Rescheduling of Generators with Pumped Hydro Storage Units to Relieve Congestion Incorporating Flower Pollination Optimization

Abstract

In this paper, a Flower Pollination Algorithm (FPA) has been proposed for relieving congestion in the deregulated power electricity industry. Congestion in the power market is one the contemplative challenges to be overcome in the era of deregulation. The primary cause of congestion is due to the loss of the transmission line, an increase in load, or loss of generator(s). Hence, managing congestion is one of the issues which have to be tackled in the present scenario. There are several techniques to relieve congestion. It is quite well-known that the thermal limits of transmission lines in a power system are fixed. One of the methods to abate congestion is to reschedule the real power of the generators. The purpose of the present work is to benefit the Independent System Operator (ISO) in reliving congestion. (1) In order to meet this objective effectively, a FPA algorithm has been proposed for relieving congestion and is simulated on a modified IEEE 30-bus system initially. (2) Congestion cost, compared with and without the application of FPA, is computed. (3) To validate its effectiveness, the obtained results are compared with recent power system optimization algorithms present in the literature. (4) Further, the work has been extended with the incorporation of a Pumped Hydro Storage Unit (PHSU). Here an economic analysis of congestion cost reduction employing FPA before and after the incorporation of PHSU is investigated applying FPA. In comparison with other evolutionary algorithms, the uniqueness of generating a new population is attained in FPA by the levy flight procedure. It is one of the latest evolved algorithms and is suited for different power system problem due to fewer clear-cut tuning parameters in contrast with other algorithms. (5) Furthermore, the effects of other network parameters, including system losses and voltage, has been computed. The result obtained is tested in terms of congestion mitigation with and without the incorporation of PHSU, in terms of novel objective improvement, and with and without applying recently evolving FPA for the above application. Thus the objective-wise and algorithmic-wise innovative concept has been presented. This proves effectiveness of the algorithm in terms of minimized cost convergence and other parameter including system losses and voltage before and after the incorporation of PHSU as compared with other recent trendsetting reported optimization techniques.