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Goal, Scope and Background. The environmental sustainability is one of the current priorities of the Portuguese pulp and paper industry. Life Cycle Assessment (LCA) was the methodology chosen to evaluate the sustainability of the printing and writing paper production activity. This paper grade represents about 60% of the total production of paper in Portugal and its production is expected to increase in the near future. The main goal of this study was to assess the potential environmental impacts associated with the entire life cycle of the printing and writing paper produced in Portugal from Eucalyptus globulus pulp and consumed in Germany, in order to identify the processes with the largest environmental impacts. Another goal of this study was to evaluate the effect on the potential environmental impacts of changing the market where the Portuguese printing and writing paper is consumed: German market vs. Portuguese market. Methods. The main stages considered in this study were: forestry, pulp production, paper production, paper distribution, and paper final disposal. Transports and production of chemicals, fuels and energy in the grid were also included in these stages. Whenever possible and feasible, average or typical data from industry were collected. The remaining data were obtained from the literature and specialised databases. A quantitative impact assessment was performed for five impact categories: global warming over 100 years, acidification, eutrophication, non-renewable resource depletion and photochemical oxidant formation. Results. In the German market scenario, the paper production stage was a remarkable hot spot for air emissions (non-renewable CO2, NOx and SO2) and for non-renewable energy consumption, and, consequently, for the impact categories that consider these parameters: global warming, acidification and non-renewable resource depletion. These important environmental impacts are due to the energy requirements in the printing and writing paper production process, which are fulfilled by on-site fuel oil burning and consumption of electricity from the national grid, which is mostly based on the use of fossil fuels. The pulp production stage was identified as the largest contributor to water emissions (COD and AOX) and to eutrophication. Considering that energy consumed by the pulp production processes comes from renewable fuels, this stage was also the most contributing to renewable energy consumption. Discussion. The paper distribution stage showed an important contribution to NOx emissions, which, however, did not result in a major contribution to acidification or eutrophication. The final disposal stage was the main contributor to the photochemical oxidant formation potential due to CH4 emissions from wastepaper landfilling. On the other hand, paper consumption in Portugal was environmentally more favourable than in Germany for the parameters/impact categories where the paper distribution stage has a significant contribution (non-renewable CO2, NOx, non-renewable energy consumption, acidification, eutrophication and non-renewable resource depletion) due to shorter distances needed to deliver paper to the consumers. For the remaining parameters/impact categories, the increase observed in the final disposal stage in the Portuguese market was preponderant, and resulted from the existence of significant differences in the final disposal alternatives in the analysed markets (recycling dominates in Germany, whereas landfilling dominates in Portugal). Conclusions. The pulp and paper production stages were found to be of significance for almost all of the inventory parameters as well as for the impact assessment categories. The paper distribution and the final disposal stages were only of importance for some of the inventory parameters and some of the impact categories.… [ABSTRACT FROM AUTHOR]

Building-integrated flexible resources can offer economical availability to accommodate high-penetrated renewable energy sources (RESs), which can be potentially coordinated to achieve cost-effective supply. This paper proposes a resilience-oriented planning model of urban distribution system source–network–load–storage in the context of high-penetrated building-integrated resources. In this model, source–network–load–storage resources are cost-optimally planned, including the lines, soft open point (SOP), building-integrated photovoltaics (BIPVs), building-integrated wind turbine (BIWT), building-integrated energy storage system (ESS), etc. To enhance fault recovery capability during extreme faults, fault scenarios are incorporated into the distribution system operation via coupled multiple recovery stages. The resilience-oriented planning is a thorny problem due to its source–network–load–storage couplings, normal-fault couplings, etc. The original resilience-oriented planning is reformulated as a mixed-integer linear programming (MILP) problem, which can then be solved with a two-stage method and evaluated via a multi-dimensional evaluation metrics. The proposed planning methodology is benchmarked over a Portugal 54-node urban distribution system to verify the superiority and effectiveness on the system economy and resilience levels. Case studies show that the proposed methodology can exploit the optimal synergies of different source–network–load–storage components and enhance system dispatchability. [ABSTRACT FROM AUTHOR]

The transition from the current energy architecture to a new model is evident and inevitable. The coming future promises innovative and increasingly rigorous projects and challenges for everyone involved in this value chain. Technological developments have allowed the emergence of new concepts, such as renewable energy communities, decentralized renewable energy production, and even energy storage. These factors have incited consumers to play a more active role in the electricity sector and contribute considerably to the achievement of environmental objectives. With the introduction of renewable energy communities, the need to develop new management and optimization tools, mainly in generation and load management, arises. Thus, this paper proposes a platform capable of clustering consumers and prosumers according to their energy and geographical characteristics to create renewable energy communities. Thus, this paper proposes a platform capable of clustering consumers and prosumers according to their energy and geographical characteristics to create renewable energy communities. Moreover, through this platform, the identification (homogeneous energy communities, mixed energy communities, and self-sufficient energy communities) and the size of each community are also obtained. Three algorithms are considered to achieve this purpose: K-means, density-based spatial clustering of applications with noise, and linkage algorithms (single-link, complete-link, average-link, and Wards' method). With this work, it is possible to verify each algorithm's behavior and effectiveness in clustering the players into communities. A total of 233 members from 9 cities in the northern region of Portugal (Porto District) were considered to demonstrate the application of the proposed platform. The results demonstrate that the linkage algorithms presented the best classification performance, achieving 0.631 by complete-ink in the Silhouette score, 2124.174 by Ward's method in the Calinski-Harabasz index, and 0.329 by single-link on the Davies-Bouldin index. Additionally, the developed platform demonstrated adequacy, versatility, and robustness concerning the classification and sizing of renewable energy communities. [ABSTRACT FROM AUTHOR]

With the deregulation of electricity market in distribution systems, renewable distributed generations (RDG) are being invested in by third-party social capital, such as distributed generations operators (DGOs) and load aggregators (LAs). However, their arbitrary RDG investment and electricity trading behavior can bring great challenges to distribution system planning. In this paper, to reduce distribution system investment, a distribution system expansion planning model based on a bi-level Stackelberg game is proposed for the distribution system operator (DSO) to guide this social capital to make suitable RDG investment. In the proposed model, DSO is the leader, while DGOs and LAs are the followers. In the upper level, the DSO determines the expansion planning scheme including investments in substations and lines, and optimizes the variables provided for followers, such as RDG locations and contract prices. In the lower level, DGOs determine the RDG capacity and electricity trading strategy based on the RDG locations and contract prices, while LAs determine the RDG capacity, demand response and electricity trading strategy based on contract prices. The capacity information of the DRG is sent to the DSO for decision-making on expansion planning. To reduce the cost and risk of multiple agents, two long-term renewable energy contracts are introduced for the electricity trading. Conditional value-at-risk method is used to quantify the RDG investment risk of DGOs and LAs with different risk preferences. The effectiveness of the proposed model and method is verified by studies using the Portugal 54-bus system. [ABSTRACT FROM AUTHOR]

