Article
Engineering, Electrical & Electronic
Marco Balletti, Veronica Piccialli, Antonio M. Sudoso
Summary: This paper proposes a novel two-stage optimization-based approach for energy disaggregation, which efficiently infers the energy consumption of each appliance. The approach leverages appliance-specific constraints and prior knowledge to overcome the drawbacks of existing optimization methods.
IEEE TRANSACTIONS ON SMART GRID
(2022)
Article
Energy & Fuels
Mang Jiang, Qinglai Guo, Hongbin Sun, Huaichang Ge
Summary: This paper proposes a model called DPWLPF for optimizing power flow problems in transmission systems. The P-Q decoupling characteristic reduces the coupling between variables and an UVLS method based on DPWLPF is presented. For large systems, DPWLPF outperforms conventional piecewise models.
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
(2021)
Article
Automation & Control Systems
Shitikantha Dash, Ranjana Sodhi, Balwinder Sodhi
Summary: This article proposes a simple yet effective two-stage nonintrusive appliance load monitoring scheme, combining automatic state detection and enhanced integer programming-based load disaggregation to address household appliance power consumption measurement effectively.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Operations Research & Management Science
Sonja Steffensen
Summary: In this paper, a method for dealing with non-linear sparse optimization problems is introduced. The exact reformulations and their relaxations using the l(0) norm are presented, leading to standard non-linear but non-convex programming problems. The effectiveness of this method is verified through numerical tests.
Article
Computer Science, Interdisciplinary Applications
Guowen Lei, Thiago Lima Silva, Milan Stanko
Summary: A compact formulation has been developed for optimizing early-stage field development planning of multi-reservoir fields, maximizing project economic value. This novel approach includes scalable model for well combination selection, logarithmic piecewise-linear model to approximate well production potential curves, and realistic field development optimization. Simulation analysis shows that logarithmic formulation significantly reduces computational time and improves accuracy over standard SOS2 formulations.
COMPUTERS & CHEMICAL ENGINEERING
(2021)
Article
Green & Sustainable Science & Technology
Khaled Alhamad, Yousuf Alkhezi, M. F. Alhajri
Summary: Preventive maintenance is a program designed to reduce the likelihood of failure or deterioration of item performance. This study proposes a preventive maintenance schedule for electricity and water in power plants using a nonlinear integer programming model.
Article
Computer Science, Artificial Intelligence
Bahriye Akay, Dervis Karaboga, Beyza Gorkemli, Ebubekir Kaya
Summary: This paper reviews the use of Artificial Bee Colony algorithm for solving discrete numeric optimization problems, discussing various encoding types, search operators and selection operators integrated into ABC. It is the first comprehensive survey study on this topic and aims to benefit readers interested in utilizing ABC for binary, integer and mixed integer discrete optimization problems.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Hardware & Architecture
Kiyo Ishii, Shu Namiki
Summary: This study developed an optical path computation prototype based on a functional block-based disaggregation approach, supporting various optical node structures and computationally intensive flexible grid mechanism. By employing integer linear programming as a generic computational method, universal path computation applicable to any node structure was achieved, and the computation time was evaluated and optimized.
JOURNAL OF OPTICAL COMMUNICATIONS AND NETWORKING
(2022)
Article
Thermodynamics
Yannick Wack, Sylvain Serra, Martine Baelmans, Jean-Michel Reneaume, Maarten Blommaert
Summary: This paper compares two nonlinear topology optimization methods for District Heating Networks in terms of computational cost and optimality gap. The benchmark demonstrates that the density-based approach has subquadratic scaling in computational cost, making it suitable for large-scale problems, while the combinatorial approach has exponential scaling. The density-based method optimized a network for 600 streets in only 35 minutes, compared to 29 hours required by the combinatorial approach. Resolving the integer constraint on pipe placement does not necessarily lead to a superior design, but makes optimization of large-scale problems intractable. Further study highlights the importance of initialization strategies when solving the nonlinear topology optimization problem.
