Method for evaluating in-disaster resistance of power system

Abstract

The invention belongs to the technical field of power system elasticity evaluation, and particularly relates to a method for evaluating the in-disaster resistance of a power system. Vectors of voltage and phase angles of all nodes of the power system are used for representing the state of the power system, and for the power system comprising Nb nodes, a 2Nb-1-dimensional system state vector of the power system is calculated; when a disaster occurs, it is assumed that an m-dimensional measurement vector is used to accommodate state data collected by remaining available real-time measurement equipment in a power system, and a measurement vector of a node b is selected; all measurement quantities in the system are recorded as vectors z, the relation between a measurement truth value ztrue and a system state x can be expressed by a group of nonlinear equations, and a measurement equation of a node b is solved: based on state estimation of a weighted least square method, a state estimation result is solved. According to the state estimation technology, measurement errors caused by random interference are eliminated by measuring the redundancy of the system in real time, the precision of overall data of the system is improved, and the operation state of the power system is accurately estimated or forecasted.

Description

Technical Field

[0001] The invention belongs to the technical field of power system resilience assessment, and in particular relates to a method for assessing the disaster resistance capability of a power system. Background Art

[0002] With the continuous advancement of smart grids and cyber-physical systems, the power system will gradually be coupled with the information system as an organic whole, namely the ubiquitous power Internet of Things. This will help the system control department to quickly and accurately obtain the fault detection and power outage load information during the disaster. Accordingly, the core of the research on resilience during disasters is to evaluate the real-time resistance of the power system to disasters, which reveals the actual operating status of the system.

[0003] Resistance, as an important characteristic of a resilient power system, mainly depends on the characteristics of the disaster, the strength of the equipment, and the system operation mode. However, the real-time operating status of the system is constantly changing in different time periods, and there is a certain error between the monitoring system data and the actual data. Therefore, even for the same power system, its resistance may fluctuate in different time periods, so the assessment of resistance needs to be specifically analyzed based on the actual characteristics of the power grid.

[0004] The development and progress of cutting-edge information technology has not only improved the production and operation efficiency of power systems, but also deepened the degree of information-physical coupling of power systems. The smooth operation and dispatching of modern power grids are inseparable from the information security of communication and measurement systems. However, after large-scale and severe natural disasters, the level of information collection in power systems is inevitably reduced, as measuring elements such as voltage and current transformers may be damaged to varying degrees, and other communication facilities are shut down. As the measured data at this time is relatively scarce and the accuracy is difficult to guarantee, it is difficult to directly assess the system's disaster status and guide power grid dispatching and post-disaster recovery. It is necessary to use state estimation technology to improve the system's measurement accuracy. Summary of the invention

[0005] To overcome the above defects, the purpose of the present invention is to provide a method for evaluating the disaster resistance capability of a power system, which can accurately evaluate the actual operating status of the power system and realize accurate evaluation of the system operating status and real-time resistance capability during a disaster.

[0006] To achieve the above object, the present invention adopts the following technical solution:

[0007] A method for evaluating the disaster resistance capability of a power system comprises the following steps:

[0008] The vectors of voltage magnitude and phase angle of all nodes in the power system are used to represent the state of the power system. b For a power system with 2 nodes, its 2N bThe -1-dimensional system state vector can be expressed as:

[0009]

[0010] Where V b With δ b are the voltage magnitude and phase angle of node b respectively;

[0011] When a disaster occurs, it is assumed that an m-dimensional measurement vector is used to accommodate the status data collected by the remaining available real-time measurement devices in the power system. The measurement vector of node b is selected as:

[0012]

[0013] Where P b With Q b is the active and reactive load size on node b, P k,b With Q k,b is the active and reactive power flow of line k connected to node b, N n,b is the number of measurements on node b;

[0014] All the measured quantities in the system are recorded as vector z, and the measured true value z true The relationship between and the system state x can be expressed by a set of nonlinear equations:

[0015] z true =h(x)

[0016] h b (x) represents the measurement equation of node b:

[0017]

[0018] Based on the state estimation of weighted least squares method, the result of state estimation is obtained:

[0019] min[zh(x)] T R -1 [zh(x)]

[0020] Among them, the covariance matrix R of the measurement error represents the confidence weight of each measurement quantity.

