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Distributed generation entities such as renewable energy sources have posed great challenges on power system economic dispatch because of their output variability and stochasticity. Accordingly, operators need to lessen unpredictable changes in scheduled generation settings by fully utilizing available forecast information in the decision-making process. This paper proposes a closed-loop algorithm for solving economic dispatch at runtime while reducing potential deviations of generation schedules. At first, a traditional centralized approach that addresses the economic dispatch problem is presented with discussions on potential enhancement enabled by model predictive control (MPC) techniques. The MPC application makes it possible for operators to address the concern of variability and stochasticity. This paper develops a dual decomposition-based distributed model predictive control (DDMPC) strategy …