Article
Mathematics
Giresse Franck Noudjiep Djiepkop, Senthil Krishnamurthy
Summary: This study developed a Discrete Particle Swarm Optimization (DPSO) method to solve the problem of distribution system feeder reconfiguration. The method is capable of meeting power demand in both steady-state and dynamic power system operations, and outperforms other optimization algorithms in terms of actual power loss reduction and load balancing.
Article
Thermodynamics
Maryam Parvin, Hossein Yousefi, Younes Noorollahi
Summary: This study applied a multi-objective particle swarm optimization algorithm to three renewable micro grid configurations in Shiraz, Iran. The results showed that the simultaneous utilization of wind and solar energy was more beneficial, especially when considering carbon tax policies or renewable energy incentives for future applications.
ENERGY CONVERSION AND MANAGEMENT
(2023)
Article
Mathematics, Interdisciplinary Applications
Zhigao Huang, Farid Shahbaazy, Afshin Davarpanah
Summary: This study discusses the reconfiguration of distribution networks using UPQC and demonstrates through simulation experiments that it can reduce power loss and increase voltage.
Article
Computer Science, Artificial Intelligence
Diana Cristina Valencia-Rodriguez, Carlos A. Coello Coello
Summary: Particle Swarm Optimization (PSO) is a bio-inspired metaheuristic algorithm that utilizes information exchange between particles to explore the search space. This study focuses on the influence of the number of connections among particles in Multi-Objective Particle Swarm Optimizers (MOPSOs) using random regular graphs as the swarm topology. Experimental results indicate that a higher connection degree can lead to algorithm instability in various problems, and MOPSOs with the same connection degree exhibit similar behavior.
SWARM AND EVOLUTIONARY COMPUTATION
(2023)
Article
Energy & Fuels
Hui Hwang Goh, Shuaiwei Shi, Xue Liang, Dongdong Zhang, Wei Dai, Hui Liu, Shen Yuong Wong, Tonni Agustiono Kurniawan, Kai Chen Goh, Chin Leei Cham
Summary: This paper proposes a multi-stage methodology to optimize the energy management problem of microgrids considering the uncertainty of carbon trading market and demand side response. The scenario analysis method is used to tackle the uncertainty of renewable energy, and the characteristics of different load types are analyzed. The quantum particle swarm optimization algorithm is utilized to obtain the optimal solution. The results show that carbon trading market policy contributes to the reduction of carbon emissions and fossil fuel consumption, and a high load participation rate in demand side response can improve the operational economics of microgrids.
Article
Automation & Control Systems
Reza Sepehrzad, Ali Reza Moridi, Mohammad Esmaeil Hassanzadeh, Ali Reza Seifi
Summary: A control strategy based on PSO and energy management algorithms was proposed to optimize power distribution in the micro-grid and improve its reliability and control levels.
Article
Energy & Fuels
F. Sheidaei, A. Ahmarinejad, M. Tabrizian, M. Babaei
Summary: This paper presents a multi-objective optimization framework for solving the distribution feeder reconfiguration problem, considering factors such as demand response, renewable energy sources, and electrical energy storages. The results indicate that increasing system reliability and reducing losses lead to higher local generation unit production and operating costs. Additionally, considering dynamic topology and implementing demand response programs can effectively reduce losses and enhance reliability.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Computer Science, Information Systems
Zhenyu Meng, Yuxin Zhong, Guojun Mao, Yan Liang
Summary: In this paper, a new PSO variant is proposed to improve optimization performance by introducing a sorted particle swarm, novel adaptation schemes, and a fully-informed search scheme. Experimental results demonstrate the competitiveness of this algorithm with other state-of-the-art PSO variants on multiple test suites.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Interdisciplinary Applications
Xiaoli Shu, Yanmin Liu, Jun Liu, Meilan Yang, Qian Zhang
Summary: This paper proposes a multi-objective particle swarm optimization algorithm (D-MOPSO) to solve complex multi-objective optimization problems in the real world. It addresses the lack of convergence and diversity in traditional optimization methods and makes use of existing resources in the search process. D-MOPSO dynamically adjusts the population size based on the resources in the archive, improves particle exploration through local perturbations, and controls population size through non-dominated sorting and population density.
JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING
(2023)
Article
Multidisciplinary Sciences
Heba Askr, M. A. Farag, Aboul Ella Hassanien, Vaclav Snasel, Tamer Ahmed Farrag
Summary: This paper proposes a novel many-objective African vulture optimization algorithm (MaAVOA) to solve many-objective optimization problems by simulating African vultures' foraging and navigation behaviors. The algorithm introduces a new social leader vulture for the selection process and adapts an environmental selection mechanism based on the alternative pool to maintain diversity. The best-nondominated solutions are saved in an external Archive based on the Fitness Assignment Method (FAM) and a Reproduction of Archive Solutions (RAS) procedure is developed to improve the quality of archiving solutions.
Article
Computer Science, Artificial Intelligence
Ling-Ling Li, Jun-Lin Xiong, Ming-Lang Tseng, Zhou Yan, Ming K. Lim
Summary: This study establishes a dynamic reconfiguration integrated optimization model for active distribution network (ADN) and proposes a novel solving approach using multi-objective sparrow search algorithm. By considering distributed generation and time-varying load, the study aims to improve the power quality, economic benefits, and energy benefits of ADN. Experimental results show that the proposed method effectively reduces power loss and node voltage deviation.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Review
Green & Sustainable Science & Technology
Pouya Ifaei, Atefeh Tamaskani Esfehankalateh, Fatemeh Ghobadi, Behnam Mohammadi-Ivatloo, ChangKyoo Yoo
Summary: In recent decades, extensive research has been conducted to optimize sustainable energy, focusing on technical performance, economic profitability, and social acceptance. However, there has been limited systematic review of the most popular heuristic algorithms in this field. This study developed a Boolean logic-based program to investigate the applications of heuristic solvers in sustainable energy and explore the factors contributing to their success.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Computer Science, Artificial Intelligence
Boyang Qu, Guosen Li, Li Yan, Jing Liang, Caitong Yue, Kunjie Yu, Oscar D. Crisalle
Summary: This paper proposes a grid-guided particle swarm optimizer for solving multimodal multi-objective optimization problems. By using a grid in the decision space, the algorithm is able to detect promising subregions and generate multiple subpopulations, maintaining diversity and improving search efficiency. Experimental results demonstrate that the proposed algorithm outperforms other evolutionary methods.
