Core power distribution network analysis device considering key load power supply capability
The core distribution network analysis device solves the problem of insufficient quantitative assessment of the importance of substations, realizes the scientific nature of power grid planning and the safe and stable power supply of critical loads, and provides accurate decision support tools.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- STATE GRID SHANGHAI MUNICIPAL ELECTRIC POWER CO
- Filing Date
- 2024-11-05
- Publication Date
- 2026-05-08
AI Technical Summary
The lack of quantitative assessment of the importance of substations in existing technologies leads to a lack of scientific basis for power grid planning, resource allocation and emergency response, making it impossible to accurately identify and prioritize high-risk areas. Furthermore, treating all substations of the same importance level may result in unnecessary losses of critical loads.
Design a core power distribution network analysis device, including a data acquisition module, a voltage level identification unit, a load importance assessment engine, a substation quantitative assessment model, and a risk assessment decision support system. Combined with an electronic map integration module, it realizes the quantitative assessment and priority processing of the importance of substations, taking into account the differences in power supply capacity and load importance of different voltage levels.
It enables quantitative assessment and prioritization of the importance of substations, improves the scientific nature and reliability of power grid planning, ensures the safe and stable power supply of critical loads, reduces overall system losses, and provides precise decision support tools.
Smart Images
Figure CN121998268A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to a core distribution network analysis device that takes into account the power supply capacity of critical loads. Background Technology
[0002] Currently, urban power systems typically include substations at different voltage levels, such as 10kV, 35kV, 110kV, 220kV, and 500kV, to meet the ever-increasing electricity demand. These substations play a crucial role in the power system, responsible for the transmission, distribution, and final delivery of electricity to users. The importance of substations at different voltage levels varies depending on their location within the power grid structure, their power supply range, and their ability to supply power to critical infrastructure. However, existing technologies are insufficient in quantifying the importance of substations. Traditional assessment methods often rely on qualitative analysis and empirical judgment, lacking unified quantitative standards and precise calculation models. This results in a lack of scientific basis for decisions in power grid planning, resource allocation, risk management, and emergency response, and an inability to effectively identify and prioritize high-risk areas in the power grid. Existing power system planning models and equipment theories lack quantitative assessment devices for the importance of substations at different voltage levels, thus failing to accurately predict and assess the actual role and potential risks of substations in the power system, and making it difficult to provide accurate data support for power grid planning and construction. Furthermore, the existing power system lacks a systematic analysis of the differences in the importance levels of substation loads. Treating all substations of the same importance level for optimized scheduling may cause unnecessary losses to critical loads under extreme conditions. Summary of the Invention
[0003] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a core distribution network analysis device that takes into account the power supply capacity of critical loads. During power system planning, it can quantitatively assess and analyze the importance of substations in urban power systems by considering the differences in the importance level of loads and the proportional constraints of the number of substations at each voltage level. This provides reference data for subsequent planning and system construction. Compared with existing research theories, this device has the ability to handle power systems of multiple voltage levels, which can expand its planning scope and quantitatively assess and analyze substations of different levels on a larger spatial scale.
[0004] The technical solution to achieve the above objectives is: a core distribution network analysis device that considers the power supply capacity of critical loads, comprising a data acquisition module, a voltage level identification unit, a load importance assessment engine, a substation quantitative assessment model, a risk assessment decision support system, and an electronic map integration module connected in sequence. The risk assessment decision support system is connected to a report generator and a user interface.
[0005] The data acquisition module automatically collects real-time data of the distribution network; the voltage level identification unit intelligently classifies the distribution network to obtain user types and power supply area functions; the load importance assessment engine assigns weights to different load levels based on user types and power supply area functions; the substation quantitative assessment model integrates information from the load importance assessment engine to calculate the importance index of each substation, while also considering the proportional constraints of the number of substations; the risk assessment decision support system provides distribution network analysis and planning schemes based on the substation importance indexes calculated by the substation quantitative assessment model and the proportional constraints of the number of substations, and uses the electronic map integration module to visualize the results of the distribution network analysis and planning schemes, displaying them directly on the user interface for intuitive understanding by operators; the report generator automatically compiles the corresponding distribution network analysis and planning reports.
