ISE - Artigos em revistas internacionais
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- 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.
- 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.
- 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.
- RES.Trade: An Open-Access Simulator to Assess the Impact of Different Designs on Balancing Electricity MarketsPublication . Algarvio, Hugo; Couto, António; Estanqueiro, AnaABSTRACT: The 2050 global ambition for a carbon-neutral society is increasing the penetration of the most competitive variable renewable technologies, onshore wind and solar PV. These technologies are known for their near-zero marginal costs but highly variable time-dependent generation. Power systems with major penetrations of variable generation need high balancing flexibility to guarantee their stability by maintaining the equilibrium between demand and supply. This work presents the open-access Multi-agent Trading of Renewable Energy Sources (RES.Trade) system, which includes different market designs of the imbalance settlement and the secondary and tertiary reserves. A new imbalance settlement is also proposed in this work. The main features of RES.Trade are demonstrated using two case studies and projected 2030 scenarios: the first analysed four imbalance settlement mechanisms in Portugal, achieving a 43% reduction in penalties using the new method; the second case study assesses the impact of five procurement mechanisms of secondary power reserves in the Spanish power system, resulting in a cost reduction by 34% in the case of dynamic reserves.
- Technological innovations in decarbonisation strategies: a text-mining approach to technological readiness and potentialPublication . Costa, Paulo Moisés; Duarte, António; Tomé, Paulo; Bento, Nuno; Fontes, MargaridaABSTRACT: This study presents a novel, multifaceted approach to evaluating decarbonisation technologies by integrating advanced text-mining tools with comprehensive data analysis. The analysis of scientific documents (2011-2021) and mapping 368 technologies from the IEA's Energy Technology Perspectives identified 41 technology domains, including 20 with the highest relevance and occurrence. Domain readiness was assessed using mean Technology Readiness Levels (TRLs) and linked to six decarbonisation pathways. The "Electrification of uses" pathway ranked highest, demonstrating significant CO2 mitigation potential and high readiness (mean TRL 7.4, with two-thirds of technologies scoring over 7) despite challenges in hard-to-electrify sectors. The findings provide actionable insights for policymakers, highlighting the need for pathway-specific strategies, a deeper understanding of synergies between pathways, and balancing innovation with deployment to accelerate decarbonisation.
- Multi-Scenario-Based Strategic Deployment of Electric Vehicle Ultra-Fast Charging Stations in a Radial Distribution NetworkPublication . Nandi, Sharmistha; Ghatak, Sriparna Roy; Acharjee, Parimal; Lopes, FernandoABSTRACT: In the present work, a strategic multi-scenario EV ultra-fast charging station (CS) planning framework is designed to provide advantages to charging station owners, Distribution Network Operators, and EV owners. Locations of CSs are identified using zonal division and the Voltage Stability Index strategy. The number of chargers is determined using the Harris Hawk Optimization (HHO) technique while minimizing the installation, operational costs of CS, and energy loss costs considering all the power system security constraints. To ensure a realistic planning model, uncertainties in EV charging behavior and electricity prices are managed through the 2m-Point Estimate Method. This method produces multiple scenarios of uncertain parameters, which effectively represent the actual dataset, thereby facilitating comprehensive multi-scenario planning. This study incorporates annual EV and system load growth in a long-term planning model of ten years, ensuring the distribution network meets future demand for sustainable transportation infrastructure. The proposed research work is tested on a 33-bus distribution network and a 51-bus real Indian distribution network. To evaluate the financial and environmental benefits of the planning, a cost-benefit analysis in terms of the Return-on-Investment index and a carbon emission analysis are performed, respectively. Furthermore, to prove the efficacy of the HHO technique, the results are compared with several existing algorithms.
