Distributed Energy Management Strategy for Reaching Cost-Driven Optimal Operation Integrated With Wind Forecasting in Multimicrogrids System

This paper considers the cost-driven optimal energy management strategy under a complex environment, multimicrogrids system. To provide the flexibility of load in depth, the heating, ventilating, and air conditioning (HVAC) load is investigated and explicitly formulated incorporated with indoor temperature dynamic function. The operation cost of wind generation includes the basic cost and additional cost to deal with the uncertainty of wind generation, which provides the tradeoff between optimality and possibility. Furthermore, the energy management problem of multimicrogrid is presented according to different characteristics of generation devices, storage devices, and load. A distributed neurodynamic algorithm is presented to solve the nonsmooth optimization of energy management of multimicrogrids system. By this method, the only information exchanged among microgrids is the intermediate variable when computing. The simulation results validate the effectiveness of the proposed cost-driven energy management strategy.