Meteorology encompasses the science of both weather and climate. The energy sector has diverse requirements for meteorological services to support decision-making for both day-to-day operations and for longer-term strategic planning.
This requirement is driven in part by the natural climate variability (including extreme weather events) and increasingly by climate change as manifested through the physical climate and through policy responses to the issue.
The required meteorological services can be broadly categorized in two ways:
- Those that support decision-making concerning the implementation and operation of new technologies for energy production; and
- Those that support decision-making for reducing greenhouse gas and polluting emissions by existing energy sector infrastructure.
This article addresses the issues surrounding the availability, supply and use of meteorological services in the energy sector, particularly that part of the sector responsible for producing electricity. It also endeavours to examine the challenges and opportunities that meteorological services could assist in addressing. The WMO-led Global Framework for Climate Services (GFCS) – a new global information service – is also described.
Factors affecting electricity production
The energy sector’s requirement for meteorological services clearly needs to be addressed within the context of climate change. But this is certainly not the only, and possibly not even the dominant, driver of change for the sector in the decades ahead. The economics of the industry will always be fundamental. Evolution and revolution in the cost of the various energy production technologies, whether determined through government policy or by new scientific and technological developments, will be the key driver. Also, the demographics of the market (size and location of the energy consumers) for energy will continue to be an important driver in the overall market.
Starting with demographics, it is clear that rising population, particularly in urban centres, is increasing the demand for energy, with peak demand in many countries now occurring in summer as the total capacity of installed air conditioning systems continues to grow. Added to this is the demand for reliable, high-quality electricity supply as more and more businesses and homes rely on, or at least expect, that the electronic devices they use will be continuously available. The aggregate sensitivity of demand for domestic electricity to the meteorological conditions is reflected by the use of the measure of degree days. A relatively benign climate is one for which the sum of the annual average number of Heating Degree Days and Cooling Degree Days (Figure 1) is relatively small (say less than 2 000). However, national averages hide important regional variations for large countries, such as Australia. It must also be noted that the energy industry must be scaled to accommodate the extremes, not just the annual mean values of heating and cooling degree days1, now and in the future.
|Figure 1 — Spread of annual mean number of heating degree days (HDD) against cooling degree days (CDD) for 171 countries, using a baseline of 18°C for the zero HDD and CDD temperature (Baumert and Selman, 2003).|
Technological change is also occurring at a rapid pace. For countries with access to reserves of coal, it is clear that large-scale, coal-fired plants are the most cost effective way to generate electricity. The price competitiveness of niche energy production systems whose efficiency is affected by meteorological conditions, such as wind and solar, is improving. However, for large-scale, grid-connected applications coal-, hydro-and increasingly gas-generations are the preferred options.
Meteorological conditions also affect production. Extreme events such as Australia’s Queensland floods, that occurred in December 2010 through to early 2011, caused widespread disruption as open-cut coal mines, a source of coal for power stations, were flooded. For the producers of hydroelectricity the occurrence, or lack of rainfall is a major determinant on their ability to generate electricity. For solar producers the key is sunshine hours, while for wind farms the variable used to assess sites is the mean wind speed at the height of the hub of the wind-generating propeller, with a mean wind speed exceeding 8 m/s found at excellent sites and 7 m/s at good sites.
From Table 1 it can be seen that as the efficiency of the wind generation technologies improves to make them economically viable at lower speeds, the area of land suitable for wind farms increases logarithmically.
Table 1 — Wind field mapping for 80 000 km2 (Coppin, Ayotte and Steggel, 2003) in the vicinity of the Great Dividing range in Eastern New South Wales showing the percentage of the non-woodland area, and actual area, where specified mean wind thresholds are exceeded.
This section takes a user perspective on the demand for meteorological services to the sector of the economy responsible for electricity generation and distribution. To further limit the scope of the analysis, the article considers five classes of decision-makers who might conceivably use weather and climate information to make decisions relating to the electricity supply sector: the public, electricity grid managers, policy-makers, energy sector investors and energy traders (see Table 2). The requirements of these different classes of decision-makers differ markedly and have the potential to conflict in some areas.
The public generally expects their electricity supply to work effectively day-in, day-out. The times when meteorological factors work towards threatening supply will most likely be during severe weather. If a severe storm or bushfire during a heat wave threatens supply, the public has a reasonable expectation of forewarning.
Similarly, if high demand for electricity during a heat wave is likely to lead to power outages or electricity rationing, again the public expects forewarning. In the lead up to and during such events, products and services that combine weather information from the meteorological community integrated with information relating to infrastructure vulnerability and likely demand are required from the electricity sector.
There may also be interest in the climatology, or likelihood of the occurrence, of such events. Given the broad range of experience and expertise in the public using meteorological services, the emphasis is often placed on simple products that are routinely available.
