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Journal : International Journal of Electrical, Energy and Power System Engineering (IJEEPSE)

Study on the Potential of Waste in Pangkalpinang as Source of Power Generation Welly Yandi; Sunanda, Wahri; Fitsa Alfazumi , Nada
International Journal of Electrical, Energy and Power System Engineering Vol. 4 No. 3 (2021): International Journal of Electrical, Energy and Power System Engineering (IJEEP
Publisher : Electrical Engineering Department, Faculty of Engineering, Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/ijeepse.4.3.196-199

Abstract

The Waste Power Plant is one of the power plants with a new renewable energy concept that utilizes waste as fuel. The processing of waste into electrical energy is carried out in two ways: the thermal conversion process and the biological conversion process to find the potential for waste that can be used as fuel to generate electricity. The analysis is needed, especially for Pangkalpinang, which currently has a lot of unprocessed waste. This research was conducted through calculations using several formulas that have been used in previous studies. From these results, the potential waste in 2015 is 97.25 tons/day and produces energy of 18548.10 MWh/year, and in 2020, it was about 186.57 tons/day and produced energy of 35547.18 MWh/year. The projection calculations are carried out to determine the potential for 2021 to 2030. Waste as much as 182523 tons/day in2021 can produce energy of as much as 34776.11 MWh/year. And in 2030, the amount of waste as much as 218132 tons/day can generate an energy potential of 41560.69 MWh/year.
The Potential Utilization of Oil Palm Production Waste at PT. Tata Hamparan Eka Persada Ramadhanti, Debby; Puriza, Muhammad Yonggi; Sunanda, Wahri
International Journal of Electrical, Energy and Power System Engineering Vol. 6 No. 1 (2023): The International Journal of Electrical, Energy and Power System Engineering (I
Publisher : Electrical Engineering Department, Faculty of Engineering, Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/ijeepse.6.1.99-104

Abstract

Oil palm (Elaeis guineensis Jacq.) is one of the commodities that is expected to increase the economic income of the community, especially plantation farmers. The palm oil industry in Bangka district in 2020 is 41.88 thousand tons. The production process of crude palm oil produces waste that has the potential to pollute the environment, namely solid waste and liquid waste. Palm oil mill effluent (POME) contains methane gas (CH4) which has the potential to be a source of energy that can be processed into biogas and solid waste in the form of shells, fiber, EFB has the potential to become biomass. The results obtained from the calculation of the total power that can be generated for 2.5 years of liquid waste (POME) is 6.9462 MW in the category of high heat waste, followed by solid waste (TKS) of 1.4881 MW, fiber waste of 0.9864 MW and shell waste of 0.5646 MW. The total CO2 emissions generated from the generator for 2.5 years for solid waste are 73893.63 tons of CO2 in the category of high-heat waste, and for liquid waste, it is 65867.09 tons of CO2.
Penetration of DWT & ANFIS to Power Transmission Disturbances Ahmad, Sandy; Azhari Zakri, Azriyenni; Oktaviandri, Muchamad; Sunanda, Wahri; Suryadi, Aris
International Journal of Electrical, Energy and Power System Engineering Vol. 6 No. 1 (2023): The International Journal of Electrical, Energy and Power System Engineering (I
Publisher : Electrical Engineering Department, Faculty of Engineering, Universitas Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31258/ijeepse.6.1.105-110

Abstract

This study proposes a hybrid method to classify and estimate the location of short circuit disturbance on power transmission lines. The hybrid method uses Discrete Wavelet Transform (DWT) and Adaptive Neuro-Fuzzy Inference System (ANFIS). The transmission system is implemented in a real system, in which the electric power transmission system on the KP bus to the GS bus is with a length of 64 Km. The DWT is used to process information from each phase voltage and current transient signal as well as the zero-sequence current for one cycle after the disturbance has started. The ANFIS classification is designed to detect disturbance on each phase and ground in determining the type of short circuit disturbance. ANFIS estimation is used to measure the location of disturbance that occur on the transmission line. The training and testing data are generated by simulating the types of short circuit disturbance using software with variations in disturbance location and fault resistance. The result is that the disturbance classification is with 100% accuracy and the estimated disturbance location is with the lowest error of 0.0006% and the highest error is 0.03%.