Enhancing privacy of electricity consumption in smart cities through morphing of anticipated demand pattern utilizing self-elasticity and genetic algorithms

Author:

Alamaniotis Miltiadis,Bourbakis Nikolaos,Tsoukalas Lefteri H.

Publisher

Elsevier BV

Subject

Transportation,Renewable Energy, Sustainability and the Environment,Civil and Structural Engineering,Geography, Planning and Development

Reference41 articles.

1. Privacy-driven electricity group demand response in smart cities using particle swarm optimization;Alamaniotis;Tools With Artificial Intelligence (ICTAI), 2016 IEEE 28th International Conference on,2016

2. Anticipatory driven nodal electricity load morphing in smart cities enhancing consumption privacy;Alamaniotis;PowerTech, 2017 IEEE Manchester,2017

3. Smart cities of the future;Batty;The European Physical Journal Special Topics,2012

4. An internet of things architecture for preserving privacy of energy consumption;Belligianni;10th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (Med Power 2016),2016

5. Energy networks in sustainable cities: Towards a full integration of renewable systems in urban area;Bellosio;IECON 2011-37th Annual Conference on IEEE Industrial Electronics Society,2011

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