Nodal Electricity Price Based Optimal Size and Location of DGs in Electrical Distribution Networks Using ANT LION Optimization Algorithm

Authors

  • Md Irfan Ahmed Department of Electrical Engineering, National Institute of Technology Patna, India
  • Ramesh Kumar Department of Electrical Engineering, National Institute of Technology Patna, India

DOI:

https://doi.org/10.13052/dgaej2156-3306.3816

Keywords:

Distributed generation (DG), locational marginal price (LMP), distribution network (DN), electricity market (EM), antlion optimization (ALO), optimal size and location (OSL)

Abstract

Distribution system has been the weakest link in the entire power system supply chain. It is also one of the most vital parts of the power system. However, a lot of methods have been developed to improve the condition of the distribution system. The use of distributed generations (DGs) is one such method where the generated power is closer to the load center, and the DG is also providing ancillary services to the grid. The nodal electricity price for DGs location is determined based on the Locational Marginal Price (LMP). LMP implies the price to buy and sell power at each node within electrical distribution markets. In the nodal electricity market (EM), the cost of energy is determined by the location of DG to which it is provided. This paper presents a novel approach that utilizes nodal electricity price for optimal sizing and location (OSL) of DGs. A multi-objective ANTLION optimization (MOALO) has been utilized as an optimization approach to compute the OSL of DGs units. ANTLION optimization (ALO) is based on the unique hunting behaviour of antlions. Optimization has been done for social welfare maximization, loss minimization, and voltage profile improvement in distribution networks (DNs). The results of the proposed technique have been evaluated for IEEE 33 bus DNs.

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Author Biographies

Md Irfan Ahmed, Department of Electrical Engineering, National Institute of Technology Patna, India

Md Irfan Ahmed received the bachelor’s degree in electrical and electronics engineering from MITS Rayagada, Orissa in 2009, the master’s degree in power system engineering from National Institute of Technology Patna in 2014, and he is currently pursuing Ph.D. from National Institute of Technology Patna, Bihar, India. His current research interest includes electricity markets, distributed generation, and power system economics.

Ramesh Kumar, Department of Electrical Engineering, National Institute of Technology Patna, India

Ramesh Kumar received the bachelor’s degree in electrical engineering from Patna University, in 1986, the master’s degree in control system engineering from Patna University in 2001, and the philosophy of doctorate degree in Electrical Engineering from Patna University in 2009. He is currently working as Professor in the Department of Electrical Engineering, National Institute of Technology Patna. His research areas include control system, distributed generation, and power system economics.

References

IEA. Publication, “Distributed Generation in liberalized electricity market,” 2002. [Online]. Available: http://www.iea.org/dbtw-wpd/text-base/nppdf/free/2000/distributed2002.pdf.

L. Kaplow, “Market definition, market power,” Int. J. Ind. Organ., vol. 43, pp. 148–161, 2015.

P. F. Borowski, “Zonal and Nodal Models of Energy Market in European Union,” Energies, vol. 13, pp. 1–21, 2020, [Online]. Available: doi:10.3390/en13164182.

N. L. Gubbala Venkata, J. L. Askani, and V. Veeramsetty, “Optimal placement of distributed generation based on DISCO’s additional benefit using self adaptive levy flight based black widow optimization,” Int. J. Emerg. Electr. Power Syst., vol. 22, no. 4, pp. 401–410, 2021, doi: 10.1515/ijeeps-2020-0280.

S. Kansal, V. Kumar, and B. Tyagi, “Optimal placement of different type of DG sources in distribution networks,” Int. J. Electr. Power Energy Syst., vol. 53, no. 1, pp. 752–760, 2013, doi: 10.1016/j.ijepes.2013.05.040.

A. M. and S. K. Mohan Kashyap, “Optimal Placement of Distributed Generation Using Genetic Algorithm Approach,” 2017, [Online]. Available: https://doi.org/10.1007/978-981-10-8234-4_47.

E. Mohamed, A.-A. A. Mohamed, and Y. Mitani, “Genetic-Moth Swarm Algorithm for Optimal Placement and Capacity of Renewable DG Sources in Distribution Systems,” Int. J. Interact. Multimed. Artif. Intell., vol. 5, no. 7, p. 105, 2019, doi: 10.9781/ijimai.2019.10.005.

W. Haider, S. J. Ul Hassan, A. Mehdi, A. Hussain, G. O. M. Adjayeng, and C. H. Kim, “Voltage profile enhancement and loss minimization using optimal placement and sizing of distributed generation in reconfigured network,” Machines, vol. 9, no. 1, pp. 1–16, 2021, doi: 10.3390/machines9010020.

R. B. Magadum and D. B. Kulkarni, “Power loss reduction by optimal location of DG using fuzzy logic,” 2015 Int. Conf. Smart Technol. Manag. Comput. Commun. Control. Energy Mater. ICSTM 2015 – Proc., no. May, pp. 338–343, 2015, doi: 10.1109/ICSTM.2015.7225438.

