Article
Construction & Building Technology
Jani Mukkavaara, Farshid Shadram
Summary: The building design process involves a trade-off between embodied and operational energy, and multi-objective optimization can help generate optimal solutions. However, selecting the best solution from the set of optimal solutions can be challenging. A proposed approach integrates post-optimization sensitivity analysis into the multi-objective optimization process to support decision-makers in selecting the optimal design solution. The case study demonstrates how this method can provide valuable information to complement the results obtained from the optimization process.
ENERGY AND BUILDINGS
(2021)
Article
Thermodynamics
L. Bartolucci, S. Cordiner, V. Mulone, S. Pasquale, A. Sbarra
Summary: Multi energy systems are effective in moving towards a decentralized low-carbon system, with hydrogen being a promising energy carrier. Research shows that building-scale configurations can achieve simultaneous environmental and economic benefits, and the integration of hydrogen technologies and storage systems is an effective solution for reducing energy consumption and carbon dioxide emissions.
Article
Construction & Building Technology
Sepehr Foroushani, Rob Bernhardt, Mark Bernhardt
Summary: Achieving net-zero energy levels of operational efficiency is crucial for decarbonizing the building sector at a large scale. The Passive House energy performance level is gaining global consensus as a net-zero energy ready standard. However, the North American Reference Building Approach (RBA) used to assess building energy performance has significant flaws, including the inability to deliver net-zero energy performance and the promotion of inefficient designs and poor energy modeling practices.
ENERGY AND BUILDINGS
(2022)
Article
Energy & Fuels
Zeming Zhao, Hangxin Li, Shengwei Wang
Summary: This study conducts a sensitivity analysis to identify the most influential design parameters for building envelopes in different climate zones. The impacts of climate and building height are studied and compared. The findings provide valuable references for building envelope design under different climate conditions.
Article
Construction & Building Technology
Abed Al Waheed Hawila, Abdelatif Merabtine
Summary: Designing energy-efficient buildings that balance between energy savings and occupants' thermal comfort is crucial. Advanced control strategies based on thermal comfort are proposed, with sensitivity analysis and optimization used to identify design parameter values and optimize building design. Results show significant heating energy savings and enhanced thermal comfort with the suggested strategy, highlighting the importance of integrating thermal comfort in energy-efficient building design.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Energy & Fuels
Musik Park, Zhiyuan Wang, Lanyu Li, Xiaonan Wang
Summary: With increasing concerns over carbon dioxide emissions, the concept of Zero Energy Building (ZEB) and Electric Vehicles (EVs) have emerged to address environmental issues. This paper develops a new framework to find the optimal energy system design that meets EV charging demand and ZEB requirements, using machine learning models to predict charging demand and Genetic Algorithm and PROBID method to optimize costs and self-sufficiency ratio. The study finds that EV charging demand significantly affects energy system design, especially in small-size buildings.
Article
Construction & Building Technology
Emad Elbeltagi, Hossam Wefki, Rana Khallaf
Summary: This study introduces an optimization model for early-stage sustainable building design considering end-user energy consumption. The model aims to achieve minimal energy consumption for residential buildings during the early design stages by optimizing key design parameters using genetic algorithms. The results show a 25% reduction in energy consumption using the developed optimization model.
Article
Construction & Building Technology
Hossein Omrany, Ruidong Chang, Veronica Soebarto, Yanquan Zhang, Amirhosein Ghaffarianhoseini, Jian Zuo
Summary: This study provides a comprehensive overview of research developments in the field of Net-Zero Energy Buildings (NZEBs) over the past three decades using bibliometric analysis techniques. The study identifies influential researchers, sources, and countries in the field, explores thematic research focus areas and hot topics, and analyzes the thematic evolution of NZEBs. The results indicate that the field has expanded from initial limited themes to encompassing more themes, but is still evolving with emerging themes. This study offers important insights into the research developments and emerging themes in the field of NZEBs.
