Substation management system

Abstract

The invention relates to the technical field of new energy and energy conservation, and discloses a substation management system, which comprises a data acquisition and monitoring module for acquiring operation data of equipment in a substation, monitoring the operation state of the equipment and preprocessing the data; the dynamic energy consumption optimization module is used for optimizing the operation state and power distribution of the equipment and reducing the total energy consumption of the transformer substation; the hierarchical load regulation and control module is used for performing hierarchical management on equipment in the transformer substation according to priorities and optimizing operation of the equipment through dynamic start and stop; and the new energy access optimization module is used for dynamically adjusting the power distribution proportion of the new energy and the traditional energy according to the real-time power fluctuation of the new energy and the traditional energy. Through integrated multi-module collaborative optimization, efficient energy consumption management and dynamic equipment regulation and control of the transformer substation are realized, the energy utilization rate is improved, energy consumption waste and equipment wear are reduced, new energy is scheduled preferentially, supply and demand balance is guaranteed, equipment maintenance is planned reasonably, and long-term stable operation of the system is ensured.

Description

Technical Field

[0001] The present invention relates to the field of new energy and energy-saving technology, and in particular to a management system for a transformer substation. Background Art

[0002] In modern power systems, substations are the core hubs of power transmission and distribution, and their operating efficiency and management level are directly related to the stability and economy of the power grid. However, with the adjustment of energy structure and the gradual increase in the proportion of new energy access, the management mode of traditional substations can no longer adapt to the complex and changeable operating needs. Traditional systems usually adopt fixed scheduling and management strategies, which are difficult to effectively respond to the dynamic changes in load demand, resulting in high energy consumption of equipment operation and low resource utilization efficiency. In addition, the lack of coordinated scheduling capabilities between traditional energy and new energy has aggravated the impact of new energy volatility on the system, further reducing the overall energy utilization efficiency.

[0003] In terms of equipment management, the traditional operation mode lacks flexibility, and the operating status of the equipment is difficult to dynamically adjust according to the actual load demand. Frequent start and stop or long-term full-load operation not only increases energy waste, but also has an adverse effect on the service life of the equipment. At the same time, the traditional system has limited response capabilities under load fluctuations and cannot adjust power distribution in time, resulting in an imbalance between supply and demand and increasing the risk of power grid operation. In addition, due to the lack of data-driven intelligent analysis, equipment maintenance plans often rely on experience, which is difficult to optimize in combination with long-term energy consumption goals and equipment status, and easily leads to problems of insufficient or excessive maintenance.

[0004] In view of these problems, the present invention proposes a management system for a substation. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a management system for a substation, which solves the problems of efficient energy consumption management, dynamic equipment regulation and coordinated utilization of new and traditional energy in substations under complex load conditions.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A management system for a substation, comprising: Data acquisition and monitoring module, used to collect operating data of equipment in the substation, monitor the operating status of equipment and pre-process the data; Dynamic energy consumption optimization module, used to optimize equipment operating status and power distribution to reduce the total energy consumption of the substation; The hierarchical load control module is used to manage the equipment in the substation in a hierarchical manner according to priority, and optimize the operation of the equipment through dynamic start and stop; the new energy access optimization module is used to dynamically adjust the power allocation ratio of new energy and traditional energy according to the real-time power fluctuations of the two; A multi-timescale scheduling module is used to respond to load fluctuations in the short timescale and formulate equipment operation and maintenance plans in the long timescale.

[0007] Preferably, the data acquisition and monitoring module includes: Data acquisition device, used to collect voltage, current, power, temperature and load rate parameters of the equipment; A data preprocessing unit, used for noise reduction, normalization and outlier detection of the collected data; The monitoring unit is used to display the equipment operation status in real time and provide visual analysis.

[0008] Preferably, the dynamic energy consumption optimization module includes: Energy consumption optimization unit, used to construct energy consumption objective function and optimize the total energy consumption of the substation; The operating status analysis unit is used to analyze the operating efficiency of the equipment and provide power allocation suggestions.

[0009] Preferably, the energy consumption objective function constructed by the energy consumption optimization unit is: Among them, E total is the total energy consumed by all devices in the system during the time interval, is the sum of the instantaneous power of all N devices in the substation at time t, P i (t) is the instantaneous power of the i-th device at time t, P loss (t) is the transmission power loss of the substation at time t.

[0010] Preferably, the hierarchical load regulation module includes: Hierarchical management unit, used to classify devices into core devices, auxiliary devices, and backup devices, and dynamically manage the device operation status according to priority; The start-stop optimization unit is used to optimize the start-stop strategy of the equipment and minimize the switching frequency of the equipment.

