Weather Matters for Energy

In this chapter it is argued that the successful transformation of the world’s energy systems depends on enhanced interplay between the meteorological and energy sciences. Key drivers of the energy transformation are described and the likely attributes and challenges of our future energy system are outlined. We identify a framework and give examples of ways in which a new cross-disciplinary science that truly combines energy and meteorological expertise will significantly reduce the risks and costs inherent in energy infrastructure. The need for this cross-disciplinary science is urgent given the scale and complexity of current and future energy infrastructure and its increasing vulnerability to the vagaries of the weather. Short-term opportunities to foster a much closer collaboration between energy and meteorology are also discussed.

Climate change adds a new source of unknowns for the electricity sector. Despite considerable risks and opportunities, energy sector actions to manage climate change risks and take advantage of future opportunities remain limited and patchy. An estimate of the sums spent since 2000 and planned out to the 2020s by five utilities on climate risk management totals US$1.5 billion. Considering that these investments are to address climate change risks or opportunities of a considerable magnitude, they are relatively modest. The sector has focused on climate data analysis and research on impacts rather than on concrete capital, technological and/or behavioral adaptation responses. Further, most of this research is concentrated for the most part in the developed world and on a handful of climate change impacts. Analysis of early adapters in the electricity sector offers a number of useful lessons for power utilities, regulators and stakeholders in the developing world, for instance: (i) joint efforts between the electricity sector and hydrometeorological offices to develop high quality and tailored climate data and information are needed to avoid ‘wait-and-see’ strategies among power utilities; (ii) energy sector adaptation requires going beyond high level research on impacts and adaptation to produce information that can be applied operationally; (iii) without a business environment favorable to climate change adaptation, power utilities have little incentive to go beyond ‘business-as-usual’ weather risk management; and (iv) it is by building the economic case for adaptation that utilities can be incentivized to take action.

Why do we need to be concerned about the role of meteorology in the energy system? How large a change in meteorological variables could have adverse effect on energy systems? These are the underlying questions explored in this chapter. In particular, we note that not only is the energy sector at risk from future climate changes, it is also at risk from current hydro-meteorological climate variability and change. It is important therefore to assess the climate observed in recent decades along with the changes we might expect in the future. By examining a selection of meteorological variables, this chapter exposes how climate has been, and will continue to be, variable on climatic timescales. The extent to which such variability (and extremes) could be modified under climate change, and therefore have an impact on the energy sector is discussed. Current understanding of pertinent changes in extreme weather events, and estimates of impacts on the energy sector given climate change are also summarised.

Renewable energy systems currently meet only around 7–8 % of the total global heating, cooling, electricity and transport end-use energy demands (Traditional biomass provides around 6.3 % of global primary energy and all other renewables around 6.7 %, but end-use energy is a more useful statistic used in this context). However, rapid growth in renewable energy has been apparent in recent years as a result of improved technology performance efficiencies and lower costs being demonstrated. Given appropriate support policies, renewables have the economic potential to significantly increase their share of total energy supply over the next few decades. The IPCC Special Report on this subject released in May 2011, covered cost trends, opportunities and barriers. This chapter summarises the findings of that report (The author, who was a Co-ordinating Lead Author for “Integration” of this IPCC report and co-author of the Summary for Policy Makers (SPM) and Technical Summary, acknowledges the inputs from around 150 co-authors and staff of the IPCC Technical Support Unit who contributed to writing the report and producing the SPM on which this chapter is largely based. See http://​srren.​org for the full report, list of authors, and extensive list of references that support the assessment). Most renewable energy resources are dependent on the local climate so there is a risk that they may be impacted by climate change. The size of the technical potentials of renewable energy resources and their geographic distribution could be affected, but there remains much uncertainty. The potential of renewable energy resources, even if significantly reduced, will still far exceed the projected global demand for primary energy, at least out to 2050. All mitigation scenarios show that renewable energy could provide a large share of energy demand in all regions.