Article
Computer Science, Software Engineering
Ashutosh Mahajan, Sven Leyffer, Jeff Linderoth, James Luedtke, Todd Munson
Summary: The study introduces a flexible MINLP framework called Minotaur, which allows for algorithm exploration and structure exploitation while maintaining high computational efficiency. Efficient implementations of standard MINLP techniques and structure-exploiting extensions are demonstrated to have a significant impact on solution times. Global solutions to difficult nonconvex MINLP problems may be unreachable without a flexible framework that enables structure exploitation.
MATHEMATICAL PROGRAMMING COMPUTATION
(2021)
Article
Computer Science, Artificial Intelligence
Daniel Molina-Perez, Efren Mezura-Montes, Edgar Alfredo Portilla-Flores, Eduardo Vega-Alvarado, Barbara Calva-Yanez
Summary: This paper presents a new proposal based on two fundamental strategies to improve the performance of the differential evolution algorithm when solving MINLP problems. The proposal considers a set of good fitness-infeasible solutions to explore promising regions and introduces a composite trial vector generation method to enhance combinatorial exploration and convergence capacity.
SWARM AND EVOLUTIONARY COMPUTATION
(2024)
Article
Chemistry, Multidisciplinary
Min Yuan, Yu Li, Wenqiang Xu, Wei Cui
Summary: The study optimized the blending scheme of industrial lubricating oil through a linear weighted multi-objective optimization model based on integer nonlinear programming, providing good prospects for application.
APPLIED SCIENCES-BASEL
(2021)
Article
Management
Thomas L. Magnanti
Summary: Optimization is one of the most fundamental contributions of management science/operations research, with early researchers laying the foundations for fields such as linear programming and integer programming. With the development of computational methods, optimization has been widely applied in various fields.
MANAGEMENT SCIENCE
(2021)
Article
Operations Research & Management Science
Hacene Ouzia, Nelson Maculan
Summary: This work introduces new mixed integer nonlinear optimization models for the Euclidean Steiner tree problem in high dimensions (d >= 3), featuring nonsmooth objective functions with convex continuous relaxations. Four convex mixed integer linear and nonlinear relaxations derived from these models are considered, each having the same feasible solutions as their respective original models. Preliminary computational results discussing the main features of these relaxations are presented.
JOURNAL OF GLOBAL OPTIMIZATION
(2022)
Article
Computer Science, Software Engineering
Ilias Zadik, Miles Lubin, Juan Pablo Vielma
Summary: We investigate the structural geometric properties of mixed-integer convex representable (MICP-R) sets and compare them with the class of mixed-integer linear representable (MILP-R) sets. We provide examples of MICP-R sets that are countably infinite unions of convex sets with countably infinitely many different recession cones, and countably infinite unions of polytopes with different shapes. These examples highlight the differences between MICP-R sets and MILP-R sets.
MATHEMATICAL PROGRAMMING
(2023)
Article
Computer Science, Information Systems
Mehdi Mehdinejad, Heidar Ali Shayanfar, Behnam Mohammadi-Ivatloo, Hamed Nafisi
Summary: This paper proposes a fully decentralized local energy market for small-scale prosumers based on peer-to-peer trading. The buyers and sellers can engage in energy trading with each other, and the buyer prosumers can participate in demand response programs while protecting their privacy. The proposed approach uses robust optimization and the fast alternating direction method of multipliers for solving the decentralized robust problem.
Article
Thermodynamics
Mehdi Mehdinejad, Heidarali Shayanfar, Behnam Mohammadi-Ivatloo
Summary: This paper designs and models a fully decentralized peer-to-peer energy token market for small-scale prosumers using blockchain technology. The market incorporates the demand response program and demurrage mechanism, allowing sellers and buyers to engage in energy token transactions with each other under agreed prices. The proposed market-clearing scheme guarantees a global and feasible solution without players' private information. Numerical studies demonstrate the feasibility and effectiveness of the proposed market and clearing approach.
