Quantitative analysis method of active distribution network operation flexibility based on node marginal electricity price

Abstract

A method for quantitative analysis of the operational flexibility of an active distribution network based on node marginal electricity prices: according to the selected active distribution network, the parameter information of the active distribution network and the daily operating status of the distribution network obtained by calculating the current flow of the active distribution network a day ago are input; according to the provided content, a quantitative constraint on the operational flexibility of the active distribution network is established; an active distribution network operational flexibility conduction model based on node net power is established, and the flexibility-node net power sensitivity factor is calculated; a Lagrangian dual function for pricing the operational flexibility of the distribution network is established, and the flexibility price results of the node net active power and the node net reactive power of different nodes in each time period are solved; the results are output to power users with flexible resources to guide power users to adjust the operational strategy of dispatchable resources. The present invention realizes flexibility quantification under a unified framework, provides reference information for the optimal scheduling of multiple types of flexible equipment on the source-grid-load-storage side in the active distribution network, and thus improves the operational flexibility of the system.

Description

Technical Field

[0001] The present invention relates to a method for quantitative analysis of the operating flexibility of a distribution network, and in particular to a method for quantitative analysis of the operating flexibility of an active distribution network based on node marginal electricity prices. Background Art

[0002] The high penetration rate of distributed generators (DG) has led to increasingly significant network congestion, excessive losses, severe voltage fluctuations, and even over-limit in the distribution system, which not only endangers the operation of the system, but also limits the further improvement of the DG consumption level. At the same time, the current distribution network has connected a large number of new equipment using advanced power electronics technology on the source-grid-load side, such as DG on the source side, energy storage system (ESS) on the grid side, smart soft switches (soft openpoint, SOP), electric vehicles on the load side, data centers and other dispatchable loads (DL), all of which have flexible and adjustable power output or consumption. Therefore, how to dispatch flexible equipment, improve system operation flexibility, and maximize social benefits has become an urgent problem to be solved in the research on the optimization of distribution network operation with high penetration rate of DG.

[0003] In this context, starting from the perspective of flexibility, the characteristics of distribution network operation flexibility can be described, and effective means can be taken to reasonably utilize flexibility resources, fully tap the operation flexibility, and effectively improve the flexible operation level of the distribution system. Since the node is the basic unit of distribution system operation, the study of operation flexibility generally establishes a model description related to the power of the distribution network node. However, at present, the research on the quantitative analysis of distribution network operation flexibility at home and abroad mainly focuses on how to quantify the power operation range of equipment or distribution network, and uses linear programming method to solve it, which is difficult to reveal the flexibility value contained in the operation strategy. The value quantification of distribution network operation flexibility constraints at the time and space scale needs further development. Therefore, there is an urgent need for a quantitative analysis method of distribution network operation flexibility based on node marginal price (distribution locational marginal pricing, DLMP). On the basis of analyzing the factors affecting the operation flexibility of the distribution network, a unified quantitative analysis framework is established and the price mechanism is used to realize the flexibility quantification. The obtained flexibility price signal not only quantifies the flexibility of the distribution system, but also covers all users of the system, providing reference flexibility scheduling information for distribution system operators (DSO) and power users. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a method for quantitative analysis of the operation flexibility of an active distribution network based on node marginal electricity prices, which can realize the quantification of the operation flexibility of the distribution network.

[0005] The technical solution adopted by the present invention is: a method for quantitatively analyzing the operational flexibility of an active distribution network based on node marginal electricity prices, characterized in that it comprises the following steps:

[0006] 1) According to the selected active distribution network, input the parameter information of the active distribution network, including: the network topology and branch impedance of the active distribution network, the access location and capacity of fixed loads, the access location and capacity of flexible resources including dispatchable loads, energy storage equipment, intelligent soft switches and distributed power sources, the power prediction curves of fixed loads and distributed power sources, and the basic parameter information of system reference voltage and reference power; and input the daily operation status of the distribution network obtained by calculating the flow of the active distribution network a day ago, including: the branch active flow value and reactive flow reference value of each time period;

[0007] 2) According to the active distribution network parameter information provided in step 1) and the daily operation status of the distribution network obtained by the current flow calculation of the active distribution network, establish the quantitative constraints on the operation flexibility of the active distribution network, including: node operation flexibility constraints, branch transfer flexibility constraints, and active distribution network aggregation flexibility constraints;

[0008] 3) According to the quantitative constraints on the operational flexibility of the active distribution network in step 2), an active distribution network operational flexibility conduction model based on node net power is established, and the flexibility-node net power sensitivity factor is calculated, including: branch transfer sensitivity factor, node voltage sensitivity factor, and network loss sensitivity factor;

[0009] 4) According to the flexibility-node net power sensitivity factor in step 3), establish the Lagrangian dual function for distribution network operation flexibility pricing, and solve the node net active power and node net reactive power flexibility price results of different nodes in each time period based on the node marginal electricity price, including: node operation flexibility price, branch transfer flexibility price, and system aggregation flexibility price;

[0010] 5) The flexibility price results of the node net active power and node net reactive power of different nodes in each time period obtained in step 4) are output to the power users with flexible resources to guide the power users to adjust the operation strategy of the dispatchable resources.

