Method for uniformly quantifying flexible resource safety adjustment capability of power distribution network

Abstract

The invention discloses a method for uniformly quantifying the flexible resource safety regulation capability of a power distribution network, which mainly comprises the definition, calculation and application of the flexible resource safety regulation capability of the power distribution network, and comprises the following steps of: acquiring static data and dynamic data of a power distribution system; the flexible resource safety regulation capability is defined as follows: flexible resources in a certain range of the medium-voltage power distribution network conform to the safety demand direction and can continuously exceed the power regulation quantity required by the safety demand time at a certain operation moment; comprising node safety adjustment capability, feeder safety adjustment capability and feeder priority safety adjustment capability; the real-time safety monitoring and early warning of the safety adjusting capability are considered before the fault; and after the fault, performing safety emergency control considering the safety regulation capability, wherein the safety emergency control comprises safety demand analysis, control result pre-judgment and control scheme generation. According to the invention, the safety regulation capability is applied to the safety monitoring function of the power distribution network, so that the potential of flexible resources is fully utilized.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent distribution network security analysis, and in particular relates to a method for uniformly quantifying the security regulation capability of flexible resources in a distribution network. Background Art

[0002] Flexible resources such as distributed generation, energy storage, demand response, microgrids, and flexible soft switches are increasingly appearing on the distribution system side. Since the power of flexible resources is adjustable, they provide new control methods for distribution network operators.

[0003] There have been many studies on the operation of power systems considering flexible resources. They take into account the role of flexible resources by adding the active and reactive power of flexible resources into the power flow equation. There are literatures on the optimal dispatch of transmission networks considering multiple flexible resources. [1-5] There are some papers focusing on distribution network security, including renewable energy and different types of flexible resources for distribution network security analysis. [6-10] , some of which take into account N-1 safety constraints [6-8] There are also literatures that consider the safety constraints of normal operation of distribution networks, establish optimization models and algorithms for operation, and obtain the optimization results of distribution network operation under the participation of flexible resources. [11-15] These literatures use the adjustable power of flexible resources to relax operational constraints such as capacity and voltage, achieving effects that cannot be achieved without flexible resources.

[0004] Describing the power regulation of flexible resources is a basic task. Most literature models list the operating constraints of various flexible resources and describe the regulation capabilities of different flexible resources separately. [1,6,11,16] There are many types of flexible resources, and the operating principles and mechanisms of different types of flexible resources are different; different types of flexible resources may also form multiple combinations on the low-voltage side, resulting in a complex model. References [17-19] established a unified power node model that integrates parameters related to power regulation, such as "power curtailment", "loaded shedding", and "energy storage capacity". However, there is currently no unified indicator to quantify the maximum power regulation of flexible resources, that is, the flexible resource regulation capacity.

[0005] [References]

[0006] [1]REDDY S.Surender.Optimal scheduling of thermal-wind-solar powersystem with storage[J].Renewable Energy.2017,101:1357-1368.

[0007] [2]HE Zhenglei, LIU Chang, WANG Yutao, et al. Optimal operation of wind-solar-thermal collaborative power system considering carbon trading and energystorage[J].Applied Energy.2023,352:121993.

[0008] [3]HU Jingzhe, CONG Hao, JIANG Chuanwen. Coordinated scheduling model of power system with active distribution networks based on multi-agent system [J]. Journal of Modern Power Systems and Clean Energy. 2018, 6(3): 521-531.

[0009] [4] LI N., C.,CONSTANTINESCU EM,et al.Flexible Operation of Batteries in Power System Scheduling With Renewable Energy[J].IEEETransactions on Sustainable Energy.2016,7(2):685-696.

[0010] [5] Shao Jiangcheng, Li Wenwu, Qiu Xianda, et al. An optimal dispatching method for a pumped storage power system considering demand response and deep peak regulation of thermal power[P]. Hubei Province: CN202310743062.0, 2023-10-27.

[0011] [6] Xiao Jun, Zu Guoqiang, Zhou Huan, et al. Full quadrant security domain of active distribution network[J]. Automation of Electric Power Systems, 2017, 41(21): 79-85.

[0012] [7]ZU Guoqiang,XIAO Jun,SUN Kai.Mathematical Base and Deduction ofSecurity Region for Distribution Systems With DER[J].IEEE Transactions onSmart Grid.2019,10(3):2892-2903.

[0013] [8] Xiao Jun, Gang Fayun, Deng Weimin, et al. Security domain model of flexible distribution network[J]. Power System Technology, 2017, 41(12): 3764-3774.

[0014] [9] Xiao Jun, Bao Zhenyu, She Buxin. A method for calculating the absorption capacity of active distribution network based on TAC curve [P]. Tianjin: CN201910940422.X, 2020-01-10.

[0015]

[10] Xiao Jun, Wang Chuanqi, Li Xiaohui. Calculation method and analysis application of DG absorption capacity curve of urban distribution network[J]. Electric Power Automation Equipment, 2023, 43(10): 200-207.

[0016]

[11] KARTHIKEYAN N.,PILLAI JR,BAK-JENSEN B.,et al.Predictive Control of Flexible Resources for Demand Response in Active Distribution Networks[J].IEEE Transactions on Power Systems.2019,34(4):2957-2969.

[0017]

[12] Liao Bin, Xie Wenzheng, Wang Wenyuan, et al. Coordinated optimization dispatching method for energy storage participating in distribution network interaction based on demand response [P]. Beijing: CN202410084287.4, 2024-05-14.

[0018]

[13] Song Meng, Yao Yunting, Gao Ciwei, et al. A distribution network load recovery method and system considering 5G base station backup energy storage [P]. Jiangsu Province: CN202310550359.5, 2024-05-28.

[0019]

[14] WATSON JD,WATSON NR,LESTAS I.Optimized Dispatch of EnergyStorage Systems in Unbalanced Distribution Networks[J].IEEE Transactions onSustainable Energy.2018,9(2):639-650.

[0020]

[15] Sun Kai, Wan Ye, Di Rui, et al. A multi-objective decision-making method for distributed photovoltaic dispatching in distribution networks[P]. Jiangsu Province: CN202311564877.9, 2024-05-07.

[0021]

[16] RAHIMINEJAD A.,VAHIDI B.,HEJAZI MA,et al.Optimal scheduling ofdispatchabledistributed generation in smart environment with the aimof energyloss minimization[J].Energy.2016,116:190-201.

[0022]

[17] ULBIG A.,ANDERSSON G.On operational flexibility in power systems[C] / / 2012IEEE Power and Energy Society General Meeting,2012,1-8.

[0023]

[18] HEUSSEN K.,KOCH S.,ULBIG A.,et al.Unified System-Level Modelingof Intermittent Renewable Energy Sources and Energy Storage for Power SystemOperation[J].IEEE Systems Journal.2012,6(1):140-151.

[0024]

[19] ULBIG Andreas, ANDERSSON Analyzing operational flexibility of electric power systems[J].International Journal of Electrical Power&EnergySystems.2015,72:155-164.

[0025]

[20] XIAO Jun,HE Qibo,ZU Guoqiang.Distribution management systemframework based on security region for future low carbon distribution systems[J].Journal of Modern Power Systems and Clean Energy.2015,3(4):544-555.

[0026]

[21] Xiao Jun, Zhen Guodong, Wang Bo, et al. Safety distance of distribution network: definition and method[J]. Proceedings of the CSEE, 2017, 37(10): 2840-2851.

[0027]

[22] Xiao Jun, Zhang Baoqiang, Shao Jingpeng, et al. A full-dimensional observation method for distribution network security domain[P]. Tianjin: CN201710706170.5, 2020-07-10.

[0028]

[23] Hao Ziyuan. Research on distribution network security domain and power supply capacity considering transmission and distribution coordination demand response[D]. Tianjin University, 2020. Summary of the invention

[0029] The access of various flexible resources to the distribution system requires the updating of security analysis content and methods. The most important thing is to quantify the effect of power regulation of flexible resources on the safety of the distribution network. The present invention provides the definition and calculation of the security regulating capability (SRC) of flexible resources in the distribution network, which can uniformly quantify the regulation capability of flexible resources for the safety of the distribution network. After the distribution network integrates various flexible resources, the security analysis needs to consider the power regulation of flexible resources. The present invention also provides an application method of the security regulation capability, proposes a security monitoring, early warning and emergency control method taking into account the security regulation capability, and proposes a flexible resource security regulation capability indicator to uniformly quantify the maximum power regulation amount of flexible resources in the distribution network, and use the security regulation capability in the security monitoring function of the distribution network to fully utilize the potential of flexible resources.

