integrating variable renewable energy into power system … · 2016. 7. 10. · 3. integrating...

The boTTom line

Wind and solar energy are a fast-growing share of the global energy mix. But integrating them into power-system operations requires significant adaptations to compensate for their variability. Solutions include increasing the amount of flexible generation within the system, combining and dispersing variable resources to smooth aggregate output, expanding the transmission network, using smart technology to control supply and demand, and storing electricity. Each power system will require its own set of measures.

integrating Variable Renewable energy into Power System operationsWhy is this issue important?The variable and unpredictable nature of solar and wind power poses challenges for conventional grid operationsTo reduce greenhouse gas emissions and improve the security of energy supply, many countries are seeking affordable replacements for fossil fuels—183 have adopted targets for generation of renew-able energy. Because technology advances and economies of scale over the past decade have cut the cost of solar photovoltaic (PV) and wind technologies, their share in the global energy mix is expected to grow substantially. However, integrating high levels of variable renewable energy (VRE) into power system operations is challenging.

In a power system, supply must match demand at all times. The necessary balance is achieved in conventional systems by

controlling the amount of electricity generated at any given time and dispatching it as needed to maintain balance. Although variability and unpredictability are very low in such systems, uncertainty persists because of changes in load over time. (Load is the amount of electric power delivered or required at specific points in a power system.) Uncertainly is also inherent in some parts of the grid—for example, generators and transmission lines can fail. Power systems are generally designed to deal with such situations, as described in the next section.

By contrast, wind and solar resources produce electricity only intermittently—that is, when sun and wind are available. This means that, unlike fossil-fueled power, solar and wind power outputs at a spe-cific location cannot be controlled at will. (They are “nondispatchable.”) Moreover, short-term variations in wind and solar resources cannot be perfectly predicted, even over the next hour or day (figure 1).

Thomas Nikolakakis is an energy specialist in the World Bank’s Energy and Extractives Global Practice.

Debabrata Chatopadhyay is a senior energy specialist in the same practice.

A k n o w l e d g e n o t e s e r i e s f o r t h e e n e r g y p r A c t i c e

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Figure 1. Variability of wind and solar output over a two-day period

Source: Ela and others (2013).

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2 I n t E g r a t I n g V a r I a B l E r E n E W a B l E E n E r g y I n t o P o W E r S y S t E m o P E r a t I o n S

“To fully account for load

variability and be ready to

meet peak demand, the

power system’s generating

mix must include flexible

units that can vary their

output in a responsive

way.”

VRE is integrated into the power system by making adjustments to controllable sources of generation (including large hydropower installations) and to demand so as to keep supply and demand in constant balance.

What is the conventional practice with interconnected power systems?

Grid operations have been designed to manage known risks

In its simplest form, operating an interconnected power system can be reduced to a few tasks (Kirby 2007). The first, as noted, is to gener-ate enough power to satisfy aggregate load at all times (including after the unexpected failure of a generator or a link in the transmis-sion chain), while also maintaining frequency. The other tasks are to maintain voltages throughout the power system (under normal and contingency conditions), to avoid overloading system elements (transmission lines, generators, transformers), and to restart the system after a collapse.

Two types of grid operations are deployed to accomplish these tasks: (i) energy operations, and (ii) ancillary services. Note that some systems may not incorporate all of the operations described in this section. Also, similar operations are known by different names in different power systems.

Energy operations serve the function of scheduling energy supply ahead of delivery over various time frames that reflect uncer-tainties in load forecasting. A large share of aggregate demand can normally be predicted with high accuracy and is scheduled the day before (“day-ahead economic dispatch”1) using a least-cost optimiza-tion process (also called “unit commitment”). To fully account for load variability and be ready to meet peak demand, the power system’s generating mix must include flexible units that can vary their output in a responsive way (figure 2). In most systems the scheduling time frame is an hour or half an hour. Because unit commitment takes place on a one-hour basis, however, it cannot balance instantaneous (subhourly) mismatches between supply and demand.

1. In addition to day-ahead services, some power systems also operate real-time energy markets to balance unanticipated

differences.

