Abstract:

The extensive penetration of renewable resources and utilizing advanced energy management techniques as well as enabling demand response programs (DRPs), especially in microgrids and active distribution networks, has had an impressive impact on the operation of such grids. Thus, with respect to the active and influential role of distribution grids in the restructured environment and the objective of achieving optimal operation of microgrids, energy management in this new environment requires more comprehensive analytic studies and rigorous researches. In this regard, the present research proposes a new strategy of optimal energy management and the subsequent day-ahead scheduling of a microgrid in the presence of micro compressed air energy storage (MCAES) and considering the uncertainties of renewable energy resources. The minimization of operation costs of energy storage facilities, environmental emission, the costs corresponded with the energy not supplied (ENS) and excess generation capacity are the main objectives of this study while the load satisfaction constraints are imposed. The technical constraints of distributed generation resources and energy storage facilities are imposed on this optimization problem. Besides, the execution of demand-side management programs is modelled to flatten the demand curve and to close the operational condition on the most optimum point. Employing the teaching-learning-based optimization (TLBO) algorithm, the proposed method is simulated for a test microgrid. The simulation’s results show that the utilization of MCAES facilities and executing DRPs have been concluded to the mitigation of generation cost, alleviation of emission, and reduction of ENS and excess generation capacity of the microgrid.

Keywords: