CN119765522A - An optimal dispatching method for AC/DC flexible interconnected distribution network - Google Patents
An optimal dispatching method for AC/DC flexible interconnected distribution network Download PDFInfo
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Abstract
本发明公开了一种交直流柔性互联配电网络优化调度方法，首先深入分析分布式电源不确定性、负荷动态变化和柔性直流设备特性等考虑因素；接着设定运行成本最小化、能源利用效率最大化、电能质量最优和可靠性最高的目标；再在调度策略上，采用分层分区调度实现区域内平衡与跨区域功率交换，运用多智能体协同调度让各单元智能协作，通过实时优化根据实时数据调整方案；然后算法选择上构建遗传算法与深度学习算法结合的混合智能算法，并不断优化改进；最后建立协调控制机制，确保柔性直流与传统交流系统有效配合；本发明可更加有效地应对交直流柔性互联配电网面临的新需求和新挑战，从而实现交直流柔性互联配电网的安全、稳定、高效运行。
The present invention discloses an optimization scheduling method for an AC/DC flexible interconnected distribution network. First, the uncertainty of distributed power sources, dynamic changes in loads, and characteristics of flexible DC equipment are deeply analyzed. Then, the goals of minimizing operating costs, maximizing energy utilization efficiency, optimizing power quality, and maximizing reliability are set. In terms of scheduling strategy, hierarchical and partitioned scheduling is adopted to achieve regional balance and cross-regional power exchange, and multi-agent collaborative scheduling is used to allow each unit to collaborate intelligently, and the plan is adjusted according to real-time data through real-time optimization. Then, a hybrid intelligent algorithm combining a genetic algorithm and a deep learning algorithm is constructed in algorithm selection, and continuously optimized and improved. Finally, a coordinated control mechanism is established to ensure effective cooperation between flexible DC and traditional AC systems. The present invention can more effectively respond to new demands and challenges faced by AC/DC flexible interconnected distribution networks, thereby achieving safe, stable, and efficient operation of AC/DC flexible interconnected distribution networks.
Description
Technical Field
The invention belongs to the technical field of alternating current-direct current flexible interconnection power distribution networks, and particularly relates to an alternating current-direct current flexible interconnection power distribution network optimization scheduling method.
Background
The flexible direct current technology is fully integrated with the existing alternating current network, and the construction of an alternating current-direct current hybrid power distribution network is a new development trend. In recent years, a plurality of research institutions at home and abroad develop research on an architecture system of an alternating current-direct current flexible interconnection power distribution network, and technical progress and local application are achieved. The system is divided into a leather network, a nano network, a micro network and a sub network according to voltage grades, wherein the network systems are connected through flexible interconnection equipment, an alternating current-direct current hybrid micro network system constructed by Mitsubishi corporation of Japan is connected with an external alternating current system through a bypass standby line in addition to power supply through a direct current bus so as to improve power supply reliability, an off-grid micro network system designed by Zhejiang province electric power test institute adopts an alternating current-direct current hybrid power network structure, and a flexible interconnection device is used for forming a bipolar +/-10 kV direct current bus so as to interconnect two 110kV substations and the like.
At present, aiming at the application of the flexible direct current technology in the urban power distribution network, the flexible direct current technology is mainly focused on the practical key equipment for constructing an alternating current-direct current hybrid power distribution network and a series of key technologies such as planning design, coordination control and optimal scheduling technology are not formed into a systematic theory and technology system, and the optimal scheduling of the power distribution network by increasingly developed large-scale distributed power supplies, electric automobiles, direct current loads and the like is also provided with new demands and new challenges.
In order to solve the above problems, it is necessary to develop an optimal scheduling method for an ac/dc flexible interconnection power distribution network.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides an alternating current-direct current flexible interconnection power distribution network optimization scheduling method which can more effectively cope with new requirements and new challenges faced by an alternating current-direct current flexible interconnection power distribution network, thereby realizing safe, stable and efficient operation of the alternating current-direct current flexible interconnection power distribution network.