[0011] The method for quantitative analysis of the operational flexibility of active distribution networks based on node marginal electricity prices of the present invention is based on solving the problem of quantitative operation flexibility of distribution networks. It analyzes and establishes flexibility constraints of distribution networks from three levels: node operation flexibility, branch transfer flexibility, and system aggregation flexibility. Then, a distribution network operation flexibility conduction model is established, and the flexibility sensitivity factor of each node is calculated. Finally, the operation flexibility price of each node is obtained based on the node marginal electricity price. The present invention describes the operational flexibility characteristics of distribution networks from the perspective of flexibility. It not only realizes flexibility quantification under a unified framework, but also provides reference information for the optimal scheduling of multiple types of flexibility equipment on the source, grid, load, and storage sides of active distribution networks, which is conducive to analyzing and improving the operational flexibility of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a flow chart of a method for quantitatively analyzing the operational flexibility of an active distribution network based on node marginal electricity prices according to the present invention;

[0013] Figure 2 It is an improved IEEE 33-node example diagram;

[0014] Figure 3 It is the photovoltaic, wind turbine and load operation curve;

[0015] Figure 4 It is the time-of-use electricity price curve and the standby electricity price curve;

[0016] Figure 5 It is the flexibility price-time-node three-dimensional graph of node net active power;

[0017] Figure 6 It is the flexibility price-time-node three-dimensional graph of node net reactive power;

[0018] Figure 7 It is the flexibility price composition diagram of the node net active power at 3:00;

[0019] Figure 8 It is the flexibility price composition diagram of the node net reactive power at 3:00;

[0020] Fig. 9 It is the flexibility price composition diagram of the node net reactive power at 12:00;

[0021] Fig.10 It is the flexibility price composition diagram of the node net active power at 12:00;

[0022] Fig.11 is the flexibility price composition diagram of the node net active power of node 17;

[0023] Fig.12 is the flexibility price composition diagram of the node net reactive power of node 17;

[0024] Fig.13 is a flexibility price composition diagram of node net active power of node 18;

[0025] Fig.14 is the flexibility price composition diagram of the node net reactive power of node 17;

[0026] Fig.15 is a flexibility price composition diagram of node net active power of node 33;

[0027] Fig.16 is a flexibility price composition diagram of node net active power of node 33;

[0028] Fig.17 is the node operation flexibility price-time-node heat map of the node net active power;

[0029] Fig.18 It is the node operation flexibility price-time-node heat map of node net reactive power;

[0030] Fig.19 is the branch transfer flexibility price-time-node heat map of node net active power;

[0031] Fig. 20 It is the branch transfer flexibility price-time-node heat map of node net reactive power. DETAILED DESCRIPTION

[0032] The following is a detailed description of the method for quantitatively analyzing the operating flexibility of an active distribution network based on node marginal electricity prices according to the present invention in conjunction with the embodiments and drawings.

[0033] like Figure 1 As shown, the method for quantitatively analyzing the operation flexibility of active distribution network based on node marginal electricity price of the present invention comprises the following steps:

[0034] 1) According to the selected active distribution network, input the parameter information of the active distribution network, including: the network topology and branch impedance of the active distribution network, the access location and capacity of fixed loads, the access location and capacity of flexible resources including dispatchable loads, energy storage equipment, intelligent soft switches and distributed power sources, the power prediction curves of fixed loads and distributed power sources, and the basic parameter information of system reference voltage and reference power; and input the daily operation status of the distribution network obtained by calculating the active distribution network flow a day ago, including: the branch active power flow value and reactive power flow reference value in each time period.

[0035] For the embodiment of the present invention, an improved IEEE 33-node calculation example is selected, such as Figure 2 Detailed parameters are shown in Table 1 and Table 2.

[0036] Table 1 Load access location and power of the improved IEEE 33-node example

[0037]

[0038] Table 2 Improved IEEE 33-node line parameters

[0039]

[0040]

[0041] In order to consider the impact of high penetration rate distributed power access, the distributed power access situation is shown in Table 3. The distributed power output and load demand curves are shown in Figure 3 As shown. The energy storage equipment parameters are shown in Table 4, the dispatchable load parameters are shown in Table 5, the converter capacity of each port of the intelligent soft switch is 1MVA, the loss coefficient is set to 0.02, and the other equipment parameters are shown in Tables 1 to 3. The voltage safe operating range is [0.9, 1.1] (pu), and the expected operating range is [0.97, 1.03] (pu). The price parameters are shown in Table 6, and the time-of-use electricity price curve and the standby electricity price curve are shown in Figure 4 , set α=10%.