[0030] The distribution network of the present invention refers to a 10kV medium voltage distribution network. The flexible resources of the present invention include: distributed generation (DG), energy storage system (ESS), demand response (DR), microgrid (MG), and soft open point (SOP). Among them, DG includes intermittent DG (IDG) and controllable distributed generation (CDG). IDG includes wind turbines (WT) and photovoltaics (PV); CDG includes diesel generators, biomass power generation, etc. DG can be centralized and connected to the medium voltage distribution network through a step-up transformer; it can also be distributed and connected to the low voltage side of the distribution transformer.

[0031] In order to solve the above technical problems, the present invention proposes a method for uniformly quantifying the safe regulation capability of flexible resources of distribution networks, including the definition, calculation and application of the safe regulation capability of flexible resources of distribution networks, and the steps are as follows:

[0032] Step 1: Collect data, including static data and dynamic data of the power distribution system;

[0033] Step 2: Determine the direction and time of security requirements:

[0034] The safety demand direction is the power regulation direction required by the distribution network, including increasing outflow (OUT+), reducing outflow (OUT-), increasing injection (IN+), and reducing injection (IN-). The safety demand direction is different in different distribution network operation scenarios. According to the branch power flow direction, the power supply scenario and the reverse transmission scenario are divided. In the power supply scenario, the forward power flow overload or voltage exceeding the lower limit is prone to occur or approach after the accident, and the safety demand direction is to reduce the outflow or increase the injection; in the reverse transmission scenario, the reverse power flow overload or voltage exceeding the upper limit is prone to occur or approach after the accident, and the safety demand direction is to increase the outflow or reduce the injection.

[0035] The safety demand time is the shortest time that the distribution network needs to adjust and maintain node power, denoted as ΔT S . In calculating the user demand response and energy storage SRC, ΔT is required S . ΔT can be set according to the distribution network fault processing time requirements S .

[0036] Step 3: Calculate the safety regulation capacity (SRC):

[0037] The flexible resource safety regulation capability is defined as: at a certain operating moment, the flexible resources within a certain range of the medium voltage distribution network meet the safety demand direction and can continuously exceed the power regulation amount required for the safety demand time; including: node SRC, feeder SRC and feeder priority SRC;

[0038] 3-1) Node SRC

[0039] Node SRC is defined as the maximum power adjustment that the medium voltage node can make based on the current power according to the safety demand direction. The increase and decrease of node outflow and injection power are achieved through internal flexible resource adjustment. i Safety Regulation Capability is denoted as SRC i (t).

[0040]

[0041] Where: k∈N i Indicates that flexible resource k is in node N i within; D k represents the power adjustable direction of flexible resource k; ΔS k D (t) represents the flexible resource k along direction D at time t k The amount of power that can be adjusted.

[0042] 3-2) Feeder SRC

[0043] Feeder SRC is defined as, feeder F j The sum of the safety regulation capabilities of all nodes on the feeder F at time t j Safety Regulation Capability is denoted as SRC Fj (t).

[0044]

[0045] Where: N i ∈F j Represents node N i In the feeder F j superior.

[0046] Because the SRC of the flexible soft switch at N-0 and after N-1 is different, the feeder SRC is also different in the N-0 and N-1 scenarios, which are recorded as and

[0047] 3-3) Feeder Priority SRC

[0048] Feeder priority SRC is defined as, feeder F j The sum of the SRCs of all nodes that do not affect the user. It is the SRC that should be used first. Feeder F jThe node set that does not affect the user in the above security adjustment is recorded as Feeder F at time t j The priority SRC is recorded as PSRC Fj (t),

[0049]

[0050] The safety regulation of the flexible soft switch does not affect the user, so the feeder PSRC includes the SRC of the SOP. Also, because the SRC of the SOP at N-0 is different from that after N-1, the feeder PSRC is also different in the N-0 and N-1 scenarios, which are recorded as and

[0051] Step 4: Real-time safety monitoring and early warning of SRC before failure

[0052] Distribution network security monitoring and early warning refers to the use of collected dynamic data to monitor, discover safety problems and hidden dangers and issue early warnings

[20] The monitoring data of the existing methods are mainly the real-time operating point and its safety margin. According to the Distribution System Security Region (DSSR) theory, the safety boundary of the system is calculated in advance.

[20] ; The operating point is composed of the real-time power of the distribution network; The safety margin is usually reflected by the safety distance, that is, the distance from the operating point to the safety boundary [21-22] When the operating point N-0 is unsafe, the system will give an alarm; when the operating point N-0 is safe but N-1 is unsafe, the system will give an early warning.

