scholarly journals Decomposed Iterative Optimal Power Flow with Automatic Regionalization

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4987
Author(s):  
Xinhu Zheng ◽  
Dongliang Duan ◽  
Liuqing Yang ◽  
Haonan Wang
Keyword(s):  
Power System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Large Scale ◽  
Optimization Techniques ◽  
Test Cases ◽  
Global Optimality ◽  
Large Scale Systems ◽  
Optimal Power ◽  
And Control

The optimal power flow (OPF) problem plays an important role in power system operation and control. The problem is nonconvex and NP-hard, hence global optimality is not guaranteed and the complexity grows exponentially with the size of the system. Therefore, centralized optimization techniques are not suitable for large-scale systems and an efficient decomposed implementation of OPF is highly demanded. In this paper, we propose a novel and efficient method to decompose the entire system into multiple sub-systems based on automatic regionalization and acquire the OPF solution across sub-systems via a modified MATPOWER solver. The proposed method is implemented in a modified solver and tested on several IEEE Power System Test Cases. The performance is shown to be more appealing compared with the original solver.

scholarly journals Customized Sequential Quadratic Programming for Solving Large-Scale AC Optimal Power Flow

2021 ◽  
Author(s):  
Sayed Abdullah Sadat ◽  
mostafa Sahraei-Ardakani
Keyword(s):  
Quadratic Programming ◽  
Sequential Quadratic Programming ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Large Scale ◽  
Optimization Problems ◽  
Test Cases ◽  
Time Limits ◽  
Optimal Power ◽  
Wide Range

After decades of research, efficient computation of AC Optimal Power Flow (ACOPF) still remains a challenge. ACOPF is a nonlinear nonconvex problem, and operators would need to solve ACOPF for large networks in almost real-time. Sequential Quadratic Programming (SQP) is one of the powerful second-order methods for solving large-scale nonlinear optimization problems and is a suitable approach for solving ACOPF with large-scale real-world transmission networks. However, SQP, in its general form, is still unable to solve large-scale problems within industry time limits. This paper presents a customized Sequential Quadratic Programming (CSQP) algorithm, taking advantage of physical properties of the ACOPF problem and the choice of the best performing ACOPF formulation. The numerical experiments suggest that CSQP outperforms commercial and noncommercial nonlinear solvers and solves test cases within the industry time limits. A wide range of test cases, ranging from 500-bus systems to 30,000-bus systems, are used to verify the test results.

scholarly journals Customized Sequential Quadratic Programming for Solving Large-Scale AC Optimal Power Flow

2021 ◽  
Author(s):  
Sayed Abdullah Sadat ◽  
mostafa Sahraei-Ardakani
Keyword(s):  
Quadratic Programming ◽  
Sequential Quadratic Programming ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Large Scale ◽  
Optimization Problems ◽  
Test Cases ◽  
Time Limits ◽  
Optimal Power ◽  
Wide Range

After decades of research, efficient computation of AC Optimal Power Flow (ACOPF) still remains a challenge. ACOPF is a nonlinear nonconvex problem, and operators would need to solve ACOPF for large networks in almost real-time. Sequential Quadratic Programming (SQP) is one of the powerful second-order methods for solving large-scale nonlinear optimization problems and is a suitable approach for solving ACOPF with large-scale real-world transmission networks. However, SQP, in its general form, is still unable to solve large-scale problems within industry time limits. This paper presents a customized Sequential Quadratic Programming (CSQP) algorithm, taking advantage of physical properties of the ACOPF problem and the choice of the best performing ACOPF formulation. The numerical experiments suggest that CSQP outperforms commercial and noncommercial nonlinear solvers and solves test cases within the industry time limits. A wide range of test cases, ranging from 500-bus systems to 30,000-bus systems, are used to verify the test results.

scholarly journals OPTIMAL POWER FLOW WITH TCSC DEVICE USING CUCKOO OPTIMIZATION ALGORITHM

2018 ◽  
Vol 54 (3A) ◽  
pp. 52
Author(s):  
Duong Thanh Long
Keyword(s):  
Power System ◽  
Optimization Algorithm ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Power Transmission ◽  
Optimization Techniques ◽  
Operating Conditions ◽  
Cuckoo Optimization Algorithm ◽  
Facts Devices ◽  
Optimal Power

