A substation reconstruction and expansion commissioning boundary determination method and system

Abstract

This invention discloses a method and system for determining the commissioning boundary during substation expansion and renovation. The method includes: acquiring the entire substation configuration file; mapping intelligent devices and virtual loops to nodes and directed edges in a directed graph; calculating the sub-cyclic redundancy check (CRC) code corresponding to each directed edge; dividing nodes into expansion domains, directly associated domains, and indirectly associated domains based on configuration change identifiers and topological relationships; performing sub-CRC comparison and constructing a state transition matrix based on the dataset priority attributes; starting with high-risk seed nodes, calculating the attenuation probability of configuration change risk propagating outwards based on the state transition matrix; iteratively adding nodes with probabilities greater than the safety confidence threshold to the target test boundary set until convergence. This invention integrates underlying communication semantics with graph theory probabilistic inference to define the minimum safety test boundary, avoiding unnecessary shutdowns of primary equipment on-site, and improving the safety and efficiency of power grid commissioning.

Description

Technical Field

[0001] This invention relates to the field of substation relay protection and secondary system commissioning technology, and in particular to a method and system for determining the commissioning boundary during substation renovation and expansion. Background Technology

[0002] With the widespread application of smart substations, secondary systems built based on the IEC 61850 standard are gradually replacing traditional hard-wiring methods. Substations increasingly utilize virtual loops based on network communication (such as GOOSE messages and sampled value SV messages) to achieve information exchange between protection, measurement and control, and automation functions. Correspondingly, the Substation Configuration Description (SCD) file has become the core data carrier describing all intelligent electronic devices (IEDs) in the substation and their communication relationships.

[0003] During the renovation and expansion of substations, the need to connect newly added or upgraded equipment to the existing system inevitably leads to adjustments and reconfigurations of virtual loop configurations. To ensure system operational safety, commissioning and transmission tests must be conducted on the affected equipment to determine reasonable commissioning boundary ranges.

[0004] In existing technologies, determining the debugging boundary typically relies on two methods: one is to use existing SCD file parsing software to perform overall or device-level version text comparison; the other is to rely on engineering experience and combine static drawings for manual topology tracing. However, both existing auxiliary software and manual methods have deep-seated technical limitations.

[0005] First, existing file comparison methods based on automated software mainly focus on extracting differences from XML text nodes, resulting in a coarse-grained comparison that struggles to characterize fine-grained variations in virtual loops at the underlying communication semantic level. When a local modification occurs in an SCD file, existing tools often fail to accurately pinpoint the specific affected underlying communication link through text differences, leading to a lack of precise data support for defining the debugging scope.

[0006] Secondly, complex topological relationships exist between virtual circuits within the substation secondary system, and configuration changes propagate implicitly through multi-level connections. Existing topology retrieval technologies are mostly limited to static connectivity queries, lacking quantitative analysis and probabilistic extrapolation methods for multi-level relationships. This prevents the system from accurately assessing the true impact of changes on indirectly related devices, and further hinders the identification of hidden risks where unexpected changes have occurred in actual communication links even though configuration files have not been issued.

[0007] Due to the limitations of the aforementioned technical methods, in situations where the risk diffusion boundary cannot be accurately located, on-site commissioning typically relies on conservative judgments based on experience, generally adopting a strategy of expanding the scope rather than overlooking anything. This approach includes a large number of operating devices unrelated to the renovation and expansion within the testing scope, not only causing unnecessary equipment power outages and operational risks but also significantly increasing commissioning costs and timelines.

[0008] Therefore, how to achieve refined analysis of virtual loop connection relationships based on configuration files during the renovation and expansion of substations, and on this basis, quantitatively extrapolate and evaluate the impact range of configuration changes, so as to accurately determine the minimum commissioning boundary, has become a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0009] To address the technical problems in existing technologies, such as coarse-grained SCD file parsing and comparison, inability to characterize the semantic variations of underlying communication in virtual loops, and lack of quantitative deduction methods for configuration change-related risks, leading to excessive expansion of the commissioning scope and increased on-site power outages and operational risks, this invention provides a method and system for determining the commissioning boundary during substation renovation and expansion. The method includes: acquiring the entire substation configuration file; mapping intelligent devices and virtual loops to nodes and directed edges in a directed graph; calculating the subcyclic redundancy check (CDR) code corresponding to each directed edge; dividing nodes into expansion domains, directly associated domains, and indirectly associated domains based on configuration change identifiers and topological relationships; performing CDR code comparison and constructing a state transition matrix based on dataset priority attributes; starting from a high-risk seed node, calculating the attenuation probability of configuration change risk propagating outwards based on the state transition matrix; iteratively adding nodes with probabilities greater than the safety confidence threshold to the target test boundary set until convergence. This invention integrates underlying communication semantics with graph theory probabilistic deduction to define the minimum safety test boundary, avoiding unnecessary shutdowns of primary equipment on-site and improving the safety and efficiency of power grid commissioning.

[0010] The present invention adopts the following technical solution.

[0011] Preferably, a method for determining the commissioning boundary during substation renovation and expansion includes: Obtain the substation configuration file before and after the substation renovation and expansion, and extract intelligent electronic devices, virtual loop connection relationships, and dataset priority attributes; map the intelligent electronic devices as nodes in a directed graph structure, and map the virtual loop connection relationships as directed edges; calculate the subcyclic redundancy check code corresponding to each directed edge based on preset feature extraction rules. Based on the node configuration change identifier and the adjacency topology of the directed graph structure, the nodes are divided into an extended domain node set, a directly associated domain node set, and an indirectly associated domain node set. The expanded domain node set is assigned to the target test boundary set; if the directed edge between the directly associated domain node set and the expanded domain node set has a new or changed subcyclic redundancy check code after the expansion, the corresponding node is assigned to the target test boundary set. Perform a consistency comparison of the subcyclic redundancy check codes before and after the modification and expansion on the directed edges in the indirect association domain node set that are connected to the target test boundary set, and construct a state transition matrix in combination with the priority attribute of the dataset; Based on the state transition matrix, the attenuation probability of the nodes in the target test boundary set propagating to the outer nodes is calculated, and the nodes with attenuation probability greater than the preset safety confidence threshold are included in the target test boundary set until the iteration converges, thus obtaining the substation renovation and expansion commissioning boundary.

