A method and system for optimizing a disaster-preventive backbone grid of a transmission network

Abstract

The present invention discloses a method and system for optimizing the disaster prevention backbone grid of a transmission network. The method takes the minimum investment cost of the differentiated reinforcement lines already constructed in the transmission network and the maximum load supply under the disaster operation state of the lines as the objective function, and establishes a first optimization model of the disaster prevention backbone grid of the transmission network in combination with the constraint conditions of the objective function. The first optimization model is simplified using separation inequality constraints, and all important loads and power supply nodes are connected through the optimization model. Therefore, the optimization model not only takes into account the differentiated investment costs of the backbone grid and the power supply guarantee for important users, but also considers improving the power supply capacity of general users, so that the scope of guaranteed power supply in the event of a disaster includes but is not limited to important loads. The line information and load distribution information of the transmission network are input into the second optimization model to obtain a differentiated reinforcement plan for the disaster prevention backbone grid of the transmission network, so that the reinforcement scope of the disaster prevention backbone grid can be determined through the optimal cost of the entire society.

Description

Technical Field

[0001] The present invention relates to the technical field of power transmission network planning, and in particular to an optimization method and system for a disaster prevention backbone network of a power transmission network. Background Art

[0002] We have entered a new phase of developing large-scale power grids and large-scale generating units, which places higher demands on power grid planning and design. Transmission network planning, as a key component of grid planning, is crucial for the safe and reliable operation of the power system. Highly destructive extreme weather events have caused significant damage and losses to infrastructure such as transmission networks, which have a high concentration of exposed equipment. Therefore, grid planning urgently needs to enhance the transmission network's resilience to extreme disasters to ensure the safety and reliability of the power system.

[0003] A disaster-resistant backbone grid refers to a grid that improves the design standards and principles of some lines, towers, and substations in the power grid, and forms a core backbone grid that meets the constraints of topological connectivity and safe and stable system operation. It can be used to ensure power supply to important loads in the system during sudden events such as extreme disasters, and lay the foundation for subsequent system maintenance and power restoration.

[0004] However, the geographical locations of different lines in the transmission network and the loads they need to bear are different. If the disaster prevention construction standards of all lines are improved, the investment will be large and the economic efficiency will be poor. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a method and system for optimizing the disaster prevention backbone network of a transmission network, which can take into account lines with different power supply capabilities, realize enhanced optimization of the disaster prevention backbone network and improve the optimization economy.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0007] A method for optimizing a disaster-prevention backbone grid of a power transmission network comprises the following steps:

[0008] Receive line information and load distribution information of the transmission network;

[0009] Taking the minimization of investment cost of the differentiated reinforcement lines already built in the transmission network and the maximization of load supply under the disaster operation state of the lines as the objective function, the first optimization model of the disaster-resistant backbone grid of the transmission network is established based on the objective function and the constraints.

[0010] Separating discrete variables and continuous variables in the first optimization model by using separation inequality constraints, and simplifying the first optimization model into a second mixed integer linear optimization model;

[0011] Adding a virtual power flow constraint condition to the second optimization model so that the second optimization model connects all important loads and power nodes;

[0012] The line information and load distribution information of the transmission network are input into the second optimization model to solve and obtain a differentiated reinforcement scheme for the disaster-proof backbone grid of the transmission network.

[0013] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0014] An optimization system for a disaster-prevention backbone grid of a power transmission network, comprising:

[0015] A data input module, used for receiving line information and load distribution information of the transmission network;

[0016] An optimization model module is configured to establish a first optimization model for a disaster-resistant backbone grid of the transmission network based on the objective function and constraints, taking the minimization of the investment cost of the differentiated reinforcement lines already constructed in the transmission network and the maximization of the load supply under the line disaster operation state as objective functions; to separate discrete variables and continuous variables in the first optimization model using separation inequality constraints, thereby simplifying the first optimization model into a second mixed integer linear optimization model; and to add virtual power flow constraints to the second optimization model so that the second optimization model connects all important loads and power nodes.

[0017] The disaster prevention backbone network decision module is used to input the line information and load distribution information of the transmission network into the second optimization model to solve and obtain a differentiated reinforcement plan for the disaster prevention backbone network of the transmission network.