The invention aims to realize the optimal scheduling method of the alternating current-direct current flexible interconnection power distribution network, which comprises the following steps:
Step A, considering the key characteristics of the alternating current-direct current flexible interconnection power distribution network, namely the uncertainty of a distributed power supply, the dynamic change of load and the characteristics of flexible direct current equipment, and analyzing in detail;
Setting a target, namely setting a target for optimizing scheduling according to the previous consideration after the actual condition of the power grid is clear;
Step C, a scheduling strategy is established based on the set target and considered factors, and the specific scheduling strategy comprises hierarchical partition scheduling and multi-agent cooperative scheduling;
Step D, algorithm selection, namely selecting a hybrid intelligent algorithm to realize solving of an optimal scheduling scheme on the basis of determining a scheduling strategy, and providing calculation and data support for the scheduling strategy by utilizing the global searching capability of a genetic algorithm and the prediction capability of a deep learning algorithm;
And E, coordination control, namely establishing a coordination control mechanism on the basis of the target setting, the scheduling strategy and the algorithm selection, ensuring effective coordination between the flexible direct current system and the traditional alternating current system, and enabling the power grid to stably operate.
Preferably, the step a specifically includes:
(1) Analyzing distributed power supply uncertainty in detail:
firstly, collecting historical meteorological data and distributed power supply output data, establishing a distributed power supply output prediction model based on time sequence analysis and a machine learning algorithm, and predicting the output of the distributed power supply in short term and medium term by using the prediction model, wherein the prediction time span can cover several hours to several days in the future;
Then, determining probability distribution of distributed power output according to a prediction result, and obtaining probability density functions of distributed power output in different time periods through multiple simulation predictions so as to consider various possible output conditions in scheduling;
(2) Load dynamic changes are studied in depth:
firstly, installing intelligent ammeter equipment, collecting load data in real time, analyzing time sequence characteristics, seasonal changes and user behavior patterns of the load by utilizing a big data analysis technology, and finding out load change rules of weekdays and weekends and different seasons and electricity utilization characteristics of certain specific user groups by analyzing historical load data;
Then, by combining with economic development trend and population growth factors, predicting future load growth, predicting load growth trend in the next years, and providing reference for power grid planning and scheduling;
(3) Comprehensively understand the characteristics of the flexible direct current equipment:
Firstly, performing performance test and modeling on key equipment of a flexible direct current system, measuring efficiency, response time and power adjustment range parameters of each equipment, and establishing an accurate equipment mathematical model so as to accurately consider operation limit and performance characteristics of the equipment in scheduling;
And then, researching the interaction effect of the flexible direct current system and the alternating current system, analyzing the influence of reactive power injected into the alternating current system by the flexible direct current system on alternating current voltage and the impact of the fault of the alternating current system on the flexible direct current system, and providing a basis for coordination control.
Preferably, the step B specifically includes:
(1) The running cost is minimized:
firstly, a power generation cost model is established, the fuel cost, maintenance cost and carbon emission cost of different power supplies are considered, and the fuel cost and equipment maintenance cost of the traditional thermal power generation are calculated;
then, optimizing the operation strategy of the equipment, and reducing the equipment loss;
(2) Energy utilization efficiency maximization:
Firstly, establishing an energy efficiency index, and comprehensively evaluating the energy utilization efficiency of the whole power distribution network;
then, optimizing the power flow distribution, and reducing the line loss;
(3) The electric energy quality is optimal:
firstly, setting voltage fluctuation and frequency stability indexes, and timely adjusting power output and reactive compensation equipment by monitoring the voltage and frequency of a power grid in real time to ensure that the quality of electric energy meets the requirements;
Then, advanced power electronic equipment and control technology are adopted to inhibit harmonic waves and voltage flicker and improve the electric energy quality;
(4) The reliability is highest:
Firstly, establishing a reliability index system, including power supply reliability, equipment reliability and system stability, and evaluating the reliability level of a power grid;
then, the fault handling strategy is optimized, and the fault isolation and recovery speed is improved.