[0042] Table 3 Distributed power supply parameters

[0043] type Access Node Maximum active power / MW Capacity / MVA Photovoltaic (PV) 8,11,21 0.5 0.6 Fan (WT) 16,30 0.8 1.0

[0044] Table 4 Energy storage access parameters

[0045] Access Node Active power range / kW Initial state of charge / kWh State of charge range kWh 32 [-600,600] 300 100～900

[0046] Table 5 Dispatchable load parameters

[0047]

[0048]

[0049] Table 6 Price parameters

[0050] type Number / (CNY / MWh) Purchase (sell) active power unit price Time-of-use electricity price curve Reactive power purchase (sale) price 10% of the purchase (sale) active power unit price Node voltage deviation penalty unit price 350 Unit price of reactive auxiliary services provided by flexibility resources 1.5 Unit price of active scheduling cost of flexible resources Time-of-use electricity price curve Flexibility resources Active power Reserve price Reserve electricity price curve

[0051] 2) According to the active distribution network parameter information provided in step 1) and the daily operation status of the distribution network obtained by the current flow calculation of the active distribution network, the quantitative constraints on the operation flexibility of the active distribution network are established, including: node operation flexibility constraints, branch transfer flexibility constraints, and active distribution network aggregation flexibility constraints; wherein,

[0052] 1. The node operation flexibility constraints include:

[0053] (1) Node net power balance constraint, expressed as:

[0054]

[0055] In the formula, is the net active power of node i at time t; is the net reactive power of node i at time t; and are the active power consumption and reactive power consumption of the fixed load at node i at time t, respectively; and are the active power consumption and reactive power consumption of the delayable load at node i at time t, respectively; and They are the active power injection and reactive power injection of the distributed generation at node i at time t respectively; and They are the active power injection and reactive power injection of energy storage at node i at time t respectively; and They are the active power injection and reactive power injection of the intelligent soft switch at node i at time t respectively;

[0056] (2) Node voltage flexibility constraint, expressed as:

[0057]

[0058] Where V i,t is the voltage amplitude of node i at time t; V min and V max is the lower and upper limits of node voltage safety operation, V flx and are the ideal operating lower and upper limits of the node voltage, and

[0059] 2. The branch transfer flexibility constraint is expressed as:

[0060]

[0061] Where P l,t and Q l,t are the active power and reactive power flowing through branch l at time t; S l is the rated capacity of branch l; and are the total active power loss and reactive power loss of the distribution network at time t; Ω b is the collection of branches in the active distribution network; r l and x l are the per-unit resistance and per-unit reactance values ​​of branch l respectively; V i,t is the voltage amplitude of node i at time t.

[0062] 3. The active distribution network system aggregation flexibility constraint is expressed as:

[0063] (1) Aggregate flexibility constraints for interaction with the external grid, expressed as:

[0064]

[0065] In the formula, and is the active aggregate power and reactive aggregate power of the active distribution network interacting with the external power grid at time t; Ω n is the set of active distribution network nodes; and are the total active power loss and reactive power loss of the distribution network at time t respectively; is the net active power of node i at time t; is the net reactive power of node i at time t;

[0066] (2) The flexibility margin constraint of the equipment in the active distribution network is expressed as:

[0067]

[0068]

[0069] In the formula, and Ω is the up power margin and down power margin provided by the flexibility resource at node i at time t; res is a set of flexible resources that can provide active power margin reserve in the active distribution network; α is a coefficient constant, 0≤α≤100%; and are the maximum and minimum active power that the flexibility resource at node i can inject into the distribution network at time t, respectively; is the active power injected into the distribution network by the flexibility resource at node i at time t; Ω n is the set of active distribution network nodes;

[0070] Among them, formula (7) introduces auxiliary variables It is further expressed as follows:

[0071]

[0072] 3) According to the quantitative constraints on the operational flexibility of the active distribution network in step 2), an active distribution network operational flexibility conduction model based on node net power is established, and the flexibility-node net power sensitivity factor is calculated, including: branch transfer sensitivity factor, node voltage sensitivity factor, and network loss sensitivity factor; wherein,

[0073] 1. The active distribution network operation flexibility conduction model based on node net power is expressed as:

[0074]

[0075]

[0076]

[0077]

[0078] Where P l,t and P l-1,t are the active power flow values ​​of branch l and branch l-1 respectively; Q l,t and Q l-1,t are the reactive power flow values ​​of branch l and branch l-1 respectively; is the net active power of node i at time t; is the net reactive power of node i at time t; and are the node active loss and node reactive loss at node i at time t respectively; V i,t and V i-1,t are the voltage amplitudes of node i and node i-1 at time t; V 0,t is the voltage amplitude of the source node at time t; and represents the reference value of active power and reactive power flowing through branch l at time t in the distribution network operation state obtained by the day-ahead power flow calculation; r l and x l are the per-unit resistance and per-unit reactance values ​​of branch l respectively; ξ(i) represents the set of branches connected to node i; formula (12) is the node loss model, which uses the initial value to evenly distribute the branch loss to the first and last nodes of the branch to correct the loss;

[0079] Number the nodes in the radial distribution network from the source node and define the node association matrix as follows:

