Optimal Planning for Deployment of DG and RPC Considering Techno-Economic Aspects with Different Scenarios

International Journal of Electrical and Electronics Engineering

© 2024 by SSRG - IJEEE Journal

Volume 11 Issue 8

Year of Publication : 2024

Authors : Jaydeepsinh Sarvaiya, Mahipalsinh Chudasama

10.14445/23488379/IJEEE-V11I8P112

How to Cite?

Jaydeepsinh Sarvaiya, Mahipalsinh Chudasama, "Optimal Planning for Deployment of DG and RPC Considering Techno-Economic Aspects with Different Scenarios," SSRG International Journal of Electrical and Electronics Engineering, vol. 11,  no. 8, pp. 134-144, 2024. Crossref, https://doi.org/10.14445/23488379/IJEEE-V11I8P112

Abstract:

The growing demand for electrical energy has made Distributed Energy Resources (DER), including wind and solar photovoltaics, increasingly prominent in distribution networks. Placement of these distributed resources across the distribution network changes the line flows and modifies network performance parameters like network losses and voltage profile predominantly. Distributed Generators and Reactive Power Compensator deployment at load buses inject a partial reactive and active demand, making the distribution system bidirectional and modified line flows need more detailed analysis to improve network performance parameters. The locations and size of these distributed resources have a strong influence on network losses and power quality. The optimal placement problem of DG and RPC simultaneously has been addressed for the IEEE-33 bus network. Minimization type multi-criteria function incorporates four criteria, i.e., loss minimization, investment cost minimization, voltage stability and improvement in network bus voltage. The proposed strategy has been tested for three different scenarios where DGs have been modelled for the PQ bus and PV bus along with RPC. The proposed MOF has been minimized by the GA metaheuristic algorithm to serve all objectives having a conflict of interest. The proposed strategy helps distribution planners maximize the benefits of these distributed resources, considering future load growth.

Keywords:

Distributed generator, Genetic Algorithm, Multi-objective function, Optimization, Reactive power compensator.

References:

