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Resilience Analysis of Energy Supply Networks by Agent-based Modelling and Simulation

Adelipour, Sajjad | 2022

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 55914 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): shadrokh Sikari, Shahram
  7. Abstract:
  8. In this thesis, the resilience of energy supply networks and the application of Agent Based Modeling in the resilience analysis of power microgrids are studied. The main idea is to use microgrids as a solution to make power systems resilient. A microgrid with autonomous agents consisting of renewable resources, non-dispatchable generators, dispatchable generators, residential loads, critical loads, battery storages, and microgrid controller is investigated. Each agent is autonomous and has independent behavior such that the interaction between these agents produces emergent phenomena at the system level in the microgrid. In the developed model, residential consumers try to optimize their consumption in order to maximize their utility and minimize the cost of power usage. Microgrid controller, also, operates microgrid in a resilient and cost-efficient manner by solving a multi-objective problem. In this regard, microgrid controller can utilize the capacity of battery storages and controllable power generators, exchanging power with the upstream network, and power shading of curtailable consumers. The two mentioned multi-objective optimization problems are solved by each residential agent and the microgrid controller agent using goal programming and a weighted-sum approach, respectively. By Simulating the model for 24 hours indicates the ability of the microgrid controller agent to prevent blackouts in the microgrid and maintain the system’s performance when a disruption occurs. Additionally, Residential agents use less power during peak hours than expected to reduce costs and use more amount of power during off-peak hours to increase their utility
  9. Keywords:
  10. Network Resiliance ; Microgrid ; Renewable Energy Resources ; Agent Based Simulation ; Energy Supply Network ; Agent Based Modeling

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