The world is facing many challenges to keep up with growing energy demand and greenhouse gas and pollutant emissions. A possible solution is to integrate renewable energy sources (RESs) into residences and create energy management systems (EMSs) that reduce consumption and relieve the main grid in critical hours. This paper is focused on analyzing different EMSs using solar photovoltaic (PV) modules and three energy storage systems (ESSs) to increase savings without affecting the user's needs, with thirty-three power consumption profiles and three energy tariffs over a 25-year investment to compare which solution presents the best economic result in each of the 297 analyzed scenarios. The results show that the higher the overall daily consumption values, the greater the profits for all EMSs. The lowest demand profiles lead to the best self-consumption and self-sufficiency results. PV-only systems with a tri-hourly tariff have the best overall results. In the case of battery operation, each case should be carefully analyzed in order to choose the correct technologies and tariff. The results also allowed us to verify that even though having more PV modules generates more energy, it can make a project less economically desirable. [ABSTRACT FROM AUTHOR]

The adoption of new global approaches in the field of energy democratization requires inquiring into how people act to shape the energy system. This is where the concept of energy citizenship (ENCI) appears as a constellation of actors that enable and/or support citizens to became active participants in the debates and energy systems both in private and public sphere, or as a collective citizen that contributes to change (Pel et al., 2021). The aim of this paper is to explore the concept of ENCI in Southern Europe. Using a mixed approach, an extensive mapping of 43 ENCI initiatives in Spain (n = 29) and Portugal (n = 14) was conducted through desktop research, and a stakeholder consultation workshop (n = 7) was carried out through a focus group. Results revealed the major presence of collective ENCI types, with the citizen-based/hybrid one standing out (e.g., energy cooperatives). Most of them were motivated by the interest to contribute to energy transition or to produce and/or use renewable energy, and aimed at promoting energy saving, energy justice and reducing the carbon footprint. The general tendency is towards active participation (in Spain) and transformative forms (in Portugal). The possibilities for citizen control in the initiatives analysed is still limited. These results were confirmed by stakeholders who, additionally, pointed out the major political, social, economic, and geographical factors related to ENCI forms. In short, various types of ENCI could be validated in the Spanish and Portuguese context, showing a commitment to sustainability, democracy, and energy justice. Other non-evidenced forms may be raised as a challenge to further in-depth research on latent forms of ENCI in Southern Europe. [ABSTRACT FROM AUTHOR]

The extent to which infrastructures being deployed for a postcarbon transition can be considered sustainable has been increasingly scrutinized within the critical turn in energy justice research. However, the focus therein tends to be on how new megaprojects still reveal Global North–Global South colonial relations and energy-related injustices. In this paper, we aim to contribute to widening critical energy justice research by illustrating how it needs to also consider the spatio-temporalities of renewable energy colonialism in the Global North. To that end, we undertake a psychosocial historiography of selected large-scale hydroelectric power plants in Portugal, from the twentieth century to the present day. This historiography is undertaken via archival data and interviews. Our analysis illustrates how hydrocolonialism has been enacted – discursively, infrastructurally, and psychosocially – in rural areas in Portugal, across different socio-political regimes; and also how it can be contested, by identifying some examples of resistance. [ABSTRACT FROM AUTHOR]

As the global demand for renewable energy continues to increase, marine renewable energy has attracted much attention as a potential source of clean energy. As a country with rich marine resources, Portugal's marine environment is of great significance to the development of marine energy. However, the current impact assessment of marine renewable energy projects has shortcomings such as incomplete understanding of ecosystems, incomplete consideration of fishery resources and socioeconomic impacts, lack of accuracy, and failure to consider geographical differences, thus lacking comprehensiveness and accuracy. To this end, we propose the ACO-TCN- Attention model to address these shortcomings in current impact assessments of marine renewable energy projects. The goal of this model is to provide a more comprehensive, precise and nuanced analysis to better understand the impacts of these projects on ecosystems, socio-economics and local communities. "ACO-TCN-Attention" is a model architecture that combines multiple machine learning and deep learning concepts. It includes three main parts: Ant Colony Optimization (ACO), Temporal Convolutional Network (TCN) and Attention mechanism. The ant colony optimization model simulates the behavior of ants and is used to optimize the operating strategies of marine renewable energy projects. Temporal Convolutional Network specializes in processing time series data and improves the prediction accuracy of the model. The attention mechanism allows the model to dynamically focus on the pieces of information that are most important for the current task. Extensive experimental evaluation shows that our method performs well on multiple datasets, significantly outperforming other models. This research is of great significance as it provides new methods and tools for improving the environmental impact assessment of marine renewable energy projects. By understanding the potential impacts of projects more accurately, we can better balance the relationship between the development of renewable energy and environmental protection, supporting the achievement of the Sustainable Development Goals. This research also provides useful guidance and reference for future research and practice in the field of marine energy. [ABSTRACT FROM AUTHOR]

The decarbonisation of the building sector is crucial for Portugal's goal of achieving economy-wide carbon neutrality by 2050. To mobilize communities towards energy efficiency measures, it is important to understand the primary drivers and barriers that must be overcome through policymaking. This paper aims to review existing Energy Policies and Actions (EPA) in Portugal and assess their effectiveness in improving Energy Efficiency (EE) and reducing CO2 emissions in the building sector. The Local Energy Planning Assistant (LEPA) tool was used to model, test, validate and compare the implementation of current and alternative EPAs in the North of Portugal, including the national EE plan. The results indicate that electrification of heating and cooling, EE measures, and the proliferation of Renewable Energy Sources (RES) are crucial for achieving climate neutrality. The study found that the modelling of alternative EPAs can be improved to reduce investment costs and increase Greenhouse Gas (GHG) emissions reduction. Among the alternatives assessed, the proposed one (Alternative 4) presents the best returns on investment in terms of cost savings and emissions reduction. It allows for 52% investment cost savings in the residential sector and 13% in the service sector when compared to the current national roadmap to carbon neutrality (Alternative 2). The estimated emission reduction in 2050 for Alternative 4 is 0.64% for the residential sector and 3.2% for the service sector when compared to Alternative 2. [ABSTRACT FROM AUTHOR]

Hydrogen is a promising commodity, a renewable secondary energy source, and feedstock alike, to meet greenhouse gas emissions targets and promote economic decarbonization. A common goal pursued by many countries, the hydrogen economy receives a blending of public and private capital. After European Green Deal, state members created national policies focused on green hydrogen. This paper presents a study of energy transition considering green hydrogen production to identify Portugal's current state and prospects. The analysis uses energy generation data, hydrogen production aspects, CO 2 emissions indicators and based costs. A comprehensive simulation estimates the total production of green hydrogen related to the ratio of renewable generation in two different scenarios. Then a comparison between EGP goals and Portugal's transport and energy generation prospects is made. Portugal has an essential renewable energy matrix that supports green hydrogen production and allows for meeting European green hydrogen 2030–2050 goals. Results suggest that promoting the conversion of buses and trucks into H 2 -based fuel is better for CO 2 reduction. On the other hand, given energy security, thermoelectric plants fueled by H 2 are the best option. The aggressive scenario implies at least 5% more costs than the moderate scenario, considering economic aspects. [ABSTRACT FROM AUTHOR]

