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Lyapunov Optimization Based Online Energy Flow Control for Multi-energy Community Microgrids

机译:基于Lyapunov优化的多能量社区微电网的在线能量流量控制

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This paper proposes an online optimization method for energy flow control (EFC) in Multi-energy Community Microgrids (MECMs) to realize cost savings as well as renewable energy source (RES) utilization rate increasing. To be specifically, the event-triggering mechanisms are firstly established considering queue length variations of energy storage system, active load, and user comfort. Without relying on the accurate forecasting of RES scenarios and load data, we use Lyapunov optimization method to collect only the current period data to implement the system optimization, which avoids the problem of stochastic nature imposed by both supply and demand sides. Finally, the performance analysis of the proposed event-driven based online algorithm is evaluated through real data cases in Hangzhou, China. Simulation results illustrate the feasibility and the effectiveness of the proposed method.
机译:本文提出了一种在多能量社区微电网(MECMS)中的能量流量控制(EFC)的在线优化方法,实现成本节省,以及可再生能源(RES)利用率增加。具体地,首先考虑考虑队列长度变化的能量存储系统,主动负载和用户舒适度的事件触发机制。如果不依赖于RES场景和负载数据的准确预测,我们使用Lyapunov优化方法仅收集当前时期数据来实现系统优化,这避免了供应和需求侧施加的随机性质问题。最后,通过杭州杭州的实际数据案例评估了基于事件驱动的在线算法的绩效分析。仿真结果说明了所提出的方法的可行性和有效性。

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