Adaptive Energy Consumption Scheduling for Connected Microgrids Under Demand Uncertainty

Abstract

Energy consumption scheduling to achieve low-power generation cost and a low peak-to-average ratio is a critical component in distributed power networks. Implementing such a component requires the knowledge of the whole power demand throughout the network. However, due to the diversity of power demands, this requirement is not always satisfied in practical scenarios. To address this inconsistency, this paper addresses energy consumption scheduling in a distribution network with connected microgrids consisting of a local area with a determined demand and neighboring areas with an uncertain demand. The total cost and peak-to-average ratio minimizations are formulated as a multi objective optimization problem. In addition to a deterministic optimal solution, an adaptive scheduling approach is provided with online stochastic iterations to capture the randomness of the uncertain demand over time. Numerical results demonstrate the effectiveness of the proposed adaptive scheduling schemes in the following results obtained from optimal solutions.