[0080]

[0081] Where N n is the number of nodes in the distribution network; A(i,j) represents the correlation factor between node i and node j;

[0082] The branch l with node k as the end node is numbered L k-1 , and node k and node i belonging to the subtree of node k are the generalized end nodes of branch l, and then define the generalized branch node association matrix as follows:

[0083]

[0084] Where N b is the number of branches in the distribution network; M l-i Represents the correlation factor between branch l and node i;

[0085] Formulas (9)-(12) are further expressed as formulas (15)-(17), as follows:

[0086]

[0087]

[0088]

[0089]

[0090] Where, ΔV i,t It represents the voltage deviation value of node i to the source node at time t; and are the total active power loss and reactive power loss of the distribution network at time t; Ω b It is a collection of branches in the active distribution network.

[0091] 2. In the flexibility-node net power sensitivity factor:

[0092] (1) Branch transfer sensitivity factor, expressed as:

[0093]

[0094] In the formula, is the sensitivity factor of the net active power of node i to the active power flowing through branch l at time t; is the sensitivity factor of the net reactive power of node i to the active power flowing through branch l at time t; is the sensitivity factor of the net reactive power of node i to the reactive power flowing through branch l at time t; is the sensitivity factor of the net active power of node i to the reactive power flowing through branch l at time t; is the net active power of node i at time t; is the net reactive power of node i at time t; P l,t and Q l,t are the active power and reactive power flowing through branch l at time t; M l-i Represents the correlation factor between branch l and node i;

[0095] (2) Node voltage sensitivity factor, expressed as:

[0096]

[0097] In the formula, is the sensitivity factor of the net active power of node i to the voltage deviation at time t; is the sensitivity factor of the net reactive power of node i to the voltage deviation at time t; ΔV i,t represents the voltage deviation value of node i to the source node at time t; ξ(i) represents the set of branches with node i as the generalized first node; N n is the number of nodes in the distribution network; r l and x l are the per-unit resistance and per-unit reactance values ​​of branch l respectively;

[0098] (3) Network loss sensitivity factor, expressed as:

[0099]

[0100] In the formula, is the sensitivity factor of the net active power of node i at time t to the network active power loss; is the sensitivity factor of the net reactive power of node i at time t to the active power loss of the network; is the sensitivity factor of the net active power of node i at time t to the network reactive power loss; is the sensitivity factor of the net reactive power of node i at time t to the reactive power loss of the network; and are the total active power loss and reactive power loss of the distribution network at time t respectively; and It represents the reference value of active power and reactive power flowing through branch l at time t in the distribution network operation state obtained by the current flow calculation a day ago; Ω b is the collection of branches in the active distribution network; r l and x l are the per-unit resistance and per-unit reactance values ​​of branch 1 respectively.

[0101] 4) According to the flexibility-node net power sensitivity factor in step 3), establish the Lagrangian dual function for distribution network operation flexibility pricing, and solve the node net active power and node net reactive power flexibility price results of different nodes in each time period based on the node marginal electricity price, including: node operation flexibility price, branch transfer flexibility price, system aggregation flexibility price; where,

[0102] 1. The Lagrangian dual function for pricing distribution network operation flexibility is expressed as:

[0103]

[0104]

[0105] Where L(·) is the Lagrangian dual function of distribution network operation flexibility pricing; x is the control vector; λ is the dual variable vector of equality constraints; μ is the slack variable vector of inequality constraints; T is the operation period; f(·) is the linear function representing the flexibility operation cost; and is the slack variable of the node voltage flexibility constraint of node i at time t; μ l,c,t is the slack variable of the c-th branch transfer flexibility constraint of branch l at time t; α c,0 , α c,1 and α c,2 is the constant coefficient value of the cth formula in the polygonal approximation method; and is the dual variable of the system aggregation flexibility constraint at time t; and is the slack variable of the equipment flexibility margin constraint at time t; is the sensitivity factor of the net active power of node i to the active power flowing through branch l at time t; is the sensitivity factor of the net reactive power of node i to the reactive power flowing through branch l at time t; is the sensitivity factor of the net active power of node i to the voltage deviation at time t; is the sensitivity factor of the net reactive power of node i to the voltage deviation at time t; is the sensitivity factor of the net active power of node i at time t to the network active power loss; is the sensitivity factor of the net reactive power of node i at time t to the active power loss of the network; is the sensitivity factor of the net active power of node i at time t to the network reactive power loss; is the sensitivity factor of the net reactive power of node i at time t to the reactive power loss of the network; and is the active aggregate power and reactive aggregate power of the active distribution network interacting with the external power grid at time t; Ω n is the set of active distribution network nodes; and They are respectively the active power loss and reactive power loss of the active distribution network at time t; is the net active power of node i at time t; is the net reactive power of node i at time t; N n is the number of nodes in the distribution network; V min and V max It is the lower and upper limits of node voltage safe operation; Ω res is the set of flexible resources that can provide active power reserve in the active distribution network; α is the coefficient constant; S l is the rated capacity of branch l; is an auxiliary variable representing the absolute value of the total active power margin requirement provided by the flexibility resources at node i at time t; Ω b It is a collection of branches in the active distribution network.

