An Enhanced Artificial Ecosystem-Based Optimization for Optimal Allocation of Multiple Distributed Generations

Optimal allocation of distributed generations (DGs) is vital to the proper operation of the distribution systems, which leads to power loss minimization and acceptable voltage regulation. In this paper, an Enhanced Artificial Ecosystem-based Optimization (EAEO) algorithm is proposed and used to solve the optimization problem of DG allocations to minimize the power loss in distribution systems. In the suggested algorithm, the search space is reduced using operator G and sine-cosine function. The G-operator affects the balance between explorative and exploitative phases. At the same time, it gradually decreases during the iterative process in order to converge to the optimal global solutions. On the other hand, the sine-cosine function creates different and random solutions. The EAEO algorithm is applied for solving the standard 33-bus 69-bus, and 119-bus distribution systems with the aim of minimizing the total power losses. Multiple DG units operating at various power factors, including unity-, fixed-, and optimal-power factors, are considered. Both single and multiple objectives are considered to minimize the total voltage deviation (TVD), maximize the system stability, and reduce the total power losses. The obtained results are compared with those obtained by the AEO and other algorithms. The results demonstrate a significant reduction of total power losses and improvement of the voltage profile of the network, especially for the DGs operating at their optimal power factors. Comparisons show the dominance of the proposed EAEO algorithm against other analytical, metaheuristic, or hybrid algorithms. Moreover, the EAEO outperforms the original AEO algorithm with a faster convergence speed and better system performance.

[1]  Gholamreza Khademi,et al.  Voltage stability assessment using multi-objective biogeography-based subset selection , 2018, International Journal of Electrical Power & Energy Systems.

[2]  Bikash Das,et al.  DG placement in radial distribution network by symbiotic organisms search algorithm for real power loss minimization , 2016, Appl. Soft Comput..

[3]  Douglas H. Werner,et al.  The Wind Driven Optimization Technique and its Application in Electromagnetics , 2013, IEEE Transactions on Antennas and Propagation.

[4]  Nadarajah Mithulananthan,et al.  Multiple Distributed Generator Placement in Primary Distribution Networks for Loss Reduction , 2013, IEEE Transactions on Industrial Electronics.

[5]  C. Lakshminarayana,et al.  Multiple DG Placements in Distribution System for Power Loss Reduction Using PSO Algorithm , 2016 .

[6]  Saad Mekhilef,et al.  Optimal reconfiguration of distribution system connected with distributed generations: A review of different methodologies , 2017 .

[7]  Zhenxing Zhang,et al.  Atom search optimization and its application to solve a hydrogeologic parameter estimation problem , 2019, Knowl. Based Syst..

[8]  Mamdouh Abdel-Akher,et al.  Effective Demand Side Scheme for PHEVs Operation Considering Voltage Stability of Power Distribution Systems , 2017 .

[9]  M. Geethanjali,et al.  Application of Modified Bacterial Foraging Optimization algorithm for optimal placement and sizing of Distributed Generation , 2014, Expert Syst. Appl..

[10]  Nebojša Arsić,et al.  Optimal Placement and Sizing of Renewable Distributed Generation Using Hybrid Metaheuristic Algorithm , 2020, Journal of Modern Power Systems and Clean Energy.

[11]  Naoto Yorino,et al.  Optimal Distributed Generation Allocation in Distribution Systems for Loss Minimization , 2016, IEEE Transactions on Power Systems.

[12]  M. M. Aman,et al.  A new approach for optimum simultaneous multi-DG distributed generation Units placement and sizing based on maximization of system loadability using HPSO (hybrid particle swarm optimization) algorithm , 2014 .

[13]  Mohammad Hassan Moradi,et al.  An efficient hybrid method for solving the optimal sitting and sizing problem of DG and shunt capacitor banks simultaneously based on imperialist competitive algorithm and genetic algorithm , 2014 .

[14]  K. Ravi,et al.  Optimal size and siting of multiple DG and DSTATCOM in radial distribution system using Bacterial Foraging Optimization Algorithm , 2016 .

[15]  Antonio José Gil Mena,et al.  Optimal distributed generation location and size using a modified teaching–learning based optimization algorithm , 2013 .

[16]  Salah Kamel,et al.  Effective Parameter Extraction of Different Polymer Electrolyte Membrane Fuel Cell Stack Models Using a Modified Artificial Ecosystem Optimization Algorithm , 2020, IEEE Access.

[17]  Vishal Kumar,et al.  Hybrid approach for optimal placement of multiple DGs of multiple types in distribution networks , 2016 .

[18]  Tomonobu Senjyu,et al.  Fast quasi-static time-series analysis and reactive power control of unbalanced distribution systems , 2018, International Transactions on Electrical Energy Systems.

[19]  Faten H. Fahmy,et al.  Genetic single objective optimisation for sizing and allocation of renewable DG systems , 2017 .

[20]  Weiguo Zhao,et al.  Artificial ecosystem-based optimization: a novel nature-inspired meta-heuristic algorithm , 2019, Neural Computing and Applications.

[21]  Salah Bahramara,et al.  Improved harmony search algorithm for electrical distribution network expansion planning in the presence of distributed generators , 2018 .

[22]  Jordan Radosavljević,et al.  Metaheuristic Optimization in Power Engineering , 2018 .

[23]  N. Zareen,et al.  Grey wolf optimizer based placement and sizing of multiple distributed generation in the distribution system , 2016 .

[24]  Salah Kamel,et al.  Modified water cycle algorithm for optimal direction overcurrent relays coordination , 2019, Appl. Soft Comput..

