This study evaluates the efficiency of European Union (EU) countries in terms of energy use and environmental performance by employing an input-oriented Data Envelopment Analysis (DEA) framework. The analysis incorporates energy consumption and CO₂ emissions as inputs, and GDP per capita and environmental performance index as outputs, providing an integrated assessment of eco-efficiency. The findings reveal that only a limited number of countries, namely Ireland and Malta, operate on the efficiency frontier, while most countries exhibit varying degrees of inefficiency. The results further indicate that many countries need to significantly reduce energy use and carbon emissions to achieve efficient performance, although the required improvement levels differ considerably across countries. Reference set analysis highlights the dominant role of Malta as a benchmark unit, suggesting that efficient resource allocation is a key determinant of performance. By combining economic and environmental indicators within a single DEA framework, this study contributes to the literature and offers policy-relevant insights for improving energy efficiency and environmental sustainability across EU countries and provides policy implications for sustainable development strategies aligned with EU climate and energy targets, supporting evidence-based decision-making for resource efficiency improvements.
Bus wood (Melaleuca viridiflora) is an underutilized sawmill residue in the Merauke region of South Papua. Converting this residue into densified fuel can support local biomass utilization while reducing unmanaged wood waste. This study evaluates the effect of donut-briquette compaction pressure (30, 40, and 50 bar) on the thermal behavior of a multilayer annular pyrolysis stove. The stove was instrumented with nine K-type thermocouples arranged at outer, middle, and inner radial positions across three vertical layers. Temperature profiles were recorded at 2 min intervals, and thermal output was assessed using Water Boiling Tests (WBTs; n = 16 per pressure). The inner-edge sensors produced the highest temperatures, with transient peaks approaching 900-950 °C, whereas middle-position sensors generally operated between about 400 and 750 °C. Outer-edge sensors remained cooler, although the upper-layer outer sensor reached approximately 450 °C. Mean WBT energy rates were 3.79 ± 0.23, 3.89 ± 0.17, and 3.92 ± 0.26 MJ h⁻¹ for 30, 40, and 50 bar, respectively. One-way ANOVA indicated no significant difference in mean energy rate among the three pressures (p = 0.215). The 40-bar condition showed the lowest coefficient of variation in WBT energy rate and a comparatively sustained intermediate-temperature response. These results indicate that compaction pressure affects temperature evolution and stability more strongly than mean useful energy rate within the tested range.
This study proposes a planning-stage techno-economic framework for sizing a standalone PV–wind–battery–diesel microgrid under simultaneous reliability and operational carbon-intensity constraints. Candidate system configurations defined by photovoltaic capacity, wind capacity, battery storage size, and diesel generator rating are evaluated using an hourly energy-balance simulation over a full annual cycle. Supply reliability is enforced through a loss-of-power-supply probability (LPSP) constraint of 1%, while environmental performance is controlled via a delivered-energy CO₂-intensity threshold of 0.25 kg CO₂/kWh. Renewable resource and load profiles were obtained from publicly available datasets to support transparency and reproducibility. System performance metrics included unmet load, renewable curtailment, battery utilization, diesel dispatch, fuel consumption, and levelized cost of electricity (LCOE). Results showed that feasible configurations achieved LCOE values between 0.19 – 0.31 USD/kWh and operational CO₂ intensity between 0.14 – 0.29 kg CO₂/kWh. Increasing renewable penetration and battery storage reduced diesel energy contribution by 52 – 78%. The framework provides a transparent and reproducible screening approach for identifying technically feasible and economically viable hybrid microgrid configurations prior to detailed optimization.
Adding the photovoltaic distributed generation (PVDG) and distribution static compensators (DSTATCOM) to power distribution networks is an effective technique to improve voltage stability and reduce power losses. This research introduces a new hybrid optimization approach that combines genetic algorithms (GAs), glowworm swarm optimization (GSO), and particle swarm optimization (PSO) to determine the optimal sizes and positions for PVDG and DSTATCOM units in radial distribution networks. The primary goal is to minimize total active power loss (TAPL) and total voltage deviation (TVD), while maintaining voltage stability at its peak. To achieve superior optimization results, the GA-GSO-PSO algorithm is produced. It takes advantage of GA’s power in exploring multiple solutions, GSO’s capacity to search locally, and PSO’s rapid convergence. A technique on IEEE 33- and 69-bus systems is performed and a comparison with other algorithms, namely PSO, GSA, PPSOGSA, and MOEA/D is discussed. The results are found to be outstanding since the active power loss in the 33-bus system is decreased by 94.68%, from 210.98 kW to 11.61 kW. The 69-bus system shows an even greater reduction of 98.11%, with losses reducing from 224.94 kW to 4.25 kW. The minimum bus voltage is also improved further. It increases from 0.9038 p.u to 0.992 p.u in the 33-bus system, and from 0.9092 p.u to 0.9943 p.u in the 69-bus system. At the same time, the total voltage deviation is decreased by up to 94.17%. It has been proven that strategically installing suitably sized PVDG and DSTATCOM units can significantly improve power quality, voltage stability, and network efficiency.
The Eastern Economic Corridor (EEC) of Thailand, comprising Chonburi, Rayong, and Chachoengsao, is a major industrial hub where the public transport sector is a significant source of greenhouse gas (GHG) emissions. This study assesses GHG emissions from fossil-fuel-powered buses and discusses the potential for transitioning to of battery-electric buses (BEBs). The assessment is conducted using a bottom-up approach compatible with Intergovernmental Panel on Climate Change (IPCC) guideline principles. The assessment is based on 2019 activity data, disaggregated by route category (intra-provincial and inter-provincial) and by province. For inter-provincial routes, travel volumes were proportionally allocated to each province according to the distance traversed within its boundaries. Results indicate that inter-provincial routes account for approximately 89% of total emissions, with Chonburi alone contributing nearly half of the EEC total. Full electrification of these high-demand corridors, particularly when powered by renewable energy sources, offers substantial potential for emission reduction. Policy measures recommended include targeted infrastructure deployment, financial incentives, and integrated energy management strategies. The findings provide actionable insights for regional decarbonization planning and support Thailand’s broader sustainable transport goals.
