Article
Thermodynamics
Miguel Gonzalez-Salazar, Julia Klossek, Pascal Dubucq, Thomas Punde
Summary: Long-term portfolio optimization for district heating systems is challenging due to the need for high accuracy and computational speed. This paper investigates the advantages and disadvantages of using merit order (MO) models compared to mixed integer linear programming (MILP) models. Results suggest that MO models, especially those incorporating heat storage and detailed description of CHP plants, can significantly reduce computation time without sacrificing accuracy. Combining MO and MILP models offers a faster and more robust decision-making process.
Article
Mechanics
G. Ntourmas, F. Glock, F. Daoud, G. Schuhmacher, D. Chronopoulos, E. Oezcan
Summary: This manuscript presents two novel formulations for manufacturable stacking sequence retrieval, achieving solutions that meet both design and manufacturing requirements through a two-stage optimization approach. Using mathematical programming algorithms, high-quality solutions can be consistently obtained, with increased design freedom concerning blending formulation.
COMPOSITE STRUCTURES
(2021)
Article
Engineering, Electrical & Electronic
Dominik Putz, Daniel Schwabeneder, Hans Auer, Bernadette Fina
Summary: This paper addresses the Unit Commitment problem in power supply systems by using mixed-integer linear programming and backward dynamic programming. By enhancing the dynamic programming algorithm with state prediction, the proposed formulation significantly reduces computation time and delivers satisfactory solutions in a shorter time compared to other approaches. Additionally, the linear dependence of computation time on the number of steps is a key advantage of the dynamic programming strategy, especially for longer planning horizons.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Management
Maria Sierra-Paradinas, Oscar Soto-Sanchez, Antonio Alonso-Ayuso, F. Javier Martin-Campo, Micael Gallego
Summary: From an economic perspective, innovation is crucial for the steel industry to tackle new challenges. This paper introduces a mathematical methodology to solve the slitting problem in a European steel company, aiming to reduce leftover waste and improve order accuracy.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Mathematics
Islem Snoussi, Nadia Hamani, Nassim Mrabti, Lyes Kermad
Summary: This paper proposes robust optimization models for the distribution network design problem in a collaborative context to address uncertainty cases. Utilizing mixed-integer linear programming formulations, the study examines the economic and environmental aspects of sustainability to minimize logistical costs and CO2 emissions. A case study in France validates the models, demonstrating the impacts of uncertainty on logistical costs and CO2 emissions by comparing robust and deterministic models.
Article
Energy & Fuels
Frank Wendel, Markus Blesl, Lukasz Brodecki, Kai Hufendiek
Summary: In order to meet decarbonization targets, contemporary district heating networks need to transform into more efficient low-temperature networks. Economic challenges can be addressed by implementing appropriate transformation strategies, reducing excessive network expansion and decommissioning. Furthermore, generalized claims for lowest supply and return temperatures may not be economically viable.
Article
Energy & Fuels
Bernadette Fina, Mike B. Roberts, Hans Auer, Anna Bruce, Iain MacGill
Summary: The deployment of solar photovoltaic systems in residential buildings globally is uneven, especially in apartment buildings. Australia benefits from superior climate and lower investment costs, driving larger optimal system sizes and bill savings, but lower electricity tariffs and regulatory barriers hinder deployment; in contrast, European enabling legislation has not yet successfully overcome higher investment costs and administrative obstacles.
Article
Energy & Fuels
Michael-Allan Millar, Zhibin Yu, Neil Burnside, Greg Jones, Bruce Elrick
Summary: Implementing renewable heating on a large scale is crucial for achieving Net Zero 2050 emission targets. Utilizing 5th generation district heating networks for energy sharing can significantly reduce carbon emissions and energy cost equivalent, with low temperature district heating networks potentially providing greater economic benefits with appropriate thermal storage and time of use tariffs. Developers should define whether their primary goal is carbon saving or profit making, as these objectives are challenging to achieve synergistically.
Article
Thermodynamics
Hjoerleifur G. Bergsteinsson, Phillip B. Vetter, Jan Kloppenborg Moller, Henrik Madsen
Summary: This paper proposes a method for estimating network temperatures using smart meter data, and using these temperatures to estimate network characteristics. Compared to traditional physical measurement methods at critical points, this method eliminates the need for actual physical critical points and allows for changing the location of critical points if needed. The proposed method utilizes a stochastic state-space model and maximum likelihood estimation, with the Kalman Filter used to evaluate the likelihood function.
ENERGY CONVERSION AND MANAGEMENT
(2022)
Article
Thermodynamics
Dominik Hering, Mehmet Ege Cansev, Eugenio Tamassia, Andre Xhonneux, Dirk Mueller
Summary: Lowering the operating temperatures of district heating networks is crucial to reduce energy losses and utilize low-temperature heat sources, such as waste heat. This paper focuses on modeling, control, and optimization of a low-temperature district heating network, with a case study on waste heat from high-performance computers. The optimization model presented in the study demonstrates energy savings of 1.55%-5.49% by controlling the operation temperatures of heat pumps and thermal energy storages.