Over the next 50 years changes to temperatures, rainfall patterns, sea levels and more extreme weather are expected globally. The UK energy industry must prepare its infrastructure for the challenges ahead. The Government is investing GBP 200 billion over the next 5–10 years to build a low carbon society. The challenge lies in using this funding to build a climate resilient infrastructure through national strategic planning. This will ensure best value for adaptation and long-term sustainability that supports the transition. The UK Energy companies have taken a sector lead, combining existing and new infrastructure assets with long operational lifetimes to increase the sector’s resilience to climate change.

This chapter describes some activities carried out in Italy dealing with the impact of climatic and meteorological variability on the Italian Electric System. Every item presented attends to a real problem coming from the interaction between atmosphere and energy system. In particular the activities described are relevant to the evaluation of climate change impact on the energy system, the prediction of solar and wind energy production, the monitoring and forecasting of risks for the power system coming from the weather due to insulators surface pollution, ice and snow loads on overhead lines, storms and lightning phenomena.

This chapter presents information on weather and climate effects in the Australian National Electricity Market (NEM). The effects are considered in two classifications: Operational effects and impacts, representing the short- to medium-term effects and responses and how these are managed by power system operators. Planning impacts, representing the longer term considerations that must be given to power system planning and development in order to accommodate increasing renewable energy generation and climatic changes. The main focus is on wind and solar power, both of which are already present in the NEM and both of which are forecast to increase significantly over the coming decade. Solar and wind variability and diversity are key characteristics for both operational and planning purposes and existing and proposed approaches are discussed.

The impact of weather on the generation, transmission, distribution and use of energy is wide and severe in Africa, where 80 % of the population relies on traditional biomass (solid wood, twigs, and cow dung) energy. Achieving quick transition from traditional to modern energy sources and increasing access to clean and affordable energy services are among the key objectives of energy strategies of many African countries and the New Partnership for Africa’s Development (NEPAD)—the blueprint for Africa’s development. In this endeavor, modern bioenergy, particularly the production and processing of its liquid form, biofuels, has ascended to the top of the energy development agenda. This chapter explores the two way connection between bioenergy and weather/climate change to shed light on the extent of vulnerabilities of the bioenergy sector to weather and how climate change is impacted by developments in the sector. The chapter caps its analysis by proposing measures to better adapt to and mitigate climate change while improving energy production and efficiency.

Weather and climate information plays an important role in decision-making in the energy sector. Energy-specific meteorological services are based heavily on the national and international meteorological infrastructure put in place to provide information, forecasting, warning and advisory services to all weather- and climate-sensitive sectors of society. Recent advances in atmospheric, oceanic and hydrological observation, data collection, modelling, forecasting and warning systems, and in national and international arrangements for service provision, offer many opportunities for increased benefit for the energy industry from effective application of meteorological and related science and services.

The energy sector has a diverse requirement 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 meteorological services required for decision-making in this sector can be broadly categorised into two ways: (i) those that support decision-making concerning the implementation and operation of new technologies for energy production, and (ii) those that support decision-making for maintaining service and reducing emissions by existing energy sector infrastructure. This chapter focuses on the electricity production sector and examines the types of services that are currently available, and also those that are likely to be needed in the future. The chapter concludes with a discussion of the likely climate and weather service provision mechanisms that will best meet the energy sector’s needs, and the role that the Global Framework for Climate Services could be expected to play in meeting these needs.

This chapter briefly describes how Earth Observation (EO) from space—in particular from satellite missions of the European Space Agency (ESA)—can support the energy sector by delivering accurate, consistent, and timely information on the state of the environment and natural resources. Some examples are presented of EO demonstration pilot projects performed in partnership with leading industrial players in Oil and Gas and Renewable Energy sector within the framework of the ESA Earth Observation Market Development (EOMD) program. The benefits and limitations of EO-based information services in supporting the whole life cycle of energy production, from technical and investment feasibility study up to the distribution and trading of electricity are highlighted and discussed.

