Persona:
Colmenar Santos, Antonio

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ORCID
0000-0001-8543-4550
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Colmenar Santos
Nombre de pila
Antonio
Nombre

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2020 - 20223
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Ajustes

Autor: Rosales Asensio, Enrique × Fecha de inicio: 2020 ×

Resultados de la búsqueda

Mostrando 1 - 3 de 3
  • Miniatura
    Publicación
    Technical challenges for the optimum penetration of grid-connected photovoltaic systems: Spain as a case study
    (Elsevier, 2020-01) Linares Mena, Ana Rosa; Molina Ibáñez, Enrique Luis; Rosales Asensio, Enrique; Borge Díez, David; Colmenar Santos, Antonio
    This research reviews the technical requirements of grid-connected photovoltaic power plants to increase their competitiveness and efficiently integrate into the grid to satisfy future demand requirements and grid management challenges, focusing on Spain as a case study. The integration of distributed resources into the electric network, in particular photovoltaic energy, requires an accurate control of the system. The integration of photovoltaic energy has resulted in significant changes to the regulatory framework to ensure proper integration of distributed generation units in the grid. In this study, the requirements of the system operator for the management and smart control are first analysed and then the technical specifications established by the network operator in reference to the components of the facility are evaluated. This analysis identifies the shortcomings of the current legislation and concludes with a summary of the main technical recommendations and future regulatory challenges that need to be undertaken in the future. It is presented as a reference case that can be adapted worldwide.
  • Miniatura
    Publicación
    Adaptive model predictive control for electricity management in the household sector
    (Elsevier, 2022-05) Muñoz Gómez, Antonio Miguel; Rosales Asensio, Enrique; Fernández Aznar, Gregorio; Galán Hernández, Noemi; Colmenar Santos, Antonio
    This paper focuses on the optimisation of electricity consumption in residential buildings. To deal with the increase in electricity consumption, the intermittency of renewable energy generation and grid contingencies, a greater effort is required towards residential management optimisation. A novel adaptive model predictive control algorithm is proposed to achieve this objective. The challenges for this research included recognising and modelling the economic and technical constraints of the sources and appliances and addressing the uncertainties concerning the weather and user behaviour. Data-driven models are developed and trained to predict the user behaviour and buildings. Artificial neural networks and statistical models based on the weighted moving average are proposed to capture the patterns of deferrable and non-deferrable appliances, battery storage, electric vehicles, photovoltaic modules, buildings and grid connections. A dual optimisation method is devised to minimise the electricity bill and achieve thermal comfort. The proposed optimisation solver is a two-step optimisation method based on genetic algorithm and mixed integer linear programming. A comprehensive simulation study was carried out to reveal the effectiveness of the proposed method through a set of simulation scenarios. The results of the quantitative analysis undertaken as part of this study show the effectiveness of the proposed algorithm towards reducing electricity charges and improving grid elasticity.
  • Miniatura
    Publicación
    Study on the economics of wind energy through cryptocurrency
    (Elsevier, 2022-11-02) Vega Marcosa, Raúl; Mur Pérez, Francisco; Pérez Molina, Clara María; Rosales Asensio, Enrique; Colmenar Santos, Antonio
    The Green Pact signed by the European Union establishes a trend towards renewable energies to combat the greenhouse gas emissions. Among the technologies used to produce this type of energy, wind power generation technology stands out, which, in countries such as Spain, already has significant installed power. The main problems posed by this technology plans are the uncertainty intervals of wind power and its inclusion in the electricity market, due to the complex price system that does not always favor the producers. The main purpose of this research is to promote the installation of more wind power plants. For this, the installation of cryptocurrency mining equipment is proposed, which will be powered by the generation produced by these wind power plants. The article analyzes the production of cryptocurrencies is a growing business. In the research process, the latest cryptocurrency mining equipment is evaluated. It is analyzed which equipment is the most suitable for its installation in the wind power plant and an economic study is made for the construction project of a large wind power plant. Finally, it will be seen that in this way the amortization time of the facilities decreases and also the project is more attractive for the investor since they can decide between injecting energy into the electrical network or mining cryptocurrencies. If a wind power plant invests in cryptocurrency mining in parallel to the production of electrical energy for the grid, it can decide when to enter the electricity market pool or engage in mining. In this way, the idea of building many more wind power plants becomes more attractive. This would lead to a market where this renewable energy would be much more abundant and the price curve would shift to a lower price, as well as a significant reduction in greenhouse emissions.