[0021] Preferably, the least squares method calculation steps are as follows:

[0022] (1) Variable initialization, read the remaining measurement vector z and set the initial value of the state vector to x (0) ;

[0023] (2) Calculate the measured Jacobian matrix H(x (k) ), as shown in the formula:

[0024]

[0025] (3) Using the gain matrix G(x (k) ) to judge the observability of the system, G(x (k) ) can be obtained by H(x (k) ) and R calculation

[0026] G(x (k) )=H T (x (k) )R -1 H(x (k) )

[0027] In the formula, k is the number of iterations;

[0028] (4) Calculate the correction vector

[0029] Δx (k) =[G(x (k) )] -1 H T (x (k) )R -1 [Zh(x (k) )]

[0030] Then update the state vector:

[0031] x (k+1) =Δx (k) +x (k)

[0032] (5) Continue iterating until convergence conditions are met Final calculation results is the current system state vector, that is

[0033] (6) Calculate the current system status and real-time resistance capability evaluation index.

[0034] Preferably, the real-time resistance capacity evaluation index includes the current load shedding ratio, the available transmission capacity of the section and the active power shortage in the area.

[0035] Preferably, the calculation formula of the current load shedding ratio is as follows:

[0036]

[0037] Where, L nl,b represents the load demand of node b under normal conditions, L dl,b represents the actual load demand of node b during the disaster, N b represents the number of nodes in the power system;

[0038] Preferably, the calculation formula of the available transmission capacity of the cross section is as follows:

[0039]

[0040] In the formula, C k,d represents the transmission power of line k in the disaster, l during Represents the set of normal lines that are disconnected during a disaster.

[0041] Preferably, the calculation formula for the active power shortage in the area is as follows:

[0042]

[0043] In the formula, G g,d Indicates the active output of unit g in the disaster, G during Indicates the set of normal units in the disaster area.

[0044] The positive beneficial effects of the present invention are:

[0045] 1. Since the data accuracy of the real-time measurement system is difficult to guarantee under the influence of disasters, the present invention eliminates the monitoring errors caused by disasters through state estimation technology, improves the overall accuracy of system data, and thus accurately evaluates the actual operating status of the power system, and realizes accurate evaluation of the system operating status and real-time resistance capability during disasters.

[0046] The present invention discloses a method for evaluating the disaster resistance capability of an electric power system based on state estimation technology. The state estimation technology utilizes the redundancy of a real-time measurement system to eliminate measurement errors caused by random interference, improves the accuracy of the overall system data, and accurately estimates or predicts the operating state of the electric power system. The evaluation method of the present invention provides an emergency solution for evaluating the operating status of the electric power system and compensating for the loss of the measuring device, and helps to ensure the reliability of the operation and dispatching of the power grid when encountering severe disasters. DETAILED DESCRIPTION

[0047] The present invention is further described below in conjunction with some specific implementation methods.

[0048] A method for evaluating the disaster resistance capability of a power system comprises the following steps:

[0049] The vectors of voltage magnitude and phase angle of all nodes in the power system are used to represent the state of the power system. b For a power system with 2 nodes, its 2N b The -1-dimensional system state vector can be expressed as:

[0050]

[0051] Where V b With δb are the voltage magnitude and phase angle of node b respectively;

[0052] The system state vector can be updated through iteration to minimize the residual between its measured value and estimated value, and finally obtain the most accurate system state estimate. When a disaster occurs, it is assumed that an m-dimensional measurement vector is used to accommodate the state data collected by the remaining available real-time measurement devices in the power system. For example, the measurement vector of node b is selected as:

[0053]

