the root node of the feeder line according to a formula (2)₁Changing F to F₁As the original load fluctuation value of the grid.

Step S230, updating the original load fluctuation value according to the constraint condition of the power grid to obtain a target load fluctuation value; the target load fluctuation value meets the preset fluctuation value convergence condition; the constraint condition comprises at least one of a power error constraint condition, a user satisfaction constraint condition, a power balance constraint condition, a voltage constraint condition, a capacity constraint condition, a charging and discharging electric quantity constraint condition, a charging demand constraint condition and a power utilization constraint condition.

And the target load fluctuation value is an optimal value of the load fluctuation value obtained by calculating the power grid flexible load control optimization model.

In specific implementation, the following constraint conditions can be set for the power grid flexible load control optimization model, including the constraint conditions for the power distribution network and the constraint conditions for the flexible load. The constraint conditions for the power distribution network comprise a power error constraint condition, a user satisfaction constraint condition, a power balance constraint condition, a voltage constraint condition and a capacity constraint condition, which are respectively as follows,

a) the power error constraint condition can set that the average error η between the actual power of the flexible load and the operation control command sent by the power distribution network does not exceed a certain threshold, for example, η is less than or equal to 3%, wherein the error calculation formula between the actual power of the flexible load and the operation control command sent by the power distribution network is

Wherein P is_{felx_plan,j}And adjusting the load value after the flexible load is adjusted for the period j, namely the actual power of the flexible load.

b) User satisfaction degree constraint conditions can be set, and user satisfaction degree C can be set_flexNot lower than a certain threshold, e.g. C_flex ³0.8 of, wherein C_flex＝min(C_air,C_ev)，C_evFor electric vehicle load satisfaction, C_airThe air conditioning load satisfaction degree is achieved. The electric vehicle load satisfaction degree can comprise ordered charging satisfaction degree and disordered charging satisfaction degree.

In the satisfaction model of the orderly power utilization electric automobile, electric automobile users participating in orderly power utilization pay most attention to the economy of charging and discharging, the requirement on charging timeliness is low, meanwhile, because the time of accessing a power grid is long, the final battery electric quantity can be generally guaranteed, therefore, the satisfaction model is established for the orderly power utilization users based on the economy of user charging, and according to the power utilization cost of each user, a power utilization satisfaction membership function can be established as

Wherein the content of the first and second substances,

the maximum charge and discharge cost of the ith electric vehicle is obtained;

the minimum charge and discharge cost is the ith electric automobile;

the ordered electricity utilization satisfaction degree of the ith electric automobile is obtained; f_1,iThe charging and discharging cost of the ith electric automobile is obtained.

In the satisfaction model of the electric automobile with disordered power utilization, the electric automobile users participating in disordered power utilization pay most attention to charging timeliness, the requirements on charging cost are low, and a charging mode of 'plug and play' is adopted, so that the satisfaction model is established for the disordered power utilization users based on the charging amount of the users. The out-of-order electricity utilization user satisfaction degree model can be formulated as

Wherein the content of the first and second substances,

the maximum value of the charging capacity of the ith electric automobile;

the minimum value of the charging electric quantity of the ith electric automobile is obtained;

the disorder power utilization satisfaction degree of the ith electric automobile is obtained; SOC_iAnd charging the ith electric automobile.

The load satisfaction degree of the electric automobile can be the average value of all the electric automobile satisfaction degrees, and the formula is

Wherein the content of the first and second substances,

is the ith₁The satisfaction degree of the electric automobile for orderly using the electricity of the electric automobile;

is the ith₂The satisfaction degree of the electric automobile using electricity disorderly; n is a radical of_ordThe quantity of all orderly power-using electric vehicles is calculated; n is a radical of_disThe quantity of all disordered electric vehicles is calculated; n is a radical of_evThe number of all electric vehicles.

In the air conditioner load satisfaction model, the air conditioner load can comprise a fixed-frequency air conditioner and a variable-frequency air conditioner, the fixed-frequency air conditioner can adopt direct start-stop control, and the variable-frequency air conditioner can adopt temperature regulation control.

In the user satisfaction model of the fixed-frequency air conditioner, when the fixed-frequency air conditioner is controlled, the requirement of the user on the temperature needs to be met, namely, the indoor temperature meets the range appointed in advance. The fixed-frequency air conditioner maintains the indoor temperature within a set range by controlling the start and stop of the compressor, and the calculation formula of the continuous start and stop time of the air conditioner in the j time period for the kth group of air conditioner load can be

Wherein, tau_on,k(j) The duration of continuous start-up in the period j; tau is_off,k(j) The duration of continuous shutdown in the period j; s_k(j) Is controlled for period j, when s_k(j) When the value of (1) indicates that the kth group of air conditioners is controlled, i.e., the air conditioners are turned off, when s is_k(j) When the value of (b) is 0, it means that the kth group of air conditioners are not controlled, i.e., the air conditioners are turned on.

In direct load control, τ_offAnd τ_onRespectively corresponding to two restriction conditions. Tau is_offDuring each group of load interruption, the time for each load control cannot be too long and cannot exceed the maximum continuous interruptible time. Tau is_onTo limit frequent start-ups and stops, each group of loads also has minimal continuous run time constraints. Taken together, the following constraints need to be satisfied in implementing direct control

Wherein, tau_on,min，τ_off,maxRespectively a minimum continuous running time and a maximum continuous interruptible time.

