Reduction of Emission Cost, Loss Cost and Energy Purchase Cost for Distribution Systems With Capacitors, Photovoltaic Distributed Generators, and Harmonics

Thai Dinh Pham, Hung Duc Nguyen, Thang Trung Nguyen

Abstract


In this paper, a bonobo optimizer (BO) and two other methods, particle swarm optimization (PSO) and salp swarm algorithm (SSA), are implemented to determine the location and sizing of photovoltaic distributed generators (PDGs) and capacitors in IEEE 69-bus radial distribution system with many nonlinear loads. The objective of the study is to minimize the costs for purchasing energy from main grid for load demand and power loss on transmission lines as well as cost for emission fines from fossil fuel generation units of the grid under considering strict constraints on penetration, voltage, current and harmonic distortions. The results have shown that BO is the best and most stable method in solving the considered optimization problem. With the use of the optimal solution from BO, the total cost is significantly reduced up to 80.52%. As compared to base system without capacitors and PDGs, the obtained solution can reduce power loss up to 94.48% and increase the voltage profile from the range of [0.9092 1.00] pu to higher range of [0.9907 1.0084] pu. In addition, total harmonic distortion (THD) and individual harmonic distortion (IHD) are also much improved and satisfied under the IEEE Std. 519. Thus, BO is a suitable method for the application of installing capacitors and PDGs in distribution systems.


Keywords


Bonobo optimizer; Capacitor Emissions; Power loss; Harmonic; Voltage profile

References


S.S. Kola, “A review on optimal allocation and sizing techniques for DG in distribution systems”, International Journal of Renewable Energy Research (IJRER), vol.8, No.3, pp. 1236-1256, 2018.

H. HassanzadehFard, and A. Jalilian, “Optimal sizing and location of renewable energy based DG units in distribution systems considering load growth”, International Journal of Electrical Power & Energy Systems, vol.101, pp. 356-370, 2018.

L. Che, X. Zhang, M. Shahidehpour, A. Alabdulwahab, and A. Abusorrah, “Optimal interconnection planning of community microgrids with renewable energy sources”, IEEE Transactions on Smart Grid, vol.8, no.3, pp. 1054-1063, 2015.

V. Kalkhambkar, B. Rawat, R. Kumar, and R. Bhakar, Optimal allocation of renewable energy sources for energy loss minimization. Journal of Electrical Systems, vol.13, no.1, 115-130, 2017.

R.A. Kordkheili, B. Bak-Jensen, R. Jayakrishnan, and P. Mahat, “Determining maximum photovoltaic penetration in a distribution grid considering grid operation limits”, In 2014 IEEE PES General Meeting| Conference & Exposition, IEEE, pp.1-5, 2014.

A. Hoke, R. Butler, J. Hambrick, and B. Kroposki, “Maximum photovoltaic penetration levels on typical distribution feeders (No. NREL/JA-5500-55094)”, National Renewable Energy Lab.(NREL), Golden, CO (United States), 2012.

H.A. Abdel-Ghany, A.M Azmy, N.I. Elkalashy, and E.M. Rashad, “Optimizing DG penetration in distribution networks concerning protection schemes and technical impact”, Electric Power Systems Research, vol.128, pp.113-122, 2015.

P.R.P Dinakara, R.V.C Veera, and M.T. Gowri, “Ant Lion optimization algorithm for optimal sizing of renewable energy resources for loss reduction in distribution systems”, Journal of Electrical Systems and Information Technology, vol.5, no.3, pp.663-680, 2018.

A.F. Buitrago-Velandia, O.D. Montoya, and W. Gil-González, “Dynamic Reactive Power Compensation in Power Systems through the Optimal Siting and Sizing of Photovoltaic Sources”. Resources, vol.10, no.5, 47, 2021.

S. Settoul, R. Chenni, H.A. Hasan, M. Zellagui, and M.N. Kraimia, “MFO algorithm for optimal location and sizing of multiple photovoltaic distributed generations units for loss reduction in distribution systems”, In 2019 7th International Renewable and Sustainable Energy Conference (IRSEC). IEEE, pp. 1-6, 2019.

C. Chen, X. Wang, H. Yu, M. Wang, and H. Chen, “Dealing with multi-modality using synthesis of Moth-flame optimizer with sine cosine mechanisms”, Mathematics and Computers in Simulation, vol.188, pp.291-318, 2021.

