A communication infrastructure is an essential part to the success of the emerging smart grid. A scalable and pervasive communication infrastructure is crucial in both construction and operation of a smart grid. In this paper, we present the background and motivation of communication infrastructures in smart grid systems. We also summarize major requirements that smart grid communications must meet. From the experience of several industrial trials on smart grid with communication infrastructures, we expect that the traditional carbon fuel based power plants can cooperate with emerging distributed renewable energy such as wind, solar, etc, to reduce the carbon fuel consumption and consequent green house gas such as carbon dioxide emission. The consumers can minimize their expense on energy by adjusting their intelligent home appliance operations to avoid the peak hours and utilize the renewable energy instead. We further explore the challenges for a communication infrastructure as the part of a complex smart grid system. Since a smart grid system might have over millions of consumers and devices, the demand of its reliability and security is extremely critical. Through a communication infrastructure, a smart grid can improve power reliability and quality to eliminate electricity blackout. Security is a challenging issue since the on-going smart grid systems facing increasing vulnerabilities as more and more automation, remote monitoring/controlling and supervision entities are interconnected.

https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1315&context=electricalengineeringfacpub

A Survey on Smart Grid CommunicationInfrastructures: Motivations, Requirements andChallenges

DC microgrids encounter the challenges of constant power loads (CPLs) and pulsed power loads (PPLs), which impose the requirements of fast dynamics, large stability margin, high robustness that cannot be easily addressed by conventional linear control methods. This necessitates the implementation of advanced control technologies in order to significantly improve the robustness, dynamic performance, stability and flexibility of the system. This article presents an overview of advanced control technologies for bidirectional dc/dc converters in dc microgrids. First, the stability issue caused by CPLs and the power balance issue caused by PPLs are discussed, which motivate the utilization of advanced control technologies for addressing these issues. Next, typical advanced control technologies including model predictive control, backstepping control, sliding-mode control, passivity-based control, disturbance estimation techniques, intelligent control, and nonlinear modeling approaches are reviewed. Then the applications of advanced control technologies in bidirectional dc/dc converters are presented for the stabilization of CPLs and accommodation of PPLs. Finally, advanced control techniques are explored in other high-gain nonisolated (e.g., interleaved, multilevel, cascaded) and isolated converters (e.g., dual active bridge) for high-power applications.

Review on Advanced Control Technologies for Bidirectional DC/DC Converters in DC Microgrids

Operations and maintenance of offshore wind turbines (OWTs) play an important role in the development of offshore wind farms. Compared with operations, maintenance is a critical element in the levelized cost of energy, given the practical constraints imposed by offshore operations and the relatively high costs. The effects of maintenance on the life cycle of an offshore wind farm are highly complex and uncertain. The selection of maintenance strategies influences the overall efficiency, profit margin, safety, and sustainability of offshore wind farms. For an offshore wind project, after a maintenance strategy is selected, schedule planning will be considered, which is an optimization problem. Onsite maintenance will involve complex marine operations whose efficiency and safety depend on practical factors. Moreover, negative environmental impacts due to offshore maintenance deserve attention. To address these issues, this paper reviews the state-of-the-art research on OWT maintenance, covering strategy selection, schedule optimization, onsite operations, repair, assessment criteria, recycling, and environmental concerns. Many methods are summarized and compared. Limitations in the research and shortcomings in industrial development of OWT operations and maintenance are described. Finally, promising areas are identified with regard to future studies of maintenance strategies.

Offshore wind turbine operations and maintenance: A state-of-the-art review

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 article 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.

Distributed Control and Communication Strategies in Networked Microgrids

Load frequency control in modern-complex-uncertain power systems (PSs) assumes significance due to their challenging nature of the operation and hence utilisation of robust controllers is indispensable. In the industry, conventional single-loop controllers may not offer robust behaviour under changed operating conditions. Alternatively, two-loop cascade fuzzy structured controllers can show significant robust performance in dynamic conditions and best suited in systems having non-linearities. Hence, a novel optimal cascade fuzzy-fractional order integral derivative with filter (CF-FOIDF) controller is utilised for 2-area thermal and hydrothermal PSs considering various physical constraints from a practical point of view. As physical constraints mandate an energy storage system, hence in this study, batteries of electric vehicles (EVs) are employed to assist power plants to swiftly arrest oscillations in the system frequency following load demands. A combined model of EV fleets is incorporated in the control areas of PSs. Numerous simulations are conducted to authenticate the robustness and excellence of EVs and the suggested control strategy over existing methods.

Effect of electric vehicles on load frequency control in interconnected thermal and hydrothermal power systems utilising CF-FOIDF controller

An effective hybrid harmony search and cuckoo optimization algorithm based fuzzy PID controller for load frequency control

In this article, a novel fuzzy proportional integral derivative (PID) controller with filtered derivative action and fractional order integrator (fuzzy PIλDF controller) is proposed to solve automa...

