- RENEWABLE ENERGY Journal
- December 2019
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- This paper analyses the capacity credits (CCs) of renewable photovoltaic (PV), concentrated solar power (CSP) and wind technologies in the Spanish power system. This system has steadily increased the share of renewables, reaching a penetration level of over 30%. The predictions made by ENTSO-e suggest that this level will increase to 50% by 2030. Therefore, different scenarios are studied in this paper to investigate the evolution of renewable integration and assess the corresponding contributions to reliability. The assessment is performed using a sequential Monte Carlo (SMC) method considering the seasonality of renewable generation and the uncertainties related to renewable sources, failure issues and the maintenance of thermal-based units. The baseline for SMC is provided by historical annual time series of irradiance and wind power data from the Spanish system. In the solar case, these time series are transformed into power time series with models of CSP and PV generation. The former includes different thermal storage strategies. For wind generation, a moving block bootstrap (MBB) technique is used to generate new wind power time series. The CC is assessed based on the equivalent firm capacity (EFC) using standard reliability metrics, namely, the loss of load expectation (LOLE). The results highlight the low contribution of renewables to power system adequacy when the Spanish power system has a high share of renewable generation. In addition, the results are compared with those of similar studies.
- Renewable Energies
- capacity credit; capacity value; equivalent firm capacity; loss of load expectation; power system reliability; sequential monte carlo simulation