Electric vehicles and energy storage systems are technologies in the stage of intensive development. One of the innovative ways to use electric cars is the Vehicle to Grid (V2G) concept. V2G charging points are characterized by the ability of bidirectional energy flow while charging EV/BEV (Electric Vehicles/Battery Electric Vehicles). In periods of low energy consumption and the presence of the highest shares of renewable sources, the cleanest electricity is drawn from the grid at the lowest prices and stored in a “mobile warehouse”, which is an electric car. During the reported peaks in electricity demand and the presence of high tariffs, the previously stored energy may be sold back to the distribution network operator. Thanks to this application, the technology determines the highest profitability of the system and assigns EV/BEV the ability to manage electricity flows, while improving the energy balance of the economy. The prospects for the spread of V2G have increased along with the growing requirements for domestic economies, closely related to the significant share of renewable energy sources. The vision of connecting EV/BEV with the power grid creates completely new ways of managing energy and makes it possible to build smart agglomerations in line with the Smartcity idea. Especially since Turkey is one of the countries promoting this idea. The scientific aim of the study is to maximize the aggregator’s profits for V2G by creating a coalition with renewable energy producers and combining the capacities of many EVs and offering their total capacities to the electricity markets. The subject of the research was to obtain extensive knowledge about the vehicle–grid interactions taking place in the Turkish power system. For this purpose, an analysis is conducted to determine the optimal preferred operating points and the amount of regulation proposals that maximize the profit of the EV users while satisfying the constraints of each stochastic parameter. The results show the system benefits from the implementation of the algorithms are significant to optimal bidirectional V2G impacts on distribution systems with high penetration of EVs. The research can find practical applications in assessing the role of electric vehicles and their integration in the vehicle–grid system in power systems. At the same time, pointing to the benefits related to the implementation of such solutions for Turkey and other countries in the field of electromobility, stability of energy systems, and energy independence through the possibility of achieving the desired synergy effect.

Energy security is one of the main factors in the development and diffusion of microgrid applications. In networks operating without storage, the operation of their systems is greatly affected by sudden load demand and intermittent generation fluctuations. The main purposes of using energy storage systems in microgrids are stabilizing the intermittent generation of renewable energy sources locally, to ensure that energy production matches energy demands, participating in the frequency regulation process, maintaining the energy balance between generation and demand in renewable energy microgrids, and increasing energy reliability. This study investigates the frequency and power balance of an isolated microgrid system, by including storage systems (battery and pump-hydro). Realistic data for wind and solar sources are used for the optimal tuning of the proportional-integral controller, using the integral of the absolute error criterion multiplied by time, with a Quasi-Newton method. Simulation studies have been carried out, to investigate the performance of the microgrid system, by including the hydroelectric power plant system with pump storage for 24 h, under various operating conditions. The results reveal that by including the storage units in the system, it exhibits a more consistent and smooth dynamic performance, using renewable energy efficiently.

One of the research areas related to renewable energy sources is the search for new applications for currently used technologies. An important postulate is to achieve the synergy effect by including the existing infrastructure in this process. The innovation described in this article is the integration of solar cells into a modular sound barrier on the highway. The contribution of this article is mainly based on the introduction of the potential feasibility of the first Turkish solar highway, describing the installation of PV systems based on a multi-criteria evaluation (azimuth angle, loss of shade, and dirt). The aim of the study is to determine the economic dimension by examining the costs of implementing such an investment and answering the question concerning the efficiency of solar cells on sound barriers. The research took into account various scenarios regarding the shadow effect and inclination of solar panels and their impact on solar energy production in the example of a given case study, an identified urban area. The research is limited to the model for assessing the feasibility of solar cells on sound barriers based on NPV and the essence of the relationship regarding the LCOE averaged electricity costs. In this study, the function and technical parameters of solar cells are not specified, but the article is limited to the basic information and characteristics required to investigate the payback period and profitability of an investment. Research has shown that if the investment is carried out in accordance with the proposed model, the expected amount of energy produced is 62,257 kWh per year. This value corresponds to the average consumption of electricity in a household by 24 apartments for a given destination, or to providing energy for a selected electric vehicle for one year of its operation, at the same time leading to a significant reduction of CO₂. The presented research can find practical application in the area of developing a strategy for the development and popularization of renewable energy sources while increasing the use of the existing road infrastructure, presenting an important postulate in promoting this type of solution for other geographic destinations.