M.G. Hemeida, A.A. Ibrahim, A.A.A. Mohamed, S. Alkhalaf, and A.M.B. El-Dine, “Optimal allocation of distributed generators DG based Manta Ray Foraging Optimization algorithm (MRFO)”, Ain Shams Engineering Journal, vol. 12, no.1, pp.609-619, 2021.

O.E. Turgut, “A novel chaotic manta-ray foraging optimization algorithm for thermo-economic design ptimization of an air-fin cooler”, SN Applied Sciences, vol.3, no.1, pp.1-36, 2021.

A. Ymeri, and S. Mujović, “Optimal location and sizing of photovoltaic systems in order to reduce power losses and voltage drops in the distribution grid”, methods, vol.3, no.4, 2017.

I.J. Hasan, M.R. Ab Ghani, and C.K. Gan, :Optimum distributed generation allocation using PSO in order to reduce losses and voltage improvement”, 3rd IET Internatinal conference on clean energy and technology, 1-6, 2014

J. A. D. Costa, D.A. Castelo Branco, M.C. Pimentel Filho, M.F.D. Medeiros Júnior, and N.F.D. Silva, “Optimal sizing of photovoltaic generation in radial distribution systems using lagrange multipliers,” Energies, vol.12, no.9, 1728, 2019.

A.K. Pandey, and S. Kirmani, “Optimal location and sizing of hybrid system by analytical crow search optimization algorithm", International Transactions on Electrical Energy Systems, vol.30, no.5, e12327, 2020.

M. Khasanov, S. Kamel, M. Tostado-Véliz, and F. Jurado, “Allocation of photovoltaic and wind turbine based DG units using artificial ecosystem-based optimization”, In 2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Systems Europe (EEEIC/I&CPS Europe), IEEE, pp. 1-5, 2020.

A.L. Bukar, A, C.W. Tan, and K.Y. Lau, “Optimal sizing of an autonomous photovoltaic/wind/battery/diesel generator microgrid using grasshopper optimization algorithm”, Solar Energy, 188, pp.685-696, 2019.

T.T. Nguyen, T.T. Nguyen, and N.A. Nguyen, “Maximum Penetration of Distributed Generations and Improvement of Technical Indicators in Distribution Systems”, Mathematical Problems in Engineering, 2020.

E.S. Ali, S.M. Abd Elazim, and A.Y. Abdelaziz, “Ant lion optimization algorithm for renewable distributed generations”, Energy, vol.116, pp. 445-458, 2016.

A. Faramarzi, M. Heidarinejad, B. Stephens, and S. Mirjalili, “Equilibrium optimizer: A novel optimization algorithm”, Knowledge-Based Systems, vol.191, 105190, 2020.

S. Saha, and V. Mukherjee, “A novel multiobjective chaotic symbiotic organisms search algorithm to solve optimal DG allocation problem in radial distribution system”, International Transactions on Electrical Energy Systems, vol.29, No.5, e2839, 2019.

E.E. Elattar, and S.K. Elsayed, “Optimal location and sizing of distributed generators based on renewable energy sources using modified moth flame optimization technique”, IEEE Access, vol.8, pp.109625-109638, 2020.

S.M. Abd Elazim, and E.S. Ali, “Optimal network restructure via improved whale optimization approach”, International Journal of Communication Systems, vol.34, No.1, e4617, 2021.

A. Al Khatib, and H. Shareef, “Optimal Placement and Sizing of Distributed Generation for Power Loss Mitigation and Voltage Profile Enhancement Using Atom Search Optimization”, 5th splitech 2020, 2020.

M. Khasanov, K. Xie, S. Kamel, L. Wen, and X. Fan, “Combined Tree Growth Algorithm for Optimal Location and Size of Multiple DGs with Different Types in Distribution Systems”, In 2019 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), IEEE, pp. 1265-1270, 2019.

K.S. Sambaiah, and T. Jayabarathi, “Optimal reconfiguration and renewable distributed generation allocation in electric distribution systems”, International Journal of Ambient Energy, vol.42, no.9, pp.1018-1031, 2021.

K. Bhumkittipich, and W. Phuangpornpitak, “Optimal placement and sizing of distributed generation for power loss reduction using particle swarm optimization”, Energy procedia, vol.34, pp.307-317, 2013.

A.K. Das, and D.K. Pratihar, “A new bonobo optimizer (BO) for real-parameter optimization”, In 2019 IEEE Region 10 Symposium (TENSYMP), IEEE, pp. 108-113, 2019.

