The current global energy crisis is one of the most pressing challenges of the 21st century, it highlights the fragility of an old power system based on fossil fuels, geopolitical dependencies and often the precariousness and age of equipment and installations, affecting the economy, security and social stability on a national, regional and world scale. The risk of blackout thus becomes not only a technological threat, but a symbol of the need for a paradigm shift. The energy future must be sustainable, collaborative and adaptable—to guarantee not only the continuity of services with electricity, but also the stability of modern society. This paper provides an intrinsic interdisciplinary analysis on the causes, implications and possible solutions related to major imbalances in contemporary power systems, emphasizing the growing risk of blackout (large power outages). The main causes of crises are analyzed interdisciplinary, such as: insecurity in the functioning of the National Power System, terrorist attack on the National Power System, extreme weather condition, natural calamity, energy insecurity and political/military insecurity. The paper highlights the interdependence between energy infrastructure and energy security, as well as the vulnerability of power grids to cyberattacks, natural disasters and consumer pressures. In addition, socio-economic, technological and political issues are addressed, providing an integrated view of the phenomenon. Finally, national, regional and bilateral mitigation, limitation and restoration (resilience) procedures and measures are proposed in the event of an electricity crisis—blackout.

The paper presents the structure of an active parallel filter for reducing harmonic pollution and reactive power. The active power filter control is based on instantaneous reactive power theory. The authors present the modelling of parallel active filter based on this theory and the simulation results in MATLAB-SIMULINK. The method is based on instantaneous reactive power (TPRI_P).

The transition toward active distribution networks requires advanced control solutions capable of handling the rapid dynamics of distributed energy resources. This paper proposes a low-cost, intelligent IoT architecture designed for the real-time optimization and analysis of energy systems within low-voltage networks. Unlike centralized monitoring approaches constrained by communication latency, the proposed solution leverages Intelligent Edge Processing (IEP) implemented on ESP32 embedded nodes to optimize data flow and decision-making. This architecture executes stability assessments directly at the network edge, calculating critical analysis indicators such as the Voltage Deviation Index (VDI) and Rate of Change of Frequency (RoCoF). The system was validated on the CIGRE European LV benchmark under severe stress scenarios, including rapid solar transients and voltage sags. The results demonstrate that the proposed architecture effectively coordinates storage interventions, ensuring voltage recovery within 300 ms and maintaining power quality within EN 50160 limits even during severe voltage sags. The study validates the feasibility of using industrial IoT edge computing as a resilient, non-wire alternative for modernizing complex energy systems.

The rapid proliferation of single-phase non-linear loads, such as LED lighting and IT equipment, in modern Smart Buildings has introduced significant power quality challenges in low-voltage electrical installations. A critical but often underestimated consequence is the severe overloading of the neutral conductor caused by triplen harmonics (particularly the 3rd harmonic), which sum algebraically even in balanced three-phase systems. This paper analyzes the electrical and thermal impact of these distortions using a detailed MATLAB/Simulink model of a 400/230 V (3P + N) network. The simulation results demonstrate that under highly distorted conditions (Scenario S3), the neutral current can reach 180% of the nominal phase current (18 A vs. 10 A). Furthermore, the Joule losses analysis reveals a thermal stress more than three times higher on the neutral conductor (peak ~65 W) compared to the phase conductor (~20 W), challenging the traditional design practice of neutral undersizing. To address these safety issues, this study proposes a novel neutral-to-phase current ratio index (k_N) and a proactive decision matrix for Building Management Systems (BMS). Unlike traditional mitigation strategies that rely on static hardware oversizing, passive filters, or specialized transformers, the proposed approach offers a dynamic, cost-effective, and software-driven solution that can be easily integrated into the existing automation infrastructure of modern Smart Buildings. The model identifies a critical tipping point at a 3rd harmonic content of 35.3%, where k_N ≥ 1. By continuously monitoring the k_N parameter, the proposed algorithm enables a transition from passive protection to active power management, triggering automated responses to prevent insulation degradation and mitigate fire hazards.

Due to the human needs of energy, there is a need to apply new technologies in energy conversion to supply the demand of clean and cheap energy in the context of environmental issues. Renewable energy sources like solar energy has one of the highest potentials. In this paper, solar panel is the key part of a photovoltaic system which converts solar energy to electrical energy. The purpose of this paper is to give a MATLAB/ Simulink simulation for photovoltaic module based on the one-diode model of a photovoltaic cell made of polycrystalline silicon. This model reveals the effect of the ambient temperature and the heating of the panel due to the solar infrared radiation. Also the measurements on the solar cell exposed to solar radiation can confirm the simulation.