Robust Multi-Objective Congestion Management in Distribution Network

被引:9
|
作者
Khan, Omniyah Gul M. [1 ]
Youssef, Amr [2 ]
Salama, Magdy [1 ]
El-Saadany, Ehab [3 ]
机构
[1] Univ Waterloo, Elect & Comp Engn Dept, Waterloo, ON N2L 3G1, Canada
[2] Concordia Univ, Concordia Inst Informat Syst Engn, Montreal, PQ H3G 1M8, Canada
[3] Khalifa Univ, EECS Dept, Adv Power & Energy Ctr, Abu Dhabi, U Arab Emirates
基金
加拿大自然科学与工程研究理事会;
关键词
Multi-Objective; Pareto; valley-filling; price-based; Demand Side Management; DISTRIBUTION-SYSTEMS; DEMAND RESPONSE;
D O I
10.1109/TPWRS.2022.3200838
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
Increased penetration of heavy loads is expected to lead to congestion in distribution networks. The distribution network operator can use Demand Side Management (DSM) to motivate consumers to shift their load from peak to off-peak times. In this paper, multi-objective optimization is utilized to schedule flexible load to alleviate potential congestions. The proposed scheme minimizes consumers' electricity cost and decreases the peak to average ratio of the load curve to a required level that alleviates existing congestion. This results in a consumer load schedule that is economical and does not require the imposition of congestion tariffs. However, the success of the proposed congestion management scheme relies on the accuracy of the consumer load consumption. Hence, in this paper, uncertainty analysis of consumers' flexible load schedule is executed to ensure the desired robustness of the power flowing in the distribution network to changes in uncertain variables. The results obtained are compared with the existing congestion management scheme demonstrating the advantage of the proposed multi-objective framework in terms of decreasing price and flattening the load curve while alleviating congestion.
引用
收藏
页码:3568 / 3579
页数:12
相关论文
共 50 条
  • [11] Distributionally robust hierarchical multi-objective voltage risk management for unbalanced distribution systems
    Zhang, Shida
    Ge, Shaoyun
    Liu, Hong
    Zhao, Bo
    Ni, Chouwei
    Xu, Zhengyang
    Gu, Chenghong
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2023, 154
  • [12] Multi-Objective Network Congestion Control via Constrained Reinforcement Learning
    Liu, Qiong
    Yang, Peng
    Lyu, Feng
    Zhang, Ning
    Yu, Li
    2021 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2021,
  • [13] Multi-objective planning of distribution network considering network survivability
    Wei, Z. (wzn_nj@263.net), 1600, Automation of Electric Power Systems Press (38):
  • [14] Multi-Objective Demand Side Management at Distribution Network Level in Support of Transmission Network Operation
    Ponocko, Jelena
    Milanovic, Jovica, V
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2020, 35 (03) : 1822 - 1833
  • [15] Congestion Management Using Multi-Objective Glowworm Swarm Optimization Algorithm
    Salkuti, Surender Reddy
    Kim, Seong-Cheol
    JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, 2019, 14 (04) : 1565 - 1575
  • [16] Congestion Management Using Multi-Objective Glowworm Swarm Optimization Algorithm
    Surender Reddy Salkuti
    Seong-Cheol Kim
    Journal of Electrical Engineering & Technology, 2019, 14 : 1565 - 1575
  • [17] Multi-Class Freeway Congestion and Emission Based on Robust Dynamic Multi-Objective Optimization
    Chen, Juan
    Feng, Qinxuan
    Guo, Qi
    ALGORITHMS, 2021, 14 (09)
  • [18] Multi-objective distribution network reconfiguration optimization problem
    Souifi, Hayfa
    Kahouli, Omar
    Abdallah, Hsan Hadj
    ELECTRICAL ENGINEERING, 2019, 101 (01) : 45 - 55
  • [19] Multi-objective optimisation of the operation of a water distribution network
    Mulholland, Michael
    Latifi, M. Abderrazak
    Purdon, Andrew
    Buckley, Christopher
    Brouckaert, Christopher
    JOURNAL OF WATER SUPPLY RESEARCH AND TECHNOLOGY-AQUA, 2015, 64 (03): : 235 - 249
  • [20] Multi-objective distribution network reconfiguration optimization problem
    Hayfa Souifi
    Omar Kahouli
    Hsan Hadj Abdallah
    Electrical Engineering, 2019, 101 : 45 - 55