[0012] Preferably, based on preset feature extraction rules, the sub-cyclic redundancy check code corresponding to each directed edge is calculated, including: The entire site configuration file is parsed to extract the communication control block parameters, dataset configuration information, and receiving virtual terminal configuration information between the sending node and the receiving node corresponding to each directed edge; wherein, the communication control block parameters include GOOSE control block parameters and / or SV control block parameters; The communication control block parameters, the dataset configuration information, and the communication parameters contained in the receiving virtual terminal configuration information are concatenated into a data string according to a preset format; The data string is input into the Cyclic Redundancy Check (CRC) algorithm model to generate a sub-CRC code that represents the state of the directed edge communication link.

[0013] Preferably, based on the node configuration change identifier and the adjacency topology of the directed graph structure, the nodes are divided into an extended domain node set, a directly associated domain node set, and an indirectly associated domain node set, including: Based on the node configuration change identifier, identify target nodes in the renovation and expansion project that have new or changed states, and assign the target nodes to the expansion domain node set; In the directed graph structure, a single-hop topological traversal is performed starting from the extended domain node set to extract the first adjacent node that has a direct directed edge connected to the extended domain node set. The first adjacent node that needs to reissue the configuration file is then included in the directly associated domain node set. Starting from the set of directly associated domain nodes, continue topological traversal, extract the second adjacent nodes that have a direct directed edge connected to the set of directly associated domain nodes, and add the second adjacent nodes that do not require re-issuing configuration files to the set of indirectly associated domain nodes.

[0014] Preferably, the consistency comparison of subcyclic redundancy check codes before and after modification is performed on the directed edges connected to the target test boundary set in the indirect association domain node set, and a state transition matrix is ​​constructed in conjunction with the priority attribute of the dataset, including: The nodes within the target test boundary set are designated as high-risk seed nodes; Extract the target directed edges between the high-risk seed nodes and the nodes within the indirect association domain node set, compare the subcyclic redundancy check codes before and after the expansion, and generate the basic risk transfer weights of the corresponding target directed edges based on the consistency comparison results. The dataset priority attribute bound to the target directed edge is parsed, and the dataset priority attribute is converted into a corresponding priority level coefficient according to a preset mapping rule; The basic risk transfer weight and the priority level coefficient are weighted and multiplied to obtain the comprehensive risk weight of the corresponding target directed edge. The comprehensive risk weights pointing outward from the same node are summed, and the normalized state transition matrix is ​​constructed based on the ratio of each comprehensive risk weight of the node to the summation value.

[0015] Preferably, the process of obtaining the commissioning boundary for substation renovation and expansion includes: Construct a global node risk probability vector, and set the initial probability value of the high-risk seed node in the global node risk probability vector to 1, and set the probability value of the remaining nodes to 0; The global node risk probability vector is iteratively multiplied with the state transition matrix, and a preset topology decay factor is introduced to update the global node risk probability vector after each iteration. Calculate the difference between the global node risk probability vectors of two adjacent iterations. If the difference is less than the convergence tolerance, the iteration is determined to be converged, and the final global node risk probability vector is obtained. Extract the attenuation probabilities of each item corresponding to the set of indirectly associated domain nodes in the final global node risk probability vector, and incorporate the nodes that are greater than the preset safety confidence threshold into the target test boundary set to obtain the substation renovation and expansion commissioning boundary.

[0016] Preferably, after obtaining the substation renovation and expansion commissioning boundaries, the process also includes test plan generation and automated testing steps: The communication parameters corresponding to each node in the target test boundary set are extracted, and the communication parameters are converted into standard test model signals based on the preset general intermediate database and dictionary mapping rules. Based on the node attributes of the extended domain node set, the directly associated domain node set, or the indirectly associated domain node set to which each node belongs within the target test boundary set, the corresponding test sub-item is retrieved from the preset standardized test template library. The retrieved test sub-items and the standard test model signals are assembled in a time sequence to generate instantiated test case scripts and debugging outlines; The instantiated test case scripts are automatically sent to the target intelligent electronic device or field test equipment via the electrical Ethernet interface, based on the manufacturing message specification communication protocol, to execute automated closed-loop testing and generate test reports.

[0017] Preferably, before automatically sending the instantiated test case script to the target intelligent electronic device or field testing equipment, an offline virtual simulation verification step is also included: Extract the instance configuration files of each node within the target test boundary set, and construct a digital twin model of the substation that is equivalent to the physical topology on site in the preset virtualization engine; The instantiated test case script is converted into a virtual stimulus signal and injected into the virtual transmission channel of the corresponding sending node in the digital twin model in a timely manner. Traverse and listen to the logic triggering state of the virtual receiving terminal of the corresponding receiving terminal node in the digital twin model, and compare it with the preset expected action logic for consistency. If the detected logical trigger state does not match the preset expected action logic, a static configuration vulnerability alarm is generated, and the issuance command of the instantiated test case script is intercepted; if they match, the issuance command is allowed and automated closed-loop testing is executed.

