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.

Legal Control of Fishing Industry in Kerala

This work is a study on ‘Legal Control of Fishing Industry in Kerala.Fishery and Fishery-related legislations are sought to be examined in the light of scientific opinion and judicial decisionsThis work is divided into five Part.The thrust of time Study is on the success of legislative measures in attempting to achieve socio-economic justice for the fishermen community.Fishing is more an avocation than an industry. It is basically the avocation of the artisanal or traditional fishermen who depend on it for their livelihood. As an ‘industry’, it is a generator of employment, income and wealth.The modern tendency in national legislations is to integrate legal proivisions relating to EEZ fisheries into the general fisheries legislation.Chartered fishing was introduced by the Central Government during 1977-78 to establish the abundance and distribution of fishery resources in Indian EEZ, for transfer of technology and for related purposes.Going by the provisions of Articles 61 and 62 of the U.N. Convention on the Law of the Sea, 1982, foreign fishing need be permitted in our EEZ area only if there is any surplus left after meeting our national requirements.Conservation of the renewable fishery resources should start with identification of the species, their habitats, feeding and breeding patterns, their classification and characteristics. Fishing patterns and their impact on different species and areas require to be examined and investigated.the Central Government, that the Kerala Marine Fishing Regulation Act, 1980 was passed.our traditional fishermen that our Governments in power in Kerala resorted to the appointment of Commissions after Commissions to enquire into the problems of resource management and conservation of the resources. The implementation of the recommendations of these Commissions is the need of the times.General infrastructure has increased to a certain extent in the fishery villages; but it is more the result of the development efforts of the State rather than due to increase in earnings from fishing. Fisherwomen ar e still unable to enjoy the status and role expected of them in the society and the family.Around 120 million people around the tuorld are economically dependent on fisheries. In developing countries like India, small-scale fishers are also the primary suppliers of fish, particularly for local consumption. A most important role of the fisheries sector is as a source of domestically produced food. Fish, as a food item, is a nutrient and it has great medicinal value.Consumers in our country face a dramatic rise in fish prices as our ‘fishing industry’ is linked with lucrative markets in industrial countries. Autonomy of States should be attempted to be maintained to the extent possible with the help and co-operation of the Centre. Regional co-operation of the coastal states interse and with the Centre should be attempted to be achieved under the leadership of the Centre in matters of regional concern. At time national level, a ifisheries management policy and plan should be framed in conformity with the national economic policies and plans as also keeping pace with the local and regional needs and priorities. Any such policy, plan and legislation should strive to achieve sustainability of the resources as well as support to the subsistence sector.

Social Media- A relevant tool for tourism and hospitality marketing

Tourism is an industry which is heavily dependent on marketing. Mouth to mouth communication has played a major role in shaping a number of destinations.This is particularly true in modern parlance.This is social networking phenomenon which is fast spreading over the internet .Many sites provide visitors a lot of freedom to express their views.Promotion of a destination depends lot on conversation and exchange of information over these social networks.This paper analyses the social networking sites their contribution to marketing tourism and hoapitality .The negetive impacts phenomena are also discussed