Wide frequency oscillation monitoring device configuration method for large-scale high-proportion new energy power system

Abstract

This invention relates to a method for configuring a broadband oscillation monitoring device in a large-scale, high-proportion renewable energy power system. First, observability and controllability indices for each node under different oscillation modes are constructed. Second, based on these indices, a criticality index describing the participation of each node in broadband oscillations under different operating conditions is constructed. Then, based on the node criticality indices, an optimized configuration model for the broadband oscillation monitoring device in a high-proportion renewable energy power system is constructed. This invention defines the criticality index of each node under different operating conditions based on the controllability and observability of system nodes under different oscillation modes, thereby proposing a method for configuring a broadband oscillation monitoring device in a large-scale, high-proportion renewable energy power system.

Description

Technical Field

[0001] This invention relates to the field of monitoring high-proportion renewable energy power systems, and in particular to a method for configuring a broadband oscillation monitoring device for large-scale high-proportion renewable energy power systems. Background Technology

[0002] In recent years, broadband oscillation events in the power system caused by the integration of new energy sources have occurred frequently, posing a significant threat to the safe operation of the power system. To ensure the safe and stable operation of power systems with a high proportion of new energy and avoid unnecessary economic losses caused by broadband oscillations, real-time monitoring of the power system can be conducted to understand the grid's operating status and provide effective data support for the analysis, protection, and suppression of broadband oscillations. However, considering cost constraints, the configuration of broadband oscillation monitoring devices should minimize the number of devices while ensuring global observability of the system. Priority should be given to installing them on nodes with high observability of oscillation modes and nodes prone to oscillation after disturbances. Therefore, this invention proposes a method for configuring broadband oscillation monitoring devices in large-scale, high-proportion new energy power systems. First, observability and controllability indices for each node under different oscillation modes are constructed. Second, based on this, a criticality index describing the participation of each node in broadband oscillations under different operating modes is constructed. Then, based on the node criticality index, an optimized configuration model for broadband oscillation monitoring devices in high-proportion new energy power systems is constructed. Summary of the Invention

[0003] The purpose of this invention is to ensure the global objectivity of broadband oscillations in new energy power systems and to obtain better monitoring results. It provides a method for configuring broadband oscillation monitoring devices in large-scale, high-proportion new energy power systems, which can achieve reasonable configuration of broadband oscillation monitoring devices.

[0004] To achieve the above objectives, the technical solution of the present invention is: a method for configuring a broadband oscillation monitoring device for a large-scale, high-proportion new energy power system, comprising:

[0005] Step 1: Construct observability and controllability indices for each node under different oscillation modes;

[0006] Step 2: Construct the criticality of each node in the power grid participating in broadband oscillation;

[0007] Step 3: Construct an optimized configuration model for broadband oscillation monitoring devices in high-proportion new energy power systems.

[0008] In one embodiment of the present invention, step 1 is specifically implemented as follows:

[0009] Suppose the network has M oscillation modes, denoted as s. m =σ m ±jω m , where σ mand ω m The oscillation modes are s respectively. m The oscillation frequency and oscillation damping; when a unit pulse current excitation is applied to a node n of the impedance network, the node voltage of any node j can be expressed as...

[0010]

[0011] In the formula, Let represent the instantaneous node voltage values ​​of each node in the network, with the subscripts j and n indicating the observation node and the excitation node, respectively. node voltage The m-th oscillation mode s m The initial oscillation amplitude of (m=1,2,…,M), For oscillation mode s m The initial phase, where N is the total number of nodes in the network;

[0012] For any oscillation mode s m When a current excitation is applied to a node, the amplitude of the resulting mode oscillation reflects the degree to which the node can be excited about that oscillation mode, i.e., its controllability. Therefore, the controllability index of a node to an oscillation mode is expressed as:

[0013]

[0014] In the formula, This indicates that node n represents the oscillation mode s. m Controllability;

[0015] For any oscillation mode s m The initial oscillation amplitude of the mode in each node voltage reflects the observability of that oscillation mode at the node; therefore, the observability index of a node for an oscillation mode is expressed as:

[0016]

[0017] In the formula, This indicates that node j corresponds to oscillation mode s. m The degree of its significance.