Article
Engineering, Civil
Andries M. Heyns, Robert Banick
Summary: This paper introduces a new multi-modal accessibility model for rural road planning, considering remote populations that are far from existing roads. The paper also presents an innovative heuristic solution approach to determine well-performing road-combination plans using multi-objective optimization methods. The comparison between this approach and traditional methods demonstrates the new planning and analysis benefits of the heuristic for rural roads planning.
Article
Energy & Fuels
Laura Maier, Marius Schoenegge, Sarah Henn, Dominik Hering, Dirk Mueller
Summary: Model predictive control can reduce heating systems' operating costs and energy consumption, especially for heat pumps. This study develops two different air-source heat pump modeling approaches using the supply temperature as a control variable and compares them with a simplified linear model. The results show that both the piecewise linear model and the quadratic model have lower operating costs and energy demand compared to the simplified linear model, but they require longer computation times. Future work is recommended to apply this method to other types of heat pumps and coupled building energy systems to further validate its feasibility.
Article
Computer Science, Interdisciplinary Applications
Chao Guan, Zeqiang Zhang, Juhua Gong, Silu Liu
Summary: This study investigates the bi-objective double-floor corridor allocation problem using a mixed integer linear programming model and a genetic algorithm with a variable neighbourhood search technique, demonstrating superior performance through comparisons and updating lower bounds of benchmark instances.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Thermodynamics
Hamid Bakhshi Yamchi, Amin Safari, Josep M. Guerrero
Summary: This paper presents a new integrated electricity and gas networks expansion planning model using multi-objective mixed integer linear programming, aiming to reduce emissions and greenhouse gases. By incorporating photovoltaic power plants, reduced disjunctive model, and stochastic method to study correlated uncertainty, it is possible to decrease costs and emissions in the expansion planning process.
Article
Computer Science, Artificial Intelligence
Cheng Fang, Brian C. Williams
Summary: Resistance to the adoption of autonomous systems is addressed by deploying decision making algorithms to define failure and find plans with the highest reward while limiting the probability of failure. This can be achieved using a chance-constrained mixed logical-linear program (CC-MLLP) formulation, which allows for the specification of linear and logical constraints with probabilistic continuous variables. By partitioning CC-MLLPs into discrete and continuous portions and developing faster solution methods for the continuous chance constrained linear programs, the resulting algorithm achieves a 10 times speed up over prior approaches on autonomous path planning benchmarks.
ARTIFICIAL INTELLIGENCE
(2023)
Article
Thermodynamics
Yong Cheng, Fukai Song, Lei Fu, Saishuai Dai, Zhiming Yuan, Atilla Incecik
Summary: This paper investigates the accessibility of wave energy absorption by a dual-pontoon floating breakwater integrated with hybrid-type wave energy converters (WECs) and proposes a hydraulic-pneumatic complementary energy extraction method. The performance of the system is validated through experiments and comparative analysis.
Article
Thermodynamics
Jing Gao, Chao Wang, Zhanwu Wang, Jin Lin, Runkai Zhang, Xin Wu, Guangyin Xu, Zhenfeng Wang
Summary: This study aims to establish a new integrated method for biomass cogeneration project site selection, with a focus on the application of the model in Henan Province. By integrating Geographic Information System and Multiple Criterion Decision Making methods, the study conducts site selection in two stages, providing a theoretical reference for the construction of biomass cogeneration projects.
Article
Thermodynamics
Mert Temiz, Ibrahim Dincer
Summary: The current study presents a hybrid small modular nuclear reactor and solar-based system for sustainable communities, integrating floating and bifacial photovoltaic arrays with a small modular reactor. The system efficiently generates power, hydrogen, ammonia, freshwater, and heat for residential, agricultural, and aquaculture facilities. Thermodynamic analysis shows high energy and exergy efficiencies, as well as large-scale ammonia production meeting the needs of metropolitan areas. The hybridization of nuclear and solar technologies offers advantages of reliability, environmental friendliness, and cost efficiency compared to renewable-alone and fossil-based systems.
Editorial Material
Thermodynamics
Wojciech Stanek, Wojciech Adamczyk
Article
Thermodynamics
Desheng Xu, Yanfeng Li, Tianmei Du, Hua Zhong, Youbo Huang, Lei Li, Xiangling Duanmu
Summary: This study investigates the optimization of hybrid mechanical-natural ventilation for smoke control in complex metro stations. The results show that atrium fires are more significantly impacted by outdoor temperature variations compared to concourse/platform fires. The gathered high-temperature smoke inside the atrium can reach up to 900 K under a 5 MW train fire energy release. The findings provide crucial engineering insights into integrating weather data and adaptable ventilation protocols for smoke prevention/mitigation.
