Fast Distributed Voltage Control for PV Generation Clusters Based on Approximate Newton Method

Solar power generation is exhibiting a distributed development trend, and has changed conventional characteristics of power supply and consumption. The integration of large-scale distributed photovoltaic (PV) generation forms high-penetration PV clusters in distribution networks, which aims to organize and control geographically scattered resources. However, due to the inherent uncertainty, high-penetration PV clusters are suffering from random disturbances and serious voltage risks. Besides, integrating system via power electronic interfaces, PV generation usually tracks system frequency without any backup and regulation capacity, which poses significant challenges to system operation, and requires greater flexibility of voltage control. In fact, by using appropriate methods, PV inverters can autonomously regulate reactive power output in a distributed manner to improve voltage profiles in clusters. In this article, a distributed voltage control method for PV generation clusters is presented to realize decentralized coordination of PV inverters. Based on matrix splitting and approximate Newton method, it can fast respond to reactive power mismatch and realize voltage profiles optimization. Exhibiting a more efficient, reliable and flexible performance than existing decentralized methods in case studies, the proposed method is demonstrated to effectively organize and control PV cluster to provide corresponding reactive power support and exert friendly effect on system operation.

[1]  Kumars Rouzbehi,et al.  Innovative primary frequency control in low‐inertia power systems based on wide‐area RoCoF sharing , 2020, IET Energy Systems Integration.

[2]  Zhang Bo,et al.  Research on local voltage control strategy based on high-penetration distributed PV systems , 2019 .

[3]  M. Projected Newton Methods and Optimization of Multicommodity Flows , 2022 .

[4]  Asuman E. Ozdaglar,et al.  A Distributed Newton Method for Network Utility Maximization—Part II: Convergence , 2010, IEEE Transactions on Automatic Control.

[5]  Hao Jan Liu,et al.  Fast Local Voltage Control Under Limited Reactive Power: Optimality and Stability Analysis , 2015, IEEE Transactions on Power Systems.

[6]  L.A.F. Ferreira,et al.  Distributed Reactive Power Generation Control for Voltage Rise Mitigation in Distribution Networks , 2008, IEEE Transactions on Power Systems.

[7]  Asuman E. Ozdaglar,et al.  Distributed Subgradient Methods for Multi-Agent Optimization , 2009, IEEE Transactions on Automatic Control.

[8]  Michael Chertkov,et al.  Options for Control of Reactive Power by Distributed Photovoltaic Generators , 2010, Proceedings of the IEEE.

[9]  Boming Zhang,et al.  A Distributed Quasi-Newton Method for Droop-Free Primary Frequency Control in Autonomous Microgrids , 2018, IEEE Transactions on Smart Grid.

[10]  Xin Wang,et al.  Distributed Subgradient-Based Coordination of Multiple Renewable Generators in a Microgrid , 2014, IEEE Transactions on Power Systems.

[11]  Michael Chertkov,et al.  Optimal Distributed Control of Reactive Power Via the Alternating Direction Method of Multipliers , 2013, IEEE Transactions on Energy Conversion.

[12]  Kenji Hirata,et al.  Decentralized Voltage Regulation for PV Generation Plants Using Real-Time Pricing Strategy , 2017, IEEE Transactions on Industrial Electronics.

[13]  Steven H. Low,et al.  Optimization flow control—I: basic algorithm and convergence , 1999, TNET.

[14]  Aryan Mokhtari,et al.  Network Newton-Part II: Convergence Rate and Implementation , 2015, 1504.06020.

[15]  Aryan Mokhtari,et al.  An approximate Newton method for distributed optimization , 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[16]  Wei Zhang,et al.  Distributed Multiple Agent System Based Online Optimal Reactive Power Control for Smart Grids , 2014, IEEE Transactions on Smart Grid.

[17]  José Pablo Chaves-Ávila,et al.  The Green Impact: How Renewable Sources Are Changing EU Electricity Prices , 2015, IEEE Power and Energy Magazine.

[18]  N.D. Hatziargyriou,et al.  Centralized Control for Optimizing Microgrids Operation , 2008, IEEE Transactions on Energy Conversion.

[19]  M. E. Baran,et al.  Optimal capacitor placement on radial distribution systems , 1989 .

[20]  Georgios B. Giannakis,et al.  Distributed Optimal Power Flow for Smart Microgrids , 2012, IEEE Transactions on Smart Grid.

[21]  Steven H. Low,et al.  Optimal inverter VAR control in distribution systems with high PV penetration , 2011, 2012 IEEE Power and Energy Society General Meeting.

[22]  Albert Y. S. Lam,et al.  An Optimal and Distributed Method for Voltage Regulation in Power Distribution Systems , 2012, IEEE Transactions on Power Systems.

[23]  Janusz Bialek,et al.  Generation curtailment to manage voltage constraints in distribution networks , 2007 .

[24]  Boming Zhang,et al.  A fully distributed active power control method with minimum generation cost in grid-connected microgrids , 2015, 2015 IEEE Power & Energy Society General Meeting.

[25]  Richard M. Murray,et al.  Consensus problems in networks of agents with switching topology and time-delays , 2004, IEEE Transactions on Automatic Control.

[26]  Gustavo Valverde,et al.  Model Predictive Control of Voltages in Active Distribution Networks , 2013, IEEE Transactions on Smart Grid.

[27]  Badrul H. Chowdhury,et al.  Distributed dynamic grid support using smart PV inverters during unbalanced grid faults , 2019, IET Renewable Power Generation.

[28]  Qiuye Sun,et al.  Power flow calculation based on local controller impedance features for the AC microgrid with distributed generations , 2019 .

[29]  Lijun Chen,et al.  Equilibrium and dynamics of local voltage control in distribution systems , 2013, 52nd IEEE Conference on Decision and Control.

[30]  D. Kirschen,et al.  A Survey of Frequency and Voltage Control Ancillary Services—Part I: Technical Features , 2007, IEEE Transactions on Power Systems.

[31]  Thomas Ackermann,et al.  Integrating Variable Renewables in Europe : Current Status and Recent Extreme Events , 2015, IEEE Power and Energy Magazine.

[32]  Christoforos N. Hadjicostis,et al.  A Two-Stage Distributed Architecture for Voltage Control in Power Distribution Systems , 2013, IEEE Transactions on Power Systems.

[33]  Hen-Geul Yeh,et al.  Adaptive VAR Control for Distribution Circuits With Photovoltaic Generators , 2012, IEEE Transactions on Power Systems.

[34]  Frede Blaabjerg,et al.  Distributed Power-Generation Systems and Protection , 2017, Proceedings of the IEEE.

[35]  Allen J. Wood,et al.  Power Generation, Operation, and Control , 1984 .

[36]  Shin-Yeu Lin,et al.  Distributed Optimal Power Flow With Discrete Control Variables of Large Distributed Power Systems , 2008, IEEE Transactions on Power Systems.

[37]  Trudie Wang,et al.  Dynamic Control and Optimization of Distributed Energy Resources in a Microgrid , 2014, IEEE Transactions on Smart Grid.

[38]  Aryan Mokhtari,et al.  Network Newton-Part I: Algorithm and Convergence , 2015, 1504.06017.

[39]  Boming Zhang,et al.  A Fully Distributed Power Dispatch Method for Fast Frequency Recovery and Minimal Generation Cost in Autonomous Microgrids , 2016, IEEE Transactions on Smart Grid.

[40]  Dionysios Aliprantis,et al.  Distributed Volt/VAr Control by PV Inverters , 2013, IEEE Transactions on Power Systems.