A novel techno-economic risk-averse strategy for optimal scheduling of renewable-based industrial microgrid

Nowadays, increasing concerns regarding the harmful effects of fossil fuel-based energy production systems have accelerated the decarbonization efforts particularly in equipping the electric power grid with a high level of renewable energy sources. In deregulated energy networks with a high share of renewables, adopting an effective strategy for appropriately dealing with intermittences of stochastic producers is necessary to provide a continuous and reliable energy supply. This paper proposes a novel techno-economic risk-averse strategy for optimal scheduling of the industrial microgrid considering both the technical and economical objectives. The robustness function of the information gap decision theory method is exerted for developing the risk-averse strategy aiming to properly manage the fluctuations of uncertain parameters in the system. The demand-side energy management is carried out by developing the price and load response schemes as the demand response programs. The industrial microgrid equipped with renewable energy sources and energy storage systems is intended as a real case study for examining the effectiveness of the proposed strategy. The problem is studied under two models, which Model I assesses the scheduling of the industrial microgrid without intending the stochastic behaviors of uncertain parameters while Model II models uncertainties based on the proposed strategy. The results indicated the effectiveness of the proposed strategy in realizing robustness condition for the renewable-based industrial microgrid to supply reliable and continuous energy in the deregulated environment.