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Impact of aging and performance degradation on the operational costs of distributed generation systems

Mo, Huadong, Sansavini, Giovanni
Renewable energy 2019 v.143 pp. 426-439
Monte Carlo method, algorithms, data collection, energy, models, operating costs, renewable energy sources, reports (publications)
Renewable and conventional generators in distributed generation system (DGS) are affected by aging and degradation progressively decreases their efficiency and nameplate capacity. This fact is, however, often omitted in the adequacy calculations of the energy not supplied (ENS) and O&M costs (Co) for DGS done via optimal power flow (OPF), leading to the underestimation of unreliability and costs. Moreover, these estimates are hard to compute due to the uncertain aging process. To overcome this limitation, we show that the degradation paths for generators of the same type are intrinsically variable, even for similar operating environments, and capture this by Wiener degradation process with unit-to-unit variability, whose parameters are estimated using the EM algorithm. The Wiener degradation model and the cross-correlation of Co and efficiency are validated using data from the Electric Utility Annual Report of the US Federal Energy Regulatory Commission. Monte Carlo Simulation and OPF are integrated to generate multiple degradation paths and variable operational conditions, and, ultimately, to evaluate the ENS and Co. The application to an empirical dataset and the IEEE 13 node test feeder shows that generator degradation has an increasing influence on the DGS and causes around 8% and 12% increments in ENS and Co.