A method for security check of auxiliary services based on static security domain

Abstract

This invention discloses an ancillary service security verification method based on a static security domain, comprising: Step 1: obtaining the generator operating status according to the topology and parameters of a specified power system, as well as the upper and lower limits of active power output of system nodes; Step 2: establishing a power system ancillary service security model based on the generator operating status; Step 3: verifying the circuit system ancillary service security model offline. If the conditions are met, a backup thermal stability security domain is output; otherwise, return to Step 2. This invention can facilitate dispatchers and power plants to rationally formulate power energy and backup ancillary service dispatch output schemes.

Description

Technical Field

[0001] This invention relates to the field of power system security domain theory, and in particular to an optimization method for ancillary service security verification based on static security domains. Background Technology

[0002] The development of new energy technologies has become a key pathway to sustainable human development, and the establishment of spot markets will facilitate the absorption of renewable energy. Spot markets trade in electrical energy, reserves, and other ancillary services. Developing spot markets helps to discover the value attributes of scarce resources, reduce trading risks, ensure the safe operation of the power grid, and achieve rational resource allocation. The role of reserve ancillary services in ensuring the safe and reliable operation of the power system is becoming increasingly prominent. Research on reserve markets is of great significance for the current construction of my country's spot market and the future improvement of its ancillary service market.

[0003] Due to the inherent uncertainty and randomness of new energy sources, dispatch plans based solely on day-ahead forecasts of new energy output and load power are often insufficient for actual dispatch, and may even lead to stability issues. To address the problem of dispatch plans failing to meet verification requirements due to uncertainty, simply revising the dispatch plan is clearly not feasible. Therefore, there is an urgent need for effective technologies to perform safety verification of power generation plans, constructing low-dimensional safety domains or safety domains that consider critical nodes, and assisting operators in developing economical and effective dispatch schemes. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention primarily studies a dimensionality reduction method for static security domains. It qualitatively defines the thermally stable security domain considering power flow transmission limits, then filters effective constraints, and finally reduces the dimensionality of the static security domain from a high-dimensional space to a space corresponding to specified nodes using the Fourier-Motzkin elimination method. Finally, a visualized security domain for the specified nodes is obtained, facilitating scheduling personnel to monitor the stability of critical nodes and important lines.

[0005] To address the problems of the existing technology, the present invention adopts the following technical solution:

[0006] A method for security verification of auxiliary services based on static security domains, characterized by the following steps:

[0007] Step 1: Obtain the generator operating status based on the topology and parameters of the specified power system, as well as the upper and lower limits of the active power output of the system nodes;

[0008] Step 2: Establish a power system ancillary service security model based on the generator operating status;

[0009] Step 3: Verify the auxiliary service safety model of the circuit system offline. If the conditions are met, output the backup thermal stability safety domain; otherwise, return to step 2. Wherein:

[0010] The offline verification process for the safety model of the circuit system's auxiliary services includes the following steps:

[0011] Based on the DC power flow in the power system topology, the thermal stability security domain of the hyperplane is constructed according to the following formula:

[0012]

[0013] in: P is the hyperplane coefficient. k S represents the node power injection value. B Let f(x) = P be the set of branches, and f(x) = P be other constraints.

[0014] Principal component analysis is used to reduce the dimensionality of key nodes in the thermal stability safe region of the hyperplane to obtain a visualized thermal stability safe region.

[0015] The backup thermal stability safety region is obtained by calculating the visualized thermal stability safety region using the Fourier-Motzkin elimination method.

[0016] Furthermore, in step 3, the process of constructing the thermally stable safe region of the hyperplane includes the following steps:

[0017] The power system ancillary service security model constructs a thermally stable security domain through active power injection at nodes of branches:

[0018]

[0019] From Ω THSR As can be seen from the definition of (h), the key to solving the thermal stability security domain lies in establishing the mapping relationship between the active power injection of nodes and the active power flow of branches.

[0020] The thermal stability safety domain introduces the following sharing coefficient for active power injection at the balancing node.

[0021]

[0022] The sensitivity model of the balancing node is obtained based on the active power injection of the balancing node:

[0023]

[0024] The thermal stability constraint of the sensitivity model branch is expressed by the following equation:

[0025]

[0026] make, Then we get:

[0027]

[0028] The Ω corresponding to the thermal stability constraint of branch l in the above equation THSR (h) Thermally stable safe domain of the local boundary hyperplane.

[0029] Furthermore, in step 3, principal component analysis is used to reduce the dimensionality of the key nodes of the thermal stability safe region of the hyperplane to obtain a visualized thermal stability safe region process, including the following steps:

[0030] Classify and sort all generating units in the power system to construct a dominant generating unit set;

[0031] The dominant unit set establishes a comprehensive sensitivity model according to the following formula;

[0032]

[0033] Where: n represents the number of generating units, and m represents the number of overload branches in the cross section.

