Stochastic economic analysis of FACTS devices on contingent transmission networks using hybrid biogeography-based optimization

• Published in: Electrical engineering 2019-09, Vol.101 (3), p.829-843
• Main Authors: Ghaemi, Sina, Hamzeh Aghdam, Farid, Safari, Amin, Farrokhifar, Meisam
• Format: Article
• Language: English
• Subjects: Algorithms; Biogeography; Construction costs; Contingency; Control stability; Controllability; Economic analysis; Economics and Management; Electrical Engineering; Electrical Machines and Networks; Electronic devices; Energy Policy; Engineering; Flexible AC power transmission systems; Heuristic methods; Load shedding; Mathematical analysis; Networks; Nonlinear programming; Optimization; Original Paper; Power Electronics; Power transfer; Renewable energy sources; Service life assessment; Sizing
• ISSN: 0948-7921; 1432-0487
• DOI: 10.1007/s00202-019-00825-6

Flexible AC transmission systems (FACTS) devices have advantages of enhancing AC system controllability and stability, increasing power transfer capability and relieving congestion. Finding the best sizing and siting of them is obligatory to obtain the maximum benefit. In this paper, the optimum planning is done for determining the suitable sizing and siting of the FACTS devices during their lifetime span. The proposed planning approach is implemented to the networks, which are suffering from the contingency to demonstrate that how proper sizing and siting of the FACTS devices are able to deal with the existing problems in such networks. In fact, the maximum social welfare, reducing load shedding cost and construction cost of the new branches besides of the technical issues such as voltage improvement are the main concerns of the present work. To accomplish these aims accurately and reduce the computation time, a hybrid approach, consisting of mathematical and heuristic methods, is proposed for solving the proposed planning problem. The mentioned algorithm is a combination of biogeography-based optimization (BBO) as a heuristic algorithm and nonlinear programming as a mathematical approach. Furthermore, since the stochastic natures of renewable energy sources and load variations contribute to the optimum decisions, the stochastic formulation has been considered in the planning problem using the efficient point estimation ( 2 m + 1 ) scheme. Finally, the proposed planning approach is tested on different test systems, namely IEEE 14-bus, IEEE 57-bus and IEEE 300-bus, in order to verify its effectiveness from a different point of views.