Abstract
Combined Cooling, Heating, and Electrical (CCHP)-based microgrids meet various energy demands at the same time. Risk analysis of such CCHP-based microgrids under environmental and economic constraints is a challenging issue. Furthermore, high penetration of various renewable energy sources in such CCHP-based microgrids clouds the issue. Thus, Downside risk constraints technique (DRCT) is employed in this paper to manage and minimize the risk associated with various uncertainties in the studied sample CCHP-based microgrid under environmental and economic constraints. The uncertainties of solar radiation, wind speed, market tariff and cooling, heating, and electrical demands are considered, and the stochastic optimization approach is used to model the mentioned uncertainties. The effect of the Real-Time Pricing rate of the Demand Response Program (RTP-DRP) has been studied in this paper. By analyzing the obtained results, it can be found that with considering DRCT, the risk-in-cost (RC) level can plunge to 0 respectively by paying 2.61% and 1.68% without and with RTP-DRP.
Highlights
Nowadays, the uncertainties of various renewable energy source outputs have significant effects on the performance of the CCHP-based microgrids [1]–[3]
Reviewed papers in the field of planning of CCHP-based microgrids under various uncertainties can be reviewed as follows: A novel robust planning method has been implemented on a sample CCHP-based model considering the heating, cooling, and electrical demands uncertainties in [22]
Using Downside risk constraints technique (DRCT) to manage the risk associated with various uncertainties in a CCHP-based microgrid considering environmental and economic constraints and high penetration of renewable energy sources
Summary
The uncertainties of various renewable energy source outputs have significant effects on the performance of the CCHP-based microgrids [1]–[3]. Various risk modeling and management approaches such as robust optimization approach [4], [5], information gap decision theory [6], stochastic optimization approach [7], [8], and whale algorithm [9] are used to handle uncertainties. The emission reduction is another factor that should be considered when scheduling the CCHP-based microgrids [10]. Some steps should be taken toward decreasing the level of CO2 emission. It should be noted that RTP-DRP is a useful tool to decrease the EOC and manage the emitted CO2 emission [11], [12]
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