This paper uncover a new perception of the dynamic interconnection between CO2 emission and economic growth, renewable energy use, trade openness, and technological innovation in the Portuguese economy utilizing innovative Morlet wavelet analysis. The research applied continuous wavelet transform, wavelet correlation, the multiple and partial wavelet coherence, and frequency domain causality analyses are applied on variables of investigation using dataset between 1980 and 2019. The result of these analyses disclosed that the interconnection among the indicators progresses over time and frequency. The present analysis finds notable wavelet coherence and significant lead and lag interconnections in the frequency domain, while conflicting relationships among the variables are found in the time domain. The wavelet analysis according to economic viewpoint affirms that renewable energy consumption helps to curb CO2 while trade openness, technological innovation, and economic growth contribute to CO2. The outcomes also proposed that renewable energy consumption decreases CO2 in medium and long run in Portugal. Therefore, policymakers in Portugal should stimulate investment in renewable energy sources, establish restrictive laws, and enhance energy innovation. [ABSTRACT FROM AUTHOR]

Decreasing greenhouse gas emissions plays a crucial role in the Europe energy transition and the production of hydrogen using electricity from renewable sources (green H 2) contributes significantly to this objective. As the renewable energy production capacity grows, the impact of green H 2 is likely to increase. In the case of the Iberian Electricity Market (MIBEL), no quantitative studies have so far tested the viability of the H 2 growth plans. This paper fills this gap through a novel mathematical programming model, which integrates H2 generation into the MIBEL. The model reveals a mismatch between the sustainability goals and the expansion plans of renewable and green H 2 for Spain and Portugal. [Display omitted] • Mathematical Programming to analyse green hydrogen production in the MIBEL. • Influence of the electricity market on hydrogen production and prices. • Generating green hydrogen is preferable to hydro pumping. • Green hydrogen integration might entail additional emissions. • MIBEL hydrogen strategy must be revised to achieve sustainability. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel nonlinear approach to solve the short-term hydro scheduling problem under deregulation, considering head-dependency. The actual size of hydro systems, the continuous reservoir dynamics and constraints, the hydraulic coupling of cascaded hydro systems, and the complexity associated with head-sensitive hydroelectric power generation still pose a real challenge to the modelers. These concerns are all accounted for in our approach. Results from a case study based on one of the main Portuguese cascaded hydro systems are presented, showing that the proposed nonlinear approach is proficient. [ABSTRACT FROM AUTHOR]

The integration of 5G base station (5G BS) clusters and edge data services introduces novel digital loads (NDLs) into the distribution system (DS), significantly impacting the interactive coordination of 5G-DS. This paper proposes an expansion planning model of 5G and DS considering source-network-load-storage coordination. Here, renewable energy resources (RESs), 5G BS clusters, edge data centers (EDCs), and DS source-network-load-storage are coordinately planned. The dynamic service access of 5G BS cluster are formulated to capture the coupled nature and inherent flexibility of 5G services. Considering the flexible processing of EDCs, a detailed categorization is conducted based on data service type, leveraging the synergies between cloud and edge computing to achieve flexible data load distribution. The original expansion planning model is reformulated as a mixed integer linear programming (MILP) problem to facilitate its computational solution. Simulation results from case studies on Portugal 54 node network over individual expansion planning and 5G static-access are performed to validate the effective and superior performances of the proposed method. Simulations results show that the system cost can be reduced by at most 15% with a higher operational flexibility. [Display omitted] • An expansion planning model of 5G and DS considering source-network-load-storage coordination is proposed. • NDLs from 5G BS clusters and EDCs are introduced to accommodate the RESs. • Dynamic access services of 5G BS clusters are formulated to leverage their flexibility. • Synergies of cloud and edge computing in EDCs are captured to facilitate source-network-load- storage coordination. [ABSTRACT FROM AUTHOR]

Addressing climate urgency and unpredicted crisis, such as pandemics and wars, requires the acceleration of the sustainable transition and, particularly, the development and implementation of new renewable energy technologies. This acceleration depends on the capacity for mobilizing resources and skills present in the territory. In particular, the transition to a commercial phase poses important challenges that may be met drawing on the capacities developed in the initial experimentation phase, whose effects remain poorly studied. Portugal has a long experience in the development of marine renewable energy technologies - wave energy and floating offshore wind energy. This paper uses a longitudinal analysis, supported on a database of actors involved with the technology, to investigate whether the activities carried out during the initial phase of development permitted to start mobilizing the national industry, and to what extent this mobilization generated sectoral and regional centers of activity that can support future developments. The analysis shows that test and demonstration projects have a role in the mobilization of firms from relevant sectors, even if their ability to attract local companies is still limited. The activities are based on networks of companies distributed throughout the territory, with a predominance of the main metropolitan areas. These results can inform strategies to accelerate technology diffusion and increase the potential for industrial transformation. [ABSTRACT FROM AUTHOR]

Transport is one of the sectors of the energy consumption where the presence of renewable energies is lower and its increase is hard to achieve especially in countries that import all the fuels that they consume. This paper addresses the progress that Portugal is making toward a more sustainable transport sector. A near- and medium- term scenario analysis is performed, based on the energy consumption in the past and on a detailed evaluation of the trends for renewable energy in the transport sector. The near-term scenarios aim at portraying the conditions that allow the country to fulfill the target of 10% renewable share in transportation established by the European Union. The medium-term scenarios highlight the implications, in terms of emission reduction and of energy independence, deriving from the use of electric vehicles and natural gas, synthetic and fossil, as alternatives to liquid fuels. The results show that electric vehicles would substantially reduce the total energy consumption and the greenhouse gas emissions, while the promotion of routes for synthetic natural gas would contribute to taking advantage of local resources. The paper also provides some insights about the design of future policies to build a more sustainable transport sector. [ABSTRACT FROM AUTHOR]

Wind power is one of the most important renewable energy sources worldwide. However, integrating these technologies in electricity markets faces challenges due to the intermittent wind speed, resulting in potential imbalances within power grids and subsequent inefficiencies. Traditional approaches for modeling the uncertainty simulate fixed wind power values in operational and planning models, which work well for the short term but are inadequate for medium-term decision-making due to lower forecasting accuracy and the inability to differentiate the imbalance risk faced in each simulated value. This paper proposes a novel methodology for incorporating wind energy imbalance risk into medium-term generation planning models. For this, we first simulate realistic wind power scenarios and perform a fitting distribution process to characterize the hourly wind power behavior. Then, we model the imbalance risk using quadratic-uncertainty cost functions for each simulated value. Subsequently, we conduct a temporal aggregation to reduce the computational burden, preserving the conceptual framework of the imbalance risk modeling. Finally, we propose a medium-term generation planning model that includes the imbalance risk model and the temporal aggregation strategy. Our approach is evaluated in a real-size case study formed by Spain, Portugal, and France's electricity markets, demonstrating accurate wind power imbalance risk modeling and lowered planning costs. • A new methodology to include wind energy imbalance risk in generation planning models. • Introducing a fitting process for modeling the distribution asymmetries of wind power. • Proposing a temporal aggregation method for efficient imbalance risk modeling. • The methodology is validated in Spanish, Portuguese, and French electricity markets. [ABSTRACT FROM AUTHOR]

