The increasing interest in integrating intermittent renewable energy sources into microgrids presents major challenges from the viewpoints of reliable operation and control. In this paper, the major issues and challenges in microgrid control are discussed, and a review of state-of-the-art control strategies and trends is presented; a general overview of the main control principles (e.g., droop control, model predictive control, multi-agent systems) is also included. The paper classifies microgrid control strategies into three levels: primary, secondary, and tertiary, where primary and secondary levels are associated with the operation of the microgrid itself, and tertiary level pertains to the coordinated operation of the microgrid and the host grid. Each control level is discussed in detail in view of the relevant existing technical literature.

Trends in Microgrid Control

In this paper, the analysis of recent advances in genetic algorithms is discussed. The genetic algorithms of great interest in research community are selected for analysis. This review will help the new and demanding researchers to provide the wider vision of genetic algorithms. The well-known algorithms and their implementation are presented with their pros and cons. The genetic operators and their usages are discussed with the aim of facilitating new researchers. The different research domains involved in genetic algorithms are covered. The future research directions in the area of genetic operators, fitness function and hybrid algorithms are discussed. This structured review will be helpful for research and graduate teaching.

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A review on genetic algorithm: past, present, and future

This paper presents a review of control strategies, stability analysis, and stabilization techniques for dc microgrids (MGs). Overall control is systematically classified into local and coordinated control levels according to respective functionalities in each level. As opposed to local control, which relies only on local measurements, some line of communication between units needs to be made available in order to achieve the coordinated control. Depending on the communication method, three basic coordinated control strategies can be distinguished, i.e., decentralized, centralized, and distributed control. Decentralized control can be regarded as an extension of the local control since it is also based exclusively on local measurements. In contrast, centralized and distributed control strategies rely on digital communication technologies. A number of approaches using these three coordinated control strategies to achieve various control objectives are reviewed in this paper. Moreover, properties of dc MG dynamics and stability are discussed. This paper illustrates that tightly regulated point-of-load converters tend to reduce the stability margins of the system since they introduce negative impedances, which can potentially oscillate with lightly damped power supply input filters. It is also demonstrated that how the stability of the whole system is defined by the relationship of the source and load impedances, referred to as the minor loop gain. Several prominent specifications for the minor loop gain are reviewed. Finally, a number of active stabilization techniques are presented.

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DC Microgrids—Part I: A Review of Control Strategies and Stabilization Techniques

(1990). ENERGY FUNCTION ANALYSIS FOR POWER SYSTEM STABILITY. Electric Machines & Power Systems: Vol. 18, No. 2, pp. 209-210.

Energy function analysis for power system stability

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

Advanced control strategies are vital components for realization of microgrids. This paper reviews the status of hierarchical control strategies applied to microgrids and discusses the future trends. This hierarchical control structure consists of primary, secondary, and tertiary levels, and is a versatile tool in managing stationary and dynamic performance of microgrids while incorporating economical aspects. Various control approaches are compared and their respective advantages are highlighted. In addition, the coordination among different control hierarchies is discussed.

Hierarchical Structure of Microgrids Control System

This paper proposes a secondary voltage control of microgrids based on the distributed cooperative control of multi-agent systems. The proposed secondary control is fully distributed; each distributed generator only requires its own information and the information of some neighbors. The distributed structure obviates the requirements for a central controller and complex communication network which, in turn, improves the system reliability. Input-output feedback linearization is used to convert the secondary voltage control to a linear second-order tracker synchronization problem. The control parameters can be tuned to obtain a desired response speed. The effectiveness of the proposed control methodology is verified by the simulation of a microgrid test system.

/pdf/distributed-cooperative-secondary-control-of-microgrids-2g3woto403.pdf

Distributed Cooperative Secondary Control of Microgrids Using Feedback Linearization

Partial shading in photovoltaic (PV) arrays renders conventional maximum power point tracking (MPPT) techniques ineffective. The reduced efficiency of shaded PV arrays is a significant obstacle in the rapid growth of the solar power systems. Thus, addressing the output power mismatch and partial shading effects is of paramount value. Extracting the maximum power of partially shaded PV arrays has been widely investigated in the literature. The proposed solutions can be categorized into four main groups. The first group includes modified MPPT techniques that properly detect the global MPP. They include power curve slope, load-line MPPT, dividing rectangles techniques, the power increment technique, instantaneous operating power optimization, Fibonacci search, neural networks, and particle swarm optimization. The second category includes different array configurations for interconnecting PV modules, namely series-parallel, total-cross-tie, and bridge-link configurations. The third category includes different PV system architectures, namely centralized architecture, series-connected microconverters, parallel-connected microconverters, and microinverters. The fourth category includes different converter topologies, namely multilevel converters, voltage injection circuits, generation control circuits, module-integrated converters, and multiple-input converters. This paper surveys the proposed approaches in each category and provides a brief discussion of their characteristics.

Control and Circuit Techniques to Mitigate Partial Shading Effects in Photovoltaic Arrays

This study proposes a secondary voltage and frequency control scheme based on the distributed cooperative control of multi-agent systems. The proposed secondary control is implemented through a communication network with one-way communication links. The required communication network is modelled by a directed graph (digraph). The proposed secondary control is fully distributed such that each distributed generator only requires its own information and the information of its neighbours on the communication digraph. Thus, the requirements for a central controller and complex communication network are obviated, and the system reliability is improved. The simulation results verify the effectiveness of the proposed secondary control for a microgrid test system.

https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/iet-gtd.2012.0576

Secondary control of microgrids based on distributed cooperative control of multi-agent systems

Existing electric power distribution networks are operating near full capacity and facing rapid changes to address environmental concerns and improve their reliability and sustainability. These concerns are satisfied through the effective integration and coordination of distributed generators (DGs), which facilitate the exploitation of renewable energy resources, including wind power, photovoltaics, and fuel cells [1]. Although DGs can be of rotating machinery type, more recently, DGs have been designed to support renewable energy resources by electronic interfacing through voltage source inverters (VSI). Each DG corresponds to one energy source, and its control inputs are given to the interface VSI [1]-[5]. The successful coordination of DGs can be realized through microgrids, which are small-scale power systems consisting of local generation, local loads, and energy storage systems. Microgrids are autonomous subsystems with dedicated control systems that provide guaranteed power quality for local loads such as hospitals, economic centers, apartments, and universities. The microgrid concept, with its local control and power quality support, allows for the scalable integration of local power resources and loads into the existing power grid and enables a high penetration of distributed generation [5]-[10].

Ali Bidram

Papers

Hierarchical Structure of Microgrids Control System

Distributed Cooperative Secondary Control of Microgrids Using Feedback Linearization

Control and Circuit Techniques to Mitigate Partial Shading Effects in Photovoltaic Arrays

Secondary control of microgrids based on distributed cooperative control of multi-agent systems

Distributed Control Systems for Small-Scale Power Networks: Using Multiagent Cooperative Control Theory