Ontology-Driven Resource Selecting in the Grid Environments

An Energy Efficient Authentication Scheme based on Chebyshev Chaotic Map for Smart Grid Environments

IEEE Internet of Things Journal ◽

10.1109/jiot.2021.3078175 ◽

2021 ◽

pp. 1-1

Author(s):

Liping Zhang ◽

Yue Zhu ◽

Wei Ren ◽

Yinghan Wang ◽

Kim-Kwang Raymond Choo ◽

...

Keyword(s):

Smart Grid ◽

Energy Efficient ◽

Chaotic Map ◽

Authentication Scheme ◽

Chebyshev Chaotic Map ◽

Grid Environments

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An Automatic Aggregator of Power Flexibility in Smart Buildings Using Software Based Orchestration

Sensors ◽

10.3390/s21030867 ◽

2021 ◽

Vol 21 (3) ◽

pp. 867

Author(s):

Dharmendra Sharma ◽

Jari Rehu ◽

Klaus Känsälä ◽

Heikki Ailisto

Keyword(s):

Control Signal ◽

External Control ◽

Data Logging ◽

Building Energy Management ◽

Hardware System ◽

Temperature Thresholds ◽

Grid Environments ◽

End Use ◽

Maintenance Requirements ◽

Control And Management

This paper presents a software-based modular and hierarchical building energy management system (BEMS) to control the power consumption in sensor-equipped buildings. In addition, the need of this type of solution is also highlighted by presenting the worldwide trends of thermal energy end use in buildings and peak power problems. Buildings are critical component of smart grid environments and bottom-up BEMS solutions are need of the hour to optimize the consumption and to provide consumption side flexibility. This system is able to aggregate the controls of the all-controllable resources in building to realize its flexible power capacity. This system provides a solution for consumer to aggregate the controls of ‘behind-the-meter’ small loads in short response and provide ‘deep’ demand-side flexibility. This system is capable of discovery, status check, control and management of networked loads. The main novelty of this solution is that it can handle the heterogeneity of the installed hardware system along with time bound changes in the load device network and its scalability; resulting in low maintenance requirements after deployment. The control execution latency (including data logging) of this BEMS system for an external control signal is less than one second per connected load. In addition, the system is capable of overriding the external control signal in order to maintain consumer coziness within the comfort temperature thresholds. This system provides a way forward in future for the estimation of the energy stored in the buildings in the form of heat/temperature and use buildings as temporary batteries when electricity supply is constrained or abundant.

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