Enhancing Energy Efficiency for Optimal Multiple Photovoltaic DG and DSTATCOM Integration for Techno-Economic and Environmental Analysis: A Case Study of Adrar City Distribution System

Authors

  • Adel Lasmari Department of Electrotechnic, Mentouri University of Constantine 1, Constantine, Algeria
  • Mohamed Zellagui Department of Electrical Engineering, Faculty of Technology, University of Batna 2, Fesdis, Algeria
  • Rachid Chenni Department of Electrical Engineering, University of Québec, Montréal, Canada

DOI:

https://doi.org/10.57056/ajet.v6i1.66

Keywords:

PV Distributed Generated, DSTATCOM, Efficient Energy, Optimal Integration, Weight Inertia PSO Algorithm, Multi-Objective Function, Power Distribution System

Abstract

The insertion of renewable energy resources in existing distribution systems has effectively improved its performance and operation. This paper presents the efficiency of the optimal integration of multiple Photovoltaic DG (PV-DG), and Distribution Static Compensator (DSTATCOM) simultaneously in a practical Power Distribution System (PDS), through the maximization of the Multi-objective function (MOF) based on the Real Power Loss Level (RPLL), the Short Circuit Level (SCL), the Voltage Deviation Level (VDL), the Net Saving Level (NSL), and Environmental Pollution Reduction Level (EPRL) by various Inertia Weight Particle Swarm Optimization (IW-PSO) algorithms. The proposed IW-PSO algorithms applied in the practical Adrar city 205-bus distribution system in Algeria. The obtained results prove the efficiency of the algorithms in terms of achieving the minimum power loss and improvement of the voltage profiles, the EIW-PSO exhibits the best results of MOF compared to other algorithms.

References

Okoye CO, Solyal O. Optimal sizing of stand-alone photovoltaic systems in residential Buildings, Energy. 2017, 126: 573–584. https://doi.org/10.1016/j.energy.2017.03.032

Ehsan A, Yang Q. Optimal integration and planning of renewable distributed generation in the power distribution networks: A review of analytical techniques, Applied Energy. 2018, 210: 44–59. https://doi.org/10.1016/j.apenergy.2017.10.106

Bianchi M, Branchini L, Ferrari C, Melino F. Optimal sizing of grid-independent hybrid photovoltaic–battery power systems for household sector, Applied Energy. 2014, 136: 805–816. https://doi.org/10.1016/j.apenergy.2014.07.058

Khatib T, Mohamed A, Sopian K, Mahmoud M. Optimal sizing of hybrid PV/wind systems for Malaysia using loss of load probability, Energy Sources, Part A: Recovery, Utilization, and Environmental Effects. 2015, 37(7): 687–695. https://doi.org/10.1080/15567036.2011.592920

Lian J, Zhang Y, Ma C, Yang Y, Chaima E. A review on recent sizing methodologies of hybrid renewable energy systems, Energy Conversion and Management. 2019, 199: 112027. https://doi.org/10.1016/j.enconman.2019.112027

Bagherian MA, Mehranzamir K, A comprehensive review on renewable energy integration for combined heat and power production, Energy Conversion and Management. 2020, 224: 113454. https://doi.org/10.1016/j.enconman.2020.113454

Latreche Y, Bouchekara HREH, Kerrour F, Naidu K, Mokhlis H, Javaid MS. Comprehensive review on the optimal integration of distributed generation in distribution systems, Journal of Renewable and Sustainable Energy. 2018, 10: 1-33. https://doi.org/10.1063/1.5020190

Settoul S, Zellagui M, Abdelaziz AY, Chenni R. Optimal integration of renewable distributed generation in practical distribution grids based on moth-flame optimization algorithm, International Conference on Advanced Electrical Engineering (ICAEE), Algiers, Algeria, 19-21 November 2019. https://doi.org/10.1109/ICAEE47123.2019.9014662

Settoul S, Zellagui M, Chenni R. A new optimization algorithm for optimal wind turbine location problem in constantine city electric distribution network based active power loss reduction, Journal of Optimization in Industrial Engineering.1 202 14(2): 13-22, 2021. https://doi.org/10.22094/JOIE.2020.1892184.1725

Hassan HA, Zellagui M. MVO algorithm for optimal simultaneous integration of DG and DSTATCOM in standard radial distribution systems based on technical-economic indices, 21st International Middle East Power Systems Conference, Tanta, Egypt, 17-19 December, 2019. https://doi.org/10.1109/MEPCON47431.2019.9007995

Lasmari A, Zellagui M, Hassan HA, Settoul S, Abdelaziz AY, Chenni R. optimal energy-efficient integration of photovoltaic DG in radial distribution systems for various load models, 11th International Renewable Energy Congress (IREC), Hammamet - Tunisia, 29-31 October 2020. https://doi.org/10.1109/IREC48820.2020.9310429

Zellagui M, Settoul S, Lasmari A, El-Bayeh CZ, Chenni R, Hassan HA. Optimal Allocation of Renewable Energy Source Integrated-Smart Distribution Systems Based on Technical-Economic Analysis Considering Load Demand and DG Uncertainties, Lecture Notes in Networks and Systems. 2021, 174: 391-404. https://doi.org/10.1007/978-3-030-63846-7_37

Lasmari A, Zellagui M, Chenni R, Semaoui S, El-Bayeh CZ, Hassan HA. Optimal energy management system for distribution systems using simultaneous integration of PV-based DG and DSTATCOM units, Energetika. 2020, 66(1): 1-14. https://doi.org/10.6001/energetika.v66i1.4294

Zellagui M. Optimal placement and sizing of PVDGs in radial distribution system using hybrid PSO-GSA, Journal of Advanced Research in Science and Technology. 2018, 5(1): 627-639.

