Risk Management of Cascading Failure in Composite Reliability of a Deregulated Power System with Microgrids
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Due to power system deregulations, transmission expansion not keeping up with the load growth, and higher frequency of natural hazards resulting from climate change, major blackouts are becoming more frequent and are spreading over larger regions, entailing higher losses and costs to the economy and the society of many countries in the world. Large-scale blackouts typically result from cascading failure originating from a local event, as typified by the 2003 U.S.-Canada blackout. Their mitigation in power system planning calls for the development of methods and algorithms that assess the risk of cascading failures due to relay over-tripping, short-circuits induced by overgrown vegetation, voltage sags, line and transformer overloading, transient instabilities, voltage collapse, to cite a few. How to control the economic losses of blackouts is gaining a lot of attention among power researchers. In this research work, we develop new Monte Carlo methods and algorithms that assess and manage the risk of cascading failure in composite reliability of deregulated power systems. To reduce the large computational burden involved by the simulations, we make use of importance sampling techniques utilizing the Weibull distribution when modeling power generator outages. Another computing time reduction is achieved by applying importance sampling together with antithetic variates. It is shown that both methods noticeably reduce the number of samples that need to be investigated while maintaining the accuracy of the results at a desirable level. With the advent of microgrids, the assessment of their benefits in power systems is becoming a prominent research topic. In this research work, we investigate their potential positive impact on power system reliability while performing an optimal coordination among three energy sources within microgrids, namely renewable energy conversion, energy storage and micro-turbine generation. This coordination is modeled when applying sequential Monte Carlo simulations, which seek the best placement and sizing of microgrids in composite reliability of a deregulated power system that minimize the risk of cascading failure leading to blackouts subject to fixed investment budget. The performance of the approach is evaluated on the Roy Billinton Test System (RBTS) and the IEEE Reliability Test System (RTS). Simulation results show that in both power systems, microgrids contribute to the improvement of system reliability and the decrease of the risk of cascading failure.
- Doctoral Dissertations