A unified optimal power flow modeling for VSC-HVDC converter: a novel methodology for optimal installation based on average loadability index

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sunilkumar Agrawal ◽  
Prasanta Kundu
Keyword(s):  
Objective Function ◽  
Direct Current ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Pso Algorithm ◽  
Transmission Network ◽  
Content Type ◽  
Hvdc Transmission ◽  
Optimal Power ◽  
The Impact

Purpose This paper aims to propose a novel methodology for optimal voltage source converter (VSC) station installation in hybrid alternating current (AC)/direct current (DC) transmission networks. Design/methodology/approach In this analysis, a unified power flow model has been developed for the optimal power flow (OPF) problem for VSC-based high voltage direct current (VSC-HVDC) transmission network and solved using a particle swarm optimization (PSO) algorithm. The impact of the HVDC converter under abnormal conditions considering N-1 line outage contingency is analyzed against the congestion relief of the overall transmission network. The average loadability index is used as a severity indicator and minimized along with overall transmission line losses by replacing each AC line with an HVDC line independently. Findings The developed unified OPF (UOPF) model converged successfully with (PSO) algorithm. The OPF problem has satisfied the defined operational constraints of the power system, and comparative results are obtained for objective function with different HVDC test configurations represented in the paper. In addition, the impact of VSC converter location is determined on objective function value. Originality/value A novel methodology has been developed for the optimal installation of the converter station for the point-to-point configuration of HVDC transmission. The developed unified OPF model and methodology for selecting the AC bus for converter installation has effectively reduced congestion in transmission lines under single line outage contingency.

scholarly journals Application of the Multiverse Optimization Method to Solve the Optimal Power Flow Problem in Direct Current Electrical Networks

2021 ◽  
Vol 13 (16) ◽  
pp. 8703
Author(s):  
Andrés Alfonso Rosales-Muñoz ◽  
Luis Fernando Grisales-Noreña ◽  
Jhon Montano ◽  
Oscar Danilo Montoya ◽  
Alberto-Jesus Perea-Moreno
Keyword(s):  
Objective Function ◽  
Successive Approximation ◽  
Direct Current ◽  
Optimization Algorithm ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Flow Problem ◽  
Distributed Generators ◽  
Optimal Power ◽  
Power Flow Problem

This paper addresses the optimal power flow problem in direct current (DC) networks employing a master–slave solution methodology that combines an optimization algorithm based on the multiverse theory (master stage) and the numerical method of successive approximation (slave stage). The master stage proposes power levels to be injected by each distributed generator in the DC network, and the slave stage evaluates the impact of each power configuration (proposed by the master stage) on the objective function and the set of constraints that compose the problem. In this study, the objective function is the reduction of electrical power losses associated with energy transmission. In addition, the constraints are the global power balance, nodal voltage limits, current limits, and a maximum level of penetration of distributed generators. In order to validate the robustness and repeatability of the solution, this study used four other optimization methods that have been reported in the specialized literature to solve the problem addressed here: ant lion optimization, particle swarm optimization, continuous genetic algorithm, and black hole optimization algorithm. All of them employed the method based on successive approximation to solve the load flow problem (slave stage). The 21- and 69-node test systems were used for this purpose, enabling the distributed generators to inject 20%, 40%, and 60% of the power provided by the slack node in a scenario without distributed generation. The results revealed that the multiverse optimizer offers the best solution quality and repeatability in networks of different sizes with several penetration levels of distributed power generation.

scholarly journals Particle Swarm Optimization with Various Inertia Weight Variants for Optimal Power Flow Solution

2010 ◽  
Vol 2010 ◽  
pp. 1-15 ◽  
Author(s):  
Prabha Umapathy ◽  
C. Venkataseshaiah ◽  
M. Senthil Arumugam
Keyword(s):  
Particle Swarm Optimization ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Test System ◽  
Swarm Optimization ◽  
Inertia Weight ◽  
Optimal Power ◽  
The Impact

This paper proposes an efficient method to solve the optimal power flow problem in power systems using Particle Swarm Optimization (PSO). The objective of the proposed method is to find the steady-state operating point which minimizes the fuel cost, while maintaining an acceptable system performance in terms of limits on generator power, line flow, and voltage. Three different inertia weights, a constant inertia weight (CIW), a time-varying inertia weight (TVIW), and global-local best inertia weight (GLbestIW), are considered with the particle swarm optimization algorithm to analyze the impact of inertia weight on the performance of PSO algorithm. The PSO algorithm is simulated for each of the method individually. It is observed that the PSO algorithm with the proposed inertia weight yields better results, both in terms of optimal solution and faster convergence. The proposed method has been tested on the standard IEEE 30 bus test system to prove its efficacy. The algorithm is computationally faster, in terms of the number of load flows executed, and provides better results than other heuristic techniques.

