Article
Engineering, Electrical & Electronic
Ahmad M. Alshamrani
Summary: This research focuses on developing a mathematical methodology for joint transmission network and wind power investment problem under a centralized approach. The objective function is defined as the ratio of total cost to total wind power generation, allowing the operator to minimize overall cost while maximizing wind power output.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Computer Science, Information Systems
Baha Alzalg, Hadjer Alioui
Summary: This paper discusses five applications that lead to stochastic mixed-integer second-order cone programming problems, presents solution algorithms for solving these problems, and explores how bringing applications to the surface can detect tractable special cases.
Article
Environmental Sciences
Jin Huang, Jantien Stoter, Ravi Peters, Liangliang Nan
Summary: This paper presents a fully automatic approach for reconstructing compact 3D building models from large-scale airborne point clouds. The approach addresses the challenge of missing vertical walls by inferring them directly from the data. The method outperforms state-of-the-art methods in terms of reconstruction accuracy and robustness, as demonstrated in experiments on various large-scale airborne LiDAR point clouds. Additionally, the authors have generated a new dataset with their method, which can stimulate research in urban reconstruction and the use of 3D city models in urban applications.
Article
Management
Evren Guney, Markus Leitner, Mario Ruthmair, Markus Sinnl
Summary: Influence maximization aims to identify key individuals in a network to maximize the number of individuals reached through information propagation. It can be modeled as a stochastic maximal covering location problem based on the probabilistic independent cascade model. Preprocessing tests and efficient algorithms for separating Benders cuts play crucial roles in the branch-and-cut algorithm.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Operations Research & Management Science
Saravanan Venkatachalam, Lewis Ntaimo
Summary: This paper develops the theory of integer set reduction for solving two-stage stochastic mixed-integer programs with general integer variables in the second-stage. The goal is to generate a valid inequality by using the smallest possible subset of the subproblem feasible integer set, similar to Fenchel decomposition cuts, in order to reduce computation time. An algorithm is devised to obtain such a subset based on the solution of the subproblem linear programming relaxation and incorporated into a decomposition method for SMIP. A computational study based on randomly generated knapsack test instances demonstrates the effectiveness of the new integer set reduction methodology in speeding up cut generation and obtaining better bounds compared to using a direct solver in solving SMIPs with pure integer recourse.
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
(2023)
Article
Construction & Building Technology
Amirhossein Fani, Amir Golroo, S. Ali Mirhassani, Amir H. Gandomi
Summary: The study aims to develop an optimization framework for network-level pavement maintenance and rehabilitation planning considering the uncertain nature of pavement deterioration and the budget with a multistage stochastic mixed-integer programming model. The proposed model can find the optimal plan feasible for all possible scenarios of uncertainty and optimize the expectation of the objective function.
INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
(2022)
Article
Computer Science, Software Engineering
Xian Yu, Siqian Shen
Summary: In this study, we investigate multistage distributionally robust mixed-integer programs with endogenous uncertainty. We propose two ambiguity sets based on decision-dependent bounds and empirical moments. We show that the subproblems in each stage can be formulated as mixed-integer linear programs. Additionally, we extend the moment-based ambiguity set and derive mixed-integer semidefinite programming reformulations. We develop methods to approximate the optimal objective value and solve the problem using the Stochastic Dual Dynamic integer Programming (SDDiP) method. Numerical experiments demonstrate the effectiveness of the proposed approach in solving multistage facility-location problems with decision-dependent distributional ambiguity.
MATHEMATICAL PROGRAMMING
(2022)
Article
Construction & Building Technology
Md. Tareq Hossain Khondoker
Summary: This research aims to optimize the use of market length rebars in RC frame construction by proposing an automated framework based on BIM and MILP. By automatically extracting reinforcement detailing data and generating necessary cutting patterns, the proposed method efficiently reduces trim waste in a cost-effective manner.
