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Stochastic Multiperiod Decision Making Framework of an Electricity Retailer Considering Aggregated Optimal Charging and Discharging of Electric Vehicles | ||
| Journal of Operation and Automation in Power Engineering | ||
| مقاله 3، دوره 3، شماره 1، شهریور 2015، صفحه 34-46 اصل مقاله (2.67 M) | ||
| نوع مقاله: Research paper | ||
| نویسندگان | ||
| A. Badri* ؛ K. Hoseinpour Lonbar | ||
| Faculty of Electrical Engineering, Shahid RajaeeTeacher Training University, Tehran, Iran | ||
| چکیده | ||
| This paper proposes a novel decision making framework for an electricity retailer to procure its electric demand in a bilateral-pool market in presence of charging and discharging of electric vehicles (EVs). The operational framework is a two-stage programming model in which at the first stage, the retailer and EV aggregator do their medium-term planning. Determination of retailer's optimum selling price and the amount of energy that should be purchased from bilateral contracts are medium-term decisions that are made one month prior to real-time market. At the second stage, market agents deal with their activities in the short-term period. In this stage the retailer may modify its preliminary strategy by means of pool market option, interruptible loads (ILs), self-scheduling and EVs charging and discharging (V2G). Thus, a bi-level programming is introduced in which the upper sub-problem maximizes retailer profit, whereas the lower sub-problem minimizes the aggregated EVs charging and discharging costs. Final decision making is obtained in this stage that may be considered as a day-ahead market, keeping in mind the medium-term decisions. Due to the volatility of pool price and uncertainties associated with the consumers and EVs demand, the proposed framework is a mixed integer nonlinear stochastic optimization problem; therefore, Monte Carlo Simulation (MCS) is applied to solve it. Furthermore, a market quota curve is utilized to model the uncertainty of the rivals and obtaining retailer's actual market share. Finally, a case study is presented in order to show the capability and accuracy of the proposed framework. | ||
| کلیدواژهها | ||
| Aggregator؛ Bilateral؛ Decision making؛ Electric Vehicle | ||
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