N. Kaur and S. K. Jain, “Analytical approach for optimal allocation of distributed generators to minimize losses,” J. Electr. Eng. Technol., vol. 11, no. 6, pp. 1582–1589, 2016, doi: 10.5370/JEET.2016.11.6.1582.

E. A. Mohamed, A. A. A. Mohamed, and Y. Mitani, “Hybrid GMSA for optimal placement and sizing of distributed generation and shunt capacitors,” J. Eng. Sci. Technol. Rev., vol. 11, no. 1, pp. 55–65, 2018, doi: 10.25103/jestr.111.07.

M. N. Bin Kamarudin, T. J. T. Hashim, and A. Musa, “Optimal sizing and location of distributed generation for loss minimization using firefly algorithm,” Indones. J. Electr. Eng. Comput. Sci., vol. 14, no. 1, pp. 421–427, 2019, doi: 10.11591/ijeecs.v14.i1.pp421-427.

A. Selim, S. Kamel, A. S. Alghamdi, and F. Jurado, “Optimal Placement of DGs in Distribution System Using an Improved Harris Hawks Optimizer Based on Single- And Multi-Objective Approaches,” IEEE Access, vol. 8, pp. 52815–52829, 2020, doi: 10.1109/ACCESS.2020.2980245.

E. Karunarathne, J. Pasupuleti, J. Ekanayake, and D. Almeida, “Network loss reduction and voltage improvement by optimal placement and sizing of distributed generators with active and reactive power injection using fine-tuned pso,” Indones. J. Electr. Eng. Comput. Sci., vol. 21, no. 2, pp. 647–656, 2020, doi: 10.11591/ijeecs.v21.i2.pp647-656.

A. S. Assiri, A. G. Hussien, and M. Amin, “Ant lion optimization: Variants, hybrids, and applications,” IEEE Access, vol. 8, pp. 77746–77764, 2020, doi: 10.1109/ACCESS.2020.2990338.

L. Abualigah, M. Shehab, M. Alshinwan, S. Mirjalili, and M. A. Elaziz, “Ant Lion Optimizer: A Comprehensive Survey of Its Variants and Applications,” Arch. Comput. Methods Eng., vol. 28, no. 3, pp. 1397–1416, 2021, doi: 10.1007/s11831-020-09420-6.

G. V. N. Lakshmi, A. Jayalaxmi, and V. Veeramsetty, “Optimal Placement of Distribution Generation in Radial Distribution System Using Hybrid Genetic Dragonfly Algorithm,” Technol. Econ. Smart Grids Sustain. Energy, vol. 6, no. 1, 2021, doi: 10.1007/s40866-021-00107-w.

A. S. Hassan, Y. Sun, and Z. Wang, “Multi-objective for optimal placement and sizing DG units in reducing loss of power and enhancing voltage profile using BPSO-SLFA,” Energy Reports, vol. 6, pp. 1581–1589, 2020, doi: 10.1016/j.egyr.2020.06.013.

M. C. V. Suresh and J. B. Edward, “A hybrid algorithm based optimal placement of DG units for loss reduction in the distribution system,” Appl. Soft Comput. J., vol. 91, 2020, doi: 10.1016/j.asoc.2020.106191.

Z. Ullah, S. Wang, and J. Radosavljević, “A Novel Method Based on PPSO for Optimal Placement and Sizing of Distributed Generation,” IEEJ Trans. Electr. Electron. Eng., vol. 14, no. 12, pp. 1754–1763, 2019, doi: 10.1002/tee.23001.

R. A. Swief, T. S. Abdel-Salam, and N. H. El-Amary, “Photovoltaic and wind turbine integration applying Cuckoo Search for probabilistic reliable optimal placement,” Energies, vol. 11, no. 1, pp. 1–17, 2018, doi: 10.3390/en11010139.

C. K. Das, O. Bass, G. Kothapalli, T. S. Mahmoud, and D. Habibi, “Optimal placement of distributed energy storage systems in distribution networks using artificial bee colony algorithm,” Appl. Energy, vol. 232, no. April, pp. 212–228, 2018, doi: 10.1016/j.apenergy.2018.07.100.

V. Vita, “Development of a decision-making algorithm for the optimum size and placement of distributed generation units in distribution networks,” Energies, vol. 10, no. 9, 2017, doi: 10.3390/en10091433.

S. Kansal, B. Tyagi, and V. Kumar, “Cost–benefit analysis for optimal distributed generation placement in distribution systems,” Int. J. Ambient Energy, vol. 38, no. 1, pp. 45–54, 2017, doi: 10.1080/01430750.2015.1031407.

S. Kansal, V. Kumar, and B. Tyagi, “Hybrid approach for optimal placement of multiple DGs of multiple types in distribution networks,” Int. J. Electr. Power Energy Syst., vol. 75, pp. 226–235, 2016, doi: 10.1016/j.ijepes.2015.09.002.

