Open AccessNetwork expansion planning with microgrid aggregators under uncertainty
Author(s) -
Goroohi Sardou Iman,
AzadFarsani Ehsan
Publication year - 2018
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.2017.1076
Subject(s) - interior point method , mathematical optimization , computer science , dual (grammatical number) , microgrid , component (thermodynamics) , electric power system , minification , control (management) , mathematics , artificial intelligence , power (physics) , art , physics , literature , quantum mechanics , thermodynamics
In this paper, a bi‐objective robust model is proposed for network expansion planning (NEP) considering the integration of the microgrid aggregators. The objectives include minimization of both the expansion cost and transmission lines loading index. Forced outages of system components are taken into account as the system uncertainties. A hybrid method as the combination of gravitational search algorithm (GSA) and primal‐dual interior point (PDIP) method is employed to solve the nonlinear programming (NLP) problem of the NEP. In the proposed hybrid method, the operation sub‐problems are solved by the PDIP method under the worst‐case single component contingencies, while the expansion plan is defined as scenario independent variables obtained by the GSA algorithm. To detect the worst‐case single component contingencies with the severest effects on the system security, a subsidiary optimization problem is solved for each load level of the system. A realistic network of Qom as a part of Tehran Regional Electric Company, Iran, as well as IEEE 118‐bus test system are analysed to evaluate the efficiency of the proposed method. A key conclusion is that the stochastic model may not provide sufficient security level, and a robust model is required to ensure the system security against the severe contingencies.