Current discourse on the transition to a decarbonized energy system future is dominated by renewable energy solutions. Initial conditions for this transition may vary across different regions and countries. There are, however, also opportunities for innovative solutions that utilize other low‐carbon energy sources and technology mix. Sustainable development is a contested concept and varies with priorities attached to social, economic, and environmental goals. Therefore, the one‐size‐fits‐all type of solution paradigm needs to be broadened, to accelerate action in the short to medium term. Our argument is that natural gas can be an important complementary transition fuel to support renewable energy in the short‐ and medium‐term transition phases. This means that the goal of zero fossil fuel as a short‐ and medium‐term solution needs to be reconsidered. This takes us to the next argument that innovation and upgraded technology in the low‐carbon fossil fuel sector will provide an important impetus for low‐carbon transition, which we see as a phase lasting until the middle of the century. However, the transition toward a sustainable energy future of gas‐fueled solutions has challenges from the social, technical, economic, geographical, and political points of view. Suitable local solutions should, however, also be assessed. These should take into consideration infrastructure, local demands, resources, and economic aspects as well as national energy policies. An analysis based on the experiences of four countries, both developed and developing, is presented in this study. The countries selected for this study can be placed in two categories: those with an abundance of natural gas reserves (Iran and Norway) and those that are import‐dependent (India and UK). The cross‐country analysis will help us to understand the realistic challenges and opportunities of natural gas as a transition fuel.

Microgrids are new technologies for integrating renewable energies into power systems. Optimal operation of renewable energy sources in standalone micro-grids is an intensive task due to the continuous variation of their output powers and intermittant nature. This work addresses the optimum operation of an independent microgrid considering the demand response program (DRP). An energy management model with two different scenarios has been proposed to minimize the costs of operation and emissions. Interruptible/curtailable loads are considered in DRPs. Besides, due to the growing concern of the developing efficient optimization methods and algorithms in line with the increasing needs of microgrids, the focus of this study is on using the whale meta-heuristic algorithm for operation management of microgrids. The findings indicate that the whale optimization algorithm outperforms the other known algorithms such as imperialist competitive and genetic algorithms, as well as particle swarm optimization. Furthermore, the results show that the use of DRPS has a significant impact on the costs of operation and emissions.

In the climate change mitigation context based on the blue hydrogen concept, a narrative frame is presented in this paper to build the argument for solving the energy trilemma, which is the possibility of job loss and stranded asset accumulation with a sustainable energy solution in gas- and oil-rich regions, especially for the Persian Gulf region. To this aim, scientific evidence and multidimensional feasibility analysis have been employed for making the narrative around hydrogen clear in public and policy discourse so that choices towards acceleration of efforts can begin for paving the way for the future hydrogen economy and society. This can come from natural gas and petroleum-related skills, technologies, experience, and infrastructure. In this way, we present results using multidimensional feasibility analysis through STEEP and give examples of oil- and gas-producing countries to lead the transition action along the line of hydrogen-based economy in order to make quick moves towards cost effectiveness and sustainability through international cooperation. Lastly, this article presents a viewpoint for some regional geopolitical cooperation building but needs a more full-scale assessment.

Remote communities that have limited or no access to the power grid commonly employ diesel generators for communal electricity provision. Nearly 65% of the overall thermal energy input of diesel generators is wasted through exhaust and other mechanical components such as water-jackets, intercoolers, aftercoolers, and friction. If recovered, this waste heat could help address the energy demands of such communities. A viable solution would be to recover this heat and use it for direct heating applications, as conversion to mechanical power comes with significant efficiency losses. Despite a few examples of waste heat recovery from water-jackets during winter, this valuable thermal energy is often discarded into the atmosphere during the summer season. However, seasonal thermal energy storage techniques can mitigate this issue with reliable performance. Storing the recovered heat from diesel generators during low heat demand periods and reusing it when the demand peaks can be a promising alternative. At this point, seasonal thermal storage in shallow geothermal reserves can be an economically feasible method. This paper proposes the novel concept of coupling the heat recovery unit of diesel generators to a borehole seasonal thermal storage system to store discarded heat during summer and provide upgraded heat when required during the winter season on a cold, remote Canadian community. The performance of the proposed ground-coupled thermal storage system is investigated by developing a Computational Fluid Dynamics and Heat Transfer model.

A vast variety of population-based optimization techniques have been formulated in recent years for use in different engineering applications, most of which are inspired by natural processes taking place in our environment. However, the mathematical and statistical analysis of these algorithms is still lacking. This paper addresses a comparative performance analysis on some of the most important nature-inspired optimization algorithms with a different basis for the complex high-dimensional curve/surface fitting problems. As a case study, the point cloud of an in-hand gas turbine compressor blade measured by touch trigger probes is optimally fitted using B-spline curves. In order to determine the optimum number/location of a set of Bezier/NURBS control points for all segments of the airfoil profiles, five dissimilar population-based evolutionary and swarm optimization techniques are employed. To comprehensively peruse and to fairly compare the obtained results, parametric and nonparametric statistical evaluations as the mathematical study are presented before designing an experiment. Results illuminate a number of advantages/disadvantages of each optimization method for such complex geometries’ parameterization from several different points of view. In terms of application, the final appropriate parametric representation of geometries is an essential, significant component of aerodynamic profile optimization processes as well as reverse engineering purposes.