On performance of distributed model predictive control in power system frequency regulation

This paper describes the implementation of a distributed model predictive approach for automatic generation control. Performance results are discussed by comparing classical techniques (based on integral control) with model predictive control solutions (centralized and distributed) for different operational scenarios with two interconnected networks. These scenarios include variable load levels (ranging from a small to a large unbalance generated power to power consumption ratio) and simultaneously variable distance between the interconnected networks systems. For the two networks the paper also examines the impact of load variation in an island context (a network isolated from each other).

Prospective system analysis of stationary battery systems under the frame of Constructive Technology Assessment

Based on the report for the unit “Project IV” of the PhD programme on Technology Assessment under the supervision of Dr.-Ing. Marcel Weil and Prof. Dr. António Brandão Moniz. The report was presented and discussed at the Doctorate Conference on Technologogy Assessment in July 2013 at the University Nova Lisboa, Caparica campus.

System analysis of a Peer-to-Peer Video-on-Demand architecture: Kangaroo

Architectural design and deployment of Peer-to-Peer Video-on-Demand (P2PVoD) systems which support VCR functionalities is attracting the interest of an increasing number of research groups within the scientific community; especially due to the intrinsic characteristics of such systems and the benefits that peers could provide at reducing the server load. This work focuses on the performance analysis of a P2P-VoD system considering user behaviors obtained from real traces together with other synthetic user patterns. The experiments performed show that it is feasible to achieve a performance close to the best possible. Future work will consider monitoring the physical characteristics of the network in order to improve the design of different aspects of a VoD system.

Towards a system analysis of the early steps of infectious endocarditis pathogenesis