Article
Thermodynamics
Da Guo, Heping Xie, Mingzhong Gao, Jianan Li, Zhiqiang He, Ling Chen, Cong Li, Le Zhao, Dingming Wang, Yiwei Zhang, Xin Fang, Guikang Liu, Zhongya Zhou, Lin Dai
Summary: This study proposes a new in-situ pressure-preserved coring tool and elaborates its pressure-preserving mechanism. The experimental and field test results demonstrate that this tool has a high pressure-preservation capability and can maintain a stable pressure in deep wells. This study provides a theoretical framework and design standards for the development of similar technologies.
Article
Thermodynamics
Aolin Lai, Qunwei Wang
Summary: This study assesses the impact of China's de-capacity policy on renewable energy development efficiency (REDE) using the Global-MSBM model and the difference-in-differences method. The findings indicate that the policy significantly enhances REDE, promoting technological advancements and marketization. Moreover, regions with stricter environmental regulations experience a higher impact.
Article
Thermodynamics
Mostafa Ghasemi, Hegazy Rezk
Summary: This study utilizes fuzzy modeling and optimization to enhance the performance of microbial fuel cells (MFCs). By simulating and analyzing experimental data sets, the ideal parameter values for increasing power density, COD elimination, and coulombic efficiency were determined. The results demonstrate that the fuzzy model and optimization methods can significantly improve the performance of MFCs.
Article
Thermodynamics
Zhang Ruan, Lianzhong Huang, Kai Wang, Ranqi Ma, Zhongyi Wang, Rui Zhang, Haoyang Zhao, Cong Wang
Summary: This paper proposes a grey box model for fuel consumption prediction of wing-diesel hybrid vessels based on feature construction. By using both parallel and series grey box modeling methods and six machine learning algorithms, twelve combinations of prediction models are established. A feature construction method based on the aerodynamic performance of the wing and the energy relationship of the hybrid system is introduced. The best combination is obtained by considering the root mean square error, and it shows improved accuracy compared to the white box model. The proposed grey box model can accurately predict the daily fuel consumption of wing-diesel hybrid vessels, contributing to operational optimization and the greenization and decarbonization of the shipping industry.
Article
Thermodynamics
Huayi Chang, Nico Heerink, Junbiao Zhang, Ke He
Summary: This study examines the interaction between off-farm employment decisions between couples and household clean energy consumption in rural China, and finds that two-paycheck households are more likely to consume clean energy. The off-farm employment of women is a key factor driving household clean energy consumption to a higher level, with wage-employed wives having a stronger influence on these decisions than self-employed ones.
Article
Thermodynamics
Hanguan Wen, Xiufeng Liu, Ming Yang, Bo Lei, Xu Cheng, Zhe Chen
Summary: Demand-side management is crucial to smart energy systems. This paper proposes a data-driven approach to understand the relationship between energy consumption patterns and household characteristics for better DSM services. The proposed method uses a clustering algorithm to generate optimal customer groups for DSM and a deep learning model for training. The model can predict the possibility of DSM membership for a given household. The results demonstrate the usefulness of weekly energy consumption data and household socio-demographic information for distinguishing consumer groups and the potential for targeted DSM strategies.
Article
Thermodynamics
Xinglan Hou, Xiuping Zhong, Shuaishuai Nie, Yafei Wang, Guigang Tu, Yingrui Ma, Kunyan Liu, Chen Chen
Summary: This study explores the feasibility of utilizing a multi-level horizontal branch well heat recovery system in the Qiabuqia geothermal field. The research systematically investigates the effects of various engineering parameters on production temperature, establishes mathematical models to describe their relationships, and evaluates the economic viability of the system. The findings demonstrate the significant economic feasibility of the multi-level branch well system.
Article
Thermodynamics
Longxin Zhang, Songtao Wang, Site Hu
Summary: This investigation reveals the influence of tip leakage flow on the modern transonic rotor and finds that the increase of tip clearance size leads to a decline in rotor performance. However, an optimal tip clearance size can extend the rotor's stall margin.
Article
Thermodynamics
Kristian Gjoka, Behzad Rismanchi, Robert H. Crawford
Summary: This paper proposes a framework for assessing the performance of 5GDHC systems and demonstrates it through a case study in a university campus in Melbourne, Australia. The results show that 5GDHC systems are a cost-effective and environmentally viable solution in mild climates, and their successful implementation in Australia can create new market opportunities and potential adoption in other countries with similar climatic conditions.
Article
Thermodynamics
Jianwei Li, Guotai Wang, Panpan Yang, Yongshuang Wen, Leian Zhang, Rujun Song, Chengwei Hou
Summary: This study proposes an orientation-adaptive electromagnetic energy harvester by introducing a rotatable bluff body, which allows for self-regulation to cater for changing wind flow direction. Experimental results show that the output power of the energy harvester can be greatly enhanced with increased rotatory inertia of the rotating bluff body, providing a promising solution for harnessing wind-induced vibration energy.