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Optimal operation of wind-hydrothermal systems considering certainty and uncertainty of wind
- Source :
- Alexandria Engineering Journal, Vol 60, Iss 6, Pp 5431-5461 (2021)
- Publication Year :
- 2021
- Publisher :
- Elsevier, 2021.
-
Abstract
- This paper proposes a High Performance Cuckoo Search Algorithm (HPCSA) for determining suitable operation parameters of the optimal wind-hydro-thermal system scheduling (OWHTSS) problem. The objective of the problem is to reach the lowest electricity generation cost of thermal power plants (TPPs) and wind power plants (WPPs) while exactly meeting all constraints of TPPs, WPPs and hydroelectric plants (HEPs). HPCSA is formed by applying improvements on the two main techniques of original Cuckoo Search Algorithm (CSA) to cover CSA’ drawbacks such as searching random solution spaces, always using two random solutions for getting a jumping step and suffering from slow convergence. HPCSA accompany with CSA, Adaptive CSA (ACSA), Snap-Drift CSA (SDCSA) and Water Cycle Algorithm (WCA) are run for solving four test systems in which the largest and complicated system is comprised of four TPPs, four HEPs and two WPPs with the uncertain wind feature. The result comparisons indicate that HPCSA is superior to applied and previous methods, and other modified versions of CSA in the literature in terms of better cost, higher stability, faster search ability and higher success rate. As a result, it leads to a conclusion that HPCSA is a strong metaheuristic algorithm for solving OWHTSS problem.
- Subjects :
- Mathematical optimization
Computer science
020209 energy
Stability (learning theory)
Thermal power station
02 engineering and technology
Fuel cost
01 natural sciences
010305 fluids & plasmas
Scheduling (computing)
Cuckoo search algorithm
Hydrothermal system
Hydroelectricity
Hydroelectric plants
0103 physical sciences
Wind turbines
0202 electrical engineering, electronic engineering, information engineering
Thermal power plants
Cuckoo search
Metaheuristic
Wind power
business.industry
General Engineering
Engineering (General). Civil engineering (General)
Electricity generation
TA1-2040
business
Subjects
Details
- Language :
- English
- ISSN :
- 11100168
- Volume :
- 60
- Issue :
- 6
- Database :
- OpenAIRE
- Journal :
- Alexandria Engineering Journal
- Accession number :
- edsair.doi.dedup.....8825ac90fefa63ec7c46b1b435e17c21