**7. Conclusions**

This paper proposed a CEED approach with the EBDR program by using the WU-ABC algorithm. The objective function was constructed in consideration of generation costs and pollutant emission. The emission function took the emitted quantities of CO2, SOx, and NOx, into account and converts their sum into operation costs through unit conversion, using a penalty factor. To meet the maximum emission constraint considered in addition to the CEED in our work, the EBDR program was proposed to balance economics and environmental issues. The EBDR program is based on the concept of elasticity, and the participation volume changes depending on the violation of emission constraints. To solve the multiobjective optimization problem, we proposed the use of the WU-ABC algorithm, a combination of the weighting update method and the conventional ABC algorithm. To demonstrate the effectiveness of the proposed CEED approach, simulations were conducted on the modified grid-connected MG system. Three cases were considered depending on the maximum emission constraint and the application of a DR program. The proposed approach was able to reduce operation costs compared to the conventional solution without DR program. Furthermore, it was easy to satisfy the maximum emission constraints by updating the penalty factor. In summary, the use of the EBDR program reduced operation costs and pollutant emissions, and the maximum emission constraints were satisfied through the WU-ABC algorithm. Although operation costs were slightly increased compared to that of a conventional economic DR, an emission violation fee was not imposed. In addition, the performance test results indicated that the WU-ABC algorithm outperformed other algorithms in terms of cost and CPU time. Therefore, the proposed CEED approach can assist MGOs in optimizing MG operations under environmental constraints. Our future work will be under way to focus on solving the sensitivity problem in MG when the consumers do not comply with the command of MGO in the CEED problem.

**Author Contributions:** H.-S.R. proposed the main idea of this paper and M.-K.K. coordinated the proposed approach and thoroughly reviewed the manuscript. All authors read and approved the manuscript.

**Funding:** This research was supported by the Korea Electric Power Corporation (grant numbers: R18XA06-75). This research was also supported by Basic Science Research Program through the National Research Foundation of Koera (NRF) funded by the Ministry of Education (2020R1A2C1004743).

**Conflicts of Interest:** The authors declare no conflict of interest.