Here we discuss the status and challenges in the development of atlases for the assessment of the regional and global wind resources. The text more specifically describes a methodology that is under development at DTU Wind Energy in Denmark. As the wind assessment is based on mesoscale modelling, some of the specific challenges in mesoscale modelling for wind energy purposes are discussed such as wind profiles and long-term statistics of the wind speed time series. Solutions to these challenges will help secure an economic and effective deployment of wind energy.

The National Center for Atmospheric Research (NCAR) has configured a Wind Power Forecasting System for Xcel Energy that integrates high resolution and ensemble modeling with artificial intelligence methods. This state-of-the-science forecasting system includes specific technologies for short-term detection of wind power ramps, including a Variational Doppler Radar Analysis System and an expert system. This chapter describes this forecasting system and how wind power forecasting can significantly improve grid integration by improving reliability in a manner that can minimize costs. Errors in forecasts become opportunity costs in the energy market; thus, more accurate forecasts have the potential to save substantial amounts of money for the utilities and their ratepayers. As renewable energy expands, it becomes more important to provide high-quality forecasts so that renewable energy can carve out its place in the energy mix.

Detailed, regionally specific information about the present and future climate is useful to the energy industry. Climate change impacts both energy demand (e.g. heating and cooling) and also generation (e.g. wind regime for turbines). New projects need to consider the current climate as well as future climate projections for the lifespan of the infrastructure. Typical global climate models give information for a 100–200 km grid box but dynamically downscaling using a regional climate model (RCM) can give more detailed information. This chapter describes the different approaches to dynamical downscaling, the issues associated with them and possible applications for the energy sector.

Weather forecasts will never be perfect and hence they will always contain some degree of uncertainty. In this chapter, we argue that uncertain weather forecasts expressed in a probabilistic format can provide more value to users in the energy sector than simple, apparently confident deterministic forecasts, even when the latter show a satisfactory level of accuracy. Knowledge of the user-specific loss function is required to achieve best value.

Probability methods provide quantitative insight into the implications of atmospheric variability for the energy industry. Contemporary computer probability forecasts of climate anomalies for the weeks, months, or seasons ahead offer new precision in managing both risk and opportunity. The forecasts of two major international centers and a multi-model constructed from them by the World Climate Service demonstrate that the contemporary probability forecasts have sufficient skill and reliability to provide advantageous guidance for energy decisions. An analytical model of choices available in response to predicted anomalies illustrates how and when to act on forecasts. Atmospheric informatics is introduced as a system for creating, transferring, and applying atmospheric information in important endeavors. The aim is to show energy and other industry decision-makers what they need to know—now.

Weather and climate information is essential to the energy sector. The power sector in particular has been using both observations and forecasts of many meteorological and hydrological parameters for several decades. In the last 10 years, a clear upward trend has been observed in the number, complexity, and value of data provided by National Meteorological and Hydrological Services (NMHSs) or produced by the energy sector itself. Much progress has been made, especially in the medium-term and longer time ranges; the development of reliable probabilistic forecasting systems has allowed many improvements in demand and production forecasts, although there is still a lot to do because of the difficulty in integrating probabilistic weather forecasts in management tools. In addition, the rise of renewable energy (RE) production systems, in particular wind and solar energy, has emphasized new needs for more accurate and reliable short-term forecasts, from real-time to a few days ahead. Rapid fluctuations in wind and solar radiation at local scale certainly raise a serious problem for the management of power grids. Significant and swift improvements in local forecasts, at hourly or even sub-hourly time step, become increasingly important and will be among the drivers for the large-scale development of RE systems. In this paper, we present some important results concerning monthly ensemble forecasts of temperature and river streamflows in France. We then point to the principal needs in weather forecasting associated with the development of RE. We also discuss the importance of collaboration and relationships between providers and users of weather, water, and climate information.

The role of storage in managing the variability in wind, solar and wave energy generation is well understood. Shifting energy from periods of high generation to low generation is seen as an ideal role for storage. However, the rapid fluctuations in wind and solar generation with periods less than 1 h can lead to very significant problems on the grid, reducing carrying capacity of lines and increasing the amount of spinning reserve and regulation services required to unachievable levels. A number of electrical storage technologies which are aimed at removing these rapid fluctuations are now being successfully demonstrated at the MW-scale. The various storage technologies are outlined and an example of wind smoothing system is examined in detail.

