Abstract
With the huge rise of energy demand, the power system in the current era is moving to a new standard with increased access to renewable energy sources (RESs) integrated with distribution generation (DG) network. The RESs necessitate interfaces for controlling the power generation. The multilevel inverter (MLI) can be exploited for RESs in two diverse modes, namely, the power generation mode (stand-alone mode), and compensator mode (statcom). Few works have been carried out in optimization of controller gains with the load variations of the single type such as reactive load variation in different cases. Nevertheless, this load type may be unbalanced hence, to overcome such issues. So, a sophisticated optimization algorithm is important. This paper aims to introduce a control design via an optimization assisted PI controller for a 7-level inverter. In the present technique, the gains of the PI controller are adjusted dynamically by the adopted hybrid scheme, grey optimizer with dragon levy update (GD-LU), based on the operating conditions of the system. Here, the gains are adjusted such that the error between the reference signal and fault signal should be minimal. Thus, better dynamic performance could be attained by the present optimized PI controller. The proposed algorithm is the combined version of grey wolf optimization (GWO) and dragonfly algorithm (DA). Finally, the performance of the proposed work is compared and validated over other state-of-the-art models concerning error measures.
摘要
随着能源需求的巨大增长, 当前的电力系统急需适应新的要求, 能将再生能源接入电网从而整 合利用可再生能源。多级变频器(MLI)可在两种不同的模式下实现这个功能, 即发电模式(独立模式) 和补偿器模式(STATCOM)。目前, 对于不同工况的单一类型负荷的变化, 如无功负荷的变化, 优化控 制器增益的研究很少。这类负荷的稳定性不好的问题急需解决。因此, 一个适用的优化算法尤显重要。 本文介绍了一种基于优化辅助PI 控制器的七级变频器控制设计算法。在所提出的算法中, PI 控制器 的增益是根据系统的运行条件, 通过采用混合方案, 即龙形更新的灰色优化器(GD-LU), 对增益进行 动态调整, 使参考信号与故障信号之间的误差最小, 以便所提出的优化PI 控制器可以获得更好的动 态性能。提出的算法是灰狼优化(GWO)和蜻蜓算法(DA)的组合版本。最后, 对所提出算法的性能与其 他先进的模型就误差方面进行了比较和验证。
Similar content being viewed by others
Abbreviations
- RES:
-
Renewable energy sources
- GD-LU:
-
Grey optimizer with dragon levy update
- DG:
-
Distribution generation
- VSC:
-
Voltage source converter
- GWO:
-
Grey wolf optimization
- DA:
-
Dragon fly algorithm
- DG:
-
Distributed generation
- PQ:
-
Power-quality
- PV:
-
Photo voltaic
- APF:
-
Active power filters
- KEPCO:
-
Korea electric power corporation
- AFPI:
-
Adaptive fuzzy PI
- GIC:
-
Grid-interactive converter
- FLC:
-
Fuzzy logic control
- NGS:
-
National grid system
- APS:
-
Autonomous power system
- rSOCs:
-
Reversible solid oxide cells
- MPPT:
-
Maximum power point tracking
- WECS:
-
Wind energy conversion system
- MPC:
-
Model predictive control
- MLIP:
-
Mixed linear integer programming
- HRES:
-
Hybrid RES
- BSS:
-
Battery storage system
- SC:
-
Super-capacitor
- GIS:
-
Gases insulation substation
- PWM:
-
Pulse width modulation
- PCU:
-
Power conditioning unit
- EPLL:
-
Enhanced phase-locked loop
- LPF:
-
Low pass filter
References
DIB M, RAMZI M, NEJMI A. Voltage regulation in the medium voltage distribution grid in the presence of renewable energy sources [J]. Materials Today: Proceedings, 2019, 13: 739–745. DOI: https://doi.org/10.1016/j.matpr.2019.04.035.
WORIGHI I, MAACH A, HAFID A, HEGAZY O, van MIERLO J. Integrating renewable energy in smart grid system: Architecture, virtualization and analysis[J] Sustainable Energy, Grids and Networks, 2019, 18: 100226. DOI: https://doi.org/10.1016/j.segan.2019.100226.
SHARMA D, YADAV N K. Lion algorithm with levy update: Load frequency controlling scheme for two-area interconnected multi-source power system [J]. Transactions of the Institute of Measurement and Control, 2019, 41(14): 4084–4099. DOI: https://doi.org/10.1177/0142331219848033.
KONG Ling-cheng, ZHU Zhen-ning, XIE Jia-ping, LI Jing, CHEN Yu-ping. Multilateral agreement contract optimization of renewable energy power grid-connecting under uncertain supply and market demand [J]. Computers & Industrial Engineering, 2019, 135: 689–701. DOI: https://doi.org/10.1016/j.cie.2019.06.016.
