Stochastic Decision-Making Model for Aggregation of Residential Units with PV-Systems and Storages

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Publication Date: 8/2/2020

Event: The 2020 IEEE PES General Meeting, Montreal, Canada

Reference: pp. 1-5, 2020

Authors: Hossein Khazaei, Stony Brook University, NEC Laboratories America, Inc.; Ramin Moslemi, NEC Laboratories America, Inc.; Ratnesh Sharma, NEC Laboratories America, Inc.

Abstract: Many residential energy consumers have installed photovoltaic (PV) panels and energy storage systems. These residential users can aggregate and participate in the energy markets. A stochastic decision making model for an aggregation of these residential units for participation in two-settlement markets is proposed in this paper. Scenarios are generated using Seasonal Autoregressive Integrated Moving Average (SARIMA) model and joint probability distribution function of the forecast errors to model the uncertainties of the real-time prices, PV generations and demands. The proposed scenario generation model of this paper treats forecast errors as random variable, which allows to reflect new information observed in the real-time market into scenario generation process without retraining SARIMA or re-fitting probability distribution functions over the forecast errors. This approach significantly improves the computational time of the proposed model. A simulation study is conducted for an aggregation of 6 residential units, and the results highlights the benefits of aggregation as well as the proposed stochastic decision-making model.

Publication Link: https://ieeexplore.ieee.org/document/9281448