Preferably, the step C specifically includes:
(1) Hierarchical partition scheduling:
Firstly, dividing a power distribution network into a plurality of areas according to the topological structure and load distribution of a power grid, setting up an area control center in each area, and taking charge of power supply scheduling, load management and equipment monitoring in the area, wherein each area is provided with an area control system;
Then, local distributed power supplies and energy storage equipment are preferentially scheduled in the area to meet the local load requirement, and when the output force of the local distributed power supplies is larger than the load requirement, redundant electric energy can be stored in the local energy storage equipment or is conveyed to other areas through a flexible direct current system;
Finally, power exchange is carried out through a flexible direct current system across regions, so that global optimization is realized;
(2) Multi-agent co-scheduling:
Firstly, a power supply, a load, energy storage equipment and a flexible direct current system are regarded as different intelligent agents, each intelligent agent has autonomous decision making and communication capability, and corresponding decision making can be made according to self state and surrounding environment information;
then, establishing a communication mechanism between the intelligent agents to realize information sharing and collaborative decision-making;
finally, a distributed optimization algorithm is utilized to realize the cooperative scheduling of multiple agents;
(3) And (3) real-time optimization:
firstly, a real-time monitoring system is established, voltage, current and power parameters of a power grid are collected and analyzed in real time, and operation data of the power grid are transmitted to a dispatching center in real time, so that a dispatcher can grasp the operation state of the power grid in time;
Then, according to the real-time monitoring data, the scheduling scheme is adjusted in real time by utilizing a rapid optimization algorithm, and according to the current power grid state and the prediction condition of a period of time in the future, the optimal scheduling scheme is rapidly calculated and is issued to each intelligent agent for execution in time;
And finally, considering the coping strategy of the emergency, and improving the strain capacity of the power grid.
Preferably, the step D specifically includes:
(1) And (3) constructing a hybrid intelligent algorithm:
Firstly, combining the advantages of a genetic algorithm and a deep learning algorithm to construct a hybrid intelligent algorithm;
then, determining a coding mode, an fitness function and genetic operation parameters of a genetic algorithm;
finally, a distributed power output and load prediction model is established by using a deep learning algorithm, historical data is trained, and distributed power output and load requirements in a future period of time are predicted;
(2) Optimization and improvement of algorithm:
firstly, in order to improve the solving efficiency and precision of the algorithm, the hybrid intelligent algorithm can be optimized and improved;
then, a simulated annealing and tabu search local search algorithm is introduced, and the local search capability of the algorithm is improved by combining with a genetic algorithm.
Preferably, the step E specifically includes:
(1) Establishing a coordination control mechanism:
firstly, formulating a coordination control strategy, and defining a coordination control mode between a flexible direct current system and a traditional alternating current system;
Then, a communication network is established to realize information interaction between the flexible direct current system and the traditional communication system;
finally, a coordination controller is designed to realize unified control of the flexible direct current system and the traditional alternating current system;
(2) Implementation of coordination control:
under the normal operation condition, the coordination controller automatically adjusts the power output of the flexible direct current system and the operation parameters of the traditional alternating current system according to the load demand of the power grid and the output condition of the distributed power supply, so as to realize optimal power flow distribution and power quality control;
under the fault condition, the coordination controller rapidly starts a fault response strategy to realize fault isolation and recovery.
The method has the beneficial effects that the method firstly deeply analyzes the considerations such as uncertainty of a distributed power supply, dynamic change of load, characteristics of flexible direct current equipment and the like, then sets the targets of minimum running cost, maximum energy utilization efficiency, optimal power quality and highest reliability, and then adopts layered partition scheduling to realize balance and cross-regional power exchange in a region on a scheduling strategy, intelligent cooperation of each unit is realized by multi-agent cooperative scheduling according to a real-time data adjustment scheme through real-time optimization, then the algorithm is selected to construct a hybrid intelligent algorithm combining a genetic algorithm and a deep learning algorithm, the hybrid intelligent algorithm is optimized and improved continuously, finally, a coordination control mechanism is established to ensure that the flexible direct current is matched with the traditional alternating current system effectively, and new requirements and new challenges faced by an alternating current and direct current flexible interconnection power distribution network can be met more effectively, so that safe, stable and efficient operation of the alternating current and direct current flexible interconnection power distribution network is realized.
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FIG. 1 is a schematic flow chart of the method of the present invention.
Detailed Description
The technical scheme of the invention is further specifically described below through examples and with reference to the accompanying drawings.
As shown in FIG. 1, the invention aims to realize the optimal scheduling method of the alternating current-direct current flexible interconnection power distribution network, which comprises the following steps:
And step A, considering the key characteristics of the alternating current-direct current flexible interconnection power distribution network, namely the uncertainty of a distributed power supply, the dynamic change of load and the characteristics of flexible direct current equipment, and carrying out detailed analysis.