[0054] Where P b With Q b is the active and reactive load size on node b, P k,b With Q k,b is the active and reactive power flow of line k connected to node b, N n,b is the number of measurements on node b. Due to the uncertainty of disasters, the remaining measurements of each node will vary in quantity and type;

[0055] All the measured quantities in the system are recorded as vector z, and the measured true value z true The relationship between and the system state x can be expressed by a set of nonlinear equations:

[0056] z true =h(x)

[0057] h b (x) represents the measurement equation of node b:

[0058]

[0059] The weighted least square (WLS) method, which is the most widely used in state estimation, is used to reduce the estimated residual. The following formula gives the goal of the weighted least square method, and the state estimation result can be further obtained by iterative solution:

[0060] min[zh(x)] T R -1 [zh(x)]

[0061] Among them, the covariance matrix R of the measurement error represents the confidence weight of each measurement quantity.

[0062] Furthermore, the least squares method calculation steps are as follows:

[0063] (1) Variable initialization: read the remaining measurement vector z and set the initial value of the state vector to x(0);

[0064] (2) Calculate the measured Jacobian matrix H(x (k) ), as shown in the formula:

[0065]

[0066] (3) Using the gain matrix G(x (k) ) to judge the observability of the system, G(x (k) ) can be obtained by H(x (k) ) and R calculation

[0067] G(x (k) )=H T (x (k) )R -1 H(x (k) )

[0068] In the formula, k is the number of iterations;

[0069] If the measurement redundancy is too low or G(x (k) ) is even singular, the historical data is added to the measurement vector z as a pseudo-measurement;

[0070] (4) Calculate the correction vector

[0071]

[0072] Then update the state vector:

[0073] x (k+1) =Δx (k) +x (k)

[0074] (5) Continue iterating until convergence conditions are met Final calculation results is the current system state vector, that is

[0075] (6) Calculate the current system status and real-time resistance capability evaluation index;

[0076] By fitting the remaining measurements in the normal system area with the measurement function, a comprehensive and accurate estimation of the missing measurements is made. Three evaluation indicators are defined from three levels: real-time loss of load and equipment, current regional power shortage, and transmission capacity of available transmission sections to reflect the post-disaster recovery capability of the system:

[0077] (1) Current load loss percent (CLLP) is used to indicate the ratio of the load loss size to the overall load size when load loss occurs in the system:

[0078]

[0079] Where, L nl,b represents the load demand of node b under normal conditions, L dl,b represents the actual load demand of node b during the disaster, N b represents the number of nodes in the power system;

[0080] (2) The available transmission capacity of the section (ATCS) is used to indicate the transmission power margin of the line section during the disaster:

[0081]

[0082] In the formula, C k,d represents the transmission power of line k in the disaster, l during Represents the set of normal lines that are disconnected during a disaster.

[0083] (3) The active power deficiency of the area (APD A) is used to indicate the lack of active power in the disaster area:

[0084]

[0085] In the formula, G g,d Indicates the active output of unit g in the disaster, G during Indicates the set of normal units in the disaster area.

[0086] Taking a certain power system as an example, assuming that the disaster destroyed the transmission section, lines 11-13, 11-14 and 12-13 were shut down due to faults, and the measurement devices on lines 11-13, 11-14, 12-13 and 12-23 failed, the estimation results of the active power flow on line 12-23 are shown in Table 1;

[0087] Table 1 Practical application of state estimation in disasters

[0088]

[0089] As can be seen from Table 1, due to the destructive effects of the disaster, the flow of line 12-23 has exceeded the upper limit of the transmission capacity. Due to the failure of lines 11-13, 11-14 and 12-13, line 12-23 has become one of the only two lines connecting area 1 and area 2.

[0090] By adjusting the output of the generators at nodes 1, 2, 7, and 13 (see Table 2), the flow of the remaining available lines between the transmission sections is restored to the normal range, which can be proved by the state estimation results in Table 2. Obviously, the state estimation provides reliable data and information reference for emergency dispatch and control of the power system during the disaster, making up for the lack of measurement device failure during the disaster.