[0011] Preferably, the start-stop optimization unit optimizes the number of equipment starts and stops using the following objective function: Where C is the total number of starts and stops of all devices in the system within the time interval [1, T], N is the total number of devices in the system, T is the total number of time steps analyzed or the total number of moments in the time interval, S i (t) is the operating state variable of the i-th device at time t, |S i (t)-S i (t-1)| is the state change of the i-th device between time t and time t-1.

[0012] Preferably, the new energy access optimization module includes: Power balancing unit, used to ensure that the power of new energy and traditional energy meets the load balance relationship; The power optimization unit is used to construct the optimization objective function to dynamically adjust the power of new energy.

[0013] Preferably, the load balance relationship in the power balancing unit satisfies the following formula: P load (t) = P new (t)+P trad (t) Among them, P load (t) is the total load power demand of the system at time t, P new (t) is the power provided by the new energy source to the system at time t, P trad (t) is the power provided by the traditional energy to the system at time t; the new energy power optimization unit constructs the power allocation optimization target formula as follows: Where L is the total loss or total cost of the system in the time interval [0, T], is the power loss of the system at time t due to the fluctuation characteristics of new energy, P trad (t) is the power of the system using traditional energy at time t; the power optimization unit uses the Lagrange multiplier method to optimize the new energy power distribution, the formula is: Among them, P new (t) is the power provided by the new energy to the system at time t, λ is the Lagrange multiplier, and H(t) is the new energy fluctuation coefficient.

[0014] Preferably, the multi-time scale scheduling module includes: Short-time scheduling unit for optimizing real-time power distribution; The long-term scheduling unit is used to optimize equipment operation and maintenance plans and build an objective function for long-term energy consumption.

[0015] Preferably, the short-time scheduling unit uses the following formula to optimize real-time power allocation: Minimize:ΔP=|P load (t)-P gen (t)| Where ΔP is the power imbalance value of the system at time t, P load (t) is the total load power demand of the system at time t, P gen (t) is the total power generation of the system at time t; the long-term energy consumption objective function constructed in the long-term scheduling unit is; Among them, E total is the total energy consumption of the system in the entire time interval, P i (d) The average power of the i-th device in time period d, t i (d) is the operating time of the i-th device in time period d; the equipment maintenance plan formulated by the long-term scheduling unit must meet the following time constraints: Among them, t maint (i) is the maintenance time of equipment i, T max (i) is the maximum allowable maintenance interval.

[0016] The present invention provides a management system for a substation, which has the following beneficial effects: 1. The present invention uses a dynamic energy consumption optimization module to analyze the equipment operating status in real time and dynamically adjust the equipment power distribution to ensure that energy waste is reduced while meeting load requirements. The system can intelligently optimize transmission losses and optimize the equipment operating status according to real-time load conditions, significantly reducing the overall energy consumption of the substation and improving the system operating efficiency, thereby achieving energy-saving effects.

[0017] 2. The present invention performs priority hierarchical management of equipment through a hierarchical load control module. The core equipment runs continuously to ensure system stability, and the auxiliary equipment and spare equipment are dynamically started and stopped according to load demand to avoid wear and tear caused by frequent switching of equipment. The start-stop optimization unit further reduces the number of unnecessary switching times of equipment, improves operating efficiency, extends the service life of equipment, and reduces equipment maintenance costs.

[0018] 3. The present invention dynamically adjusts the power allocation ratio of new energy and traditional energy through the new energy access optimization module, gives priority to the use of new energy to reduce the use cost and carbon emissions of traditional energy, improves the efficiency of new energy utilization by smoothing the impact of new energy fluctuations on the system, and realizes efficient coordination between new energy and traditional energy, which is in line with the trend of green energy development.

[0019] 4. The present invention uses a multi-time scale scheduling module to quickly adjust power distribution in a short period of time, ensure real-time balance between supply and demand, and reduce the risk of system instability caused by load fluctuations. On a long time scale, by optimizing equipment operation plans and maintenance cycles, it ensures long-term stable operation of equipment, while improving the overall reliability and economy of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a framework diagram of the system of the present invention; Figure 2 It is a framework diagram of the data acquisition and monitoring module of the present invention; Figure 3 It is a framework diagram of the dynamic energy consumption optimization module of the present invention; Figure 4 It is a framework diagram of the hierarchical load regulation module of the present invention; Figure 5 This is a framework diagram of the new energy access optimization module of the present invention; Figure 6 It is a framework diagram of the multi-time scale scheduling module of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the specification of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] Please refer to the attached Figure 1 , an embodiment of the present invention provides a management system for a substation, including: Data acquisition and monitoring module, used to collect the operating data of equipment in the substation, monitor the operating status of the equipment and pre-process the data; Dynamic energy consumption optimization module, used to optimize equipment operating status and power distribution to reduce the total energy consumption of the substation; The hierarchical load control module is used to manage the equipment in the substation in a hierarchical manner according to priority, and optimize the operation of the equipment through dynamic start and stop; the new energy access optimization module is used to dynamically adjust the power allocation ratio of new energy and traditional energy according to the real-time power fluctuations of the two; A multi-timescale scheduling module is used to respond to load fluctuations in the short timescale and formulate equipment operation and maintenance plans in the long timescale.

