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Browsing Integração de Sistemas de Energia - ISE by Sustainable Development Goals (SDG) "12:Produção e Consumo Sustentáveis"
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- Bridging Regional Divides in Decarbonization: Firm Strategies, Policy Tensions, and Structural Trade-offs in Portugal [Resumo]Publication . Vale, Mário; Alves, Tiago; Fontes, Margarida; Mamede, Ricardo; Bento, NunoABSTRACT: The transition to a low-carbon economy is shaped by structural tensions and trade-offs that impact firms, regions, and policymakers. A central challenge is balancing regional equity, industrial specialization, and technological innovation in decarbonization policies (Markard & Rosenbloom, 2022). This study critically examines these tensions by analysing firm-level decarbonization strategies within the Portugal 2020 (PT2020) program, revealing how economic structures shape sustainability transitions and the effectiveness of policy interventions.
- Critical transitions: Unpacking decarbonization strategies in Portuguese industry and regional disparitiesPublication . Vale, Mário; Alves, Tiago; Duarte de Castro Fontes, Maria Margarida; Mamede, Ricardo; Bento, NunoABSTRACT: In the wake of the Paris Agreement, the urgency for decarbonization has intensified globally, prompting varied responses from different regions and sectors. This study critically examines the uneven decarbonization trajectories of Portuguese firms within the framework of the Portugal 2020 (PT2020) program, informed by transition theory and regional innovation systems. Employing a multi-method approach that combines natural language processing and a systematic literature review, we identify and categorize the decarbonization strategies of 278 out of 2,793 firms funded by PT2020 between 2020 and 2023. Our findings reveal a modest (less than 10 % of all projects) but pivotal engagement in decarbonization, predominantly focused on the Porto metropolitan area and adjacent regions, indicating a pattern of uneven geographical transitions. Larger, established firms predominantly undertake these initiatives, reflecting a skew in policy effectiveness towards more stable entities. The most common pathways—demand and co-benefits (49 %) and decarbonization of electricity (34 %)—suggest a preference for immediately actionable strategies (electrification of uses and technological breakthroughs). This study underscores the disparity in decarbonization efforts across firms, but also regions, correlating higher industrial productivity and urbanization with increased activity. Such trends reveal the influence of existing economic structures and regional capacities on the adoption of green technologies, which exacerbate regional inequalities in the face of global decarbonization mandates. This study improves the understanding on the potential of decarbonization to increase or decrease inequalities among companies and regions. It provides crucial lessons for policies aiming to accelerate decarbonization to achieve the 2030 goals. Further research is required to explore the impact of regional specialization on decarbonization strategies and to develop more inclusive and equitable policies.
- Decarbonization Transition Pathways and Regional Trends: Insights from One Million StudiesPublication . Bento, Nuno; Alves, Tiago; Ribeiro, Ricardo; Fontes, MargaridaABSTRACT: As global temperatures near critical thresholds and emissions continue to rise, the urgency for strategic, accelerated decarbonization grows. Despite a vast climate mitigation literature, a systematic understanding of actionable pathways remains limited. Here, we apply artificial intelligence to analyze over one million scientific papers (2011–2021), generating a data-driven typology of six archetypal decarbonization pathways: Technology Breakthrough, Electrification of Uses, Integrated Policy, Decarbonization of Electricity, Demand Reduction & Co-benefits, and Land Use & Circularity. Regional patterns show Electrification of Uses prevailing in Europe (EU27), while Technology Breakthrough dominates in China, the US, and Japan. Increasing political and societal resistance to mitigation makes the strategic selection and combination of pathways even more critical. Our analysis highlights key synergies between pathways, the scientific competencies required to support them, and persistent gaps—particularly in Land Use and Circularity. We also compare current climate policy directions with the typology, revealing alignment gaps that may weaken policy effectiveness. This framework enables policymakers to better match strategies with regional capacities and research strengths, offering a more coherent approach to decarbonization. Strengthening the integration of science, technology, and policy is essential to overcome fragmentation and deliver the emissions reductions needed to meet the net-zero climate targets.
