Flow direction algorithm based optimal power flow for isolated microgrid integrated with renewable energy sources Himanshu Raj, Supriya Jaiswal, Ankur Maheshwari Wind Engineering, 2026 This study explores microgrids as small, independent electrical systems that reduce emissions, lower costs, and improve the efficiency and reliability of renewable energy sources (RES). It focuses on solving the optimal power flow (OPF) problem in isolated microgrids to minimize production costs, integrating variable RES like solar photovoltaic systems and wind turbines with a stable small hydropower plant. A novel physics-based Flow Direction Algorithm (FDA), inspired by the D8 hydrological model, is introduced, offering superior precision compared to bio-inspired metaheuristics. The FDA balances global and local search for accurate solutions. Monte Carlo simulation models uncertainties in wind speeds and solar irradiance. Validated on IEEE 33-bus, 69-bus, and 15-bus systems, the FDA outperforms algorithms like Whale Optimization, Ant Lion, Dung Beetle, and Walrus Optimization in efficiency and reliability, advancing microgrid performance.
UPQC Controller to Improve Power Quality in Smart GRID Anushka Dogra, Supriya Jaiswal 5th IEEE International Conference on Sustainable Energy and Future Electric Transportation Sefet 2025, 2025 In a resilient and sustainable energy landscape, the integration of solar photovoltaic arrays and battery energy storage - due to their intermittency and reliance on power-electronic interfaces - causes voltage instability and current harmonics at the grid interface.The suggested architecture showed a spectacular restoration of voltage to its nominal waveform, a drastic reduction in overall harmonic distortion of current and a smooth adaptation of changing generation and load needs through time-domain simulations under extreme distortion scenarios. By weaving together advanced control theory, intelligent algorithm design, and holistic system modeling, this work illuminates a path toward harmonized integration of renewable energy sources, ensuring both reliability and efficiency for future distribution networks.
Energy Management in Grid-Connected Microgrid by using Hippopotamus Optimization Algorithm Himanshu Raj, Supriya Jaiswal 2025 IEEE 4th International Conference on Smart Technologies for Power Energy and Control Stpec 2025 Conference Report, 2025 Microgrids that are connected to the larger grid have emerged as a result of smart grid technology and the inclusion of renewable energy sources as an effective means of enhancing energy resilience and sustainability. Using the Hippopotamus Optimization Algorithm (HOA), this study suggests a new way to enhance grid-connected microgrids' energy management and reduce operational costs. To address the energy management issue in MGs, HOA is a newly introduced metaheuristic technique inspired by the unique behaviours of hippopotamuses, aiming to efficiently solve complex optimization problems. Through its trinary-phase model encompassing exploration, exploitation, and evasion, HOA demonstrates a strong capability to strike a balance between local refining and global search. In this investigation, microgrid incorporates distributed generation (DG) sources, wind turbines (WT), microturbines (MT), photovoltaic systems (PV), and fuel cells (FC). The primary motive is to minimize the microgrid operating expenses. A traditional microgrid is used to assess the suggested method's efficacy, and the simulation results achieved through the Hippopotamus Optimization Algorithm are compared with outcomes from various optimization techniques.
Optimized Power Flow Management in High Renewable and PEV Penetration Scenarios Using Multi-Verse Optimizer Ankur Maheshwari, Supriya Jaiswal, Himanshu Raj 2025 IEEE 4th International Conference on Smart Technologies for Power Energy and Control Stpec 2025 Conference Report, 2025 The increasing integration of renewable energy sources (RESs), such as wind and solar power plants, along with plug-in electric vehicles (PEVs), poses challenges in optimal power flow (OPF) management due to their inherent intermittency and the unpredictable charging/discharging behaviour of PEVs. Ensuring efficient and cost-effective OPF is crucial as power systems transition toward low-carbon, decentralized networks. This paper presents an OPF management framework for the IEEE 57-bus system under two contrasting operational scenarios: a conventional configuration with only thermal generators and a high-penetration configuration incorporating largescale RESs and PEVs. The Multi-Verse Optimizer (MVO), a metaheuristic algorithm inspired by cosmological theories, is employed to solve the OPF problem with the objective of minimizing total operating cost over a 24-hour scheduling horizon. The simulation results show that integrating renewables and plugin electric vehicles (PEVs) into the 57-bus system substantially enhances economic efficiency. Compared to the conventional case, the high-penetration scenario achieves lower peak operating costs, smoother dispatch patterns, and improved cost stability, particularly during mid-day and evening demand peaks. The study confirms that MVO-based OPF offers a powerful tool for managing modern, renewable-rich systems while maintaining grid reliability and economic performance.
