Short-term scheduling problem in smart grid considering reliability improvement in bad weather conditions

• Published in: IET generation, transmission & distribution transmission & distribution, 2017-07, Vol.11 (10), p.2521-2533
• Main Authors: Yousefi-khangah, Babak, Ghassemzadeh, Saeid, Hosseini, Seyed Hossein, Mohammadi-Ivatloo, Behnam
• Format: Article
• Language: English
• Subjects: bad weather conditions; benefit maximisation; consumer interruption costs; demand response programs; demand side management; DGO; DisCo; distributed generation‐and‐energy storage owners; distributed power generation; distribution companies; dynamic economic dispatch; electrical grids; energy not supplied reduction; energy storage; energy storage system; ENS cost; hourly forecasted weather information; intelligent scheduling; multiobjective optimisation problem; objective functions; optimisation; power distribution reliability; power generation dispatch; power generation scheduling; reliability improvement; Research Article; short‐term scheduling problem; smart grid; smart power grids
• ISSN: 1751-8687; 1751-8695; 1751-8695
• DOI: 10.1049/iet-gtd.2016.1261

The worldwide needs to increase the reliability of the electrical grids and to reduce energy not supplied (ENS) are the major goals in traditional grids. Smart grids have key features such as intelligence, adaption and flexibility abilities, to reduce the effects of outages in society. This study proposes an optimised operational strategy which increases the robustness of smart grid against outages caused by bad weather conditions. The proposed method takes advantage of dynamic economic dispatch and hourly forecasted weather information. Intelligent scheduling of demand response programs and energy storage system, are formulated as a multi-objective optimisation problem considering consumer interruption costs. In this study, the objective functions consist of benefit maximisation of the distribution companies, benefit of the distributed generation and energy storage owners (DGO). In the proposed approach, line interruption rates are affected by weather conditions and consequently the ENS cost will be influenced in each time interval. DisCohas the ability to modify energy cost to overcome bad weather conditions and reduce ENS in different time periods. Simulation results show that the presented method reduces the real operation and ENS cost for DisCo. In addition, DisCo increases the benefits of DGO.