 Three powerful nature-inspired algorithms to optimize power flow in Algeria's Adrar power systemSaida Makhloufi, Abdelouahab Mekhaldi and Madjid Teguar Energy, 2016, vol. 116, issue P1, 1117-1130 Abstract: This paper is intended to solve the optimal power flow (OPF) dispatch in the presence of wind power generation (WPG) in the Adrar power system. Towards this aim, the performances of three powerful meta-heuristic algorithms-namely, the cuckoo search algorithm (CSA), firefly algorithm (FFA), and flower pollination algorithm (FPA) are investigated. The proposed algorithms are applied to best capture the active power produced with the minimum value of a multi-objective function. This latter includes: the fuel cost, the NOx emissions, and the imbalance cost of the WPGs. Furthermore, considering the uncertainties governing wind resources, the maximum wind power output is estimated using the wind speed carrying maximum energy. It was found that all algorithms perform well in providing accurate solutions. Interestingly, the convergence is reached in the first 135 iterations. A remarkable outcome of the present work is that CSA outperforms FPA and FFA. CSA has proved itself to be a great tool to optimize Adrar's power flow system in term of iterations and computational time. Keywords: Optimal power flow; Cuckoo search; Firefly; Flower pollination; Wind speed carrying maximum energy (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:116:y:2016:i:p1:p:1117-1130 DOI: 10.1016/j.energy.2016.10.064 Access Statistics for this article Energy is currently edited by Henrik Lund and Mark J. Kaiser More articles in Energy from Elsevier |
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