Estimation of solar photovoltaic energy curtailment due to volt–watt control

Abstract

The widespread deployment of autonomous inverter-based solutions for mitigating voltage and frequency excursions caused by high-penetration photovoltaic (PV) systems has drawn increased attention due to their potential impact on PV production. It is now important to quantify the amount of solar energy curtailed as a result of the activation of inverter-based grid support functions (GSFs). This study proposes a methodology for estimating the impact of volt-watt on customer PV energy curtailment using smart meter voltage data. This method estimates maximum possible curtailment for a given volt-watt curve based on the customer smart meter voltage during the time period of interest. This study compares the proposed methodology with field measurements using irradiance and customer inverter data from Hawaii as well as with results from a previous simulation-driven study on the impact of advanced inverter GSF activation on PV energy curtailment. Results show that the proposed method for estimating lost PV production caused by volt-watt control aligns reasonably well with field measurements and computer simulations for hundreds of customers. The proposed method could be used to estimate customer energy curtailment, which could inform future compensation mechanisms for utilities leveraging customer-sited resources to mitigate high voltage and defer infrastructure upgrades.

Power Factor Estimation of Distributed Energy Resources Using Voltage Magnitude Measurements

“…This will help address the instability in the estimate as L approaches M 2. In the case of uncertain DER location, we propose the sparse approximation model (12), which is an augmented form of the problem in (11):…”

“…For both of the regularized regression models described in (12) and (15), the norm penalty λ can easily be chosen in practice using modern cross-validation algorithms such as those in [19].…”

“…An interest has grown in analyzing how distributed inverter-based systems behave with fixed control parameters [1], [11], [12]. Reference [1] presents a fast quasi-static time-se-ries algorithm for computing the impacts of dynamic var control, providing an estimate for the states of all controllers with a candidate control curve.…”

“…Reference [1] presents a fast quasi-static time-se-ries algorithm for computing the impacts of dynamic var control, providing an estimate for the states of all controllers with a candidate control curve. In [12], a robust estimate for solar PV energy curtailment is provided for a distributed generation system operating with a fixed volt-watt curve.…”

“…Furthermore, in large feeder models, it may be more difficult to preprocess the S PQ matrix so that electrically identical rows and columns are removed due to incomplete information regarding the state of the switches. Figure 9 shows the results of LASSO estimation methods outlined in (12). In this experiment, a 10-fold cross-validation is used to select the Lagrange multiplier λ.…”