The Global Centre for Risk and Innovation (GCRI)
Wind and solar output follows the weather, so a power system built on them must plan for the hours, days and seasons when the weather does not cooperate. Storage, flexible demand, interconnection and dispatchable generation fill the gaps, each over a different duration. This page sets out how weather variability becomes a system risk, how storage technologies differ, and what evidence planners, operators and regulators use to size flexibility.
GCRI · Established · service level R0
Renewable variability is the change in wind and solar output with the weather over hours, days and seasons. A power system built on these sources must plan for spells when output is low across wide areas, and fills the gaps with storage, flexible demand, interconnection and dispatchable plants, each covering a different duration.
Where demand concentrates in cities and the rail, road and port corridors that move fuel and equipment, shown for Viet Nam as an example geography for this subject.
The working screen behind this subject: its structure, terms and states. Names are placeholders and values illustrative.
Renewables and storage · Day ahead · Control area 2
available vs required
| ST-1 | Battery | 34 | 107 | Available |
| PH-2 | Pumped hydro | 88 | 269 | Available |
| DR-East | Demand response | n/a | 74 | Contracted |
Storage technologies and weather variability. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Wind output varies with pressure systems over days, and solar with cloud, season and latitude. Long, calm, overcast spells in winter, sometimes called dark doldrums, are the stress case that planners size firm capacity and storage against.
Plants spread over a large area smooth each other only when their weather is uncorrelated. A persistent high-pressure system can suppress wind across several countries at once, so interconnection helps less than geography alone suggests.
Batteries shift energy over hours, pumped hydro over hours to days, and hydrogen or other long-duration options over weeks or seasons. Each duration answers a different gap, and no single technology answers all of them at acceptable cost.
Inverter-based plants provide no inertia unless designed and paid to. Fault ride-through, grid-forming control and fast frequency response decide whether a grid with a high share of renewables survives a disturbance.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Capacity factor | Actual generation over a period divided by the generation at full rated output for the same period. |
| Dunkelflaute | A spell of low wind and low solar output, often in winter, also called a dark doldrum. |
| Residual load | Demand minus variable renewable generation, the load the rest of the system must meet. |
| Round-trip efficiency | The share of energy put into storage that can be taken back out. |
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Wind and solar capacity factor | percent of rated output | hourly and annual | Metered generation against installed capacity | OBSERVED |
| Residual load | megawatts | hourly | Demand minus variable generation | ESTIMATED |
| Low-generation spell duration | hours below a stated output threshold | per event | Reanalysis-driven generation models | MODELLED |
| Curtailed renewable energy | megawatt hours | monthly | Operator reports | REPORTED |
| Installed storage power and energy | megawatts; megawatt hours | quarterly | Capacity registers and statistics | OFFICIAL |
| Storage round-trip efficiency | percent | per asset | Metered charge and discharge | OBSERVED |
| Solar and wind resource | kilowatt hours per square metre; metres per second | long-term average | Resource atlases | MODELLED |
The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.
Fig. 02Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| IRENA renewable capacity and generation statistics (IRENASTAT) | Installed capacity and generation by technology and country | Free, attribution |
| Ember electricity data | Monthly and annual generation by source for many countries | Free and open, attribution |
| Global Solar Atlas and Global Wind Atlas (World Bank, ESMAP, DTU) | Long-term solar irradiation and wind resource maps | Free and open, attribution |
| ERA5 reanalysis (Copernicus) | Hourly wind, irradiance and temperature to build weather-driven generation series | Free and open, attribution |
| Copernicus Climate Change Service energy indicators | Climate-driven wind, solar and demand indicators for Europe | Free and open, attribution |
| Renewables.ninja | Simulated hourly wind and solar output for any location | Free for non-commercial use, attribution |
| DOE Global Energy Storage Database (Sandia) | Storage projects by technology, status and size | Public domain |
Energy Nexus prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| System planners and transmission operators | How much firm and flexible capacity a high-renewable system needs, and of which duration | Multi-decade weather-year ensembles; low-generation spell catalogues |
| Energy regulators | How to design markets and grid codes that reward flexibility and grid-forming capability | Curtailment records, residual load profiles, grid code requirements |
| Ministries and development finance institutions | Which storage technologies to support and where | Storage scenarios by duration with costs, materials and safety stated |
| Fire services and local planning authorities | What battery storage sites require in permitting and emergency planning | Thermal-runaway evidence from published incidents and fire safety standards |
Large weather systems affect many wind and solar sites at once. Geographic spread reduces but does not remove correlation.
Storage has a power rating and an energy capacity. Short-duration batteries handle fast balancing; long gaps need much larger energy stores.
Battery cells age with cycling and temperature, and thermal runaway is a known hazard that design and siting must address.
Decades of reconstructed weather allow simulation of wind and solar output over many years. Reanalysis smooths local extremes and may misrepresent future climate.
Optimization models choose least-cost mixes of generation and storage. Results are sensitive to cost assumptions and to how many weather years are included.
Laboratory and field data on cell ageing and failure, grounded in materials science and chemistry. Field data on large installations is still accumulating.
Tests whether a given mix meets demand through rare weather sequences. The rarest events are, by nature, the least well sampled.
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.