An AC-Feasible Linear Model in Distribution Networks With Energy Storage

被引:7
作者
Lin, Wei [1 ]
Chen, Yue [2 ]
Li, Qifeng [3 ]
Zhao, Changhong [4 ]
机构
[1] Hong Kong Polytech Univ, Dept Elect Engn, Hong Kong 999077, Peoples R China
[2] Chinese Univ Hong Kong, Dept Mech & Automat Engn, Hong Kong 999077, Peoples R China
[3] Univ Cent Florida, Dept Elect & Comp Engn, Orlando, FL 32816 USA
[4] Chinese Univ Hong Kong, Dept Informat Engn, Hong Kong 999077, Peoples R China
关键词
Distribution network; AC-feasible dispatch; linear model; energy storage; CONGESTION MANAGEMENT; PREDICTION MODEL; OPTIMIZATION; ALLEVIATION; OVERLOADS;
D O I
10.1109/TPWRS.2023.3244959
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
With the increasing deployment of distributed energy resources (DERs), dispatching DERs subject to operational constraints in distribution networks draws much attention. One challenge is the non-convexities in 1) system-wide AC power flow constraints and 2) the individual complementarity constraint of energy storage. To resolve this challenge, this paper studies an AC-feasible linear model in distribution networks with energy storage, including its formulation, analysis, and applications. First, an AC-feasible linear model is formulated as a set of linear constraints on controllable DERs and uncontrollable power demand by 1) converting the non-convex system-wide constraints into linear constraints based on the Brouwer's fixed-point theorem and the second-order Taylor expansion, and 2) replacing the non-convex individual complementarity constraint of energy storage with one properly designed linear constraint. Furthermore, to analyze the power demand level at which the proposed linear model can provide a solution, this paper proposes an examination-based projection method under the Monte Carlo framework to handle projections of thousands of dimensions from linear constraints over time periods. Finally, the potential applications of our AC-feasible linear model are discussed. Numerical experiments are conducted in the IEEE 33-bus and 136-bus test systems to demonstrate the effectiveness of the proposed methods.
引用
收藏
页码:1224 / 1239
页数:16
相关论文
共 66 条
  • [1] Transmission Lines Overload Alleviation by Generation Rescheduling and Load Shedding
    Abbas, Abdelaziz Y. M.
    Hassan, Salah Eldeen Gasim Mohamed
    Abdelrahim, Yousif Hassan
    [J]. JOURNAL OF INFRASTRUCTURE SYSTEMS, 2016, 22 (04)
  • [2] Achiam J, 2017, PR MACH LEARN RES, V70
  • [3] Battery control with lookahead constraints in distribution grids using reinforcement learning
    Andre, Joel da Silva
    Stai, Eleni
    Stanojev, Ognjen
    Hug, Gabriela
    [J]. ELECTRIC POWER SYSTEMS RESEARCH, 2022, 211
  • [4] Anticipatory load shedding for line overload alleviation using Teaching learning based optimization (TLBO)
    Arya, L. D.
    Koshti, Atul
    [J]. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2014, 63 : 862 - 877
  • [5] A Unified Online Deep Learning Prediction Model for Small Signal and Transient Stability
    Azman, Syafiq Kamarul
    Isbeih, Younes J.
    El Moursi, Mohamed Shawky
    Elbassioni, Khaled
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2020, 35 (06) : 4585 - 4598
  • [6] Birge JR, 2011, SPRINGER SER OPER RE, P3, DOI 10.1007/978-1-4614-0237-4
  • [7] Chollet F., 2015, Keras
  • [8] Chow G. R. J., 2008, Power system toolbox
  • [9] Transmission Lines Overload Alleviation: Distributed Online Optimization Approach
    Ding, Li
    Hu, Ping
    Liu, Zhi-Wei
    Wen, Guanghui
    [J]. IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2021, 17 (05) : 3197 - 3208
  • [10] Donnot B., 2020, Grid2op-A testbed platform to model sequential decision making in power systems