A comparative study of modified swarm intelligence based algorithms for solving multi-objective optimal power flow incorporating wind power and load uncertainties

2017 ◽  
Author(s):  
I. Srikun ◽  
B. Sawetsakulanond
Keyword(s):  
Comparative Study ◽  
Swarm Intelligence ◽  
Wind Power ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Multi Objective ◽  
Optimal Power

scholarly journals Multi-objective optimal power flow in the presence of intermittent renewable energy sources

2018 ◽  
Vol 7 (4) ◽  
pp. 2766 ◽  
Author(s):  
S. Surender Reddy
Keyword(s):  
Wind Power ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Cost Minimization ◽  
Renewable Energy Sources ◽  
Thermal Power ◽  
Wind Farms ◽  
Multi Objective ◽  
Optimal Power ◽  
Generation Cost

This paper solves a multi-objective optimal power flow (MO-OPF) problem in a wind-thermal power system. Here, the power output from the wind energy generator (WEG) is considered as the schedulable, therefore the wind power penetration limits can be determined by the system operator. The stochastic behavior of wind power and wind speed is modeled using the Weibull probability density function. In this paper, three objective functions i.e., total generation cost, transmission losses and voltage stability enhancement index are selected. The total generation cost minimization function includes the cost of power produced by the thermal and WEGs, costs due to over-estimation and the under-estimation of available wind power. Here, the MO-OPF problems are solved using the multi-objective glowworm swarm optimiza-tion (MO-GSO) algorithm. The proposed optimization problem is solved on a modified IEEE 30 bus system with two wind farms located at two different buses in the system.  

Probabilistic multi-objective optimal power flow considering correlated wind power and load uncertainties

2016 ◽  
Vol 94 ◽  
pp. 10-21 ◽  
Author(s):  
S. Shargh ◽  
B. Khorshid ghazani ◽  
B. Mohammadi-ivatloo ◽  
H. Seyedi ◽  
M. Abapour
Keyword(s):  
Wind Power ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Multi Objective ◽  
Optimal Power

scholarly journals Multi-objective optimal power flow with DG placement using TLBO and MIPSO: A comparative study

2017 ◽  
Vol 117 ◽  
pp. 236-243 ◽  
Author(s):  
Subhrajyoti Sahu ◽  
Ajit Kumar Barisal ◽  
Abhishek Kaudi
Keyword(s):  
Comparative Study ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Multi Objective ◽  
Optimal Power

Research on interval multi-objective optimal power flow in AC-DC systems considering wind power fluctuation

2021 ◽  
pp. 0309524X2199277
Author(s):  
Hongfen Zhang ◽  
Youchao Zhang
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Flow Model ◽  
Power Fluctuation ◽  
Affine Arithmetic ◽  
Multi Objective ◽  
Optimal Power ◽  
Generation Cost

Aiming at the influence of the uncertainty of power system operating parameters such as wind power fluctuation on AC-DC hybrid system, an interval optimal power flow calculation method based on interval and affine arithmetic is proposed in this paper. First, AC and DC interval power flow model is constructed based on the relationship between interval and affine arithmetic, and the uncertainties such as the new energy generation output of the system are expressed as interval variables; static security performance index (PI) is introduced in AC-DC multi-objective optimal power flow objective functions, which take the system’s power generation cost and network loss into account; the Pareto optimal solution set is distributed uniformly in space by using the particle swarm algorithm to solve the interval optimal power flow model. Finally, MATLAB simulation examples are used to verify that the method can optimize the system’s power generation cost, network loss and static safety index while considering wind power fluctuation.

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