Convex Optimization of PV-Battery System Sizing and Operation with Non-Linear Loss Models

TL;DR

This paper introduces a convex optimization approach for PV-battery system sizing and operation that accurately models non-linear losses, improving over traditional linear models by providing more precise system sizing and utilization insights.

Contribution

It presents a convex relaxation method for non-linear loss models in PV-battery optimization, enabling more accurate system sizing and operation analysis.

Findings

Linear loss models underestimate battery size and cost.

The convex relaxation closely approximates the original non-linear problem.

The method offers a good balance between accuracy and computational efficiency.

Abstract

In the literature, when optimizing the sizing and operation of a residential PV system in combination with a battery energy storage system, the efficiency of the battery and the converter is generally assumed constant, which corresponds to a linear loss model that can be readily integrated in an optimization model. However, this assumption does not always represent the impact of the losses accurately. For this reason, an approach is presented that includes non-linear converter and battery loss models by applying convex relaxations to the non-linear constraints. The relaxed convex formulation is equivalent to the original non-linear formulation and can be solved more efficiently. The difference between the optimization model with non-linear loss models and linear loss models is illustrated for a residential DC-coupled PV-battery system. The linear loss model is shown to result in an underestimation of the battery size and cost as well as a lower utilization of the battery. The proposed method is useful to accurately model the impact of losses on the optimal sizing and operation in exchange for a slightly higher computational time compared to linear loss models, though far below that of solving the non-relaxed non-linear problem.