The application of artificial intelligence-based techniques has covered a wide range of applications related to electric power systems (EPS). Particularly, a metaheuristic technique known as Particle Swarm Optimization (PSO) has been chosen for the tuning of parameters for Power System Stabilizers (PSS) with success for relatively small systems. This article proposes a tuning methodology for PSSs based on the use of PSO that works for systems with ten or even more machines. Our new methodology was implemented using the source language of the commercial simulation software DigSilent PowerFactory. Therefore, it can be translated into current practice directly. Our methodology was applied to different test systems showing the effectiveness and potential of the proposed technique.

A method is proposed to fit parameters of Power System Stabilizer controllers in electromechanical multimachine power systems. The use of the Non-dominated Sorting Genetic Algorithm II heuristic method and Tabu search is considered to be initial search criteria. These methods give an approximation of the values that define the controllers. Then, the stochastic approach was used to evaluate the behavior of the parameters found when considering the system’s response to the presence of random and self-sustained in-time disturbances that affect the response of the system under steady state. The stochastic approach allows the evaluation of the system’s response through the calculation of the cost of energy loss under steady state. The method is applied to two systems: a three-machine nine-busbar system, and the Interconnected System of the Greater North (Sistema Interconectado del Norte Grande) in Chile. For these systems, the proposed methodology effectively optimized the controllers and Tabu search was shown to have a better performance than the Non-dominated Sorting Genetic Algorithm II.

This paper presents a methodology to represent ocean wave power generation based on real data observation for significant wave height (SWH or $H_s$ ) and wave period (WP or T). This technique is based on a hybrid model, which considers Fourier series and stochastic differential equations, allowing a continuous time representation of the random changes in the parameters associated with wave power generation ( $H_s$ and T). The methodology is explained, including estimation methods and a validation procedure. The data series generated by the models erre used to create simulated wave power output applying a transformed matrix and a theoretical model. The results validate the utilization of this technique, when the objective is to obtain a robust dynamic representation of a random process, oriented to linear studies.

This work presents the design and assessment of four control schemes for the monitoring and regulation of joint trajectories applied in the dynamic model of a SCORBOT-ER V plus robot, which includes the dynamics of the actuators, and the estimation of the friction forces present within the joints. The two classical control strategies calculated torque and PID, and the two advanced control strategies, fuzzy and predictive, are considered. In the latter case, a gravitational compensation stage is incorporated, as well as the inverse models of the motors and the transmissions of belt movement for each joint. Computational tests are performed by applying an external step-type disturbance to the third joint of the robot. Finally, an evaluation of the results obtained is presented through trajectory curves, joint errors, and the three performance indexes residual mean square, residual standard deviation, and index of agreement.

The Chilean government is looking to liberalize the retail electricity market to increase competitiveness and reduce the price of electricity for residential and small/medium commercial customers. Under this context, the article aims to enrich the legislative debate by providing an overview of the international experience of the electricity market liberalization that started in the early 1990s and presents forecasting for the regulated Chilean price until 2034, considering the current tenders and the price stabilization mechanism. In addition, multiple simulations are developed to measure the market effect of retail liberalization on regulated customers. In this regard, the results suggest a significant regulated price increase from 2022 to 2032, produced mainly by the stabilization mechanism, which overshadows the low prices obtained in recent renewable generation supply tenders. However, if the retail market is liberalized, the simulation indicates that regulated customers could save between 15% and 20% on their electricity bills.

The effects associated with the pandemic of COVID-19 have left several consequences. The large confinements have caused formal and independent job losses. Therefore, families have been forced to prioritize their monthly utility bills. Most countries have decided on suspending cuts in utility services and give them payment arrangements for the future instead. In this article, the actions taken in Latin America and Europe are presented. Additionally, for the Chilean case, a mechanism for financing the accumulated debt is proposed. The main objective of this is to establish a procedure that allows users to regain the habit of paying for public utilities (water, electricity and piped gas).