<span>Distributed generation (DG) is an essential attributor in smart grid to fulfill the uncontrollable increase in the demand for energy. Artificial intelligent optimization techniques are widely used within automation systems for guarantee the optimal operation and utilization of DG allocation on the day-ahead power scheduling. In this paper, the genetic algorithm technique used for obtaining the optimal utilization of the automated operation of distributed generation for power losses and total cost minimization as well as user comfort maximization considering all operating constraints technique. Distributed generation represented by fuel cells to supply part of the daily demand in the power system. The target is to apply decision-making strategy of smart operation for economical and reliable operation of power system. Concentrated fuel cell units considered representing the available DG at the load centers. The methodology applied to the 11-bus test system. The simulation results have demonstrated that the GA capability for full automation of DGs in a smart manner within the power system for economic and safe operation</span>
With the increasing penetration of market driven distributed resources, namely decentralised generation, in the distribution networks, the operations become increasingly challenging. From the perspective of the DSO, it is of utmost importance to develop the right tools to deal with these challenges, in order to maintain secure, stable and efficient operation of the network, while assuming the role of market facilitator providing data to the market players. The architecture developed in the Upgrid Portuguese Demo will connect prosumers, retailers and the DSO, in order to allow an integrated management and operation of the electric grid with all these actors and the associated resources, thus enabling the growth of decentralised generation and distributed energy resources.
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