Cost Allocation Model for Distribution Networks Considering High Penetration of Distributed Energy Resources

The high penetration of distributed energy resources (DER) in distribution networks and the competitiveenvironment of electricity markets impose the use of new approaches in several domains. The networkcost allocation, traditionally used in transmission networks, should be adapted and used in the distribu-tion networks considering the specifications of the connected resources. The main goal is to develop afairer methodology trying to distribute the distribution network use costs to all players which are usingthe network in each period. In this paper, a model considering different type of costs (fixed, losses, andcongestion costs) is proposed comprising the use of a large set of DER, namely distributed generation(DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehi-cles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). Theproposed model includes three distinct phases of operation. The first phase of the model consists in aneconomic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen’s andBialek’s tracing algorithms are used and compared to evaluate the impact of each resource in the net-work. Finally, the MW-mile method is used in the third phase of the proposed model. A distributionnetwork of 33 buses with large penetration of DER is used to illustrate the application of the proposedmodel.

Cost allocation model for distribution networks considering high penetration of distributed energy resources

The high penetration of distributed energy resources (DER) in distribution networks and the competitive environment of electricity markets impose the use of new approaches in several domains. The network cost allocation, traditionally used in transmission networks, should be adapted and used in the distribution networks considering the specifications of the connected resources. The main goal is to develop a fairer methodology trying to distribute the distribution network use costs to all players which are using the network in each period. In this paper, a model considering different type of costs (fixed, losses, and congestion costs) is proposed comprising the use of a large set of DER, namely distributed generation (DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehicles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). The proposed model includes three distinct phases of operation. The first phase of the model consists in an economic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen's and Bialek's tracing algorithms are used and compared to evaluate the impact of each resource in the network. Finally, the MW-mile method is used in the third phase of the proposed model. A distribution network of 33 buses with large penetration of DER is used to illustrate the application of the proposed model.

Parametric portfolio policies: An application for a global tactical asset allocation model

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

Personal redistribution and the regional allocation of public investment

How should an equity-motivated policy-marker allocate public capital (infrastructure) across regions. Should it aim at reducing interregional differences in per capita output, or at maximizing total output? Such a normative question is examined in a model where the policy-marker is exclusively concerned about personal inequality and has access to two policy instruments. (i) a personal tax-transfer system (taxation is distortionary), and (ii) the regional allocation of public investment. I show that the case for public investment as a significant instrument for interpersonal redistribution is rather weak. In the most favorable case, when the tax code is constrained to be uniform across regions, it is optimal to distort the allocation of public investment in favor of the poor regions, but only to a limited extent. The reason is that poor individuals are relatively more sensitive to public trans fers, which are maximized by allocating public investment efficiently. If! the tax code can vary across regions then the optimal policy may involve an allocation of public investment distorted in favor of the rich regions.

Cardenolides in nectar may be more than a consequence of allocation to other plant parts: a phylogenetic study of Asclepias

The primary function of secondary plant metabolites is thought to be defence against herbivores. The frequent occurrence of these same noxious compounds in floral nectar, which functions primarily to attract pollinators, has been seen as paradoxical. Although these compounds may have an adaptive purpose in nectar, they may also occur as a nonadaptive consequence of chemical defence in other plant parts. If nectar chemistry reflects physiological constraints or passive leakage from other tissues, we expect that the identity and relative concentration of nectar cardenolides to be correlated with those of other plant parts; in contrast, discordant distributions of compounds in nectar and other tissues may suggest adaptive roles in nectar. We compared the concentrations and identities of cardenolides in the nectar, leaves and flowers of 12 species from a monophyletic clade of Asclepias. To measure putative toxicity of nectar cardenolides, we then examined the effects of a standard cardenolide (digoxin) on the behaviour of bumblebees, a common generalist pollinator of Asclepias. We found that the average cardenolide concentrations in nectar, leaves and flowers of the 12 Asclepias species were positively correlated as predicted by nonadaptive hypotheses. However, significant differences in the identities and concentrations of individual cardenolides between nectar and leaves suggest that the production or allocation of cardenolides may be independently regulated at each plant part. In addition, cardenolide concentrations in leaves and nectar exhibited no phylogenetic signal. Surprisingly, bumblebees did not demonstrate an aversion to digoxin-rich nectar, which may indicate that nectar cardenolides have little effect on pollination. Although the idea that discordant patterns of secondary metabolites across tissue types may signal adaptive functions is attractive, there is evidence to suggest constraint contributes to nectar secondary chemistry. Further work testing the ecological impacts of such patterns will be critical in determining the functional significance of nectar cardenolides