- Driving Transformative Change: Assessing the Direction and Design of Decarbonization Policies in the EU, US, China, and JapanPublication . Fontes, Margarida; Sousa, Cristina; Bento, NunoABSTRACT: The transition to low‐carbon economies demands policies that drive both decarbonization and deep socioeconomic transformation. This paper assesses the “transformative potential” of 3,400 decarbonization policies from Europe, the US, China, and Japan. We define transformative potential considering both policy direction – alignment with sustainability goals, and policy design ‐ presence of mechanisms that can induce transformation, such as experimentation, actor diversity, multiscale coordination, and reflexivity. The research shows that when we consider a broad universe of decarbonization policies, transformative potential is still limited: only 20% of policies align with at least one transition pathway and include at least one transformative mechanism; and just 2% include three or more mechanisms. By identifying distinguishing features of these higher transformative potential policies, the paper contributes to understanding how technological, sectoral and contextual factors shape the capacity of policies to enable transformative change.
- Dynamic Line Rating Models and Their Potential for a Cost-Effective Transition to Carbon-Neutral Power SystemsPublication . Estanqueiro, Ana; Algarvio, Hugo; Couto, António; Michiorri, Andrea; Salas, Sergio; Pudjianto, Danny; Hagglund, Per; Dobschinski, Jan; Bolgaryn, Roman; Kanefendt, Thomas; Gentle, Jake; Alam, S. M. Shafiul; Priest, Zachary M.; Abboud, Alexander W.ABSTRACT: Most transmission system operators (TSOs) currently use seasonally steady-state models considering limiting weather conditions that serve as reference to compute the transmission capacity of overhead power lines. The use of dynamic line rating (DLR) models can avoid the construction of new lines, market splitting, false congestions, and the degradation of lines in a cost-effective way. DLR can also be used in the long run in grid extension and new power capacity planning. In the short run, it should be used to help operate power systems with congested lines. The operation of the power systems is planned to have the market trading into account; thus, it computes transactions hours ahead of real-time operation, using power flow forecasts affected by large errors. In the near future, within a "smart grid" environment, in real-time operation conditions, TSOs should be able to rapidly compute the capacity rating of overhead lines using DLR models and the most reliable weather information, forecasts, and line measurements, avoiding the current steady-state approach that, in many circumstances, assumes ampacities above the thermal limits of the lines. This work presents a review of the line rating methodologies in several European countries and the United States. Furthermore, it presents the results of pilot projects and studies considering the application of DLR in overhead power lines, obtaining significant reductions in the congestion of internal networks and cross-border transmission lines.
- From Day-Ahead to a 6-Hour Period-Ahead Market Adapted to the Stochastic Behaviour of Variable Energy Renewable SourcesPublication . Couto, António; Algarvio, Hugo; Lopes, Fernando; Estanqueiro, Ana; Santos, Gabriel; Lezama, Fernando; Faia, Ricardo; Carvalho, Rui; Vale, ZitaABSTRACT: The existing electricity market design challenges the fair and competitive participation of variable renewable energy sources (vRES) due to their weather dependence and limited forecasting accuracy, especially for long-time horizons, as required in the day-ahead market (DAM). These challenges impact market clearing prices and create imbalances, leading to inefficiencies, such as market-splitting events. To enhance the market efficiency and fairness for vRES producers, this work proposes a period-ahead market (PAM) with a 6-hour rolling horizon instead of the traditional 24-hour DAM. A case study of the Iberian electricity market with 2030 energy mix scenarios for Portugal and Spain, demonstrates that, in PAM, vRES producers can reduce wind and solar power forecast errors by over 7 % and 4 %, respectively, when compared with DAM. This leads to a 2 % decrease in electricity prices and an annual reduction of marketsplitting events in 158 hours thus enhancing price harmonization between Portugal and Spain. Additionally, balancing prices also decreased in PAM benefiting the balance responsible parties. The findings highlight that PAM improves the market's efficiency, a key factor in the pathway for the decarbonization of power systems.
