Cluster voltage control method for “Whole County” distributed photovoltaics based on improved differential evolution algorithm
Received date: 11 Mar 2023
Accepted date: 01 Oct 2023
Published date: 15 Dec 2023
Copyright
China is vigorously promoting the “whole county promotion” of distributed photovoltaics (DPVs). However, the high penetration rate of DPVs has brought problems such as voltage violation and power quality degradation to the distribution network, seriously affecting the safety and reliability of the power system. The traditional centralized control method of the distribution network has the problem of low efficiency, which is not practical enough in engineering practice. To address the problems, this paper proposes a cluster voltage control method for distributed photovoltaic grid-connected distribution network. First, it partitions the distribution network into clusters, and different clusters exchange terminal voltage information through a “virtual slack bus.” Then, in each cluster, based on the control strategy of “reactive power compensation first, active power curtailment later,” it employs an improved differential evolution (IDE) algorithm based on Cauchy disturbance to control the voltage. Simulation results in two different distribution systems show that the proposed method not only greatly improves the operational efficiency of the algorithm but also effectively controls the voltage of the distribution network, and maximizes the consumption capacity of DPVs based on qualified voltage.
Jing ZHANG , Tonghe WANG , Jiongcong CHEN , Zhuoying LIAO , Jie SHU . Cluster voltage control method for “Whole County” distributed photovoltaics based on improved differential evolution algorithm[J]. Frontiers in Energy, 2023 , 17(6) : 782 -795 . DOI: 10.1007/s11708-023-0905-8
1 |
Bonthagorla P K, Mikkili S, Optimal P V. Array configuration for extracting maximum power under partial shading conditions by mitigating mismatching power losses. CSEE Journal of Power and Energy Systems, 2022, 8(2): 499–510
|
2 |
Swenson R. The solar evolution: Much more with way less, right now—The disruptive shift to renewables. Energies, 2016, 9(9): 676
|
3 |
Martins F, Felgueiras C, Smitkova M.
|
4 |
Wang S C. Current status of PV in China and its future forecast. CSEE Journal of Power and Energy Systems, 2020, 6(1): 72–82
|
5 |
Ahadi A, Miryousefi Aval S M, Hayati H. Generating capacity adequacy evaluation of large-scale, grid-connected photovoltaic systems. Frontiers in Energy, 2016, 10(3): 308–318
|
6 |
Shahsavari A, Akbari M. Potential of solar energy in developing countries for reducing energy-related emissions. Renewable & Sustainable Energy Reviews, 2018, 90: 275–291
|
7 |
Singla P, Duhan M, Saroha S. A comprehensive review and analysis of solar forecasting techniques. Frontiers in Energy, 2022, 16(2): 187–223
|
8 |
Lu Q, Yu H, Zhao K L.
|
9 |
Liu S Y, Bie Z H, Liu F.
|
10 |
Wu Y N, Xu M J, Tao Y.
|
11 |
Gandhi O, Kumar D S, Rodríguez-Gallegos C D.
|
12 |
Chen J L, Xu X Y, Yan Z.
|
13 |
Zhang Y J, Qiao Y, Lu Z X.
|
14 |
Camilo F M, Almeida M E, Castro R.
|
15 |
Hashemi S, Ostergaard J. Methods and strategies for overvoltage prevention in low voltage distribution systems with PV. IET Renewable Power Generation, 2017, 11(2): 205–214
|
16 |
Nour A M M, Hatata A Y, Helal A A.
|
17 |
Xu J, Fu H B, Liao S Y.
|
18 |
Jamal T, Urmee T, Calais M.
|
19 |
Yang A Q, Cai Y X, Chen X P.
|
20 |
LiQ RZhang J C. Solutions of voltage beyond limits in distribution network with distributed photovoltaic generators. Automation of Electric Power Systems, 2015, 39(22): 117–123 (in Chinese)
|
21 |
WangYWen F SZhaoB,
|
22 |
Wang C L, Tao Y G. Locally and globally optimal solutions of global optimisation for max-plus linear systems. IET Control Theory & Applications, 2022, 16(2): 219–228
|
23 |
Zhao B, Xu Z C, Xu C.
|
24 |
Chai Y Y, Guo L, Wang C S.
|
25 |
Ding J J, Zhang Q, Hu S J.
|
26 |
Cao D, Zhao J B, Hu W H.
|
27 |
Liu L J, Zhang Y, Da C.
|
28 |
Sun J, Xu J, Ke D P.
|
29 |
Newman M E J. Fast algorithm for detecting community structure in networks. Physical Review E: Statistical, Nonlinear, and Soft Matter Physics, 2004, 69(6): 066133
|
30 |
Newman M E J. Modularity and community structure in networks. Proceedings of the National Academy of Sciences of the United States of America, 2006, 103(23): 8577–8582
|
31 |
Deng L B, Sun H L, Zhang L L.
|
32 |
Qian J, Wang P, Chen G G. Improved gravitational search algorithm and novel power flow prediction network for multi-objective optimal active dispatching problems. Expert Systems with Applications, 2023, 223: 119863
|
33 |
WagleRSharma PSharmaC,
|
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〈 | 〉 |