AUTOMATION IN CONSTRUCTION
(2021)
Article
Engineering, Electrical & Electronic
Bruno Colonetti, Erlon Finardi, Samuel Brito, Victor Zavala
Summary: Unit commitment is a complex problem in power system operations that has yet to be fully solved. Operators currently use optimization solvers and simplifications to address the problem, but solving it in a timely manner remains a challenge. This study proposes a parallel dynamic integer programming approach for solving the unit commitment problem, which has been successfully applied to different power systems with impressive speed-ups compared to sequential strategies.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Computer Science, Software Engineering
Fengqiao Luo, Sanjay Mehrotra
Summary: The paper introduces a decomposition algorithm for distributionally-robust two-stage stochastic mixed-integer convex conic programs, ensuring finite convergence by solving second-stage problems to optimality and identifying worst-case probability distribution. The algorithm can be used with a branch and cut algorithm or a parametric cuts based algorithm for solving second stage problems. An example illustration of the decomposition algorithm shows significant improvements in solution time, making solutions possible for previously intractable models. Computational results also indicate similar optimality gaps between distributionally robust instances and their stochastic programming counterparts.
MATHEMATICAL PROGRAMMING
(2022)
Article
Management
Niels van der Laan, Ward Romeijnders
Summary: We propose a new solution method for two-stage mixed-integer recourse models that can handle general mixed-integer variables in both stages. Our method is based on Benders' decomposition, where we iteratively construct tighter approximations of the expected second stage cost function using a new family of optimality cuts derived from extended formulations of the second stage problems. We show convergence of our method by proving that the optimality cuts recover the convex envelope of the expected second stage cost function. Finally, we demonstrate the potential of our approach through numerical experiments on investment planning and capacity expansion problems.
OPERATIONS RESEARCH
(2023)
Article
Biochemical Research Methods
Enio Gjerga, Aurelien Dugourd, Luis Tobalina, Abel Sousa, Julio Saez-Rodriguez
Summary: Protein post-translational modifications are crucial for cellular processes, and mass spectrometry analysis of proteome modifications can provide insights into signaling mechanisms. The newly formulated PHONEMeS method as an Integer Linear Program (ILP) is significantly more efficient and can analyze data sets with multiple time points to understand signal propagation dynamics. This study expands the analysis scenarios and sheds light on signaling mechanisms and drug modes of action.
JOURNAL OF PROTEOME RESEARCH
(2021)
Article
Energy & Fuels
Cormac O'Malley, Patrick de Mars, Luis Badesa, Goran Strbac
Summary: Decarbonisation is driving the growth of renewable power generation and increasing uncertainty in power plant scheduling. This paper compares traditional mathematical programming methods with emerging reinforcement learning methods, finding that the former is more reliable and scalable with lower costs. However, the strength of reinforcement learning lies in its ability to produce instant solutions.
Article
Thermodynamics
Yingzong Liang, Chi Wai Hui, Xianglong Luo, Jianyong Chen, Zhi Yang, Ying Chen
Summary: The proposed equation-based optimization framework provides a comprehensive modeling structure for various thermodynamic cycle design problems, offering efficient and effective solutions for solving thermodynamic cycle and related energy systems optimization problems.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Management
Btissam Er-Rahmadi, Tiejun Ma
Summary: In this paper, a new Mixed Integer Linear Programming (MILP) optimization-based failure detector (FD) algorithm is proposed. The MILP formulation is obtained via piecewise linearization relaxations and aims to find optimal FD parameters that meet the desired system requirements. The proposed approach improves overall FD performance and scalability by considering network conditions and system parameters as constraints and adapting to real-time network changes. The results obtained from testing in a realistic environment show consistent improvement in the performance and scalability of the FD. This paper is the first attempt to combine MILP-based optimization modeling with FD to achieve performance guarantees.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Green & Sustainable Science & Technology
V. N. Sewdien, R. Preece, J. L. Rueda Torres, E. Rakhshani, M. van der Meijden
Review
Energy & Fuels
Zameer Ahmad, Jose Rueda Torres, Nidarshan Veera Kumar, Elyas Rakhshani, Peter Palensky, Mart van der Meijden
Article
Energy & Fuels
Mostafa Abdollahi, Jose Ignacio Candela, Andres Tarraso, Mohamed Atef Elsaharty, Elyas Rakhshani
Summary: Modern power converters in renewable power plants provide flexible electromechanical characteristics through developed control technologies, such as Synchronous Power Controller (SPC), to support dynamic stability in the power generation area. A novel mathematical pattern and strategy were proposed to adjust dynamic parameters in Renewable Static Synchronous Generators controlled by SPC (RSSG-SPC), showing effective results in grid connection.
