In recent years, with the advent of globalization, the world is witnessing a steep rise in its energy consumption. The world is transforming itself into an industrial and knowledge society from an agricultural one which in turn makes the growth, energy intensive resulting in emissions. Energy modeling and energy planning is vital for the future economic prosperity and environmental security. Soft computing techniques such as fuzzy logic, neural networks, genetic algorithms are being adopted in energy modeling to precisely map the energy systems. In this paper, an attempt has been made to review the applications of fuzzy logic based models in renewable energy systems namely solar, wind, bio-energy, micro-grid and hybrid applications. It is found that fuzzy based models are extensively used in recent years for site assessment, for installing of photovoltaic/wind farms, power point tracking in solar photovoltaic/wind, optimization among conflicting criteria. The review indicates that fuzzy based models provide realistic estimates.

Applications of fuzzy logic in renewable energy systems – A review

The aim of the paper is to provide a comprehensive critical review towards the solar water heating (SWH) technology in terms of its theory, application, market potential and research questions. The theoretical issues relating to the solar water heating technology were illustrated in terms of the working principle, classification and associated mathematical expressions. The existing SWH production and engineering application were introduced and its future market potential was also predicted. Furthermore, research questions relating to the SWH were analysed involving (1) whole structure and individual components layout, sizing and optimisation; (2) thermal performance simulation and prediction; (3) laboratory based measurement compared against the modelling prediction; (4) dynamic performance evaluation through real time and on-site measurement; (5) energy saving, economic and environmental performance assessment, and social acceptance analyses; and (6) dissemination, marketing and exploitation strategies. Finally, the opportunities for the further works on the SWH were identified. This study will help understand the current status of the economic and technical developments, identify the barriers remaining to the existing solar water heating systems, develop the potential research areas to improve the performance of the systems, establish the associated strategic plans related to the design and installation of the system and promote the solar thermal global market. The study will contribute to achieving the China and international targets for energy saving, renewable energy utilisation, as well as carbon emission reduction in building sector.

Solar water heating: From theory, application, marketing and research

The solar water heating system (SWHS) is one of the most common application of solar energy utilization system The usage of solar water heating system is not commonly employed throughout the globe, due to its high initial cost The advancement in SWHS will lead to be beneficial over conventional system over the long span of time The eco-friendly nature of such system promotes these systems to be used frequently in both domestic and industrial heating The investigators throughout the globe focusing on technical advancement as well as economic feasibility of SWHS The present study focused on to report such studies, which demonstrates the economic feasibility of SWHS in the long run The payback period of SWHS varies from one origin to other as it depends on numerous factors like price of fossil fuels, rate of subsidy, solar insolation etc Initially the paper reported the basic components of SWHS, and their advancements, further the global scenario of SWHS is discussed, followed by the studies reported on a techno economic analysis of SWHS, which shows that the economic feasibility is equally important as technical feasibility for its implementation The last section inculcates the recent studies on the technical advancement of SWHS and the future research trends of SWHS were discussed

A review on technical improvements, economic feasibility and world scenario of solar water heating system

Review of water-heating systems: General selection approach based on energy and environmental aspects

A review of modern advances in analyses and applications of single-phase natural circulation loop in nuclear thermal hydraulics

Fuzzy model representation of thermosyphon solar water heating system

In this paper, a mixed method of model order reduction for a continuous-time single-input single-output system is presented. The denominator of a reduced-order model (ROM) is obtained by clustering...

Model order reduction using Fuzzy C-Means clustering

This paper proposes a novel hybrid approach that combines factor division algorithm and fuzzy c-means clustering technique for reducing the model order of high-order linear time invariant system. T...

Model order reduction using factor division algorithm and fuzzy c-means clustering technique:

There is an increasing number of applications in high precision motion control systems in manufacturing, i.e., ultra-precision machining, assembly of small components and micro devices. It is very difficult to assure such accuracy due to many factors affecting the precision motion, such as frictions and disturbances in the drive system. The standard proportional-integral-derivative (PID) type servo control algorithms are not capable of delivering the desired precision under the influence of frictions and disturbances. In this paper neural network model reference adaptive controller (NNMRAC) is used to compensate the frictions and disturbances and the desired precision under the influence of frictions and disturbances is achieved. Therefore the proposed scheme can be applicable to a wide class of mechanical systems. The simulation results of single link robot arm with friction verify the effectiveness of the proposed scheme.

Friction compensation using neural networks applicable to high precision motion control systems in manufacturing

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Anirudha Narain

Papers

Fuzzy model representation of thermosyphon solar water heating system

Model order reduction using Fuzzy C-Means clustering

Model order reduction using factor division algorithm and fuzzy c-means clustering technique:

Friction compensation using neural networks applicable to high precision motion control systems in manufacturing

Model Order Reduction of Discrete-Time Systems Using Fuzzy C-Means Clustering