Design an optimal fuzzy fractional proportional integral derivative controller with derivative filter for load frequency control in power systems

The intermittent feature of renewable energy sources leads to the mismatch between supply and load demand on microgrids. In such circumstance, the system experiences large fluctuations, if the secondary load frequency control (LFC) mechanism is unable to compensate the mismatch. In this issue, this paper presents a well-structured combination of the fuzzy PD and cascade PI-PD controllers named FPD/PI-PD controller as a supplementary (secondary) controller for the secondary load frequency control in the islanded multi-microgrid (MMG). Additionally, two modifications to the JAYA algorithm are made to enhance the diversity of the initial population and ameliorate the global searching ability in the iterative process. Afterward, the improved JAYA algorithm, referred to as IJAYA, is employed for fine-tuning the proposed structured controller installed in areas of the studied MMG. The superiority of the proposed IJAYA is validated by comparative analysis with genetic algorithm and basic JAYA in a similar structure of the PID controller. Furthermore, it will be shown that the proposed FPD/PI-PD controller employing IJAYA provides a higher degree of stability in suppressing the responses deviations as compared with the conventional PID and FPID controller structures. Finally, the novel optimal proposed approach is validated and implemented in the hardware-in-the-loop (HIL) based on OPAL-RT to integrate the fidelity of physical simulation and the flexibility of numerical simulation.

Secondary load frequency control for multi-microgrids: HiL real-time simulation

The high-penetration of distributed generation technologies in the form of MicroGrids (MGs), in recent years, has increased the risk of frequency instability since their energy is supplied by renewable energy resources (RESs) with uncertain nature. Under such circumstances, providing an MG model with an efficient load frequency control (LFC) has a fundamental role in restoring the stability of the unstructured power system. In this study, a hybrid power system with the application of the Tidal Power Unit (TPU) and Vehicle-to-Grid (V2G) is effectively planed as an isolated MG. A new fractional gradient descent (FGD) based on a single-input interval type-2 fuzzy logic controller (SIT2-FLC) is suggested as the main LFC controller, where the footprint of uncertainty (FOU) coefficient of the SIT2-FLC is specifically adjusted to enhance the LFC performance. Additionally, a deep deterministic policy gradient (DDPG) with the actor-critic framework is considered to generate the supplementary control action, which is useful for the frequency stabilization by adapting to the randomness of load disturbances and RESs. Lastly, a model-in-the-loop (MiL) simulation is conducted to appraise the feasibility and applicability of the suggested design method from a systemic perspective.

A Novel Deep Reinforcement Learning Controller Based Type-II Fuzzy System: Frequency Regulation in Microgrids

The nonlinearities and unmodeled dynamics inevitably degrade the quality and reliability of power conversion, and as a result, pose big challenges on higher-performance voltage stabilization of dc–dc buck converters. The stability of such power electronic equipment is further threatened when feeding the nonideal constant power loads (CPLs) because of the induced negative impedance specifications. In response to these challenges, the advanced regulatory and technological mechanisms associated with the converters require to be developed to efficiently implement these interface systems in the microgrid configuration. This article addresses an intelligent proportional-integral based on sliding mode (SM) observer to mitigate the destructive impedance instabilities of nonideal CPLs with time-varying nature in the ultralocal model sense. In particular, in the current article, an auxiliary deep deterministic policy gradient (DDPG) controller is adaptively developed to decrease the observer estimation error and further ameliorate the dynamic characteristics of dc–dc buck converters. The design of the DDPG is realized in two parts: (i) an actor-network which generates the policy commands, while (ii) a critic-network evaluates the quality of the policy command generated by the actor. The suggested strategy establishes the DDPG-based control to handle for what the iPI-based SM observer is unable to compensate. In this application, the weight coefficients of the actor and critic networks are trained based on the reward feedback of the voltage error, by using the gradient descent scheme. Finally, to investigate the merits and implementation feasibility of the suggested method, some experimental results on a laboratory prototype of the dc–dc buck converter, which feeds a time-varying CPL, are presented.

Meysam Gheisarnejad

Papers

An effective hybrid harmony search and cuckoo optimization algorithm based fuzzy PID controller for load frequency control

Design an optimal fuzzy fractional proportional integral derivative controller with derivative filter for load frequency control in power systems

Secondary load frequency control for multi-microgrids: HiL real-time simulation

A Novel Deep Reinforcement Learning Controller Based Type-II Fuzzy System: Frequency Regulation in Microgrids

A Novel Nonlinear Deep Reinforcement Learning Controller for DC–DC Power Buck Converters