[0034] The weight of each overloaded branch in the total overload is calculated using the following formula;

[0035]

[0036] Where: Let α be the weight coefficient corresponding to each of the m indicators. l , representing the weight corresponding to the overloaded branch;

[0037] The algebraic sum of the products of the computer group's sensitivity to each overload branch and its corresponding weight yields the set of the unit's overall sensitivity to this over-limit situation, namely:

[0038]

[0039] Calculate the covariance matrix of the comprehensive sensitivity set Z, and obtain m eigenvalues ​​λ1≥λ2≥λ3≥…≥λ m ≥0;

[0040] Calculate the variance contribution rate and cumulative variance contribution rate of the principal components, determine the top c principal components that can comprehensively represent m indicators, and obtain the corresponding unit eigenvector e. l , and obtain the l-th principal component evaluation value of the i-th unit;

[0041] The comprehensive evaluation value of each unit is obtained by using the variance contribution rate of each principal component as the weight.

[0042] Furthermore, in step 3, the process of calculating the backup thermal stability safety region from the visualized thermal stability safety region using the Fourier-Motzkin elimination method includes the following steps:

[0043] The visual thermal stability safety domain boundary of the critical node space is established using the following formula:

[0044]

[0045] Among them, P i Represents the active power injection at node i; α l,i c represents the hyperplane coefficient of the safety domain boundary of node i with respect to branch l; l denoted by , where na represents the influence coefficient of non-critical nodes on branch l; and na is the dimension of the critical node space.

[0046] The alternative thermal stability safety region is obtained by calculating the visualized thermal stability safety region based on the Fourier-Motzkin elimination method, namely:

[0047]

[0048] Where: P k a′ is the node power injection value. l,k and a″ l,k These represent different hyperplane coefficients, b′ l and b″ l These are different hyperplane constants.

[0049] Beneficial effects

[0050] Compared with the prior art, the beneficial effects of the present invention are:

[0051] The auxiliary service security verification method based on static security domains can be divided into the following parts:

[0052] (1) Based on the DC power flow model of the given topology, a hyperplane thermal stability safety domain is constructed, and the mapping relationship between the branch transmission limit and the active power injection of the node is given. Then, sensitivity analysis is performed on all nodes in the system to screen the dominant factors.

[0053] (2) The set of effective branch safety domains is reduced in dimension by Fourier-Motzkin elimination method. By transforming several elements in the hyperplane a finite number of times, the nodes with lower priority are eliminated first according to the priority of the node set. Finally, the dimension-reduced visualization safety interval of the key nodes is obtained, and finally the backup safety interval is obtained.

[0054] First, based on the DC power flow model, an explicit expression of the thermal stability safety domain for a given topology system is given. It is worth noting that this is only related to the system topology and does not change with the operating scenario. This means that one or several linear expressions can effectively describe the system's safety boundary. Then, based on the Fourier-Motzkin elimination method, the dimensionality of the critical branch set is reduced, and the high-dimensional hyperplane is projected onto the space of the key nodes of focus. This facilitates dispatchers and power plants in rationally formulating power supply and backup ancillary service dispatch output plans. Attached Figure Description

[0055] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments of this application and their descriptions are used to explain this application and do not constitute an undue limitation of this application.

[0056] Figure 1 The security verification flowchart provided by this invention is used to guide the construction of security intervals for auxiliary services;

[0057] Figure 2 The node diagram of the test system provided by this invention;

[0058] Figure 3 This invention provides an effective set of branch security domains.

[0059] Figure 4 The backup safety range provided by this invention shows that the backup safety upper limit is lower than the output upper limit, thus verifying the effectiveness of the auxiliary service safety check. Detailed Implementation

[0060] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0061] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0062] As introduced in the background section, existing ancillary service scheduling methods only consider when the reserve capacity meets the demand, without considering the constraints of transmission capacity. This will affect the feasibility of reserve call. This application proposes an ancillary service security verification method based on static security domain, which gives a thermally stable security domain that considers the power flow transmission limit and projects a high-dimensional hyperplane onto the key node space of focus, so as to facilitate dispatchers and power plants to reasonably formulate power and reserve ancillary service scheduling output schemes.

[0063] like Figure 1-4 As shown, to better explain the mechanism of the security verification method proposed in this invention, the following sections describe the two steps of constructing the thermally stable security domain set and constructing the backup call security interval.

[0064] 1. Construction of thermal stability safety domain

[0065] Power system thermal stability safety domain Ω THSR Defined in the node-injected power space, it is the set of all operating points (complex power injections) that satisfy the system's thermal stability safety constraints.

