Article
Engineering, Chemical
Ariel A. Boucheikhchoukh, Christopher L. E. Swartz, Eric Bouveresse, Pierre Lutran, Anna Robert
Summary: Uncertainty in refinery planning poses challenges to the day-to-day operations of an oil refinery. Stochastic programming framework can incorporate parameter uncertainty and provide robust solutions, which is more effective than deterministic modeling techniques.
Article
Thermodynamics
Tetsuya Wakui, Moe Hashiguchi, Ryohei Yokoyama
Summary: The translated paragraph introduces a near-optimal solution method for solving a large-scale design problem by combining multiple energy-supply systems into a distributed energy network. Through hierarchical combination of variables and constraint-based decompositions, the original design problem is decomposed into upper-level design problem and lower-level coordinated operation problem, resulting in a near-optimal solution.
Article
Engineering, Electrical & Electronic
Shiyi Jiang, Jianqiang Cheng, Kai Pan, Feng Qiu, Boshi Yang
Summary: The planning of distributed energy resources is challenging due to uncertainties and complexities. This paper introduces a new approach, the partial sample average approximation (PSAA), using real data to improve computational tractability.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Energy & Fuels
Wei Gan, Mingyu Yan, Jianfeng Wen, Wei Yao, Jing Zhang
Summary: This paper proposes a low-carbon planning method for joint regional district multi-energy system (MES) that ensures the privacy of regional and district energy systems. The results show the effectiveness of the proposed method.
Article
Computer Science, Interdisciplinary Applications
R. Cory Allen, Funda Iseri, C. Doga Demirhan, Iosif Pappas, Efstratios N. Pistikopoulos
Summary: The optimal design of large-scale energy systems can be achieved through integrated multi-period planning and scheduling mathematical programming. However, due to complexity, decomposition techniques and valid inequalities have been developed to address convergence issues. In this study, a machine learning framework is proposed to identify subproblems, and results indicate that it significantly reduces computational burden.
COMPUTERS & CHEMICAL ENGINEERING
(2023)
Article
Energy & Fuels
Fernando Garcia-Munoz, Sebastian Davila, Franco Quezada
Summary: New consumer-centric electricity market schemes are emerging as an alternative to manage energy balancing in distribution networks with high distributed energy resources penetration. Peer-to-peer energy trading is an attractive scheme for reducing user and distribution system operator costs by exchanging energy surplus between energy community users. This article presents a two-stage stochastic mixed-integer linear programming model to address the day-ahead scheduling problem in an energy community operating under a peer-to-peer energy trading scheme. The proposed model minimizes community costs, considers network limitations, and allows consumers to act as buyers or sellers depending on their consumption and self-generation.
Article
Engineering, Electrical & Electronic
Abdulraheem Hassan Alobaidi, Mahdi Khodayar, Ali Vafamehr, Harsha Gangammanavar, Mohammad E. Khodayar
Summary: This paper introduces a stochastic expansion planning framework to determine installation time, location, and capacity of battery energy storage systems in distribution networks with significant photovoltaic and data center penetration. The framework aims to minimize costs while ensuring energy supply security and network reliability.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Xiaofan Lai, Xiaolong Lu, Xinyao Yu, Ning Zhu
Summary: This study introduces a new vaccination station location model that takes into account the planning of medical professionals, vaccine procurement, and inventory decisions. A two-stage stochastic mixed integer linear program is used to address the uncertain demands for multiple types of vaccines over multiple periods. By developing a heuristic algorithm based on Benders decomposition, the effectiveness and efficiency of the model and new heuristics are demonstrated through numerical experiments and sensitivity analysis.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Engineering, Industrial
Adel Aazami, Mohammad Saidi-Mehrabad
Summary: This paper develops a new multi-period production-distribution planning for perishable products in a seller-buyer system, optimizing the seller's profit in a three-level supply chain. It includes cooperative actions between factories and distribution centers, a vertical competition involving retailers, and strategies to encourage retailers. The proposed hierarchical heuristic approach shows efficient performance in solving the NP-hard problem.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Management
Rodolphe Griset, Pascale Bendotti, Boris Detienne, Marc Porcheron, Halil Sen, Francois Vanderbeck
Summary: Optimizing nuclear unit outages is crucial for the economic performance of French electricity company EDF, as it involves substituting more expensive means to meet electricity demand. This study proposes a combined decomposition approach to tackle the challenges posed by the specific operating constraints of nuclear units, stochastic demand and non-nuclear unit availability, and the scale of the problem. The approach incorporates the operating constraints into a Dantzig-Wolfe pricing subproblem and handles demand and non-nuclear unit availability using Benders decomposition. The scalability of the approach is demonstrated on real-life instances of the French nuclear fleet.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Energy & Fuels
Ji Hyun Yi, Rachid Cherkaoui, Mario Paolone, Dmitry Shchetinin, Katarina Knezovic
Summary: This paper presents a combined framework for optimizing power distribution network expansion planning (DNEP) and energy storage systems (ESSs) allocation in active distribution networks (ADNs) hosting large amount of photovoltaic (PV) generations and loads. The proposed framework ensures reliable operation of the target ADN while minimizing grid losses by determining optimal grid expansion, reinforcement of existing lines, and ESS allocation. The allocated ESSs compensate for stochastic power flows caused by stochastic loads and generation, allowing ADNs to follow a predefined power schedule. The framework utilizes a modified augmented relaxed optimal power flow (AR-OPF) model to effectively model grid constraints and solve the OPF problem for radial networks. The complexity of the DNEP problem is handled using a sequential algorithm and Benders decomposition algorithm. The simulations conducted on a real 55-node Swiss ADN demonstrate the effectiveness of the proposed framework.
