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 >

Chao Zhang¹, Weidong Zhong¹, Xu An Wang¹, Weiwei Jiang^2,*, Ziteng Wang², Miao Tian¹, Jianhong Ling¹, Hangjiang Du¹, Yunhui Duan¹

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.081399 - 15 June 2026

Abstract The integrity risks posed by data outsourcing in cloud storage have driven the development of remote data integrity auditing (RDIA) technologies. However, traditional schemes rely on trusted third-party auditors (TPAs), leading to potential collusion and single-point failure vulnerabilities. The integration of blockchain alleviates these issues through decentralization and transparency, yet existing blockchain-based certificateless auditing schemes still suffer from security flaws in the tag generation phase. Addressing the tag forgery vulnerability in Miao et al.’s scheme, which stems from the absence of random parameters in the hash function input, this paper proposes a lightweight enhancement mechanism: More >

Bin Fang¹, Qi Yu¹, Han Wu², Xingxing Hou², Jingyu Zhang^2,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.080210 - 15 June 2026

Abstract The integration of Internet of Things (IoT) with blockchain technology introduces significant challenges in handling massive and frequent transaction data generated by distributed IoT devices. The Unspent Transaction Output (UTXO) model, widely adopted in blockchain systems like Bitcoin, faces critical scalability issues when applied to IoT environments. This is because the datasets it processes expand rapidly, which consumes a large amount of memory and increases the disk access latency of resource-constrained IoT nodes. Existing optimization approaches exhibit limitations in dynamic adaptability and protocol compatibility. To address these challenges, we propose an improved blockchain-empowered storage service More >

Xiang Li^1,2, Jie Zhang^1,2,*, Yuxin Cheng^1,2, Jiaohao Xie^1,2, Zhaoqi Xiong^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.5, 2026, DOI:10.32604/fdmp.2026.079253 - 27 May 2026

Abstract Current prediction methods for wellbore temperature and pressure in gas storage injection–production wells are commonly based on the simplifying assumption of pure methane, thereby neglecting the multi-component nature of real natural gas and limiting predictive accuracy. To overcome this shortcoming, this study develops a comprehensive model for the coupled temperature and pressure fields in wellbores transporting multi-component natural gas mixtures. The proposed framework explicitly accounts for compositional effects by integrating key thermophysical properties, including density, viscosity, compressibility factor, and Joule–Thomson coefficient, into the governing flow equations, thereby enhancing the fidelity of the ensuing injection and More >

Jawad Hameed^*, Jiefeng Hu, Md Liton Hossain, Syed Islam

Energy Engineering, Vol.123, No.6, 2026, DOI:10.32604/ee.2026.074998 - 27 May 2026

Abstract This paper presents a dynamic energy management strategy for a community-scale campus hybrid microgrid integrating photovoltaic (PV) generation, aggregated wind power, a proton exchange membrane fuel cell, and battery energy storage to support electric vehicle (EV) charging infrastructure under variable environmental and load conditions. The system configuration is inspired by existing renewable energy installations and planned developments at the Federation University Mt Helen Campus, enabling realistic modeling of aggregated demand and coordinated multi-source operation. To enhance physical realism, power electronic conversion efficiencies and hierarchical control dynamics are incorporated, while the wind subsystem is represented using… 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 >

Shan Yuan^1,2, Fei Wang^2,*, Jinping Zhang^2,*, Yuxin Jiang², Kaibo Gu², Chenhao Qiao², Yutong Bai², Jie Yu², Quan Chen¹, Dedi Han³

Chalcogenide Letters, Vol.23, No.4, 2026, DOI:10.32604/cl.2026.082805 - 09 May 2026

Abstract Sodium metal batteries stand as a highly promising electrochemical energy storage system; however, their commercialization is severely impeded by challenges such as anode dendrite formation, the shuttle effect of highly reactive intermediates at the cathode, electrode volume expansion, and interfacial instability. Owing to their high electronic conductivity, high theoretical specific capacity, and superior sodiumphilic affinity, tellurium and its tellurides have emerged as pivotal functional materials for enhancing the performance of sodium metal batteries. This study reviews the advancements in their applications within sodium metal batteries, elaborates rational design strategies carbon-based composites, alloying, and heterostructure construction More >