Stochastic optimal bid to electricity markets with environmental risk constraints

There are many factors that influence the day-ahead market bidding strategies of a generation company (GenCo) in the current energy market framework. Environmental policy issues have become more and more important for fossil-fuelled power plants and they have to be considered in their management, giving rise to emission limitations. This work allows to investigate the influence of both the allowances and emission reduction plan, and the incorporation of the derivatives medium-term commitments in the optimal generation bidding strategy to the day-ahead electricity market. Two different technologies have been considered: the coal thermal units, high-emission technology, and the combined cycle gas turbine units, low-emission technology. The Iberian Electricity Market and the Spanish National Emissions and Allocation Plans are the framework to deal with the environmental issues in the day-ahead market bidding strategies. To address emission limitations, some of the standard risk management methodologies developed for financial markets, such as Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR), have been extended. This study offers to electricity generation utilities a mathematical model to determinate the individual optimal generation bid to the wholesale electricity market, for each one of their generation units that maximizes the long-run profits of the utility abiding by the Iberian Electricity Market rules, the environmental restrictions set by the EU Emission Trading Scheme, as well as the restrictions set by the Spanish National Emissions Reduction Plan. The economic implications for a GenCo of including the environmental restrictions of these National Plans are analyzed and the most remarkable results will be presented.

On optimal learning schedules and the marginal value of cumulative cultural evolution.

The age-dependent choice between expressing individual learning (IL) or social learning (SL) affects cumulative cultural evolution. A learning schedule in which SL precedes IL is supportive of cumulative culture because the amount of nongenetically encoded adaptive information acquired by previous generations can be absorbed by an individual and augmented. Devoting time and energy to learning, however, reduces the resources available for other life-history components. Learning schedules and life history thus coevolve. Here, we analyze a model where individuals may have up to three distinct life stages: "infants" using IL or oblique SL, "juveniles" implementing IL or horizontal SL, and adults obtaining material resources with learned information. We study the dynamic allocation of IL and SL within life stages and how this coevolves with the length of the learning stages. Although no learning may be evolutionary stable, we find conditions where cumulative cultural evolution can be selected for. In that case, the evolutionary stable learning schedule causes individuals to use oblique SL during infancy and a mixture between IL and horizontal SL when juvenile. We also find that the selected pattern of oblique SL increases the amount of information in the population, but horizontal SL does not do so.

On Certain Greedoid Polyhedra, Partially Indexable Scheduling Problems, and Extended Restless Bandit Allocation Indices

We present a polyhedral framework for establishing general structural properties on optimal solutions of stochastic scheduling problems, where multiple job classes vie for service resources: the existence of an optimal priority policy in a given family, characterized by a greedoid (whose feasible class subsets may receive higher priority), where optimal priorities are determined by class-ranking indices, under restricted linear performance objectives (partial indexability). This framework extends that of Bertsimas and Niño-Mora (1996), which explained the optimality of priority-index policies under all linear objectives (general indexability). We show that, if performance measures satisfy partial conservation laws (with respect to the greedoid), which extend previous generalized conservation laws, then the problem admits a strong LP relaxation over a so-called extended greedoid polytope, which has strong structural and algorithmic properties. We present an adaptive-greedy algorithm (which extends Klimov's) taking as input the linear objective coefficients, which (1) determines whether the optimal LP solution is achievable by a policy in the given family; and (2) if so, computes a set of class-ranking indices that characterize optimal priority policies in the family. In the special case of project scheduling, we show that, under additional conditions, the optimal indices can be computed separately for each project (index decomposition). We further apply the framework to the important restless bandit model (two-action Markov decision chains), obtaining new index policies, that extend Whittle's (1988), and simple sufficient conditions for their validity. These results highlight the power of polyhedral methods (the so-called achievable region approach) in dynamic and stochastic optimization.

