Effect of Voltage Dependent Load Model on Placement and Sizing of Distributed Generator in Large Scale Distribution System

  • Gopisetti Manikanta Department of Engineering Electrical & Electronics, ASET, Amity University, Uttar Pradesh, Noida, India.
  • Ashish Mani Department of Engineering Electrical & Electronics, ASET, Amity University, Uttar Pradesh, Noida, India.
  • Hemender Pal Singh Department of Engineering Electrical & Electronics, ASET, Amity University, Uttar Pradesh, Noida, India.
  • Devendra Kumar Chaturvedi Department of Engineering Electrical, F.O.E, Dayalbagh Educational Institute (Deemed University), Dayalbagh, Agra, India.
Keywords: AQIEA, Distributed Generator, Power Loss, Industrial Load, Commercial Load, Residential Load, Voltage Dependent Load

Abstract

Distribution system supplies power to variety of load depending upon the consumer’s demand, which is increasing day by day and lead to high power losses and poor voltage regulation. The increase in demand can be met by integrating Distributed Generators (DG) into the distribution system. Optimal location and capacity of DG plays an important role in distribution network to minimize the power losses. Some researchers have studied this important optimization problem with constant power load which is independent of voltage. However, majority of consumers at load center uses voltage dependent load models, which are primarily dependent on magnitude of supply voltage. In practical distribution network, the assumption of constant power load can significantly affect the location and size of DG, which in turn can lead to higher power losses and poor voltage regulation. In this study, an investigation has been performed to find the increase in power loss due to the use of inappropriate load models, while solving the optimization problem. Furthermore, an attempt has been made in this study to reduce power losses occurring in large test bus systems with loads being dependent on voltage rather than the constant power load. Different test cases are created to analyse the power losses with appropriate load model and in-appropriate load model (constant power load model). The load at distribution network is not mainly dependent on any single type of load model, it is a combination of all load models.  In this study, a class of mix load viz., combination of residential, industrial, constant power, and commercial load, is also considered. In order to solve this critical combinatorial optimization problem with voltage dependent load model, which requires an extensive search, Adaptive Quantum inspired Evolutionary Algorithm (AQiEA) is used. The proposed algorithm uses entanglement and superposition principles, which does not require an operator to avoid premature convergence and tuning parameters for improving the convergence rate. A Quantum Rotation inspired Adaptive Crossover operator has been used as a variation operator for a better convergence. The effectiveness of AQiEA is demonstrated and computer simulations are carried out on two standard benchmark large test bus systems viz., 85 bus system and 118 bus system. In addition to AQiEA, four other algorithms (Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Grey Wolf Optimization (GWO), and Ecogeography-based Optimization (EBO) with Classification based on Multiple Association Rules (CMAR)) have also been employed for comparison. Tabulated results show that the location and size of DGs determined using in-appropriate load model (constant power load model) has significantly high power losses when applied in distribution system with different load model (other voltage dependent load models) as compared with the location and size of DGs determined using the appropriate load model. Experimental results indicate that AQiEA has a better performance compared to other algorithms which are available in the literature.

References

[1] M. J. Kasaei and J. Nikoukar, “DG Allocation with Consideration of Costs and Losses in Distribution Networks Using Ant Colony Algorithm”, Majlesi Journal of Electrical Engineering, Vol. 10, No. 1, Jul. 2015.
[2] D. Esmaeili, K. Zare, B. Mohammadi-Ivatloo, and S. Nojavan, “Simultaneous Optimal Network Reconfiguration, DG and Fixed/Switched Capacitor Banks Placement in Distribution Systems using Dedicated Genetic Algorithm”, Majlesi Journal of Electrical Engineering, Vol. 9, No. 4, pp. 31-41, Dec. 2015.
[3] Yari, A.R., Shakarami, M.R., Namdari, F. et al. “A New Practical Approach to Optimal Switch Placement in the Presence of Distributed Generation”. Iran J Sci Technol Trans Electr Eng 44, 989–1002 (2020). https://doi.org/10.1007/s40998-019-00284-6
[4] Z. Boor and S. M. Hosseini, “Optimal Placement of DG to Improve the Reliability of Distribution Systems Considering Time Varying Loads using Genetic Algorithm”, Majlesi Journal of Electrical Engineering, Vol. 7, No. 1, Oct. 2012.