[0018] The beneficial effects of the present invention are as follows: the investment cost of the differentiated reinforcement lines already constructed in the transmission network is minimized, and the load supply is maximized under the disaster operation state of the lines is taken as the objective function, and the first optimization model of the disaster prevention backbone grid of the transmission network is established in combination with the constraint conditions of the objective function. The first optimization model is simplified using separation inequality constraints, and all important loads and power supply nodes are connected through the optimization model. Therefore, the optimization model not only takes into account the differentiated investment cost of the backbone grid and the power supply guarantee for important users, but also considers improving the power supply capacity of general users, so that the scope of guaranteed power supply in the event of a disaster includes but is not limited to important loads, and improves the optimization economy. The line information and load distribution information of the transmission network are input into the second optimization model to obtain a differentiated reinforcement plan for the disaster prevention backbone grid of the transmission network, so that the reinforcement scope of the disaster prevention backbone grid can be determined through the optimal cost of the whole society. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1This is a flow chart of a method for optimizing a disaster-resistant backbone grid of a transmission network according to an embodiment of the present invention;

[0020] Figure 2 A schematic diagram of an optimization system for a disaster prevention backbone grid of a transmission network according to an embodiment of the present invention;

[0021] Figure 3 This is a schematic diagram of simulation results of the disaster prevention backbone network planning method according to an embodiment of the present invention in the IEEE118 standard node system. DETAILED DESCRIPTION

[0022] To illustrate the technical content, achieved objectives and effects of the present invention in detail, the following description is given in conjunction with the embodiments and accompanying drawings.

[0023] Please refer to Figure 1 The embodiment of the present invention provides a method for optimizing a disaster-proof backbone network of a power transmission network, comprising the steps of:

[0024] Receive line information and load distribution information of the transmission network;

[0025] Taking the minimization of investment cost of the differentiated reinforcement lines already built in the transmission network and the maximization of load supply under the disaster operation state of the lines as the objective function, the first optimization model of the disaster-resistant backbone grid of the transmission network is established based on the objective function and the constraints.

[0026] Separating discrete variables and continuous variables in the first optimization model by using separation inequality constraints, and simplifying the first optimization model into a second mixed integer linear optimization model;

[0027] Adding a virtual power flow constraint condition to the second optimization model so that the second optimization model connects all important loads and power nodes;

[0028] The line information and load distribution information of the transmission network are input into the second optimization model to solve and obtain a differentiated reinforcement scheme for the disaster-proof backbone grid of the transmission network.

[0029] As can be seen from the above description, the beneficial effects of the present invention are: taking the minimum investment cost of the differentiated reinforcement lines already built in the transmission network and the maximum load supply under the line disaster operation state as the objective function, and combining the objective function constraints to establish a first optimization model for the disaster-resistant backbone grid of the transmission network, using separation inequality constraints to simplify the first optimization model, and connecting all important loads and power supply nodes through the optimization model. Therefore, the optimization model not only takes into account the differentiated investment costs of the backbone grid and the power supply guarantee for important users, but also considers improving the power supply capacity of general users, so that the scope of guaranteed power supply in the event of a disaster includes but is not limited to important loads, and improves the optimization economy. The line information and load distribution information of the transmission network are input into the second optimization model to obtain a differentiated reinforcement plan for the disaster-resistant backbone grid of the transmission network, so that the reinforcement scope of the disaster-resistant backbone grid can be determined through the optimal overall social cost.

[0030] Furthermore, the objective function of minimizing the investment cost of the differentiated reinforcement lines already constructed in the transmission network and maximizing the load supply under the disaster operation state of the lines includes:

[0031] The objective function is:

[0032]

[0033] Where, Ψ is the set of planned lines to be built; C t is the investment cost of converting the line to be built t into a common line; C t ′ is the investment cost of building the line t to be built into a differentiated enhanced line; L t is a 0-1 decision variable indicating whether to build line t, 0 means not to build, 1 means to build; D t is a 0-1 decision variable indicating whether to build a differentiated enhanced line t, 0 indicates not to build a differentiated enhanced line, and 1 indicates to build a differentiated enhanced line;

[0034] S H To differentiate and enhance the set of existing lines, K ij represents the incremental investment cost of differentiated enhancement of existing line ij; H ij is a 0-1 decision variable indicating whether differentiated enhancement construction is carried out on line ij, where 0 indicates no differentiated enhancement and 1 indicates differentiated enhancement;

[0035] S N is the set of all nodes, W L is the unit power supply benefit of node load under disaster operation state, represents the load power of node i in the disaster operation state, and the superscript (d) indicates the disaster operation state.

[0036] From the above description, it can be seen that the objective function includes the requirement of minimizing the investment cost of differentiated reinforcement of important lines and the requirement of maximizing the load supply capacity in the disaster operation state. Since the load power supply benefit in the disaster operation state is positive, the last term of the objective function takes a negative sign, thereby achieving the minimization of the objective function.

[0037] Furthermore, the constraints include guaranteed output constraints of node units in disaster operation states and normal operation states, power supply constraints of important loads, balance constraints of node power and power flow safety constraints of lines.