Money, Fame and the Allocation of Talent: Brain Drain, the Matthew Effect and the Institution of Science

The earning structure in science is known to be flat relative to the one in the private sector, which could cause a brain drain toward the private sector. In this paper, we assume that agents value both money and fame and study the role of the institution of science in the allocation of talent between the science sector and the private sector. Following works on the Sociology of Science, we model the institution of science as a mechanism distributing fame (i.e. peer recognition). We show that since the intrinsic performance is less noisy signal of talent in the science sector than in the private sector, a good institution of science can mitigate the brain drain. We also find that providing extra monetary incentives through the market might undermine the incentives provided by the institution and thereby worsen the brain drain. Finally, we study the optimal balance between monetary and non-monetary incentives in science.

On optimal monetary and fiscal policy interactions in open economies

This paper studies monetary and fiscal policy interactions in a two country model, where taxes on firms sales are optimally chosen and the monetary policy is set cooperatively.It turns out that in a two country setting non-cooperative fiscal policy makers have an incentive to change taxes on sales depending on shocks realizations in order to reduce output production. Therefore whether the fiscal policy is set cooperatively or not matters for optimal monetary policy decisions. Indeed, as already shown in the literature, the cooperative monetary policy maker implements the flexible price allocation only when special conditions on the value of the distortions underlying the economy are met. However, if non-cooperative fiscal policy makers set the taxes on firms sales depending on shocks realizations, these conditions cannot be satisfied; conversely, when fiscal policy is cooperative, these conditions are fulfilled. We conclude that whether implementing the flexible price allocation is optimal or not depends on the fiscal policy regime.

On certain greedoid polyhedra, partially indexable scheduling problems and extended restless bandit allocation indices

We present a polyhedral framework for establishing general structural properties on optimal solutions of stochastic scheduling problems, where multiple job classes vie for service resources: the existence of an optimal priority policy in a given family, characterized by a greedoid(whose feasible class subsets may receive higher priority), where optimal priorities are determined by class-ranking indices, under restricted linear performance objectives (partial indexability). This framework extends that of Bertsimas and Niño-Mora (1996), which explained the optimality of priority-index policies under all linear objectives (general indexability). We show that, if performance measures satisfy partial conservation laws (with respect to the greedoid), which extend previous generalized conservation laws, then theproblem admits a strong LP relaxation over a so-called extended greedoid polytope, which has strong structural and algorithmic properties. We present an adaptive-greedy algorithm (which extends Klimov's) taking as input the linear objective coefficients, which (1) determines whether the optimal LP solution is achievable by a policy in the given family; and (2) if so, computes a set of class-ranking indices that characterize optimal priority policies in the family. In the special case of project scheduling, we show that, under additional conditions, the optimal indices can be computed separately for each project (index decomposition). We further apply the framework to the important restless bandit model (two-action Markov decision chains), obtaining new index policies, that extend Whittle's (1988), and simple sufficient conditions for their validity. These results highlight the power of polyhedral methods (the so-called achievable region approach) in dynamic and stochastic optimization.

Money, fame and the allocation of talent: Brain drain and the institution of science

The earning structure in science is known to be flat relative to the one in theprivate sector, which could cause a brain drain toward the private sector. In thispaper, we assume that agents value both money and fame and study the role ofthe institution of science in the allocation of talent between the science sector andthe private sector. Following works on the Sociology of Science, we model theinstitution of science as a mechanism distributing fame (i.e. peer recognition). Weshow that since the intrinsic performance is less noisy signal of talent in the sciencesector than in the private sector, a good institution of science can mitigate thebrain drain. We also find that providing extra monetary incentives through themarket might undermine the incentives provided by the institution and therebyworsen the brain drain. Finally, we study the optimal balance between monetaryand non-monetary incentives in science.