scholarly journals Metaheuristic Optimization Methods for Optimal Power Flow Analysis in DC Distribution Networks

2020 ◽  
Vol 1 (1) ◽  
pp. 13-31
Author(s):  
Luis Fernando Grisales Noreña ◽  
Oscar Daniel Garzón Rivera ◽  
Jauder Alexander Ocampo Toro ◽  
Carlos Andres Ramos Paja ◽  
Miguel Angel Rodriguez Cabal
Keyword(s):  
Objective Function ◽  
Direct Current ◽  
Power Loss ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Flow Problem ◽  
Electrical Grid ◽  
Optimal Power ◽  
Solution Methods ◽  
Power Flow Problem

In this paper is addressed the optimal power flow problem in direct current grids, by using solution methods based on metaheuristics techniques and numerical methods. For which was proposed a mixed integer nonlinear programming problem, that describes the optimal power flow problem in direct current grids. As solution methodology was proposed a master–slave strategy, which used in master stage three continuous solution methods for solving the optimal power flow problem: a particle swarm optimization algorithm, a continuous version of the genetic algorithm and the black hole optimization method. In the slave stages was used a methods based on successive approximations for solving the power flow problem, entrusted for calculates the objective function associated to each solution proposed by the master stage. As objective function was used the reduction of power loss on the electrical grid, associated to the energy transport. To validate the solution methodologies proposed were used the test systems of 21 and 69 buses, by implementing three levels of maximum distributed power penetration: 20%, 40% and 60% of the power supplied by the slack bus, without considering distributed generators installed on the electrical grid. The simulations were carried out in the software Matlab, by demonstrating that the methods with the best performance was the BH/SA, due to that show the best trade-off between the reduction of the power loss and processing time, for solving the optimal power flow problem in direct current networks.

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 Power Flow Control on Power System Transmission Network using UPFC

2016 ◽  
Vol 33 (3) ◽  
pp. 118-125
Author(s):  
France O Akpojedje ◽  
◽  
Abel O Olomo ◽  
Emmanuel C. Mormah ◽  
Ese M Okah
Keyword(s):  
Power System ◽  
Flow Control ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Transmission Network ◽  
Power Flow Control ◽  
Optimal Power

Minimization of cost and congestion management using interline power flow controller

2016 ◽  
Vol 35 (5) ◽  
pp. 1495-1512
Author(s):  
Uma Velayutham ◽  
Lakshmi Ponnusamy ◽  
Gomathi Venugopal
Keyword(s):  
Social Welfare ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Real Power ◽  
Content Type ◽  
Optimal Power ◽  
Lower Level Problem ◽  
Level Problem ◽  
Upper Level ◽  
Power Flow Controller

Purpose The purpose of this paper is to optimally locate and size the FACTS device, namely, interline power flow controller in order to minimize the total cost and relieve congestion in a power system. This security analysis helps independent system operator (ISO) to have a better planning and market clearing criteria during any operating state of the system. Design/methodology/approach A multi-objective optimization problem has been developed including real power performance index (RPPI) and expected security cost (ESC). A security constrained optimal power flow has been developed as expected security cost optimal power flow problem which gives the probabilities of operating the system in all possible pre-contingency and post-contingency states subjected to various equality and inequality constraints. Maximizing social welfare is the objective function considered for normal state, while minimizing compensations for generations rescheduling and maximizing social welfare are the objectives in case of contingency states. The proposed work is viewed as a two level problem wherein the upper-level problem is to optimally locate IPFC using RPPI and the lower-level problem is to minimize the ESC subjected to various system constraints. Both upper-level and lower-level problem are solved using particle swarm optimization and The performance of the proposed algorithm is tested under severe line outages and has been validated using IEEE 30 bus system. Findings The proposed methodology shows that IPFC controls the power flows in the network without generation rescheduling or topological changes and thus improves the performance of the system. It is found that the benefit achieved in the ESC due to the installation of IPFC is greater than the annual investment cost of the device. ISO cannot achieve minimum total system cost by merely rescheduling generators. Instead of rescheduling, FACTS devices can be used for compensation by achieving minimum cost. IPFC can be used to compensate the congested lines and transfer cheaper power from generators to consumers. Originality/value Operational reliability, financial profitability and efficient utilization of the existing transmission system infrastructure has been achieved using single FACTS device. Instead of using multiple FATCS devices, if a single FACTS device like IPFC which itself can compensate several transmission lines is used, then in addition to the facility for independently controlled reactive (series) compensation of each individual line, it provides a capability to directly transfer real power between the compensated lines. Hence an attempt has been made in this paper to incorporate IPFC for relieving congestion in a deregulated environment. However, no previous researches have considered incorporating compensation of multi-transmission line using single IPFC in minimizing ESC. Thus, in this paper, the authors indicate how much the ESC is reduced by installing IPFC.

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