Electricity grid managers
The managers of the grid affecting the public (and industry) have a great deal of responsibility placed upon them in terms of managing the mix of sources and the distribution of electricity between regions.
The variability in demand will be driven by a number of parameters. For example, is it a weekend, public holiday or normal working day, and will it be a high heating or cooling degree day for some part of the grid? Variability of supply is also important; has rainfall been high enough to support a good level of peak hydro-electricity supply, will the peak demand have to be accommodated with a high level of electricity from gas generation, and, as the newer sources such as wind and solar become significant, how will they impact supply?
The electricity grid manager needs real-time temperature, wind and rainfall data as inputs to relatively sophisticated supply and demand models, the output from which is an input to decision-making. It is likely that the grid manager would have some interest in climatological information, but it is most likely that this would not be highly important for day-to-day operations.
Policymakers have two timescales of interest. They are keenly interested in extreme weather events that impact negatively on supply of electricity. They will expect detailed warnings of the likelihood of such events along with frequent updates during the lifetimes of such events. Policymakers will also be critically interested in the timescales of the investments in infrastructure in the industry, typically 40–50 years. On the longer timescales they would expect climatological scenarios to be integrated with sophisticated modelling of energy demand.
Policymakers would expect to be supplied with a mixture of “in confidence” advice from the model analysis, as well as products and information tailored for public release.
Investors, as distinct from energy traders, are likely to be less interested in the short-term outlook for the energy sector than that of the medium to long term. It is considered here that the investor has the intention of investing in some aspect of electricity generation for the medium to long term through the commitment of funds to electricity by way of equity or debt mechanisms.
The investor will most probably require access to sophisticated modelling that would underpin decision-making if the scale of investment were to be significant. For example, at the level of state and national governments multidisciplinary analysis bringing together the known climatology of extremes; some assessment of their possible changes under climate change; and evolutions in electricity generating technologies, changing population and industry demographics, would all need to be brought together in an integrated assessment of the financial viability of the investment.
Smaller-scale investments and one-off investment decisions would be unlikely to command such detailed and expensive analyses.
From the meteorological sector energy traders require good forecasts of likely disruptions to supply along with forecasts of heating and cooling degree days, preferably ones that are not available to their fellow traders until they have made their trades. To obtain a market edge, high-volume traders would likely seek a “bespoke” model that takes real-time meteorological inputs and provide traders with forecasts of likely demand that are uniquely available to them.
Table 2 — The demand for different types of meteorological information for five classes of decision-makers with an interest in the electricity segment of the energy sector. Coloured shading provides a subjective assessment of the importance of three types of meteorological product.
Uses of meteorological information
Providing basic real-time meteorological data – including observations of temperature, wind velocity, rainfall, radar and satellite imagery – is a valuable service needed to underpin decision-making in this sector. All decision-makers also require good forecasts and climatological norms of these parameters where scientifically possible for informed decision-making. The real-time observations and short-term forecasts need to be authoritative, quality controlled and reliably and routinely available if decision-making is to be properly informed. Markets need information. Efficient markets provide all decision-makers access, at least in principle, to the same data. If the market for electricity is to be efficient, buyers and sellers in that marketplace must have access to meteorological data services.
It should be emphasized that real-time, routine short-term (“weather timescale” of 12 hours to 10 days) forecasts of temperature, wind and rain are produced by a small number of very advanced centres operating massive supercomputer installations and supported by hundreds of scientists. A large amount of data outputs from these centres are freely exchanged around the world by the meteorological community and, sometimes more on a commercial basis, are available for integration into bespoke energy sector forecast systems.
It is clear that the greatest return on the investment in these systems, in global terms, is achieved by the most widespread use of the resultant data in decision-making processes.
With the possible exception of the public, which requires access to robust but simple analyses and forecasts, all sectors have a high demand for integrated, multidisciplinary analyses that make the most effective use of meteorological information relevant to their decision-making. Integrating different data types into sophisticated, user-specific analyses and forecast systems is a specialist skill requiring multidisciplinary inputs, including from climate scientists. Even in developed countries the pool of such expertise is relatively small.
