A stochastic–probabilistic energy and reserve market clearing scheme for smart power systems with plug-in electrical vehicles

• Published in: Energy conversion and management Vol. 105; pp. 1046 - 1058
• Main Authors: Khazali, Amirhossein, Kalantar, Mohsen
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.11.2015
• Subjects: Aggregator; Automotive components; Clearing; Energy and reserve market clearing; Markets; Mathematical models; Plug-in electric vehicle; Probability theory; Randomness; Reserves; Smart power systems; Stochastic programming; Aggregator; Plug-in electric vehicle; Smart power systems; Energy and reserve market clearing; Stochastic programming
• ISSN: 0196-8904; 1879-2227
• DOI: 10.1016/j.enconman.2015.08.050

•A new tri-level energy and reserve market clearing scheme is presented.•A new model is presented for PEV aggregator participation in the energy and reserve market.•A multiobjective framework is formulated for cost and reliability optimization. In this paper, a novel stochastic–probabilistic energy and reserve market clearing scheme is proposed in the presence of plug-in vehicles (PEV) and wind power introducing a new model for PEV aggregators. The method is capable of managing the charging and discharging patterns of PEV aggregators. In this research, the total reserve for the day ahead market is detached into two different parts using the stochastic–probabilistic market clearing approach. The first part of the reserve is scheduled to overcome imbalances caused by uncertain generation and consumption. The second part of the reserve is procured in order to handle the probability of unit outages according to the reliability constraints. The approach is able to determine that how much of each types of reserves has to be provided by generation units or PEV aggregators. The PEV aggregators are modeled as large scale storage devices with stochastic capacities. The reliability formulations are linearized with the integration of the PEV aggregator models in order to form a mixed integer linear programming (MILP) problem. Finally, a multi-objective framework is formulated which considers the reliability metrics as an objective function instead of a constraint in addition to the total operation costs.