Vinicio Iñiguez-Morán

The growing complexity of distributed energy systems and the rise of peer-to-peer energy markets demand innovative solutions for efficient, resilient, and sustainable energy management. However, existing research often remains fragmented, with limited integration between control strategies, optimization frameworks, and practical implementation. This paper presents a comprehensive systematic review, following the PRISMA methodology, that synthesizes findings from 94 high-quality studies and addresses the lack of consolidated insights across technical, operational, and architectural layers. This review highlights advancements in six key areas: optimization and modeling, multi-agent systems, simulations, blockchain and smart contracts, robust frameworks, and electric machines. Despite progress, several studies reveal challenges related to scalability, data privacy, computational complexity, and system adaptability, particularly in dynamic and decentralized environments. Stochastic–robust optimization and multi-agent systems improve decentralized coordination, while blockchain enhances security and automation in peer-to-peer trading. Simulations validate energy strategies, bridging theory and practice, and electric machines support renewable integration and grid flexibility. The synthesis underscores the need for unified frameworks that combine artificial intelligence, predictive control, and secure communication protocols. This review aims to provide a roadmap for advancing distributed energy systems toward scalable, resilient, and sustainable energy solutions.

The integration of renewable energy sources into isolated microgrids introduces significant power fluctuations due to their intermittent nature. This study addresses the need for advanced power smoothing methods to enhance the stability of isolated networks. An innovative adaptive strategy is presented, combining photovoltaic solar generation with vehicle-to-grid technology, utilizing an enhanced adaptive moving average filter with fuzzy logic control. The primary objective is to dynamically optimize the time frame of the Li-ion battery energy storage system for immediate power stabilization, leveraging the high energy density and rapid response capabilities inherent in electric vehicle batteries. The methodology encompasses data acquisition from photovoltaic panels, definition of fuzzy logic control rules, and implementation of the proposed method within a computer-controlled system connected to a bidirectional three-phase inverter. Experimental results highlight the proposed method’s superiority over conventional moving averages and ramp-rate filters.

Implementing Energy Storage Systems (ESS) is increasingly significant in power electrical systems. This is attributed to their ability to store surplus electricity generated by renewable energy sources such as wind and solar, contributing to the balance between generation and demand. Literature studies indicate that this practice enhances network stability and diminishes the need for expensive redesigns in infrastructure. This paper presents an exhaustive experimentation-based study of the dynamic response provided by three energy storage system technologies: supercapacitors, Lithium-Ion batteries, and Vanadium redox flow batteries, technologies with significant academic, research, and industrial interests nowadays. The objective of this research is the experimental evaluation of the performance of such technologies in real electrical system operations, focusing on determining the efficiency of charge and discharge, as well as the tracking of active and reactive power achieved through the associated grid interface. The experimental tests performed in a microgrid laboratory show these technologies’ advantages and limitations in different grid-integration applications, with the Lithium-Ion battery-based ESS demonstrating the highest efficiency and faster power response. The results achieved and reported in the article can serve as an essential input for researchers and technology developers to feed their models with more precise parameters and data that might provide results closer to the actual behaviour of the studied prototypes. The methodological framework used in this research is descriptive, experimental, and quantitative.

The reliance on imported fuels for electricity generation and internal transportation in insular electrical systems has historically posed a significant challenge due to their geographic isolation. The vulnerability of insular ecosystems to pollution has driven the need to transition toward renewable energy sources. Despite their inherent variability, wind and solar energy have gained acceptance. Integrating these renewable technologies into insular grids presents technical challenges that impact the quality of the power supply, particularly with the increasing presence of electric vehicles. Nevertheless, the batteries of these vehicles provide an opportunity to enhance network performance. This article introduces an innovative power smoothing technique that utilizes electric vehicle batteries to optimize self-consumption and reduce power fluctuations. The proposed method is an enhanced version of the ramp-rate energy smoothing method, incorporating adaptability through real-time control of the ramp-rate using fuzzy logic. It employs an aggregated model of lithium-ion batteries with a bidirectional power electronic converter. Experimental validation is carried out in the Micro-Grid Laboratory of the University of Cuenca, Ecuador. Experimental results demonstrate a significant 14% reduction in energy generation variability, resulting in a more stable electrical supply profile. Additionally, there is a marginal improvement in energy delivery, with an additional injection of 0.23 kWh compared to scenarios without the participation of electric vehicle batteries in power smoothing tasks. These findings support the effectiveness of the proposed approach in optimizing the integration of intermittent renewable generators and electric vehicle charging in insular energy systems.

Nowadays, energy decarbonization due to integrating renewable energy sources presents important challenges to overcome. The intermittent nature of photovoltaic systems reduces power quality by producing voltage variations and frequency deviations in electrical system networks, especially in weak and isolated distribution systems in developing countries. This paper presents a power smoothing method for improving the low-pass filter and moving average for grid-connected photovoltaic systems. This novel method includes state-of-charge monitoring control of the supercapacitor’s energy storage system to reduce the fluctuations of photovoltaic power at the point of common coupling. A case study for a microgrid in a high-altitude city in Ecuador is presented with exhaustive laboratory tests using real data. This research aims to improve energy power quality in electrical distribution systems to cope with the growth of renewable penetration. The results demonstrate significant power quality and stability improvements achieved through the proposed method. For instance, the power smoothing method effectively reduced power fluctuations by 16.7% with the low-pass filter, 14.05% with the ramp-rate filter, and 9.7% with the moving average filter.

Nowadays, energy decarbonization due to the integration of renewable energy sources presents important challenges to overcome. The intermittent nature of photovoltaic systems reduces power quality by producing voltage variations and frequency deviations in electrical systems networks, especially, in weak and isolated distribution systems in developing countries. This paper presents a power smoothing method improving the low pass filter and moving average for grid-connected photovoltaic system, the novel method includes state-of-charge monitoring control of the supercapacitors energy storage system to reduce the fluctuations of photovoltaic power at the point of common coupling. A case study for a microgrid in a high-altitude city in Ecuador is presented with exhaustive laboratory tests using real data. The ultimate goal of this research is to improve energy power quality in electrical distribution systems to cope with the growth of renewable penetration.

Este artículo presenta la implementación práctica de una técnica de control de frecuencia (inercia virtual) en un sistema de almacenamiento energético basado en el uso de supercondensadores (SAE-SC). La propuesta estuvo diseñada para brindar soporte de frecuencia a una microrred eléctrica aislada real que integra fuentes de generación renovable (solar fotovoltaica, 15 kWp), generación síncrona convencional (térmico diésel, 44 kVA) y sistemas de almacenamiento energético (SAE-SC, 30 kW). Tomando como caso base la operación en condiciones normales de una microrred híbrida solar-diésel (una situación típica de sistemas insulares), se comprobó la efectividad de las labores de soporte de frecuencia provisto por el SAE-SC y se evaluó la resiliencia de la microrred en términos de esta variable. Los resultados experimentales mostraron que la implementación de la propuesta permitió reducir las fluctuaciones de frecuencia de la microrred en un 30%, representando una mejora significativa en la calidad del suministro eléctrico. Los experimentos se llevaron a cabo en el Laboratorio de Micro-Red del Centro Científico, Tecnológico y de Investigación Balzay (CCTI-B) de la Universidad de Cuenca.