Carbon dioxide (CO₂) is a major driver of greenhouse gas emissions, which lead to an increase in Earth's temperature and subsequently drive climate change. CO₂ is primarily produced from fossil fuel-based power generation. Carbon capture and storage (CCS) is a CO₂ capture technology that can be added to fossil fuel power generation. This study evaluates the he technological, financial, and ecological impacts of upgrading CCS technology on a Natural Gas Combined Cycle (NGCC) power generation with three blocks. Amine-based post-combustion capture technology is applied in this study. Simulations were performed employing the Integrated Environment Control Model software. The addition of CCS significantly reduces net power output across all blocks. For Block 1, net power declines from 133 MW to 97.6 MW, a 27% reduction, while Block 2 drops by 17%, from 441.7 MW to 368.1 MW. Block 3 shows a 13% decrease, with net power falling from 441.9 MW to 385.5 MW. Thermal efficiency also declines with the installation of CCS. Corresponding efficiency losses are also notable: Block 1 falls from 40.85% to 30%, Block 2 from 45.24% to 37.69%, and Block 3 from 53.89% to 46.79%. The levelized cost of electricity increases considerably alongside CCS implementation, rising by 80% for Block 1 (0.0843 to 0.1522 USD/kWh), 47% for Block 2 (0.0761 to 0.1114 USD/kWh), and 42% for Block 3 (0.06618 to 0.0874 USD/kWh). Sensitivity analysis indicates that LCOE competitiveness with the national weighted average is achievable when carbon prices exceed 145 USD/t CO₂ for Block 1, 90 USD/t CO₂ for Block 2, and 45 USD/t CO₂ for Block 3. These findings emphasize the trade-offs between power generation efficiency, costs, and carbon capture, providing essential insights for future energy policy and CCS adoption strategies.

Applying coal-biomass co-firing power generation is the strategy to accelerate the renewable energy share in the energy mix to reach 23% by 2025. Although biomass co-firing trials have been carried out at several Coal-Fired Power Plants (CFPP), the potential for implementing biomass co-firing on a larger scale and for the long-term propose still needs to be identified. This article evaluates emission characteristics and economic aspects of implementing biomass and coal in power plants. The traditional review method is used by identifying journal articles as data sources and further elaborating according to the context of the study. The primary emissions from co-firing biomass with coal contain CO, SO2, NOx, and particulate matter. The coal-biomass co-firing power generation has been widely adopted due to its various positive effects. However, it is still necessary to consider the cost of retrofitting, OM, biomass prices, and incentives in its application.

The Association of the Southeast Asian Nations (ASEAN) region is a critical contributor to global development from an environmental perspective. This study has reviewed carbon emissions from energy generation, influence factors from the population, economic growth and renewable energy, emission and energy intensity projection, spatial distribution characteristics, and decarbonization strategy. This work utilizes a comparison methodology between ASEAN countries in the emission intensity and energy intensity in the future projection of electricity conditions in 2030 or 2040, as well as opportunities for reducing greenhouse gas (GHG) emissions as determined by the national policies of each government. The results show that Indonesia, Vietnam, Thailand, and Malaysia produce 79.7% of the electricity in the ASEAN region. As a developing country, Indonesia has the largest population and gross domestic product (GDP) but has the highest predicted emission intensity, of 0.97 CO₂e/MWh, in 2030. Vietnam is predicted to have an emission intensity of about 3.56t-CO₂e/cap and 0.747t-CO₂e/GDP in 2030. Vietnam is expected to increase in energy intensity to 1241 MWh/GDP, while Brunei Darussalam has a high energy intensity of 11.35 MWh/cap. However, the capacity of solar power plants (more than 11 GW) and wind-power plants (2384 MW) have generally increased in ASEAN from 2015 to 2019, indicating the positive development of renewable energy source (RES) use. The national policies strongly influence the estimated GHG emission in ASEAN by aggressively replacing fossil fuels with RESs. Support, via government policies, can reduce the cost of electricity generation from RESs is needed to increase and enhance the installment of clean power generation systems. In future work, the research needs to consider the intermittent characteristics of variable RES in power system operation.

The numeral of academic publications in the microgrid system field has rapidly grown. A microgrid system is a group of interconnected distributed generation, loads, and energy storage operating as a single controllable entity. Many published articles recently focused on distributed generation, system control, system stability, power quality, architectures, and broader focus areas. This work analyzes microgrid: alternating current (AC), direct current (DC), and hybrid AC/DC microgrid systems with bibliometric network analysis through descriptive analysis, authors analysis, sources analysis, words analysis, and evolutionary path based on the Scopus database between 2010 and 2021. The finding helps find out the top authors and most impact sources, most relevant and frequently used in the research title, abstract, and keyword, graphically mapping the research evolved and identifying trend topic.

Objective: This study aims to examine the determinants of public acceptance behavior regarding biomass provision for co-firing in coal-fired power plants (CFPPs), to encourage community participation in supporting the sustainability of biomass co-firing initiatives while promoting circular economy practices in the transition toward low-carbon energy systems. Methods: A quantitative survey was conducted using a conceptual model based on the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB), extended by integrating the information dissemination variable to examine public intentions and behaviors regarding biomass energy. Data from 414 individuals were analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS). Findings: The results show that attitude and perceived behavioral control are the strongest predictors of intention, while intention has a substantial effect on community participation behavior (path coefficient = 0.594). The model explains 35.3% of the variance in behavior, indicating a moderate level of explanatory capability. Information dissemination significantly strengthens both attitudes and perceived behavioral control. Originality: This study addresses a gap in the existing literature by examining public intention and acceptance regarding biomass provision within a developing country context in Indonesia. Practical/Policy implication: The findings of this study highlight the importance of collaboration among stakeholders in designing community engagement programs that effectively communicate the practical benefits of participation to local communities.

Continuous Emission Monitoring System (CEMS) is generally used for monitoring compliance with emission standards set by the government regulations and has not been optimally used for other additional purposes yet. If operated CEMS can produce reliable and accurate data, they can develop further specific data such as emission factors. These emission factors can be used for estimating pollutant emission loads from coal combustion activity in Coal-Fired Power Plants (CFPPs) without conducting direct source measurements. In this study, hourly 1 yr CEMS data from several units of CFPPs were processed to develop specific emission factors for principal air pollutants (SO₂, NO_x, particulates) and greenhouse gases (represented by CO₂). Emission factors were determined by dividing the emission load of each pollutant by the amount of combusted coal during 1 yr. The results showed that emission factor ratings for this study could not be classified as A ratings due to the limited number of investigated CEMS facilities. According to the variability of the derived emission factor values, SO₂ and CO₂ emission factors can be rated as B or above average (with fewer variability values). In comparison, NO_x and particulate emission factors can be placed as C or average (with more variability values).