A power distribution network voltage control method and device and storage medium

Abstract

The application discloses a power distribution network voltage control method and device and a storage medium, and belongs to the technical field of power distribution control. The method comprises the following steps: in response to a first day-ahead voltage control scheduling request sent by a new energy monitoring control substation of a power distribution network to a master station, obtaining day-ahead prediction results of photovoltaic output and power distribution network load and network topology parameters of the master station; calculating an OLTC tapping position at a preset time, so that the OLTC control terminal adjusts the tapping to the corresponding position at the preset time; sending a second day-ahead voltage control scheduling request to the master station at the preset time, and obtaining short-time prediction results of photovoltaic output and power distribution network load of the master station at the preset time; calculating basic reactive power output and control parameters of a photovoltaic inverter, so that the photovoltaic inverter terminal adjusts the parameters of the inverter and adjusts the reactive power output of the photovoltaic inverter, thereby realizing layered multi-stage optimization control on the voltage of the power distribution network, reducing network power loss and bus voltage deviation, and improving network voltage stability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power distribution control, and particularly relates to a power distribution network voltage control method and device and a storage medium. BACKGROUND

[0002] The voltage control of the power distribution network is a key part of the new energy monitoring service. If the voltage control performance of the power distribution network is poor, on the one hand, the penetration rate of the new energy of the power distribution network will also be limited, and it is difficult to withstand the access of a high proportion of new energy; on the other hand, it will lead to problems in voltage quality, and the voltage quality will significantly affect the working efficiency of the power utilization equipment, and also bear the pressure brought by the high-quality power supply requirements of users.

[0003] In the current power distribution system, OLTC, switched capacitor or inverter is mainly used for voltage regulation of the power distribution network. At present, there are mainly OLTC-based voltage control method, inverter-based voltage control method and capacitor compensation method. The basic strategy of the OLTC-based voltage control method is to measure the feeder current at the substation end and estimate the voltage drop along the distribution feeder, and then adjust the tap to minimize the voltage deviation in the system. The basic strategy of the inverter-based voltage control method is to adjust the voltage by controlling the reactive power absorption and injection of the inverter. The capacitor compensation method generally realizes automatic switching control of the capacitor according to the pre-set relevant technical guidelines.

[0004] The integration of distributed new energy in the power distribution network makes the power flow bidirectional, and the voltage distribution of the network depends on the location of the DGs, the injection of active power and the power factor of the distributed power supply. The overall situation of the feeder cannot be predicted, so it is difficult for the OLTC-based voltage control method to effectively regulate the voltage. The inverter-based voltage control method is easy to make the power factor of the feeder node too low and increase the line network loss, and even cause overheating phenomenon (such as transformer). The voltage control method is mainly committed to maintaining the network voltage within the limit range, without considering the potential network loss and voltage stability problems. The capacitor and OLTC scheme have limitations on the number and frequency of actions, and cannot be adjusted continuously for many times, which is difficult to solve the high-frequency change mode operation in the system with high penetration rate of renewable distributed power supply. Therefore, the existing voltage control method has poor voltage regulation effect on the power distribution system, resulting in poor voltage stability of the power distribution system. SUMMARY

[0005] The present application provides a power distribution network voltage control method and device and a storage medium to realize hierarchical multi-stage optimization control of the voltage of the power distribution network, to reduce network power loss and bus voltage deviation, and to improve network voltage stability.

[0006] The application provides a power distribution network voltage control method, which is applied to a power distribution network new energy monitoring control substation, and the method comprises the following steps:

[0007] In response to a first day-ahead voltage control scheduling request sent by the power distribution network new energy monitoring control substation to a master station, day-ahead prediction results of photovoltaic output and power distribution network load and network topology parameters of the master station are obtained;

[0008] According to the day-ahead prediction results of photovoltaic output and power distribution network load and the network topology parameters of the master station, an OLTC tap position at a preset time is calculated, and the OLTC tap position at the preset time is sent to an OLTC control terminal, so that the OLTC control terminal adjusts the tap to the corresponding position at the preset time;

[0009] A second day-ahead voltage control scheduling request is sent to the master station at the preset time, and short-time prediction results of photovoltaic output and power distribution network load of the master station at the preset time are obtained;

[0010] According to the short-time prediction results of photovoltaic output and power distribution network load of the master station at the preset time, basic reactive power output and control parameters of a photovoltaic inverter are calculated;

[0011] The basic reactive power output and control parameters of the photovoltaic inverter are sent to a responding photovoltaic inverter terminal, so that the photovoltaic inverter terminal adjusts the parameters of the inverter and adjusts the reactive power output of the photovoltaic inverter.

[0012] Further, the OLTC tap position at the preset time is calculated according to the day-ahead prediction results of photovoltaic output and power distribution network load and the network topology parameters of the master station, and specifically,

[0013] The day-ahead prediction results of photovoltaic output and power distribution network load and the network topology parameters of the master station are input into an OLTC scheduling model, and the OLTC tap position at each hour in a day is calculated;

[0014] The optimization target of the OLTC scheduling model is to minimize the network loss in a day;

[0015] The decision variable of the OLTC scheduling model is the OLTC tap position at each hour in a day and the total reactive power output of the inverter;

[0016] The constraint condition of the OLTC scheduling model comprises an OLTC tap position change constraint, a photovoltaic inverter reactive power output constraint and a power flow constraint.

[0017] Further, the optimization target of the OLTC scheduling model is specifically,

[0018] ;

[0019] Wherein, Indicates the position of the OLTC tap changer; t represents the total reactive power output of the inverter; B represents the set of feeder segments in the distribution network, ij represents the feeder segment between distribution network node i and distribution network node j; t represents the scheduling cycle period, which is 1 hour; k represents the kth scheduling cycle; K represents the total number of scheduling cycles in a day.

