Optimal Power Flow Problem Solution Based on Hybrid Firefly Krill Herd Method

2019 ◽  
Vol 44 ◽  
pp. 213-228 ◽  
Author(s):  
Aboubakr Khelifi ◽  
Bachir Bentouati ◽  
Saliha Chettih
Keyword(s):  
Light Intensity ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Optimization Problems ◽  
Test System ◽  
Optimization Techniques ◽  
System Control ◽  
Problem Solution ◽  
Optimal Power ◽  
Krill Herd

Optimal Power Flow (OPF) problem is one of the most important and widely studied nonlinear optimization problems in power system operation. This study presents the implementation of a new technology based on the hybrid Firefly and krill herd method (FKH), which has been provided and used for OPF problems in power systems. In FKH, an improved formulation of the attractiveness and adjustment of light intensity operator initially employed in FA, named attractiveness and light intensity the update operator (ALIU), is inserted into the KH approach as a local search perform. The FKH is prove with the solving of the OPF problem for various types of single-objective and multi-objective functions such as generation cost, reduced emission, active power losses and voltage deviation which are optimized simultaneously on exam system, viz the IEEE-30 Bus test system, which is used to test and confirm the efficiency of the proposed FKH technique. By comparing with several optimization techniques, the results produced by using the recommended FKH technique are provided in detail. The results obtained in this study appear that the FKH technique can be efficiency used to solve the non-linear and non-convex problems and high performance compared with other optimization methods in the literature. This study can achieve a minimum objective by finding the optimum setting for system control variables.

scholarly journals Marine predators algorithm for solving single-objective optimal power flow

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256050
Author(s):  
Mohammad Zohrul Islam ◽  
Mohammad Lutfi Othman ◽  
Noor Izzri Abdul Wahab ◽  
Veerapandiyan Veerasamy ◽  
Saifur Rahman Opu ◽  
...  
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Foraging Strategy ◽  
Test System ◽  
Optimization Techniques ◽  
Encounter Rate ◽  
Marine Predator ◽  
Optimal Power ◽  
Single Objective

This study presents a nature-inspired, and metaheuristic-based Marine predator algorithm (MPA) for solving the optimal power flow (OPF) problem. The significant insight of MPA is the widespread foraging strategy called the Levy walk and Brownian movements in ocean predators, including the optimal encounter rate policy in biological interaction among predators and prey which make the method to solve the real-world engineering problems of OPF. The OPF problem has been extensively used in power system operation, planning, and management over a long time. In this work, the MPA is analyzed to solve the single-objective OPF problem considering the fuel cost, real and reactive power loss, voltage deviation, and voltage stability enhancement index as objective functions. The proposed method is tested on IEEE 30-bus test system and the obtained results by the proposed method are compared with recent literature studies. The acquired results demonstrate that the proposed method is quite competitive among the nature-inspired optimization techniques reported in the literature.

Solving OPF Problems using Biogeography Based and Grey Wolf Optimization Techniques

2017 ◽  
Vol 6 (3) ◽  
pp. 55-77 ◽  
Author(s):  
Kingsuk Majumdar ◽  
Puja Das ◽  
Provas Kumar Roy ◽  
Subrata Banerjee
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
High Efficiency ◽  
Test System ◽  
Optimization Techniques ◽  
Mixed Integer ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
System A ◽  
Optimal Power

This paper presents biogeography-based optimization (BBO) and grey wolf Optimization(GWO) for solving the multi-constrained optimal power flow (OPF) problems in the power system. In this paper, the proposed algorithms have been tested in 9-bus system under various conditions along with IEEE 30 bus test system. A comparison of simulation results reveals optimization efficacy of the proposed scheme over evolutionary programming (EP), genetic algorithm (GA), mixed-integer particle swarm optimization (MIPSO) for the global optimization of multi-constraint OPF problems. It is observed that GWO is far better in comparison to other listed optimization techniques and can be used for aforesaid problems with high efficiency.

scholarly journals Line-Wise Power Balance Equations and Applications

2021 ◽  
Author(s):  
Amr Adel Fathy Mohamed
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Voltage Stability ◽  
Optimization Problems ◽  
Solution Space ◽  
Optimization Techniques ◽  
Power Balance ◽  
Balance Equations ◽  
Stable States ◽  
Optimal Power

