Elastic flexible unit commitment: A scenario-based power-electric fleet analysis

Abstract

This paper presents an elastic flexible unit commitment (EFUC) in a coupled power and electric fleet (P-EF) network. In this framework, a master independent system operator (MISO) coordinates the day-ahead unit commitment problem (UCP) while various sources of both networks are integrated. On the power side, battery energy storage (BES) is allocated, and on the electric fleet side, private electric vehicles (PEVs), electric buses (EBs), and electric taxis (ETs) are integrated. The temporalities of PEVs and EBs are managed by PEV to grid (P2G) and bus to grid (B2G) technologies, respectively. Traveling patterns present the spatial impact of PEVs and ETs on day-ahead commitment. In this P-EF network, an incentive-based demand response (IBDR) program is implemented by MISO. A scenario-based technique is applied to generate operation scenarios for coupled uncertainties of load demand and the number of PEVs. The overall mixed integer linear programming (MILP) model is tested on IEEE 6-bus and 24-bus systems which are integrated with traveling patterns of PEVs and ETs. Results confirm that classifying the behavior of various electric vehicles leads to an explicit understanding of each source’s impact on UCP cost and required energy. The results indicate that MISO prioritizes the utilization of spatio-temporal sources (e.g., PEVs) over only stationary temporal ones (e.g., EBs or BES) since both time and location are under control. Also, MISO damps the spike prices by the IBDR program while offering incentives to responsive loads under uncertainty.