Flexible control method for three-phase imbalance of low-voltage power distribution network

Abstract

The invention relates to the technical field of power distribution management, in particular to a three-phase imbalance flexible control method for a low-voltage power distribution network. Comprising the following steps: firstly, establishing voltage-active and voltage-reactive quantitative relation models; and establishing a low-voltage power distribution network multi-objective optimization operation model and a resource cooperative scheduling method. The flexible management and control technology designed by the invention can reduce asymmetry, improve the stability and reliability of power grid operation and effectively improve the three-phase asymmetry of the system by adjusting and optimizing the wind and light storage operation power in real time; by formulating an optimal coordinated operation model, the operation power of distributed resources can be optimized on the premise of meeting three-phase balance constraints, and a three-phase imbalance control target is achieved with the minimum cost; the voltage is also used as a constraint condition for calculation, so that the voltage of each node of the low-voltage power distribution network is not out of limit, the voltage is ensured to be qualified, the voltage deviation and the possible power utilization safety risk of a user are reduced, and the voltage quality is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power distribution management, and in particular to a flexible control method for three-phase imbalance in a low-voltage power distribution network. Background Art

[0002] With the continuous development of social economy and the growing demand for clean energy, the scale of access of distributed power sources (such as photovoltaics, wind turbines, etc.) in low-voltage distribution networks has shown a rapid growth trend. At the same time, the application of energy storage equipment is becoming more and more extensive, aiming to improve energy utilization efficiency and the stability of power grid operation. However, the surge in distributed resources and the single-phase random access method have brought many severe challenges to the low-voltage distribution system, among which the three-phase imbalance problem is particularly prominent and has become one of the key factors restricting the safe and efficient operation of low-voltage distribution networks.

[0003] The traditional low-voltage distribution network is usually designed and operated based on the assumption of three-phase balance. However, with the current large-scale access of distributed resources, the random access of single-phase distributed power sources (such as single-phase photovoltaic inverters) makes the distribution of three-phase loads extremely unbalanced. From the perspective of the physical characteristics of the power system, three-phase imbalance will lead to uneven distribution of current in the three-phase line, which will in turn cause a series of negative effects. For example, in a three-phase four-wire system, the neutral line current will increase significantly. Since the wire diameter of the neutral line is usually designed according to the normal three-phase balance, excessive neutral line current will increase its heating, which will not only increase line losses, but also accelerate insulation aging, reduce the service life of the line, and even cause safety accidents such as fire, which seriously threatens the safe operation of the low-voltage distribution network.

[0004] Furthermore, three-phase imbalance will have a serious impact on the power quality of the power grid. In terms of voltage, unbalanced three-phase loads will cause deviations in the amplitude and phase of each phase voltage. This voltage deviation will deteriorate the operating conditions of power equipment, reduce its operating efficiency, and increase equipment losses. For example, for motors, three-phase voltage imbalance will cause negative sequence currents, which will lead to torque pulsation and increased heat generation of the motor, reducing the efficiency and service life of the motor. At the same time, three-phase imbalance may also cause voltage fluctuations and flickers, affecting the normal operation of electrical equipment at the user end, such as causing lights to flicker and electronic equipment to work unstably, seriously affecting the user's electricity experience and the normal order of production and life.

[0005] The traditional solution to the three-phase imbalance problem mainly adopts phase-changing switch technology. The phase-changing switch attempts to achieve the redistribution of the three-phase load by changing the phase difference of the load access, thereby achieving the purpose of improving the three-phase imbalance. However, this method has many limitations. On the one hand, the phase-changing switch can only alleviate the three-phase imbalance problem to a certain extent, and it is difficult to achieve complete three-phase balance. Because it only makes a simple adjustment to the load access phase difference, it cannot fundamentally solve the three-phase power imbalance problem caused by the random access of distributed power sources. On the other hand, there are certain risks in the operation of the phase-changing switch. For example, a phase-to-phase short circuit may occur during the phase-changing process, which will instantly cause a large short-circuit current, causing serious impact on the power grid equipment, and even damage the equipment. In addition, the phase-changing operation may also cause a short-term power outage, affecting the normal power consumption of users, especially for some places with high requirements for power supply continuity (such as hospitals, data centers, etc.), such a short-term power outage may have serious consequences.

[0006] In order to deal with the three-phase imbalance problem more effectively and give full play to the advantages of distributed resources, a more advanced and intelligent control technology is urgently needed. Therefore, the present invention proposes a flexible control technology based on photovoltaic, wind power and energy storage. By comprehensively considering various constraints such as power flow and voltage deviation, an optimization model for three-phase imbalance control is constructed to achieve flexible control of three-phase imbalance in low-voltage distribution networks. While ensuring the safe and reliable operation of the power grid, it improves the quality of electric energy, reduces control costs, and provides strong support for the sustainable development of low-voltage distribution networks. In view of this, we propose a flexible control method for three-phase imbalance in low-voltage distribution networks. Summary of the invention

[0007] The object of the present invention is to provide a flexible control method for three-phase unbalance in a low-voltage distribution network to solve the problems raised in the above-mentioned background technology.

[0008] In order to solve the above technical problems, the present invention aims to provide a flexible control method for three-phase unbalance of a low-voltage distribution network, comprising the following steps:

[0009] S1. Establishing voltage-active power and voltage-reactive power quantitative relationship models; specifically including:

[0010] S1.1. A radial distribution network topology is used to construct a single radial distribution network with n nodes containing photovoltaic power sources, and the voltage-active power sensitivity and voltage-reactive power sensitivity are calculated using the injection disturbance power sensitivity calculation method;

[0011] S1.2. Simultaneously solve the quantitative results of the active / reactive effects on the voltage of the low-voltage feeder with branch lines;

[0012] S2. Establish a multi-objective optimization operation model for low-voltage distribution network and a resource collaborative dispatching method; specifically including:

[0013] S2.1. Set the objective function of minimizing the control cost of photovoltaic, wind turbine and energy storage;

[0014] S2.2. Set the operation constraints of the multi-objective optimization operation model of the low-voltage distribution network; the operation constraints include: photovoltaic constraints, wind turbine constraints, energy storage constraints, node voltage constraints, sensitivity constraints, power balance constraints and three-phase imbalance constraints;

[0015] S2.3. The objective function of minimizing the control cost and the model of each operating constraint condition are established as a linear programming model and solved using an open source solver.

[0016] As a further improvement of the technical solution, in step S1.1, in a single radial distribution network containing n nodes and a photovoltaic power source, the voltage of each node varies due to the photovoltaic injection and the load consumption of active and reactive power, and there is a problem that the voltage of some or all nodes is high; then the calculation process of voltage-active sensitivity and voltage-reactive sensitivity is:

[0017] Voltage-active power sensitivity is:

[0018]

[0019] Voltage-reactive sensitivity is:

[0020]

[0021] In the formula, is the line and node set from node 0 to node i, is the line and node set from node 0 to node j; V i is the voltage at node i, P j is the active power of node j, Q j is the reactive power of node j; is the voltage-active power sensitivity, i.e., the partial derivative of the voltage at node i with respect to the active power at node j; is the voltage-reactive power sensitivity, that is, the partial derivative of the voltage at node i with respect to the reactive power at node j; R l is the line resistance, X l is the line reactance, V l is the voltage of the node on line l.

[0022] As a further improvement of the technical solution, in step S1.2, the low-voltage feeder with branch lines is solved in a similar manner, and the result is the same as equation (1) and equation (2); by comparing equation (1) and equation (2), the quantitative result of the active / reactive effect on the voltage can be obtained. Assuming that the feeder adopts a unified line model, the unit resistance and reactance of the feeder of the unified model are set to r0 and x0 respectively, and it can be obtained:

[0023]

[0024] It can be seen from equations (1) and (2) that the strength of the voltage-active power and voltage-reactive power coupling relationship between any two nodes is directly related to the resistance and reactance values ​​of the feeder: the larger the resistance value, the stronger the voltage-active power coupling relationship, and the larger the reactance value, the stronger the voltage-reactive power coupling relationship; vice versa;

[0025] It can be seen from formula (3) that the ratio of the voltage-active power to voltage-reactive power coupling strength is equal to the ratio of the unit resistance to the reactance of the line. For the same type of line, the larger the line cross-section, the smaller the line resistance value, and the smaller r / x. The reactance value of the cable line is small, and r / x is significantly greater than that of the overhead line with the same cross-section, where r and x represent the resistance and reactance of the line respectively.

[0026] As a further improvement of the technical solution, in the voltage-active power and voltage-reactive power quantitative relationship models, the relationship between the voltage change of any node i and the node power change of the entire network can be expressed as:

[0027]

[0028] Where ΔV i represents the voltage change at node i, represents the voltage-active sensitivity between nodes i and j, ΔP j represents the active power change of node j, represents the voltage-reactive sensitivity between nodes i and j, ΔQ j Represents the reactive power change of node j.

[0029] As a further improvement of the technical solution, in step S2.1, the objective function of minimizing the control cost of photovoltaic, wind turbine and energy storage is expressed as follows:

[0030] minp=C pv (t)+C es (t)+C wt (t) (5)

[0031] In the formula, minp represents the objective of minimizing the control cost, C pv (t) represents the dispatching cost of photovoltaic power generation during period t; Ces (t) represents the dispatching cost of the energy storage system; C wt (t) represents the dispatching cost of the wind turbine during period t.

[0032] As a further improvement of the technical solution, the calculation formulas for the various costs in the objective function of minimizing the control cost of photovoltaic, wind turbine and energy storage are as follows:

[0033] Control costs of distributed photovoltaics: Distributed photovoltaics mainly consider the control costs of photovoltaic units. The specific expression is as follows:

[0034]

[0035] Where N pv Indicates the number of photovoltaic units; λ p is the photovoltaic grid-connected electricity price; ΔP pv (t) represents the control power of unit p in time period t (unit: kW); δt is the duration of a time period (unit: hour);

[0036] Fan control cost: The fan mainly considers the control cost of the fan unit. The specific expression is as follows:

[0037]

[0038] Where N wt Indicates the number of fan units; w is the on-grid electricity price of the wind turbine; ΔP wt (t) represents the control power of unit w in period t (unit: kW); δt is the duration of a period (unit: hour);

[0039] Energy storage operating costs: The operating costs of energy storage include the electricity price of energy storage charging and discharging. The specific expression is as follows:

[0040]

[0041] In the formula, l(t), l min , l max Respectively represent the time t value, daily minimum value, and daily maximum value of energy storage charging and discharging price, unit: yuan / kWh; Respectively represent the increased discharge power and charging power of unit e, unit: kW; N es Indicates the number of energy storage units.

[0042] As a further improvement of the technical solution, in the operation constraint conditions, the calculation method of the photovoltaic constraint is:

[0043]

[0044] In the formula, is the regulated active power of the i-th photovoltaic group at time t, which means the active power of the i-th photovoltaic group adjusted at time t relative to its initial operating state or the previous operating state, i.e., time (t-1); is the active power of the i-th photovoltaic group at the current time t, indicating the actual active power that the i-th photovoltaic group can output at the current time t; is the regulated reactive power of the ith photovoltaic group at time t; S iN is the apparent power of the i-th inverter; is the maximum power angle of the ith photovoltaic group;

[0045] The fan constraint is calculated as:

[0046]

[0047] In the formula, is the regulated active power of the i-th group of fans at time t; is the active power of the i-th group of wind turbines at the current time t; is the regulated reactive power of the i-th group of fans at time t; S iN The apparent power of the i-th fan; is the maximum power angle of the i-th group of fans.

[0048] As a further improvement of the technical solution, in the operation constraint conditions, the energy storage constraint includes a charge and discharge constraint and an SOC constraint; wherein the charge and discharge constraint is calculated as follows:

[0049] The charge and discharge power constraints are as follows:

[0050]

[0051] In the formula, They represent the maximum discharge power and maximum charging power of the energy storage unit respectively. They represent the minimum discharge power and minimum charging power of the energy storage unit respectively; the energy storage can be operated in the optimal charging power state by setting the maximum charging power and the minimum charging power; They respectively represent the increased discharge power and charging power of the energy storage unit e at time t; They represent the discharge state and charge state of energy storage, respectively. They are both 0-1 variables. When the value is 1, it means discharge / charge, and when the value is 0, it means no discharge / no charge. The two are mutually exclusive, that is, they meet the following constraints:

[0052]

[0053] The calculation method of SOC constraint is:

[0054]

[0055] In the formula, represents the SOC of unit e in period t, represents the SOC of unit e at time t-1, They represent the maximum and minimum allowable values ​​of SOC respectively (related to SOH. The upper and lower limits of SOC are updated according to SOH before each calculation, and a certain margin is reserved, such as 20%, that is, the minimum SOC value is 0.2 and the maximum value is 0.8); It represents the charge and discharge power of unit e at time t (charging is positive, discharging is negative); SOC(0) represents the initial capacity of SOC, and SOC(N) represents the SOC capacity of the last period.

[0056] As a further improvement of the technical solution, in the operation constraint conditions, the calculation method of the node voltage constraint is:

[0057]

[0058] Where U i,max , U i,min Indicates the maximum and minimum voltage of node i, U i represents the voltage of line node i, N represents the number of system nodes; The flag bit for over / under crossing. When the value is 1, it is over the limit, and when the value is 0, it is not over the limit. It indicates the part of the voltage exceeding the upper limit when the voltage of node i exceeds the upper limit; It represents the part of the voltage below the lower limit (taking the absolute value) when the voltage of node i is lower than the lower limit; the constraint condition of formula (17) helps to accurately judge the voltage state in the voltage control process and avoid the confusion of the control strategy;

[0059] The sensitivity constraint is calculated as:

[0060] The voltage sensitivity of the photovoltaic active output connected at node m to node k is:

[0061]

[0062] Where, ΔV m is the voltage change at node m, P k is the active power of node k; is the voltage-active sensitivity of node m to node k, that is, the voltage change of node m caused by the unit power change of node k, which is the partial derivative of the voltage change of node m with respect to the active power of node k; is the intersection of the lines and nodes on the path from node 0 to node m and from node 0 to node k; R l is the line resistance, V lis the voltage of the node on line l;

[0063] The voltage sensitivity of the photovoltaic reactive output connected at node m to node k is:

[0064]

[0065] In the formula, Q k Reactive power of node k; is the voltage-reactive power sensitivity of node m to node k, which is the partial derivative of the voltage change of node m with respect to the reactive power of node k; sign(Q k ) is Q k The sign function is positive when inductive reactive power is emitted and negative when capacitive reactive power is emitted; X l is the line reactance.

[0066] As a further improvement of the technical solution, in the operation constraint condition, the calculation method of the power balance constraint is:

[0067]

[0068] In the formula, is the active power of the i-th group of energy storage at the current time t; N ES is the number of energy storage; is the active power of the ith photovoltaic group at the current time t; N PV is the number of photovoltaic units; is the active power of the i-th group of wind turbines at the current time t; N wt is the number of fan units; P Load (t) is the active power of the load at the current moment t; P grid (t) is the active power of the power grid at the current moment t;

[0069] The calculation method of the three-phase unbalance constraint is:

[0070] ε I %≤ε I,max % (twenty one)

[0071] In the formula, ε I % indicates the three-phase current unbalance, ε I,max % is the maximum value of three-phase unbalance;

[0072] Calculate the three-phase current unbalance, the expression is as follows:

[0073]

[0074] In the formula, They are the effective values ​​of the maximum and minimum phase currents in phases A, B, and C respectively.

[0075] Compared with the prior art, the present invention has the following beneficial effects:

[0076] 1. In the flexible control method for three-phase imbalance of low-voltage distribution network, for the problem of three-phase asymmetry of the system caused by random access of single-phase, the flexible control technology can reduce asymmetry by real-time adjustment and optimization of wind, solar and storage operating power, improve the stability and reliability of grid operation, and effectively improve the three-phase asymmetry of the system;

[0077] 2. In the flexible control method of three-phase unbalance in low-voltage distribution network, by formulating the optimal coordinated operation model, this technology can optimize the operating power of distributed resources under the premise of satisfying the three-phase balance constraint, achieve the three-phase unbalance control target at the minimum cost, and reduce the cost of three-phase unbalance control;

[0078] 3. In the flexible control method of three-phase unbalanced low-voltage distribution network, voltage is also calculated as a constraint condition. Therefore, the optimized calculation results can ensure that the voltage of each node in the low-voltage distribution network does not exceed the limit, thereby ensuring the voltage is qualified, reducing voltage deviation and the possible safety risks of user electricity use, thereby improving voltage quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 is an exemplary control method flow chart of the present invention;

[0080] Figure 2 This is a structural diagram of an exemplary radiation distribution network containing photovoltaic power sources in the present invention. DETAILED DESCRIPTION

[0081] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0082] Example 1

[0083] like Figure 1-Figure 2 As shown, this embodiment provides a three-phase unbalanced flexible control method for a low-voltage distribution network, comprising the following steps:

[0084] S1. Establishing voltage-active power and voltage-reactive power quantitative relationship models; specifically including:

[0085] S1.1. A radial distribution network topology is used to construct a single radial distribution network with n nodes containing photovoltaic power sources, and the voltage-active power sensitivity and voltage-reactive power sensitivity are calculated using the injection disturbance power sensitivity calculation method;

[0086] In this step, the general distribution network topology is radial, and the flow direction of the power flow is relatively simple. This method is more applicable and has better convergence characteristics and calculation speed than the Newton-Raphson method. Therefore, it is proposed to use the injection disturbance power sensitivity calculation method;

[0087] like Figure 2 As shown in the figure, in a single radial distribution network with n nodes and a photovoltaic power source, the voltage of each node varies due to the photovoltaic injection and load consumption of active and reactive power, and there is a problem of high voltage at some or all nodes; the calculation process of voltage-active sensitivity and voltage-reactive sensitivity is:

[0088] Voltage-active power sensitivity is:

[0089]

[0090] Voltage-reactive sensitivity is:

[0091]

[0092] In the formula, is the line and node set from node 0 to node i, is the line and node set from node 0 to node j; V i is the voltage at node i, P j is the active power of node j, Q j is the reactive power of node j; is the voltage-active power sensitivity, i.e., the partial derivative of the voltage at node i with respect to the active power at node j; is the voltage-reactive power sensitivity, that is, the partial derivative of the voltage at node i with respect to the reactive power at node j; R l is the line resistance, X l is the line reactance, V l is the voltage of the node on line l.

[0093] S1.2. Simultaneously solve the quantitative results of the active / reactive effects on the voltage of the low-voltage feeder with branch lines;

[0094] In this step, the solution method for the low-voltage feeder with branch lines is similar, and the results are the same as those of equations (1) and (2). By comparing equations (1) and (2), the quantitative results of the effect of active / reactive power on voltage can be obtained. Assuming that the feeder adopts a unified line model, the unit resistance and reactance of the feeder of the unified model are set to r0 and x0 respectively, and the following can be obtained:

[0095]

[0096] It can be seen from equations (1) and (2) that the strength of the voltage-active power and voltage-reactive power coupling relationship between any two nodes is directly related to the resistance and reactance values ​​of the feeder: the larger the resistance value, the stronger the voltage-active power coupling relationship, and the larger the reactance value, the stronger the voltage-reactive power coupling relationship; vice versa;

[0097] It can be seen from formula (3) that the ratio of the voltage-active power to voltage-reactive power coupling strength is equal to the ratio of the unit resistance to the reactance of the line. For the same type of line, the larger the line cross-section, the smaller the line resistance value, and the smaller r / x. The reactance value of the cable line is small, and r / x is significantly greater than that of the overhead line with the same cross-section, where r and x represent the resistance and reactance of the line respectively.

[0098] Furthermore, in the voltage-active power and voltage-reactive power quantitative relationship models, the relationship between the voltage change of any node i and the node power change of the entire network can be expressed as:

[0099]

[0100] Where ΔV i represents the voltage change at node i, represents the voltage-active sensitivity between nodes i and j, ΔP j represents the active power change of node j, represents the voltage-reactive sensitivity between nodes i and j, ΔQ j Represents the reactive power change of node j.

[0101] S2. Establish a multi-objective optimization operation model for low-voltage distribution network and a resource collaborative dispatching method; specifically including:

[0102] S2.1. Set the objective function of minimizing the control cost of photovoltaic, wind turbine and energy storage;

[0103] In this step, the objective function of minimizing the control cost of photovoltaic, wind turbine and energy storage is expressed as follows:

[0104] minp=C pv (t)+C es (t)+C wt (t) (5)

[0105] In the formula, minP represents the goal of minimizing the control cost, C pv (t) represents the dispatching cost of photovoltaic power generation during period t; C es (t) represents the dispatching cost of the energy storage system; C wt (t) represents the dispatching cost of the wind turbine during period t.

[0106] Furthermore, the calculation formula for each part of the cost is as follows:

[0107] Control costs of distributed photovoltaics: Distributed photovoltaics mainly consider the control costs of photovoltaic units. The specific expression is as follows:

[0108]

[0109] Where N pv Indicates the number of photovoltaic units; λ p is the photovoltaic grid-connected electricity price; ΔP pv (t) represents the control power of unit p in time period t (unit: kW); δt is the duration of a time period (unit: hour);

[0110] Fan control cost: The fan mainly considers the control cost of the fan unit. The specific expression is as follows:

[0111]

[0112] Where N wt Indicates the number of fan units; w is the on-grid electricity price of the wind turbine; ΔP wt (t) represents the control power of unit w in period t (unit: kW); δt is the duration of a period (unit: hour);

[0113] Energy storage operating costs: The operating costs of energy storage include the electricity price of energy storage charging and discharging. The specific expression is as follows:

[0114]

[0115] In the formula, l(t), l min , l max Respectively represent the time t value, daily minimum value, and daily maximum value of energy storage charging and discharging price, unit: yuan / kWh; Respectively represent the increased discharge power and charging power of unit e, unit: kW; N es Indicates the number of energy storage units.

[0116] S2.2. Set the operation constraints of the multi-objective optimization operation model of the low-voltage distribution network; the operation constraints include: photovoltaic constraints, wind turbine constraints, energy storage constraints, node voltage constraints, sensitivity constraints, power balance constraints and three-phase imbalance constraints;

[0117] In this step, the operating constraints are:

[0118] 1) The calculation method of photovoltaic constraints is:

[0119]

[0120] In the formula, is the regulated active power of the i-th photovoltaic group at time t, which means the active power of the i-th photovoltaic group adjusted at time t relative to its initial operating state or the previous operating state, i.e., time (t-1); is the active power of the i-th photovoltaic group at the current time t, indicating the actual active power that the i-th photovoltaic group can output at the current time t; is the regulated reactive power of the ith photovoltaic group at time t; S iN is the apparent power of the ith inverter. The apparent power is the total power capacity that the inverter can provide. It has a relationship with the active power and reactive power (S 2 =P 2 +Q 2 ), through this apparent power limit, it can be ensured that the photovoltaic power will not exceed the capacity limit of the inverter when adjusting the reactive power, thereby ensuring the safe operation of the equipment; is the maximum power angle of the i-th photovoltaic group. The power angle is an important parameter reflecting the operating status of the synchronous generator. For the photovoltaic system, the power angle will also affect the power exchange characteristics between it and the power grid. By limiting the lower limit of reactive power through this maximum power angle, the stable operation of the photovoltaic system can be guaranteed to a certain extent, avoiding problems such as system instability caused by improper reactive power regulation. For example, when the power angle is close to the maximum value, the adjustment range of reactive power may be limited to prevent the system from abnormal operation.

[0121] in, The size of depends on many factors, such as light intensity, characteristics of photovoltaic modules, temperature, etc. For example, at noon when there is sufficient sunlight and the temperature is suitable, may reach a higher value; in the early morning or evening when the light is weak, will be relatively low;

[0122] for Reactive power plays an important role in maintaining the voltage stability of the power grid. By adjusting the reactive power, the grid voltage can be supported or adjusted. For example, when the grid voltage is low, photovoltaics can output a certain amount of reactive power to increase the voltage; when the grid voltage is high, photovoltaics can absorb a certain amount of reactive power to reduce the voltage. The range in formula (9) is related to factors such as the active power output of photovoltaics, the apparent power of the inverter, and the maximum power angle. It is a reasonable constraint condition used to ensure that the reactive power of photovoltaics during operation is adjusted within a reasonable range to maintain the stable operation of the system.

[0123] 2) The calculation method of fan constraints is:

[0124]

[0125] In the formula, is the regulated active power of the i-th group of fans at time t; is the active power of the i-th group of wind turbines at the current time t; is the regulated reactive power of the i-th group of fans at time t; S iN The apparent power of the i-th fan; is the maximum power angle of the i-th group of fans.

[0126] 3) Energy storage constraints include charge and discharge constraints and SOC constraints; the calculation method of charge and discharge constraints is:

[0127] A. The charging and discharging power constraints are as follows:

[0128]

[0129] In the formula, They represent the maximum discharge power and maximum charging power of the energy storage unit respectively. They represent the minimum discharge power and minimum charging power of the energy storage unit respectively; the energy storage can be operated in the optimal charging power state by setting the maximum charging power and the minimum charging power; They respectively represent the increased discharge power of the energy storage unit e at time t (it reflects the additional discharge power of the energy storage unit at the current moment relative to the previous state) and the charging power (it reflects the additional charging power of the energy storage unit at the current moment relative to the previous state); They represent the discharge state and charge state of energy storage, respectively. They are both 0-1 variables. When the value is 1, it means discharge / charge, and when the value is 0, it means no discharge / no charge. The two are mutually exclusive, that is, they meet the following constraints:

[0130]

[0131] The maximum discharge power of the energy storage unit is the maximum power value that the energy storage unit can output under the physical performance and safety limitations. Exceeding this value may cause battery overheating, damage or other safety problems, and may also cause impact on connected power equipment. For example, in an emergency, when the energy storage unit needs to discharge quickly to provide a large amount of electricity, its discharge power cannot exceed

[0132] The maximum charging power of the energy storage unit is the maximum power value that the energy storage unit can withstand under the constraints of battery characteristics, charger performance and safety requirements. Exceeding this value may cause dangerous situations such as battery overcharging, heating or even explosion. For example, when connected to a high-power power source for fast charging, the charging power cannot exceed

[0133] The minimum discharge power of the energy storage unit is the minimum power value that the energy storage unit can discharge safely and stably under the design or operation requirements. If the discharge power is lower than this value, it may lead to low efficiency of the energy storage system, shortened battery life or other unstable situations. For example, for some types of battery energy storage systems, too small a discharge current (corresponding to a smaller discharge power) may cause problems such as uneven chemical reactions inside the battery.

