Hybrid Robust-CVaR optimization of Hybrid AC-DC Microgrid

Abstract

In this paper, the risk assessment of a hybrid AC-DC (HACDC) microgrid (MG) and a conventional AC (CAC) MGs in the presence of renewable resources and electric vehicles (EVs) is studied and compared with each other. Due to the presence of the renewable resources, AC/DC loads, and EVs that are modeled using stochastic optimization, an applicable risk measure is required to model the risk of such parameters. Besides, the grid price is another uncertain parameter that is modeled using robust optimization (RO). To deal with the risks of these uncertainties, a hybrid robust-conditional value-at-risk (CVaR) risk measure is proposed in this paper. Using the proposed method, the risks related to the arrival/departure times, arriving charge of EVs, AC and DC loads, and power generation of renewable resources (wind and PV units) are modeled using the CVaR. Also, the risk of the day-ahead market price is modeled by RO. Based on obtained results, the operation cost of the CAC is more than HACDC MG and the proposed risk measure has the same effects on both MGs.