Multi-Objective Optimization of a Hybrid Solar-Wind-Battery System Under Negative Price Market Conditions

Fossil fuels are finite. Global reserves are diminishing, and their contribution to increased climate risks signifies a demand for alternatives. Renewable sources have solidified their position as the future of energy, with global initiatives underway to transition towards a net zero future. This transition comes with challenges, one being the rising incidence of negative energy prices from increased renewable penetration. This paper provides insight into the operation of a Hybrid Renewable Energy System within a region of high negative price market saturation and contributes to developing optimization strategies for transitioning regions, using South Australia as a case study. A Mixed-Integer Linear Programming model is developed with two primary objectives: maximizing Self-Sufficiency and minimizing Net Operating Costs. The model is executed under four weather scenarios and three battery sizes and evaluated for Self-Sufficiency, Net Operating Cost, and Curtailment. Results found the Low Solar/High Wind scenario produced the greatest performance due to its steady renewable profile, whereas battery scaling demonstrated diminishing returns. This indicates battery scaling alone is insufficient in tackling transitional challenges. The study highlights the demand for more extensive strategies to support net zero transitions and minimise the impact and occurrence of negative market prices.