Distributionally Robust Two-Stage Energy Management for Hybrid Energy Powered Cellular Networks

Risk-averse decision under worst-case continuous and discrete uncertainties in transmission system with the support of active distribution systems

“…(ii) How to mitigate destructive effects of worst-case continuous and discrete uncertainties on the TS. Recently, a considerable literature has grown up around the theme of uncertainty methods for addressing the impacts of worst-case wind power uncertainty and contingencies on the power system operation, e.g., stochastic method (SM) [3], [4] distributionally-robust optimization (DRO) method [5], [6] and [7] the IGDT method [8] and [9] and contingency-constrained method [10]. The SM is mainly based on a set of generated scenarios to characterize the probable realizations of wind uncertainty and contingencies.…”

“…The wind power uncertainty was modeled by scenario-based method. Recently, a considerable literature has grown up around the theme of distributionally-robust optimization (DRO) method [5], [6] and [7]. It combines stochastic optimization with robust optimization to find the worst probability distribution in the range of given confidence sets [5], [6].…”

“…Recently, a considerable literature has grown up around the theme of distributionally-robust optimization (DRO) method [5], [6] and [7]. It combines stochastic optimization with robust optimization to find the worst probability distribution in the range of given confidence sets [5], [6]. The DRO method is employed to model the continuous uncertainty instead of the discrete uncertainty [5] and [6].…”

“…It combines stochastic optimization with robust optimization to find the worst probability distribution in the range of given confidence sets [5], [6]. The DRO method is employed to model the continuous uncertainty instead of the discrete uncertainty [5] and [6]. The DRO method needs to know the first-and second-order statistics information (i.e., the mean, the variance of stochastic parameters and the lower bound, the upper bound), which leads to the challenge that directly solving the original optimization problem is generally unaffordable [6].…”

“…Ref [6] proposes a DRO method for the decomposition of contract electricity, which regards the difference between the unit's monthly power generation and the contract electricity as one of its optimization targets. Ref [5] proposes a distributionally robust two stage stochastic optimization framework to minimize the expected total energy cost of mobile network operators in the finite time horizon. The IGDT method is one of the practical methods among the uncertainty methods, that can be used for handling the uncertainty of wind power to avoid problem caused through this phenomena [11].…”