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Percorrer Integração de Sistemas de Energia - ISE por Objetivos de Desenvolvimento Sustentável (ODS) "11:Cidades e Comunidades Sustentáveis"
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- Analysis of Techno-Economic and Social Impacts of Electric Vehicle Charging Ecosystem in the Distribution Network Integrated with Solar DG and DSTATCOMPublication . Bonela, Ramesh; Ghatak, Sriparna Roy; Swain, Sarat Chandra; Lopes, Fernando; Nandi, Sharmistha; Sannigrahi, Surajit; Acharjee, ParimalABSTRACT: In this work, a comprehensive planning framework for an electric vehicle charging ecosystem (EVCE) is developed, incorporating solar distributed generation (DG) and a distribution static compensator (DSTATCOM), to assess their long-term techno-economic and environmental impacts. The optimal locations and capacities of the EVCE, solar DG, and DSTATCOM are determined using an improved particle swarm optimization algorithm based on the success rate technique. The study aims to maximize the technical, financial, and social benefits while ensuring that all security constraints are met. To assess the financial viability of the proposed model over a 10-year horizon, a detailed economic analysis comprising installation cost, operation, and maintenance cost is conducted. To make the model more realistic, various practical parameters, such as the inflation rate and interest rate, are incorporated during the financial analysis. Additionally, to highlight the societal benefits of the approach, the study quantifies the long-term carbon emissions and the corresponding cost of emissions. The proposed framework is tested on both a 33-bus distribution network and a 108-bus Indian distribution network. Various planning scenarios are explored, with different configurations of the EVCE, solar-based DG, and DSTATCOM, to assist power system planners in selecting the most suitable strategy.
- 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.
- 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.
- Optimized Planning Framework for Radial Distribution Network Considering AC and DC EV Chargers, Uncertain Solar PVDG, and DSTATCOM Using HHOPublication . Bonela, Ramesh; Tripathy, Sasmita; Roy Ghatak, Sriparna; Swain, Sarat Chandra; Lopes, Fernando; Acharjee, ParimalABSTRACT: This study aims to provide an efficient framework for the coordinated integration of AC and DC chargers, intermittent solar Photovoltaic (PV) Distributed Generation (DG) units, and a Distribution Static Compensator (DSTATCOM) across residential, commercial, and industrial zones of a Radial Distribution Network (RDN) considering the benefits of various stakeholders: Electric Vehicle (EV) charging station owners, EV owners, and distribution network operators. The model uses a multi-zone planning method and healthy-bus strategy to allocate Electric Vehicle Charging Stations (EVCSs), Photovoltaic Distributed Generation (PVDG) units, and DSTATCOMs. The proposed framework optimally determines the numbers of EVCSs, PVDG units, and DSTATCOMs using Harris Hawk Optimization, considering the maximization of techno-economic benefits while satisfying all the security constraints. Further, to showcase the benefits from the perspective of EV owners, an EV waiting-time evaluation is performed. The simulation results show that integrating EVCSs (with both AC and DC chargers) with solar PVDG units and DSTATCOMs in the existing RDN improves the voltage profile, reduces power losses, and enhances cost-effectiveness compared to the system with only EVCSs. Furthermore, the zonal division ensures that charging infrastructure is distributed across the network increasing accessibility to the EV users. It is also observed that combining AC and DC chargers across the network provides overall benefits in terms of voltage profile, line loss, and waiting time as compared to a system with only AC or DC chargers. The proposed framework improves EV owners' access and reduces waiting time, while supporting distribution network operators through enhanced grid stability and efficient integration of EV loads, PV generation, and DSTATCOM.
- Systemic complementarities and transformative change: A tentative methodology to examine bidirectionality effects across connected systems [Resumo]Publication . Padua, Muriela; Fontes, MargaridaABSTRACT: Achieving energy-sustainable goals involves large-scale production and social changes necessary to fulfil societal functions (Geels, 2004; Markard, 2011). These long-term goals imply a transformative change requiring multiple transitions involving multiple socio-technical systems and their interplay (Raven and Verbong, 2007; Geels, 2007; Papachristos, 2013; Rosenbloom, 2020). To fully address system change, it is necessary to consider that changes in one system affect the other (Geels, 2007; Papachristos, 2013), i.e., the presence of bidirectionality in system interactions. However, bidirectionality has only recently started being tackled and remains under-conceptualized.