Optimal Power Flow By Newton Approach

Sun, D.; Ashley, Bruce; Brewer, Brian; Hughes, A.; Tinney, W.F.

doi:10.1109/tpas.1984.318284

Cited by 820 publications

(169 citation statements)

References 11 publications

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“…Over the last three decades, many successful OPF techniques have been developed such as, the generalized reduced gradient method [3], linear programming solution, quadratic programming, the Newton method [4,5], the Interior Point Method (IPM). However the disadvantage of these techniques is that it is not possible to use these techniques in practical systems because of nonlinear characteristics such as valve point effects, prohibited operating zones, piecewise quadratic cost function and incorporation of FACTS devices to systems.…”

Section: Introductionmentioning

confidence: 99%

Optimal Power Flow With TCSC Device Using Cuckoo Optimization Algorithm

Long¹

2018

JST

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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.

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Section: Introductionmentioning

confidence: 99%

Optimal Power Flow With TCSC Device Using Cuckoo Optimization Algorithm

Long¹

2018

JST

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“…These methods have a problem in handling many local minima due to the non-convexity of OPF problems. Gradient-based methods overcome the convergence problem, but sometime fail to meet inequality constraints [6]. Due to the limitations of deterministic methods, evolutionary methods were introduced to remedy these…”

Section: Introductionmentioning

confidence: 99%

Optimal Power Flow Using Particle Swarm Optimization of Renewable Hybrid Distributed Generation

2017

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Abstract:The problem of voltage collapse in power systems due to increased loads can be solved by adding renewable energy sources like wind and photovoltaic (PV) to some bus-bars. This option can reduce the cost of the generated energy and increase the system efficiency and reliability. In this paper, a modified smart technique using particle swarm optimization (PSO) has been introduced to select the hourly optimal load flow with renewable distributed generation (DG) integration under different operating conditions in the 30-bus IEEE system. Solar PV and wind power plants have been introduced to selected buses to evaluate theirs benefits as DG. Different solar radiation and wind speeds for the Dammam site in Saudi Arabia have been used as an example to study the feasibility of renewable energy integration and its effect on power system operation. Sensitivity analysis to the load and the other input data has been carried out to predict the sensitivity of the results to any deviation in the input data of the system. The obtained results from the proposed system prove that using of renewable energy sources as a DG reduces the generation and operation cost of the overall power system.

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“…The EPD problem is a large-scale highly constrained nonlinear non-convex optimization problem [2]. To solve it, a number of conventional optimization techniques such as nonlinear programming (NLP) [3], quadratic programming (QP) [4], linear programming (LP) [5,6], and interior point methods [7], Newton-based method [8], mixed integer programming [9], dynamic programming [10], and branch and bound [11] have been applied. All of these mathematical methods are fundamentally based on the convexity of objective function to find the global minimum.…”

Section: Introductionmentioning

confidence: 99%

A new technique for solving the multi-objective optimization problem using hybrid approach

2014

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Energy efficiency, which consists of using less energy or improving the level of service to energy consumers, refers to an effective way to provide overall energy. But its increasing pressure on the energy sector to control greenhouse gases and to reduce CO 2 emissions forced the power system operators to consider the emission problem as a consequential matter besides the economic problems. The economic power dispatch problem has, therefore, become a multi-objective optimization problem. Fuel cost, pollutant emissions, and system loss should be minimized simultaneously while satisfying certain system constraints. To achieve a good design with different solutions in a multi-objective optimization problem, fuel cost and pollutant emissions are converted into single optimization problem by introducing penalty factor. Now the power dispatch is formulated into a bi-objective optimization problem, two objectives with two algorithms, firefly algorithm for optimization the fuel cost, pollutant emissions and the real genetic algorithm for minimization of the transmission losses. In this paper the new approach (firefly algorithm-real genetic algorithm, FFA-RGA) has been applied to the standard IEEE 30-bus 6-generator. The effectiveness of the proposed approach is demonstrated by comparing its performance with other evolutionary multiobjective optimization algorithms. Simulation results show the validity and feasibility of the proposed method.

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Optimal Power Flow By Newton Approach

Cited by 820 publications

References 11 publications

Optimal Power Flow With TCSC Device Using Cuckoo Optimization Algorithm

Optimal Power Flow With TCSC Device Using Cuckoo Optimization Algorithm

Optimal Power Flow Using Particle Swarm Optimization of Renewable Hybrid Distributed Generation

A new technique for solving the multi-objective optimization problem using hybrid approach

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