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The growing penetration of electric vehicles (EVs) significantly changes typical load curves in smart grids. With the development of fast charging technology, the volatility of EV charging demand is increasing, which requires additional…

To improve the quality of computation experience for mobile devices, mobile-edge computing (MEC) is emerging as a promising paradigm by providing computing capabilities within radio access networks in close proximity. Nevertheless, the…

An effective way to oppose global warming and mitigate climate change is to electrify our energy sectors and supply their electric power from renewable wind and solar. Spatio-temporal predictions of electric load become increasingly…

In this paper, we systematically investigate the feasibility of different extremum-seeking (ES) control schemes to improve the conversion efficiency of wave energy converters (WECs). Continuous-time and model-free ES schemes based on the…

As electric vehicle (EV) adoption is growing year after year, there is no doubt that EVs will occupy a significant portion of transporting vehicle in the near future. Although EVs have benefits for environment, large amount of…

High penetration of plug-in electric vehicles (PEVs) can potentially put the utility assets such as transformer under overload stress causing decrease in their lifetime. The decrease in PV and battery energy storage system (BESS) prices has…

The provision of renewable electricity is the foundation for a sustainable future. To achieve the goal of sustainable renewable energy, Battery Energy Storage Systems (BESS) could play a key role to counteract the intermittency of solar and…

With the advent of ever-growing vehicular applications, vehicular edge computing (VEC) has been a promising solution to augment the computing capacity of future smart vehicles. The ultimate challenge to fulfill the quality of service (QoS)…

The optimal planning of electromagnetic skins (EMSs) installed on the building facades to enhance the received signal strength, thus the wireless coverage and/or the quality-of-service (QoS) in large-scale urban areas, is addressed. More…

End-to-end learning for wireless communications has recently attracted much interest in the community, owing to the emergence of deep learning-based architectures for the physical layer. Neural network-based autoencoders have been proposed…

The global energy landscape is experiencing a significant transformation driven by increased awareness of climate change and rapid technological advancements in renewable energy and electric vehicles (EVs). Packetized energy management…

In this paper, a dynamic spectrum management framework is proposed to improve spectrum resource utilization in a multi-access edge computing (MEC) in autonomous vehicular network (AVNET). To support the increasing data traffic and guarantee…

Coordination of distributed energy resources (DERs) can engender flexibility necessary to improve grid reliability. Packetized Energy Management (PEM) is a method for coordinating DERs, such as thermostatically controlled loads (TCLs) and…

Battery Energy Storage Systems (BESS) are critical for modern power networks, supporting grid services such as frequency regulation, peak shaving, and black start. Delivering a BESS under an Engineering, Procurement, and Construction (EPC)…

The year of 2020 has witnessed the unprecedented development of 5G networks, along with the widespread deployment of 5G base stations (BSs). Nevertheless, the enormous energy consumption of BSs and the incurred huge energy cost have become…

Large-scale integration of plug-in electric vehicles (PEV) in power systems can cause severe issues to the existing distribution system, such as branch congestions and significant voltage drops. As a consequence, smart charging strategies…

Transmission Expansion Planning (TEP) is the process of optimizing the development and upgrade of the power grid to ensure reliable, efficient, and cost-effective electricity delivery while addressing grid constraints. To support growing…

Undoubtedly, the increase of available data and competitive machine learning algorithms has boosted the popularity of data-driven modeling in energy systems. Applications are forecasts for renewable energy generation and energy consumption.…

The power system is undergoing rapid evolution with the roll-out of advanced metering infrastructure and local energy applications (e.g. electric vehicles) as well as the increasing penetration of intermittent renewable energy at both…

In this paper, we aim to leverage peer to peer (P2P) transactive energy framework for optimal control of rooftop or neighborhood solar power with battery electric storage systems (BESS). Here we propose that the multiple neighboring…