[0006] The aforementioned core distribution network analysis device, which considers the power supply capacity of critical loads, includes real-time distribution network data such as voltage levels and load conditions.
[0007] The aforementioned core distribution network analysis device, which considers the power supply capacity of critical loads, wherein the load importance assessment engine comprehensively considers the importance of different facilities in social operation and performs intelligent hierarchical processing of power system loads; in emergency situations, the power supply of government agencies and fire brigades is given the highest priority; medical facilities, residential electricity, and important factories where power outages would cause serious economic losses are identified as the second priority; and the power demand of warehouses, convenience stores, and shopping malls is classified as the lowest priority.
[0008] The substations are weighted according to the above priority order. Substations connected to the highest priority loads receive the highest weight in the algorithm to ensure the safe and stable power supply of these substations. For substations connected to the next lower priority loads, power quality and grid resilience are considered to ensure the continuous power supply of these critical loads. Substations mainly connected to the lowest priority loads receive a correspondingly lower weight in the algorithm, and power supply is carried out reasonably according to the overall operation of the grid and resource allocation.
[0009] The aforementioned core distribution network analysis device, which considers the power supply capacity of critical loads, dynamically calculates and determines the power supply priority order of each facility based on real-time distribution network data and preset priority standards, and presents this information in an intuitive way on an electronic map, thereby providing grid operators with a clear decision support tool.
[0010] The aforementioned core distribution network analysis device that considers the power supply capacity of critical loads includes a substation quantitative evaluation model that takes into account the operating characteristics of the power system at different voltage levels, automatically identifies the voltage levels covered by the connected distribution network, and automatically adjusts its internal algorithm and evaluation parameters based on this information to adapt to the characteristics of the power system at different levels.
[0011] The aforementioned core distribution network analysis device takes into account the power supply capacity of critical loads, wherein the distribution networks of different voltage levels include 500kV ultra-high voltage transmission networks, 220kV high voltage transmission networks, 35kV distribution networks, and 10kV distribution networks.
[0012] The aforementioned core distribution network analysis device considers the power supply capacity of critical loads. For the 500kV ultra-high voltage transmission network, the losses caused by faults are enormous. Furthermore, the power supply reliability of various important power users N within its coverage area is also considered, as shown in Formula 1:
[0013]
[0014] In formula (1): U quality Representing power quality, α1 and α2 are weighting coefficients for different types of users, taking into account the power quality of all users within its scope, but with greater weight for critical loads and lower weight for other user set M;
[0015] 8. A core distribution network analysis device considering the power supply capacity of critical loads according to claim 6, characterized in that, for a 220kV high-voltage transmission network, the optimization objective is set to meet the randomness of users' electricity consumption for a long period of time, as shown in Formula 2, so that the power shortage of users in the entire transmission network is minimized during the calculation period:
[0016] min∑E gap (2)
[0017] In formula (2), E gap The objective function for optimizing the power shortage is denoted as .
[0018] The aforementioned core distribution network analysis device, which considers the power supply capacity of critical loads, includes a 35kV distribution network that connects the high-voltage and low-voltage power grids and directly supplies power to industrial and commercial users; and a 10kV distribution network that is closer to the end users and is responsible for supplying power to residential and small commercial users. It has a shorter transmission distance and a smaller transmission capacity. The constraints of the 35kV and 10kV distribution networks are mainly power flow constraints, and the compensation equipment of each distributed node needs to be taken into account.
[0019] The aforementioned core distribution network analysis device, which takes into account the power supply capacity of critical loads, has the ability to access power grid planning data, display the analysis results of the current situation and considering future additions to the network, and provide analysis and planning results of the optimal site selection, optimal capacity ratio, and optimal compensation device configuration for different sites.