The daily profile of energy demand, known as “load,” has constant and variable components. So-called base load (the mini-mum daily demand) is met by a set of generators that run constantly at close to their rated power output. Base-load generators have high capital and start-up costs but low operational costs. They are usually coal, nuclear, or hydro generators. The variable share of demand can be split into intermediate and peak components. Variable load is met by flexible generators that can track changes in demand. Known as load-following units, these intermediate and peak generators have relatively low start-up and capital costs but higher operational costs. Such units are usually gas, oil, or hydro generators.

Ancillary services, as described below, allow the system opera-tor to balance instantaneous generation and demand while ensuring that voltage and frequency remain at acceptable levels even after a generator or transmission line fails.

Even a small mismatch between the actual and forecasted load can disturb the frequency of the electricity in the system, which

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Figure 2. Base, intermediate, and peak demand

Source: Kirby (2007).


“Although the rapid growth

of solar and wind power

have challenged power

systems, the impact of

VRE integration and its

associated costs can

be reduced by a set of

complementary solutions

that enhance the capacity

of the system to balance

the net load by minimizing

load variability, increasing

the system’s control

capabilities, or both.”

has to be kept nearly constant to avoid mechanical damage to generators and transformers. Frequency regulation is performed by a set of fast-responding oil and gas units that increase or decrease their output according to central signaling to balance real-time mismatches not covered by energy operations.

Load following ensures that generation meets the variable por-tion of demand. Balancing occurs through an automated generator control system. While both frequency regulation and load following deal with forecasting errors, their fundamental differences is the time frame of operation. The former responds to rapid load fluctuations on the order of a minute or less, whereas the latter responds to changes on the order of 5 to 30 minutes.

In case of a contingency (such as the loss of a large generator), a set of generation units must respond very quickly. For that reason one set of contingency reserves (known as “spinning reserves”) is synchronized with the grid and kept ready to respond within a few minutes of a contingency. Another set of fast-responding units is not synchronized (nonspinning) but can respond within about 10 minutes of a contingency.

Other ancillary service operations include voltage control and “black start.” Voltage control equipment provides reactive power when necessary, for example, after a generator fails. Black start service is provided by generators that can start up quickly without an external electricity source. Their role is to restart the system in case of a major blackout.

how does introducing VRe change the situation?

Adding VRe to a power system greatly increases uncertainty and variability, but solutions are available

Integrating VRE sources into a power system creates something referred to as “net load” (net load = actual load – VRE production). As in a conventional system, the net load must be managed by grid operations, with the key difference that it is more variable and less predictable than the actual load (figure 3).

For example, adding wind power to a system increases (i) the ramping rate, or the speed at which load-following units must increase their output; (ii) the ramping range, or the difference between minimum and maximum demand on a daily basis; and (iii) forecasting uncertainty.

The greater variability and unpredictability introduced into the system by VRE complicate the operator’s task of balancing supply and demand and maintaining system reliability and stability. Specifically, large-scale VRE integration increases the need for flexible generation to provide operating and contingency reserves, thus lowering the efficiency of short-term dispatch. Adding a substantial amount of VRE to a system also creates the need for continuous cycling of intermediate, peak, and, in some cases, base-load gener-ators. Cycling causes wear and tear on mechanical equipment and reduces fuel efficiency. One final effect of the concentrated injection of variable power on a large scale is that it can overload transmission lines and require upgrades to the transmission system.

Although the rapid growth of solar and wind power have challenged power systems, the impact of VRE integration and its associated costs can be reduced by a set of complementary solutions that enhance the capacity of the system to balance the net load by minimizing load variability, increasing the system’s control capabilities, or both. These solutions are summarized below.

Adding flexible generation. The ability of a power system to vary its output to meet fluctuations in demand depends on how fast its generation units can alter power output, a process known as ramping up (or down). The most common thermal generating units

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Figure 3. movement of load, wind generation, and net load over a two-week period

Source: Denholm and others (2010).


“Because VRE sources

are site-constrained,

transmission networks

often must be expanded

to reach them. A ramified

transmission infrastructure

may also be needed

to achieve the optimal

geographic dispersion of

VRE output.”

heat water for use in steam turbines, which means that ramping speeds are relatively slow. An optimal generation mix must include fast-ramping generators such as gas turbines that use air as the working fluid or hydropower turbines that can quickly increase or decrease output through regulating pressure valves. Both types of unit are appropriate for balancing net load, as well as for providing ancillary services. Their deployment adds to the flexibility to the grid.

