Hybrid of Lambda Iteration and Meta-Heuristic Methods for Solving Economic Dispatch Problem

Aurasopon, Apinan; Takeang, Chiraphon

doi:10.15199/48.2020.06.05

Cited by 1 publication

(1 citation statement)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This iterative process allows for the optimization of generation schedules while considering various operational constraints. However, the lambda iteration method can be computationally intensive, especially when applied to large-scale systems with numerous generating units 19) .…”

Section: Introductionmentioning

confidence: 99%

Vectorized Lambda Iteration Method for Swift Economic Dispatch Analysis

Rifki Rahman Nur Ikhsan,

Raharjo,

Rahmat

2024

Evergreen

View full text Add to dashboard Cite

The economic dispatch process in power markets aims to find the optimal generation schedule based on cost-based bids from generators. The lambda iteration method is commonly used but faces computational challenges for large-scale systems. To address this, a novel approach called the vectorized lambda iteration method is proposed. This method utilizes vectorization techniques to reduce computation time while maintaining accuracy. By parallelizing the computation of schedules and Lagrange multipliers, it achieves faster convergence and enables real-time decision-making. The method improves efficiency, competitiveness, and adaptability in power markets, ensuring reliable operation. Software and hardware optimizations further enhance performance. The results demonstrate a significant reduction in computation time and the lowest cost across three test systems. The vectorized lambda iteration method offers an efficient solution for power system operation and decision-making, with the potential for optimization in practical applications. The proposed vectorized variant that we introduced is capable of reducing computation time by 99% compared to conventional methods, while also achieving a 2% cost reduction.

show abstract

Section: Introductionmentioning

confidence: 99%