[0020] This invention relates to a core distribution network analysis device that considers the power supply capacity of critical loads. By establishing a comprehensive evaluation model that takes into account differences in load importance levels and the constraints of the proportion of substations, it achieves a quantitative analysis of the importance of substations. This device can provide scientific and accurate decision support for power grid planning, construction, risk assessment, and emergency response, thereby improving the reliability and resilience of the power system. During power system planning, geographical information of the power system and parameters of each substation are collected, along with load data. The data is processed through a core algorithm, considering the importance differences between different loads, the constraints of the proportion of substations at each voltage level, operating condition constraints, and safety and stability constraints, to quantitatively assess the importance of each substation, providing a reference for future planning and system construction. Attached Figure Description
[0021] Figure 1 A schematic diagram of the core distribution network analysis device that takes into account the power supply capacity of critical loads;
[0022] Figure 2 This is a schematic diagram of load classification in a power distribution network;
[0023] Figure 3 This is a schematic diagram illustrating the characteristics of a multi-voltage-level power grid.
[0024] Figure 4 Generate a schematic diagram for the Monte Carlo method scene;
[0025] Figure 5 This is a schematic diagram for photovoltaic site selection.
[0026] Figure 6 This is a schematic diagram for power system planning and analysis. Detailed Implementation
[0027] To enable those skilled in the art to better understand the technical solution of the present invention, its specific embodiments are described in detail below with reference to the accompanying drawings:
[0028] Please see Figure 1 According to an embodiment of the present invention, a core distribution network analysis device that takes into account the power supply capacity of critical loads includes a data acquisition module 1, a voltage level identification unit 2, a load importance assessment engine 3, a substation quantitative assessment model 4, a risk assessment decision support system 5, and an electronic map integration module 6 connected in sequence. The risk assessment decision support system 5 is connected to a report generator 7 and a user interface 8.
[0029] The data acquisition module 1 automatically collects real-time data from the distribution network, including voltage levels and load conditions. The voltage level identification unit 2 intelligently classifies the distribution network to obtain user types and power supply area functions. The load importance assessment engine 3 assigns weights to different load levels based on user types and power supply area functions. The substation quantitative assessment model 4 integrates information from the load importance assessment engine to calculate the importance index of each substation, while also considering the proportional constraints of the number of substations. The risk assessment decision support system 5 provides forward-looking distribution network analysis and planning schemes based on the substation importance indexes calculated by the substation quantitative assessment model and the proportional constraints of the number of substations. The results of the distribution network analysis and planning schemes are visualized using the electronic map integration module 6 and directly displayed on the user interface 8 for intuitive operator understanding. The report generator 7 automatically generates corresponding distribution network analysis and planning reports. The design of the user interface 8 makes monitoring and interaction simple and direct. The device's communication interface ensures seamless data exchange with external systems, providing power system operators and planners with an efficient and accurate power grid planning and operation management tool.
[0030] This invention relates to a core distribution network analysis device that considers the power supply capacity of critical loads. It can not only process complex power system data but also accurately quantify the load importance of each substation while meeting specific proportional constraints. This device provides power system planners with a scientific and reliable decision support tool, helping them optimize substation layout and resource allocation. The device is expected to significantly improve the planning efficiency and power supply reliability of power systems, and has significant practical application value for the modernization and intelligentization of urban power systems. This device can handle the complexity of multi-voltage-level power systems. It not only enhances the applicability of planning but also allows for accurate quantitative assessment and in-depth analysis of substations at different voltage levels over a wider geographical area. This device considers the operating characteristics of power systems at different voltage levels, possessing high flexibility and adaptability. It can automatically identify the voltage levels covered by the connected power grid and automatically adjust its internal algorithms and evaluation parameters based on this information to adapt to the characteristics of power systems at different levels. This device is capable of handling loads of varying importance levels. During planning calculations, it considers the importance of loads connected to different substations and assigns weights to substations of different importance, improving the operational quality and safety of critical loads and reducing overall system losses. The device can access grid planning data, displaying analysis results both current and considering future additions to the grid. It provides optimal site selection, capacity allocation, and compensation device configuration for different substations, offering decision-making support and reference for investors and power system operators. Furthermore, the device is equipped with the ability to link with electronic maps and geographic information systems. The aforementioned calculation results and analytical decisions can be marked on electronic maps, providing intuitive information to power system operators. It can directly, accurately, and quickly identify the importance of each substation within its processing range, facilitating on-site response and rapid dispatch by operators.
