Application of Renewable Energy System With Fuzzy Logic

Application of Renewable Energy System With Fuzzy Logic

Sweta Singh, Divya Zindani, Apurba Kumar Roy, Kaushik Kumar
Copyright: © 2019 |Pages: 26
DOI: 10.4018/978-1-5225-5709-8.ch013
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Abstract

There has been rapid surge in energy consumption owing to the industrialization and the growing population. There has been a shift from agrarian economy to the industrial economy. This transformation has led to increased energy consumption in tandem with the emissions associated with it. Thus, the energy consumption has led to environmental concerns. Therefore, the planning and modeling of energy resources has become critical to economic growth and should be efficiently done for securing the health of the environment as well. Looking at the importance of modeling and planning, the present chapter is an attempt to explore the fuzzy based models used for the renewable systems and in particular the wind energy systems. It has been found that the fuzzy based models have been used extensively for installation of wind farms, for optimization of the parameters related to wind systems and for the site selection of the different wind energy farms.
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Fuzzy Logic Models For Energy Systems

Upcoming projects are based on renewable energy in most of the countries, which also providing employability and business opportunities. According to international energy agency IRENA the jobs opportunity in the area of renewable energy (solar and wind), increased by 5%. Electricity from renewable energy is argued to be irregular and is therefore not reliable. Given the environmental benefits of the renewable energy resources it is required to educate the consumers on using the non-polluting energy sources and also legislations regarding the same must be bought up by the government. For improving the reliability and making them more environment friendly energy from home spun commercial, if an energy model is developed then it would be beneficial to leave in a healthy environment for coming generations. Fuzzy logic builds a set of user-supplied rules for human, these rules combine and form mathematical equivalent model for proper solution.

It simplifies the job of the system designer and the computer, and it handles problems with imprecise and incomplete data. Fuzziness of fuzzy logic is crisp quantifiable parameter which helps in conceptualizing the fuzziness. Thus, fuzzy logic model can be achieve as a supervisory control technique to handle various changes power supply and demand of power for planning to adopt effective energy with practical solution

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