[0023] Specifically, this system realizes efficient management of substation equipment, energy consumption optimization and coordinated dispatch of new energy and traditional energy through modular design. The core of the system consists of five modules, which work together to achieve intelligent management goals.

[0024] The system first deploys sensors and smart meters through the data acquisition and monitoring module to monitor the operating status of equipment in the substation in real time, including key parameters such as voltage, current, power, temperature and load rate of the equipment. After pre-processing such as noise reduction, normalization and outlier detection, the collected multi-dimensional data is input into the subsequent modules in a high-quality form, and a visual interface is provided to display the operation status of the equipment to ensure the transparency and security of the system operation.

[0025] The core of the optimization system is the dynamic energy consumption optimization module, which builds energy consumption targets based on real-time data and dynamically optimizes the operating status and power distribution of each device. Under the premise of meeting the load requirements of the substation, the total energy consumption of the entire system is reduced and the operating efficiency is improved by adjusting the power distribution of the equipment and reducing transmission losses. This optimization process not only dynamically adapts to load changes, but also reduces energy waste when the equipment is not operating optimally.

[0026] To ensure efficient collaboration of substation equipment, the system introduces a hierarchical load control module. This module divides the equipment into three categories: core equipment, auxiliary equipment, and backup equipment according to their importance, and manages them in layers. Core equipment remains in full-time operation, auxiliary equipment is dynamically started and stopped according to load demand, and backup equipment is only started during peak load periods. By optimizing the start and stop frequency of equipment, the module effectively reduces energy consumption and wear caused by frequent equipment switching, while extending the service life of the equipment.

[0027] In the scenario of new energy access, the new energy access optimization module of the system plays a key role in the coordinated dispatch of new energy and traditional energy. The module dynamically adjusts the power allocation ratio of new energy and traditional energy according to load demand and new energy fluctuations. Giving priority to the use of new energy not only improves its utilization rate, but also reduces the cost and carbon emissions of traditional energy. At the same time, the module optimizes power allocation and smoothes the power loss caused by new energy fluctuations to ensure the stable operation of the system.

[0028] In order to achieve a combination of short-term response and long-term optimization, the system also designed a multi-time scale scheduling module. In the short time scale, the module quickly responds to load demand fluctuations by dynamically adjusting power distribution to ensure the balance of system supply and demand. In the long time scale, the module formulates equipment operation and maintenance plans, extends equipment life and improves the long-term operation efficiency of the system by optimizing maintenance cycles. The synergy of short-term and long-term scheduling enables the system to dynamically adapt to load changes while maintaining overall efficiency and reliability.

[0029] The modular design of this system ensures efficient data collection, dynamic optimization of operating status and reasonable scheduling of energy, thereby improving substation operating efficiency and maximizing energy utilization. The functions of each module complement each other, both independent and collaborative, forming a comprehensive, intelligent and efficient substation management system.

[0030] Please refer to the attached Figure 2 , the data acquisition and monitoring modules include: Data acquisition device, used to collect voltage, current, power, temperature and load rate parameters of the equipment; A data preprocessing unit, used for noise reduction, normalization and outlier detection of the collected data; The monitoring unit is used to display the equipment operation status in real time and provide visual analysis.

[0031] Specifically, in view of the above content, the data acquisition and monitoring module is the basic component of the substation management system, which mainly realizes the real-time monitoring and data acquisition of the equipment operation status, ensuring that the subsequent optimization module can process and calculate based on accurate and high-quality data. This module obtains key operating parameters such as voltage, current, power, temperature and load rate through the data acquisition device, and performs noise reduction, normalization and anomaly detection on the data through the data preprocessing unit, providing highly reliable data support for subsequent analysis. At the same time, the monitoring unit displays the operating status of the equipment in a visual way, providing a basis for the real-time status evaluation of the substation.

[0032] In this embodiment, the data acquisition device collects multi-dimensional parameters such as voltage, current, power, temperature and load rate in the substation in real time by deploying smart meters, sensors and monitoring terminals.

[0033] in: Voltage and current: The working voltage U(t) and working current I(t) of the equipment are collected through the transformer, which serves as an important basis for calculating power.

