### Literature Review  
An energy hub is an integrated facility with multiple input and output energy resources as well as energy conversion and storage units. Current research is mainly devoted to the operation and planning of energy hubs using different optimization methods. From the operational perspective, based on the classical matrix description of energy hubs developed in [3,4], a general structure for energy hubs with renewable energy and power, heating, and cooling demands is put forward in [5]; the day-ahead operation problem is formulated as a mixed integer linear program considering demand response. The optimal network dispatch of a multi-energy system connected through energy hubs is studied in [6]; the gas transmission equation is approximate via multidimensional piecewise linear functions, so the network dispatch comes down to a mixed integer linear program, which can be processed by off-the-shelf solvers. The operation of a concentrating solar power energy hub connecting a power distribution system and a district heating system is studied in [7]; the linearized branch flow model and the hydraulic-thermal model are employed to describe the two networks. Energy hubs including wind, solar, hydro, and gas inputs are discussed in [8]; a matrix coupling model is proposed to describe the energy flow in the hub. Demand response with reducible and deferrable electric load, as well as flexible thermal load, is incorporated in energy hub scheduling problem in [9]; integrated demand response of power and heat is considered in the operation of networked energy hubs in power and natural gas systems [10]; a potential game is developed to capture the interactive behavior among energy hubs. A residential energy hub is a particular scenario for the multi-energy system without a network. Management of a residential energy hub comprising a CHP unit and an electric vehicle as battery storage is considered in [11], while in [12], the CHP unit is replaced with a concentrating solar power plant. The residential energy hub considered in [13] incorporates solar electricity and heat generation. A rule-based control method is reported in [14] for optimizing daily operational cost of an energy hub comprised of a CHP unit and battery/heat storage units. To deal with uncertainty in energy hub operation, [PERSON] et al. in [15] develop a linear model for energy hub dispatch; uncertainty of demand is handled by a static robust optimization approach with relaxed equality constraints. A similar robust optimization method is also used in [16,17]. A stochastic programming technique is used in [18] to address the uncertain factors in energy hub operation, such as demand and market prices; it is found that the participation of heat energy in the market environment influences the optimal operation point. A risk-averse stochastic dynamic programming model for dispatching an energy hub is proposed in [19], in which electric and heat demands and market prices are modeled by stochastic processes. A chance-constrained stochastic optimization model is formulated in [20] for energy hub operation; the Cornish-Fisher expansion is adopted to transform chance constraints into deterministic ones. A probabilistic optimization model of renewable-powered residential energy hubs is suggested in [21]; the two-point estimate method is incorporated to mimic the uncertainty of rooftop solar generation. In short, the stochastic optimization model assumes an exact empirical distribution, which may be difficult to obtain in practice because the historical data are usually limited; robust optimization does not refer to the probability distribution and optimizes system performance in the worst-case scenario, but it is sometimes thought to be conservative because the worst case rarely happens in practice.