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Energy Management in Active Distribution System Considering Shared Energy Storage System and Peer-to-Peer Trading using Robust Optimization

Soltanian, Hamid | 2024

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 56935 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Hosseini, Hamid
  7. Abstract:
  8. Peer-to-peer (P2P) tradings are one of the energy management techniques that economically benefit prosumers and they can transact their energy as goods and services. In this work, a robust framework is proposed to address optimal energy management of an energy community considering peer-to-peer and peer-to-grid (P2G) tradings. Adaptive distributionally robust optimization (ADRO) is used to minimizing total community cost. Uncertainties in the load and output power of renewable energy sources (RES) are modeled by using this method. The production cost of prosumers and shared energy storage costs are considered as objective function. The problem is formulated as a bi-level minimum-maximum optimization problem and is solved in two levels. In upper level, by maximizing costs related to uncertain variables, the worst case for them is determined using distributionally robust chance constraint (DRCC) technique. In lower level, according to the results obtained in the upper level, by minimizing total cost of energy community, the final optimal solution is obtained using mixed integer linear programming (MILP) approach. The obtained solution results demonstrate that energy storages, renewable energy sources and peer-to-peer trading can reduce the need for prosumers to buy energy from the grid during load peak time and high energy prices. This approach is applied to an energy community with 10 grid-connected prosumers consisting of renewable energy sources (photovoltaic and wind turbine), diesel generator, shared and individual energy storage systems
  9. Keywords:
  10. Energy Management ; Robust Optimization ; Uncertainty ; Peer-to-Peer Trading ; Renewable Energy Resources ; Energy Storage ; Distributionally Robust Chance Constraint

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