The challenge of enhancing long-term efficiency and reliability in power systems is tackled through Transmission Expansion Planning (TEP). This study evaluates the actual failure probabilities of system components within the TEP framework, with particular attention given to the impact of plug-in electric vehicles (PEVs) and their integration with demand response (DR) strategies. The analysis explores how the growing integration of PEVs into the grid affects system loading and, consequently, the loading and failure probabilities of transmission lines. Due to their capability to charge locally, PEVs impose less strain on the transmission infrastructure when compared to Grid-level energy storage systems (ESS), such as pumped hydro storage. To quantify the benefits of DR strategies, their implementation cost is incorporated into the TEP objective function and compared against the DR contributions of other consumer categories. Additionally, effective demand management may reduce the need for constructing new transmission lines by decreasing the failure risk of existing ones. Thus, a comprehensive valuation of the transmission network is essential and must be reflected within the objective function. The proposed framework is validated using three case scenarios based on the IEEE 24bus RTS, demonstrating the practicality and efficiency of the suggested approach.

Transitioning to renewable energy is part of the answer to, on the one hand, growing industrial development and the rising demand for energy and, on the other,  environmental concerns and the need to preserve fossil fuel resources for future generations. This research focuses on the potential for integrating hydrogen storage into a highly reliable renewable energy system. The purpose of this study is to determine the potential of renewable energy in an Iranian location, in a project that looks at a power grid in various connected and disconnected scenarios involving hydrogen storage. The energy potential is identified: annual production capacity is 2218818 kW, requiring a total investment outlay of US$697,624.

 Due to the increasing need for energy and limited fossil resources on the one hand, and the increasing environmental pollution caused by the burning of these resources, on the other hand, the use of renewable energy has become more and more important. Wind and solar energy are one of the main types of renewable energy that has long attracted the human mind, so he has always thought about using these energies in the industry. In this study, the optimal combination of scattered production sources (wind-solar) has been added to a 33 IEEE bus system and beta distribution has been used to model wind speed. Also, load and production planning is 24 hours. The aim of this study is to improve voltage profiles, increase reliability and reduce losses. As a result, a 39% reduction in casualties in the presence of wind turbines and a 40% reduction in the presence of photovoltaic cells highlights the role of these resources in the grid.

Reconstructing power systems has changed the traditional planning of power systems and has raised new challenges in transmission expansion planning (TEP). In this paper, investment cost, cost of density and dependability have been considered three objectives of optimization. Also, multi-objective genetic algorithm NSGAII was used to solve this non-convex and mixed integer problem. A fuzzy decision method has been used to choose the final optimal answer from the Pareto solutions obtained from NSGAII. Moreover, to confirm the efficiency of NSGAII multi-objective genetic algorithm in solving TEP problem, the algorithm was implemented in an IEEE 24 bus system and the gained results were compared with previous works in this field.