Hydropower and Pumped Hydro Energy StorageProject Battery of the Nation Future State NEM Analysis (Stage 2)
The Battery of the Nation initiative is investigating and developing a pathway for future development opportunities for Tasmania to make a greater contribution to the NEM. ARENA has co-funded six projects with HydroTasmania under the initiative, which are helping to explore locations, finance models, market challenges and opportunities.
Australia’s National Electricity Market (NEM) is undergoing a transformation; over coming years, the NEM is expected to be very different from today. Planning for the changing power system requires strategic decision making – and these decisions must be informed to the greatest extent possible.
There are a range of options to inform strategic planning; however, in a rapidly changing system, it is critical to understand and capture the impact of the factors that are influencing the change. ‘Common sense’, experience-educated guesses and extrapolated trends are all firmly based on the past. Modelling can capture the impact of new and changing drivers that might influence the future power system. Therefore, modelling has the best chance to represent the future behaviours and patterns of development for a transforming or transitioning power system. This information will be critical to strategic planning. Modelling is the best option we have to try to understand and plan for the future power system – yet models are far from perfect. During a transformation, substantial uncertainty is unavoidable. Moreover, the fundamental characteristics of the market are expected to change, and this is likely to challenge the capabilities of our existing tools.
It is critical that decision makers understand the context and the challenges faced by modelling to be able to best use the information in their decision making processes. The days of being given a simple single answer are probably gone – we need more nuanced information to make decisions based on a wider range of inputs, patterns, projections and plausible scenarios.
The modellers also need to understand the questions that need to be answered. Since no model is perfect, there are always trade-offs to be made. If the modellers understand the decisions that need to be made, they can develop scenarios and tools that are suited to answering those specific uncertainties.