Ramping-Based Variable-Timescale Co-Optimization for Distribution Planning and Operation

Abstract

The growing penetration of distributed photovoltaic (PV) poses new challenges, such as voltage security and output uncertainty, in distribution networks. The efficient and secure integration of high-level PV has recently garnered much attention. This work proposes a novel variable timescale model for the planning-operation co-optimization, aiming to unlock more flexibility for PV integration. We introduce a novel ramp event detection algorithm to adjust timescales, focusing on critical time periods. Consequently, this allows for flexibility unlocking by adjusting high-resolution time periods with binary variables while maintaining an efficient model size. To guarantee the robustness and nonanticipativity in planning, we propose a multistage optimization model with a variable uncertainty set. A hybrid solution approach is then proposed to solve the challenging model. In the meantime, the model takes into account utilization of the mobile energy storage system (MESS). To validate the approach, we perform the case study using the 13-bus system, 141-bus system, and 906-bus system. The numerical test results demonstrate the efficiency and accuracy of the proposed methodologies.