Two-Stage Stochastic Day-Ahead Market Clearing in Gas and Power Networks Integrated With Wind Energy

The significant penetration rate of wind turbines in power systems has caused a number of challenges in the operation of systems such as large-scale power fluctuations induced by wind farms. gas-fired plants with fast starting ability and high ramping can handle natural uncertainties of wind power better than any other traditional plants. therefore, the integration of electrical and natural gas systems has great potential of enhancing the flexibility of power systems to incorporate more renewable power sources such as wind turbines. in this area, the uncertainty associated with wind speed has a meaningful impact on the optimal management of the generation units in power grids. in classic models, the operation of gas and power networks is studied independently, which does not ensure the global optimality of the networks due to the mutual dependency of such networks. accordingly, the interconnected operation of the combined power and gas systems has been considered as an important research topic in recent years. this study proposes a stochastic market-based model for clearing of energy in interconnected power and gas systems through the integration of wind power. stochastic programming is developed for studying the uncertainty of wind power production using a normal distribution function in a two-stage model. it should be remarked that the proposed two-stage model covers the uncertainty of wind power generation and load demand in real-time dispatch, determining the hourly scheduling of units in the first stage. it is expected that the operation cost of the integrated networks, local marginal pricing of the gas and power, and the load shedding will be increased by an increase in the residential gas load. the investigations showed a 4.2 % increase in total operation costs of the integrated power and gas system by a 5 % increase in the residential gas load.