Joint energy and reserve scheduling of renewable powered microgrids accommodating price responsive demand by scenario: A risk-based augmented epsilon-constraint approach

Microgrids can effectively gather various renewable resources for increasing the profit of the system, as well as the trend toward improving energy efficiency and reducing greenhouse gas emissions. Nevertheless, the energy and reserve scheduling of microgrids will be significantly sophisticated due to the inherent uncertainty and variability of such resources. To address the operational challenges associated with these new technologies, this paper introduces an innovative stochastic cost-emission based scheme for optimal simultaneous energy and reserve scheduling of a renewable-based microgrid in the lookahead energy market aimed at maximizing social welfare of microgrid as well as minimizing environmental emissions. Besides, the time of use program is accompanied by the model to optimize the procurement costs of the microgrid. The conditional value-at-risk method is also incorporated into the problem to hedge the microgrid in confronting the risk of exposure to the uncertainty. The proposed problem is formulated as a computationally efficient multi-objective mixed-integer linear programming through augmented epsilon-constraint technique and is solved using an off-the-shelf solver. Finally, a realistic case study with the integration of renewables and energy storage devices is conducted. The results evidenced that the proposed algorithm can properly immunize microgrid against uncertainties and participation of demand-side flexibility not only significantly reduces operational costs, but also changes the dispatching patterns of controllable distributed generations and prevents non-renewable resources to be stand-by only for providing reserve. (C) 2020 Elsevier Ltd. All rights reserved.