[0134] The minimum charging power of the energy storage unit is the minimum charging power value that the energy storage unit can accept while ensuring the normal charging process and battery performance; if the charging power is lower than this value, it may cause the charging time to be too long, incomplete battery charging or other problems; for example, for some battery management systems, too small a charging current (corresponding to a smaller charging power) may not activate certain charging protection mechanisms inside the battery, affecting the long-term performance of the battery.

[0135] B. The calculation method of SOC constraint is:

[0136]

[0137] In the formula, represents the SOC of unit e in period t, represents the SOC of unit e at time t-1, They represent the maximum and minimum allowable values ​​of SOC respectively (related to SOH. The upper and lower limits of SOC are updated according to SOH before each calculation, and a certain margin is reserved, such as 20%, that is, the minimum SOC value is 0.2 and the maximum value is 0.8); It represents the charging and discharging power of unit e at time t (charging is positive and discharging is negative); When the energy storage unit is charging, the SOC will increase; when When the energy storage unit is discharging, the SOC will decrease. This means that unit e is discharged at 2 kW at time t, which will cause the SOC to decrease accordingly according to the formula;

[0138] SOC(0) represents the initial capacity of SOC (it is the SOC state of the energy storage system at the start of scheduling and the starting point for subsequent SOC calculations), and SOC(N) represents the SOC capacity of the last period.

[0139] Among them, SOC is an important indicator to measure the remaining power of energy storage batteries, usually expressed as a percentage. For example, It means that the remaining battery capacity of the unit is 50% of the total capacity. It is a key parameter reflecting the current energy state of the energy storage system and is of great significance for the operation control and scheduling of the energy storage system, such as determining whether the energy storage system can continue to discharge or needs to be charged.

[0140] Further, and It reflects the continuity of SOC in time, and calculates the SOC at the current moment by the SOC at the previous moment and the charge and discharge power change at the current moment. If there is a discharge power output at time, then according to the formula Will decrease.

[0141] Finally, the constraint in equation (15) ensures that the SOC of the energy storage system remains balanced at the beginning and end of the entire dispatch cycle (or close to balance under certain losses), avoiding unreasonable accumulation or consumption of SOC during long-term operation and ensuring that the energy storage system can continuously and stably participate in the energy regulation of the power grid.

[0142] 4) The calculation method of node voltage constraint is:

[0143]

[0144] Where U i,max , U i,min Indicates the maximum and minimum voltage of node i, U i represents the voltage of line node i, N represents the number of system nodes; The flag bit for over / under crossing. When the value is 1, it is over the limit, and when the value is 0, it is not over the limit. It indicates the part of the voltage exceeding the upper limit when the voltage of node i exceeds the upper limit; It represents the part of the voltage that is lower than the lower limit (taking the absolute value) when the voltage of node i is lower than the lower limit. The constraint condition of formula (17) helps to accurately judge the voltage state in the voltage control process and avoid confusion of the control strategy.

[0145] 5) The calculation method of sensitivity constraint is:

[0146] The voltage sensitivity of the photovoltaic active output connected at node m to node k is:

[0147]

[0148] Where ΔV m is the voltage change at node m, P k is the active power of node k; is the voltage-active sensitivity of node m to node k, that is, the voltage change of node m caused by the unit power change of node k, which is the partial derivative of the voltage change of node m with respect to the active power of node k; is the intersection of the lines and nodes on the path from node 0 to node m and from node 0 to node k; R l is the line resistance, Vl is the voltage of the node on line l;

[0149] The voltage sensitivity of the photovoltaic reactive output connected at node m to node k is:

[0150]

[0151] In the formula, Q k Reactive power of node k; is the voltage-reactive power sensitivity of node m to node k, which is the partial derivative of the voltage change of node m with respect to the reactive power of node k; sign(Q k ) is Q k The sign function is positive when inductive reactive power is emitted and negative when capacitive reactive power is emitted; X l is the line reactance.

[0152] 6) The calculation method of power balance constraint is:

[0153]

[0154] In the formula, is the active power of the i-th group of energy storage at the current time t; N ES is the number of energy storage; is the active power of the ith photovoltaic group at the current time t; N PV is the number of photovoltaic units; is the active power of the i-th group of wind turbines at the current time t; N wt is the number of fan units; P Load (t) is the active power of the load at the current moment t; P grid (t) is the active power of the power grid at the current moment t.

[0155] 7) The calculation method of three-phase unbalance constraint is:

[0156] ε I %≤ε I,max % (twenty one)

[0157] In the formula, ε I % indicates the three-phase current unbalance, ε I,max % is the maximum value of three-phase unbalance;

[0158] According to the "Distribution Network Operation and Maintenance Regulations", the three-phase current imbalance is calculated as follows:

[0159]

[0160] In the formula, They are the effective values ​​of the maximum and minimum phase currents in phases A, B, and C respectively.

[0161] S2.3. The objective function of minimizing the control cost and the models of various operating constraints are established as linear programming models and solved using an open source solver;

[0162] Among them, the open source solver can adopt commercial software such as CPLEX or lpsolve.

[0163] This technical solution aims at the three-phase imbalance problem caused by the surge of distributed resources and the random access of single-phase. It proposes a flexible control technology for photovoltaic, wind power and energy storage, establishes an optimization model for three-phase imbalance control, and realizes flexible control of three-phase imbalance in low-voltage distribution network with the goal of minimizing control cost under the constraints of power flow and voltage deviation, improves the power quality of low-voltage distribution network, and ensures the safe operation of low-voltage distribution system. The new three-phase imbalance flexible control technology for low-voltage distribution network provided by this embodiment has significant control effect and technical and economic advantages, which is of great significance for improving the safety and power quality of low-voltage distribution system.

[0164] Those skilled in the art will appreciate that the process of implementing all or part of the steps of the above embodiments may be completed by hardware, or may be completed by instructing related hardware through a program.

[0165] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A three-phase unbalanced flexible control method for a low-voltage distribution network, characterized in that: The steps include: S1. Establishing voltage-active power and voltage-reactive power quantitative relationship models; specifically including: S1.

1. A radial distribution network topology is used to construct a single radial distribution network with n nodes containing photovoltaic power sources, and the voltage-active power sensitivity and voltage-reactive power sensitivity are calculated using the injection disturbance power sensitivity calculation method; S1.

2. Simultaneously solve the quantitative results of the active / reactive effects on the voltage of the low-voltage feeder with branch lines; S2. Establish a multi-objective optimization operation model for low-voltage distribution network and a resource collaborative dispatching method; specifically including: S2.

1. Set the objective function of minimizing the control cost of photovoltaic, wind turbine and energy storage; S2.

2. Set the operation constraints of the multi-objective optimization operation model of the low-voltage distribution network; the operation constraints include: photovoltaic constraints, wind turbine constraints, energy storage constraints, node voltage constraints, sensitivity constraints, power balance constraints and three-phase imbalance constraints; S2.

3. The objective function of minimizing the control cost and the model of each operating constraint condition are established as a linear programming model and solved using an open source solver.

2. The three-phase unbalanced flexible control method of a low-voltage distribution network according to claim 1 is characterized in that: In step S1.1, in a single radial distribution network with n nodes including a photovoltaic power source, the voltage of each node varies due to photovoltaic injection and load consumption of active and reactive power, and there is a problem of high voltage at some or all nodes; the calculation process of voltage-active sensitivity and voltage-reactive sensitivity is: Voltage-active power sensitivity is: Voltage-reactive sensitivity is: In the formula, is the line and node set from node 0 to node i, is the line and node set from node 0 to node j; V i is the voltage at node i, P j is the active power of node j, Q j is the reactive power of node j; is the voltage-active power sensitivity, i.e., the partial derivative of the voltage at node i with respect to the active power at node j; is the voltage-reactive power sensitivity, that is, the partial derivative of the voltage at node i with respect to the reactive power at node j; R l is the line resistance, X l is the line reactance, V l is the voltage of the node on line l.

3. The three-phase unbalanced flexible control method of low-voltage distribution network according to claim 2 is characterized in that: In step S1.2, the solution method for the low-voltage feeder with branch lines is similar, and the result is the same as that of equations (1) and (2). By comparing equations (1) and (2), the quantitative result of the effect of active / reactive power on voltage can be obtained. Assuming that the feeder adopts a unified line model, the unit resistance and reactance of the feeder of the unified model are set to r0 and x0 respectively, and the following can be obtained: It can be seen from equations (1) and (2) that the strength of the voltage-active power and voltage-reactive power coupling relationship between any two nodes is directly related to the resistance and reactance values ​​of the feeder: the larger the resistance value, the stronger the voltage-active power coupling relationship, and the larger the reactance value, the stronger the voltage-reactive power coupling relationship; vice versa; It can be seen from formula (3) that the ratio of the voltage-active power to voltage-reactive power coupling strength is equal to the ratio of the unit resistance to the reactance of the line. For the same type of line, the larger the line cross-section, the smaller the line resistance value, and the smaller r / x. The reactance value of the cable line is small, and r / x is significantly greater than that of the overhead line with the same cross-section, where r and x represent the resistance and reactance of the line respectively.

4. The three-phase unbalanced flexible control method of low-voltage distribution network according to claim 3 is characterized in that: In the voltage-active power and voltage-reactive power quantitative relationship models, the relationship between the voltage change of any node i and the node power change of the entire network can be expressed as: Where ΔV i represents the voltage change at node i, represents the voltage-active sensitivity between nodes i and j, ΔP j represents the active power change of node j, represents the voltage-reactive sensitivity between nodes i and j, ΔQ j Represents the reactive power change of node j.

5. The three-phase unbalanced flexible control method of low-voltage distribution network according to claim 1 is characterized in that: In step S2.1, the objective function of minimizing the control cost of photovoltaic, wind turbine and energy storage is expressed as follows: minp=C pv (t)+C es (t)+C wt (t) (5) In the formula, minp represents the objective of minimizing the control cost, C pv (t) represents the dispatching cost of photovoltaic power generation during period t; C es (t) represents the dispatching cost of the energy storage system; C wt (t) represents the dispatching cost of the wind turbine during period t.