[0053] In the actual system, the present invention can be used to add flexible resource adjustment capability data to the security monitoring data, and calculate the SRC data of nodes and feeders at all levels in real time. After the dispatcher has real-time grasp of the SRC data at all levels, when no fault occurs, he can grasp the size and change trend of the flexible resource adjustment capability of nodes, feeders, and the entire network in real time.

[0054] Safety assessment is the main theoretical tool for safety monitoring and early warning, and the flexible resource adjustment capability will affect the safety assessment results. For example, if the operating point N-1 is unsafe, an early warning is required; but if the flexible resource adjustment capability is taken into account, an early warning may not be required. This paper comprehensively evaluates the safety status of the system based on the safety distance and SRC: after determining the current operating point, the operating point after the SRC is applied is also simulated; if the operating point N-1 itself is unsafe, but N-1 is safe after SRC is taken into account, no early warning is required.

[0055] Step 5: Safety emergency control of SRC after failure, including: safety demand analysis, control result prediction and control plan generation;

[0056] 5-1) After an accident occurs, conduct a safety demand analysis based on the safety issues that arise; determine the safety demand direction based on the scenarios where the safety issues arise d (χ); in the power supply scenario, it is to reduce the outflow in the OUT- direction or increase the injection in the IN+ direction; in the reverse delivery scenario, it is to increase the outflow in the OUT+ direction or reduce the injection in the IN- direction; according to the degree of over-limit of the safety problem, calculate the safety demand ΔS d (χ);

[0057] ΔS d (χ)=M(1+r)ΔS (4)

[0058] In formula (4), ΔS refers to the power of the feeder overload exceeding the rated capacity, r is the network loss coefficient, and M is the margin coefficient; the physical meaning is how much the power of the overloaded feeder can be reduced to restore to normal with a certain margin.

[0059] 5-2) Prediction of control results

[0060] (1) Calculate the available SRC for security problem x. Available SRC is defined as the SRC in the distribution network that can be used to handle security problem x, which is equal to the sum of the SRCs of all nodes related to security problem x. The set of nodes related to security problem x is denoted as N(x). The available security regulation capacity for security problem x is denoted as SRC(x).

[0061]

[0062] Where: N i ∈N(χ) indicates that the node N i Related to the security issue χ.

[0063] (2) Calculate the available priority SRC of the security problem χ. The available priority SRC is defined as the number of all the security problems in the distribution network. χ The sum of the node security adjustment capabilities that do not affect users. χ The set of nodes that are relevant and whose security adjustments do not affect users is denoted as N NA The available security adjustment capability for security issue χ that does not affect users is denoted as PSRC(χ).

[0064]

[0065] (3) Compare the available safety regulation capacity SRC(χ), the available priority safety regulation capacity PSRC(χ) and the safety demand ΔS d Size of (χ):

[0066] If ΔS d(χ)≤PSRC(χ)≤SRC(χ), then flexible resource security adjustment can solve the security problem χ without affecting users;

[0067] If PSRC(χ)<ΔS d (χ)≤SRC(χ), then flexible resource security adjustment can solve the security problem χ, but it will affect users;

[0068] If PSRC(χ)≤SRC(χ)<ΔS d (χ), then flexible resource security regulation cannot solve the security problem χ;

[0069] 5-3) Control scheme generation

[0070] Generate control plans based on the principles of reducing the impact on users and reducing the number of operations.

[0071] Deduct N(χ), N NA The nodes with SRC of 0 in (χ) are the set of nodes N that can participate in the regulation. PR (χ), a set of nodes that can participate in regulation without affecting users

[0072] If flexible resource security adjustment can solve security issues without affecting users. Compare SRC in turn i and safety requirement ΔS d (χ) size: when SRC i ≥ΔS d (χ), then only N i Security adjustment can solve the security problem χ and generate alternative solutions; otherwise, it cannot. If the single node security adjustment in cannot solve χ, then consider multiple node security adjustments and increase the number of nodes one by one based on the principle of reducing the number of operations.

[0073] If flexible resource security adjustment can solve the security problem, it will affect users. After all the SRCs of all nodes in the , that is, all the available priority SRCs, still cannot meet the safety requirements. At this time, further select N PR (χ) But For nodes other than χ, use the available SRC that affects the user. Similarly, first consider single node security adjustment; when single node security adjustment cannot solve χ, then consider multiple node security adjustment, and increase the number of nodes one by one according to the principle of reducing the number of operations.

[0074] Furthermore, the method for uniformly quantifying the safe regulation capability of flexible resources in a distribution network according to the present invention comprises:

[0075] The distribution network refers to a 10kV medium voltage distribution network.

