Optimal stochastic scheduling of reconfigurable active distribution networks hosting hybrid renewable energy systems

Morteza Zare Oskouei, Behnam Mohammadi-Ivatloo, Mehdi Abapour, Reza Razzaghi

Research output: Contribution to journalArticleResearchpeer-review

3 Citations (Scopus)


Renewable energy sources (RESs) have a remarkable role in advancing the goals of restructured power systems to reduce greenhouse gas emissions and increase the level of reliability. However, due to the non-uniform utilisation of these resources in various sectors of power grids, a major part of the generated renewable energies is spilled to satisfy the power system constraints. Motivated by this challenge, the role of the reconfiguration mechanism in maximising the utilisation of RESs in active distribution networks (ADNs) is investigated herein. To this end, a two-stage stochastic model is presented for optimal scheduling of reconfigurable distribution networks in the presence of high-power hybrid wind/photovoltaic systems. The main goal of the presented model is to maximise the hybrid system owner's profit. In the first stage of the presented structure, the optimal hourly bilateral dispatches between the hybrid system and the ADN in the day-ahead electricity market are determined to maximise the hybrid system owner's profit. In the second stage, the power spillage of the hybrid renewable energy systems are minimised using reconfiguration technology in the real-time electricity market. For practical implementation, the proposed operational strategy is applied to the modified 33-bus and 69-bus distribution test systems, and is solved using GAMS software. The simulation results indicate that the proposed strategy can considerably reduce renewable power spillage, increase the hybrid system owner's profit, and decrease total active power loss of the ADN. According to the obtained results in the 33-bus test system, the profit of the hybrid system owner is increased by up to 6.8% as well as the total active power loss being decreased by up 75.58% through the presented structure.

Original languageEnglish
Pages (from-to)297-306
Number of pages10
JournalIET Smart Grid
Issue number3
Publication statusPublished - Jun 2021

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