JOHNSON S C, PAPAGEORGIOU D J, MALLAPRAGADA D S, DEETJEN T A, RHODES J D, WEBBER M E. Evaluating rotational inertia as a component of grid reliability with high penetrations of variable renewable energy [J]. Energy, 2019, 180: 258–271. DOI: https://doi.org/10.1016/j.energy.2019.04.216.
ISLAM MS. A techno-economic feasibility analysis of hybrid renewable energy supply options for a grid-connected large office building in southeastern part of France [J]. Sustainable Cities and Society, 2018, 38: 492–508. DOI: https://doi.org/10.1016/j.scs.2018.01.022.
SHARMA D, KUMAR YA DAV N, Gunjan, Anju Bala. Impact of distributed generation on voltage profile using different optimization techniques [C]//2016 International Conference on Control, Computing, Communication and Materials (ICCCCM). Allahbad, India: IEEE, 2016. DOI: https://doi.org/10.1109/ICCCCM.2016.7918261.
KUMAR YA DAV N, KUMAR M, SHARMA D, BALA A, BHARGAVA G. Implementation of particle swarm optimization in bidding strategy under deregulated environment [C]//2016 International Conference on Control, Computing, Communication and Materials (ICCCCM). Allahbad, India: IEEE, 2016. https://doi.org/10.1109/ICCCCM.2016.7918259.
IEEE application guide for IEEE STD 1547(TM), IEEE standard for interconnecting distributed resources with electric power systems [M]//IEEE STD 1547.2-2008.
HUH J H. Smart grid test bed using OPNET and power line communication[M]. IGI Global, 2018.
KO J S, HUH J H, KIM J C. Improvement of temperature control performance of thermoelectric dehumidifier used industry 4.0 by the SF-PI controller [J]. Processes, 2019, 7(2): 98.
POURESMAEIL E, MIGUEL-ESPINAR C, MASSOTCAMPOS M, MONTESINOS-MIRACLE D, GOMIS-BELLMUNT O. A control technique for integration of DG units to the electrical networks [J]. IEEE Transactions on Industrial Electronics, 2013, 60(7): 2881–2893. DOI: https://doi.org/10.1109/TIE.2012.2209616.
WU Xian-qing, HE Xiong-xiong, SUN Ning, FANG Yong-chun. A novel anti-swing control method for 3-D overhead cranes [C]//2014 American Control Conference. Portland, OR, USA: IEEE, 2014: 2821–2826.
WU Xian-qing, HE Xiong-xiong. Enhanced damping-based anti-swing control method for underactuated overhead cranes [J]. IET Control Theory & Applications, 2015, 9(12): 1893–1900. DOI: https://doi.org/10.1049/iet-cta.2014.1353.
KIM J C, HUH J H, KO J S. Improvement of MPPT control performance using fuzzy control and VGPI in the PV system for micro grid [J]. Sustainability, 2019, 11(21): 5891. DOI: https://doi.org/10.3390/su11215891.
LEE H H, CHO S K, CHO J S. A new anti-swing control of overhead cranes [J]. IFAC Proceedings Volumes, 1997, 30(13): 115–120. DOI: https://doi.org/10.1016/S1474-6670(17)44380-1.
MA Wei-wu, FAN Jia-qian, FANG Song, LIU Gang. Techno-economic potential evaluation of small-scale grid-connected renewable power systems in China [J]. Energy Conversion and Management, 2019, 196: 430–442. DOI: https://doi.org/10.1016/j.enconman.2019.06.013.
VITERI J P, HENAO F, CHERNI J, DYNER I. Optimizing the insertion of renewable energy in the off-grid regions of Colombia [J]. Journal of Cleaner Production, 2019, 235: 535–548. DOI: https://doi.org/10.1016/j.jclepro.2019.06.327.
ABDELSHAFY A M, HASSAN H, JURASZ J. Optimal design of a grid-connected desalination plant powered by renewable energy resources using a hybrid PSO-GWO approach [J]. Energy Conversion and Management, 2018, 173: 331–347. DOI: https://doi.org/10.1016/j.enconman.2018.07.083.
KIM S, LEE H, KIM H, JANG D H, KIM H J, HUR J, CHO Y S, HUR K. Improvement in policy and proactive interconnection procedure for renewable energy expansion in South Korea [J]. Renewable and Sustainable Energy Reviews, 2018, 98: 150–162. DOI: https://doi.org/10.1016/j.rser.2018.09.013.
VIGNEYSH T. Grid interconnection of renewable energy sources using multifunctional grid-interactive converters: A fuzzy logic based approach [J]. Electric Power Systems Research, 2017, 151: 359–368. DOI: https://doi.org/10.1016/j.epsr.2017.06.010.
