Our Common Future Under Climate Change

International Scientific Conference 7-10 JULY 2015 Paris, France

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Thursday 9 July - 14:30-16:00 UNESCO Fontenoy - ROOM I

3303 - Decarbonizing Electricity/Electricity Transition

Parallel Session

Chair(s): E. Wilson (Humphrey School of Public Affairs, Minneapolis, MN, United States of America)

Convener(s): O. Boucher (Laboratoire de Météorologie Dynamique, Paris, France), N. Maizi (Mines ParisTech, Paris, France), S. Fu (Chongqing University of Arts and Sciences, Chongqing, China)

14:30

Does climate change threaten the future of the PV sector in Europe?

S. Jerez (University of Murcia, Murcia, Spain), I. Tobin, (Laboratoire des Sciences du Climat et de l'Environnement (LSCE), Gif sur Yvette, France), R. Vautard (LSCE-IPSL, Gif-sur-Yvette, France), J. P. Montavez, (University of Murcia, Murcia, Spain), F. Thais, (Institut de Technico-Economie des Systèmes Energétiques (I-Tésé), Saclay, France), O. B. Christensen, (Danish Meteorological Institute (DMI), Copenhague, Denmark), A. Colette (INERIS, Verneuil-en-Halatte, France), M. Déqué (Météo-France/CNRM, Toulouse, France), S. Kotlarski, (Institute for Atmospheric and Climate Science - ETH Zürich, Zürich, Switzerland), M. E. Van (Royal Netherlands Meteorological Institute (KNMI), Bilt, Netherlands), G. Nikulin, (Rossby Centre SMHI, Norrköping, Sweden), C. Teichmann, (Climate Service Center 2.0, Hamburg, Germany)

Abstract details
Does climate change threaten the future of the PV sector in Europe?

S. Jerez (1) ; I. Tobin, (2) ; R. Vautard () ; JP. Montavez, (1) ; F. Thais, (3) ; OB. Christensen, (4) ; A. Colette (5) ; M. Déqué (6) ; S. Kotlarski, (7) ; ME. Van (8) ; G. Nikulin, (9) ; C. Teichmann, (10)
(1) University of Murcia, Department of physics, Murcia, Spain; (2) Laboratoire des Sciences du Climat et de l'Environnement (LSCE), Gif sur Yvette, France; (3) Institut de Technico-Economie des Systèmes Energétiques (I-Tésé), Saclay, France; (4) Danish Meteorological Institute (DMI), Copenhague, Denmark; (5) INERIS, Verneuil-en-Halatte, France; (6) Météo-France/CNRM, Toulouse, France; (7) Institute for Atmospheric and Climate Science - ETH Zürich, Zürich, Switzerland; (8) Royal Netherlands Meteorological Institute (KNMI), Bilt, Netherlands; (9) Rossby Centre SMHI, Norrköping, Sweden; (10) Climate Service Center 2.0, Hamburg, Germany

Abstract content

The bet on renewable energies is a key aspect of the mitigation strategies aimed at abating climate change, in which Europe is a world leader. In particular, PV power has been receiving large investments and its future deployment is expected to be spectacular, specially in southern countries. However, development plans remain widely blind to the potential impacts of a hereafter changed climate on renewable energy resources. In order to shed light on this issue, this study makes use of a new generation multi-model and multi-scenario ensemble of high-resolution climate simulations spanning up to the end of this century to assess changes in both PV power generation potential (PVpot) and actual production (PVprod) considering a future scenario with a high penetration of PV installations. Results show that the projected increase in the surface air temperature adversely affects the projections for PVpot, as it acts to diminish the efficiency of the PV cells. Thus, while surface solar radiation is projected to slightly increase in southern regions, PVpot is not. In the most extreme scenario considered (RCP8.5), PVpot would diminish in the range 5-15% (from South to North within Europe) by the end of this century according to the ensemble mean. In terms of production, significant changes are not expected southward but for a plausible reduction of the daily variability of the PVprod series, which would indeed be beneficial. However, further north, worse projections, with the Scandinavian region holding robust reductions in the mean production (about -10% under the RCP8.5) and uncertain projections regarding its future variability. In any case, all signals depict limited impacts indicating that climate change does not seem to pose a serious risk for the PV sector in Europe.

14:40

Advances in multi-scale models to shed light on the plausibility of longterm scenarios

N. Maizi (Mines ParisTech, Paris, France), N. Maïzi (PSL, MINES ParisTech, Paris, France)

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Advances in multi-scale models to shed light on the plausibility of longterm scenarios

N. Maïzi (1)
(1) PSL, MINES ParisTech, Mathematics and Systems, Center for Applied Mathematics, Paris, France

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Given the complex international situation, mitigation strategies to tackle energy-related issues need effective normative tools to deal with the different types of constraint (e.g. climate-related, financial, legal, political, technical). Various scenarios are now

available to provide an insight into the challenges of energy transition under

environmental constraint. However, the regional, technological and social conditions

that trigger this transition require developing tools to identify the policy mixes needed

for new directions in technical systems and modes of development. And this is more stringent in the electricity sector.

