scispace - formally typeset
Search or ask a question
Author

Alfredo Alcayde

Bio: Alfredo Alcayde is an academic researcher from University of Almería. The author has contributed to research in topics: Geometric algebra & AC power. The author has an hindex of 12, co-authored 62 publications receiving 1968 citations.

Papers published on a yearly basis

Papers
More filters
Journal ArticleDOI
TL;DR: A review of the current state of the art in computational optimization methods applied to renewable and sustainable energy can be found in this article, which offers a clear vision of the latest research advances in this field.
Abstract: Energy is a vital input for social and economic development. As a result of the generalization of agricultural, industrial and domestic activities the demand for energy has increased remarkably, especially in emergent countries. This has meant rapid grower in the level of greenhouse gas emissions and the increase in fuel prices, which are the main driving forces behind efforts to utilize renewable energy sources more effectively, i.e. energy which comes from natural resources and is also naturally replenished. Despite the obvious advantages of renewable energy, it presents important drawbacks, such as the discontinuity of generation, as most renewable energy resources depend on the climate, which is why their use requires complex design, planning and control optimization methods. Fortunately, the continuous advances in computer hardware and software are allowing researchers to deal with these optimization problems using computational resources, as can be seen in the large number of optimization methods that have been applied to the renewable and sustainable energy field. This paper presents a review of the current state of the art in computational optimization methods applied to renewable and sustainable energy, offering a clear vision of the latest research advances in this field.

1,394 citations

Journal ArticleDOI
TL;DR: In this article, the authors reviewed the scientific production of renewable energies, namely, solar, wind, biomass, hydropower and geothermal, from 1979 to 2009, and analyzed the production of all the countries in the world, paying particular attention to renewable energies and research institutions.
Abstract: This paper reviews the scientific production of renewable energies, namely, solar, wind, biomass, hydropower and geothermal, from 1979 to 2009. The production of all the countries in the world is analysed, paying particular attention to renewable energies and research institutions. The production of scientific research for each type of energy is represented on world maps to show the degree of relationship between this research and the resources of these energies. It is observed that biomass is the most studied, both by number of publications, with 56% of the publications on renewable energy, and by geographical distribution. The next in importance by number of publications is solar energy (26%). The countries investigating solar energy, however, are not necessarily those with the greatest availability of this resource. Wind is the third positioned in publication (11%). Wind is being investigated by countries that most have implemented this type of energy production. Hydro and geothermal energies are also investigated by countries with great abundance of this resource. It is observed that research on renewable energy is highly concentrated in a few countries (12 or 14, depending on the energy type), accounting for between 70 and 80% of scientific production. The role of the USA as a leader in research in all renewable energies studies is emphasised. NASA is the leading institution for solar and wind energy, the Chinese Academy of Sciences leads in hydropower and biomass, and the U.S. Geological Survey leads in geothermal energy.

302 citations

Journal ArticleDOI
TL;DR: This paper presents a new generational genetic algorithm (GGA+) that includes efficient initialisation methods and search operators under the guidance of modularity that enables a flexible and adaptive analysis of the characteristics of a network from different levels of detail according to an analyst’s needs.
Abstract: Community detection is a challenging optimisation problem that consists in searching for communities that belong to a network or graph under the assumption that the nodes of the same community share properties that enable the detection of new characteristics or functional relationships in the network A large number of methods have been proposed to address this problem in many research fields, such as power systems, biology, sociology or physics Many of those optimisation methods use modularity to identify the optimal network subdivision This paper presents a new generational genetic algorithm (GGA+) that includes efficient initialisation methods and search operators under the guidance of modularity Further, this approach enables a flexible and adaptive analysis of the characteristics of a network from different levels of detail according to an analyst’s needs Results obtained in networks of different sizes and characteristics show the good performance of GGA+ in comparison with other five genetic algorithms, including efficient algorithms published in recent years

95 citations

Journal ArticleDOI
TL;DR: This method is based on automatically obtaining bibliographic data from scientific publications through the use of the Scopus Database API Interface, which are then analysed using graph visualization software and statistical tools and show that it is possible to determine in a fast way and with high reliability the main research lines of an institution as well as the structure of the collaboration network.
Abstract: Science is essential for human prosperity because social and technological advances often depend on scientific advances. Science is living a golden era characterized by a rapidly growing number of researchers worldwide exploring different disciplines and research fields. Keeping in mind that funding is limited, many researchers are encouraged to establish new collaborations with individuals or groups of researchers. Furthermore, the funding bodies use increasingly complex criteria to determine the researchers and projects to be supported. In this regard, the analysis of scientific collaboration networks can help to determine the main areas of specialization of universities and research centres, as well as the type of internal and external collaborations of their researchers. This paper presents an advanced method for analysing scientific collaboration networks at universities and research institutions. This method is based on automatically obtaining bibliographic data from scientific publications through the use of the Scopus Database API Interface, which are then analysed using graph visualization software and statistical tools. This model has been validated through the analysis of a real university, and the results show that it is possible to determine in a fast way and with high reliability the main research lines of an institution as well as the structure of the collaboration network. The method opens new perspectives for the study of scientific collaboration networks because it can be applied at different levels of detail, from small research groups to large academic and research centres, and over different time frames.

94 citations

Journal ArticleDOI
TL;DR: In this paper, the authors analyzed the impact of green packaging from business and consumer viewpoints, including some specific issues such as the design and materials used in green packaging, green packaging costs, marketing strategies and corporate social responsibility related to green packaging.
Abstract: Sustainable development is a global objective that aims to address the societal challenge of climate action, the environment, resource efficiency, and raw materials. In this sense, an important strategy is the promotion of green packaging, that is, the use of sustainable materials and designs for the packaging of goods. In recent years, many research works have been published in the specialised area covering the different perspectives and dimensions of green packaging. However, to our knowledge, no previous investigations have analysed the research activity on green packaging from business and consumer perspectives. The present study intends to fill this gap by analysing all of the publications found in the Scopus database with the help of visual analytic tools, including word clouds and Gephi network visualization software. More specifically, our study analyses the impact of green packaging from business and consumer viewpoints, including some specific issues such as the design and materials used in green packaging, green packaging costs, marketing strategies and corporate social responsibility related to green packaging, and the impact of green packaging in waste management, the circular economy, logistics, and supply chain management. The results obtained reveal the growing interest of scholars and researchers in all of these dimensions, as is made patently clear by the increasing number of journal publications in recent years. The practical implications of this study are significant, given the growing awareness among companies and consumers about the importance of the promotion of sustainable development through green packaging alternatives. More specifically, the results of this research could be very useful for all of those agents who are interested in learning about the main lines of research being developed in the field of green packaging.

59 citations


Cited by
More filters
Journal ArticleDOI
TL;DR: In this paper, the authors reviewed the opportunities associated with renewable energy sources which include: Energy Security, Energy Access, Social and Economic development, Climate Change Mitigation, and reduction of environmental and health impacts.
Abstract: The world is fast becoming a global village due to the increasing daily requirement of energy by all population across the world while the earth in its form cannot change. The need for energy and its related services to satisfy human social and economic development, welfare and health is increasing. Returning to renewables to help mitigate climate change is an excellent approach which needs to be sustainable in order to meet energy demand of future generations. The study reviewed the opportunities associated with renewable energy sources which includes: Energy Security, Energy Access, Social and Economic development, Climate Change Mitigation, and reduction of environmental and health impacts. Despite these opportunities, there are challenges that hinder the sustainability of renewable energy sources towards climate change mitigation. These challenges include Market failures, lack of information, access to raw materials for future renewable resource deployment, and our daily carbon footprint. The ...