[0076] The flexible resources include: distributed generation, energy storage, demand response, microgrid, and flexible soft switch. Among them, the distributed generation includes intermittent distributed generation and controllable distributed generation; the intermittent distributed generation includes wind turbines and photovoltaics; the controllable distributed generation includes diesel generators and biomass power generation.

[0077] The distributed generation is connected to the medium voltage distribution network through a step-up transformer or to the low voltage side of a distribution transformer.

[0078] The static data include: 10kV side main connection of 110kV substation; 110kV main transformer capacity; 10kV distribution network topology; feeder capacity; distribution transformer capacity; centralized wind and solar capacity; public energy storage capacity, upper and lower limits of state of charge, charging and discharging efficiency; distributed generation capacity of low-voltage substations; each energy storage capacity, upper and lower limits of state of charge, charging and discharging efficiency; maximum reduction ratio of demand response load agreement, maximum increase ratio of agreement

[23] ; Flexible soft switching capacity.

[0079] The dynamic data include: feeder switch status, current at the switch; medium voltage active and reactive power of distribution transformer; centralized wind and solar active and reactive power, public energy storage active and reactive power, and charge status; distributed power generation active and reactive power in low-voltage substations, active and reactive power of energy storage, and charge status; flexible soft switch port active and reactive power.

[0080] Compared with the prior art, the present invention has the following beneficial effects:

[0081] The present invention proposes a definition, calculation and application method of the safety regulation capability of the distribution network's flexible resources. The safety regulation capability uniformly quantifies the maximum power regulation amount of the flexible resources, so that the distribution network dispatchers can grasp the flexible resource regulation capability of the distribution network in real time. Then, a comprehensive safety assessment taking into account the safety regulation capability can be performed before a fault occurs, and the assessment is more accurate and comprehensive; after a fault occurs, the safety regulation capability is used for emergency safety control, which can help improve the safety level of the distribution system operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] Figure 1 This is a distribution network example with multiple flexible resources;

[0083] Figure 2 It is the 24-hour SRC result of different nodes;

[0084] Figure 3 Safety monitoring based on safety distance and SRC (feeder F1), where (a) is feeder SRC (F1), (b) is N-0 safety distance (F1), and (c) is N-1 safety distance (F1);

[0085] Figure 4It is the safety assessment based on safety distance and SRC before N-1 fault (18h);

[0086] Figure 5 It is the power, SRC and fault location at 18h. DETAILED DESCRIPTION

[0087] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, but the following embodiments are by no means intended to limit the present invention in any way.

[0088] 1. Basic information of the instance

[0089] The distribution network example Figure 1 As shown. In addition to the load (Load, L), the example considers flexible resources including distributed generation (DG), energy storage (ESS), demand response (DR), microgrid (MG), and flexible soft switch (SOP). Among them, DG is divided into intermittent DG (IDG) and controllable DG (CDG). IDG includes centralized wind turbines (WT), photovoltaics (PV), and distributed user IDG. The feeder capacity is 7MVA.

[0090] 2. A method for realizing a unified quantitative distribution network flexible resource security regulation capability for an example, comprising the following steps: (1) collecting data

[0091] The basic data of the node is shown in Table 1.

[0092] Table 1 Node basic data

[0093]

[0094]

[0095] The upper and lower limits of the state of charge (SOC) of the ESS are 100% and 25%, and the charge and discharge efficiency is 0.95. The SOP port capacity is 4MVA.

[0096] The centralized wind and solar power of nodes 3, 10, and 13 is shown in Table 2-1.

[0097] The public ESS power and SOC of node 7 are shown in Table 2-2 and Table 2-3.

[0098] The power on the medium voltage side of the distribution transformer is shown in Table 2-4.

[0099] The SOP port power is shown in Table 2-5.

[0100] The DG power of the low-voltage side of the distribution transformers at nodes 4, 5, 11, and 12 is shown in Table 2-6.

[0101] The ESS power and SOC of the low-voltage side area of ​​nodes 6, 11, and 14 are shown in Table 2-7 and Table 2-8.

[0102] Table 2-1

[0103]

[0104] Table 2-2

[0105]

[0106] Table 2-3

[0107]

[0108]

[0109] Table 2-4

[0110]

[0111]

[0112] Table 2-5

[0113]

[0114] Table 2-6

[0115]

[0116] Table 2-7

[0117]

[0118]

[0119] Table 2-8

[0120]

[0121] (2) Determine the direction and time of security requirements

[0122] Assume that 1:00-5:00 is the reverse delivery scenario, and the safety requirement direction is OUT+ or IN-; 6:00-24:00 is the power supply scenario, and the safety requirement direction is OUT- or IN+.

