STOCHASTIC MULTIPERIOD DECISION MAKING FRAMEWORK OF AN ELECTRICITY RETAILER CONSIDERING AGGREGATED OPTIMAL CHARGING AND DISCHARGING OF ELECTRIC VEHICLES

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BADRI A.; HOSEINPOUR LONBAR K.

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Paper Information

Journal: JOURNAL OF OPERATION AND AUTOMATION IN POWER ENGINEERING Year:2015 | Volume:3 | Issue:1 Page(s): 34-46

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Information Journal Paper

Title

STOCHASTIC MULTIPERIOD DECISION MAKING FRAMEWORK OF AN ELECTRICITY RETAILER CONSIDERING AGGREGATED OPTIMAL CHARGING AND DISCHARGING OF ELECTRIC VEHICLES

Author(s)

BADRI A. | HOSEINPOUR LONBAR K. | Issue Writer Certificate

Keywords

AGGREGATOR

BILATERAL

DECISION MAKING

ELECTRIC VEHICLE

INTERRUPTIBLE LOAD

RETAILER

SELFPRODUCTION

Abstract

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.

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APA: Copy

BADRI, A., & HOSEINPOUR LONBAR, K.. (2015). 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, 3(1 ), 34-46. SID. https://sid.ir/paper/268333/en

Vancouver: Copy

BADRI A., HOSEINPOUR LONBAR K.. 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[Internet]. 2015;3(1 ):34-46. Available from: https://sid.ir/paper/268333/en

IEEE: Copy

A. BADRI, and K. HOSEINPOUR LONBAR, “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, vol. 3, no. 1 , pp. 34–46, 2015, [Online]. Available: https://sid.ir/paper/268333/en

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