Impact assessment of shared storage and peer-to-peer trading on industrial buildings in the presence of electric vehicle parking lots: A hybrid robust-CVaR analysis

Abstract

Local power markets and peer-to-peer (P2P) power transaction plans between the clients have lately received attractions as a cost-effective approach to encourage flexible energy options and sharing the internal power resources. For the integration of industrial consumers (ICs) in the presence of electric vehicle parking lot, this study modeled local power markets to share the surplus power of ICs between each other. Other hands, shared storage is modeled in the proposed system to benefit consumers. In order to investigate the proposed system under uncertain conditions, a hybrid optimization method is proposed for uncertainty modeling. In this paper, the well-known uncertainty modeling tools, including the robust optimization and Conditional Value at Risk (CVaR) embedded stochastic optimization approach, are proposed to model the uncertainties. The markets price uncertainty is one of the important uncertain parameters assumed as an unknown-distribution parameter due to insufficient historical data or not following a specific distribution; thus, the risks of this parameter are modeled by robust optimization, which has no need for big historical data of uncertain parameter. The other uncertain parameter is solar irradiation. The corresponding risks of solar irradiation is modeled by CVaR modeling because of the following Beta distribution. Thus, the financial risks of different uncertain parameters can be modeled effectively using the proposed hybrid optimization framework. According to obtained results, using peer-to-peer trading reduces the operation cost by 7.94%, while using the shared storage along with peer-to-peer trading reduces the operation cost by 21.49%.