Optimum generation scheduling incorporating wind energy using HHO–IGWO algorithm

• Published in: Journal of Electrical Systems and Information Technology Vol. 10; no. 1; pp. 1 - 21
• Main Authors: Dhawale, Dinesh, Kamboj, Vikram Kumar, Anand, Priyanka
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2023; Springer Nature B.V; SpringerOpen
• Subjects: Algorithms; Alternative energy sources; Decision making; Economic dispatch; Electric power demand; Energy management; Energy resources; Engineering; Generation scheduling (GS); Generators; Harris Hawks optimizer (HHO); Improved gray wolf optimizer (IGWO); Mechanical Engineering; Optimization; Optimization algorithms; Penetration; Probability distribution; Renewable energy; Renewable energy sources; Renewable resources; Scheduling; Unit commitment; Wind power; Economic dispatch; Generation scheduling (GS); Renewable energy; Improved gray wolf optimizer (IGWO); Harris Hawks optimizer (HHO)
• ISSN: 2314-7172; 2314-7172
• DOI: 10.1186/s43067-022-00067-w

Recently, renewable energy participation is gaining importance in the existing power system. However, the large penetration of these renewable energy sources into the existing power system network may cause an imbalance in supply and demand response. Unit commitment is the decision-making process in which generating units are turned ON and OFF at the hourly interval as per the load demand under certain constraints to provide economic scheduling. Thus, an advanced intelligent approach is needed to cope with this combined unit commitment problem with a large penetration of intermittent sources. This paper offers the solution to optimal scheduling by implementing the hybrid Harris Hawks optimizer algorithm (HHO–IGWO). Standard IEEE systems with 10-, 19-, 20-, and 40 units are simulated. Further, to test the feasibility and effectiveness of the proposed method, a comparative analysis for a 10-, 20-, and 40-unit system has also been performed with penetration. The comparative analysis reveals that proposed is more efficient in tackling unit commitment problem in the presence of wind as renewable energy source.