Emerging technologies are helping to accelerate the ongoing energy transition. At the forefront of these new technologies is blockchain, which has the potential to disrupt energy trading markets. This article explores this potential by presenting an innovative multilevel transactive energy (TE) optimization model for the scheduling of distributed energy resources (DERs) within connected virtual power plants (VPPs). The model allows for energy transactions within a given VPP as well as between connected VPPs. A blockchain-based smart contract layer is applied on top of the TE optimization model to automate and record energy transactions. The model is formulated to adhere to the new regulations for the self-generation and self-consumption of energy in Portugal. This new set of regulations can ease barriers to entry for consumers and increase their active participation in energy markets. Results show a decrease in energy costs for consumers and increased generation of locally produced electricity. This model shows that blockchain-based smart contracts can be successfully integrated into a hierarchical energy trading model, which respects the novel energy regulation. This combination of technologies can be used to increase consumer participation, lower energy bills, and increase the penetration of locally generated electricity from renewable energy sources. [ABSTRACT FROM AUTHOR]

Agriculture being an essential activity sector for the survival and prosperity of humanity, it is fundamental to use sustainable technologies in this field. With this in mind, some statistical data are analyzed regarding the food price rise and sustainable development indicators, with a special focus on the Portugal region. It is determined that one of the main factors that influences agriculture's success is the soil's characteristics, namely in terms of moisture and nutrients. In this regard, irrigation processes have become indispensable, and their technological management brings countless economic advantages. Like other branches of agriculture, the wine sector needs an adequate concentration of nutrients and moisture in the soil to provide the most efficient results, considering the appropriate and intelligent use of available water and energy resources. Given these facts, the use of renewable energies is a very important aspect of this study, which also synthesizes the main irrigation methods and examines the importance of evaluating the evapotranspiration of crops. Furthermore, the control of irrigation processes and the implementation of optimization and resource management models are of utmost importance to allow maximum efficiency and sustainability in this field. [ABSTRACT FROM AUTHOR]

This paper analyses the current energy balance of Portugal, considering the actual sources which are mainly traditional fossil fuels, hydroelectric power and renewables. Other potential sources are also discussed and taken into consideration in view of the previewed evolution of the country in energetic terms. Among these, nuclear power, once regarded as an option, is now being re-considered. This paper also sums up the main issues to be considered in a future debate on the subject. [ABSTRACT FROM AUTHOR]

Sustainability is frequently defined by its three pillars: environmental, economic and social. Consequently the evaluation of the sustainability of a decision, public or private, requires information on these three dimensions. This paper focuses on social sustainability. In the context of renewable energy sources, the consideration of social sustainability requires the analysis of not only the efficiency but also the equity of the welfare impacts, including spatially differentiated impacts. The present paper proposes and applies a methodology to generate the information necessary to conduct a more complete welfare analysis of the social sustainability of renewable energy production facilities, so that equity considerations are treated alongside efficiency issues. The analysis focuses on the case of investments in renewable energy electricity production facilities, where the impacts on local residents’ welfare are often significantly different from the welfare effects on the general population. We apply the contingent valuation method to specific facilities across the different renewable energy sources in operation in Portugal and conclude that local residents acknowledge the damage sustained differently depending on the type, location and operation of the facilities. The results from these case studies attest to the need of acknowledging and quantifying the negative impacts on local communities so as to be able to assess the social sustainability of renewable energy projects, alongside the two other pillars of sustainability. [ABSTRACT FROM AUTHOR]

• Technology innovation assessed in terms of its effects in other sectors. • Industrial transformative capacity driven by context, complementarities and competition. • Proximity to existing activities accelerates growth but distance create opportunities. • Industrial specialization and technology characteristics as sources of variation. • Indicator to measure the transformative capacity of innovations is proposed. This paper investigates the conditions in which the development of new technologies induce structural change in the economy. A literature review reveals three factors that influence the industrial transformative capacity of a technology: context; complementarities; competition. We explore the dynamics of these factors, focusing on the extent and nature of induced activities in adjacent sectors. We apply this framework to study marine renewable energy technologies (MRET) in Portugal. Adjacent sector firms active in several MRET exhibited diversified activity, innovation and internal change. Comparing with Norway, where an offshore sector (oil & gas) supports the emergence of offshore wind, the absence of such sector in Portugal raises challenges but also creates opportunities for the transformation of several other sectors. We develop a new indicator to identify and compare the industrial transformative capacity of innovations. Finally, we discuss the extent to which context, complementarities and competition contribute to accelerate or hinder transformative change. [ABSTRACT FROM AUTHOR]

Addressing Europe's decarbonisation challenge involves widespread deployment of nearly zero-energy buildings, deep energy renovations and renewable energy integration in the building sector. Enhancing energy efficiency in public buildings necessitates tailored solutions and strategic planning involving Local Public Administration. This work focuses on advancing insights into the application of the PrioritEE Decision Support Tool in Portuguese public buildings, highlighting the energy and financial savings and carbon dioxide emission reduction potential. Using detailed building characterisation data from energy performance certificates, we applied the tool across 22 public buildings of diverse typologies in three distinct regions of Portugal, representing various public entities. Results demonstrate the tool's adaptability, enabling a comprehensive assessment of energy performance and facilitating the exploration of customised energy efficiency and renewable energy solutions. The research emphasises the critical role of user-friendly tools in aiding policymakers and local administration technicians in meeting national renovation targets and contributing to the broader energy transition objectives. [ABSTRACT FROM AUTHOR]

The incorporation of renewable energy systems in the world energy system has been steadily increasing during the last few years. In terms of the building sector, the usual consumers are becoming increasingly prosumers, and the trend is that communities of energy, whose households share produced electricity, will increase in number in the future. Another observed tendency is that the aggregator (the entity that manages the community) trades the net community energy in public energy markets. To accomplish economically good transactions, accurate and reliable forecasts of the day-ahead net energy community must be available. These can be obtained using an ensemble of multi-step shallow artificial neural networks, with prediction intervals obtained by the covariance algorithm. Using real data obtained from a small energy community of four houses located in the southern region of Portugal, one can verify that the deterministic and probabilistic performance of the proposed approach is at least similar, typically better than using complex, deep models. [ABSTRACT FROM AUTHOR]

Despite the fact that the current level of energy supply security in Europe is quite satisfactory, new challenges present a potential risk of jeopardising the current state of affairs. Among others, key challenges are related to the strengthening of the market framework (in the context of deregulation and unbundling as imposed by EU directives) and the increasing penetration of renewable energy sources in the generation mix (with inherently greater variability). Under these circumstances, assessing the value of lost load (VoLL) is useful to support energy decision-making, including benefit-cost analysis and the design of suitable regulatory frameworks. This paper develops VoLL estimation using a macroeconomic technique, namely the production-function approach. The VoLL determines the foregone value added due to electricity outage. The production-function method is applied to the Portuguese case and an average VoLL of 5.12 €/kWh is found. The paper also presents the VoLL results obtained for various economic sectors as well as households. Moreover, the temporal variation of the VoLL along typical weekdays and weekend, in winter and in summer, and for the most relevant sectors (manufacturing, retail services, and households) is demonstrated and discussed. [ABSTRACT FROM AUTHOR]