[0020] ;

[0021] This represents the loss of the feeder segment between distribution network node i and distribution network node j in the kth scheduling cycle; r ij Indicates the resistance of the power distribution network lines; P ij，k This represents the active power output of the feeder segment between distribution network node i and distribution network node j in the kth scheduling cycle. Q ij，k This represents the reactive power output of the feeder segment between distribution network node i and distribution network node j in the kth scheduling cycle. V 0 This represents the initial transformer output voltage.

[0022] Furthermore, the OLTC tap position change constraint includes: the maximum number of times the OLTC tap changes in a day, and the maximum range of change of the OLTC tap position within an hourly interval.

[0023] The expression for the constraint on the maximum number of changes to an OLTC tap in a day is:

[0024] ;

[0025] The expression for the maximum range constraint of OLTC tap position change within an hourly interval is:

[0026] ;

[0027] Among them, OLTC max This represents the sum of the largest range of changes within a day for the tap; This indicates the maximum range of change within a given time period. and These represent the tap positions of the OLTC in the k-th and (k-1)-th scheduling cycles, respectively.

[0028] Furthermore, the reactive power output constraint of the photovoltaic inverter is specifically as follows:

[0029] ;

[0030] ;

[0031] in, The apparent power of the photovoltaic inverter is a constant parameter. Let be the active power output of the photovoltaic inverter at node i in the k-th scheduling cycle. Let be the reactive power output of the photovoltaic inverter at node i during the k-th scheduling cycle; Let be the maximum reactive power output of the photovoltaic inverter at node i during the k-th scheduling cycle.

[0032] Furthermore, the power flow constraint specifically refers to:

[0033] ;

[0034] ;

[0035] ;

[0036] ;

[0037] ;

[0038] in, For nodes i The injected active power of photovoltaic power in the k-th scheduling cycle, Represents a node i Active load in the k-th scheduling cycle P ij，k This represents the active power output of the feeder segment between distribution network node i and distribution network node j in the kth scheduling cycle. Q ij，k This represents the reactive power output of the feeder segment between distribution network node i and distribution network node j in the kth scheduling cycle. Let be the reactive power output of the photovoltaic inverter at node i in the k-th scheduling cycle; Represents a node i The reactive load in the k-th scheduling cycle; J(i) Indicates connection with all nodes i Connected network nodes j ; H(i) Represents all nodes i Upstream node of the connection h ; r ij and x ij These are the resistance and reactance of the power distribution network lines, respectively. V j,k Indicates the node of the k-th scheduling cycle. j Voltage; V i,k Indicates the node of the k-th scheduling cycle.i Voltage; Represents a node i The lower limit of voltage. Represents a node i upper limit of voltage, V 0 This represents the initial transformer output voltage during the k-th scheduling cycle; Indicates the line ij The power capacity. Further, based on the short-time forecast results of the photovoltaic output and distribution network load at the master station at a preset time, the basic reactive power output and control parameters of the photovoltaic inverter are calculated, specifically as follows:

[0039] The short-term forecast results of the photovoltaic output and distribution network load of the main station for each hour of the day are input into the intraday scheduling optimization model. The optimization objective of the intraday scheduling optimization model is:

[0040] ;

[0041] in, Q is the inverter droop factor. base This is the basic reactive power output of the inverter; v itc The control parameters for the inverter are: B is the set of feeder segments in the distribution network, ij represents the feeder segment between distribution network node i and distribution network node j; t represents the scheduling cycle time period, which is 1 hour; T represents the total number of scheduling cycles in a day. r ij Indicates the resistance of the power distribution network lines; P ij，t This represents the active power output of the feeder segment between distribution network node i and distribution network node j during time period t; Q ij，t This represents the reactive power output of the feeder segment between distribution network node i and distribution network node j during time period t. V 0 This represents the initial transformer output voltage;

[0042] The constraints of the intraday scheduling optimization model include: droop coefficient constraints, photovoltaic inverter power constraints, voltage deviation equality constraints, and power flow constraints.

[0043] Furthermore, the constraints of the intraday scheduling optimization model include: droop coefficient constraints, power constraints of the photovoltaic inverter, and equality constraints and power flow constraints for voltage deviation, specifically:

[0044] The expression for the droop coefficient constraint of voltage stability is:

[0045] ;

[0046] in, is a critical droop coefficient of the photovoltaic inverter, ε is a value tending to 0, is a droop coefficient of node i;

[0047] An expression of the power constraint of the photovoltaic inverter is:

[0048] ;

[0049] is a reactive power output of the photovoltaic inverter at a t time period; is a maximum value of the reactive power output of the photovoltaic inverter at the t time period;

[0050] An expression of the equation constraint of the voltage deviation is:

[0051] ;

[0052] wherein, denotes a voltage deviation of node i at a t time period; V i,t denotes a voltage of node i at a t time period; denotes a bus voltage setting value of node i.

[0053] Further, the photovoltaic inverter terminal adjusts parameters of the inverter, adjusts the reactive power output of the photovoltaic inverter, and specifically:

[0054] The photovoltaic inverter terminal adjusts the reactive power output of the photovoltaic inverter according to a real-time bus voltage;

[0055] An expression of adjusting the reactive power output of the photovoltaic inverter is:

[0056] ;

[0057] ;

[0058] wherein, denotes a real-time adjusted reactive power output of node i at a real-time time point s; is a droop coefficient of node i; denotes a voltage deviation of node i at a real-time time point s; V i,s denotes a voltage of node i at a real-time time point s; denotes a bus voltage setting value of node i.

[0059] As a preferred solution, the application estimates the OLTC tap position of the photovoltaic power distribution network every hour in the future day in the day-ahead, and sends the OLTC control terminal to schedule and control the OLTC tap position; the basic reactive power output of each photovoltaic node inverter is calculated in the day, and is sent to each node inverter terminal for scheduling control, the coordination of different types of voltage control resources such as OLTC and photovoltaic inverter of high-penetration photovoltaic power distribution network and the factors such as network loss and voltage stability are comprehensively considered, and the layered multi-stage optimization control of the power distribution network voltage is realized, so as to reduce the network power loss and bus voltage deviation, and improve the network voltage stability.

[0060] Other features and advantages of the present application will be described in detail in the following specific embodiments.

[0061] Correspondingly, the application also provides a power distribution network voltage control device applied to a power distribution network new energy monitoring control substation, the device comprising: a day-ahead scheduling module, an intra-day scheduling module and a real-time scheduling module;

[0062] The day-ahead scheduling module is used for obtaining the photovoltaic output, the day-ahead prediction result of the power distribution network load and the network topology parameters of the main station in the day-ahead in response to the first day-ahead voltage control scheduling request sent by the power distribution network new energy monitoring control substation to the main station.

[0063] According to the photovoltaic output, the day-ahead prediction result of the power distribution network load and the network topology parameters of the main station in the day-ahead, the OLTC tap position at a preset time is calculated, and the OLTC tap position at the preset time is sent to the OLTC control terminal, so that the OLTC control terminal adjusts the tap to the corresponding position at the preset time.

[0064] The intra-day scheduling module is used for sending a second day-ahead voltage control scheduling request to the main station at a preset time, and obtaining the short-time prediction result of the photovoltaic output and the power distribution network load of the main station at the preset time.

[0065] According to the short-time prediction result of the photovoltaic output and the power distribution network load of the main station at the preset time, the basic reactive power output and the control parameter of the photovoltaic inverter are calculated.

[0066] The real-time scheduling module is used for sending the basic reactive power output and the control parameter of the photovoltaic inverter to the responding photovoltaic inverter terminal, so that the photovoltaic inverter terminal adjusts the parameters of the inverter and adjusts the reactive power output of the photovoltaic inverter.

[0067] Correspondingly, the application also provides a computer readable storage medium, the computer readable storage medium comprises a stored computer program; wherein the computer program controls the device where the computer readable storage medium is located to execute the power distribution network voltage control method as described in the summary of the application when running. BRIEF DESCRIPTION OF DRAWINGS

[0068] Figure 1 is a flowchart of an embodiment of the power distribution network voltage control method provided by the present application;

[0069] Figure 2 is a droop characteristic curve diagram of an embodiment of the power distribution network voltage control method provided by the present application;

[0070] Figure 3 is a structural diagram of an embodiment of the power distribution network voltage control device provided by the present application. DETAILED DESCRIPTION

[0071] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0072] Embodiment one

[0073] Please refer to Figure 1 A power distribution network voltage control method provided by an embodiment of the present application is applied to a power distribution network new energy monitoring control substation, and includes steps S101-S103:

[0074] Step S101: In response to a first day-ahead voltage control scheduling request sent by the power distribution network new energy monitoring control substation to a master station, obtaining day-ahead prediction results of photovoltaic output and power distribution network load and network topology parameters of the master station;

[0075] According to the day-ahead prediction results of photovoltaic output and power distribution network load and the network topology parameters of the master station, the OLTC tap position at a preset time is calculated, and the OLTC tap position at the preset time is sent to an OLTC control terminal, so that the OLTC control terminal adjusts the tap to the corresponding position at the preset time;

[0076] In this embodiment, when the master station receives the first day-ahead voltage control scheduling request sent by the power distribution network new energy monitoring control substation, the day-ahead prediction results of photovoltaic output and power distribution network load and the network topology parameters of the master station are calculated, and the day-ahead prediction results of photovoltaic output and power distribution network load and the network topology parameters of the master station in the power distribution network region are sent to the power distribution network new energy monitoring control substation.

[0077] Specifically, the day-ahead photovoltaic output of the master station includes: the injected active power of the photovoltaic of node i , the active load of node i and the reactive load of node i ;

[0078] The day-ahead prediction result of the distribution network load is a day-ahead 24h prediction value of the distribution network load.

[0079] The network topology parameters include: distribution network line parameters, resistance r ij and reactance x ij .

[0080] The OLTC tap position at the preset time is calculated by inputting the day-ahead photovoltaic output of the main station, the day-ahead prediction result of the distribution network load, and the network topology parameters into the power flow constraint of the OLTC scheduling model, and is used to calculate the OLTC tap position every hour in a day.

[0081] Further, the OLTC tap position at the preset time is calculated according to the day-ahead photovoltaic output of the main station, the day-ahead prediction result of the distribution network load, and the network topology parameters, and specifically:

[0082] The OLTC tap position every hour in a day is calculated by inputting the day-ahead photovoltaic output of the main station, the day-ahead prediction result of the distribution network load, and the network topology parameters into the OLTC scheduling model;

[0083] The optimization objective of the OLTC scheduling model is to minimize the network loss in a day;

[0084] The decision variable of the OLTC scheduling model is the OLTC tap position and the total reactive power output of the inverter every hour in a day.

[0085] The constraint conditions of the OLTC scheduling model include: OLTC tap position change constraint, photovoltaic inverter reactive power output constraint, and power flow constraint.

[0086] Further, the optimization objective of the OLTC scheduling model is specifically:

[0087] ;

[0088] Wherein, represents the position of the OLTC tapping switch; is the total reactive power output of the inverter; B is the set of feeder sections of the distribution network, ij represents the feeder section between the distribution network node i and the distribution network node j; t represents the scheduling period, which is 1 hour; k represents the kth scheduling period; K represents the total number of scheduling periods in a day;

[0089] ;

[0090] represents the loss of the feeder section between the distribution network node i and the distribution network node j in the kth scheduling period; rij represents the resistance of the distribution network line; P ij，k represents the active power output of the feeder section between distribution network node i and distribution network node j in the kth dispatch period; Q ij，k represents the reactive power output of the feeder section between distribution network node i and distribution network node j in the kth dispatch period; V 0 represents the initial transformer output voltage.

[0091] Further, the OLTC tap position change constraint comprises: a maximum change number constraint of the OLTC tap in a day, and a maximum change range constraint of the OLTC tap position in a small time interval;

[0092] The expression of the maximum change number constraint of the OLTC tap in a day is:

[0093] ;

[0094] The expression of the maximum change range constraint of the OLTC tap position in a small time interval is:

[0095] ;

[0096] wherein, OLTC max represents the sum of the maximum change ranges of the tap in a day; represents the maximum change range value in a time period, and respectively represent the tap position of the OLTC in the kth dispatch period and the k-1th dispatch period.

[0097] Further, the reactive power output constraint of the photovoltaic inverter, specifically:

[0098] ;

[0099] ;

[0100] wherein, is the apparent power of the photovoltaic inverter, is a constant parameter, is the active power output of the photovoltaic inverter of node i in the kth dispatch period, is the reactive power output of the photovoltaic inverter of node i in the kth dispatch period; is the maximum value of the reactive power output of the photovoltaic inverter of node i in the kth dispatch period.

[0101] Further, the power flow constraint, specifically:

[0102] ;

[0103] ;

[0104] ;

[0105] ;

[0106] ;

[0107] wherein, is the node i injected active power of the photovoltaic in the kth dispatch period, denotes the node i active load in the kth dispatch period, P ij，k denotes the active power output of the feeder section between distribution network node i and distribution network node j in the kth dispatch period; Q ij，k denotes the reactive power output of the feeder section between distribution network node i and distribution network node j in the kth dispatch period; is the reactive power output of the photovoltaic inverter of node i in the kth dispatch period; denotes the node i reactive load in the kth dispatch period; J(i) denotes the network node i connected to all nodes j ; H(i) denotes all upstream nodes i connected to the node h ; r ij and x ij are the resistance and reactance of the distribution network line, respectively; V j,k denotes the node j voltage in the kth dispatch period; V i,k denotes the node i voltage in the kth dispatch period; denotes the lower limit of the node i voltage, denotes the upper limit of the node i voltage, V 0 denotes the initial transformer output voltage in the kth dispatch period; denotes the power capacity of the line ij . In the present embodiment, the power flow constraints are used to calculate the active and reactive power of each line of the distribution network, as well as the point bus voltage, and to constrain the bus voltage of each node, limiting the bus voltage from being too high and too low.

[0108] In the embodiment, according to the parameters of the day before, the coordination of the characteristics of different types of voltage control resources such as the OLTC of the photovoltaic power distribution network and the photovoltaic inverter is considered, and the calculation result of the day-ahead scheduling of each scheduling period, i.e., the tap position of the OLTC (OLTC tap position) of each hour of a day, is calculated by using the OLTC scheduling model.

[0109] When the time of each scheduling period (one hour) of the day arrives, the OLTC adjusts the tap to the corresponding position according to the calculation result of the day-ahead scheduling.

[0110] Step S102: sending a second day-ahead voltage control scheduling request to the master station at a preset time, obtaining short-time prediction results of photovoltaic output and distribution network load of the master station at the preset time;

[0111] According to the short-time prediction results of photovoltaic output and distribution network load of the master station at the preset time, the basic reactive power output and control parameters of the photovoltaic inverter are calculated;

[0112] Further, the calculation of the basic reactive power output and control parameters of the photovoltaic inverter according to the short-time prediction results of photovoltaic output and distribution network load of the master station at the preset time is specifically:

[0113] The short-time prediction results of photovoltaic output and distribution network load of the master station at each hour of a day are input into an intra-day scheduling optimization model, and the optimization objective of the intra-day scheduling optimization model is:

[0114] ;

[0115] Wherein, is the droop coefficient of the inverter, Q base is the basic reactive power output of the inverter; v itc is the control parameter of the inverter: B is the set of feeder sections of the distribution network, ij represents the feeder section between the distribution network node i and the distribution network node j; t represents the scheduling period, which is 1 hour; T represents the total number of scheduling periods in a day; r ij represents the resistance of the distribution network line; P ij，t represents the active power output of the feeder section between the distribution network node i and the distribution network node j at the t period; Q ij，t represents the reactive power output of the feeder section between the distribution network node i and the distribution network node j at the t period; V 0 represents the initial transformer output voltage;

[0116] The constraints of the intra-day scheduling optimization model include: droop coefficient constraint, power constraint of the photovoltaic inverter, equation constraint of voltage deviation, and power flow constraint.

[0117] Further, the constraints of the intra-day scheduling optimization model include: droop coefficient constraints, power constraints of the photovoltaic inverter, and equation constraints of voltage deviation and power flow constraints, specifically:

[0118] The expression of the droop coefficient constraints of voltage stability is:

[0119] ;

[0120] Wherein, is the critical droop coefficient of the photovoltaic inverter, and ε is a value tending to 0, is the droop coefficient of node i;

[0121] The expression of the power constraints of the photovoltaic inverter is:

[0122] ;

[0123] is the reactive power output of the photovoltaic inverter at time period t; is the maximum value of the reactive power output of the photovoltaic inverter at time period t;

[0124] The expression of the equation constraints of voltage deviation is:

[0125] ;

[0126] Wherein, represents the voltage deviation; V i,t represents the voltage of node i at time period t; represents the bus voltage setting value of node i.

[0127] In the embodiment, the power flow constraints of the intra-day scheduling optimization model are the same as the power flow constraints of the OLTC scheduling model.

[0128] In the embodiment, the decision target of the intra-day scheduling strategy is the total reactive power output of the inverter. The intra-day scheduling strategy is at an interval of one hour, and further adjusts the total reactive power output of the inverter according to the short-term load prediction (i.e. the photovoltaic output and network load prediction within one hour), which can further reduce the deviation caused by insufficient day-ahead prediction accuracy, and can improve the voltage stability.

[0129] Step S103: sending the basic reactive power output of the photovoltaic inverter and the control parameter to a responding photovoltaic inverter terminal, so as to make the photovoltaic inverter terminal adjust the parameter of the inverter and adjust the reactive power output of the photovoltaic inverter.

[0130] Further, the photovoltaic inverter terminal adjusts the parameter of the inverter and adjusts the reactive power output of the photovoltaic inverter, specifically:

[0131] The photovoltaic inverter terminal adjusts the reactive power output of the photovoltaic inverter according to the real-time bus voltage;

[0132] The expression for adjusting the reactive power output of the photovoltaic inverter is:

[0133] ;

[0134] ;

[0135] wherein, represents the real-time adjusted reactive power output of node i at the real-time time point s; is the droop coefficient of node i; represents the voltage deviation of node i at the real-time time point s; V i,s represents the voltage of node i at the real-time time point s; represents the bus voltage set value of node i.

[0136] In the present embodiment, the control of the photovoltaic inverter is divided into a centralized control stage and a local control stage.

[0137] Specifically, in the centralized control stage, the basic reactive power output set point of the inverter is optimized by minimizing the network loss under the condition of meeting the bus voltage constraint . At this time, the bus voltage tends to the set value of the central control . The relationship between the inverter basic output set point and the bus expected voltage can be modeled as:

[0138] ;

[0139] wherein is the intercept of the droop control curve on the voltage axis, is the droop coefficient, please refer to Figure 2 is a schematic diagram of the droop characteristic curve.

[0140] In the present embodiment, in the local control stage, the inverter further adjusts the reactive power output in real time by droop control , which reduces the deviation from the expected voltage , which is represented as:

[0141] ;

[0142] Therefore, the total reactive power output of the inverter is represented as the sum of the basic output and the real-time change , which is represented as:

[0143] ;

[0144] The embodiment of the present application has the following effects:

[0145] The present application estimates the OLTC tap position of the photovoltaic power distribution network every hour in the future one day, and sends the OLTC control terminal to schedule and control the OLTC tap position. The basic reactive power output of each photovoltaic node inverter is calculated in the day, and is sent to each node inverter terminal for scheduling control. The coordination of different types of voltage control resources such as OLTC and photovoltaic inverter of high-penetration photovoltaic power distribution network, network loss and voltage stability, etc. are comprehensively considered, and the hierarchical multi-stage optimization control of the distribution network voltage is realized, so as to reduce the network power loss and bus voltage deviation, and improve the network voltage stability.

[0146] Embodiment two

[0147] Please refer to Figure 3 The power distribution network voltage control device provided by the embodiment of the present application is applied to a power distribution network new energy monitoring control substation, and the device comprises a day-ahead scheduling module 201, an intra-day scheduling module 202 and a real-time scheduling module 203.

[0148] The day-ahead scheduling module is used to obtain the day-ahead photovoltaic output, the day-ahead prediction result of the power distribution network load and the network topology parameters of the main station in response to the first day-ahead voltage control scheduling request sent by the power distribution network new energy monitoring control substation to the main station.

[0149] According to the day-ahead photovoltaic output, the day-ahead prediction result of the power distribution network load and the network topology parameters of the main station, the OLTC tap position at a preset time is calculated, and the OLTC tap position at the preset time is sent to the OLTC control terminal, so that the OLTC control terminal adjusts the tap to the corresponding position at the preset time.

[0150] The intra-day scheduling module is used to send a second day-ahead voltage control scheduling request to the main station at a preset time, and obtain the short-time prediction result of the photovoltaic output and the power distribution network load of the main station at the preset time.

[0151] According to the short-time prediction result of the photovoltaic output and the power distribution network load of the main station at the preset time, the basic reactive power output and the control parameter of the photovoltaic inverter are calculated.

[0152] The real-time scheduling module is used to send the basic reactive power output and the control parameter of the photovoltaic inverter to the responding photovoltaic inverter terminal, so that the photovoltaic inverter terminal adjusts the parameters of the inverter and adjusts the reactive power output of the photovoltaic inverter.

[0153] Further, the OLTC tap position at the preset time is calculated according to the day-ahead photovoltaic output of the main station, the day-ahead prediction result of the distribution network load and network topology parameters, and specifically,

[0154] The day-ahead photovoltaic output of the main station, the day-ahead prediction result of the distribution network load and network topology parameters are input into the OLTC scheduling model, and the OLTC tap position every hour in a day is calculated;

[0155] The optimization objective of the OLTC scheduling model is to minimize the network loss in a day;

[0156] The decision variable of the OLTC scheduling model is the OLTC tap position and the total reactive power output of the inverter every hour in a day;

[0157] The constraint condition of the OLTC scheduling model includes the OLTC tap position change constraint, the reactive power output constraint of the photovoltaic inverter and the power flow constraint.

[0158] Further, the optimization objective of the OLTC scheduling model is specifically:

[0159] ;

[0160] Wherein, represents the position of the OLTC tapping switch; is the total reactive power output of the inverter; B is the feeder segment set of the distribution network; ij represents the feeder segment between the distribution network node i and the distribution network node j; t represents the scheduling period, which is 1 hour; k represents the kth scheduling period; K represents the total number of scheduling periods in a day;

[0161] ;

[0162] represents the loss of the feeder segment between the distribution network node i and the distribution network node j in the kth scheduling period; r ij represents the resistance of the distribution network line; P ij，k represents the active power output of the feeder segment between the distribution network node i and the distribution network node j in the kth scheduling period; Q ij，k represents the reactive power output of the feeder segment between the distribution network node i and the distribution network node j in the kth scheduling period; V 0 represents the initial transformer output voltage.

