Article
Mathematics, Interdisciplinary Applications
Saurav Raj, Sheila Mahapatra, Rohit Babu, Sumit Verma
Summary: This work presents the Chimp Optimization Algorithm (COA), a contemporary heuristic approach that consolidates chaotic maps. By adding ten chaotic maps to COA, the hybrid Chaotic COA (CCOA) is formed, which generates solutions with enhanced mobility in the search space. The robustness of the proposed hybrid method is validated through benchmarking on different test functions and statistical analysis. The results show that merging chaotic maps, especially the Chaotic 4 Iterative type (CCOA4), improves the performance of COA. The recommended algorithm is applied to the challenging problem of reactive power dispatch (RPD) in power system operation, resulting in a significant reduction in operating cost.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Computer Science, Artificial Intelligence
Bimal Kumar Dora, Abhishek Rajan, Sourav Mallick, Sudip Halder
Summary: This paper introduces an enhanced Butterfly Optimization Algorithm (EBOA) to solve the Optimal Reactive Power Dispatch (ORPD) problem. The algorithm is evaluated using various test systems and benchmark problems, and the results demonstrate its efficiency and robustness in reducing power loss, voltage deviation, and improving voltage stability.
APPLIED SOFT COMPUTING
(2023)
Article
Transportation Science & Technology
Chengqian Zhu, Guifu Du, Yawen Ding, Weiguo Huang, Jun Wang, Mingdi Fan, Zhongkui Zhu
Summary: This study proposed a timetable optimization approach for multi-train systems based on an improved Seeker Optimization Algorithm (SOA) to suppress abnormally elevated rail potential and enhance reflux safety.
INTERNATIONAL JOURNAL OF RAIL TRANSPORTATION
(2022)
Article
Energy & Fuels
Mostafa Mojtahedzadeh Larijani, Mehrdad Ahmadi Kamarposhti, Tohid Nouri
Summary: In this paper, a new hybrid multiobjective algorithm, namely, the modified bald eagle search Algorithm (MBES), integrated with the grasshopper optimization algorithm, is proposed to solve the unit commitment (UC) problem. The UC problem is tackled under uncertainties related to demand and renewable generation capacities, and two innovative objective functions based on operation cost and emissions are introduced. Our findings demonstrate that the proposed MOGOA-MBES algorithm outperforms other algorithms in terms of reducing operation cost and emissions, and the inclusion of flexible loads can effectively mitigate cost and emission levels.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2023)
Article
Thermodynamics
Akanksha Sharma, Sanjay K. Jain
Summary: This paper investigates a day-ahead reactive power ancillary service procurement problem to minimize cost and voltage deviation under wind power generation uncertainties in a pool -based deregulated system. A developed Pareto-based multi-objective artificial electric field algorithm is proposed to solve the problem effectively, validated through comparisons with other algorithms on different test systems. The algorithm utilizes advanced optimization techniques and is analyzed for convergence characteristics and performance under various scenarios.
Article
Computer Science, Artificial Intelligence
Chaofan Yu, Yuanzheng Li, Yun Liu, Leijiao Ge, Hao Wang, Yunfeng Luo, Linqiang Pan
Summary: This study develops a bi-objective stochastic dispatch model to investigate the relationship between renewable energy utilization and transmission security. The model considers the objectives of renewable energy curtailment and the capacity margin of transmission lines, and proposes a data-driven Bayesian assisted optimization algorithm to improve the searching efficiency.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Jiaxin Liu, Yungang Liu, Huijun Liang, Yongchao Man, Fengzhong Li, Wenjuan Li
Summary: This paper proposes a collaborative optimization strategy for dynamic grid dispatch, optimizing economic dispatch and reactive power dispatch simultaneously. By establishing a collaborative optimization model and improving the multi-objective hybrid bat algorithm with an unbalanced power distribution method, the dynamic grid dispatch problem is tackled. Additionally, the integration of wind power predicted by neural network is studied for its impact on grid dispatch.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Energy & Fuels
Yuanye Wei, Yongquan Zhou, Qifang Luo, Wu Deng
Summary: The paper introduces an improved slime mould algorithm (ISMA) to solve the optimal reactive power dispatch (ORPD) problem, and the performance evaluation and experimental results show that ISMA outperforms in accuracy and computational efficiency.
Article
Thermodynamics
Hany M. Hasanien, Ibrahim Alsaleh, Marcos Tostado-Veliz, Miao Zhang, Ayoob Alateeq, Francisco Jurado, Abdullah Alassaf
Summary: This research introduces a novel technique, the Hybrid Particle Swarm Optimization and Sea Horse Optimization (PSOSHO) algorithm, for solving the optimal reactive power dispatch (ORPD) problem in electrical grids. Simulation studies verify its efficacy and real data on electric vehicles are incorporated for realistic analyses.
Article
Energy & Fuels
Yu Zhou, Zhengshuo Li, Guangrui Wang
Summary: This paper suggests leveraging the reactive power range embedded in wind farms to improve safety and optimality during the power system reactive power optimization process. An uncertain reactive power optimization problem involving wind farm reactive power range is introduced, which is recast as a deterministic optimization problem. The study confirms that wind farms are competent reactive power resources even with notable uncertainty.
Article
Computer Science, Information Systems
Muhammad Shahzar Saddique, Salman Habib, Shaikh Saaqib Haroon, Abdul Rauf Bhatti, Salman Amin, Emad M. Ahmed
Summary: Optimal reactive power dispatch (ORPD) is important for the safety, reliability, and economical operation of the electric power system. In this study, a novel algorithm named sine-cosine algorithm (SCA) is proposed to solve the non-linear and non-convex ORPD problem. The algorithm considers both dependent and independent control variable constraints and has been tested on standard power systems. The results show that SCA outperforms other meta-heuristic algorithms in minimizing power losses and is robust and computationally easy to use.
Article
Engineering, Chemical
Rong Zheng, Heming Jia, Laith Abualigah, Qingxin Liu, Shuang Wang
Summary: A new hybrid algorithm, DESMAOA, based on the combination of SMA and AOA, is proposed in this paper to enhance optimization capability. The analysis using 23 benchmark functions demonstrates the superior performance of DESMAOA.
Article
Computer Science, Artificial Intelligence
Malik Braik, Hussein Al-Zoubi, Mohammad Ryalat, Alaa Sheta, Omar Alzubi
Summary: Crow Search Algorithm (CSA) is a promising meta-heuristic method that mimics the intelligent behavior of crows in nature. By combining it with Particle Swarm Optimization (PSO), the Memory based Hybrid CSA (MHCSA) achieves a stronger diversity ability and a better balance between exploration and exploitation, effectively overcoming the early convergence and imbalance issues. Test results have demonstrated the superiority of MHCSA over other methods in terms of accuracy and stability.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Engineering, Electrical & Electronic
Pooja Verma, Raghav Prasad Parouha
Summary: An innovative hybrid algorithm (ihPSODE) is proposed to solve non-convex dynamic economic dispatch (DED) problem, integrating novel particle swarm optimization and differential evolution methods. Strategies are implemented to avoid stagnation and premature convergence, and by identifying the best members, the algorithm aims to find global optima more quickly.
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Liming Wang, Yingming Liu, Xinfu Pang, Qimin Wang, Xiaodong Wang
Summary: This paper establishes a multiobjective environmental economic dispatching model of power system with minimum economic cost and pollution emission as optimization objectives to address the challenges of power system dispatching caused by the global energy crisis and climate warming, and to promote the achievement of the double carbon goal. A multiobjective artificial bee colony algorithm (MOABC) based on nondominant sorting and improved greedy criterion is designed according to the characteristics of the model. The simulation results show that the MOABC algorithm achieves the lowest economic cost and pollution emission compared to other algorithms, such as the multiobjective wind driven optimization, multiobjective particle swarm optimization, and NSGA-II algorithms.
ELECTRICAL ENGINEERING
(2023)