Optimal Power Flow (OPF) problem is an optimization tool through which secure and economic operating conditions of power system is obtained. In recent years, Flexible AC Transmission System (FACTS) devices, have led to the development of controllers that provide controllability and flexibility for power transmission. Series FACTS devices such as Thyristor controlled series compensators (TCSC), with its ability to directly control the power flow can be very effective to power system security. Thus, integration TCSC in the OPF is one of important current problems and is a suitable method for better utilization of the existing system. This paper is applied Cuckoo Optimization Algorithm (COA) for the solution of the OPF problem of power system equipped with TCSC. The proposed approach has been examined and tested on the IEEE 30-bus system. The results presented in this paper demonstrate the potential of COA algorithm and show its effectiveness for solving the OPF problem with TCSC devices over the other evolutionary optimization techniques.

An Optimizer-Tool-Based Improved Metaheuristic Method for Solving Security Optimal Power Flow

2018 ◽  
pp. 191-226
Author(s):  
Belkacem Mahdad
Keyword(s):  
Power System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Power System Planning ◽  
System Planning ◽  
Planning And Control ◽  
Optimal Power ◽  
Interactive Tool ◽  
Metaheuristic Methods ◽  
And Control

In this chapter, an interactive tool using graphic user interface (GUI) environment-based MATLAB is proposed to solve practical optimal power system planning and control. The main particularity of the proposed tool is to assist student and researchers understanding the mechanism search of new metaheuristic methods. The proposed tool allows users to interact dynamically with the program. The users (students or experts) can set parameters related to a specified metaheuristic method to clearly observe the effect of choosing parameters on the solution quality. In this chapter, a new global optimization method named grey wolf optimizer (GWO) and pattern search algorithm (PS) have been successfully applied within the interactive tool to solve the optimal power flow problem. The robustness of the two proposed metaheuristic methods is validated on many standard power system tests. The proposed interactive optimal power flow tool is expected to be a useful support for students and experts specialized in power system planning and control.

scholarly journals An Efficient Hybrid Method for Solving Security-Constrained Optimal Power Flow Problem

2020 ◽  
Vol 12 (4) ◽  
pp. 933-955
Author(s):  
Phuong Minh Le ◽  
◽  
Thanh Long Duong ◽  
Dieu Ngoc Vo ◽  
Tung Thanh Le ◽  
...  
Keyword(s):  
Power System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Large Scale ◽  
Flow Problem ◽  
Optimal Operation ◽  
Optimal Power ◽  
Gradient Based ◽  
Constriction Factor ◽  
Power Flow Problem

The optimal operation for different states such as normal and contingency cases of a power system has a very important role in the operation. Therefore, it is necessary to analyze contingencies in the system so as the most severe cases should be considered for integrating into the optimal power flow (OPF) problem and the security-constrained optimal power flow (SCOPF) becomes an important problem for considering in the power system operation. This paper proposes a combined pseudo-gradient based particle swarm optimization with constriction factor (PGPSO) and the differential evolution (DE) method for solving the SCOPF problem. The PGPSO-DE method is a newly developed method for utilizing the advantages of the pseudogradient guided PSO method with a constriction factor and the DE method. The proposed PGPSO-DE has been tested on the IEEE 30 bus system for the normal case and the contingency case with two types of the objective function. The results yielded from the proposed method have been validated via comparing to those from the conventional PSO, DE, and other methods reported in the literature. The comparisons for the results obtained from the proposed PGPSODE method have shown that it is very effective to solve the large-scale and complex SCOPF problem.

scholarly journals A Generic Approach for Solving Nonlinear-Discrete Security-Constrained Optimal Power Flow Problems in Large-Scale Systems

2014 ◽  
Vol 29 (3) ◽  
pp. 1194-1203 ◽  
Author(s):  
Ludovic Platbrood ◽  
Florin Capitanescu ◽  
Christian Merckx ◽  
Horia Crisciu ◽  
Louis Wehenkel
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Large Scale ◽  
Large Scale Systems ◽  
Flow Problems ◽  
Optimal Power
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