Reproductive allocation and size constraints in the cladoceran Simocephalus vetulus (Müller)

Like many organisms, the cladoceran Simocephalus vetulus (Müller) continues to grow when reproducing, whereas the optimal strategy is to stop growing at maturity, and to invest all available production into reproduction thereafter. It has been proposed that a size constraint is responsible for the observed strategy (Perrin, Ruedi & Saiah, 1987), by preventing organisms from investing more than a given amount of energy into reproduction. This hypothesis is developed here and the two folowing prediction are derived: (1) the onset of reproduction should be independent of age and (2) the reproductive investement should be size-specific, thus independent of the productin rate. Both predictions are tested by rearing a clone of S.vetulus in a gradient of productivity. The results support the first prediction, but not the second one, so that the size-constraint hypothesis is disproved.

Blood pressure and LDL-cholesterol targets for prevention of recurrent strokes and cognitive decline in the hypertensive patient: design of the European Society of Hypertension-Chinese Hypertension League Stroke in Hypertension Optimal Treatment randomized trial.

BACKGROUND AND OBJECTIVES: The SBP values to be achieved by antihypertensive therapy in order to maximize reduction of cardiovascular outcomes are unknown; neither is it clear whether in patients with a previous cardiovascular event, the optimal values are lower than in the low-to-moderate risk hypertensive patients, or a more cautious blood pressure (BP) reduction should be obtained. Because of the uncertainty whether 'the lower the better' or the 'J-curve' hypothesis is correct, the European Society of Hypertension and the Chinese Hypertension League have promoted a randomized trial comparing antihypertensive treatment strategies aiming at three different SBP targets in hypertensive patients with a recent stroke or transient ischaemic attack. As the optimal level of low-density lipoprotein cholesterol (LDL-C) level is also unknown in these patients, LDL-C-lowering has been included in the design. PROTOCOL DESIGN: The European Society of Hypertension-Chinese Hypertension League Stroke in Hypertension Optimal Treatment trial is a prospective multinational, randomized trial with a 3 × 2 factorial design comparing: three different SBP targets (1, <145-135; 2, <135-125; 3, <125 mmHg); two different LDL-C targets (target A, 2.8-1.8; target B, <1.8 mmol/l). The trial is to be conducted on 7500 patients aged at least 65 years (2500 in Europe, 5000 in China) with hypertension and a stroke or transient ischaemic attack 1-6 months before randomization. Antihypertensive and statin treatments will be initiated or modified using suitable registered agents chosen by the investigators, in order to maintain patients within the randomized SBP and LDL-C windows. All patients will be followed up every 3 months for BP and every 6 months for LDL-C. Ambulatory BP will be measured yearly. OUTCOMES: Primary outcome is time to stroke (fatal and non-fatal). Important secondary outcomes are: time to first major cardiovascular event; cognitive decline (Montreal Cognitive Assessment) and dementia. All major outcomes will be adjudicated by committees blind to randomized allocation. A Data and Safety Monitoring Board has open access to data and can recommend trial interruption for safety. SAMPLE SIZE CALCULATION: It has been calculated that 925 patients would reach the primary outcome after a mean 4-year follow-up, and this should provide at least 80% power to detect a 25% stroke difference between SBP targets and a 20% difference between LDL-C targets.

Analyse de réseau piéton et gestion scolaire: sinuosité, centricité et transport optimal régularisé

