A self-peak control method for terminal distribution network in surplus power off-grid mode

Abstract

The present invention discloses a self-peaking control method in a mode where surplus power is not connected to the grid in a terminal distribution network, which belongs to the field of power system control and includes the following steps: in response to receiving a dispatching instruction, a peak-shaving instruction and a frequency modulation instruction from a superior power grid, the response states of distributed power sources, demand-side resources and energy storage devices in the distribution network are adjusted by self-peaking control under three time scales; according to the adjustment result, the return peak problem of the operation and control platform of the terminal distribution network when performing power return of the PCC node is eliminated to ensure that surplus power is not connected to the grid at any time. The present invention enables the terminal distribution network to ensure that the active power of the PCC point is not less than 0, and the surplus power is always controlled not to be connected to the grid, under the premise of responding to the dispatching instruction, the peak-shaving instruction and the frequency modulation instruction. The present invention fills the gap in the control method of the terminal distribution network in the mode where surplus power is not connected to the grid.

Description

Technical Field

[0001] The present invention relates to the field of power system control, and in particular to a self-peak regulation control method in a terminal distribution network surplus power off-grid mode. Background Art

[0002] At present, the proportion of new energy in the new power system is increasing, and the flexibility demand of the power grid is increasing. Aggregating the adjustable resources of the terminal distribution network to participate in the regulation of the large power grid is an effective measure to alleviate the contradiction of the shortage of flexible resources in the power grid. In the process of the terminal distribution network calling on the adjustable resources to participate in responding to the peak and frequency regulation instructions of the large power grid, its active power regulation demand at different time scales will change. "Self-generation and self-use, surplus power is not connected to the grid" is one of the common operating modes of the terminal distribution network. When the terminal distribution network works in the surplus power is not connected to the grid mode, the fluctuation of wind and solar power output within the second time scale will cause the power return of the tie line node, which may trigger the "reverse power protection" mechanism of the PCC node, causing the terminal distribution network to stop operating.

[0003] Aggregating the flexibility resources of the power system to respond to peak-shaving and frequency regulation is a current research hotspot. The main research direction is to dispatch the adjustable resources aggregated within the large power grid, such as wind, solar and storage integrated stations, commercial central air-conditioning loads, and electric vehicles-charging piles, in order to respond to the peak-shaving and frequency regulation instructions of the large power grid. However, the research mainly focuses on aggregating the flexibility resources within the power grid to respond to peak-shaving and frequency regulation instructions, without further exploring the flexibility resources of the subordinate distribution network.

[0004] At present, there are many related studies on the active power optimization control of terminal distribution networks at home and abroad. For example, the active power dispatching strategy is decomposed into four links: day-ahead plan, rolling plan, real-time dispatching plan and AGC control, and the uncertain impact of large-scale wind power access on the power system is reduced step by step; there are also studies that take the optimal economic operation of the system as the goal of the day-ahead plan, and the intraday plan adopts rolling optimization and feedback correction strategies to adjust the wind and solar load output to ensure the minimum deviation between the PCC node power and the energy storage state of charge (SOC). For example, in view of the uncertainty of source and load, a multi-time scale rolling dispatching optimization model is constructed by generating a typical scenario set at different time scales, and the optimal response strategy is obtained by combining the stochastic MPC method. However, these studies all optimize active power from the perspective of the distribution network's own interests, and do not consider the optimization problem from the perspective of the distribution network's participation in the regulation of the large power grid; in addition, the minimum time scale of the above optimization is only at the minute level, and the power backfeed problem caused by wind and solar fluctuations at the second time scale of the AGC control command execution is not noticed.

[0005] Therefore, for the terminal distribution network working in the surplus power off-grid mode, an adaptive self-peak control mode is proposed to realize peak regulation, frequency regulation, and surplus power off-grid control on a second time scale. This is of great significance for making full use of the flexibility resource regulation potential in the distribution network and ensuring the safe and stable operation of the new power system. Summary of the invention

[0006] In order to solve the above problems, the purpose of the present invention is to provide a self-peak control method in the terminal distribution network surplus power not online mode, aiming to solve the problem of lack of "surplus power not online" control in the existing control technology of the terminal distribution network.

