A Reinforcement Learning Algorithm to Economic Dispatch Considering Transmission Losses

Reinforcement Learning (RL) refers to a class of learning algorithms in which learning system learns which action to take in different situations by using a scalar evaluation received from the environment on performing an action. RL has been successfully applied to many multi stage decision making problem (MDP) where in each stage the learning systems decides which action has to be taken. Economic Dispatch (ED) problem is an important scheduling problem in power systems, which decides the amount of generation to be allocated to each generating unit so that the total cost of generation is minimized without violating system constraints. In this paper we formulate economic dispatch problem as a multi stage decision making problem. In this paper, we also develop RL based algorithm to solve the ED problem. The performance of our algorithm is compared with other recent methods. The main advantage of our method is it can learn the schedule for all possible demands simultaneously.

A Study of Coir Vyvasaya Co-Operative Societies in Kerala – Performance, Problems and Prospects

The present study was undertaken to evaluate the performance of Coir Vyavasaya Co-operative societies (CVCs) in Kerala. It was also intended to examine the extent of fulfillment of the objectives of Co-operativisation Scheme and the socio-economic betterment of worker members, Further the study was directed to find out the level of participation of members in the affairs of CVCs and to identify the major problems confronting the CVCs and the future prospects of the industry. The objectives of this study are to evaluate the performance of CVCs in Kerala with reference to the objectives of co-operativisation, socio-economic background of the worker members of the CVCs in the state, extent of members participation, major problems etc. Major findings of the study shows that 84% of CVCs surveyed were incurring losses, the long-term solvency position of the CVCS shows very pathetic situation, ration analysis shows and unhealthy state of affaires with respect to short-term solvency position and operating efficiency of all categories of CVS were found to be extremely poor. If CVCs are enabled to increase their quantity of production and there by the volume of business, their amount of loss can be reduced. If this is so, the societies can provide more days of employment to their work members, which will help them to earn more wages and thereby improve their economic and social conditions

Studies on the Effect of High Energy Ball Milling On the Structural, Electrical and Magnetic Properties of Some Normal Spinets in the Ultrafine Regime

The present work is an attempt to understand the characteristics of high energy ball milling on the structural, electrical and magnetic properties of some normal spinets in the ultra fine regime, Magnetism and magnetic materials have been a fascinating subject for the mankind ever since the discovery of lodestone. Since then, man has been applying this principle of magnetism to build devices for various applications. Magnetism can be classified broadly into five categories. They are diamagnetic, paramagnetic, ferromagnetic antiferromagnetic and ferrimagnetic. Of these, ferro and ferri magnetic materials assume great commercial importance due to their unique properties like appropriate magnetic characteristics, high resistivity and low eddy current losses. The emergence of nanoscience and nanotechnology during the last decade had its impact in the field of magnetism and magnetic materials too. Now, it is common knowledge that materials synthesized in the nanoregime exhibit novel and superlative properties with respect to their coarser sized counterparts in the micron regime. These studies reveal that dielectric properties can be varied appreciably by high-energy ball milling in nanosized zinc ferrites produced by coprecipitation method. A semi conducting behaviour was observed in these materials with the Oxygen vacancies acting as the main charge carrier for conduction, which was produced at the time of coprecipitation and milling. Thus through this study, it was possible to successfully investigate the finite size effects on the structural, electrical and magnetic properties of normal spinels in the ultra fine regime

Phase modulation of microwave signals using point contact Germanium signal diodes

A forward - biased point contact germanium signal diode placed inside a waveguide section along the E -vector is found to introduce significant phase shift of microwave signals . The usefulness of the arrangement as a phase modulator for microwave carriers is demonstrated. While there is a less significant amplitude modulation accompanying phase modulation , the insertion losses are found to be negligible. The observations can be explained on the basis of the capacitance variation of the barrier layer with forward current in the diode

Fabrication and Characterization of All-Fiber Components for Optical Access Networks

This Thesis deals with the fabrication and characterization of novel all-fiber components for access networks. All fiber components offer distinctive advantages due to low forward and backward losses, epoxy free optical path and high power handling. A novel fabrication method for monolithic 1x4 couplers, which are vital components in distributed passive optical networks, is realized. The fabrication method differs from conventional structures with a symmetric coupling profile and hence offers ultra wideband performance and easy process control. New structure for 1x4 couplers, by fusing five fibers is proposed to achieve high uniformity, which gives equivalent uniformity performance to 1x4 planar lightwave splitters, isolation in fused fiber WDM is improved with integration of long period gratings. Packaging techniques of fused couplers are analyzed for long term stability.