[0018] In one embodiment of the present invention, step 2 is specifically implemented as follows:

[0019] Combining the observability and controllability of oscillation modes, a criticality index is constructed to describe the participation of each node in the broadband oscillation. Considering that the observability and controllability of nodes change under different operating conditions, the node criticality is defined as a weighted average under different operating conditions, i.e.

[0020]

[0021] In the formula,

[0022]

[0023] In the formula, W n Let K be the node criticality of node n, and K be the total number of selected execution modes. and Let r represent the observability and controllability of node n under the k-th operating mode for the broadband oscillation mode, respectively. k The weight represents the k-th operating mode. Since the greater the negative damping, the stronger the oscillation, the weight of the operating mode is proportional to the absolute value of the system's broadband oscillation damping under the corresponding operating condition.

[0024] In one embodiment of the present invention, step 3 is specifically implemented as follows:

[0025] Based on the node criticality index, an optimal configuration model for broadband oscillation measurement devices in high-proportion new energy power systems is constructed. The optimization objectives include minimizing the number of nodes with installed devices and maximizing node criticality. The constraint condition is global observability, meaning that at least one node itself or its adjacent nodes must have a measurement device installed. The optimization model is represented as follows:

[0026]

[0027] Where x i For 0-1 decision variables, x i =0 indicates that the measuring device is not installed at node i, x i =1 indicates that the measuring device is installed in section i, Ω i Let N be the set of adjacent nodes of node i, including node i itself, and N be the total number of nodes in the network.

[0028] Compared with the prior art, the present invention has the following beneficial effects: The present invention defines the criticality of broadband oscillation of each node under different operating modes based on the controllability and observability of system nodes under different oscillation modes, thereby proposing a configuration method for broadband oscillation monitoring devices in large-scale, high-proportion new energy power systems, which can realize the reasonable configuration of broadband oscillation monitoring devices. Attached Figure Description

[0029] Figure 1 This is a flowchart illustrating the design and implementation steps of the high-proportion new energy power system broadband oscillation monitoring device configuration method of the present invention. Detailed Implementation

[0030] The technical solution of the present invention will now be described in detail with reference to the accompanying drawings.

[0031] The proposed method for configuring a broadband oscillation monitoring device in a high-proportion renewable energy power system will be designed and implemented according to the following steps, as shown in the flowchart. Figure 1 As shown:

[0032] Step 1: Construct observability and controllability indices for each node under different oscillation modes.

[0033] Apply current excitation to a node in the power grid, and calculate the observability and controllability indices of each node based on the voltage generated by each node.

[0034] Suppose the network has M oscillation modes, denoted as s. m =σ m ±jω m , where σ m and ω m The oscillation modes are s respectively. m The oscillation frequency and oscillation damping; when a unit pulse current excitation is applied to a node n of the impedance network, the node voltage of any node j can be expressed as...

[0035]

[0036] In the formula, Let represent the instantaneous node voltage values ​​of each node in the network, with the subscripts j and n indicating the observation node and the excitation node, respectively. node voltage The m-th oscillation mode s m The initial oscillation amplitude of (m=1,2,…,M), For oscillation mode s m The initial phase, where N is the total number of nodes in the network;

[0037] For any oscillation mode s m When a current excitation is applied to a node, the amplitude of the resulting mode oscillation reflects the degree to which the node can be excited about that oscillation mode, i.e., its controllability. Therefore, the controllability index of a node to an oscillation mode is expressed as:

[0038]

[0039] In the formula, This indicates that node n represents the oscillation mode s. m Controllability;

[0040] For any oscillation mode s m The initial oscillation amplitude of the mode in each node voltage reflects the observability of that oscillation mode at the node; therefore, the observability index of a node for an oscillation mode is expressed as:

[0041]

[0042] In the formula, This indicates that node j corresponds to oscillation mode s. m The degree of its significance.

[0043] Step 2: Construct the criticality of each node in the power grid participating in broadband oscillations

[0044] By combining the observability and controllability of oscillation modes, a key index is constructed that can describe the participation of each node in the power grid in broadband oscillations.

[0045] Considering that the observability and controllability of nodes will change under different operating conditions, the criticality of a node is defined as a weighted average under different operating conditions, i.e.