One of the challenges in providing improved climate services is to build this skill pool. A second challenge is that while the basic data and forecasts are clearly a public good, the bespoke forecasting systems serving a specific user are clearly in the commercial domain. Where public interest ends and private interest begins is a matter of government policy in order to define the scope of government services, including those that are to be provided to support the private sector.
|The Babinda open-cut coal mine, Queensland, Australia, was flooded in January 2011.|
To assist the private investors and companies investing in solar or wind electricity generation technologies, governments in developed countries may produce national or regional climatologies of parameters such as the available solar energy for domestic hot water production or conversion to electricity for the country (Figure 2).
|Figure 2 - Concentrating solar potential for the United States (Units kWh/m2/Day).|
|Source: US EPA. The US Department of Energy’s National Renewable Energy Laboratory (NREL) developed the Concentrating Solar Resource model (Maxwell, George, and Wilcox, 1998; and George and Maxwell, 1999).|
Governments and the private sector may generate more detailed products such as regional scale maps of mean wind speed at a typical wind generator hub height (Figure 3), with the added advantage of also illustrating where transmission lines are available to collect electricity generated using wind power.
|Figure 3 - Regional wind power resources.|
A new global information service
There are many potential weather and climate services that will be of great use for the electricity production and distribution sector. The United Nations System, with leadership from WMO, is now implementing a Global Framework for Climate Services (GFCS). GFCS is aimed at making available globally the best possible climate information, which will inevitably also provide access to a growing array of real-time (weather timescale) data. This data will be structured in a way that will help decision-makers (business people, politicians, workers, etc.) make the best possible decisions for activities affected by climate.
In countries that have effective climate services, these services already contribute greatly to reducing risks and maximizing opportunities associated with climate. However, there is a significant gap between the supply of climate services and the needs of users. As noted above, current capabilities to provide climate services do not exploit all that is known about climate, fall far short of meeting present and future needs, and are not delivering their full and potential benefits. This is particularly the case in developing and least developed countries, which are also the most vulnerable to the impacts of climate variability and change.
Meeting users’ needs
To be useful, climate information must be tailored to meet the needs of users. Existing climate services are not focused well enough on user needs. In addition, the level of interaction between providers and users of climate services is inadequate. Users need access to expert advice and support to help them select and properly apply climate information.
To support climate services, high-quality observations, which also consider relevant socio-economic variables, are required across the entire climate system. While existing capabilities for climate observation provide a reasonable basis for strengthening climate services, commitment to sustaining high-quality observations is inadequate and enhancements to existing networks are required, particularly in developing countries. Further effort is also needed by governments and others to improve and enhance sharing of, and access to, climate and other relevant data.
Effective climate services will depend on maximizing the potential of existing knowledge, new research developments and strong support from and strengthened collaboration between all relevant research communities. Understanding of the climate system is advancing quickly but is not being effectively translated into services that can inform decision-making. In particular, further effort is required to improve our ability to predict climate and help users incorporate its inherent uncertainty into their decision-making.
Managing climate risk
Efforts to provide effective climate services globally will only be successful if capacity is systematically built to enable all countries to manage climate risk effectively. Current capacity building activities to support climate services need to be scaled up and better coordinated. A comprehensive capacity building initiative is needed to strengthen existing capabilities in the areas of governance, management, human resources development, leadership, partnership creation, science communication, service delivery and resource mobilization.
To make this new GFCS truly effective for the electricity production and distribution elements of the energy sector, for the energy sector more generally and for the broader community, a closer engagement between meteorological professionals and decision-makers will be needed. This will ensure that the most effective research and development is carried out, that observation systems are designed to meet contemporary and emerging needs, that data sets from various disciplines (meteorology, economics, geography, etc.) are interoperable, and that the most useful products are reliably and rapidly distributed to those who need them. But most importantly, there needs to be close engagement between service users and providers.
Today, industry relevant meteorological consultants are a rare breed and operational weather and climate services tailored to maximize the effectiveness of decision-making in the private sector are relatively rare. A key outcome of implementing the GFCS would be the building of this sector throughout the world.
Baumert K., and M. Selman, 2003: Heating and Cooling Degree Days. A report of the World Resource Institute.
Coppin, P. A., K.A. Ayotte and N. Steggel, 2003: “Wind Resource Assessment in Australia – A Planners Guide”. A Report of the CSIRO Wind Energy Research Unit, CSIRO Land and Water.
George, R. and E. Maxwell, 1999: “High-Resolution Maps of Solar Collector Performance Using A Climatological Solar Radiation Model”. Proceedings of the 1999 Annual Conference, American Solar Energy Society; Portland, Maine.
Maxwell, E., R. George, and S. Wilcox, 1998: “A Climatological Solar Radiation Model”. Proceedings of the 1998 Annual Conference, American Solar Energy Society; Albuquerque, New Mexico.
World Meteorological Organization, 2011: Climate Knowledge for Action: A Global Framework for Climate Services. (WMO No. 1065, 240 pp.), Geneva.
1 Unit for estimating the demand for energy required for heating or cooling. In the United States, the typical standard indoor temperature is 65°F (18.3°C). For each 1°F decrease or increase from this standard in the average outside temperature for each day this occurs, one heating or cooling degree day is recorded.