Fatin Nadhirah¹, Surajudeen Sikiru^1,2,*, Mohd Muzamir Mahat^1,3

Energy Engineering, Vol.123, No.9, 2026, DOI:10.32604/ee.2026.082624 - 06 August 2026

Abstract Agricultural waste has received increased attention as a sustainable precursor for activated carbon manufacture because of its availability, inexpensive price, and ecological benefits. However, the search for the right biomass and optimization of the activation process remain one of the major challenges in the production of high-performance composites in energy storage applications. In this study, pyrolysis of durian and eggshells was performed for activated carbon production using sodium sulfite (Na₂SO₃) and orthophosphoric acid (H₃PO₄) as activating agents, then combined both together with a ratio of 1:1 to produce a hybrid activated carbon to increase the performance… More >

Yiqun Kang^1,*, Zhe Li¹, Li You¹, Haozhe Xiong², Yuxuan Hu³, Fei Wang^4,*

Energy Engineering, Vol.123, No.9, 2026, DOI:10.32604/ee.2026.078724 - 06 August 2026

Abstract As the world’s energy framework shifts towards a low-carbon model, the widespread incorporation of renewable energy (RE) sources, primarily wind power and photovoltaics (PV), into the power grid is an unavoidable development. The micro-energy grid (MEG), as an integrated system that combines distributed energy, energy storage (ES), and power loads, can achieve efficient consumption of RE by implementing multi-machine optimal allocation and unified coordinated power control for parallel operation of grid-forming energy storage (GFES). For this purpose, this paper puts forward a low-carbon and economic dispatch strategy for MEG that considers multi-machine optimal allocation of… More >

Qiang Liu¹, Yongqiang Zhou¹, Chaoyang Lu², Zhen Yan¹, Gangui Yan², Cheng Yang^2,*, Yupeng Wang²

Energy Engineering, Vol.123, No.9, 2026, DOI:10.32604/ee.2025.073028 - 06 August 2026

Abstract The increasing proportion of power generated by new energy has meant that grid-forming energy storage has become a key method for improving power grid flexibility. However, the small disturbance stability problem has become an important challenge. The issue is that grid-forming energy storage is prone to low-frequency oscillation under strong grid conditions. Therefore, this study proposes a multi damping torque model to analyze the small signal stability of grid-forming energy storage converters. The impact of grid strength, operating conditions, and control parameters on the damping characteristics of the low-frequency oscillation by the system was quantitatively More >

Alireza Norouzpour Shahrbejari¹, Nafiseh Pishbin², Mohammad Reza Maghami^3,*, Mazlan Mohamed^4,*, Mohammad Golmohammad¹

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.1, 2026, DOI:10.32604/cmes.2026.083763 - 27 July 2026

Abstract This study presents a weighted-sum multi-criteria optimization framework using PSO for the optimal siting, sizing, and scenario-based operation of energy storage systems (ESSs) in renewable-integrated distribution networks. The proposed model concurrently addresses technical, economic, and reliability objectives—minimizing active power losses (PL), voltage deviation (VD), expected energy not supplied (EENS), and short-circuit level (SCL), while maximizing voltage sensitivity index (VSI) and power-loss sensitivity factor (PLSF). A Particle Swarm Optimization (PSO) algorithm with weighted-sum scalarization is employed to solve this complex, nonlinear optimization problem and effectively balance the conflicting operational goals. The framework is validated using IEEE… More >

Berry Lamy^*, Romaine Byfield, Yiding Cao

Frontiers in Heat and Mass Transfer, Vol.24, No.3, 2026, DOI:10.32604/fhmt.2026.079339 - 29 June 2026

Abstract Climate change and the ongoing dependence on fossil fuels present major challenges for global agriculture, with fossil fuel use in the agrifood sector accounting for a substantial and growing share of greenhouse gas (GHG) emissions. Agrifood systems currently contribute approximately one-third of total anthropogenic GHG emissions. Integrating renewable energy solutions for heating and power can help offset a significant fraction of these emissions. In this study, an analytical heat transfer and thermodynamic model is developed to evaluate the performance, energy balance, and thermal losses of the proposed system under realistic operating conditions. The model enables… More >

Tao Wang¹, Ze Feng^1,*, Jinghao Ma², Shenhui Chen², Jihui Zhang², Tong Wang²

Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2025.074054 - 18 June 2026

Abstract This paper develops an MPPT control strategy utilizing the particle swarm optimization (PSO) algorithm to enhance the tracking accuracy of photovoltaic arrays under complex operating conditions and to mitigate the transient effects on energy storage batteries during grid-connected and off-grid transitions. Initially, the operational principle of the three-phase voltage source PWM converter and the bidirectional DC/DC converter within solar power generation and energy storage systems is carefully examined, leading to the establishment of the appropriate mathematical model. Secondly, a voltage and current double closed-loop control structure utilizing feedforward decoupling is devised to meet the cooperative… More >

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 >

Danilo Greco^*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.082708 - 15 June 2026

Abstract The Enhanced Graph Neural Network Autoencoder (Enhanced GNN-AE), recently proposed for unsupervised cybersecurity monitoring in battery energy storage systems (BESSs), builds a multiscale k-nearest neighbour graph over measurement samples and learns compact latent representations via manifold-regularised training. Its spatial encoder, however, employs the original Graph Attention Network (GAT), which has been formally shown to compute a rank-1 attention function equivalent to graph convolutional networks on many graph structures. This work investigates whether replacing the GAT encoder with the strictly more expressive GATv2 formulation—which applies the attention vector after a joint, asymmetric linear transformation of source… More >

Yangjun Zhou¹, Chenying Yi¹, Wei Zhang¹, Juntao Pan^2,*, Ke Zhou¹, Weixiang Huang¹, Like Gao¹, Shan Li¹, Yuanchao Zhou³, Ling Li², Liwen Qin¹, Hongwen Wu⁴, Lijuan Yan²

Energy Engineering, Vol.123, No.6, 2026, DOI:10.32604/ee.2025.073787 - 27 May 2026

Abstract The increasing integration of distributed generation (DG) and energy storage systems (ESS) has significantly enhanced the flexibility and efficiency of distribution networks. However, the growing frequency of extreme weather events has exposed the vulnerability of distribution lines, posing serious challenges to the reliability and resilience of such systems. Existing DG and ESS planning models often neglect this vulnerability dimension, leading to suboptimal siting decisions and reduced system robustness. To address this issue, this paper proposes a comprehensive multi-objective optimization framework that coordinates the allocation of DG and ESS and explicitly incorporates line vulnerability under extreme… More >

Qingguo Nie, Yongfang Nie^*

Energy Engineering, Vol.123, No.6, 2026, DOI:10.32604/ee.2026.069025 - 27 May 2026

Abstract This study proposes an optimized design method for wind-solar-storage microgrid systems in the Gobi Desert region of northwest China. The core innovation is the development of a Modified Dragonfly Algorithm (MDA) to address the challenges of optimal system sizing and operation under complex desert conditions characterized by high renewable volatility and demanding environmental constraints. To strengthen the algorithm’s global search capability and convergence speed, three key enhancements are introduced: optimal point set initialization for even population distribution, cosine similarity guidance for balanced exploration-exploitation, and a nonlinear convergence factor for adaptive adjustment. The multi-objective optimization model… More >