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.
Scalable Distributed Optimization Combining Conic Projection and Linear Programming for Energy Community Scheduling / Dolatabadi M.; Borghetti A.; Siano P.. - In: JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY. - ISSN 2196-5625. - ELETTRONICO. - 11:6(2023), pp. 10136529.1814-10136529.1826. [10.35833/MPCE.2022.000783]
Scalable Distributed Optimization Combining Conic Projection and Linear Programming for Energy Community Scheduling
Borghetti A.;
2023
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.File | Dimensione | Formato | |
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