Article
Energy & Fuels
Salman Habib, Mehrdad Ahmadi Kamarposhti, Hassan Shokouhandeh, Ilhami Colak, El Manaa Barhoumi
Summary: Increasing electrical energy use has led to the development of power systems. This paper proposes a mutant version of the honey bee mating optimization algorithm for solving the economic-emission dispatch problem. The algorithm improves the efficiency and balance of the standard algorithm by using an adaptive nonlinear system.
Article
Engineering, Electrical & Electronic
Yuanzheng Li, Jingjing Huang, Yun Liu, Zhixian Ni, Yu Shen, Wei Hu, Lei Wu
Summary: This paper proposes a multi-objective economic dispatch model to tackle the economic dispatch problem in a high wind power penetration environment. The model considers three indices: generation cost, upside potential, and downside risk, and uses a group search optimizer for solving. The optimal solution is selected using a fuzzy decision-making method. Case studies demonstrate the effectiveness of the proposed model and algorithm.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2022)
Article
Biotechnology & Applied Microbiology
S. D. Sundarsingh Jebaseelan, N. B. Muthu Selvan, C. Kumar, A. Kalaimurugan, A. Srujana, C. N. Ravi
Summary: This paper addresses the optimization problem of reducing both emission and generation cost in the thermal power plant industry. Intelligent algorithms are utilized to solve these practical problems, with a hybrid approach of firefly algorithm and differential evolution technique being adopted for constrained emission minimization and cost minimization. The aim of the research work is to reduce the carbon foot print and generation cost of the power system.
ENVIRONMENTAL TECHNOLOGY & INNOVATION
(2021)
Article
Computer Science, Artificial Intelligence
Wenguan Luo, Xiaobing Yu
Summary: This paper discusses the importance of carbon neutrality in the task of social development and proposes a Reinforcement Learning-based Modified Cuckoo Search algorithm (RLMCS) to solve the economic dispatch problem. Experimental results demonstrate that RLMCS is more competitive and robust in solving standard and valve-point effects economic dispatch problems.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Thermodynamics
Ashkan Toopshekan, Ali Abedian, Arian Azizi, Esmaeil Ahmadi, Mohammad Amin Vaziri Rad
Summary: Using optimization algorithms and developing dispatch strategies are crucial for sizing renewable energy systems. This study employs the Teaching Learning-based Optimization (TLBO) algorithm to determine the optimal size of a Combined Heat and Power (CHP) system. The developed dispatch strategy considers various factors and has led to cost reduction and improved efficiency.
Article
Green & Sustainable Science & Technology
Chao Chen, Linan Qu, Ming-Lang Tseng, Lingling Li, Chih-Cheng Chen, Ming K. Lim
Summary: This study contributes to solving the economic load dispatch problem and promoting cleaner and sustainable power production through an improved manta ray foraging optimization algorithm. The results show that the algorithm can effectively improve the economic benefits and adaptive ability of thermal power generation units.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Mathematics
Alaa A. K. Ismaeel, Essam H. Houssein, Doaa Sami Khafaga, Eman Abdullah Aldakheel, Ahmed S. AbdElrazek, Mokhtar Said
Summary: The osprey optimization algorithm (OOA) is a new metaheuristic inspired by the strategy of hunting fish in seas. In this study, OOA is applied to solve the economic load dispatch (ELD) problem in a power system. The performance of OOA is compared against several techniques and it is found to be superior in solving the ELD and combined emission and economic dispatch (CEED) problems compared to other algorithms.
Article
Thermodynamics
Abdullah M. Shaheen, Ahmed R. Ginidi, Ragab A. El-Sehiemy, Ehab E. Elattar
Summary: The paper presents a manta ray foraging MRF optimizer for solving the Economic Dispatch in Cogeneration Systems problem, considering valve point impacts and wind power. The MRF optimizer is designed with adaptive penalty functions to acquire the most feasible and best operational points. By meeting equality constraints, the power and heat loading are completely achieved while fulfilling the cogeneration units' dynamic operating limits.
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
Thermodynamics
Le Zhang, Mohammad Khishe, Mokhtar Mohammadi, Adil Hussein Mohammed
Summary: This research introduces a new algorithm, NPChOA, to address the challenges of environmental economic dispatch. NPChOA outperforms other algorithms in terms of performance metrics and has shown remarkable efficacy in both single and multiobjective optimizations.
Article
Thermodynamics
Wenqiang Yang, Xinxin Zhu, Qinge Xiao, Zhile Yang
Summary: This paper proposes an improved version of the multi-objective marine predator algorithm (IMOMPA) for solving the optimization of multi-objective dynamic economic-grid fluctuation dispatch (MODEGD). The IMOMPA algorithm improves population diversity, convergence speed, and global search ability. Numerical experiments on benchmark functions and generation units demonstrate the superiority of the IMOMPA algorithm, and plug-in electric vehicles (PEVs) connected to the grid (V2G) can help mitigate grid fluctuations.
Article
Green & Sustainable Science & Technology
Hossein Nourianfar, Hamdi Abdi
Summary: Due to environmental concerns and high penetration of wind power and electric vehicles (EVs), reducing generation costs and emissions while coordinating EV charging and addressing wind power uncertainty are challenging issues in power system control. This paper proposes an enhanced multi-objective exchange market algorithm to solve the multi-objective dynamic economic emission dispatch problem integrated with EVs and wind farms. The algorithm introduces a novel point-to-point distance technique for finding Pareto front solutions and proposes a smart strategy for charging and discharging EVs to smooth the load curve. Simulation results show that the proposed method effectively extracts the Pareto front solutions with uniformity and diversity. The presence of EVs and the application of the smart strategy lead to significant reductions in operation costs and emissions, as well as improvements in load factors.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Thermodynamics
Yeganeh Sharifian, Hamdi Abdi
Summary: This study proposes a hybrid meta-heuristic algorithm to solve the multi-area economic dispatch problem, and evaluates the effectiveness and robustness of the algorithm through multiple case studies.
Article
Engineering, Chemical
Wei Wu, Fu-Teng Hsu, Wei-Chen Chang, Jenn-Jiang Hwang, Zukui Li
Summary: This study investigates the power dispatching of a solid oxide fuel cell/gas turbine-based cogeneration system. By employing forecasting models and optimization algorithms, the system aims to minimize operating costs considering natural gas and coal prices, as well as load demand. The use of flexible fuel purchasing strategies is validated to improve the system's performance.
JOURNAL OF THE TAIWAN INSTITUTE OF CHEMICAL ENGINEERS
(2022)
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
Engineering, Electrical & Electronic
Elango Umamaheswari, Sivarajan Ganesan, Manoharan Abirami, Srikrishna Subramanian
IET SCIENCE MEASUREMENT & TECHNOLOGY
(2017)
Article
Energy & Fuels
Srinivasa Acharya, Ganesan Sivarajan, D. Vijaya Kumar, Subramanian Srikrishna
Summary: The paper introduces a new algorithm, Refraction based Whale Optimization Algorithm (RWOA), to solve the Combined Economic Emission Dispatch problem based on the production of an optimum solar energy system, and validates its robustness in Hybrid Renewable Energy Systems (HRES). Connecting wind turbines with thermal power plants is essential to control emission and economic costs. Experimental results show that at the 40th iteration, RWOA method outperforms GA, GWO, WOA, DA, GWSO, LGSO, and WWO by 92.81%, 99.2%, 92.8%, 80%, 37.8%, 47.34%, and 45.83% respectively.
ENERGY SOURCES PART B-ECONOMICS PLANNING AND POLICY
(2021)
Article
Engineering, Electrical & Electronic
Kaliyan Naveenkumar, Ramanujam Kannan, Sivarajan Ganesan, Srikrishna Subramanian
IET SCIENCE MEASUREMENT & TECHNOLOGY
(2020)
Article
Business
Ponnambalam Suriya, Srikrishna Subramanian, Sivarajan Ganesan, Manoharan Abirami
INTERNATIONAL JOURNAL OF ENGINEERING BUSINESS MANAGEMENT
(2019)
Article
Management
E. Umamaheswari, S. Ganesan, M. Abirami, S. Subramanian
INTERNATIONAL JOURNAL OF QUALITY & RELIABILITY MANAGEMENT
(2018)
Article
Engineering, Electrical & Electronic
S. Siva Sakthi, R. K. Santhi, N. Murali Krishnan, S. Ganesan, S. Subramanian
RECENT ADVANCES IN ELECTRICAL & ELECTRONIC ENGINEERING
(2018)
Article
Engineering, Multidisciplinary
Umamaheswari Elango, Ganesan Sivarajan, Abirami Manoharan, Subramanian Srikrishna
WORLD JOURNAL OF ENGINEERING
(2018)
Article
Management
Balachandar Pandiyan, Sivarajan Ganesan, Nadanasabapathy Jayakumar, Srikrishna Subramanian
INTERNATIONAL JOURNAL OF ENERGY SECTOR MANAGEMENT
(2018)
Proceedings Paper
Computer Science, Artificial Intelligence
P. Balachandar, S. Ganesan, N. Jayakumar, S. Subramanian
PROCEEDINGS OF 2017 IEEE INTERNATIONAL CONFERENCE ON CIRCUIT ,POWER AND COMPUTING TECHNOLOGIES (ICCPCT)
(2017)
Article
Engineering, Electrical & Electronic
Manoharan Hariprasath, Srikrishna Subramanian, Sivarajan Ganesan, Manoharan Abirami
INTERNATIONAL JOURNAL OF POWER AND ENERGY SYSTEMS
(2017)
Proceedings Paper
Automation & Control Systems
E. Umamaheswari, S. Ganesan, M. Abirami, S. Subramanian
FIRST INTERNATIONAL CONFERENCE ON POWER ENGINEERING COMPUTING AND CONTROL (PECCON-2017 )
(2017)
Article
Energy & Fuels
P. Balachandar, S. Ganesan, N. Jayakumar, S. Subramanian
INTERNATIONAL JOURNAL OF ENERGY OPTIMIZATION AND ENGINEERING
(2017)
Article
Management
Janagaraman Radha, Srikrishna Subramanian, Sivarajan Ganesan, Manoharan Abirami
INTERNATIONAL JOURNAL OF ENERGY SECTOR MANAGEMENT
(2017)
Article
Engineering, Electrical & Electronic
R. Saravanan, S. Subramanian, V. Dharmalingam, S. Ganesan
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
(2017)
Article
Management
R. Saravanan, S. Subramanian, S. SooriyaPrabha, S. Ganesan
INTERNATIONAL JOURNAL OF ENERGY SECTOR MANAGEMENT
(2018)