[0106] 2. The flexibility price result of the node net active power and node net reactive power of different nodes in each time period is solved based on the node marginal electricity price, and the formula is:

[0107]

[0108]

[0109]

[0110]

[0111]

[0112]

[0113]

[0114]

[0115] In the formula, and They represent the flexibility prices of net active power and net reactive power of node i at time t respectively; L is the Lagrangian dual function of distribution network operation flexibility pricing; and The node operation flexibility prices represent the net active power and net reactive power of node i at time t, respectively; and They represent the branch transfer flexibility prices of the net active power and net reactive power of node i at time t, respectively; and denote the system aggregate flexibility price of the net active power and net reactive power of node i at time t respectively; and is the slack variable of the node voltage flexibility constraint of node i at time t; μ l,c,t is the slack variable of the c-th branch transfer flexibility constraint of branch l at time t; α c,0 , α c,1 and α c,2 is the constant coefficient value of the cth formula in the polygonal approximation method; and is the dual multiplier of the system aggregate flexibility constraint at time t; and is the slack variable of the system flexibility margin constraint at time t; is the sensitivity factor of the net active power of node i to the active power flowing through branch l at time t; is the sensitivity factor of the net reactive power of node i to the reactive power flowing through branch l at time t; is the sensitivity factor of the net active power of node i to the voltage deviation at time t; is the sensitivity factor of the net reactive power of node i to the voltage deviation at time t; is the sensitivity factor of the net active power of node i at time t to the network active power loss; is the sensitivity factor of the net reactive power of node i at time t to the active power loss of the network; is the sensitivity factor of the net active power of node i at time t to the network reactive power loss; is the sensitivity factor of the net reactive power of node i at time t to the reactive power loss of the network; Ω b is the set of branches in the distribution system; α is the coefficient constant; is the net active power of node i at time t; is the net reactive power of node i at time t; where formulas (23) and (24) are the flexibility prices of node net active power and node net reactive power, respectively; formulas (25) and (26) are the node operation flexibility prices of node net active power and node net reactive power, respectively; formulas (27) and (28) are the branch transfer flexibility prices of node net active power and node net reactive power, respectively; and formulas (29) and (30) are the system aggregation flexibility prices of node net active power and node net reactive power, respectively.

[0116] 5) The flexibility price results of the node net active power and node net reactive power of different nodes in each time period obtained in step 4) are output to the power users with flexible resources to guide the power users to adjust the operation strategy of the dispatchable resources.

[0117] In order to verify the feasibility and effectiveness of the quantitative analysis method of active distribution network operation flexibility based on node marginal electricity price in the present invention, in the embodiment of the present invention, the following two scenarios are adopted for verification and analysis:

[0118] Solution 1: DSO has no coordination strategy, no intelligent soft switches and energy storage for network-side regulation equipment. The resources on the source and load side only need to arrange their own operation plans within the safe operation range of the system to maximize their own interests.

[0119] Solution 2: DSO adopts the proposed flexibility quantitative analysis method, takes the optimal flexibility cost as the optimization target, and obtains the flexibility price used to guide the operation of various resources in the system.

[0120] Taking 1 hour as the control cycle, the comparison of the flexibility operating costs of the two schemes is shown in Table 7. Figure 5 and Figure 6 The flexibility price-time-node three-dimensional graph is the node net active power and node net reactive power. Figure 7 and Figure 8 The flexibility price composition diagram of the node net active power and node net reactive power at 3:00 is shown in Figure 2. Fig. 9 and Fig.10 This is the flexibility price composition diagram of the node net active power and node net reactive power at 12:00. Fig.11 and Fig.12 is the flexibility price composition diagram of the node net active power and node net reactive power of node 17, Fig.13 and Fig.14 is the flexibility price composition diagram of the node net active power and node net reactive power of node 18, Fig.15 and Fig.16 FIG. 4 is a flexibility price composition diagram of the node net active power and the node net reactive power of node 33. FIG. Fig.17 and Fig.18 The node operation flexibility price-time-node heat map for node net active power and node net reactive power, Fig.19 and Fig. 20 The branch transfer flexibility price-time-node heat map for node net active power and node net reactive power.

[0121] Table 7 Comparison of flexibility operating costs

[0122]

[0123] The computer hardware environment for performing optimization calculations is Intel(R)Xeon(R)CPU E5-1620, with a main frequency of 3.70GHz and a memory of 32GB; the software environment is Windows 10 operating system.

[0124] From the perspective of operating costs, it can be seen from Table 7 that compared with the initial scenario of Scheme 1, Scheme 2 has a lower system active power purchase fee under the dispatch strategy with the goal of optimizing flexibility cost. Due to the improvement of the reactive power of the flexible equipment in Scheme 2, the reactive power purchase fee of the upper level in Scheme 2 has been significantly reduced by 74.24%. The flexible local support provided by the flexibility resources has significantly reduced the penalty fee for system voltage deviation, and the total system operating cost has been reduced by 52.47%.