[0007] In order to achieve the above technical objectives, the present application provides a method for self-peak load regulation in a terminal distribution network surplus power off-grid mode, comprising the following steps:

[0008] In response to receiving dispatching instructions, peak load regulation instructions and frequency regulation instructions from the upper power grid, the response state of distributed power sources, demand-side resources and energy storage devices in the distribution network is adjusted through self-peak load regulation control at three time scales;

[0009] According to the adjustment results, the return peak problem of the operation and control platform of the terminal distribution network when performing power return of the PCC node is eliminated to ensure that the surplus power is not connected to the grid at any time.

[0010] Preferably, in the process of self-peak control, the self-peak control of three time scales includes: the first time scale is 15min~1h time scale of self-peak control in response to scheduling instructions and peak-shaving instructions, the second time scale is 3min~5min time scale of self-peak control in response to AGC frequency modulation instructions, and the third time scale is 0.5s~1s time scale of self-peak control.

[0011] Preferably, in the process of executing the self-peak-shaving control when responding to the scheduling instruction and the peak-shaving instruction at the first time scale, the first objective function of the self-peak-shaving control corresponding to the first time scale is:

[0012]

[0013] In the formula, C DR , C ess , C W , C PV , C PCC are the demand-side response cost coefficient, energy storage charging and discharging cost coefficient, wind and solar abandonment penalty cost coefficient, and electricity purchase price from the large power grid; P DR (t) is the demand side response amount; P ess (t) is the energy storage charging and discharging power, P ess,c (t) is negative, when discharging, P ess,d (t) is positive; Forecast output of wind and solar power units, P W (t), P PV (t) is the actual output of the wind and solar power unit; P PCC (t) is the power of the PCC node in the terminal distribution network; T1 is the total time period of the peak load response; k1 is the deviation penalty coefficient of the distribution network tracking the PCC node power plan during peak load; P PCC,p (t) is the planned power value of the PCC node in the terminal distribution network during peak load regulation.

[0014] Preferably, in the process of constructing the first objective function, the constraint condition of the first objective function is:

[0015] Power balance constraints:

[0016] P PV (t)+P W (t)+P ess (t)+P PCC (t) = P load (t),

[0017] P load (t) = P load,D (t)+P DR (t),

[0018] Where: P load,D (t) is the fixed load;

[0019] Transmission power limit of tie line:

[0020]

[0021] Where: is the maximum power allowed by the tie line; since power reverse transmission is not allowed, P PCC (t)≥0;

[0022] Unit output constraints:

[0023]

[0024] The output of wind and solar power units cannot exceed their maximum and minimum values;

[0025] Demand-side response constraints:

[0026]

[0027] Where: The lower and upper limits of the load call volume for demand-side response;

[0028] Energy storage related constraints:

[0029]

[0030] Where: are the maximum charge and discharge powers respectively.

[0031]

[0032] SOC min <SOC(t)<SOC max ,

[0033] Where: SOC min and SOC max are the lower and upper limits of energy storage SOC respectively; η d and η c are discharge efficiency and charging efficiency respectively; E is the total capacity of the energy storage device.

[0034] Preferably, during the period of responding to the peak load instruction, the part of the PCC node power exceeding the peak load in the daily scheduling plan should be adjusted down to the peak load, and the part not exceeding the peak load should be executed according to the original daily scheduling plan, and the expression is:

[0035]

[0036] Where P PCC,p (t) is the power plan value of the PCC node in the terminal distribution network after responding to the peak load instruction, P PS For peak value adjustment, P PCC,r (t) is the planned power value of the PCC node in the terminal distribution network in the intraday dispatch plan.

[0037] Preferably, in the process of executing the self-peak control in response to the AGC frequency modulation instruction at the second time scale, the second objective function of the self-peak control corresponding to the second time scale includes:

[0038]

[0039] Where: C W , C PV , C DR , C ess are the power adjustment cost coefficients of wind turbines, photovoltaic units, demand-side response, and energy storage equipment; ΔP W (t), ΔP PV (t), ΔP DR (t), ΔP ess (t) are the secondary frequency regulation power adjustment of wind turbines, photovoltaic units, demand-side response, and energy storage equipment respectively; k2 is the deviation penalty coefficient of the distribution network tracking the PCC node power plan during frequency regulation; T2 is the total response frequency regulation period; P PCC,t(t) is the power plan value of the PCC node of the terminal distribution network after responding to the frequency modulation instruction, wherein the constraints of the second objective function are the same as the constraints of the first objective function.