In particular, the aim is to reconcile and connect different scales (temporal, spatial,

social) in order to understand:

  • The political implications that necessarily take place at several levels, from

global to local,

  • The impact of phenomena with different dynamics (several decades versus

seconds), and

  • The central role of people (for whom the future must be acceptable and

desirable, i.e. compatible with aspirations and behavior).

 

This multi-scale integration brings up significant methodological obstacles that we

propose to examine in three stages to understand the needed reconciliation of long-term

approaches employed in prospective exercises at different scales:

 

1. Short-term/long-term temporal scales : reconciliation involves examining the “inertia” of systems, e.g. urbanization or the composition of current mixes, versus the

“instantaneousness” of usage (e.g. mobility using electric vehicles or smart grid

solutions, energy efficiency) as well as the technical conditions for operating

systems (i.e. network reliability, availability and stability);

2. Spatial scales : different levels of spatial issues will be tackled such as

top-down versus bottom-up pledges for emerging countries, centralized versus

decentralized networks, managing intermittent electricity production sources

and integration into the network;

3. Societal scales : this will involve discussing the assessment of different development paradigms (degrowth/growth) and the integration of behavior as relevant modeling

characteristics.

 

Each issue will be illustrated using specific examples. 

14:50

Using big data to make decisions in the electricity sector under deep uncertainty

I. Azevedo (Carnegie-Mellon University, Pittsburgh, United States of America), B. Sovacool (Danish Center for Energy Technologies (Center for Energiteknologier), Herning, Denmark), K. Jones (Vermont Law School, South Royalton, United States of America), M. Dworkin (Institute for Energy and the Environment, South Royalton, United States of America), I. Azevedo (Carnegie Mellon University, Pittsburgh, PA, United States of America)

Abstract details
Using big data to make decisions in the electricity sector under deep uncertainty

I. Azevedo (1) ; B. Sovacool (2) ; K. Jones (3) ; M. Dworkin (4) ; I. Azevedo (5)
(1) Carnegie-Mellon University, Department of engineering and public policy, Pittsburgh, United States of America; (2) Danish Center for Energy Technologies (Center for Energiteknologier), Herning, Denmark; (3) Vermont Law School, Vermont law school, South Royalton, United States of America; (4) Institute for Energy and the Environment, Vermont law school, South Royalton, United States of America; (5) Carnegie Mellon University, Engineering and Public Policy, Pittsburgh, PA, United States of America

Abstract content

Creating resilient, reliable, and low-carbon electricity systems to help mitigate the effects of greenhouse gas emissions (GHG) and adapt to a changing climate remains a critical global challenge.

Electricity consumption accounts for a large portion of greenhouse gas emissions worldwide, making it one of the key sectors for climate mitigation strategies. Decarbonizing the electricity system becomes an even more daunting task given about 17% of the world population does not yet have access to energy services.

Changes in the electricity sector to move towards a low carbon energy system leave to important trade-offs in terms of costs to the overall energy system, how such costs are distributed, how to address issues related to fuel security and diversity, how to improve the level of energy services provided, and environmental consequences.

While decisions regarding different strategies to decarbonizing electricity systems may be done under deep uncertainty, in recent years the emergence of very detailed data – i.e., the big data revolution, paired with big data analytics – provides the ability to draw new insights and new ways to approach decisions.

This talk will focus on the ability to make decisions in the electricity sector under deep uncertainty in the United States. In the United States, the data from the Continuous Emission Monitoring System (CEMS), which is collected and made publicly available by the U.S. Environmental Protection Agency, provides data regarding the hourly power generation, and emissions from GHGs and criteria air pollutants, for every single fossil fuel based generator in the United States that is larger than 25MW. This data, coupled with air quality models and health and environmental valuation models, allows us today to estimate the regional effects of different interventions in the U.S. grid (such as increasing renewable (Siler-Evans et al., 2012; 2013), building codes (Gilbraith et al., 2014), storage (Hittinger and Azevedo, 2015) in a way that was not possible before. Similarly, on the consumption side, the deployment of smart meters coupled with information on energy efficiency and demand side management programs provides a new way to use big data analytics to assess whether the intended goals of the programs have been achieved (Azevedo, 2014).

In this session, we will (1) provide an overview of some of the recent big data analytics efforts that have been pursued to improve decision making under uncertainty in decisions aiming at the decarbonization of the electricity sector in the United States; (2) provide a map of data needs for several regions across the world that would be critical for one of the able to perform systematic international comparisons; (3) provide a research roadmap of the critical research questions we believe need to be addressed to make better decisions under uncertainty in the electricity sector.

References:

Siler-Evans. K., Azevedo, I.L., Morgan, M.G., (2012). Marginal emissions factors for the US electricity system. Environmental Science & Technology, 46 (9): 4742–4748.

Siler-Evans, K., Azevedo, I. L., Morgan, M.G, Apt, J. (2013). Regional variations in the health, environmental, and climate benefits from wind and solar generation, Proceedings of the National Academy of Sciences, 110 (29): 11768-11773.

