An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

The Self-Organizing Map

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

Microgrids are now emerging from lab benches and pilot demonstration sites into commercial markets, driven by technological improvements, falling costs, a proven track record, and growing recognition of their benefits. They are being used to improve reliability and resilience of electrical grids, to manage the addition of distributed clean energy resources like wind and solar photovoltaic (PV) generation to reduce fossil fuel emissions, and to provide electricity in areas not served by centralized electrical infrastructure. This review article (1) explains what a microgrid is, and (2) provides a multi-disciplinary portrait of today's microgrid drivers, real-world applications, challenges, and future prospects.

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Microgrids: A review of technologies, key drivers, and outstanding issues

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 new concept for future energy distribution system that enables renewable energy integration. It generally consists of multiple distributed generators that are usually interfaced to the grid through power inverters. For the islanding operation of ac microgrids, two important tasks are to share the load demand among multiple parallel connected inverters proportionately, and maintain the voltage and frequency stabilities. This paper reviews and categorizes various approaches of power sharing control principles. Simultaneously, the control schemes are graphically illustrated. Moreover, various control approaches are compared in terms of their respective advantages and disadvantages. Finally, this paper presents the future trends.

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Review of Power Sharing Control Strategies for Islanding Operation of AC Microgrids

Distribution network Greenfield planning is recognized as an important task of the planning studies. This importance lies in its use as a regulatory tool to determine the distribution charges applied to final users. However, the Greenfield planning requires solving a combinatorial optimization problem classified as a NP-hard. Because of its complexity, different models based on heuristic strategies have been proposed to solve this problem. In this work, an evolutionary strategy -as a global search methodology-is proposed. The corresponding Greenfield problem is formulated considering the network capacity constraints and the voltage drop. The proposed algorithm assumes that the system elements costs and its optimal assignment are provided beforehand. Next, the individuals' generation is based on a heuristic biased construction of random spanning trees. Then, the fitness function penalizes the unfeasible solutions with a dynamic function. Finally, four crossover methodologies are proposed and evaluated on a test case. A comparison of the solutions and the algorithm performance is performed on a test case system.

An Evolutionary Approach for the Greenfield Planning Problem in Distribution Networks

In model based control approaches for the dynamic operation of renewable-energy based microgrid, an accurate demand forecast is crucial. However, the high level of uncertainties in the system and non-linearities make the task of prediction not easy. In this context, we propose the use of a stable Takagi & Sugeno (T&S) fuzzy model to perform the demand forecasting in a real-life microgrid located in Huatacondo, Chile. Based on real-data from the microgrid, located in northern Chile, the T&S fuzzy model was identified and compared with an adaptive neural network, showing the T&S fuzzy model better open-loop prediction capabilities. To increase the prediction capability, an analysis of the amount of historical data needed, and the frequency required for training purposes was also done. For the case study, it is suggested to use a large amount of data rather than increasing the training frequency.

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Fuzzy demand forecasting in a predictive control strategy for a renewable-energy based microgrid

Smart grid is understood to be the key enabling technology for renewable energy development. This concept can be extended to the energy supply challenge in rural areas in Latin America. Abundant distributed renewable energy resources surrounding isolated towns offer an unique opportunity for the development of smart and cost-effective isolated microgrids allowing: efficient use of local resources, reduction in the operational costs and fossil fuels dependency, extension of the system components lifetime, commitment of the local community. This paper presents a smart microgrid design solution covering both the technical and the community integration aspects. The approach is applied in the framework of an R&D project to a real isolated town located in the Chilean northern region. Finally, the extension of the proposal for other Latin American regions is discussed.

Smart grid solutions for rural areas

The pattern recognition approach for security analysis (SA) of power systems has been presented as a promising tool for on-line applications. This paper applies a learning-based nonlinear classifier, which is a support vector machine (SVM) for SA. Three single SVM are trained to classify the state of the system: secure, alert and emergency. The final classification is obtained combining the output of each classifier with a Bayesian rule. The effectiveness of the proposed approach has been demonstrated on two IEEE test systems.

Support vector machines for on-line security analysis of power systems

Summary
This paper proposes a novel simulator of energy consumption patterns that allows designing demand side management (DSM) strategies without economic incentives. The simulator emulates consumers' patterns with and without installed DSM interfaces, based on both actual consumption measurements and surveys applied to the inhabitants of an existing isolated microgrid (Huatacondo, Chile) that has a particular DSM strategy without economic incentives. The simulator uses Markov chains to generate data characterizing consumption patterns without DSM and Bayesian networks for cases in which the users respond to the DSM strategy. Data obtained from the simulator are used to derive a response model of the consumers to the DSM interface, which can be included for the energy management system design. Results show that the implemented strategy can be effective and can generate savings up to 4.45% in diesel consumption for an ideal case where all the dwellings have the interface installed. Copyright © 2016 John Wiley & Sons, Ltd.

Guillermo Jimenez-Estevez

Papers

An Evolutionary Approach for the Greenfield Planning Problem in Distribution Networks

Fuzzy demand forecasting in a predictive control strategy for a renewable-energy based microgrid

Smart grid solutions for rural areas

Support vector machines for on-line security analysis of power systems

Consumption modeling based on Markov chains and Bayesian networks for a demand side management design of isolated microgrids