[1] Hany E. Farag et al., “A Generalized Power Flow Analysis for Distribution Systems with High Penetration of Distributed Generation,” Electric Power Systems Research, vol. 81, no. 7, pp. 1499-1506, 2011.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Edris Pouresmaeil et al., “A Multi-Objective Control Strategy for Grid Connection of DG (Distributed Generation) Resources,” Energy, vol. 35, no. 12, pp. 5022-5030, 2010.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Joseph Salvatore et al., “World Energy Perspective: Cost of Energy Technologies,” World Energy Council, 2013.
[Publisher Link]
[4] P. Chiradeja, and R. Ramakumar, “An Approach to Quantify the Technical Benefits of Distributed Generation,” IEEE Transactions on Energy Conversion, vol. 19, no. 4, pp. 764-773, 2004.
[CrossRef] [Google Scholar] [Publisher Link]
[5] G. Pepermans et al., “Distributed Generation: Definition, Benefits and Issues,” Energy Policy, vol. 33, no. 6, pp. 787-798, 2005.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Seyed Ali Arefifar, and Yasser Abdel-Rady I. Mohamed, “Probabilistic Optimal Reactive Power Planning in Distribution Systems with Renewable Resources in Grid-Connected and Islanded Modes,” IEEE Transactions on Industrial Electronics, vol. 61, no. 11, pp. 5830-5839, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Mohamed Imran A., and Kowsalya M., “Optimal Distributed Generation and Capacitor Placement in Power Distribution Networks for Power Loss Minimization,” 2014 International Conference on Advances in Electrical Engineering (ICAEE), pp. 1-6, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Ye Tang et al., “Impact of PV Inverter Penetration on Voltage Profile and Power Loss in Medium Voltage Distribution Systems,” IEEE 17th Workshop on Control and Modeling for Power Electronics (COMPEL), pp. 1-8, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Reinaldo Tonkoski, and Luiz A.C. Lopes, “Voltage Regulation in Radial Distribution Feeders with High Penetration of Photovoltaic,” IEEE Energy 2030 Conference, pp. 1-7, 2008.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Yuzuru Ueda et al., “Analysis Results of Output Power Loss Due to the Grid Voltage Rise in Grid-Connected Photovoltaic Power Generation Systems,” IEEE Transactions on Industrial Electronics, vol. 55, no. 7, pp. 2744-2751, 2008.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Jukka V. Paatero, and Peter D. Lund, Effects of Large-Scale Photovoltaic Power Integration on Electricity Distribution Networks, Renewable Energy, Routledge, 1st ed., 2011.
[Google Scholar] [Publisher Link]
[12] B.H. Chowdhury, and A.W. Sawab, “Evaluating the Value of Distributed Photovoltaic Generations in Radial Distribution Systems,” IEEE Transactions on Energy Conversion, vol. 11, no. 3, pp. 595-600, 1996.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Wendy Miller et al., “Power Quality and Rooftop-Photovoltaic Households: An Examination of Measured Data at Point of Customer Connection,” Sustainability, vol. 10, no. 4, pp. 1-27, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Ainah Priye Kenneth, and Komla Folly, “Voltage Rise Issue with High Penetration of Grid Connected PV,” IFAC Proceedings Volumes, vol. 47, no. 3, pp. 4959-4966, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Waseem Ahmad Nosimohomed, “Performance Analysis of Distribution Networks under High Penetration of Photovoltaics in Mauritius,” International Conference on Intelligent and Innovative Computing Applications (ICONIC), pp. 1-9, 2018. [CrossRef] [Google Scholar] [Publisher Link]
[16] Walid A. Omran, Mehrdad Kazerani, and M.M.A. Salama, “A Study of the Impacts of Power Fluctuations Generated from Large PV Systems,” IEEE PES/IAS Conference on Sustainable Alternative Energy (SAE), pp. 1-6, 2009.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Danling Cheng et al., “PV Impact Assessment for Very High Penetration Levels,” IEEE 42nd Photovoltaic Specialist Conference (PVSC), pp. 1-6, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Jeremy D. Watson, “Impact of Solar Photovoltaics on the Low Voltage Distribution Network in New Zealand,” IET Generation, Tranmission & Distribution, vol. 10, no. 1, pp. 1-9, 2016.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Jack Fitzer, and W.E. Dillon, “Impact of Residential Photovoltaic Power Systems on the Distribution Feeder,” IEEE Transactions on Energy Conversion, no. 4, pp. 39-42, 1986.
[CrossRef] [Google Scholar] [Publisher Link]
[20] N. Flatabo, R. Ognedal, and T. Carlsen, “Voltage Stability Condition in a Power Transmission System Calculated by Sensitivity Methods,” IEEE Transactions on Power Systems, vol. 5, no. 4, pp. 1286-1293, 1990.
[CrossRef] [Google Scholar] [Publisher Link]
[21] C.L. DeMarco, and T.J. Overbye, “An Energy-Based Security Measure for Assessing Vulnerability to Voltage Collapse,” IEEE Transactions on Power Systems, vol. 5, no. 2, pp. 419-427, 1990.
[CrossRef] [Google Scholar] [Publisher Link]
[22] A. A. El-Keib and X. Ma, “Application of artificial neural networks in voltage stability assessment,” IEEE Transactions on Power Systems, vol. 10, no. 4, pp. 1890-1896, 1995.
[CrossRef] [Google Scholar] [Publisher Link]
[23] F.D. Gallana, and Z.C. Zeng, “Analysis of the Load Flow Behaviour near a Jacobian Singularity,” IEEE Transactions on Power Systems, vol. 7, no. 3, pp. 1362-1369, 1992.
[CrossRef] [Google Scholar] [Publisher Link]
[24] Chih-Wen Liu, Chen-Sung Chang, and Mu-Chun Su, “Neuro-Fuzzy Networks for Voltage Security Monitoring Based on Synchronized Phasor Measurements,” IEEE Transactions on Power Systems, vol. 13, no. 2, pp. 326-332, 1998.
[CrossRef] [Google Scholar] [Publisher Link]
[25] B. Gao, G.K. Morison, and P. Kundur, “Voltage Stability Evaluation Using Modal Analysis,” IEEE Transaction on Power Systems, vol. 4, no. 7, pp. 1529-1542, 1992.
[CrossRef] [Google Scholar] [Publisher Link]
[26] M. Padma Lalitha et al., “Clonal Selection Algorithm for DG Sources Allocation for Minimum Loss in Distribution System,” International Journal of Computer Science & Emerging Technologies, vol. 1, no. 3, pp. 85-91, 2010.
[Google Scholar] [Publisher Link]