Gilbraith, N., Azevedo, I.L., Jaramillo, P., (2014). Regional energy and GHG savings from building codes across the United States, Environmental Science & Technology, Volume 48, Issue 24, pp 14121–14130.

Azevedo, I.L. (2014) Energy efficiency and rebound effects: a review, Annual Reviews of Environment and Resources, Volume 39.

Hittinger, E., Azevedo, I.L., (2015). Bulk Energy Storage Increases US Electricity System Emissions, Environmental Science & Technology, January 2015.

15:00

Integrated pathway to decarbonizing electricity in China

S. Fu (Chongqing University of Arts and Sciences, Chongqing, China), Q. Yameng (University of Tampere, Tampere, Finland)

Abstract details
Integrated pathway to decarbonizing electricity in China

S. Fu (1) ; Q. Yameng (2)
(1) Chongqing University of Arts and Sciences, Chongqing, China; (2) University of Tampere, School of information sciences, Tampere, Finland

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1. Background: Economy, electricity and carbon mitigation in China

The momentum of economy growth is strong. i) urbanization; ii) poverty; iii) all-round Open-up and Reform policy; iv) 6.5-7.5% growth rate during 2016 to 2020.

Power industry faces rigorous environmental challenge. Per capita electricity is 3510 KWH and will continue to rise sharply. Energy-intensive industries are backward, which results in low energy efficiency. As 78% electricity comes from fossil fuel, CO2 intensity remains 0.514-1.246 tCO2e/MWH. Power industry discharges 39% CO2 and still appears upward trend. Pricing and universal services are far from perfect; moreover, institution has CO2 lock-in weakness.

Carbon mitigation achievements in power industry. Energy intensity per unit GDP dropped by 20.7%, reducing 1,967 million tCO2e. Non-fossil energy accounted for 8% of primary energy consumption, saving over 600 million tCO2e annually. China eliminated 80 million KW small thermal power units, reducing 166 million tCO2e every year. What more, innovation of generating technology and reformation of institutional arrangement contributed to huge CO2 abatement.

2. A big deal: China-U.S. Joint Announcement on Climate Change

Benefits and protocol. Smart action on climate can promote economic growth and broad benefits. China-U.S. will jointly propose a protocol under the COP21.

Post-2020 actions. The U.S. targets to reduce CO2 by 26-28% in 2025. By 2030, China will peak CO2 emission and increase the share of non-fossil fuels to 20%.

Technology cooperation. China-U.S. have a robust program of energy technology cooperation and will jointly invest more in clean technological innovation.

Policy dialogue and practical cooperation. The two sides announced additional measures to strengthen and expand practical cooperation in climate change.

3. Integrated pathway option: Decarbonizing electricity in China

Decarbonizing electricity goal. Chinese electricity need follow a path featuring high efficiency, less pollution as well as satisfying economy growth. At 2015 energy intensity will drop by 16% and CO2 decrease by 17%. At 2020 non-fossil energy will take 15% and CO2 lower by 40-45%.

Demand side management. China adopts key actions in electricity-saving among industry, building and transportation; actively transforms economy into capital- and technology-intensive mode. It lists technologies of energy-saving and sets energy intensity standard. China encourages green building, improves heat-supply as well as electricity-saving by public building. It also promotes green transportation, electricity-saving education; therefore, fosters a green lifestyle.

Develop renewable electricity. Renewable power is to take 30% by 2015. Hydropower will get 290 million KW, half of its potential. Currently nuclear power is 1.8%; thereafter China will endeavor to reach 40 million KW. It stresses intensive and distributed exploiting wind power; corresponding capacity will get 100 million KW. China develops diverse patterns of solar power; thereafter solar collection will exceed 400 million m2. It also actively exploits biomass electricity.

Promote clean fossil electricity. China emphasizes coal washing, shuts small thermal units, speeds up supercritical- and ultra-supercritical- technology, encourages thermoelectricity cogeneration as well as IGCC generation; actively develops circular economy. It expands power transmission from western to eastern; strengthens ultra-high voltage as well as smart grids. It will construct many CCS projects; thereafter, set up platform of national technology innovation.

Optimize institutional arrangement. China is to reform legal regime as well as regulations on electricity; especially separate transmission from distribution, revise pricing mechanism, and extend international cooperation. It will deepen electricity market and carbon market, improve CO2 auditing, diverse mitigation approaches; meanwhile, coordinate mitigation and power generation. 

15:10

Panel discussion:

E. Wilson (Humphrey School of Public Affairs, Minneapolis, MN, United States of America)

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Panel discussion:
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Professor Daphne Mah, Hong Kong Baptist University, Daphne Mah, daphnema@hku.hk

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Professor Daphne Mah, Hong Kong Baptist University, Daphne Mah, daphnema@hku.hk
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Professor Dan Kammen, UC Berkeley, USA kammen@berkeley.edu

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Professor Dan Kammen, UC Berkeley, USA kammen@berkeley.edu
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Professor Benjamin Sovacool , Danish Center for Energy Technology, benjaminso@auhe.au.dk

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Professor Benjamin Sovacool , Danish Center for Energy Technology, benjaminso@auhe.au.dk
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