The Southeast Asian region has been eagerly exploring the concepts of smart city initiatives in recent years due to the enormous opportunities and potential. The initiatives are in line with their plan to promote energy efficiency, phase down/out fossil fuel-based generation, and reduce greenhouse gas emission intensity and electrification of various sectors in addition to renewable energy targets and policies to achieve net zero emissions by 2050 or 2060. However, the major challenges for these countries are related to leadership, governance, citizen support, investment, human capacity, smart device heterogeneity, and efficient modeling and management of resources, especially the energy systems. An intelligent energy system is one of the most significant components for any functional smart city, where artificial intelligence (AI), the internet of things (IoT), and big data are expected to tackle various existing and evolving challenges. This article starts with a brief discussion of smart city concepts and implementation challenges. Then, it identifies different types of smart city initiatives in Southeast Asian countries focusing on energy systems. In addition, the article investigates the status of smart systems in energy generation and storage, infrastructure, and model development. It identifies the unique challenges of these countries in implementing smart energy systems. It critically reviews many available energy modeling approaches and addresses their limitations and strengths, focusing on the region. Moreover, it also provides a preliminary framework for a successful energy system that exploits AI, IoT, and big data. Finally, the roadmap for a successful energy system requires appropriate policy development, innovative technological solutions, human capacity building, and enhancement of the effectiveness of current energy systems.

This study presented a detailed investigation into the performance of a plate–frame water gap membrane distillation (WGMD) system for the desalination of untreated real seawater. One approach to improving the performance of WGMD is through the proper selection of cooling plate material, which plays a vital role in enhancing the gap vapor condensation process. Hence, the influence of different cooling plate materials was examined and discussed. Furthermore, two different hydrophobic micro-porous polymeric membranes of similar mean pore sizes were utilized in the study. The influence of key operating parameters, including the feed water temperature and flow rate, was examined against the system vapor flux and gained output ratio (GOR). In addition, the used membranes were characterized by means of different techniques in terms of surface morphology, liquid entry pressure, water contact angle, pore size distribution, and porosity. Findings revealed that, at all conditions, the PTFE membrane exhibits superior vapor flux and energy efficiency (GOR), with 9.36% to 14.36% higher flux at a 0.6 to 1.2 L/min feed flow rate when compared to the PVDF membrane. The copper plate, which has the highest thermal conductivity, attained the highest vapor flux, while the acrylic plate, which has an extra-low thermal conductivity, recorded the lowest vapor flux. The increasing order of GOR values for different cooling plates is acrylic < HDPE < copper < aluminum < brass < stainless steel. Results also indicated that increasing the feed temperature increases the vapor flux almost exponentially to a maximum flux value of 30.36 kg/m²hr. The system GOR also improves in a decreasing pattern to a maximum value of 0.4049. Moreover, a long-term test showed that the PTFE membrane, which exhibits superior hydrophobicity, registered better salt rejection stability. The use of copper as a cooling plate material for better system performance is recommended, while cooling plate materials with very low thermal conductivities, such as a low thermally conducting polymer, are discouraged.

The combustion characteristics of liquid ethanol in air and oxygen–carbon dioxide environments are investigated numerically inside a vertical reactor. Gambit 2.2 was used to construct the mesh and Fluent 12.1 was used to perform the calculations. Different oxidizer environments were considered including pure air, oxygen-enriched air, in addition to the cases of OF21 (21% O₂ and 79% CO₂) and OF29 (29% O₂ and 71% CO₂). Comparisons were performed between the different cases and the results were validated against wide range of the experimental data. Nonpremixed combustion model which utilizes probability density function to predict the scalar quantities was incorporated to simulate the combustion process. Two turbulence models, realizable k–ɛ (RKE) model and Reynolds stress model (RSM), were applied and their results were compared. The Euler–Lagrange approach was utilized to solve the discrete phase model. The results showed the ability of the RKE model to predict much closer data to the experimental data than the RSM which over predicts the temperature. For the case of OF21, the flame was lifted and the combustion temperature was reduced as compared to the air combustion case. However, the OF29 combustion case resulted in a very close performance to the case of air combustion.