Congestion Management of Microgrids With Renewable Energy Resources and Energy Storage Systems

被引:4
作者
Chen, Yaling [1 ]
Liu, Yinpeng [2 ]
机构
[1] Hunan Univ, Strateg Emerging Ind Dev Res Ctr, Changsha, Peoples R China
[2] Chinese Acad Sci, Inst Sci & Dev, Beijing, Peoples R China
关键词
congestion management; microgrid; dynamic tariff-subsidy; energy storage system; renewable energy resources; DISTRIBUTION NETWORKS; DYNAMIC TARIFF;
D O I
10.3389/fenrg.2021.708087
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 increasing share of renewable energy resources in the microgrid, the microgrid faces more and more challenges in its reliable operation. One major challenge is the potential congestion caused by the uncoordinated operation of flexible demands such as heat pumps and the high penetration of renewable energy resources such as photovoltaics. Therefore, it is important to conduct microgrid energy management to ensure its reliable operation. The energy storage system (ESS) scheduling as an efficient means to alleviate congestion has been widely used. However, in the existing literature, the ESSs are usually scheduled by the microgrid system operator (MSO) in a direct control manner, which is impractical in the case where customers own ESSs and are willing to schedule ESSs by themselves. To resolve this issue, this study proposes a network reconfiguration integrated dynamic tariff-subsidy (DTS) congestion management method to utilize ESSs and network reconfiguration to alleviate congestion in microgrids caused by renewable energy resources and flexible demands. In the proposed method, the MSO controls sectionalization switches while customers or aggregators schedule ESSs in response to DTS to alleviate congestion. The DTS calculation model is formulated as a mixed-integer linear programming model, considering heat pumps (HPs), ESSs, and reconfigurable microgrid topology. The numerical results demonstrate that the proposed method can effectively use ESSs and network topology to alleviate congestion and the MSO does not need to take over the scheduling of the ESS.
引用
收藏
页数:10
相关论文
共 28 条
[1]   A RELIABILITY TEST SYSTEM FOR EDUCATIONAL PURPOSES - BASIC DISTRIBUTION-SYSTEM DATA AND RESULTS [J].
ALLAN, RN ;
BILLINTON, R ;
SJARIEF, I ;
GOEL, L ;
SO, KS .
IEEE TRANSACTIONS ON POWER SYSTEMS, 1991, 6 (02) :813-820
[2]   Identifying suitable models for the heat dynamics of buildings [J].
Bacher, Peder ;
Madsen, Henrik .
ENERGY AND BUILDINGS, 2011, 43 (07) :1511-1522
[3]  
Biegel B., 2012, IFAC Proc, V45, P518, DOI 10.3182/20120902-4-FR-2032.00091
[4]   Echo State Network-Based Backstepping Adaptive Iterative Learning Control for Strict-Feedback Systems: An Error-Tracking Approach [J].
Chen, Qiang ;
Shi, Huihui ;
Sun, Mingxuan .
IEEE TRANSACTIONS ON CYBERNETICS, 2020, 50 (07) :3009-3022
[5]   Adaptive Nonsingular Fixed-Time Attitude Stabilization of Uncertain Spacecraft [J].
Chen, Qiang ;
Xie, Shuzong ;
Sun, Mingxuan ;
He, Xiongxiong .
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2018, 54 (06) :2937-2950
[6]   Fault Diagnosis of Wind Turbine Gearboxes Based on DFIG Stator Current Envelope Analysis [J].
Cheng, Fangzhou ;
Qu, Liyan ;
Qiao, Wei ;
Wei, Chun ;
Hao, Liwei .
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2019, 10 (03) :1044-1053
[7]  
Haque A. N. M. M., 2016, 2016 Power Systems Computation Conference (PSCC), P1, DOI 10.1109/PSCC.2016.7540985
[8]   Dynamic Tariff-Subsidy Method for PV and V2G Congestion Management in Distribution Networks [J].
Huang, Shaojun ;
Wu, Qiuwei .
IEEE TRANSACTIONS ON SMART GRID, 2019, 10 (05) :5851-5860
[9]   Dynamic Power Tariff for Congestion Management in Distribution Networks [J].
Huang, Shaojun ;
Wu, Qiuwei ;
Shahidehpour, Mohammad ;
Liu, Zhaoxin .
IEEE TRANSACTIONS ON SMART GRID, 2019, 10 (02) :2148-2157
[10]   Real-Time Congestion Management in Distribution Networks by Flexible Demand Swap [J].
Huang, Shaojun ;
Wu, Qiuwei .
IEEE TRANSACTIONS ON SMART GRID, 2018, 9 (05) :4346-4355