Risk-based scheduling of CCHP-based microgrid considering economic and environmental aspects using confidence degree theory and CVaR approach

Abstract

The combined cooling, heating, and power (CCHP) co-generation system is an alternative for developing sustainable energy systems. Inside a multi-energy CCHP microgrid, electric, heat, and cool demands are supplied with a high efficiency. Integrating various energy conversion technologies and storage systems allows managing different resources and taking advantage of electric market participation. However, the uncertainties associated with source demand and prices should be taken into account. In this regard, this paper proposes stochastic programming to optimize the operation cost and emission penalty of a multi-energy CCHP microgrid considering the mathematical model of components and related uncertainties. Using the proposed optimization problem, the system operator can derive bidding/offering curves in the electric market. To mitigate the financial risks, the conditional value-at-risk (CVaR) approach is integrated to provide different risk-averse strategies. From the results, it is found that under the risk-averse strategy, by paying 0.4% more money, the risk of CCHP's operation cost instability will be reduced by approximately 16.82%.