In recent days, aiming for power generation with less carbon emission, led to the high penetration of renewable energy into the distribution grid. To improve the intermittency caused by renewables and to increase the grid flexibility, grid integrated Energy Storage Units (ESUs) are proposed as the promising solution in the literature. However, considering the investment cost, ESUs are optimally placed by satisfying the network electrical constraints. On the other hand, consideration of environmental impacts and other practical constraints are also equally important. Therefore, in this article, on top of grid performance parameters, realistic parameters that may affect the location and its size such as (1) environmental impact, (2) land requirement & its associated cost for ESU installation and (3) renewable purchase obligation are formulated in the objective function. Decision making on ESU installation is a planning activity, which follows uncertainty. Consequently, it is essential to model the uncertainty parameters into the objective function, for better planning. In this article, optimal planning of hybrid ESUs based on realistic parameters along with uncertainty is addressed. For this study, a practical 156-bus distribution system of Dehradun district, India is considered. From the results obtained, it is evident that, formulating hybrid ESU constrained with the environmental impact has significantly decreased the emission of CO2 with maximum grid stability.

The purpose of microgrids is to improve system flexibility and resilience during normal and emergency conditions. The ceaseless load growth mandates to increase microgrid's capacity, thereby improving the system flexibility and resilience. However, capacity expansion requires significant investments, making it essential to identify the optimal capacity of energy resources. The methodologies proposed in the literature identifies the microgrid's capacity with an assumption of investments with a single installment. This way of theoretical approach leads to unrealistic solutions. Besides, microgrid's participation in a flexible market will enhance its performance both in commercial and technical aspects. Therefore, this paper proposes a realistic framework with the concept “expansion through time” inspired by “Real Options Theory.” This framework includes practical parameters like resource & load uncertainty, physical space required to install, revenue generated by resources, and maximum demand penalty, on top of electrical parameters; constrained with significant return in investments to improve the overall savings. In addition, this paper proposes a market participation model for microgrid, which defines a bidding process with two components, such as regular and flexible portions under both normal and extreme conditions. This study considers renewable-based energy resources like solar-photovoltaic plants (SPPs) and battery energy storage systems (BESSs) as microgrids' energy resources. The system chosen for testing the efficacy of the proposed framework is a real-world active-microgrid of Malta College of Arts, Science and Technology (MCAST), located on an island.

Natural hazards, such as storms, increasingly threaten interconnected critical infrastructure systems (CISs), necessitating integrated resilience strategies that account for interdependencies, cascading failures, and dynamic recovery. To contextualize the research within existing developments, a bibliometric analysis is conducted, revealing key trends and gaps in hazard-resilient CIS modeling. This article proposes a comprehensive framework that models interdependent behavior across power, telecommunication, and transportation networks under evolving storm conditions. A dedicated hazard engine captures the spatiotemporal progression of storms and simulates their direct and cascading impacts across infrastructure layers. The framework incorporates a dynamic, safety-aware restoration strategy that deploys repair crews and mobile energy resources in alignment with real-time storm conditions. The proposed framework is demonstrated through a case study inspired by the realistic infrastructure of Cyprus. Results show the model's ability to capture cascading disruptions, illustrate the operational effectiveness of dynamic restoration, and provide insights from sensitivity and tradeoff analyses.

The quest for electrification of railway tracks is very high at developing countries, with a very high ratio of population per kilometre length of railway track. India has electrified almost 50% of its track length and aiming 3000 km track electrification every year. Presently in Indian traction system, all the fault locating methods and power factor correction methods for AC high voltage line are based on the conventional model of railway Overhead Equipment (OHE). The conventional OHE model does not include the effect of self-generated reactive power at the geographically challenged area. This paper explains, how the variations in parasite capacitance of OHE adversely affect the prevailing conventional power factor improving methods; after monitoring the active power, apparent power, leading reactive power injected to improve the power factor of AC high voltage traction system for one calendar year, at two different Traction Sub Stations (TSS). Further simulation of 61 km track with actual mixed geographical terrain to validate the experimental results and to develop a new power factor correction algorithm has been done. The proposed algorithm has been implemented on one TSS of Southern Indian Railways division, and it turns out in reducing penalty around 2.5 million Indian rupees per year, paid by sampling region TSS.