Genetic Algorithms for Optimal Reactive Power Compensation of a Power System with Wind Generators based on Artificial Neural Networks

نویسندگان

  • L. Krichen
  • H. Hadj Abdallah
  • A. Ouali
چکیده

In this paper, we develop a method to maintain an acceptable voltages profile and minimization of active losses of a power system including wind generators in real time. These tasks are ensured by acting on capacitor and inductance benches implemented in the consuming nodes. To solve this problem, we minimize an objective function associated to active losses under constraints imposed on the voltages and the reactive productions of the various benches. The minimization procedure was realised by the use of genetic algorithms (GA). The major disadvantage of this technique is that it requires a significant computing time thus not making it possible to deal with the problem in real time. After a training phase, a neural model has the capacity to provide a good estimation of the voltages, the reactive productions and the losses for forecast curves of the load and the wind speed, in real time.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Optimal Locating and Sizing of Unified Power Quality Conditioner- phase Angle Control for Reactive Power Compensation in Radial Distribution Network with Wind Generation

In this article, a multi-objective planning is demonstrated for reactive power compensation in radial distribution networks with wind generation via unified power quality conditioner (UPQC). UPQC model, based on phase angle control (PAC), is used. In presented method, optimal locating of UPQC-PAC is done by simultaneous minimizing of objective functions such as: grid power loss, percentage of n...

متن کامل

Improve Estimation and Operation of Optimal Power Flow(OPF) Using Bayesian Neural Network

The future of development and design is impossible without study of Power Flow(PF), exigency the system outcomes load growth, necessity add generators, transformers and power lines in  power system. The urgency for Optimal Power Flow (OPF) studies, in addition to the items listed for the PF and in order to achieve the objective functions. In this paper has been used cost of generator fuel, acti...

متن کامل

Yarn tenacity modeling using artificial neural networks and development of a decision support system based on genetic algorithms

Yarn tenacity is one of the most important properties in yarn production. This paper addresses modeling of yarn tenacity as well as optimally determining the amounts of the effective inputs to produce yarn with desired tenacity. The artificial neural network is used as a suitable structure for tenacity modeling of cotton yarn with 30 Ne. As the first step for modeling, the empirical data is col...

متن کامل

Optimal Coordinated Voltage Control in Distribution Networks in presence of Solar and Wind Power Plants Considering Uncertainties

Abstract: In the last decade, the amount of distributed generation connected to the distribution network is increasing. The presence of distributed generation resources in distribution systems has a great influence on its behavior and it is necessary to consider the impact of these resources on the distribution network design. In this study, Optimal Coordinated Voltage Control (OCVC) using wind...

متن کامل

Presenting a New Algorithm for Determining Optimal Replaceable Capacity of Conventional Power Plants by Renewable Power Plants Based on Monte Carlo Method

Given the substitution process of generators using renewable energy sources instead of conventional generators in modern power systems, this paper proposes a Monte Carlo based method to determine an optimal level of this change. At first, LOLE index of the system was calculated without wind power to obtain the reference index. Then, the wind turbine units are replaced with the conventional gene...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007