[0125] Figure 5 and Figure 6 The active power and reactive power flexibility prices of each node shown are the flexibility prices that each node needs to pay to the DSO to meet its own flexible power demand while ensuring the flexibility of the distribution network operation. At the same time, the flexibility price also reflects the flexibility value corresponding to the unit net power of each node. Figure 5 and Figure 6 It can be seen that the flexibility price of node net power varies significantly with time and location. The flexibility price reflects the comprehensive impact of the node's access location in the distribution network, net power value, etc. on the node's provision / application of system flexibility services, and is composed of three price components: node operation flexibility, branch transfer flexibility, and system aggregation flexibility.

[0126] The factors that affect the flexibility price of each node are as follows: (1) the flexibility sensitivity factor, which describes the proportion of the node's influence on a certain flexibility price component in the entire system, and is related to the electrical distance of the node from the source node and its topological position in the system; (2) the marginal change in the cost corresponding to different operating flexibility constraints caused by the node's net power, that is, the shadow price, which is related to the impact of the net power injection at different times on flexibility at different levels.

[0127] Therefore, the price component values ​​and proportions of each node at different times are different, and the price of each component quantifies the degree of matching of the unit net power of the node to different flexibility supply and demand at a certain moment. Figure 7-10 and Figure 11-16 It can be seen that the unit net power change of different nodes has different impacts on the system operation flexibility, resulting in large differences in the flexibility prices of different nodes at the same time. Since different nodes contribute or demand different operational flexibility at different times, the price proportions of each component of the flexibility of the node at different times are different, and the overall flexibility price changes over time.

[0128] From the comparison between Scheme 1 and Scheme 2, it can be seen that the proposed method of quantitative analysis of the operational flexibility of active distribution networks based on node marginal electricity prices can be used to obtain the flexibility price of each node by establishing a quantitative description constraint of flexible operation and an operational flexibility conduction model, which is used to guide the operation of power-adjustable flexible resources in the system. This method can not only effectively adjust the reactive power of equipment, provide on-site support, fully adjust the spatiotemporal distribution of operational flexibility of each node in the distribution network, and improve the level of flexible operation of the system, but also quantify the value of distribution network operational flexibility by using a price mechanism.

Claims

1. A quantitative analysis method for the operational flexibility of active distribution networks based on node marginal electricity prices, characterized in that: The steps include: 1) According to the selected active distribution network, input the parameter information of the active distribution network, including: the network topology and branch impedance of the active distribution network, the access location and capacity of fixed loads, the access location and capacity of flexible resources including dispatchable loads, energy storage equipment, intelligent soft switches and distributed power sources, the power prediction curves of fixed loads and distributed power sources, and the basic parameter information of system reference voltage and reference power; and input the daily operation status of the distribution network obtained by calculating the flow of the active distribution network a day ago, including: the branch active flow value and reactive flow reference value of each time period; 2) According to the active distribution network parameter information provided in step 1) and the daily operation status of the distribution network obtained by the current flow calculation of the active distribution network, establish the quantitative constraints on the operation flexibility of the active distribution network, including: node operation flexibility constraints, branch transfer flexibility constraints, and active distribution network aggregation flexibility constraints; 3) According to the quantitative constraints on the operational flexibility of the active distribution network in step 2), an active distribution network operational flexibility conduction model based on node net power is established, and the flexibility-node net power sensitivity factor is calculated, including: branch transfer sensitivity factor, node voltage sensitivity factor, and network loss sensitivity factor; The active distribution network operation flexibility conduction model based on node net power is expressed as: Where P l,t and P l-1,t are the active power flow values ​​of branch l and branch l-1 respectively; Q l,t and Q l-1,t are the reactive power flow values ​​of branch l and branch l-1 respectively; is the net active power of node i at time t; is the net reactive power of node i at time t; and are the node active loss and node reactive loss at node i at time t respectively; V i,t and V i-1,t are the voltage amplitudes of node i and node i-1 at time t; V 0,t is the voltage amplitude of the source node at time t; and represents the reference value of active power and reactive power flowing through branch l at time t in the distribution network operation state obtained by the day-ahead power flow calculation; r l and x l are the per-unit resistance and per-unit reactance values ​​of branch l respectively; ξ(i) represents the set of branches connected to node i; formula (12) is the node loss model, which uses the initial value to evenly distribute the branch loss to the first and last nodes of the branch to correct the loss; Number the nodes in the radial distribution network from the source node and define the node association matrix as follows: Where N n is the number of nodes in the distribution network; A(i,j) represents the correlation factor between node i and node j; The branch l with node k as the end node is numbered L k-1 , and node k and node i belonging to the subtree of node k are the generalized end nodes of branch l, and then define the generalized branch node association matrix as follows: M l-i =A(k,i),i∈{1,2,…,N n },L k-1 ∈{1,2,…,N b } Where N b is the number of branches in the distribution network; M l-i Represents the correlation factor between branch l and node i; Formulas (9)-(12) are further expressed as formulas (15)-(17), as follows: Where ΔV i,t It represents the voltage deviation value of node i to the source node at time t; and are the total active power loss and reactive power loss of the distribution network at time t; Ω b It is a collection of branches in the active distribution network; 4) According to the flexibility-node net power sensitivity factor in step 3), establish the Lagrangian dual function for distribution network operation flexibility pricing, and solve the node net active power and node net reactive power flexibility price results of different nodes in each time period based on the node marginal electricity price, including: node operation flexibility price, branch transfer flexibility price, and system aggregation flexibility price; 5) The flexibility price results of the node net active power and node net reactive power of different nodes in each time period obtained in step 4) are output to the power users with flexible resources to guide the power users to adjust the operation strategy of the dispatchable resources.