[25]  P. Lokender Reddy,et al.  PSO based optimal reactive power dispatch for voltage profile improvement , 2015, 2015 IEEE Power, Communication and Information Technology Conference (PCITC).

[26]  Amin Khodabakhshian,et al.  Simultaneous placement and sizing of DGs and shunt capacitors in distribution systems by using IMDE algorithm , 2016 .

[27]  Mamdouh Abdel-Akher,et al.  Power Loss Reduction using Adaptive PSO in Unbalanced Distribution Networks , 2019, 2019 21st International Middle East Power Systems Conference (MEPCON).

[28]  Almoataz Y. Abdelaziz,et al.  A Multi-objective Optimization for Sizing and Placement of Voltage-controlled Distributed Generation Using Supervised Big Bang–Big Crunch Method , 2015 .

[29]  Ravi Kuppan,et al.  Multi-objective simultaneous placement of DG and DSTATCOM using novel lightning search algorithm , 2017 .

[30]  Sandeep Kaur,et al.  A MINLP technique for optimal placement of multiple DG units in distribution systems , 2014 .

[31]  Mahmoud Hassaballah,et al.  Lévy flight distribution: A new metaheuristic algorithm for solving engineering optimization problems , 2020, Eng. Appl. Artif. Intell..

[32]  S. Jayalalitha,et al.  Optimal placement and sizing of distributed generators and shunt capacitors for power loss minimization in radial distribution networks using hybrid heuristic search optimization technique , 2016 .

[33]  Mohammad Rasoul Narimani,et al.  A hybrid evolutionary algorithm for secure multi-objective distribution feeder reconfiguration , 2017 .

[34]  Attia A. El-Fergany,et al.  Optimal allocation of multi-type distributed generators using backtracking search optimization algorithm , 2015 .

[35]  Sydulu Maheswarapu,et al.  A solution to multi‐objective optimal accommodation of distributed generation problem of power distribution networks: An analytical approach , 2019, International Transactions on Electrical Energy Systems.

[36]  Hossein Nezamabadi-pour,et al.  GSA: A Gravitational Search Algorithm , 2009, Inf. Sci..

[37]  Belkacem Mahdad,et al.  Adaptive differential search algorithm for optimal location of distributed generation in the presence of SVC for power loss reduction in distribution system , 2016 .

[38]  Bin Wang,et al.  Multi-objective optimization using teaching-learning-based optimization algorithm , 2013, Eng. Appl. Artif. Intell..

[39]  A. Lashkar Ara,et al.  A hybrid of ant colony optimization and artificial bee colony algorithm for probabilistic optimal placement and sizing of distributed energy resources , 2015 .

[40]  Kim-Fung Man,et al.  A real-coding jumping gene genetic algorithm (RJGGA) for multiobjective optimization , 2007, Inf. Sci..

[41]  A MohamedImran,et al.  Optimal size and siting of multiple distributed generators in distribution system using bacterial foraging optimization , 2014, Swarm Evol. Comput..

[42]  T. Jayabarathi,et al.  Optimal Allocation of Distributed Generation Using Hybrid Grey Wolf Optimizer , 2017, IEEE Access.

[43]  Usharani Raut,et al.  An improved Elitist–Jaya algorithm for simultaneous network reconfiguration and DG allocation in power distribution systems , 2019, Renewable Energy Focus.

[44]  C. Lakshminarayana,et al.  Multiple DG placements in radial distribution system for multi objectives using Whale Optimization Algorithm , 2018, Alexandria Engineering Journal.

[45]  Debapriya Das,et al.  Voltage Stability Analysis of Radial Distribution Networks , 2001 .

[46]  P. N. Suganthan,et al.  Differential Evolution Algorithm With Strategy Adaptation for Global Numerical Optimization , 2009, IEEE Transactions on Evolutionary Computation.

[47]  Seyedali Mirjalili,et al.  SCA: A Sine Cosine Algorithm for solving optimization problems , 2016, Knowl. Based Syst..

[48]  Almoataz Y. Abdelaziz,et al.  Fuzzy multi-objective placement of renewable energy sources in distribution system with objective of loss reduction and reliability improvement using a novel hybrid method , 2019, Appl. Soft Comput..

[49]  Ponnuthurai N. Suganthan,et al.  A multiobjective approach for optimal placement and sizing of distributed generators and capacitors in distribution network , 2017, Appl. Soft Comput..

[50]  Akbar Bayat,et al.  Optimal active and reactive power allocation in distribution networks using a novel heuristic approach , 2019, Applied Energy.

[51]  Jianyong Sun,et al.  A decomposition-based archiving approach for multi-objective evolutionary optimization , 2018, Inf. Sci..

[52]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[53]  L. F. Grisales-Norena,et al.  An exact MINLP model for optimal location and sizing of DGs in distribution networks: A general algebraic modeling system approach , 2020 .

[54]  M. E. El-Hawary,et al.  Optimal Distributed Generation Allocation and Sizing in Distribution Systems via Artificial Bee Colony Algorithm , 2011, IEEE Transactions on Power Delivery.

[55]  Almoataz Y. Abdelaziz,et al.  Improved Harmony Algorithm for optimal locations and sizing of capacitors in radial distribution systems , 2016 .

[56]  C. K. Das,et al.  Optimal placement of distributed energy storage systems in distribution networks using artificial bee colony algorithm , 2018, Applied Energy.

[57]  Pavlos S. Georgilakis,et al.  Optimal distributed generation placement under uncertainties based on point estimate method embedded genetic algorithm , 2014 .