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Distorted voltage supplied as unbalanced and/or non-constant frequency can be found in weak grids, such as microgrids, or systems working in islanding mode. These kinds of systems are more sensitive under load changes. Particularly, an unbalanced voltage supply may be produced for large, single-phase loads. On the other hand, the connection/disconnection of high current loads may lead to important frequency variation, especially in weak grids where the short circuit current capacity is reduced. These conditions make the control of the power converter a more difficult task, because of the variations in the frequency and unbalancing. To address these issues, this paper proposes a resonant control algorithm to deal with variations in the voltage amplitude as well as grid frequency when a distorted power supply is considered. The frequency variation is an important drawback for resonant control because the resonance must be tuned at the grid frequency. This issue is overcome by using a variable sampling frequency in order to avoid re-tuning the controller parameters. On the other hand, under unbalanced conditions, the proposed method relaxes the phase with lower voltage amplitude by taking more power from the other phases in order to help the stability of the grid supply. To corroborate the mathematical analysis and the proposed control, a stability study is performed, including experimental and simulated results.

Over the past few decades, Central American countries have seen a steady increase in their energy needs. Luckily, the region has abundant renewable energy resources and, as a result, has been busy constructing wind and photovoltaic power facilities. However, while these renewable sources are promising, they come with some risks—mainly, their variable power generation can pose a challenge to the interconnected regional system. This paper explores the current state of the Central American power system and the obstacles it faces as it strives to transition to a more environmentally-friendly energy system. To do so, the authors employed power flow analysis and transient stability studies, which were conducted using ETAP (Electrical Transient Analyzer Program) to model and simulate the power system. Their study revealed that the Central American power system is at risk of instability, and they suggest that integrating ancillary services and storage solutions could strengthen its resilience. Additionally, the authors advocate for the development of microgrids, energy management, and sustainable decarbonization plans. Lastly, the authors emphasize the importance of short-, medium-, and long-term power planning to make better decisions.

The growing demand for electricity and the constant increase in electricity rates have intensified the interest of residential and non-residential energy consumers to reduce their energy consumption. The introduction of non-conventional renewable energies (photovoltaic and wind, in the residential case) demands new proposals to obtain a home energy management system (HEMS), which allows reducing the use of electrical energy. This article incorporates artificial intelligence techniques to demand response, allowing control, switching, turning on and off of appliances, modifying and reducing consumption, and achieving improvements in the quality of life in the home. In addition, an architecture based on a smart socket and an artificial intelligence model that recognizes the consumption of electrical appliances in high resolution (sampling every 10 s) is proposed. The system uses the Wi-Fi communication protocol, ensuring that the smart sockets wirelessly provide the data obtained to the public cloud. The use of Deep Learning allows us to obtain a central control model of the home, which, when interconnected to the smart electrical distribution networks of companies, could generate a positive impact on the environmental effects and CO2 reduction.

The integration of renewable energy sources into electrical power systems presents enormous challenges in technical terms, especially with energy storage. Battery electrochemical storage systems (BESSs) are becoming a crucial solution for reducing the intermittency of renewable energy supply and enhance the stability of power networks. Nonetheless, its extensive implementation confronts constraints, including expense, life expectancy, and energy efficiency. Simultaneously, these technologies present prospects for improved energy management, increase the hosting capacity of renewable energy, and diminish reliance on fossil fuels. This paper investigates the obstacles of integrating electrochemical storage into electrical power systems, explores solutions to use its promise for creating more resilient and sustainable grids, and presents a method for the size estimation and strategic allocation of electrochemical energy storage systems (EESSs). The aim is to improve grid voltage profiles, manage demand response, increase the adoption of renewable energy resources, enhance power transfer among various areas, and subsequently improve the stability of a power system during large disturbances. The methodology utilizes a multi-stage optimization process based on economic considerations supported by dynamic simulation. This methodology was tested employing a validated dynamic model of the Interconnected Electrical System of the Central American Countries (SIEPAC). The system experienced multiple significant blackouts in recent years, primarily due to the increasing amount of renewable energy generation without adequate inertial support and limited power transfer capabilities among countries. Based on the results of using the technique, EESSs can effectively lower the risk of instability caused by an imbalance between power generation and demand during extreme situations, as seen in past event reports. Based on economical constraints, it has been determined that the cost of installing EESSs for the SIEPAC, which amounts to 1200 MWh/200 MW, is 140.91 USD/MWh.