2. The method for quantitative analysis of active distribution network operation flexibility based on node marginal electricity price according to claim 1 is characterized in that The node operation flexibility constraint described in step 2) includes: (1) Node net power balance constraint, expressed as: In the formula, is the net active power of node i at time t; is the net reactive power of node i at time t; and are the active power consumption and reactive power consumption of the fixed load at node i at time t, respectively; and are the active power consumption and reactive power consumption of the delayable load at node i at time t, respectively; and They are the active power injection and reactive power injection of the distributed generation at node i at time t respectively; and They are the active power injection and reactive power injection of energy storage at node i at time t respectively; and They are the active power injection and reactive power injection of the intelligent soft switch at node i at time t respectively; (2) Node voltage flexibility constraint, expressed as: In min ≤V i,t ≤V max Where V i,t is the voltage amplitude of node i at time t; V min and V max are the lower and upper limits of node voltage safety operation, V flx and are the ideal operating lower and upper limits of the node voltage, 3. The method for quantitative analysis of active distribution network operation flexibility based on node marginal electricity price according to claim 1 is characterized in that: The branch transfer flexibility constraint described in step 2) is expressed as: Where P l,t and Q l,t are the active power and reactive power flowing through branch l at time t; S l is the rated capacity of branch l; and are the total active power loss and reactive power loss of the distribution network at time t; Ω b is the collection of branches in the active distribution network; r l and x l are the per-unit resistance and per-unit reactance values ​​of branch l respectively; V i,t is the voltage amplitude of node i at time t.

4. The method for quantitative analysis of active distribution network operation flexibility based on node marginal electricity price according to claim 1 is characterized in that: The system aggregation flexibility constraint described in step 2) is expressed as: (1) Aggregate flexibility constraints for interaction with the external grid, expressed as: In the formula, and is the active aggregate power and reactive aggregate power of the active distribution network interacting with the external power grid at time t; Ω n is the set of active distribution network nodes; and are the total active power loss and reactive power loss of the distribution network at time t respectively; is the net active power of node i at time t; is the net reactive power of node i at time t; (2) The flexibility margin constraint of the equipment in the active distribution network is expressed as: In the formula, and Ω is the up power margin and down power margin provided by the flexibility resource at node i at time t; res is a set of flexible resources that can provide active power margin reserve in the active distribution network; α is a coefficient constant, 0≤α≤100%; and are the maximum and minimum active power that the flexibility resource at node i can inject into the distribution network at time t, respectively; is the active power injected into the distribution network by the flexibility resource at node i at time t; Ω n is the set of active distribution network nodes; Among them, formula (7) introduces auxiliary variables It is further expressed as follows:

5. The method for quantitative analysis of active distribution network operation flexibility based on node marginal electricity price according to claim 1 is characterized in that: In the flexibility-node net power sensitivity factor described in step 3), (1) Branch transfer sensitivity factor, expressed as: In the formula, is the sensitivity factor of the net active power of node i to the active power flowing through branch l at time t; is the sensitivity factor of the net reactive power of node i to the active power flowing through branch l at time t; is the sensitivity factor of the net reactive power of node i to the reactive power flowing through branch l at time t; is the sensitivity factor of the net active power of node i to the reactive power flowing through branch l at time t; is the net active power of node i at time t; is the net reactive power of node i at time t; P l,t and Q l,t are the active power and reactive power flowing through branch l at time t; M l-i Represents the correlation factor between branch l and node i; (2) Node voltage sensitivity factor, expressed as: In the formula, is the sensitivity factor of the net active power of node i to the voltage deviation at time t; is the sensitivity factor of the net reactive power of node i to the voltage deviation at time t; ΔV i,t represents the voltage deviation value of node i to the source node at time t; ξ(i) represents the set of branches with node i as the generalized first node; N n is the number of nodes in the distribution network; r l and x l are the per-unit resistance and per-unit reactance values ​​of branch l respectively; (3) Network loss sensitivity factor, expressed as: In the formula, is the sensitivity factor of the net active power of node i at time t to the network active power loss; is the sensitivity factor of the net reactive power of node i at time t to the active power loss of the network; is the sensitivity factor of the net active power of node i at time t to the network reactive power loss; is the sensitivity factor of the net reactive power of node i at time t to the reactive power loss of the network; and are the total active power loss and reactive power loss of the distribution network at time t respectively; and It represents the reference value of active power and reactive power flowing through branch l at time t in the distribution network operation state obtained by the current flow calculation a day ago; Ω b is the collection of branches in the active distribution network; r l and x l are the per-unit resistance and per-unit reactance values ​​of branch 1 respectively.

