A tabu-based heuristic optimization algorithm for load shedding minimization

Efficient supply and distribution of energies in the power sector is a very important issue for development. The smart grid technologies allow the distribution and production of the commodity flow so that the proper communication is maintained and optimized depending on the demand. All the demand sites will be connected to the grid and the load over each sources are to be distributed in such a way that the load is minimized per source so that they can keep some of the power as residue. The power flow is required to be maintained continuously by choosing the best path which has minimum cost and transmission loss. For this different optimization technique could be used to be finding an optimal or maximal flow path for transmission. In this paper, we propose a deterministic graph model to represent the flow in the power grid and apply tabu-based heuristic local search to find the optimal flow such that the load shedding is being minimized. We applied a number of local search algorithms on different data sets and the results shows the potential for applying such meta-heuristic algorithms to solve the problem.