The significant benefits associated with microgrids have led to vast efforts to expand their penetration in electric power systems. Although their deployment is rapidly growing, there are still many challenges to efficiently design, control, and operate microgrids when connected to the grid, and also when in islanded mode, where extensive research activities are underway to tackle these issues. It is necessary to have an across-the-board view of the microgrid integration in power systems. This paper presents a review of issues concerning microgrids and provides an account of research in areas related to microgrids, including distributed generation, microgrid value propositions, applications of power electronics, economic issues, microgrid operation and control, microgrid clusters, and protection and communications issues.

State of the Art in Research on Microgrids: A Review

Microgrid is a key enabling solution to future smart grids by integrating distributed renewable generators and storage systems to efficiently serve the local demand. However, due to the random and intermittent characteristics of renewable energy, new challenges arise for the reliable operation of microgrids. To address this issue, we study in this paper the real-time energy management for a single microgrid system that constitutes a renewable generation system, an energy storage system, and an aggregated load. We model the renewable energy offset by the load over time, termed net energy profile, to be practically predictable, but with finite errors that can be arbitrarily distributed. We aim to minimize the total energy cost (modeled as sum of time-varying strictly convex functions) of the conventional energy drawn from the main grid over a finite horizon by jointly optimizing the energy charged/discharged to/from the storage system over time subject to practical load and storage constraints. To solve this problem in real time, we propose a new off-line optimization approach to devise the online algorithm. In this approach, we first assume that the net energy profile is perfectly predicted or known ahead of time, under which we derive the optimal off-line energy scheduling solution in closed-form. Next, inspired by the optimal off-line solution, we propose a sliding-window based online algorithm for real-time energy management under the practical setup of noisy predicted net energy profile with arbitrary errors. Finally, we conduct simulations based on the real wind generation data of the Ireland power system to evaluate the performance of our proposed algorithm, as compared with other heuristically designed algorithms, as well as the conventional dynamic programming based solution.

Real-Time Energy Storage Management for Renewable Integration in Microgrid: An Off-Line Optimization Approach

The increasing integration of the distributed renewable energy sources highlights the requirement to design various control strategies for microgrids (MGs) and microgrid clusters (MGCs). The multiagent system (MAS)-based distributed coordinated control strategies show the benefits to balance the power and energy, stabilize voltage and frequency, achieve economic and coordinated operation among the MGs and MGCs. However, the complex and diverse combinations of distributed generations (DGs) in MAS increase the complexity of system control and operation. In order to design the optimized configuration and control strategy using MAS, the topology models and mathematic models such as the graph topology model, noncooperative game model, the genetic algorithm, and particle swarm optimization algorithm are summarized. The merits and drawbacks of these control methods are compared. Moreover, since the consensus is a vital problem in the complex dynamical systems, the distributed MAS-based consensus protocols are systematically reviewed. On the other hand, the communication delay issue, which is inevitable no matter in the low- or high-bandwidth communication networks, is crucial to maintain the stability of the MGs and MGCs with fixed and random delays. Various control strategies to compensate the effect of communication delays have been reviewed, such as the neural network-based predictive control, the weighted average predictive control, the gain scheduling scheme, and synchronization schemes based on the multitimer model for the case of fixed communication delay, and the generalized predictive control, networked predictive control, model predictive control, Smith predictor, $H_{\infty}$ -based control, sliding mode control for the random communication delay scenarios. Furthermore, various control methods have been summarized to describe switching topologies in MAS with different objectives, such as the plug-in or plug-out of DGs in an MG, and the plug-in or plug-out of MGs in an MGC, and multiagent-based energy coordination and the economic dispatch of the MGC. Finally, the future research directions of the multiagent-based distributed coordinated control and optimization in MGs and MGCs are also presented.

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MAS-Based Distributed Coordinated Control and Optimization in Microgrid and Microgrid Clusters: A Comprehensive Overview

The smart grid is an unprecedented opportunity to shift the current energy industry into a new era of a modernized network where the power generation, transmission, and distribution are intelligently, responsively, and cooperatively managed through a bi-directional automation system. Although the domains of smart grid applications and technologies vary in functions and forms, they generally share common potentials such as intelligent energy curtailment, efficient integration of Demand Response, Distributed Renewable Generation, and Energy Storage. This paper presents a comprehensive review categorically on the recent advances and previous research developments of the smart grid paradigm over the last two decades. The main intent of the study is to provide an application-focused survey where every category and sub-category herein are thoroughly and independently investigated. The preamble of the paper highlights the concept and the structure of the smart grids. The work presented intensively and extensively reviews the recent advances on the energy data management in smart grids, pricing modalities in a modernized power grid, and the predominant components of the smart grid. The paper thoroughly enumerates the recent advances in the area of network reliability. On the other hand, the reliance on smart cities on advanced communication infrastructure promotes more concerns regarding data integrity. Therefore, the paper dedicates a sub-section to highlight the challenges and the state-of-the-art of cybersecurity. Furthermore, highlighting the emerging developments in the pricing mechanisms concludes the review.

A Comprehensive Review of Recent Advances in Smart Grids: A Sustainable Future with Renewable Energy Resources

Energy management systems for microgrids (EMS-MG) play an important role in ensuring their stable and economic operation. This paper presents a multiagent-based hybrid EMS-MG (HEMS-MG) with both centralized and decentralized energy control functionalities. Based on this framework, three-level hierarchical energy management strategies are presented, in which a cooperation method with contract net protocol and multifactor evaluation mechanisms are applied. A coordinated energy management framework is realized by the combination of autonomous control of local distributed energy resources at the local level with coordinated energy control at the central level of the microgrid. A novel simulation platform for the HEMS-MG is designed in terms of the client–server frame and implemented under the C++ Builder environment. To prove the effectiveness and benefits of the proposed control system, an example of generation cooperation control of a laboratory microgrid is provided. The simulation results show that the proposed control system is an effective way to manage and optimize microgrid operation.

Multiagent-Based Hybrid Energy Management System for Microgrids

Advances in smart grid technology have yet to coalesce into a comprehensive solution integrating the landscape of future power systems. The microgrid concept may offer a solution for combining advanced components and enabling technologies within an infrastructure that must expand to meet emerging demands. As autonomous power system entities, microgrids require robust real-time power management and control to simultaneously operate jointly with the utility, provide reliable service, and help achieve customer-driven objectives utilizing local power system assets. In this paper, a decentralized control architecture for microgrids is presented, along with a simulation environment appropriate for on-going investigations into real-time, agent-based decision-making. Challenges faced by operating self-organizing multi-agent system (MAS) are presented, as well as results for a representative power management scenario for a multi-asset microgrid capable of operating in grid-interconnected or islanded mode. The system and formulations presented demonstrate the viability and capability of decentralized agent-based control for microgrids and illustrate their potential towards achieving smart grid goals.

Comprehensive Real-Time Microgrid Power Management and Control With Distributed Agents

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Comprehensive Real-Time Microgrid Power Management and Control With Distributed Agents