(1) Analyzing distributed power supply uncertainty in detail:
Historical meteorological data and distributed power output data are collected, and a distributed power output prediction model based on time sequence analysis and a machine learning algorithm is established. For example, the LSTM long-term memory network can be used for short-term and medium-term prediction of the output of a distributed power source such as solar energy, wind energy and the like, and the prediction time span can cover a plurality of hours to a plurality of days in the future.
And determining the probability distribution of the distributed power supply output according to the prediction result. For example, the probability density function of distributed power source output over different time periods may be derived through multiple simulated predictions to account for various possible output scenarios in scheduling.
(2) Load dynamic changes are studied in depth:
And installing intelligent ammeter and other equipment, collecting load data in real time, and analyzing the time sequence characteristics, seasonal change, user behavior patterns and the like of the load by utilizing a big data analysis technology. For example, the load change laws of weekdays and weekends, different seasons, and the electricity usage characteristics of certain specific user groups (e.g., industrial users, business congestion) can be found by analyzing the historical load data.
And predicting future load increase by combining factors such as economic development trend, population increase and the like. For example, load growth trend in the next years can be estimated according to local economic development planning and population growth prediction, and reference can be provided for power grid planning and scheduling.
(3) Comprehensively understand the characteristics of the flexible direct current equipment:
And performing performance test and modeling on key equipment such as converters, circuit breakers and the like of the flexible direct current system. For example, parameters such as efficiency, response time, power regulation range, etc. of the inverter may be measured, and an accurate mathematical model of the equipment may be built to accurately account for operational limitations and performance characteristics of the equipment in the scheduling.
The interaction effect of the flexible direct current system and the alternating current system is studied. For example, the influence of reactive power injected into the alternating current system by the flexible direct current system on alternating current voltage, impact of faults of the alternating current system on the flexible direct current system and the like can be analyzed, and basis is provided for coordination control.
And B, setting a target, namely setting a target for optimizing scheduling according to the previous consideration after the actual condition of the power grid is clear.
(1) The running cost is minimized:
And (3) establishing a power generation cost model, and considering fuel cost, maintenance cost, carbon emission cost and the like of different power supplies. For example, for traditional thermal power generation, the fuel cost and equipment maintenance cost are calculated, and for distributed renewable energy, the equipment investment cost and the operation maintenance cost are considered, and the renewable energy subsidy policy factors are considered.
Optimizing the operation strategy of the equipment and reducing the equipment loss. For example, switching of the transformer can be reasonably arranged, the transformer is prevented from running under the low-voltage load rate, no-load loss of the transformer is reduced, power regulation of the flexible direct current system can be optimized, and switching loss of the converter is reduced.
(2) Energy utilization efficiency maximization:
And establishing energy efficiency indexes including energy conversion efficiency, transmission efficiency, terminal utilization efficiency and the like. For example, the power generation efficiency of the distributed power supply, the transmission efficiency of the power grid and the energy utilization efficiency of the user terminal equipment can be calculated, and the energy utilization efficiency of the whole power distribution network can be comprehensively estimated.
And the power flow distribution is optimized, and the line loss is reduced. For example, the power flow direction and the power flow of the flexible direct current system can be adjusted, so that the power flow is distributed in the power grid more reasonably, the line resistance loss is reduced, the power factor of the power grid can be optimized by using reactive compensation equipment, the reactive power transmission is reduced, and the energy utilization efficiency is improved.
(3) The electric energy quality is optimal:
Voltage fluctuation and frequency stability indexes are set. For example, the voltage fluctuation range can be regulated to be within +/-5%, the frequency deviation is within +/-0.2 Hz, and then the power output and reactive compensation equipment are timely adjusted by monitoring the voltage and frequency of the power grid in real time, so that the power quality is ensured to meet the requirements.
Advanced power electronics and control techniques are employed to suppress harmonics and voltage flicker. For example, devices such as an active filter, a dynamic voltage restorer and the like can be installed at a distributed power access point and an important load, so that harmonic waves and voltage flicker are effectively eliminated, and the power quality is improved.