- Hybrid Variable Renewable Power Plants: A Case Study of ROR Hydro ArbitragePublication . Catarino, Isabel; Romão, Inês; Estanqueiro, AnaABSTRACT: Wind and solar energy sources, while sustainable, are inherently variable in their power generation, posing challenges to grid stability due to their non-dispatchable nature. To address this issue, this study explores the synergistic optimization of wind and solar photovoltaic resources to mitigate power output variability, reducing the strain on local grids and lessening the reliance on balancing power in high-penetration renewable energy systems. This critical role of providing stability can be effectively fulfilled by run-of-river hydropower plants, which can complement fluctuations without compromising their standard operational capabilities. In this research, we employ a straightforward energy balance model to analyze the feasibility of a 100 MW virtual hybrid power plant, focusing on the northern region of Portugal as a case study. Leveraging actual consumption and conceptual production data, our investigation identifies a specific run-of-river plant that aligns with the proposed strategy, demonstrating the practical applicability of this approach.
- A Machine Learning Model for Procurement of Secondary Reserve Capacity in Power Systems with Significant vRES PenetrationsPublication . dos Santos, Joao; Algarvio, HugoABSTRACT: The growing investment in variable renewable energy sources is changing how electricity markets operate. In Europe, players rely on forecasts to participate in day-ahead markets closing between 12 and 37 h ahead of real-time operation. Usually, transmission system operators use a symmetrical procurement of up and down secondary power reserves based on the expected demand. This work uses machine learning techniques that dynamically compute it using the day-ahead programmed and expected dispatches of variable renewable energy sources, demand, and other technologies. Specifically, the methodology incorporates neural networks, such as Long Short-Term Memory (LSTM) or Convolutional neural network (CNN) models, to improve forecasting accuracy by capturing temporal dependencies and nonlinear patterns in the data. This study uses operational open data from the Spanish operator from 2014 to 2023 for training. Benchmark and test data are from the year 2024. Different machine learning architectures have been tested, but a Fully Connected Neural Network (FCNN) has the best results. The proposed methodology improves the usage of the up and down secondary reserved power by almost 22% and 11%, respectively.
- Pre-Solve Methodologies for Short-Run Identification of Critical Sectors in the ACSR Overhead Lines While Using Dynamic Line Rating Models for Resource SustainabilityPublication . Algarvio, HugoABSTRACT: Most transmission system operators (TSOs) use seasonally static models considering extreme weather conditions, serving as a reference for computing the transmission capacity of power lines. The use of dynamic line rating (DLR) models can avoid the construction of new lines, market splitting, false congestions and the degradation of lines in a cost-effective way. The operation of power systems is planned based on market results, which consider transactions hours ahead of real-time operation using forecasts with errors. The same is true for the DLR. So, during real-time operation TSOs should rapidly compute the DLR of overhead lines to avoid considering an ampacity above their lines' design, reflecting the real-time weather conditions. Considering that the DLR of the lines can affect the power flow of an entire region, the use of the complete indirect DLR methodology has a high computation burden for all sectors and lines in a region. So, this article presents and tests three pre-solve methodologies able to rapidly identify the critical sector of each line. These methodologies solve the problem of the high computation burden of the CIGR & Eacute; thermodynamic model of overhead lines. They have been tested by using real data of the transmission grid and the weather conditions for two different regions in Portugal, leading to errors in the computation of the DLR lower than 1% in relation to the complete CIGR & Eacute; model, identifying the critical sector in significantly less time.
- The Role of Demand and Vres Flexibility in Carbon-Neutral Power Systems: Insights from Portugal and Spain in Prospective 2050 ScenariosPublication . Algarvio, Hugo; Couto, António; Lopes, Fernando; Estanqueiro, Ana; Faia, Ricardo; Santos, Gabriel; Carvalho, Rui; Faria, Pedro; Vale, ZitaABSTRACT: The goal of a carbon-neutral society by 2050 is speeding up the integration of variable renewable energy sources (vRES) in European power systems. For the expected levels of vRES, the adaptation of the demand will be crucial to manage the stochastic behaviour of these technologies. This work evaluates the impact of four prospective 2050 energy mix scenarios in the Iberian electricity market. All scenarios consider near 100% vRES shares. Scenarios that incentivize demand flexibility (S2 and S4) result in the lowest wholesale prices and costs for society. Peak load reduction using demand response occurred in the two scenarios (S1 and S3) with low demand flexibility and high share of renewable generation. S3 is the most unstable leading to the higher wholesale prices. The results highlight that an equilibrium between demand flexibility and investments in the generation side is essential for reducing costs and ensuring stability.