[0040] Preferably, in response to executing the self-peak control of the first time scale and the second time scale, when the wind, solar and energy storage output can meet the load requirements, the PCC node dead-zone power is set as the trigger condition for the self-peak control of the third time scale, and the wind and solar unit output and the energy storage charging power are adjusted in real time, and the PCC node power is controlled to always track the planned value and the adjustment value, wherein the PCC node dead-zone power is determined based on the ultra-short-term prediction error of the wind and solar output and the load.

[0041] Preferably, in the process of executing the self-peak control of the third time scale, by predicting the output of the controllable units in the future limited time domain, and selecting the PCC node power of the terminal distribution network as the output variable, according to the power balance constraint of the first time scale, the predicted value corresponding to the PCC node power is obtained;

[0042] The PCC node power plan value output by the self-peak control at the first time scale and the second time scale is selected as the reference target, and the optimization target of the self-peak control model at the third time scale is set to minimize the PCC node power correction deviation, where the optimization objective function is:

[0043]

[0044] Where Y%(k+i) is the upper layer optimized PCC node power tracking value at the future k+i moment, and M is the prediction step size.

[0045] Preferably, in the process of performing the self-peaking control at the third time scale, the constraints of the self-peaking control at the third time scale include:

[0046] Controllable unit output constraints:

[0047]

[0048] Where: P max (k+i) and P min (k+i) are the maximum and minimum output power of wind and solar generators and energy storage, respectively;

[0049] Energy storage SOC constraints:

[0050]

[0051] Where: and They are respectively the upper and lower limits of the energy storage SOC constrained by the upper-level scheduling.

[0052] Preferably, in the process of executing the self-peak control of the third time scale, the optimization objective function is solved by the sequential quadratic programming method, and the control variable sequence of the future M time periods is used. The first column vector in the sequence is sent down to calculate the active output of the wind and solar power units and energy storage in the distribution network at time k+1. Through the feedback correction method, the current actual wind and solar power output and energy storage power are used as the initial values ​​of the next round of rolling optimization to reduce the uncertainty caused by the wind and solar power output.

[0053] The present invention discloses the following technical effects:

[0054] The present invention enables the terminal distribution network to ensure that the active power of the PCC point is not less than 0 under the premise of responding to the dispatching instruction, the peak load regulation instruction and the frequency regulation instruction, and always controls the surplus power not to be connected to the Internet. The present invention makes up for the lack of a control method for the terminal distribution network in the surplus power not to be connected to the Internet mode.

[0055] The present invention realizes the response control of the terminal distribution network under the constraints of the dispatching instructions, peak-shaving instructions and frequency modulation instructions through the terminal distribution network, thus filling the gap of the terminal distribution network participating in the power grid control. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0057] Figure 1 It is a self-peak control framework diagram in the terminal distribution network surplus power off-grid mode described in the present invention;

[0058] Figure 2 This is the self-peak control flow chart of the present invention. DETAILED DESCRIPTION

[0059] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0060] like Figure 1-2 As shown, the overall framework of the self-peak control method in the terminal distribution network surplus power off-grid mode provided by the present invention is as follows: Figure 1 shown.

[0061] The present invention provides a self-peak-shaving control method in a terminal distribution network surplus power off-grid mode, and provides a method for the control software of the terminal distribution network operation and control platform, aiming to solve the problem of lack of "surplus power off-grid" control in the existing control technology of the terminal distribution network, so that the terminal distribution network can ensure that the active power of the PCC point is not less than 0 under the premise of responding to dispatching instructions, peak-shaving instructions and frequency regulation instructions.

[0062] The self-peak regulation control in the terminal distribution network surplus power off-grid mode is implemented by multi-time active power optimization control, that is:

[0063] (1) Self-peak load control in response to dispatching instructions and peak load instructions on a time scale of 15 minutes to 1 hour

[0064] On a time scale of 15min-1h, the terminal distribution network, based on the intraday dispatch plan and short-term wind and solar load forecast data, calls on demand-side response resources, adjusts the energy storage charging and discharging power and the output of wind and solar units, realizes active power optimization control during the peak-shaving period, controls the PCC nodes to execute according to the peak-shaving instructions, and prevents the surplus power from being connected to the grid.

