Department of Electrical and Electronics Engineering
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Item Digital twin simulation and comparative study to understand the microgrid operation and control(IEEE, 2025-01) Mathur, Hitesh Datt; Gautam, Aditya R.Solar photovoltaic (PV) microgrid (MG) systems are the future of the growing electrical industry. However, these systems have a dependency on the environment. To mitigate this dependency, better control and technologies are required. The digital twin (DT) technology can be utilized to make these MGs more sustainable and promising. In this paper, the DT of the installed MG has been developed on the Simulink platform. The irradiance data, and load power consumption data have been used as input for the DT of the MG. Moreover, it is found that the DT of the MG is working stably with the given data. On the output side, the grid power data of the physical MG has been compared with the output grid power of DT. Further, it has been found that the solar power generation, load power consumption data, and grid power data have matched the results of the physical MG.Item Techno-economic and reliability assessment of an off-grid solar-powered energy system(Elsevier, 2024-10) Mathur, Hitesh Datt; Gautam, Aditya R.In the current era of the world, electricity has become a basic need of every individual. Therefore, the global energy demand has doubled from 77 trillion kWh to nearly 155 trillion kWh since 1980. However, despite the rising energy demand in developing countries, the per capita energy consumption only grew by about 14% globally. It is mainly because of the rural and remote areas where grid supply infrastructure is unavailable or inaccessible. Therefore, a solar-based microgrid (MG) can be considered an alternative energy solution. These MGs with energy storage support can be considered a viable solution because of the intermittent nature of solar photovoltaic (PV). In this regard, this paper describes the design, development, and deployment of a solar rooftop microgrid (SRMG) at the commercial building of BITS Pilani, India. Further, a comprehensive economic analysis is performed using a novel method of levelized cost of energy (LCOE) and payback period, and the results are compared with the traditional method's results. In order to improve the reliability of the SRMG, a demand side management (DSM) strategy is developed and implemented. It can effectively cater the unbalance between load and generation by shifting the non-critical loads to unused solar PV generation hours. It was found from the results that a significant energy of BESS is conserved which is reflected by the high state of charge (SOC) value. The developed design, economic analysis, and proposed DSM make the SRMG an economical and reliable energy solution.Item Development of a Novel Strategy with Electrical Vehicles to Mitigate Frequency Aberration in Microgrid(IEEE, 2018) Mathur, Hitesh DattPower system complexity is growing rapidly with changing scenario of load characteristic. Microgrid is a feasible solution to cater to varying load for maintaining power quality parameters especially frequency and voltage. The microgrid, consisting of different types of intermittent sources and loads, is liable to a substantially high frequency aberration. This needs to be mitigated at a faster rate in order to supply quality power supply to consumers. This paper focuses on development of a novel control strategy for quick active power support by electric vehicles (EV) to suppress frequency deviation caused due to fluctuating load. This approach senses the frequency change and communicates with EV aggregator to supply required amount of active power to microgrid. It is simulated on MATLAB/Simulink platform and results obtained are encouraging in terms of critical parameters i.e. settling time and peak over/undershootItem Digital twin of a commercial building microgrid: Economic & Environmental sustainability analysis(IEEE, 2022) Mathur, Hitesh DattDigital twin of a commercial building microgrid: Economic & Environmental sustainability analysis - CentraleSupélec Accéder directement au contenu Accéder directement à la navigation Nouvelle interface Toggle navigation HAL Accueil Dépôt Je dépose Questions pratiques Questions juridiques C'est quoi l'OA ? Consultation Consultation par période Consultation par auteurs Consultation par collections Outils Créer son IdHAL et CVHALItem Optimal energy management in microgrid including stationary and mobile storages based on minimum power loss and voltage deviation(Wiley, 2021-10) Mathur, Hitesh Datt; Mishra, PuneetThe grid-connected microgrid (MG) may depend on the utility grid (UG) during peak load hours to meet its unequaled load demand. Also, the rapid increase in penetration of plug-in hybrid electric vehicles (PHEV) affects the system's stability and the load demand. Therefore, it is an indisputable fact that MG demands, an effective energy management strategy to manage the peak load that occurred due to PHEV charging. To address this challenge, an optimal energy management strategy (OEMS) is proposed that aims at maximum utilization of DERs, promotes energy trading, and diminishes the dependency of MG on UG. It is achieved by optimizing the energy exchanged between MG and UG with simultaneously minimizing the active power losses (APL) and voltage deviation (VD) of a MG. Further, a state flow-based coordinated charging/discharging scheduling algorithm is also proposed to improve the performance, lifetime, and utilization of an energy storage system. The performance of OEMS is evaluated for different PHEV penetration levels (EVPL) and simulation results are compared with the recently reported strategy. The obtained results reveal that the proposed OEMS is superior to other strategy as it fulfills the MG's load with the minimum APL and VD and by optimally feeding energy to the UG it increases the MG operator's (MGO) profit in the range of 8.4%–13%. Lastly, the peak load management of MG is achieved and the efficacy of OEMS is further improved by introducing Governed charging/discharging mode of PHEVs in the system. The economic analysis discloses that OEMS with GCDM has increased the MGO's profit by 10.8%–29.5% depending on EVPL.Item Frequency Excursion Mitigation in a Multi-source Islanded Energy System Using Meta-Heuristic Optimization Strategies(IEEE, 2020) Mathur, Hitesh DattDistributed Energy Resources and Electric vehicles are getting more popular in the energy market. They are emerging as promising concepts that can bring a revolution in the field of energy resources and transportation systems. The integration of different renewable energy resources and electric vehicles leads to a comprehensive microgrid (MG). It is a fact that an increase in power demand leads to a drop in power frequency and vice-versa, which adversely affects the power quality of the system. Therefore, the primary idea of this research work is to regulate frequency by controlling the wind power and available EV power. In this paper, a detailed MG model is simulated in MATLAB/Simulink with wind and EV as one of the sources using fractional order PID (FOPID) controller. Further, parameters of FOPID controller is optimized by using Ant Colony Optimization(ACO) and Particle Swarm Optimization (PSO). The frequency responses, wind power, and EV power results are compared for three cases; FOPID without optimization, ACO based FOPID, and PSO based FOPID. The generalized wind model and total energy model (TEM) are used for simulating wind source and EV, respectively. Optimizer based FOPID controller provides a better response for the defined objective function.Item Forecasting of solar and wind power using LSTM RNN for load frequency control in isolated microgrid(Taylor & Francis, 2020) Mathur, Hitesh Datt; Bhanot, SurekhaRenewable sources such as solar PV and wind are stochastic in nature, hence their integration with emerging isolated microgrid (MG) is challenging especially with regards to stability issues. An accurate prediction model of wind and solar sources is necessary to analyze the uncertainty in MG system and to encourage the reliable participation of wind and solar power in the energy market. The advancement in deep learning methods has made it possible to develop a multi-step forecasting model unlike shallow neural networks (SNNs). The time series forecasting using SNN and Recurrent Neural Network (RNN) suffers from the problem of vanishing/exploding gradient while training. To eliminate this problem the long short-term memory (LSTM) RNN has been used in this study for wind speed and solar irradiance prediction. The forecasted solar and wind power is applied to analyze the load frequency behavior and the response of nonrenewable sources for sudden rise and fall in load power demand and PI controller is used to mitigate frequency deviation to ensure the stability of the MG power system.