Adaptive primal-dual control for distributed energy resource management

被引:0
|
作者
Comden, Joshua [1 ]
Wang, Jing [1 ]
Bernstein, Andrey [1 ]
机构
[1] Natl Renewable Energy Lab, 15013 Denver West Pkwy, Golden, CO 80401 USA
关键词
Distributed energy resource management; system; Virtual power plant; Primal-dual control; Grid service; FEEDBACK;
D O I
10.1016/j.apenergy.2023.121883
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
With the increased adoption of distributed energy resources (DERs) in distribution networks, their coordinated control with a DER management system (DERMS) that provides grid services (e.g., voltage regulation, virtual power plant) is becoming more necessary. One particular type of DERMS using primal-dual control has recently been found to be very effective at providing multiple grid services among an aggregation of DERs; however, the main parameter, the primal-dual step size, must be manually tuned for the DERMS to be effective, which can take a considerable amount of engineering time and labor. To this end, we design a simple method that self -tunes the step size(s) and adapts it to changing system conditions. Additionally, it gives the DER management operator the ability to prioritize among possibly competing grid services. We evaluate the automatic tuning method on a simulation model of a real-world feeder in Colorado with data obtained from an electric utility. Through a variety of scenarios, we demonstrate that the DERMS with automatically and adaptively tuned step sizes provides higher-quality grid services than a DERMS with a manually tuned step size.
引用
收藏
页数:16
相关论文
共 50 条
  • [41] Return of the Primal-Dual: Distributed Metric Facility Location
    Pandit, Saurav
    Pemmaraju, Sriram
    PODC'09: PROCEEDINGS OF THE 2009 ACM SYMPOSIUM ON PRINCIPLES OF DISTRIBUTED COMPUTING, 2009, : 180 - 189
  • [42] An adaptive primal-dual framework for nonsmooth convex minimization
    Quoc Tran-Dinh
    Ahmet Alacaoglu
    Olivier Fercoq
    Volkan Cevher
    Mathematical Programming Computation, 2020, 12 : 451 - 491
  • [43] Adaptive coordinate sampling for stochastic primal-dual optimization
    Liu, Huikang
    Wang, Xiaolu
    So, Anthony Man-Cho
    INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, 2022, 29 (01) : 24 - 47
  • [44] Distributed Primal-Dual Optimization for Non-uniformly Distributed Data
    Cheng, Minhao
    Hsieh, Cho-Jui
    PROCEEDINGS OF THE TWENTY-SEVENTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2018, : 2028 - 2034
  • [45] Stability of the primal-dual algorithm for congestion control
    Tian, YP
    Chen, G
    INTERNATIONAL JOURNAL OF CONTROL, 2006, 79 (06) : 662 - 676
  • [46] Stability and Performance Limits of Adaptive Primal-Dual Networks
    Towfic, Zaid J.
    Sayed, Ali H.
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2015, 63 (11) : 2888 - 2903
  • [47] An adaptive primal-dual framework for nonsmooth convex minimization
    Quoc Tran-Dinh
    Alacaoglu, Ahmet
    Fercoq, Olivier
    Cevher, Volkan
    MATHEMATICAL PROGRAMMING COMPUTATION, 2020, 12 (03) : 451 - 491
  • [48] Distributed Microgrid Management Using Passivity-based Generalized Primal-Dual Dynamics
    Namba, Takumi
    Yamashita, Shunya
    Hatanaka, Takeshi
    Takaba, Kiyotsugu
    2019 3RD IEEE CONFERENCE ON CONTROL TECHNOLOGY AND APPLICATIONS (IEEE CCTA 2019), 2019, : 573 - 580
  • [49] Distributed Frequency and Voltage Control for AC Microgrids based on Primal-Dual Gradient Dynamics
    Koelsch, Lukas
    Wieninger, Katharina
    Krebs, Stefan
    Hohmann, Soeren
    IFAC PAPERSONLINE, 2020, 53 (02): : 12229 - 12236
  • [50] ON PRIMAL-DUAL ALGORITHMS
    BELL, EJ
    JENNINGS, C
    COMMUNICATIONS OF THE ACM, 1966, 9 (09) : 653 - &