Distributed generation aggregators considering low-carbon credits optimize dispatch strategies

Abstract

Abstract Against the backdrop of China’s implementation of the “dual carbon” target and carbon emissions trading policies, renewable energy generation technologies have matured and received support from related policies. Distributed power sources have played a crucial role in the power system, and aggregators have integrated a large number of distributed power sources with diverse characteristics, shielding the complex characteristics of the underlying distributed power sources from grid scheduling. This article introduces the revenue optimization of low-carbon integration to optimize the aggregator’s scheduling model, designs distributed renewable energy generation units, and studies the solution strategy based on quantum genetic algorithms for large-scale optimization scheduling problems. The aggregator’s optimization variables divide the entire optimization problem and consider low-carbon integration to achieve distributed management of green energy parks, providing a feasible theoretical framework for the further development of distributed power sources. It has important practical significance in energy conservation, emissions reduction, and ecological environmental protection.