According to the fuzzy set theory, a fuzzy membership function is established by utilizing continuous operation time and continuous controlled time, then the satisfaction degree of the user is represented by utilizing the fuzzy membership function, and then the satisfaction degree model formulas of the kth group of loads to the continuous controlled and continuous power supply operation in the j time period are respectively

Wherein, t_off,k,best，t_off,k,maxRespectively setting the k group of loads as the continuous controlled optimal time length and the continuous controlled maximum time length; t is t_off,k(j) The length of time during which the load is continuously controlled for the kth group during period j; t is t_on,k,best，t_on,k,minRespectively supplying power to the kth group of loads for the optimal time length of continuous power supply operation and the minimum time length of continuous power supply operation; t is t_on,k(j) For continuous supply operation of load of kth group during period jA length of time;

the satisfaction degree of the users for the continuous controlled and continuous power supply operation in the j period is respectively given to the kth group load.

The comprehensive satisfaction degree of the user can be expressed by formula

Since the state of the load k is unique (controlled or uncontrolled) at a certain time, the user satisfaction at a certain time is determined by either the controlled duration or the uncontrolled duration. The average satisfaction of the kth group of air conditioning load users over the entire study period during the entire control may be formulated as

In the user satisfaction model of the variable frequency air conditioner, the variable frequency air conditioner adopts temperature regulation control, the set temperature is regulated and adjusted through a load aggregation quotient to change the load size, and therefore, the satisfaction model established based on the user set temperature can be expressed as a formula

Wherein, T_max,kSetting a maximum temperature value for the kth group of variable frequency air conditioners; t is_min,kSetting a minimum temperature value for the kth group of variable frequency air conditioners; t is_best,kIdeally setting a minimum temperature value for the kth group of variable frequency air conditioners; t is_set,kSetting temperature for the jth time period of the kth group of variable frequency air conditioners; c_{var_air,k}(j) The user satisfaction degree of the variable frequency air conditioner is achieved.

The average satisfaction degree formula of the kth group of variable frequency air conditioners in the whole research time period is

Air conditioner load satisfaction degree C_airCan be formulated as

Wherein, C_{fix_air,k}User satisfaction degree of the kth group of fixed-frequency air conditioners; c_{var_air,k}The satisfaction degree of the kth group of variable frequency air conditioners is obtained; n is a radical of_fixThe number of groups is the number of the variable frequency air conditioners; n is a radical of_varThe number of the fixed-frequency air conditioner polymerization groups; n is a radical of_airThe group number is aggregated for all air conditioners.

c) The power balance constraints, active and reactive power balance constraints may be formulated as

Wherein P is_Gm,j，Q_Gm,jRespectively the active power and the reactive power input by the node m in the period j; p_Lm,j，Q_Lm,jRespectively active and reactive loads of a node m in a period j; p_{felx_load} _m,j，Q_{felx_load} _m,jRespectively the active power and the reactive power of the flexible load in the period of j; b is_m,nIs the imaginary part, V, of the transadmittance between nodes m, n_m,j，V_n,jThe voltage amplitudes of the m and n nodes for the j period,_mn,jthe phase angle difference of the nodes m, n in the period j.

d) Voltage constraint, node m voltage V_mCan be formulated as

Wherein the content of the first and second substances,

upper and lower limits, S, respectively, of the voltage at node m_BIs the set of all nodes.

e) The capacity constraint, the line capacity constraint, may be formulated as

Wherein P is_mn,jThe active power flow flowing through the branch m, n in the period j;

and the maximum active power flow of m and n flows through the branch in the period j.

The constraint conditions for the flexible load comprise a charge and discharge electric quantity constraint condition, a charge demand constraint condition, an electricity utilization constraint condition and a user satisfaction constraint condition which are respectively as follows,

f) the charge/discharge capacity constraint condition, for example, the charge/discharge capacity constraint condition of the electric vehicle can be formulated as

Therein, SOC_i,jFor the electric vehicle i at the j time period, η_chaFor charging efficiency η_{dis_cha}To discharge efficiency; j is a function of_i ^bak，j_i ^leaRespectively representing the i-home and the i-home periods of the electric automobile; q_bRepresents the battery capacity, P, of the electric vehicle_chaDenotes the charging power, u_i,jThe value of 1 or 0 respectively represents that the electric automobile i is in a charging state and a non-charging state in the period j; v. of_i,jThe value of 1 or 0 can be taken as well, which respectively indicates that the electric automobile i is in a discharge state and a non-discharge state in the period j, and P_{dis_cha}Represents the electric vehicle discharge power, and deltat represents the scheduling time interval, which is generally set to 15 min.

g) The charging requirement constraint condition of the user can be formulated as

Therein, SOC_i ^leaFor the charge state of the battery when the automobile is away from homeState; SOC_i ^demAnd (5) charging the automobile i.

h) The electrical constraints, e.g. the i-th air conditioning load temperature constraint of a constant-frequency air conditioning user, can be formulated as

Wherein the content of the first and second substances,

the number of states corresponding to the set temperature of the ith group of air conditioners in the period j;

the number of the shutdown states corresponding to the temperature set in the j time period for the ith group of air conditioners;

the number of open states corresponding to the set temperature;

the number of the shutdown states corresponding to the set temperature.

i) User satisfaction constraint

Wherein the content of the first and second substances,

the lower limit of the satisfaction degree of the air conditioner load user is set;

the lower limit of the load satisfaction degree of the electric automobile.