H.M. Farh, A.A. Al-Shamma’a, A.M. Al-Shaalan, A. Alkuhayli, A.M. Noman, and T. Kandil, “Technical and economic evaluation for off-grid hybrid renewable energy system using novel bonobo optimizer”, Sustainability, vol.14, No.3, 1533, 2022.

M.H. Hassan, S.K. Elsayed, S.K. Kamel, C. Rahmann, and I.B. Taha, “Developing chaotic Bonobo optimizer for optimal power flow analysis considering stochastic renewable energy resources”, International Journal of Energy Research, vol. 46, No.8, pp. 11291-11325, 2022.

M. Kharrich, O.H. Mohammed, S. Kamel, A. Selim, H.M. Sultan, M. Akherraz, and F. Jurado, “Development and implementation of a novel optimization algorithm for reliable and economic grid- independent hybrid power system”, Applied Sciences, vol. 10, No. 18, 6604, 2020

A.K. Das and D.K. Pratihar,” Bonobo optimizer (BO): an intelligent heuristic with self-adjusting parameters over continuous spaces and its applications to engineering problems”, Applied Intelligence, vol. 52, No. 3, pp. 2942-2974, 2022.

J.H. Teng, and C.Y. Chang, “Backward/forward sweep-based harmonic analysis method for distribution systems” IEEE transactions on power delivery, vol.22, no.3, pp.1665-1672, 2007.

V. Janamala, and K. Radha Rani, “Optimal allocation of solar photovoltaic distributed generation in electrical distribution networks using Archimedes optimization algorithm”, Clean Energy, vol.6, no.2, pp.271-287, 2022.

L.C. Kien, T.T.B. Nga, T.M. Phan, T.T. Nguyen, “Coot Optimization Algorithm for Optimal Placement of Photovoltaic Generators in Distribution Systems Considering Variation of Load and Solar Radiation”, Mathematical Problems in Engineering, 2022

A. Navarro-Espinosa, and L.F. Ochoa, “Probabilistic impact assessment of low carbon technologies in LV distribution systems”, IEEE Transactions on Power Systems, vol.31, no.3, pp.2192-2203, 2015.

T.T. Nguyen, T.D. Pham, L.C. Kien, and L.V. Dai, “Improved coyote optimization algorithm for optimally installing solar photovoltaic distribution generation units in radial distribution power systems”, Complexity, 2020.

M. Madhusudhan, N. Kumar, and H. Pradeepa, “Optimal location and capacity of DG systems in distribution network using genetic algorithm”, International Journal of Information Technology, vol.13, no.1, pp.155-162, 2021.

S.M. Abd Elazim, and E.S. Ali, “Optimal locations and sizing of capacitors in radial distribution systems using mine blast algorithm”, Electrical Engineering, vol.100, pp.1-9, 2018.

T.D. Pham, T.T. Nguyen, and L.C. Kien, “An Improved Equilibrium Optimizer for Optimal Placement of Distributed Generators in Distribution Systems considering Harmonic Distortion Limits”, Complexity, 2022.

S.K. Dash, L.R. Pati, S. Mishra, P.K. Satpathy, “Multi-objective Optimal Location and Size of Embedded Generation Units and Capacitors Using Metaheuristic Algorithms,” In Green Technology for Smart City and Society, Springer, Singapore, pp. 471-486, 2021.

A. Eid, S. Kamel, M.H. Hassan, and B. Khan, “A Comparison Study of Multi-Objective Bonobo Optimizers for Optimal Integration of Distributed Generation in Distribution Systems”, Energy Res, vol.10, 847495, 2022.

E.S. Oda, A.M. Abd El Hamed, A. Ali, A.A. Elbaset, M. Abd El Sattar and M. Ebeed, “Stochastic optimal planning of distribution system considering integrated photovoltaic-based DG and DSTATCOM under uncertainties of loads and solar irradiance”, IEEE access, vol. 9, pp. 26541-26555, 2021.

M.S. Alam, and S.A. Arefifar, “Cost & emission analysis of different DGs for performing energy management in smart grids,” In 2018 IEEE International Conference on Electro/Information Technology (EIT), IEEE, pp. 0667-0672, 2018.

S. Mirjalili, A.H. Gandomi, S.Z. Mirjalili, S. Saremi, H. Faris, and S.M. Mirjalili, “Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems”, Advances in engineering software, vol.114, pp.163-191, 2017.


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