No abstract

The power system expansion and the integration of technologies, such as renewable generation, distributed generation, high voltage direct current, and energy storage, have made power system simulation challenging in multiple applications. The current computing platforms employed for planning, operation, studies, visualization, and the analysis of power systems are reaching their operational limit since the complexity and size of modern power systems results in long simulation times and high computational demand. Time reductions in simulation and analysis lead to the better and further optimized performance of power systems. Heterogeneous computing—where different processing units interact—has shown that power system applications can take advantage of the unique strengths of each type of processing unit, such as central processing units, graphics processing units, and field-programmable gate arrays interacting in on-premise or cloud environments. Parallel Heterogeneous Computing appears as an alternative to reduce simulation times by optimizing multitask execution in parallel computing architectures with different processing units working together. This paper presents a review of Parallel Heterogeneous Computing techniques, how these techniques have been applied in a wide variety of power system applications, how they help reduce the computational time of modern power system simulation and analysis, and the current tendency regarding each application. We present a wide variety of approaches classified by technique and application.

No abstract

The integration of different energy resources from traditional power systems presents new challenges for real-time implementation and operation. In the last decade, a way has been sought to optimize the operation of small microgrids (SMGs) that have a great variety of energy sources (PV (photovoltaic) prosumers, Genset CHP (combined heat and power), etc.) with uncertainty in energy production that results in different market prices. For this reason, metaheuristic methods have been used to optimize the decision-making process for multiple players in local and external markets. Players in this network include nine agents: three consumers, three prosumers (consumers with PV capabilities), and three CHP generators. This article deploys metaheuristic algorithms with the objective of maximizing power market transactions and clearing price. Since metaheuristic optimization algorithms do not guarantee global optima, an exhaustive search is deployed to find global optima points. The exhaustive search algorithm is implemented using a parallel computing architecture to reach feasible results in a short amount of time. The global optimal result is used as an indicator to evaluate the performance of the different metaheuristic algorithms. The paper presents results, discussion, comparison, and recommendations regarding the proposed set of algorithms and performance tests.

Obstructive sleep apnoea-hypopnoea syndrome (OSA) is a respiratory disorder characterised by repetitive obstruction of the upper airway, leading to several interruptions during sleep. It is currently one of the main public health problems worldwide and one of the main cardiovascular risk factors in developed and intermediate developing countries, whose populations are increasing in rates of obesity and age. One of the common treatments for OSA is a continuous positive airway pressure (CPAP) device, which pumps air through a hose, reaches a mask that the patient has over his or her nose and travels the airway, keeping the upper airway open during sleep and avoiding episodes of airway collapse. The problem is that CPAP is not accepted by some patients due to a lack of adaptation, so alternative treatments may be needed. For some years, there have been explorations of treatments related to electrical stimulation of the muscles of the upper airway as therapy to reduce the number of episodes of apnoea (measured through the apnoea–hypopnoea index) during the night, strengthening these muscles through stimulation. This is the protocol of the first clinical study of a rehabilitation device for home use that not only provides functional stimulation of the upper-airway dilator muscles but also provides sensory stimulation. This device works by strengthening the dilating muscles of the upper respiratory tract and improving the sensory capacity of the laryngo-pharyngeal tract and is based on existing publications on the effectiveness of functional and somatosensory neurostimulation through neuroplasticity in the recovery of neurological deficits. Trial registration: Clinicaltrials.gov NCT04607343 (29/10/2020)