Media Nadhim Mahmood¹, Oday I. Abdullah^1,2,3,*, Amani I. Altmimi⁴

Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.078421 - 18 June 2026

Abstract The highly important requirement for achieving urban sustainability for any city is the availability of renewable energy, as reducing carbon emissions is considered one of the most important factors in improving the quality of life and health of people in green cities. The main objective of this research is to provide an in-depth study and analysis of the role of renewable energies, especially solar energies, in promoting sustainable development in cities around the world, in general, and in Iraq in particular. Strategies for using clean energy sources in a hybrid manner, such as solar energy,… More >

Siying Li¹, Xinyu Feng², Xin Ma², Hui Huang², Zhipeng Wang², Baolian Liu², Zujun Ding², Weihong Ding², Xiaolong Huang², Jie Ji^2,*

Energy Engineering, Vol.123, No.7, 2026, DOI:10.32604/ee.2026.078062 - 18 June 2026

Abstract This study introduces a novel Dual-Stage GT-RO-PCC (Game Theory-Robust Optimization-Price Coupling Control) paradigm to address operational challenges in community-integrated energy microgrids (CIEMs) characterized by multi-energy complementarity and distributed generation. By synergizing strategic interaction mechanisms with uncertainty-aware energy management, the proposed framework establishes a tripartite governance structure integrating microgrid operators, user-side aggregators, and shared energy storage operators. The first stage formulates a Stackelberg game-theoretic model to optimize day-ahead electricity/heat pricing strategies through bilevel optimization, incorporating flexible load management modeling with flexible load disaggregation and carbon emission trading mechanisms. The second stage constructs a two-stage stochastic robust… More >

S. D. Al-Sahafi^*

Chalcogenide Letters, Vol.23, No.5, 2026, DOI:10.32604/cl.2026.082364 - 02 June 2026

Abstract In this study, a lead-free double perovskite solar cell structure based on Cs₂BiAgI₆ was simulated and optimized to enhance photovoltaic performance. The device architecture follows the configuration: ITO/PCBM/C₆₀/Cs₂BiAgI₆/CdTe/Au. The thicknesses of the electron transport layer (ETL), absorber layer, and hole transport layer (HTL) are systematically optimized to evaluate their impact on key performance parameters. The results indicate that optimal performance is achieved with 600 nm thicknesses for all ETLs and HTL, and 2 μm for the Cs₂BiAgl₆ absorber. Under these conditions, the device exhibits a short-circuit current density of 23.23 mA/cm², an open-circuit voltage of 1.08 V, More >

Sravani Parvathareddy^1,*, Abid Yahya¹, Lilian Amuhaya¹, Ravi Samikannu¹, Raymond S. Suglo²

Energy Engineering, Vol.123, No.6, 2026, DOI:10.32604/ee.2026.079449 - 27 May 2026

Abstract This paper presents a novel framework for the development of a real-time energy management system for mining microgrids, which integrates the benefits of a long short-term memory (LSTM) network and a feedforward neural network (FNN) for the prediction of the load and solar power, and the optimization of the dispatch, respectively, while ensuring the safety of the microgrid through the application of a convex safety filter. In the proposed framework, the LSTM provides probabilistic multi-step forecasts of load and photovoltaic generation, capturing the high volatility characteristic of mining operations with ramp rates up to 5… More > Graphic Abstract

Said Benkachcha^1,*, Mustapha Adar¹, Mohamed Maniana², Youssef Najih¹, Mourad Kaddiri¹, Mutapha Mabrouki¹

Energy Engineering, Vol.123, No.6, 2026, DOI:10.32604/ee.2026.075406 - 27 May 2026

Abstract Accurate forecasting of solar photovoltaic (PV) power generation is essential for enabling reliable integration of renewable energy into modern power systems. Variability in solar production, driven by meteorological fluctuations and inherent nonlinear dynamics, presents significant challenges for grid stability, operational planning, and energy management. This study investigates and compares the performance of classical statistical forecasting techniques and advanced deep learning approaches using real PV production data from a Moroccan solar plant. The analysis focuses on accuracy, robustness, computational efficiency, and suitability for short-term operational applications. Among statistical approaches, the Holt–Winters model demonstrated strong capability in… More > Graphic Abstract

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 >

Zujun Ding, Zhi Liu, Peng Huang, Yuhan Qian, Chengyi Li, Zizhuo Yu, Hui Huang, Baolian Liu, Wan Chen, Jie Ji^*

Energy Engineering, Vol.123, No.6, 2026, DOI:10.32604/ee.2025.074440 - 27 May 2026

Abstract Under extreme weather conditions (such as hurricanes and heatwaves causing sudden drops in renewable energy output and surges in load), microgrid operations face severe challenges due to the uncertainty of renewable energy and load fluctuations. Although existing research has focused on microgrid optimal scheduling or electric vehicle integration, there has not yet been a systematic approach to multi-timescale scheduling that combines electric vehicle fleets under extreme weather scenarios, and particularly, explicit modeling of weather events and their impact on component failure rates and transmission lines is lacking. This paper proposes, for the first time, a… More >

Federico Minelli^1,*, Diana D’Agostino¹, Vennapusa Jagadeeswara Reddy², Panagiotis Michailidis^3,4

Energy Engineering, Vol.123, No.6, 2026, DOI:10.32604/ee.2026.074048 - 27 May 2026

Abstract This study investigates the problem of prioritizing rooftop renewable energy (RE) system configurations for a multi-family residential building in Mediterranean climate. The analysis focuses on fixed-tilt photovoltaics (PV), single-axis and dual-axis tracking PV, and small vertical-axis wind turbines (VAWT), each assessed with and without lithium-ion storage. A co-simulation framework is used, coupling EnergyPlus building-HVAC system simulation with PV and wind generation modeling and rule-based battery dispatch to evaluate hourly demand–supply interactions. Three decision criteria are considered for each alternative: total system cost, annual building electric energy demand reduction, and net avoided life-cycle emissions. Stakeholder preferences… More > Graphic Abstract

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 >

Asma Nousheen¹, Silvia Peruccacci², Cosimo Magazzino^3,4,5,*

Energy Engineering, Vol.123, No.5, 2026, DOI:10.32604/ee.2026.076916 - 27 April 2026

Abstract Green growth has revolutionized society by reducing carbon dioxide (CO₂) emissions, intensifying energy efficiency, and promoting environmentally friendly technologies and energy utilization, eventually leading to sustainable economic development. However, research on the intricate relationship between green growth and CO₂ emissions is limited. This study aims to evaluate the impact of green growth, Information and Communication Technology (ICT), renewable energy, and population on environmental sustainability for a panel of 20 OECD countries from 2000 to 2023. Cointegration regression methods (Fully Modified Ordinary Least Squares, Dynamic Ordinary Least Squares, and Pooled Mean Group-AutoRegressive Distributed Lags) and pairwise panel More > Graphic Abstract