For the power grid flexible load control optimization model, after initial control parameters and an original load fluctuation value (load fluctuation standard deviation) are obtained, the control parameters can be iteratively updated according to a certain updating rule, and the obtained control parameters are enabled to be updatedThe updated value of the control parameter satisfies the constraint of at least one constraint condition, for example, the control parameter may be updated in a certain update direction and update step length, and the power distribution equipment 102 may record the updated value of the control parameter obtained from each update

P_cha，P_{dis_cha}，v_i,j，u_i,jAnd judging whether the updated value of the control parameter meets the constraint condition, if not, discarding, and if so, reserving. The power distribution equipment 102 also inputs the updated values of the control parameters obtained by each updating into formula (2), and calculates the corresponding standard deviation F of the load fluctuation of the root node₁When a fluctuation value convergence condition is satisfied, for example, when the number of iterations reaches a maximum number of iterations 8000, and/or F₁Stopping iteration when the capacity of the node is less than 5%, and F is equal to F₁Can be regarded as a target load fluctuation value; and if the fluctuation value convergence condition is not met, repeating the iteration updating process.

And step S240, determining a target control parameter of the power grid according to the target load fluctuation value, and performing charge and discharge control on charge and discharge equipment and/or performing power utilization control on power consumption equipment by the power supply network according to the target control parameter.

In a specific implementation, after determining the target load fluctuation value, the power distribution equipment 102 may search for a control parameter update value corresponding to the target load fluctuation value according to a control parameter update value recorded before

P_cha，P_{dis_cha}，v_i,j，u_i,jUsing it as target control parameter and according to the target control parameter

Adjusting the power of the air conditioner according to P_chaAnd u_i,jControlling the charging of the electric vehicle according to P_{dis_cha}And v_i,jAnd performing discharge control on the electric automobile. In practical application, the particle swarm optimization can be adoptedAnd solving the power grid flexible load control optimization model by using a chemoalgorithm, and obtaining a target control parameter and a target load fluctuation value by calculating an optimal solution.

According to the power grid flexible load control method, the control parameters of the power grid for the flexible load equipment are obtained, the original load fluctuation value of the power grid is obtained according to the control parameters, and the initial value of the power grid flexible load optimization control can be obtained; updating the original load fluctuation value according to the constraint conditions of the power grid to obtain a target load fluctuation value, wherein the updated target load fluctuation value can meet the constraint conditions of power grid charging and discharging electric quantity, charging demand, power utilization and the like, and the obtained target load fluctuation value is an optimal value; and determining target control parameters of the power grid according to the target load fluctuation value, obtaining the optimal target control parameters according to the optimal target load fluctuation value, optimally controlling various flexible loads in the power grid, ensuring that the power grid load fluctuation is small, and ensuring the safe operation of the power grid.

In one embodiment, the step S230 includes:

step S231, constructing a target function representing the minimum load fluctuation value, and updating the control parameters to obtain updated values of the control parameters;

step S232, if the control parameter update value meets the constraint condition, updating the original load fluctuation value according to the control parameter update value and the target function to obtain a load fluctuation update value;

step S233, judging whether the load fluctuation update value meets the fluctuation value convergence condition;

step S234, if not, returning to the step of updating the control parameters to obtain the updated values of the control parameters;

and step S235, if yes, updating the value according to the load fluctuation to obtain a target load fluctuation value.

F＝min F₁， (1)

the average value of the loads of the root nodes of the power distribution network layer in all time periods is obtained; p_loss,jFor the network loss of the whole power distribution network layer in the period j, the optimization target of the formula (1) is that the standard deviation of the load fluctuation of the root node of the feeder line is minimum, namely the load fluctuation value is minimum. The constraint conditions may include the above-mentioned power error constraint condition, user satisfaction constraint condition, power balance constraint condition, voltage constraint condition, capacity constraint condition, charge/discharge electric quantity constraint condition, charge demand constraint condition, and power utilization constraint condition. After obtaining the initial values of the control parameter and the load fluctuation value, the power distribution equipment may iteratively update the control parameter according to a certain update rule, and make the obtained update value of the control parameter satisfy the constraint of at least one constraint condition, for example, the control parameter may be updated according to a certain update direction and update step length, and the power distribution equipment may record the update value of the control parameter obtained by each update

P_cha，P_{dis_cha}，v_i,j，u_i,jAnd judging whether the updated value of the control parameter meets the constraint condition, if not, discarding, and if so, reserving. The power distribution equipment can input the updated value of the control parameter into the formula (2) and calculate the corresponding standard deviation F of the load fluctuation of the root node₁As the load fluctuation update value, when the load fluctuation update value satisfies the fluctuation value convergence condition, for example, when the number of iterations reaches a maximum number of iterations 8000, and/or F₁Stopping iteration when the capacity of the node is less than 5%, and F is equal to F₁Can be used as a target load fluctuation value; and if the fluctuation value convergence condition is not met, repeating the iteration updating process. In practical application, the particle swarm optimization algorithm can be adopted to solve an optimization model for power grid flexible load control, and target control parameters and target load fluctuation values are obtained by calculating an optimal solution.