Lasmari A, Settoul S, Zellagui M, Chenni R. Optimal hourly scheduling of PV sources in EDS considering the power variability of load demand and DG using MOGWO algorithm, 6th International Conference on Electric Power and Energy Conversion Systems, Istanbul, Turkey, 5-7 October, 2020. https://doi.org/10.1109/EPECS48981.2020.9304970

Bebnabid R, Zellagui M, Boudour M, Chaghi A. Considering the series compensation in optimal coordination of directional overcurrent protections using PSO technique, IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (AEECT), Amman, Jordan, 3-5 December 2013. https://doi.org/10.1109/AEECT.2013.6716460

Hassan HA, Zellagui M. Optimal coordination of directional overcurrent relays using BFOA-PSO Algorithm, Electrotehnica, Electronica, Automatica. 2015, 63(2): 116-125.

Kennedy J, Eberhart R. Particle swarm optimization, IEEE International Conference on Neural Networks, Perth, Australia, 27 November - 1 December 1995. https://doi.org/10.1109/ICNN.1995.488968

Nickabadi A, Ebadzadeh MM, Safabakhsh R. A novel particle swarm optimization algorithm with adaptive inertia weight, Applied Soft Computing. 2011, 11: 3658–3670, 2011. https://doi.org/10.1016/j.asoc.2011.01.037

Zhu X, Wang H. A new inertia weight control strategy for particle swarm optimization, In: AIP Conference Proceedings, AIP Publishing LLC, 1955(1), 2018. https://doi.org/10.1063/1.5033759

Feng Y, Teng G-F, Wang AX, Yao Y-M. Chaotic inertia weight in particle swarm optimization, In: Second International Conference on Innovative Computing, Information and Control, Kumamoto, Japan, 5-7 September, 2007. https://doi.org/10.1109/ICICIC.2007.209

Fan SKS, Chiu YY. A decreasing inertia weight particle swarm optimizer, Engineering Optimization. 2007, 39: 203–228. https://doi.org/10.1080/03052150601047362

Ting TO, Shi Y, Cheng S, Lee S. Exponential inertia weight for particle swarm optimization, In: Advances in Swarm Intelligence. Berlin, Heidelberg: Springer, 2012. https://doi.org/10.1007/978-3-642-30976-2_10

Yang C, Gao W, Liu N, Song C. Low-discrepancy sequence initialized particle swarm optimization algorithm with high-order nonlinear time-varying inertia weight, Applied Soft Computing. 2015, 29: 386–394. https://doi.org/10.1016/j.asoc.2015.01.004

Chatterjee A, Siarry P. Nonlinear inertia weight variation for dynamic adaptation in particle swarm optimization, Computers & Operations Research. 2006, 33: 859–871. https://doi.org/10.1016/j.cor.2004.08.012

Kentzoglanakis K, Poole M. Particle swarm optimization with an oscillating inertia weight, In: Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation, 1749-1750, 2009. https://doi.org/10.1145/1569901.1570140

Eberhart RC, Shi Y. Tracking and optimizing dynamic systems with particle swarms, In: Proceedings of the 2001 Congress on Evolutionary Computation Presented at the 2001 Congress on Evolutionary Computation. Seoul, South Korea, 27-30 May, 2001. https://doi.org/10.1109/CEC.2001.934376

Lasmari A, Zellagui M, Gupta AA, El-sehiemy RA, Chenni R. Multi-objective salp swarm algorithm for performance enhancement of electrical distribution system including DG and DSTATCOM simultaneously. In: the 4th International Conference on Artificial Intelligence in Renewable Energetic Systems (IC-AIRES). Tipasa, Algeria: 22-24 November, 2020.

Zellagui M, Lasmari A, Settoul S, El-sehiemy RA, El-Bayeh CZ, Chenni R. Simultaneous allocation of photovoltaic DG and DSTATCOM for techno-economic and environmental benefits in electrical distribution systems at different loading conditions using novel hybrid optimization algorithms, 2021. e12992. https://doi.org/10.1002/2050-7038.12992

PV Distributed Generated;  DSTATCOM; Efficient Energy; Optimal Integration; Weight Inertia PSO Algorithm; Multi-Objective Function; Power Distribution System.

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Published

2022-06-28

How to Cite

Lasmari, A., Zellagui, M., & Chenni, R. (2022). Enhancing Energy Efficiency for Optimal Multiple Photovoltaic DG and DSTATCOM Integration for Techno-Economic and Environmental Analysis: A Case Study of Adrar City Distribution System. Algerian Journal of Engineering and Technology, 6(1), 1–8. https://doi.org/10.57056/ajet.v6i1.66