[0018] Secondly, a substation renovation and expansion commissioning boundary determination system, operating the substation renovation and expansion commissioning boundary determination method as described in the first aspect, includes: The data parsing and modeling module is used to obtain the full station configuration file before and after the substation renovation and expansion, extract intelligent electronic devices, virtual loop connection relationships and dataset priority attributes; map the intelligent electronic devices as nodes in a directed graph structure, and map the virtual loop connection relationships as directed edges; and calculate the subcyclic redundancy check code corresponding to each directed edge based on preset feature extraction rules. The topology domain partitioning module is used to partition the nodes into an extended domain node set, a directly associated domain node set, and an indirectly associated domain node set based on the node configuration change identifier and the adjacency topology relationship of the directed graph structure. The deterministic boundary locking module is used to assign the expanded domain node set to the target test boundary set; if the directed edge between the directly associated domain node set and the expanded domain node set has a new or changed subcyclic redundancy check code after the expansion, then the corresponding node is assigned to the target test boundary set. The state transition construction module is used to perform a consistency comparison of the subcyclic redundancy check codes before and after the modification and expansion of the directed edges in the indirect association domain node set that are connected to the target test boundary set, and to construct a state transition matrix in combination with the priority attribute of the dataset. The risk simulation and convergence module is used to calculate the attenuation probability of the propagation from the nodes in the target test boundary set to the peripheral nodes based on the state transition matrix, and to include the nodes with attenuation probability greater than the preset safety confidence threshold into the target test boundary set until iterative convergence is achieved, thereby obtaining the substation renovation and expansion commissioning boundary.

[0019] Thirdly, an electronic device includes: Memory and processor; The memory is used to store computer programs; The processor is used to execute the computer program to implement the steps of the substation renovation and expansion commissioning boundary determination method as described in the first aspect.

[0020] In a second aspect, a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the substation renovation and expansion commissioning boundary determination method as described in the first aspect.

[0021] The beneficial effects of this invention are compared with those of the prior art: 1. This invention integrates the underlying configuration state of virtual circuits with graph theory topology. By introducing a state transition matrix and a decay probability convergence algorithm, the propagation process of configuration change risks is rigorously quantified mathematically. This method can accurately converge to the minimum safe test boundary while ensuring that no potential logical vulnerabilities are overlooked, fundamentally avoiding unnecessary primary equipment shutdowns caused by on-site generalization isolation, and greatly reducing the scope of power outages and debugging costs.

[0022] 2. To address the challenges of joint debugging caused by differing interpretations of the IEC 61850 standard by field equipment manufacturers, this invention achieves standardization of heterogeneous underlying parameters from multiple manufacturers by constructing a universal intermediate database and dictionary mapping rules. Based on boundary judgment results, the system can automatically retrieve configuration templates and instantiate test outlines and scripts, directly issuing them to the field for execution via standard communication protocols. This eliminates the heavy reliance on manual experience in test template configuration and achieves seamless integration from boundary judgment to automated closed-loop testing.

[0023] 3. This invention introduces an offline virtual simulation verification mechanism before issuing test commands to on-site physical equipment. By extracting instance configuration files and constructing a digital twin model equivalent to the on-site physical topology, automatically generated test cases are transformed into virtual excitation signals for timing injection and logic monitoring. This mechanism can expose and intercept deep-seated configuration blind spots and static logic errors in a pure software environment, adding a digital firewall to on-site operations and effectively ensuring the safe and stable operation of the substation. Attached Figure Description

[0024] Figure 1 This is an overall flowchart of a method for determining the commissioning boundary during substation renovation and expansion provided by the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of this invention. The embodiments described in this application are merely some embodiments of this invention, and not all embodiments. Based on the spirit of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this invention.

[0026] Example 1: like Figure 1 As shown, this invention provides a method for determining the commissioning boundary during substation renovation and expansion, including: S1: Obtain the full station configuration file before and after the substation renovation and expansion, and extract the intelligent electronic devices, virtual loop connection relationships, and dataset priority attributes; map the intelligent electronic devices as nodes in a directed graph structure, and map the virtual loop connection relationships as directed edges; calculate the subcyclic redundancy check code corresponding to each directed edge based on preset feature extraction rules.

[0027] In practice, the specific execution logic and implementation details of S1 are as follows: (1) Parsing the entire site configuration file and extracting multidimensional features First, obtain the substation configuration file (SCD) before the substation renovation and expansion (original system operating status) and after the renovation and expansion (design plan planning status). The SCD file is an XML format file built based on the IEC61850 standard, which contains the instantiation configuration information of all equipment in the substation.

[0028] The underlying XML parsing engine is used to parse the SCD files before and after the above modifications and expansions, extracting the following three types of core information: Information on intelligent electronic devices (IEDs): including physical device nodes such as protection devices, measurement and control devices, merging units, and intelligent terminals.

[0029] Virtual loop connection relationship: Extract the network communication link association relationship based on GOOSE (substation events for general objects) and SV (sampled value) protocols.

[0030] Dataset priority attribute: Extract the service attributes of the datasets transmitted in the virtual loops mentioned above. For example, trip control data sets have the highest priority, followed by protection sampling data sets, and then general status monitoring data sets. The dataset priority attribute is determined based on a preset mapping rule or according to the IEC61850 service type.

[0031] (2) Construct a directed graph model of the substation communication topology To enable computer algorithms to quantitatively analyze the complex communication networks of substations, the physical configuration files are transformed into mathematical graph theory models. Specifically, a directed graph model is constructed. ,in: The set V represents the nodes in the directed graph structure, which maps each extracted smart electronic device to an independent node.

[0032] Set E represents the directed edges in the directed graph structure, that is, mapping the extracted virtual loop connections to directed edges between nodes. Since the virtual loops in the substation have clearly defined sending and receiving ends, the connection relationship is represented as directed edges with definite directions.

[0033] (3) Calculate the sub-cyclic redundancy check code (sub-CRC) based on the underlying communication parameters. Traditional methods often rely on overall hash comparison of the entire SCD file or a single IED node, resulting in widespread discrepancy alerts even from a single, insignificant text modification. To address this issue, this embodiment proposes a sub-cyclic redundancy check (CRC) code calculation mechanism based on the granularity of directed edges (single communication links). Specific steps include: Precise parameter extraction: For each directed edge in model G, the communication control block parameters (including GOOSE control block parameters and / or SV control block parameters, such as MAC address, APPID, VLANID, etc.), dataset configuration information (FCDA member configuration in DataSet), and receiver virtual terminal configuration information (pin binding relationships in ExtRef) between the sending and receiving nodes are extracted. During parameter extraction, only key configuration fields affecting the semantic consistency of virtual loop communication are selected, and non-functional fields are ignored or normalized.

