Investigation of Carrier Demand Response Uncertainty on Energy Flow of Renewable-Based Integrated Electricity-Gas-Heat Systems

Since there are heavy interdependencies among the electrical, heat, and gas systems to supply various load types worldwide, operation of multi-energy carrier (MEC) systems faces critical challenges. Moreover, any uncertainty rising in one carrier would directly influence the energy flow and the secure operation of the whole MEC system. This issue intensifies when an MEC system is integrated with industrial energy carrier demand response (ECDR) consumers and renewable energy sources (RESs). Large industrial ECDR consumers can increase the system uncertainty by randomly participating in the demand response programs and utilizing various carriers. Accordingly, this paper presents a powerful probabilistic tool named 2m + 1 point estimate strategy for energy flow analysis of an integrated MEC system considering ECDR, RES, and various load types uncertainties to control the risks associated with the uncertainties. In addition, a new decomposition technique is presented to accelerate the energy flow solving of the integrated MEC systems. This technique has been promoted by adding a novel noniterative method named holomorphic embedding and the less-computational graph methods for solving the energy flow of the MEC. The proposed probabilistic energy flow is tested on an integrated MEC system employing various incentives for industrial ECDR consumers.