Fossil fuel dependency in Portugal is represented in around 76% of the total primary energy use, from which almost half is associated to the road transport sector. The reduction of imported fossil energy, pollutants and CO2 emissions is seen as a solution to a more sustainable energy system. This paper analyzes the market penetration of battery electric vehicles in the road transport sector as an alternative and more efficient technology, considering its maximum share in the transport sector in 2050. The main goal is to evaluate the energy consumption, air pollutants (including CO2 emissions), and the economic impacts of conventional and electric vehicles in Portugal. The environmental Kuznets effect in the studied factors is also evaluated. Life cycle methodology was applied to the "fuel" production and use stage, and to the materials of the vehicle. Although reducing energy consumption and emissions is essential, the relation of such impact within the region economy is also extremely important. Based on a Kuznets curve hypothesis, some of those impacts were possible to co-relate with the gross domestic product evolution in Portugal. The evolution of the energy source share, energy production efficiency, vehicle type share in the Portuguese light duty vehicle fleet, and technology efficiency, was also considered. Although the electrification of the road sector can potentially lower the fossil fuel importation, the electricity demand should increase. Nevertheless, it is estimated that around 43% of the energy consumption, 47% of CO2 emissions, and 17%-40% of air pollutants could be reduced with the expected electric vehicle evolution. [ABSTRACT FROM AUTHOR]

Hydrokinetic energy has been mainly studied in areas where the principal driver of the current is the tide. However, in certain areas river discharges play also a principal role. The exploitation of the hydrokinetic resource in such areas has its own peculiarities, dictated by the combined influence of the two driving agents. The objective of this paper is to investigate the exploitation of hydrokinetic energy in the Miño Estuary, the largest estuary in NW Spain and N Portugal, with a focus on the site-specific performance of hydrokinetic energy converters (HECs) and its intra-annual variability. A state-of-the-art hydrodynamics numerical model is implemented and successfully validated based on field data. A third-generation HEC—to be more specific, the new Smart Freestream Turbine (SFT)—is considered, and its performance at the location with the greatest potential is assessed by means of: (i) site-specific efficiency, (ii) availability factor, and (iii) capacity factor. We find that, whereas the site-specific efficiency does not vary significantly, the availability and capacity factors do experience substantial intra-annual (seasonal) variability. In summer and autumn, river discharges are low, and the tide dominates the hydrokinetic resource. In contrast, during winter and spring, the river discharges significantly contribute to the resource, leading to a considerable increase in the availability and capacity factors. More generally, the results imply that in areas subject to combined fluvial and tidal influences the performance of HECs may depart significantly from that in tide-dominated areas, and this departure must be carefully weighed in assessing a project. • Hydrokinetic resource under influence of tide and river discharges is investigated. • River discharges induce a pronounced seasonal variability in the hydrokinetic resource. • The hydrokinetic resource is controlled to a large extent by the hydrological regime. • River discharges lead to a considerable increase in the performance during winter. [ABSTRACT FROM AUTHOR]

Short-term photovoltaic (PV) power forecasting is essential for integrating renewable energy sources into the grid as it provides accurate and timely information on the expected output of PV systems. Deep learning (DL) networks have shown promising results in this area, but depending on the weather conditions and the particularities of each PV system, different DL architectures may perform best. This paper proposes a meta-learning method to improve one-hour-ahead deterministic forecasts of PV systems by dynamically blending the base forecasts of multiple DL models to learn under what conditions each model performs best. Four base models of different long short-term memory architectures are used to produce PV production forecasts without using numerical weather predictions, with the objective to enhance the generalizability of the proposed solution. The accuracy of the meta-learner is evaluated using three rooftop PV systems in Lisbon, Portugal. Results indicate that different base models perform best at different PV plants, and meta-learning can improve accuracy by up to 5% over the most accurate base model per plant and up to 4.5% over the equal-weighted combination of the base forecasts. These improvements are statistically significant and even larger during peak production hours. • Four LSTM models for hour-ahead PV production forecasting. • A meta-learning model to optimally blend the forecasts of the four LSTM models. • Focus on NWP independent approaches, resulting in faster and more reliable models. • Evaluation on three PV plants located in Portugal using representative benchmarks. [ABSTRACT FROM AUTHOR]

Portugal, in line with the European Union, is aiming for carbon neutrality by 2050 (Net Zero), which implies a transition to sustainable energy sources. Climate change is all too evident, as extreme weather periods are occurring in a cyclical manner with greater brevity to such an extent that the grid operator must deal with production scenarios where it can no longer rely on hydroelectric production given the recurring drought situation. This situation increases dependence on thermal production using natural gas and imports. This has significant economic implications. Portugal has exploited its onshore wind potential, reaching an installed capacity of 5.671 MW by 2022. However, the expansion of onshore wind energy is limited to reinforcing the existing infrastructure. To overcome these challenges, it is necessary to expand the exploitation of the offshore wind potential that is already underway. This article proposes the location of offshore wind production platforms along the Portuguese coast. This allows for an analysis of offshore production and its optimization according to the minimum cost per MWh in the face of extreme scenarios, i.e., in periods of extreme drought where the hydroelectric production capacity is practically non-existent. The model is fed by using market price indications and the amount of energy needed for the following day. Using forecast data, the model adapts offshore wind production for the following day according to the minimization of the average market price. This study presents an optimization model adapted to combat the unpredictability of extreme weather conditions. This strategic framework significantly increases the resilience and reliability of offshore wind energy production, marking a significant advance in the management of renewable energy under the pressure of climate variability. The results of the simulations allow us to conclude that despite the high cost of offshore technology (in deep waters), in extreme climate scenarios, it enables cost reduction and a clear decrease in imports. [ABSTRACT FROM AUTHOR]

Abstract: Directive 2010/31/EU adopted that by the end of 2020 all new buildings should be nearly Zero-Energy Buildings (nZEB) and Member States should achieve cost-optimal levels by ensuring minimum energy performance requirements for buildings. This paper discusses how low should be the energy required by a nZEB, in the context of housing energy consumption in a Mediterranean climate (Lisbon). For selected houses built after 1990, the calculated primary energy loads for regulated uses – heating, cooling and domestic hot water – are found to be below 90kWh/(m2 year). Applying the cost-optimal solutions of thermal insulation and glazing type and considering energy efficiency improved systems, this study concludes that housing energy loads are ‘low’ for the indicative range of 70kWh/(m2 year) for regulated uses or 100–110kWh/(m2 year) for total uses, taking primary energy indicators (PEI) from EN 15603. Assuming PEI from Passive House Planning Package or those to be assumed in Portugal for 2013, the threshold decreases to 60kWh/(m2 year) for regulated uses or 90–100kWh/(m2 year) for total uses. Only the first nZEB condition is explored by this paper. The second condition requires that the nZEB energy load is covered by a ‘significant’ part of renewable energy sources produced on-site or ‘nearby’. [Copyright &y& Elsevier]

