Reliability Modeling of Run-of-the-River Power Plants in Power System Adequacy Studies

Deployment of renewable energies for the electricity generation is on the rise around the world, among which is the run-of-the-river (ROR) power plant whose output power is variable throughout the year depending on the water flow of the respective river. The inherent uncertainty associated with renewable energy resources calls for new stochastic modeling approaches to measure the impacts of using these energies on the power system performance. This paper develops an analytical reliability model for ROR power plants. The model is based on the state-space analysis and is devised with the intention of being used in adequacy studies of power systems. Failure of related components and the intermittent nature of water flow are concurrently accommodated in the proposed model. The well-known technique of fuzzy c-means clustering is employed to find the optimal states of the resultant multistate reliability model. Two reliability test systems, i.e., Roy Billinton Test System (RBTS) and IEEE Reliability Test System (IEEE-RTS), are examined to demonstrate the effectiveness of the proposed reliability model. The water-flow data of Sheshpir River in Pars province of Iran are used.