[0066]

[0067] The thermal stability safety domain is determined by the system's network topology and does not change with the operating point. For ease of description, it can be abbreviated as Ω. THSR (h), where h represents a certain predetermined network topology.

[0068] Considering factors such as local reactive power balance in the transmission network, the thermal stability security constraint of a branch is mainly affected by its transmitted active power. In practice, the thermal stability security domain can be defined on the active power injection space of the node, as shown in the following formula.

[0069]

[0070] From Ω THSR As can be seen from the definition of (h), the key to solving the thermal stability security domain lies in establishing the mapping relationship between the active power injection of nodes and the active power flow of branches.

[0071] The active power flow equations of a power system can be simplified to the following:

[0072]

[0073] By rearranging, the above equation can be transformed into the matrix shown below.

[0074] P=Bθ (4)

[0075] Transforming the above equation, we get:

[0076] θ=XP (5)

[0077] Correspondingly, the active power flow of branch l can be calculated by the following formula:

[0078]

[0079] According to equations (5) and (6), all nodes except the balancing node can be obtained:

[0080]

[0081] For actual large power grid operation and dispatching, the impact of changes in active power injection at the balancing node on the active power flow of branches must be taken into account; therefore, a sharing factor is introduced:

[0082]

[0083] The quasi-steady-state active power sensitivity considering the equilibrium node is obtained as follows:

[0084]

[0085] As can be seen from the above derivation process and results, when the influence of reactive power and node voltage is ignored, the sensitivity of branch active power flow to node active power injection is a constant determined by the network structure parameters and is independent of the specific node injection.

[0086] Therefore, the thermal stability constraint of the branch can be further expressed as follows:

[0087]

[0088] make, Then we get:

[0089]

[0090] The above equation describes the Ω corresponding to the thermal stability constraint of branch l. THSR (h) Local boundary, considering the definition of thermal stability safety region, then:

[0091]

[0092] Principal component analysis (PCA) was used to evaluate the overall sensitivity of the generating units under overload conditions. PCA is a commonly used dimensionality reduction statistical analysis method. Through orthogonal transformation, it converts the original random vectors with correlated components into new random vectors with uncorrelated components. While maintaining the original variable information, a new set of fewer comprehensive indicators is established to replace the original multiple indicators with some correlation. These new comprehensive indicators more centrally reflect the information of the original indicators and are uncorrelated with each other, making it an effective method to solve the overlap problem. The overall sensitivity evaluation of the generating units was calculated based on PCA. Since the indicators to be calculated are all sensitivity indicators, there are no differences in dimensions or orders of magnitude; therefore, data normalization is not required during the analysis. Before ranking the unit sensitivity, the units must be classified. First, the weight of the overload of each overload branch in the total overload is calculated. Then, the algebraic sum of the product of the group's sensitivity to each overload branch and its corresponding weight is calculated to obtain the unit's overall sensitivity to the overload condition. Units with positive overall sensitivity are classified as reduced-output units, while those with negative overall sensitivity are classified as increased-output units. After determining the unit classification, the overall sensitivity index for the two types of units is calculated. The specific analysis steps are as follows:

[0093] 1) Constructing the sensitivity matrix Where n represents the number of generating units and m represents the number of overloaded branches in the cross section.

[0094] 2) Let α be the weight coefficient corresponding to each of the m indicators. l , representing the weight corresponding to the overload branch l. The weight coefficients are assigned to the sensitivity matrix to obtain...

[0095]

[0096] 3) Calculate the covariance matrix of matrix Z, and find its characteristic equation. Calculate the m eigenvalues ​​λ1≥λ2≥λ3≥…≥λ m ≥0.

[0097] 4) Calculate the variance contribution rate and cumulative variance contribution rate of the principal components, determine the top c principal components that can comprehensively represent the m indicators, and obtain the corresponding unit eigenvector e. l , and obtain the l-th principal component evaluation value of the i-th unit;

[0098] 5) The variance contribution rate of each principal component is used as the weight. The larger the weight, the more information the principal component reflects, and the comprehensive evaluation value of each unit is obtained.

[0099] Finally, based on the comprehensive evaluation value, the dominant factors were selected, and the pre-selected key nodes together formed the thermal stability safety domain, thus initially constructing the parameter space.

[0100] 2. Construction of a backup call safety zone

[0101] Assuming the system has m branches, the boundary of the thermally stable safety domain based on the critical node space can be expressed as:

[0102]

[0103] Among them, P i Represents the active power injection at node i; α l,i c represents the hyperplane coefficient of the safety domain boundary of node i with respect to branch l; l denoted by , where na represents the influence coefficient of non-critical nodes on branch l; and na is the dimension of the critical node space.