Weather forecasting has traditionally been primarily used in the energy industry to estimate the impact of weather, particularly temperature, on future electrical demand. As a growing proportion of electricity generation comes from intermittent renewable sources such as wind, weather forecasting techniques need to be extended to this highly variable and site-specific resource. We demonstrate that wind speed forecasts from Numerical Weather Prediction (NWP) models can be significantly improved by implementing a bias correction methodology. For the study presented here, we used the Australian Bureau of Meteorology (BoM) MesoLAPS 5 km limited domain NWP model, focused over the Victoria/Tasmania region of Australia. The site for this study is the Woolnorth wind farm, situated in north-west Tasmania. We present a comparison of the accuracy of uncorrected hourly NWP forecasts and bias-corrected forecasts over the period March 2005 to May 2006. This comparison includes both the wind speed regimes of importance for typical daily wind farm operation, as well as infrequent but highly important weather risk scenarios that require turbine shutdown. In addition to the improved accuracy that can be obtained with a basic bias correction method, we show that further improvement can be gained from an additional correction that makes use of real-time wind turbine data and a smoothing function to correct for timing-related issues that result from use of the basic correction alone. With full correction applied, we obtain a reduction in the magnitude of the wind speed error by as much as 50 % for ‘hour ahead’ forecasts specific to the wind farm site.

Power generation from solar and wind energy systems is highly variable due to its dependence on meteorological conditions. With the constantly increasing contribution of photovoltaic (PV) power to the electricity mix, reliable predictions of the expected PV power production are getting more and more important as a basis for management and operation strategies. We give an overview of different approaches for solar irradiance and PV power prediction, including numerical weather predictions for forecast horizons of several days, very short-term forecasts based on the detection of cloud motion in satellite or ground-based sky images, and statistical methods to optimize and combine different data sources as well as methods for PV simulation and upscaling to regional PV power predictions. Evaluation results for selected irradiance and power prediction schemes show the benefit of different approaches for different timescales.

The UK makes for a fascinating case study regarding variability in renewable energy resource, impacting on the safe degree of penetration of renewable energy into the electricity grid. In this chapter, we highlight temporal and spatial scale wind speed variability which impacts upon UK wind farm operation both onshore and offshore. We argue how natural variations in wind climate at the monthly, seasonal and decadal scale, linked to the changing frequency of largescale weather patterns, need to be built into assessments of renewable energy revenue streams and consideration of associated insurance products.

A pilot study of energy efficiency measures, or retrofit actions, was carried out for a single-story detached (single-family) house. It used climate downscaling to project the climatic conditions of a region, and building simulation techniques with two thermal comfort approaches for scenarios of “Climate Change” and “Scarce Resources” in the year 2050. This study was the first stage of a research program to find cost-effective retrofit actions to lower greenhouse gas (GHG) emissions for existing Australian houses in a temperate climate. The pilot study ranked retrofit actions that were cost-effective in reducing the heating and cooling energy usage of a house. These actions included removing carpet from a concrete floor for added thermal mass, and adding external shading with deciduous trees to lower summer radiation from the northern windows (in the southern hemisphere). Also, the alternative thermal comfort approach showed that occupants had more control to lower their energy usage than the standard Australian approach.

This concluding chapter draws on the main aspects covered in this book, such as the discussions on the increasing reliance of the energy sector on meteorological information. We then describe current and potential funding models of National Meteorological and Hydrological Services. These are the main, though not the only, providers of meteorological information for energy and all the other sectors affected by meteorological phenomena. It emerges that public sector funding for such Services are dwindling. This is in spite of the recognised impacts that meteorology has on the energy industry, and on other sectors. Some lessons from the important interaction between aviation and meteorology are discussed with a view to drawing some parallels with energy. We then discuss possible options for strengthening the relationship between energy and meteorology in order for society to be better prepared for the increasing vulnerability of the energy sector to the vagaries of weather and climate.