[0031] Example 1
[0032] In this embodiment, the device employs an advanced load management strategy. By comprehensively considering the importance of different facilities in social operation, it achieves intelligent hierarchical processing of power system loads. The core algorithm of this device can dynamically calculate and determine the power supply priority order of each facility based on real-time data and preset priority standards, and present this information in an intuitive way on an electronic map, thereby providing grid operators with a clear decision support tool.
[0033] In this embodiment, the device places particular emphasis on ensuring power supply to critical social facilities. For example, in emergency situations, the power supply to government agencies and fire brigades is given the highest priority to ensure law, order, social stability, and the continuity of emergency rescue services. The operational stability of these facilities is crucial for maintaining public safety and the normal functioning of society. Following closely behind are medical facilities, residential electricity, and important factories where power outages would cause severe economic losses; these are identified as second-highest priority. Continuous power supply to medical facilities is essential for treating patients and maintaining medical order, while the stability of residential electricity supply directly affects people's quality of life. Furthermore, ensuring the stability of power supply to factories with significant economic impact, such as large-scale manufacturing and critical infrastructure, is crucial for ensuring the smooth operation of the national economy. Finally, the device also considers the power needs of commercial facilities such as warehouses, convenience stores, and shopping malls, which are classified as lowest priority. Although these facilities are also important to socio-economic activities, their power supply priority is relatively low given the limited power resources. A schematic diagram of all load levels in a distribution network is shown below. Figure 2 As shown.
[0034] When performing power system analysis and calculations, this device weights substations according to the aforementioned priority order. Substations connected to the most critical load levels, such as government agencies and fire stations, will receive higher weights in the algorithm to ensure their safe and stable power supply. For substations connected to secondary critical load levels, such as medical facilities, important factories, and residential power, the device will prioritize power quality and grid resilience to ensure continuous power supply to these critical loads. Substations primarily connected to lower critical load levels will have correspondingly lower weights in the algorithm, but will still receive power supply rationally based on the overall grid operation and resource allocation.
[0035] Through this intelligent load management and prioritization, this device not only improves the operating efficiency and reliability of the power system, but also provides grid operators with an effective risk management and emergency response tool, ensuring that the most appropriate power supply decisions can be made in the face of various complex situations, so as to minimize socio-economic losses and protect public safety.
[0036] Example 2
[0037] The core distribution network analysis device of this invention, which considers the power supply capacity of critical loads, incorporates the characteristics of multiple levels of transmission and distribution networks, taking into account both general power flow constraints and their respective unique features, such as... Figure 3 As shown.
[0038] Transmission networks of different voltage levels, such as 500kV, 220kV, 35kV, and 10kV, each play a unique role and function in the power system.
[0039] 500kV ultra-high voltage transmission networks are mainly used for long-distance, large-capacity power transmission. They employ ring or mesh structures to improve power supply reliability and flexibility, while requiring high-standard insulation and advanced control and protection systems. Analysis and calculations must emphasize the reliability and flexibility of the insulation and protection network. Power transmission models are established for complex ring and mesh network structures. Due to the long transmission distances and large transmission capacities, losses during analysis and calculations cannot be ignored. Because the losses caused by faults in ultra-high voltage transmission networks are enormous and can cause destructive failures to a wide range of power systems, the power supply reliability of various important power users N within its coverage area is additionally considered, as shown in Formula 1, where U... quality Representing power quality, α1 and α2 are the weighting coefficients for different types of users, taking into account the power quality of all users within its scope, but with greater weight for critical loads and lower weight for other user sets M.
[0040]
[0041] The 220kV high-voltage transmission network is used for medium-distance power transmission. While its structure is relatively simple, it still requires strong power supply capacity and stability. Its constraints should focus on power supply stability. The algorithm of this device sets one of its optimization objectives as meeting the randomness of users' electricity consumption over a long period, as shown in Formula 2, minimizing the power shortage for users throughout the entire transmission network during the calculation period, E. gap The objective function for optimizing the power shortage is denoted as .