Combining resources to reduce variability. Solar and wind resources are often negatively correlated: Solar power peaks in the summer, whereas wind tends to peak in the winter. On the other hand, solar power peaks during the day, while winds tend to be stronger in the afternoon and at night. These correlations make it possible to mix wind and solar resources to yield a combined power output that mimics the demand curve, a phenomenon called natural balancing.

Expanding the transmission network. The richest solar and wind energy sites are often geographically dispersed and distant from consumption centers or existing transmission networks. Unlike power sources based on fossil fuels, where planners have discretion over location, moving VRE plant sites can greatly affect the quality of the resource. Because VRE sources are site-constrained, transmis-sion networks often must be expanded to reach them. A ramified transmission infrastructure may also be needed to achieve the optimal geographic dispersion of VRE output. Geographic dispersion of solar and wind generation can dramatically reduce the costs of their integration because dispersion reduces the variability of the aggregated output (Mills and Wiser 2010).

Using smart grids. Smart grids use advanced technologies to control various grid components and to enlist customers in efforts to manage demand (Kempener, Komor, and Hoke 2013). They increase the efficiency, flexibility, and intelligence of a power system. They also can contribute to VRE integration.

• The codes and standards adopted by smart grids promote manufacturing of reliable (and smart!) solar and wind equipment that ensures safe and nondisruptive flow to the network while supporting system operations (e.g., by providing data).

• Smart grids increase supply flexibility through the ability to control generation from small-scale distributed PV units with

controls that make it possible to reduce the output of individual units (or even disconnect them entirely) to avoid violating ramping limits set by utilities (through so-called ramp-rate control systems).

• Demand-response programs made possible by smart technology enable utilities to control consumption (and thus load) directly or through voluntary load reduction. A smart grid using direct load controls may regulate consumers’ thermostats or switch from one power source to another in response to the availability or nonavailability of VRE. On a cold and windy night, for example, the smart grid may use the spike in wind power to provide more heat (by raising the thermostats of consumers), thus maintaining the balance between supply and demand and obviating the need for base-load generators to operate at inefficient levels.

• Smart grids can reduce the operational impacts of VRE by taking advantage of short-term solar and wind forecasts. Smart wind turbines can incorporate millisecond wind forecasting (“nowcasting”) to optimize power output by dynamically adjusting the pitch of turbine blades. Short-term solar forecasting includes ground-based sky imaging to measure cloud speed and short-term output. In general, increasing a grid’s forecasting capabilities can lead to more responsive energy markets and more flexible day-ahead and real-time dispatch.

Storing electricity. Storage can be used to enhance grid operations because of the quick response times and good cycling efficiency of many storage technologies. Storage technologies are differentiated by various attributes, such as rated power and discharge time. The three general categories of large-scale energy storage technology described in table 1 have specific applications in grid operations based on their operational time scale.

In addition to enhancing grid operations, energy storage can be used to increase supply flexibility. As an example, compressed air energy storage and pumped hydro can be used to capture high winds at night when demand is low and release it during peak hours. This example shows how storage technologies can help decrease the variability of VRE output.


“Smart wind turbines can

incorporate millisecond

wind forecasting

(“nowcasting”) to

optimize power output

by dynamically adjusting

the pitch of turbine

blades.” “Every power

system has its own

set of capabilities and

resources for managing

VRE integration; each

country should choose the

actions that best match its

circumstances.”

What have we learned?

The impact of VRe on grid operations teaches three key lessons

Power systems are different. Every power system has its own set of capabilities and resources for managing VRE integration. Larger power systems generally have more options available to them and therefore are better able to deal with high levels of VRE. Small, isolated grids have fewer opportunities—for example, to achieve geographic dispersion of VRE or to increase the share of dispatch-able hydropower generation in the portfolio.

Each country should choose the actions that best match its circumstances. In few countries today do solar and wind energy account for more than 10 percent of the energy mix. As VRE penetration increases, however, the least-expensive solutions should be implemented first (figure 4). These include demand-side man-agement, geographic dispersion of solar and wind generation, and inter-grid cooperation. Such solutions increase system flexibility with minimal investment in new equipment. When these solutions are no longer enough to manage the system’s load, it will be necessary to increase supply-side flexibility and build energy storage. These are expensive solutions that require large investments.

