scholarly journals Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5739
Author(s):  
Nallapaneni Manoj Kumar ◽  
Aneesh A. Chand ◽  
Maria Malvoni ◽  
Kushal A. Prasad ◽  
Kabir A. Mamun ◽  
...  
Keyword(s):  
Data Storage ◽  
Smart Grids ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Self Healing ◽  
Distributed Energy ◽  
Knowledge Based ◽  
Comprehensive Survey ◽  
Digital Transactions ◽  
Real Time Information

Smart grid (SG), an evolving concept in the modern power infrastructure, enables the two-way flow of electricity and data between the peers within the electricity system networks (ESN) and its clusters. The self-healing capabilities of SG allow the peers to become active partakers in ESN. In general, the SG is intended to replace the fossil fuel-rich conventional grid with the distributed energy resources (DER) and pools numerous existing and emerging know-hows like information and digital communications technologies together to manage countless operations. With this, the SG will able to “detect, react, and pro-act” to changes in usage and address multiple issues, thereby ensuring timely grid operations. However, the “detect, react, and pro-act” features in DER-based SG can only be accomplished at the fullest level with the use of technologies like Artificial Intelligence (AI), the Internet of Things (IoT), and the Blockchain (BC). The techniques associated with AI include fuzzy logic, knowledge-based systems, and neural networks. They have brought advances in controlling DER-based SG. The IoT and BC have also enabled various services like data sensing, data storage, secured, transparent, and traceable digital transactions among ESN peers and its clusters. These promising technologies have gone through fast technological evolution in the past decade, and their applications have increased rapidly in ESN. Hence, this study discusses the SG and applications of AI, IoT, and BC. First, a comprehensive survey of the DER, power electronics components and their control, electric vehicles (EVs) as load components, and communication and cybersecurity issues are carried out. Second, the role played by AI-based analytics, IoT components along with energy internet architecture, and the BC assistance in improving SG services are thoroughly discussed. This study revealed that AI, IoT, and BC provide automated services to peers by monitoring real-time information about the ESN, thereby enhancing reliability, availability, resilience, stability, security, and sustainability.

scholarly journals Concept of Designing Thermal Condition Monitoring System with ZigBee/GSM Communication Link for Distributed Energy Resources Network in Rural and Remote Applications

Processes ◽  
2019 ◽  
Vol 7 (6) ◽  
pp. 383 ◽  
Author(s):  
Payne ◽  
Lu ◽  
Wang ◽  
Wu
Keyword(s):  
Data Storage ◽  
Mobile Communications ◽  
Electrical Power ◽  
Thermal Conditions ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Communication Link ◽  
Distributed Energy ◽  
Rural And Remote ◽  
Integrated Network

Monitoring the thermal behavior of distributed energy resources (DERs) network explores the dualism between thermal effects and electrical power flow. This paper proposes a design concept that monitors thermal conditions of DER grids, using ZigBee/GSM wireless sensor networks (WSNs) for real-time monitoring in rural and remote areas. The concept seeks to improve upon existing designs by integrating composite functions. The functions comprise temperature conditions monitoring, data acquisition, and wireless data transmission including data storage and abnormal conditions alert/notification for control solutions. Thus, the concept determines the thermal impact on the DERs integrated network. WSNs with temperature sensors LM35 are utilized to complement ZigBee and Global System for Mobile Communications (GSM) technologies as a communication assisted link. Temperatures are measured from solar Photovoltaic PV modules, wind turbine, distribution cables, protection control units, and energy storage facilities. The ATMEGA328P microcontroller is assigned for signal and control processing. The circuit performance is coordinated and displayed on an LCD screen for normal conditions, whereas abnormal scenarios communicate through an alert/notification by GSM Short Message Service (SMS) protocol. The development analysis was performed through algorithm and circuit simulations. Proteus software was used for circuit design. Both the algorithm and circuit analysis passed the assigned simulation stages.

scholarly journals Internet of Things Technologies for Smart Grid

2022 ◽  
pp. 805-832
Author(s):  
Imed Saad Ben Dhaou ◽  
Aron Kondoro ◽  
Syed Rameez Ullah Kakakhel ◽  
Tomi Westerlund ◽  
Hannu Tenhunen
Keyword(s):  
Internet Of Things ◽  
Smart Grid ◽  
Smart Grids ◽  
Reference Model ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Reference Architecture ◽  
Distributed Energy ◽  
Research Gaps ◽  
Utility Company

Smart grid is a new revolution in the energy sector in which the aging utility grid will be replaced with a grid that supports two-way communication between customers and the utility company. There are two popular smart-grid reference architectures. NIST (National Institute for Standards and Technology) has drafted a reference architecture in which seven domains and actors have been identified. The second reference architecture is elaborated by ETSI (European Telecommunications Standards Institute), which is an extension of the NIST model where a new domain named distributed energy resources has been added. This chapter aims at identifying the use of IoT and IoT-enabled technologies in the design of a secure smart grid using the ETSI reference model. Based on the discussion and analysis in the chapter, the authors offer two collaborative and development frameworks. One framework draws parallels' between IoT and smart grids and the second one between smart grids and edge computing. These frameworks can be used to broaden collaboration between the stakeholders and identify research gaps.

Optimal Electricity Procurement in Smart Grids With Autonomous Distributed Energy Resources

2015 ◽  
Vol 6 (6) ◽  
pp. 2975-2984 ◽  
Author(s):  
Amir Safdarian ◽  
Mahmud Fotuhi-Firuzabad ◽  
Matti Lehtonen ◽  
Farrokh Aminifar
Keyword(s):  
Smart Grids ◽  
Energy Resources ◽  
Distributed Energy Resources ◽  
Distributed Energy
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