  Incorporating Renewable Energy Sources (RES) incurs a high level of
uncertainties to electric power systems. This level of uncertainties makes the
conventional energy management methods inefficient and jeopardizes the security
of distribution systems. In this connection, a scenario-based stochastic
programming is introduced to harness uncertainties in the load, electricity
price, and photovoltaic generation. Further, a hybrid evolutionary algorithm
based on Grey Wolf Optimizer and Particle Swarm Optimisation algorithm is
proposed to find the best operation cost, and Energy Not Supplied (ENS) as two
important objective functions, which almost always are in stark contrast with
each other. The proposed algorithm is applied to the modified IEEE 69-bus test
system and the results are validated in terms of efficiency, which indicates a
cogent trade-off between the fitness functions addressed above.
