Economic Load Dispatch Incorporating Wind Power Using Hybrid Biogeography-Based Optimization: Salp Swarm Algorithm

被引:1
作者
Saha, Bikram [1 ]
Roy, Provas Kumar [1 ]
Mandal, Barun [1 ]
机构
[1] Kalyani Govt Engn Coll, Elect Engn Dept, Kalyani, W Bengal, India
关键词
Biogeography-Based Optimization (BBO); Economic Load Dispatch (ELD); Overestimation Cost; Salp Swarm Algorithm (SSA); Underestimation Cost; Valve Point Loading; Weibull Distribution; Wind Power; EMISSION DISPATCH; LINE FLOW; SYSTEM; REAL;
D O I
10.4018/IJAMC.2021070103
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article represents salp swarm algorithm (SSA) for the most favourable operating solution of economic load dispatch (ELD). For making the convergence first along with SSA, another optimization algorithm (i.e., BBO [biogeography;based optimization]) is also used. For lowering the operational cost, wind power is employed with thermal units. SSA is inspired by swarming behaviour of salp, which belongs to salpiside family. Salp possess a special kind of swarm while hunting for food and navigating. The recommended algorithm is executed on two systems of SIX units and 40 units. In both of the cases, load dispatch problem is carried out with renewable sources and also without renewable sources. Individually, BBO, SSA, and hybrid BBO-SSA are applied to all the test systems to justify effectiveness of hybrid BBO-SSA. Obtained results assure the prospective and advantages of recommended algorithm in contrast to algorithms mentioned in the article. Results come out to be very satisfying and reveal that hybrid BBO-SSA is a powerful algorithm to solve ELD problems.
引用
收藏
页码:54 / 80
页数:27
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