Probabilistic energy management with emission of renewable micro-grids including storage devices based on efficient salp swarm algorithm.

In this paper, the efficient salp swarm algorithm (ESSA) is proposed to solve the energy management (EM) with emission problem of renewable micro-grid (MG) including storage devices. Because of the uncertainties in the renewable energy sources (RESs), load demand and market prices, the probabilistic approach based on (2m + 1) point estimate method and ESSA is employed to solve the probabilistic EM problem. The proposed ESSA can be derived by introducing two modifications on the conventional salp swarm algorithm (SSA) to improve the balance between exploration and exploitation, speed up the convergence and avoiding the stuck in local optima of the SSA. The ESSA is employed to solve the deterministic and probabilistic EM with emission problem. Where the multi-objective optimization problem of cost and emission functions is transferred into a single objective function to minimize the total operating cost of the MG. The proposed ESSA is evaluated using a typical grid-connected MG with energy storage devices and compared with other methods. The results verify the superiority of the ESSA to solve the EM problem of the MG over other methods. • The probabilistic approach based on ESSA and point estimate method is proposed. • The proposed method is used to solve the deterministic and probabilistic EM of MG. • The EM problem considers minimization of cost and emission as a single problem. • The proposed method has been evaluated using a typical MG with different scenarios. • Results of all cases show the superiority of the proposed method over other methods. [ABSTRACT FROM AUTHOR]