[0038] Furthermore, the differentiated enhanced line satisfies the DC power flow equation under disaster operation:

[0039]

[0040]

[0041] Where, is the load power flowing through line ij under disaster operation state, is the load power limit flowing through line t under disaster conditions, x ij 、x t are the reactance values ​​of line ij and line t respectively, are the phase angle values ​​of nodes i and j under the disaster operation state respectively;

[0042] The differentiated enhanced line satisfies the DC power flow equation under normal operating conditions:

[0043]

[0044]

[0045] In the formula are the phase angle values ​​of nodes i and j under normal operating conditions, is the load power flowing through line ij under normal operating conditions, is the load power limit flowing through line t under normal operating conditions; (L t ||D t ) is the binary OR operator.

[0046] From the above description, it can be seen that the differentiated enhanced line satisfies the DC power flow equation, which facilitates the subsequent variable separation and model simplification based on the separable inequality constraints.

[0047] Furthermore, adding a virtual power flow constraint condition to the second optimization model so that the second optimization model connects all important loads and power supply nodes includes:

[0048] Constructing all the differentiated reinforcement lines into a disaster-proof backbone network;

[0049] Constructing a virtual power supply for the important load line, and externally connecting the virtual power supply to the node of the disaster-proof backbone network, and providing supply for the virtual load of the node through the virtual power supply;

[0050] The nodes of the disaster-proof backbone network meet the following requirements:

[0051]

[0052] Where, f ij is the virtual power flow value of branch ij in the backbone network, and f ij The branch virtual power flow constraints should also be met:

[0053]

[0054] Where, is the maximum virtual flow limit flowing through branch ij.

[0055] As can be seen from the above description, in this way, important loads can be connected through the backbone network without being disconnected.

[0056] Please refer to Figure 2 Another embodiment of the present invention provides an optimization system for a disaster-proof backbone grid of a power transmission network, comprising:

[0057] A data input module, used for receiving line information and load distribution information of the transmission network;

[0058] An optimization model module is configured to establish a first optimization model for a disaster-resistant backbone grid of the transmission network based on the objective function and constraints, taking the minimization of the investment cost of the differentiated reinforcement lines already constructed in the transmission network and the maximization of the load supply under the line disaster operation state as objective functions; to separate discrete variables and continuous variables in the first optimization model using separation inequality constraints, thereby simplifying the first optimization model into a second mixed integer linear optimization model; and to add virtual power flow constraints to the second optimization model so that the second optimization model connects all important loads and power nodes.

[0059] The disaster prevention backbone network decision module is used to input the line information and load distribution information of the transmission network into the second optimization model to solve and obtain a differentiated reinforcement plan for the disaster prevention backbone network of the transmission network.

[0060] Furthermore, the objective function of minimizing the investment cost of the differentiated reinforcement lines already constructed in the transmission network and maximizing the load supply under the disaster operation state of the lines includes:

[0061] The objective function is:

[0062]

[0063] Where, Ψ is the set of planned lines to be built; C t is the investment cost of converting the line to be built t into a common line; C t ′ is the investment cost of building the line t to be built into a differentiated enhanced line; L t is a 0-1 decision variable indicating whether to build line t, 0 means not to build, 1 means to build; D t is a 0-1 decision variable indicating whether to build a differentiated enhanced line t, 0 indicates not to build a differentiated enhanced line, and 1 indicates to build a differentiated enhanced line;

[0064] S H To differentiate and enhance the set of existing lines, K ij represents the incremental investment cost of differentiated enhancement of existing line ij; H ij is a 0-1 decision variable indicating whether differentiated enhancement construction is carried out on line ij, where 0 indicates no differentiated enhancement and 1 indicates differentiated enhancement;

[0065] S N is the set of all nodes, W L is the unit power supply benefit of node load under disaster operation state, represents the load power of node i in the disaster operation state, and the superscript (d) indicates the disaster operation state.

[0066] Furthermore, the constraints include guaranteed output constraints of node units in disaster operation states and normal operation states, power supply constraints of important loads, balance constraints of node power and power flow safety constraints of lines.

[0067] Furthermore, the differentiated enhanced line satisfies the DC power flow equation under disaster operation:

[0068]

[0069]

[0070] Where, is the load power flowing through line ij under disaster operation state, is the load power limit flowing through line t under disaster conditions, x ij 、x t are the reactance values ​​of line ij and line t respectively, are the phase angle values ​​of nodes i and j under the disaster operation state respectively;

[0071] The differentiated enhanced line satisfies the DC power flow equation under normal operating conditions:

[0072]

[0073]

[0074] In the formula are the phase angle values ​​of nodes i and j under normal operating conditions, is the load power flowing through line ij under normal operating conditions, is the load power limit flowing through line t under normal operating conditions; (L t ||D t ) is the binary OR operator.

