Journal of Advanced Research in Power Electronics and Power Systems

Performance Analysis of Solar Photovoltaic Generation System Equipped with IoT-Enabled Solar Power Inverters

2025-08-30T06:03:02+00:00

The Internet of Things is discovering new applications every day. One prominent use of these IoT-based technologies is in solar power generation inverters. These inverters are considered smart in comparison to non-Internet of Things (IoT) inverters. This paper explores the use of IoT-based solar inverters in large-scale solar power generation. A 210-kW solar power plant, designed and analyzed using PVsyst^® software to meet the energy needs of an industry, was selected for study at the Metoda location in Rajkot, Gujarat, India. A detailed technical and performance analysis of this industrial-scale solar power plant is performed. Performance ratios, daily output charts, monthly and yearly energy yields, and an indepth review of the characteristics of IoT-based solar inverters are also included. Results are also presented for the selected industrial site, which has a 210-kW solar power generation capacity.

Automation of Hydroponic Systems using Micro-controllers

2026-01-20T11:33:14+00:00

Ever-increasing population and desertification of the evergreen area lead researchers to think of different ways of farming. Though there is enough availability of agricultural land, the farmers have low land holdings. Hydroponics is the alternative way of farming to produce the crop despite unsuitable environmental conditions. The requirement of human involvement in farmland is not possible due to extreme weather conditions; thus, automation plays an important role. Hydroponics systems are capable of using vertical places which remain unused. The system is automated with a microcontroller, input sensors and output sensors. Our hydroponic system is capable of switching from 12-volt experimental devices to 240-volt actual farm utility devices. The microcontroller will send the information to the local server by the in-built ESP32 Wi-Fi for remote supervision and data analysis. This paper shows a business model for automated hydroponic farming using the device IAIHS. A sampling of the desired crop was planted with input parameters to get maximum output. Switching the same device with the same input parameters in the actual hydroponic system, which saves time and also minimises the probability of losses.

Detection of Denial-of-Wallet Attacks Using Deep Learning Models

2026-01-21T07:23:54+00:00

Due to their ease and security, digital wallets are becoming more and more popular; yet, they are also susceptible to a new type of malware called Denial of Wallet (DoW) attacks. These attacks cause major discomfort and financial danger by interfering with users’ access to their digital funds. Three models—Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and Feedforward Neural Network (FNN)—are used in this paper’s deep learning-based method of DoW attack detection to find attack patterns in network traffic data. The LSTM model had the highest accuracy of 96.19 per cent and the lowest validation loss of 0.0636 over 50 epochs after each model was trained and assessed for accuracy, loss, and validation metrics. Effectiveness was also shown by the CNN and FNN models, which achieved accuracies of 88.06 per cent and 90.01 per cent, respectively. These results demonstrate the potential of deep learning models—in particular, LSTM—for reliable DoW attack detection in real-time network settings, which would improve security and dependability for users of digital wallets.

Reduction of Voltage Fluctuations in the Hybrid Solar-Wind energy-based power systems using FACTS devices

2026-01-21T11:51:41+00:00

Solar and wind power systems are becoming more popular at this time. The system becomes unstable as the number of unconventional sources of energy grows. The two non-conventional energy sources must be improved. The extensive work that has been done in this area. In this paper, the simulation model for a solar or wind power system is explained. The voltage instability is mitigated in the power system by using FACTS devices. ETAP software is employed to perform the simulation. FACTS devices, such as Static Synchronous Compensators (STATCOM) and Unified Power Flow Controllers (UPFC), serve as a critical strategy to enhance system reliability. These devices facilitate dynamic reactive power control, thereby stabilising voltage levels and improving the overall performance of the power system. Our findings demonstrate that by strategically incorporating FACTS devices, we can significantly reduce the current electrical network's ability to carry alternative power sources in a more stable and reliable manner.