There is no single global solution to deal with the variability introduced by VRE. Just as power system operations have their own response times, so do solutions. Figure 5 illustrates solutions to the problem of VRE variability based on their operational time scale and cost of implementation. The green area highlights the time frames of various system operations. The blue area shows

the effects of VRE integration on those operations. The orange area shows the time scale of specific solutions while ranking them based on their cost.

As noted earlier, regulation units must respond within seconds; load-following units, within minutes. Economic dispatch (unit

Table 1. Categories of electricity storage technologies

Category Applications Operational time scale Technologies

Power quality Frequency regulation, voltage stability Seconds to minutes Flywheels, capacitors, superconducting magnetic storage, batteries

Bridging power Contingency reserves, ramping Minutes to about an hour High-energy-density batteries

Energy management

Load following, capacity, transmission, and deferral of distribution

Hours to days Compressed air energy storage, pumped water, high-energy batteries

Source: Electricity Storage Association (2009); Ibrahim, Ilinca, and Perron (2008).

Manage net load variabilityIncrease system capacity to balance net loadSolutions that fit both categories above

Increasing RE penetration

High cost

Low cost

Supply and

reserve sharing

Flexible

generation

Demand-side

management

Geographic

dispersio

n of

solar, wind

Energy storage

Curtailm

ent

of VRE

Figure 4. Solutions to the problem of VrE variability

Source: Author’s adaptation of figure 5.1 in Denholm and others (2010).

Note: This figure is indicative, and individual cases may differ. For example, on a small island grid, energy storage may be cheaper and more effective than adding flexible generation.


xxx

commitment) is scheduled hours before. Because solar PV systems can experience very sharp decreases in their output within seconds as a cloud passes (thus posing the risk of frequency disruption), appropriate solutions must be found either to minimize net-load variability in the very short term or to increase system capabilities to respond within seconds. Flywheels are a very fast energy storage technology appropriate for frequency regulation (and therefore suitable for mitigating very-short-term variations from solar plants), whereas pumped hydropower is much better suited for load following (and therefore for mitigating the short-term variation from wind plants, which require load-following operations). In sum, each system will require its own set of solutions.

References

Denholm Paul, Erik Ela, Brendan Kirby, and Michael Milligan. 2010. “The Role of Energy Storage with Renewable Electricity Generation.” Technical report NREL/TP-6A2-47187. National Renewable Energy Laboratory, Golden, CO, USA.

Ela, E., V. Diakov, E. Ibanez, and M. Heaney. 2013. “Impacts of Variability and Uncertainty in Solar Photovoltaic Generation at Multiple Timescales.” Technical report NREL/TP-5500-58274. National Renewable Energy Laboratory, Golden, CO, USA.

Electricity Storage Association. 2009. http://www.electricitystorage.org/about/welcome.

Ibrahim, H., A. Ilinca, and J. Perron. 2008. Energy Storage Systems—Characteristics and Comparisons. Renewable and Sustainable Energy Reviews 12(5): 1221–1250.

Kempener R., Komor P., Hoke A., 2013. “ Smart Grids and Renewables. A Guide for Effective Deployment”, Working paper by the International Renewable Energy Agency (IRENA), 2013

Kirby, Brendan. 2007. “Ancillary Services: Technical and Commercial Insights.” Report prepared for WARTSILA. July.

Mills, Andrew, and Ryan Wiser. 2010. “Implications of Wide-Area Geographic Diversity for Short-Term Variability of Solar Power.” Report LBNL-3884E, Environmental Energy Technologies Division, Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley, CA, USA. September.

The peer reviewers for this note were Silvia Martinez (senior renewable energy specialist), Efstratios Tavoulareas (senior operations officer), and Peter Johansen (senior energy specialist), all within the World Bank’s Energy and Extractives Global Practice. The authors acknowledge contributions from Marcelino Madrigal (Energy Regulatory Commission of Mexico) and from Rhonda Lenai Jordan (energy specialist) and Morgan Bazilian (lead energy specialist), both at the World Bank.

Figure 5. Solutions to the problem of VrE variability based on their operation timescale and cost of implementation

Source: Authors.

Note: CAES = compressed air energy storage; EMS = electromagnetic storage.

