Manajemen Inovasi Mode Hybrid Menuju Sekolah Kejuruan Mandiri Energi
Authors
Muliadi Muliadi , Syamsul HadiDOI:
10.29303/jipp.v8i4.1875Published:
2023-11-30Issue:
Vol. 8 No. 4 (2023): NovemberKeywords:
Hybrid Method, Innovation Management, Renewable Energy.Articles
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Abstract
The issue of new and renewable energy sources in the future will increasingly have a very important role in meeting energy needs. The use of fossil fuels for conventional power plants over a long period of time will deplete petroleum resources. Renewable Energy (RE) is increasingly in demand worldwide due to environmental concerns. The new policy requires power grids to supply a certain percentage of their load with Renewable Energy Sources (RES). The aim of writing this article is to provide an innovative management model to accelerate towards energy independent schools based on renewable energy, hybrid wind and solar energy mode. The method used in this study is a qualitative approach with document study as a data source and descriptive analysis methods. This article discusses the management model in controlling the Hybrid system towards efficiency of system input and output. In addition, there is a discussion about the school community regarding energy sources and its application in schools in protecting the environment. This study found that the renewable energy management system model using a combination of HRES technology using Homer and GA, GA-based optimization is more cost-effective than Homer with a COE of at least 0.163 $/kWh and 0% unmet load. This GA based system has more PV penetration and less co2 emissions than Homer. HRES optimization is mostly achieved using artificial methods or commercial software, the artificial methods used are based on fuzzy. This study also recommends the Home PRO and Retscreen control systems as the most widely used commercial software in optimization and MPPT as the most widely used control method to ensure stability, protection and power balance of the system. This method is often used based on practical optimization, neural networks and fuzzy logic. Artificial methods are the most widely used methods in optimization because of their higher efficiency, good accuracy, and fast convergence. The disadvantage of this method is that it requires a complicated processing program. High efficiency and speed of classical methods, accuracy. The hybrid method uses the advantages of each method by maximizing performance and minimizing optimization processing time.
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Copyright (c) 2023 Muliadi Muliadi, Syamsul Hadi
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