L'endocardite infectieuse (EI) est une maladie potentiellement mortelle qui doit être prévenue dans toute la mesure du possible. Au cours de ces dernières 50 années, les recommandations Américaines et Européennes pour la prophylaxie de PEI proposaient aux patients à risques de prendre un antibiotique, préventif avant de subir une intervention médico-chirurgicale susceptible d'induire une bactériémie transitoire. Cependant, des études épidémiologiques récentes ont montré que la plupart des EI survenaient en dehors de tous actes médico-chirurgicaux, et indépendamment de la prise ou non de prophylaxie antibiotique . L'EI pourrait donc survenir suite à la cumulation de bactériémies spontanées de faibles intensités, associées à des activités de la vie courante telle que le brossage dentaire pour le streptocoques, ou à partir de tissus colonisés ou de cathéters infectés pour les staphylocoques. En conséquence, les recommandations internationales pour la prophylaxie de PEI ont été revues et proposent une diminution drastique de l'utilisation d'antibiotiques. Cependant, le risque d'EI représenté par le cumul de bactériémies de faibles intensités n'a pas été démontré expérimentalement. Nous avons développé un nouveau modèle d'EI expérimentale induite par une inoculation en continu d'une faible quantité de bactéries, simulant le cumul de bactériémies de faibles intensités chez l'homme, et comparé l'infection de Streptococcus gordonii et de Staphylococcus aureus dans ce modèle avec celle du modèle d'IE induite par une bactériémie brève, mais de forte intensité. Nous avons démontré, après injection d'une quantité égale de bactéries, que le nombre de végétations infectées était similaire dans les deux types d'inoculations. Ces résultats expérimentaux ont confirmé l'hypothèse qu'une exposition cumulée à des bactériémies de faibles intensités, en dehors d'une procédure médico-chirurgicale, représentait un risque pour le développement d'une El, comme le suggéraient les études épidémiologiques. En plus, ces résultats ont validé les nouvelles recommandations pour la prophylaxie de l'El, limitant drastiquement l'utilisation d'antibiotiques. Cependant, ces nouvelles recommandations laissent une grande partie (> 90%) de cas potentiels d'EI sans alternatives de préventions, et des nouvelles stratégies prophylactiques doivent être investiguées. Le nouveau modèle d'EI expérimentale représente un modèle réaliste pour étudier des nouvelles mesures prophylactiques potentielles appliquées à des expositions cumulées de bactériémies de faible nombre. Dans un contexte de bactériémies spontanées répétitives, les antibiotiques ne peuvent pas résoudre le problème de la prévention de l'EI. Nous avons donc étudié la une alternative de prévention par l'utilisation d'agents antiplaquettaires. La logique derrière cette approche était basée sur le fait que les plaquettes sont des composants clés dans la formation des végétations cardiaques, et le fait que les bactéries capables d'interagir avec les plaquettes sont plus enclines à induire une El. Les agents antiplaquettaires utilisés ont été l'aspirine (inhibiteur du COX1), la ticlopidine (inhibiteur du P2Y12, le récepteur de l'ADP), et l'eptifibatide et Pabciximab, deux inhibiteurs du GPIIb/IIIa, le récepteur plaquettaire pour le fibrinogène. Les anticoagulants étaient le dabigatran etexilate, inhibant lathrombine et l'acenocumarol, un antagoniste de la vitamine K. L'aspirine, la ticlopidine ou l'eptifibatide seuls n'ont pas permis de prévenir l'infection valvulaire (> 75% animaux infectés). En revanche, la combinaison d'aspirine et de ticlopidine, aussi bien que l'abciximab, ont protégé 45% - 88% des animaux de l'EI par S. gordonii et par S. aureus. L'antithrombotique dabigatran etexilate à protégé 75% des rats contre l'EI par S. aureus, mais pas (< 30% de protection) par S. gordonii. L'acenocoumarol n'a pas eu d'effet sur aucun des deux organismes. En général, ces résultats suggèrent un possible rôle pour les antiplaquettaires et du dabigatran etexilate dans la prophylaxie de l'EI dans un contexte de bactériémies récurrentes de faibles intensités. Cependant, l'effet bénéfique des antiplaquettaires doit être soupesé avec le risque d'hémorragie inhérent à ces molécules, et le fait que les plaquettes jouent un important rôle dans les défenses de l'hôte contre les infections endovasculaires. En plus, le double effet bénéfique du dabigatran etexilate devrait être revu chez les patients porteurs de valves prothétiques, qui ont besoin d'une anticoagulation à vie, et chez lesquels l'EI à S. aureus est associée avec une mortalité de près de 50%. Comme l'approche avec des antiplaquettaires et des antithrombotiques pourrait avoir des limites, une autre stratégie prophylactique pourrait être la vaccination contre des adhésines de surfaces des pathogènes. Chez S. aureus, la protéine de liaison au fibrinogène, ou dumping factor A (ClfA), et la protéine de liaison à la fibronectine (FnbpA) sont des facteurs de virulence nécessaires à l'initiation et l'évolution de PEI. Elles représentent donc des