Interactive demand response and dynamic thermal line rating for minimizing the wind power spillage and carbon emissions

被引:1
作者
Fawzy, Samaa [1 ]
Abd-Raboh, Elhossaini E. [1 ]
Eladl, Abdelfattah A. [1 ]
机构
[1] Mansoura Univ, Fac Engn, Elect Engn Dept, Mansoura 35516, Egypt
关键词
Wind power spillage; Demand response; Dynamic thermal line rating; Optimal power flow; Bi-level optimization; GENERATION; SYSTEMS; OPERATION; FARMS;
D O I
10.1016/j.epsr.2024.110399
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
Spilling has already occurred as a result of rising the penetration of intermittent renewable generation, and it is anticipated that the level of renewable energy curtailment will continue to soar. This leads to an increase in operating costs, CO2 2 emissions, and not good utilization of renewable energy resources. A bi-level multi-objective optimization model is proposed in this paper to reduce wind power spillage (WPS) based on demand response (DR) and dynamic thermal line rating (DTLR). In the upper level, multiple objectives will be satisfied based on the optimal allocation and time of DR programs considering DTLR obtained in the lower level. The minimization of WPS, load shedding, power losses, and CO2 2 emissions are the objectives of this level. While the lower-level aims to maximize social welfare under different scenarios and overall system constraints. Under the uncertainty of the wind power and load demand, a collection of lower-level problems that represent the market clearing conditions is used to constrain the upper-level. The effectiveness of the proposed algorithm is examined on a modified two-area IEEE 24-bus test system. Results depict that the suggested bi-level model enables considerable reductions in the WPS by up to 32.7 %. Also, there is an enhancement in load shedding, power losses, and CO2 2 emissions by 28.93 %, 23.07 %, and 13.9 % respectively. Finally, the social welfare increased by up to 36.6 %.
引用
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页数:15
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  • [31] Coordinated operation of reconfigurable networks with dynamic line rating for optimal utilization of renewable generation
    Numan, Muhammad
    Feng, Donghan
    Abbas, Farukh
    Habib, Salman
    Hao, Su
    [J]. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2021, 125 (125)
  • [32] Stochastic security-constrained unit commitment with wind power generation based on dynamic line rating
    Park, Hyeongon
    Jin, Young Gyu
    Par, Jong-Keun
    [J]. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2018, 102 : 211 - 222
  • [33] Distributed demand response market model for facilitating wind power integration
    Saebi, Javad
    Thanh Nguyen, Duy
    [J]. IET SMART GRID, 2020, 3 (03) : 394 - 405
  • [34] Toward mitigating wind-uncertainty costs in power system operation: A demand response exchange market framework
    Saebi, Javad
    Javidi, Mohammad Hossein
    Buygi, Majid Oloomi
    [J]. ELECTRIC POWER SYSTEMS RESEARCH, 2015, 119 : 157 - 167
  • [35] IoT-based optimal demand side management and control scheme for smart microgrid
    Sedhom, Bishoy E.
    El-Saadawi, Magdi M.
    El Moursi, M. S.
    Hassan, Mohamed A.
    Eladl, Abdelfattah A.
    [J]. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2021, 127
  • [36] Wind Power Scenario Generation and Reduction in Stochastic Programming Framework
    Sharma, Kailash Chand
    Jain, Prerna
    Bhakar, Rohit
    [J]. ELECTRIC POWER COMPONENTS AND SYSTEMS, 2013, 41 (03) : 271 - 285
  • [37] A review on microgrid decentralized energy/voltage control structures and methods
    Shirkhani, Mohammadamin
    Tavoosi, Jafar
    Danyali, Saeed
    Sarvenoee, Amirhossein Khosravi
    Abdali, Ali
    Mohammadzadeh, Ardashir
    Zhang, Chunwei
    [J]. ENERGY REPORTS, 2023, 10 : 368 - 380
  • [38] Comparative analysis of dynamic line rating models and feasibility to minimise energy losses in wind rich power networks
    Simms, Mathew
    Meegahapola, Lasantha
    [J]. ENERGY CONVERSION AND MANAGEMENT, 2013, 75 : 11 - 20
  • [39] Hierarchical and distributed energy management framework for AC/DC hybrid distribution systems with massive dispatchable resources
    Su, Yi
    Teh, Jiashen
    Liu, Wei
    [J]. ELECTRIC POWER SYSTEMS RESEARCH, 2023, 225
  • [40] Optimal Dispatching for AC/DC Hybrid Distribution Systems With Electric Vehicles: Application of Cloud-Edge-Device Cooperation
    Su, Yi
    Teh, Jiashen
    Chen, Changqing
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2024, 25 (03) : 3128 - 3139