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Showing papers by "Hiroshi Morita published in 2021"


Journal ArticleDOI
TL;DR: Numerical results from the model could help policy makers effectively address the trade-off between system stability and economy correlated with budgetary limits and determine effective weight coefficients for the preferred control levels.

11 citations


Journal ArticleDOI
01 Jun 2021
TL;DR: In this paper, a stochastic frontier analysis (SFA) with inefficiency effects was applied to both renewable energy and fossil fuel-fired power plants in Thailand, and the results showed that power plant capacity was positively correlated with plant efficiency and that plant age was negatively correlated with efficiency.
Abstract: 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 analysis (SFA) with inefficiency effects was applied to both renewable energy and fossil fuel-fired power plants in Thailand. The empirical results showed that power plant capacity was positively correlated with plant efficiency, and that plant age was negatively correlated with efficiency. In addition, in terms of efficiency scores, renewable power plants tended to be 7.13% more efficient than fossil-fuel plants, and base-load power plants were 9.44% more efficient than peak-load plants. In addition, the efficacy of four different carbon tax scenarios and their effects on the technical efficiency of power plants were evaluated. The results of the tax-rate analysis demonstrated that even low carbon taxes (e.g., 1 USD/tCO2e) can encourage the notable cleaner energy system.

7 citations


Journal ArticleDOI
TL;DR: In this article, 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.

2 citations