Challenges to accommodate renewables increases as the share of variable renewable energy grows. To address this, power sector transformation should be approached in a multi-dimensional way, as these challenges and related measures are dependent on characteristics including: country-size; temperature and seasonal patterns; existing generation fleet; storage assets; transmission grid; renewables-load mismatch; neighbour-country profiles; market design; regulatory framework and many other aspects.
The IRENA Knowledge Framework for the power sector transformation helps countries identify the next steps towards power system decarbonisation by diagnosing areas that might require further attention to move forward with renewables. By observing front-runner countries’ learning-by-doing pathways, the Power Sector Transformation Knowledge Framework gathers useful information, benchmark experiences, and successful measures, that can be shared with other countries that have similar enabling conditions in place.
As part of this approach, IRENA has developed over twenty indicators allocated in the following macro-sectors: flexibility; transmission; demand response and storage; interconnectors; operation and markets.
The Knowledge Framework assists IRENA Members by providing possible solutions to address specific power sector transformation challenges in a given country. Recently, the Framework provided inputs for the current state and outlook of solutions to integrate high shares of variable renewable energy (VRE) for G20 countries on request by the 2019 Japanese G20 presidency.
IRENA organises workshops with countries that have faced similar challenges, as well as with countries that have successfully overcome such challenges, to discuss best practices and their applicability based on enabling conditions and efficient ways to put them into place. In addition, relevant literature and other materials are provided from IRENA and its partners’ work in the field, to highlight methodologies and power system studies to develop the solutions identified.