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.     

Application of Newton's optimal power flow in voltage/reactive power control

1990 ◽  
Vol 5 (4) ◽  
pp. 1447-1454 ◽  
Author(s):  
M. Bjelogrlic ◽  
M.S. Calovic ◽  
P. Ristanovic ◽  
B.S. Babic
Keyword(s):  
Power Control ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Reactive Power Control ◽  
Optimal Power

scholarly journals Comparative Analysis of a Performance of Metaheuristic Algorithms in Solving Optimal Power Flow Problems with UPFC Device in the Transmission System

2021 ◽  
Vol 9 (5) ◽  
pp. 316-326
Author(s):  
K. Padma ◽  
Yeshitela Shiferaw Maru
Keyword(s):  
Optimization Algorithm ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Test System ◽  
Transmission System ◽  
Voltage Profile ◽  
Proper Position ◽  
Optimal Position ◽  
Optimal Power

Incremental industrialization and urbanization is the cause of enhanced energy use as it increases the building of new lines and more inductive loads. As a result, the transmission system losses increased, and the magnitudes of voltage profile values deviated from the stated value, resulting in increased cost of active power generation. To mitigate these issues, adequate reactive power compensation in the transmission line and bus systems should be done. Reactive power is regulated by the proper position of the Flexible AC Transmission System (FACTS). Unified Power Flow Controller (UPFC) is a voltage converter system that increases the voltage profile and reduces loss. In this paper, the optimal power flow solution is considered using a FACTS device based on Multi Population Modified Jaya (MPMJ) optimization algorithm. Using the Analytical Hierarchy Process (AHP) system, the optimal position of the UPFC device is determined by considering the most useful objective function provided by priorities and weighting factors. Therefore, on the standard IEEE-57 bus test system, the proposed MPMJ optimization algorithm is implemented with UPFC for optimal fuel cost values of generation, real power loss, voltage deviation and sum of squared voltage stability index. The result obtained by the proposed algorithm is contrasted with the recent literature algorithm

scholarly journals Computational Impacts of SVCs on Optimal Power Flow using Approximated Active-Set Interior Point Algorithm

2021 ◽  
Author(s):  
Sayed Abdullah Sadat ◽  
Xinyang Rui ◽  
mostafa Sahraei-Ardakani
Keyword(s):  
Interior Point ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Optimization Problems ◽  
Interior Point Algorithm ◽  
Active Set ◽  
Computational Performance ◽  
Optimal Power ◽  
Power Dispatch

Interior point methods (IPMs) are popular and powerful methods for solving large-scale nonlinear and nonconvex optimization problems, such as AC optimal power flow (ACOPF). There are various ways to model ACOPF, depending on the objective and the physical components that need to be optimized. This paper models shunt flexible AC transmission systems (FACTS). Shunt FACTS devices such as static VAR compensators (SVCs) are sources for reactive power compensations and addressing voltage stability issues. The co-optimization of SVCs with power dispatch can impact the computational performance of ACOPF. In this paper, we evaluate the performance of different ACOPF formulations with approximated active-set interior point (AASIP) algorithm and co-optimization of SVC set points alongside other decision variables. Our numerical results suggest that both AASIP and SVCs alone improves the computation performance of almost all formulations. The gain in performance, however, depends on the sparsity of the formulation. The most spares formulation, such as branch power flow rectangular voltages (BPFRV), shows the highest gain in performance. In the event of co-optimizing SVCs with power dispatch using AASIP, the performance gain is minimal. Finally, the results are verified using various test cases ranging from 500-bus systems to 9591-bus systems.

A Probabilistic Optimal Power Flow in Wind-Thermal Coordination Considering Intermittency of the Wind

2021 ◽  
Vol 10 (1) ◽  
pp. 82-110
Author(s):  
Sriparna Banerjee ◽  
Dhiman Banerjee ◽  
Provas Kumar Roy ◽  
Pradip Kumar Saha ◽  
Goutam Kumar Panda
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Reactive Power ◽  
Optimization Techniques ◽  
Wind Energy Conversion ◽  
Optimal Power ◽  
Generation Cost ◽  
Bus Voltage ◽  
Doubly Fed ◽  
Probabilistic Nature

This article specifically aims to prove the superiority of the proposed moth swarm algorithm (MSA) in view of wind-thermal coordination. In the present article, a probabilistic optimal power flow (POPF) problem is formulated to reflect the probabilistic nature of wind. Modelling of doubly fed induction generator (DFIG) is included in the proposed POPF to represent the wind energy conversion system (WECS). To reduce DFIG imposed deviation of bus voltage ancillary reactive power support is considered. Moreover, three different optimization techniques, namely, MSA, biogeography-based optimization (BBO), and particle swarm optimization (PSO) are independently applied for the minimization of active power generation cost for wind-thermal coordination, considering different instances in case of IEEE 30-bus and IEEE 118-bus system. From the simulation results, it is confirmed and validated that the proposed MSA performs considerably better than BBO and PSO.

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