Journal of Renewable Energy and Smart Grid Technology

Artificial Neural Network Estimation of Daily Net Radiation Using Meteorological Data in Thailand

Chutimon Phoemwong — 2025-01-24

Net radiation is the difference between downward and upward radiation, considering both shortwave and longwave radiation. The net radiation controls the water cycle, plant photosynthesis, the earth’s climate changes, and the energy balance. In this paper, the Artificial Neural Network (ANN) model is developed for estimating daily net radiation from meteorological data that are based on maximum air temperature, minimum air temperature, daily relative humidity, and daily solar radiation. Net radiation and meteorological data collected for 7 years (2017-2023) from Chiang Mai meteorological station (CM: 18.77°N, 98.96°E), Ubon Ratchathani meteorological station (UB: 15.24°N, 105.02°E), Nakhon Pathom meteorological station (NP: 14.01°N, 99.96°E), and Songkhla meteorological station (SK: 7.41°N, 100.62°E) were used to train and test the model. The discrepancy between the net radiation estimated by the ANN and the measured net radiation was presented in terms of determination coefficient (R2), relative root mean square error (RMSE), and relative mean bias error (MBE). The model showed 0.98, 14.48%, and -2.17%, respectively. The result shows that the artificial neural network model is an accurate and easy option for estimating surface net radiation.

Energy Conservation in Palm Oil Mill by Installing Inverters for Motors

Kanitpong Chitsopon — 2025-03-14

Thailand is the third largest palm oil producer, accounting for 3.9% of global palm oil production, approximately 84.6%. Energy Efficiency Plan 2018 (EEP2018) aims to reduce energy consumption (Energy intensity) by 30% in 2037. This study investigates the conversational energy of palm oil mills (POM) by installing motor inverters to save energy and reduce the cost of electricity. The experiment was an energy consumption estimate pre- and post-installation of a motor inverter for Thongmongkol Palm Oil Industry Co., Ltd. That analysis used energy consumption and a payback period. The result was that Thongmongkol Palm Oil Industry Co., Ltd. used energy consumption of 4,923.09-6,364.54 MWh. The factory can generate energy for approximately 99% of the factory and purchases from the Electricity Generating Authority of Thailand (EGAT) approximately 1%. These are several motors of 229 units, a Power of 2,785.44 kW, and a horsepower of 3,742.97 HP. Station 4 is the primary process of the oil palm mill. Installing the motor inverter decreases the electricity power consumption by 10.43%. It can save energy costs of 51,091.35 Baht/year. Specific energy consumption (SEC) of 0.013 MWh/ton from 0.015-0.20 MWh/ton. It reduced SEC by 13.33-35.00%. The payback period for installing the motor inverter is 3.16 years.

Energy Development Assessment of Biomass Power Plant with Rice Husk Fuel Source in Thailand: Analysis of the Performance, LCOE and Carbon Emissions Reduction

Prachuab Peerapong — 2025-03-18

This study was conducted from the technical and financial from two rice husk power plants in Thailand. A proposed rice husk power plants use Rankine cycle power plant as a combustion configuration for electricity generation. The simulation in this research uses the System Advisor Model (SAM) to study the plant performance and financial analysis. This research investigates by using input technical plant data, and the financial variable assumptions. The results in this research can be concluded that the LCOE (the Levelized cost of electricity) of the electricity generation from the rice husk power plants at 6.62-6.63 ¢/kWh. The potentials of CO2 reduction of rice husk plants in this study are 38,319 tons/year for plant A, and 53,923 tons/year for plant B. These results can be used as a useful tool for developing strategic plans for biomass power plants in Thailand.