Microgrids have gathered a significant amount of attention within the past decade and becoming an essential asset in the energy industry. The ability to integrate sustainable energy generation methods into the distribution network is one of the main reasons for microgrids popularity. A wide variety of Distributed Generation (DG) including wind and other micro-turbine generation, photovoltaic generation along with energy storage, makes the microgrid viable in both grid-connected and islanded modes while reducing the power losses. There are various technical challenges to be tackled in order to harvest the full potential of microgrids, and protection is one of them. Various solutions were introduced, driven by the development of protection techniques. One of the most promising approaches for microgrid protection is adaptive protection. This paper contains a systematic review on adaptive protection of microgrids, including a wide range of applicability variants, their strengths, and drawbacks. It also explores the state-of-the-art researches that utilize computational intelligence to achieve adaptive protection. These solutions are currently at the verge of totally redefining protection solutions with a more flexible and reliable system that will be applied globally.

The application of Multi-Agent Systems (MAS) in electrical power systems are becoming popular due to their inherent benefits such as increased autonomy, reactivity, proactivity and social ability. This paper reviews current research on the application of multi-agent systems in microgrid schemes. The paper is mainly focused on recent developments of multi-agent systems in different aspects of microgrids such as control, market modeling, optimization and power restoration. The future directions of multi-agent systems in microgrid applications are also discussed briefly. Furthermore, this review is concluded by discussing the development of an enhanced multi-agent based distributed control framework for microgrids.

Over the last century, there has been no significant change in the centrally controlled structure of electrical power grids. The economic and population growth throughout the planet increases the pressure on the power sector. Power electrical grid, as the main structure for power transmission has to reconsider its concepts. The flexible controlling of DER (Distributed Energy Resources) such as wind power, solar power, hydropower, wave power, geo-thermal power and biomass power has to be considered to overcome these challenges. The demand for electricity is steadily increasing and current centrally controlled structure is ill-suited to fulfill the modern complex power requirements. As a result the concepts like micro grids, smart grids, multi-energy systems, virtual power plants are emerging combined with new concepts like MAS (Multi-Agent Systems) and IoT (Internet of Things). They move our electrical power grid to a more decentralized, highly efficient energy management system. The objective of this paper is to discuss how multi-agent concept based energy management systems will behave for micro grids. The paper contributes a description of smart micro grids, MAS based Energy management systems and controlling of DER in micro grids, and future of power electrical grid structure with MAS.

High penetration of renewable energies to smart grid technologies has lead the traditional electrical transmission and distribution network to undergo a significant evolution. Here, advanced control strategies are required to ensure the load balance in order to keep the voltage and frequency variation within an acceptable range. With the integration of dc energy sources and storages, another control constraint would be added due to the limitations in a storage system. Among recent developments in control techniques, fuzzy logic and multi agent systems have emerged due to its strong control action in an uncertain environment. Researchers have made satisfactory efforts in optimizing hybrid renewable energy sources using these technologies. This paper strives to highlight the approaches of controlling the energy storage systems, dc voltage, frequency, and ac voltage with the aid of the fuzzy logic and multi agent systems related controllers.

Even though solar power generation has become an emerging trend in the world, its penetration into the utility grid as a distributed generation source is not a satisfactory measure due to the inherent issues related to solar photovoltaic systems (SPVSs). In addressing these issues, microgrids have been identified as suitable integrating platforms for distributed, clean energy resources such as SPV. Different SPV and microgrid architectures are available for different applications depending on the resource availability and controllability. Reconfigurability is a concept that makes a system adaptable to two or more different environments by effectively utilizing the available resources. The review explains the applications of reconfigurable approaches on solar PV systems such as reconfigurable PV arrays, power conditioning unit (DC/DC converter, DC/AC inverter), microgrid controller and topology of distribution network with relevant studies. An analysis is also presented considering the unique features of reconfigurable systems in comparison to the static systems.

Microgrids have been popularized in the past decade because of their ability to add distributed generation into the classic distribution systems. Protection problems are among several other problems that need solutions in order to extract the full capability of these novel networks. This research follows the branches of two major solutions, namely adaptive protection and protection optimization. Adaptive protection implementation with a novel concept of clustering is considered, and protection setting optimization is done using a novel hybrid nature-inspired algorithm. Adaptive protection is utilized to cope with the topology variations, while optimization techniques are used to calculate the protection settings that provide faster fault clearances in coordination with backup protection. A modified IEEE 14 bus system is used as the test system. Validation was done for the fault clearing performance. The selected algorithm was effective than most other algorithms, and the clustering approach for adaptive overcurrent protection was able to reduce the number of relays’ setting groups.