Systemoperations

Increased needfor regulationunits Impacts

Solutions

Voltagesags

Establishinggrid codestandards

10 sec … 1 min … 10 min … 30 min 1 hour … 1 day … days …

Less efficient unitcomitment and economic dispatch,congestion issues

Increased need for flexiblegeneration

Increased needfor contingencyreserves

Cost ofsolution

Time

Powerquality

Regulation Load following Unit commitment

Implement demand response programs; combine resources;disperse VRE; improve ramp rate controls Managing net load

CAES, pumped hydroBatteriesFlywheelsEMS Energy storage

Add more gas and hydro unitsIncreased supply-side flexibility

Increase supply and reserve sharing (expand system)Transmission expansion

Contingencyreserves

http://www.electricitystorage.org/about/welcome

http://www.electricitystorage.org/about/welcome

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Get Connected to live Wire

1 T r a c k i n g P r o g r e s s T o w a r d P r o v i d i n g s u s T a i n a b l e e n e r g y f o r a l l i n e a s T a s i a a n d T h e Pa c i f i c

THE BOTTOM LINE

where does the region stand

on the quest for sustainable

energy for all? in 2010, eaP

had an electrification rate of

95 percent, and 52 percent

of the population had access

to nonsolid fuel for cooking.

consumption of renewable

energy decreased overall

between 1990 and 2010, though

modern forms grew rapidly.

energy intensity levels are high

but declining rapidly. overall

trends are positive, but bold

policy measures will be required

to sustain progress.

2014/28

Elisa Portale is an

energy economist in

the Energy Sector

Management Assistance

Program (ESMAP) of the

World Bank’s Energy and Extractives

Global Practice.

Joeri de Wit is an

energy economist in

the Bank’s Energy and

Extractives Global

Practice.

A K N O W L E D G E N O T E S E R I E S F O R T H E E N E R G Y & E X T R A C T I V E S G L O B A L P R A C T I C E

Tracking Progress Toward Providing Sustainable Energy

for All in East Asia and the Pacific

Why is this important?

Tracking regional trends is critical to monitoring

the progress of the Sustainable Energy for All

(SE4ALL) initiative

In declaring 2012 the “International Year of Sustainable Energy for

All,” the UN General Assembly established three objectives to be

accomplished by 2030: to ensure universal access to modern energy

services,1 to double the 2010 share of renewable energy in the global

energy mix, and to double the global rate of improvement in energy

efficiency relative to the period 1990–2010 (SE4ALL 2012).

The SE4ALL objectives are global, with individual countries setting

their own national targets in a way that is consistent with the overall

spirit of the initiative. Because countries differ greatly in their ability

to pursue the three objectives, some will make more rapid progress

in one area while others will excel elsewhere, depending on their

respective starting points and comparative advantages as well as on

the resources and support that they are able to marshal.

To sustain momentum for the achievement of the SE4ALL

objectives, a means of charting global progress to 2030 is needed.

The World Bank and the International Energy Agency led a consor-

tium of 15 international agencies to establish the SE4ALL Global

Tracking Framework (GTF), which provides a system for regular

global reporting, based on rigorous—yet practical, given available

1 The universal access goal will be achieved when every person on the planet has access

to modern energy services provided through electricity, clean cooking fuels, clean heating fuels,

and energy for productive use and community services. The term “modern cooking solutions”

refers to solutions that involve electricity or gaseous fuels (including liquefied petroleum gas),

or solid/liquid fuels paired with stoves exhibiting overall emissions rates at or near those of

liquefied petroleum gas (www.sustainableenergyforall.org).

databases—technical measures. This note is based on that frame-

work (World Bank 2014). SE4ALL will publish an updated version of

the GTF in 2015.

The primary indicators and data sources that the GTF uses to

track progress toward the three SE4ALL goals are summarized below.

• Energy access. Access to modern energy services is measured

by the percentage of the population with an electricity

connection and the percentage of the population with access

to nonsolid fuels.2 These data are collected using household

surveys and reported in the World Bank’s Global Electrification

Database and the World Health Organization’s Household Energy

Database.

• Renewable energy. The share of renewable energy in the

energy mix is measured by the percentage of total final energy

consumption that is derived from renewable energy resources.

Data used to calculate this indicator are obtained from energy

balances published by the International Energy Agency and the

United Nations.

