Economic Feasibility of a Standalone Hybrid Power System for a Rural Destination in India

Demand of energy in isolated parts of India is solved by extension of grid power supply but it is not economical at all as cost varies depending upon distance,land and load demand.In view of this problem,supply of power to remote area demands advanced skill with updated technical and economical strategies.Because of that expensive and insufficient grid power in rural places have been replaced by renewable energy sources.So this particular work chooses the best hybrid technology for rural electric generation for a village area in Bhubaneswar. The solution obtained from using HOMER software presents the economic feasibility of the hybrid generation system for a rural conglomerate in Ghatikia, Bhubaneswar with latitude 20.26 0 N and longitude 85.76 0E.This paper contains four different type of Hybrid configuration. The optimization result obtained by using a hybrid con?guration composed of a wind energy system, a solar PV system and a diesel generator used as a backup system

Fuzzy Logic and ANFIS based Short Term Solar Energy Forecasting

Accurate forecasting of solar energy is a key issue for a meaningful integration of the solar power plants into the grid. Solar photovoltaic technology is most preferable and vital all other sources of renewable energy. We know that the solar Energy is very irregular so the result output of solar voltaic systems (SPV) diverted by the atmospheric nature like temperatures, humidity, wind velocity, solar irradiance and other climatologically facts. It�s necessary to prediction of solar energy is most important to minimise uncertainty in power harness from solar photovoltaic system. In this work fuzzy logic model and ANFIS model have been developed for manipulating solar irradiation (w/m2) data to forecasting short term solar energy. In the month of September 2017 has been monitoring for an hourly data of solar irradiance used as input and actual desired output. In the present paper sets the Normalization of input and desired output in between 0.1 to 0.9 for reducing confluence problems. Acquired results are match up to the manipulated data and get valid result. The implementation of the model is estimated on the basis of mean absolute percentage error

Reactive Power Compensation in a Stand-alone Wind-diesel-tidal Hybrid System by a Fuzzy Logic Based UPFC

AbstractThis paper gives a novel idea of application of fuzzy based UPFC controller for Reactive Power compensation in an isolated hybrid system and also discusses the improvement of stability in the hybrid system. For detailed analysis a small signal linear model of the hybrid wind- Diesel- tidal model is considered with different loading conditions. The reactive power compensation and stability analysis have been thoroughly analysed by a UPFC Controller. A fuzzy logic controller is designed to tune the parameters of UPFC controller. Simulation result shows that the system parameters attend steady state value with lesser time and complexities

A novel multi-attribute decision making approach for selection of appropriate product conforming ergonomic considerations

Ergonomic design of a product considers design, cognitive and behavioral information during the design stage with a view to improve the comfort level of the user and aesthetic look of the product. However, a large number of products are available in the market place possessing a wide range of features to address the ergonomic considerations. Many times, the features may be redundant and hardly enhance interaction between the user and the product leading to user dissatisfaction. But few important features focusing its functionality and physical comfort can possibly address the usability of product and improve satisfaction level of the user. This paper proposes a fuzzy multi-attribute decision making (MADM) approach integrating both subjective and objective weights for each criterion so that superior ergonomically designed product can be evaluated. The methodology is explained with the help of an example of selection of an office chair. Three popular approaches have been considered to compare the ranking of alternatives. Keywords: Multi-attribute decision making (MADM), TOPSIS (Techniques for Order Preference by Similarity to Identical Solution), VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenjea), PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluations

Reactive power control and optimisation of hybrid off shore tidal turbine with system uncertainties

This paper projects an isolated hybrid model of Offshore wind-diesel-tidal turbine and discusses the stability and reactive power management issue of the whole system. The hybrid system often loses its stability as it becomes prone to uncertain load and input parameters and therefore the necessity of Reactive power management becomes necessary. The overall stability of the hybrid offshore wind-diesel-tidal turbine is made possible by the management of reactive power in the hybrid system through the application of FACTS devices. And therefore the dynamic hybrid model of the DFIG and DDPMSG based offshore wind-diesel-tidal turbine is analysed for stability with different input parameters like wind and tidal energies. For detailed modelling and simulation, a small signal model of the whole hybrid system is designed and reactive power management of the system is achieved by the incorporation of a STATCOM controller. For improvement of stability and reactive power compensation of the hybrid system, GA and PSO optimised STATCOM controller is used

Prediction of recommendations for employment utilizing machine learning procedures and geo-area based recommender framework

With increment in the utilization of Internet, the pace of increment of social networks is getting ubiquitous in recent years. This paper focuses on the job portal websites. The research objective of this paper is that the recommender framework takes the abilities from the website and makes suggestion to the candidates with the jobs whose descriptions are coordinating with their profiles the most. This paper additionally presents a short presentation on recommender framework and talks about different categories of this framework. From the start, information is cleaned by expelling the filthy information as extra space and duplicates. Then the job recommendations are made to the target applicants on the basis of their preferences. It utilizes different Machine Learning procedures which results show that Random Forest Classifier (RFC) gives the most noteworthy expectation accuracy when contrasted with different procedures. Finally, the optimization technique is utilized to get the most exact outcome. The advantage of recommender framework in career orientation is expressed. Geo-area based recommendation framework is utilized to find the organization's position which can assist the ideal applicants with reaching their destination. This examination shows that the utilization of job recommender system can assist with improving the recommendation of appropriate employment for work searchers