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Publications

Publications by CPES

2020

Wind variability mitigation using multi-energy systems

Authors
Coelho, A; Neyestani, N; Soares, F; Lopes, JP;

Publication
International Journal of Electrical Power and Energy Systems

Abstract
Around the world, there is a great concern with the emission of greenhouse gases, creating great interest in turning the energy systems more sustainable. Multi-energy systems are considered as a potential solution to help to this cause and in recent years, it has gained much attention from both research and industry. In this paper, an optimization model is proposed to use the flexibility of multi-energy systems to mitigate the uncertainty associated with wind generation. The differences between the flexibility provided by multi-energy systems and electrical storage systems in the network were studied. The results prove that the flexibility of the multi-energy systems can benefit the system in several aspects and provide insights on which is the best approach to take full advantage of renewable resources even when a high degree of uncertainty is present. © 2019 Elsevier Ltd

2020

Aggregated dynamic model of active distribution networks for large voltage disturbances

Authors
Fulgencio, N; Moreira, C; Carvalho, L; Lopes, JP;

Publication
Electric Power Systems Research

Abstract

2020

Defining connection requirements for autonomous power systems

Authors
Beires, PP; Moreira, CL; Lopes, JP; Figueira, AG;

Publication
IET Renewable Power Generation

Abstract

2020

Optimal Load Restoration in Active Distribution Networks Complying with Starting Transients of Induction Motors

Authors
Sekhavatmanesh, H; Rodrigues, J; Moreira, CL; Lopes, JAP; Cherkaoui, R;

Publication
IEEE Transactions on Smart Grid

Abstract

2020

Flexibility assessment of multi-energy residential and commercial buildings

Authors
Coelho, A; Soares, F; Lopes, JP;

Publication
Energies

Abstract
With the growing concern about decreasing CO2 emissions, renewable energy sources are being vastly integrated in the energy systems worldwide. This will bring new challenges to the network operators, which will need to find sources of flexibility to cope with the variable-output nature of these technologies. Demand response and multi-energy systems are being widely studied and considered as a promising solution to mitigate possible problems that may occur in the energy systems due to the large-scale integration of renewables. In this work, an optimal model to manage the resources and loads within residential and commercial buildings was developed, considering consumers preferences, electrical network restrictions and CO2 emissions. The flexibility that these buildings can provide was analyzed and quantified. Additionally, it was shown how this model can be used to solve technical problems in electrical networks, comparing the performance of two scenarios of flexibility provision: flexibility obtained only from electrical loads vs. flexibility obtained from multi-energy loads. It was proved that multi-energy systems bring more options of flexibility, as they can rely on non-electrical resources to supply the same energy needs and thus relieve the electrical network. It was also found that commercial buildings can offer more flexibility during the day, while residential buildings can offer more during the morning and evening. Nonetheless, Multi-Energy System (MES) buildings end up having higher CO2 emissions due to a higher consumption of natural gas. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.

2020

A strategy for electricity buyers in futures markets

Authors
Monteiro, C; Ramirez Rosado, IJ; Fernandez Jimenez, LA;

Publication
E3S Web of Conferences

Abstract
This paper presents an original trading strategy for electricity buyers in futures markets. The strategy applies a medium-term electricity price forecasting model to predict the monthly average spot price which is used to evaluate the Risk Premium for a physical delivery under a monthly electricity futures contract. The proposed trading strategy aims to provide an advantage relatively to the traditional strategy of electricity buyers (used as benchmark), anticipating the good/wrong decision of buying electricity in the futures market instead in the day-ahead market. The mid-term monthly average spot price forecasting model, which supports the trading strategy, uses only information available from futures and spot markets at the decision moment. Both the new trading strategy and the monthly average spot price forecasting model, proposed in this paper, have been successfully tested with historical data of the Iberian Electricity Market (MIBEL), although they could be applied to other electricity markets.

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