Article
Green & Sustainable Science & Technology
Andres Alfonso Rosales-Munoz, Luis Fernando Grisales-Norena, Jhon Montano, Oscar Danilo Montoya, Alberto-Jesus Perea-Moreno
Summary: This study addresses the optimal power flow problem in DC networks using a master-slave solution methodology combining an optimization algorithm based on multiverse theory and the numerical method of successive approximation. Various optimization methods were used to validate the robustness and repeatability of the solution, with results showing that the multiverse optimizer offers the best solution quality and repeatability in networks of different sizes with various penetration levels of distributed power generation.
Article
Computer Science, Information Systems
Mohammad H. Nadimi-Shahraki, Shokooh Taghian, Seyedali Mirjalili, Laith Abualigah, Mohamed Abd Elaziz, Diego Oliva
Summary: The optimal power flow is a crucial tool in optimizing control parameters of a power system, with the whale optimization algorithm being widely used for such problems. This paper proposes an enhanced whale optimization algorithm to improve exploration ability and achieve better solutions across diverse power system scales. The comparison of results demonstrates that the enhanced algorithm outperforms other comparative algorithms in solving both single- and multi-objective optimal power flow problems.
Review
Engineering, Chemical
Ehsan Naderi, Hossein Narimani, Mahdi Pourakbari-Kasmaei, Fernando V. Cerna, Mousa Marzband, Matti Lehtonen
Summary: OPF is an essential tool in the operation and control of power grids, aiming to meet system demand at minimum cost, emission, and voltage deviation. As new limitations are introduced by power system operators, the complexity of the OPF problem increases, requiring the identification of appropriate solving methods.
Article
Engineering, Electrical & Electronic
Farid Mohammadi, Hamdi Abdi
Summary: This paper addresses the integrated optimal power and gas flow problem in a multicarrier energy system. It proposes a complex optimization problem and introduces a population-based evolutionary algorithm to solve it. The superior performance of the algorithm is confirmed through comparisons and benchmark function tests.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Engineering, Multidisciplinary
Ibrahim Demir, Berna Kiraz, Fatma Corut Ergin
Summary: In this study, two meta-heuristic approaches based on NSGA-II and AMOSA were proposed to solve the multi-objective capacitated multiple allocation hub location problem (MOCMAHLP). Experimental analysis and fine-tuning tests revealed that NSGA-II performs better for larger networks, while AMOSA performs better for smaller networks.
ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH
(2022)
Article
Energy & Fuels
Amir Imanloozadeh, Mohammad Nazififard, Seyyed Ali Sadat
Summary: The study aims to develop a sustainable smart energy management system for desert climate, analyzing the effectiveness of five metaheuristic optimization algorithms. The presented system is able to reduce energy expenses by around 50% in different cases, considering uncertain user behaviors and utilizing various weighting factors in a multiobjective function.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Computer Science, Information Systems
Mohamed A. M. Shaheen, Hany M. Hasanien, Ahmed Al-Durra
Summary: This paper proposes using the Heap optimization algorithm (HOA) to solve the optimal power flow (OPF) problem in electricity networks. The relationship between cost optimization and fitness function is crucial. Experimental results show that the proposed algorithm is flexible and applicable in various electric grids.
Article
Computer Science, Information Systems
Andres Alfonso Rosales Munoz, Luis Fernando Grisales-Norena, Jhon Montano, Oscar Danilo Montoya, Diego Armando Giral-Ramirez
Summary: This paper addresses the Optimal Power Flow (OPF) problem in Direct Current (DC) networks with Distributed Generators (DGs) integration using a master-slave methodology that combines the Salp Swarm Algorithm (SSA) and the Successive Approximations (SA) method. The results show that the proposed solution methodology achieved the best trade-off between power loss reduction and processing time for networks of any size.
Article
Engineering, Electrical & Electronic
Yaru Gu, Xueliang Huang, Zhong Chen
Summary: A novel data-driven approach is proposed to address the uncertainty caused by distributed generations in the distribution network. This approach learns the joint probability distribution of uncertain variables and uses robust optimization to solve the multi-stage stochastic linear dynamic optimal power flow problem. The feasibility and robustness of the proposed approach are verified through application verification for the IEEE-33 system and results are compared with other data-driven stochastic optimization methods.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Automation & Control Systems
Mahdi Mokhtarzadeh, Reza Tavakkoli-Moghaddam, Chefi Triki, Yaser Rahimi
Summary: This study develops a novel p-mobile hub location-allocation problem and proposes a multi-objective mixed-integer non-linear programming model to solve it. Implementing mobile hubs can reduce the costs of opening and closing hubs, but it also reduces facility lifespan and adds relevant costs.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2021)
Article
Computer Science, Information Systems
Andres Alfonso Rosales Munoz, Luis Fernando Grisales-Norena, Jhon Montano, Oscar Danilo Montoya, Alberto-Jesus Perea-Moreno
Summary: In this paper, a master-slave methodology combining multiverse optimization algorithm and power flow method is proposed to solve the optimal power flow problem in alternating current networks. The proposed approach divides the problem into master stage and slave stage, achieving significant reduction in power losses and excellent computational performance.
Article
Computer Science, Information Systems
Burcin Ozkaya, Ugur Guvenc, Okan Bingol
Summary: This paper presents an improved version of the LSHADE algorithm, which uses the FDB selection method to enhance search performance. Experimental results demonstrate the superior performance of the FDB-LSHADE algorithm in solving both benchmark and EHED problems.
