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.

Modeling and Mapping Golden-winged Warbler Abundance to Improve Regional Conservation Strategies

Conservation planning requires identifying pertinent habitat factors and locating geographic locations where land management may improve habitat conditions for high priority species. I derived habitat models and mapped predicted abundance for the Golden-winged Warbler (Vermivora chrysoptera), a species of high conservation concern, using bird counts, environmental variables, and hierarchical models applied at multiple spatial scales. My aim was to understand habitat associations at multiple spatial scales and create a predictive abundance map for purposes of conservation planning for the Golden-winged Warbler. My models indicated a substantial influence of landscape conditions, including strong positive associations with total forest composition within the landscape. However, many of the associations I observed were counter to reported associations at finer spatial extents; for instance, I found Golden-winged Warblers negatively associated with several measures of edge habitat. No single spatial scale dominated, indicating that this species is responding to factors at multiple spatial scales. I found Golden-winged Warbler abundance was negatively related with Blue-winged Warbler (Vermivora cyanoptera) abundance. I also observed a north-south spatial trend suggestive of a regional climate effect that was not previously noted for this species. The map of predicted abundance indicated a large area of concentrated abundance in west-central Wisconsin, with smaller areas of high abundance along the northern periphery of the Prairie Hardwood Transition. This map of predicted abundance compared favorably with independent evaluation data sets and can thus be used to inform regional planning efforts devoted to conserving this species.

Using phylogeny to investigate the origins of the Cape flora: the importance of taxonomic, gene and genome sampling strategies

Phylogenetic methods hold great promise for the reconstruction of the transition from precursor to modern flora and the identification of underlying factors which drive the process. The phylogenetic methods presently used to address the question of the origin of the Cape flora of South Africa are considered here. The sampling requirements of each of these methods, which include dating of diversifications using calibrated molecular trees, sister pair comparisons, lineage through time plots and biogeographical optimizations are reviewed. Sampling of genes, genomes and species are considered. Although increased higher-level studies and increased sampling are required for robust interpretation, it is clear that much progress is already made. It is argued that despite the remarkable richness of the flora, the Cape flora is a valuable model system to demonstrate the utility of phylogenetic methods in determining the history of a modern flora.

Using high-frequency water quality data to assess sampling strategies for the EU Water Framework Directive

The EU Water Framework Directive (WFD) requires that the ecological and chemical status of water bodies in Europe should be assessed, and action taken where possible to ensure that at least "good" quality is attained in each case by 2015. This paper is concerned with the accuracy and precision with which chemical status in rivers can be measured given certain sampling strategies, and how this can be improved. High-frequency (hourly) chemical data from four rivers in southern England were subsampled to simulate different sampling strategies for four parameters used for WFD classification: dissolved phosphorus, dissolved oxygen, pH and water temperature. These data sub-sets were then used to calculate the WFD classification for each site. Monthly sampling was less precise than weekly sampling, but the effect on WFD classification depended on the closeness of the range of concentrations to the class boundaries. In some cases, monthly sampling for a year could result in the same water body being assigned to three or four of the WFD classes with 95% confidence, due to random sampling effects, whereas with weekly sampling this was one or two classes for the same cases. In the most extreme case, the same water body could have been assigned to any of the five WFD quality classes. Weekly sampling considerably reduces the uncertainties compared to monthly sampling. The width of the weekly sampled confidence intervals was about 33% that of the monthly for P species and pH, about 50% for dissolved oxygen, and about 67% for water temperature. For water temperature, which is assessed as the 98th percentile in the UK, monthly sampling biases the mean downwards by about 1 °C compared to the true value, due to problems of assessing high percentiles with limited data. Low-frequency measurements will generally be unsuitable for assessing standards expressed as high percentiles. Confining sampling to the working week compared to all 7 days made little difference, but a modest improvement in precision could be obtained by sampling at the same time of day within a 3 h time window, and this is recommended. For parameters with a strong diel variation, such as dissolved oxygen, the value obtained, and thus possibly the WFD classification, can depend markedly on when in the cycle the sample was taken. Specifying this in the sampling regime would be a straightforward way to improve precision, but there needs to be agreement about how best to characterise risk in different types of river. These results suggest that in some cases it will be difficult to assign accurate WFD chemical classes or to detect likely trends using current sampling regimes, even for these largely groundwater-fed rivers. A more critical approach to sampling is needed to ensure that management actions are appropriate and supported by data.