[0163] Further, the OLTC tap position change constraint includes the maximum change times constraint of the OLTC tap in a day and the maximum change range constraint of the OLTC tap position in a small time interval;

[0164] The expression of the maximum number of OLTC tap changes in a day is:

[0165] ;

[0166] The expression of the maximum range of OLTC tap position changes in a small time interval is:

[0167] ;

[0168] wherein OLTC max represents the sum of the maximum range of tap changes in a day; represents the maximum range of changes in a time period, and represent the tap position of the OLTC in the kth scheduling period and the (k-1)th scheduling period, respectively.

[0169] Further, the reactive power output constraint of the photovoltaic inverter, in particular:

[0170] ;

[0171] ;

[0172] wherein, is the apparent power of the photovoltaic inverter, which is a constant parameter, is the active power output of the photovoltaic inverter of node i in the kth scheduling period, is the reactive power output of the photovoltaic inverter of node i in the kth scheduling period; is the maximum value of the reactive power output of the photovoltaic inverter of node i in the kth scheduling period.

[0173] Further, the power flow constraint, in particular:

[0174] ;

[0175] ;

[0176] ;

[0177] ;

[0178] ;

[0179] wherein, is the active power injection of the photovoltaic of node i in the kth scheduling period, represents the active load of node i in the kth scheduling period,P ij，k represents the active power output of the feeder segment between distribution node i and distribution node j in the kth dispatch period; Q ij，k represents the reactive power output of the feeder segment between distribution node i and distribution node j in the kth dispatch period; represents the reactive power output of the photovoltaic inverter for node i in the kth dispatch period; represents the voltage of node i in the kth dispatch period; J(i) represents the reactive load connected to all nodes i in the kth dispatch period; j ; H(i) represents all upstream nodes i connected to node h in the kth dispatch period; r ij and x ij are the resistance and reactance of the distribution network line, respectively; V j,k represents the voltage of node j in the kth dispatch period; V i,k represents the voltage of node i in the kth dispatch period; represents the lower limit of the voltage of node i , represents the upper limit of the voltage of node i , V 0 represents the initial transformer output voltage in the kth dispatch period; represents the power capacity of the line ij .

[0180] Further, the basic reactive power output and control parameters of the photovoltaic inverter are calculated according to the short-term prediction results of the photovoltaic output and distribution network load of the master station at a preset time, specifically:

[0181] The short-term prediction results of the photovoltaic output and distribution network load of the master station every hour in a day are input into an intraday dispatch optimization model, and the optimization objective of the intraday dispatch optimization model is:

[0182] ;

[0183] wherein, is the droop coefficient of the inverter, Q base is the basic reactive power output of the inverter; v itcB is a set of feeder segments of the power distribution network, ij represents a feeder segment between a power grid node i and a power grid node j; t represents a dispatch period, which is 1 hour; T represents a total number of dispatch periods in a day; r ij represents a resistance of a line of the power distribution network; P ij，t represents an active power output of a feeder segment between a power grid node i and a power grid node j at a time period t; Q ij，t represents a reactive power output of a feeder segment between a power grid node i and a power grid node j at a time period t; V 0 represents an initial transformer output voltage;

[0184] The constraints of the intra-day dispatch optimization model include: droop coefficient constraints, power constraints of the photovoltaic inverter, equation constraints of voltage deviation, and power flow constraints.

[0185] Further, the constraints of the intra-day dispatch optimization model include: droop coefficient constraints, power constraints of the photovoltaic inverter, equation constraints of voltage deviation, and power flow constraints, specifically:

[0186] The expression of the droop coefficient constraint of voltage stability is:

[0187] ;

[0188] wherein, is a critical droop coefficient of the photovoltaic inverter, ε is a value tending to 0, is a droop coefficient of node i;

[0189] The expression of the power constraint of the photovoltaic inverter is:

[0190] ;

[0191] is a reactive power output of the photovoltaic inverter at a time period t; is a maximum value of the reactive power output of the photovoltaic inverter at a time period t;

[0192] The expression of the equation constraint of voltage deviation is:

[0193] ;

[0194] wherein, represents a voltage deviation; V i,t represents a voltage of node i at a time period t; represents a bus voltage setting value of node i.

[0195] Further, the photovoltaic inverter terminal adjusts parameters of the inverter, adjusts the reactive power output of the photovoltaic inverter, and specifically:

[0196] The photovoltaic inverter terminal adjusts the reactive power output of the photovoltaic inverter according to the real-time bus voltage;

[0197] The expression for adjusting the reactive power output of the photovoltaic inverter is:

[0198]

[0199]

[0200] wherein, represents the real-time adjusted reactive power output of the node i at the real-time time point s; is the droop coefficient of the node i; represents the voltage deviation of the node i at the real-time time point s; V i,s represents the voltage of the node i at the real-time time point s; represents the bus voltage set value of the node i.

[0201] The power distribution network voltage control device described above can implement the power distribution network voltage control method of the method embodiment described above. The optional items in the method embodiment described above are also applicable to the present embodiment, and will not be described in detail herein. The remaining content of the present embodiment can be referred to the content of the method embodiment described above, and will not be described in detail herein.

[0202] Embodiment Three

[0203] Correspondingly, the present application also provides a computer readable storage medium, which comprises a stored computer program, wherein the computer readable storage medium controls a device where the computer readable storage medium is located to execute the power distribution network voltage control method according to any one of the embodiments described above when the computer program is running.

[0204] Illustratively, the computer program can be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present application. The one or more modules / units can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the terminal device.