Studies on Some Aspects of Light Beam Propagation Through Certain Nonlinear Media

This thesis deals with the study of light beam propagation through different nonlinear media. Analytical and numerical methods are used to show the formation of solitonS in these media. Basic experiments have also been performed to show the formation of a self-written waveguide in a photopolymer. The variational method is used for the analytical analysis throughout the thesis. Numerical method based on the finite-difference forms of the original partial differential equation is used for the numerical analysis.In Chapter 2, we have studied two kinds of solitons, the (2 + 1) D spatial solitons and the (3 + l)D spatio-temporal solitons in a cubic-quintic medium in the presence of multiphoton ionization.In Chapter 3, we have studied the evolution of light beam through a different kind of nonlinear media, the photorcfractive polymer. We study modulational instability and beam propagation through a photorefractive polymer in the presence of absorption losses. The one dimensional beam propagation through the nonlinear medium is studied using variational and numerical methods. Stable soliton propagation is observed both analytically and numerically.Chapter 4 deals with the study of modulational instability in a photorefractive crystal in the presence of wave mixing effects. Modulational instability in a photorefractive medium is studied in the presence of two wave mixing. We then propose and derive a model for forward four wave mixing in the photorefractive medium and investigate the modulational instability induced by four wave mixing effects. By using the standard linear stability analysis the instability gain is obtained.Chapter 5 deals with the study of self-written waveguides. Besides the usual analytical analysis, basic experiments were done showing the formation of self-written waveguide in a photopolymer system. The formation of a directional coupler in a photopolymer system is studied theoretically in Chapter 6. We propose and study, using the variational approximation as well as numerical simulation, the evolution of a probe beam through a directional coupler formed in a photopolymer 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.

Development of Safety and Quality Management System in Shrimp Farming

Shrimp Aquaculture has provided tremendous opportunity for the economic and social upliftment of rural communities in the coastal areas of our country Over a hundred thousand farmers, of whom about 90% belong to the small and marginal category, are engaged in shrimp farming. Penaeus monodon is the most predominant cultured species in India which is mainly exported to highly sophisticated, quality and safety conscious world markets. Food safety has been of concem to humankind since the dawn of history and the concern about food safety resulted in the evolution of a cost effective, food safety assurance method, the Hazard Analysis Critical Control Point (HACCP). Considering the major contribution of cultured Penaeus monodon to the total shrimp production and the economic losses encountered due to disease outbreak and also because traditional methods of quality control and end point inspection cannot guarantee the safety of our cultured seafood products, it is essential that science based preventive approaches like HACCP and Pre requisite Programmes (PRP) be implemented in our shrimp farming operations. PRP is considered as a support system which provides a solid foundation for HACCP. The safety of postlarvae (PL) supplied for brackish water shrimp farming has also become an issue of concern over the past few years. The quality and safety of hatchery produced seeds have been deteriorating and disease outbreaks have become very common in hatcheries. It is in this context that the necessity for following strict quarantine measures with standards and code of practices becomes significant. Though there were a lot of hue and cry on the need for extending the focus of seafood safety assurance from processing and exporting to the pre-harvest and hatchery rearing phases, an experimental move in this direction has been rare or nil. An integrated management system only can assure the effective control of the quality, hygiene and safety related issues. This study therefore aims at designing a safety and quality management system model for implementation in shrimp farming and hatchery operations by linking the concepts of HACCP and PRP.

Thermal transport properties of selected ferroelectrics, mixed valance perovskites and dielectric ceramics using photopyroelectric technique

Photothermal spectroscopy is a group of high sensitivity methods used to measure optical absorption and thermal characteristics of a sample.The basis of photothermal spectroscopy is a photo-induced change in the thermal state of the sample.Light energy absorbed and not lost by subsequent emission results in sample heating.This heating results in a temperature change as well as changes in thermodynamic parameters of the sample which are related to temperature.Measurements of the temperature,pressure,or density changes that occur due to optical absorption are ultimately the basis for the photothermal spectroscopic methods.This is a more direct measure of optical absorption than optical transmission based spectroscopies.Sample heating is a direct consequence of optical absorption and so photothermal spectroscopy signals are directly dependent on light absorption.Scattering and reflection losses do not produce photothermal signals.Subsequently,photothermal spectroscopy more accurately measures optical absorption in scattering solutions,in solids,and at interfaces.This aspect makes it particularly attractive for application to surface and solid absorption studies,and studies in scattering media.

Studies on Chaos and Synchronization in ac-driven Josephson junctions

The main goal of this thesis is to study the dynamics of Josephson junction system in the presence of an external rf-biasing.A system of two chaotically synchronized Josephson junction is studied.The change in the dynamics of the system in the presence of at phase difference between the applied fields is considered. Control of chaos is very important from an application point of view. The role Of phase difference in controlling chaos is discussed.An array of three Josephson junctions iS studied for the effect of phase difference on chaos and synchronization and the argument is extended for a system of N Josephson junctions. In the presence of a phase difference between the external fields, the system exhibits periodic behavior with a definite phase relationship between all the three junctions.Itdeals with an array of three Josephson junctions with a time delay in the coupling term. It is observed that only the outer systems synchronize while the middle system remain uncorrelated with t-he other two. The effect of phase difference between the applied fields and time-delay on system dynamics and synchronization is also studied. We study the influence of an applied ac biasing on a serniannular Josephson junction. It is found the magnetic field along with the biasing induces creation and annihilation of fluxons in the junction. The I-V characteristics of the junction is studied by considering the surface loss term also in the model equation. The system is found to exhibit chaotic behavior in the presence of ac biasing.

Creation and Annihilation of Fluxons in ac‐driven Semi-annular Josephson Junction

A new geometry (semiannular) for Josephson junction has been proposed and theoretical studies have shown that the new geometry is useful for electronic applications [1, 2]. In this work we study the voltage‐current response of the junction with a periodic modulation. The fluxon experiences an oscillating potential in the presence of the ac‐bias which increases the depinning current value. We show that in a system with periodic boundary conditions, average progressive motion of fluxon commences after the amplitude of the ac drive exceeds a certain threshold value. The analytic studies are justified by simulating the equation using finite‐difference method. We observe creation and annihilation of fluxons in semiannular Josephson junction with an ac‐bias in the presence of an external magnetic field.

Statistical Machine Learning Techniques for the Prediction of Learning Disabilities in School-Age Children

Learning Disability (LD) is a general term that describes specific kinds of learning problems. It is a neurological condition that affects a child's brain and impairs his ability to carry out one or many specific tasks. The learning disabled children are neither slow nor mentally retarded. This disorder can make it problematic for a child to learn as quickly or in the same way as some child who isn't affected by a learning disability. An affected child can have normal or above average intelligence. They may have difficulty paying attention, with reading or letter recognition, or with mathematics. It does not mean that children who have learning disabilities are less intelligent. In fact, many children who have learning disabilities are more intelligent than an average child. Learning disabilities vary from child to child. One child with LD may not have the same kind of learning problems as another child with LD. There is no cure for learning disabilities and they are life-long. However, children with LD can be high achievers and can be taught ways to get around the learning disability. In this research work, data mining using machine learning techniques are used to analyze the symptoms of LD, establish interrelationships between them and evaluate the relative importance of these symptoms. To increase the diagnostic accuracy of learning disability prediction, a knowledge based tool based on statistical machine learning or data mining techniques, with high accuracy,according to the knowledge obtained from the clinical information, is proposed. The basic idea of the developed knowledge based tool is to increase the accuracy of the learning disability assessment and reduce the time used for the same. Different statistical machine learning techniques in data mining are used in the study. Identifying the important parameters of LD prediction using the data mining techniques, identifying the hidden relationship between the symptoms of LD and estimating the relative significance of each symptoms of LD are also the parts of the objectives of this research work. The developed tool has many advantages compared to the traditional methods of using check lists in determination of learning disabilities. For improving the performance of various classifiers, we developed some preprocessing methods for the LD prediction system. A new system based on fuzzy and rough set models are also developed for LD prediction. Here also the importance of pre-processing is studied. A Graphical User Interface (GUI) is designed for developing an integrated knowledge based tool for prediction of LD as well as its degree. The designed tool stores the details of the children in the student database and retrieves their LD report as and when required. The present study undoubtedly proves the effectiveness of the tool developed based on various machine learning techniques. It also identifies the important parameters of LD and accurately predicts the learning disability in school age children. This thesis makes several major contributions in technical, general and social areas. The results are found very beneficial to the parents, teachers and the institutions. They are able to diagnose the child’s problem at an early stage and can go for the proper treatments/counseling at the correct time so as to avoid the academic and social losses.

