| 引用本文: | 殷林飞,郑宝敏,余涛.人工情感Q学习的互联电网自动发电控制算法[J].控制理论与应用,2016,33(12):1650~1657.[点击复制] |
| YIN Lin-fei,ZHENG Bao-min,YU Tao.Artificial emotionnal Q-learning for automatic generation control of interconnected power grids[J].Control Theory and Technology,2016,33(12):1650~1657.[点击复制] |
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| 人工情感Q学习的互联电网自动发电控制算法 |
| Artificial emotionnal Q-learning for automatic generation control of interconnected power grids |
| 摘要点击 3009 全文点击 2176 投稿时间：2016-05-20 修订日期：2016-12-16 |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| DOI编号 10.7641/CTA.2016.60340 |
| 2016,33(12):1650-1657 |
| 中文关键词 人工情感 Q学习 Q(λ)学习 自动发电控制 |
| 英文关键词 arti?cial emotion Q-learning Q(λ)-learning automatic generation control |
| 基金项目 国家自然科学基金项目(51177051, 51477055), 国家“973”计划项目(2013CB228205)资助. |
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| 中文摘要 |
| 对互联电网中自动发电控制AGC中控制策略进行改进, 设计了人工智能中的人工心理学和人工智能中的
机器学习结合的控制策略.分别对Q学习算法和Q(λ)学习算法进行改进,设计了具有人工情感的智能体.提出了人
工情感Q学习算法和人工情感Q(λ)学习算法. 且将人工情感分别作用于Q学习算法和Q(λ)学习算法中的输出动作、
学习率和奖励函数. 最后在IEEE标准两区域和南方电网四区域的互联电网Simulink模型中进行数值仿真. 绘制并统
计了控制性能指标、区域控制误差和频率偏差的值.从仿真结果看,所提人工情感Q学习算法和人工情感Q(λ)学习
算法控制效果优于原有Q学习算法、 Q(λ)学习算法、 R(λ)算法、 Sarsa算法、 Sarsa(λ)算法和PID控制算法, 该数值仿
真结果验证了所提算法的可行性和有效性. |
| 英文摘要 |
| Arti?cial psychology and machine learning are combined in the automatic generation control strategy of
interconnected power grids. An agent obtaining arti?cial emotion is designed, and the Q-learning and Q(λ)-learning algo-
rithms are improved by arti?cial emotion. The novel arti?cial emotional Q-learning and arti?cial emotional Q(λ)-learning
algorithms are proposed. The arti?cial emotion is respectively applied to the selection of output action, learning rate and
reward function in Q-learning and Q(λ)-learning, and then simulated on the standard IEEE two-area model and the China
Southern Power Grid four-area model. The control performance standard, area control error and frequency deviation are
?gured. Simulation results verify the feasibility and effectiveness of the proposed algorithms and their superiority to the
Q-learning, Q(λ)-learning, R(λ), Sarsa, Sarsa(λ) and PID algorithms. |
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