Sh Shap aping ing so soci cial al ac acce ceptance ptance of - PowerPoint PPT Presentation

Sh Shap aping ing so soci cial al ac acce ceptance ptance of of ene nergy rgy pr proj ojects cts Mathilde TESSIER, Sandrine SELOSSE, Nadia MAIZI

Intr trodu oduction ction (1/3) 3) Energy modeling Climate crisis • Long service lifes of the • Limiting GHG to limit the technologies global rise in temperature to 1,5/2°C • Design long-term scenarios • Need to design low-carbon • Looking for robust and solutions and rethink reliable scenarios (that energy systems could be actually used) Centre de MathématiquesAppliquées - MINES ParisTech 2

Introduction (2/3) Social issues • Energy projects have been hindered by local opposition • Start research on the phenomenon and how public perception is formed • Wide phenomenon studied mostly by social scientists Centre de MathématiquesAppliquées – MINES ParisTech 3

Intr trodu oduction ction (2/2) 2) Goal of the PhD : Connect nect the dot ots bet etween een energ ergy model elling ling and d social al issue ues • Two very diverse fields • No literature linking the two topics • Lack of social aspects in current long-term scenarios -> less realistic scenarios First t step of the PhD : Under ersta stand nd social al acceptance nce of ene nerg rgy pro rojec ects ts Resear search question stion : What are the impacts of social acceptance of energy projects on long-term modelling ? Centre de MathématiquesAppliquées – MINES ParisTech 4

Plan an I. Concepts involved II. Analysis of the literature III. Key issues Centre de MathématiquesAppliquées – MINES ParisTech 5

Concept ncepts s at at stak ake an and points ints of vi view Citizens: people living near the project • Acceptance : a posteriori evaluation who might oppose or support it. of a project Industrials: companies locally or • Acceptability : a priori evaluation of nationally involved in the design or the a project realization of the project. • Support : active engagement for a Decision makers: local and national project politicians who have an impact on • Opposition : active engagement location decisions, public investments, against a project etc. • NIMBY (Not In My Back Yard) : Opposition between a general positive opinion and a local opposition Centre de MathématiquesAppliquées – MINES ParisTech 6

Three ree-dim dimen ensional sional as asses essm sment nt of social ial ac acceptance eptance Social acceptance as a three-dimensional assessment (Wüstenhagen et al, 2007): • Community acceptance : Stakeholders concerned by a local project • Socio-political acceptance : broad, policy making • Market acceptance : adoption and diffusion of technologies Market Socio- Community political Centre de MathématiquesAppliquées – MINES ParisTech 7

Diver ersity sity of the e literature erature / / then en interest erest for for a a map ap • Differences in : – Aim of the articles – Geography studied – Technology / kind of project studied • Are they technologies more studied in specific areas ? Need for a geographical representation Centre de MathématiquesAppliquées – MINES ParisTech 8

Ge Geogra graphical phical focus focus Social acceptance of energy projects: A geographical focus based on literature (based on the analysis of 96 papers ) Centre de MathématiquesAppliquées – MINES ParisTech 9

Map ap an anal alysis sis Sorted by area : • Most studied zones: Western Europe, Middle East, North America. • Average studied zones: South America and Oceania. • Least studied zones: Africa, Asia, former USSR. Sorted by technology / policy : • Nuclear mostly in Asia. • Wind power in Western Europe. • Solar power in developing countries. • Energy policy in developed countries. • North America: mostly oil & gas & bioenergies. Centre de MathématiquesAppliquées – MINES ParisTech 10

Extracting social acceptance characteristics to feed the energy model Goal : Extracting key parameters that explain social acceptance to feed the energy model Method : - Identification of « measure » articles - Spot parameters put forward in the articles Centre de MathématiquesAppliquées – MINES ParisTech 11

From the map to TIAM FR (1/2) Geographical zones of TIAM Centre de MathématiquesAppliquées - MINES ParisTech 12

From the map to TIAM FR (2/2) Energy mix evolution - BAU and 2°C scenarios 700000 ALL ALCOHOLS 600000 ALL BIO 500000 ALL COALS 400000 ALL ELECTRICITY PJ ALL GAS 300000 ALL HEAT 200000 ALL HYDROGEN ALL NUCLEAR 100000 ALL OIL PRODUCTS 0 ALL OTHER RNW 2C_2100 BAU_2100_415 2C_2100 BAU_2100_415 2C_2100 BAU_2100_415 2010 2050 2100 Year / Scenario Centre de MathématiquesAppliquées - MINES ParisTech 13

Most st impor portan tant t par arame ameter ers (1/2) 2) Community parameters : • Individual parameters : gender, age, level of education, political ideology or lack of knowledge and pre-conceived ideas on the project ; • Projects parameters (projects’ characteristics) : technology chosen, stakeholders involved, and communication on the project • Local parameters : type of landscape, history of the region, power sources already in operation, etc. Socio political parameters : • General context : – Paris Agreement -> non-fossil energies • Specific events : – Fukushima-Daishi nuclear disaster -> specific technologies Centre de MathématiquesAppliquées – MINES ParisTech 14

Most st impor portan tant t par arame ameter ers (2/2) 2) Market acceptance Dynamics of the acceptance (technology): • will of industrials to diffuse a technology • will of customers to use it • Opposition between :  envy for green power offers and  reluctance to local projects (NIMBY). -> lack in green power • intra-firm acceptance . Dreyer et al, 2017 – Temporal change in acceptability and acceptance Centre de MathématiquesAppliquées – MINES ParisTech 15

Diffi ficul cultie ties / / lac ack of quan antif ified ied dat ata • Qualitative parameters, but TIMES model is quantitative • Few data in the literature • Very diverse literature and methodology -> non coherent set of data Centre de MathématiquesAppliquées – MINES ParisTech 16

Key issues ues (1/2) 2) • A risk to forget developing countries in our analysis:  In developed countries: the transition is mainly electric, from big thermal power plants toward small renewable installations.  In developing countries: the transition is mostly from firewood toward off-grid renewable power. Centre de MathématiquesAppliquées – MINES ParisTech 17

Key issues ues (2/2) 2) • Focus on reducing of opposition: Most articles focus on the ways to reduce opposition to a project. Our goal is to think of how to include this reluctance in our model. • Focus on citizens: Articles often focus on citizens and not on the other stakeholders shaping projects, which can elude some of the important parameters. Centre de MathématiquesAppliquées – MINES ParisTech 18

Conclusion nclusion an and Next xt steps eps • Conclusion : – Very diverse and broad phenomenon – Qualitative phenomenon that will be difficult to quantify • Next steps: – Understand the possibilities to modify of the TIMES/TIAM model Centre de MathématiquesAppliquées – MINES ParisTech 19

THA HANK NK YOU FOR YOUR UR ATTEN ENTION TION Centre de Mathématiques Appliquées 20 MINES ParisTech