Future trends and scope Supriya Jaiswal, Ajay Kumar, Sanjeevikumar Padmanaban Development of Electric Vehicles in Smart Grid Concepts, 2025
A review of energy management strategy and forecasting techniques in multi microgrids Himanshu Raj, Supriya Jaiswal, Ankur Maheshwari International Journal of Ambient Energy, 2025 Microgrids have indeed escalated substantial interest in the latest time, primarily owing to their capacity to improve energy resiliency, efficiency, and sustainability. Multi microgrid systems have come out as an optimistic solution in addressing complex power distribution challenges. Because of widespread use of distributed generators, fluctuating weather patterns and sporadic natural energy outputs make it difficult to offer local clients a steady, dependable power supply. Similarly, seasonal variations and human behaviour in response to energy pricing variations influence the amount of electricity consumed. It is vital to incorporate energy management systems and forecast approaches to resolve unit commitment. The aim of this article is to offer a review of the current developments in Energy management strategies and forecasting approaches. First, a broad overview of the field's fundamentals is provided for microgrids. Then, a comprehensive literature assessment of the various techniques used for energy management optimisation and forecasting in microgrid applications is carried out. It underscores the growing relevance of multi-microgrid systems in situations where multiple interconnected microgrids can efficiently share resources and maximise energy consumption and generation.
Electric vehicle global market survey Sukriti Tiwari, Paramjeet Singh Jamwal, Supriya Jaiswal Development of Electric Vehicles in Smart Grid Concepts, 2025 This survey explores the dynamics of the global electric vehicle (EV) market, analyzing key trends, consumer preferences, and market drivers shaping its growth. With the rise of environmental awareness and advancements in battery technology, EVs have gained significant traction in recent years. The study delves into various aspects, including adoption rates, charging infrastructure development, government incentives, and the impact of EVs on the automotive industry and the environment. By examining factors such as range anxiety, cost of ownership, and public perception, the survey offers insights into challenges and opportunities for EV manufacturers and stakeholders. Furthermore, it investigates regional variances, industry regulations, and the competitive landscape to provide a comprehensive overview of the EV market's current state and future prospects.
Single-Phase Pseudo-Open-Loop Grid Voltage Attributes Tracking Scheme Based on Nonadaptive Linear-Phase Filters Chandrasekaran S, Animesh Kumar Sahoo, Sandeep Negi, Supriya Jaiswal IEEE Transactions on Instrumentation and Measurement, 2025 In this article, an open-loop technique based on digital filtering is proposed for the extraction of single-phase grid voltage parameters. Furthermore, it proposes the combination of modulated sliding discrete Fourier transform (mSDFT) with three distinct frequency estimators known as: 1) linear phase-locked loop (LPLL); 2) two-point method; and 3) empirical method. Nonadaptive mSDFT is employed to provide the required fundamental orthogonal components rejecting the dc offset and harmonics. When the grid frequency drifts from its nominal value, to enhance harmonic rejection, two cascaded moving average filters (MAFs) (tuned to reject dominant harmonics) are included as prefilters. With off-nominal grid frequency, due to attenuation offered by these fixed-frequency filters, the amplitude and phase of the in-phase and quadrature components will be different from the input values. Furthermore, it was found that the ratio of peak values of these components is different for different frequencies and there exists a relation between this ratio and frequency deviation. Based on this finding, an algorithm for the estimation of frequency deviation and then to correct the amplitude and phase errors in a feed-forward manner is developed. It is revealed that the estimator relying on the empirical method provides faster settling with comparatively higher overshoots. LPLL and the two-point method achieve fewer overshoots at the cost of additional delay in the estimations. Finally, real-time experimental validations considering various grid abnormalities are provided to support the simulation outcomes.
IoT based Solar Photo Voltaic Fault Detection System Mridul Mridul, Bhuvnesh Vashishat, Anil Kumar, Rohit Kumar, Supriya Jaiswal 2023 International Conference on Computer Electronics and Electrical Engineering and their Applications Ic2e3 2023, 2023
Game Theory based EV Charge Scheduling: A Comprehensive Review Zaid Siddique, Supriya Jaiswal, Vaibhav Chaturvedi, Ankur Maheshwari 3rd IEEE International Virtual Conference on Innovations in Power and Advanced Computing Technologies I Pact 2021, 2021
