Modern distribution power systems face more complex challenges compared to the conventional systems. A powerful technique to react to such challenges is network reconfiguration, which needs to be adapted with 'recent' concerns of modern power systems. Hence, it is essential to determine optimal configurations 'rapidly' for better time management of hour-ahead system's decision making. This paper proposes an optimization algorithm, named parallel frog migrating algorithm (PFMA), to rapidly identify the optimal system topology for hour-ahead systems operation. The significance of the proposed technique is the development of a fuzzy-based decision making unit to realistically evaluate the necessity of implementing the identified topologies. This will noticeably decrease the computational burden of system operator in analyzing the identified optimal configurations. The effectiveness of the proposed PFMA is validated on an unbalanced 136-bus distribution network containing wind turbine and photovoltaic (PV) distributed generation units (DGs). It is demonstrated that the presented PFMA is able to identify close to optimal solutions faster than the nonlinear solver of General Algebraic Modeling System (GAMS) software. More importantly, it is verified that the developed decision making mechanism effectively takes advantage of renewable DGs and reduces the necessity of network reconfiguration.
|Original language||English (US)|
|Number of pages||12|
|Journal||IEEE Transactions on Sustainable Energy|
|State||Published - Jan 2021|
All Science Journal Classification (ASJC) codes
- Renewable Energy, Sustainability and the Environment