Contribution of PV Generation With Embedded Battery Storage to Capacity Adequacy

This paper proposes a real-time redispatch method for including PV-plus-battery plants in resource adequacy assessment (RAA) studies. The method offers the possibility to represent the market operation of the assets, while at the same time considering their response to reliability events, unlike existing methods in the literature that manage such assets in a single-dimensional manner, driven solely by adequacy contribution considerations or entirely ignoring this capability. In the proposed method, while the plant is initially dispatched in a market-oriented manner, i.e., with the objective of maximizing market revenues, its actual operation is adapted to meet system needs when reliability events take place. The method is incorporated into a Monte Carlo (MC) based RAA model in a computationally efficient manner, relying on a deterministic implementation of redispatching that does not impact significantly the computational burden of the RAA model, thus enabling the execution of multiple MC samples to achieve a high stochastic process accuracy. A merit order algorithm is also embedded into the RAA model to evaluate the PV-plus-battery market revenues. The model developed allows a refined calculation of the capacity value (CV) of such assets for different plant configurations and inverter loading ratios, while the upper and lower CV bounds are approximated via application of the adequacy- and market-oriented approaches available in the literature. Results show that the embedded storage energy capacity is crucial for the CV afforded by the assets, while any decrease in the inverter capacity does not significantly impact the CV value. Further, the CV of storage embedded in tightly coupled PV-plus-battery plants, where batteries are exclusively charged by the plant's own PV generation, is generally lower than the value of similar stand-alone storages operating without any charging constraints.