[5] “Bibliography on load models for power flow and dynamic performance simulation,” in IEEE Transactions on Power Systems, vol. 10, no. 1, pp. 523-538, Feb. 1995. https://doi: 10.1109/59.373979
[6] “Standard load models for power flow and dynamic performance simulation,” in IEEE Transactions on Power Systems, vol. 10, no. 3, pp. 1302-1313, Aug 1995. https://doi: 10.1109/59.466523
[7] C. Concordia and S. Ihara, “Load Representation in Power System Stability Studies,” in IEEE Transactions on Power Apparatus and Systems, Vol. PAS-101, No. 4, pp. 969-977, April 1982. https://doi: 10.1109/TPAS.1982.317163
[8] “Load representation for dynamic performance analysis of power systems,” in IEEE Transactions on Power Systems, vol. 8, no. 2, pp. 472-482, May 1993. https://doi: 10.1109/59.260837
[9] A. Arif, Z. Wang, J. Wang, B. Mather, H. Bashualdo and D. Zhao, "Load Modeling—A Review," in IEEE Transactions on Smart Grid, Vol. 9, No. 6, pp. 5986-5999, Nov. 2018. Doi: 10.1109/TSG.2017.2700436
[10] Sumit Banerjee, Debapriya Das, Chandan Kumar, “Voltage stability of radial distribution networks for different types of loads”, International Journal of Power & Energy Conservation, Vol. 5, No. 1, 2014.
[11] N. K. Roy, M. J. Hossain and H. R. Pota, "Effects of load modeling in power distribution system with distributed wind generation," AUPEC 2011, Brisbane, QLD, 2011, pp. 1-6.
[12] D. Sattianadan, M. Sudhakaran, S.S. Dash, K. Vijayakumar, "Power Loss Minimization by the Placement of DG in Distribution System using GA" in Lecture Notes in Computer Science (Springer), Vol. 7677, pp. 259-266, Dec 2012.
[13] G. Manikanta, A. Mani, H. P. Singh and D. K. Chaturvedi, "Minimization of power losses in distribution system using symbioitic organism search algorithm," 2017 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), Bangalore, 2017, pp. 1-6.
[14] K. Vinothkumar, M. P. Selvan and S. Srinath, "Impact of DG model and load model on placement of multiple DGs in distribution system," International conference on Industrial and Information Systems (ICIIS), pp. 508-513, 29 July-1 August 2010.
[15] D. Singh, D. Singh and K. S. Verma, "Multiobjective Optimization for DG Planning With Load Models," in IEEE Transactions on Power Systems, Vol. 24, No. 1, pp. 427-436, Feb. 2009. https://doi: 10.1109/TPWRS.2008.2009483.
[16] D. Singh, R. K. Misra and D. Singh, "Effect of Load Models in Distributed Generation Planning," in IEEE Transactions on Power Systems, Vol. 22, No. 4, pp. 2204-2212, Nov. 2007.
[17] A. M. El-Zonkoly, "Optimal placement of multi-distributed generation units including different load models using particle swarm optimisation," in IET Generation, Transmission & Distribution, Vol. 5, No. 7, pp. 760-771, July 2011.
[18] A. K. Bohre, G. Agnihotri and M. Dubey, "Optimal sizing and sitting of DG with load models using soft computing techniques in practical distribution system," in IET Generation, Transmission & Distribution, Vol. 10, No. 11, pp. 2606-2621, 8 4 2016.
[19] Chandrasekhar Yammani, Sydulu Maheswarapu, Sailaja Kumari Matam, “A Multi-objective Shuffled Bat algorithm for optimal placement and sizing of multi distributed generations with different load models”, In International Journal of Electrical Power & Energy Systems, Vol. 79, 2016, Pages 120-131, ISSN 0142-0615,
https://doi.org/10.1016/j.ijepes.2016.01.003
[20] R.P. Payasi, A.K. Singh and D. Singh “Planning of different types of distributed generation with seasonal mixed load models” International Journal of Engineering, Science and Technology, Vol. 4, No. 1, 2012, pp. 112-124.
[21] V. Swetha, “Impact of various load models in distribution system with DG using Harmony and Backtracking Search Algorithms”, International Journal of Engineering Science Invention, Volume 6 Issue 11, November 2017, PP 34-42, ISSN (Print): 2319 – 6726.