[0065] The total cost of terminal distribution network operation is taken as the target. In order to respond to the "dual carbon" goal and increase the new energy consumption rate, the penalty cost of wind and solar abandonment is added to the total cost of terminal distribution network operation. By adjusting the output of wind and solar units, demand-side response and energy storage charging and discharging, the power generation and consumption of wind and solar units can be maximized. During the self-peak control process, when the output fluctuation of wind and solar units causes the power of the PCC node to be unstable, it should be as close to the target value as possible. Therefore, the deviation between the PCC node power and the target value is converted into a penalty cost and included in the optimization target. The objective function is as follows:

[0066]

[0067] Where: C DR , C ess , C W , C PV , C PCC are the demand-side response cost coefficient, energy storage charging and discharging cost coefficient, wind and solar abandonment penalty cost coefficient, and electricity purchase price from the large power grid; P DR (t) is the demand side response amount; P ess (t) is the energy storage charging and discharging power, P ess,c (t) is negative, when discharging, P ess,d (t) is positive; Forecast output of wind and solar power units, P W(t), P PV (t) is the actual output of the wind and solar power unit; P PCC (t) is the power of the PCC node in the terminal distribution network; T1 is the total time period of the peak load response; k1 is the deviation penalty coefficient of the distribution network tracking the PCC node power plan during peak load; P PCC,p (t) is the planned power value of the PCC node in the terminal distribution network during peak load regulation.

[0068] During the period of responding to the peak load instruction, the part of the PCC node power exceeding the peak load in the daily scheduling plan should be adjusted down to the peak load, and the part not exceeding should be executed according to the original daily scheduling plan. The expression is:

[0069]

[0070] Where P PCC,p (t) is the power plan value of the PCC node in the terminal distribution network after responding to the peak load instruction, P PS For peak value adjustment, P PCC,r (t) is the planned power value of the PCC node in the terminal distribution network in the intraday dispatch plan.

[0071] The constraints are:

[0072] 1) Power balance constraints

[0073] P PV (t)+P W (t)+P ess (t)+P PCC (t) = P load (t), (3)

[0074] P load (t) = P load,D (t)+P DR (t), (4)

[0075] Where: P load,D (t) is the fixed load.

[0076] 2) Transmission power limit of tie line

[0077]

[0078] Where: is the maximum power allowed by the tie line; since power reverse transmission is not allowed, P PCC (t)≥0.

[0079] 3) Unit output constraints

[0080]

[0081] The output of wind and solar power units cannot exceed their maximum and minimum values.

[0082] 4) Demand-side response constraints

[0083]

[0084] Where: The lower and upper limits of the demand-side response load call amount.

[0085] 5) Energy storage related constraints

[0086]

[0087] Where: are the maximum charge and discharge powers respectively.

[0088]

[0089] SOC min <SOC(t)<SOC max , (10)

[0090] Where: SOC min and SOC max are the lower and upper limits of energy storage SOC respectively; η d and η c are discharge efficiency and charging efficiency respectively; E is the total capacity of the energy storage device.

[0091] (2) Self-peak control in response to AGC frequency modulation instructions in a 3- to 5-minute time scale

[0092] On a time scale of 3min-5min, the terminal distribution network controls the frequency and standby of wind and solar power units, demand-side resources, and energy storage equipment based on the self-peak control results at the intraday dispatch plan or peak-shaving time scale, as well as short-term wind and solar load forecast data. This achieves active power optimization control during the frequency regulation period, controls the PCC nodes to execute according to the frequency regulation instructions, and prevents the surplus power from being connected to the grid.

[0093] The goal is to minimize the regulation cost of each unit. The power deviation of the PCC node after receiving the frequency regulation command is converted into a penalty cost and included in the objective function. The objective function is as follows:

[0094]

[0095] Where: C W , C PV , C DR , C ess are the power adjustment cost coefficients of wind turbines, photovoltaic units, demand-side response, and energy storage equipment; ΔP W (t), ΔP PV (t), ΔPDR (t), ΔP ess (t) are the secondary frequency regulation power adjustment of wind turbines, photovoltaic units, demand-side response, and energy storage equipment respectively; k2 is the deviation penalty coefficient of the distribution network tracking the PCC node power plan during frequency regulation; T2 is the total response frequency regulation period; P PCC,t (t) is the planned power value of the PCC node in the terminal distribution network after responding to the frequency regulation command.

[0096] The terminal distribution network responds to the AGC frequency modulation command and needs to ensure that the PCC node power is adjusted according to the allocated frequency modulation command under the constraint of formula (2), that is,

[0097] P PCC,t (t) = P PCC,p (t)-ΔP FR , (12)

[0098] In the formula, ΔP FR It is the frequency modulation instruction, that is, the power that the terminal distribution network needs to adjust.