[0034] Power: Based on the real-time collected voltage and current, combined with the power factor cosφ, the instantaneous active power P(t) and reactive power Q(t) of the device are calculated: P(t)=U(t)·I(t)·cosφQ(t)=U(t)·I(t)·sinφ Temperature: Use thermocouples or infrared temperature measuring devices to collect the equipment surface and ambient temperature T(t) and T env (t), monitor the thermal operation status of the equipment.

[0035] Load rate: The load rate η(t) is calculated by the ratio of the current power of the equipment to the rated power: This parameter reflects the operating load level of the equipment and provides data support for optimizing load distribution.

[0036] In this embodiment, the data preprocessing unit cleans and preprocesses the collected multidimensional data, mainly including the following steps: Noise reduction: Use the sliding window average method to smooth the time series data and eliminate the impact of noise: Among them, X(i) is the sampled data and n is the window size.

[0037] Normalization: Normalize data of different dimensions to eliminate dimension differences. The calculation formula is: P load(t) = P new (t)+P trad (t) Anomaly detection: Use the outlier detection method to remove outliers, using the three times standard deviation rule: Outlier:|X(t)-X avg (t)|>3σ Here, σ is the standard deviation of the data.

[0038] After data preprocessing, the obtained high-quality time series data is input into the subsequent optimization module.

[0039] In this embodiment, the monitoring unit visualizes the equipment operation status through charts and dashboards. Real-time data display includes: Equipment voltage, current and power curves to monitor the electrical operating status of the equipment; Temperature trend, used to assess the thermal load of the equipment; The dynamic change of load rate is used to evaluate whether the equipment load is within a reasonable range.

[0040] The visual interface can prompt abnormal equipment operation in real time, providing a basis for operation and maintenance personnel to quickly diagnose problems.

[0041] Please refer to the attached Figure 3 , the dynamic energy consumption optimization module includes: Energy consumption optimization unit, used to construct energy consumption objective function and optimize the total energy consumption of the substation; The operating status analysis unit is used to analyze the operating efficiency of the equipment and provide power allocation suggestions.

[0042] The energy consumption objective function constructed by the energy consumption optimization unit is: Among them, E total is the total energy consumed by all devices in the system during the time interval, is the sum of the instantaneous power of all N devices in the substation at time t, P i (t) is the instantaneous power of the i-th device at time t, P loss (t) is the transmission power loss of the substation at time t.

[0043] Specifically, the dynamic energy consumption optimization module undertakes key optimization tasks in the substation management system, and effectively reduces the total energy consumption of the substation by dynamically optimizing the equipment operation status and power distribution. The core functions of the module include building an energy consumption objective function and optimizing the power distribution of the equipment, while providing specific optimization suggestions based on the equipment operation status analysis, thereby improving the overall energy utilization efficiency of the system.

[0044] In this embodiment, the energy consumption optimization unit quantifies the total energy consumption of the substation in a given time interval by constructing an energy consumption objective function, and minimizes the objective as the optimization direction. The energy consumption objective function is defined as follows: in: E total It is the total energy consumed by all devices in the system in the time interval [0,T]; Represents the total instantaneous power of all N devices in the substation at time t: Among them, P i (t) is the instantaneous power of the i-th device; P loss (t) is the transmission power loss of the substation at time t, and the calculation formula is: P loss (t) = R·I(t) 2 R is the equivalent resistance, and I(t) is the total system current at time t.

[0045] During the optimization process, the system adjusts the power distribution P of the equipment i (t), while meeting the substation load requirements, the total energy consumption is minimized.

[0046] Optimization calculation method: In order to minimize the energy consumption target, the system uses the gradient descent method to iteratively optimize the power allocation of the equipment: in: is the power of the i-th device after the k+1th iteration; α is the learning rate, which controls the optimization step size; The energy consumption objective function is about the equipment power P i The gradient of is expressed as; Through multiple iterations, the system gradually approaches the optimal power allocation solution to ensure the total energy consumption E total minimize.

[0047] In this embodiment, the operating status analysis unit monitors and analyzes the operating efficiency and load status of the equipment in real time, and provides power allocation suggestions based on the current equipment status. The analysis process mainly involves the following contents: Equipment efficiency evaluation: Based on the collected operating data, the efficiency indicators of the equipment are calculated, including the load rate η(t) and the power factor cosφ, so as to identify equipment with inefficient operation: Outlier:|X(t)-Xavg (t)|>3σ Here, σ is the standard deviation of the data. Load distribution suggestions: Based on the optimization results and equipment operating efficiency, a specific plan for load redistribution between devices is proposed. Prioritize the allocation of loads to equipment with high efficiency and low power consumption to reduce energy waste.

