Optimal Power Flow of a Power System Incorporating Stochastic Wind Power Based on Modified Moth Swarm Algorithm

The combined heat and power (CHP) generator not only generates electrical power but also generates heat energy in a single process, which decreases the emission level significantly. The integration of wind power into the power system will lead to an impact on the economic operation of the system as well as the bus voltage and transmission losses. In this paper, a formulation of optimal power flow (OPF) problem of a power system incorporating stochastic wind power is presented. To solve this problem, a modified version of the moth swarm algorithm (MMSA) is proposed. Three objective functions, which are the minimization of operating cost, the minimization of transmission power loss, and the voltage profile improvement, are considered in this paper. To minimize the operating cost, the direct, overestimation, and underestimation costs of wind power units are considered. Two test systems are considered to prove the effectiveness and the superiority of the proposed MMSA in comparison with other methods. The comparison with other methods proves the efficiency and the superiority of the proposed MMSA.

[1]  Francisco D. Galiana,et al.  A survey of the optimal power flow literature , 1991 .

[2]  T. Y. Ji,et al.  Quasi-Monte Carlo Based Probabilistic Optimal Power Flow Considering the Correlation of Wind Speeds Using Copula Function , 2018, IEEE Transactions on Power Systems.

[3]  Malabika Basu,et al.  Combined heat and power economic emission dispatch using nondominated sorting genetic algorithm-II , 2013 .

[4]  P. K. Chattopadhyay,et al.  Application of biogeography-based optimisation to solve different optimal power flow problems , 2011 .

[5]  Ponnuthurai Nagaratnam Suganthan,et al.  Optimal power flow solutions incorporating stochastic wind and solar power , 2017 .

[6]  Antonio J. Conejo,et al.  Adaptive robust AC optimal power flow considering load and wind power uncertainties , 2018 .

[7]  Ehab E. Elattar,et al.  A hybrid genetic algorithm and bacterial foraging approach for dynamic economic dispatch problem , 2015 .

[8]  Bijay Ketan Panigrahi,et al.  Hybrid flower pollination algorithm with time-varying fuzzy selection mechanism for wind integrated multi-objective dynamic economic dispatch , 2015 .

[9]  David H. Wolpert,et al.  No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..

[10]  Victor O. K. Li,et al.  Optimal Power Flow With Power Flow Routers , 2017, IEEE Transactions on Power Systems.

[11]  A. Karami,et al.  Artificial bee colony algorithm for solving multi-objective optimal power flow problem , 2013 .

[12]  Ranjit Roy,et al.  Optimal power flow solution of power system incorporating stochastic wind power using Gbest guided artificial bee colony algorithm , 2015 .

[13]  O. Alsac,et al.  Optimal Load Flow with Steady-State Security , 1974 .

[14]  Kiran Teeparthi,et al.  Multi-objective hybrid PSO-APO algorithm based security constrained optimal power flow with wind and thermal generators , 2017 .

[15]  Yixin Ni,et al.  A Solution of Optimal Power Flow Incorporating Wind Generation and Power Grid Uncertainties , 2018, IEEE Access.

[16]  M. A. Abido,et al.  Optimal power flow using Teaching-Learning-Based Optimization technique , 2014 .

[17]  R. Venkata Rao,et al.  Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems , 2011, Comput. Aided Des..

[18]  Shaorong Wang,et al.  A Solution to the Optimal Power Flow Problem Considering WT and PV Generation , 2019, IEEE Access.

[19]  Ehab E. Elattar,et al.  Optimal reactive power resources sizing for power system operations enhancement based on improved grey wolf optimiser , 2018 .

[20]  Ugur Güvenc,et al.  Chaotic Moth Swarm Algorithm , 2017, 2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA).

[21]  Yang Shi,et al.  Optimal power flow and PGU capacity of CCHP systems using a matrix modeling approach , 2013 .

[22]  Chun-Lung Chen,et al.  Optimal power flow of a wind-thermal generation system , 2014 .

[23]  Chetan Mishra,et al.  Optimal power flow in the presence of wind power using modified cuckoo search , 2015 .

[24]  N. Amjady,et al.  Solution of Optimal Power Flow Subject to Security Constraints by a New Improved Bacterial Foraging Method , 2012, IEEE Transactions on Power Systems.

[25]  Serhat Duman,et al.  A Modified Moth Swarm Algorithm Based on an Arithmetic Crossover for Constrained Optimization and Optimal Power Flow Problems , 2018, IEEE Access.

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

[27]  P. K. Chattopadhyay,et al.  Dynamic optimal power flow of combined heat and power system with Valve-point effect using Krill Herd algorithm , 2017 .

[28]  Nenad Jovanovic,et al.  Moth Swarm Algorithm for Solving Combined Economic and Emission Dispatch Problem , 2017 .

[29]  Al-Attar Ali Mohamed,et al.  Optimal power flow using moth swarm algorithm , 2017 .