[0099] The constraints are:

[0100] The power balance constraint, interconnection line transmission power constraint, wind and solar power unit output constraint, demand side response constraint, and energy storage related constraints are the same as equations (3) to (10).

[0101] (3) Self-adjusting peak control on a time scale of 0.5 to 1 s

[0102] When executing the first two levels of self-peak control, when the wind and solar storage output can meet the load requirements, the power of the terminal distribution network PCC node will be close to 0. In order to avoid power return due to instantaneous fluctuations of wind and solar, the dead zone power of the PCC node can be set. When the self-peak control is triggered at the second level, the output of wind and solar power units and energy storage charging power are adjusted in real time to control P PCC (t) Always track the planned value and the adjusted value. The dead zone power of the PCC node can be determined based on the ultra-short-term forecast error of wind and solar power output and load.

[0103] The self-peak control of this layer performs rolling correction with a period of 0.5 to 1s, so that the PCC node power always tracks the output results of the first two layers of self-peak control, and controls the surplus power not to be connected to the grid. It is mainly divided into three parts: prediction model, optimization target and solution, and feedback correction.

[0104] The prediction model is to achieve the output prediction of controllable units (i.e. wind and solar units and energy storage) within a limited time domain in the future by establishing an ultra-short-term prediction model:

[0105]

[0106] Δu(k+t|k)=[ΔPPV (k+t|k),ΔP W (k+t|k),ΔP ess (k+t|k)], (14)

[0107] Where: P(k+i|k) is the active output value of the controllable unit predicted at time k+i in the future; P0(k) is the initial value of the controllable unit output, which is obtained by actual measurement; Δu(k+t|k) is the active increment in the future [k+(t-1), k+t] period predicted at time k, which is the control variable to be optimized; M is the prediction step size.

[0108] The PCC node power of the terminal distribution network is selected as the output variable:

[0109] Y(k+t|k)=[P PCC (k+t|k)], (15)

[0110] According to the power balance equation (3), the predicted value corresponding to the PCC node power is obtained:

[0111]

[0112] Where P PCC (k+i|k) is the power of the PCC node in the distribution network predicted at time k+i in the future; P PCC (k) is the measured PCC node power at time k; ΔP load (k+t|k) is the ultra-short-term predicted power increment of the load in the future [k+t-1, k+t] period; I is the unit vector; Δu T (k+t|k) is the column vector of the output change of each controllable unit at the future k+i moment predicted at the k moment.

[0113] The optimization goal and solution are to select the PCC node power plan value output by the first two layers of self-peak control as the reference target. The optimization goal of the self-peak control model at the second time scale is to minimize the PCC node power correction deviation. A rolling optimization model is established, and the objective function is as follows:

[0114]

[0115] Where: Optimize PCC node power tracking value for upper layers.

[0116] The constraints that need to be met are as follows:

[0117] 1) Output constraints of controllable units

[0118]

[0119] Where: Pmax (k+i) and P min (k+i) are the maximum and minimum output powers of wind and solar generators and energy storage, respectively.

[0120] 2) Energy storage SOC constraints

[0121]

[0122] Where: and They are respectively the upper and lower limits of the energy storage SOC constrained by the upper-level scheduling.

[0123] The sequential quadratic programming method is used to solve equation (17) to obtain the control variable sequence for the next M time periods:

[0124] [Δu T (k+1|k),Δu T (k+2|k),...,Δu T (k+M|k)], (20)

[0125] The first column vector in the sequence is sent down to find the active output of wind and solar power generators and energy storage in the distribution network at time k+1:

[0126] P(k+1|k)=P0(k)+Δu T (k+1|k), (21)

[0127] The feedback correction mentioned above means that due to the prediction error of wind and solar power output, the control variable output issued in advance during the rolling optimization may deviate from the actual value, and a feedback correction link needs to be added. The current actual wind and solar power output and energy storage power are used as the initial values ​​of the next round of rolling optimization to reduce the uncertainty caused by wind and solar power output, so that the new round of prediction values ​​are more in line with reality, thereby achieving higher accuracy, that is:

[0128] P0(k+1)=P r (k+1), (22)

[0129] Where: P r (k+1) is the actual output value at time k+1 obtained through actual measurement after the predicted output value at time k is sent; P0(k+1) is the initial output value of the unit at time k+1.