• Energy efficiency. The rate of improvement of energy efficiency

is approximated by the compound annual growth rate (CAGR)

of energy intensity, where energy intensity is the ratio of total

primary energy consumption to gross domestic product (GDP)

measured in purchasing power parity (PPP) terms. Data used to

calculate energy intensity are obtained from energy balances

published by the International Energy Agency and the United

Nations.

2 Solid fuels are defined to include both traditional biomass (wood, charcoal, agricultural

and forest residues, dung, and so on), processed biomass (such as pellets and briquettes), and

other solid fuels (such as coal and lignite).

1 T r a c k i n g P r o g r e s s To wa r d P r o v i d i n g s u s Ta i n a b l e e n e r g y f o r a l l i n e a s T e r n e u r o P e a n d c e n T r a l a s i a

THE BOTTOM LINE



energy for all? The region

has near-universal access to

electricity, and 93 percent of

the population has access


despite relatively abundant

hydropower, the share

of renewables in energy

consumption has remained

relatively low. very high energy

intensity levels have come

down rapidly. The big questions

are how renewables will evolve

when energy demand picks up

again and whether recent rates

of decline in energy intensity

will continue.

2014/29

Elisa Portale is an

energy economist in

the Energy Sector




Global Practice.

Joeri de Wit is an

energy economist in


Extractives Global

Practice.



for All in Eastern Europe and Central Asia




(SE4ALL) initiative


All,” the UN General Assembly established three global objectives

to be accomplished by 2030: to ensure universal access to modern

energy services,1 to double the 2010 share of renewable energy in

the global energy mix, and to double the global rate of improvement

in energy efficiency relative to the period 1990–2010 (SE4ALL 2012).






















the GTF in 2015.



Energy access. Access to modern energy services is measured

by the percentage of the population with an electricity connection

and the percentage of the population with access to nonsolid fuels.2

These data are collected using household surveys and reported

in the World Bank’s Global Electrification Database and the World

Health Organization’s Household Energy Database.

Renewable energy. The share of renewable energy in the energy

mix is measured by the percentage of total final energy consumption

that is derived from renewable energy resources. Data used to

calculate this indicator are obtained from energy balances published

by the International Energy Agency and the United Nations.

Energy efficiency. The rate of improvement of energy efficiency is

approximated by the compound annual growth rate (CAGR) of energy

intensity, where energy intensity is the ratio of total primary energy

consumption to gross domestic product (GDP) measured in purchas-

ing power parity (PPP) terms. Data used to calculate energy intensity

are obtained from energy balances published by the International

Energy Agency and the United Nations.

This note uses data from the GTF to provide a regional and

country perspective on the three pillars of SE4ALL for Eastern




“Live Wire is designed

for practitioners inside

and outside the Bank.

It is a resource to

share with clients and

counterparts.”

1 U n d e r s t a n d i n g C O 2 e m i s s i O n s f r O m t h e g l O b a l e n e r g y s e C t O r

Understanding CO2 Emissions from the Global Energy Sector

Why is this issue important?

Mitigating climate change requires knowledge of the

sources of CO2 emissions

Identifying opportunities to cut emissions of greenhouse gases

requires a clear understanding of the main sources of those emis-

sions. Carbon dioxide (CO2) accounts for more than 80 percent of

total greenhouse gas emissions globally,1 primarily from the burning

of fossil fuels (IFCC 2007). The energy sector—defined to include

fuels consumed for electricity and heat generation—contributed 41

percent of global CO2 emissions in 2010 (figure 1). Energy-related

CO2 emissions at the point of combustion make up the bulk of such

emissions and are generated by the burning of fossil fuels, industrial

waste, and nonrenewable municipal waste to generate electricity

and heat. Black carbon and methane venting and leakage emissions

are not included in the analysis presented in this note.

Where do emissions come from?

Emissions are concentrated in a handful of countries

and come primarily from burning coal

The geographical pattern of energy-related CO2 emissions closely

mirrors the distribution of energy consumption (figure 2). In 2010,

almost half of all such emissions were associated with the two

largest global energy consumers, and more than three-quarters

were associated with the top six emitting countries. Of the remaining

energy-related CO2 emissions, about 8 percent were contributed

by other high-income countries, another 15 percent by other

1 United Nations Framework Convention on Climate Change, Greenhouse Gas Inventory

Data—Comparisons By Gas (database). http://unfccc.int/ghg_data/items/3800.php

middle-income countries, and only 0.5 percent by all low-income

countries put together.