The integration of advanced control strategies into building energy management systems (BEMS) is essential for achieving energy efficiency and sustaining thermal comfort. Model predictive control (MPC) has gained significant traction as a model-based approach capable of optimizing control actions by predicting future system behavior under dynamic conditions. The current review offers an in-depth analysis of MPC, combining its core theoretical foundations with a broad survey of impactful applications in buildings, for extracting key breakthroughs and trends that have defined the field over the past decade. Emphasis is placed on multiverse MPC configurations and their application across various BEMS frameworks integrating HVACs, energy storage, renewable energy, domestic hot water, electric vehicle charging, and lighting systems. A detailed evaluation of MPC key attributes is then conducted, based on essential aspects of MPC, such as algorithms, optimization solvers, baselines, performance indexes, and building types, as well as simulation tools that support system modeling and real-time validation. The study concludes by outlining key research trends and proposing future directions, with a strong emphasis on addressing real-world deployment challenges and advancing scalable, interoperable solutions on smart building ecosystems. According to the evaluation, MPC research is shifting from simple white-box setups to gray- and black-box models paired with metaheuristic or hybrid solvers, leveraging machine learning for forecasting and multi-objective optimization, but still lacking robustness, benchmarks, and real-world validation. Consequently, next-generation MPC is anticipated to evolve into adaptive, hybrid, and multi-agent frameworks that integrate forecasting and control, embed occupant behavior, enable grid-interactive flexibility, and support lightweight, explainable deployment in real building environments.

The current investigation was based on a simulation employing CFD in COMSOL Multiphysics. The base fluid that was used in this simulation was blood. The flow was considered as a laminar, unsteady and incompressible Newtonian fluid, and the Newtonian nature of blood is acceptable at high shear rate. The behavior of blood flow was analyzed with the objective of obtaining pressure, temperature and velocity effects through an arterial stenosis. Two types of nanoparticles were used in this work: silver (Ag) and gold (Au). The equations of mass, momentum and energy were solved by utilizing the CFD technique. A fine element size mesh was generated through COMSOL. The results of this analysis show that velocity changes through confined parts of the artery, the velocity in a diseased region is higher and the velocity decreases before and after the stenotic region. In the heat transfer feature, the upper and lower boundary temperature was set to 24.85 °C and 27.35 °C, respectively. The nanoparticles affected the physical properties of blood, such as thermal conductivity, density, dynamic viscosity and specific heat. The addition of gold and silver nanoparticles prevented overheating because both nanoparticles have a high thermal conductivity, which has a principal role in dissipating temperature quickly. Nusselt number variations were also calculated and the results show that the curve decreases inside the stenosis. It could be concluded that the streamlines show abnormal behavior and recirculation occurs just after the stenosed area at t = 0.7 s and 1 s. These results will help greatly in the treatment of stenosed arteries.

Undoubtedly, the transition to electromobility with several million new, efficient charging points will have consequences for the energy industry, and in particular for network operators of the distribution infrastructure. At the same time, in the coming years the energy landscape will change into a system in which an increase in decentralized systems based on renewable energy sources will take over the leading function. This transformation process will further increase the complexity and overall pressure for change in energy systems over the next decade. In order to be able to ensure the energy supply and the reliable system operation of the grids in the future as well, communicative networking of generators, storage systems, electrical consumers and grid equipment is indispensable. This study aims to investigate the consequences of including electric vehicles in Istanbul’s power system using a unit commitment simulation model. The presented considerations analyze how uncertain and managed charging strategies affect the power system in terms of operating costs and renewable resources. The presented simulations indicate that, in economic terms, the use of a managed charging strategy saves 2.3%, reducing the total cost from USD 66.71 million to USD 65.18 million. The recipients of the presented research are both the demand and supply sides of the future energy transformation based on the idea of synergy of electromobility and renewable energy sources within the framework of the smart city idea.