[0048] The dynamic energy consumption optimization module realizes real-time optimization of power distribution for substations through the construction of energy consumption objective functions and operation status analysis. The energy consumption optimization unit ensures that the system meets the load demand with minimum energy consumption, while the operation status analysis unit provides data support and optimization suggestions for the efficient operation of the equipment. The two work together to improve the energy efficiency of the substation management system.

[0049] Please refer to the attached Figure 4 , the hierarchical load control module includes: Hierarchical management unit, used to classify devices into core devices, auxiliary devices, and backup devices, and dynamically manage the device operation status according to priority; The start-stop optimization unit is used to optimize the start-stop strategy of the equipment and minimize the switching frequency of the equipment.

[0050] The start-stop optimization unit uses the following objective function to optimize the number of equipment starts and stops: Where C is the total number of starts and stops of all devices in the system within the time interval [1, T], N is the total number of devices in the system, T is the total number of time steps analyzed or the total number of moments in the time interval, S i (t) is the operating state variable of the i-th device at time t, |S i (t)-S i (t-1)| is the state change of the i-th device between time t and time t-1.

[0051] Specifically, the hierarchical load control module in the substation management system realizes dynamic control of the equipment operation status through hierarchical management and start-stop optimization of the equipment. The module takes reducing the equipment switching frequency and optimizing the equipment operation status as the core goal, and ensures the efficiency and stability of the system operation through classified management of core equipment, auxiliary equipment and spare equipment, combined with the start-stop optimization algorithm.

[0052] In this embodiment, the hierarchical management unit divides the equipment in the substation into three categories according to the operation priority: core equipment, auxiliary equipment and spare equipment: Core equipment: Maintain full-time operation status, serve as the basic load guarantee of the system, and ensure that the substation can operate stably under any working conditions. For example, main transformers and key line switches.

[0053] Auxiliary equipment: Dynamically start and stop according to load demand to provide flexible load support. For example, cooling devices or conditioning equipment.

[0054] Backup equipment: used during peak load or emergency situations to provide load regulation or backup support, such as backup generators or backup line switches.

[0055] Through hierarchical management, the system can reasonably allocate the operating status of various types of equipment according to actual load requirements, reduce ineffective power consumption, and improve the overall operating efficiency of the system.

[0056] Dynamic management method: The hierarchical management unit dynamically adjusts the start and stop status of each device by monitoring the operating status and load requirements of the device in real time: When load demand increases, auxiliary equipment is started first to meet the additional load; When load demand decreases, the backup equipment and auxiliary equipment are shut down in sequence, while the core equipment remains in operation.

[0057] In this embodiment, the start-stop optimization unit optimizes the number of device starts and stops by constructing an objective function, minimizing the frequent switching of devices in the system and reducing energy waste and equipment wear caused by switching. The start-stop optimization objective function is defined as: Where: C is the total number of starts and stops of all devices in the system within the time interval [1, T]; N is the total number of devices in the system; T is the total number of moments in the analysis time interval; S i (t) is the operating state variable of the i-th device at time t: S i (t)-S i (t-1) represents the state change of the i-th device between time t and time t-1: If the value is 1, the device status switches; If the value is 0, the device status remains unchanged.

[0058] By optimizing the objective function C, the start-stop optimization unit can reduce the start-stop frequency of the equipment, thereby reducing energy loss and switching wear during equipment operation.

[0059] Optimization calculation method: The start-stop optimization unit uses dynamic programming to solve the optimal start-stop strategy based on real-time load demand and equipment operating status: Build a state transition model for the equipment start-stop strategy and define the start-stop cost and operation cost; At each time t, the optimal start and stop state of the current equipment is calculated according to the load demand to ensure that the load demand is met while reducing the number of start and stop times; Through recursive iterative calculation, the optimal start and stop plan of the device in the entire time interval is output.

[0060] The hierarchical load control module realizes dynamic hierarchical management and start-stop optimization of equipment through the synergy of the hierarchical management unit and the start-stop optimization unit. The hierarchical management unit reasonably divides the operation priority of the equipment according to the load demand, and the start-stop optimization unit optimizes the start-stop frequency of the equipment through the objective function, reduces the energy waste and wear caused by equipment switching, and improves the operation efficiency and reliability of the substation system.

[0061] Please see attached Figure 5 , the new energy access optimization module includes: Power balancing unit, used to ensure that the power of new energy and traditional energy meets the load balance relationship; The power optimization unit is used to construct the optimization objective function to dynamically adjust the power of new energy.

