Solving probabilistic load flow in smart distribution grids using heuristic methods

Uncertainties in smart distribution grids operation are important and challenging issues. The integration of the renewable energy resources (RERs) into the conventional distribution networks changes the radial structure of the network while its inherent characteristics such as high R/X ration of feeders remained unchanged. Conventional power flow methods may be not be suitable or efficient for smart distribution networks. This paper proposes a heuristic optimization based Probabilistic Load Flow (PLF) method to overcome new problems of future distribution networks. The proposed algorithm is suitable for any smart distribution networks with RERs. Imperialist Competitive Algorithm is used to formulate and solve the PLF considering RERs. Comparative studies with small and large sample numbers of RERs and load data are done to evaluate the effect of the samples number on the performance and simulation time. The results are compared with Monte Carlo Simulation (MCS) method. Some network parameters such as buses voltage, feeders power, and network loss in modified 33-bus network are given as Probability Density Function and compared by MCS. Based on the results the proposed algorithm can solve the PLF, regardless of the type of distribution network. (C) 2015 AIP Publishing LLC.