ENERGY AND BUILDINGS
(2022)
Article
Thermodynamics
T. Sathish, Pelluru Suresh, Kamal Sharma, C. Ahamed Saleel, Saboor Shaik, Sher Afghan Khan, Hitesh Panchal
Summary: This research aims to develop a zero-emission/energy-building heating system with a PCM. Experimental results show that the KNO3-NaNO3 PCM outperformed by exhibiting a higher heat transfer rate. The system achieved a maximum output water temperature of 94 degrees C, a heat transfer of 6273 W, an energy efficiency of 50.6%, and an exergy of 5.99%.
CASE STUDIES IN THERMAL ENGINEERING
(2023)
Article
Chemistry, Analytical
Muhammad Shahbaz Aziz, Muhammad Adil Khan, Harun Jamil, Faisal Jamil, Alexander Chursin, Do-Hyeun Kim
Summary: Pakistan has suitable land for photovoltaic production and utilizes a hybrid renewable energy solution including a hydroelectric turbine to reduce carbon footprint. The study shows that a system combining hydroelectric and photovoltaic energy provides the most cost-effective option.
Article
Construction & Building Technology
Ugur Acar, Onder Kaska, Nehir Tokgoz
Summary: This study focused on multi-objective optimization of building envelope parameters to enhance the energy and economic performance of buildings, with experiments conducted in two provinces of Turkey showing that correct selection of parameters at the preliminary design stage can significantly reduce life cycle costs and provide better solutions for zero energy buildings.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Energy & Fuels
Helder R. O. Rocha, Rodrigo Fiorotti, Danilo M. Louzada, Leonardo J. Silvestre, Wanderley C. Celeste, Jair A. L. Silva
Summary: This paper presents a solution to the energy planning problem in buildings by implementing the net Zero Energy cost Building (nZEcB) concept, using Artificial Intelligence (AI) techniques. The study shows the feasibility and effectiveness of using AI techniques to design a distributed generation system for nZEcBs more efficiently and economically.
Article
Construction & Building Technology
Jing Wang, Xu Han, Jinfeng Mao, Weihua Li
Summary: In cold plateau areas, prefabricated net zero energy buildings can achieve energy self-sufficiency through the use of lightweight components, solar energy, and wind energy. The study aims to design and construct a modular building with rapid construction and energy self-sufficiency to meet the special needs of extraordinary periods.
ENERGY AND BUILDINGS
(2021)
Article
Construction & Building Technology
Manav Mahan Singh, Chirag Deb, Philipp Geyer
Summary: This article presents an approach using building information modelling and machine learning to provide quick energy performance information through a web tool. The study found that the tool supports early-stage design decisions and enables design space exploration, energy performance evaluation, and more.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Energy & Fuels
Bilel Najlaoui, Abdullah Alghafis, Mohamed Nejlaoui
Summary: A multi-criteria robust design based on multi-objective optimization for flat plate collector systems is developed to reduce the impact of uncertain design parameters on the performance of the collector. The results show that this approach improves the performance sensitivity of the design compared to literature results.
Article
Energy & Fuels
Hong Tang, Shengwei Wang
Summary: This study develops a novel model-based predictive dispatch strategy for hybrid building energy systems to maximize economic benefits in electricity markets by considering the correlation between multiple flexibility resources and grid control signals, which can lower electricity costs in the electricity market.
Article
Energy & Fuels
Wenzhuo Li, Shengwei Wang
Summary: This paper proposes a fully distributed optimal control approach for HVAC systems to be implemented in IoT-enabled building automation networks. It utilizes the Incremental Cost Consensus (ICC) algorithm and the average consensus algorithm to optimize the individual rooms' outdoor air volume and estimate the outdoor air volume mismatch. Through tests and comparisons, it is found that the proposed approach with the fully connected topology outperforms existing hierarchical distributed approaches, demonstrating higher robustness, lower computation complexity, and higher optimization efficiency.
Article
Thermodynamics
Shaobo Sun, Shengwei Wang, Kui Shan
Summary: This study quantifies the measurement uncertainties of water flow meters in multiple water-cooled chiller systems using a Bayesian approach, proposing a quantification strategy that performs well in quantifying both systematic and random uncertainties with acceptable accuracy. The strategy can be used to optimize the control of chiller systems and improve their reliability.
