Title :
Intelligent load management for a shopping mall model in a smartgrid enviroment
Author :
Adinolfi, F. ; Massucco, Stefano ; Silvestro, Federico ; De Danieli, A. ; Fidigatti, A. ; Ragaini, E.
Author_Institution :
DITEN, Univ. of Genova, Genoa, Italy
Abstract :
The future electricity demand is expected to increase as well as the will to exploit in deeper the generation from renewable resources. These facts will make necessary to achieve more flexibility in managing the electrical systems. One effective way to manage distribution networks with this increase of demand, is to apply all the different techniques that smart grid technologies bring such as load balancing, load shifting and peak shaving through intelligent load management (ILM). The aim of this work is to present a model of a shopping mall used as a study case for ILM, in order to evaluate and compare the different results achieved using a predictive rate control algorithm to control the power consumption of the electrical loads. All the models, algorithms and simulations have been implemented in MATLAB.
Keywords :
demand side management; distribution networks; predictive control; smart power grids; ILM; MATLAB simulation; demand side management; distribution networks; electricity demand; intelligent load management; load balancing; load shifting; peak shaving; predictive rate control; renewable resources; shopping mall model; smart grid environment; Absorption; Energy consumption; Lighting; Load management; Load modeling; Mathematical model; Power demand; Demand Response (DR); Demand Side Management; Intelligent Load Management; peak shaving; smartgrid;
Conference_Titel :
PowerTech (POWERTECH), 2013 IEEE Grenoble
Conference_Location :
Grenoble
DOI :
10.1109/PTC.2013.6652287