Article
Computer Science, Artificial Intelligence
Serhat Duman, Jie Li, Lei Wu, Nuran Yorukeren
Summary: In modern power systems, energy obtained from different generating units must be suitably planned for optimal operating conditions. This paper addressed the security-constrained AC-DC optimal power flow problem using a symbiotic organisms search (SOS) algorithm, taking into account the uncertainty of wind, solar, and plug-in electric vehicle (PEV) energy systems.
Article
Computer Science, Information Systems
Joel A. Trejo-Sanchez, Candelaria E. Sansores-Perez, Jesus Garcia-Diaz, Jose Alberto Fernandez-Zepeda
Summary: This paper proposes the first approximation algorithm for computing the minimum hub cover set in arbitrary graphs. Experimental results show that the algorithm outperforms the theoretical approximation ratio for the input graph instances.
Article
Automation & Control Systems
Li-Ning Liu, Guang-Hong Yang
Summary: This article addresses the multiobjective energy management problem of integrated energy systems (IESs) in a distributed manner. A distributed algorithm with dynamic weights is proposed to assign multiple energy sources, allowing each participant to compute locally and share information with neighbors. Simulation studies demonstrate that the proposed algorithm can coordinate the conflicting objectives of economy and environment simultaneously and obtain the entire Pareto front.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Information Systems
Mohsen Tajdinian, Ali Reza Seifi, Mehdi Allahbakhshi
IEEE SYSTEMS JOURNAL
(2019)
Article
Green & Sustainable Science & Technology
Dariush Keihan Asl, Alireza Hamedi, Ali Reza Seifi
IET RENEWABLE POWER GENERATION
(2020)
Article
Engineering, Electrical & Electronic
Amin Farjah, Teymoor Ghanbari, Ali Reza Seifi
INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS
(2020)
Article
Engineering, Electrical & Electronic
Mehdi Zareian Jahromi, Mohsen Tajdinian, Junbo Zhao, Payman Dehghanian, Mehdi Allahbakhshi, Ali Reza Seifi
IET GENERATION TRANSMISSION & DISTRIBUTION
(2020)
Article
Engineering, Electrical & Electronic
Mohammad Javad Bordbari, Mohammad Rastegar, Ali Reza Seifi
IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF ELECTRICAL ENGINEERING
(2020)
Article
Computer Science, Information Systems
Soroush Senemar, Ali Reza Seifi, Mohammad Rastegar, Masood Parvania
IEEE SYSTEMS JOURNAL
(2020)
Article
Engineering, Electrical & Electronic
Babak Abdolmaleki, Qobad Shafiee, Ali Reza Seifi, Mohammad Mehdi Arefi, Frede Blaabjerg
IEEE TRANSACTIONS ON SMART GRID
(2020)
Article
Engineering, Electrical & Electronic
Mohsen Tajdinian, Mehdi Allahbakhshi, Ali Reza Seifi, Harold R. Chamorro, Mehdi Zareian Jahromi, Vijay K. Sood
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2020)
Article
Automation & Control Systems
Mehdi Ahrarinouri, Mohammad Rastegar, Ali Reza Seifi
Summary: This article explores the multiagent reinforcement learning approach for residential multicarrier energy management, employing Q-learning to provide the optimal solution and using a scenario-based method to address uncertainties. The simulated results demonstrate that the proposed method leads to lower cost schemes for consumers compared to traditional optimization-based energy management programs.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Review
Chemistry, Physical
Amin Shabanpour-Haghighi, Mina Karimaghaei
Summary: Multi-carrier energy networks (MCENs) have become an engaging research topic in recent years. This paper provides a comprehensive review on MCENs, including an overview of the energy hub concept, identification of less utilized devices, categorization of common problems, and discussion on future trends, main concerns, and challenges.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2022)
Article
Thermodynamics
Borhan Soleimani, Dariush Keihan Asl, Javad Estakhr, Ali Reza Seifi
Summary: This paper investigates the optimal operation of integrated electrical and water energy networks at the distribution level, taking into account the demand response program. By modeling and using specific methods, the coupling of water and electrical networks is achieved, leading to the objective of reducing operation costs.
Article
Computer Science, Information Systems
Dariush Keihan Asl, Ali Reza Seifi, Mohammad Rastegar, Morteza Dabbaghjamanesh, Nikos D. Hatziargyriou
Summary: This study proposes a two-level distributed energy scheduling framework for the coordinated operation of regional integrated energy systems, and investigates its effects on the optimal operation of multiarea energy systems. The research implements a distributed optimization framework based on the analytical target cascading structure, using an Augmented Lagrangian based penalty function to solve coordinated optimization problems of interconnected subsystems, and utilizing the teaching-learning based optimization algorithm to solve local optimization problems of individual energy systems.
IEEE SYSTEMS JOURNAL
(2022)
Article
Energy & Fuels
Mehdi Ahrarinouri, Mohammad Rastegar, Kiana Karami, Ali Reza Seifi
Summary: Energy management optimization in residential buildings is crucial for addressing the global energy crisis. This paper introduces a novel method that optimizes energy scheduling for multiple residential buildings through the transfer of energy concepts. The proposed method demonstrates effectiveness in improving energy costs.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Article
Computer Science, Hardware & Architecture
Reza Taghavi, Haidar Samet, Ali Reza Seifi, Ziad M. Ali
Summary: The study proposes a probabilistic optimal power-flow method that investigates spatial correlation among variables to achieve practical output distributions in power systems. The method offers high accuracy with less computational effort, and does not require knowledge of the probability distribution of the input variables.
IEEE CANADIAN JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING
(2022)
Article
Computer Science, Information Systems
Mahdi Amini, Haidar Samet, Ali Reza Seifi, Mujahed Al-Dhaifallah, Ziad M. Ali