[0075] Furthermore, adding a virtual power flow constraint condition to the second optimization model so that the second optimization model connects all important loads and power supply nodes includes:

[0076] Constructing all the differentiated reinforcement lines into a disaster-proof backbone network;

[0077] Constructing a virtual power supply for the important load line, and externally connecting the virtual power supply to the node of the disaster-proof backbone network, and providing supply for the virtual load of the node through the virtual power supply;

[0078] The nodes of the disaster-proof backbone network meet the following requirements:

[0079]

[0080] Where, f ij is the virtual power flow value of branch ij in the backbone network, and f ij The branch virtual power flow constraints should also be met:

[0081]

[0082] Where, is the maximum virtual flow limit flowing through branch ij.

[0083] The above-mentioned method and system for optimizing the disaster-resistant backbone grid of a transmission network of the present invention are applicable to lines with different power supply capabilities, realizing enhanced optimization of the disaster-resistant backbone grid and improving the optimization economy. The following is an explanation through specific implementation methods:

[0084] Example 1

[0085] Please refer to Figure 1 A method for optimizing a disaster prevention backbone grid of a power transmission network comprises the following steps:

[0086] S1. Receive line information and load distribution information of the transmission network.

[0087] Specifically, it receives data on the grid nodes, lines, transformers, power sources, conventional loads, important loads, etc. of the transmission network.

[0088] S2. Taking the minimum investment cost of the differentiated reinforcement lines already constructed in the transmission network and the maximum load supply under the disaster operation state of the lines as the objective function, a first optimization model of the disaster-proof backbone grid of the transmission network is established based on the objective function and the constraints.

[0089] Among them, the objective function of the first optimization model is:

[0090]

[0091] Where, Ψ is the set of planned lines to be built; C t is the investment cost of converting the line to be built t into a common line; C t ′ is the investment cost of building the line t to be built into a differentiated enhanced line; L t is a 0-1 decision variable indicating whether to build line t, 0 means not to build, 1 means to build; D t is a 0-1 decision variable indicating whether to build a differentiated enhanced line t, 0 means not to build a differentiated enhanced line, 1 means to build a differentiated enhanced line; since only constructed lines can be differentiated enhanced, D t The number is less than L t The number of

[0092] S H To differentiate and enhance the set of existing lines, K ij represents the incremental investment cost of differentiated enhancement of existing line ij; H ij is a 0-1 decision variable indicating whether differentiated enhancement construction is carried out on line ij, where 0 indicates no differentiated enhancement and 1 indicates differentiated enhancement;

[0093] S N is the set of all nodes, W L is the unit power supply benefit of node load under disaster operation state, represents the load power of node i in the disaster operation state, and the superscript (d) indicates the disaster operation state.

[0094] Since the objective function is minimized, the load power supply benefit under the disaster operation state is positive, so the last term of the objective function takes a negative sign.

[0095] Among them, the constraints of the first optimization model include the guaranteed output constraints of node units under disaster operation status and normal operation status, the power supply constraints of important loads, the balance constraints of node power and the power flow safety constraints of the line.

[0096] The guaranteed output constraint of the node unit under the disaster operation state is:

[0097]

[0098] In the formula, the superscript (d) indicates the disaster operation status; represents the output of the unit connected to node i in the disaster operation state; It represents the guaranteed output upper limit of the node i unit under the disaster operation state.

[0099] The power supply constraints of important loads under disaster operation state are:

[0100]

[0101] Where, is the variable to be optimized; represents the minimum power required to supply all important loads at node i under disaster operation; It represents the maximum possible power to guarantee the supply of all loads at node i under the disaster operation state.

[0102] The balance constraint of node power under disaster operation state is:

[0103]

[0104] Where Ω is the set of all lines; is the load power flowing through line ij in the disaster operation state, and the positive direction is from node i to node j.

[0105] The power flow safety constraint of the line under disaster operation state is:

[0106] For differentiated enhancement lines in existing lines: Where, is the maximum load power limit flowing through line ij in case of disaster;

[0107] For differentiated enhanced lines to be built: Where, P t (d)max is the maximum load power limit flowing through line t in disaster conditions.

[0108] During normal operation, the disaster-resistant backbone network should also meet the constraints of normal grid operation:

[0109] Guaranteed output constraints of node units under normal operating conditions:

[0110]

[0111] Where, Indicates the output of the unit connected to node i under normal operating conditions; They represent the upper and lower limits of the unit output connected to node i, respectively. The superscript (0) indicates that it is in normal operation.

[0112] Node voltage constraints under normal operating conditions:

[0113]

[0114] Where, is the voltage of node i under normal operating conditions, are the upper and lower bound constraints respectively.