In the embodiment, an objective function representing the minimum load fluctuation value is constructed, and the control parameters are updated to obtain the updated values of the control parameters, so that the control parameters can be optimized by taking the load stability of the power grid as an optimization target; if the updated value of the control parameter meets the constraint condition, updating the original load fluctuation value according to the updated value of the control parameter and the target function to obtain an updated value of the load fluctuation, judging whether the updated value of the load fluctuation meets the convergence condition of the fluctuation value, if not, returning to the step of updating the control parameter to obtain the updated value of the control parameter, and continuously searching for the optimal load fluctuation value when the convergence condition of the fluctuation value is not met; if so, updating the value according to the load fluctuation to obtain a target load fluctuation value, so as to obtain an optimal load fluctuation value.

In one embodiment, the step S232 includes: acquiring charge and discharge cost and charge and discharge electric quantity of charge and discharge equipment; obtaining the ordered power utilization satisfaction of ordered power utilization users according to the charge and discharge cost, and obtaining the unordered power utilization satisfaction of unordered power utilization users according to the charge and discharge electric quantity; obtaining the satisfaction degree of a charging and discharging user according to the satisfaction degree of the orderly power utilization and the satisfaction degree of the unordered power utilization; and if the charging and discharging user satisfaction accords with the charging and discharging user satisfaction constraint condition, inputting the control parameter update value into the objective function to obtain a load fluctuation update value.

The charging and discharging device is a device capable of charging or discharging, and can be used as a temporary energy storage device in a power grid to charge at a low peak period of power utilization and discharge at a high peak period, for example, an electric automobile.

The orderly power utilization users are users concerned about the economy of charging and discharging and have low requirements on charging timeliness; the unordered electricity utilization users are users concerned about charging timeliness and have low requirements on charging cost.

In a specific implementation, the charging and discharging user satisfaction degree may include an orderly power utilization satisfaction degree and an unordered power utilization satisfaction degree. Taking an electric automobile as an example, in the ordered power utilization satisfaction model, electric automobile users participating in ordered power utilization pay the most attention to the economy of charging and discharging, the requirement on charging timeliness is low, and meanwhile, because the time of accessing a power grid is long, the final battery electric quantity can be generally guaranteed, so that the satisfaction model is established for the ordered power utilization users based on the economy of user charging, and the power utilization satisfaction membership function can be established according to the power utilization cost of each user as

Wherein the content of the first and second substances,

the maximum charge and discharge cost of the ith electric vehicle is obtained;

the minimum charge and discharge cost is the ith electric automobile;

the ordered electricity utilization satisfaction degree of the ith electric automobile is obtained; f_1,iThe charging and discharging cost of the ith electric automobile is obtained. In the disordered power utilization satisfaction model, the electric vehicle users participating in disordered power utilization pay most attention to charging timeliness, the requirements on charging cost are low, and a charging mode of 'plug and play charging' is adopted, so that the satisfaction model is established for the disordered power utilization users based on the charging amount of the users. The out-of-order electricity utilization user satisfaction degree model can be formulated as

Wherein the content of the first and second substances,

the maximum value of the charging capacity of the ith electric automobile;

the disorder power utilization satisfaction degree of the ith electric automobile is obtained; SOC_iAnd charging the ith electric automobile. The load satisfaction degree of the electric automobile can be the average value of all the electric automobile satisfaction degrees, and the formula is

Wherein the content of the first and second substances,

is the ith₂The satisfaction degree of the electric automobile using electricity disorderly; n is a radical of_ordThe quantity of all orderly power-using electric vehicles is calculated; n is a radical of_disThe quantity of all disordered electric vehicles is calculated; n is a radical of_evThe number of all electric vehicles. The user satisfaction constraint condition of the electric automobile can be

Wherein

If the constraint condition is met, the updated value of the control parameter can be input into the objective function to obtain an updated value of the load fluctuation.

In the embodiment, the charge and discharge cost and the charge and discharge electric quantity of the charge and discharge equipment are obtained; obtaining the ordered power utilization satisfaction of ordered power utilization users according to the charge and discharge cost, and obtaining the unordered power utilization satisfaction of unordered power utilization users according to the charge and discharge electric quantity; obtaining the satisfaction degree of a charging and discharging user according to the satisfaction degree of the orderly power utilization and the satisfaction degree of the unordered power utilization; if the charging and discharging user satisfaction accords with the charging and discharging user satisfaction constraint condition, the control parameter update value is input into the objective function to obtain a load fluctuation update value, so that the charging and discharging control of the power distribution equipment can reach certain user satisfaction.

In an embodiment, the step S232 further includes: acquiring fixed-frequency power utilization parameters and variable-frequency power utilization parameters of power consumption equipment; obtaining the fixed-frequency power utilization satisfaction degree of a fixed-frequency power utilization user according to the fixed-frequency power utilization parameters, and obtaining the variable-frequency power utilization satisfaction degree of a variable-frequency power utilization user according to the variable-frequency power utilization parameters; obtaining the satisfaction degree of a power consumption user according to the satisfaction degree of the fixed-frequency power consumption and the satisfaction degree of the variable-frequency power consumption; and if the power consumption user satisfaction accords with the power consumption user satisfaction constraint condition, inputting the control parameter update value into the objective function to obtain a load fluctuation update value.

Wherein, the power consumption equipment is equipment using power in a power grid, such as an air conditioner; the fixed-frequency power utilization is the power utilization of equipment with unchanged power supply frequency, and the variable-frequency power utilization is the power utilization of equipment with changeable power supply frequency.

The fixed-frequency power utilization parameters can be the starting time and the stopping time of the fixed-frequency air conditioner, and the variable-frequency power utilization parameters can be the set temperature of the variable-frequency air conditioner.