[0042] min∑E gap (2)
[0043] 35kV distribution networks are typically part of a larger distribution network, connecting high-voltage and low-voltage grids. Their structure may be radial or tree-like, directly supplying power to industrial and commercial users. 10kV distribution networks, on the other hand, are closer to the end user, supplying power to residential and small commercial users, and have shorter transmission distances and smaller transmission capacities. In both types of distribution networks, power flow constraints are the primary factor, and the compensation equipment at each distributed node needs to be taken into account.
[0044] These different levels of networks vary in terms of voltage level, transmission distance, network structure, line and equipment specifications, insulation requirements, losses, power supply reliability, user connections, control automation, investment costs, and environmental impact. This requires power grid planners and operators to make reasonable plans, constructions, and management based on their respective characteristics and needs. The analysis and calculations of the device in this invention can ensure the safe, reliable, and efficient operation of the entire power system.
[0045] Example 3
[0046] Site selection for modern power grid expansion is a crucial aspect of power system planning, directly impacting the grid's stability, economic viability, and environmental friendliness. The device of this invention allows for comprehensive consideration of various factors during site selection, including but not limited to geographical location, population distribution, industrial layout, availability of natural resources, and environmentally sensitive areas. The rational site selection provided by this device maximizes transmission efficiency, reduces construction costs and operational risks, and minimizes negative impacts on the ecological environment. Furthermore, with the large-scale grid integration of renewable energy and the development of smart grid technologies, grid expansion site selection must also consider future flexibility and scalability, ensuring the grid can adapt to ever-changing energy demands and technological innovations. Therefore, carefully planned grid expansion site selection plays a vital role in achieving sustainable grid development, ensuring energy security, and promoting regional economic growth.
[0047] By analyzing historical load data empirically, a corresponding stochastic distribution model can be derived. This device simulates a large number of load scenarios using the Monte Carlo method, such as... Figure 4 As shown.
[0048] The algorithm design of this computing device is shown in Formulas 3 and 4, where... These represent the revenue from PV and ESS, respectively. and C represents transmission power, respectively. PV-EV C PV -Grid C PV-ESS C ESS-EV and C PV-ESS These represent the product of the electricity purchase cost, the installed capacity, and the cost of transmission. and The installation costs are for PV and ESS, respectively.
[0049]
[0050] Compare the economic calculation results under all scenarios, such as Figure 5 As shown in the figure, the optimal site selection suggestion is given. In this embodiment, the site selection suggestion for this node is not suitable for installing a photovoltaic power generation system. Under the set electricity price, the photovoltaic power generation system will be in a loss-making state for a long time. However, as can be seen from the figure, the load type here is suitable for installing a large-capacity energy storage system to provide power support for the distribution network.
[0051] Example 4
[0052] In this embodiment, a power distribution network is provided, and the load classification scheme of Embodiment 1 has been implemented. Figure 5The classification results of the distribution network are presented, with two critical loads marked within the red dashed box. Analysis by the device of this invention indicates that the transmission distance of this distribution network is relatively long, suggesting the integration of compensation devices or distributed power sources within the network to improve the resilience and flexibility of the power system. Furthermore, slow-charging electric vehicle (EV) loads and fast-charging EV loads are connected to the vicinity of the two critical loads in this distribution network, respectively. Based on the economic calculations and comparisons in Example 3, the reference recommendations provided by this device are as follows: Figure 6 As shown, a large-capacity energy storage system is installed at the slow-charging EV load, while a photovoltaic power generation system is installed at the fast-charging EV load. During normal operation, the energy storage system serves as a peak-shaving and valley-filling compensation mechanism to assist the power system's operation, ensuring its safe and stable operation, voltage stability, and frequency stability. The photovoltaic power generation system, matching the characteristics of the fast-charging EV load, effectively addresses the impact of the randomness of the fast-charging EV load. In the event of a line fault, the energy storage system can provide power to critical loads before repair personnel arrive, reducing corresponding economic losses. The photovoltaic power generation system can act as a localized distributed renewable energy source, ensuring regional power supply and facilitating the rapid completion of repair tasks. The invented analytical device will provide power system managers with reliable, scientific, and clear recommendations to support the planning, construction, and operation of power systems.
