
Optimal DG allocation and sizing in presence of storage systems considering network configuration effects in distribution systems
Author(s) -
Abbasi Fazel,
Hosseini Seyed Mehdi
Publication year - 2016
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.2015.0367
Subject(s) - sizing , sorting , control reconfiguration , genetic algorithm , reliability (semiconductor) , power (physics) , computer science , fault (geology) , distributed generation , process (computing) , reliability engineering , mathematical optimization , control theory (sociology) , engineering , mathematics , algorithm , control (management) , operating system , art , physics , quantum mechanics , artificial intelligence , seismology , visual arts , embedded system , geology
Optimal performance of power distribution networks greatly depends on network configuration, location and size of distributed generations (DGs) units and storage systems. That is, for different configurations, different optimal locations and sizes of DGs can be found and vice versa. Therefore, the impact of both location and size of DG and network configuration should be considered in the planning process, simultaneously. Also, the presence of storage systems in the distribution system leads to some loads to be supplied even in fault conditions. In this study, distribution system reconfiguration (DSR), for considering network configuration effect that runs in offline mode with constant loads, and optimal DG allocation and sizing problems are studied simultaneously to find an optimal condition for distribution network based on operational thresholds and reliability improvements. Non‐dominated Sorting Genetic Algorithm is used to solve these problems simultaneously. Power losses, energy not supplied (ENS) and the costs associated with DG are the objectives that are studied. The method of calculating ENS in DSR problem in the presence of DGs with storage systems is explained and the impact of protective equipment is considered, as well. The proposed approach is applied on different test systems, and its effectiveness is shown in various conditions.