[0123] Safety demand time ΔT S Set to 1h.

[0124] (3) Calculate SRC

[0125] The 24-hour SRC results of node 4 are shown in Table 3.

[0126] Table 3 24-hour SRC results of example node 4

[0127]

[0128]

[0129] The 24-hour SRC results of different nodes are as follows Figure 2 shown.

[0130] The SRC of feeder F1 at typical times is shown in Table 4.

[0131] Table 4 Feeder F1 SRC

[0132]

[0133]

[0134] (4) Real-time safety monitoring and early warning of SRC before failure

[0135] Feeder SRC real-time data is an important data for dispatchers to monitor safety. For example, the SRC safety monitoring of feeder F1 at 18 hours is as follows: Figure 3 As shown in (a). Figure 3 As can be seen in (b), the N-0 safety distance is greater than 0; after considering SRC, the N-0 safety distance is further increased. Figure 3 It can be seen from (c) that at 18h, the N-1 safety distance is negative and the system N-1 is unsafe; after the PSRC acts, the N-1 safety distance increases but remains negative; after the SRC acts, the N-1 safety distance increases and turns to 1540kVA, and the system turns from N-1 unsafe to safe.

[0136] Comprehensively evaluate the system safety status based on the real-time operating point and SRC data. Safety boundaries, operating points, and operating points after simulating SRC action are as follows: Figure 4 As shown. Figure 4 see:

[0137] (4-1) The operating point is within the N-0 safety boundary but outside the N-1 safety boundary. N-1 is unsafe. If SRC is not taken into account, an early warning is required.

[0138] (4-2) After N-1, if the SRC of feeders F1 and F2 is activated, the operating point can enter the N-1 safety boundary, and the safety distance is 1540kVA. Therefore, considering the SRC, N-1 is safe and no warning is required.

[0139] (4-3) After N-1, if only PSRC is in effect, that is, SRC does not affect the user, the operating point cannot enter the N-1 safety boundary.

[0140] (5) Safety emergency control taking SRC into account after a fault

[0141] 5-1) Security Requirements Analysis

[0142] Take the accident at 18h as an example: feeder segment F on feeder F2 2,3 N-1 fault occurs. The fault location and the power of each node, node SRC and feeder SRC at this time are shown in Figure 5 , where the red characters refer to real-time security regulation capability data.

[0143] After the accident, the fault section was isolated and the load was transferred. The load downstream of the F2 fault point was transferred from F1 through SOP.

[0144] After N-1 transfer, a safety problem will arise: F1 export capacity exceeds the limit ΔS = 2249kVA.

[0145] Because the safety issue χ occurs when the capacity exceeds the limit in the power supply scenario, the safety demand direction is determined to reduce outflow and increase injection.

[0146] Considering the network loss and safety margin, the safety demand is calculated by formula (4), r is taken as 2%, and M is taken as 1.08.

[0147] ΔS d (χ) = M (1 + r) ΔS = 2477 kVA

[0148] 5-2) Prediction of control results

[0149] Calculate the available SRC of security problem χ. Find the relevant nodes through topological search based on the location of security problem χ. After N-1 transfer, the nodes downstream of F1 exit are related to χ, that is, N(χ)={N2,N3,N4,N5,N6,N7,N 15 ,N 16 ,N 14 ,N 13 ,N 12 ,N 11}. The available SRC of χ is calculated by formula (5):

[0150]

[0151] Then calculate the available SRC that does not affect the user. The node set N that does not affect the user NA (χ)={N7,N 15 ,N 16 ,N 14}, the available SRC of χ that does not affect the user is calculated by formula (6)

[0152]

[0153] The safety demand is 2477 kVA. The available SRC that does not affect the user is less than the safety demand, but the available SRC is greater than the safety demand. The predicted control result is: the safe adjustment of flexible resources on the feeder can solve the safety problem χ, but it will affect the user.

[0154] 5-3) Control scheme generation

[0155] Deduct N(χ), N NA The nodes with SRC of 0 in (χ) are the set of nodes N that can participate in the regulation. PR (χ) = {N4,N5,N7,N 11 ,N 14}, a set of nodes that can participate in regulation without affecting users

[0156] According to the principle of reducing the impact on users and reducing the number of operations, emergency control plans 1 to 4 are generated as shown in Table 5.

