Climate Impacts on Energy Systems

Page 118

76

World Bank Study

Table 5.4. Hydro-meteorological and/or Climate Parameters and Select Energy Uses Hydro-meteorological and/or climate parameter

Selected energy sector uses

Air temperature

Turbine production efficiency, air source generation potential and output, demand (cooling/heating), demand simulation/modeling, solar PV panel efficiency

Rainfall

Hydro-generation potential and efficiency, biomass production, demand, demand simulation/modeling

Wind speed and/or direction

Wind generation potential and efficiency, demand, demand simulation/ modeling

Cloudiness

Solar generation potential, demand, demand simulation/modeling

Snowfall and ice accretion

Power line maintenance, demand, demand simulation/modeling

Humidity

Demand, demand simulation/modeling

Short-wave radiation

Solar generation potential and output, output modeling, demand, demand simulation/modeling

River flow

Hydro-generation and potential, hydro-generation modeling (including dam control), power station cooling water demands

Coastal wave height and frequency, and statistics

Wave generation potential and output, generation modeling, off-shore infrastructure protection and design

Sub-surface soil temperatures

Ground source generation potential and output

Flood statistics

Raw material production and delivery, infrastructure protection and design, cooling water demands

Drought statistics

Hydro-generation output, demand

Storm statistics (includes strong winds, heavy rain, hail, lightning)

Infrastructure protection and design, demand surges

Sea level

Offshore operations

Source: Generated by authors.

Numerous sources of these data are available for a range of time scales, both historical and as predicted for the future, as listed in Table 5.5. Locations of global data received on one particular day in 2007 at European Centre for Medium-Range Weather Forecasts (ECMWF) (Reading, UK) are shown in Figure 5.1, which illustrates (clockwise from top left): surface, aircraft, orbiting satellites, stationary satellites. Data-sparse areas over the continents stand out as blank areas in the surface plot, over Africa in particular, and while data for these areas can be in-filled using information from the satellites, doing so creates a Catch-22 situation, as it cannot be done to high quality without using concurrent in situ data (Tribbia and Troccoli, 2008). The forms in which hydro-meteorological/climate information is typically provided to the energy (and for that ma er, most other) sector(s) are as presented in Table 5.6.


Issuu converts static files into: digital portfolios, online yearbooks, online catalogs, digital photo albums and more. Sign up and create your flipbook.