Chance Constrained Co-Optimization of Integrated Electrical and District Heating Networks

Abstract

Integrated electrical and heating systems(IEHS) are drawing huge attention because of their cost-effective and flexible operational capabilities. Optimal dispatch of renewable units in an IEHS is challenging because of their intermittent and stochastic nature. Uncertainties in the renewable energy source (RES) forecast, electrical, and thermal loads can cause voltage and temperature violations compromising the operational security of the system. In this paper, a rule-based dynamic dispatch is proposed to handle the increasing levels of uncertain RES and ensure the system's security. A chance-constrained (CC) co-optimization algorithm considering the uncertain loads and RES is developed. In the proposed method, electric boiler power and curtailment of RES are dynamically dispatched to reduce operational costs and network losses. The developed method is tested on the IEEE 15 bus distribution system and U.K. Generic Distribution System (UKGDS) 95 bus test system models. The results show that the proposed method significantly reduces the voltage deviations and temperature violations compared to the deterministic case.