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

Some expansion plans consider a lower demand scenario, producing an increase in the network losses and the risk of a failure on the protection devices. The solution of this problem comprises addition of new feeders to get the system back to an adequate operating level. The formulation of this problem results in a optimization problem classified as of NP- hard. Additionally, there are operational constraints that must be considered, such as the maximum current per feeder and the consideration that some feeders are forced to share routes in urban areas. Given the real demand data and the planning period, a new load forecast is performed making possible to determine the number of feeders to supply the loads. Due to the size of the problem, a ldquodivide and conquerrdquo strategy is applied by means of Voronoi polygons, making possible to establish coverage areas for each feeder. The final assigned areas are determined using a genetic algorithm (GA) that balances the load among feeders. Thus, the expansion problem is divided into coverage areas and for each of them a GA based on the generation of random spanning trees where three different types of costs are considered (expansion costs, reinforcement costs and operational costs) is applied. This paper presents results for artificially simulated system.

Genetic algorithms and Voronoi polygons applied to decision making in the distribution systems expansion problem

This paper proposes a dynamic integrated electricity and gas investment (DIEGI) model based on multi-objective optimization concepts that can capture uncertainty in both hydro conditions (i.e. inflows) and demand growth. Thus, our model can determine efficient and adequate electricity and natural gas infrastructure that can deal with hydro conditions driven by extreme natural hazards (e.g. drought), and it also considers the risk of stranded assets in future periods when demand growth is less than expected (both hydro conditions and demand growth can be extremely volatile in countries such as Colombia, Brazil, Chile and Peru). Our multi-objective approach allows regulators and policy-makers to determine not only the least investment and operational cost solution, but also an array of investment portfolios that are Pareto efficient when considering budget constraints (that is the case in some developing countries). Through a case of study, we demonstrate that gas infrastructure plays a critical role in cost and reliability levels of the electricity infrastructure, and that integrated electricity and gas planning can significantly improve the robustness of the combined energy infrastructure to face uncertain scenarios in terms of demand and hydro inflows.

Integrated planning of electricity and natural gas systems under uncertain hydro inflows: A multi-objetive approach

The increasing use of variable generation technologies (VGTs) in power systems, such as wind and photovoltaic generation, has introduced new challenges in the definition of capacity remuneration mechanisms for promoting system reliability. In this context, in this article we propose a novel framework for determining the capacity value of VGTs to contribute to the generation system adequacy, as well as a corresponding method for allocating capacity payments in hydrothermal power systems. We show that the capacity value of VGTs increases with the presence of water reservoirs, since VGTs help relieving hydropower plants from using scarce water resources during off-peak hours thus making more resources available to supply the demand during peak hours.

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Capacity payment allocation in hydrothermal power systems with high shares of renewable energies

This paper presents a new robust distributed approach for the energy management of rural multi‐microgrids communities in Chile. These rural communities are often geographically isolated and have a poor connection to the main electricity grid. Operating them as individual microgrids allows the community to connect to the grid or behave as a stand‐alone system (islanded). Connecting and coordinating the operation of the microgrids can improve the system's robustness to energy and demand uncertainty, as well as reducing the dependency on the main grid. However, this coordination can be challenging because the communication between the different microgrids can sometimes deteriorate, moreover, both load and local generation profiles are challenging to predict. For these reasons, in this paper, a new robust distributed hierarchical Energy Management System (EMS) for coordination of multiple microgrids (multi‐microgrids) is introduced, which uses robust distributed Model Predictive Control (MPC). Distributed optimisation permits improving reliability in the presence of poor or lack of communications between microgrids. To consider the uncertainty associated with renewable energy generation and load consumption, fuzzy prediction interval models are included in the MPC design. The proposed method is compared with robust centralised MPC and deterministic distributed MPC to assess its performance. Simulation results are presented using data representative of a rural community in coastal Chile applied to the robust MPC design. The outcomes of this work demonstrate that the proposed robust distributed EMS can improve the power supply, apply peak shaving, and can successfully operate when there is a loss of communication between microgrids. The use of decreasing fuzzy intervals allows an accurate prediction of both load and renewable energy generation, making the system robust to uncertainty in the available resources. Moreover, results show that in absence of communication, the power supply obtained under different scenarios with the distributed EMS is better than the equivalent centralised EMS.

A robust distributed energy management system for the coordinated operation of rural multi‐microgrids

This paper presents an interactive algorithm based on game theory for optimizing an energy management system (EMS) of a microgrid. As agents in game, load, storage and energy resources adopt an individual strategy and through a potential game, they are able to reach a Nash Equilibrium. Results show energy dispatch for four different agents conditions, including exclusion of one of the energy sources to emulate plug and play behavior. Availability and ease to change parameters for agents in proposed algorithm allows users tune it for several different conditions, achieving a useful tool for energy management in a microgrid.

Guillermo Jimenez-Estevez

Papers

Genetic algorithms and Voronoi polygons applied to decision making in the distribution systems expansion problem

Integrated planning of electricity and natural gas systems under uncertain hydro inflows: A multi-objetive approach

Capacity payment allocation in hydrothermal power systems with high shares of renewable energies

A robust distributed energy management system for the coordinated operation of rural multi‐microgrids

Microgrid Energy Management System Optimization using Game Theory