In a specific implementation, the power consumption user satisfaction may include a fixed-frequency power consumption satisfaction of a fixed-frequency power consumption user and a variable-frequency power consumption satisfaction of a variable-frequency power consumption user. Taking an air conditioner as an example, in the fixed-frequency electricity utilization satisfaction model, when the fixed-frequency air conditioner is controlled, the requirement of a user on the temperature needs to be met, namely, the indoor temperature meets the range stipulated in advance. The fixed-frequency air conditioner maintains the indoor temperature within a set range by controlling the start and stop of a compressor, a fuzzy membership function is established by utilizing continuous operation time and continuous controlled time according to a fuzzy set theory, then the satisfaction degree of a user is represented by utilizing the fuzzy membership function, and then the satisfaction degree model formulas of the kth group of loads to the continuous controlled and continuous power supply operation in the j time period are respectively

The comprehensive satisfaction degree of the user can be expressed by formula

In the frequency conversion electricity utilization satisfaction model, the frequency conversion air conditioner adopts temperature regulation control, the set temperature is regulated and adjusted through a load aggregation quotient to change the load size, and therefore, the satisfaction model established based on the set temperature of a user can be expressed as a formula

Power consumption user satisfaction C_airCan be formulated as

The air conditioner user satisfaction constraint condition can be

Wherein the content of the first and second substances,

if the constraint condition is met, the control parameter update value can be input into the objective function to obtain a load fluctuation update value.

In the embodiment, the fixed-frequency power utilization parameters and the variable-frequency power utilization parameters of the power consumption equipment are obtained; obtaining the fixed-frequency power utilization satisfaction degree of a fixed-frequency power utilization user according to the fixed-frequency power utilization parameters, and obtaining the variable-frequency power utilization satisfaction degree of a variable-frequency power utilization user according to the variable-frequency power utilization parameters; obtaining the satisfaction degree of a power consumption user according to the satisfaction degree of the fixed-frequency power consumption and the satisfaction degree of the variable-frequency power consumption; if the satisfaction degree of the power consumption user meets the satisfaction degree constraint condition of the power consumption user, the updated value of the control parameter is input into the objective function to obtain the updated value of the load fluctuation, so that the power consumption of the power consumption equipment by the power distribution equipment can reach certain user satisfaction degree.

In an embodiment, the step S232 further includes: according to the control parameter update value, obtaining the charging power and the discharging power of the charging and discharging equipment and the power consumption power of the power consumption equipment; obtaining a flexible load actual value of the power grid according to the charging power, the discharging power and the power consumption power; obtaining a node load value of the power grid according to the actual value of the flexible load, the conventional load value and the grid loss of the power grid; and performing standard deviation operation on the node load value to obtain a load fluctuation update value.

In specific implementation, the power distribution equipment acquires the control parameter update value of the power consumption equipment

And a control parameter update value P of the charge and discharge device_cha，P_{dis_cha}，v_i,j，u_i,jThe power consumption of the power consuming equipment can then be obtained as

Charging power of the discharging device is P_chau_i,jDischarge power of P_{dis_cha}v_i,jSubstituting the above parameters into equation (3) to obtain the actual value of the flexible load

According to the actual value P of the flexible load_{felx_load,j}Normal load P_{con_load,j}And loss P_loss,jThe node load value P of the root node of the power distribution network can be calculated_loadAnd load average

Are respectively as

P_load＝P_{con_load,j}+P_loss,j+P_{felx_load,j}，

Standard deviation calculation is carried out on the node load value, so that the standard deviation of the load fluctuation of the root node of the feeder line can be obtained

The standard deviation of the feeder root node load fluctuation can be used as a load fluctuation update value.

In this embodiment, the charging power and the discharging power of the charging and discharging device and the power consumption power of the power consumption device are obtained according to the updated value of the control parameter; obtaining a flexible load actual value of the power grid according to the charging power, the discharging power and the power consumption power; obtaining a node load value of the power grid according to the actual value of the flexible load, the conventional load value and the grid loss of the power grid; the load fluctuation updated value is obtained by carrying out standard deviation operation on the node load value, the load fluctuation updated value can be obtained by controlling the parameter updated value in each iteration updating process, and then the iteration is stopped when the load fluctuation updated value meets a certain fluctuation value convergence condition, so that the optimal solution of the target function is obtained.

In an embodiment, the method for controlling a grid flexible load further includes: solving an objective function through a particle swarm optimization method to obtain a aggregator control parameter for the flexible load aggregator; generating an operation control instruction of a flexible load aggregator for the flexible load according to the aggregator control parameter; and sending an operation control command to the flexible load.

In the specific implementation, the power distribution equipment can also solve an objective function under the constraints of a power error constraint condition, a user satisfaction constraint condition, a power balance constraint condition, a voltage constraint condition, a capacity constraint condition, an electric vehicle charging and discharging constraint condition, a charging demand constraint condition and an air conditioner temperature constraint condition through a particle swarm optimization algorithm, the optimal solution of the objective function is a aggregator control parameter given by a flexible load aggregator, and the aggregator can make an operation control plan according to the aggregator control parameter and send an operation instruction to flexible loads such as an air conditioner and an electric vehicle.