Editorial Material
Chemistry, Multidisciplinary
Amjad Anvari-Moghaddam, Behnam Mohammadi-Ivatloo, Somayeh Asadi, Mohammad Shahidehpour
APPLIED SCIENCES-BASEL
(2022)
Article
Automation & Control Systems
Amirhossein Ahmadi, Mojtaba Nabipour, Saman Taheri, Behnam Mohammadi-Ivatloo, Vahid Vahidinasab
Summary: With the increasing penetration of renewable energies and information technology, power systems are evolving into more efficient and intelligent cyber-physical energy systems. Accurate and complex forecasting is crucial for these systems, but relies heavily on data quality, which is vulnerable to cyberattacks. This article proposes a novel data-driven mechanism to detect false data injection (FDI) attacks, enhancing the reliability and resilience of energy forecasting systems without relying on system models or parameters.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Chemistry, Multidisciplinary
Waleed Abdulrazzaq Oraibi, Behnam Mohammadi-Ivatloo, Seyed Hossein Hosseini, Mehdi Abapour
Summary: This paper proposes a practical and effective planning approach that utilizes mobile energy storage systems (MESSs) to enhance distribution system resilience against blackouts. A joint post-disaster restoration strategy is suggested to reduce total system costs and account for uncertainties. The suggested model effectively decreases costs and enhances the DS resilience level.
APPLIED SCIENCES-BASEL
(2023)
Review
Energy & Fuels
Mehrdad Tarafdar-Hagh, Kamran Taghizad-Tavana, Mohsen Ghanbari-Ghalehjoughi, Sayyad Nojavan, Parisa Jafari, Amin Mohammadpour Shotorbani
Summary: The transportation sector is a major contributor to greenhouse gas emissions globally, and electrifying this sector can significantly reduce pollutant emissions. The widespread connection of electric vehicles (EVs) to the power grid may bring challenges, such as increasing the network's peak load. Therefore, optimizing the use of EVs is necessary to improve the network's economic, security, and stability indicators. This review article examines different control models, EV models, and their comparison, communication standards for charging stations, the effects of EV integration with the power grid, and various charging methods. Additionally, it investigates battery technology and energy management systems in the electric vehicle industry, as well as government incentives and the combination of EVs with renewable energy sources.
Article
Computer Science, Information Systems
Amin Mansour Saatloo, Mohammad Amin Mirzaei, Behnam Mohammadi-Ivatloo
Summary: This article proposes a novel platform for MG prosumers to actively trade energy with each other directly. P2P energy trading is introduced to achieve a win-win outcome and facilitate energy balance locally. The numerical results show that prosumers can actively trade with each other and achieve economic benefits.
IEEE SYSTEMS JOURNAL
(2023)
Article
Computer Science, Information Systems
Ramin Nourollahi, Reza Gholizadeh-Roshanagh, Hamideh Feizi-Aghakandi, Kazem Zare, Behnam Mohammadi-Ivatloo
Summary: This article proposes a risk-based stochastic optimization framework to model the participation of distribution system operators in distribution expansion planning problems in the presence of electricity wholesale multimarkets. By using the benefits and risks of the existing multimarkets, DSOs can manage long-term uncertainties and cover their costs by offering fair retail prices. Additionally, DSOs can form diverse portfolios from different electricity markets to procure the forecasted loads and loss power. By considering multimarkets and market price uncertainties, DSOs can reduce network loss costs and increase profit.
IEEE SYSTEMS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Mohammadreza Daneshvar, Behnam Mohammadi-Ivatloo, Kazem Zare
Summary: This paper proposes a transactive energy solution for the operation of multi-carrier multi-microgrids with 100% renewable energy sources by co-optimizing power and gas grids. The stochastic CVaR technique is developed to model the risk of energy interactions in the presence of uncertainties in the energy production sector. The results demonstrate the effectiveness of the proposed model in integrating 100% renewable energy sources and providing a fair condition for multi-carrier microgrids in the energy grid.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Green & Sustainable Science & Technology
Hassan Khazaei, Hossein Aghamohammadloo, Milad Habibi, Mehdi Mehdinejad, Amin Mohammadpour Shotorbani
Summary: This paper proposes a novel decentralized energy market that allows retailers and prosumers to trade electricity and gas in a peer-to-peer manner. The market considers integrated demand response and aims to maximize welfare for retailers. The study demonstrates the feasibility and effectiveness of the proposed decentralized market using a fully decentralized approach called the fully decentralized ADMM. The results show that the proposed decentralized algorithm achieves the optimal global solution compared with the centralized approach.