(4) The reliability is highest:
And establishing a reliability index system comprising power supply reliability, equipment reliability, system stability and the like. For example, the system's average outage time, average outage frequency, and equipment failure rate may be calculated to evaluate the reliability level of the grid.
And the fault handling strategy is optimized, and the fault isolation and recovery speed is improved. For example, the rapid control capability of the flexible direct current system can be utilized to rapidly isolate a fault area when a fault occurs, and power supply can be recovered as soon as possible by means of load transfer, standby power supply starting and the like.
And C, a scheduling strategy is established based on the set target and considered factors, and the scheduling strategy specifically comprises hierarchical partition scheduling and multi-agent cooperative scheduling.
(1) Hierarchical partition scheduling:
According to the topological structure and load distribution of the power grid, the power distribution network is divided into a plurality of areas, and each area is provided with an area control center which is responsible for power supply dispatching, load management, equipment monitoring and the like in the area. For example, a power distribution network of a city may be divided into administrative or power supply areas, each of which is equipped with a set of regional control systems.
And in the area, the local distributed power supply and the energy storage equipment are preferentially scheduled to meet the local load requirement. For example, when the output force of the local distributed power supply is larger than the load demand, the redundant electric energy can be stored in the local energy storage device or is transmitted to other areas through the flexible direct current system, and when the output force of the local distributed power supply is insufficient, the local energy storage device is preferentially called to discharge or the electric energy is introduced from other areas.
And power exchange is carried out through a flexible direct current system in a cross-region manner, so that global optimization is realized. For example, when the load of a certain area suddenly increases and the local power supply cannot meet the requirement, the power support between the areas can be realized by introducing electric energy from adjacent areas through a flexible direct current system.
(2) Multi-agent co-scheduling:
The power supply, the load, the energy storage equipment, the flexible direct current system and the like are regarded as different intelligent agents, each intelligent agent has autonomous decision making and communication capability, and corresponding decision making can be made according to the state and surrounding environment information of the intelligent agent. For example, the distributed energy intelligent agent can decide whether to supply power to the power grid according to the self-processing condition and market price information, and the load intelligent agent can adjust the power consumption behavior according to the self-demand and the power grid power supply condition.
And establishing a communication mechanism between the intelligent agents, and realizing information sharing and collaborative decision-making. For example, through wireless communication network or power line communication technology, the intelligent agents can exchange data such as power demand, price information, equipment state and the like in real time, and negotiate together to formulate an optimal scheduling scheme.
And the cooperative scheduling of multiple agents is realized by using a distributed optimization algorithm. For example, a distributed particle swarm optimization algorithm or a distributed genetic algorithm can be adopted, so that each intelligent agent performs optimization calculation locally and gradually converges to a global optimal solution through an information interaction and coordination mechanism.
(3) And (3) real-time optimization:
And establishing a real-time monitoring system, collecting and analyzing parameters such as voltage, current and power of the power grid in real time, and transmitting operation data of the power grid to a dispatching center in real time so as to enable a dispatcher to grasp the operation state of the power grid in time.
And according to the real-time monitoring data, utilizing a rapid optimization algorithm to adjust the scheduling scheme in real time. For example, a model predictive control algorithm or an online optimization algorithm can be adopted, and an optimal scheduling scheme can be rapidly calculated according to the current power grid state and the predicted condition of a future period of time and then is issued to each intelligent agent for execution.
And the coping strategy of the emergency is considered, so that the strain capacity of the power grid is improved. For example, when the distributed power supply suddenly fails or the load suddenly increases, the scheduling system may quickly start the standby power supply or adjust the power output of the flexible direct current system to maintain the stable operation of the power grid.
And D, selecting an algorithm, namely selecting a hybrid intelligent algorithm to realize solving an optimal scheduling scheme on the basis of determining a scheduling strategy, and providing calculation and data support for the scheduling strategy by utilizing the global searching capability of a genetic algorithm and the prediction capability of a deep learning algorithm.
(1) And (3) constructing a hybrid intelligent algorithm:
And combining the advantages of the genetic algorithm and the deep learning algorithm to construct the hybrid intelligent algorithm. The genetic algorithm has the characteristics of strong global searching capability, good robustness and the like, can be used for searching an optimal scheduling scheme, has strong data analysis and prediction capability, can be used for predicting the output and load of a distributed power supply, and provides data support for scheduling.
And determining parameters such as a coding mode, an fitness function, genetic operation and the like of the genetic algorithm. For example, a binary coding mode can be adopted to represent the scheduling scheme as a string of binary character strings, the fitness function can be constructed according to a comprehensive objective function determined by objective setting, the quality of the scheduling scheme is measured, and the genetic operation can comprise selection, crossover, mutation and the like, and the optimal scheduling scheme is found through continuous iterative evolution.
And establishing a distributed power output and load prediction model by using a deep learning algorithm. For example, deep learning models such as CNN convolutional neural networks or RNN convolutional neural networks can be used to train historical data and predict distributed power output and load requirements over a period of time in the future.
(2) Optimization and improvement of algorithm:
In order to improve the solving efficiency and precision of the algorithm, the hybrid intelligent algorithm can be optimized and improved. For example, parallel computing technology can be adopted to accelerate the searching speed of the genetic algorithm, self-adaptive learning rate and other technologies can be adopted to improve the training effect of deep learning.
And a simulated annealing and tabu search local search algorithm is introduced, and the local search capability of the algorithm is improved by combining with a genetic algorithm. For example, in the evolution process of the genetic algorithm, when the fitness value of a certain individual is better, a simulated annealing algorithm or a tabu search algorithm can be adopted to locally optimize the individual, so that the quality of a scheduling scheme is further improved.
And E, coordination control, namely establishing a coordination control mechanism on the basis of the target setting, the scheduling strategy and the algorithm selection, ensuring effective coordination between the flexible direct current system and the traditional alternating current system, and enabling the power grid to stably operate.
(1) Establishing a coordination control mechanism:
And (3) formulating a coordination control strategy to define a coordination control mode between the flexible direct current system and the traditional alternating current system. For example, a master-slave control mode, a peer-to-peer control mode or a layered control mode can be adopted, and a proper coordination control strategy is selected according to the actual condition and the operation requirement of the power grid.
And establishing a communication network to realize information interaction between the flexible direct current system and the traditional alternating current system. For example, high-speed optical fiber communication networks or wireless communication techniques may be employed to ensure real-time and reliable transmission of information.
And designing a coordination controller to realize unified control of the flexible direct current system and the traditional alternating current system. For example, advanced control technologies such as a fuzzy controller, a neural network controller and the like can be adopted, and the coordination control can be realized according to the operation state of a power grid and the operation parameters of a traditional alternating current system and an automatic flexible direct current system.
(2) Implementation of coordination control:
Under the normal running condition, the coordination controller automatically adjusts the power output of the flexible direct current system and the running parameters of the traditional alternating current system according to the load demand of the power grid and the output condition of the distributed power supply, so as to realize optimal power flow distribution and power quality control. For example, when the distributed power supply output is large, the coordination controller can transmit the redundant electric energy to other areas through the flexible direct current system or store the redundant electric energy in the energy storage device, and when the load demand is large, the coordination controller can call the energy storage device to discharge or introduce the electric energy from other areas through the flexible direct current system.
Under the fault condition, the coordination controller rapidly starts a fault response strategy to realize fault isolation and recovery. For example, when the AC system fails, the coordination controller can rapidly cut off the connection between the failure area and the flexible DC system to avoid failure diffusion, and meanwhile, the power supply recovery of the non-failure area is realized through the rapid control capability of the flexible DC system.
In summary, the optimal scheduling method can more effectively meet new requirements and new challenges of the alternating current-direct current flexible interconnection power distribution network, and realize safe, stable and efficient operation of the alternating current-direct current flexible interconnection power distribution network.
Finally, it should be noted that the above-mentioned embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same, and although the present invention has been described in detail with reference to the above-mentioned embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the specific embodiments of the present invention without departing from the spirit and scope of the present invention, and any modifications and equivalents are intended to be encompassed in the scope of the claims of the present invention.
