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Optimal energy management of distribution networks in post-contingency conditions

Fattaheian Dehkordi, S ; Sharif University of Technology | 2022

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  1. Type of Document: Article
  2. DOI: 10.1016/j.ijepes.2022.108022
  3. Publisher: Elsevier Ltd , 2022
  4. Abstract:
  5. Emergence of reformation and privatization in energy systems has caused the development of multi-agent distribution systems. In this context, each agent as an independent entity aims to efficiently operate its respective resources; while, the distribution network operator (DNO) strives to control the grid in an efficient and reliable manner. Respectively, in case of failure incidences in the grid, DNO should address the economic losses as well as reliability concerns of the agents. Consequently, this paper intends to organize a framework that enables the DNO in order to incentivize the cooperation of agents to alleviate operational effects of the contingency condition. Accordingly, DNO provides bonuses to agents to modify their scheduling with the aim of optimizing the incurred operating costs in post-contingency conditions. Respectively, Stackelberg game is applied to model the incentivizing resource scheduling optimization in post-contingency conditions, and strong duality condition is used to re-cast the preliminary bi-level model into a one-level mathematical problem. Furthermore, a step-wise strategy is illustrated to facilitate the application of the obtained optimization model while considering islanded areas in the grid. Eventually, the proposed strategy is implemented on the IEEE-33-bus-test-network to examine its usefulness and applicability in management of the distribution networks in post-contingency conditions. © 2022
  6. Keywords:
  7. Renewable energy ; Resource scheduling ; Stackelberg game ; Energy management systems ; Losses ; Multi agent systems ; Operating costs ; Privatization ; Reliability ; Renewable energy resources ; Scheduling ; Agent distribution ; Condition ; Contingency management ; Distribution systems ; Flexible resources ; Multi agent ; Multi-agent distribution system ; Renewable energies ; Resource-scheduling ; Stackelberg Games ; Energy management
  8. Source: International Journal of Electrical Power and Energy Systems ; Volume 141 , 2022 ; 01420615 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/abs/pii/S0142061522000667