分布式能源与多设备协调合作的分布式计算方法研究

Shiyuan Ning, Quanbo Ge, Haoyu Jiang
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引用次数: 4

摘要

随着分布式可再生能源技术的快速发展,智能电网产生的数据量增加更为显著,传统的集中控制方式在任务处理上存在较高的延迟问题,给智能电网的稳定运行带来不利影响。针对这一问题,本文提出了一种边缘计算与云计算相结合的分布式计算方案,以提高电力系统的数据处理能力和系统响应能力。此外,本文还分析了边缘节点计算能力的有限性。根据任务负载均衡理论,以任务性能最小化为目标函数,提出了一种基于该分布式计算架构的免疫混沌粒子群算法(ICPSO)的高性能负载均衡策略。最后,通过仿真结果验证了系统架构和负载均衡策略的可行性和有效性。
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Research on distributed computing method for coordinated cooperation of distributed energy and multi-devices
With the rapid development of the distributed renewable energy technologies, there is more significant increase in the amount of data generated by the smart grids, and there are a higher delay problem in the task processing, with the traditional centralized control methods, which brings in an adverse effect on the stable operation of the smart grid. Aiming at the problem, this paper proposes a distributed computing scheme that combines edge computing and cloud computing to improve power system data processing capabilities and system response capabilities. Besides, the paper analyzes the finiteness of edge node computing ability. According to the task load balancing theory, a task performance minimization as an objective function is proposed, and a high-performance load balancing strategy for immune chaotic particle swarms algorithm (ICPSO) is proposed based on this distributed computing architecture. Finally, the feasibility and effectiveness of the system architecture and load balancing strategy are verified through the simulation results.
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