Coal is, by far, the largest source of energy-related CO2 emissions

globally, accounting for more than 70 percent of the total (figure 3).

This reflects both the widespread use of coal to generate electrical

power, as well as the exceptionally high CO2 intensity of coal-fired

power (figure 4). Per unit of energy produced, coal emits significantly

more CO2 emissions than oil and more than twice as much as natural

gas.

2014/5

THE BOTTOM LINE

the energy sector contributes

about 40 percent of global

emissions of CO2. three-

quarters of those emissions

come from six major

economies. although coal-fired

plants account for just

40 percent of world energy

production, they were

responsible for more than

70 percent of energy-sector

emissions in 2010. despite

improvements in some

countries, the global CO2

emission factor for energy

generation has hardly changed

over the last 20 years.

Vivien Foster is sector

manager for the Sus-

tainable Energy Depart-

ment at the World Bank

([email protected]).

Daron Bedrosyan

works for London

Economics in Toronto.

Previously, he was an

energy analyst with the

World Bank’s Energy Practice.

A K N O W L E D G E N O T E S E R I E S F O R T H E E N E R G Y P R A C T I C E

Figure 1. CO2 emissions

by sector

Figure 2. energy-related CO2

emissions by country

Energy41%

Roadtransport

16%

Othertransport

6%

Industry20%

Residential6%

Othersectors

10%China30%

USA19%

EU11%

India7%

Russia7%

Japan 4%

Other HICs8%

Other MICs15%

LICs0.5%

Notes: Energy-related CO2 emissions are CO2 emissions from the energy sector at the point

of combustion. Other Transport includes international marine and aviation bunkers, domestic

aviation and navigation, rail and pipeline transport; Other Sectors include commercial/public

services, agriculture/forestry, fishing, energy industries other than electricity and heat genera-

tion, and other emissions not specified elsewhere; Energy = fuels consumed for electricity and

heat generation, as defined in the opening paragraph. HIC, MIC, and LIC refer to high-, middle-,

and low-income countries.

Source: IEA 2012a.

1 T r a c k i n g P r o g r e s s To wa r d P r o v i d i n g s u s Ta i n a b l e e n e r g y f o r a l l i n e a s T e r n e u r o P e a n d c e n T r a l a s i a

THE BOTTOM LINE



energy for all? The region

has near-universal access to

electricity, and 93 percent of

the population has access


despite relatively abundant

hydropower, the share

of renewables in energy

consumption has remained

relatively low. very high energy

intensity levels have come

down rapidly. The big questions

are how renewables will evolve

when energy demand picks up

again and whether recent rates

of decline in energy intensity

will continue.

2014/29

Elisa Portale is an

energy economist in

the Energy Sector




Global Practice.

Joeri de Wit is an

energy economist in


Extractives Global

Practice.



for All in Eastern Europe and Central Asia




(SE4ALL) initiative


All,” the UN General Assembly established three global objectives

to be accomplished by 2030: to ensure universal access to modern

energy services,1 to double the 2010 share of renewable energy in

the global energy mix, and to double the global rate of improvement

in energy efficiency relative to the period 1990–2010 (SE4ALL 2012).






















the GTF in 2015.



Energy access. Access to modern energy services is measured

by the percentage of the population with an electricity connection

and the percentage of the population with access to nonsolid fuels.2

These data are collected using household surveys and reported

in the World Bank’s Global Electrification Database and the World

Health Organization’s Household Energy Database.

Renewable energy. The share of renewable energy in the energy

mix is measured by the percentage of total final energy consumption

that is derived from renewable energy resources. Data used to

calculate this indicator are obtained from energy balances published

by the International Energy Agency and the United Nations.

Energy efficiency. The rate of improvement of energy efficiency is

approximated by the compound annual growth rate (CAGR) of energy

intensity, where energy intensity is the ratio of total primary energy

consumption to gross domestic product (GDP) measured in purchas-

ing power parity (PPP) terms. Data used to calculate energy intensity

are obtained from energy balances published by the International

Energy Agency and the United Nations.

This note uses data from the GTF to provide a regional and

country perspective on the three pillars of SE4ALL for Eastern




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