大阪大学 · 意思決定科学
スドロップ・ラタナクアカングワン教授の研究室は、エネルギーや環境の持続可能性を柱に、エネルギーシステムの最適化と効率評価を主眼とする研究を展開しています。特に、不確実性を伴う将来予測を考慮した最適化モデル（ステージストリック最適化、ロバスト最適化）を用い、コスト、環境負荷、エネルギー安全保障、社会的公平性といった複数の政策的側面を統合的に評価する手法を開発しています。また、データエンvelopment analysis（DEA）を活用したエネルギー効率の相対的評価や、再生可能エネルギー・化石燃料両分野における生産効率分析（SFA）も実施しており、政策立案に実用的で科学的根拠を提供することを目的としています。
Figures are computed from collected data and may differ slightly.
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
Open papers in the app to read, cite, and organize with AI.
