Abstract

Abstract

Abstract
Renewable Energy Communities (RECs) are emerging as key enablers of decentralized, sustainable, and consumer-driven energy systems. Beyond environmental benefits, RECs possess significant potential to enhance resilience against extreme weather, price volatility, and infrastructure fragility. This article integrates resilience and relia bility constraints directly into the planning and operation of RECs, assessing their impact on system cost, sizing, and dispatch. Two optimization models are developed: a design model that sizes community assets (PV and BESS) using varying resilience indicators, and an operational model that minimizes costs while monitoring reliability. The analysis introduces two resilience metrics, deterministic hourly autonomy and average autonomy, and eval uates them using real-world data from the Caxias Living Lab. Results demonstrate that average resilience can be increased with minimal cost impacts due to non-linear trade-offs, whereas strict hourly resilience requires signifi cant storage investment. Furthermore, a Value of Lost Load (VoLL) reliability indicator is shown to cost-effectively trigger maintenance events. This framework offers actionable guidance for designing sustainable, adaptive, and economically viable energy communities.

Abstract

Abstract
With the growing popularity of DevOps culture among companies and the corresponding increase in Microservices architecture development-both known to boost productivity and efficiency in software development-an increasing number of organizations are aiming to integrate them. Implementing DevOps culture and best practices can be challenging, but it is increasingly important as software applications become more robust and complex, and performance is considered essential by end users. By following the Design Science Research methodology, this paper proposes an iterative framework that closely follows the recommended DevOps practices, validated with the assistance of expert interviews, for implementing DevOps practices into Microservices architecture software development, while also offering a series of tools that serve as a base guideline for anyone following this framework, in the form of a theoretical use case. Therefore, this paper provides organizations with a guideline for adapting DevOps and offers organizations already using this methodology a framework to potentially enhance their established practices.

Abstract
This study aims to contribute to a better understanding of the current state of Primary Health Care, specifically in terms of efficiency and user satisfaction at 8 Health Centers in Praia City, Cape Verde, observed in 2017, 2018, 2020 and 2021. The Data Envelopment Analysis (DEA) model with input orientation and Constant Returns of Scale (CRS) is used to measure operational efficiency, and the income to expenditure ratio is used to measure economic and financial efficiency. User satisfaction is assessed using a questionnaire survey involving 408 respondents. The results indicate that 8 Decision-Making Units (DMUs) are operationally efficient. Regarding economic and financial efficiency, the ratios observed were generally higher than 1 in the different Health Centers analyzed. The satisfaction results show that most users are satisfied with the organization and services provided by the Health Centers. However, some improvements are needed in all the categories evaluated. A positive association between operational efficiency and the economic and financial efficiency ratio stands out as a result of comparing the different types of efficiency. Operational efficiency shows a negative relationship with the dimensions of satisfaction related to organization, service process, medical and nursing services, but this relationship is only statistically significant for the service process.