###### Abstract
The demand response program (DRP) is employed in the model to minimize the total cost. An integrated wind-photovoltaic system incorporated with CAES, DRP, and thermal units aiming to the cost minimization was studied in [18]. A scenario-based bi-level approach for designing a hybrid system pinpointed by wind, CAES, and thermal units in addition to DRP was proposed in [19]. The first objective minimizes total daily operational costs, while the second objective minimizes the total emission cost. An information gap decision theory (IGDT)-based risk constraint bidding strategy for a CAES-self scheduling model was studied to maximize the profit by participating in the power market [20]. The results illustrate profitable scheduling in the presence of CAES considering the price uncertainty. Stochastic energy management of the intelligent electric vehicle and DRP was proposed by [21]. P2G facility as an innovative technology that effectively converts the surplus electrical energy into other energy vectors can improve system flexibility [22]. This promising technology not only plays a significant role in storing energy but also is known as an environmental-friendly technology [23]. The P2G allows the power system to have a bidirectional coupling with other energy systems such as natural gas and heating district by trading synthetic natural gas and the produced heat as the final power conversion product [24]. Many researchers have used the P2G facility to improve the integrated power and natural gas systems' reliability and security. The environmental performance of P2G using life cycle assessment was investigated [25] to analyze the effects of the approach for CO\({}_{2}\) capturing, processes of producing hydrogen and methane, and environmental impacts of the P2G facility. The coordinated renewable Energy and P2G was considered a potential solution to diminish CO\({}_{2}\) emission and improve wind power variability in the power grid [26]. An optimal scheduling method of combined P2G and gas-fired power plant systems to quantify the coordinated system ability for reducing CO\({}_{2}\) emission and employing renewable resources was investigated in [27]. In [28], the operation of a collocated gas-fired unit, P2G facility, and natural gas storage system was analyzed via a robust day-ahead scheduling model to minimize the total operation cost of electricity and gas supply. Also, the coupled energy system in the presence of P2G facilities operating in an uncertain environment was investigated in [29]. The proposed two-stage robust optimization method can effectively improve the system's flexibility to decrease system operational cost. A management strategy considering a multi-objective optimization framework for a multi-carrier MG (MCMG) system consists of integrated local wind resources, P2G facility, and solid oxide fuel cell/gas hybrid turbine system was proposed in [30]. An optimal multi-objective optimization framework using Conditional Value at Risk criteria and a robust optimization approach was presented in [31]. Profit maximization and risk minimization aims are ensued in the model by coordinating virtual power plant and P2G facility. In [32], the multi-objective day-ahead scheduling method was used to analyze the effect of the P2G in a coupled energy system comprising electricity, gas, and district heating systems. The renewable energy integration in combined cooling, heating, and power processes was developed [33]. The distributed coordination control for multi-MGs based on the game-theoretic non-cooperative method was studied in [34]. In [35], the need for intelligent energy networks for a higher global efficiency through a multi-carrier system was developed. Similarly, a multi-objective two-stage structure for both electricity and gas networks regarding P2G facility, DRP, and wind energy was investigated [36].