6. The three-phase unbalanced flexible control method for low-voltage distribution network according to claim 5 is characterized in that: The calculation formulas for the various costs in the objective function of minimizing the control cost of photovoltaic, wind turbine and energy storage are as follows: Control costs of distributed photovoltaics: Distributed photovoltaics mainly consider the control costs of photovoltaic units. The specific expression is as follows: Where N pv Indicates the number of photovoltaic units; λ p is the photovoltaic grid-connected electricity price; ΔP pv (t) represents the control power of unit p in period t, unit: kW; δt is the duration of a time period, unit: hour; Fan control cost: The fan mainly considers the control cost of the fan unit. The specific expression is as follows: Where N wt Indicates the number of fan units; w is the on-grid electricity price of the wind turbine; ΔP wt (t) represents the control power of unit w in period t, unit: kW; δt is the duration of a time period, unit: hour; Energy storage operating costs: The operating costs of energy storage include the electricity price of energy storage charging and discharging. The specific expression is as follows: In the formula, l(t), l min , l max Respectively represent the time t value, daily minimum value, and daily maximum value of energy storage charging and discharging price, unit: yuan / kWh; Respectively represent the increased discharge power and charging power of unit e, unit: kW; N es Indicates the number of energy storage units.

7. The method for flexible control of three-phase unbalance in a low-voltage distribution network according to claim 6, characterized in that: Among the operating constraints, the calculation method of the photovoltaic constraint is: In the formula, is the regulated active power of the i-th photovoltaic group at time t, which means the active power of the i-th photovoltaic group adjusted at time t relative to its initial operating state or the operating state at the previous moment; is the active power of the i-th photovoltaic group at the current time t, indicating the actual active power that the i-th photovoltaic group can output at the current time t; is the regulated reactive power of the ith photovoltaic group at time t; S iN is the apparent power of the i-th inverter; is the maximum power angle of the ith photovoltaic group; The fan constraint is calculated as: In the formula, is the regulated active power of the i-th group of fans at time t; is the active power of the i-th group of wind turbines at the current time t; is the regulated reactive power of the i-th group of fans at time t; S iN The apparent power of the i-th fan; is the maximum power angle of the i-th group of fans.

8. The three-phase unbalanced flexible control method for low-voltage distribution network according to claim 7 is characterized in that: Among the operation constraints, the energy storage constraints include charge and discharge constraints and SOC constraints; wherein the charge and discharge constraints are calculated as follows: The charge and discharge power constraints are as follows: In the formula, They represent the maximum discharge power and maximum charging power of the energy storage unit respectively. They represent the minimum discharge power and minimum charging power of the energy storage unit respectively; the energy storage can be operated in the optimal charging power state by setting the maximum charging power and the minimum charging power; They respectively represent the increased discharge power and charging power of the energy storage unit e at time t; They represent the discharge state and charge state of energy storage, respectively. They are both 0-1 variables. When the value is 1, it means discharge / charge, and when the value is 0, it means no discharge / no charge. The two are mutually exclusive, that is, they meet the following constraints: The calculation method of SOC constraint is: In the formula, represents the SOC of unit e in period t, represents the SOC of unit e at time t-1, Respectively represent the maximum and minimum allowable values ​​of SOC: It represents the charge and discharge power of unit e at time t, with charging being positive and discharging being negative; SOC(0) represents the initial capacity of SOC, and SOC(N) represents the SOC capacity of the last period.

9. The three-phase unbalanced flexible control method of a low-voltage distribution network according to claim 8, characterized in that: Among the operation constraints, the calculation method of the node voltage constraint is: Where U i,max , U i，min Indicates the maximum and minimum voltage of node i, U i represents the voltage of line node i, N represents the number of system nodes; The flag bit for over / under crossing. When the value is 1, it is over the limit, and when the value is 0, it is not over the limit. It indicates the part of the voltage exceeding the upper limit when the voltage of node i exceeds the upper limit; It means that when the voltage of node i is lower than the lower limit, the absolute value of the voltage below the lower limit is taken; The sensitivity constraint is calculated as: The voltage sensitivity of the photovoltaic active output connected at node m to node k is: Where, ΔV m is the voltage change at node m, P k is the active power of node k; is the voltage-active sensitivity of node m to node k, that is, the voltage change of node m caused by the unit power change of node k, which is the partial derivative of the voltage change of node m with respect to the active power of node k; is the intersection of the lines and nodes on the path from node 0 to node m and from node 0 to node k; R l is the line resistance, V l is the voltage of the node on line l; The voltage sensitivity of the photovoltaic reactive output connected at node m to node k is: In the formula, Q k Reactive power of node k; is the voltage-reactive power sensitivity of node m to node k, which is the partial derivative of the voltage change of node m with respect to the reactive power of node k; sign(Q k ) is Q k The sign function is positive when inductive reactive power is emitted and negative when capacitive reactive power is emitted; X l is the line reactance.

10. The three-phase unbalanced flexible control method of low-voltage distribution network according to claim 9, characterized in that: Among the operating constraints, the calculation method of the power balance constraint is: In the formula, is the active power of the i-th group of energy storage at the current time t; N ES is the number of energy storage; is the active power of the ith photovoltaic group at the current time t; N PV is the number of photovoltaic units; is the active power of the i-th group of wind turbines at the current time t; N wt is the number of fan units; P Load (t) is the active power of the load at the current moment t; P grid (t is the active power of the power grid at the current moment t; The calculation method of the three-phase unbalance constraint is: e I %≤e I,max %21 In the formula, ε I % indicates the three-phase current unbalance, ε I,max % is the maximum value of three-phase unbalance; Calculate the three-phase current unbalance, the expression is as follows: In the formula, They are the effective values ​​of the maximum and minimum phase currents in phases A, B, and C respectively.

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