DESAIN POWER MANAGEMENT HYBRID SYSTEM BERBASIS OPERATIONAL CONTROL SYSTEM UNTUK MEMENUHI LOAD DEMAND
| Main Author: | Perdana, Fachmy Faizal |
|---|---|
| Format: | Thesis NonPeerReviewed Book |
| Bahasa: | eng |
| Terbitan: |
, 2018
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| Subjects: | |
| Online Access: |
http://eprints.umm.ac.id/42941/1/PENDAHULUAN.pdf http://eprints.umm.ac.id/42941/2/BAB%20I.pdf http://eprints.umm.ac.id/42941/3/BAB%20II.pdf http://eprints.umm.ac.id/42941/4/BAB%20III.pdf http://eprints.umm.ac.id/42941/5/BAB%20IV.pdf http://eprints.umm.ac.id/42941/6/BAB%20V.pdf http://eprints.umm.ac.id/42941/7/LAMPIRAN.pdf http://eprints.umm.ac.id/42941/ |
Daftar Isi:
- Renewable energy is an energy of unlimited availability covering wind, sunshine and water which in its development can be used as a source of renewable power plant. This power plant has advantages such as low pollution, low operating costs and abundant resources, but also has disadvantages such as expensive generation costs, the difficulty of being raised because of renewable energy resources (RER) that are not constant. In this study, Power Management Hybrid system uses 3 power plants, Photovoltaic (PV), Wind Power, Micro Hydro Power Plant (PLTmH) and Battery as storage system. The focus of this research is to determine the activation of each plant using Artificial Neural Network (ANN) method so that load demand can be fulfilled. From this research can be concluded that ANN has target accuracy level of 80%. This happens because ANN always calculates the weight based on the dominant data (Behavior data), so that the target data that is not dominant will not be achieved. When interconnecting the entire plant, the ANN experienced a misreading due to the voltage drop in each generator that affected the ANN input. This system simulation uses Matllab / Simulink.