[0062] The load balance relationship in the power balance unit satisfies the following formula: P load (t) = P new (t)+P trad (t) Among them, P load (t) is the total load power demand of the system at time t, P new (t) is the power provided by the new energy source to the system at time t, P trad (t) is the power provided by the traditional energy to the system at time t; the new energy power optimization unit constructs the power allocation optimization target formula as follows: Where L is the total loss or total cost of the system in the time interval [0, T], is the power loss of the system at time t due to the fluctuation characteristics of new energy, P trad (t) is the power of the system using traditional energy at time t; the power optimization unit uses the Lagrange multiplier method to optimize the power distribution of new energy, the formula is: Among them, P new (t) is the power provided by the new energy to the system at time t, λ is the Lagrange multiplier, and H(t) is the new energy fluctuation coefficient.

[0063] Specifically, the new energy access optimization module realizes the coordinated dispatch of new energy and traditional energy in the substation management system, ensuring that the system gives priority to the use of new energy while meeting the load demand to reduce the cost and carbon emissions of traditional energy. The module ensures real-time supply and demand balance through the power balancing unit, and dynamically adjusts the power allocation ratio of new energy and traditional energy in combination with the power optimization unit to further improve the efficiency of new energy utilization.

[0064] In this embodiment, the power balancing unit dynamically adjusts the power distribution of new energy and traditional energy according to the load demand and the real-time power generation to ensure the power balance of the system. The power balance relationship is expressed as: P load (t) = P new (t)+P trad (t) Where: P load (t) is the total load power demand of the system at time t, P new (t) is the power provided by the new energy source to the system at time t, P trad (t) is the power provided by traditional energy to the system at time t.

[0065] This balance relationship requires the system to allocate the two energy powers in real time to ensure that the load demand is met. At the same time, the system gives priority to the use of new energy power P with less volatility. new (t) to reduce the proportion of traditional energy use.

[0066] In this embodiment, the power optimization unit minimizes the total loss or cost in system operation by constructing an objective function. The optimization objective formula is as follows: Where: L is the total loss or total cost of the system in the time interval [0, T]; H(t) is the new energy fluctuation characteristic coefficient, reflecting the instability of the new energy power generation; P new (t) is the power provided by the new energy at time t; P trad (t) is the power provided by traditional energy at time t.

[0067] There are two main parts to the objective function: Represents the loss cost caused by the volatility of new energy; P trad (t): represents the cost of using traditional energy.

[0068] The optimization goal is to reduce the power output of new energy sources with high volatility, while reducing the use of traditional energy, and balancing the overall economy and stability of the system.

[0069] Optimization calculation method: In order to achieve the optimal allocation of new energy power, the power optimization unit uses the Lagrange multiplier method for optimization. The Lagrange objective function is constructed as: Where: L is the Lagrangian objective function; λ is the Lagrangian multiplier, which is used to adjust the impact of constraints on the optimization objective.

[0070] right About P new (t) Take the partial derivative and set it to zero to obtain the optimal solution: The solution is: This formula shows that the new energy power P new (t) is inversely proportional to the fluctuation coefficient H(t). When H(t) is large (new energy fluctuation is strong), the system reduces the output of new energy; when H(t) is small (new energy fluctuation is weak), the system gives priority to the use of new energy to reduce operating costs.

[0071] The new energy access optimization module realizes the dynamic allocation of new energy and traditional energy through the collaborative work of the power balancing unit and the power optimization unit. The power balancing unit ensures the balance of supply and demand in real time, and the power optimization unit improves the utilization efficiency of new energy and reduces the proportion of traditional energy through objective functions and optimization algorithms, ensuring the stability and economy of system operation. The module design effectively supports the efficient use of green energy and provides optimization support for the substation management system.

[0072] Please see attached Figure 6 ,The multi-timescale scheduling module includes: Short-time scheduling unit for optimizing real-time power distribution; The long-term scheduling unit is used to optimize equipment operation and maintenance plans and build an objective function for long-term energy consumption.

[0073] The short-time dispatch unit uses the following formula to optimize real-time power allocation: Minimize:ΔP=|P load (t)-P gen (t)| Where ΔP is the power imbalance value of the system at time t, P load (t) is the total load power demand of the system at time t, P gen (t) is the total power generation of the system at time t; the long-term energy consumption objective function constructed in the long-term scheduling unit is; Among them, E totalis the total energy consumption of the system in the entire time interval, P i (d) The average power of the i-th device in time period d, t i (d) is the operating time of the i-th equipment in time period d; the equipment maintenance plan formulated by the long-term scheduling unit must meet the following time constraints: Among them, t maint (i) is the maintenance time of equipment i, T max (i) is the maximum allowable maintenance interval.

[0074] Specifically, the multi-time scale dispatch module ensures the stability and efficiency of system operation in the substation management system through real-time response to short-term load fluctuations and global optimization of long-term equipment operation and maintenance. The module is divided into a short-term dispatch unit and a long-term dispatch unit, which work together to solve the problems of real-time load dynamic adjustment and long-term equipment energy consumption management respectively.