[0205] The terminal device can be a desktop computer, a notebook, a palm computer, a cloud server and other computing devices. The terminal device can include, but is not limited to, a processor, a memory.

[0206] ​​The processor can be a central processing unit (CPU), and can also be other general-purpose processors, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor or the like, and is a control center of the terminal device, which connects all parts of the terminal device through various interfaces and lines.

[0207] The memory can be used to store the computer programs and / or modules, and the processor realizes various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application program required by a function, etc.; and the data storage area can store data created according to the use of the terminal device, etc. In addition, the memory can include a high-speed random access memory, and can also include a nonvolatile memory, for example, a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state memory device.

[0208] The modules / units integrated in the terminal device, if in the form of software function units and sold or used as independent products, can be stored in a computer readable storage medium. Based on this understanding, all or part of the processes in the above-mentioned embodiment methods can also be completed by a computer program instructing related hardware. The computer program can be stored in a computer readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned various method embodiments can be implemented. The computer program includes computer program code, which can be in the form of source code, object code, executable files or some intermediate forms, etc. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0209] The above specific embodiments further illustrate the purpose, technical solutions and beneficial effects of the present application. It should be understood that the above description is only for specific embodiments of the present application and is not intended to limit the protection scope of the present application. It is particularly pointed out that any modification, equivalent replacement, improvement, etc. made by those skilled in the art within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A power distribution network voltage control method, characterized by, The method is applied to a new energy monitoring and control substation of a power distribution network, and the method comprises the following steps: In response to a first day-ahead voltage control scheduling request sent by the new energy monitoring and control substation of the power distribution network to a main station, day-ahead prediction results of photovoltaic output and power grid load of the main station and network topology parameters are obtained; OLTC tap position at a preset time is calculated according to the day-ahead prediction results of photovoltaic output and power grid load of the main station and the network topology parameters, and the OLTC tap position at the preset time is sent to an OLTC control terminal, so that the OLTC control terminal adjusts the tap to the corresponding position at the preset time; A second day-ahead voltage control scheduling request is sent to the main station at the preset time, and short-time prediction results of photovoltaic output and power grid load of the main station at the preset time are obtained; Basic reactive power output and control parameters of a photovoltaic inverter are calculated according to the short-time prediction results of photovoltaic output and power grid load of the main station at the preset time, and the calculation of the basic reactive power output and the control parameters of the photovoltaic inverter according to the short-time prediction results of photovoltaic output and power grid load of the main station at the preset time is specifically as follows: The short-time prediction results of photovoltaic output and power grid load of the main station at each hour of a day are input into an intra-day scheduling optimization model, and an optimization objective of the intra-day scheduling optimization model is as follows: ； wherein, is the droop coefficient of the inverter, Q base is the basic reactive output of the inverter; v itc is the control parameter of the inverter: B is the set of feeder segments of the distribution network, ij represents the feeder segment between the distribution network node i and the distribution network node j; t represents the dispatch cycle period, which is 1 hour; T represents the total number of dispatch cycle periods in a day; r ij represents the resistance of the distribution network line; P ij，t represents the active output of the feeder segment between the distribution network node i and the distribution network node j at the t period; Q ij，t represents the reactive power output of the feeder segment between the distribution network node i and the distribution network node j at the t period; V 0 represents the initial transformer output voltage; The constraints of the intra-day scheduling optimization model include droop coefficient constraints, power constraints of the photovoltaic inverter, equation constraints of voltage deviation and power flow constraints; The basic reactive power output and the control parameters of the photovoltaic inverter are sent to a responding photovoltaic inverter terminal, so that the photovoltaic inverter terminal adjusts the parameters of the inverter and adjusts the reactive power output of the photovoltaic inverter.

2. A power distribution network voltage control method as claimed in claim 1, characterized in that, The calculation of the OLTC tap position at the preset time according to the day-ahead prediction results of photovoltaic output and power grid load of the main station and the network topology parameters is specifically as follows: The day-ahead prediction results of photovoltaic output and power grid load of the main station and the network topology parameters are input into an OLTC scheduling model, and the OLTC tap position at each hour of a day is calculated; The optimization objective of the OLTC scheduling model is to minimize the network loss within a day; The decision variables of the OLTC scheduling model are the tap position of the OLTC and the total reactive power output of the inverter at each hour of a day; The constraint conditions of the OLTC scheduling model include OLTC tap position change constraints, reactive power output constraints of the photovoltaic inverter and power flow constraints.

3. A power distribution network voltage control method as claimed in claim 2, characterized in that, The optimization objective of the OLTC scheduling model is specifically as follows: ； wherein, represents the position of OLTC tap changer; is the total reactive power output of inverters; B is the set of feeder segments of distribution network; ij represents the feeder segment between distribution network node i and distribution network node j; t represents the dispatch period, which is 1 hour; k represents the kth dispatch period; K represents the total number of dispatch periods in a day; ； represents the loss of the feeder segment between distribution network node i and distribution network node j in the kth dispatch period; r ij represents the resistance of the distribution network line; P ij，k represents the active output of the feeder segment between distribution network node i and distribution network node j in the kth dispatch period; Q ij，k represents the reactive power output of the feeder segment between distribution network node i and distribution network node j in the kth dispatch period; V 0 represents the initial transformer output voltage.

4. The power distribution network voltage control method of claim 2, wherein, The OLTC tap position change constraints include maximum change frequency constraints of the OLTC tap within a day and maximum change range constraints of the OLTC tap position within a small time interval; The expression of the maximum change frequency constraints of the OLTC tap within a day is as follows: ； The expression of the maximum change range constraints of the OLTC tap position within a small time interval is as follows: ； wherein OLTC max represents the sum of the maximum variation range of the tap in one day; represents the maximum variation range value in a time period, and respectively represent the tap position of the OLTC in the kth dispatch cycle and the k-1th dispatch cycle.

