Future Sustainability

Greenhouse gas inventory mapping: a case study in Malaysia’s solid fuel testing facility

Mohammad Nurizat Rahman — 2025-01-15

Solid fuels still play an important role as energy sources in Malaysia. The Solid Fuel Testing Facility (SFTF) system is one of the best systems for assessing the performance of various solid fuel types before their adoption in thermal power plants in Peninsular Malaysia. Given the inherent nature of solid fuel combustion, greenhouse gas (GHG) emissions are unavoidable during SFTF operations. By thoroughly examining the GHG emissions associated with the SFTF system, the reporting company can significantly contribute to environmental stewardship in the power generation sector. The study conducted an assessment of the GHG emissions mapping (Scopes 1 to 3) from the SFTF facility during the reporting year. The decarbonization of international shipping and the progress of energy transition in Malaysia hold significant potential to reduce GHG emissions across all scopes effectively. Additionally, utilizing local biomass to reduce dependence on external coal suppliers for SFTF testing is essential for lowering GHG emissions. Investments in technological advancements that minimize or eliminate reliance on Liquefied Petroleum Gas (LPG) in SFTF operations can reduce Scope 1 GHG emissions. Furthermore, procurement policies that prioritize low-GHG-emitting goods are essential for future GHG emissions reduction.

An overview of Optimization and learning algorithms for energy management in smart homes

Andile Ngcobo — 2025-01-17

Smart home electric energy management systems are designed to optimize energy efficiency, reduce waste, and promote sustainability. This paper aims to conduct a literature review on optimization and learning algorithms for energy management in smart homes. The research methodology involves retrieving data from the Scopus database and visualizing the information through VOSviewer. The results of the literature reviewed encompass a wide range of strategies and algorithms aimed at optimizing energy management in smart homes. A key noticeable aspect is the diverse application of advanced optimization techniques and machine learning algorithms to enhance energy efficiency, reduce costs, and promote sustainability. The study contributes by providing an in-depth analysis of optimization algorithms for energy cost reduction, evaluating and categorizing learning algorithms, and identifying best practices for optimizing energy consumption in smart homes.

Simulation and analysis of energy consumption in all types of residential complexes and choosing the best form from the perspective of sustainability

Rahim Zahedi — 2025-01-27

Energy demand in residential buildings is growing with the immigration of people to urban areas. This study simulates and analyses five different types of residential buildings. The possibility of using a solar thermal system is studied, and then five choices are ranked with the PSI method, which is a mathematical approach. For HVAC simulations, Design builder software, and solar simulations, T*Sol software is used. The results show that in terms of heating load, towers and skyscraper types of residential buildings demand more energy, with 3.67 MW and 3.62 MW, respectively. In terms of cooling, towers and surrounding types need bigger values than others, with 1.84 MW and 1.82 MW, respectively. Solar simulations indicate that the highest solar fraction with no area limitations belongs to the sky scrapper type with 26.9 percent, while collector efficiencies of all types are between 9.9 and 11.6 percent. However, with rooftop areas in each type, the highest solar fraction belongs to linear and surround types both with 24.6 percent. Mathematical analysis shows that by taking into account the importance of heating load and solar fraction for all types, the best form of residential buildings to use is a mixed type with the first rank.

Integration of a biomass-fired thermal plant with solar-turbine and solar-assisted dryer for multi-energy generation

John Isaac — 2025-01-29

The study analyzed the thermodynamics and environmental performance of a biomass-based solar-assisted trigeneration system for power, cooling, and hot water production. The system uses municipal waste in an incinerator and a solar tower with a gas turbine supplemented by natural gas. It includes an Organic Rankine Cycle (ORC) for power, a vapor absorption system (VAS) for refrigeration, and a gas turbine. The analysis focused on thermodynamic, exergoeconomic, and thermo-environmental perspectives, considering indicators like the exergetic utility index (EUI), exergo thermal index (ETI), waste exergy ratio (WER), and sustainability index (SI). Simulation results show a net output of 6.128 MW, a cooling capacity of 131.1 kW, and a cooling water flow of 65.14 kg/s. The energy and exergy efficiencies are 66.68% and 53%, respectively. The solar tower helps reduce natural gas use by 633.6 kg/h, lowering carbon emissions. Exergy destruction is highest in the incinerator and combustion chamber. The exergoeconomic analysis shows minimal cost reduction in the gas turbine air compressor and incinerator. Thermo-environmental indicators were recorded as EUI 0.6992, ETI 0.9161, WER 1.092, and SI 0.6109, reflecting the system's environmental friendliness due to efficient energy use and low discharge temperatures.

Evaluating the economic impact of solar energy on local industries in Semnan, Iran

Marziyeh Razeghi — 2025-01-31

This study provides a comprehensive technical, economic, and environmental analysis for the implementation of a 10 MW solar power plant in Semnan Industrial Park. With increasing global energy demand, the transition from fossil fuels to renewable energy sources is essential to mitigate environmental impacts and reduce greenhouse gas emissions. This research highlights innovative developments in photovoltaic systems and energy storage solutions, demonstrating their potential for increased efficiency and reliability. From an economic perspective, the analysis shows that solar energy can achieve competitive energy production costs estimated at around $0.05/kWh, especially in semi-arid and solar resource-rich regions. Furthermore, the study emphasizes the importance of supportive government policies and incentives to facilitate investment in solar technologies. The results show that adopting solar energy solutions not only addresses environmental concerns but also offers significant economic benefits, including a 7-10 year payback period for the proposed power plant. Overall, this research highlights the vital role of solar energy in fostering sustainable industrial development while contributing to climate change mitigation efforts.