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

作     者：Mohammad Dolatabadi Alberto Borghetti Pierluigi Siano Mohammad Dolatabadi;Alberto Borghetti;Pierluigi Siano

作者机构：Department of MathematicsVali-e-Asr University of RafsanjanRafsanjan 77188-97111Iran Department of ElectricalElectronicand Information EngineeringUniversity of BolognaBolognaItaly Department of Management&Innovation SystemsUniversity of SalernoSalernoItaly Department of Electrical and Electronic Engineering ScienceUniversity of JohannesburgJohannesburg 2006South Africa 

出 版 物：《Journal of Modern Power Systems and Clean Energy》 (现代电力系统与清洁能源学报（英文）)

年 卷 期：2023年第11卷第6期

页      面：1814-1826页

核心收录：

学科分类：0808[工学-电气工程] 080802[工学-电力系统及其自动化] 08[工学] 0701[理学-数学] 

主　　题：Accelerated gradient method battery storage system conic projection energy community energy scheduling linear programming renewable resource 

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.