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 Total Quality Management System in Seafood (Freezing) Industry in Kerala

Quality related problems have become dominant in the seafood processing industry in Kerala. This has resulted in the rejection of seafood sent from India to many destinations. The latest being the total block listing of seafood companies from India from being exported to Europe and partial block listing by the US. The quality systems prevailed in the seafood industry in India were outdated and no longer in use in the developed world. According to EC Directive discussed above all the seafood factories exporting to European countries have to adopt HACCP. Based on this, EIA has now made HACCP system mandatory in all the seafood processing factories in India. This transformation from a traditional product based inspection system to a process control system requires thorough changes in the various stages of production and quality management. This study is conducted by the author with to study the status of the existing infrastructure and quality control system in the seafood industry in Kerala with reference to the recent developments in the quality concepts in international markets and study the drawbacks, if any, of the existing quality management systems in force in the seafood factories in Kerala for introducing the mandatory HACCP concept. To assess the possibilities of introducing Total Quality Management system in the seafood industry in Kerala in order to effectively adopt the HACCP concept. This is also aimed at improving the quality of the products and productivity of the industry by sustaining the world markets in the long run.

Cost accountancy and cost control in hospitals

It is a fact that there now exists a sound framework of accounting theory to ascertain the working results and the investment status of hospitals. Yet, there is no system of accounting in practice to conduct its activities with utmost efficiency. No attempts have hitherto been made for the continuous improvement in the servics rendered by hospitals. Personal investments in hospitals have made the interaction of business to some extent.Planning, decision making and control assume increasing importance as hospitals grow in size and complexity. Moreover, wise and effective utilisation of resources should be ensured. The importance of cost cannot be overlooked in this context. Cost is the most effective factor in the determination of the prices of hospital services rendered. The important managerial functions have to rely heavily on accurate and timely cost information. More people can be provided with services if no services cost more than what is a must to provide the necessary level of care. The price paid for high cost technology for a few is no technology at all for the many. Hence no pains must be spared in ascertaining, presenting, controlling and reducing costs. An effective system of Cost Accountancy and Cost Control is imperative for the survival of hospitals in the intensely competitive conditions of today. The valuable objective of "better patient care" can be attained only if the management can make use of the various tools and techniques to ascertain, control and reduce each item of cost in hospitals. Constant efforts must be made by the management to continuously improve their services and bring down costs and prices of all hospital services. Cost Accountancy has made its impresssive impact on almost all the spheres of human activities. It is high time a comprehensive Cost Accountancy and Cost Control system be implemented in hospitals. The problem under study thus is the designing of a sound and full-fledged Cost Accountancy and Cost Control system that suits the requirements of hospitals. It is for the first time in India during the evolution of Cost Accountancy that a comprehensive cost system is tried in hospitals.

Materials management in state transport undertakings in india with special reference to kerala state road transport corporation

Scientific studies on the materials management systems and practices actually followed in various organizations in India are rather limited. This is particularly true with respect to service industries. In this context ,the present study on the “materials management in state transport undertakings in India, with special reference to kerala state road corporation” assumes particular significance . This study, examines critically, the prevailing set up, procedures and practices of materials management in the Kerala state road transport corporation and compares them with the prevailing practices in other similar state transport undertakings. It indicates several areas for improvement with respect to the organization, materials planning, purchasing, store keeping and other aspects. It also seeks to develop a comprehensive inventory control system for KSRTC.