[0075] In this embodiment, the short-time dispatching unit mainly adjusts the power generation P in real time to deal with the load fluctuation of the substation on a minute-level time scale. gen (t) to meet the total load demand P load (t), optimize the instantaneous power distribution of the system. The optimization goal is to minimize the power imbalance value ΔP, the formula is: ΔP=|P load (t)-P gen (t)| Where: ΔP is the power imbalance value of the system at time t; P load (t) is the total load power demand of the system at time t; P gen (t) is the total power generated by the system at time t.

[0076] Optimization strategy: The short-term dispatch unit dynamically allocates new energy and traditional energy power, giving priority to new energy power P new (t), supplement the traditional energy power P when new energy is insufficient trad (t) to reduce the deviation of ΔP.

[0077] Specific strategies include: Calculate the load demand P at the current time point load (t); Adjust the power generation P gen (t), give priority to the use of energy output with higher stability; Quickly correct the load supply and demand differences caused by new energy fluctuations to ensure real-time balance of system supply and demand.

[0078] In this embodiment, the long-term scheduling unit constructs a long-term energy consumption objective function by optimizing the equipment operation and maintenance plan to minimize the total system energy consumption in the entire time interval. The long-term energy consumption objective function is: Where: E total is the total energy consumption of the system in the entire time interval; D is the total number of time periods (such as days, weeks or months) into which the time interval is divided; N is the total number of devices in the system; P i (d) is the average power of the i-th device in time period d; t i (d) is the operating time of the i-th device in time period d.

[0079] Optimization constraints for equipment maintenance planning: Long-term scheduling units also need to develop equipment maintenance plans to ensure the healthy operation of the equipment and comply with the following time constraints: t maint (i)≤T max (i) in: t maint (i): maintenance time of equipment i; T max (i): The maximum permissible maintenance interval for equipment i.

[0080] Through this constraint, the system can reasonably plan the operation and maintenance time of each device to avoid losses caused by excessive operation of the equipment or failures caused by insufficient maintenance.

[0081] Optimization strategy: Combine load forecast data and equipment operation history to allocate equipment operation time t i (d) and power P i (d); Dynamically adjust maintenance schedules to avoid scheduling maintenance of critical equipment during high-load periods; Optimize equipment rotation strategy, balance equipment load, and extend equipment service life.

[0082] The multi-time scale dispatch module realizes efficient operation of substations under dynamic load conditions and intelligent management of equipment maintenance plans through real-time response of short-time dispatch units and global optimization of long-time dispatch units. The short-time dispatch unit quickly responds to load fluctuations to ensure the balance of system supply and demand; the long-time dispatch unit optimizes equipment operation and maintenance plans from a global perspective, reducing long-term energy consumption and extending equipment life. This multi-time scale collaborative optimization design provides reliable guarantee for system operation.

[0083] Working principle: When the system is running, the sensors and smart meters deployed in the data acquisition and monitoring module first collect the operating data of the substation equipment in real time, including voltage, current, power, temperature, load rate, etc. After noise reduction, normalization and outlier detection, the collected data forms high-quality time series data, and the operating status of the equipment is displayed through a visual interface. These data provide real-time input for the optimization module as the basis for optimization calculations.

[0084] In the process of dynamic energy consumption optimization, the system analyzes the operating power and status of each device in real time, builds energy consumption optimization targets, and adjusts the power distribution of the equipment to the optimal state, thereby reducing the total energy consumption of the entire substation. This optimization not only takes into account the operating requirements of the equipment, but also dynamically adjusts the loss parameters in transmission to achieve energy saving.

[0085] The hierarchical load control module manages the operating status of the equipment according to its importance. The core equipment runs continuously to ensure the stability of the system; the auxiliary equipment starts and stops dynamically according to the load demand, and the backup equipment is only started when the load is peak. By optimizing the frequency of equipment start and stop, this module reduces the energy consumption and wear caused by equipment switching, while improving the operating efficiency of the equipment.

[0086] When the system is connected to new energy, the new energy access optimization module dynamically adjusts the power allocation ratio of new energy and traditional energy according to the real-time load demand and new energy fluctuations. The system gives priority to the use of new energy, smoothes the power loss caused by its fluctuations, and reduces the use of traditional energy, reducing the overall operating cost. This module effectively improves the utilization rate of new energy while ensuring the stable satisfaction of load demand.

[0087] In terms of scheduling, the system dynamically adjusts power distribution in a short time scale through collaborative optimization of multiple time scales to ensure a balance between real-time load demand and actual power supply; it formulates equipment operation and maintenance plans in a long time scale to ensure that each device is maintained as planned, thereby extending equipment life and improving system reliability.

