Quadratic programming approach for security constrained optimal power flow

Wibowo, Rony Seto; Maulana, Rendhi; Taradini, Annisaa; Pamuji, Feby Agung; Soeprijanto, Adi; Penangsang, Ontoseno

doi:10.1109/iciteed.2015.7408941

Cited by 10 publications

(4 citation statements)

References 4 publications

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“…Although the SCOPF still faces challenges related to computations, it is expected that it eventually become a standard tool in the electricity market [7]. Various mathematical programming solutions have been proposed to solve the SCOPF problem such as iterative approach [8], Benders decomposition approach [9], linear programming [10], quadratic programming [11], and interior point method [12]. Recently, many Artificial Intelligence algorithms have been proposed for solving optimization problems in power system [13][14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Application of Sunflower Optimization Algorithm for Solving the Security Constrained Optimal Power Flow Problem

Duong

Nguyen

2020

Eng. Technol. Appl. Sci. Res.

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Finding the Optimal Power Flow (OPF) which minimizes total generator cost is the answer to one of the most important problems in the electricity market operation. Independent System Operators (ISO) face many challenges while operating the system in order to obtain economic benefits and security. The solution to this problem is known as Security Constrained Optimal Power Flow (SCOPF). SCOPF is a very large-scale and nonlinear optimization problem with many complex constraints. This paper proposes the Sunflower Optimization (SFO) algorithm for solving the SCOPF problem. The proposed method is tested on the IEEE 30-bus and the IEEE 118-bus systems for both normal and outage cases. The result comparison with other known methods showed that the proposed SFO algorithm is an effective method for solving the SCOPF problem in the electricity market.

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Section: Introductionmentioning

confidence: 99%

Application of Sunflower Optimization Algorithm for Solving the Security Constrained Optimal Power Flow Problem

Duong

Nguyen

2020

Eng. Technol. Appl. Sci. Res.

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“…There are many approaches to finding a solution and they can be classified as conventional and heuristic/intelligent approaches. The conventional approaches include the interior point method [10,11], non-linear programming [12,13], quadratic programming [14,15], gradient based method, Newton method [16], sequential unconstrained minimization technique [17] and the alternating direction method of multipliers [8]. The conventional methods though very reliable can sometimes be entrapped in the local minimum of the solution thereby not realizing the global minimum value of the objective function [6].…”

Section: Introductionmentioning

confidence: 99%

Archives of Electrical Engineering

Suresh,

Janik,

Jasinski

2020

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This paper presents the application of an improved ant colony optimization algorithm called mixed integer distributed ant colony optimization to optimize the power flow solution in power grids. The results provided indicate an improvement in the reduction of operational costs in comparison with other optimization algorithms used in optimal power flow studies. The application was realized to optimize power flow in the IEEE 30 and the IEEE 57 bus test cases with the objective of operational cost minimization. The optimal power flow problem described is a non-linear, non-convex, complex and heavily constrained problem.

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“…For many years, classical programming methods are used to solve OPF such us Gradient method [1,2] linear programming (LP) and non linear programming (NLP) [3,4], in the literature we find also Newton methods [5][6][7][8][9][10] and quadratic programming (QP) [11,12]. As these methods have proven their efficiency, They have been vastly applied to several Optimal Power Flow problems.…”

Section: Introductionmentioning

confidence: 99%

Modified Flower Pollination Algorithm Constrained Optimal Power Flow

Hocine¹,

Salem²

2019

ISI

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In power systems, the power flow must satisfy a set of operational and safety requirements. It is a highly nonlinear problem to optimize the power flow. In this paper, the flower pollination algorithm (FPA) is modified and applied to optimize the power flow. Firstly, the author set up a mathematical model for power flow optimization problem, and formulated all the constraints. Next, the FPA was introduced in details, including the self-pollination, cross-pollination and other operations. After that, the local search strategy of the FPA was modified to replace the worst individuals in the current population with the best individuals in the previous population. Finally, the modified FPA (MFPA) was proved more efficient and better in convergence than standard algorithms like the firefly algorithm.

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Quadratic programming approach for security constrained optimal power flow

Cited by 10 publications

References 4 publications

Application of Sunflower Optimization Algorithm for Solving the Security Constrained Optimal Power Flow Problem

Application of Sunflower Optimization Algorithm for Solving the Security Constrained Optimal Power Flow Problem

Archives of Electrical Engineering

Modified Flower Pollination Algorithm Constrained Optimal Power Flow

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