The Role of Motivational Strategies in the Upper Elementary Classroom : A systematic literature review about teacher strategies that promote self-confidence, motivation and a conducive learning environment

The aim of this literature review is to investigate which strategies teachers use to motivate pupils to communicate orally in English. The literature review also investigates how these teacher strategies affect pupils. The methodology used for this investigation is a systematic literature review. Various databases have been used when searching for literature. Scientific articles and theses have been searched for. They have also been read and analyzed before they have become a part of this review. The results indicate that some teachers feel insecure when speaking English. Therefore Swedish is spoken in many language classrooms. Teachers speaking in front of the class is the traditional way of teaching, and it does not seem to be a strategy who influences pupils positively. If teachers speak the target language among pupils they often get more motivated and focused pupils who feel comfortable speaking English. Young pupils are fast learners. By exposing them to the English language in early ages they receive great opportunities to learn a foreign language and strengthen their self-confidence. Drama, songs and rhymes are preferable strategies to use when teaching young learners. What position teachers decide to take in the classroom is also a significant element when teaching foreign languages.

Xylella fastidiosa: An in vivo system to study possible survival strategies within citrus xylem vessels based on global gene expression analysis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Molecular engineering strategies to control photo-induced birefringence and surface-relief gratings on layer-by-layer films from an azopolymer

The interactions governing adsorption of layer-by-layer (LBL) films from an azopolymer, PS-119(R), and poly(allylamine hydrochloride) (PAH) have been controlled by modifying the pH of the solutions used to form the films. The thickness per bilayer was varied by one order of magnitude, from 10 to 240 A, as the pH changed from 4 to 10. Thick layers were formed at higher pHs because in this case the PAH is only partially charged adopting a loopy conformation. This change in molecular conformation caused the kinetics of isomerization and mass transport to be much slower than at lower pHs. The writing time defined as the time to achieve 50% of maximum birefringence dropped from 110 to 18 min for films prepared from solutions with pH 10 and pH 4, respectively. This decrease is probably due to the higher free volume for isomerization in the films prepared at lower pHs, in which PAH molecules are less coiled than at higher pHs. For the same reason, the rate of inscription of surface-relief gratings with an interference pattern of p-polarized light was also much slower at higher pHs. (C) 2003 Elsevier B.V. All rights reserved.

Strategies to reduce the number of variables and the combinatorial search space of the multistage transmission expansion planning problem

This paper proposes strategies to reduce the number of variables and the combinatorial search space of the multistage transmission expansion planning problem (TEP). The concept of the binary numeral system (BNS) is used to reduce the number of binary and continuous variables related to the candidate transmission lines and network constraints that are connected with them. The construction phase of greedy randomized adaptive search procedure (GRASP-CP) and additional constraints, obtained from power flow equilibrium in an electric power system are employed for more reduction in search space. The multistage TEP problem is modeled like a mixed binary linear programming problem and solved using a commercial solver with a low computational time. The results of one test system and two real systems are presented in order to show the efficiency of the proposed solution technique. © 1969-2012 IEEE.

