Abstract
Renewable technologies are suitable investments to achieve a low carbon electricity production system and to reduce the external energy dependency of Portugal in a long term period. The aim of this work was to develop and evaluate a variety of scenarios to promote these goals until 2030. A long-term electricity expansion planning model is used to design these scenarios and multi-criteria analysis is applied in the evaluation. The results demonstrated that imposing a minimum contribution of renewable energy sources (RES) for the electricity system, can be more costly than imposing CO2 emissions limitations. Taking into account the technical criteria, scenarios with high coal power share are favoured. However, under a pure social approach, the best scenario would be a 100% RES electricity system. When environmental and economic dimensions are more valued, the best options seems to be the ones with higher investments on natural gas and wind power plants.

Abstract
Electricity power planning is a serious national task that encompasses not only forecasts but more importantly the evolution in short, medium and long term of each element that composes the assumptions, the constraints and/or the parameters of the planning model. Deterministic models can bring simplicity to the electricity power planning but do not consider the uncertainties and sources of risk of the electricity system. On the other hand, stochastic models tend to include the behavior of one or more uncertain parameters that are critical to obtain a robust solution, being however more detailed and lengthy than deteministic models. The aim of this work was to identify the major sources of risk and uncertainties facing electricity system, representing valuable input for the electricit planner task. From this study it can be observed that several different behaviours for each uncertain parameter can be found along a time horizon. Thus, it is concluded that reling on average lowers can represent a reductionist approach and in order to obtain more reliable scenarios for future electricity system, the statistical charcateristics of each parameter should be considered in the electricity power planning.

Abstract
The Brazilian power generation sector faces a paradigm change driven, on one hand, by a shift from a hydropower dominated mix and, on the other, by international goals for reducing greenhouse gases emissions. The objective of this work was to evaluate five scenarios for the Brazilian power system until 2050 using a multi-criteria decision analysis tool. These scenarios include a baseline trend and low carbon policy scenarios based on carbon taxes and carbon emission limits. To support the applied methodology, a questionnaire was elaborated to integrate the perceptions of experts on the scenario evaluation process. Taking into account the results from multicriteria analysis, scenario preference followed the order of increasing share of renewables in the power system. The preferable option for the future Brazilian power system is a scenario where wind and biomass have a major contribution. The robustness of the multi-criteria tool applied in this study was tested by a sensitivity analysis. This analysis demonstrated that, regardless the respondents' preferences and backgrounds, scenarios with higher shares of fossil fuel sources are the least preferable option, while scenarios with major contributions from wind and biomass are the preferable option to supply electricity in Brazil through 2050.

Abstract
Food waste poses a significant challenge to the sustainability of traditional food production systems, prompting global efforts to combat waste throughout the supply chain. Sustainable food production emerges as a critical concept in response to increasing concerns about environmental degradation and the need for alternative protein sources driven by global population growth. In this context, insect production offers a promising solution by converting low-value organic waste into nutrient-rich products, thus reducing waste and environmental impact. This paper addresses the urgent need for sustainable and efficient food production systems by introducing a facility location problem within the network design of insect production. The objective is to develop methods to scale insect-derived product production by identifying optimal locations with the best conditions for establishing insect production facilities. Emphasis is placed on connecting suppliers with production, highlighting the critical role suppliers and their by-products play in promoting a sustainable industry. Instances were generated to assess model performance, including supplier and facility locations, by-product availability and selection. Varying by-product availability yielded different optimization outcomes. The experiments results offered insights into the model’s behavior under different conditions. The results shown that varying the composition of substrate had a major implication on the augment of costs compared to varying the by-product availability.