Smart mobile devices (SMDs) can meet users’ high expectations by executing computational intensive applications but they only have limited resources including CPU, memory, battery power and wireless medium. To tackle this limitation, partial computation offloading can be used as a promising method to schedule some tasks of applications from resource-limited SMDs to high-performance edge servers. However, it brings communication overhead issues caused by limited bandwidth, and inevitably increases latency of tasks offloaded to edge servers. Therefore, it is highly challenging to achieve the balance between high-resource consumption in SMDs and high communication cost for providing energy-efficient and latency-low services to users. This work proposes a partial computation offloading method to minimize the total energy consumed by SMDs and edge servers by jointly optimizing offloading ratio of tasks, CPU speeds of SMDs, allocated bandwidth of available channels and transmission power of each SMD in each time slot. It jointly considers execution time of tasks performed in SMDs and edge servers, and transmission time of data. It also jointly considers latency limits, CPU speeds, transmission power limits, available energy of SMDs, and maximum number of CPU cycles and memories in edge servers. Considering these factors, a nonlinear constrained optimization problem is formulated and solved by a novel hybrid meta-heuristic algorithm named Genetic Simulated-annealing-based Particle swarm optimization (GSP) to produce a close-to-optimal solution. GSP achieves joint optimization of computation offloading between a cloud data center and the edge, and resource allocation in the data center. Real-life data-based experimental results prove that it achieves lower energy consumption in less convergence time than its three typical peers.

Networked microgrids (NMGs) provide a promising solution for accommodating various distributed energy resources (DERs) and enhancing the system performance in terms of reliability, resilience, flexibility, and energy efficiency. With the penetration of MGs, the communication-based distributed control is playing an increasingly important role in NMGs for coordinating a multitude of heterogeneous and spatially distributed DERs, which feature enhanced efficiency, reliability, resilience, scalability, and privacy-preserving as compared with conventional centralized control. This paper aims to provide a comprehensive survey of distributed control and communication strategies in NMGs. We provide thorough discussions and elaborate on: 1) Essential merits of MGs and NMGs, and their practical implementations; 2) Distributed communication network characteristics and specific operation objectives of NMGs; 3) Classifications of distributed control strategies in NMGs and their salient features; 4) Communication reliability issues concerning data timeliness, data availability, and data accuracy, and the development of countermeasures; 5) Advancements in several promising communication and computation technologies and their potential applications in NMGs.

This paper proposes a two-level networkconstrained peer-to-peer (P2P) transactive energy for multimicrogrids (MGs), which guarantees the distribution power network security and allows MGs to trade energy with each other flexibly. At the lower level, a P2P transactive energy is employed for multi-MGs to trade energy with each other. A multi-leader multi-follower (MLMF) Stackelberg game approach is utilized to model the energy trading process among MGs. We prove the existence and the uniqueness of the Stackelberg equilibrium (SE) and provide the closed-form expression for SE. For privacy concerns, we provide several distributed algorithms to obtain SE. At the upper level, the distribution system operator (DSO) reconfigures the distribution network based on the P2P transactive energy trading results by applying the AC optimal power flow considering the distribution network reconfiguration. If there are any network violations, DSO requests trading adjustments at the lower level for network security. We reformulate the DSO operation problem in a mixed-integer second-order cone programming (MISOCP) model and ensure its solution accuracy. Numerical results for a 4-Microgrid system, a modified IEEE 33-bus and 123-bus distribution power system show the effectiveness of the proposed transactive model and its solution technique.

Integrated power systems are popular in the shipbuilding industry. DC shipboard microgrids (dc-SMGs) have many advantages compared with ac ones in terms of system efficiency, operation flexibility, component size, and fault protection performance. Being in the exploring stage, dc-SMGs have several potential configurations with different system architectures and voltage levels. In a dc-SMG, functional blocks integrated include power generation modules (PGMs), propulsion system, high power loads, and pulsed loads specifically in naval ships. In modern ships, the PGMs include not only generators and fuel cells but also energy storage systems (ESSs), which cooperate with generators to improve the overall efficiency and reliability. High power electric converters are vital interfaces between the functional blocks and the dc distribution system. Rectifiers for generators take the tasks of dc bus voltage regulation and power sharing. Inverters for propulsion motors are responsible for the motor drive in different operating conditions. Bidirectional dc/dc converters for ESSs are used to provide supply-demand balance and voltage fluctuation mitigation. This article makes a comprehensive review of power architecture, functional blocks including electrical machines and energy storage, as well as power converters in dc shipboard power systems.

Considering the high penetration of distributed energy resources (DERs), extensive communication networks are deemed necessary to realize the coordinated control of DERs in microgrids (MGs). The reliance on communication networks introduces potential cyber security issues into MGs. However, such attacks are difficult to be detected when a global situational awareness is lacking in distributed systems. In this paper, we analyze the impacts of cyber-attacks on communication links, local controllers, and master controller, which would drive MGs away from optimal operating points. We propose a cyber-attack resilient distributed control strategy in which each participant can detect and isolate corrupted links and controllers in a timely and economic fashion. The proposed control strategy is effective against time-varying attack signals and successive attacks while retaining the MG operational merits. The proposed control strategy is examined for different types of attacks. In this case, we consider various operating conditions and apply the time-domain PSCAD/EMTDC to the simulation and analyses of two MG systems.