Peritoneal response to abdominal surgery: the role of equine abdominal adhesions and current prophylactic strategies

Intra-abdominal adhesions constitute a significant clinical and surgical problem that can lead to complications such as pain and bowel occlusion or subocclusion. These adhesions are frustrating and potentially fatal, representing a major postoperative complication in abdominal surgery. It is estimated that 32% of horses undergoing laparotomy will present clinical symptoms due to adhesions, but the true prevalence is not known because a large proportion of animals with postoperative recurrent colics are medically treated or submitted to euthanasia without necropsy. Adhesions are highly cellular, vascularized, dynamic structures that are influenced by complex signaling mechanisms. Understanding their pathogenesis could assist in applying better therapeutic strategies and in developing more effective antiadhesion products. Currently, there are no definitive strategies that prevent adhesion formation, and it is difficult to interpret the results of existing studies due to nonstandardization of an induction model and evaluation of their severity. The best clinical results have been obtained from using minimally traumatic surgical techniques, anti-inflammatory agents, antimicrobials, anticoagulants, and mechanical separation of serosal surfaces by viscous intraperitoneal solutions or physical barriers. This paper aims to review adhesion formation pathogenesis, guide the understanding of major products and drugs used to inhibit adhesion formation, and address their effectiveness in the equine species.

Xylella fastidiosa: An in vivo system to study possible survival strategies within citrus xylem vessels based on global gene expression analysis

Xylella fastidiosa inhabits the plant xylem, a nutrient-poor environment, so that mechanisms to sense and respond to adverse environmental conditions are extremely important for bacterial survival in the plant host. Although the complete genome sequences of different Xylella strains have been determined, little is known about stress responses and gene regulation in these organisms. In this work, a DNA microarray was constructed containing 2,600 ORFs identified in the genome sequencing project of Xylella fastidiosa 9a5c strain, and used to check global gene expression differences in the bacteria when it is infecting a symptomatic and a tolerant citrus tree. Different patterns of expression were found in each variety, suggesting that bacteria are responding differentially according to each plant xylem environment. The global gene expression profile was determined and several genes related to bacterial survival in stressed conditions were found to be differentially expressed between varieties, suggesting the involvement of different strategies for adaptation to the environment. The expression pattern of some genes related to the heat shock response, toxin and detoxification processes, adaptation to atypical conditions, repair systems as well as some regulatory genes are discussed in this paper. DNA microarray proved to be a powerful technique for global transcriptome analyses. This is one of the first studies of Xylella fastidiosa gene expression in vivo which helped to increase insight into stress responses and possible bacterial survival mechanisms in the nutrient-poor environment of xylem vessels.

Dietary strategies to minimize the detrimental impact of weaning on gut morphology, physiology and microbiota of piglets

Weaning is a crucial period in the management of piglets. In modern piggeries economic interest make weaning age decrease more and more and the detrimental consequences of weaning have as much importance as earlier the weaning occurs. The risk of development of post-weaning diarrhea (PWD) in piglets is high and PWD is the cause of serious economic losses in pig herds. In the past the supplementation of the feed given after weaning with growth promoters antibiotics, in order to keep PWD under control, used to be a common practice, but their usage has been banned in EU since 2006. This measure led to the investigation of alternative suitable feed supplements that would be reasonably efficient in protecting and sustaining animal health and performance. Aim of this thesis was to evaluate the effect of some different alternatives to growth-promoters antibiotics on weaning piglets and to assess if some of them could be considered as valuables options to replace auxinic in animal feeding. The study is composed by four experimental trials. The first one aims to identify mechanisms involved in the auxinic effects of antibiotics in the diets; the following three evaluate the addition butyric acid, tryptophan, and nitrate as alternative to in-feed antimicrobials. Although some results are controversial, it appears from the data presented that the alternatives to in-feed antibiotics considered may exert positive effects on some zootechnical and health parameters on piglet in the post-weaning period. Anyway, the mechanism of action and the interaction with microbiota of such additives should be investigated inside out because many effects remains poorly understood.