[0034] Formatted concatenation: The communication parameters extracted above, the data set configuration information, and the communication parameters contained in the receiving virtual terminal configuration information are concatenated into a standardized data string according to a pre-defined sorting and delimiter format.

[0035] Sub-CRC generation: The concatenated data string is input into a cyclic redundancy check algorithm model, such as CRC-32, to generate a unique check code. The sub-cyclic redundancy check code remains unchanged while maintaining the semantic consistency of virtual loop communication.

[0036] The generated sub-CRC can uniquely and accurately represent the underlying communication link status of a specific virtual loop. If, during the upgrade and expansion process, only the text description of an IED is modified without substantially changing the communication control block or virtual terminal binding relationship of the directed edge, the sub-CRC of that directed edge remains unchanged. This provides reliable data support for subsequently accurately eliminating false changes and locking down the truly affected boundaries. Finally, a sub-CRC mapping relationship indexed by directed edges is generated to represent the connection status of virtual loops across the entire site.

[0037] S2: Based on the node configuration change identifier and the adjacency topology of the directed graph structure, the nodes are divided into an extended domain node set, a directly associated domain node set, and an indirectly associated domain node set.

[0038] After establishing the directed graph model of the entire substation, to avoid the subsequent risk estimation algorithm performing an unordered, exponential, blind search across the entire network, this step employs a topological traversal addressing algorithm from graph theory (such as breadth-first search) to reduce the dimensionality of the physically chaotic substation network and structure it into three distinct risk topology domains. The specific partitioning logic and execution process are as follows: (1) Lock the set of nodes in the extended domain First, read the node configuration change identifiers in the entire site's SCD configuration file. For example, by comparing the configuration versions before and after the expansion, identify IED nodes with change tags such as "Add" and "Modify".

[0039] Any target nodes that are newly added or have changed status during the renovation and expansion project will be uniformly included in the expansion domain node set. Target nodes include, for example, newly added bay equipment and replaced or upgraded old relay protection devices. This set is the core of this renovation and expansion project and also the physical source of subsequent configuration change risks radiating to the surrounding network.

[0040] (2) Set of directly associated domain nodes in single-hop addressing After identifying the source of risk, in the directed graph structure In this process, a single-hop topological traversal is performed, starting with the set of nodes in the extended domain.

[0041] Along the directed edges, extract the first adjacent node of all nodes that have a direct directed edge connected to the set of nodes in the extended domain, i.e., the nodes that have a direct GOOSE / SV virtual loop send / receive relationship.

[0042] Next, a secondary filtering process is performed using the comparison results of on-site engineering business rules and virtual circuit CRC: among these first adjacent nodes, nodes whose internal virtual terminal subscription relationships have undergone substantial changes due to the renovation and expansion project, thus requiring a re-deployment of configuration files, are identified. Examples include bus differential protection devices that need to subscribe to trip messages sent by newly added or expanded equipment. These first adjacent nodes that require re-configuration are assigned to the directly associated domain node set. Since these nodes have undergone explicit configuration refactoring, their state changes are knowable and must be measured.

[0043] (3) Extrapolate the set of indirect related domain nodes outwards Traditional manual investigations often stop at direct associations, easily overlooking deeper hidden dangers. To eliminate blind spots, we continue to traverse the topology of the outer network, starting from the set of directly associated domain nodes.

[0044] Extract the second adjacent node of the set of directly related domain nodes that has a directly connected directed edge.

[0045] During this process, node mutual exclusion and deduplication rules are executed: if a node has already been assigned to a higher-priority directly associated domain during a single-hop traversal, the node is ignored to ensure that the same node is not assigned to a domain repeatedly. Subsequently, for nodes that have not yet been assigned to an expanded domain or a directly associated domain, based on the CRC consistency of the virtual loop between the node and its upstream node, nodes that have not undergone explicit configuration changes (i.e., do not require re-issuance of configuration files) but have potential impact on the propagation path are identified and assigned to the indirectly associated domain node set.

[0046] Although the nodes in this set have not undergone explicit file modifications, they are highly susceptible to the implicit impact of mutations in the underlying messages of the upstream virtual loop. This makes them a hidden risk area that is prone to causing malfunctions and tripping, and is also the core target of the subsequent quantitative deduction algorithm.

[0047] After the above multi-level topology addressing, the remaining nodes in the directed graph model of the entire station that are not included in the above three sets are the safe operating devices that are not logically coupled with this renovation and expansion project. These devices are naturally outside the target test boundary set, thus forming a hierarchical node set based on the dual constraints of topology and communication semantics. At the algorithm level, this achieves test exemption and power outage exemption, avoiding the equipment shutdown caused by generalized isolation.

[0048] S3: Incorporate the expanded domain node set into the target test boundary set; if the directed edge between the directly associated domain node set and the expanded domain node set has a newly added or changed subcyclic redundancy check code after the expansion, then incorporate the corresponding node into the target test boundary set.

[0049] The purpose of this step is to first identify the core physical boundaries with deterministic risks in a complex network, and then use them as seed nodes for the subsequent outward radiation of hidden risks.

[0050] (1) Directly lock the extended domain The expanded domain node set includes devices that are newly added or whose hardware and main logic have been replaced in this project. Since their internal logic and external interfaces are all new, they are unconditionally included in the target test boundary set.

[0051] (2) Precise filtering based on direct association domain of sub-CRC For directly related domain nodes, instead of blindly including them all in the test boundary, the sub-CRC calculated in S1 is introduced for precise discrimination: Extract the directed edges between directly related domain nodes and extended domain nodes.

