Based on Improvement Immunity Algorithm Electrical Power System Optimal Power Flow Computation

2013 ◽  
Vol 278-280 ◽  
pp. 1314-1317
Author(s):  
Li Xiao
Keyword(s):  
Power System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Electrical Power ◽  
Point System ◽  
Electrical Power System ◽  
Optimal Power ◽  
System Optimal ◽  
Comprehensive Search ◽  
Introduction Vector

Proposed one kind of improvement artificial immunization algorithm calculates the electrical power system most superior tidal current, this algorithm maintained the basic immunity algorithm comprehensive search ability, also the concept which is apart from through the introduction vector causes the immunity algorithm theoretically to guarantee the understanding the multiplicity. Through the IEEE-30pitch point system computed result indicated this algorithm is feasible. And so on compares with the heredity algorithm, this algorithm overall situation search ability strong, the convergence rate is quick.

scholarly journals LP based solution for Security Constrained Optimal Power Flow including Power Routers

2020 ◽  
Vol 15 ◽  
Keyword(s):  
Power System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Electrical Power ◽  
Flow Analysis ◽  
Time Frame ◽  
Electrical Power System ◽  
Piecewise Linearization ◽  
Dc Power ◽  
Optimal Power

Power Routers offers many benefits to the power system, it helps in improving the existing transmission asset utilization. Security Constrained Optimal Power Flow (SCOPF) is becoming more important in the electrical power system especially in the present deregulated environment. This paper focuses on completely linearizing the complex non-linear SCOPF problem. The objective function is linearized using Piecewise linearization technique and the constraints are framed using linear sensitivity factors. A formal extension is made to the traditional SCOPF by including power router control in the post contingency time frame. DC power flow analysis is used to calculate the real power flow in the lines.Thus, in this paper, further minimization of cost is achieved by using Power Router control and it is compared with the conventional SCOPF.

scholarly journals HEURISTIC METHODE FOR OPTIMIZING POWER LOAD FLOW ANALYSIS IN ELECTRICAL POWER SYSTEM

2010 ◽  
Vol 13 (2) ◽  
pp. 36-45
Author(s):  
Anh Huy Quyen ◽  
Anh Viet Truong ◽  
Huong Thi Thanh Vi
Keyword(s):  
Power System ◽  
Optimal Power Flow ◽  
Electrical Power ◽  
Flow Analysis ◽  
Load Flow ◽  
Electrical Power System ◽  
Large Power ◽  
Load Flow Analysis ◽  
Optimal Power ◽  
Power Load

The primary goal of a generic optimal power load flow problem Is minimizing total fuel costs of generating units in an electrical power system while maintaining the security of the system. This paper presents an algorithm for optimizing power load flow analysis through the application of Newton ’s method and attends to interchange power between the different power systems. Specifically, it will explore the implementation of data structure such as the binary tree in searching OPF variables (controls, states, constraints) in large power system. So the OPF solution is quickly converging. The primary goal of a generic OFF has been tested by simulation method for 6- bus system in Power World environment. The optimal power flow results is shown that total generation fuel cost in the interchange power case is less expensive than in no interchange power case as well as total transmission losses in the power system are smaller.

scholarly journals Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods

2020 ◽  
Vol 34 (01) ◽  
pp. 630-637 ◽  
Author(s):  
Ferdinando Fioretto ◽  
Terrence W.K. Mak ◽  
Pascal Van Hentenryck
Keyword(s):  
Deep Learning ◽  
Power Systems ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Large Scale ◽  
Renewable Energy Sources ◽  
Electrical Power ◽  
Practical Applications ◽  
Fundamental Building Block ◽  
Optimal Power

The Optimal Power Flow (OPF) problem is a fundamental building block for the optimization of electrical power systems. It is nonlinear and nonconvex and computes the generator setpoints for power and voltage, given a set of load demands. It is often solved repeatedly under various conditions, either in real-time or in large-scale studies. This need is further exacerbated by the increasing stochasticity of power systems due to renewable energy sources in front and behind the meter. To address these challenges, this paper presents a deep learning approach to the OPF. The learning model exploits the information available in the similar states of the system (which is commonly available in practical applications), as well as a dual Lagrangian method to satisfy the physical and engineering constraints present in the OPF. The proposed model is evaluated on a large collection of realistic medium-sized power systems. The experimental results show that its predictions are highly accurate with average errors as low as 0.2%. Additionally, the proposed approach is shown to improve the accuracy of the widely adopted linear DC approximation by at least two orders of magnitude.

Comparative analysis of a new VSC‐optimal power flow formulation for power system security planning

2020 ◽  
Vol 30 (3) ◽  
Author(s):  
Oludamilare Bode Adewuyi ◽  
Harun Or Rashid Howlader ◽  
Isaiah Opeyemi Olaniyi ◽  
David Abdul Konneh ◽  
Tomonobu Senjyu
Keyword(s):  
Comparative Analysis ◽  
Power System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
System Security ◽  
Power System Security ◽  
Optimal Power ◽  
Security Planning
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