Review
Energy & Fuels
Jose Rueda Torres, Zameer Ahmad, Nidarshan Veera Kumar, Elyas Rakhshani, Ebrahim Adabi, Peter Palensky, Mart van der Meijden
Summary: Future electrical power systems will be dominated by power electronic converters, where control strategies play a crucial role in system stability. Research shows that laboratory-scale setups are key tools for evaluating the performance of different converter technologies and control strategies.
Article
Engineering, Electrical & Electronic
Elyas Rakhshani, Iman Mohammad Hosseini Naveh, Hasan Mehrjerdi
Summary: This paper introduces a new application of an advanced SMPI controller for frequency control in an interconnected dynamic system with VSP-based HVDC links. The SMPI is tuned using PSO, GOA, and GWO algorithms, with a focus on enhancing dynamic performance during contingencies and emulating virtual inertia. The study demonstrates significant improvements in frequency deviations and damping of inter-area oscillations, especially when using the GWO method for tuning the SMPI controller.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Elyas Rakhshani, Iman Mohammad Hosseini Naveh, Hasan Mehrjerdi, Kaikai Pan
Summary: This paper proposes a novel application of the optimal LQG servo controller for better coordination of AC/HVDC interconnected system with VSP-based inertia emulation. The proposed LQG controller design combines Kalman Filter and Linear Quadratic Integrator for state observation and reference tracking while rejecting noise, and utilizes a swarm-based optimization algorithm for tuning. The optimal LQG controller stabilizes the system, minimizes performance index, and achieves satisfactory performance in estimating state variables and tracking reference signals.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Computer Science, Information Systems
Jose Rueda Torres, Nidarshan Veera Kumar, Elyas Rakhshani, Zameer Ahmad, Ebrahim Adabi, Peter Palensky, Mart van der Meijden
Summary: This paper discusses the feasibility of Fast Active Power Regulation (FAPR) in renewable energy hubs, utilizing advanced FAPR strategies to control various controllable devices within a hub. Real-time simulations show that FAPR strategies, especially the VSP-based FAPR, can successfully help to significantly and promptly limit undesirable large instantaneous frequency deviations.
Article
Engineering, Electrical & Electronic
Reza Bakhshi-Jafarabadi, Javad Sadeh, Elyas Rakhshani, Marjan Popov
Summary: The paper introduces a new methodology based on high PQ maximum power point tracking for detecting the islanding operating mode of grid-connected photovoltaic systems. By injecting disturbance into the MPPT algorithm and applying passive criteria under suspicious conditions, precise islanding classification within 137 ms is achieved.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Review
Green & Sustainable Science & Technology
Reza Bakhshi-Jafarabadi, Javad Sadeh, Alexandre Serrano-Fontova, Elyas Rakhshani
Summary: This paper provides a comprehensive review on the recently developed islanding detection methods for grid-following/grid-connected photovoltaic system, analyzing their existing limitations and suggesting possible future research implementations. Through an in-depth comparison considering main features such as non-detection zone, detection time, implementation cost and complexity, and power quality degradation, the advantages and disadvantages of these methods are evaluated. The main technical requirements established by the current grid codes are also recalled, and potential multi-functional approaches to expand the current islanding detection capabilities are identified.
IET RENEWABLE POWER GENERATION
(2022)
Article
Energy & Fuels
Mansour Selseleh Jonban, Luis Romeral, Elyas Rakhshani, Mousa Marzband
Summary: This study proposes a novel smart multi-agent-based framework under a tendering process framework with a bottom-up approach to control and manage the flow of energy into a grid-connected microgrid. The first-price sealed-bid algorithm is implemented to optimize the electricity cost and decrease the use of grid power. The proposed approach optimally allocates energy among generators and guarantees the system from blackouts.
Article
Computer Science, Information Systems
Seyed Ebrahim Hosseini Kakolaki, Vahid Hakimian, Javad Sadeh, Elyas Rakhshani
Summary: The sudden outage of a transformer due to a fault can cause irreparable damage to the electricity industry. By conducting momentarily inspections of the transformer's condition, faults can be promptly detected and disconnected from the power grid to prevent subsequent failures. Frequency Response Analysis (FRA) is a promising technique for fault detection as it compares the transformer's response in healthy and faulty conditions.
