Interval method based optimal planning of multi-energy microgrid with uncertain renewable generation and demand

Abstract

Creating an optimal design for multi-energy microgrids is a challenge owing to the complicated energy flows existing between sources and demands. In addition, the uncertainties of microgrids, in particular, the stochastic problem of wind, solar, and energy demands, are difficult to describe and overcome. To address these problems, this study proposes an interval method based planning model for MEMGs that determines the device to be installed, the optimal device capacity, the optimal device placement, and the associated optimal operation of multiple energy types with considering uncertainties, the electrical power flow and heat flow equations was also included in our model. These uncertainties of renewable energy and demand are described as intervals, and based on the interval linear programming theory, the corresponding uncertain constraints could be converted to deterministic ones. The developed model is formulated as mixed-integer linear programming, which renders the design model easy to understand and compute. The feasibility and superiority of the model are verified via case studies and analyses, although the results of proposed model turn to be more conservative which means low efficiency in economy, the planning scheme is able to adapt to different uncertain scenarios and maintain the reliability of operation, which means that the robustness of the result were enhanced.