Review
Mathematics, Interdisciplinary Applications
Masoud Alilou, Hatef Azami, Arman Oshnoei, Behnam Mohammadi-Ivatloo, Remus Teodorescu
Summary: The rapid growth in the worldwide energy crisis and greenhouse emissions have prompted the adoption of demand-side manageable energy systems such as wind turbines, photovoltaic panels, electric vehicles, and energy storage systems. The control system of renewable energy units and energy storage systems play a crucial role in their performance and overall power network efficiency. This paper provides a comprehensive review of the energy system of renewable energy units and energy storage devices, evaluating various papers and presenting their methods and results. It also explores the potential of fractional-order control techniques for modeling and controlling energy systems, categorizing studies based on different parameters and explaining the mathematical fundamentals behind fractional-order calculus. The findings highlight the significant efficiency and accuracy of fractional-order techniques in estimating, controlling, and improving the performance of energy systems compared to other methods.
FRACTAL AND FRACTIONAL
(2023)
Article
Engineering, Electrical & Electronic
Amirhossein Ahmadi, Saman Taheri, Reza Ghorbani, Vahid Vahidinasab, Behnam Mohammadi-Ivatloo
Summary: This study proposes a new ensemble model for dynamic line rating forecasting of overhead transmission lines. By utilizing multivariate empirical mode decomposition, the proposed ensemble model overcomes the limitations of single models and improves the forecasting performance. The results show that the ensemble model can accurately predict the dynamic line rating and is robust to noisy data.
IEEE TRANSACTIONS ON POWER DELIVERY
(2023)
Article
Green & Sustainable Science & Technology
Mohammadreza Daneshvar, Behnam Mohammadi-ivatloo, Amjad Anvari-Moghaddam
Summary: A comprehensive water-energy nexus model is developed for cooperative prosumers equipped with 100% renewable energy sources in the modern interconnected energy structure. The model utilizes transactive energy technology to enable prosumers to cooperatively share multi-energy in a deregulated environment, ensuring reliable power and water supply. A risk-averse stochastic operational model is proposed to address the high risks associated with renewable energy intermittences.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2023)
Article
Computer Science, Information Systems
Hamed Moayyed, Arash Moradzadeh, Amin Mansour-Saatloo, Behnam Mohammadi-Ivatloo, Mehdi Abapour, Zita Vale
Summary: This article presents a novel model for dynamic line rating (DLR) forecasting using a federated learning approach. By generating a global model, the approach accurately predicts the maximum current carrying capacity of transmission lines while ensuring data security and protection from cyberattacks. The proposed model is trained using data from nine different regions in Iran and successfully predicts DLR values for new regions with correlation coefficients of 96%, 94%, and 97% for Boroujen, Nahavand, and Rafsanjan, respectively.
IEEE SYSTEMS JOURNAL
(2023)
Article
Business
Mohammadreza Daneshvar, Behnam Mohammadi-ivatloo, Kazem Zare, Amjad Anvari-Moghaddam
Summary: This article aims to develop a novel framework for achieving techno-economic-environmental goals in the grid modernization process. It explores the optimal utilization of energy hubs equipped with 100% renewables to pursue environmental goals while considering technical and economic constraints. The power-to-gas system enables multienergy interactions between electricity and gas networks. Risk-averse and seeker strategies are developed to deal with uncertain fluctuations, based on robustness and opportunistic modes of the information gap decision theory. The proposed framework provides a rational decision-making model for balancing multienergy in the hybrid energy grid with 100% renewables.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2023)