Article
Engineering, Electrical & Electronic
Naga Yasasvi Puvvada, Abheejeet Mohapatra, Suresh Chandra Srivastava
Summary: This paper proposes a novel nonlinear dual-based bi-level approach for robust AC Transmission Expansion Planning (TEP) with uncertainties in RES generations and loads. It introduces a convex relaxation and utilizes Benders Decomposition (BD) to solve the problem. The approach is tested on various systems, demonstrating its robustness and efficacy.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Management
Florin Leutwiler, Francesco Corman
Summary: Railway timetable planning is crucial for the successful operation of a railway network. This study introduces a logic Benders decomposition approach to solve the challenging problem of microscopic railway timetable planning. The proposed method shows improved scalability compared to existing benchmark approaches, as demonstrated through experiments on real-world cases of the Swiss Federal Railways.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Jian Chen, Wenjing Ma, Xudong Ye, Zhiheng Zhao
Summary: This paper studies the problem of order acceptance and scheduling in distributed manufacturing. It proposes two mixed-integer programming models and improvement techniques, as well as a logic-based Benders decomposition method and a branch and check search framework. The results demonstrate the effectiveness and efficiency of the proposed methods, and validate the value of distributed manufacturing and the sensitivity of key cost factors.
ADVANCED ENGINEERING INFORMATICS
(2023)
Article
Energy & Fuels
Jinhui Liu, Zhanbo Xu, Jiang Wu, Kun Liu, Xiaohong Guan
Summary: Hydrogen as a clean and renewable energy source has gained attention for replacing fossil fuels. Multi-energy storage units in distributed hydrogen-based systems can significantly reduce system costs, with hot water storage units showing the best benefits. The DHME system is environmentally friendly and can reduce carbon emissions drastically, especially in regions with high solar radiation. Additionally, with optimistic hydrogen pricing targets set by the USA Department of Energy, the DHME system can reduce operating expenses by up to 60.0% compared to conventional electricity-driven systems.
Article
Construction & Building Technology
Gabriele Bernardini, Tiago Miguel Ferreira, Pilar Baquedano Julia, Rafael Ramirez Eudave, Enrico Quagliarini
Summary: This research offers a methodology for combined spatiotemporal flood risk assessment, considering hazard, physical vulnerability, user exposure, and vulnerability. It adopts a mesoscale approach and investigates indoor and outdoor users' exposure and vulnerability, using the Analytical Hierarchy Process to combine risk factors.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Ying Liu, Chunli Chu, Ruijun Zhang, Shaoqing Chen, Chao Xu, Dongliang Zhao, Chunchun Meng, Meiting Ju, Zhi Cao
Summary: This study investigates the effects of increasing road, wall, and roof albedo on mitigating the urban heat island (UHI) effect in different areas of Tianjin. The results reveal that increasing road albedo is more effective in fringe areas, while increasing wall and roof albedo is more effective in central areas. The temperature changes induced by albedo changes also show seasonal characteristics.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Xisheng Lin, Yunfei Fu, Daniel Z. Peng, Chun-Ho Liu, Mengyuan Chu, Zengshun Chen, Fan Yang, Tim K. T. Tse, Cruz Y. Li, Xinxin Feng
Summary: This study employed computational fluid dynamics and neural network models to investigate and predict pollutant dispersion in urban environments, providing valuable insights for designing effective strategies to mitigate the impacts of hazardous pollutants.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Dipanjan Nag, Arkopal Kishore Goswami
Summary: Future-oriented urban planning should continue to focus on the principles of accessible and walkable cities. The perception of people is crucial for developing better urban walking infrastructure, but current evaluation tools often neglect the "perceived" features of the walking network. This study used conjoint analysis to evaluate users' perception of link and network attributes, revealing the importance of considering both in improving the walking environment.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Yongxin Su, Tao Zhang, Mengyao Xu, Mao Tan, Yuzhou Zhang, Rui Wang, Ling Wang
Summary: This study proposes an optimization method for household integrated demand response (HIDR) by combining rough knowledge and a dueling deep Q-network (DDQN), aiming to address uncertainties in a household multi-energy system (HMES). The simulation results demonstrate that the proposed method outperforms rule-based methods and DDQN in terms of energy cost savings.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Sijia Sun, S. F. A. Batista, Monica Menendez, Yuanqing Wang, Shuang Zhang
Summary: This paper comprehensively analyzes the energy consumption characteristics of electric buses (EBs) and diesel buses (DBs) on different bus lane configurations and operational conditions. The study shows that EBs consume less energy in suburban areas when using regular lanes, while both EBs and DBs save substantial energy when operating on dedicated bus lanes in downtown areas. Notably, shared-use bus lanes have the highest energy consumption.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Shangshang Shen, Dan Yan, Xiaojie Liu
