Multi-objective multi-stage transmission network expansion planning considering life cycle cost and risk value under uncertainties

2012 ◽  
Vol 23 (3) ◽  
pp. 438-450 ◽  
Author(s):  
Lu Liu ◽  
Hao-zhong Cheng ◽  
Liang-zhong Yao ◽  
Ze-liang Ma ◽  
Masoud Bazargan
Keyword(s):  
Life Cycle ◽  
Life Cycle Cost ◽  
Transmission Network ◽  
Network Expansion ◽  
Multi Objective ◽  
Expansion Planning ◽  
Multi Stage

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.

Research on Maintenance Model of Main Equipment Based on UMM

2014 ◽  
Vol 488-489 ◽  
pp. 1277-1280
Author(s):  
Shi Cong Deng ◽  
Ding Yao Xiao ◽  
Lin Fa Li ◽  
Wei Zhao Huang
Keyword(s):  
Decision Making ◽  
Life Cycle ◽  
Life Cycle Cost ◽  
Maintenance Strategy ◽  
Practical Applications ◽  
Multi Objective ◽  
Operation And Maintenance ◽  
Multi Stage ◽  
Decision Making Model ◽  
Maintenance Model

In this paper the problems of traditional operation maintenance strategy is introduced. Uncertain multi-stage and multi-objective decision-making model of operation and maintenance is shown in this paper. Considering the life cycle cost, the best maintenance scheme is determined through the establishment of an uncertain multi-stage and multi-objective decision-making model of operation and maintenance. It also proves the practical applications of UMM model by GIS example.

scholarly journals Flexible Transmission Network Expansion Planning Based on DQN Algorithm

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1944
Author(s):  
Yuhong Wang ◽  
Lei Chen ◽  
Hong Zhou ◽  
Xu Zhou ◽  
Zongsheng Zheng ◽  
...  
Keyword(s):  
Test System ◽  
Transmission Network ◽  
Adaptive Planning ◽  
Network Expansion ◽  
Expansion Planning ◽  
Multi Stage ◽  
Fault Severity ◽  
Experience Replay ◽  
Speed Up ◽  
Expansion Scheme

Compared with static transmission network expansion planning (TNEP), multi-stage TNEP is more in line with the actual situation, but the modeling is also more complicated. This paper proposes a new multi-stage TNEP method based on the deep Q-network (DQN) algorithm, which can solve the multi-stage TNEP problem based on a static TNEP model. The main purpose of this research is to provide grid planners with a simple and effective multi-stage TNEP method, which is able to flexibly adjust the network expansion scheme without replanning. The proposed method takes into account the construction sequence of lines in the planning and completes the adaptive planning of lines by utilizing the interactive learning characteristics of the DQN algorithm. In order to speed up the learning efficiency of the algorithm and enable the agent to have a better judgment on the reward of the line-building action, the prioritized experience replay (PER) strategy is added to the DQN algorithm. In addition, the economy, reliability, and flexibility of the expansion scheme are considered in order to evaluate the scheme more comprehensively. The fault severity of equipment is considered on the basis of the Monte Carlo method to obtain a more comprehensive system state simulation. Finally, extensive studies are conducted with IEEE 24-bus reliability test system, and the computational results demonstrate the effectiveness and adaptability of the proposed flexible TNEP method.

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