[0088] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A substation management system, characterized in that: include: Data acquisition and monitoring module, used to collect operating data of equipment in the substation, monitor the operating status of equipment and pre-process the data; Dynamic energy consumption optimization module, used to optimize equipment operating status and power distribution to reduce the total energy consumption of the substation; The hierarchical load control module is used to manage the equipment in the substation in a hierarchical manner according to priority, and optimize the operation of the equipment through dynamic start and stop; the new energy access optimization module is used to dynamically adjust the power distribution ratio of new energy and traditional energy according to the real-time power fluctuations of the two; A multi-timescale scheduling module is used to respond to load fluctuations in the short timescale and formulate equipment operation and maintenance plans in the long timescale.

2. A substation management system according to claim 1, characterized in that: The data acquisition and monitoring module includes: Data acquisition device, used to collect voltage, current, power, temperature and load rate parameters of the equipment; A data preprocessing unit, used for noise reduction, normalization and outlier detection of the collected data; The monitoring unit is used to display the equipment operation status in real time and provide visual analysis.

3. A substation management system according to claim 1, characterized in that: The dynamic energy consumption optimization module includes: Energy consumption optimization unit, used to construct energy consumption objective function and optimize the total energy consumption of the substation; The operating status analysis unit is used to analyze the operating efficiency of the equipment and provide power allocation suggestions.

4. A substation management system according to claim 3, characterized in that: The energy consumption objective function constructed by the energy consumption optimization unit is: Among them, E total is the total energy consumed by all devices in the system during the time interval, is the sum of the instantaneous power of all N devices in the substation at time t, P i (t) is the instantaneous power of the i-th device at time t, P loss (t) is the transmission power loss of the substation at time t.

5. A substation management system according to claim 1, characterized in that: The hierarchical load regulation module includes: Hierarchical management unit, used to classify devices into core devices, auxiliary devices, and backup devices, and dynamically manage the device operation status according to priority; The start-stop optimization unit is used to optimize the start-stop strategy of the equipment and minimize the switching frequency of the equipment.

6. A substation management system according to claim 5, characterized in that: The start-stop optimization unit uses the following objective function to optimize the number of equipment starts and stops: Where C is the total number of starts and stops of all devices in the system within the time interval [1, T], N is the total number of devices in the system, T is the total number of time steps analyzed or the total number of moments in the time interval, S i (t) is the operating state variable of the i-th device at time t, |S i (t)-S i (t-1)| is the state change of the i-th device between time t and time t-1.

7. A substation management system according to claim 1, characterized in that: The new energy access optimization module includes: Power balancing unit, used to ensure that the power of new energy and traditional energy meets the load balance relationship; The power optimization unit is used to construct the optimization objective function to dynamically adjust the power of new energy.

8. A substation management system according to claim 7, characterized in that: The load balance relationship in the power balance unit satisfies the following formula: P load (t)=P new (t)+P trad (t) Among them, P load (t) is the total load power demand of the system at time t, P new (t) is the power provided by the new energy source to the system at time t, P trad (t) is the power provided by the traditional energy to the system at time t; the new energy power optimization unit constructs the power allocation optimization target formula as follows: Where L is the total loss or total cost of the system in the time interval [0, T], H(t)·P n 2 ew (t) is the power loss of the system at time t due to the fluctuation characteristics of new energy, P trad (t) is the power of the system using traditional energy at time t; the power optimization unit uses the Lagrange multiplier method to optimize the new energy power distribution, the formula is: Among them, P new (t) is the power provided by the new energy to the system at time t, λ is the Lagrange multiplier, and H(t) is the new energy fluctuation coefficient.

9. A substation management system according to claim 1, characterized in that: The multi-timescale scheduling module includes: Short-time scheduling unit for optimizing real-time power distribution; The long-term scheduling unit is used to optimize equipment operation and maintenance plans and build an objective function for long-term energy consumption.

10. A substation management system according to claim 9, characterized in that: The short-time scheduling unit uses the following formula to optimize real-time power allocation: Minimize:ΔP=|P load (t)-P gen (t)| Where ΔP is the power imbalance value of the system at time t, P load (t) is the total load power demand of the system at time t, P gen (t) is the total power generation of the system at time t; the long-term energy consumption objective function constructed in the long-term scheduling unit is; Among them, E total is the total energy consumption of the system in the entire time interval, P i (d) The average power of the i-th device in time period d, t i (d) is the operating time of the i-th device in time period d; the equipment maintenance plan formulated by the long-term scheduling unit must meet the following time constraints: Among them, t maint (i) is the maintenance time of equipment i, T max (i) is the maximum allowable maintenance interval.

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