[0115] The balance constraint of node power under normal operating conditions:

[0116]

[0117] Where, is the load power flowing through line ij under normal operating conditions, It represents the supply power of all loads of node i under normal operating conditions.

[0118] Under normal operating conditions, the power flow safety constraints of the line under normal operating conditions are:

[0119] For existing lines:

[0120] Where, It is the maximum load power limit flowing through line ij under normal circumstances.

[0121] For lines to be built:

[0122] Where, P t (0)max is the maximum load power limit flowing through line t under normal circumstances, is the load power limit flowing through line t in disaster conditions.

[0123] S3. Separate the discrete variables and the continuous variables in the first optimization model using separation inequality constraints, and simplify the first optimization model into a second mixed integer linear optimization model.

[0124] All differentiated reinforcement lines in the disaster prevention backbone grid planning of the transmission network can be approximately considered to satisfy the DC power flow equation:

[0125]

[0126]

[0127] Where x ij 、x t are the reactance values ​​of line ij and line t respectively; are the phase angle values ​​of nodes i and j under the disaster operating state, respectively. Because the product term in the formula contains both 0-1 discrete decision variables and continuous variables, the constraint is nonlinear, which is not conducive to solving the model. To address the limitations of nonlinear constraints, this embodiment adopts the method of separating inequality constraints, rewriting the guaranteed output constraints and node voltage constraints of node units that meet the normal operation of the power grid as follows:

[0128]

[0129]

[0130] Where, is the penalty coefficient, which is a large constant. ij =1, D t = 1, the node power balance constraint that satisfies the normal operation of the power grid and the power flow safety constraint of the line under normal operation are converted into the conventional power flow equation equality constraint; when H ij =0, D t = 0, according to the power flow safety constraints of the line, it can be seen that is 0, so we can further deduce:

[0131]

[0132]

[0133] Where, is the upper limit of the node phase angle under the disaster operation state; x ij 、x t are the lower limits of line ij and line t respectively, so we can get the constant Desirable Desirable And when H ij =0, D t = 0, the node power balance constraint under normal grid operation and the power flow safety constraint of the line under normal operation form a relaxation constraint. The separation inequality constraint effectively separates the discrete decision variables and continuous variables, and establishes a 0-1 mixed integer linear programming model.

[0134] Similarly, under normal operating conditions, the line can be approximately considered to satisfy the DC power flow equation:

[0135]

[0136]

[0137] In the formula are the phase angle values ​​of nodes i and j under normal operating conditions, is the load power flowing through line ij under normal operating conditions, is the load power limit flowing through line t under normal operating conditions; (L t ||D t ) is the binary OR operator.

[0138] Similarly, the method of separating inequality constraints is used to rewrite the DC power flow equation as follows:

[0139]

[0140] Where, Desirable It is the upper limit of the node phase angle under normal operating conditions.

[0141] S4. Add virtual power flow constraints to the second optimization model so that the second optimization model connects all important loads and power supply nodes.

[0142] All the differentiated reinforced lines are constructed into a disaster-proof backbone network, which should also meet connectivity constraints, that is, important loads in the system can be connected through the backbone network without being disconnected.

[0143] In this embodiment, the "virtual flow" method is used to evaluate the connectivity of the backbone network:

[0144] A virtual power source is constructed for the important load line and connected to node i of the disaster-resistant backbone network. Assume that the backbone network has N nodes, each of which has one unit of "virtual load". The supply of the "virtual load" is provided by the external "virtual power source". The flow of the "virtual flow" of each branch is hypothetical and independent of the existence of the real flow. Therefore, if the planned backbone network has connectivity, then for each node i of the backbone network, the following conditions should be met:

[0145]

[0146] Where, f ij is the virtual power flow value of branch ij in the backbone network, and f ij The branch virtual flow constraints must also be met:

[0147]

[0148] Where, is the maximum virtual flow limit flowing through branch ij.

[0149] S5. Input the line information and load distribution information of the transmission network into the second optimization model to obtain a differentiated reinforcement scheme for the disaster-resistant backbone network of the transmission network.

[0150] Specifically, the second optimization model takes as input the existing grid parameters, including data on nodes, lines, transformers, power sources, conventional loads, and critical loads. The output is a disaster prevention backbone grid construction plan, specifying which existing lines require differentiated reinforcement and which new lines require differentiated reinforcement.