[0052] Perform a consistency comparison on the sub-CRC corresponding to the directed edges before and after the renovation and expansion. When the sub-CRC does not exist or changes, it is determined to be a newly added state or a changed state, respectively. If, in the modified configuration file, the sub-CRC of a directed edge shows a new or changed state—for example, if an older device adds a GOOSE subscription link to accommodate a new device, or modifies the channel mapping of the receiving virtual terminal—it indicates that the older device has experienced a substantial communication disruption. Since the directed edge represents the state of the virtual loop communication link between nodes, a change in its sub-CRC signifies a change in communication semantics, thereby affecting the node's control or protection logic. Only then are the directly associated domain nodes whose corresponding sub-CRC shows a new or changed state formally included in the target test boundary set.

[0053] If the CRC of a directly associated domain node remains unchanged, it will not be included in the core test boundary for the time being, but will be left for subsequent algorithm evaluation.

[0054] S4: Perform a consistency comparison of the subcyclic redundancy check codes before and after the modification and expansion on the directed edges in the indirect association domain node set that are connected to the target test boundary set, and construct a state transition matrix in combination with the priority attribute of the dataset.

[0055] The specific construction process includes: (1) Establish high-risk seed nodes Following the above screening process, the nodes included in the target test boundary set have undergone not only physical configuration reconstruction but also substantial changes in underlying communication semantics. These nodes are defined as high-risk seed nodes and will participate in subsequent risk propagation modeling calculations.

[0056] (2) Generate basic risk transfer weights based on sub-CRC comparison Extract the indirect association domains pointed to by high-risk seed nodes, and the target directed edges between nodes within the indirect association domains. Assign basic weights by comparing the sub-CRC consistency of these directed edges before and after the upgrade: If the sub-CRC is inconsistent, i.e. a mutation has occurred, it indicates that the underlying communication link has been tampered with, and an extremely high basic risk transfer weight is assigned, for example, set to 0.9.

[0057] If the sub-CRC is consistent, meaning no mutation has occurred, considering the potential hidden penetration risk brought about by upstream data distortion, its weight is not set to 0, but rather assigned a lower but non-zero basic risk transfer weight, for example, set to 0.1.

[0058] (3) Parse business semantics to generate priority level coefficients The risks of a substation are not only related to whether the data link has changed, but also to the business purpose carried by that link. The priority attribute of the dataset bound to the directed edge of the above target is parsed and converted into coefficients according to a preset mapping rule: If the directed edge transmits a trip control type GOOSE signal, since its malfunction will cause a direct power outage, it is assigned the highest priority coefficient, such as 1.5.

[0059] If the transmitted signal is a fast sampled value SV signal used for protection actions, assign a higher coefficient, such as 1.2.

[0060] If the transmitted signal is a normal status monitoring MMS signal, the risk of false activation is extremely small, so a very low coefficient is assigned, such as 0.5.

[0061] The priority level coefficient is obtained by grading and quantifying the business risk level rather than using a single fixed constant, thereby improving the scalability and adaptability of the mathematical model to different substation business scenarios.

[0062] (4) Obtain the overall transition probability by weighted product The basic risk transfer weights obtained from the above steps are multiplied by the priority coefficients to calculate the comprehensive risk weight of the corresponding target directed edge. Even if the sub-CRC of a link remains unchanged and the basic weight is low, if it is an extremely dangerous tripping link and the priority coefficient is extremely high, the comprehensive risk probability will still increase after multiplying the two, thus ensuring that the algorithm does not miss any high-risk business links.

[0063] (5) Normalize and construct the state transition matrix To meet the mathematical requirements of subsequent probability iteration calculations, it is essential to ensure that the total probability of outward radiation from any node is 1 to achieve normalization. For each node in the graph model, the comprehensive risk weights pointing outward from it are summed. Then, the comprehensive risk weight of each outward pointing from that node is divided by this summation. After this normalization process, the original weight ratios are strictly mapped to state transition probabilities that satisfy probability distribution constraints. Through this proportional conversion, a standard state transition matrix is ​​constructed. This matrix solidifies the current physical modification status of the substation and the operational hazard level into a mathematical model for risk projection.

[0064] S5: Calculate the attenuation probability of the nodes in the target test boundary set propagating to the outer nodes based on the state transition matrix, and include the nodes with attenuation probability greater than the preset safety confidence threshold into the target test boundary set until the iteration converges to obtain the substation renovation and expansion commissioning boundary.

[0065] The specific iteration and convergence process is as follows: (1) Construct a global node risk probability vector First, construct a global node risk probability vector with a dimension equal to the total number of nodes in the directed graph of the entire site. Each element in this vector physically represents the probability of a corresponding node in the global network being affected by a configuration change. This global node risk probability vector characterizes the cumulative risk state of each node in the current iteration, rather than the actual probability of a failure occurring.

[0066] For the high-risk seed nodes identified in S3, they will be placed in The initial probability value is set to an absolute value of 1, representing that this location is a 100% certain risk source of physical reconstruction.

[0067] For all other nodes in the entire network, including indirectly related nodes, their initial probability values ​​are uniformly set to 0. This vector This constitutes the initial distribution state for the algorithm to walk in the graph theory space.

[0068] (2) Introducing the probability deduction and iterative multiplication of the attenuation factor Since the implicit risks of configuration variations are not infinitely propagated, the risk diminishes with each logical operation and forwarding through a device. To align with this physical law, a preset topology attenuation factor is introduced. For example, setting .

[0069] The global node risk probability vector from the previous moment Perform matrix multiplication with the state transition matrix M constructed from S4, and multiply by the aforementioned topological decay factor. Simultaneously, after each calculation, the probability value of the high-risk seed node is forcibly kept at 1 to maintain a constant injection of risk sources, thereby updating the global node risk probability vector for the current iteration round t. .

[0070] (3) Calculate the convergence tolerance and stopping iteration. As the number of iterations *t* increases, the risk probability is continuously diluted and decayed within the network. The absolute difference between the global node risk probability vectors of two adjacent iterations is calculated. Vector norms (such as L∞ norm or L1 norm) are preferably used as convergence criteria.