Claims (6)
1. An alternating current-direct current flexible interconnection power distribution network optimization scheduling method is characterized by comprising the following steps:
Step A, considering the key characteristics of the alternating current-direct current flexible interconnection power distribution network, namely the uncertainty of a distributed power supply, the dynamic change of load and the characteristics of flexible direct current equipment, and analyzing in detail;
Setting a target, namely setting a target for optimizing scheduling according to the previous consideration after the actual condition of the power grid is clear;
Step C, a scheduling strategy is established based on the set target and considered factors, and the specific scheduling strategy comprises hierarchical partition scheduling and multi-agent cooperative scheduling;
Step D, algorithm selection, namely selecting a hybrid intelligent algorithm to realize solving of an optimal scheduling scheme on the basis of determining a scheduling strategy, and providing calculation and data support for the scheduling strategy by utilizing the global searching capability of a genetic algorithm and the prediction capability of a deep learning algorithm;
And E, coordination control, namely establishing a coordination control mechanism on the basis of the target setting, the scheduling strategy and the algorithm selection, ensuring effective coordination between the flexible direct current system and the traditional alternating current system, and enabling the power grid to stably operate.
2. The method for optimal scheduling of the ac/dc flexible interconnection power distribution network according to claim 1, wherein the step a specifically includes:
(1) Analyzing distributed power supply uncertainty in detail:
firstly, collecting historical meteorological data and distributed power supply output data, establishing a distributed power supply output prediction model based on time sequence analysis and a machine learning algorithm, and predicting the output of the distributed power supply in short term and medium term by using the prediction model, wherein the prediction time span can cover several hours to several days in the future;
Then, determining probability distribution of distributed power output according to a prediction result, and obtaining probability density functions of distributed power output in different time periods through multiple simulation predictions so as to consider various possible output conditions in scheduling;
(2) Load dynamic changes are studied in depth:
firstly, installing intelligent ammeter equipment, collecting load data in real time, analyzing time sequence characteristics, seasonal changes and user behavior patterns of the load by utilizing a big data analysis technology, and finding out load change rules of weekdays and weekends and different seasons and electricity utilization characteristics of certain specific user groups by analyzing historical load data;
Then, by combining with economic development trend and population growth factors, predicting future load growth, predicting load growth trend in the next years, and providing reference for power grid planning and scheduling;
(3) Comprehensively understand the characteristics of the flexible direct current equipment:
Firstly, performing performance test and modeling on key equipment of a flexible direct current system, measuring efficiency, response time and power adjustment range parameters of each equipment, and establishing an accurate equipment mathematical model so as to accurately consider operation limit and performance characteristics of the equipment in scheduling;
And then, researching the interaction effect of the flexible direct current system and the alternating current system, analyzing the influence of reactive power injected into the alternating current system by the flexible direct current system on alternating current voltage and the impact of the fault of the alternating current system on the flexible direct current system, and providing a basis for coordination control.
3. The method for optimal scheduling of the ac/dc flexible interconnection power distribution network according to claim 1, wherein the step B specifically comprises:
(1) The running cost is minimized:
firstly, a power generation cost model is established, the fuel cost, maintenance cost and carbon emission cost of different power supplies are considered, and the fuel cost and equipment maintenance cost of the traditional thermal power generation are calculated;
then, optimizing the operation strategy of the equipment, and reducing the equipment loss;
(2) Energy utilization efficiency maximization:
Firstly, establishing an energy efficiency index, and comprehensively evaluating the energy utilization efficiency of the whole power distribution network;
then, optimizing the power flow distribution, and reducing the line loss;
(3) The electric energy quality is optimal:
firstly, setting voltage fluctuation and frequency stability indexes, and timely adjusting power output and reactive compensation equipment by monitoring the voltage and frequency of a power grid in real time to ensure that the quality of electric energy meets the requirements;
Then, advanced power electronic equipment and control technology are adopted to inhibit harmonic waves and voltage flicker and improve the electric energy quality;
(4) The reliability is highest:
Firstly, establishing a reliability index system, including power supply reliability, equipment reliability and system stability, and evaluating the reliability level of a power grid;
then, the fault handling strategy is optimized, and the fault isolation and recovery speed is improved.
