Development and testing of a micro-grid excess power production forecasting algorithms

被引:3
|
作者
Mavrigiannaki, Angeliki [1 ]
Kampelis, Nikos [1 ]
Kolokotsa, Denia [1 ]
Marchegiani, Daniele [2 ]
Standardi, Laura [2 ]
Isidori, Daniela [2 ]
Christalli, Cristina [2 ]
机构
[1] Tech Univ Crete, Sch Environm Engn, Khania 73100, Greece
[2] Loccioni Grp, Dept Res Innovat, Via Fiume 16, I-60030 Ancona, Italy
关键词
micro-grid; forecasting; integration; artificial neural network; ENERGY MANAGEMENT; SYSTEM; PV;
D O I
10.1016/j.egypro.2017.09.583
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Traditional electricity grids lack flexibility in power generation and load operation in contrast to smart-micro grids that form semi-autonomous entities with energy management capabilities. Load forecasting is invaluable to smart micro-grids towards assisting the implementation of energy management schedules for cost-efficient and secure operation. In the present paper is examined the 24h forecasting of excess production in an existing micro-grid. Alternative input parameters are considered for achieving an accurate prediction. The prediction can be used for scheduling the charging process of a thermal storage during weekends based on excess power production levels. (C) 2017 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:654 / 663
页数:10
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