cibles potentielles pour le développement de vaccins contre cette infection. Récemment, des nombreuses publications ont décrit que la bactérie Lactococcus lactis pouvait être utilisée comme vecteur pour la diffusion d'antigènes bactériens in vivo, et que cette approche pourrait être une stratégie de vaccination contre les infections bactériennes. Nous avons exploré l'effet de l'immunisation par des recombinant de L. lactis exprimant le ClfA, la FnbpA, ou le ClfA ensemble avec et une forme tronquée de la FnbpA (Fnbp, comprenant seulement le domaine de liaison à la fibronectine mais sans le domaine A de liaison au fibrinogène [L. lactis ClfA/Fnbp]), dans la prophylaxie de PIE expérimentale à S. aureus. L. lactis ClfA a été utilisés comme agent d'immunisation contre la souche S. aureus Newman (qui a particularité de n'exprimer que le ClfA, mais pas la FnbpA). L. lactis ClfA, L. lactis FnbpA, et L. lactis ClfA/Fnbp, ont été utilisé comme agents d'immunisation contre une souche isolée d'une IE, S. aureus P8 (exprimant ClfA et FnbpA). L'immunisation avec L. lactis ClfA a généré des anticorps anti-ClfA fonctionnels, capables de bloquer la liaison de S. aureus Newman au fibrinogène in vitro et protéger 13/19 (69%) animaux d'une El due à S. aureus Newman (P < 0.05 comparée aux contrôles). L'immunisation avec L. lactis ClfA, L. lactis FnbpA, ou L. lactis ClfA/Fnbp, a généré des anticorps contre chacun de ces antigènes. Cependant, ils n'ont pas permis de bloquer l'adhésion de S. aureus P8 au fibrinogène et à la fibronectine in vitro. De plus, l'immunisation avec L. lactis ClfA ou L. lactis FnbpA s'est avérée inefficace in vivo (< 10% d'animaux protégés d'une El) et l'immunisation avec L. lactis ClfA/Fnbp a fourni une protection limitée de l'EI (8/23 animaux protégés; P < 0.05 comparée aux contrôles) après inoculation avec S. aureus P8. Dans l'ensemble, ces résultats indiquent que L. lactis est un système efficace pour la présentation d'antigènes in vivo et potentiellement utile pour la prévention de PEI à S. aureus. Cependant, le répertoire de protéines de surface de S. aureus capable d'évoquer une panoplie d'anticorps efficace reste à déterminer.. En résumé, notre étude a démontré expérimentalement, pour la première fois, qu'une bactériémie répétée de faible intensité, simulant la bactériémie ayant lieu, par exemple, lors des activités de la vie quotidienne, est induire un taux d'EI expérimentale similaire à celle induite par une bactériémie de haute intensité suite à une intervention médicale. Dans ce contexte, où l'utilisation d'antibiotiques est pas raisonnable, nous avons aussi montré que d'autres mesures prophylactiques, comme l'utilisation d'agents antiplaquettaires ou antithrombotiques, ou la vaccination utilisant L. lactis comme vecteur d'antigènes bactériens, sont des alternatives prometteuses qui méritent d'être étudiées plus avant. Thesis Summary Infective endocarditis (IE) is a life-threatening disease that should be prevented whenever possible. Over the last 50 years, guidelines for IE prophylaxis proposed the use of antibiotics in patients undergoing dental or medico-surgical procedures that might induce high, but transient bacteremia. However, recent epidemiological studies indicate that IE occurs independently of medico-surgical procedures and the fact that patients had taken antibiotic prophylaxis or not, i.e., by cumulative exposure to random low-grade bacteremia, associated with daily activities (e.g. tooth brushing) in the case of oral streptococci, or with a colonized site or infected device in the case of staphylococci. Accordingly, the most recent American and European guidelines for IE prophylaxis were revisited and updated to drastically restrain antibiotic use. Nevertheless, the relative risk of IE represented by such cumulative low-grade bacteremia had never been demonstrated experimentally. We developed a new model of experimental IE due to continuous inoculation of low-grade bacteremia, mimicking repeated low-grade bacteremia in humans, and compared the infectivity of Streptococcus gordonii and Staphylococcus aureus in this model to that in the model producing brief, high-level bacteremia. We demonstrated that, after injection of identical bacterial numbers, the rate of infected vegetations was similar in both types of challenge. These experimental results support the hypothesis that cumulative exposure to low-grade bacteremia, outside the context of procedure-related bacteremia, represents a genuine risk of IE, as suggested by human epidemiological studies. In addition, they validate the newer guidelines for IE prophylaxis, which drastic limit the procedures in which antibiotic prophylaxis is indicated. Nevertheless, these refreshed guidelines leave the vast majority (> 90%) of potential IE cases without alternative propositions of prevention, and novel strategies must be considered to propose effective alternative and "global" measures to prevent IE initiation. The more realistic experimental model of IE induced by low-grade bacteremia provides an accurate experimental