APPLIED SOFT COMPUTING
(2022)
Article
Engineering, Electrical & Electronic
Waseem Haider, S. Jarjees Ul Hassan, Arif Mehdi, Arif Hussain, Gerardo Ondo Micha Adjayeng, Chul-Hwan Kim
Summary: Efficient network reconfiguration with the integration of distributed generation units plays a crucial role in mitigating power loss and voltage instability in distribution systems. The optimal placement and sizing of DGs, determined through a multi-objective particle swarm optimization algorithm, significantly improve system stability, reliability, and efficiency. Simulation results on an IEEE-33 bus radial distribution system demonstrate a substantial reduction in power loss and voltage deviation with the inclusion of DG units.
Article
Thermodynamics
Congyu Wang, Jiwei Song, Lingkai Zhu, Wei Zheng, Zhaozhao Liu, Chengkun Lin
Summary: This paper examines the relationship between the operational flexibility of CHP plants and consumption of renewable energy generation, proposing that plant-level operation domain models can improve overall flexibility. Additionally, reducing heating extraction pressure can further increase the operational flexibility of CHP plants and reduce CO2 emissions.
APPLIED THERMAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Hossein Lotfi, Reza Ghazi
Summary: Feeder reconfiguration is a crucial operational process in power distribution grids to manage system performance. A multi-objective optimization model is proposed in this study for dynamic feeder reconfiguration problem, considering distributed generators, energy storage systems, and solar photovoltaic units over multiple time intervals. The study also introduces a demand response program to incentivize energy consumers to rethink their consumption patterns.
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Hossein Lotfi
Summary: The paper suggests the joint operation of Distributed Generation Units (DGUs) and shunt capacitors (SCs) in the presence of demand response program (DRP) to maximize benefits. The Time of Use (TOU) mechanism is utilized to alter subscriber consumption patterns and enhance distribution system performance. A modified shuffled frog leaping algorithm (MSFLA) is proposed to overcome the complexity of determining optimal capacity for DGUs and SCs.
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Mohsen Noruzi Azghandi, Ali Asghar Shojaei, Saman Toosi, Hossein Lotfi
Summary: This study proposes a dynamic distribution network reconfiguration in the presence of distributed generation units and electrical vehicles, and introduces a time of use mechanism to enhance demand response. To address the complexity of the optimization problem, a hybrid improved particle swarm optimization - artificial bee colony optimization algorithm is presented. The experimental results demonstrate that the proposed method outperforms other evolutionary algorithms.
EVOLUTIONARY INTELLIGENCE
(2023)
Article
Engineering, Electrical & Electronic
Hossein Lotfi
Summary: This paper proposes a multi-objective framework for distribution network reconfiguration and capacitor allocation problem in the presence of distributed generation. An enhanced artificial bee colony optimization method is introduced to solve the complex optimization problem. The proposed approach achieves significant reductions in energy not supplied in two small-scale test systems.
ELECTRIC POWER COMPONENTS AND SYSTEMS
(2022)
Article
Energy & Fuels
Hossein Lotfi, Ali Asghar Shojaei
Summary: This research proposes an improved particle swarm optimization (IPSO) algorithm to address the problem of dynamic distribution feeder reconfiguration. Through changing customers' consumption patterns and introducing technologies such as energy storage systems, distributed generation units, and solar photovoltaic arrays, the performance of the distribution system is enhanced.
ENERGY SYSTEMS-OPTIMIZATION MODELING SIMULATION AND ECONOMIC ASPECTS
(2023)
Article
Engineering, Electrical & Electronic
Hossein Lotfi, Ali Azizivahed, Ali Asghar Shojaei, Seyedalireza Seyedi, Mohd Fauzi Bin Othman
Summary: This study aims to improve system reliability and network voltage security by solving the distribution network reconfiguration problem. Objective functions of energy not supplied and voltage stability index are defined for reliability and voltage security. A modified gravitational search algorithm is suggested, and the efficiency of the proposed method is demonstrated by comparing results with other evolutionary algorithms on two test systems.
ELECTRIC POWER COMPONENTS AND SYSTEMS
(2022)
Article
Multidisciplinary Sciences
Farshid Kiomarsi, Ali Asghar Shojaei, Sepehr Soltani, Hossein Lotfi
Summary: This study aims to propose optimal placement and power system development for electricity supply to a Nuclear Power Plant after an accident, by identifying suitable locations and using probabilistic methods and optimization algorithms for site determination and system development.
SN APPLIED SCIENCES
(2021)
Article
Multidisciplinary Sciences
Hossein Lotfi, Ali Asghar Shojaei, Vahid Kouhdaragh, Iraj Sadegh Amiri
SN APPLIED SCIENCES
(2020)
Article
Energy & Fuels
Hossein Lotfi, Reza Ghazi, Mohammad bagher Naghibi-Sistani
ENERGY SYSTEMS-OPTIMIZATION MODELING SIMULATION AND ECONOMIC ASPECTS
(2020)
