Distribution systems management is becoming an increasingly complicated issue due to the introduction of new energy trading strategies and new technologies. In this paper, an optimal reinforcement strategy to provide reliable and economic service to customers in a given time frame is investigated. In the new deregulated energy market and considering the incentives coming from the political and economical fields, it is reasonable to consider distributed generation (DG) as a viable option for systems reinforcement. In the paper, the DG technology is considered as a possible solution for distribution systems capacity problems, along several years. Therefore, compound solutions comprising the installation of both feeders and substations reinforcement and DG integration at different times are considered in the formulation of a minimum cost distribution systems reinforcement strategy problem. An application on a medium size network, hypothesizing a scenario of reinforcement also using as DG gas micro-turbines, is carried out using a novel optimization technique allowing the identification of optimal paths in trees or graphs. The proposed technique is the Dynamic Ant Colony Search algorithm.
|Data di pubblicazione:||2007|
|Titolo:||Optimal Electrical Distribution Systems Reinforcement Planning Using Gas Micro Turbines by Dynamic Ant Colony Search Algorithm|
|Autori:||FAVUZZA, S; GRADITI, G; IPPOLITO, MG; RIVA SANSEVERINO, E|
|Autori interni:||IPPOLITO, Mariano Giuseppe|
RIVA SANSEVERINO, Eleonora
|Tipologia:||Articolo su rivista|
|Citazione:||FAVUZZA, S., GRADITI, G., IPPOLITO, M.G., & RIVA SANSEVERINO, E. (2007). Optimal Electrical Distribution Systems Reinforcement Planning Using Gas Micro Turbines by Dynamic Ant Colony Search Algorithm. IEEE TRANSACTIONS ON POWER SYSTEMS, 22, no.2, 580-587.|
|Digital Object Identifier (DOI):||10.1109/TPWRS.2007.894861|
|Appare nelle tipologie:||01 - Articolo su rivista|
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