[0130] Depending on whether the terminal distribution network responds to the dispatch plan, peak load regulation instruction and frequency regulation instruction, in the above time scale control objective function, it is seen that changes occur according to specific scenarios, specifically:

[0131] 1) If there is no response to the dispatch plan and peak load instructions, there is no control of objective function (1);

[0132] 2) If there is no response to the frequency modulation command, there is no control of the objective function (11).

[0133] The self-peak control process is as shown in the attached Figure 2 Specifically:

[0134] 1) When the terminal distribution network responds to the peak load regulation instruction, self-peak load regulation control is carried out on a time scale of 15min-1h. With the goal of minimizing the total cost of system operation, the PCC node power plan and wind, solar, load and storage output plan after the response are solved and output.

[0135] 2) When the terminal distribution network responds to the frequency regulation command, self-peak regulation control is performed on a time scale of 3min-5min, with the goal of minimizing the adjustment cost of each unit, and the PCC node power plan and wind, solar, load and storage output plan after the response are solved and output.

[0136] 3) According to the upper optimization results, when Trigger the self-peak control work on a time scale of seconds, use the prediction model to obtain the predicted value within the optimization period as the input; use the actual system value measured at the current moment as the initial value.

[0137] 4) Establish the output increment of wind-solar units and energy storage equipment as the control variable, and the PCC node power as the output variable.

[0138] 5) Taking the upper-level scheduling instruction result as the reference value and minimizing the correction deviation as the optimization goal, the control variable sequence for the future M time periods is optimized and solved.

[0139] 6) Send the first control variable sequence and calculate the output of the controllable unit at time k+1.

[0140] 7) Take the actual value of the controllable unit at time k+1 as the initial value of the optimization model, return to step 4, and perform a new round of optimization.

[0141] 8) When When the rolling optimization stops, the system continues to perform optimization scheduling according to the upper-level control results.

[0142] Compared with the existing methods, the present invention provides a terminal distribution network self-peak control method, which ensures that the active power of the PCC point is not less than 0 and always controls the surplus power not to be connected to the Internet under the premise of responding to the dispatching instruction, peak-shaving instruction and frequency modulation instruction. The method of the present invention makes up for the lack of control methods of the terminal distribution network in the surplus power not to be connected to the Internet mode.

[0143] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0144] In the description of the present invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0145] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A self-peak control method in a terminal distribution network surplus power off-grid mode, characterized in that: The following steps are involved: In response to receiving dispatching instructions, peak load regulation instructions and frequency regulation instructions from the upper power grid, the response state of distributed power sources, demand-side resources and energy storage devices in the distribution network is adjusted through self-peak load regulation control at three time scales; According to the adjustment results, the peak value problem of the power return of the terminal distribution network operation and control platform during the PCC node power return is eliminated to ensure that the surplus power is not connected to the grid at any time; In the process of self-peak control, the self-peak control of three time scales includes: the first time scale is 15min~1h time scale of self-peak control in response to scheduling instructions and peak-shaving instructions, the second time scale is 3min~5min time scale of self-peak control in response to AGC frequency modulation instructions, and the third time scale is 0.5s~1s time scale of self-peak control; In the process of executing the self-peak-shaving control when responding to the scheduling instruction and the peak-shaving instruction at the first time scale, the first objective function of the self-peak-shaving control corresponding to the first time scale is: In the formula, C DR , C ess , C W , C PV , C PCC are the demand-side response cost coefficient, energy storage charging and discharging cost coefficient, wind and solar abandonment penalty cost coefficient, and electricity purchase price from the large power grid; P DR (t) is the demand side response amount; P ess (t) is the energy storage charging and discharging power, P ess,c (t) is negative, when discharging, P ess,d (t) is positive; Forecast output of wind and solar power units, P W (t), P PV (t) is the actual output of the wind and solar power unit; P PCC (t) is the power of the PCC node in the terminal distribution network; T1 is the total time period of the peak load response; k1 is the deviation penalty coefficient of the distribution network tracking the PCC node power plan during peak load; P PCC,p (t) is the power plan value of the PCC node of the terminal distribution network during peak load regulation; In the process of executing the self-peak control in response to the AGC frequency modulation instruction at the second time scale, the second objective function of the self-peak control corresponding to the second time scale includes: Where: CW , C PV , C DR , C ess are the power adjustment cost coefficients of wind turbines, photovoltaic units, demand-side response, and energy storage equipment; ΔP W (t), ΔP PV (t), ΔP DR (t), ΔP ess (t) are the secondary frequency regulation power adjustment of wind turbines, photovoltaic units, demand-side response, and energy storage equipment respectively; k2 is the deviation penalty coefficient of the distribution network tracking the PCC node power plan during frequency regulation; T2 is the total response frequency regulation period; P PCC,t (t) is the power plan value of the PCC node of the terminal distribution network after responding to the frequency modulation instruction, wherein the constraints of the second objective function are the same as the constraints of the first objective function.