Optimal power flow (OPF) refers to optimize power systems considering a chosen objective subject to a set of constraints. Existing OPF formulations used to settle electricity markets include a set of bus-wise power balance equations (PBE) that is comprised exclusively of high order terms which have sinusoidal components. Accordingly, such OPF formulations remain nonlinear and nonconvex optimization problems. Even though commercial OPF solvers are robust and efficient, they still cannot guarantee a global optimum. The US Federal Energy Regulatory Commission estimates that the best commercial OPF solvers are off by 10%, amounting to an annual loss of US $400 billion worldwide. For these motivating reasons, OPF remains a major research focus and forms the topic of this thesis. This thesis aims to: (1) develop new sets of PBE with lower order terms and lesser numbers of sinusoidal terms yielding better solution space, (2) build new OPF formulations using this new set of PBE, and (3) incorporate voltage stability constraints into the developed OPF formulations. The genesis of the new set of PBE stems from: (1) the fact that power of a constant impedance load is proportional to the square of voltage magnitude, and, (2) power flow in branches can be expressed in terms of square of voltage magnitude. Accordingly, a set of line-wise PBE is developed, both in polar and rectangular forms and are solved Newton-Raphson technique. Tests show that the proposed line-wise power flow (LWPF) algorithms are accurate, provide monotonic convergence, and scale well for large systems. The algorithms are faster comparing to classical bus-wise power flow methods. Further, the ability to directly identify the set of critical lines that are the most susceptible to Voltage collapse. A novel line-wise optimal power flow (LWOPF) formulation is developed based on polar LWPF and solved using successive linear programming technique. Tests show that LWOPF consistently yields a better solution than that computed using bus-wise OPF, namely in half the time. LWOPF is extended to include voltage stability constraints and implemented using both linear and nonlinear optimization techniques. It demonstrates improved performance in achieving lower cost optimal solutions with better voltage-stable states.

scholarly journals Line-Wise Power Balance Equations and Applications

2021 ◽  
Author(s):  
Amr Adel Fathy Mohamed
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Voltage Stability ◽  
Optimization Problems ◽  
Solution Space ◽  
Optimization Techniques ◽  
Power Balance ◽  
Balance Equations ◽  
Stable States ◽  
Optimal Power

Optimal power flow (OPF) refers to optimize power systems considering a chosen objective subject to a set of constraints. Existing OPF formulations used to settle electricity markets include a set of bus-wise power balance equations (PBE) that is comprised exclusively of high order terms which have sinusoidal components. Accordingly, such OPF formulations remain nonlinear and nonconvex optimization problems. Even though commercial OPF solvers are robust and efficient, they still cannot guarantee a global optimum. The US Federal Energy Regulatory Commission estimates that the best commercial OPF solvers are off by 10%, amounting to an annual loss of US $400 billion worldwide. For these motivating reasons, OPF remains a major research focus and forms the topic of this thesis. This thesis aims to: (1) develop new sets of PBE with lower order terms and lesser numbers of sinusoidal terms yielding better solution space, (2) build new OPF formulations using this new set of PBE, and (3) incorporate voltage stability constraints into the developed OPF formulations. The genesis of the new set of PBE stems from: (1) the fact that power of a constant impedance load is proportional to the square of voltage magnitude, and, (2) power flow in branches can be expressed in terms of square of voltage magnitude. Accordingly, a set of line-wise PBE is developed, both in polar and rectangular forms and are solved Newton-Raphson technique. Tests show that the proposed line-wise power flow (LWPF) algorithms are accurate, provide monotonic convergence, and scale well for large systems. The algorithms are faster comparing to classical bus-wise power flow methods. Further, the ability to directly identify the set of critical lines that are the most susceptible to Voltage collapse. A novel line-wise optimal power flow (LWOPF) formulation is developed based on polar LWPF and solved using successive linear programming technique. Tests show that LWOPF consistently yields a better solution than that computed using bus-wise OPF, namely in half the time. LWOPF is extended to include voltage stability constraints and implemented using both linear and nonlinear optimization techniques. It demonstrates improved performance in achieving lower cost optimal solutions with better voltage-stable states.

Flexible Genetic Algorithm Based Optimal Power Flow of Power Systems

2018 ◽  
Vol 24 (3) ◽  
pp. 84
Author(s):  
Hassan Abdullah Kubba ◽  
Mounir Thamer Esmieel
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Test System ◽  
Multi Objective ◽  
Optimal Power ◽  
Blending Method ◽  
Real Coded Genetic Algorithm

Nowadays, the power plant is changing the power industry from a centralized and vertically integrated form into regional, competitive and functionally separate units. This is done with the future aims of increasing efficiency by better management and better employment of existing equipment and lower price of electricity to all types of customers while retaining a reliable system. This research is aimed to solve the optimal power flow (OPF) problem. The OPF is used to minimize the total generations fuel cost function. Optimal power flow may be single objective or multi objective function. In this thesis, an attempt is made to minimize the objective function with keeping the voltages magnitudes of all load buses, real output power of each generator bus and reactive power of each generator bus within their limits. The proposed method in this thesis is the Flexible Continuous Genetic Algorithm or in other words the Flexible Real-Coded Genetic Algorithm (RCGA) using the efficient GA's operators such as Rank Assignment (Weighted) Roulette Wheel Selection, Blending Method Recombination operator and Mutation Operator as well as Multi-Objective Minimization technique (MOM). This method has been tested and checked on the IEEE 30 buses test system and implemented on the 35-bus Super Iraqi National Grid (SING) system (400 KV). The results of OPF problem using IEEE 30 buses typical system has been compared with other researches.     