[0151] Example 2

[0152] The difference between this embodiment and the first embodiment is that, in order to verify the correctness of the proposed transmission network disaster prevention backbone grid optimization model and the effectiveness of the corresponding solution algorithm, a simulation test was conducted on the IEEE118 standard node system:

[0153] In the IEEE118 standard node system, except for nodes 8-10, 24-26, 30, 37, 38, 61, 63-65, 68, 69, 71-73, 81, 87, 89, 91, 99, 111, 113, and 116, the remaining nodes are all important load nodes or plant nodes, and their load supply must be guaranteed in the event of a disaster. The data size is shown in Table 1.

[0154] Table 1 Computational scale and planning results of IEEE118 node system

[0155] type Size Total number of nodes 118 Power plant node 54 Substation node 64 Important power plant nodes 38 Important substation nodes 53 Original ordinary line 186 Differential enhancement of the original line 80 New construction enhanced line 13 New construction of ordinary lines 8 Number of power plants experiencing power outages 14 Number of power outage substations 10

[0156] Using the disaster prevention backbone network planning method proposed in this embodiment, Figure 3 The simulation results for the IEEE 118 standard node system are shown. Black dots represent nodes connected to power plants, white dots represent load nodes or zero injection nodes, and solid and dashed lines represent branches between nodes. In the event of a disaster, power plant nodes 8, 10, 24-26, 65, 72, 73, 87, 91, 99, 111, 113, and 116 will cease operation, and substation nodes 5, 9, 30, 37, 38, 63, 64, 68, 71, and 81 will be shut down. Substations subject to power outages are marked with crosses in the diagram; the lines connected to these substations are assumed to be shut down in the event of a disaster. Figure 3 The solid lines in the figure are the branches that need differentiated reinforcement construction for existing lines. A total of 80 branches need differentiated reinforcement. Figure 3The dotted lines in the figure represent the differentiated reinforcement lines that need to be newly constructed. Thirteen differentiated reinforcement lines are required. These 93 differentiated reinforcement branches together form a disaster-resistant backbone network that meets topological connectivity and grid operation constraints, ensuring load supply at key nodes in the event of a disaster.

[0157] Example 3

[0158] Please refer to Figure 2 , an optimization system for a disaster prevention backbone grid of a transmission network, comprising:

[0159] The data input module is used to receive line information and load distribution information of the transmission network.

[0160] The optimization model module is used to establish a first optimization model of the disaster-resistant backbone grid of the transmission network based on the objective function and the constraint conditions, taking the minimum investment cost of the differentiated enhanced lines already constructed in the transmission network and the maximum load supply under the disaster operation state of the lines as the objective function; using separation inequality constraints to separate discrete variables and continuous variables in the first optimization model, and simplifying the first optimization model into a second mixed integer linear optimization model; adding virtual power flow constraints in the second optimization model so that the second optimization model connects all important loads and power nodes.

[0161] Among them, the objective function is:

[0162]

[0163] Where, Ψ is the set of planned lines to be built; C t is the investment cost of converting the line to be built t into a common line; C t ′ is the investment cost of building the line t to be built into a differentiated enhanced line; L t is a 0-1 decision variable indicating whether to build line t, 0 means not to build, 1 means to build; D t is a 0-1 decision variable indicating whether to build a differentiated enhanced line t, 0 indicates not to build a differentiated enhanced line, and 1 indicates to build a differentiated enhanced line;

[0164] S H To differentiate and enhance the set of existing lines, K ij represents the incremental investment cost of differentiated enhancement of existing line ij; H ij is a 0-1 decision variable indicating whether differentiated enhancement construction is carried out on line ij, where 0 indicates no differentiated enhancement and 1 indicates differentiated enhancement;

[0165] S N is the set of all nodes, W Lis the unit power supply benefit of node load under disaster operation state, represents the load power of node i in the disaster operation state, and the superscript (d) indicates the disaster operation state.

[0166] The constraints include: guaranteed output constraints of node units, power supply constraints of important loads, balance constraints of node power and power flow safety constraints of lines.

[0167] The differentiated enhanced line satisfies the DC power flow equation:

[0168]

[0169]

[0170] Where, is the load power flowing through line ij under disaster operation state, is the load power limit flowing through line t under disaster conditions, x ij 、x t are the reactance values ​​of line ij and line t respectively, are the phase angle values ​​of nodes i and j under disaster operation status respectively.

[0171] The virtual power flow constraints include:

[0172] Constructing all the differentiated reinforcement lines into a disaster-proof backbone network;

[0173] Constructing a virtual power supply for the important load line, and externally connecting the virtual power supply to the node of the disaster-proof backbone network, and providing supply for the virtual load of the node through the virtual power supply;

[0174] The nodes of the disaster-proof backbone network meet the following requirements:

[0175]

[0176] Where, f ij is the virtual power flow value of branch ij in the backbone network, and f ij The branch virtual flow constraints must also be met:

[0177]

[0178] Where, is the maximum virtual flow limit flowing through branch ij.

