Journal of Modern Power Systems and Clean Energy

ISSN 2196-5625 CN 32-1884/TK

Scalable Distributed Optimization Combining Conic Projection and Linear Programming for Energy Community Scheduling
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Affiliation:

1.Department of Mathematics, Vali-e-Asr University of Rafsanjan, Rafsanjan 77188-97111, Iran
2.Department of Electrical, Electronic, and Information Engineering, University of Bologna, Bologna, Italy
3.Department of Management & Innovation Systems, University of Salerno, Salerno, Italy
4.Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg 2006, South Africa

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    Abstract:

    In this paper, a new method to address the scheduling problem of a renewable energy community while considering network constraints and users’ privacy preservation is proposed. The method decouples the optimization solution into two interacting procedures: conic projection (CP) and linear programming (LP) optimization. A new optimal CP method is proposed based on local computations and on the calculation of the roots of a fourth-order polynomial for which a closed-form solution is known. Computational tests conducted on both 14-bus and 84-bus distribution networks demonstrate the effectiveness of the proposed method in obtaining the same quality of solutions compared with that by a centralized solver. The proposed method is scalable and has features that can be implemented on microcontrollers since both LP and CP procedures require only simple matrix-vector multiplications.

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History
  • Received:November 29,2022
  • Revised:February 21,2023
  • Adopted:
  • Online: November 16,2023
  • Published: