A comprehensive review of planning, modeling, optimization, and control of distributed energy systems

被引:41
作者
Hao, Junhong [1 ]
Yang, Yongping [1 ]
Xu, Chao [1 ]
Du, Xiaoze [1 ]
机构
[1] North China Elect Power Univ, Sch Energy Power & Mech Engn, Key Lab Power Stn Energy Transfer Convers, Minist Educ, Beijing 102206, Peoples R China
来源
CARBON NEUTRALITY | 2022年 / 1卷 / 01期
基金
中国国家自然科学基金;
关键词
Distributed energy systems; Planning; Evaluation; Modeling; Optimization; Operation; Control; SOURCE HEAT-PUMP; POWER DISTRIBUTION NETWORKS; OPTIMAL-DESIGN; MULTIOBJECTIVE OPTIMIZATION; OPERATION OPTIMIZATION; EXERGY ANALYSIS; INTEGRATED EVALUATION; SENSITIVITY-ANALYSIS; GENERATION SYSTEMS; PROGRAMMING MODEL;
D O I
10.1007/s43979-022-00029-1
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Distributed energy system, a decentralized low-carbon energy system arranged at the customer side, is characterized by multi-energy complementarity, multi-energy flow synergy, multi-process coupling, and multi-temporal scales (n-M characteristics). This review provides a systematic and comprehensive summary and presents the current research on distributed energy systems in three dimensions: system planning and evaluation, modeling and optimization, and operation and control. Under the regional environmental, resource, and policy constraints, planning distributed energy systems should fully integrate technical, economic, environmental, and social factors and consider device characteristics, system architecture, and source-load uncertainties. Further, this review presents four modeling perspectives for optimizing and analyzing distributed energy systems, including energy hub, thermodynamics, heat current, and data-driven. The system's optimal operation and scheduling strategies, disturbance analysis, and related control methods are also discussed from the power system and thermal system, respectively. In all, more research is required for distributed energy systems based on an integrated energy perspective in optimal system structure, hybrid modeling approaches, data-driven system state estimation, cross-system disturbance spread, and multi-subject interaction control.
引用
收藏
页数:29
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