Optimal Scheduling of a Renewable Integrated Combined Heat Power Microgrid with Energy Storage and Load Uncertainties.

Presently, several communities are employing renewable integrated combined heat-power (CHP) microgrids to optimally supply connected heat-power loads. Whilst microturbines are often employed in CHP microgrids, their operational flexibility as a CHP technology remains underexamined. The proposed work studies this perspective with acceptable penetrations of renewable energy sources (RES). Dynamic scheduling of combined heat-power islanded microgrid with RES and energy storage is presented for optimizing cost, emission, losses, and heat output considering RES and load uncertainties. RES uncertainties are modeled using Weibull distribution while load uncertainties are generated stochastically. To obtain the best solution for the contradictory multiple objectives and to reduce dependency on any specific tuning parameter, a fuzzy attainment module is integrated into the modified differential evolution algorithm with dynamic mutation rates. First, the operational flexibility of cogeneration units with RES and RES uncertainties is studied without storage. Secondly, with storage, and finally with storage under different load uncertainty scenarios. With both electrical and thermal storage, total operating costs are found to be reduced by 2.6%, emission by 1.2%, waste heat by 12.1%, and power losses by 25.4% per day. Random load scenarios in ± 25% uncertainty range were found to produce variations in cost in the range of − 2.49% to + 5.93% and emission from − 1.13 to 2.22% showing the capability of the proposed approach under practical conditions. This study demonstrates a cost-effective combined heat-power dispatch to do away with unwarranted auxiliary units with environmental, and climatic benefits. [ABSTRACT FROM AUTHOR]