Overview and applications of Robust optimization in the avant-garde energy grid infrastructure: A systematic review

Abstract

Over the past decade, escalating trends toward renewable energy resources, electrified transportation, magnifying load demand, erratic energy reserve capacities, dynamic demand response programs, and fast ubiquitous connectivity models have amplified the complexity of energy predicaments owing to the acute intensification of operational and technical uncertainties in the energy grid’s evolutionary phases, one of the pressing challenges that need to be properly addressed. For risk hedging and circumventing the impact of ambiguous parameters, several experts and decision-makers have developed uncertainty modeling approaches for optimization problems under uncertainty. This article first offers a generic overview of traditional uncertainty modeling techniques (such as probabilistic techniques, possibilistic techniques, hybrid probabilistic–possibilistic methods, information gap decision theory, and interval-based analysis) to highlight the significance of robust optimization (RO) method, a state-of-the-art deterministic set-based uncertainty methodology used to optimize a system having uncertain inputs. For this reason – a most popular and pertinent uncertainty modeling technique, the RO approach is precisely introduced to study and recapitulate its remarkable features, decisive modules, and shortcomings. Next, the preceding research on the RO’s contributions in the domain of the power grid is reviewed over three key enablers: Decentralization, Decarbonization, and Digitalization. More specifically, the literature on microgrid, virtual power plant, co/trigeneration, renewable energy with storage units, electric mobility, demand response, and security threats are covered in this survey. Finally, a rigorous discussion on foremost prospects, research gaps, and future directions is quantified. This strategic study can be utilized by researchers, engineers, and power industrialists to anticipate open research areas and unprecedented opportunities related to the application of the RO uncertainty handling method in the futuristic power grid.