The Optimal Integration of Multiple DGs under Different Load Models using Artificial Bee Colony-Hill Climbing Algorithm
DOI:
https://doi.org/10.48048/tis.2022.4633Keywords:
Optimization technique, Radial distribution system, Distributed generation, Artificial bee colony, Hill climbingAbstract
With the continual advances in technologies, there is a significantly increased demand for electricity leads to a drastic increase in usage and penetration of DGs into the distribution network. The incorrect addition of DGs into the distribution system resulting in declining stability, power losses, voltage profile, reliability, and power quality of the system. Therefore, the optimal planning of DGs (OPDG) has always been under constant investigation and development for the maximum beneficiary. The proposed framework presents a novel meta-heuristic hybrid optimization technique called Artificial Bee Colony-Hill Climbing (ABC-HC) to find the best siting and sizing of multiple DGs using a weighted multi-objective function which includes real and reactive power loss index and voltage deviation index. The results clearly indicate the significant reduction in losses and voltage deviation achieved by integration of single and multiple DGs. The research work is also extended to assess the voltage harmonics of the system before and after the placement of DGs. The effectiveness of the proposed ABC-HC algorithm has been demonstrated on the standard IEEE-33 bus RDS under different voltage dependent load models using MATLAB 2017a.
HIGHLIGHTS
- As demand grows, technologies advance, and power system infrastructure changes, there are more opportunities to integrate distributed generators into the distribution system
- The maximum benefit from the DG integration is achieved by selecting the optimal size and optimal site in the distribution system
- A new hybrid optimization technique has been developed for optimal planning of DGs under different voltage dependent loads. The work was also extended to carry out harmonic analysis
GRAPHICAL ABSTRACT
Downloads
References
AF Abdul Kadir, A Mohamed, H Shareef and MZC Wanik. Optimal placement and sizing of distributed generations in distribution systems for minimizing losses and THD v using evolutionary programming. Turk. J. Electr. Eng. Comput. Sci. 2013; 21, 2269.
AM El-Zonkoly. Optimal placement of multi-distributed generation units including different load models using particle swarm optimisation. IET Gener. Transm. Distrib. 2011; 5, 760-71.
SS Kamel and F Jurado. Efficient optimization technique for multiple DG allocation in distribution networks. Appl. Soft Comput. J. 2019; 86, 105938.
M Kefayat, AL Ara and SAN Niaki. A hybrid of ant colony optimization and artificial bee colony algorithm for probabilistic optimal placement and sizing of distributed energy resources. Energy Conv. Manag. 2015; 92, 149-61.
KR Devabalaji and K Ravi. Optimal size and siting of multiple DG and DSTATCOM in radial distribution system using bacterial foraging optimization algorithm. Ain Shams Eng. J. 2015; 7, 959-71.
MH Moradi and M Abedini. A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution system. Electr. Power Energy Syst. 2012; 34, 66-74.
VVVSN Murty and A Kumar. Optimal DG integration and network reconfiguration in microgrid system with realistic time varying load model using hybrid optimisation. IET Smart Grid. 2019; 2, 192-202.
A Onlam, D Yodphet, R Chatthaworn, C surawanitkum, A Siritaratiwat and P Khunkitti. Power loss minimization and voltage stability improvement in electrical distribution system via network reconfiguration and distributed generation placement using novel adaptive shuffled frogs leaping algorithm. Energies 2019; 12, 553.
A El-Fergany. Multi-objective allocation of multi-type distributed generators along distribution networks using backtracking search algorithm and fuzzy expert rules. Electr. Power Compon. Syst. 2016; 44, 252-67.
D Rama prabha, T jayabarathi, R Umamageswari and S Saranya. Optimal location and sizing of distributed generation unit using intelligent water drop algorithm. Sustain. Energy Technol. Assess. 2015; 11, 106-13.
DR Prabha and T Jayabarathi. Optimal placement and sizing of multiple distributed generating units in distribution networks by invasive weed optimization algorithm. Ain Shams Eng. J. 2015, 7, 683-94.
K S Sambaiah and T Jayabarathi. Optimal allocation of renewable distributed generation and capacitor banks in distribution systems using Salp swarm algorithm. Int. J. Renew. Energy Res. 2019; 9.
R Bala and C Ghosh. Optimal position and rating of DG in distribution networks by ABC-CS from load flow solution illustrated by fuzzy-PSO. The Nat. Comput. Appl. Forum 2017; 31, 489-507.
MV Bhat and N Manjappa. Flower pollination algorithm-based sizing and placement of DG and D-Statcom simultaneously in radial distribution systems. In: Proceedings of the National Power Systems Conference - IEEE, Tiruchirappalli, India, 2018.
Y Thangaraj and R Kuppan. Multi-objective simultaneous placement of DG and DSTATCOM using novel lightning search algorithm. J. Appl. Res. Technol. 2017; 15, 477-91.
IB Hamida, SB Salah, F Msahli and MF Mimouni. Optimal network reconfiguration and renewable DG integration considering time sequence variation in load and DGs. Renew. Energy 2018; 121, 66e80.
LF Ochoa, A Padilha-Feltrin and GP Harrison. Evaluating distributed generation impacts with a multi-objective index. IEEE Trans. Power Deliv. 2006; 21, 1452-8.
D Karaboga and B Basturk. Artificial bee colony (ABC) optimization algorithm for solving constrained optimization problems. In: Proceedings of the 12th International Fuzzy Systems Association World Congress, Cancun, Mexico, 2007, p. 789-98.
D Karaboga and B Basturk. On the performance of artificial bee colony (ABC) algorithm. Appl. Soft Comput. 2007; 8, 687-97.
AK Tagore and AR Gupta. Harmonic load flow analysis of radial distribution system in presence of distributed generation. In: Proceedings of the International Conference on Power and Embedded Drive Control, Chennai, India, 2017.
S Bhullar and S Ghoosh. Optimal integration of multi distributed generation sources in radial distribution netwroks using a hybrid algorithm. Energies 2018; 11, 628.
AK Tagore. 2017, Harmonic load flow analysis of radial distribution system with DG and D-SATSCOM. M. Tech. Dissertation. National Institute of Technology Warangal, Kurukshetra, India.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
