Future changes of wind energy potentials over Europe in a large CMIP5 multi-model ensemble

A statistical-dynamical downscaling method is used to estimate future changes of wind energy output (Eout) of a benchmark wind turbine across Europe at the regional scale. With this aim, 22 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble are considered. The downscaling method uses circulation weather types and regional climate modelling with the COSMO-CLM model. Future projections are computed for two time periods (2021–2060 and 2061–2100) following two scenarios (RCP4.5 and RCP8.5). The CMIP5 ensemble mean response reveals a more likely than not increase of mean annual Eout over Northern and Central Europe and a likely decrease over Southern Europe. There is some uncertainty with respect to the magnitude and the sign of the changes. Higher robustness in future changes is observed for specific seasons. Except from the Mediterranean area, an ensemble mean increase of Eout is simulated for winter and a decreasing for the summer season, resulting in a strong increase of the intra-annual variability for most of Europe. The latter is, in particular, probable during the second half of the 21st century under the RCP8.5 scenario. In general, signals are stronger for 2061–2100 compared to 2021–2060 and for RCP8.5 compared to RCP4.5. Regarding changes of the inter-annual variability of Eout for Central Europe, the future projections strongly vary between individual models and also between future periods and scenarios within single models. This study showed for an ensemble of 22 CMIP5 models that changes in the wind energy potentials over Europe may take place in future decades. However, due to the uncertainties detected in this research, further investigations with multi-model ensembles are needed to provide a better quantification and understanding of the future changes.

Emergency energy resource management in SmartGrids

Energy resources management can play a very relevant role in future power systems in a SmartGrid context, with intensive penetration of distributed generation and storage systems. This paper deals with the importance of resource management in incident situations. The paper presents DemSi, an energy resources management simulator that has been developed by the authors to simulate electrical distribution networks with high distributed generation penetration, storage in network points and customers with demand response contracts. DemSi is used to undertake simulations for an incident scenario, evidencing the advantages of adequately using flexible contracts, storage, and reserve in order to limit incident consequences.

Distributed energy resources management with cyber-physical SCADA in the context of future smart grids

In the energy management of a small power system, the scheduling of the generation units is a crucial problem for which adequate methodologies can maximize the performance of the energy supply. This paper proposes an innovative methodology for distributed energy resources management. The optimal operation of distributed generation, demand response and storage resources is formulated as a mixed-integer linear programming model (MILP) and solved by a deterministic optimization technique CPLEX-based implemented in General Algebraic Modeling Systems (GAMS). The paper deals with a vision for the grids of the future, focusing on conceptual and operational aspects of electrical grids characterized by an intensive penetration of DG, in the scope of competitive environments and using artificial intelligence methodologies to attain the envisaged goals. These concepts are implemented in a computational framework which includes both grid and market simulation.

Distributed Energy Resources Management using Plug-in Hybrid Electric Vehicles as a Fuel-Shifting Demand Response Resource

In the smart grids context, distributed energy resources management plays an important role in the power systems’ operation. Battery electric vehicles and plug-in hybrid electric vehicles should be important resources in the future distribution networks operation. Therefore, it is important to develop adequate methodologies to schedule the electric vehicles’ charge and discharge processes, avoiding network congestions and providing ancillary services. This paper proposes the participation of plug-in hybrid electric vehicles in fuel shifting demand response programs. Two services are proposed, namely the fuel shifting and the fuel discharging. The fuel shifting program consists in replacing the electric energy by fossil fuels in plug-in hybrid electric vehicles daily trips, and the fuel discharge program consists in use of their internal combustion engine to generate electricity injecting into the network. These programs are included in an energy resources management algorithm which integrates the management of other resources. The paper presents a case study considering a 37-bus distribution network with 25 distributed generators, 1908 consumers, and 2430 plug-in vehicles. Two scenarios are tested, namely a scenario with high photovoltaic generation, and a scenario without photovoltaic generation. A sensitivity analyses is performed in order to evaluate when each energy resource is required.

Real-Time Simulation of energy Management in a Domestic Consumer

Recent and future changes in power systems, mainly in the smart grid operation context, are related to a high complexity of power networks operation. This leads to more complex communications and to higher network elements monitoring and control levels, both from network’s and consumers’ standpoint. The present work focuses on a real scenario of the LASIE laboratory, located at the Polytechnic of Porto. Laboratory systems are managed by the SCADA House Intelligent Management (SHIM), already developed by the authors based on a SCADA system. The SHIM capacities have been recently improved by including real-time simulation from Opal RT. This makes possible the integration of Matlab®/Simulink® real-time simulation models. The main goal of the present paper is to compare the advantages of the resulting improved system, while managing the energy consumption of a domestic consumer.