Proceedings Paper
Automation & Control Systems
C. Zhang, E. Rakhshani, N. Veera Kumar, J. L. Rueda-Torres, P. Palensky, F. Gonzalez-Longatt
Summary: This paper introduces a novel approach to improve frequency dynamics by combining ultracapacitors with fully decoupled wind power generation units; The presented UC model implementation is suitable for real-time simulations, demonstrating the fast UC dynamics occurring within the first milliseconds of the time period of action for fast active-power frequency control services.
IECON 2021 - 47TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY
(2021)
Review
Energy & Fuels
Mehran Dehghan, Carlos F. Pfeiffer, Elyas Rakhshani, Reza Bakhshi-Jafarabadi
Summary: This paper discusses the feasibility of solar water heating systems in the Middle East region from technical and economic perspectives, while examining progress, challenges, and barriers in this market. It assesses pay-back times and CO2 emissions reduction under different incentive frameworks and system configurations. Additionally, it reports on the advantages and weaknesses of SWHS in several countries and proposes guidelines to enhance the development of this technology.
Article
Computer Science, Information Systems
Iman M. Hosseini Naveh, Elyas Rakhshani, Hasan Mehrjerdi, Mohamed A. Elsaharty
Summary: This study presents a comprehensive evaluation of the utilization of quasi-oppositional-based learning method in output tracking control through a swarm-based multivariable Proportional-Integral-Derivative (SMPID) controller tuned by a novel performance index. The results demonstrate that the tuned SMPID controller significantly enhances the capability of tracking control on the proposed AC/HVDC interconnected model.
Article
Computer Science, Information Systems
Chenrui Zhang, Elyas Rakhshani, Nidarshan Veerakumar, Jose Luis Rueda Torres, Peter Palensky
Summary: This paper investigates the improvement of frequency response of fully decoupled wind power generators by introducing ultracapacitors and hybrid energy storage systems in real-time simulations, and discusses the trade-off between frequency performance and cost through optimization. The results show that fast UC power injection enhances the frequency response speed, with virtual synchronous power providing faster frequency support compared to other control strategies.
Article
Green & Sustainable Science & Technology
Lars odegaard Bentsen, Narada Dilp Warakagoda, Roy Stenbro, Paal Engelstad
Summary: This study investigates uncertainty modeling in wind power forecasting using different parametric and non-parametric methods. Johnson's SU distribution is found to outperform Gaussian distributions in predicting wind power. This research contributes to the literature by introducing Johnson's SU distribution as a candidate for probabilistic wind forecasting.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Xing Liu, Qiuchen Wang, Yunhao Wen, Long Li, Xinfang Zhang, Yi Wang
Summary: This study analyzes the characteristics of process parameters in three lean gas ethane recovery processes and establishes a prediction and multiobjective optimization model for ethane recovery and system energy consumption. A new method for comparing ethane recovery processes for lean gas is proposed, and the addition of extra coolers improves the ethane recovery. The support vector regression model based on grey wolf optimization demonstrates the highest prediction accuracy, and the multiobjective multiverse optimization algorithm shows the best optimization performance and diversity in the solutions.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Cairong Song, Haidong Yang, Xian-Bing Meng, Pan Yang, Jianyang Cai, Hao Bao, Kangkang Xu
Summary: The paper proposes a novel deep learning-based prediction framework, aTCN-LSTM, for accurate cooling load predictions. The framework utilizes a gate-controlled multi-head temporal convolutional network and a sparse probabilistic self-attention mechanism with a bidirectional long short-term memory network to capture both temporal and long-term dependencies in the cooling load sequences. Experimental results demonstrate the effectiveness and superiority of the proposed method, which can serve as an effective guide for HVAC chiller scheduling and demand management initiatives.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Zhe Chen, Xiaojing Li, Xianli Xia, Jizhou Zhang
Summary: This study uses survey data from the Loess Plateau in China to evaluate the impact of social interaction on the adoption of soil and water conservation (SWC) technology by farmers. The study finds that social interaction increases the likelihood of farmers adopting SWC, and internet use moderates this effect. The positive impact of social interaction on SWC adoption is more pronounced for farmers in larger villages and those who join cooperative societies.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Chenghua Zhang, Yunfei Yan, Kaiming Shen, Zongguo Xue, Jingxiang You, Yonghong Wu, Ziqiang He
Summary: This paper reports a novel method that significantly improves combustion performance, including heat transfer enhancement under steady-state conditions and adaptive stable flame regulation under velocity sudden increase.
JOURNAL OF CLEANER PRODUCTION
(2024)
