Sudlop Ratanakuakangwan 교수

The most recent power generation policy adopted by the government of Thailand focusses on three different areas: security, to ensure a stable power supply; economy, to ensure that the costs associated with implementation of facilities is appropriate; and ecology, to reduce environmental emissions and social impacts. In order to address these requirements, this study proposes a practical model modification for assessing the energy efficiency of power plants. Specifically, stochastic frontier anal

This paper proposes an optimization method for energy planning that will efficiently meet multiple requirements subject to uncertain future projections. A stochastic optimization model is used to identify appropriate energy mixes under various scenarios of uncertainty, and the performance of three different energy policies—a pro-economic policy, a pro-environmental policy, and a governmental plan—is compared. Data envelopment analysis is applied to measure the relative energy efficiency of the o

This paper presents and compares two alternatives of cokes in power generation which are the metallurgical coke with coke oven gas and the coke from lignite under the consideration of the energy and the environment. These alternatives not only consume less fuel due to their higher heat content than conventional coal but also has less SO2 emission. The metallurgical coke and its by-product which is coke oven gas can be obtained from the carbonization process of coking coal. According to high grad

This paper proposes an optimization model for clean energy planning in farming that takes uncertain future projections into account. A stochastic optimization model is applied to determine optimal energy and farming equipment combinations, considering scenarios of uncertainty under multiple farming area sizes. The energy mixes comprise solar photovoltaic panels and battery storage to provide electricity to farm-related equipment, which is categorized into two types by their load usage pattern, i

This study proposes a modified energy planning model that considers a broad range of future uncertainties. Modifications to hybrid stochastic robust optimization and robust optimization methodology allow for the introduction of multi-objective functions that reflect the various dimensions of energy planning including cost, emission, and social impact. Changing the priorities of the objective functions generates different energy policies, which are then compared. Data envelopment analysis is appl