Eakbodin Gedkhaw, Nantinee Soodtoetong^*

Energy Engineering, Vol.122, No.11, pp. 4349-4363, 2025, DOI:10.32604/ee.2025.068577 - 27 October 2025

Abstract This research aimed to study the efficiency of solar power system in controlling hydro-organic smart farming system in closed greenhouse by developing an off-grid system consisting of 450 W solar panel, MPPT charge controller, 500 W Pure Sine Wave inverter and 2150 Ah Deep Cycle batteries in series as 24 V system to supply power to automatic control devices, including temperature, humidity, pH sensor and water pump in NFT (Nutrient Film Technique) hydroponic system using organic nutrient solution. The test result between 08:00–17:00 or 30 days found that the system can produce a maximum of… More > Graphic Abstract

Siwakorn Banluesapy, Mahasak Ketcham^*, Montean Rattanasiriwongwut

Energy Engineering, Vol.122, No.10, pp. 4261-4296, 2025, DOI:10.32604/ee.2025.068422 - 30 September 2025

Abstract Traditional agricultural irrigation systems waste significant amounts of water and energy due to inefficient scheduling and the absence of real-time monitoring capabilities. This research developed a comprehensive IoT-based smart irrigation control system to optimize water and energy management in agricultural greenhouses while enhancing crop productivity. The system employs a sophisticated four-layer Internet of Things (IoT) architecture based on an ESP32 microcontroller, integrated with multiple environmental sensors, including soil moisture, temperature, humidity, and light intensity sensors, for comprehensive environmental monitoring. The system utilizes the Message Queuing Telemetry Transport (MQTT) communication protocol for reliable data transmission and… More >

Asrar Mahboob¹, Muhammad Rashad¹, Ghulam Abbas¹, Zohaib Mushtaq², Tehseen Mazhar^3,*, Ateeq Ur Rehman^4,*

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3805-3823, 2025, DOI:10.32604/cmc.2025.067615 - 23 September 2025

Abstract This paper presents a novel blockchain-embedded cybersecurity framework for industrial solar power systems, integrating immutable machine learning (ML) with distributed ledger technology. Our contribution focused on three factors, Quantum-resistant feature engineering using the UNSW-NB15 dataset adapted for solar infrastructure anomalies. An enhanced Light Gradient Boosting Machine (LightGBM) classifier with blockchain-validated decision thresholds, and A cryptographic proof-of-threat (PoT) consensus mechanism for cyber attack verification. The proposed Immutable LightGBM model with majority voting and cryptographic feature encoding achieves 96.9% detection accuracy with 0.97 weighted average of precision, recall and F1-score, outperforming conventional intrusion detection systems (IDSs) by… More >

S. M. Rezaul Karim^1,2, Md. Shouquat Hossain^1,3, Khadiza Akter¹, Debasish Sarker⁴, Md. Moniul Kabir ², Mamdouh Assad^5,*

Energy Engineering, Vol.122, No.8, pp. 3041-3054, 2025, DOI:10.32604/ee.2025.066867 - 24 July 2025

Abstract Knowing the influence of the size of datasets for regression models can help in improving the accuracy of a solar power forecast and make the most out of renewable energy systems. This research explores the influence of dataset size on the accuracy and reliability of regression models for solar power prediction, contributing to better forecasting methods. The study analyzes data from two solar panels, aSiMicro03036 and aSiTandem72-46, over 7, 14, 17, 21, 28, and 38 days, with each dataset comprising five independent and one dependent parameter, and split 80–20 for training and testing. Results indicate… More > Graphic Abstract

Zahrah F. Hussein^1,2,*, Abas Ramiar¹, Karima E. Amori³

Frontiers in Heat and Mass Transfer, Vol.23, No.3, pp. 765-817, 2025, DOI:10.32604/fhmt.2025.059507 - 30 June 2025

Abstract The deficiency of potable water resources and energy supply is emerging as a significant and concerning obstacle to sustainable development. Solar and waste heat-powered humidification dehumidification (HDH) desalination systems become essential due to the severe impacts of global warming and water shortages. This problem highlights the need to apply boosted water desalination solutions. Desalination is a capital-intensive process that demands considerable energy, predominantly sourced from fossil fuels worldwide, posing a significant carbon footprint risk. HDH is a very efficient desalination method suitable for remote areas with moderate freshwater requirements for domestic and agricultural usage. Several… More >