[22] Muhammad Faisal Nadeem Khan and Tahir Nadeem Malik, “Probablistic generation model for optimal allocation of PV DG in distribution system with time-varying load models”. Journal of Renewable and Sustainable Energy 9, 065503 (2017); https://doi.org/10.1063/1.5000282.
[23] Muhammad Faisal Nadeem Khan, Tahir Nadeem Malik, and Intisar Ali Sajjad, “Impact of time varying load models on PV DG planning”, Journal of Renewable and Sustainable Energy 10, 035501 (2018); Doi: 10.1063/1.5028170
[24] H. Hizarci and B. E. Turkay, “Impact of Distributed Generation on Radial Distribution Network with Various Load Models”, 52nd International Universities Power Engineering Conference (UPEC), Greece, 2017.
[25] H. S. E. Mansour, A. A. Abdelsalam and A. A. Sallam, "Optimal distributed energy resources allocation using ant-lion optimizer for power losses reduction," 2017 IEEE International Conference on Smart Energy Grid Engineering (SEGE), Oshawa, ON, 2017, pp. 346-352.
[26] Yahyazadeh, M., Rezaeeye, H. “Optimal Placement and Sizing of Distributed Generation Using Wale Optimization Algorithm Considering Voltage Stability and Voltage Profile Improvement, Power Loss and Investment Cost Reducing”. Iran J Sci Technol Trans Electr Eng 44, 227–236 (2020). https://doi.org/10.1007/s40998-019-00224-4
[27] Muthukumar K., Jayalalitha S., “Integrated approach of network reconfiguration with distributed generation and shunt capacitors placement for power loss minimization in radial distribution networks”, Applied Soft Computing, Vol. 52, pp. 1262-1284, 2017.
[28] Tri Phuoc Nguyen, Dieu Ngoc Vo, “A novel stochastic fractal search algorithm for optimal allocation of distributed generators in radial distribution systems”, Applied Soft Computing, Vol. 70, Pages 773-796, 2018.
[29] M. Mohsen, A. Youssef, M. Ebeed and S. Kamel, "Optimal planning of renewable distributed generation in distribution systems using grey wolf optimizer GWO," 2017 Nineteenth International Middle East Power Systems Conference (MEPCON), Cairo, 2017, pp. 915-921.
[30] S. Sultana and P. K. Roy, “Oppositional gravitational search algorithm for optimal location of distributed generator,” Int. J. Power Energy Convers., Vol. 6, No. 4, pp. 281–325, 2015.
[31] Hlal, M.I., et al. “NSGA-II and MOPSO based optimization for sizing of hybrid PV/wind/battery energy storage system”. Int. J. Power Electron. Drive Syst. 1, pp. 463–478, 2016.
[32] A. Kumar, R. K. Misra and D. Singh, "Improving the local search capability of Effective Butterfly Optimizer using Covariance Matrix Adapted Retreat Phase," 2017 IEEE Congress on Evolutionary Computation (CEC), San Sebastian, 2017, pp. 1835-1842.
[33] S. H. A. Kaboli, J. Selvaraj and N. A. Rahim, "Rain-fall optimization algorithm: a population based algorithm for solving constrained optimization problems", J. Comput. Sci..
[34] Kaboli SHA, Alqallaf AK. “Solving non-convex economic load dispatch problem via artificial cooperative search algorithm”. Expert Syst Appl 2019; 128:14e27.
[35] S. H. A. Kaboli, J. Selvaraj, and N. A. Rahim, "Long-term electric energy consumption forecasting via artificial cooperative search algorithm," Energy, Vol. 115, Part 1, pp. 857-871, 11/15/ 2016.
[36] A. Pourdaryaei, H. Mokhlis, H. A. Illias, S. H. A. Kaboli and S. Ahmad, "Short-term electricity price forecasting via hybrid backtracking search algorithm and ANFIS approach", IEEE Access, Vol. 7, pp. 77674-77691, 2019.
[37] Aghay Kaboli, S.H.; Al Hinai, A.; Al-Badi, A.; Charabi, Y.; Al Saifi, A. “Prediction of Metallic Conductor Voltage Owing to Electromagnetic Coupling Via a Hybrid ANFIS and Backtracking Search Algorithm”. Energies 2019, 12, 3651.
