Optimal allocation of distribution generator in a radial–distribution system using self–adaptive modified firefly algorithm with voltage, power and line capacity limit constraints. (2015)

• Record Type: Journal Article
• Authors: Saha, Sanjoy Kumar; Banerjee, Sumit; Chanda, Chandan Kumar
• Is Part Of: International journal of power and energy conversion. Volume 6:Number 2(2015)
• Page Start: 148
• Page End: 164
• Publication Date: 2015
• Subjects: distributed generation -- distribution systems -- loss sensitivity factor -- LSF -- two point method scheme -- self–adaptive modified firefly algorithm -- SAMFA -- optimal allocation -- voltage limits -- power limits -- line capacity limits -- electricity generation -- peak load demand -- optimisation -- load flow -- network power losses; Energy conversion -- Periodicals; Power resources -- Periodicals; Electric power production -- Periodicals; 621.31205
• Languages: English
• ISSNs: 1757-1154

Abstract

As a result of the application of deregulation in the electric power sector, a new identity appeared in the electric power system map known as 'distribution generator' (DG). To meet out the peak load demand caused by increased power demand in the distribution system, DGs are greatly utilised by placing DGs in optimal location with optimal size. This paper presents a novel firefly optimisation–based approach to optimally incorporate a distribution generator into a distribution system. The proposed algorithm combines firefly optimisation with load flow algorithm to solve the problem in a single step. While developing the algorithm, by satisfying the voltage, power and line capacity limit, the objective function, i.e., the total network power losses will be minimised. Loss sensitivity factors (LSFs) are used to select the location for the multiple DG placements and self–adaptive modified firefly algorithm (SAMFA) is used to estimate the optimal size of DGs at optimal locations determined. Taking the self–adaptive modified firefly algorithm (SAMFA) and IEEE 69–node system as the example, the results show the effectiveness of the proposed algorithm.