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Journal : kinetik game technology information system computer network computing electronics and control

The Design of DC Micro Grid with a Load-Based Battery Discharge Method for Remote Island Electrification Utilizes Marine Currents and Solar Photovoltaic Faanzir; Mochamad Ashari; Soedibyo; Suwito; Umar
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 7, No. 4, November 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v7i4.1576

Abstract

This paper presents the design of DC micro grid with a load-based battery discharge method for remote island electrification utilising marine currents and solar photovoltaic. To anticipate the intermittent, a load-based battery discharge method is proposed. A centralized battery storage is sized according to the unfilled load demand by the marine current and the solar PV. Thus, the length of the turbine diameter is varied to meet the optimum system size. Hourly data of marine current speed from Cipalulu Strait in Maluku, Indonesia is provided. Data at a typical time, shows that the marine current peak power occurs every 6 hours perday, whereas the PV is at noon. The loads divide into 6 categories, including household 1, household 2, villagse office, school, mosque, and public health center with the peak demand as 112 kW and 856 kWh perday. All loads, mainly for lightings and electronic equipment work in 24 V DC through converters. The distribution network employs 320 V DC connecting from the power plan to the community residents. Simulations demonstrate that the battery size, solar PV, and turbine radius matches to meet the loads. Simulations also show that the battery utilization meets its current and capacity, meaning that an optimum size and filling the load profile can be smoothly conducted.
Improving Fuel Consumption Efficiency of Synchronous Diesel Generator Operated at Adjustable Speed using Adaptive Inertia Weight Particle Swarm Optimization Algorithm Muhtadi, M Zaky Zaim; Suryoatmojo, Heri; Soedibyo; Ashari, Mochamad
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 8, No. 4, November 2023
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v8i4`.1756

Abstract

Diesel generator is a reliable source of electricity, but it requires quite high operational costs, especially for fuel. This paper describes a technique for reducing fuel consumption in Diesel Engine Synchronous Generator systems. The system is originally a Constant Speed Diesel Synchronous Generator (CSD-SG), but during certain conditions, the speed is reduced to minimize fuel consumption by adjusting the Specific Fuel Consumption (SFC) map. SFC is defined as the amount of fuel consumed by a diesel engine generator for each unit of power output. It shows various numbers depending on the speed and operating power. In this paper, we use the Adaptive Inertia Weight Particle Swarm Optimization (AIWPSO) algorithm to select of the proper SFC curve at a certain speed and operating power. AIWPSO employs an adaptive inertial weight adjustment method, which enables this algorithm to achieve faster convergence than conventional Particle Swarm Optimisation (PSO) algorithms. The system is embedded with AC/DC/AC power electronics converter to regulate the frequency. Data set of 1000 kVA Cummins diesel engine generator from the oil and gas company in Central Java, Indonesia was taken for simulations. The results show that the AIWPSO algorithm calculates the fuel consumption as 1,678 liters per day on a typical condition, whereas in the previous method, the linear line needs 1,693 liters per day. Therefore, using AIWPSO method can save up to 450 liters of fuel per month. The simulation results show that the proposed method can improve fuel efficiency compared to the previous model.
ANFIS-Controlled High Step Up DC DC Converter for Fuel Cell Systems with Enhanced Efficiency Against Load Variation Harmini Harmini; Mochamad Ashari; Feby Agung Pamuji
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 11, No. 1, February 2026
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v11i1.2456

Abstract

The primary challenge in utilizing Fuel Cell (FC) systems lies in their inherently low and fluctuating output voltage, which contrasts with the requirements of a Direct Current (DC) bus network that demands a stable and relatively high voltage level. Ensuring consistent voltage regulation in the DC bus network is essential for reliable system performance. An interface converter is required to elevate and stabilize the voltage output under dynamic operating conditions. This paper introduces a high step-up DC–DC converter integrated with an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based control scheme for enhancing the performance of FC power systems. The proposed work encompasses the modeling, analytical design, and structural development of the converter and its intelligent control mechanism. The proposed high step-up converter exhibits a novel structural configuration that integrates a clamp unit, a Multiplier Cell (MC), and cascaded Quadratic Boost Converter (QBC) stages. The contribution of this converter topology lies in its ability to enhance the reliability of fuel cell–based renewable energy systems, achieve high voltage amplification, ensure optimal efficiency, and maintain dynamic stability. This topology is specifically developed to attain an ultra-high voltage conversion ratio, achieving a significant voltage gain of up to 9.65 times, thereby effectively increasing the input voltage from 45 V to 400 V. The ANFIS controller effectively maintains a stable output voltage of 400 V with a maximum deviation of only ±3.5%. The proposed converter achieves a peak efficiency of 87% under varying load conditions, demonstrating its suitability for fuel cell-based energy systems.