Summary: This study developed a comprehensive theoretical framework for evaluating, diagnosing, and optimizing multi-functional urban agriculture. The framework was applied in Xiamen, China to identify the obstacles that impede its coordinated development and propose optimized modes for its development. Results showed that urban agriculture in Xiamen exhibits sound social function, moderate economic function, and poor ecological function.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Oluwafemi E. Adeyeri, Akinleye H. Folorunsho, Kayode I. Ayegbusi, Vishal Bobde, Tolulope E. Adeliyi, Christopher E. Ndehedehe, Akintomide A. Akinsanola
Summary: This study examines the impact of land cover, vegetation health, climatic forcings, elevation heat loads, and terrain characteristics on land surface temperature distribution over West Africa. The random forest model performs the best in downscaling predictands. The southern regions consistently exhibit healthy vegetation, while areas with unhealthy vegetation coincide with hot land surface temperature clusters. Positive Normalized Difference Vegetation Index trends in the Sahel highlight rainfall recovery and subsequent greening. Southwest winds cause the upwelling of cold waters, resulting in low land surface temperatures in southern West Africa. Considering LVCET factors is crucial for prioritizing greening initiatives and urban planning.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Yuchi Cao, Yan Li, Shouyun Shen, Weiwei Wang, Xiao Peng, Jiaao Chen, Jingpeng Liao, Xinyi Lv, Yifan Liu, Lehan Ma, Guodian Hu, Jinghuan Jiang, Dan Sun, Qingchu Jiang, Qiulin Liao
Summary: The study reveals significant disparities in urban green equity, with high property price areas having better access to green spaces than low property price areas. Landscape and greening have the most significant impact on urban green space differentiation.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Shaobo Sun, Kui Shan, Shengwei Wang
Summary: Economizer control is an important measure for energy savings in air-conditioning systems during moderate seasons. Humidity measurement uncertainties have a significant impact on enthalpy-based economizer control, and an uncertainty-tolerant control strategy is proposed to mitigate these effects.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Ding Mao, Peng Wang, Yi-Ping Fang, Long Ni
Summary: This study analyzes the structure, function, operation, and failure characteristics of district heating networks (DHNs) and proposes vulnerability analysis methods. The effectiveness of these methods is validated through application to a DHN in a Chinese city. The study finds that the heat source connectivity efficiency loss rate effectively characterizes topological and functional vulnerability. It also reveals that controllable DHNs have higher functional vulnerability under large area failure scenarios.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Hamid Karimi, Saeed Hasanzadeh, Hedayat Saboori
Summary: This paper presents a stochastic and cooperative approach for the operation of a cluster of interconnected multi-energy systems. The proposed model investigates the interaction among energy systems and integrates hydrogen and water systems into the overall energy structure. The model studies the performance of energy system agents in decentralized and cooperative scheduling.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Zhiyu Yan, Xiaogang Guo, Zilong Zhao, Luliang Tang
Summary: This study proposes a novel framework for fine-grained information extraction and dynamic spatial-temporal awareness in disaster-stricken areas based on social media data. The framework utilizes deep learning modules to extract location and water depth information from text and images, and analyzes the spatio-temporal distribution characteristics. The results show that the fusion of text and image-based information can enhance the perception of flood processes.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
M. A. Pans, G. Claudio, P. C. Eames
Summary: This study simulated and optimized a speculative district heating system in an existing urban area in Loughborough, UK. The system used only renewable heat sources and thermal energy storage to address the mismatch between heat generation and demand. The study assessed the impact of long-term storage volume and charging temperature on system cost and energy efficiency.
SUSTAINABLE CITIES AND SOCIETY
(2024)
Article
Construction & Building Technology
Jianmei Zhong, Wei Zhang, Xiaoli Wang, Jinsheng Zhan, Tao Xia, Lingzhi Xie, Xiding Zeng, Kun Yang, Zhangyu Li, Ruiwen Zou, Zepu Bai, Qing Wang, Chenyang Zhang
Summary: This study aims to propose a suitable air distribution design and reduce the energy consumption of the BSL-4 laboratory. It analyzes the diffusion characteristics of aerosols, infection risk under different air distributions, and ventilation parameters. The results show that the proposed energy-saving operation strategy can reduce the energy consumption of the laboratory by 15-30%.
SUSTAINABLE CITIES AND SOCIETY
(2024)