Transmission expansion planning based on merchandizing surplus of transmission lines

2015 ◽  
Author(s):  
Iman Ehsani ◽  
Alireza Soofiabadi
Keyword(s):  
Transmission Lines ◽  
Expansion Planning ◽  
Transmission Expansion Planning ◽  
Transmission Expansion

scholarly journals Transmission Expansion Planning Considering Wind Energy Conversion Systems Using PSO

2019 ◽  
Vol 8 (6S3) ◽  
pp. 761-766
Keyword(s):  
Transmission Lines ◽  
Planning Horizon ◽  
Test System ◽  
Distribution Functions ◽  
Wind Generation ◽  
Monte Carlo Simulation Study ◽  
Expansion Planning ◽  
Transmission Expansion Planning ◽  
Transmission Expansion ◽  
Energy Conversion Systems

In power system studies the most important issue is Transmission Expansion Planning (TEP). The intend of TEP problem is to choose the placement as well as number of additional transmission lines, which are to be added to the existing system to suit growing demand in planning horizon. In this paper a new methodology for TEP is proposed, the presented Transmission planning is linked with generation cost, active power loss minimization by considering wind uncertainties. Firstly, the uncertainties involved in wind generation can be determined by using weigbull probability functions. Monte Carlo simulation study is able to be used to find the probability distribution functions of wind generation. Then, in TEP formulation the WTG uncertainties are considered. Particle swarm optimization (PSO) technique is used for solving the proposed single objective optimization problem. Simulation studies conducted on an IEEE 30 bus test system to certify effectiveness of the TEP problem with considering wind uncertainties.

scholarly journals Metaheuristics and Transmission Expansion Planning: A Comparative Case Study

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3618
Author(s):  
Hamdi Abdi ◽  
Mansour Moradi ◽  
Sara Lumbreras
Keyword(s):  
Transmission Lines ◽  
Standard Test ◽  
Comparative Case Study ◽  
Computational Time ◽  
Stochastic Decomposition ◽  
Grey Wolf Optimizer ◽  
Expansion Planning ◽  
Transmission Expansion Planning ◽  
Transmission Expansion ◽  
Classical Optimization

Transmission expansion planning (TEP), the determination of new transmission lines to be added to an existing power network, is a key element in power system planning. Using classical optimization to define the most suitable reinforcements is the most desirable alternative. However, the extent of the under-study problems is growing, because of the uncertainties introduced by renewable generation or electric vehicles (EVs) and the larger sizes under consideration given the trends for higher renewable shares and stronger market integration. This means that classical optimization, even using efficient techniques, such as stochastic decomposition, can have issues when solving large-sized problems. This is compounded by the fact that, in many cases, it is necessary to solve a large number of instances of a problem in order to incorporate further considerations. Thus, it can be interesting to resort to metaheuristics, which can offer quick solutions at the expense of an optimality guarantee. Metaheuristics can even be combined with classical optimization to try to extract the best of both worlds. There is a vast literature that tests individual metaheuristics on specific case studies, but wide comparisons are missing. In this paper, a genetic algorithm (GA), orthogonal crossover based differential evolution (OXDE), grey wolf optimizer (GWO), moth–flame optimization (MFO), exchange market algorithm (EMA), sine cosine algorithm (SCA) optimization and imperialistic competitive algorithm (ICA) are tested and compared. The algorithms are applied to the standard test systems of IEEE 24, and 118 buses. Results indicate that, although all metaheuristics are effective, they have diverging profiles in terms of computational time and finding optimal plans for TEP.

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