2. According to claim 1, a self-peak load regulation control method in a terminal distribution network surplus power non-online mode is characterized by: In the process of constructing the first objective function, the constraint condition of the first objective function is: Power balance constraints: P PV (t)+P W (t)+P ess (t)+P PCC (t)=P load (t), P load (t)=P load,D (t)+P DR (t), Where: P load,D (t) is the fixed load; Transmission power limit of tie line: Where: is the maximum power allowed by the tie line; since power reverse transmission is not allowed, P PCC (t) ≥ 0; Unit output constraints: The output of wind and solar power units cannot exceed their maximum and minimum values; Demand-side response constraints: Where: The lower and upper limits of the load call volume for demand-side response; Energy storage related constraints: Where: are the maximum charging and maximum discharging power respectively; SOC min <SOC(t)<SOC max , Where: SOC min and SOC max are the lower and upper limits of energy storage SOC respectively; η d and η c are discharge efficiency and charging efficiency respectively; E is the total capacity of the energy storage device.

3. According to claim 1, a self-peak control method in a terminal distribution network surplus power non-grid-connected mode, characterized in that: During the period of responding to the peak load instruction, the part of the PCC node power in the daily scheduling plan that exceeds the peak load should be adjusted down to the peak load, and the part that does not exceed the peak should be executed according to the original daily scheduling plan. The expression is: Where P PCC,p (t) is the power plan value of the PCC node in the terminal distribution network after responding to the peak load instruction, P PS For peak value adjustment, P PCC,r (t) is the planned power value of the PCC node in the terminal distribution network in the intraday dispatch plan.

4. According to claim 1, a self-peak load control method in a terminal distribution network surplus power non-grid-connected mode, characterized in that: In response to executing the self-peaking control of the first time scale and the second time scale, when the wind, solar and energy storage output can meet the load requirements, the PCC node dead-zone power is set as the trigger condition for the self-peaking control of the third time scale, and the wind and solar unit output and energy storage charging power are adjusted in real time, and the PCC node power is controlled to always track the planned value and the adjustment value, wherein the PCC node dead-zone power is determined based on the ultra-short-term prediction error of the wind and solar output and the load.

5. According to claim 4, a self-peak load regulation control method in a terminal distribution network surplus power non-grid-connected mode is characterized in that: In the process of executing the self-peak control of the third time scale, by predicting the output of the controllable units in the future limited time domain, and selecting the PCC node power of the terminal distribution network as the output variable, according to the power balance constraint of the first time scale, the predicted value corresponding to the PCC node power is obtained; The PCC node power plan value output by the self-peak control at the first time scale and the second time scale is selected as a reference target, and the optimization target of the self-peak control model at the third time scale is set to minimize the PCC node power correction deviation, wherein the optimization objective function is: In the formula, The upper layer optimizes the PCC node power tracking value at the future k+i time, and M is the prediction step size.

6. According to claim 5, a method for self-peak load regulation in a terminal distribution network surplus power non-grid-connected mode, characterized in that: In the process of executing the self-peaking control of the third time scale, the constraints of the self-peaking control of the third time scale include: Controllable unit output constraints: Where: P max (k+i) and P min (k+i) are the maximum and minimum output power of wind and solar generators and energy storage, respectively; Energy storage SOC constraints: Where: and They are respectively the upper and lower limits of the energy storage SOC constrained by the upper-level scheduling.

7. According to claim 6, a self-peak load control method in a terminal distribution network surplus power not connected to the grid mode is characterized in that: In the process of executing the self-peak control of the third time scale, the optimization objective function is solved by the sequential quadratic programming method, and the control variable sequence of the future M time periods is sent down. The active output of the wind and solar power units and energy storage in the distribution network at time k+1 is calculated. Through the feedback correction method, the current actual wind and solar power output and energy storage power are used as the initial values ​​of the next round of rolling optimization to reduce the uncertainty caused by the wind and solar power output.

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