ZAFEIRATOU E, SPATARU C. Investigation of high renewable energy penetration in the island of Syros following the interconnection with the national grid system [J]. Energy Procedia, 2015, 83: 237–247. DOI: https://doi.org/10.1016/j.egypro.2015.12.178.
BALDINELLI A, BARELLI L, BIDINI G. Progress in renewable power exploitation: reversible solid oxide cells-flywheel hybrid storage systems to enhance flexibility in micro-grids management [J]. Journal of Energy Storage, 2019, 23: 202–219. DOI: https://doi.org/10.1016/j.est.2019.03.018.
PRABAHARAN N, CAMPANA P E, ANN JE RIN A R, PALANISAMY K. A new approach for grid integration of solar photovoltaic system with maximum power point tracking using multi-output converter [J]. Energy Procedia, 2019, 159: 521–526. DOI: https://doi.org/10.1016/j.egypro.2018.12.005.
HUANG Wei, LU Miao, ZHANG Li. Survey on microgrid control strategies [J]. Energy Procedia, 2011, 12: 206–212. DOI: https://doi.org/10.1016/j.egypro.2011.10.029.
HUH J H, SEO K. Hybrid AMI design for smart grid using the game theory model [J]. Advanced Science and Technology Letters, 2015, 108: 86–92. DOI: https://doi.org/10.14257/astl.2015.108.19.
KUSAKANA K. Optimal energy management of a residential grid-interactive wind energy conversion system with battery storage [J]. Energy Procedia, 2019, 158: 6195–6200. DOI: https://doi.org/10.1016/j.egypro.2019.01.488.
BIFARETTI S, CORDINER S, MULONE V, ROCCO V, ROSSI J L, SPAGNOLO F. Grid-connected microgrids to support renewable energy sources penetration [J]. Energy Procedia, 2017, 105: 2910–2915.
SEDAGHATI R, SHAKARAMI M R. A novel control strategy and power management of hybrid PV/FC/SC/battery renewable power system-based grid-connected microgrid [J]. Sustainable Cities and Society, 2019, 44: 830–843. DOI: https://doi.org/10.1016/j.scs.2018.11.014.
GHARIBI M, ASKARZADEH A. Size and power exchange optimization of a grid-connected diesel generator-photovoltaic-fuel cell hybrid energy system considering reliability, cost and renewability [J]. International Journal of Hydrogen Energy, 2019, 44(47): 25428–25441. DOI: https://doi.org/10.1016/j.ijhydene.2019.08.007.
LUNARDI A S, SGUAREZI FILHO A J, CAPOVILLA C E, CASELLA I R S, DE MEDEIROS A A M. A wireless coded predictive direct power control for renewable energy sources in smart grid environment [J]. International Journal of Electrical Power & Energy Systems, 2019, 112: 319–325. DOI: https://doi.org/10.1016/j.ijepes.2019.05.004.
NG E J, EL-SHATSHAT R A. Multi-microgrid control systems (MMCS) [C]//IEEE PES General Meeting. Providence, RI, USA: IEEE, 2010: 1–6.
SWAMY S M, RAJAKUMAR B R, VALARMATHI I R. Design of hybrid wind and photovoltaic power system using opposition-based genetic algorithm with Cauchy mutation [C]//IET Chennai Fourth International Conference on Sustainable Energy and Intelligent Systems (SEISCON 2013). Chennai, India: Institution of Engineering and Technology, 2013. DOI: https://doi.org/10.1049/ic.2013.0361.
PARISIO A, RIKOS E, TZAMALIS G, GLIELMO L. Use of model predictive control for experimental microgrid optimization [J]. Applied Energy, 2014, 115: 37–46.
GOEL S, SHARMA R. Performance evaluation of stand alone, grid connected and hybrid renewable energy systems for rural application: A comparative review [J]. Renewable and Sustainable Energy Reviews, 2017, 78: 1378–1389. DOI: https://doi.org/10.1016/j.rser.2017.05.200.
MASAKI M S, ZHANG Li-jun, XIA Xiao-hua. A hierarchical predictive control for supercapacitor-retrofitted grid- connected hybrid renewable systems [J]. Applied Energy, 2019, 242: 393–402. DOI: https://doi.org/10.1016/j.apenergy.2019.03.049.
AN P Q, SCULLY T, BREEN M., MURPHY M D. Determination of optimal battery utilization to minimize operating costs for a grid-connected building with renewable energy sources [J]. Energy Conversion and Management, 2018, 174: 157–174. DOI: https://doi.org/10.1016/j.enconman.2018.07.081.
JAALAM N, RAHIM N A, BAKAR A H A, TAN C, HAIDAR A M A. A comprehensive review of synchronization methods for grid-connected converters of renewable energy source [J]. Renewable and Sustainable Energy Reviews, 2016, 59: 1471–1481. DOI: https://doi.org/10.1016/j.rser.2016.01.066.
