Renewable energy is generated through the conversion process of energy sources whic h are abundant in the earth such as wind, sun, heat, rain, geothermal, hydro, ocean
As stated in Government Regulation No. 79 of 2014 on National Energy Policy (KEN), the New and Renewable Energy (NRE) mix target is at least 23% by 2025. Now the utilization of solar energy in Indonesia has only reached about 0.05% or 100 MW. Government compiles a roadmap for the use of solar energy that targets the installed PV mini-grid capacity until 2025 is 6.5 GW. Technically, before installing a solar power plant, solar potential data is needed for a certain period of time. This is absolutely necessary considering the potential for solar is intermittent. The solar data are then processed to create a model forecasting so that it can optimize the resulting energy output. Forecasting using artificial intelligence with artificial neural network algorithms is a good solution because it has higher accuracy. To see the comparison of the performance of the ANN of this research with previous research. The finding shows that Baron 1-7-1 performed better than 2P 1-2-1 and Baron 1-2-1, regardless that the RMSE have a slight difference but still Baron 1-7-1 outperformed the others, with the best value of RMSE 0.15185 and R2 of 0.88996.
The southern coast of Yogyakarta province in Indonesia has large potential for wave energy, where the most ideal location is Pantai Baron. This research was conducted to study the potential wave energy using OWC (Oscillating Water Column) at Pantai Baron. Wave height and wave periods are needed to find the potential wave energy that can be generated. Wind, fetch and bathymetry data will be used to determine wave height in deep sea. Refraction and shoaling calculation will be used to calculate wave height in shallow depth area. Wave height after refraction-shoaling combine with tidal data will be used to determine optimum position for OWC system. Wave height, wave incoming direction, total efficiency for OWC system and capacity factor will be used to calculate potential wave energy that can be produced. Average wave height on deep sea is 1.08 m, wave period is 9.73 sec and incoming wave dominant is from east. Optimum depth of system OWC is -5.0 m below MSL. Average wave height after refraction and shoaling effect is 1.1 – 1.2 m. Potential wave energy that can be generated is 3.9 – 5.6 MWh per year per 1 OWC system with chamber width is 2.4 m.
The depletion of non-renewable energy reserves and increased awareness of environmental damage caused by fossil-based fuel use have encouraged the world's efforts to develop and utilize new and renewable energy sources, including in Indonesia, especially in the special region of Yogyakarta. The potential for wind power plants can be developed in 3 districts in the southern part of Yogyakarta, bordering the Java Sea, to be converted into hydrogen through an electrolysis process. The three research locations were Bugel Beach in Kulon Progo, Pandansimo Baru Beach in Bantul, and Baron Techno Park at Baron Beach in Gunung Kidul. The selection of the most optimum location was made employing the Analytic Hierarchy Process (AHP) method by considering three factors, namely technical, location, and socio-economic factors.The first factor includes the potential for electricity generation from wind power and the available land area. The second one consists of sub-factors, namely access to the location and the distance to the PLN electricity distribution line. Then the last one includes conflicts with tourism and the economic activities of the surrounding community. After obtaining the most suitable location, planning is carried out for the wind farm that is built, the amount of electrical energy produced, the cost of generating electricity, and the cost of producing hydrogen from the electrolysis process. Pandansimo Baru Beach is an ideal location, with an average wind speed of 4.833 m/s. Five Vestas V80 2000/80 wind turbines were selected according to the available land. The annual electrical energy that can be produced from this system is 161,677,216 kWh/year with a generation cost of 0.118 USD/kWh and is capable of producing 230,960 kgH2 of hydrogen at 4.35 USD/kg.
This paper presents the analysis of wind data at KST Baron Techno Park in the form of a wind rose diagram. Wind data analyzed in the 2019 period. The wind data is very important for evaluating wind potential, namely, the production of electricity from wind sources. This is because, KST Baron Techno Park is still experiencing difficulties in obtaining long-term anemometric data and short-term data related to wind speed and wind direction. Even though this is very important for the optimization of the operation and maintenance of the Wind Power Plant (PLTB) which is part of the hybrid electricity system. This is to examine the characteristics of the wind that several times caused damage to the blade until it broke. Making wind rose diagrams using Microsoft Excel. From the analysis, it is known that the wind direction is dominated by the southeast (SE) with a wind speed of 1-4 m/s.
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