[0046]

[0047] In the formula,

[0048]

[0049] In the formula, W n Let K be the node criticality of node n, and K be the total number of selected execution modes. and Let r represent the observability and controllability of node n under the k-th operating mode for the broadband oscillation mode, respectively. k The weight represents the k-th operating mode. Since the greater the negative damping, the stronger the oscillation, the weight of the operating mode is proportional to the absolute value of the system's broadband oscillation damping under the corresponding operating condition.

[0050] Step 3: Construct an optimal configuration model for broadband oscillation monitoring devices in high-proportion renewable energy power systems.

[0051] With the optimization objectives of minimizing the number of installed nodes and maximizing node criticality, and with global observability as the constraint, an optimal configuration model for broadband oscillation measurement devices in high-proportion new energy power systems is constructed.

[0052] The optimization objectives include minimizing the number of nodes with installed devices and maximizing node criticality. The constraint is global observability, meaning that at least one node itself or one of its adjacent nodes must have a measuring device installed. The optimization model is represented as follows:

[0053]

[0054] Where x i For 0-1 decision variables, x i =0 indicates that the measuring device is not installed at node i, x i =1 indicates that the measuring device is installed in section i, Ω i Let N be the set of adjacent nodes of node i, including node i itself, and N be the total number of nodes in the network.

[0055] The above are preferred embodiments of the present invention. Any changes made to the technical solution of the present invention that do not exceed the scope of the technical solution of the present invention shall fall within the protection scope of the present invention.

Claims

1. A method for configuring a broadband oscillation monitoring device in a large-scale, high-proportion new energy power system, characterized in that, include: Step 1: Construct observability and controllability indices for each node under different oscillation modes; Step 2: Construct the criticality of each node in the power grid participating in broadband oscillation; Step 3: Construct an optimal configuration model for broadband oscillation monitoring devices in high-proportion new energy power systems; Step 1 is implemented as follows: Suppose the network has M oscillation modes, denoted as Moscillation. , where σ m and ω m The oscillation modes are s respectively. m The oscillation damping and oscillation frequency; when a unit pulse current excitation is applied to a node n of the impedance network, the node voltage of any node j can be expressed as... In the formula, (j, n=1, 2, …, N) represents the instantaneous node voltage values ​​of each node in the network, where the subscripts j and n represent the observation node and the excitation node, respectively. node voltage The m-th oscillation mode s m The initial oscillation amplitude of (m=1, 2, …, M), For oscillation mode s m The initial phase, where N is the total number of nodes in the network; For any oscillation mode s m For any oscillation mode s For any oscillation mode s In the formula, (n=1, 2, …, N, m=1, 2, …., M) represents node n pairs of oscillation modes s m Controllability; For any oscillation mode s m The initial oscillation amplitude of the mode in each node voltage reflects the observability of that oscillation mode at the node; therefore, the observability index of a node for an oscillation mode is expressed as: In the formula, (j=1, 2, …, N, m=1, 2, …., M) represents node j paired with oscillation mode s m The spectacles; Step 2 is implemented as follows: Combining the observability and controllability of oscillation modes, a criticality index is constructed to describe the participation of each node in the broadband oscillation. Considering that the observability and controllability of nodes change under different operating conditions, the node criticality is defined as a weighted average under different operating conditions, i.e. In the formula, In the formula, W n Let K be the node criticality of node n, and K be the total number of selected execution modes. and Let r represent the observability and controllability of node n under the k-th operating mode for the broadband oscillation mode, respectively. k The weight represents the k-th operating mode. Since the larger the negative damping, the stronger the oscillation, the weight of the operating mode is proportional to the absolute value of the system's broadband oscillation damping under the corresponding operating condition. Step 3 is implemented as follows: Based on the node criticality index, an optimal configuration model for broadband oscillation measurement devices in high-proportion new energy power systems is constructed. The optimization objectives include minimizing the number of nodes with installed devices and maximizing node criticality. The constraint condition is global observability, meaning that at least one node itself or its adjacent nodes must have a measurement device installed. The optimization model is represented as follows: Where x i For 0-1 decision variables, x i =0 indicates that the measuring device is not installed at node i, x i =1 indicates that the measuring device is installed at node i, Ω i Let N be the set of adjacent nodes of node i, including node i itself, and N be the total number of nodes in the network.

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