[0053] Example 5
[0054] In this embodiment, the analysis device of the present invention aims to comprehensively analyze the operating status of the distribution network, not just its power supply capacity. It transforms complex power system data into intuitive visualizations through a graphical interface, enabling researchers and operations engineers to quickly grasp the overall operating status of the distribution network, including key parameters such as voltage levels, line loads, and node stability. This rapid understanding capability is crucial for making timely and accurate decisions in emergency situations or extreme scenarios.
[0055] The device's key feature is its ability to combine network topology maps of the distribution network to demonstrate the physical structure of the grid and the power supply status of critical nodes. It not only highlights critical nodes and links but also analyzes potential site selection for distribution network expansion, providing strategic recommendations for grid expansion. This includes identifying bottlenecks in the grid, predicting future load growth, and assessing the economic benefits and environmental impacts of different expansion schemes.
[0056] Furthermore, the device's intelligent design enables seamless integration with smart grid interactive platforms, facilitating real-time data exchange and communication. This feature not only enhances the control speed and flexibility of grid operation but also simplifies the operating process, resulting in a user-friendly and easy-to-operate interface. It can also comprehensively consider the mutual influences of multi-voltage level grids, providing comprehensive technical support for optimized grid management, fault diagnosis, and preventative maintenance.
[0057] In summary, the device in this embodiment significantly improves the convenience and reliability of real-time operation of the distribution network through its efficient visualization and intelligent data processing capabilities. It provides strong technical support for the optimized management, fault diagnosis, and preventative maintenance of the power system, ensuring the stability and economy of power grid operation, while also providing a scientific basis for decision-making regarding the expansion and upgrading of the distribution network.
[0058] In summary, the core distribution network analysis device of this invention, which considers the power supply capacity of critical loads, calculates the differences in importance levels of different loads during power system planning, takes into account the proportional constraints of the number of substations at each voltage level, and achieves a quantitative assessment and analysis of the importance of substations in urban power systems. This provides reference data for power system operators, decision-makers, and planners.
[0059] This invention can automatically adapt to the voltage levels covered by the connected power grid and analyze complex power system problems with different voltage levels. Simultaneously, this device also has the ability to handle loads of various importance levels. During planning calculations, this device can consider the importance of loads connected to different substations, autonomously balance their advantages and disadvantages, adjust the analysis results, ensure the safe and stable operation of critical loads, and minimize the potential losses of power grids with loads of various importance levels.
[0060] Simultaneously, this device also possesses the ability to access power grid planning data, displaying analysis results both currently available and considering future additions to the network. It provides analysis results on the optimal site selection, optimal capacity allocation, and optimal compensation device configuration for different substations, offering decision-making basis and reference for subsequent planning and system construction. Furthermore, this invention is equipped with the ability to link with electronic maps and geographic information systems. The aforementioned calculation results and analysis decisions can be marked on electronic maps, directly, accurately, and quickly identifying the importance of each substation within the processing range.
[0061] Those skilled in the art should recognize that the above embodiments are merely illustrative of the present invention and are not intended to limit the present invention. Any variations or modifications to the above embodiments that are within the spirit and essence of the present invention will fall within the scope of the claims of the present invention.
Claims
1. A core distribution network analysis device that considers the power supply capacity of critical loads, characterized in that, The system includes, in sequence, a data acquisition module, a voltage level identification unit, a load importance assessment engine, a substation quantitative assessment model, a risk assessment decision support system, and an electronic map integration module. The risk assessment decision support system is connected to a report generator and a user interface. The data acquisition module automatically collects real-time data of the distribution network; the voltage level identification unit intelligently classifies the distribution network to obtain user types and power supply area functions; the load importance assessment engine assigns weights to different load levels based on user types and power supply area functions; the substation quantitative assessment model integrates information from the load importance assessment engine to calculate the importance index of each substation, while also considering the proportional constraints of the number of substations; the risk assessment decision support system provides distribution network analysis and planning schemes based on the substation importance indexes calculated by the substation quantitative assessment model and the proportional constraints of the number of substations, and uses the electronic map integration module to visualize the results of the distribution network analysis and planning schemes, displaying them directly on the user interface for intuitive understanding by operators; the report generator automatically compiles the corresponding distribution network analysis and planning reports.
