The development of DGs will bring new changes to traditional power systems. Distributed Generation has important consequences for the operation of the distribution networks. Appropriate size and location of Distributed Generation (DG) play a significant role in minimizing power losses in Distribution Systems. This paper represents techniques to minimize power losses and improves voltage stability in a distribution feeder by optimizing DG model in terms of size, location and operating point of DG through sensitivity analysis. The methods have been developed with considering load characteristics and representing loads with constant impedance and constant current models, separately. A DG injection into the Distribution System improves the voltage profile with minimum loss. The proposed techniques have been tested on IEEE 37 bus Distribution system and TNEB 11 KV Distribution feeder.

The need for higher frequency in state estimation execution covering larger supervised networks has led to the investigation of faster and numerically more stable state estimation algorithms. However, technical developments in distributed Energy Management Systems based on fast data communication networks open up the possibility of parallel or distributed state estimation implementation. In this paper, this possibility is exploited to derive a solution methodology based on conventional WLS distributed state estimation algorithms and an Intelligent ANN technique. Numerical experiments show suitable performance of the proposed method with regard to estimation accuracy, convergence robustness and computational efficiency. The above methods are demonstrated with IEEE 37 bus Distributed Distribution system with comparison of simulated estimated outputs.

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