[0157] Table 5 Emergency control schemes and effects taking SRC into account

[0158]

[0159]

[0160] If you can accept a small safety margin after N-1 and pay more attention to the impact on users and the number of operations, you can use solution 1. If you pay more attention to the safety margin after N-1 and can accept a certain user impact and a slightly higher number of operations, you can use solution 2, 3 or 4.

[0161] Although the present invention has been described above in conjunction with the accompanying drawings, the present invention is not limited to the above-mentioned specific embodiments, which are merely illustrative rather than restrictive. Under the guidance of the present invention, ordinary technicians in this field can make many improvements and changes without departing from the purpose of the present invention, which are all within the protection of the present invention.

Claims

1. A unified method for quantifying the secure regulation capability of distribution network flexible resources, including the definition, calculation, and application of the secure regulation capability of distribution network flexible resources, is provided. The steps are as follows: Step 1: Collect data, including static and dynamic data of the power distribution system; Step 2: Determine the direction and time of security requirements: The safety demand direction is different in different distribution network operation scenarios. The distribution network operation scenarios are divided into power supply scenarios and reverse flow scenarios according to the branch flow direction. In the power supply scenario, the safety demand direction is to reduce the outflow direction or increase the injection direction. In the reverse flow scenario, the safety demand direction is to increase the outflow direction or reduce the injection direction. The safety demand time is the shortest time that the distribution network needs to regulate and maintain node power, and is set according to the distribution network fault processing time requirements; Step 3: Definition and calculation of flexible resource security adjustment capability: The flexible resource safety regulation capability is defined as the ability of flexible resources within a certain range of the medium-voltage distribution network to meet safety requirements and continuously exceed the safety requirements for a certain period of time at a certain operating moment. This includes: Node safety regulation capability, feeder safety regulation capability, and feeder priority safety regulation capability; 3-1) The node safety regulation capability is defined as: the maximum power regulation that the medium voltage side node can make based on the current power according to the direction of safety requirements; the increase and decrease of the node outflow and injection power are achieved through internal flexible resource regulation; at time t, the node N i Security Regulation Capability is denoted as SRC i (t); In formula (1): k∈N i Indicates that flexible resource k is in node N i within; D k represents the power adjustable direction of flexible resource k; Denotes the flexible resource k at time t along direction D k The power can be adjusted; 3-2) The feeder safety regulation capability is defined as: feeder F j The sum of the safety regulation capabilities of all nodes on the feeder F at time t j Security Regulation Capability is denoted as SRC Fj (t); In formula (2): N i ∈F j Represents node N i On feeder F j superior; The feeder safety regulation capability in N-0 and N-1 scenarios is respectively denoted as and 3-3) The feeder priority safety regulation capability is defined as: feeder F j The sum of the security adjustment capabilities of all nodes that do not affect users; feeder F j The node set that does not affect the user in the above security adjustment is recorded as Feeder F at time t j Priority Security Regulation Capability is denoted as PSRC Fj (t), The feeder priority safety regulation capabilities in N-0 and N-1 scenarios are and Step 4: Real-time safety monitoring and early warning of pre-fault and safety regulation capabilities: Distribution network safety monitoring and early warning refers to the use of collected dynamic data to monitor the real-time operating point and its safety margin; The operating point consists of the real-time power of the distribution network; The safety margin is reflected by the distance between the operating point and the safety boundary. After determining the current operating point, the operating point after the safety regulation capability is applied is simulated. When the operating point N-0 is unsafe, the system will give an alarm; When operating point N-0 is safe but N-1 is not, if N-1 is safe after taking into account the safety regulation capability, no warning is required; Otherwise, the system will issue an early warning; Step 5: Safety emergency control taking into account safety regulation capabilities after a fault, including: safety demand analysis, control result prediction and control plan generation; 5-1) After an accident occurs, conduct a safety needs analysis based on the safety issues that arise; Determine the security requirements based on the scenarios where security issues occur. d (χ); in the power supply scenario, is the outflow direction reduced or the injection direction increased? In the reverse flow scenario, is the outflow direction increased or the injection direction reduced? According to the degree of safety problem exceeding the limit, calculate the safety demand ΔS d (χ); ΔS d (x)=M(1+r)ΔS (4) In formula (4): ΔS refers to the power of the feeder overload exceeding the rated capacity, r is the network loss coefficient, and M is the margin coefficient; 5-2) Prediction of control results, including: The available security regulation capacity for calculating security problem χ is defined as follows: the security regulation capacity available in the distribution network for handling security problem χ is equal to the sum of the security regulation capacities of all nodes related to security problem χ; the set of nodes related to security problem χ is denoted as N(χ); the available security regulation capacity for security problem χ is denoted as SRC(χ); In formula (5): N i ∈N(χ) node N i Related to safety issues χ; The available priority safety regulation capacity for calculating the safety problem χ is defined as the sum of the safety regulation capacities of all nodes in the distribution network that are related to the safety problem χ and do not affect users; χ The set of nodes that are relevant and whose security adjustments do not affect users is recorded as N NA (χ); the available priority security regulation capacity for security problem χ is denoted as PSRC(χ); Compare the available safety regulation capacity SRC(χ), the available priority safety regulation capacity PSRC(χ) and the safety demand ΔS d Size of (χ): If ΔS d (χ)≤PSRC(χ)≤SRC(χ), then flexible resource security adjustment can solve the security problem χ without affecting users; If PSRC(χ)<ΔS d (χ)≤SRC(χ), then flexible resource security adjustment can solve the security problem χ, but it will affect users; If PSRC(χ)≤SRC(χ)<ΔS d (χ), then flexible resource security regulation cannot solve the security problem χ; 5-3) Generate control plans based on the principle of minimizing the impact on users and reducing the number of operations: Subtract node set N(χ) and node set N NA The nodes with security regulation capability SRC of 0 in (χ) are the set of nodes N that can participate in regulation. PR (χ) and the set of nodes that can participate in the adjustment without affecting the user If flexible resource security adjustment can solve the security problem χ without affecting users; Compare nodes N in turn i Security Regulation Capability (SRC) i and safety requirement ΔS d (χ) size: when SRC i ≥ΔS d (χ), then only N i Security adjustment can solve the security problem χ and generate alternative solutions; otherwise it cannot; when If the single node security adjustment in [1] cannot solve χ, then consider multi-node security adjustment and increase the number of nodes one by one according to the principle of reducing the number of operations; If flexible resource security adjustment can solve the security problem χ, but it will affect users; select the node set N that can participate in the adjustment PR (χ) is a set of nodes that can participate in the adjustment and do not affect the user The available security adjustment capacity SRC(χ) of the nodes other than χ is considered; in this process, the security adjustment of a single node is considered first; when the security adjustment of a single node cannot solve χ, the security adjustment of multiple nodes is considered, and the number of nodes is increased one by one according to the principle of reducing the number of operations.