The impact of sterilisation on family relationships

The major objective of the researcher was to assess the gains or losses in relationship between spouses after sterilization of the wife. The second objective was to gauge the impact of sterilisation upon parent—child relationships. Factors that were responsible in motivating women to accept sterilization were subjected to enquiry with the conviction that the information would give insight into the inadequacies of the official Family Planning Programme, offering prospects for feasible and salutary changes. The report is arranged under six chapters. The first chapter, Introduction, has three parts. The global and natural dimension of the problem of population is considered in Part I; The Importance of the topic studied namely sterilisation is discussed in the second Part: and Part III explains the background and methodology %f the study. The second chapter is a description of tubecto~ mized women who were the respondents. Their personal and family data, economic, social, educational and demographic profilesform its contents. The direct and indirect influences that were-responsible to make women decide in favour of sterilization are dealt with in the Third chapter. The Fourth Chapter is an analysis of the interspouse relations pre and post—operatively and an assessment of gains and losses in the area subsequent to sterilisation. How children have benefitted physically and emotionally as a consequence of improved care/attention from parents post~operatively constitutes the analysis attempted in the Fifth chapter.

Modifications of secondary reflector antenna patterns due to shaped beams from flanged primary horn feeds

With the advent of satellite communication and radio astronomy, the need for large and efficient reflector antennas had triggered a widespread investigation in reflector feed design techniques. Major improvements sought are reduction in spill-over, cross polarization losses and the enhancement of aperture efficiency. The search for such a feed culminated in the corrugated horn. The main idea behind the present work is to use the H-plane sectoral horns fitted with,corrugated flanges as feeds of a paraboloid and see how the secondary pattern of the reflector antenna varies with different parameters of the feed. An offset paraboloid is used as the secondary reflector in order to avoid the adverse effect of aperture ‘blocking by the feed horn structure on the secondary radiation pattern. The measurements were repeated for three different H-plane sectoral horns with the same set of corrugated flanges at various X-band frequencies. The following parameters of the whole system are studied: (a) Beam shaping. (b) Gain. (c) Variation of VSWR and (d) Cross polarization

Corrugated flange technique for beam shaping of sectoral electromagnetic horn antennas

The need for improved feed systems for large reflector antennas employed in Radio Astronomy and Satellite tracking spurred the interest in horn antenna research in the 1960's. The major requirements were to reduce spill over, cross-polarisation losses,and to enhance the aperture efficiency to the order of about 75-8O%L The search for such a feed culminated in the corrugated horn. The corrugat1e 1 horn triggered widespread interest and enthusiasm, and a large amount of work(32’34’49’5O’52’53’58’65’75’79)has already been done on this type of antennas. The properties of corrugated surfaces has been investigated in detail. It was strongly felt that the flange technique and the use of corrugated surfaces could be merged together to obtain the advantages of both. This is the idea behind the present work. Corrugations are made on the surface of flange elements. The effect of various corrugation parameters are studied. By varying the flange parameters, a good amount of data is collected and analysed to ascertain the effects of corrugated flanges. The measurements are repeated at various frequencies, in the X— and S-bands. The following parameters of the system were studied: (a) beam shaping (b) gain (c) variation of V.S.U.R. (d) possibility of obtaining circularly polarised radiation from the flanged horn. A theoretical explanation to the effects of corrugated flanges is attempted on the basis of the line-source theory. Even though this theory utilises a simplified model for the calculation of radiation patterns, fairly good agreement between the computed pattern and experimental results are observed.