GenCost 2018: Updated projections of electricity generation technology costs

[摘要] Electricity market modelling for the exploration of alternative energy futures remain an important part of strategy planning for government, institutions and industry. Regularly updated current and projected electricity generation and storage technology cost information remains a necessary and highly impactful input into electricity market modelling studies. Furthermore, there are substantial coordination benefits if all parties are using similar cost data sets for these activities or at least have a common reference point for differences.This GenCost project is the result of a collaboration between CSIRO and AEMO, together with stakeholder input, to deliver an annual process of updating electricity generation costs. CSIRO and AEMO have both committed their own resources to deliver the project with the aim of increasing the likelihood of delivering the continuity that was not achieved in predecessor studies. Wide stakeholder engagement and transparency are also built into the project design. The main workshops and other engagement supporting this activity were held in August through November 2018.The projection methodology is grounded in a global electricity generation and capital cost projection model recognising that cost reductions experienced in Australia are largely a function of global technology deployment. The updated projections indicate that solar photovoltaic (PV) capital costs continue to fall at a faster rate than most other technologies and solar PV is projected to represent one of the largest contributors to electricity generation by 2050. Wind, batteries, pumped hydro and CCS are also expected to feature more strongly in the global electricity generation mix and consequently achieve cost reduction through increased deployment. Pumpedhydro and compressed air storage are new inclusions in the technology set compared to previous equivalent studies and highlight the expected increasing role for storage in the electricity system.While the capital cost projections are primarily designed to be included in Australian electricity modelling studies as scenario inputs we recognise that some stakeholders require access to levelised cost of electricity (LCOE) data for comparing technologies outside of models. On the other hand LCOE estimates, in their current form, can be misleading if they apply the same discount rate regardless of exposure to climate policy risk and inherently do not recognise theadditional balancing technology that is required by variable renewable generation as its share of the generation mix increases. Given the variable renewable share is expected to increase in mostAustralian states, towards or beyond 50%, this is an issue that needs to be solved. This report provides some advice on what comparisons are and are not appropriate using current methods and describes a process by which future updates will seek to solve this issue with new approaches.Finally, like storage, demand management is another resource which we expect the electricity sector will need to draw on more deeply in coming years to assist in balancing the system and reducing system costs. However, demand management costs and the scale of their potential contribution varies widely depending on the customer and timeframe. We find that a significant amount of data related to demand management costs is already available, but its ongoingcollection can be costly so the next step is to prioritise the most attractive demand management resources to monitor.

[发布机构] CSIRO

[效力级别] Environment and Resource Economics [学科分类] 地球科学(综合)