5. The power distribution network voltage control method of claim 2, wherein, The reactive power output constraints of the photovoltaic inverter are specifically as follows: ； ； wherein, Ppv,i is the apparent power of the photovoltaic inverter, Ppv,i is the active power output of the photovoltaic inverter at node i in the kth scheduling period, Qpv,i is the reactive power output of the photovoltaic inverter at node i in the kth scheduling period; Qpv,i is the maximum reactive power output of the photovoltaic inverter at node i in the kth scheduling period.

6. A power distribution network voltage control method as claimed in claim 2, characterized by, The power flow constraints are specifically as follows: ； ； ； ； ； wherein, is the node i injected active power of the photovoltaic at the kth scheduling period, is the node i active load at the kth scheduling period, P ij，k is the active power output of the feeder segment between distribution network node i and distribution network node j at the kth scheduling period; Q ij，k is the reactive power output of the feeder segment between distribution network node i and distribution network node j at the kth scheduling period; is the reactive power output of the photovoltaic inverter of node i at the kth scheduling period; is the node i reactive load at the kth scheduling period; J(i) is the network node i connected to all nodes j ; H(i) is the upstream node i connected to all nodes h ; r ij and x ij are the resistance and reactance of the distribution network line, respectively; V j,k is the node j voltage at the kth scheduling period; V i,k is the node i voltage at the kth scheduling period; is the lower limit of the node i voltage, is the upper limit of the node i voltage, V 0 is the initial transformer output voltage at the kth scheduling period; is the power capacity of the line ij .

7. The power distribution network voltage control method of claim 1, wherein The constraints of the intra-day scheduling optimization model include droop coefficient constraints, power constraints of the photovoltaic inverter, equation constraints of voltage deviation and power flow constraints, and the constraints of the intra-day scheduling optimization model are specifically as follows: The expression of the droop coefficient constraints of voltage stability is as follows: ； wherein, is the critical droop coefficient of the photovoltaic inverter, ε is a number tending to 0, is the droop coefficient at the node i; An expression of a power constraint of the photovoltaic inverter is: ； reactive power output for the photovoltaic inverter t period; maximum reactive power output for the photovoltaic inverter t period; An expression of an equation constraint of the voltage deviation is: ； wherein, represents the voltage deviation of node i at time period t; V i,t represents the voltage of node i at time period t; represents the bus voltage set value of node i.

8. The power distribution network voltage control method of claim 1, wherein, The photovoltaic inverter terminal adjusts parameters of the inverter, and adjusts the reactive power output of the photovoltaic inverter, specifically: The photovoltaic inverter terminal adjusts the reactive power output of the photovoltaic inverter according to the real-time bus voltage; An expression of adjusting the reactive power output of the photovoltaic inverter is: ； ； wherein, represents the real-time adjusted reactive power output of node i at real-time time point s; is the droop coefficient for node i; represents the voltage deviation of node i at real-time time point s; V i,s represents the voltage of node i at real-time time point s; represents the bus voltage setpoint of node i.

9. An electric power distribution network voltage control device, characterized by, The device is applied to a new energy monitoring and control substation of a distribution network, and the device comprises a day-ahead scheduling module, an intra-day scheduling module and a real-time scheduling module; The day-ahead scheduling module is configured to obtain day-ahead prediction results of photovoltaic output and distribution network load and network topology parameters of a main station in response to a first day-ahead voltage control scheduling request sent by the distribution network new energy monitoring and control substation to the main station; The OLTC tap position at a preset time is calculated according to the day-ahead prediction results of photovoltaic output and distribution network load and the network topology parameters of the main station, and the OLTC tap position at the preset time is sent to an OLTC control terminal, so that the OLTC control terminal adjusts the tap to the corresponding position at the preset time; The intra-day scheduling module is configured to send a second day-ahead voltage control scheduling request to the main station at a preset time, and obtain short-time prediction results of photovoltaic output and distribution network load of the main station at the preset time; The basic reactive power output and control parameters of the photovoltaic inverter are calculated according to the short-time prediction results of photovoltaic output and distribution network load of the main station at the preset time, and the calculation of the basic reactive power output and control parameters of the photovoltaic inverter according to the short-time prediction results of photovoltaic output and distribution network load of the main station at the preset time is specifically as follows: The short-time prediction results of photovoltaic output and distribution network load of the main station at each hour of a day are input into an intra-day scheduling optimization model, and an optimization objective of the intra-day scheduling optimization model is: ； wherein, is the droop coefficient of the inverter, Q base is the basic reactive output of the inverter; v itc is the control parameter of the inverter: B is the set of feeder segments of the distribution network, ij represents the feeder segment between the distribution network node i and the distribution network node j; t represents the dispatch cycle period, which is 1 hour; T represents the total number of dispatch cycle periods in a day; r ij represents the resistance of the distribution network line; P ij，t represents the active output of the feeder segment between the distribution network node i and the distribution network node j at the t period; Q ij，t represents the reactive power output of the feeder segment between the distribution network node i and the distribution network node j at the t period; V 0 represents the initial transformer output voltage; The constraints of the intra-day scheduling optimization model include droop coefficient constraints, power constraints of the photovoltaic inverter, equation constraints of the voltage deviation and power flow constraints; The real-time scheduling module is configured to send the basic reactive power output and control parameters of the photovoltaic inverter to a responding photovoltaic inverter terminal, so that the photovoltaic inverter terminal adjusts parameters of the inverter and adjusts the reactive power output of the photovoltaic inverter.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium comprises a stored computer program; wherein the computer program controls the device where the computer readable storage medium is located to execute the power distribution network voltage control method in any one of claims 1 to 8 when running.

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