Water scarcity, water quality deterioration and the increasing demand for water and for renewable energy in water systems, require sound planning and management practices supported by computer modeling. Such management practices must ensure the sustainable use of water resources, including the achievement of a good status of water bodies as prescribed by the EU Water Framework Directive. The purpose of this paper is to establish the applicability and limitations of two commercial software products to simulate the operation of a water system based on the Sorraia water project in Portugal. Particular attention was given to two products: (1) AQUATOOL, developed by the Universidad Politécnica de Valencia (UPV); and, (2) WEAP developed by the Stockholm Environment Institute (SEI). The capabilities of the two models were analyzed focusing on the following aspects: (1) capability to reproduce the operation of a water system; (2) capacity to estimate the system's reliability to meet water demands; (3) easiness of the modeling process, including entry data requirements and presentation of results; (4) usefulness to support decisions of water authorities. From the modeling activity process it is possible to conclude that: (1) AQUATOOL and WEAP are applicable in planning exercises, for which it is necessary to evaluate possible modifications in existing water systems and to analyze the effectiveness of resource exploitation policies, by taking into account objectives and infrastructure; and, (2) within certain modeling limitations, these software products can be used for water allocation predictions, multi-reservoir modeling, and reliability assessment of water systems. [ABSTRACT FROM AUTHOR]

Abstract A new era of cleaner distributed generators, like wind and solar, dispersed along the distribution network are gaining great importance and contributing to the environment and political goals. However, the variability and intermittency of those generators pose new complexities and challenges to the network planning. This research paper proposes an innovative stochastic methodology to deal with the expansion planning of large distribution networks in a smart grid context with high penetration of distributed renewable energy sources and considering the seasonal impact. Also, new power lines locations and types, the size and the location of energy storage systems are considered in the optimization. A distribution network with 180 buses located in Portugal considering high distributed generators penetration is used to illustrate the application of the proposed methodology. The results demonstrate the advantage of the stochastic model when compared with a deterministic formulation, avoiding the need for larger investments in new lines and energy storage systems. Highlights • Seasonal and daily periods impact effect in the long-term DN expansion planning. • Two-stage stochastic model in a smart grid context with high RES penetration. • Optimal ESS size and location and optimal type and location of new lines. • Optimal investment expansion planning. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a refined description of the wave climate observed in a Portuguese location for marine energy projects. The data used in this case study were derived from 3-month in situ measurements carried out using three directional buoys that have been deployed simultaneously – yet independently (various buoy types and water depths) – on the Atlantic coast in the neighbourhood of Figueira da Foz. Two ways of reporting the statistics were adopted. In the first one, each recorded sea state was summarized as a set of global parameters accounting for energy, mean frequency and direction, spectral bandwidth and directional spreading related to the main ongoing wave field considered as unimodal. In the second one, each sea state has been decomposed into its own wave components – swells and wind-sea – which are characterised separately and individually by the same set of parameters as previously. Besides the adopted data processing techniques and the illustration of such thorough wave climate description modes, the paper also addresses the advantages and limits of each adopted parameterization in the frame of simultaneous and independent in situ wave measurements. [Copyright &y& Elsevier]

Abstract: Portugal is a country with an energy system highly dependent on oil and gas imports. Imports of oil and gas accounted for 85% of the country’s requirements in 2005 and 86% in 2006. Meanwhile, the share of renewable energy sources (RES) in the total primary energy consumption was only 14% in 2006. When focusing only on electricity production, the situation is somewhat better. The share of RES in gross electricity production varies between 20% and 35% and is dependent on the hydropower production in wet and dry years. This paper presents, on a national scale, Portugal’s energy system planning and technical solutions for achieving 100% RES electricity production. Planning was based on hourly energy balance and use of H2RES software. The H2RES model provides the ability to integrate various types of storages into energy systems in order to increase penetration of the intermittent renewable energy sources or to achieve a 100% renewable island, region or country. The paper also represents a stepping-stone for studies offering wider possibilities in matching and satisfying electricity supply in Portugal with potential renewable energy sources. Special attention has been given to intermittent sources such as wind, solar and ocean waves that can be coupled to appropriate energy storage systems charged with surplus amounts of produced electricity. The storage systems also decrease installed power requirements for generating units. Consequently, these storages will assist in avoiding unnecessary rejection of renewable potential and reaching a sufficient security of energy supply. [ABSTRACT FROM AUTHOR]

Renewable Energy Sources provide a viable solution to the problem of ever-increasing climate change. For this reason, several countries focus on electricity production using alternative sources. In this paper, the optimal positioning of the installation of wave energy converters is examined taking into account geospatial and technical limitations. Geospatial constraints depend on Land Use classes and seagrass of the coastal areas, while technical limitations include meteorological conditions and the morphology of the seabed. Suitable installation areas are selected after the exclusion of points that do not meet the aforementioned restrictions. We implemented a Deep Neural Network that operates based on heterogeneous data fusion, in this case satellite images and time series of meteorological data. This fact implies the definition of a two-branches architecture. The branch that is trained with image data provides for the localization of dynamic geospatial classes in the potential installation area, whereas the second one is responsible for the classification of the region according to the potential wave energy using wave height and period time series. In making the final decision on the suitability of the potential area, a large number of static land use data play an important role. These data are combined with neural network predictions for the optimizing positioning of the Wave Energy Converters. For the sake of completeness and flexibility, a Multi-Task Neural Network is developed. This model, in addition to predicting the suitability of an area depending on seagrass patterns and wave energy, also predicts land use classes through Multi-Label classification process. The proposed methodology is applied in the marine area of the city of Sines, Portugal. The first neural network achieves 98.7% Binary Classification accuracy, while the Multi-Task Neural Network 97.5% in the same metric and 93.5% in the F1 score of the Multi-Label classification output. [ABSTRACT FROM AUTHOR]

The need for reducing fossil fuel consumption and greenhouse gas (GHG) emissions in internal combustion engines has raised the opportunity for the use of renewable energy sources. For the progressive replacement of fossil fuels like diesel, those derived from the sustainable management of forest resources may be a good option. In Portugal, pine trees (pinus pinaster) are among the most widely cultivated tree species. Turpentine can be extracted from their sap without harming the tree. Turpentine is known to be a good fuel with a lower viscosity than regular diesel but with a comparable caloric value, boiling point and ignition characteristics, although it is not widely used as a compression ignition fuel. Moreover, recent research has highlighted the possibility of substantially increasing the turpentine yield through biotechnology, bringing it closer to economic viability. The present study investigates the performance, pollutant emissions and fuel consumption of a 1.6 L four-cylinder direct-injection diesel engine operating with several blends of commercial diesel fuel and turpentine obtained from pine trees. The aim of this study was to assess whether it would be possible to maintain or even improve the performance, fuel consumption and GHG and pollutant emissions (HC, NOx, CO and PM) of the engine with the partial incorporation of this biofuel. Turpentine blends of up to 30% in substitution of regular diesel fuel were tested. The main novelties of the present work are related to (i) the careful testing of a still-insufficiently studied fuel that could gain economical attractiveness with the recent developments in yield improvement through biotechnology and (ii) the tests conducted under fixed engine load positions typical of road and highway conditions. The addition of this biofuel only slightly impacted the engine performance parameters. However, a slightly positive effect was observed in terms of torque, with an increase of up to 7.9% at low load for the 15T85D mixture and 6.8% at high load being observed. Power registered an increase of 9% for the 15T85D mixture at low speed and an increase of 5% for the 30T70D mixture at high speed when compared to the reference fuel (commercial diesel fuel). While the efficiency and fossil GHG emissions were improved with the incorporation of turpentine, it had a mixed effect on polluting emissions such as unburned hydrocarbons (HC) and smoke (PM) and a negative effect on nitrogen oxides (NOx). NOx emissions increased by 30% for high loads and 20% for low loads, mainly as an indirect effect of the improvement in the engine performance and not so much as a consequence of the marginally higher oxygen content of turpentine relative to commercial diesel fuel. [ABSTRACT FROM AUTHOR]

This paper investigates the spatial characteristics of wind speed statistics in oceanic areas of Portugal. The main goal is to apply a regionalization method to define statistically homogeneous regions and then analyze the probabilistic moments, the wind power density, percentiles and extreme values within each region. The Regional Frequency Analysis based on L-moments was implemented using five years of atmospheric simulations. The domain convers latitudes 36.0ºN to 42.2ºN and longitudes 11.0ºW to 7.2ºW, with resolution of 0.081° X 0.097° and 6 h. The investigation using the L-moment ratios resulted in four regions: north (1), center (2), southwest (3) and south (4) of Portugal. A discussion about the potential associated with each region, in terms of the wind energy available and the extreme events severity, enriches the final analyses. Region 1 has the benefit of the highest mean wind power density, equal to 909 W / m 2 , but it presented the most extreme winds with return value of 25.4 m/s for the return period of 20 years. It was observed that extreme winds are reduced moving south, together with the wind power densities, which are analyzed in detail. The spatial and regional characteristics of wind power densities and extreme values are deeply explored. [ABSTRACT FROM AUTHOR]

Despite Portugal's effort to reduce carbon emissions, the country still emits about 1.6% of the European Union's CO2 emissions. Meanwhile, limited empirical studies have been undertaken in the context of Portugal. As a result, this study examines the asymmetric and long-term impact of CO2 intensity of GDP, energy consumption, renewable energy and economic growth on CO2 emissions in Portugal from 1990 to 2019. The nonlinear autoregressive distributed lag (NARDL) is employed to uncover the asymmetric connection. The findings show that there is nonlinear cointegration among the variables. The long-run estimation reveals a positive change in energy consumption positively affects CO2 emissions, while a negative shock in energy consumption has a neutral effect on CO2 emissions. Furthermore, positive shocks of economic growth and CO2 intensity of GDP enhance environmental deterioration by increasing CO2 emissions. Meanwhile, the negative shock of these regressors positively impacts CO2 emissions. In addition, positive shocks in renewable energy enhance environmental quality, while negative shocks in renewable energy increase environmental deterioration in Portugal. Policymakers should focus on reducing per-unit energy usage and CO2 efficiency gains, which would necessitate a significant reduction in CO2 intensity and energy density of GDP. [ABSTRACT FROM AUTHOR]

Fossil fuels, especially coal, contribute to carbon emissions, hindering the EU's decarbonization goal by 2050. This article proposes converting the Pego Coal Power Plant into a biomass plant as a potential solution. Biomass, a renewable resource abundant in Portugal, can transform the Pego plant into a sustainable energy source, reducing greenhouse gas emissions and combating climate change. It also reduces rural fire risks and ensures regional social and economic stability. The study explores the feasibility, limitations, and socioeconomic impacts of this scenario. This solution prevents plant closure, reduces environmental impacts, and promotes sustainability. Aligning with Portugal's 2030 Agenda and global climate change efforts, converting the Pego plant serves as a valuable example of renewable resource utilization for climate change mitigation and regional stability. The study's results offer insights for policymakers and stakeholders in developing sustainable energy transition strategies. Adopting such solutions can help countries achieve decarbonization goals while promoting social and economic development. [ABSTRACT FROM AUTHOR]

Renewable resources for producing energy for self-consumption are growing, namely solar energy. This work focuses on the comparison of photovoltaic systems for energy production for self-consumption on a property in three different regions of Portugal using traditional and emerging technologies, without batteries' implementation. According to Portuguese law, there is no stipulated value for selling surplus energy produced by a self consumption unit, to the public grid. In order to analyse the economic viability of the project, two scenarios are studied: the delivery, at zero cost of the surplus energy produced to the grid, and its sale. Furthermore, the same analysis is carried out considering partial shading on the photovoltaic generator. The results show that if there is no surplus production sale to the grid, the project becomes economically unviable for the four PV technologies. Otherwise, for the traditional technologies, the project is economically viable, presenting a payback time lower than 10 years. Using emerging technologies, the project becomes economically unviable. When applying partial shading on the generator, the project becomes, in all the scenarios under study, economically unviable. It can be concluded that introducing nanostructures in solar cells to power an infrastructure is not, for now, the best solution from an economic point of view, considering the current legislation. In addition, the shading makes the projects under study unviable, as it is a factor that cannot be controlled in its entirety. [ABSTRACT FROM AUTHOR]

At present, a worldwide paradigm shift has become apparent, with more and more consumers consuming the energy generated by renewable energy sources (RES) systems, such as wind or photovoltaic (PV) energy, sometimes benefiting from appropriate incentives by individual governments. Consequently, it is necessary to carry out technical–economic assessments to understand the evolution of the viability of RES investments. Within the framework of an intelligent network control environment, the smart grid (SG) concept is associated with this model, and is an important tool in the management of energy distribution networks. This article aims to make a further contribution to this issue by analyzing the economic feasibility of investing in residential consumers, considering different RES configurations. Scenarios covered in this study include: "inject all on the low voltage network/consume all on the low voltage network", self-consumption, net-metering, and storage systems. The economic study results in this article show that self-consumption with and without the injection of excess electricity into the grid is quite attractive. The bi-hourly tariff was found to be more profitable than other tariffs. Variable tariffs (bi or tri-hourly) are more profitable than fixed tariffs. It is also concluded that investment in storage systems is not yet an economically viable solution due to the high price of energy storage. [ABSTRACT FROM AUTHOR]