[0071] When the largest element in the difference value is less than the system's preset convergence tolerance, such as a minimum constant... When the risk propagation in the network has reached a steady state, the algorithm iteration officially converges. The output vector at this point is the final global node risk probability vector. .

[0072] (4) Final boundary locking based on security confidence threshold Finally, extract the final vector. The vector contains the decay probability values ​​of each element in the set of indirectly associated domain nodes. Since each element in this vector precisely maps to the risk probability of a specific node, the extracted element values ​​represent the final decay probability of the configuration change risk propagating to the corresponding indirectly associated domain nodes.

[0073] These probability values ​​are compared with a preset safety confidence threshold, which characterizes the maximum acceptable risk propagation limit for a node. The threshold ranges from (0,1) and can be adaptively configured based on the substation's operational safety level, such as 0.15. If the final attenuation probability of a node in an indirectly related domain exceeds this preset safety confidence threshold, it indicates that although the node has not undergone explicit configuration file modification, its risk of malfunction has exceeded the safety limit due to upstream spillover effects. These high-risk nodes are then incorporated into the target test boundary set.

[0074] At this point, the final commissioning boundaries for the substation renovation and expansion were determined.

[0075] This step formalizes the risk propagation process into an iteratively solvable steady-state problem by introducing topological decay constraints and a convergence determination mechanism. While ensuring full coverage of high-risk nodes, it effectively suppresses the excessive diffusion of low-risk nodes and achieves accurate convergence of the debugging boundary.

[0076] S6: After obtaining the substation renovation and expansion commissioning boundary, the process also includes test scheme generation and automated testing steps: extracting the communication parameters corresponding to each node within the target test boundary set; converting the communication parameters into standard test model signals based on a preset general intermediate database and dictionary mapping rules; retrieving corresponding test sub-items from a preset standardized test template library according to the node attributes of the expansion domain node set, the directly associated domain node set, or the indirectly associated domain node set to which each node within the target test boundary set belongs; assembling the retrieved test sub-items and the standard test model signals in a time-series manner to generate instantiated test case scripts and a commissioning outline; automatically sending the instantiated test case scripts to the target intelligent electronic device or field test equipment via an Ethernet interface based on the manufacturing message specification communication protocol, executing automated closed-loop testing, and generating a test report.

[0077] This step addresses the industry pain points of inconsistent implementation of equipment standards from multiple manufacturers and the reliance on manual configuration of test templates. Its specific execution logic is as follows: (1) Communication parameter extraction and dictionary mapping across vendor barriers First, the underlying communication parameters corresponding to each intelligent electronic device (IED) node within the target test boundary set are extracted, such as virtual terminal references and data attributes. Due to differences in the interpretation of the IEC 61850 standard among various equipment manufacturers, the naming and format of the underlying parameters are often inconsistent. To achieve unified modeling across manufacturers, a universal intermediate database is constructed, and bidirectional dictionary mapping rules are defined between the original communication parameters of the devices and the standard test model signals. These mapping rules include at least field matching rules, type conversion rules, and semantic alignment rules. Through these dictionary mapping rules, heterogeneous underlying communication parameters are uniformly converted into standard test model signals, thereby forming a unified signal expression system at the test layer that is independent of specific devices.

[0078] (2) Adaptive template retrieval based on domain attributes For devices within the test boundary, the topology domain partitioning results from step S2 were reused, and test sub-items were retrieved from the preset standardized test template library based on the domain attributes to which each node belongs: For each node in the extended domain node set, retrieve all test sub-projects, including individual debugging, logic transmission, and group testing.

[0079] For nodes belonging to the directly associated domain node set, i.e., old devices whose configurations have been passively modified, the focus is on retrieving the send / receive verification and local logic verification sub-items involving the modified links.

[0080] For nodes belonging to the set of indirectly related domain nodes, i.e. devices whose configurations have not been modified but have potential risks, only the non-intrusive message timing and status monitoring sub-item is retrieved to prevent excessive intrusive testing from causing malfunctions in the operating equipment.

[0081] This step introduces topological domain attribute constraints to achieve adaptive matching between test intensity and equipment risk level, effectively avoiding over-testing or under-testing issues caused by a unified testing strategy.

[0082] (3) Timing assembly and instantiation of test scripts The retrieved test sub-items are automatically assembled with the previously generated standard test model signals. Based on the secondary loop topology dependencies and signal triggering logic, a directed timing dependency graph is constructed between test actions. On the basis of the timing dependency graph, topology sorting is performed to generate a test execution sequence that satisfies logical constraints, thereby realizing the timing orchestration of test steps.

[0083] After assembly, the system automatically outputs: first, instantiated test case scripts, such as automatically executed code in XML or Python format, for direct execution by the on-site testing instrument; and second, a standardized debugging outline document for on-site personnel to confirm and sign.

[0084] (4) One-click closed-loop test driven by MMS protocol After the test script is generated, the instantiated test case script is automatically sent to the target IED or the field portable relay protection tester via the main control unit's Ethernet interface, based on the Manufacturing Message Specification (MMS) communication protocol.

[0085] After receiving the command, the on-site testing equipment automatically applies voltage and current excitation, or sends a GOOSE control message, to perform automated closed-loop testing. Upon completion of the test, the system automatically collects the device's action feedback messages and generates a detailed test report.

[0086] S7: Before automatically sending the instantiated test case script to the target intelligent electronic device or field test device, perform an offline virtual simulation verification step.

[0087] The specific implementation process is as follows: (1) Constructing a digital twin model of a substation Extract instance configuration files, such as CID or ICD files, for each node within the target test boundary set. Based on the logical nodes, data objects, data attributes, and internal binding relationships contained in the instance configuration files, perform parsing and mapping in a preset virtualization engine to construct a digital twin model of the substation equivalent to the physical topology on site.

