The present paper deals with an infrastructure digitization policy to optimize maintenance processes and energy efficiency to transform port areas to ZED (Zero Energy District). The Lazio Region started the process for all its ports in 2020. The Anzio port started and developed as a pilot project as it is a particularly representative sample for the Mediterranean Sea reality due to its geomorphological conformation. The study aimed to develop energy-saving procedures and strategies and integrate production systems from Renewable Energy Systems (RESs) for sustainable mobility. In the article, these strategies are described in detail and energy analysis is carried out, starting from the current state and demonstrating the potential energy self-sufficiency of the infrastructure. Finally, the investigation’s potential utilizing a Digital Twin (DT) of the area is highlighted. Furthermore, the BIM (Building Information Modeling) and GIS (Geographic Information System) combining possibility to maximize the energy efficiency measures beneficial impact are discussed.

With a goal of achieving net-zero emissions by developing Smart Cities (SCs) and industrial decarbonization, there is a growing desire to decarbonize the renewable energy sector by accelerating green buildings (GBs) construction, electric vehicles (EVs), and ensuring long-term stability, with the expectation that emissions will need to be reduced by at least two thirds by 2035 and by at least 90% by 2050. Implementing GBs in urban areas and encouraging the use of EVs are cornerstones of transition towards SCs, and practical actions that governments can consider to help with improving the environment and develop SCs. This paper investigates different aspects of smart cities development and introduces new feasible indicators related to GBs and EVs in designing SCs, presenting existing barriers to smart cities development, and solutions to overcome them. The results demonstrate that feasible and achievable policies such as the development of the zero-energy, attention to design parameters, implementation of effective indicators for GBs and EVs, implementing strategies to reduce the cost of production of EVs whilst maintaining good quality standards, load management, and integrating EVs successfully into the electricity system, are important in smart cities development. Therefore, strategies to governments should consider the full dynamics and potential of socio-economic and climate change by implementing new energy policies on increasing investment in EVs, and GBs development by considering energy, energy, techno-economic, and environmental benefits.

The world’s electricity generation has increased with renewable energy technologies such as solar (solar power plant), wind energy (wind turbines), heat energy, and even ocean waves. Iran is in the best condition to receive solar radiation due to its proximity to the equator (25.2969° N). In 2020, Iran was able to supply only 900 MW (about 480 solar power plants and 420 MW home solar power plants) of its electricity demand from solar energy, which is very low compared to the global average. Yazd, Fars, and Kerman provinces are in the top ranks of Iran, with the production of approximately 68, 58, and 47 MW using solar energy, respectively. Iran also has a large area of vacant land for the construction of solar power plants. In this article, the amount of electricity generation using solar energy in Iran is studied. In addition, the construction of a 10 MW power plant in the city of Sirjan is economically and technically analyzed. The results show that with US$16.14 million, a solar power plant can be built in the Sirjan region, and the initial capital will be returned in about four years. The results obtained using Homer software show that the highest maximum power generation is in July.

The impact of ports on urban areas’ decarbonization to reduce air and environmental pollution effects to achieve sustainable development is undeniable, especially in the marine transportation sector. In this case, applied studies that can contribute to existing knowledge on increasing ports’ energy self-sufficiency using renewable energy sources (RESs) are critical and necessary. In this study, firstly, (1) the RESs assessment prioritization methodology was designed for Lazio ports. Additionally, (2) long-term solar radiation and wind speed were analyzed using the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) dataset of Lazio ports. Furthermore, (3) the time-series, normal-distribution and correlation methods were applied to the generated energy source, based on various parameters of the RESs used in the ports. Finally, (4) Italian port areas, towards renewable energy community (REC) scenarios, were analyzed and developed.

A cost-effective and efficient wind energy production trend leads to larger wind turbine generators and drive for more advanced forecast models to increase their accuracy. This paper proposes a combined forecasting model that consists of empirical mode decomposition, fuzzy group method of data handling neural network, and grey wolf optimization algorithm. A combined K-means and identifying density-based local outliers is applied to detect and clean the outliers of the raw supervisory control and data acquisition data in the proposed forecasting model. Moreover, the empirical mode decomposition is employed to decompose signals and pre-processing data. The fuzzy GMDH neural network is a forecaster engine to estimate the future amount of wind turbines energy production, where the grey wolf optimization is used to optimize the fuzzy GMDH neural network parameters in order to achieve a lower forecasting error. Moreover, the model has been applied using actual data from a pilot onshore wind farm in Sweden. The obtained results indicate that the proposed model has a higher accuracy than others in the literature and provides single and combined forecasting models in different time-steps ahead and seasons.