For example, through particle swarm optimization operation, the power distribution equipment may send a flexible load operation control scheme to a plurality of flexible load aggregator equipment in communication with the power distribution equipment, and after receiving the operation control scheme, the aggregator equipment may generate a specific flexible load operation scheme according to the operation control scheme and send an operation control instruction to a subscriber. Specifically, the aggregator device may send an air conditioner operation control instruction to a signed air conditioner user for controlling the air conditioner to enter a power saving mode during a power consumption peak period, and the aggregator device may also send a charge and discharge control instruction to the signed electric vehicle user for controlling the electric vehicle to discharge during the power consumption peak period by using a temporary energy storage function of the electric vehicle.

In the embodiment, the objective function is solved by a particle swarm optimization method to obtain the aggregator control parameter for the flexible load aggregator, so that the optimal aggregator control parameter can be obtained; according to the control parameters of the aggregator, the operation control instruction of the flexible load aggregator for the flexible load is generated, and the operation control instruction is sent to the flexible load, so that the air conditioner and the electric vehicle flexible load can be subjected to combined optimal control, the power grid load fluctuation is small, and the safe operation of the power grid is ensured.

In one embodiment, a method for controlling a grid flexible load is provided, which is illustrated by applying the method to the power distribution equipment 102 in fig. 1, and includes the following steps: acquiring control parameters of a power grid on an air conditioner and an electric vehicle; obtaining an original load fluctuation value of the power grid according to the control parameters; updating the original load fluctuation value according to the constraint condition of the power grid to obtain a target load fluctuation value; the target load fluctuation value meets the preset fluctuation value convergence condition; the constraint condition comprises at least one of a power error constraint condition, a user satisfaction constraint condition, a power balance constraint condition, a voltage constraint condition, a capacity constraint condition, an electric vehicle charging and discharging constraint condition, a charging demand constraint condition and an air conditioner temperature constraint condition; and determining a target control parameter of the power grid according to the target load fluctuation value, and performing charge-discharge control and/or power utilization control on the electric automobile and/or the air conditioner by the power supply network according to the target control parameter.

In the specific implementation, the power distribution equipment can record historical load data of a power grid, generate an operation control instruction for the air conditioner according to the historical load data, and send the operation control instruction to the air conditioner, and the air conditioner can operate according to the instruction after receiving the instruction and return initial load data of the air conditioner, including actual start and stop and actual power consumption of the air conditioner, to the power distribution equipment; the power distribution equipment can also generate a charge and discharge control instruction for the electric automobile according to the historical load data, and sends the charge and discharge control instruction to the electric automobile, and after receiving the instruction, the electric automobile can be charged and discharged according to the instruction, and returns initial load data of the electric automobile, including the charge and discharge state and the actual charge and discharge power of the electric automobile, to the power distribution equipment. A power grid flexible load control optimization model can be established, joint optimization control is carried out on air conditioning and electric vehicle flexible load equipment in the power grid, and the optimization model comprises an objective function and constraint conditions. The objective function may use the minimum standard deviation of load fluctuation of the root node of the feeder line as an optimization objective, and the formula may be

F＝min F₁，

The constraint condition can be a power error constraint condition, a user satisfaction constraint condition, a power balance constraint condition, a voltage constraint condition, a capacity constraint condition, a charging and discharging electric quantity constraint condition, a charging demand constraint condition and a power utilization constraint condition. And solving the power grid flexible load control optimization model through iterative updating or particle swarm optimization algorithm to obtain a target load fluctuation value and a target control parameter. The charge and discharge of the electric automobile and the power consumption of the air conditioner are controlled according to the target control parameters, and the optimal control of the flexible load can be realized.

In one embodiment, as shown in fig. 3, a flow diagram of a method for controlling a grid flexible load is provided. In practical application, the power grid flexible load control method can be divided into a power distribution network layer facing a power distribution network and a flexible load control layer facing a flexible load, an upper layer model can be constructed based on the power distribution network layer, a lower layer model can be constructed based on the flexible load control layer, the upper layer model comprises an objective function formula (1), a power error constraint condition, a user satisfaction constraint condition, a power balance constraint condition, a voltage constraint condition and a capacity constraint condition, and the lower layer model comprises the objective function formula (1), an electric vehicle charging and discharging constraint condition, a charging demand constraint condition and an air conditioner temperature constraint condition. Step S310, the power distribution network layer sends an operation control instruction to the flexible load control layer according to the historical load data; s320, establishing a power distribution network layer optimization model and a flexible load control layer optimization model; s330, calculating an objective function of the power distribution network layer optimization model, and formulating each flexible load operation control scheme according to the constraint conditions of the power distribution network layer; s340, formulating each flexible load operation scheme according to each flexible load operation control scheme and the flexible load control layer optimization model; s350, obtaining user satisfaction and a flexible load actual value according to the steps; s360, judging whether the iteration times reach the preset iteration times or meet termination conditions: if so, stopping iteration, and outputting each flexible load operation control scheme, user satisfaction and a flexible load actual value; and if not, returning to the step of calculating the objective function of the optimization model of the power distribution network layer and formulating each flexible load operation control scheme according to the constraint conditions of the power distribution network layer. In the embodiment, the operation control instructions are respectively issued to the electric automobile and the air conditioner load, the actual control result and the user satisfaction degree of the electric automobile and the air conditioner load are obtained, the optimal operation method is obtained through iteration, the demand response technology is utilized, the flexible load meets the requirement of power grid adjustment, the operation of the power grid is optimized, and the safety of the power grid is maintained.