2. The method for uniformly quantifying the security regulation capability of flexible resources in a distribution network according to claim 2 is characterized in that: The distribution network mentioned refers to a 10kV medium voltage distribution network.

3. The method for uniformly quantifying the secure regulation capability of flexible resources in a distribution network according to claim 1, characterized in that: The flexible resources include: distributed generation, energy storage, demand response, microgrids, and flexible soft switches; among them, the distributed generation includes intermittent distributed generation and controllable distributed generation; the intermittent distributed generation includes wind turbines and photovoltaics; the controllable distributed generation includes diesel generators and biomass power generation.

4. The method for uniformly quantifying the secure regulation capability of flexible resources in a distribution network according to claim 3, characterized in that: The distributed generation is connected to the medium voltage distribution network through a step-up transformer.

5. The method for uniformly quantifying the secure regulation capability of flexible resources in a distribution network according to claim 3, characterized in that: The distributed generation is connected to the low voltage side of the distribution transformer.

6. The method for uniformly quantifying the secure regulation capability of flexible resources in a distribution network according to claim 1, characterized in that: In step 1, the static data includes: 10kV side main connection of 110kV substation; 110kV main transformer capacity; 10kV distribution network topology; feeder capacity; distribution transformer capacity; centralized wind and solar capacity; public energy storage capacity, upper and lower limits of state of charge, and charge and discharge efficiency; distributed power generation capacity of low-voltage substations; each energy storage capacity, upper and lower limits of state of charge, and charge and discharge efficiency; maximum reduction ratio of demand response load agreement, and maximum increase ratio of agreement [23] ; Flexible soft switching capacity.

7. The method for uniformly quantifying the secure regulation capability of flexible resources in a distribution network according to claim 1, characterized in that: In step 1, the dynamic data includes: feeder switch status, switch current; distribution transformer medium voltage active power and reactive power; centralized wind and solar active power and reactive power, public energy storage active power and reactive power, and charge status; each distributed generation in the low-voltage substation active power and reactive power, each energy storage active power and reactive power, and charge status; flexible soft switch port active power and reactive power.

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