- The role of research-based spin-offs in innovation ecosystemsPublication . Conceição, Oscarina; Sousa, Cristina; Fontes, MargaridaABSTRACT: The objective of the paper is to contribute to a better understanding of the various roles played by research-based spin-offs (RBSOs) in knowledge dissemination. It investigates if RBSOs act as connectors and knowledge translators, both between different types of organisations within an innovation ecosystem and across different geographical scales and knowledge environments. This latter role has been relatively less investigated but is important to open local innovation ecosystems. The paper analyses the networks formed by Portuguese RBSOs in the context of research, technology and product development projects. The results suggest that RBSOs play an intermediary role in the country's innovation ecosystem, which can assume different forms. In the national networks, they frequently bridge research and downstream organisations, contributing to the dissemination of knowledge within the ecosystem. In the international networks, their most important role may be as connectors and conveyors of advanced knowledge produced in external knowledge environments
- Strategic Behavior of Competitive Local Citizen Energy Communities in Liberalized Electricity MarketsPublication . Algarvio, Hugo; Couto, António; Lopes, Fernando; Estanqueiro, AnaABSTRACT: The liberalization of energy retail markets empowered consumers with the ability to be part of new emerging entities, such as Citizen Energy Communities. With the increasing penetration of decentralized variable generation, communities have the advantage of incentive local carbon neutrality and sustainability. Local generation reduces transport grid usage and costs to consumers. Furthermore, worldwide legislation incentives energy communities by providing them discounts to other fee parts of the tariff apart from wholesale prices. This paper presents a model of strategic behavior, investment, and trading of energy communities. The model comprises the investment in local renewable generation, the design of competitive tariffs, and strategic bidding on wholesale markets. Consumers have an optimization model that selects the retail tariff that minimizes their costs with energy. These models are tested using data from Portuguese consumers and the Iberian electricity market. Results from the study indicate that inflexible consumers may reduce their costs by 29% by being part of the community. Furthermore, they have the potential to reduce their costs above 50% when using demand-response, adapting themselves to local production and wholesale prices.
- Electrical driven pyrolysis reactor retrofit for indirect concentrated solar heatPublication . Azevedo, Pedro; Costa, PaulaABSTRACT: Aiming for a climate-neutral economy, and the associated transition towards fuels produced from alternative feedstock, and to overcome some biomass pyrolysis unsuitable properties for the conventional combustion devices, plastics pyrolysis also produces oils, whose main compounds are also hydrocarbons, that can be used in conventional engines without so complex and costly upgrading processes. Most of the chemical reactions found in a pyrolysis process are endothermal thus, to fulfill that energy demand, the retrofit of a 4 kW electrical furnace pyrolysis reactor to indirect solar driven energy was assessed aiming to adapt it to a central receiver solar tower with up to 100 kWth-peak, using air as heat transfer fluid. The heat demand along a typical pyrolysis test was experimentally assessed and a heat transfer mathematical model was defined to address the working constraints of the reactor. Additional analysis considering new design parameters were performed, namely sensitive analysis to the length of the new heating coil and its overall heat transfer coefficient, the reactor temperature set point, the inlet and outlet (to the atmosphere) gas temperature and working mass flow rates and temperatures were found to provide the same heat demand and minimize the waste heat. Considering both the heat source facility and the reactor constraints, it was found that the retrofit is possible providing that the product of surface area by the overall heat transfer coefficient (A·U) yields more than 17.7 W/K, for a reactor temperature set point of 450 °C and a maximum temperature inlet of 700 °C.
- Wind power plants hybridised with solar power: A generation forecast perspectivePublication . Couto, António; Estanqueiro, AnaABSTRACT: aggregation for the operation of power systems is an area of recent research. Accurate forecasts are crucial for extracting those benefits and promote an optimal integration of such plants into power systems and electricity markets. This study focuses on the hybridisation of existing wind power plants with different shares of solar photovoltaic capacity and investigates how these power plants can reduce their combined forecast errors and thus, increasing profitability in electricity markets. The work uses a forecast methodology based on a sequential forward feature selection algorithm which employs two different objective functions and an artificial neural network approach previously presented but, in this case, it is applied to the specific case of hybrid power plants. The methodology uses as input data from a numerical weather prediction model and iteratively selects meteorological features to achieve the different objective functions implemented, namely i) minimisation of the root mean square error; or ii) maximisation of the market remuneration. The methodology developed was applied to three case studies in Portugal with different levels of wind and solar generation complementarity. The results show that the hybrid power plants can increase market value by up to 5% and total remuneration can increase by up to 30% when compared with the existing wind power plant, while it is possible to reduce the forecast errors by nearly 4%. The obtained results highlight the need to select the most relevant meteorological features to maximise the accuracy of the power forecast and the renewable power producers revenues in a market environment.