Xiaohui Wang^1,#, Aiqin Liu^2,#, Zechun Ma^3,#, Nien-Hwa Lai^4,*, Rui Ding^5,*

International Journal of Mental Health Promotion, Vol.28, No.6, 2026, DOI:10.32604/ijmhp.2026.078910 - 23 June 2026

Abstract Objectives: Chinese higher education faces rising depression rates amidst fragmented campus mental health services. This pilot study examined the feasibility and preliminary outcomes of implementing a standardized psychodrama program across multiple university sites. Methods: This single-arm study was conducted across three Beijing universities from September 2024 to January 2025. A total of 27 undergraduates completed an 8-week psychodrama intervention program comprising weekly 2.5-h sessions. A unified protocol was ensured through centralized facilitator training and cross-site supervision. Depressive symptoms were assessed using the Beck Depression Inventory-II at baseline, post-intervention, 3-month, and 6-month follow-ups. Retention rates were 93.8%… More >

Zahid Javid^1,2, Kush Lohana², Danial Murtaza², William Holderbaum^3,*

Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.080073 - 18 June 2026

Abstract This paper introduces a novel hybrid method for Power System State Estimation (PS-SE) that effectively integrates the strengths of Weighted Least Squares (WLS) and the Extended Kalman Filter (EKF) through an adaptive weighting mechanism. The proposed method addresses key challenges in modern PS-SE, including measurement uncertainties, bad data detection and handling, and convergence reliability. By incorporating an adaptive weighting mechanism, the hybrid approach dynamically adjusts estimation parameters based on the quality of the measurements, enabling it to maintain high accuracy for clean data while demonstrating exceptional resilience against outliers and noisy measurements. The performance of… More >

Jalpa Thakkar¹, Siddharth Shankar Mishra², V. Shanmugapriya³, Mohan Kolhe^4,*

Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.078267 - 18 June 2026

Abstract The big challenge in developing wind energy over the past century, which has focused on environmentally friendly production methods to meet the requirements of modern power systems, is the need for holistic architectures that can cope with variability, connection issues, and sector coupling far beyond conventional electricity-only models. This review offers a critically synthesized, process-level overview of progressive wind–hydrogen hybrids, offering a collective view of advancements in electrical layouts, hydrogen-driven conversion routes, and AI-driven control schemes. In contrast to previous surveys that consider these areas in isolation, we provide an explicit examination of the technical… More >

Xiaolan Li^1,2, Yanting Wang^1,2,*

Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.076417 - 18 June 2026

Abstract To address the operational challenges of power systems with high renewable penetration, this research targets the non-stationarity and stochasticity of wind power. A novel hybrid framework for probabilistic forecasting and risk assessment is proposed. Initially, Empirical Mode Decomposition (EMD) adaptively decomposes the raw power signal into multi-scale Intrinsic Mode Functions (IMFs) and a residual trend, effectively segregating temporal features and reducing complexity. These components are then fused with historical data to form a comprehensive input. The core predictor is a Bidirectional Gated Recurrent Unit (BiGRU) network enhanced with a Temporal Attention (TA) mechanism. The BiGRU… More >

Yuanxiang Luo, Xinmeng Pan^*, Xuyang Gao

Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.076019 - 18 June 2026

Abstract The integration of a high proportion of renewable energy sources via power electronic devices poses significant challenges to power systems. Their grid-connection characteristics differ considerably from those of synchronous generators, leading to a reduction in system inertia. Furthermore, the complex interactions between renewable energy units and the power grid substantially impact the transient stability of the system. Based on the virtual synchronous control characteristics of grid-forming wind turbines (GWT), this paper proposes an adaptive control method to enhance system transient stability. Firstly, a transient stability model for integrating GWT into conventional power systems is established,… More >

Biswanath Hajoary^1,*, Ranjay Das¹, Ganesh Roy², Daijiry Narzary³

Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.075305 - 18 June 2026

Abstract The increasing integration of photovoltaic systems into smart grids requires accurate evaluation of power conversion efficiency and output performance. In this context, Z Source Multilevel Inverters function as voltage boosting converters and offer a certain degree of fault tolerance. However, conventional control strategies such as proportional integral controllers and hybrid optimization-based methods including POA-RFA (Pelican Optimization Algorithm-Random Forest Algorithm) are limited in their ability to maintain dynamic stability, efficiency, and operational safety under varying solar irradiance and load conditions. This study proposes a safe and explainable Deep Q Network based intelligent switching control framework for… More > Graphic Abstract

Yingjie Su¹, Yubin Qiu², Zhuojun Dong¹, Jiying Liu^2,*, Bo Gao^1,3,*

Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2025.074454 - 18 June 2026

Abstract In response to the high energy consumption, large load fluctuations, and insufficient adaptability associated with conventional control strategies in industrial park heating and hot water systems, this paper studies a 15,000 m² factory office building in Jinan as its object of study. A photovoltaic-thermal integrated air-source heat pump system (PVT-ASHP) is developed. This system leverages its hardware parameter co-optimization and intelligent operational strategy control to perform cost reduction and efficiency increase, while focusing on the novel innovative high effectiveness of its operational strategies. The study first employs the Hooke-Jeeves algorithm to optimize key hardware parameters so… More > Graphic Abstract

Jiguang Wu¹, Qing Zhi^2,*, Jin Guan², Ruopeng Zhang², Lixia Wu², Shuhui Zhang², Caifeng Wen^3,4

Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2025.073914 - 18 June 2026

Abstract This paper proposes a hybrid energy storage control method that coordinates the minimum output of the wind–storage system and the SOC self-recovery capability, applied to stand-alone energy storage stations. Under the premise of meeting the wind power smoothing requirements, model predictive control (MPC) is employed to rapidly regulate the SOC and output of the energy storage system during the smoothing process, thereby enhancing its sustained and stable operation capability, and decomposing the original wind power into a direct grid-connected component and a hybrid energy storage smoothing component. Subsequently, the Northern Goshawk Algorithm-Improved Complete Ensemble Empirical… More >

Yun Yu¹, Li Lin^2,*, Ximing Zhang¹, Yang Yu³, Wei Zhang², Kai Cheng³

Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2025.073445 - 18 June 2026

Abstract Traditional transient stability preventive control calculation methods suffer from low computational efficiency, struggling to meet the real-time decision demands of increasingly large-scale power systems. Meanwhile, reinforcement learning-based preventive control approaches, which adopt an “offline training, online application” framework, show greater promise in preventive control. However, they still face challenges such as low computational efficiency in electromechanical transient simulation and insufficient decision robustness. Therefore, this paper proposes a power system predictive control strategy based on Generative Adversarial Proximal Policy Optimization (GA-PPO). Firstly, considering multiple constraints in transient stability operation, a power system preventive control model is… More >

Yansen Sun^1,2, Yi Ding³, Hualei Cui⁴, Yuanchao Hui⁵, Yupeng He^1,2,*

Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2025.072860 - 18 June 2026

Abstract Integrated energy systems (IES) are pivotal for achieving low-carbon transitions, yet their optimization under carbon constraints remains challenging. This paper proposes an optimal scheduling model for IES that synergistically combines power-to-gas coupled with carbon capture systems (P2G-CCS) and hydrogen-blended natural gas under a tiered carbon trading mechanism. The model innovatively refines the P2G process into two stages (electrolysis and methanation), utilizing methanation reaction heat to enhance efficiency. It further incorporates hydrogen blending into gas turbines and boilers and implements a tiered carbon trading mechanism to constrain emissions. The objective is to minimize total costs, including… More >