Energy Management System Design and Testing for Smart Buildings Under Uncertain Generation (Wind/Photovoltaic) and Demand  

作　　者：Syed Furqan Rafique Jianhua Zhang Muhammad Hanan Waseem Aslam Atiq Ur Rehman Zmarrak Wali Khan 

机构地区：[1]Department of Electricaland Electronics Engineering, North China ElectricPower University, Beijing 102206, China.

出　　处：《Tsinghua Science and Technology》2018年第3期254-265,共12页清华大学学报（自然科学版（英文版）

摘　　要：This study provides details of the energy management architecture used in the Goldwind microgrid test bed. A complete mathematical model, including all constraints and objectives, for microgrid operational management is first described using a modified prediction interval scheme. Forecasting results are then achieved every 10 min using the modified fuzzy prediction interval model, which is trained by particle swarm optimization.A scenario set is also generated using an unserved power profile and coverage grades of forecasting to compare the feasibility of the proposed method with that of the deterministic approach. The worst case operating points are achieved by the scenario with the maximum transaction cost. In summary, selection of the maximum transaction operating point from all the scenarios provides a cushion against uncertainties in renewable generation and load demand.This study provides details of the energy management architecture used in the Goldwind microgrid test bed. A complete mathematical model, including all constraints and objectives, for microgrid operational management is first described using a modified prediction interval scheme. Forecasting results are then achieved every 10 min using the modified fuzzy prediction interval model, which is trained by particle swarm optimization.A scenario set is also generated using an unserved power profile and coverage grades of forecasting to compare the feasibility of the proposed method with that of the deterministic approach. The worst case operating points are achieved by the scenario with the maximum transaction cost. In summary, selection of the maximum transaction operating point from all the scenarios provides a cushion against uncertainties in renewable generation and load demand.

关 键 词：microgrid economic optimization generation forecast load forecast energy management system fuzzy prediction interval heuristic optimization 

分 类 号：TK018[动力工程及工程热物理] TM727[电气工程—电力系统及自动化]