setting to study new preventive measures applying to cumulative exposure to low bacterial numbers. Since in a context of spontaneous low-grade bacteremia antibiotics are unlikely to solve the problem of IE prevention, we addressed the role of antiplatelet and anticoagulant agents for the prophylaxis of experimental IE induced by S. gordonii and S. aureus. The logic of this approach was based on the fact that platelets are key players in vegetation formation and vegetation enlargement, and on the fact that bacteria capable of interacting with platelets are more prone to induce IE. Antiplatelet agents included the COX1 inhibitor aspirin, the inhibitor of the ADP receptor P2Y12 ticlopidine, and two inhibitors of the platelet fibrinogen receptor GPIIb/IIIa, eptifibatide and abciximab. Anticoagulants included the thrombin inhibitor dabigatran etexilate and the vitamin K antagonist acenocoumarol. Aspirin, ticlopidine or eptifibatide alone failed to prevent aortic infection (> 75% infected animals). In contrast, the combination of aspirin with ticlopidine, as well as abciximab, protected 45% to 88% of animals against IE due to S. gordonii and S. aureus. The antithrombin dabigatran etexilate protected 75% of rats against IE due to S. aureus, but failed (< 30% protection) against S. gordonii. Acenocoumarol had no effect against any bacteria. Overall, these results suggest a possible role for antiplatelet agents and dabigatran etexilate in the prophylaxis of IE in humans in a context of recurrent low- grade bacteremia. However, the potential beneficial effect of antiplatelet agents should be balanced against the risk of bleeding and the fact that platelets play an important role in the host defenses against intravascular infections. In addition, the potential dual benefit of dabigatran etexilate might be revisited in patients with prosthetic valves, who require life-long anticoagulation and in whom S. aureus IE is associated with high mortality rate. Because the antiplatelet and anticoagulant approach might be limited in the context of S. aureus bacteremia, other prophylactic strategies for the prevention of S. aureus IE, like vaccination with anti-adhesion proteins was tested. The S. aureus surface proteins fibrinogen-binding protein clumping-factor A (ClfA) and the fibronectin-binding protein A (FnbpA) are critical virulence factors for the initiation and development of IE. Thus, they represent key targets for vaccine development against this disease. Recently, numerous reports have described that the harmless bacteria Lactococcus lactis can be used as a bacterial vector for the efficient delivery of antigens in vivo, and that this approach is a promising vaccination strategy against bacterial infections. We therefore explored the immunization capacity of non- living recombinant L. lactis ClfA, L. lactis FnbpA, or L. lactis expressing ClfA together with Fnbp (a truncated form of FnbpA with only the fibronectin-binding domain but lacking the fibrinogen-binding domain A [L. lactis ClfA/Fnbp]), to protect against S. aureus experimental IE. L. lactis ClfA was used as immunization agent against the laboratory strain S. aureus Newman (expressing ClfA, but lacking FnbpA). L. lactis ClfA, L. lactis FnbpA, as well as L. lactis ClfA/Fnbp, were used as immunization agents against the endocarditis isolate S. aureus P8 (expressing both ClfA and FnbpA). Immunization with L. lactis ClfA produced anti-ClfA functional antibodies, which were able to block the binding of S. aureus Newman to fibrinogen in vitro and protect 13/19 (69%) animals from IE due to S. aureus Newman (P < 0.05 compared to controls). Immunization with L. lactis ClfA, L. lactis FnbpA or L. lactis ClfA/Fnbp, produced antibodies against each antigen. However, they were not sufficient to block S. aureus P8 binding to fibrinogen and fibronectin in vitro. Moreover, immunization with L. lactis ClfA or L. lactis FnbpA was ineffective (< 10% protected animals) and immunization with L. lactis ClfA/Fnbp conferred limited protection from IE (8/23 protected animals; P < 0.05 compared to controls) after challenge with S. aureus P8. Together, these results indicate that L. lactis is an efficient delivering antigen system potentially useful for preventing S. aureus IE. They also demonstrate that expressing multiple antigens in L. lactis, yet to be elucidated, will be necessary to prevent IE due to clinical S. aureus strains fully equipped with virulence determinants. In summary, our study has demonstrated experimentally, for the first time, the hypothesis that low-grade bacteremia, mimicking bacteremia occurring outside of a clinical intervention, is equally prone to induce experimental IE as high-grade bacteremia following medico-surgical procedures. In this context, where the use of antibiotics for the prophylaxis of IE is limited, we showed that other prophylactic measures, like the use of antiplatelets, anticoagulants, or vaccination employing L. lactis as delivery vector of bacterial antigens, are reasonable alternatives that warrant to be further investigated.

