Article
Energy & Fuels
Sudlop Ratanakuakangwan, Hiroshi Morita
Summary: The study integrates both stochastic robust optimization and robust optimization into a proposed model to deal with multiple uncertainties effectively. Social acceptance is considered alongside other factors such as system stability and economy. Through case studies in Thailand and Vietnam, the model demonstrates the potential to effectively balance system stability and economic factors in energy planning.
Article
Thermodynamics
Marko Mimica, Laura Gimenez de Urtasun, Goran Krajacic
Summary: This paper introduces a novel robust risk assessment method for island energy planning scenarios by using auxiliary variables and Poisson distribution to calculate probability of power system element failure. Four energy planning scenarios for Unije island are modeled and a zero-import risk energy planning scenario is presented in the study.
Article
Geosciences, Multidisciplinary
Muhammad Imran Hanif, Rehman Akhtar
Summary: This paper presents a dynamic model to evaluate the recovery of workforce-interdependent sectors after an earthquake, and assess the social and economic losses caused by workforce disruption. It also provides a risk-based framework to guide policymakers in managing the adverse effects of earthquakes. The model has been applied in the regional sectors of Pakistan and can be generalized to other regions and disaster scenarios.
Article
Engineering, Civil
Stephane Victor, Jean-Baptiste Receveur, Pierre Melchior, Patrick Lanusse
Summary: This article presents a method for tracking a reference optimal trajectory for an autonomous nonlinear vehicle model by designing robust feedback control and suitable feedforward control. The method includes a global planning and tracking process, utilizing a genetic algorithm for optimization and a potential field for reacting to unforeseen events. The results demonstrate the effectiveness of the proposed method in different scenarios.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Review
Computer Science, Information Systems
Aparna Ashok Kamble, B. M. Patil
Summary: The article highlights the significance of path optimization strategies in Wireless Sensor Networks and the potential of mobile sink in improving energy efficiency. Research shows that a fixed-speed sink can reduce communication time, but path constraints add complexity to routing.
COMPUTER SCIENCE REVIEW
(2021)
Article
Computer Science, Information Systems
Jose Almeida, Joao Soares, Fernando Lezama, Zita Vale
Summary: This paper proposes a risk-based optimization approach for centralized day-ahead energy resource management (ERM) considering extreme events. The risk-averse strategy implements the conditional value-at-risk (CVaR) method to account for worst-case scenario costs. The case study shows that the risk-averse strategy increases operational costs but reduces worst-case scenario costs, providing safer and more robust solutions.
Article
Energy & Fuels
Yuwei Wang, Minghao Song, Mengyao Jia, Bingkang Li, Haoran Fei, Yiyue Zhang, Xuejie Wang
Summary: This paper proposes a multi-objective distributionally robust optimization (DRO) model for H-RE-CCHP planning. By considering economic and environmental objectives, as well as resisting uncertainties, a balance between economy and environment is achieved, promoting the transition towards low carbon energy.
Article
Computer Science, Information Systems
Jun Gao, Jie Wang
Summary: This study focuses on optimizing routes for dry bulk shipping fleets using robust optimization approach to minimize total transportation costs while ensuring navigation risks remain under a certain threshold. The results show that this approach effectively balances navigation risks and transportation costs.
Article
Engineering, Geological
Sourav Das, Souvik Chakraborty, Yangyang Chen, Solomon Tesfamariam
Summary: The study introduced a seismic vibration mitigation system utilizing shape memory alloy (SMA) assisted nonlinear energy sink (NES) with negative stiffness, which dissipates energy through a hysteretic phase transformation triggered by cyclic loading of its microstructure. The nonlinear spring within NES is replaced by an SMA based spring, modeled by the Greaser Cozzarelli model utilizing the super-elastic effect of SMA. The robust performance of the proposed controller is ensured through determining tuning parameters by solving a robust design optimization problem, with blind Kriging used as a surrogate model for efficient solving of the optimization problem. Multiple parametric studies demonstrate the enhanced and robust performance of the proposed SMA enhanced NES with negative stiffness.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2021)
Article
Mechanics
Cherif Snoun, Baptiste Bergeot, Sebastien Berger
Summary: This paper proposes robust methods to optimize nonlinear energy sinks (NES) for mitigation of friction-induced vibrations. It predicts the discontinuity in the steady-state amplitude profile using Multi-Element generalized Polynomial Chaos and aims to maximize the Propensity of the system to undergo a Harmless Steady-State Regime (PHSSR) for a robust optimal design of the NES.
EUROPEAN JOURNAL OF MECHANICS A-SOLIDS
(2022)
Review
Green & Sustainable Science & Technology
F. A. Plazas-Nino, N. R. Ortiz-Pimiento, E. G. Montes-Paez
Summary: Energy planning is crucial for the future sustainability, affordability, and reliability of the energy mix. Energy system optimization models (ESOMs) serve as accurate tools to guide national energy planning decisions. This article provides a systematic literature review on ESOMs, including their characteristics, data requirements, trends in decarbonization scenario analysis, and challenges associated with energy system optimization modeling. The review highlights the importance of decarbonization pathways as the primary objective in energy system optimization modeling, with factors such as renewable energy integration, energy efficiency improvement, sector coupling, and sustainable transport as key drivers.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Environmental Sciences
R. Cao, G. H. Huang, J. P. Chen, Y. P. Li
Summary: A fractional multi-stage simulation-optimization energy model is developed to tackle uncertainties and conflicting objectives in regional energy systems. The study finds that carbon emissions can be reduced under scenarios of climate change mitigation and socioeconomic development, with forest carbon sink as an effective alternative.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Energy & Fuels
Neha Patankar, Hadi Eshraghi, Anderson Rodrigo de Queiroz, Joseph F. DeCarolis
Summary: This study extends and applies robust optimization methods to the energy system optimization model in the United States to explore low carbon pathways. By considering future uncertainty, the robust strategy has shown significant cost savings and improved cost control.
ENERGY STRATEGY REVIEWS
(2022)
Article
Management
Saharnaz Mehrani, Jorge A. Sefair
Summary: This paper studies a robust assortment optimization problem for substitutable products, taking into account a sequential ranking-based choice model and a cardinality constraint. The problem is shown to be NP-hard, and exact and greedy solution approaches have been developed to efficiently solve different instances. A computational study demonstrates the sensitivity of the optimal assortment to variations in the input parameters.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Energy & Fuels
Xin Zhao, Zhenqi Bai, Wanlei Xue, Nan Xu, Chenhui Li, Huiru Zhao
Summary: This study establishes a bi-level cooperative robust planning model considering the impact of distributed renewable energy and demand response on the distribution grid. Model verification and analysis show that considering demand response can delay investment costs, enhance load flexibility for power users, and effectively avoid issues such as load cutting.
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.