Implementation of hybrid optimized battery controller and advanced power management control strategy in a renewable energy integrated DC microgrid.

In Renewable Energy (RE) integrated DC Microgrid (MG), the intermittency of power variation from RE sources can lead to power and voltage imbalances in the DC network and have an impact on the MG's operation in terms of reliability, power quality, and stability. In such case, a battery energy storage (BES) technology is widely used for mitigating power variation from the RE sources to get better voltage regulation and power balance in DC network. In this study, a BES based coordinated power management control strategy (PMCS) is proposed for the MG system to get effective utilization of RE sources while maintaining the MG's reliability and stability.

A random subspace ensemble classification model for discrimination of power quality events in solar PV microgrid power network.

This study proposes SVM based Random Subspace (RS) ensemble classifier to discriminate different Power Quality Events (PQEs) in a photovoltaic (PV) connected Microgrid (MG) model. The MG model is developed and simulated with the presence of different PQEs (voltage and harmonic related signals and distinctive transients) in both on-grid and off-grid modes of MG network, respectively. In the pre-stage of classification, the features are extracted from numerous PQE signals by Discrete Wavelet Transform (DWT) analysis, and the extracted features are used to learn the classifiers at the final stage.

Marine predators algorithm for solving single-objective optimal power flow.

This study presents a nature-inspired, and metaheuristic-based Marine predator algorithm (MPA) for solving the optimal power flow (OPF) problem. The significant insight of MPA is the widespread foraging strategy called the Levy walk and Brownian movements in ocean predators, including the optimal encounter rate policy in biological interaction among predators and prey which make the method to solve the real-world engineering problems of OPF. The OPF problem has been extensively used in power system operation, planning, and management over a long time.

Development of Graphene Oxide-Based Nonedible Cottonseed Nanofluids for Power Transformers.

Sustainable materials, such as vegetable oils, have become an effective alternative for liquid dielectrics in power transformers. However, currently available vegetable oils for transformer application are extracted from edible products with a negative impact on food supply. So, it is proposed in this study to develop cottonseed oil (CSO) as an electrical insulating material and cooling medium in transformers.

An Efficacious Multi-Objective Fuzzy Linear Programming Approach for Optimal Power Flow Considering Distributed Generation.

This paper proposes a new formulation for the multi-objective optimal power flow (MOOPF) problem for meshed power networks considering distributed generation. An efficacious multi-objective fuzzy linear programming optimization (MFLP) algorithm is proposed to solve the aforementioned problem with and without considering the distributed generation (DG) effect. A variant combination of objectives is considered for simultaneous optimization, including power loss, voltage stability, and shunt capacitors MVAR reserve.