Open AccessSimultaneous optimal allocation and sizing of DGs and capacitors in radial distribution systems using SPEA2 considering load uncertainty
Author(s) -
Biswal Saubhagya Ranjan,
Shankar Gauri
Publication year - 2020
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2018.5896
Subject(s) - sizing , mathematical optimization , pareto principle , probabilistic logic , capacitor , evolutionary algorithm , computer science , control theory (sociology) , electric power system , fuzzy logic , voltage , power (physics) , mathematics , engineering , art , control (management) , artificial intelligence , electrical engineering , visual arts , physics , quantum mechanics
The rapid growth in load demand results in higher line loses in distribution systems and also demands distribution system augmentation. Apart from this, due to fluctuating loads, it becomes a challenge for the utility sectors to maintain voltage stability of the system under healthy condition. For addressing such problems, simultaneous optimal placement of distributed generations (DGs) and capacitors in radial distribution systems employing multi‐objective optimisation technique based approach is explored in this work. In line with this, the present work uses a simple and powerful multi‐objective strength Pareto evolutionary algorithm 2 (SPEA2) for solving distributed generator and capacitor placement problem considering load uncertainty. The uncertainty characteristics of load are designed by probabilistic approach and the same is utilised during the optimisation process. Thereafter, a set of non‐dominated Pareto optimal solution is obtained according to the objective function value. A compromised solution is selected from the set of Pareto optimal solutions by using fuzzy set theory. Along with the above, the impact of reverse power flow is studied by taking different test cases. The studied algorithm has been tested on different standard IEEE 33‐bus and 69‐bus radial distribution test systems.