Real-time Energy Resource Scheduling considering a Real Portuguese Scenario

The development in power systems and the introduction of decentralized generation and Electric Vehicles (EVs), both connected to distribution networks, represents a major challenge in the planning and operation issues. This new paradigm requires a new energy resources management approach which considers not only the generation, but also the management of loads through demand response programs, energy storage units, EVs and other players in a liberalized electricity markets environment. This paper proposes a methodology to be used by Virtual Power Players (VPPs), concerning the energy resource scheduling in smart grids, considering day-ahead, hour-ahead and real-time scheduling. The case study considers a 33-bus distribution network with high penetration of distributed energy resources. The wind generation profile is based on a real Portuguese wind farm. Four scenarios are presented taking into account 0, 1, 2 and 5 periods (hours or minutes) ahead of the scheduling period in the hour-ahead and realtime scheduling.

A New Heuristic Providing an Effective Initial Solution for a Simulated Annealing approach to Energy Resource Scheduling in Smart Grids

An intensive use of dispersed energy resources is expected for future power systems, including distributed generation, especially based on renewable sources, and electric vehicles. The system operation methods and tool must be adapted to the increased complexity, especially the optimal resource scheduling problem. Therefore, the use of metaheuristics is required to obtain good solutions in a reasonable amount of time. This paper proposes two new heuristics, called naive electric vehicles charge and discharge allocation and generation tournament based on cost, developed to obtain an initial solution to be used in the energy resource scheduling methodology based on simulated annealing previously developed by the authors. The case study considers two scenarios with 1000 and 2000 electric vehicles connected in a distribution network. The proposed heuristics are compared with a deterministic approach and presenting a very small error concerning the objective function with a low execution time for the scenario with 2000 vehicles.

Impacts of climate change scenarios on terrestrial productivity and biomass for energy in the Iberian Peninsula: assessment through the JSBACH model

Dissertação para obtenção do Grau de Mestre em Engenharia do Ambiente, Perfil de Gestão e Sistemas Ambientais

A green future for European electricity? :Energy sources, policies and further determinants of the household price of electricity

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

Clearing the cloudy crystal balls: Hybrid modelling for energy and climate change mitigation scenarios – A case study for Portugal

Dissertação para obtenção do Grau de Doutor em Ambiente

Scenario-based assessment of future land use change on butterfly species distributions

Species distribution models (SDMs) are increasingly used to predict environmentally induced range shifts of habitats of plant and animal species. Consequently SDMs are valuable tools for scientifically based conservation decisions. The aims of this paper are (1) to identify important drivers of butterfly species persistence or extinction, and (2) to analyse the responses of endangered butterfly species of dry grasslands and wetlands to likely future landscape changes in Switzerland. Future land use was represented by four scenarios describing: (1) ongoing land use changes as observed at the end of the last century; (2) a liberalisation of the agricultural markets; (3) a slightly lowered agricultural production; and (4) a strongly lowered agricultural production. Two model approaches have been applied. The first (logistic regression with principal components) explains what environmental variables have significant impact on species presence (and absence). The second (predictive SDM) is used to project species distribution under current and likely future land uses. The results of the explanatory analyses reveal that four principal components related to urbanisation, abandonment of open land and intensive agricultural practices as well as two climate parameters are primary drivers of species occurrence (decline). The scenario analyses show that lowered agricultural production is likely to favour dry grassland species due to an increase of non-intensively used land, open canopy forests, and overgrown areas. In the liberalisation scenario dry grassland species show a decrease in abundance due to a strong increase of forested patches. Wetland butterfly species would decrease under all four scenarios as their habitats become overgrown

Why Catalonia will see its energy metabolism increase in the near future: an application of MuSIASEM

This paper applies the so-called Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) to the economy of the Spanish region of Catalonia. By applying Georgescu-Roegen's fund-flow model, it arrives at the conclusion that within a context of the end of cheap oil, the current development model based on the growth of low productivity sectors such as services and construction must change. The change is needed not only because of the increasing scarcity of affordable energy carriers, or because of the increasing environmental impact that the present development represents, but also because of an ageing population that demands labour productivity gains. This will imply industry requiring more energy consumption per worker in order to increase its productivity, and therefore its competitiveness. Thus, we conclude that energy intensity, and exosomatic energy metabolism of Catalonia will increase dramatically in the near future unless major conservation efforts are implemented in both the household and transport sectors.

Food for thought: the importance of glucose and other energy substrates for sustaining brain function under varying levels of activity.