Large-system analysis of a CDMA dynamic channel under a Markovian input process

We study the minimum mean square error (MMSE) and the multiuser efficiency η of large dynamic multiple access communication systems in which optimal multiuser detection is performed at the receiver as the number and the identities of active users is allowed to change at each transmission time. The system dynamics are ruled by a Markov model describing the evolution of the channel occupancy and a large-system analysis is performed when the number of observations grow large. Starting on the equivalent scalar channel and the fixed-point equation tying multiuser efficiency and MMSE, we extend it to the case of a dynamic channel, and derive lower and upper bounds for the MMSE (and, thus, for η as well) holding true in the limit of large signal–to–noise ratios and increasingly large observation time T.

Impacts of increased levels of wind penetration on the Electric Power System of the Åland Islands

The application of VSC-HVDC technology throughout the world has turned out to be an efficient solution regarding a large share of wind power in different power systems. This technology enhances the overall reliability of the grid by utilization of the active and reactive power control schemes which allows to maintain frequency and voltage on busbars of the end-consumers at the required level stated by the network operator. This master’s thesis is focused on the existing and planned wind farms as well as electric power system of the Åland Islands. The goal is to analyze the wind conditions of the islands and appropriately predict a possible production of the existing and planned wind farms with a help of WAsP software program. Further, to investigate the influence of increased wind power it is necessary to develop a simulation model of the electric grid and VSC-HVDC system in PSCAD and examine grid response to different wind power production cases with respect to the grid code requirements and ensure the stability of the power system.

Reinforcement Learning Approaches to Power System Scheduling

One major component of power system operation is generation scheduling. The objective of the work is to develop efficient control strategies to the power scheduling problems through Reinforcement Learning approaches. The three important active power scheduling problems are Unit Commitment, Economic Dispatch and Automatic Generation Control. Numerical solution methods proposed for solution of power scheduling are insufficient in handling large and complex systems. Soft Computing methods like Simulated Annealing, Evolutionary Programming etc., are efficient in handling complex cost functions, but find limitation in handling stochastic data existing in a practical system. Also the learning steps are to be repeated for each load demand which increases the computation time.Reinforcement Learning (RL) is a method of learning through interactions with environment. The main advantage of this approach is it does not require a precise mathematical formulation. It can learn either by interacting with the environment or interacting with a simulation model. Several optimization and control problems have been solved through Reinforcement Learning approach. The application of Reinforcement Learning in the field of Power system has been a few. The objective is to introduce and extend Reinforcement Learning approaches for the active power scheduling problems in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning approach for Economic Dispatch. (iii) Extend the Reinforcement Learning solution to Automatic Generation Control with a different perspective. (iv) Check the suitability of the scheduling solutions to one of the existing power systems.First part of the thesis is concerned with the Reinforcement Learning approach to Unit Commitment problem. Unit Commitment Problem is formulated as a multi stage decision process. Q learning solution is developed to obtain the optimwn commitment schedule. Method of state aggregation is used to formulate an efficient solution considering the minimwn up time I down time constraints. The performance of the algorithms are evaluated for different systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch problem. A simple and straight forward decision making strategy is first proposed in the Learning Automata algorithm. Then to solve the scheduling task of systems with large number of generating units, the problem is formulated as a multi stage decision making task. The solution obtained is extended in order to incorporate the transmission losses in the system. To make the Reinforcement Learning solution more efficient and to handle continuous state space, a fimction approximation strategy is proposed. The performance of the developed algorithms are tested for several standard test cases. Proposed method is compared with other recent methods like Partition Approach Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic Generation Control loop. The RL solution is extended to take up the approach of common frequency for all the interconnected areas, more similar to practical systems. Performance of the RL controller is also compared with that of the conventional integral controller.In order to prove the suitability of the proposed methods to practical systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for case study. The perfonnance of the Reinforcement Learning solution is found to be better than the other existing methods, which provide the promising step towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in the power industry and found to give satisfactory perfonnance. Proposed solution provides a scope for getting more profit as the economic schedule is obtained instantaneously. Since Reinforcement Learning method can take the stochastic cost data obtained time to time from a plant, it gives an implementable method. As a further step, with suitable methods to interface with on line data, economic scheduling can be achieved instantaneously in a generation control center. Also power scheduling of systems with different sources such as hydro, thermal etc. can be looked into and Reinforcement Learning solutions can be achieved.

