Economic-environmental operation of an unbalanced microgrid including energy storage systems via semidefinite relaxation

• Published in: Renewable energy focus Vol. 42; pp. 129 - 145
• Main Authors: Ghazvini, Amir, Olamaie, Javad, Sedighizadeh, Mostafa
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.09.2022
• Subjects: Compressed Air Energy Storage (CAES); Convex reformulation; Electric Vehicle (EV); Energy Storage System (ESS); Information Gap Decision Theory (IGDT); Microgrid (MG); Semidefinite Programing (SDP); Microgrid (MG); Semidefinite Programing (SDP); Convex reformulation; Compressed Air Energy Storage (CAES); Energy Storage System (ESS); Electric Vehicle (EV); Information Gap Decision Theory (IGDT)
• ISSN: 1755-0084; 1878-0229
• DOI: 10.1016/j.ref.2022.06.003

[Display omitted] •Modeling of optimal operation in an unbalanced MG including CASE and EVs.•Reformulating the nonlinear and non-convex day-ahead optimal operation problem of unbalanced MG to a linear and convex problem via SDP and hence, guaranteeing the global optimum.•Considering shiftable load ToU as DRPs.•Applying the IGDT method with risk averse strategy in order to involve uncertainties in unbalanced MG. This paper proposes a mathematical optimization approach based on semidefinite programing (SDP) for optimal operation of an unbalanced microgrid (MG) equipped with renewable energy resources (RERs) as well as energy storage systems (ESSs) including compressed air energy storage (CAES) and electric vehicles (EVs). The SDP converts nonlinear and non-convex models proposed for day-ahead optimal operation into a convex approximation, which is easily implemented by commercial software. An optimization problem is formulated such that it minimizes the costs related to operation and environmental effects limited to several technical limitations. It is clear that there is an intrinsic deviation between predicted and actual uncertainty variables in MG. This paper presents a stochastic optimal operation model based on Information Gap Decision Theory (IGDT) with risk averse strategy to overcome this information gap and to help Microgrid Operator (MGO). As demand response programs (DRPs), the shiftable load and time of use (ToU) are considered for enhancing the flexibility of MG. Employing the presented model in the 21-bus test system shows that CAES and EVs, as novel ESSs, have good capability to reduce the costs pertaining to operation and emissions in the day-ahead optimal operation.