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

作　　者：Mohammad Dolatabadi Alberto Borghetti Pierluigi Siano 

机构地区：[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

出　　处：《Journal of Modern Power Systems and Clean Energy》2023年第6期1814-1826,共13页现代电力系统与清洁能源学报（英文）

摘　　要：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.

关 键 词：Accelerated gradient method battery storage system conic projection energy community energy scheduling linear programming renewable resource 

分 类 号：TM73[电气工程—电力系统及自动化]