4. The method for optimal scheduling of the ac/dc flexible interconnection power distribution network according to claim 1, wherein the step C is specifically:
(1) Hierarchical partition scheduling:
Firstly, dividing a power distribution network into a plurality of areas according to the topological structure and load distribution of a power grid, setting up an area control center in each area, and taking charge of power supply scheduling, load management and equipment monitoring in the area, wherein each area is provided with an area control system;
Then, local distributed power supplies and energy storage equipment are preferentially scheduled in the area to meet the local load requirement, and when the output force of the local distributed power supplies is larger than the load requirement, redundant electric energy can be stored in the local energy storage equipment or is conveyed to other areas through a flexible direct current system;
Finally, power exchange is carried out through a flexible direct current system across regions, so that global optimization is realized;
(2) Multi-agent co-scheduling:
Firstly, a power supply, a load, energy storage equipment and a flexible direct current system are regarded as different intelligent agents, each intelligent agent has autonomous decision making and communication capability, and corresponding decision making can be made according to self state and surrounding environment information;
then, establishing a communication mechanism between the intelligent agents to realize information sharing and collaborative decision-making;
finally, a distributed optimization algorithm is utilized to realize the cooperative scheduling of multiple agents;
(3) And (3) real-time optimization:
firstly, a real-time monitoring system is established, voltage, current and power parameters of a power grid are collected and analyzed in real time, and operation data of the power grid are transmitted to a dispatching center in real time, so that a dispatcher can grasp the operation state of the power grid in time;
Then, according to the real-time monitoring data, the scheduling scheme is adjusted in real time by utilizing a rapid optimization algorithm, and according to the current power grid state and the prediction condition of a period of time in the future, the optimal scheduling scheme is rapidly calculated and is issued to each intelligent agent for execution in time;
And finally, considering the coping strategy of the emergency, and improving the strain capacity of the power grid.
5. The method for optimal scheduling of the ac/dc flexible interconnection power distribution network according to claim 1, wherein the step D specifically comprises:
(1) And (3) constructing a hybrid intelligent algorithm:
Firstly, combining the advantages of a genetic algorithm and a deep learning algorithm to construct a hybrid intelligent algorithm;
then, determining a coding mode, an fitness function and genetic operation parameters of a genetic algorithm;
finally, a distributed power output and load prediction model is established by using a deep learning algorithm, historical data is trained, and distributed power output and load requirements in a future period of time are predicted;
(2) Optimization and improvement of algorithm:
firstly, in order to improve the solving efficiency and precision of the algorithm, the hybrid intelligent algorithm can be optimized and improved;
then, a simulated annealing and tabu search local search algorithm is introduced, and the local search capability of the algorithm is improved by combining with a genetic algorithm.
6. The method for optimal scheduling of the ac/dc flexible interconnection power distribution network according to claim 1, wherein the step E is specifically:
(1) Establishing a coordination control mechanism:
firstly, formulating a coordination control strategy, and defining a coordination control mode between a flexible direct current system and a traditional alternating current system;
Then, a communication network is established to realize information interaction between the flexible direct current system and the traditional communication system;
finally, a coordination controller is designed to realize unified control of the flexible direct current system and the traditional alternating current system;
(2) Implementation of coordination control:
under the normal operation condition, the coordination controller automatically adjusts the power output of the flexible direct current system and the operation parameters of the traditional alternating current system according to the load demand of the power grid and the output condition of the distributed power supply, so as to realize optimal power flow distribution and power quality control;
under the fault condition, the coordination controller rapidly starts a fault response strategy to realize fault isolation and recovery.
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| CN120031359A (en) * | 2025-04-24 | 2025-05-23 | 四川省气象服务中心(四川省专业气象台 四川省气象影视中心) | Complementary allocation method of water and light resources based on meteorological big data prediction |
| CN120414735A (en) * | 2025-07-02 | 2025-08-01 | 华南理工大学 | A distributed optimization scheduling method and system for AC/DC distribution networks |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN120031359A (en) * | 2025-04-24 | 2025-05-23 | 四川省气象服务中心(四川省专业气象台 四川省气象影视中心) | Complementary allocation method of water and light resources based on meteorological big data prediction |
| CN120414735A (en) * | 2025-07-02 | 2025-08-01 | 华南理工大学 | A distributed optimization scheduling method and system for AC/DC distribution networks |
| CN120414735B (en) * | 2025-07-02 | 2025-10-10 | 华南理工大学 | A distributed optimization scheduling method and system for AC/DC distribution networks |
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