Optimal energy management system for future microgrids with tight operating constraints

This paper presents a flexible energy optimizer for microgrids and virtual power plants, which can determine the optimal schedules of controllable Distributed Generators (DGs) and Battery Storage Systems (BSS). The optimization problem consists of both technical and economic aspects regarding network, DGs and BSS characteristics and restrictions. An enhanced mixed integer linear programming (MILP) method is applied to solve the unit commitment and economic dispatch problem. The proposed tool is able to attempt different strategies for fixing voltage violations and reducing losses in the grid on top of performing optimized scheduling of DGs and BSS. The functionality and effectiveness of the proposed approach is evaluated by selected case studies in the end. Results indicate that the tool can find promising solutions for highly constrained problems during microgrid operation. Finally, a comparison and validation effort against another optimization tool based on genetic algorithm will be executed.