APPLIED THERMAL ENGINEERING
(2022)
Article
Thermodynamics
Hangxin Li, Shengwei Wang
Summary: Constructing nearly and net zero-energy buildings presents the challenge of achieving energy goals post-occupancy, with traditional design methods showing high risk of failure. New ZEB design standards now focus on post-occupancy performance evaluation, posing additional challenges and calling for effective design methods.
BUILDING SIMULATION
(2022)
Article
Thermodynamics
Hangxin Li, Shengwei Wang
Summary: Model predictive control (MPC) method is superior in enhancing system performance, but is hindered by forecast uncertainties in operation. Different methods, such as shrinking horizon MPC (SHMPC) and stochastic MPC (SMPC), have been proposed to mitigate these uncertainties. However, there is limited knowledge about their year-round performance and relative performance, especially in the utilization of building flexibility-resources.
Article
Energy & Fuels
Shaobo Sun, Kui Shan, Shengwei Wang
Summary: This study proposed an online robust sequencing control strategy for chiller plants under low-quality and uncertain flow measurements, which effectively reduced the impacts of flow measurement uncertainties and improved the performance of chiller plants. The uncertainty processing model accurately quantified the measurement uncertainties of water flow rates, leading to significant reductions in root-mean-square error of cooling loads, total switching number of chillers, and cumulative unmet cooling load. The proposed control strategy showed the ability to tolerate flow measurement uncertainties.
Article
Thermodynamics
Hangxin Li, Shengwei Wang
Summary: Predictive scheduling is crucial in optimizing energy dispatch in building energy systems for demand response, as it maximizes benefits by considering future conditions. However, due to the discrepancy between predicted and actual conditions, achieving optimized demand response and fully satisfying energy demands in operation remains a challenge. This study proposes a two-time-scale coordinated optimal control strategy that considers forecast uncertainties to optimize energy dispatch in building energy systems for demand response.
Article
Construction & Building Technology
Jianing Luo, Hangxin Li, Shengwei Wang
Summary: This study proposes a quantitative approach to assess the security of microgrids by quantifying the dynamic load of power consumers. By developing generic transient models, the startup performance of motors and the blackout risk of microgrids can be effectively quantified. The results show that the approach and models can be used to assess microgrid security, and recommendations for motor/chiller capacity are provided.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Construction & Building Technology
Xiuming Li, Sida Lin, Kui Shan, Zongwei Han, Shengwei Wang
Summary: This study proposes a self-organization method based on the Semi-tensor product to solve logic control problems in distributed building automation systems. The method is demonstrated through simulation and experiment, showing its effectiveness in generating control logic through self-organization.
JOURNAL OF BUILDING ENGINEERING
(2022)
Article
Thermodynamics
Wenxuan Zhao, Hangxin Li, Shengwei Wang
Summary: This paper proposes a generic energy model based on artificial neural networks for the location and technology assessment of high-tech cleanrooms. The model is developed using energy data from a typical cleanroom in China under different climate conditions and application scenarios, and is validated and studied to provide accurate results, revealing the energy-saving potential of proper location selection.
APPLIED THERMAL ENGINEERING
(2022)
Article
Thermodynamics
Wenxuan Zhao, Hangxin Li, Shengwei Wang
Summary: This study categorizes alternative air-conditioning systems for high-tech cleanrooms and evaluates their energy and economic performance under different climatic conditions. The results show that fully decoupled systems are the most energy-efficient and cost-effective option, especially in hot and mild climates.
Article
Engineering, Electrical & Electronic
Zhuang Zheng, Shengwei Wang, Wenzhuo Li, Xiaowei Luo
Summary: This paper proposes a novel voltage control strategy that regulates the on/off states of AC clusters to address voltage issues caused by high PV penetrations. The strategy includes temperature priority-based on/off control, real-time optimal demand response resources dispatch, distributed sensing of ACs, and flexibility capacity estimation. The strategy is validated to be effective and scalable, and is incorporated into a hierarchical control framework for smart grid voltage control.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Construction & Building Technology
Wenxuan Zhao, Hangxin Li, Shengwei Wang
Summary: This study proposes a novel outdoor air ventilation strategy for high-tech cleanrooms, which enables maximum energy savings and efficiency. The strategy determines the optimal outdoor air volume by theoretically calculating the energy differential. Results show that the traditional fully coupled AHU system can achieve annual free cooling hours ranging from 662 to 2,537 in 31 major Chinese cities. Moreover, the proposed strategy achieves 8% energy savings in transition months and significant electricity and primary energy savings in a year.