2. The core distribution network analysis device considering the power supply capacity of critical loads according to claim 1, characterized in that, The real-time data of the power distribution network includes voltage levels and load conditions.
3. The core distribution network analysis device considering the power supply capacity of critical loads according to claim 1, characterized in that, The load importance assessment engine comprehensively considers the importance of different facilities in the operation of society and intelligently classifies the load of the power system; in emergency situations, the power supply to government agencies and fire brigades is given the highest priority. Medical facilities, residential electricity, and critical factories where power outages would cause severe economic losses were identified as a second priority. The electricity needs of warehouses, convenience stores, and shopping malls are classified as the lowest priority. The substations are weighted according to the above priority order. Substations connected to the highest priority loads receive the highest weight in the algorithm to ensure the safe and stable power supply of these substations. For substations connected to the next lower priority loads, power quality and grid resilience are considered to ensure the continuous power supply of these critical loads. Substations mainly connected to the lowest priority loads receive a correspondingly lower weight in the algorithm, and power supply is carried out reasonably according to the overall operation of the grid and resource allocation.
4. A core distribution network analysis device considering the power supply capacity of critical loads according to claim 3, characterized in that, Based on real-time data from the distribution network and preset priority standards, the power supply priority order of each facility is dynamically calculated and determined, and this information is presented in an intuitive way on an electronic map, thus providing grid operators with a clear decision support tool.
5. A core distribution network analysis device considering the power supply capacity of critical loads according to claim 1, characterized in that, The substation quantitative evaluation model considers the operating characteristics of the power system at different voltage levels, automatically identifies the voltage levels covered by the connected distribution network, and automatically adjusts its internal algorithms and evaluation parameters based on this information to adapt to the characteristics of the power system at different levels.
6. A core distribution network analysis device considering the power supply capacity of critical loads according to claim 5, characterized in that, Distribution networks of different voltage levels include 500kV ultra-high voltage transmission networks, 220kV high voltage transmission networks, 35kV distribution networks, and 10kV distribution networks.
7. A core distribution network analysis device considering the power supply capacity of critical loads according to claim 6, characterized in that, For 500kV ultra-high voltage transmission networks, the losses caused by faults are enormous. Furthermore, the power reliability of various important power users N within its coverage area must be considered, as shown in Formula 1: In formula (1): U quality Representing power quality, α1 and α2 are the weighting coefficients for different types of users, taking into account the power quality of all users within its scope, but with greater weight for critical loads and lower weight for other user sets M.
8. A core distribution network analysis device considering the power supply capacity of critical loads according to claim 6, characterized in that, For a 220kV high-voltage transmission network, the optimization objective is set to meet the randomness of users' electricity demand over a long period of time, as shown in Formula 2, so as to minimize the power shortage for users of the entire transmission network during the calculation period: min∑ER gap (2) In formula (2), E gap The objective function for optimizing the power shortage is denoted as .
9. A core distribution network analysis device considering the power supply capacity of critical loads according to claim 6, characterized in that, The 35kV distribution network connects the high-voltage and low-voltage power grids, directly supplying electricity to industrial and commercial users; the 10kV distribution network is closer to the end users, responsible for supplying electricity to residential and small commercial users, with shorter transmission distances and smaller transmission capacities. In the constraints of the 35kV and 10kV distribution networks, power flow constraints are the main factor, and the compensation equipment of each distributed node needs to be taken into account.
10. A core distribution network analysis device considering the power supply capacity of critical loads according to claim 1, characterized in that, It has the ability to access power grid planning data, display the analysis results of the current situation and considering the addition of future sites, and provide the analysis and planning results of the optimal site location, optimal capacity ratio, and optimal compensation device configuration for different sites.