Browsing by Author "Pousinho, Hugo Miguel Inácio"
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- An artificial neural network approach for short-term wind power forecasting in PortugalPublication . Catalão, João Paulo da Silva; Pousinho, Hugo Miguel Inácio; Mendes, VictorThis paper presents an artificial neural network approach for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. The accuracy of the wind power forecasting attained with the proposed approach is evaluated against persistence and ARIMA approaches, reporting the numerical results from a real-world case study.
- Application of adaptive neuro-fuzzy inference for wind power short-term forecastingPublication . Pousinho, Hugo Miguel Inácio; Mendes, Victor; Catalão, João Paulo da SilvaThe increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. In this paper, an adaptive neuro-fuzzy inference approach is proposed for short-term wind power forecasting. Results from a real-world case study are presented. A thorough comparison is carried out, taking into account the results obtained with other approaches. Numerical results are presented and conclusions are duly drawn. (C) 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
- A hybrid PSO-ANFIS approach for short-term wind power prediction in PortugalPublication . Pousinho, Hugo Miguel Inácio; Mendes, Victor; Catalão, João Paulo da SilvaThe increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.
- Hybrid Wavelet-PSO-ANFIS Approach for Short-Term Electricity Prices ForecastingPublication . Catalão, João Paulo da Silva; Pousinho, Hugo Miguel Inácio; Mendes, VictorA novel hybrid approach, combining wavelet transform, particle swarm optimization, and adaptive-network-based fuzzy inference system, is proposed in this paper for short-term electricity prices forecasting in a competitive market. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Finally, conclusions are duly drawn.
- Hydro energy systems management in Portugal: Profit-based evaluation of a mixed-integer nonlinear approachPublication . Catalão, João Paulo da Silva; Pousinho, Hugo Miguel Inácio; Mendes, VictorIn this paper, a novel mixed-integer nonlinear approach is proposed to solve the short-term hydro scheduling problem in the day-ahead electricity market, considering not only head-dependency, but also start/stop of units, discontinuous operating regions and discharge ramping constraints. Results from a case study based on one of the main Portuguese cascaded hydro energy systems are presented, showing that the proposedmixed-integer nonlinear approach is proficient. Conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.
- Investigation on the development of bidding strategies for a wind farm ownerPublication . Pousinho, Hugo Miguel Inácio; Mendes, Victor; Catalão, João Paulo da SilvaIn this paper, the development of bidding strategies is investigated for a wind farm owner. The optimization model is characterized by making the analysis of scenarios. The proposed approach allows evaluating alternative production strategies in order to submit bids to the electricity market with the goal of maximizing profits. The problem is formulated as a linear programming problem. An application to a case study is presented
- Mixed-integer nonlinear approach for the optimal scheduling of a head-dependent hydro chainPublication . Catalão, João Paulo da Silva; Pousinho, Hugo Miguel Inácio; Mendes, VictorThis paper is on the problem of short-term hydro scheduling (STHS), particularly concerning a head-dependent hydro chain We propose a novel mixed-integer nonlinear programming (MINLP) approach, considering hydroelectric power generation as a nonlinear function of water discharge and of the head. As a new contribution to eat her studies, we model the on-off behavior of the hydro plants using integer variables, in order to avoid water discharges at forbidden areas Thus, an enhanced STHS is provided due to the more realistic modeling presented in this paper Our approach has been applied successfully to solve a test case based on one of the Portuguese cascaded hydro systems with a negligible computational time requirement.
- Optimal generation scheduling of wind-CSP systems in day-ahead electricity marketsPublication . Pousinho, Hugo Miguel Inácio; Freire, P.; Esteves, João; Mendes, Victor; Cabrita, Carlos Pereira; Collares-Pereira, ManuelThis paper presents a coordination approach to maximize the total profit of wind power systems coordinated with concentrated solar power systems, having molten-salt thermal energy storage. Both systems are effectively handled by mixed-integer linear programming in the approach, allowing enhancement on the operational during non-insolation periods. Transmission grid constraints and technical operating constraints on both systems are modeled to enable a true management support for the integration of renewable energy sources in day-ahead electricity markets. A representative case study based on real systems is considered to demonstrate the effectiveness of the proposed approach. © IFIP International Federation for Information Processing 2015.
- Optimal offering strategies for wind power producers considering uncertainty and riskPublication . Catalão, João Paulo da Silva; Pousinho, Hugo Miguel Inácio; Mendes, VictorThis paper provides a two-stage stochastic programming approach for the development of optimal offering strategies for wind power producers. Uncertainty is related to electricity market prices and wind power production. A hybrid intelligent approach, combining wavelet transform, particle swarm optimization and adaptive-network-based fuzzy inference system, is used in this paper to generate plausible scenarios. Also, risk aversion is explicitly modeled using the conditional value-at-risk methodology. Results from a realistic case study, based on a wind farm in Portugal, are provided and analyzed. Finally, conclusions are duly drawn.
- Risk Aversion in a Mixed-Integer Nonlinear Approach to Support Decision-Making for a Hydro Power ProducerPublication . Catalão, João Paulo da Silva; Pousinho, Hugo Miguel Inácio; Mendes, VictorIn this paper, a mixed-integer nonlinear approach is proposed to support decision-making for a hydro power producer, considering a head-dependent hydro chain. The aim is to maximize the profit of the hydro power producer from selling energy into the electric market. As a new contribution to earlier studies, a risk aversion criterion is taken into account, as well as head-dependency. The volatility of the expected profit is limited through the conditional value-at-risk (CVaR). The proposed approach has been applied successfully to solve a case study based on one of the main Portuguese cascaded hydro systems.
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