Luki Septya Mahendra¹, Rezi Delfianti^2,*, Karimatun Nisa¹, Sutedjo¹, Bima Mustaqim³, Catur Harsito⁴, Rafiel Carino Syahroni⁵

Energy Engineering, Vol.122, No.7, pp. 2695-2717, 2025, DOI:10.32604/ee.2025.063807 - 27 June 2025

Abstract Ensuring the reliability of power systems in microgrids is critical, particularly under contingency conditions that can disrupt power flow and system stability. This study investigates the application of Security-Constrained Optimal Power Flow (SCOPF) using the Line Outage Distribution Factor (LODF) to enhance resilience in a renewable energy-integrated microgrid. The research examines a 30-bus system with 14 generators and an 8669 MW load demand, optimizing both single-objective and multi-objective scenarios. The single-objective optimization achieves a total generation cost of $47,738, while the multi-objective approach reduces costs to $47,614 and minimizes battery power output to 165.02 kW.… More >

Caifeng Wen¹, Feifei Xue^1,*, Hongliang Hao², Edwin E. Nyakilla², Ning Yang^1,*, Yongsheng Wang³, Yuwen Zhang²

Energy Engineering, Vol.122, No.4, pp. 1511-1529, 2025, DOI:10.32604/ee.2025.060810 - 31 March 2025

Abstract This paper presents a new capacity planning method that utilizes the complementary characteristics of wind and solar power output. It addresses the limitations of relying on a single metric for a comprehensive assessment of complementarity. To enable more accurate predictions of the optimal wind-solar ratio, a comprehensive complementarity rate is proposed, which allows for the optimization of wind-solar capacity based on this measure. Initially, the Clayton Copula function is employed to create a joint probability distribution model for wind and solar power, enabling the calculation of the comprehensive complementarity rate. Following this, a joint planning… More >

Zhihui Feng¹, Jun Zhang¹, Jun Lu¹, Zhongdan Zhang¹, Wangwang Bai¹, Long Ma¹, Haonan Lu², Jie Lin^2,*

Energy Engineering, Vol.122, No.4, pp. 1531-1560, 2025, DOI:10.32604/ee.2025.060795 - 31 March 2025

Abstract In the background of the low-carbon transformation of the energy structure, the problem of operational uncertainty caused by the high proportion of renewable energy sources and diverse loads in the integrated energy systems (IES) is becoming increasingly obvious. In this case, to promote the low-carbon operation of IES and renewable energy consumption, and to improve the IES anti-interference ability, this paper proposes an IES scheduling strategy that considers CCS-P2G and concentrating solar power (CSP) station. Firstly, CSP station, gas hydrogen doping mode and variable hydrogen doping ratio mode are applied to IES, and combined with… More >

Yuqiao Liu¹, Chen Pan¹, YeonJae Oh^2,*, Chang Gyoon Lim^1,*

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 4593-4629, 2025, DOI:10.32604/cmc.2025.061196 - 06 March 2025

Abstract Virtual Power Plants (VPPs) are integral to modern energy systems, providing stability and reliability in the face of the inherent complexities and fluctuations of solar power data. Traditional anomaly detection methodologies often need to adequately handle these fluctuations from solar radiation and ambient temperature variations. We introduce the Memory-Enhanced Autoencoder with Adversarial Training (MemAAE) model to overcome these limitations, designed explicitly for robust anomaly detection in VPP environments. The MemAAE model integrates three principal components: an LSTM-based autoencoder that effectively captures temporal dynamics to distinguish between normal and anomalous behaviors, an adversarial training module that… More >

Bernard Bayangbe^1,*, Ababacar Thiam^1,2, El hadji I. Cissé², Kory Faye¹

Energy Engineering, Vol.122, No.3, pp. 943-969, 2025, DOI:10.32604/ee.2025.060273 - 07 March 2025

Abstract Concentrating Solar Power (CSP) is one of the most promising solar technologies for sustainable power generation in countries with high solar potential, like Chad. Identifying suitable sites is of great importance for deploying solar power plants. This work focuses on the identification of potential sites for the installation of solar power plants in Chad as well as a comparative analysis using the Analytical Hierarchy Process (AHP), Fuzzy Analytical Hierarchy Process (FAHP), and Full Consistency Method (FUCOM). The results show that 35% of the Chadian territory, i.e., an area of 449,400 km², is compatible with the implementation… More >