Optimal TCSC placement for optimal power flow

2012 ◽  
Vol 63 (5) ◽  
pp. 316-321 ◽  
Author(s):  
Fatiha Lakdja ◽  
Fatima Zohra Gherbi ◽  
Redouane Berber ◽  
Houari Boudjella
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Models ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Flow Analysis ◽  
Test System ◽  
Facts Devices ◽  
Optimal Power ◽  
Current Transmission ◽  
Flexible Alternating Current Transmission

Very few publications have been focused on the mathematical modeling of Flexible Alternating Current Transmission Systems (FACTS) -devices in optimal power flow analysis. A Thyristor Controlled Series Capacitors (TCSC) model has been proposed, and the model has been implemented in a successive QP. The mathematical models for TCSC have been established, and the Optimal Power Flow (OPF) problem with these FACTS-devices is solved by Newtons method. This article employs the Newton- based OPF-TCSC solver of MATLAB Simulator, thus it is essential to understand the development of OPF and the suitability of Newton-based algorithms for solving OPF-TCSC problem. The proposed concept was tested and validated with TCSC in twenty six-bus test system. Result shows that, when TCSC is used to relieve congestion in the system and the investment on TCSC can be recovered, with a new and original idea of integration.

scholarly journals Probabilistic Optimal Power Flow for Day-Ahead Dispatching of Power Systems with High-Proportion Renewable Power Sources

2020 ◽  
Vol 12 (2) ◽  
pp. 518
Author(s):  
Yue Chen ◽  
Zhizhong Guo ◽  
Hongbo Li ◽  
Yi Yang ◽  
Abebe Tilahun Tadie ◽  
...  
Keyword(s):  
Power Systems ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Test System ◽  
Power Sources ◽  
Renewable Power ◽  
Point Estimate Method ◽  
Optimal Power ◽  
Simulation Results ◽  
Point Estimation Method

With the increasing proportion of uncertain power sources in the power grid; such as wind and solar power sources; the probabilistic optimal power flow (POPF) is more suitable for the steady state analysis (SSA) of power systems with high proportions of renewable power sources (PSHPRPSs). Moreover; PSHPRPSs have large uncertain power generation prediction error in day-ahead dispatching; which is accommodated by real-time dispatching and automatic generation control (AGC). In summary; this paper proposes a once-iterative probabilistic optimal power flow (OIPOPF) method for the SSA of day-ahead dispatching in PSHPRPSs. To verify the feasibility of the OIPOPF model and its solution algorithm; the OIPOPF was applied to a modified Institute of Electrical and Electronic Engineers (IEEE) 39-bus test system and modified IEEE 300-bus test system. Based on a comparison between the simulation results of the OIPOPF and AC power flow models; the OIPOPF model was found to ensure the accuracy of the power flow results and simplify the power flow model. The OIPOPF was solved using the point estimate method based on Gram–Charlier expansion; and the numerical characteristics of the line power were obtained. Compared with the simulation results of the Monte Carlo method; the point estimation method based on Gram–Charlier expansion can accurately solve the proposed OIPOPF model

scholarly journals A Combinatory Index based Optimal Reallocation of Generators in the presence of SVC using Krill Herd Algorithm

2017 ◽  
Vol 7 (1) ◽  
pp. 213-220
Author(s):  
Bali Sravana Kumar ◽  
Munugala Suryakalavathi ◽  
Gundavarapu Venkata Nagesh Kumar
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Combination Strategy ◽  
Normal Loading ◽  
Effective Utilization ◽  
Optimal Tuning ◽  
Krill Herd Algorithm ◽  
Facts Devices ◽  
Optimal Power ◽  
Krill Herd

AbstractIn the new competitive electric world, it is compulsory for the electrical industry to make effective utilization of the available resources. Optimal tuning of generators and implementation of FACTS devices has been found to be very effective in this regard. In this paper, a combination strategy of optimal tuning of generators using Krill herd (KH) algorithm in the presence of Static VAR Compensator (SVC) has been proposed. A combinatory index (CI), which is a combination of Vi/Vo index and L-index, has been formulated and verified for obtaining the optimal location of SVC. A multi objective function has been formulated for tuning the generators. The results obtained after performing Optimal Power Flow on an IEEE 30 bus system for normal loading and for severe system conditions due to line outage in the presence of SVC using KH has been verified with that of GA, to prove the effectiveness of the chosen methodology.

Sign in / Sign up

Export Citation Format

Share Document