A Probabilistic Economic Assessment Approach for Active Power Curtailment of Photovoltaic Based Distributed Generators

Abstract

Associated problems with high distributed generation (DG) penetration urge the distribution network operator to execute online solutions. One of the most posed solutions is the DG active power curtailment. However, in many cases, the curtailment is performed based on technical considerations only that may badly affect the DG investment. This paper presents a probabilistic economic approach for assessing the power curtailment of photovoltaic (PV) based DGs. This approach aims to determine the maximum allowable active power curtailment from the PV DG while ensuring profitable DG investment. The proposed approach utilizes Monte Carlo simulations (MCS) and T-Copula method for modeling the PV power while considering the temporal stochastic dependence of the solar irradiances. The probabilistic approach considers the taxes, the capital cost allowance, the escalation rate, and the inflation rate to ensure accurate calculation of the DG project cash flow. Moreover, the presented approach takes into account the variations in PV DG feed-in-tariffs from one interval to another. Several test cases are performed; the results and discussions show the importance of the presented study in guiding the distribution operator to take proper decisions.