ALSAYEGH O, ALHAJRAF S, ALBUSAIRI H. Grid-connected renewable energy source systems: Challenges and proposed management schemes [J]. Energy Conversion and Management, 2010, 51(8): 1690–1693. DOI: https://doi.org/10.1016/j.enconman.2009.11.042.
ARYA Y. A novel CFFOPI-FOPID controller for AGC performance enhancement of single and multi-area electric power systems [J]. ISA Transactions, 2020, 100: 126–135. DOI: https://doi.org/10.1016/j.isatra.2019.11.025.
ARYA Y. Impact of hydrogen aqua electrolyzer-fuel cell units on automatic generation control of power systems with a new optimal fuzzy TIDF-II controller [J]. Renewable Energy, 2019, 139: 468–482. DOI: https://doi.org/10.1016/j.renene.2019.02.038.
ARYA Y. Effect of energy storage systems on automatic generation control of interconnected traditional and restructured energy systems [J]. International Journal of Energy Research, 2019, 43(12): 6475–6493. DOI: https://doi.org/10.1002/er.4493.
ARYA Y. A new optimized fuzzy FOPI-FOPD controller for automatic generation control of electric power systems [J]. Journal of the Franklin Institute, 2019, 356(11): 5611–5629. DOI: https://doi.org/10.1016/j.jfranklin.2019.02.034.
ARYA Y. AGC of PV-thermal and hydro-thermal power systems using CES and a new multi-stage FPIDF-(1+PI) controller [J]. Renewable Energy, 2019, 134: 796–806. DOI: https://doi.org/10.1016/j.renene.2018.11.071.
GUPTA S K, ARYA Y, SHUKLA S, CHAWLA P. Two-area AGC in interconnected system under the restructured power system using BFO controller [C]//2014 6th IEEE Power India International Conference (PIICON). Delhi, India: IEEE, 2014: 1–6. DOI:https://doi.org/10.1109/34084POWERI.2014.7117604.
DAHIYA P, MUKHIJA P, SAXENA A R, ARYA Y. Comparative performance investigation of optimal controller for AGC of electric power generating systems [J]. Automatika, 2016, 57(4): 902–921. DOI: https://doi.org/10.7305/automatika.2017.12.1707.
ARYA Y. Improvement in automatic generation control of two-area electric power systems via a new fuzzy aided optimal PIDN-FOI controller [J]. ISA Transactions, 2018, 80: 475–490. DOI: https://doi.org/10.1016/j.isatra.2018.07.028.
ARYA Y, KUMAR N, GUPTA S K, CHAWLA P. Fuzzy logic based frequency control of four-area electrical power system considering non-linearities and boiler dynamics [J]. International Journal of Electrical and Power Engineering, 2011, 5(5): 203–213. DOI: https://doi.org/10.1016/j.isatra.2018.07.028.
SINGH M, KHADKIKAR V, CHANDRA A, VARMA R K. Grid interconnection of renewable energy sources at the distribution level with power-quality improvement features [J]. IEEE Transactions on Power Delivery, 2011, 26(1): 307–315. DOI: https://doi.org/10.1109/TPWRD.2010.2081384.
HAYT W H. Engineering circuit analysis [M]. Tata Mcgraw Hill Education Pvt. Ltd, 2010.
JAFARI M, BAYATI CHALESHTARI M H. Using dragonfly algorithm for optimization of orthotropic infinite plates with a quasi-triangular cut-out [J]. European Journal of Mechanics A, 2017, 66: 1–14. DOI: https://doi.org/10.1016/j.euromechsol.2017.06.003.
MIRJALILI S, MIRJALILI S M, LEWIS A. Grey wolf optimizer [J]. Advances in Engineering Software, 2014, 69: 46–61. DOI: https://doi.org/10.1016/j.advengsoft.2013.12.007.
Author information
Authors and Affiliations
Contributions
GAYATHRI DEVI K S conceptualized and designed the study, reviewed identified articles to determine if they met defined study inclusion and exclusion criteria, critically reviewed the manuscript, and approved the final manuscript as submitted. SUJATHA THERESE P reviewed identified articles to determine if they met defined study inclusion and exclusion criteria, critically reviewed the manuscript, and approved the final manuscript as submitted. All authors approved the final manuscript as submitted and agree to be accountable for all aspects of the work.
Corresponding author
Additional information
Conflict of interest
Authors state no conflict of interest.
Rights and permissions
About this article
Cite this article
Gayathri Devi, K.S., Sujatha Therese, P. Optimized PI controller for 7-level inverter to aid grid interactive RES controller. J. Cent. South Univ. 28, 153–167 (2021). https://doi.org/10.1007/s11771-021-4593-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11771-021-4593-1
Key words
- PI controller
- renewable energy source (RES)
- distribution generation
- utility grid
- GD-LU model
- voltage analysis