| 引用本文: | 葛乐,张伟,严锋,袁晓冬,禹永洲.基于自适应模型预测控制的柔性互联配电网优化调度[J].电力自动化设备,2020,40(6): |
| GE Le,ZHANG Wei,YAN Feng,YUAN Xiaodong,YU Yongzhou.Optimal scheduling of flexible interconnected distribution network based on adaptive model predictive control[J].Electric Power Automation Equipment,2020,40(6): |
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| 摘要: |
| 针对柔性互联配电网中源荷不确定性问题，提出了一种基于改进模型预测控制的优化调度方法。建立基于模型预测控制的柔性互联配电网日内优化调度模型，采用自适应动态权重方法处理包含综合供电成本和电压偏差的多目标优化问题，在预测模型部分采用动态场景生成及K-means聚类场景削减方法对源荷预测误差进行处理，针对经典模型预测控制滚动优化部分域参数恒定问题，提出一种域参数自适应调整的滚动优化方法。通过四馈线互联的33节点系统仿真算例验证了所提优化调度方法的有效性。 |
| 关键词: 柔性互联配电网 源荷不确定性 自适应模型预测控制 多目标优化 |
| DOI：10.16081/j.epae.202005009 |
| 分类号:TM734 |
| 基金项目:国家自然科学基金资助项目(51707089)；国网江苏省电力有限公司科技项目(J2018084) |
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| Optimal scheduling of flexible interconnected distribution network based on adaptive model predictive control |
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GE Le1, ZHANG Wei2, YAN Feng3, YUAN Xiaodong4, YU Yongzhou5
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1.School of Electrical Engineering, Nanjing Institute of Technology, Nanjing 211167, China;2.Changzhou Power Supply Company of State Grid Jiangsu Electric Power Co.,Ltd.,Changzhou 213000, China;3.Nantong Power Supply Company of State Grid Jiangsu Electric Power Co.,Ltd.,Nantong 226000, China;4.State Grid Jiangsu Electric Power Research Institute, Nanjing 211103, China;5.Taizhou Power Supply Company of State Grid Jiangsu Electric Power Co.,Ltd.,Taizhou 225300, China
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| Abstract: |
| Aiming at the uncertainties of distributed generation and load in flexible interconnected distribution network, an optimal scheduling method based on improved model predictive control is proposed. The model predictive control-based intraday optimal scheduling model of flexible interconnected distribution network is established. The adaptive dynamic weight method is used to deal with the multi-objective optimization problem including comprehensive power supply cost and voltage deviation. The dynamic scenario generation and K-means clustering scenario reduction method are used to deal with the prediction errors of distributed generation and load in the prediction model. Aiming at the problem of partial constant domain parameters in the rolling optimization of classical model predictive control, a rolling optimization method based on adaptive adjustment of domain parameters is proposed. The effectiveness of the proposed optimal scheduling method is verified by a simulation example of a 33-bus system interconnected with four feeders. |
| Key words: flexible interconnected distribution network uncertainties of distributed generation and load adaptive model predictive control multi-objective optimization |
