Chapter 16 - Reliability modeling of renewable energy sources with energy storage devices

Abstract

The global energy scenario is rapidly shifting toward renewable energy sources (RESs). The RES corresponds to wind and solar. In addition, energy storage devices (ESDs) are used for maintaining the continuity of supply. The effectiveness of RES and ESD is challenging due to diffused nature of wind speed, solar irradiance, and charging/discharging of ESD. This chapter proposes multistate modeling using discrete Markov chains. This overcomes the drawbacks of conventional methods such as Weibull and beta probability density functions. In multistate modeling, the states are identified based on wind speed or solar irradiance range or charge in the battery. In these states the power output ranges from 0MW to rated power output of the RES/ESD. Higher number of states (N) gives more accurate results. These states are individually modeled to eliminate the error due to randomness. Discrete Markov chains calculate the interstate transitions and determine the probability to remain in a particular state. From transitional probability matrix (NxN), the capacity outage probability matrix (Nx1) is obtained for system with “N” states. The errors due to repeated modeling are eliminated by Monte Carlo simulations. The power output of each state is calculated for 24h, 365days. Then the probability and duration of availability and unavailability are calculated. The performance of the system is assessed by different reliability indices. The load end reliability index is loss of load expectation (LOLE) and the supply-side indices are expected energy not supplied (EENS) and expected demand not supplied (EDNS). The effect of RES and ESD on transmission network is evaluated by load flow analysis. The IEEE RTS-79 test system and its modified version are considered for implementation. The power flow analysis shows that the active power losses reduce and active power flow improves with RES and ESD. Hence, the cost of generation is reduced. MATLAB and MATPOWER software are used for simulations.