[0088] (2) Timing injection of virtual excitation signal In a purely software-based virtual environment, the instantiated test case scripts generated by S6 are parsed and transformed into corresponding virtual stimulus signals, such as digitized virtual GOOSE control block trip messages or virtual SV sampled value messages. Based on the timestamps and execution order set in the test scripts, these virtual stimulus signals are precisely injected into the virtual transmission channels of the corresponding transmitting nodes in the digital twin model.

[0089] (3) Logic trigger listening and consistency comparison After injecting the excitation signal, the logic triggering state of the virtual receiving terminal of the corresponding receiving node in the digital twin model is traversed and monitored, for example, the output response of the external input pin and the internal protection algorithm is monitored in real time. At the same time, the expected action logic preset based on the substation standardized design specifications is retrieved, preferably expressed in the form of state transition constraints or logic truth mapping table, and the actual logic triggering state detected is compared with the preset expected action logic for consistency.

[0090] (4) Command interception and release control If the comparison results show that the detected logical trigger state does not match the expected action logic, such as an unexpected virtual trip, failure to operate, or signal misalignment, then it is determined that there is a deep-seated static logic error in the current configuration file or test script. In this case, a static configuration vulnerability alarm is immediately generated, and the physical delivery command of the instantiated test case script is forcibly intercepted at the software control layer, preventing its propagation to the field equipment. If the comparison results match completely, the delivery command is allowed, permitting the script to be delivered to the actual field equipment via the electrical Ethernet interface and executing the final automated closed-loop test.

[0091] Example 2: A substation renovation and expansion commissioning boundary determination system, operating the substation renovation and expansion commissioning boundary determination method as described in Example 1, includes: The data parsing and modeling module is used to obtain the full station configuration file before and after the substation renovation and expansion, extract intelligent electronic devices, virtual loop connection relationships and dataset priority attributes; map the intelligent electronic devices as nodes in a directed graph structure, and map the virtual loop connection relationships as directed edges; and calculate the subcyclic redundancy check code corresponding to each directed edge based on preset feature extraction rules. The topology domain partitioning module is used to partition the nodes into an extended domain node set, a directly associated domain node set, and an indirectly associated domain node set based on the node configuration change identifier and the adjacency topology relationship of the directed graph structure. The deterministic boundary locking module is used to assign the expanded domain node set to the target test boundary set; if the directed edge between the directly associated domain node set and the expanded domain node set has a new or changed subcyclic redundancy check code after the expansion, then the corresponding node is assigned to the target test boundary set. The state transition construction module is used to perform a consistency comparison of the subcyclic redundancy check codes before and after the modification and expansion of the directed edges in the indirect association domain node set that are connected to the target test boundary set, and to construct a state transition matrix in combination with the priority attribute of the dataset. The risk simulation and convergence module is used to calculate the attenuation probability of the propagation from the nodes in the target test boundary set to the peripheral nodes based on the state transition matrix, and to include the nodes with attenuation probability greater than the preset safety confidence threshold into the target test boundary set until iterative convergence is achieved, thereby obtaining the substation renovation and expansion commissioning boundary.

[0092] An electronic device, comprising: Memory and processor; The memory is used to store computer programs; The processor is used to execute the computer program to implement the steps of the substation renovation and expansion commissioning boundary determination method as described in Embodiment 1.

[0093] A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the substation renovation and expansion commissioning boundary determination method as described in Embodiment 1.

[0094] This disclosure can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this disclosure.

[0095] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0096] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0097] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0098] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A method for determining the commissioning boundary during substation renovation and expansion, characterized in that, include: Obtain the full configuration file of the substation before and after the renovation and expansion, and extract the intelligent electronic equipment, virtual loop connection relationship and dataset priority attribute; The intelligent electronic device is mapped as a node in a directed graph structure, and the virtual loop connection is mapped as a directed edge; Based on the preset feature extraction rules, calculate the sub-cyclic redundancy check code corresponding to each directed edge; Based on the node configuration change identifier and the adjacency topology of the directed graph structure, the nodes are divided into an extended domain node set, a directly associated domain node set, and an indirectly associated domain node set. The expanded domain node set is assigned to the target test boundary set; if the directed edge between the directly associated domain node set and the expanded domain node set has a new or changed subcyclic redundancy check code after the expansion, the corresponding node is assigned to the target test boundary set. Perform a consistency comparison of the subcyclic redundancy check codes before and after the modification and expansion on the directed edges in the indirect association domain node set that are connected to the target test boundary set, and construct a state transition matrix in combination with the priority attribute of the dataset; Based on the state transition matrix, the attenuation probability of the nodes in the target test boundary set propagating to the outer nodes is calculated, and the nodes with attenuation probability greater than the preset safety confidence threshold are included in the target test boundary set until the iteration converges, thus obtaining the substation renovation and expansion commissioning boundary.

2. The method for determining the commissioning boundary of substation renovation and expansion according to claim 1, characterized in that, Based on preset feature extraction rules, the sub-cyclic redundancy check code corresponding to each directed edge is calculated, including: The entire site configuration file is parsed to extract the communication control block parameters, dataset configuration information, and receiving virtual terminal configuration information between the sending node and the receiving node corresponding to each directed edge; wherein, the communication control block parameters include GOOSE control block parameters and / or SV control block parameters; The communication control block parameters, the dataset configuration information, and the communication parameters contained in the receiving virtual terminal configuration information are concatenated into a data string according to a preset format; The data string is input into the Cyclic Redundancy Check (CRC) algorithm model to generate a sub-CRC code that represents the state of the directed edge communication link.

3. The method for determining the commissioning boundary of substation renovation and expansion according to claim 1, characterized in that, Based on the node configuration change identifier and the adjacency topology of the directed graph structure, the nodes are divided into an extended domain node set, a directly associated domain node set, and an indirectly associated domain node set, including: Based on the node configuration change identifier, identify target nodes in the renovation and expansion project that have new or changed states, and assign the target nodes to the expansion domain node set; In the directed graph structure, a single-hop topological traversal is performed starting from the extended domain node set to extract the first adjacent node that has a direct directed edge connected to the extended domain node set. The first adjacent node that needs to reissue the configuration file is then included in the directly associated domain node set. Starting from the set of directly associated domain nodes, continue topological traversal, extract the second adjacent nodes that have a direct directed edge connected to the set of directly associated domain nodes, and add the second adjacent nodes that do not require re-issuing configuration files to the set of indirectly associated domain nodes.