[0091] Table 2 Unit adjustment

[0092]

[0093] Correspondingly, the calculation results of the disaster resistance index of the power system are shown in Table 3.

[0094] Table 3 Calculated values ​​of disaster resistance index

[0095]

[0096] It can be seen from Table 3 that due to the emergency adjustment in the emergency situation during the disaster, the load shedding was avoided, so the value of the CLLP index was 0. The smaller ATCS value and the larger APDA value indicate a higher risk of load shedding. Therefore, the evaluation method of the present invention can accurately estimate or predict the operating status of the power system.

[0097] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Other modifications or equivalent substitutions made to the technical solution of the present invention by ordinary technicians in the field should be included in the scope of the claims of the present invention as long as they do not depart from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for evaluating the disaster resistance capability of a power system, characterized in that: The steps include: The vectors of voltage magnitude and phase angle of all nodes in the power system are used to represent the state of the power system. b For a power system with 2 nodes, its 2N b The -1-dimensional system state vector can be expressed as: Where V b With δ b are the voltage magnitude and phase angle of node b respectively; When a disaster occurs, it is assumed that an m-dimensional measurement vector is used to accommodate the status data collected by the remaining available real-time measurement devices in the power system. The measurement vector of node b is selected as: Where P b With Q b is the active and reactive load size on node b, P k,b With Q k,b is the active and reactive power flow of line k connected to node b, N n,b is the number of measurements on node b; All the measured quantities in the system are recorded as vector z, and the measured true value z true The relationship between and the system state x can be expressed by a set of nonlinear equations: z true =h(x) h b (x) represents the measurement equation of node b: Based on the state estimation of weighted least squares method, the result of state estimation is obtained: min[z-h(x)] T R -1 [z-h(x)] Among them, the covariance matrix R of the measurement error represents the confidence weight of each measurement quantity.

2. The method for evaluating the disaster resistance capability of a power system according to claim 1, characterized in that: The least squares method calculation steps are as follows: (1) Variable initialization, read the remaining measurement vector z and set the initial value of the state vector to x (0) ; (2) Calculate the measured Jacobian matrix H(x (k) ), as shown in the formula: (3) Using the gain matrix G(x (k) ) to judge the observability of the system, G(x (k) ) can be obtained by H(x (k) ) and R calculation G(x (k) )=H T (x (k) )R -1 H(x (k) ) In the formula, k is the number of iterations; (4) Calculate the correction vector Δx (k) =[G(x (k) )] -1 H T (x (k) )R -1 [Z-h(x (k) )] Then update the state vector: x (k+1) =Δx (k) +x (k) (5) Continue iterating until convergence conditions are met Final calculation results is the current system state vector, that is (6) Calculate the current system status and real-time resistance capability evaluation index.

3. The method for evaluating the disaster resistance capability of a power system according to claim 2, characterized in that: The real-time resistance capacity evaluation index includes the current load shedding ratio, the available transmission capacity of the section and the active power shortage in the area.

4. The method for evaluating the disaster resistance capability of a power system according to claim 3, characterized in that: The calculation formula of the current load shedding ratio is as follows: Where, L nl,b represents the load demand of node b under normal conditions, L dl,b represents the actual load demand of node b during the disaster, N b Represents the number of nodes in the power system.

5. The method for evaluating the disaster resistance capability of a power system according to claim 3, characterized in that: The calculation formula for the available transmission capacity of the section is as follows: In the formula, C k,d represents the transmission power of line k in the disaster, l during Represents the set of normal lines that are disconnected during a disaster.

6. The method for evaluating the disaster resistance capability of a power system according to claim 3, characterized in that: The calculation formula for the active power shortage in the area is as follows: In the formula, G g,d Indicates the active output of unit g in the disaster, G during Indicates the set of normal units in the disaster area.

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