The lifespan of overhead transmission conductors is influenced by various factors, including design, maintenance, and operating conditions. Prolonged exposure to high temperatures, particularly near maximum design values, can significantly age transmission lines (TLs). The dynamic thermal rating (DTR) system, an advanced technology that increases TL capacities, can contribute to these stringent conditions. DTR overlays a cyber layer with communication and control systems onto the physical network, transforming it into a cyber-physical network. Currently, the increased risk of TL ageing associated with DTR, and the cyber layer’s functionality lack a unified framework for quantification. This study introduces a novel framework that considers the cyber layer’s network topology and its impact on TL ageing due to DTR implementation. It also proposes the implementation of system integrity protection schemes (SIPS) within the framework. SIPS detects abnormal conditions from DTR deployment, like excessive line loading, and takes corrective actions to optimize DTR system’s performance. The study employs a Sequential Monte Carlo Simulation (SMCS) technique on a modified cyber-physical IEEE RTS-79. The study reveals that topologies like double ring and mesh, cause higher line ageing indices compared to line and star topologies. ETNA values remain relatively stable across the network topologies within a year, suggesting minimal short-term impact on transmission line ageing. However, cumulative effects over several years can potentially reduce lifespan. SIPS can slow network ageing by up to 5hr/yr, but their contingencies can cause the opposite effect. Nonetheless, a reliable SIPS can maintain an ETNA value of 101hr/yr without increasing load curtailment.

In this paper, an innovative transactive energy approach is proposed as viable option for coordinated distribution system planning across a certain horizon. The proposed approach is evaluated across a multi-looped (meshed) test system and is implemented with load growth having prosumers participating in the electrical market in transactive energy system aiming at evaluation on techno-economic basis. Apart from prosumer sensitivity analysis, evaluations have been carried across reducing total production cost of energy, reduction in per unit price, active power losses. Whereas improving voltage profile, cost of scheduling and consumer per kWh purchase and sales in comparison with traditional counterpart. The proposed framework includes optimization algorithm aiming at sources scheduling and IEEE 69 system for validation. The algorithm minimizes cost, maximizes energy efficiency, increases renewable energy mix and reduces consumers cost of energy purchase. Reduction of 51.44 % in cost of energy is achieved, whereas loss reduction of 12.6% is achieved. The comparison of IEEE 69-bus base case with the 10 %, 15% and 20% transactive energy applied with simulations to evaluate performance parameters that will directly benefit both prosumers and utility alike in-terms of low bills and further reduction of stress on the grid amid load growth across multiple years.

Smart grid development is required to accommodate the integration of renewable generation resources into systems. Energy management is improved by smart devices that allow two-way communication. A multi-criteria decision analysis framework is used in this study to provide a model for decision making. Prior to communicating with the energy market aggregator, it considers the human-oriented viewpoint to offer an interface with a smart device within smart grid system. In this work, for decision-making optimization, the proposed framework has utilized while considering six criteria and have evaluated across three multi-criteria decision-making techniques. To assess criteria, a thorough investigation has been undertaken across five load classes aiming at demand side management (DSM) options from high load class to lowest load class and concerned load-generation balance. The findings of this research make it convenient for the framework that communicates the actual results of the energy system and the energy markets aggregator for an energy management plan. The results have been evaluated with sensitivity analysis across five DSM options and trade-off studies have been carried out usefulness in aiding effective decision-making procedures in practice. Finally, this research offers a cost-effective, clean, and effective system configuration aimed at consumer preferences.

Electrical grids are one of the major sources of emissions of greenhouse gases (GHG), which are harmful to the environment because they contribute to global warming. As the geographical, environmental, political, and policy constraints are different, policies and research frameworks from developed countries cannot be used directly in developing countries. This paper suggests a completely integrated quantification approach (IQA) and sub-methodologies, such as SM1, SM2, and SM3, that consider the limitations, evaluates the effects, and suggest a way to deal with climate change problems on the power grid. From the perspective of renewable energy (RE) integration and GHG emissions (mainly CO₂), the proposed approach addresses the limitations in the policy framework extending to 2030. In addition, the effects of the changes in the ambient temperature, from 0.5 °C to 2 °C, have been examined for thermal power generation and transformers. Lastly, the proposed method considers how energy-efficient devices (EEDs) affect the residential load sector. The results show that households used 10.7% less energy and their costs decreased significantly. This work’s quantitative approach gives a specific way to reduce the carbon footprint of the electrical grid.