4. The method for determining the commissioning boundary of substation renovation and expansion according to claim 1, characterized in that, Perform a consistency comparison of subcyclic redundancy check codes before and after the modification and expansion on the directed edges connected to the target test boundary set in the indirect association domain node set, and construct a state transition matrix in conjunction with the priority attributes of the dataset, including: The nodes within the target test boundary set are designated as high-risk seed nodes; Extract the target directed edges between the high-risk seed nodes and the nodes within the indirect association domain node set, compare the subcyclic redundancy check codes before and after the expansion, and generate the basic risk transfer weights of the corresponding target directed edges based on the consistency comparison results. The dataset priority attribute bound to the target directed edge is parsed, and the dataset priority attribute is converted into a corresponding priority level coefficient according to a preset mapping rule; The basic risk transfer weight and the priority level coefficient are weighted and multiplied to obtain the comprehensive risk weight of the corresponding target directed edge. The comprehensive risk weights pointing outward from the same node are summed, and the normalized state transition matrix is ​​constructed based on the ratio of each comprehensive risk weight of the node to the summation value.

5. The method for determining the commissioning boundary of substation renovation and expansion according to claim 4, characterized in that, The process of obtaining the commissioning boundaries for substation renovation and expansion includes: Construct a global node risk probability vector, and set the initial probability value of the high-risk seed node in the global node risk probability vector to 1, and set the probability value of the remaining nodes to 0; The global node risk probability vector is iteratively multiplied with the state transition matrix, and a preset topology decay factor is introduced to update the global node risk probability vector after each iteration. Calculate the difference between the global node risk probability vectors of two adjacent iterations. If the difference is less than the convergence tolerance, the iteration is determined to be converged, and the final global node risk probability vector is obtained. Extract the attenuation probabilities of each item corresponding to the set of indirectly associated domain nodes in the final global node risk probability vector, and incorporate the nodes that are greater than the preset safety confidence threshold into the target test boundary set to obtain the substation renovation and expansion commissioning boundary.

6. The method for determining the commissioning boundary of substation renovation and expansion according to claim 1, characterized in that, After obtaining the substation renovation and expansion commissioning boundaries, the process also includes test plan generation and automated testing steps: The communication parameters corresponding to each node in the target test boundary set are extracted, and the communication parameters are converted into standard test model signals based on the preset general intermediate database and dictionary mapping rules. Based on the node attributes of the extended domain node set, the directly associated domain node set, or the indirectly associated domain node set to which each node belongs within the target test boundary set, the corresponding test sub-item is retrieved from the preset standardized test template library. The retrieved test sub-items and the standard test model signals are assembled in a time sequence to generate instantiated test case scripts and debugging outlines; The instantiated test case scripts are automatically sent to the target intelligent electronic device or field test equipment via the electrical Ethernet interface, based on the manufacturing message specification communication protocol, to execute automated closed-loop testing and generate test reports.

7. The method for determining the commissioning boundary of substation renovation and expansion according to claim 6, characterized in that, Before automatically sending the instantiated test case script to the target intelligent electronic device or field testing equipment, an offline virtual simulation verification step is also included: Extract the instance configuration files of each node within the target test boundary set, and construct a digital twin model of the substation that is equivalent to the physical topology on site in the preset virtualization engine; The instantiated test case script is converted into a virtual stimulus signal and injected into the virtual transmission channel of the corresponding sending node in the digital twin model in a timely manner. Traverse and listen to the logic triggering state of the virtual receiving terminal of the corresponding receiving terminal node in the digital twin model, and compare it with the preset expected action logic for consistency. If the detected logical trigger state does not match the preset expected action logic, a static configuration vulnerability alarm is generated, and the issuance command of the instantiated test case script is intercepted. If a match is found, the issued command is allowed and an automated closed-loop test is performed.

8. A substation renovation and expansion commissioning boundary determination system, characterized in that, The substation renovation and expansion commissioning boundary determination method as described in any one of claims 1 to 7 includes: The data parsing and modeling module is used to obtain the full station configuration file before and after the substation renovation and expansion, extract intelligent electronic devices, virtual loop connection relationships and dataset priority attributes; map the intelligent electronic devices as nodes in a directed graph structure, and map the virtual loop connection relationships as directed edges; and calculate the subcyclic redundancy check code corresponding to each directed edge based on preset feature extraction rules. The topology domain partitioning module is used to partition the nodes into an extended domain node set, a directly associated domain node set, and an indirectly associated domain node set based on the node configuration change identifier and the adjacency topology relationship of the directed graph structure. The deterministic boundary locking module is used to assign the expanded domain node set to the target test boundary set; if the directed edge between the directly associated domain node set and the expanded domain node set has a new or changed subcyclic redundancy check code after the expansion, then the corresponding node is assigned to the target test boundary set. The state transition construction module is used to perform a consistency comparison of the subcyclic redundancy check codes before and after the modification and expansion of the directed edges in the indirect association domain node set that are connected to the target test boundary set, and to construct a state transition matrix in combination with the priority attribute of the dataset. The risk simulation and convergence module is used to calculate the attenuation probability of the propagation from the nodes in the target test boundary set to the peripheral nodes based on the state transition matrix, and to include the nodes with attenuation probability greater than the preset safety confidence threshold into the target test boundary set until iterative convergence is achieved, thereby obtaining the substation renovation and expansion commissioning boundary.

9. An electronic device, characterized in that, include: Memory and processor; The memory is used to store computer programs; The processor is used to execute the computer program to implement the steps of the substation renovation and expansion commissioning boundary determination method as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the substation renovation and expansion commissioning boundary determination method as described in any one of claims 1 to 7.

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