Que ce soit d'un point de vue, urbanistique, social, ou encore de la gouvernance, l'évolution des villes est un défi majeur de nos sociétés contemporaines. En offrant la possibilité d'analyser des configurations spatiales et sociales existantes ou en tentant de simuler celles à venir, les systèmes d'information géographique sont devenus incontournables dans la gestion et dans la planification urbaine. En cinq ans la population de la ville de Lausanne est passée de 134'700 à 140'570 habitants, alors que les effectifs de l'école publique ont crû de 12'200 à 13'500 élèves. Cet accroissement démographique associé à un vaste processus d'harmonisation de la scolarité obligatoire en Suisse ont amené le Service des écoles à mettre en place et à développer en collaboration avec l'université de Lausanne des solutions SIG à même de répondre à différentes problématiques spatiales. Établies en 1989, les limites des établissements scolaires (bassins de recrutement) ont dû être redéfinies afin de les réadapter aux réalités d'un paysage urbain et politique en pleine mutation. Dans un contexte de mobilité et de durabilité, un système d'attribution de subventions pour les transports publics basé sur la distance domicile-école et sur l'âge des écoliers, a été conçu. La réalisation de ces projets a nécessité la construction de bases de données géographiques ainsi que l'élaboration de nouvelles méthodes d'analyses exposées dans ce travail. Cette thèse s'est ainsi faite selon une dialectique permanente entre recherches théoriques et nécessités pratiques. La première partie de ce travail porte sur l'analyse du réseau piéton de la ville. La morphologie du réseau est investiguée au travers d'approches multi-échelles du concept de centralité. La première conception, nommée sinuo-centralité ("straightness centrality"), stipule qu'être central c'est être relié aux autres en ligne droite. La deuxième, sans doute plus intuitive, est intitulée centricité ("closeness centrality") et exprime le fait qu'être central c'est être proche des autres (fig. 1, II). Les méthodes développées ont pour but d'évaluer la connectivité et la marchabilité du réseau, tout en suggérant de possibles améliorations (création de raccourcis piétons). Le troisième et dernier volet théorique expose et développe un algorithme de transport optimal régularisé. En minimisant la distance domicile-école et en respectant la taille des écoles, l'algorithme permet de réaliser des scénarios d'enclassement. L'implémentation des multiplicateurs de Lagrange offre une visualisation du "coût spatial" des infrastructures scolaires et des lieux de résidence des écoliers. La deuxième partie de cette thèse retrace les aspects principaux de trois projets réalisés dans le cadre de la gestion scolaire. À savoir : la conception d'un système d'attribution de subventions pour les transports publics, la redéfinition de la carte scolaire, ou encore la simulation des flux d'élèves se rendant à l'école à pied. *** May it be from an urbanistic, a social or from a governance point of view, the evolution of cities is a major challenge in our contemporary societies. By giving the opportunity to analyse spatial and social configurations or attempting to simulate future ones, geographic information systems cannot be overlooked in urban planning and management. In five years, the population of the city of Lausanne has grown from 134'700 to 140'570 inhabitants while the numbers in public schools have increased from 12'200 to 13'500 students. Associated to a considerable harmonisation process of compulsory schooling in Switzerland, this demographic rise has driven schooling services, in collaboration with the University of Lausanne, to set up and develop GIS capable of tackling various spatial issues. Established in 1989, the school districts had to be altered so that they might fit the reality of a continuously changing urban and political landscape. In a context of mobility and durability, an attribution system for public transport subventions based on the distance between residence and school and on the age of the students was designed. The implementation of these projects required the built of geographical databases as well as the elaboration of new analysis methods exposed in this thesis. The first part of this work focuses on the analysis of the city's pedestrian network. Its morphology is investigated through multi-scale approaches of the concept of centrality. The first conception, named the straightness centrality, stipulates that being central is being connected to the others in a straight line. The second, undoubtedly more intuitive, is called closeness centrality and expresses the fact that being central is being close to the others. The goal of the methods developed is to evaluate the connectivity and walkability of the network along with suggesting possible improvements (creation of pedestrian shortcuts).The third and final theoretical section exposes and develops an algorithm of regularised optimal transport. By minimising home to school distances and by respecting school capacity, the algorithm enables the production of student allocation scheme. The implementation of the Lagrange multipliers offers a visualisation of the spatial cost associated to the schooling infrastructures and to the student home locations. The second part of this thesis recounts the principal aspects of three projects fulfilled in the context of school management. It focuses namely on the built of an attribution system for public transport subventions, a school redistricting process and on simulating student pedestrian flows.