[0179] The disaster prevention backbone network decision module is used to input the line information and load distribution information of the transmission network into the second optimization model to obtain a differentiated reinforcement plan for the disaster prevention backbone network of the transmission network.

[0180] In summary, the present invention provides a method and system for optimizing a disaster-resistant backbone grid of a transmission network. The method and system take the minimization of the investment cost of the differentiated reinforcement lines already constructed in the transmission network and the maximization of the load supply under the line disaster operation state as the objective function, and establishes a first optimization model of the disaster-resistant backbone grid of the transmission network in combination with the objective function constraint conditions. The first optimization model is simplified using separation inequality constraints, and all important loads and power supply nodes are connected through the optimization model. Therefore, the optimization model not only considers the differentiated investment cost of the backbone grid and the power supply guarantee for important users, but also considers improving the power supply capacity of general users, so that the scope of guaranteed power supply in the event of a disaster includes but is not limited to important loads, and improves the optimization economy. The line information and load distribution information of the transmission network are input into the second optimization model to obtain a differentiated reinforcement plan for the disaster-resistant backbone grid of the transmission network, so that the reinforcement scope of the disaster-resistant backbone grid can be determined through the optimal overall social cost.

[0181] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's description and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for optimizing a disaster-proof backbone grid of a power transmission network, characterized in that: Including steps: Receive line information and load distribution information of the transmission network; Taking the minimization of investment cost of the differentiated reinforcement lines already built in the transmission network and the maximization of load supply under the disaster operation state of the lines as the objective function, the first optimization model of the disaster-resistant backbone grid of the transmission network is established based on the objective function and the constraints. Separating discrete variables and continuous variables in the first optimization model by using separation inequality constraints, and simplifying the first optimization model into a second mixed integer linear optimization model; Adding a virtual power flow constraint condition to the second optimization model so that the second optimization model connects all important loads and power nodes; Inputting the line information and load distribution information of the transmission network into the second optimization model to solve and obtain a differentiated reinforcement scheme for the disaster-resistant backbone grid of the transmission network; The differentiated enhanced line satisfies the DC power flow equation under disaster operation: ； ； Where, The line flows through in disaster operation state ij The load power, For disaster situations, the flow through the line t Load power limit, x ij 、 x t Line ij and lines t The reactance value, 、 They are nodes in disaster operation state i, j The phase angle value of It is a collection of planned lines to be built; S H Enhance route collection for differentiation among existing routes; H ij To indicate whether the line ij A 0-1 decision variable for carrying out differentiated enhancement construction, where 0 means not carrying out differentiated enhancement and 1 means carrying out differentiated enhancement; L t To indicate whether to build a line t 0-1 decision variable, 0 means no construction, 1 means construction; D t To indicate whether to build a differentiated enhanced line A 0-1 decision variable, where 0 means not to build a differentiated enhanced line, and 1 means to build a differentiated enhanced line; The differentiated enhanced line satisfies the DC power flow equation under normal operating conditions: ； ； In the formula 、 They are nodes in normal operating state i, j The phase angle value, Flowing through the line under normal operating conditions ij The load power, Flowing through the line under normal operating conditions t Load power limitation; The "||" is the binary OR operator; Adding a virtual power flow constraint condition to the second optimization model so that the second optimization model connects all important loads and power supply nodes includes: Constructing all the differentiated reinforcement lines into a disaster-proof backbone network; Constructing a virtual power supply for an important load line, and externally connecting the virtual power supply to a node of the disaster-proof backbone network, so as to provide supply for the virtual load of the node through the virtual power supply; The nodes of the disaster-proof backbone network meet the following requirements: ； Where, f ij For branches flowing through the backbone network ij The virtual power flow value of f ij The branch virtual flow constraints must also be met: ； Where, For the branch ij The maximum virtual flow rate limit.

2. The method for optimizing a disaster-proof backbone grid of a power transmission network according to claim 1, characterized in that: The objective function of minimizing the investment cost of the differentiated reinforcement lines already constructed in the transmission network and maximizing the load supply under the line disaster operation state includes: The objective function is: ； Where, It is a collection of planned lines to be built; C t For the lines to be built t The investment cost of building a normal line; For the lines to be built t The investment cost of building a differentiated enhanced line; L t To indicate whether to build a line t 0-1 decision variable, 0 means no construction, 1 means construction; D t To indicate whether to build a differentiated enhanced line A 0-1 decision variable, where 0 means not to build a differentiated enhanced line, and 1 means to build a differentiated enhanced line; S H Enhance the set of routes for differentiation among existing routes, K ij Indicates that the existing line ij the incremental investment costs of making differentiated enhancements; H ij To indicate whether the line ij A 0-1 decision variable for carrying out differentiated enhancement construction, where 0 means not carrying out differentiated enhancement and 1 means carrying out differentiated enhancement; S N is the set of all nodes, W L is the unit power supply benefit of node load under disaster operation state, Representation node i Load power in disaster operation state, superscript ( d ) indicates the disaster operation status.

3. The method for optimizing a disaster-proof backbone grid of a power transmission network according to claim 1, characterized in that: The constraints include guaranteed output constraints of node units in disaster operation and normal operation, power supply constraints of important loads, balance constraints of node power and power flow safety constraints of lines.

4. An optimization system for a disaster prevention backbone grid of a power transmission network, characterized in that: include: A data input module, used for receiving line information and load distribution information of the transmission network; An optimization model module is used to establish a first optimization model of the disaster-resistant backbone grid of the transmission network based on the objective function and the constraints, taking the minimum investment cost of the differentiated reinforcement lines already built in the transmission network and the maximum load supply under the disaster operation state of the lines as the objective function; Separating discrete variables and continuous variables in the first optimization model using separation inequality constraints, simplifying the first optimization model into a mixed integer linear second optimization model; adding virtual power flow constraints to the second optimization model so that the second optimization model connects all important loads and power nodes; a disaster prevention backbone network decision module, configured to input the line information and load distribution information of the transmission network into the second optimization model to solve and obtain a differentiated reinforcement plan for the disaster prevention backbone network of the transmission network; The differentiated enhanced line satisfies the DC power flow equation under disaster operation: ； ； Where, The line flows through in disaster operation state ij The load power, For disaster situations, the flow through the line t Load power limit, x ij 、 x t Line ij and lines t The reactance value, 、 They are nodes in disaster operation state i, j The phase angle value of It is a collection of planned lines to be built; S H Enhance route collection for differentiation among existing routes; H ij To indicate whether the line ij A 0-1 decision variable for carrying out differentiated enhancement construction, where 0 means not carrying out differentiated enhancement and 1 means carrying out differentiated enhancement; L t To indicate whether to build a line t 0-1 decision variable, 0 means no construction, 1 means construction; D t To indicate whether to build a differentiated enhanced line A 0-1 decision variable, where 0 means not to build a differentiated enhanced line, and 1 means to build a differentiated enhanced line; The differentiated enhanced line satisfies the DC power flow equation under normal operating conditions: ； ； In the formula 、 They are nodes in normal operating state i, j The phase angle value, Flowing through the line under normal operating conditions ij The load power, Flowing through the line under normal operating conditions t Load power limitation; The "||" is the binary OR operator; Adding a virtual power flow constraint condition to the second optimization model so that the second optimization model connects all important loads and power supply nodes includes: Constructing all the differentiated reinforcement lines into a disaster-proof backbone network; Constructing a virtual power supply for an important load line, and externally connecting the virtual power supply to a node of the disaster-proof backbone network, so as to provide supply for the virtual load of the node through the virtual power supply; The nodes of the disaster-proof backbone network meet the following requirements: ； Where, f ij For branches flowing through the backbone network ij The virtual power flow value of f ij The branch virtual flow constraints must also be met: ； Where, For the branch ij The maximum virtual flow rate limit.

5. The optimization system for a disaster-proof backbone grid of a power transmission network according to claim 4, characterized in that: The objective function of minimizing the investment cost of the differentiated reinforcement lines already constructed in the transmission network and maximizing the load supply under the line disaster operation state includes: The objective function is: ； Where, It is a collection of planned lines to be built; C t For the lines to be built t The investment cost of building a normal line; For the lines to be built t The investment cost of building a differentiated enhanced line; L t To indicate whether to build a line t 0-1 decision variable, 0 means no construction, 1 means construction; D t To indicate whether to build a differentiated enhanced line A 0-1 decision variable, where 0 means not to build a differentiated enhanced line, and 1 means to build a differentiated enhanced line; S H Enhance the set of routes for differentiation among existing routes, K ij Indicates that the existing line ij the incremental investment costs of making differentiated enhancements; H ij To indicate whether the line ij A 0-1 decision variable for carrying out differentiated enhancement construction, where 0 means not carrying out differentiated enhancement and 1 means carrying out differentiated enhancement; S N is the set of all nodes, W L is the unit power supply benefit of node load under disaster operation state, Representation node i Load power in disaster operation state, superscript ( d ) indicates the disaster operation status.

6. The optimization system for a disaster-proof backbone grid of a power transmission network according to claim 4, characterized in that: The constraints include guaranteed output constraints of node units in disaster operation and normal operation, power supply constraints of important loads, balance constraints of node power and power flow safety constraints of lines.

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