Abstract
In an earlier work we described and applied a methodology to find an adequate distribution for Nearly Gaussian (NG) random variables. In this work, we compare two different methods, m1 and m2 to estimate a power transform parameter for NG random variables. The m1 method is heuristic and based on sample kurtosis. Herein, we describe and apply it using a new reduced data set. The second method m2 is based on the maximization of a pseudo-log-likelihood function. As an application, we compare the performance of each method using high power statistical tests for the null hypothesis of normality. The data we use are the daily errors in the forecasts of maximum and minimum temperatures in the city of Porto. We show that the high kurtosis of the original data is due to high correlation among data. We also found that although consistent with normality the data is better fitted by distributions of the power normal (PN) family than by the normal distribution. Regarding the comparison of the two parameter estimation methods we found that the m1 provides higher p-values for the observed statistics tests except for the Shapiro-Wilk test.

Abstract
The adoption of battery-powered electric vehicles in the EU is expected to grow to 30-40 million by 2030. This, together with the large adoption of other Distributed Energy Resources (DERs), represents a great challenge for Distribution System Operators (DSOs) in multiple perspectives, such as providing the needed charging infrastructure and ensuring that everyone is served with the expected Quality of Service (QoS), by having a secure and reliable system operation capable of mitigating grid congestion and voltage violation events. One of the mechanisms to mitigate these events can be the usage of these DER, such as Electric Vehicles (EVs), as flexibility sources for the improvement of the planning and operation of power distribution systems. This paper proposes harmonising the coordination of the prequalification process for flexibility provision (product and grid prequalification) among System and Market Operators from Portugal, Spain and France, enabling the participation of flexibility providers in multiple markets from cross-border countries through a harmonised and non-redundant prequalification process. © 2022 CIRED workshop on E-mobility and power distribution systems. All rights reserved.

Abstract

Abstract
Despite ever-increasing resources devoted to healthcare, lack of capacity and timeliness are still chronic problems worldwide. This systematic review aims to present an overview of the Theory of Constraints (TOC) implementations in healthcare services and their outcomes. We analysed 42 TOC implementations (15 full-text articles, 12 video proceedings, and 2 theses/disserations) from major scientific electronic databases and TOC International Certification Organization Conferences. All implementations reported positive outcomes, both tangible and intangible. The two main improvements reported by authors were in productivity (98%; n = 41) - more patients treated - and in the timeliness of care (83%; n = 35). Furthermore, the selected studies reported dramatic improvements: 50% mean reductions in patient waiting time; 38% reduction in patient length of stay; 43% mean increase in operating room productivity and 34% mean increase in throughput. TOC implementations attained positive results in all levels of the health and social care chain. Most TOC recommendations and changes showed almost immediate results and required little or no additional cost to implement. Evidence supports TOC as a promising solution for the chronic healthcare problem, improving quality and timeliness, both necessary conditions for providing effective healthcare.

Abstract
This paper addresses the optimal sizing of renewable energy systems (RESs) in a microgrid (MG), where the MG participates in the electricity market. A novel method for reliability analysis is proposed in this study to deal with the high penetration of RESs. In this framework, the MG is considered as a price maker, having a two-direction relation with the electricity market. RESs, including photovoltaic (PV) panels, wind turbines (WTs), and fuel cells, are optimally sized based on the reliability index, and the results are evaluated before and after the MG involvement in the electricity market. The results show a 3.6% decrease in the total cost of the microgrid as a result of the transactions with the electricity market. Furthermore, the efficiency of the proposed approximate reliability method is verified, where the reliability of the MG is evaluated with less computational complexity and acceptable accuracy.

Abstract
As part of the ongoing climate and energy framework, the European Commission raised recently the 2030 greenhouse gas emission reduction target, moving towards a climate-neutral economy. Transportation represents almost a quarter of Europe’s greenhouse gas emissions, and it is the remaining sector with increasing emissions, above 1990 levels. Considering also the evolving necessity for the reduction of fossil fuels dependency, Europe’s strategy has been designed to support an irreversible shift toward low-emission electric mobility. In this context, the present work assesses the performance of electric mobility in European countries, by using a dynamic analysis in the period 2015–2019, framed in four sustainable dimensions, economy, technology, environment and society. The methodology aggregates several sub-indicators in a composite indicator by using the Data Envelopment Analysis, and evaluates the dynamic change in the sustainable performance through the biennial Malmquist index. Main results indicate that the total productivity change has been improved mainly due to the progression of the frontier that has been observed for all countries from 2018. However, an increasing number of countries have had more difficulties to adopt the best sustainable electric mobility practices, being necessary to design strategies to promote them, mainly in underperforming countries. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.