Two-stage Robust Management of PEV Parking Lots Coupled with Multi-energy Prosumers under Load and Energy Market Uncertainty

Abstract

Development of multi-energy integration for the commercial/Industrial sector introduces a high level of interdependency between different energy carriers which requires integrated modeling of these multi-energy systems (MESs). Transportation electrification such as the integration of plug-in electric vehicles (PEVs) has the potential to have a significant effect on the operation of commercial MESs which are equipped with large scale PEVs' parking lots. Although the development of energy management models to optimally integrate PEVs into MES leads to higher benefits, the associated operational uncertainties can bring additional costs for system operators. Ignoring these uncertainties can result in nonoptimal or even infeasible operational solutions for MES facilities. In this paper, a two-stage robust energy management model has been proposed for MESs equipped with PEV parking facilities to optimally schedule MES facilities and its interaction with upstream network, while, supplying the required PEV charging patterns, considering the uncertainties of MES loads and energy market prices. The proposed model is developed as a min-max-min optimization problem which is solved through a column-and-constraint methodology, recasting the tri-level problem into a first-stage min problem and a second-stage maxmin problem. The second-stage problem is solved through duality theory and Big-M linearization technique. A comprehensive case study has been conducted to evaluate the effectiveness of the proposed model. According to the obtained results, MESs are able to supply PEVs and multi-energy loads, while participating in upstream network energy market with operational solutions that are robust against uncertainties, resulting in extra benefits and lower operational costs.