[0104] The safety region is represented by a set of linear inequality constraints, as follows:

[0105]

[0106] By placing the variable to be eliminated on the left side of the inequality and the remaining variable and parameter on the right side, (15) can be transformed into the following new form:

[0107]

[0108] Finally, based on the Fourier-Motzkin elimination method, the new expression is obtained as follows:

[0109]

[0110] It is understandable that the safe interval under the critical node can be obtained after a finite number of transformations.

Claims

1. A method for security verification of auxiliary services based on static security domains, characterized in that, Includes the following steps: Step 1: Obtain the generator operating status based on the topology and parameters of the specified power system, as well as the upper and lower limits of the active power output of the system nodes; Step 2: Establish a power system ancillary service security model based on the generator operating status; Step 3: Verify the power system ancillary service security model offline. If the conditions are met, output the standby thermal stability security domain; otherwise, return to step 2. Wherein: The offline verification process for the power system ancillary service security model includes the following steps: Based on the DC power flow in the power system topology, the thermal stability security domain of the hyperplane is constructed according to the following formula: ； in: For hyperplane coefficients, Inject values ​​for node power. For those with branch roads, For other constraints; Principal component analysis is used to reduce the dimensionality of key nodes in the thermal stability safe region of the hyperplane to obtain a visualized thermal stability safe region. The backup thermal stability safety region is obtained by calculating the visualized thermal stability safety region using the Fourier-Motzkin elimination method.

2. The auxiliary service security verification method based on static security domains according to claim 1, characterized in that, Step 3, the process of constructing the thermally stable safe region of the hyperplane, includes the following steps: The power system ancillary service security model constructs a thermally stable security domain through active power injection at nodes of branches: ； Depend on As can be seen from the definition, the key to solving the thermal stability security domain lies in establishing the mapping relationship between the active power injection at nodes and the active power flow in branches; The thermal stability safety domain introduces the following allocation coefficients for active power injection at the balancing node: ； in: For allocation coefficients, Power injection for node i; The sensitivity model of the balancing node is obtained based on the active power injection of the balancing node: ； in: For allocation coefficients, To correct the hyperplane coefficient, The corrected hyperplane coefficient; The thermal stability constraint of the branch in the sensitivity model is determined by the following formula: ； in: For allocation coefficients, Power injection for node k, This represents the maximum power value of branch l; make, Then we get: ； The thermal stability constraint corresponding to branch l in the above equation Thermally stable safe region of local boundary hyperplane.

3. The auxiliary service security verification method based on static security domains according to claim 1, characterized in that, In step 3, principal component analysis is used to reduce the dimensionality of the key nodes of the thermal stability safe region of the hyperplane to obtain a visualized thermal stability safe region. This process includes the following steps: Classify and sort all generating units in the power system to construct a dominant generating unit set; The dominant unit set establishes a comprehensive sensitivity model according to the following formula; X=（ ） n×m ； Where: n represents the number of generating units, and m represents the number of overload branches in the cross section. The weight of each overloaded branch in the total overload is calculated using the following formula; ； Where: Let the weight coefficients corresponding to the m indicators be respectively. , representing the weight corresponding to the overloaded branch; The algebraic sum of the products of the computer group's sensitivity to each overload branch and its corresponding weight yields the set of the unit's overall sensitivity to this overload situation, i.e.: ； Calculate the covariance matrix of the comprehensive sensitivity set Z, and obtain m eigenvalues ​​by finding the characteristic equation of this matrix. ; Calculate the variance contribution rate and cumulative variance contribution rate of the principal components, determine the top c principal components that can comprehensively represent m indicators, and obtain the corresponding unit eigenvectors. , and obtain the l-th principal component evaluation value of the i-th unit; The comprehensive evaluation value of each unit is obtained by using the variance contribution rate of each principal component as the weight.

4. The auxiliary service security verification method based on static security domains according to claim 1, characterized in that, Step 3, which involves calculating the backup thermal stability safety region using the Fourier-Motzkin elimination method, includes the following steps: The visual thermal stability safety domain boundary of the critical node space is established using the following formula: ； Among them, P i This represents the active power injection at node i; c represents the hyperplane coefficient of the safety domain boundary of node i with respect to branch l; l denoted by , where na represents the influence coefficient of non-critical nodes on branch l; na is the dimension of the critical node space. The alternative thermal stability safety region is obtained by calculating the visualized thermal stability safety region based on the Fourier-Motzkin elimination method, namely: ； in: Inject values ​​for node power. and These represent different hyperplane coefficients. and These are different hyperplane constants.

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