O. Mohamed, M. Mohamed, and A. Kansab, “Optimal placement and sizing of distributed generation sources in distribution networks using SPEA algorithm,” Int. J. Electr. Eng. Informatics, vol. 11, no. 2, pp. 326–340, 2019, doi: 10.15676/ijeei.2019.11.2.7.

T. R. Ayodele, A. S. O. Ogunjuyigbe, and O. O. Akinola, “Optimal Location, Sizing, and Appropriate Technology Selection of Distributed Generators for Minimizing Power Loss Using Genetic Algorithm,” J. Renew. Energy, vol. 2015, pp. 1–9, 2015, doi: 10.1155/2015/832917.

M. A. Darfoun and M. E. El-Hawary, “Multi-objective optimization approach for optimal distributed generation sizing and placement,” Electr. Power Components Syst., vol. 43, no. 7, pp. 828–836, 2015, doi: 10.1080/15325008.2014.1002589.

L. Liu, X. Liu, N. Wang, and P. Zou, “Modified cuckoo search algorithm with variational parameters and logistic map,” Algorithms, vol. 11, no. 3, pp. 1–11, 2018, doi: 10.3390/a11030030.

J. H. Liang and C. H. Lee, “A modification artificial bee colony algorithm for optimization problems,” Math. Probl. Eng., vol. 2015, 2015, doi: 10.1155/2015/581391.

L. Le Dinh, D. Vo Ngoc, and P. Vasant, “Artificial bee colony algorithm for solving optimal power flow problem,” Sci. World J., vol. 2013, 2013, doi: 10.1155/2013/159040.

M. R. AlRashidi and M. E. El-Hawary, “A survey of particle swarm optimization applications in electric power systems,” IEEE Trans. Evol. Comput., vol. 13, no. 4, pp. 913–918, 2009, doi: 10.1109/TEVC.2006.880326.

M. Ghasemi, E. Akbari, A. Rahimnejad, S. E. Razavi, S. Ghavidel, and L. Li, “Phasor particle swarm optimization: a simple and efficient variant of PSO,” Soft Comput., vol. 23, no. 19, pp. 9701–9718, 2019, doi: 10.1007/s00500-018-3536-8.

B. Yang et al., “Modelling, applications, and evaluations of optimal sizing and placement of distributed generations: A critical state-of-the-art survey,” Int. J. Energy Res., vol. 45, no. 3, pp. 3615–3642, 2021, doi: 10.1002/er.6104.

V. Veeramsetty, C. Venkaiah, and D. M. V. Kumar, Hybrid genetic dragonfly algorithm based optimal power flow for computing LMP at DG buses for reliability improvement, vol. 9, no. 3. Springer Berlin Heidelberg, 2018.

W. Sheng, Y. Liu, X. Meng, and T. Zhang, “An Improved Strength Pareto Evolutionary Algorithm 2 with application to the optimization of distributed generations,” Comput. Math. with Appl., vol. 64, no. 5, pp. 944–955, 2012, doi: 10.1016/j.camwa.2012.01.063.

P. C. and R. Ramakumar, “An Approach to Quantify the Technical Benefits of Distributed Generation,” IEEE Trans. energy Convers., vol. 19, no. 4, 2004.

P. Chiradeja, “Benefit of Distributed Generation: A Line Loss Reduction Analysis,” 2005.

M. C. V. S. and E. J. Belwin, “Optimal DG placement for benefit maximization in distribution networks by using Dragonfy algorithm,” Renewables Wind. Water, Sol., vol. 5, no. 4, 2018.

T. G. G. Rothwell, Electricity economics regulation and deregulation. IEEE Press Power Engineering Series, John Wiley & Sons, 2003.

L. Z. Shahidehpour M, Yamin H, Market Operations in Electric Power Systems. 2002.

S. Mirjalili, “The ant lion optimizer,” Adv. Eng. Softw., vol. 83, pp. 80–98, 2015, doi: 10.1016/j.advengsoft.2015.01.010.

D. Gautam and N. Mithulananthan, “Optimal DG placement in deregulated electricity market,” Electr. Power Syst. Res., vol. 77, no. 12, pp. 1627–1636, 2007, doi: 10.1016/j.epsr.2006.11.014.

C. C. Kayal P, “An analytical approach for allocation and sizing of distributed generation in radial distribution network,” Int Trans Elect Energ syst, vol. 27, no. 7, 2017.

S. Nematshahi, H. R. Mashhadi, “Application of Distribution Locational Marginal Price in optimal simultaneous distributed generation placement and sizing in electricity networks” International Transactions on Electrical Energy System, 2019.

Published

2022-12-09

How to Cite

Ahmed, M. I. ., & Kumar, R. . (2022). Nodal Electricity Price Based Optimal Size and Location of DGs in Electrical Distribution Networks Using ANT LION Optimization Algorithm. Distributed Generation &Amp; Alternative Energy Journal, 38(01), 111–140. https://doi.org/10.13052/dgaej2156-3306.3816

Issue

Section

Advancements in Distributed Generation and Electric Vehicle Technologies