Short-Term Load Forecast Of A Low Loadfactor Power System For Optimization Of Merit Order Dispatch Using Adaptive Learning Algorithm

Short term load forecasting is one of the key inputs to optimize the management of power system. Almost 60-65% of revenue expenditure of a distribution company is against power purchase. Cost of power depends on source of power. Hence any optimization strategy involves optimization in scheduling power from various sources. As the scheduling involves many technical and commercial considerations and constraints, the efficiency in scheduling depends on the accuracy of load forecast. Load forecasting is a topic much visited in research world and a number of papers using different techniques are already presented. The accuracy of forecast for the purpose of merit order dispatch decisions depends on the extent of the permissible variation in generation limits. For a system with low load factor, the peak and the off peak trough are prominent and the forecast should be able to identify these points to more accuracy rather than minimizing the error in the energy content. In this paper an attempt is made to apply Artificial Neural Network (ANN) with supervised learning based approach to make short term load forecasting for a power system with comparatively low load factor. Such power systems are usual in tropical areas with concentrated rainy season for a considerable period of the year

Hybrid Power System Modelling - Simulation and Energy Management Unit Development

Weltweit leben mehr als 2 Milliarden Menschen in ländlichen Gebieten. Als Konzept für die elektrische Energieversorgung solcher Gebiete kommen dezentrale elektrische Energieversorgungseinheiten zum Einsatz, die lokal verfügbare erneuerbare Ressourcen nutzen. Stand der Technik bilden Einheiten, die auf PV-Diesel-Batterie System basieren. Die verwendeten Versorgungsskonzepte in Hybridsystemen sind durch den Einsatz von Batterien als Energiespeicher meist wenig zuverlässig und teuer. Diese Energiespeicher sind sehr aufwendig zu überwachen und schwerig zu entsorgen. Den Schwerpunkt dieser Arbeit bildet die Entwicklung eines neuen Hybridsystems mit einem Wasserreservoir als Energiespeicher. Dieses Konzept eignet sich für Bergregionen in Entwicklungsländern wie Nepal, wo z.B. neben der solaren Strahlung kleine Flüsse in großer Anzahl vorhanden sind. Das Hybridsystem verfügt über einen Synchrongenerator, der die Netzgrößen Frequenz und Spannung vorgibt und zusätzlich unterstützen PV und Windkraftanlage die Versorgung. Die Wasserkraftanlage soll den Anteil der erneuerbaren Energienutzung erhöhen. Die Erweiterung des Systems um ein Dieselaggregat soll die Zuverlässigkeit der Versorgung erhöhen. Das Hybridsystem inkl. der Batterien wird modelliert und simuliert. Anschließend werden die Simulations- und Messergebnisse verglichen, um eine Validierung des Modells zu erreichen. Die Regelungsstruktur ist aufgrund der hohen Anzahl an Systemen und Parametern sehr komplex. Sie wird mit dem Simulationstool Matlab/Simulink nachgebildet. Das Verhalten des Gesamtsystems wird unter verschiedene Lasten und unterschiedlichen meteorologischen Gegebenheiten untersucht. Ein weiterer Schwerpunkt dieser Arbeit ist die Entwicklung einer modularen Energiemanagementeinheit, die auf Basis der erneuerbaren Energieversorgung aufgebaut wird. Dabei stellt die Netzfrequenz eine wichtige Eingangsgröße für die Regelung dar. Sie gibt über die Wirkleistungsstatik die Leistungsänderung im Netz wider. Über diese Angabe und die meteorologischen Daten kann eine optimale wirtschaftliche Aufteilung der Energieversorgung berechnet und eine zuverlässige Versorgung gewährleistet werden. Abschließend wurde die entwickelte Energiemanagementeinheit hardwaretechnisch aufgebaut, sowie Sensoren, Anzeige- und Eingabeeinheit in die Hardware integriert. Die Algorithmen werden in einer höheren Programmiersprache umgesetzt. Die Simulationen unter verschiedenen meteorologischen und netztechnischen Gegebenheiten mit dem entwickelten Model eines Hybridsystems für die elektrische Energieversorgung haben gezeigt, dass das verwendete Konzept mit einem Wasserreservoir als Energiespeicher ökologisch und ökonomisch eine geeignete Lösung für Entwicklungsländer sein kann. Die hardwaretechnische Umsetzung des entwickelten Modells einer Energiemanagementeinheit hat seine sichere Funktion bei der praktischen Anwendung in einem Hybridsystem bestätigen können.

