The concepts of system load and capacity are pivotal in risk analysis. The complexity in risk analysis increases when the input parameters are either stochastic (aleatory uncertainty) and/or missing (epistemic uncertainty). The aleatory and epistemic uncertainties related to input parameters are handled through simulation-based parametric and non-parametric probabilistic techniques. The complex...

The problem on measurement of power and energy in single-phase and three-phase networks is always very important. The accuracy and precision of measurement is of equal importance for both manufacturers and consumers. The general problem is to determine the uncertainty of the energy produced in a specified power station and delivered to different consumers. Measuring instruments used for energy ...

Seismic assessment of masonry structures is plagued by both inherent randomness and model uncertainty. The former is referred to as aleatory uncertainty, the latter as epistemic uncertainty because it depends on the knowledge level. Pioneering studies on reinforced concrete buildings have revealed a significant influence of modeling parameters on seismic vulnerability. However, confidence in me...

This paper presents a mathematical model and a methodology to analyze the losses in transmission expansion planning (TEP) under uncertainty in demand. The methodology is based on discrete particle swarm optimization (DPSO). DPSO is a useful and powerful stochastic evolutionary algorithm to solve the large-scale, discrete and nonlinear optimization problems like TEP. The effectiveness of the pro...

Problems associated with stimulant use have been linked to frontocingulate, insular, and thalamic dysfunction during decision making and alterations in interoceptive processing. However, little is known about how interoception and decision making interact and contribute to dysfunctions that promote the transition from recreational drug use to abuse or dependence. Here, we investigate brain acti...

The optimal responses for many decisions faced by humans are ill defined, yet we are able to choose well by associating choices with outcomes, and employing this information in decision making. Previous studies suggest that the parietal cortex is involved in "uncertain" decision making, yet uncertainty is confounded with increased difficulty and attention. Here we aim to dissociate the role of ...

In this study, a fuzzy probability-based Markov chain model is developed for forecasting regional long-term electric power demand. The model can deal with the uncertainties in electric power system and reflect the vague and ambiguous during the process of power load forecasting through allowing uncertainties expressed as fuzzy parameters and discrete intervals. The developed model is applied to...

Reconfiguration, by exchanging the functional links between the elements of the system, represents one of the most important measures which can improve the operational performance of a distribution system. Besides, reclosers use to eliminate transient faults, faults isolation, network management and enhance reliability to reduce customer outages. For load uncertainty a new method based on proba...

Due to the steady growth of decentralised distributed generation, the operational management of small, local electricity networks (microgrids) is becoming an increasing challenge to meet: How to provide an operational control for microgrids with a high share of renewable energy sources (RES) that is robust to perturbations? In this paper we address an optimal control problem (OCP) that maintain...