Data-driven load frequency control for stochastic power systems : a deep reinforcement learning method with continuous action search

• المؤلفون الرئيسيون: Yan, Ziming, Xu, Yan
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2020
• الموضوعات: Engineering::Electrical and electronic engineering; Continuous Action Search; Deep Reinforcement Learning
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/141500

This letter proposes a data-driven, model-free method for load frequency control (LFC) against renewable energy uncertainties based on deep reinforcement learning (DRL) in continuous action domain. The proposed method can nonlinearly derive control strategies to minimize frequency deviation with fas...