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Scalable Distributed Optimization Combining Conic Projection and Linear Programming for Energy Community Scheduling 被引量:2
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作者 Mohammad Dolatabadi Alberto Borghetti Pierluigi Siano 《Journal of Modern Power Systems and Clean Energy》 SCIE EI CSCD 2023年第6期1814-1826,共13页
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 optimizatio... 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. 展开更多
关键词 Accelerated gradient method battery storage system conic projection energy community energy scheduling linear programming renewable resource
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