A Tabu Search Method for Distribution Network Planning Considering Distributed Generation and Uncertainties

This paper deals with the problem of distribution network planning (DNP) considering distributed generation (DG) and uncertainties. The involved uncertainties are the output power of wind and PV generation, the future load growth in the planning period and the evolution of the electricity prices. A Tabu search (TS)-based method with an embedded probabilistic power flow analysis is developed in order to solve the DNP optimization problem. The probabilistic power flow problem is solved by Monte Carlo Simulation (MCS). The proposed method is applied to a benchmark system and to a 30-bus distribution network considering several scenarios to demonstrate the method's performance and robustness. Simulation results show how the network planning is affected from the considered uncertainties and the optimal network is rather different in comparison to the networks designed via a conventional approach without DG integration.