ABSTRACT
The intermittency and fluctuation of renewable energies have brought potential risks toward the electricity system operation. The traditional risk assessment approaches usually target the long term over the whole system, which cannot reflect the time- and location-varying influences by renewable energies. Moreover, with the wide installation of gas-fired generators and power-to-gas plants, gas networks can be utilized to accommodate the fluctuation of renewables and support the reliability of electricity systems. In this chapter, a spatial-temporal risk evaluation approach of electricity systems under a large share of renewable generations is developed. Firstly, the importance of spatial-temporal risk evaluation in electricity systems is introduced. Then, the time-space Markov modeling technique is proposed to characterize the stochastic process of wind power, as well as the correlations over various locations. The operational reliabilities of gas-fired generators and power-to-gas facilities are modeled in a multistate manner. An optimal control framework for the electricity system is then developed to re-dispatch the generating units to handle the uncertainty of renewable generations, considering the restraints imposed by gas flow dynamics. The second-order cone reformulation technique is used to convexify the nonlinearity of dynamic gas flow equations. In addition, the concept of traditional over-limit risk indices, e.g., the risk of system overload, is extended to quantify the spatial-temporal risk of the electricity system. Finally, numerical cases are simulated on a test system to validate the risk assessment technique proposed in this chapter.