6. The method for quantitative analysis of active distribution network operation flexibility based on node marginal electricity price according to claim 1 is characterized in that: The Lagrangian dual function for pricing the distribution network operation flexibility described in step 4) is expressed as: Where L(·) is the Lagrangian dual function of distribution network operation flexibility pricing; x is the control vector; λ is the dual variable vector of equality constraints; μ is the slack variable vector of inequality constraints; T is the operation period; f(·) is the linear function representing the flexibility operation cost; and is the slack variable of the node voltage flexibility constraint of node i at time t; μ l,c,t is the slack variable of the c-th branch transfer flexibility constraint of branch l at time t; α c,0 , α c,1 and α c,2 is the constant coefficient value of the cth formula in the polygonal approximation method; and is the dual variable of the system aggregation flexibility constraint at time t; and is the slack variable of the equipment flexibility margin constraint at time t; is the sensitivity factor of the net active power of node i to the active power flowing through branch l at time t; is the sensitivity factor of the net reactive power of node i to the reactive power flowing through branch l at time t; is the sensitivity factor of the net active power of node i to the voltage deviation at time t; is the sensitivity factor of the net reactive power of node i to the voltage deviation at time t; is the sensitivity factor of the net active power of node i at time t to the network active power loss; is the sensitivity factor of the net reactive power of node i at time t to the active power loss of the network; is the sensitivity factor of the net active power of node i at time t to the network reactive power loss; is the sensitivity factor of the net reactive power of node i at time t to the reactive power loss of the network; and is the active aggregate power and reactive aggregate power of the active distribution network interacting with the external power grid at time t; Ω n is the set of active distribution network nodes; and They are respectively the active power loss and reactive power loss of the active distribution network at time t; is the net active power of node i at time t; is the net reactive power of node i at time t; N n is the number of nodes in the distribution network; V min and V max It is the lower and upper limits of node voltage safe operation; Ω res is the set of flexible resources that can provide active power reserve in the active distribution network; α is the coefficient constant; S l is the rated capacity of branch l; is an auxiliary variable representing the absolute value of the total active power margin requirement provided by the flexibility resources at node i at time t; Ω b It is a collection of branches in the active distribution network.

7. The method for quantitative analysis of active distribution network operation flexibility based on node marginal electricity price according to claim 1 is characterized in that: The flexibility price result of the node net active power and node net reactive power of different nodes in each time period is solved based on the node marginal electricity price in step 4), and the formula is: In the formula, and They represent the flexibility prices of net active power and net reactive power of node i at time t respectively; L is the Lagrangian dual function of distribution network operation flexibility pricing; and The node operation flexibility prices represent the net active power and net reactive power of node i at time t, respectively; and They represent the branch transfer flexibility prices of the net active power and net reactive power of node i at time t, respectively; and denote the system aggregate flexibility price of the net active power and net reactive power of node i at time t respectively; and is the slack variable of the node voltage flexibility constraint of node i at time t; μl ,c,t is the slack variable of the c-th branch transfer flexibility constraint of branch l at time t; α c,0 , α c,1 and α c,2 is the constant coefficient value of the cth formula in the polygonal approximation method; and is the dual multiplier of the system aggregate flexibility constraint at time t; and is the slack variable of the system flexibility margin constraint at time t; is the sensitivity factor of the net active power of node i to the active power flowing through branch l at time t; is the sensitivity factor of the net reactive power of node i to the reactive power flowing through branch l at time t; is the sensitivity factor of the net active power of node i to the voltage deviation at time t; is the sensitivity factor of the net reactive power of node i to the voltage deviation at time t; is the sensitivity factor of the net active power of node i at time t to the network active power loss; is the sensitivity factor of the net reactive power of node i at time t to the active power loss of the network; is the sensitivity factor of the net active power of node i at time t to the network reactive power loss; is the sensitivity factor of the net reactive power of node i at time t to the reactive power loss of the network; Ω b is the set of branches in the distribution system; α is the coefficient constant; is the net active power of node i at time t; is the net reactive power of node i at time t; where formulas (23) and (24) are the flexibility prices of node net active power and node net reactive power, respectively; formulas (25) and (26) are the node operation flexibility prices of node net active power and node net reactive power, respectively; formulas (27) and (28) are the branch transfer flexibility prices of node net active power and node net reactive power, respectively; and formulas (29) and (30) are the system aggregation flexibility prices of node net active power and node net reactive power, respectively.

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