The environmental load associated to Hydrated Lime (HL) products is attributed to the limestone decomposition and the industrial production (combustion in the kiln, the electricity, the transports, etc.). Although the fuel and electricity mix used in the factory can be critical, no records of Life Cycle Assessment (LCA) have been found addressing this for HL. Considering the current environmental crisis, a shift to more sustainable sources of energy is expected. This paper studies, within the SUBLime EU network, the effect of the current fuel and electricity mix used in a HL plant, for Germany, Belgium, Portugal and Spain, as well as future scenarios. A theoretical Cradle-to-Gate Life Cycle Inventory for HL production was developed and used for scenario analysis, namely decarbonisation of the electricity matrix and replacement of hard coal by natural gas (NG) and biomass (B) in the fuel mix. The LCA for 2020 shows that, in 9 out of 15 indicators, the electricity consumption is significant. In terms of Global Warming Potential (GWP), 0.94 kg CO 2 eq /kg HL are produced. Spain and Belgium have shown a better performance followed by Portugal and Germany. The results of future scenarios show that the shift to almost 100% renewable energies for electricity production reduce their sharing in almost all the indicators. As NG and B increase their proportion in the fuel mix, 9, 18 and 22% reductions in GWP in comparison to 2020 are achieved. However, 4 out of 15 indicators are higher than the reference due to the fuel mix. • IEA, 2020 in Europe an average of 0.94 kg CO 2 eq /kg of Hydrated Lime are produced • 9/15 indicators are sensitive to the electricity consumption in the plant • In 2050, 4/15 indicators are higher than in 2020 due to the fuel mix • The replacement of fossil solid fuel in the kiln allows up to 22% CO 2 eq savings. [ABSTRACT FROM AUTHOR]

Biomass is an alternative energy source with high potential to contribute to the global energy mix and to countries' energetic independence. The case of Portugal is particularly relevant, given its biomass availability. Thus, the quantification of woody residual biomass is assumed to be urgent. To achieve the objective of quantifying residual woody biomass, various available data were used, namely the Land Cover and Soil Use Map (COS 2018), from which areas occupied by different categories were selected as being the most relevant. Then, based on coefficients previously established, the amounts of residual woody biomass were determined, namely for maritime pine forests, eucalyptus forests, scrubland, vineyards, olive groves, and orchards. Then, the potential for generating electricity was estimated. It was found that for the hypothetical scenario of the total conversion of the recently closed Pêgo coal power plant to biomass, the available amounts of residual woody biomass in the country would not be sufficient to ensure the operation. On the other hand, if the power plant only worked as a backup unit, the available quantities could ensure its operation and contribute to creating a value chain for residual woody biomass of forest and agricultural origin within a circular economy and sustainable development approach. [ABSTRACT FROM AUTHOR]

Over the past two decades, many countries have used aggressive policies such as feed-in tariffs and power purchase agreements to promote renewable energy. These policies have been very successful in several countries, initiating large changes in the structure of energy sectors, and conferring large environmental, economic, and social impacts. In this paper, we quantify these impacts over the period 2000–2010 for Portugal; a country that witnessed a substantial increase in renewable energy penetration rates, with the share of wind power in electricity production jumping from 0.4% in 2000 to 16.8% in 2010. We use a novel, hybrid energy-economic input–output model to compare the historical energy policy against a counterfactual scenario in which the surge in energy subsidies and concurrent expansion of renewable energies did not take place. We consider the impact of renewable energy policy stemming from three propagation modes – operational, investment, and opportunity costs – in both the energy sector and the rest of the economy. This is the first time such a comprehensive analysis has been undertaken. Our findings show that, in the period under consideration, the combined historical renewable energy policy and renewable energy developments yielded a clear reduction in emissions, in excess of 7.2 MtCO 2 eq, an increase in GDP of 1557 M€, and a creation of 160 thousand job-years. These estimates do not include opportunity costs from future FIT payments that projects built in this period may be entitled to. Therefore, this work will be of critical interest to RES-E and climate change policy makers, other scientists, and the public. [ABSTRACT FROM AUTHOR]

Within a large set of renewable energies being explored to tackle energy sourcing problems, bioenergy can represent an attractive solution if effectively managed. The supply chain design supported by mathematical programming can be used as a decision support tool to the successful bioenergy production systems establishment. This strategic decision problem is addressed in this paper where we intent to study the design of the residual forestry biomass to bioelectricity production in the Portuguese context. In order to contribute to attain better solutions a mixed integer linear programming (MILP) model is developed and applied in order to optimize the design and planning of the bioenergy supply chain. While minimizing the total supply chain cost the production energy facilities capacity and location are defined. The model also includes the optimal selection of biomass amounts and sources, the transportation modes selection, and links that must be established for biomass transportation and products delivers to markets. Results illustrate the positive contribution of the mathematical programming approach to achieve viable economic solutions. Sensitivity analysis on the most uncertain parameters was performed: biomass availability, transportation costs, fixed operating costs and investment costs. [ABSTRACT FROM AUTHOR]

Increasing recognition of the irrefutable urgency to address the global climate challenge is driving mitigation efforts to decarbonise. Countries are setting targets, technological innovation is making renewable energy sources competitive and fossil fuel actors are leveraging their incumbent privilege and political reach to modulate energy transitions. As techno-economic competitiveness is rapidly reconfigured in favour of sources such as solar energy, governance puzzles dominate the research frontier. Who makes key decisions about decarbonisation based on what metrics, and how are consequent benefits and burdens allocated? This article takes its point of departure in ambitious sustainability metrics for solar rollout that Portugal embraced in the late 2010s. This southwestern European country leads on hydro and wind power, and recently emerged from austerity politics after the 2008–2015 recession. Despite Europe's best solar irradiation, its big solar push only kicked off in late 2018. In explaining how this arose and unfolded until mid-2020 and why, the article investigates what key issues ambitious rapid decarbonisation plans must address to enhance social equity. It combines attention to accountability and legitimacy to offer an analytical framework geared at generating actionable knowledge to advance an accountable energy transition. Drawing on empirical study of the contingencies that determine the implementation of sustainability metrics, the article traces how discrete acts legitimate specific trajectories of territorialisation by solar photovoltaics through discursive, bureaucratic, technocratic and financial practices. Combining empirics and perspectives from political ecology and energy geographies, it probes the politics of just energy transitions to more low-carbon and equitable societal futures. [ABSTRACT FROM AUTHOR]

The increase of complexity in school buildings to ensure for users comfort and social and functional demands are changing energy consumption patterns. In the Portuguese context, a recent rise in energy consumption, after a major national refurbishment programme, confirms the need to improve energy management in schools in order to reduce their environmental impact. Besides building design and systems, users are also a determining factor impacting energy consumption in buildings. However, behavioural issues are still among the areas least covered by scientific literature. The present paper analyses the energy consumption patterns of eight Portuguese case-study schools, with a methodological approach that integrates quantitative and qualitative data analysis. The approach made it possible to link the energy consumption patterns of the schools (selected as Key Performance Indicators) with the user behaviour and management strategies. As a result, six Key Performance Strategies (KPS) were identified so as potentially to enhance the energy performance of school buildings through use and management. Some of the identified KPS can be implemented directly through school management policies to reduce energy use and enhance efficiency. Others can be incorporated in future building design strategies. Some have the potential for being hereafter integrated into the simulation models of buildings’ energy performance. [ABSTRACT FROM AUTHOR]