  Demand response for residential users is essential to the realization of
modern smart grids. This paper proposes a multiobjective approach to designing
a demand response program that considers the energy costs of residential users
and the load factor of the underlying grid. A multiobjective optimization
problem (MOP) is formulated and Pareto optimality is adopted. Stochastic search
methods of generating feasible values for decision variables are proposed.
Theoretical analysis is performed to show that the proposed methods can
effectively generate and preserve feasible points during the solution process,
which comparable methods can hardly achieve. A multiobjective evolutionary
algorithm is developed to solve the MOP, producing a Pareto optimal demand
response (PODR) program. Simulations reveal that the proposed method
outperforms the comparable methods in terms of energy costs while producing a
satisfying load factor. The proposed PODR program is able to systematically
balance the needs of the grid and residential users.