BUILDING AND ENVIRONMENT
(2023)
Article
Energy & Fuels
Shitong Fang, Houfan Du, Tao Yan, Keyu Chen, Zhiyuan Li, Xiaoqing Ma, Zhihui Lai, Shengxi Zhou
Summary: This paper proposes a new type of nonlinear VIV energy harvester (ANVEH) that compensates for the decrease in peak energy output at low wind speeds by introducing an auxiliary structure. Theoretical and experimental results show that ANVEH performs better than traditional nonlinear VIV energy harvesters under various system parameter variations.
Article
Energy & Fuels
Wei Jiang, Shuo Zhang, Teng Wang, Yufei Zhang, Aimin Sha, Jingjing Xiao, Dongdong Yuan
Summary: A standardized method was developed to evaluate the availability of solar energy resources in road areas, which combined the Analytic Hierarchy Process (AHP) and the Geographic Information System (GIS). By analyzing critical factors and using a multi-indicator evaluation method, the method accurately evaluated the utilization of solar energy resources and guided the optimal location selection for road photovoltaic (PV) projects. The results provided guidance for the application of road PV projects and site selection for route corridors worldwide, promoting the integration of transportation and energy.
Article
Energy & Fuels
Chang Liu, Jacob A. Wrubel, Elliot Padgett, Guido Bender
Summary: The study investigates the effects of coating defects on the performance of the anode porous transport layer (PTL) in water electrolyzers. The results show that an increasing fraction of uncoated regions on the PTL leads to decreased cell performance, with continuous uncoated regions having a more severe impact compared to multiple thin uncoated strips.
Article
Energy & Fuels
Marcos Tostado-Veliz, Xiaolong Jin, Rohit Bhakar, Francisco Jurado
Summary: In this paper, a coordinated charging price mechanism for clusters of parking lots is proposed. The research shows that enabling vehicle-to-grid characteristics can bring significant economic benefits for users and the cluster coordinator, and vehicle-to-grid impacts noticeably on the risk-averse character of the uncertainty-aware strategies. The developed pricing mechanism can reduce the cost for users, avoiding to directly translate the energy cost to charging points.
Article
Energy & Fuels
Duan Kang
Summary: Building an energy superpower is a key strategy for China and a long-term goal for other countries. This study proposes an evaluation system and index for measuring energy superpower, and finds that China has significantly improved its ranking over the past 21 years, surpassing other countries.
Article
Energy & Fuels
Fucheng Deng, Yifei Wang, Xiaosen Li, Gang Li, Yi Wang, Bin Huang
Summary: This study investigated the synergistic blockage mechanism of sand and hydrate in gravel filling layer and the evolution of permeability in the layer. Experimental models and modified permeability models were established to analyze the effects of sand particles and hydrate formation on permeability. The study provided valuable insights for the safe and efficient exploitation of hydrate reservoirs.
Article
Energy & Fuels
Hao Wang, Xiwen Chen, Natan Vital, Edward Duffy, Abolfazl Razi
Summary: This study proposes a HVAC energy optimization model based on deep reinforcement learning algorithm. It achieves 37% energy savings and ensures thermal comfort for open office buildings. The model has a low complexity, uses a few controllable factors, and has a short training time with good generalizability.
Article
Energy & Fuels
Moyue Cong, Yongzhuo Gao, Weidong Wang, Long He, Xiwang Mao, Yi Long, Wei Dong
Summary: This study introduces a multi-strategy ultra-wideband energy harvesting device that achieves high power output without the need for external power input. By utilizing asymmetry, stagger array, magnetic coupling, and nonlinearity strategies, the device maintains a stable output voltage and high power density output at non-resonant frequencies. Temperature and humidity monitoring are performed using Bluetooth sensors to adaptively assess the device.
Article
Energy & Fuels
Tianshu Dong, Xiudong Duan, Yuanyuan Huang, Danji Huang, Yingdong Luo, Ziyu Liu, Xiaomeng Ai, Jiakun Fang, Chaolong Song
Summary: Electrochemical water splitting is crucial for hydrogen production, and improving the hydrogen separation rate from the electrode is essential for enhancing water electrolyzer performance. However, issues such as air bubble adhesion to the electrode plate hinder the process. Therefore, a methodology to investigate the two-phase flow within the electrolyzer is in high demand. This study proposes using a microfluidic system as a simulator for the electrolyzer and optimizing the two-phase flow by manipulating the micro-structure of the flow.
Article
Energy & Fuels
Shuo Han, Yifan Yuan, Mengjiao He, Ziwen Zhao, Beibei Xu, Diyi Chen, Jakub Jurasz
Summary: Giving full play to the flexibility of hydropower and integrating more variable renewable energy is of great significance for accelerating the transformation of China's power energy system. This study proposes a novel day-ahead scheduling model that considers the flexibility limited by irregular vibration zones (VZs) and the probability of flexibility shortage in a hydropower-variable renewable energy hybrid generation system. The model is applied to a real hydropower station and effectively improves the flexibility supply capacity of hydropower, especially during heavy load demand in flood season.
Article
Energy & Fuels
Zhen Wang, Kangqi Fan, Shizhong Zhao, Shuxin Wu, Xuan Zhang, Kangjia Zhai, Zhiqi Li, Hua He
Summary: This study developed a high-performance rotary energy harvester (AI-REH) inspired by archery, which efficiently accumulates and releases ultralow-frequency vibration energy. By utilizing a magnetic coupling strategy and an accumulator spring, the AI-REH achieves significantly accelerated rotor speeds and enhanced electric outputs.
Article
Energy & Fuels
Yi Yang, Qianyi Xing, Kang Wang, Caihong Li, Jianzhou Wang, Xiaojia Huang
Summary: In this study, a novel hybrid Quantile Regression (QR) model is proposed for Probabilistic Load Forecasting (PLF). The model integrates causal dilated convolution, residual connection, and Bidirectional Long Short-Term Memory (BiLSTM) for multi-scale feature extraction. In addition, a Combined Probabilistic Load Forecasting System (CPLFS) is proposed to overcome the inherent flaws of relying on a single model. Simulation results show that the hybrid QR outperforms traditional models and CPLFS exceeds the best benchmarks in terms of prediction accuracy and stability.
Article
Energy & Fuels
Wen-Jiang Zou, Young-Bae Kim, Seunghun Jung
Summary: This paper proposes a dynamic prediction model for capacity fade in vanadium redox flow batteries (VRFBs). The model accurately predicts changes in electrolyte volume and capacity fade, enhancing the competitiveness of VRFBs in energy storage applications.
Article
Energy & Fuels
Yuechao Ma, Shengtie Wang, Guangchen Liu, Guizhen Tian, Jianwei Zhang, Ruiming Liu
Summary: This paper focuses on the balance of state of charge (SOC) among multiple battery energy storage units (MBESUs) and bus voltage balance in an islanded bipolar DC microgrid. A SOC automatic balancing strategy is proposed considering the energy flow relationship and utilizing the adaptive virtual resistance algorithm. The simulation results demonstrate the effectiveness of the proposed strategy in achieving SOC balancing and decreasing bus voltage unbalance.
Article
Energy & Fuels
Raad Z. Homod, Basil Sh. Munahi, Hayder Ibrahim Mohammed, Musatafa Abbas Abbood Albadr, Aissa Abderrahmane, Jasim M. Mahdi, Mohamed Bechir Ben Hamida, Bilal Naji Alhasnawi, A. S. Albahri, Hussein Togun, Umar F. Alqsair, Zaher Mundher Yaseen
Summary: In this study, the control problem of the multiple-boiler system (MBS) is formulated as a dynamic Markov decision process and a deep clustering reinforcement learning approach is applied to obtain the optimal control policy. The proposed strategy, based on bang-bang action, shows superior response and achieves more than 32% energy saving compared to conventional fixed parameter controllers under dynamic indoor/outdoor actual conditions.