The brain requires a constant and substantial energy supply to maintain its main functions. For decades, it was assumed that glucose was the major if not the only significant source of energy for neurons. This view was supported by the expression of specific facilitative glucose transporters on cerebral blood vessels, as well as neurons. Despite the fact that glucose remains a key energetic substrate for the brain, growing evidence suggests a different scenario. Thus astrocytes, a major type of glial cells that express their own glucose transporter, play a critical role in coupling synaptic activity with glucose utilization. It was shown that glutamatergic activity triggers an enhancement of aerobic glycolysis in this cell type. As a result, lactate is provided to neurons as an additional energy substrate. Indeed, lactate has proven to be a preferential energy substrate for neurons under various conditions. A family of proton-linked carriers known as monocarboxylate transporters has been described and specific members have been found to be expressed by endothelial cells, astrocytes and neurons. Moreover, these transporters are subject to fine regulation of their expression levels and localization, notably in neurons, which suggests that lactate supply could be adjusted as a function of their level of activity. Considering the importance of energetics in the aetiology of several neurodegenerative diseases, a better understanding of its cellular and molecular underpinnings might have important implications for the future development of neuroprotective strategies.

Scenario method in anticipating future opportunities of e-business in the forest industry

Tutkimuksen tavoitteena on ennakoida liiketoimintaprosessien sähköistymisen kehittymistä käyttämällä skenaariomenetelmää, yhtä laajimmin käytetyistä tulevaisuuden tutkimisen menetelmistä. Tarkastelun kohteena ovat erityisesti tulevaisuuden e-business -ratkaisut metsäteollisuudessa. Tutkimuksessa selvitetään skenaariomenetelmän ominaisuuksia, skenaariosuunnittelun periaatteita sekä menetelmän sopivuutta teknologian ja toimialan muutosten tarkasteluun. Tutkimuksen teoriaosassa selvitetään teknologian muutoksen vaikutusta toimialojen kehitykseen. Todettiin, että teknologisella muutoksella on vahva vaikutus toimialojen muutoksiin, ja että jokainen toimiala seuraa tietynlaista kehitystrajektoria. Yritysten tulee olla tietoisia teknologisen muutoksen nopeudesta ja suunnasta, ja seurata toimialansa kehityksen sääntöjä. Metsäteollisuudessa muutosten radikaali luonne sekä ICT-teknologian nopea kehitys asettavat haasteita liiketoimintaprosessien sähköistämisen kentässä. Empiriaosuudessa luotiin kolme erilaista skenaariota e-busineksen tulevaisuudesta metsäteollisuudessa. Skenaariot perustuvat pääosin aiheen asiantuntijoiden tämän hetkisiin näkemyksiin, joita koottiin skenaariotyöpajassa. Skenaarioiden muodostamisessa yhdistettiin kvalitatiivisia ja kvantitatiivisia elementtejä. Muodostetut kolme skenaariota osoittavat, että e-busineksen vaikutukset tulevaisuudessa nähdään pääosin positiivisina, ja että yritysten tulee kehittyä aktiivisesti ja joustavasti pystyäkseen hyödyntämään sähköisiä ratkaisuja tehokkaasti liiketoiminnassaan.

International bioenergy trade- scenario study on international biomass market in 2020

The markets of biomass for energy are developing rapidly and becoming more international. A remarkable increase in the use of biomass for energy needs parallel and positive development in several areas, and there will be plenty of challenges to overcome. The main objective of the study was to clarify the alternative future scenarios for the international biomass market until the year 2020, and based on the scenario process, to identify underlying steps needed towards the vital working and sustainable biomass market for energy purposes. Two scenario processes were conducted for this study. The first was carried out with a group of Finnish experts and thesecond involved an international group. A heuristic, semi-structured approach, including the use of preliminary questionnaires as well as manual and computerised group support systems (GSS), was applied in the scenario processes.The scenario processes reinforced the picture of the future of international biomass and bioenergy markets as a complex and multi-layer subject. The scenarios estimated that the biomass market will develop and grow rapidly as well as diversify in the future. The results of the scenario process also opened up new discussion and provided new information and collective views of experts for the purposes of policy makers. An overall view resulting from this scenario analysis are the enormous opportunities relating to the utilisation of biomass as a resource for global energy use in the coming decades. The scenario analysis shows the key issues in the field: global economic growth including the growing need for energy, environmental forces in the global evolution, possibilities of technological development to solve global problems, capabilities of the international community to find solutions for global issues and the complex interdependencies of all these driving forces. The results of the scenario processes provide a starting point for further research analysing the technological and commercial aspects related the scenarios and foreseeing the scales and directions of biomass streams.