Jasmin, E A; Dr. Jagathy Raj, V P(Cochin University of Science and Technology, December , 2008)
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Abstract:
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.
Description:
School of Engineering,
Cochin University of Science and Technology
Chiranjivi Jayaram, Ch V; Dr. Balchand, A N(Cochin University of Science & Technology, May , 2011)
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Abstract:
In this thesis, a variety of available satellite data products have been made use of
to bring out a synergistic analysis on the upwelling phenomenon in SEAS. Basic
concepts of remote sensing, upwelling and linked oceanography topics have been
dealt in this work .Auxiliary data products utilized in this study are described
in chapter 2. The climatological monthly variability of the upwelling signatures
are detailed under chapter 3. Chapter 4 presents the forcing factors that trigger
the upwelling process in SEAS. Chapter 5 describes the oceanic response to the
forcing factors with respect to the SST cooling and CHLA blooms. Chapter 6
presents the heat budget of the region and the variability of heat budget terms
with respect to upwelling. Chapter 7 describes the inter-annual variability of
upwelling intensity in SEAS and the influence of climatic events on upwelling.
Thara, K J; Dr. Sajeev, R(Cochin University of Science & Technology, July , 2011)
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Abstract:
The thesis attempts to study the changes in oceanographic parameters associated with extreme climatic events,the influence of oceanographic as well as meteorological parameters on fishes.The characteristics of major pelagic fishes of southwest coast of India(Oil sardine and Indian mackerel) have been described here.A description on study area and period of study is also described .The impact of extreme climatic events on the oceanographic variability of Eastern Arabian Sea.The extreme climatic event,the Indian Ocean Dipole associated with EI Nino Southern Oscillation is taken into consideration.The variability in oil sardine and mackerel landings of southwest coast of India during the study period.The trend analysis of the landings has been done and also a prediction model is applied for the landings.The influence of environmental parameters on oil sardine as well as mackerel fishery has been explained .With regression analysis ,the significant relation between environmental parameters and fish landings are also been recognized.The prediction of landings is done with these environmental parameters.
Description:
Dept.of Physical Oceanography,Cochin University of Science and Technology
Varghese,Joshua C; Krishnamoorthy,A(Department of Mathematics, 2003)
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Abstract:
Queueing system in which arriving customers who find all servers and waiting positions (if any) occupied many retry for service after a period of time are retrial queues or queues with repeated attempts. This study deals with two objectives one is to introduce orbital search in retrial queueing models which allows to minimize the idle time of the server. If the holding costs and cost of using the search of customers will be introduced, the results we obtained can be used for the optimal tuning of the parameters of the search mechanism. The second one is to provide insight of the link between the corresponding retrial queue and the classical queue. At the end we observe that when the search probability Pj = 1 for all j, the model reduces to the classical queue and when Pj = 0 for all j, the model becomes the retrial queue. It discusses the performance evaluation of single-server retrial queue. It was determined by using Poisson process. Then it discuss the structure of the busy period and its analysis interms of Laplace transforms and also provides a direct method of evaluation for the first and second moments of the busy period. Then it discusses the M/ PH/1 retrial queue with disaster to the unit in service and orbital search, and a multi-server retrial queueing model (MAP/M/c) with search of customers from the orbit. MAP is convenient tool to model both renewal and non-renewal arrivals. Finally the present model deals with back and forth movement between classical queue and retrial queue. In this model when orbit size increases, retrial rate also correspondingly increases thereby reducing the idle time of the server between services
Asha, A S; Dr.Jayaraj, M K(Cochin University of Science & Technology, December , 2007)
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Abstract:
The main objective of this thesis work is to optimize the growth conditions for
obtaining crystalline and conducting Lao.5Sro.5Co03 (LSCO) and
Lao.5Sro.5Coo.5.5Nio.5O3 (LSCNO) thin films at low processing temperatures. The
films are prepared by radio frequency magnetron sputtering under various
deposition conditions. The thin films were used as electrodes for the fabrication
of ferroelectric capacitors using BaO.7SrO.3 Ti03 (BST) and PbZro.52 Tio.4803 (PZT).
The structural and transport properties of the La1_xSrxCo03 and Lao.5Sro.5Co1_xNix03
are also investigated. The characterization of the bulk and the thin films were
performed using different tools. A powder X-ray diffractometer was used to
analyze the crystalline nature of the material. The transport properties were
investigated by measuring the temperature dependence of resistivity using a four
probe technique. The magnetoresistance and thermoelectric power were also used to investigate the transport properties. Atomic force microscope was used
to study the surface morphology and thin film roughness. The ferroelectric
properties of the capacitors were investigated using RT66A ferroelectric tester.
Description:
Department of Physics,
Cochin University of Science and Technology
Neema,C P; Babu,C A(Department of Atmospheric Science, 2004)
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Abstract:
This study deals with the salient features of the north Indian ocean associated with the summer monsoon. The focus is given on the Arabian sea mini warm pool, which is a part of the Indian ocean. It primarily study the certain aspects of the atmosphere and ocean variability in the north Indian ocean. The attempt were made to understand various aspects of time –scale variability of major features occurring in the Indian summer monsoon. The result from the thesis can be utilized as an input for model studies for prediction of monsoon, understanding ocean dynamics, radar tracking and ranging etc.
Neema,C P; Babu,C A(COCHIN UNIVERSITY OF SCIENCE AND TECHNOLOGY, 2004)
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Abstract:
This study deals with the salient features of the north Indian ocean associated with the summer monsoon. The focus is given on the Arabian sea mini warm pool, which is a part of the Indian ocean. It primarily study the certain aspects of the atmosphere and ocean variability in the north Indian ocean. The attempt were made to understand various aspects of time –scale variability of major features occurring in the Indian summer monsoon. The result from the thesis can be utilized as an input for model studies for prediction of monsoon, understanding ocean dynamics, radar tracking and ranging etc.
Alex Paikada,Mathew; Sivasankara Pillai,V N(School of rural development and appropriate technology: CUSAT Environmental studies, 2005)
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Abstract:
The study conducted on the salinity intrusion and seasonal water quality variations in the tidal canals of cochin. The main objectives are, salinity intrusion profile, water quality variation of the surface water of the canals,hierarchical utility of the water bodies and to understand the non-conservative components in the water body. The parameters monitored werepH,temperature,alkalinity,conductivity,DO(dissolvedoxygen),COD(chemical oxygen demand),BOD(biochemical oxygen demand0,chloride, total hardness, calcium hardness, dissolved phosphate, nitrate, total iron, sulphate, turbidity, total coliform and SUVA at 254nm. The tidal canals of GCDA were found to be creeks extending to the interior, canals inter connecting parts of the estuary or canals with seasonally broken segments. Based on utility the canals could be classified as: canals heavely polluted and very saline,canals polluted by urban waste , canals having fresh water for most part of the year and not much polluted, fresh water bodies heavily polluted.
During the rainy months carbon fixation by plankton is nonexistent,and during the dry months Chitrapuzha becomes a sink of phosphate. The study indicated abiotic subrouts for dissolved phosphate and revealed the potential pitfalls in LOICZ modeling exercise on sewage ladentidal canals. It was also found that all canals except for the canals of West cochin and chittoorpuzha have fresh water for some part of the year. The water quality index in the durable fresh water stretches was found to be of below average category.