Molecular strategies for genetic diversity analysis and development of markers linked to resistance traits in apple

The goal of many plant scientists’ research is to explain natural phenotypic variation in term of simple changes in DNA sequence. DNA-based molecular markers are extensively used for the construction of genome-wide molecular maps and to perform genetic analysis for simple and complex traits. The PhD thesis was divided into two main research lines according to the different approaches adopted. The first research line is to analyze the genetic diversity in an Italian apple germplasm collection for the identification of markers tightly linked to targeted genes by an association genetic method. This made it possible to identify synomym and homonym accessions and triploids. The fruit red skin color trait has been used to test the reliability of the genetic approaches in this species. The second line is related to the development of molecular markers closely linked to the Rvi13 and Rvi5 scab resistance genes, previously mapped on apple’s chromosome 10 and 17 respectively by using the traditional linkage mapping method. Both region have been fine-mapped with various type of markers that could be used for marker-assisted selection in future breeding programs and to isolate the two resistance genes.

Strategies to prevent neuronal damage in paediatric bacterial meningitis

PURPOSE OF REVIEW: The mortality of bacterial meningitis can reach 30%, and up to 50% of survivors suffer from persisting neurological deficits as a consequence of the disease. The incidence of neurological sequelae of bacterial meningitis has not improved over the last decade. Adjunctive therapeutic options are limited, and ongoing research into the pathophysiology of brain damage in bacterial meningitis aims at providing the scientific basis for future development of more efficient adjunctive options. RECENT FINDINGS: In a population with good access to health care, dexamethasone given before or at the time of initiation of antibiotic therapy acts beneficially in paediatric pneumococcal meningitis, but not in meningococcal meningitis. In experimental animal models, brain-derived neurotrophic factor protected against brain injury and improved hearing while melatonin, which has antioxidant properties among other effects, reduced neuronal death. Transgene technology can be used to provide new insights into the pathophysiology of the disease and to identify potential therapeutic targets. SUMMARY: Although dexamethasone improves outcome of bacterial meningitis under defined circumstances, the morbidity of bacterial meningitis still remains unacceptably high. Experimental models may help to identify new therapeutic strategies to further improve the neurological outcome in young children suffering from bacterial meningitis.

Strategies to increase the use and approval of gender-fair language

When masculine forms are used to refer to men and women, this causes male-biased cognitive representations and behavioral consequences, as numerous studies have shown. This effect can be avoided or reduced with the help of gender-fair language. In this talk, we will present different approaches that aim at influencing people’s use of and attitudes towards gender-fair language. Firstly, we tested the influence of gender-fair input on people’s own use of gender-fair language. Based on Irmen and Linner’s (2005) adaptation of the scenario mapping and focus approach (Sanford & Garrod, 1998), we found that after reading a text with gender-fair forms women produced more gender-fair forms than women who read gender-neutral texts or texts containing masculine generics. Men were not affected. Secondly, we examined reactions to arguments which followed the Elaboration Likelihood Model (Petty &Cacioppo, 1986). We assumed that strong pros and cons would be more effective than weak arguments or control statements. The results indicated that strong pros could convince some, but not all participants, suggesting a complex interplay of diverse factors in reaction to attempts at persuasion. The influence of people’s initial characteristics will be discussed. Currently, we are investigating how self-generated refutations, in addition to arguments, may influence initial attitudes. Based on the resistance appraisal hypothesis (Tormala, 2008), we assume that individuals are encouraged in their initial attitude if they manage to refute strong counter-arguments. The results of our studies will be discussed regarding their practical implications.

Strategies for reducing fumigant loss to the atmosphere

A model is developed to describe transport and loss of methyl bromide (MeBr) in soil following application as a soil fumigant. The model is used to investigate the effect of soil and management factors on MeBr volatilization. Factors studied include depth of injection, soil water content, presence or absence of tarp, depth to downward barrier, and irrigation after injection. Of these factors, the most important was irrigation after injection followed by covering with the tarp, which increased the diffusive resistance of the soil and prevented early loss of MeBr. The model offers an explanation for the apparently contradictory observations of earlier field studies of MeBr volatilization from soils under different conditions. The model was also used to calculate the concentration-time index for various management alternatives, showing that the irrigation application did not make the surface soil more difficult to fumigate, except at very early times. Therefore, irrigation shows promise for reducing fumigant loss while at the same time permitting control of target organisms during fumigation.