[38] G. Manikanta, A. Mani, H. P. Singh and D. K. Chaturvedi, "Sitting and sizing of capacitors in distribution system using adaptive quantum-inspired evolutionary algorithm," 2016 7th India International Conference on Power Electronics (IICPE), Patiala, 2016, pp. 1-6. DOI:10.1109/IICPE.2016.8079491
[39] G. Manikanta, Ashish Mani, H.P.Singh, D.K. Chaturvedi “Distribution Network Reconfiguration using Adaptive Quantum inspired Evolutionary Algorithm” International Conference on Recent innovation in Electrical Electronics & Communication Engineering (ICRIEECE-2018) at School of Electrical Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, India.
[40] G. Manikanta, A. Mani, H. P. Singh and D. K. Chaturvedi, “Minimization of Power Losses in Distribution System with Variation in Loads Using Adaptive Quantum inspired Evolutionary Algorithm”, 4th IEEE International Conference on Computing Communication and Automation at Galgotias University, Greater Noida, India. DOI: 10.1109/CCAA.2018.8777717
[41] G. Manikanta, A. Mani, H. P. Singh and D. K. Chaturvedi, "Distribution Network Reconfiguration with Different Load Models using Adaptive Quantum inspired Evolutionary Algorithm," 2018 International Conference on Sustainable Energy, Electronics, and Computing Systems (SEEMS), Greater Noida, India, 2018, pp. 1-7. DOI: 10.1109/SEEMS.2018.8687356
[42] G. Manikanta, A. Mani, H. P. Singh and D. K. Chaturvedi, "Placing distributed generators in distribution system using adaptive quantum inspired evolutionary algorithm," 2016 Second International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN), Kolkata, 2016, pp. 157-162. DOI: 10.1109/ICRCICN.2016.7813649
[43] G. Manikanta, A. Mani, H. P. Singh and D. K. Chaturvedi, “Adaptive Quantum inspired Evolutionary Algorithm for Optimizing Power Losses by Dynamic Load Allocation on Distributed Generators”, Serbian Journal of Electrical Engineering, Vol. 16, No. 3, 325-357, 2019. DOI: https://doi.org/10.2298/SJEE1903325M
[44] G. Manikanta, Ashish Mani, H.P.Singh, D.K. Chaturvedi “Simultaneous Placement and Sizing of DG and Capacitor to Minimize the Power Losses in Radial Distribution Network” 2nd International Conference on Soft Computing: Theories and Applications at Bhundelkhand University, Jhansi. DOI: 10.1007/978-981-13-0589-4_56
[45] Sebtahmadi, S.S.; Azad, H.B.; Kaboli, S.H.A.; Islam, M.D.; Mekhilef, S. “A PSO-DQ current control scheme for performance enhancement of Z-source matrix converter to drive IM Fed by abnormal voltage”. IEEE Trans. Power Electron. 2018, 33, 1666–1681.
[46] K. H. Han, and J. H. Kim. “Quantum--Inspired Evolutionary Algorithm for a Class of Combinatorial Optimization”, IEEE Transactions on Evolutionary Computation, pp. 580-593.
[47] G. S. Sailesh Babu, D. Bhagwan Das and C. Patvardhan, "Solution of real-parameter optimization problems using novel Quantum Evolutionary Algorithm with applications in power dispatch," 2009 IEEE Congress on Evolutionary Computation, Trondheim, 2009, pp. 1920-1927.
[48] A. Mani and C. Patvardhan, “An Improved Model of Ceramic Grinding Process and its Optimization by Adaptive Quantum inspired Evolutionary Algorithm,” International Journal of Simulations: Systems Science and Technology, Vol. 11, No. 6, pp. 76-85, ISSN: 1473-804x online, 1473-8031 print, 2012.
Published
2020-12-01
How to Cite
Manikanta, G., Mani, A., Singh, H. P., & Chaturvedi, D. K. (2020). Effect of Voltage Dependent Load Model on Placement and Sizing of Distributed Generator in Large Scale Distribution System. Majlesi Journal of Electrical Engineering, 14(4), 97-121. https://doi.org/https://doi.org/10.29252/mjee.14.4.97
Section
Articles