基于多步自校正Q學習的孤島微電網(wǎng)負荷頻率控制策略

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摘 要：在以綠色交通和間歇性清潔能源為主的未來城網(wǎng)中，其波動性對城網(wǎng)的安全性和供電可靠性提出了越來越高的要求.針對傳統(tǒng)控制策略無法解決微電網(wǎng)中新能源規(guī)?；尤霂淼念l率不穩(wěn)定，控制性能標準差的問題，提出了多步自校正Q學習算法.該算法中的自校正估計器能夠準確估計系統(tǒng)的狀態(tài)，有效提高機組控制精度.此外，資格跡機制可以實現(xiàn)多步備份，提高算法收斂速度，使得控制器能夠滿足指令信號與機組響應的時延性，減小時延所帶來的調(diào)頻影響.仿真部分，本文構建了包含儲能系統(tǒng)、風力發(fā)電以及電動汽車的兩區(qū)域負荷頻率控制模型，并分別引入正弦波、階躍和隨機階躍擾動來模擬電力系統(tǒng)中的負荷變化擾動.仿真結(jié)果表明與其他算法相比，所提算法在控制性能指標方面表現(xiàn)出更優(yōu)的效果.

關鍵詞：強化學習；微電網(wǎng)；負荷頻率控制；清潔能源

中圖分類號：TM732

文獻標志碼： A

A load frequency control strategy of island microgrid based on multi-step self-correcting Q-learning

WANG Qiang1，2，HUANG Zhen-wei1

（1.College of Electrical and New Energy， China Three Gorges University， Yichang 443002， China; 2.Hubei Provincial Engineering Research Center of Intelligent Energy Technology， China Three Gorges University， Yichang 443002， China）

Abstract：In the forthcoming era of power grids emphasizing clean energy and green transportation，stringent safety and reliability standards are imperative.This study addresses the limitations of traditional reinforcement learning in managing the control performance degradation due to the extensive integration of new energy sources in microgrid by proposing a multi-step self-correcting Q-learning algorithm.This algorithm features a self-correcting estimator for accurate system state estimation and an eligibility trace mechanism to expedite convergence，facilitating rapid controller responses to system fluctuations and minimizing the impact of frequency regulation delays.The simulation section of this paper presents an enhanced two-area load frequency control model，integrating wind power and electric vehicle modules，and subjected to various disturbances to mimic real-world power system load changes.The results demonstrate that the proposed algorithm excels in control performance metrics when compared to existing methods.

Key words：reinforcement learning；microgrid；load frequency control；clean energy

0 引言

隨著全球資源緊缺與環(huán)境問題的日益嚴峻，“雙碳”政策和相應行動已逐漸成為各國的共識.在此背景下，以清潔能源為核心的電源結(jié)構轉(zhuǎn)型以及以純電動為目標的交通工具發(fā)展，已成為全球能源和交通領域的主要趨勢。（剩余12277字）