1,545 citations

Journal ArticleDOI
TL;DR: A review of the current state of the art in computational optimization methods applied to renewable and sustainable energy can be found in this article, which offers a clear vision of the latest research advances in this field.
Abstract: Energy is a vital input for social and economic development. As a result of the generalization of agricultural, industrial and domestic activities the demand for energy has increased remarkably, especially in emergent countries. This has meant rapid grower in the level of greenhouse gas emissions and the increase in fuel prices, which are the main driving forces behind efforts to utilize renewable energy sources more effectively, i.e. energy which comes from natural resources and is also naturally replenished. Despite the obvious advantages of renewable energy, it presents important drawbacks, such as the discontinuity of generation, as most renewable energy resources depend on the climate, which is why their use requires complex design, planning and control optimization methods. Fortunately, the continuous advances in computer hardware and software are allowing researchers to deal with these optimization problems using computational resources, as can be seen in the large number of optimization methods that have been applied to the renewable and sustainable energy field. This paper presents a review of the current state of the art in computational optimization methods applied to renewable and sustainable energy, offering a clear vision of the latest research advances in this field.

1,394 citations

Journal ArticleDOI
TL;DR: The review indicates that future researches should be oriented towards improving the efficiency of search techniques and approximation methods for large-scale building optimization problems; and reducing time and effort for such activities.
Abstract: Recent progress in computer science and stringent requirements of the design of “greener” buildings put forwards the research and applications of simulation-based optimization methods in the building sector. This paper provides an overview on this subject, aiming at clarifying recent advances and outlining potential challenges and obstacles in building design optimization. Key discussions are focused on handling discontinuous multi-modal building optimization problems, the performance and selection of optimization algorithms, multi-objective optimization, the application of surrogate models, optimization under uncertainty and the propagation of optimization techniques into real-world design challenges. This paper also gives bibliographic information on the issues of simulation programs, optimization tools, efficiency of optimization methods, and trends in optimization studies. The review indicates that future researches should be oriented towards improving the efficiency of search techniques and approximation methods (surrogate models) for large-scale building optimization problems; and reducing time and effort for such activities. Further effort is also required to quantify the robustness in optimal solutions so as to improve building performance stability.

1,009 citations

Journal ArticleDOI
TL;DR: In this article, the authors present a comprehensive literature review of AC and DC microgrid (MG) systems in connection with distributed generation (DG) units using renewable energy sources (RESs), energy storage systems (ESS) and loads.
Abstract: This paper presents the latest comprehensive literature review of AC and DC microgrid (MG) systems in connection with distributed generation (DG) units using renewable energy sources (RESs), energy storage systems (ESS) and loads. A survey on the alternative DG units' configurations in the low voltage AC (LVAC) and DC (LVDC) distribution networks with several applications of microgrid systems in the viewpoint of the current and the future consumer equipments energy market is extensively discussed. Based on the economical, technical and environmental benefits of the renewable energy related DG units, a thorough comparison between the two types of microgrid systems is provided. The paper also investigates the feasibility, control and energy management strategies of the two microgrid systems relying on the most current research works. Finally, the generalized relay tripping currents are derived and the protection strategies in microgrid systems are addressed in detail. From this literature survey, it can be revealed that the AC and DC microgrid systems with multiconverter devices are intrinsically potential for the future energy systems to achieve reliability, efficiency and quality power supply.

1,004 citations

Journal ArticleDOI
TL;DR: In this paper an attempt is made to review the various energy demand forecasting models to accurately predict the future energy needs.
Abstract: Energy is vital for sustainable development of any nation – be it social, economic or environment. In the past decade energy consumption has increased exponentially globally. Energy management is crucial for the future economic prosperity and environmental security. Energy is linked to industrial production, agricultural output, health, access to water, population, education, quality of life, etc. Energy demand management is required for proper allocation of the available resources. During the last decade several new techniques are being used for energy demand management to accurately predict the future energy needs. In this paper an attempt is made to review the various energy demand forecasting models. Traditional methods such as time series, regression, econometric, ARIMA as well as soft computing techniques such as fuzzy logic, genetic algorithm, and neural networks are being extensively used for demand side management. Support vector regression, ant colony and particle swarm optimization are new techniques being adopted for energy demand forecasting. Bottom up models such as MARKAL and LEAP are also being used at the national and regional level for energy demand management.

1,002 citations