Screening Curve Method for Economic Analysis of Household Solar Energy Self-Consumption

TL;DR

This paper introduces a novel extension of the Screening Curve Method (SCM) for economically analyzing household PV self-consumption with batteries, enabling quick, intuitive, and accurate sizing of systems considering renewable intermittency.

Contribution

It generalizes the SCM framework to account for renewable variability and applies it to household PV and battery sizing, providing a practical tool for economic analysis.

Findings

The proposed SCM accurately estimates optimal PV and battery sizes.

It effectively illustrates cost curves for decision-making.

Numerical studies confirm the method's usefulness in sensitivity analysis.

Abstract

The profitability of solar energy self-consumption in households, the so-called photovoltaic (PV) self-consumption, is expected to boost the deployment of PV and battery storage systems. This paper develops a novel method for economic analysis of PV self-consumption using battery storage based on an extension of the Screening Curve Method (SCM). The SCM enables quick and intuitive estimation of the least-cost generation mix for a target load curve and has been used for generation planning for bulk power systems. In this paper, we generalize the framework of existing SCM to take into account the intermittent nature of renewable energy sources and apply it to the problem of optimal sizing of PV and battery storage systems for a household. Numerical studies are provided to verify the estimation accuracy of the proposed SCM and to illustrate its effectiveness in a sensitivity analysis, owing to its ability to show intuitive plots of cost curves for researchers or policy-makers to understand the reasons behind the optimization results.