Ever since the idea of sustainable development was proposed, how to achieve it has always been the focus of researchers and policymakers. At the same time, in the letters of sustainable development, two approaches of weak sustainability and strong sustainability have been mentioned; Two approaches with different assumptions suggest different policies and will have different consequences. On the other hand, with the increase of environmental concerns in recent decades, the concept of natural capital and physical, human, and social capital has been added to the common literature of economics. Recently, with the collection of data related to the natural capital of nations by the World Bank, the possibility of statistical studies in this field has been provided. In the form of several regression models and at the international level, the present study will analyze the most fundamental difference between the two approaches of weak sustainability and strong sustainability, i.e., the possibility or impossibility of replacing physical capital instead of natural capital. The study results show that natural capital has a direct, positive, and independent role in explaining sustainable development indicators. Even the addition of physical, human, and social capital indicators does not threaten the significant coefficient of natural capital. Therefore, it can be concluded that under the assumption of a strong sustainability model, other types of capital can not replace natural capital.

Like electricity, hydrogen is an excellent energy carrier, as it can be produced from many different and abundant precursors, such as natural gas, coal, water, and renewable energy. The use of hydrogen in fuel cells, particularly in the transport sector, will make it possible to diversify the energy supply, take advantage of domestic resources, and reduce oil imports dependence. Unlike other fuels, hydrogen (H₂) can be generated and consumed without emitting carbon dioxide (CO₂). This results in great ecological benefits and fundamental challenges. Hydrogen can operate in a closed and inexhaustible cycle based on the cleanest, most abundant, and elemental substances: water, oxygen, and hydrogen. If hydrogen is generated using light, heat, and electricity produced from solar, wind, or nuclear energy, hydrogen becomes a versatile and universal means of storing and transporting energy and a necessary element for future energy systems that operate without environmental pollution, CO₂, and other gases that contribute to the greenhouse effect. Hydrogen is necessary to eliminate environmental pollution and stabilize the composition of the planet’s atmosphere and climate. This paper investigates different methods of hydrogen production in the term of their technological and economic aspects. This paper shows that thermochemical methods dominate the hydrogen market while emerging electroreduction methods are developing fast, which might turn the tide in the future.

This article describes the optimization models recently applied to the design and operation of power systems towards forming smart grids and identifies trends, barriers, and possible gaps in this area. Models are described to optimize the design and operation of power systems considering renewable energies, distributed generation, microgrids, demand management, and energy storage systems. It was concluded that it is necessary to validate many of the models formulated recently to optimize the operation through tests with real data and on a large scale. Furthermore, demand management and microgrids are aspects in which it is necessary to develop models for optimal power flow. Finally, it is necessary to predict stochastic variables with greater precision so that these models adapt to the real behavior of the system.

Due to its geographical location, Iran has numerous capacities in renewable energy, and this issue has made the need to develop renewable energy on the authorities’ agenda. This underscores the need to provide an optimal model for developing renewable energy. Therefore, in this study, the main purpose was to provide an optimal renewable energy model. In line with this goal, by choosing the cost function as the objective function and considering the potential constraints of renewable energy (resource constraints), the amount of electricity consumption in each of the 16 electricity regions (demand constraint) and the limitation of renewable energy production coefficient (Technical constraints), the optimal model of renewable energy use was designed and solved using a solid programming model in LINGO software. The optimal model results show 15.19% small hydropower, 24.30% wind energy, 5.52% biomass energy, 6.13% is geothermal energy, 4.79% is tidal energy, and 44.07% solar energy. The optimum portfolio of renewable energy is estimated in this paper using the robust optimization approach. The results showed which renewable technology has the greater potential to take more share of the energy portfolio. The results of this investigation help policymakers to choose the most suitable renewable technologies to support.