Two-stage stochastic unit commitment for renewable energy integrated power systems considering dynamic capacity-increase technologies of transmission lines

Abstract

Dynamic capacity-increase technologies (DCITs), as a solution to reduce the stress of transmission networks, avoid long-term constructions and update the maximum transmitted capacities based on real-time environment factors and the maximum allowable operation temperatures (MAOTs), which provide flexibility in optimizing the operation modes for power systems. This paper proposes a detailed two-stage stochastic unit commitment model considering the physical processes of heat transfer as well as the uncertainties of renewable energy. The dynamic thermal rating (DTR) is calculated based on the heat balance of transmission lines in the steady state, including radiated and convective heat loss and gain from the solar heat and power flows. To simulate the uncertainties from renewable energy outputs, this paper applies the Latin hypercube sampling method to generate output scenarios in stochastic optimization. Finally, the proposed model is verified on a modified IEEE-24-bus test system. The effectiveness of DCITs is illustrated through the case study.

Keywords

• Dynamic capacity-increase technologies
• Two-stage stochastic optimization
• Unit commitment
• Dynamic thermal rating