scholarly journals An application of energy efficiency programs on multi-stage transmission network expansion and reactive power planning

2020 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
Amin Mahmoudabadi ◽  
M. Rashidinejad ◽  
amir abdollahi
Keyword(s):  
Energy Efficiency ◽  
Reactive Power ◽  
Transmission Network ◽  
Network Expansion ◽  
Multi Stage ◽  
Reactive Power Planning

scholarly journals A New Model for Transmission Network Expansion and Reactive Power Planning in a Deregulated Environment

Engineering ◽  
2012 ◽  
Vol 04 (02) ◽  
pp. 119-125
Author(s):  
Amin Mahmoudabadi ◽  
Masoud Rashidinejad ◽  
Majid Zeinaddini-Maymand
Keyword(s):  
Reactive Power ◽  
Transmission Network ◽  
New Model ◽  
Network Expansion ◽  
Reactive Power Planning

A Multi-Stage Stochastic Non-Linear Model for Reactive Power Planning Under Contingencies

2013 ◽  
Vol 28 (2) ◽  
pp. 1503-1514 ◽  
Author(s):  
Julio Cesar Lopez ◽  
Javier Contreras ◽  
Jose I. Munoz ◽  
J. R. S. Mantovani
Keyword(s):  
Linear Model ◽  
Reactive Power ◽  
Multi Stage ◽  
Non Linear ◽  
Reactive Power Planning

scholarly journals Multi-Stage Dynamic Transmission Network Expansion Planning Using LSHADE-SPACMA

2021 ◽  
Vol 11 (5) ◽  
pp. 2155
Author(s):  
Mohamed M. Refaat ◽  
Shady H. E. Abdel Aleem ◽  
Yousry Atia ◽  
Ziad M. Ali ◽  
Mahmoud M. Sayed
Keyword(s):  
Fuzzy Inference ◽  
Optimization Problems ◽  
Planning Problem ◽  
Transmission Network ◽  
Inference System ◽  
Network Expansion ◽  
Expansion Planning ◽  
Covariance Matrix Adaptation ◽  
Transmission Expansion ◽  
Multi Stage

This paper introduces a multi-stage dynamic transmission network expansion planning (MSDTNEP) model considering the N-1 reliability constraint. The integrated planning problem of N-1 security and transmission expansion planning is essential because a single line outage could be a triggering event to rolling blackouts. Two suggested scenarios were developed to obtain the optimal configuration of the Egyptian West Delta Network’s realistic transmission (WDN) to meet the demand of the potential load growth and ensure the system reliability up to the year 2040. The size of a blackout, based on the amount of expected energy not supplied, was calculated to evaluate both scenarios. The load forecasting (up to 2040) was obtained based on an adaptive neuro-fuzzy inference system because it gives excellent results compared to conventional methods. The linear population size reduction—Success-History-based Differential Evolution with semi-parameter adaptation (LSHADE-SPA) hybrid—covariance matrix adaptation evolution strategy (CMA-ES) algorithm (LSHADE-SPACMA)—is proposed to solve the problem. The semi-adaptive nature of LSHADE-SPACMA and the hybridization between LSHADE and CMA-ES are able to solve complex optimization problems. The performance of LSHADE-SPACMA in solving the problem is compared to other well-established methods using three testing systems to validate its superiority. Then, the MSDTNEP of the Egyptian West Delta Network is presented, and the numerical results of the two scenarios are compared to obtain an economic plan and avoid a partial or total blackout.

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