Identifying barriers and opportunities for transitions towards more sustainable agriculture through system analysis: the case of Vereda La Hoya, Colombia

The paper presents the results of studies which investigated farmers’ reasoning and behaviour with regards to the mis‐use of personal protective equipment and pesticide among smallholders in Colombia. First, the research approach is described. In particular, the structured mental models approach and the integrative agent‐centred framework are presented. These approaches permit to understand the farmers’ reasoning and behaviour in a system perspective. Second, the results are summarized. The methods adopted allowed not only for identifying the factors, but also the social dynamics influencing farmers. Finally, suggestions for interventions are provided, which are not limited to a technical fix, but address the underlying social causes of the problem.

Implications of the North Atlantic Oscillation for a UK–Norway renewable power system

UK wind-power capacity is increasing and new transmission links are proposed with Norway, where hydropower dominates the electricity mix. Weather affects both these renewable resources and the demand for electricity. The dominant large-scale pattern of Euro-Atlantic atmospheric variability is the North Atlantic Oscillation (NAO), associated with positive correlations in wind, temperature and precipitation over northern Europe. The NAO's effect on wind-power and demand in the UK and Norway is examined, focussing on March when Norwegian hydropower reserves are low and the combined power system might be most susceptible to atmospheric variations. The NCEP/NCAR meteorological reanalysis dataset (1948–2010) is used to drive simple models for demand and wind-power, and ‘demand-net-wind’ (DNW) is estimated for positive, neutral and negative NAO states. Cold, calm conditions in NAO− cause increased demand and decreased wind-power compared to other NAO states. Under a 2020 wind-power capacity scenario, the increase in DNW in NAO− relative to NAO neutral is equivalent to nearly 25% of the present-day average rate of March Norwegian hydropower usage. As the NAO varies on long timescales (months to decades), and there is potentially some skill in monthly predictions, we argue that it is important to understand its impact on European power systems.

Increasing thermal plant flexibility in a high renewables power system

Thermal generation is a vital component of mature and reliable electricity markets. As the share of renewable electricity in such markets grows, so too do the challenges associated with its variability. Proposed solutions to these challenges typically focus on alternatives to primary generation, such as energy storage, demand side management, or increased interconnection. Less attention is given to the demands placed on conventional thermal generation or its potential for increased flexibility. However, for the foreseeable future, conventional plants will have to operate alongside new renewables and have an essential role in accommodating increasing supply-side variability. This paper explores the role that conventional generation has to play in managing variability through the sub-system case study of Northern Ireland, identifying the significance of specific plant characteristics for reliable system operation. Particular attention is given to the challenges of wind ramping and the need to avoid excessive wind curtailment. Potential for conflict is identified with the role for conventional plant in addressing these two challenges. Market specific strategies for using the existing fleet of generation to reduce the impact of renewable resource variability are proposed, and wider lessons from the approach taken are identified.

WIND POWER SUITABILITY ANALYSIS FOR THE GULF OF MAINE

http://digitalcommons.colby.edu/atlasofmaine2005/1022/thumbnail.jpg

Wind Power Suitability Analysis for the Gulf of Maine

This map shows one option for a viable energy source that is clean, free and endless: wind power. This map shows that the coast of Maine has the potential space and wind speed to be a location for wind farms. Four NOAA buoys placed in different locations along the Maine coast are the source of the wind speed data for this project. The average wind speed of every ten minutes of every day for the year 2004 were averaged so that each buoy was represented by one number of wind speed measured in meters/ second. The values in between these four buoys were estimated, or interpolated, using ArcGIS. Other factors that I took into consideration during this lab were distance from airports (no wind farm can be with in a three mile radius of an airport ) and distance from counties (no one wants an offshore wind farm that obstructs their view). I calculated the most appropriate locations for a wind farm in ArcGIS, by adding these three layers. The final output shows an area along Mt. Desert to be the most appropriate for development.

Power system transmission network expansion planning using AC model

An optimisation technique to solve transmission network expansion planning problem, using the AC model, is presented. This is a very complex mixed integer nonlinear programming problem. A constructive heuristic algorithm aimed at obtaining an excellent quality solution for this problem is presented. An interior point method is employed to solve nonlinear programming problems during the solution steps of the algorithm. Results of the tests, carried out with three electrical energy systems, show the capabilities of the method and also the viability of using the AC model to solve the problem.