Distributed energy systems: Multi-objective optimization and evaluation under different operational strategies

In recent years, distributed energy systems (DES) have received an extensive attention, but they also face technical limitations in system architecture, operational strategies, and optimization methods. In this paper, for two typical DES, Natural Gas Cooling and Heating Triple Supply System (CCHP) and Hybrid Energy Distributed System (HDES), multi-objective optimization and evaluation have been carried out. In the optimization phase, for the two systems, a multi-objective mathematical programming (MOMP) model was developed to minimize the annual total cost and annual carbon emissions under three different operational strategies (heat load following (FTL), electrical load following (FEL), and load characteristic matching following (FCL)). Further, operational strategies were transformed into operational constraints, and models were solved using the augmented epsilon-constrain method. In the evaluation stage, the reference cost growth rate (CSR) and the reference CO2 emission reduction rate (CRR) evaluation indices were developed, and subsequently for two DES systems, comprehensive evaluations were conducted by incorporating with the weight distributed TOPSIS multi-objective decision-making method. Moreover, an office building in Nanjing was chosen as the baseline building, and the two DES systems were simulated. The results show that, under different operating strategies, CCHP has the advantage of lower cost, while the HDES has the advantage of the lower CO2 emission. Under the proposed FCL operation strategy, the maximum environmental benefits can be obtained. Compared to the FEL operation strategy, the CO2 emissions of CCHP and HDES have been reduced by approximately 4.2% and 2.9%, respectively. Compared to the FTL operating strategy, the CO2 emissions of CCHP and HDES have been reduced by approximately 15.2% and 13.7%, respectively. Published by Elsevier Ltd.

Automated summary

This paper focuses on multi-objective optimization and evaluation of two distributed energy systems, considering factors such as cost and carbon emissions. It was found that CCHP has cost advantages under different operating strategies, while HDES performs better in reducing CO2 emissions.