Distributed economic and environmental dispatch in two kinds of CCHP microgrid clusters

Abstract

Interconnected microgrids can enable mutual power support among microgrids (MGs) and improves the utilization of renewable energy sources, especially for CCHP-based (Combined Cooling, Heating, and Power) Microgrid Cluster (MGC). To preserve information privacy and achieve scheduling independence of microgrids, the problem of multi-area economic and environmental dispatch in CCHP plus MGC can be computed by distributed algorithm framework, i.e., generalized benders decomposition (GBD), optimal condition decomposition (OCD) and auxiliary problem principle (APP), respectively for interconnected topology and bus topology. Moreover, chance constrained programming (CCP) is added to address the uncertainty factors of renewable energy, cooling, heating, and electrical loads. A consensus-based distributed fair cost allocation algorithm is proposed to make a comparison with the condition of adding selfish constraints and independent operation, so that guaranteeing the stability of economic coalition of MGC. A case study with four networked CCHP microgrids in two kinds of topology is tested to demonstrate the effectiveness of the proposed approach in summer scenario. In conclusion, distributed algorithms will have a prospective application on MGC as the result of the necessity from different entities in the future.