In one embodiment, as shown in fig. 4, an information interaction diagram of a combined control method for flexible loads of an air conditioner and an electric vehicle is provided. The optimization model comprises an objective function and a constraint condition, each flexible load operation control scheme and each flexible load operation scheme are formulated by calculating the objective function of the optimization model of the power distribution network layer and according to the constraint condition of the power distribution network layer and the constraint condition of the flexible load control layer, and the power distribution network layer can send an air conditioner and electric vehicle operation control instruction to the flexible load control layer according to historical load data; after calculating the user satisfaction and the actual value of the flexible load, the flexible load control layer can report the user satisfaction and the actual value of the flexible load to the power distribution network layer, and the power distribution network layer judges whether the preset iteration times are reached or whether the termination condition is met: if so, stopping iteration, and outputting each flexible load operation control scheme, user satisfaction and a flexible load actual value; and if not, returning to the step of calculating the objective function of the optimization model of the power distribution network layer and formulating each flexible load operation control scheme according to the constraint conditions of the power distribution network layer.

In one embodiment, as shown in FIG. 5, a state transition diagram of a fixed-frequency air conditioner is provided, which is obtained based on a thermodynamic model, and the duration of continuous control of the air conditioner cannot be longer than τ_offOtherwise the user's room temperature will be out of limit, therefore, τ_off,maxCan be set as tau in the figure_offI.e. the time required for the temperature in the user's room to rise from the lowest temperature to the highest temperature. Considering only the temperature effect on the user, the shorter the time it is controlled, i.e. τ_off,minIs zero. Duration of continuous operation τ_on,k,bestThe optimum value may be set to τ_onI.e. the length of time the room temperature has dropped from the highest temperature to the lowest temperature. The service life is influenced by frequent start and stop, and tau can be set_on,k,minSize of tau_on,k,best1/3 of (1).

It should be understood that although the various steps in the flow charts of fig. 2-3 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-3 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed in turn or alternately with other steps or at least some of the other steps.

In one embodiment, as shown in fig. 6, there is provided a grid flexible load control device 600, comprising: an obtaining module 602, a calculating module 604, an iterative updating module 606, and an output module 608, wherein:

an obtaining module 602, configured to obtain a control parameter of a power grid for a flexible load device; the flexible load equipment comprises charge and discharge equipment and power consumption equipment;

the calculating module 604 is configured to obtain an original load fluctuation value of the power grid according to the control parameter;

an iteration updating module 606, configured to update the original load fluctuation value according to a constraint condition of the power grid, to obtain a target load fluctuation value; the target load fluctuation value meets the preset fluctuation value convergence condition; the constraint condition comprises at least one of a power error constraint condition, a user satisfaction constraint condition, a power balance constraint condition, a voltage constraint condition, a capacity constraint condition, a charging and discharging electric quantity constraint condition, a charging demand constraint condition and a power utilization constraint condition;

and the output module 608 is configured to determine a target control parameter of the power grid according to the target load fluctuation value, so that the power supply network performs charge and discharge control on the charge and discharge equipment and/or performs power utilization control on the power consumption equipment according to the target control parameter.

In an embodiment, the iteration updating module 606 is further configured to construct an objective function representing the minimum load fluctuation value, and update the control parameter to obtain an updated value of the control parameter; if the control parameter update value meets the constraint condition, updating the original load fluctuation value according to the control parameter update value and the target function to obtain a load fluctuation update value; judging whether the load fluctuation update value meets the fluctuation value convergence condition or not; if not, returning to the step of updating the control parameters to obtain the updated values of the control parameters; if so, updating the value according to the load fluctuation to obtain a target load fluctuation value.

In an embodiment, the iterative update module 606 is further configured to obtain charge and discharge costs and charge and discharge electric quantities of the charge and discharge device; obtaining the ordered power utilization satisfaction of ordered power utilization users according to the charge and discharge cost, and obtaining the unordered power utilization satisfaction of unordered power utilization users according to the charge and discharge electric quantity; obtaining the satisfaction degree of a charging and discharging user according to the satisfaction degree of the orderly power utilization and the satisfaction degree of the unordered power utilization; and if the charging and discharging user satisfaction accords with the charging and discharging user satisfaction constraint condition, inputting the control parameter update value into the objective function to obtain a load fluctuation update value.

In an embodiment, the iterative update module 606 is further configured to obtain a fixed-frequency power utilization parameter and a variable-frequency power utilization parameter of the power consumption device; obtaining the fixed-frequency power utilization satisfaction degree of a fixed-frequency power utilization user according to the fixed-frequency power utilization parameters, and obtaining the variable-frequency power utilization satisfaction degree of a variable-frequency power utilization user according to the variable-frequency power utilization parameters; obtaining the satisfaction degree of a power consumption user according to the satisfaction degree of the fixed-frequency power consumption and the satisfaction degree of the variable-frequency power consumption; and if the power consumption user satisfaction accords with the power consumption user satisfaction constraint condition, inputting the control parameter update value into the objective function to obtain a load fluctuation update value.

In an embodiment, the iterative update module 606 is further configured to update the value according to the control parameter to obtain a charging power and a discharging power of the charging and discharging device and a power consumption power of the power consumption device; obtaining a flexible load actual value of the power grid according to the charging power, the discharging power and the power consumption power; obtaining a node load value of the power grid according to the actual value of the flexible load, the conventional load value and the grid loss of the power grid; and performing standard deviation operation on the node load value to obtain a load fluctuation update value.

In an embodiment, the power grid flexible load control device 600 is further configured to solve an objective function by using a particle swarm optimization method to obtain an aggregator control parameter for a flexible load aggregator; generating an operation control instruction of a flexible load aggregator for the flexible load according to the aggregator control parameter; and sending an operation control command to the flexible load.

In one embodiment, another grid flexible load control device is provided, including: the device comprises an acquisition module, a calculation module, an iteration updating module and an output module, wherein: the acquisition module is used for acquiring control parameters of a power grid for an air conditioner and an electric vehicle; the calculation module is used for obtaining an original load fluctuation value of the power grid according to the control parameters; the iteration updating module is used for updating the original load fluctuation value according to the constraint condition of the power grid to obtain a target load fluctuation value; the target load fluctuation value meets the preset fluctuation value convergence condition; the constraint condition comprises at least one of a power error constraint condition, a user satisfaction constraint condition, a power balance constraint condition, a voltage constraint condition, a capacity constraint condition, an electric vehicle charging and discharging constraint condition, a charging demand constraint condition and an air conditioner temperature constraint condition; and the output module is used for determining a target control parameter of the power grid according to the target load fluctuation value, and performing charge and discharge control and/or power utilization control on the electric automobile and/or the air conditioner by the power supply network according to the target control parameter.

For specific limitations of the power grid flexible load control device, reference may be made to the above limitations of the power grid flexible load control method, which are not described herein again. All or part of each module in the power grid flexible load control device can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, which may be a server. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing the power grid flexible load control data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of grid flexible load control.

In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 7. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless communication can be realized through WIFI, an operator network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a method of grid flexible load control. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.

Those skilled in the art will appreciate that the architecture shown in fig. 7 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is further provided, which includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method embodiments when executing the computer program.

In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims

1. A method for controlling a flexible load of a power grid, the method comprising:

2. The power grid flexible load control method according to claim 1, wherein the updating the original load fluctuation value according to the constraint condition of the power grid to obtain a target load fluctuation value comprises:

constructing a target function representing the minimum load fluctuation value, and updating the control parameters to obtain updated values of the control parameters;

if the control parameter update value meets the constraint condition, updating the original load fluctuation value according to the control parameter update value and the target function to obtain a load fluctuation update value;

judging whether the load fluctuation update value meets the fluctuation value convergence condition or not;

if not, returning to the step of updating the control parameters to obtain the updated values of the control parameters;

and if so, updating the value according to the load fluctuation to obtain the target load fluctuation value.

3. The method of claim 2, wherein the user satisfaction constraints comprise charge and discharge user satisfaction constraints; if the updated value of the control parameter meets the constraint condition, updating the original load fluctuation value according to the updated value of the control parameter and the target function to obtain an updated value of load fluctuation, which comprises:

acquiring charge and discharge cost and charge and discharge electric quantity of the charge and discharge equipment;

obtaining the ordered electricity utilization satisfaction of ordered electricity utilization users according to the charge and discharge cost, and obtaining the unordered electricity utilization satisfaction of unordered electricity utilization users according to the charge and discharge electric quantity;

obtaining the charging and discharging user satisfaction according to the ordered power utilization satisfaction and the unordered power utilization satisfaction;

and if the charging and discharging user satisfaction accords with the charging and discharging user satisfaction constraint condition, inputting the control parameter update value into the objective function to obtain the load fluctuation update value.

4. The method of claim 2, wherein the user satisfaction constraints further comprise power consumption user satisfaction constraints; if the updated value of the control parameter meets the constraint condition, updating the original load fluctuation value according to the updated value of the control parameter and the target function to obtain an updated value of load fluctuation, and further comprising:

acquiring a fixed-frequency power utilization parameter and a variable-frequency power utilization parameter of the power consumption equipment;

obtaining the fixed-frequency power utilization satisfaction degree of a fixed-frequency power utilization user according to the fixed-frequency power utilization parameters, and obtaining the variable-frequency power utilization satisfaction degree of a variable-frequency power utilization user according to the variable-frequency power utilization parameters;

obtaining power consumption user satisfaction according to the fixed frequency power consumption satisfaction and the variable frequency power consumption satisfaction;

and if the power consumption user satisfaction accords with the power consumption user satisfaction constraint condition, inputting the control parameter update value into the objective function to obtain the load fluctuation update value.

5. The method of claim 2, wherein said updating said original load fluctuation value based on said updated control parameter value and said objective function to obtain an updated load fluctuation value comprises:

according to the control parameter update value, obtaining the charging power and the discharging power of the charging and discharging equipment and the power consumption power of the power consumption equipment;

obtaining a flexible load actual value of the power grid according to the charging power, the discharging power and the power consumption power;

obtaining a node load value of the power grid according to the actual value of the flexible load, the conventional load value and the grid loss of the power grid;

and performing standard deviation operation on the node load value to obtain the load fluctuation update value.

6. The grid flexible load control method according to claim 2, further comprising:

solving the objective function through a particle swarm optimization method to obtain a aggregator control parameter for the flexible load aggregator;

generating an operation control instruction of the flexible load aggregator for the flexible load according to the aggregator control parameter;

and sending the operation control instruction to the flexible load.

7. The power grid flexible load control method is characterized in that flexible load equipment comprises an air conditioner and an electric vehicle; the method comprises the following steps:

8. A grid flexible load control device, the device comprising:

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.