There is a growing interest in green hydrogen, with researchers, institutions, and countries focusing on its development, efficiency improvement, and cost reduction. This paper explores the concept of green hydrogen and its production process using renewable energy sources in several leading countries, including Australia, the European Union, India, Canada, China, Russia, the United States, South Korea, South Africa, Japan, and other nations in North Africa. These regions possess significant potential for “green” hydrogen production, supporting the transition from fossil fuels to clean energy and promoting environmental sustainability through the electrolysis process, a common method of production. The paper also examines the benefits of green hydrogen as a future alternative to fossil fuels, highlighting its superior environmental properties with zero net greenhouse gas emissions. Moreover, it explores the potential advantages of green hydrogen utilization across various industrial, commercial, and transportation sectors. The research suggests that green hydrogen can be the fuel of the future when applied correctly in suitable applications, with improvements in production and storage techniques, as well as enhanced efficiency across multiple domains. Optimization strategies can be employed to maximize efficiency, minimize costs, and reduce environmental impact in the design and operation of green hydrogen production systems. International cooperation and collaborative efforts are crucial for the development of this technology and the realization of its full benefits.

Hosting capacity calculations provide significant benefits in optimizing the amount of additional generation and/or consumption to be added to a distribution grid without the need for additional investments. This paper presents an efficient mathematical model for calculating the marginal hosting capacity of distribution nodes. It can be used to identify the maximum possible change in generation/consumption of each specific node and further identify the nodes that are more impactful in using available network capacity. The model will be of specific importance in integration of electric vehicles (EVs) to the distribution grid. The proposed model is solved in two stages based on a linear power flow model. Numerical studies are conducted on a test radial distribution network to demonstrate the effectiveness and applications of the proposed model.

This paper presents a modified formulation for the wind-battery-thermal unit commitment problem that combines battery energy storage systems with thermal units to compensate for the power dispatch gap caused by the intermittency of wind power generation. The uncertainty of wind power is described by a chance constraint to escape the probabilistic infeasibility generated by classical approximations of wind power. Furthermore, a mixed-integer linear programming algorithm was applied to solve the unit commitment problem. The uncertainty of wind power was classified as a sub-problem and separately computed from the master problem of the mixed-integer linear programming. The master problem tracked and minimized the overall operation cost of the entire model. To ensure a feasible and efficient solution, the formulation of the wind-battery-thermal unit commitment problem was designed to gather all system operating constraints. The solution to the optimization problem was procured on a personal computer using a general algebraic modeling system. To assess the performance of the proposed model, a simulation study based on the ten-unit power system test was applied. The effects of battery energy storage and wind power were deeply explored and investigated throughout various case studies.

The increasing trend of distributed generation deployment in distribution grids requires constant upgrades in the existing infrastructure to increase grid hosting capacity. In principle, it should be possible to increase the grid hosting capacity by reconfiguring the network via changing the status of tie and sectionalizing switches already installed in the distribution grid. The reconfiguration is desirable as it takes advantage of existing network architecture without the need for additional upgrades and investments in the network. This paper presents a method for maximizing distribution grid hosting capacity through such reconfiguration. Unlike classical iterative and time-consuming methods, the proposed method is based on a linearized power flow model which is formulated as a mixed-integer linear programming problem with appropriate radiality constraints. The result is a near-instantaneous and robust computation of optimal reconfiguration for maximizing grid hosting capacity. The proposed method is tested and validated on the IEEE 33-bus distribution test system.