Abstract
In the last two decades, power systems have experienced several changes, mainly related to organizational and operational restructuring. The appearance of new actors contributes to developing new business models and modifies its traditional operation activities. As a direct result, there is a need for new control solutions and strategies to integrate these different players. Agent-Based Models (ABM) have been increasingly used to model complex systems since they are especially suited to model systems influenced by social interactions between flexible, autonomous, and proactive agents. This paper provides a review of the literature regarding ABM in power systems followed by an analysis in more detail regarding specific applications that are becoming relevant in this new paradigm.

Abstract

Abstract
In many industries, the employed maintenance policies contributed to the concentration of asset replacements in a short period of time. Thus, the number of O&M activities increases, leading to rising operational costs that are not compatible with the available resources. Moreover, these assets encompass multiple failure modes, which reduce asset availability and influence its longevity. Because asset degradation is stochastic, a considerable amount of uncertainty is associated with this problem. The recent technological advances in monitoring technology may foster a reduction in degradation uncertainty but the extra effort regarding the investment plan must be carefully planned. Bearing this in mind, we propose a methodology to determine the investments in the installation of monitoring equipment accounting for the impact in maintenance budget for O&M activities for a resource-dependent asset portfolio with multiple failure modes. The budget is shared between multiple assets and must be determined, a priori, and managed throughout an established time horizon. Since investing in monitoring equipment requires substantial capital due to the system size, DMs have to define which and when a given asset monitoring technology will be installed. Hence, not every asset may have the same monitoring technology and, consequently, the same degradation uncertainty. We formulate the problem as a stochastic optimization problem to capture the dynamic uncertainty in the assets’ condition. Due to its inherent complexity, we employ a meta-heuristic based on a co-evolutionary genetic algorithm to achieve high-quality solutions under reasonable computational time for real world-sized systems. The approach is validated in a case study in the electricity distribution in which a system operator has to manage a portfolio of power transformers operating under different operational conditions. © ESREL 2021. Published by Research Publishing, Singapore.

Abstract
Kidney exchange programs aim at matching end-stage renal disease patients who have a willing but incompatible kidney donor with another donor. The programs comprise a pool of such incompatible patient-donor pairs and, whenever a donor from one pair is compatible with the patient of another pair, and vice versa, the pairs may be matched and exchange kidneys. This is typically a two-step process in which, first, a set of pairs is matched based on preliminary compatibility tests and, second, the matched pairs are notified and more accurate compatibility tests are performed to verify that actual transplantation can take place. These additional tests may reveal incompatibilities not previously detected. When that happens, the planned exchange will not proceed. Furthermore, pairs may drop out before the transplant, and thus the planned exchange is canceled. In this paper, we study the case in which a new set of pairs may be matched if incompatibilities are discovered or a pair withdraws from the program. The new set should be as close as possible to the initial set in order to minimize the material and emotional costs of the changes. Various recourse policies that determine the admissible second-stage actions are investigated. For each recourse policy, we propose a novel adjustable robust integer programming model. Wealso propose solution approaches to solve this model exactly. The approaches are validated through thorough computational experiments. Summary of Contribution: In the paper, we present an original work related to the modeling and optimization approaches for Kidney Exchange Programs (KEPs). Currently, KEPs represent an alternative way for patients suffering from renal failure to find a compatible (living) donor. The problem of determining an assignment of patients to (compatible) donors that maximizes the number of transplants in a KEP can be seen as a vertex-disjoint cycle packing problem. Thus, KEPs have been extensively studied in the literature of integer programming. In practice, the assignment determined to a KEP might not be implemented due to withdraws from the program (e.g., a more accurate compatible test shows a new incompatibility or a patient health condition unable him/her to participate on the KEP). In our paper, we model the problem of determining a robust solution to the KEP, i.e., a solution that minimizes the material and emotional costs of changing an assignment. In this way, we propose and design solution approaches for three recourse policies that anticipate withdraws. Through computational experiments we compare the three recourse policies and validate the practical interest of robust solutions.

Abstract
Nonprofit organizations are constantly challenged to find new ways of finding new donors and sources of funding for their solidarity actions. The traumatic events that occurred in the summer of 2017 in Portugal that caused more than 100 deaths consumed by the fires caused these organizations to have difficulties in coordinating the whole wave of solidarity generated in the community. In this sense, this study has developed a technological platform based exclusively on free technologies that allowed these entities to receive donations and manage this whole process. The application developed enables the reception of anonymous donations and monitoring the status of each donation. Furthermore, several requirements in terms of compatibility with mobile devices, usability, security, and privacy were implemented in the platform.

Abstract
COVID-19 has caused profound impacts on the economy and society. In Portugal, many companies needed to temporarily close, and many workers were forced to go into lay-off. However, at the same time, several companies are trying to respond to the challenges posed by this pandemic by introducing organisational innovations that would enable them to respond to the needs of the people and organisations that most require help during this period. In this sense, this study aims to explore the role of organisational innovation in the business sector in Portugal through seven case studies. The findings reveal a very diverse set of initiatives in which the role of internal and external sources of innovation stands out simultaneously. Most of the innovations identified have a procedural focus, while structural innovations have less influence. This study is particularly relevant in the practical dimension by encouraging other countries and companies to replicate these initiatives.