In this paper, a pricing alternative based on the scheme of Time of Use Pricing (TOUP) is proposed for customers connected to the Cooperativa Eléctrica San Pedro de Atacama (CESPA) microgrid, located in the far north of Chile. With this proposal, the promotion of Demand-Side Management, DSM, aims at optimizing both the use of electric energy and the available infrastructure. The pricing proposal replaces the current tariff scheme based on sections of energy consumption and does not give an incentive for customers to efficiently manage their energy consumption. The proposal considers the creation of time bands and their corresponding tariff formulas, to obtain economic benefits both for customers and the electric company. Study cases consider the operation of a photovoltaic plant of 2 MWp in the electric system of CESPA, which is currently underway. The obtained results report benefits for all parts of the electric market. For customers, favorable pricing up to a 19.1% monthly reduction in electric bills is shown, whereas the company presents an increment in their average monthly income of about 7.7%.

One of the main challenges in smart city models is consumer behaviour, namely guiding the efforts to promote optimal use of energy in the dynamics of the developing cities, through lower energy consumption without impact on the comfort level. This relates to all energy vectors and can be done through different means. The uptake stage of smart metering and information and communication technologies (ICT) varies in different countries, creating the need for tailored innovative approaches in motivating behavioural change. This paper presents the work carried out within the joint research project ITCity (an ICT platform for sustainable energy ecosystem in smart cities) between the European Union and Latin American Countries. Cooperation of energy researchers and experts in ICT and application developers facilitates adoption of a multipurpose interdisciplinary approach. This work aims at providing the smart city and energy research and innovation community broader understanding of factors influencing adoption of energy efficiency technologies. Different ways of guiding optimal energy use are addressed elaborating on the building blocks for a smart city which consider load patterns based on high resolution, high reporting rate measurements, extensive consumer surveys, available communication solution analysis and end-user interaction with the ICT tool based on gamification principles.

This work allows characterizing and classifying the consumption profiles of non-residential customers (without distributed generation) based on the consumption curves obtained from the records reported by 934 smart meters in the period from January to December 2019, and which belong to an electric power distribution company in Chile, SAESA Group S.A. To achieve the characterization and classification of the consumption profiles, three typical days are analyzed and determined, which correspond to working days (Monday to Friday), Saturdays, and Sundays or holidays. These three typical days are analyzed for each trimester of 2019. The data processing is carried out on the Power Bi and Matlab® platforms. In Power Bi, the data provided by the electricity company are worked, obtaining the average consumption curves for each client in each period of study considered, while in Matlab®, the visualization and classification of the curves is carried out using the K-means algorithm, to finally obtain the results and conclusions. The results show the existence of seven typical profiles representative of the behavior of non-residential clients, which, in some cases, show similar behaviors, despite being from different categories.

En este trabajo se presenta una metodología para minimizar la frecuencia de fallas en Sistemas de Distribución radiales considerando una carga uniformemente distribuida. Se utiliza una aproximación lineal para la ubicación de reconectadores. Este trabajo basa su estudio en la minimización del índice de Frecuencia Media de Interrupción por Potencia instalada, el cual es utilizado como parámetro de regulación y clasificación de las compañías distribuidoras chilenas, según la reglamentación eléctrica vigente. Se introduce además el concepto de Factor de Distancia entre línea Troncal y arranque, el cual puede ser utilizado como herramienta de discriminación para acotar el número de reconectadores a instalar en la línea troncal. Además permite discriminar en base a la data histórica de la línea, si un arranque cualquiera, debe ser evaluado económicamente, como un nuevo alimentador, de forma tal que el índice Frecuencia Media de Interrupción por Potencia instalada sea minimizado.This paper presents a framework for minimizing the average interruption frequency in radial Distribution Systems with uniformly distributed loads. Here, the position of the reclosers has been modeled using a linear approximation. The objective of this paper is to minimize the average interruption frequency per installed power. According to the current electric regulation in Chile, this index is the metric used to regulate and classify the performance of utilities. In the analysis a novel concept of Distance Factor between the main feeder and a branch feeder was introduced. This concept can be utilized as a theoretical limit for the number of switches to install on the main feeder. In addition, based upon the service history of the line, the distance factor determines if a certain line must be economically assessed like a new feeder so that the aforementioned performance index of average interruption frequency per installed power is minimized.

The need to determine which wireless IoT technology, currently available on the market, will be able to support a sizeable simultaneous load of information, types of electrical emergency alarms, required bandwidths, delays-latency, area coverage, and economic cost to serve areas of 600 square kilometers of surface and several users of around two million homes. This article compares Sigfox, LoRa, NB-IoT, and WiMAX technologies as possible solutions for last-mile communications. For this purpose, a network of hundreds of smart meters has been simulated, each transmitting different types of information. In conclusion, it has been obtained that, for a context with the priority of alarms and a large amount of information transport in massive last-mile communications in smart grids and for electrical metering traffic, it is highly recommended that it be done through WiMAX, which in the evaluation shows the best result compared to the other technologies.